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It will be introduced in detail in Spring Cloud and Remote Association.","s":"Remote Association","u":"/jimmer-doc/docs/mapping/advanced/remote","p":392},{"i":398,"t":"In this series of articles, we will introduce base mappings.","s":"Base mapping","u":"/jimmer-doc/docs/mapping/base/","p":398},{"i":400,"t":"To enable logical deletion for the middle table, the property needs to be specified for the org.babyfish.jimmer.sql.JoinTable annotation to indicate whether the data is normal or has been deleted.","s":"Join Table","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","p":400},{"i":406,"t":"Here, you will learn about the most important capability of ORM","s":"Association Mapping","u":"/jimmer-doc/docs/mapping/base/association/","p":406},{"i":408,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToOne annotation to declare many-to-one association properties.","s":"Many To One","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","p":408},{"i":414,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToMany annotation to declare many-to-many association properties.","s":"Many To Many","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","p":414},{"i":422,"t":"Through the discussion of Association Mapping, we know that association mapping requires a lot of foreign keys.","s":"Real and Fake Foreign Keys","u":"/jimmer-doc/docs/mapping/base/foreignkey","p":422},{"i":430,"t":"Unlike JPA, Jimmer does not support unidirectional one-to-many associations. One-to-many associations can only exist as mirrors of many-to-one associations. That is, one-to-many associations necessarily imply bidirectional associations.","s":"One To Many","u":"/jimmer-doc/docs/mapping/base/association/one-to-many","p":430},{"i":432,"t":"Basic Concepts: Short Associations","s":"IdView","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","p":432},{"i":448,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.OneToOne annotation to declare one-to-one association properties.","s":"One To One","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","p":448},{"i":458,"t":"Limitations of classic ORM associations","s":"ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","p":458},{"i":475,"t":"In addition to boolean, number, string, UUID, date, and enumeration, scalar properties also support other types, including:","s":"More Types","u":"/jimmer-doc/docs/mapping/base/more-type","p":475},{"i":483,"t":"Jimmer handles the issue of whether entity object properties can be null in a very strict way. Even for Java developers, it requires thinking about whether each property can be null in the same way as Kotlin developers.","s":"Nullity","u":"/jimmer-doc/docs/mapping/base/nullity","p":483},{"i":494,"t":"In this section, we will introduce all the capabilities in Jimmer related to modifying the database.","s":"Modification","u":"/jimmer-doc/docs/mutation/","p":494},{"i":496,"t":"@Entity","s":"Simple Mapping","u":"/jimmer-doc/docs/mapping/base/basic","p":496},{"i":515,"t":"Naming Strategy Interface","s":"Naming Strategy","u":"/jimmer-doc/docs/mapping/base/naming-strategy","p":515},{"i":530,"t":"Basic Concepts","s":"Delete Command","u":"/jimmer-doc/docs/mutation/delete-command","p":530},{"i":543,"t":"In recent months, the save instruction has undergone a major restructuring, so there hasn't been time to update all the documentation in this directory.","s":"Save Command","u":"/jimmer-doc/docs/mutation/save-command/","p":543},{"i":545,"t":"Although Jimmer entities are not POJOs, Jackson serialization can be supported by org.babyish.jimmer.jackson.ImmutableModule.","s":"JSON Converter","u":"/jimmer-doc/docs/mapping/base/json-converter","p":545},{"i":561,"t":"Concept","s":"Interceptor before save","u":"/jimmer-doc/docs/mutation/draft-interceptor","p":561},{"i":577,"t":"Overview","s":"Mutable Association Table","u":"/jimmer-doc/docs/mutation/associations","p":577},{"i":594,"t":"Basic Concepts","s":"Owner side","u":"/jimmer-doc/docs/mutation/save-command/association/owner","p":594},{"i":604,"t":"Basic Usage","s":"Delete Statement","u":"/jimmer-doc/docs/mutation/delete-statement","p":604},{"i":609,"t":"Basic Concepts","s":"Association classification","u":"/jimmer-doc/docs/mutation/save-command/association/classification","p":609},{"i":624,"t":"The save command is used to store data structures of any complexity. To facilitate discussion, we need to establish a basic classification of data structure shapes.","s":"Data Classification","u":"/jimmer-doc/docs/mutation/save-command/data-classification","p":624},{"i":638,"t":"Although the underlying save commands are very powerful, there is still some way to go before exposing data persistence APIs externally.","s":"Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/","p":638},{"i":640,"t":"When saving associated objects using the association mode AssociatedSaveMode.REPLACE,","s":"Dissociation Operations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","p":640},{"i":662,"t":"This is a very crude solution, only for learning or very simple projects.","s":"Lonely Form","u":"/jimmer-doc/docs/mutation/save-command/input-dto/lonely","p":662},{"i":664,"t":"Basic Concepts","s":"Associated Save Mode","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","p":664},{"i":687,"t":"Jimmer provides DTO language.","s":"Using DTO Language","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","p":687},{"i":697,"t":"Basic Concepts","s":"Associated Id Checking","u":"/jimmer-doc/docs/mutation/save-command/id-checking","p":697},{"i":711,"t":"In this article we discuss:","s":"Problem","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","p":711},{"i":723,"t":"Not recommended for Kotlin.","s":"Using MapStruct","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","p":723},{"i":735,"t":"Input DTO is used for data input, so it provides powerful control over nullable properties in the objects submitted by the client, and standardizes this capability.","s":"Handle Null Values","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","p":735},{"i":756,"t":"Save Command Result","s":"Other Features","u":"/jimmer-doc/docs/mutation/save-command/other","p":756},{"i":759,"t":"Basic Concepts","s":"Constraint Violation Error Handling","u":"/jimmer-doc/docs/mutation/save-command/investigation","p":759},{"i":779,"t":"Save commands support both optimistic lock and pessimistic lock.","s":"Optimistic/Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","p":779},{"i":793,"t":"Basic Usage","s":"Update Statement","u":"/jimmer-doc/docs/mutation/update-statement","p":793},{"i":802,"t":"In this series of articles, we thoroughly discuss the dynamicity and immutability of Jimmer objects:","s":"Object","u":"/jimmer-doc/docs/object/","p":802},{"i":804,"t":"Introduction","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/save-command/usage","p":804},{"i":826,"t":"The example code in this article uses a type called BookDraft, which is an interface type automatically generated by Jimmer based on the user-defined type Book.","s":"Dynamicity","u":"/jimmer-doc/docs/object/dynamic","p":826},{"i":847,"t":"Immutability is used to ensure that the data structure represented by Jimmer objects never contains circular references.","s":"Immutability","u":"/jimmer-doc/docs/object/immutable/","p":847},{"i":849,"t":"Jimmer supports triggers that allow users to listen for database changes.","s":"Trigger","u":"/jimmer-doc/docs/mutation/trigger","p":849},{"i":877,"t":"Unlike other ORMs, Jimmer uses immutable objects as entity objects.","s":"Reason","u":"/jimmer-doc/docs/object/immutable/reason","p":877},{"i":886,"t":"Java has supported immutable record types since Java 14, and Kotlin's data classes can easily implement immutable classes, even supporting copy functions. However, they are designed for simple immutable objects, and have problems dealing with complex deep data structure.","s":"Current Situation","u":"/jimmer-doc/docs/object/immutable/current-situation","p":886},{"i":888,"t":"Save Modes","s":"Save Mode of Aggregate-Root","u":"/jimmer-doc/docs/mutation/save-command/save-mode","p":888},{"i":919,"t":"Jimmer objects are dynamic and not all properties of an object need to be initialized. It allows missing some properties.","s":"Working with Jackson","u":"/jimmer-doc/docs/object/jackson","p":919},{"i":921,"t":"Jimmer provides a series of static tool methods for operating on dynamic objects or their Drafts.","s":"Tool Methods","u":"/jimmer-doc/docs/object/tool","p":921},{"i":949,"t":"Even if entity objects support dynamism to express arbitrary data structures, conversion between entities and DTOs is still unavoidable.","s":"DTO conversion","u":"/jimmer-doc/docs/object/view/","p":949},{"i":951,"t":"In previous documents we have seen that","s":"Draft","u":"/jimmer-doc/docs/object/draft","p":951},{"i":980,"t":"Introduction","s":"MapStruct","u":"/jimmer-doc/docs/object/view/mapstruct","p":980},{"i":1003,"t":"The sample code above uses a type called TreeNodeDraft, which is the interface type automatically generated by Jimmer based on the user-defined type TreeNode.","s":"Solution","u":"/jimmer-doc/docs/object/immutable/solution","p":1003},{"i":1011,"t":"In this series of articles, we will introduce:","s":"Introduction ★","u":"/jimmer-doc/docs/overview/","p":1011},{"i":1013,"t":"Previous documents have discussed in detail the dynamic and immutable properties of Jimmer entities. This introduces a new feature: visibility.","s":"Visibility","u":"/jimmer-doc/docs/object/visibility","p":1013},{"i":1021,"t":"Not only can Jimmer bring you powerful features, but it can also bring you ultimate performance.","s":"Benchmark Report","u":"/jimmer-doc/docs/overview/benchmark","p":1021},{"i":1034,"t":"To help readers better understand the key features, let's first introduce Jimmer's fundamental design philosophy","s":"Key Features ✦","u":"/jimmer-doc/docs/overview/key-features","p":1034},{"i":1042,"t":"Basic Concepts","s":"APT/KSP","u":"/jimmer-doc/docs/overview/apt-ksp","p":1042},{"i":1055,"t":"In this section, we will introduce the various queries in Jimmer without considering Cache.","s":"Query","u":"/jimmer-doc/docs/query/","p":1055},{"i":1057,"t":"Where are the Examples and Getting started?","s":"Before Reading","u":"/jimmer-doc/docs/overview/welcome","p":1057},{"i":1064,"t":"How Jimmer solves the dynamic join problem will be discussed in subsequent docs. This article first introduces the join style in Jimmer.","s":"Association Path Chaining","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","p":1064},{"i":1070,"t":"We will introduce the following contents:","s":"Dynamic JOIN","u":"/jimmer-doc/docs/query/dynamic-join/","p":1070},{"i":1072,"t":"1. Concepts","s":"DTO Language","u":"/jimmer-doc/docs/object/view/dto-language","p":1072},{"i":1148,"t":"1. What is Jimmer","s":"Overview ✦","u":"/jimmer-doc/docs/overview/introduction","p":1148},{"i":1182,"t":"Dilemma","s":"Join Features Specific to Kotlin","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","p":1182},{"i":1193,"t":"In the previous doc, we discussed dynamic queries. In this section, we will explore the problems with dynamic table joins.","s":"Problems with Other Solutions","u":"/jimmer-doc/docs/query/dynamic-join/problem","p":1193},{"i":1199,"t":"Association Tables Hidden by Object Model","s":"Querying Association Tables","u":"/jimmer-doc/docs/query/associations","p":1199},{"i":1210,"t":"The Problem to Solve","s":"Weak Join","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","p":1210},{"i":1218,"t":"Usage","s":"Merge Conflict Joins","u":"/jimmer-doc/docs/query/dynamic-join/merge","p":1218},{"i":1223,"t":"Static Ordering","s":"Dynamic Ordering","u":"/jimmer-doc/docs/query/dynamic-order","p":1223},{"i":1233,"t":"Basic Usage","s":"Dynamic Filtering","u":"/jimmer-doc/docs/query/dynamic-where","p":1233},{"i":1240,"t":"Global filters are used to automatically add filtering conditions for an entity type. Most queries for the entity type will automatically have related where conditions added.","s":"Global Filters","u":"/jimmer-doc/docs/query/global-filter/","p":1240},{"i":1242,"t":"Pagination safety is a feature designed for pagination, but table join functionality provides underlying support.","s":"Pagination Safety","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","p":1242},{"i":1262,"t":"Readers cannot find anything related to global filters in this doc, because the filter required for logical deletion is built-in and hidden by Jimmer.","s":"Logical Deletion","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","p":1262},{"i":1275,"t":"Aggregation","s":"Aggregate & Group","u":"/jimmer-doc/docs/query/group","p":1275},{"i":1280,"t":"Native SQL expressions are an important feature to leverage database-specific capabilities, as database products always have proprietary features.","s":"Native SQL Expressions","u":"/jimmer-doc/docs/query/native-sql","p":1280},{"i":1286,"t":"Collection (one-to-many or many-to-many) associations often lead to the frequent use of subqueries in queries, and implicit subqueries greatly simplify such subqueries.","s":"Implicit Subquery","u":"/jimmer-doc/docs/query/implicit-subquery","p":1286},{"i":1294,"t":"Usage","s":"Optimize Unnecessary Joins","u":"/jimmer-doc/docs/query/dynamic-join/optimization","p":1294},{"i":1315,"t":"Concept","s":"Object Fetcher","u":"/jimmer-doc/docs/query/object-fetcher/","p":1315},{"i":1320,"t":"In last doc we introduced scalar property fetching. In this doc we discuss association fetching.","s":"Associations","u":"/jimmer-doc/docs/query/object-fetcher/association","p":1320},{"i":1343,"t":"Provide Abstract Mapped Superclass","s":"Custom Filters","u":"/jimmer-doc/docs/query/global-filter/user-filter","p":1343},{"i":1368,"t":"We have introduced that object fetchers can flexibly control the shape of queried data structures, bringing tremendous flexibility for application development.","s":"Working with Spring Data","u":"/jimmer-doc/docs/query/object-fetcher/spring-data","p":1368},{"i":1370,"t":"Previously we introduced using object fetchers to flexibly control the shape of queried data structures.","s":"Querying DTOs","u":"/jimmer-doc/docs/query/object-fetcher/dto","p":1370},{"i":1381,"t":"Fetching Scalar Fields","s":"Ordinary Properties","u":"/jimmer-doc/docs/query/object-fetcher/props","p":1381},{"i":1390,"t":"Why Introduce Object Fetchers","s":"Basic Usage","u":"/jimmer-doc/docs/query/object-fetcher/usage","p":1390},{"i":1397,"t":"In this series of articles, we will introduce Jimmer's smart paging.","s":"Smart Paging","u":"/jimmer-doc/docs/query/paging/","p":1397},{"i":1399,"t":"Concept","s":"Reverse Sorting Optimization","u":"/jimmer-doc/docs/query/paging/reverse-sorting","p":1399},{"i":1408,"t":"Literal Expressions","s":"DSL Expressions","u":"/jimmer-doc/docs/query/expression","p":1408},{"i":1452,"t":"Pagination queries have a problem - when the data volume is large, if the pagination range is too far back (i.e. offset is too large), performance issues can occur.","s":"Deep Pagination Optimization","u":"/jimmer-doc/docs/query/paging/deep-optimization","p":1452},{"i":1460,"t":"IdView","s":"View Properties","u":"/jimmer-doc/docs/query/object-fetcher/view","p":1460},{"i":1475,"t":"In the previous article, we mentioned that Jimmer can not only auto-generate count-query from data-query, but also auto-optimize the count-query.","s":"Table Join Optimization","u":"/jimmer-doc/docs/query/paging/unnecessary-join","p":1475},{"i":1483,"t":"A common requirement is to handle self-associated property.","s":"Recursive Query","u":"/jimmer-doc/docs/query/object-fetcher/recursive","p":1483},{"i":1495,"t":"Typed Subqueries","s":"Subqueries","u":"/jimmer-doc/docs/query/sub-query","p":1495},{"i":1513,"t":"This section only enumerates the usage methods of the most important functions in Jimmer to allow readers to build a preliminary impression.","s":"Quick View ★","u":"/jimmer-doc/docs/quick-view/","p":1513},{"i":1515,"t":"Select-After Style","s":"Overview","u":"/jimmer-doc/docs/query/usage","p":1515},{"i":1520,"t":"Can It Be Simpler","s":"Super QBE","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","p":1520},{"i":1529,"t":"Basic Concepts","s":"1. Query Arbitrary Shape","u":"/jimmer-doc/docs/quick-view/fetch/","p":1529},{"i":1534,"t":"Jimmer supports strongly typed SQL DSL.","s":"3. Arbitrary Dynamic Query","u":"/jimmer-doc/docs/quick-view/dsl/","p":1534},{"i":1536,"t":"Through the introduction of the previous article, we quickly previewed Jimmer's powerful ability to query arbitrary data structures at will.","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/fetch/export/","p":1536},{"i":1538,"t":"The comparison is as below:","s":"Comparison","u":"/jimmer-doc/docs/quick-view/fetch/export/comparison","p":1538},{"i":1540,"t":"Features of Jimmer Pagination","s":"Usage","u":"/jimmer-doc/docs/query/paging/usage","p":1540},{"i":1562,"t":"Super QBE is a very powerful feature that uses DTO Language to generate parameter types for complex queries and automatically implement query logic.","s":"Super QBE","u":"/jimmer-doc/docs/query/super_qbe","p":1562},{"i":1592,"t":"Jimmer SQL DSL","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/dsl/feature","p":1592},{"i":1611,"t":"Through the previous chapters, we already have a basic impression of Jimmer. Now we can start practicing.","s":"Get Started","u":"/jimmer-doc/docs/quick-view/get-started/","p":1611},{"i":1613,"t":"Here is the English translation of the file, with the code indentation preserved:","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/fetch/feature","p":1613},{"i":1629,"t":"UML","s":"Create Database","u":"/jimmer-doc/docs/quick-view/get-started/create-database","p":1629},{"i":1635,"t":"Enable Web API Analysis","s":"Directly Return Entities","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","p":1635},{"i":1648,"t":"Code Generation","s":"Generate Code","u":"/jimmer-doc/docs/quick-view/get-started/generate-code","p":1648},{"i":1653,"t":"Create a Spring Boot Project","s":"Create a Project","u":"/jimmer-doc/docs/quick-view/get-started/create-project","p":1653},{"i":1664,"t":"Java/Kotlin Applications Use Query Results","s":"Return Output DTO","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","p":1664},{"i":1690,"t":"To quickly preview Jimmer's main features, we need to provide several entities here as the basic assumption of all discussions in this section.","s":"Precondition","u":"/jimmer-doc/docs/quick-view/precondition","p":1690},{"i":1703,"t":"The save directive is a very powerful capability of Jimmer. With just one function call, data structures of any shape can be saved.","s":"2. Save Arbitrary Shape","u":"/jimmer-doc/docs/quick-view/save/","p":1703},{"i":1705,"t":"Jimmer's Two Usages","s":"Final Usage","u":"/jimmer-doc/docs/quick-view/get-started/usage","p":1705},{"i":1718,"t":"In Save Any Shape/Feature Introduction, we introduced the powerful data saving capability of Jimmer,","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/save/export/","p":1718},{"i":1720,"t":"Unlike ORMs like JPA/Hibernate, entities in Jimmer are defined as interfaces instead of classes. The reasons are discussed in Why Interfaces.","s":"Define Entities","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","p":1720},{"i":1736,"t":"Concept","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/save/feature","p":1736},{"i":1747,"t":"What is Short Association","s":"Save Short Associations","u":"/jimmer-doc/docs/quick-view/save/export/short","p":1747},{"i":1758,"t":"https://discord.gg/PmgR5mpY3E","s":"Discuss","u":"/jimmer-doc/docs/resource/discuss","p":1758},{"i":1761,"t":"Jimmer focuses only on the ORM itself and does not provide auxiliary tools, such as generating entity interface definitions based on the database structure.","s":"Ecosystem","u":"/jimmer-doc/docs/resource/ecosystem","p":1761},{"i":1773,"t":"Through the previous chapters:","s":"Standard Examples","u":"/jimmer-doc/docs/quick-view/standard-demo","p":1773},{"i":1789,"t":"TODO","s":"Video","u":"/jimmer-doc/docs/resource/video","p":1789},{"i":1791,"t":"What is Long Association","s":"Save Long Associations","u":"/jimmer-doc/docs/quick-view/save/export/long","p":1791},{"i":1802,"t":"Overview","s":"Save Aggregate Root","u":"/jimmer-doc/docs/quick-view/save/export/root","p":1802},{"i":1822,"t":"There are two concepts in Jimmer","s":"1. Basic Query","u":"/jimmer-doc/docs/showcase/base","p":1822},{"i":1830,"t":"Query Dynamic Entities","s":"2.3 Deeper Association","u":"/jimmer-doc/docs/showcase/fetch-association/deeper-association","p":1830},{"i":1835,"t":"Query Dynamic Entities","s":"2.1 Associated Object","u":"/jimmer-doc/docs/showcase/fetch-association/associated-object","p":1835},{"i":1841,"t":"Unlike the previous example, here we only need to fetch the associated object id, not the entire associated object.","s":"2.4 Associated Id","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","p":1841},{"i":1850,"t":"So far, we've quickly demonstrated the following features","s":"7. Comprehensive Query","u":"/jimmer-doc/docs/showcase/comprehensive-query","p":1850},{"i":1856,"t":"Dynamic sorting refers to the sorting method being dynamically specified by the client.","s":"5.2 Dynamic Sorting","u":"/jimmer-doc/docs/showcase/order-by/dynamic","p":1856},{"i":1866,"t":"Multiple orderBy actions","s":"5.1 Basic Usage","u":"/jimmer-doc/docs/showcase/order-by/usage","p":1866},{"i":1873,"t":"标准子查询","s":"8. Other Queries","u":"/jimmer-doc/docs/showcase/other-query","p":1873},{"i":1879,"t":"Query Dynamic Entities","s":"3.2 Limit Depth","u":"/jimmer-doc/docs/showcase/recursive-query/depth","p":1879},{"i":1884,"t":"Query Dynamic Entities","s":"3.4 Multiple Properties","u":"/jimmer-doc/docs/showcase/recursive-query/multiple-props","p":1884},{"i":1889,"t":"Query Dynamic Entities","s":"2.2 More Associations","u":"/jimmer-doc/docs/showcase/fetch-association/more-association","p":1889},{"i":1894,"t":"In the past few months, save command has been undergoing a major restructuring, so it has not been written.","s":"X. To be Continued...","u":"/jimmer-doc/docs/showcase/to-be-conitnued","p":1894},{"i":1897,"t":"Query Dynamic Entities","s":"3.2 Control Recursion Of Node","u":"/jimmer-doc/docs/showcase/recursive-query/node-control","p":1897},{"i":1903,"t":"Two types of Page objects","s":"6. Paging Query","u":"/jimmer-doc/docs/showcase/page","p":1903},{"i":1910,"t":"IsNull判断","s":"4.3 Associated Id","u":"/jimmer-doc/docs/showcase/where/associated-id","p":1910},{"i":1915,"t":"Using whereIf","s":"4.2 Dynamic Conditions","u":"/jimmer-doc/docs/showcase/where/dynamic-where","p":1915},{"i":1922,"t":"The following three ways of writing are equivalent","s":"4.1 Base Usage","u":"/jimmer-doc/docs/showcase/where/usage","p":1922},{"i":1932,"t":"Jimmer itself is highly neutral and does not couple with any container framework, but can easily integrate with any container framework.","s":"Spring","u":"/jimmer-doc/docs/spring/","p":1932},{"i":1934,"t":"Jimmer provides Spring Data Repository style APIs, so you can:","s":"Spring Data","u":"/jimmer-doc/docs/spring/repository/","p":1934},{"i":1936,"t":"Query Dynamic Entities","s":"3.1 Basic usage","u":"/jimmer-doc/docs/showcase/recursive-query/usage","p":1936},{"i":1941,"t":"Jimmer has many configurations, some of which can be configured in Spring Boot's application.yml or application.properties. Such as:","s":"Appendix","u":"/jimmer-doc/docs/spring/appendix","p":1941},{"i":1943,"t":"Usage","s":"4.4 Dynamic Table Join","u":"/jimmer-doc/docs/showcase/where/dynamic-join","p":1943},{"i":1955,"t":"Implicit subqueries can only be used for collection associations. This article discusses implicit subqueries through the many-to-many Book.authors.","s":"4.5 Implicit Subquery","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","p":1955},{"i":1966,"t":"Jimmer integrates spring data and provides a base repository interface for Java and Kotlin users respectively.","s":"Define Repository","u":"/jimmer-doc/docs/spring/repository/concept","p":1966},{"i":1968,"t":"Remote associations are Jimmer's first thoughts on microservice architecture.","s":"Remote Associations","u":"/jimmer-doc/docs/spring/spring-cloud","p":1968},{"i":1984,"t":"Integrate Spring Transaction","s":"Spring Transaction","u":"/jimmer-doc/docs/spring/transaction","p":1984},{"i":1995,"t":"Jimmer provides DTO language.","s":"Query DTO","u":"/jimmer-doc/docs/spring/repository/dto","p":1995},{"i":2009,"t":"Just like other Spring Data implementations, users can define abstract methods in the Repository interface. 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we will introduce three types of cache Object Cache Association Cache Calculation Cache","s":"Cache type","u":"/jimmer-doc/docs/cache/cache-type/","h":"","p":1},{"i":4,"t":"Jimmer provides powerful cache support capabilities. Whether to use cache is completely transparent to developers Which caching technologies to use is decided by developers Not only does it support simple object cache, but also property-level cache, including association cache and calculated cache. Ultimately it provides the ability to cache arbitrary data structures, not just simple object cache. Features represented by permission systems allow different users to see different data. Therefore, Jimmer uses multi-view cache to allow different users to see different caches. Powerful cache consistency support. Developers can focus on modifying the database and Jimmer will automatically invalidate cache.","s":"Cache","u":"/jimmer-doc/docs/cache/","h":"","p":3},{"i":6,"t":"Object cache refers to mapping id to entity object. This is the simplest and most basic cache.","s":"Object Cache","u":"/jimmer-doc/docs/cache/cache-type/object","h":"","p":5},{"i":8,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forObject(type) .maximumSize(1024) .duration(Duration.ofHours(1)) .build() ) .add( RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build(); } ...omit other code... }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ChainCacheBuilder() .add( CaffeineValueBinder .forObject(type) .maximumSize(1024) .duration(Duration.ofHours(1)) .build() ) .add( RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build() ...omit other code... } } If you don't want to support object cache for some entity types, just return null. Java Kotlin @Override public Cache createObjectCache(ImmutableType type) { if (type.getJavaClass() == SomeEntity.class) { return null; } ... } override fun createObjectCache(type: ImmutableType): Cache<*, *>? = if (type.javaClass === SomeEntity::class.java) { null } else { ... }","s":"Enabling Object Caching","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#enabling-object-caching","p":5},{"i":10,"t":"There are two usage patterns that can utilize the object cache: Query entity objects (or their collections) by id (or their collections) Use object fetchers to fetch any non-id fields of associated objects","s":"Using Object Cache","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#using-object-cache","p":5},{"i":12,"t":"Java Kotlin Map bookMap = sqlClient.findMapByIds( Book.class, Arrays.asList(1L, 2L, 3L, 4L, 999L) ); System.out.println(bookMap); val bookMap = sqlClient.findMapByIds( Book::class, listOf(1L, 2L, 3L, 4L, 999L) ) println(bookMap) Jimmer first looks up the data in the cache with keys Book-1, Book-2, Book-3, Book-4 and Book-999. Suppose the data corresponding to these keys cannot be found in the cache: 127.0.0.1:6379> keys Book-* (empty array) So the following SQL is executed to load data from the database: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */, ? /* 3 */, ? /* 4 */, ? /* 999 */ ) Jimmer will put the query results into the cache, so we can view this data in the cache: 127.0.0.1:6379> keys Book-* 1) \"Book-4\" 2) \"Book-2\" 3) \"Book-3\" 4) \"Book-1\" 5) \"Book-999\" 127.0.0.1:6379> get Book-1 \"{\\\"id\\\":1,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"edition\\\":1,\\\"price\\\":50.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-2 \"{\\\"id\\\":2,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"edition\\\":2,\\\"price\\\":55.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-3 \"{\\\"id\\\":3,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"edition\\\":3,\\\"price\\\":51.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-4 \"{\\\"id\\\":4,\\\"name\\\":\\\"Effective TypeScript\\\",\\\"edition\\\":1,\\\"price\\\":73.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-999 \"\" 127.0.0.1:6379> tip The non-existent data Book-999 is also cached with the special value . Undoubtedly, before the data in the cache expires, executing the Java/Kotlin code above again will directly return the data from the cache without any SQL being generated.","s":"Query Based on Id","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#query-based-on-id","p":5},{"i":14,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().like(\"GraphQL\")) .select( table.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .name() ) ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.name like \"GraphQL\") select( table.fetchBy { allScalarFields() store { name() } } ) } .execute() println(books) 1st SQL: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME like ? /* %GraphQL% */ The fuzzy query in the code is implemented here to obtain some Book objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. 2nd SQL: Fetch many-to-one association Book.store The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return 6 aggregate root objects. The object fetcher in the code contains the many-to-one association Book.store and expects to query non-id properties of the associated object (information that cannot be expressed by the foreign key of the current table), so Jimmer will query the associated object for all aggregate root objects. Fortunately, the associated attribute Book.store is based on a real foreign key. The foreign key itself represents the id of the parent object. There is no need to obtain the associated object id through additional queries or association cache. Suppose the foreign key STORE_ID of the 6 BOOK data has two distinct values after deduplication, 1 and 2. Jimmer first looks up the data in the cache with keys BookStore-1 and BookStore-2. Suppose the data corresponding to these keys cannot be found in the cache: 127.0.0.1:6379> keys BookStore-* (empty array) Then the following SQL is executed to load data from the database: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */ ) info We only need the ID and NAME fields, but here all fields are queried, which is different from what was discussed earlier in Object Fetcher. Please view: The difference compared to not enabling cache Jimmer will put the query results into the cache, so we can view this data in the cache: 127.0.0.1:6379> keys BookStore-* 1) \"BookStore-1\" 2) \"BookStore-2\" 127.0.0.1:6379> get BookStore-1 \"{\\\"id\\\":1,\\\"name\\\":\\\"O'REILLY\\\",\\\"website\\\":null}\" 127.0.0.1:6379> get BookStore-2 \"{\\\"id\\\":2,\\\"name\\\":\\\"MANNING\\\",\\\"website\\\":null}\" 127.0.0.1:6379> Undoubtedly, before the data in the cache expires, executing the Java/Kotlin code above again will directly return the associated data from the cache without generating the 2nd SQL statement. Finally, Jimmer concatenates the results of the two steps as the final data returned to the user: [ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" } }, { ...omit... }, { ...omit... }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\" } }, { ...omit... }, { ...omit... } ]","s":"Using Object Fetchers","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#using-object-fetchers","p":5},{"i":16,"t":"caution To use Jimmer's automatic cache invalidation, triggers need to be enabled first. If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK_STORE set WEBSITE = 'https://www.manning.com' where ID = 2; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; sqlClient .createUpdate(table) .set(table.website(), \"https://www.manning.com\") .where(table.id().eq(2L)) .execute(); sqlClient .createUpdate(BookStore::class) { set(table.website, \"https://www.manning.com\") where(table.id eq 2L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [BookStore-2]","s":"Cache Invalidation","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#cache-invalidation","p":5},{"i":18,"t":"Association cache refers to mapping the current object id to the associated object id or collection. Where: BookStore.books-*: One-to-many association cache Book.store-*: Many-to-one association cache Book.authors-*: Many-to-many association cache Author.books-*: Many-to-many association cache caution Unlike other association caches, there is one scenario that does not require using one-to-one or many-to-one association cache. If a one-to-one or many-to-one association is based on a real foreign key with a corresponding foreign key constraint in the database, then the foreign key itself is the associated object id, and association cache is not required. In other cases, Jimmer will use one-to-one or many-to-one association cache. These cases include: The referenced association property is reverse side That is, @OneToOne's mappedBy is configured. The referenced association property is based on a pseudo foreign key A pseudo foreign key means that it is conceptually a foreign key in the developer's mind, but there is no corresponding foreign key constraint in the database. The pseudo foreign key field may contain illegal values, the non-null value does not mean the associated object exists, so association cache is required to filter out valid associated objects. The referenced association property is based on a join table rather than a foreign key. When implementing GraphQL with Jimmer, Object Fetcher (GraphQL and Object Fetchers are homogenous functions) should not be used in aggregate root queries, but object fetcher were incorrectly used in aggregate root queries to obtain objects without foreign keys. However, the GraphQL request body contains many-to-one associations. In the official sample code included, the many-to-one association Book.store is based on a real foreign key, so its many-to-one cache will not be used. Therefore, the examples in this article use the one-to-many association BookStore.books and the many-to-many association Book.authors.","s":"Association Cache","u":"/jimmer-doc/docs/cache/cache-type/association","h":"","p":17},{"i":20,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...omit code... } // Map current object id to associated object id // Applies to one-to-one and many-to-one associations @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ); } // Map current object id to collection of associated object ids // Applies to one-to-many and many-to-many associations @Override public Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } private Cache createPropCache( ImmutableProp prop, Duration caffeineDuration, Duration redisDuration ) { return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } ...omit other code... }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...omit code... // Map current object id to associated object id // Applies to one-to-one and many-to-one associations override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ) // Map current object id to collection of associated object ids // Applies to one-to-many and many-to-many associations override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ) private fun createPropCache(prop: ImmutableProp, duration: Duration): Cache = ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() ...omit other code... } }","s":"Enabling Association Cache","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#enabling-association-cache","p":17},{"i":22,"t":"caution For collection type associations, if we use the field filter of object fetchers to implement association-level sorting, it will cause Jimmer to ignore association cache. To make full use of association cache while keeping the sorting of the associated object collection returned by the object fetcher query controllable, you can specify the default sorting statically on the entity. BookStore.books Java Kotlin BookStore.java @Entity public interface BookStore { @OneToMany( mappedBy = \"store\", orderedProps = { @OrderedProp(\"name\"), @OrderedProp(value = \"edition\", desc = true) } ) List books(); ...omit other code... } BookStore.kt @Entity interface BookStore { @OneToMany( mappedBy = \"store\", orderedProps = { @OrderedProp(\"name\"), @OrderedProp(value = \"edition\", desc = true) } ) val books : List ...omit other code... } Book.authors Java Kotlin Book.java @Entity public interface Book { @ManyToMany( orderedProps = { @OrderedProp(\"firstName\"), @OrderedProp(\"lastName\") } ) List authors(); ...omit other code... } Book.kt @Entity interface Book { @ManyToMany( orderedProps = { @OrderedProp(\"firstName\"), @OrderedProp(\"lastName\") } ) val authors : List ...omit other code... }","s":"Sorting Collection Associations","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#sorting-collection-associations","p":17},{"i":24,"t":"As mentioned at the beginning of this article, the examples here are based on the one-to-many association BookStore.books and the many-to-many association Book.authors.","s":"Usage","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#usage","p":17},{"i":26,"t":"Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; List stores = sqlClient .createQuery(table) .select( table.fetch( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ) ) .execute(); System.out.println(stores); val stores = sqlClient .createQuery(BookStore::class) { select( table.fetchBy { allScalarFields() books { allScalarFields() } } ) } .execute() println(stores) Step 1: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ The query in the code is implemented here to obtain some BookStore objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. Step 2: Convert current object id to associated object id via association cache The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return two aggregate root objects. The object fetcher in the code contains the one-to-many association BookStore.books The primary keys ID of these 2 BOOK_STOREs are 1 and 2. Jimmer first looks up the data in Redis with keys BookStore.books-1 and BookStore.books-2. Suppose the data corresponding to these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.books-* (empty array) So the following SQL is executed to load data from the database: select tb_1_.STORE_ID, tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 1 */, ? /* 2 */ ) order by tb_1_.NAME asc, tb_1_.EDITION desc Jimmer will put the results of the query into Redis, so we can view this data in Redis: 127.0.0.1:6379> keys BookStore.books-* 1) \"BookStore.books-2\" 2) \"BookStore.books-1\" 127.0.0.1:6379> get BookStore.books-1 \"[6,5,4,3,2,1,9,8,7]\" 127.0.0.1:6379> get BookStore.books-2 \"[12,11,10]\" 127.0.0.1:6379> Thus, the two BookStore objects can obtain the associated object id collections of their respective one-to-many associations BookStore.books. Undoubtedly, before the data in Redis expires, executing the Java/Kotlin code above again will directly return the associated data from Redis without generating the second SQL statement. Step 3: Convert associated object id to associated object via object cache Such operations have been discussed in detail in Object Cache, so they are not repeated here. This article focuses on association cache. caution In the cache configuration, if association cache is enabled for an association property but object cache is not enabled for its associated object type, an exception will be thrown. info Previously in Object Fetcher, we saw that Jimmer only needs one SQL statement to query all associated objects based on a batch of current objects, but here two SQL statements are needed, please view: The difference compared to not enabling cache Finally, Jimmer concatenates the results of the two steps as the final data returned to the user: [ { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, \"price\":88 }, { \"id\":5, ...omit... }, { \"id\":4, ...omit... }, { \"id\":3, ...omit... }, { \"id\":2, ...omit... }, { \"id\":1, ...omit... }, { \"id\":9, ...omit... }, { \"id\":8, ...omit... }, { \"id\":7, ...omit... } ] }, { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80 }, { \"id\":11, ...omit... }, { \"id\":10, ...omit... } ] } ]","s":"One-to-Many: BookStore.books","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#one-to-many-bookstorebooks","p":17},{"i":28,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.edition().eq(1)) .select( table.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition eq 1) select( table.fetchBy { allScalarFields() authors { allScalarFields() } } ) } .execute() println(books) Step 1: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ where tb_1_.EDITION = ? /* 1 */ The query in the code is implemented here to obtain some Book objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. Step 2: Convert current object id to associated object ids via association cache The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return 4 aggregate root objects. The object fetcher in the code contains the many-to-many association Book.authors The primary keys ID of these 4 BOOKs are 1, 4, 7 and 10. Jimmer first looks up the data in Redis with keys Book.authors-1, Book.authors-4, Book.authors-7 and Book.authors-10. Suppose the data corresponding to these keys cannot be found in Redis: 127.0.0.1:6379> keys Book.authors-* (empty array) So the following SQL is executed to load data from the database: select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID from BOOK_AUTHOR_MAPPING tb_1_ inner join AUTHOR tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID in ( ? /* 1 */, ? /* 4 */, ? /* 7 */, ? /* 10 */ ) order by tb_3_.FIRST_NAME asc, tb_3_.LAST_NAME asc note If no default sort is specified for the association property Book.authors via @ManyToMany.orderedProps, the join here will not appear. Jimmer will put the results of the query into Redis, so we can view this data in Redis: 127.0.0.1:6379> keys Book.authors-* 1) \"Book.authors-4\" 2) \"Book.authors-1\" 3) \"Book.authors-10\" 4) \"Book.authors-7\" 127.0.0.1:6379> get Book.authors-1 \"[2,1]\" 127.0.0.1:6379> get Book.authors-4 \"[3]\" 127.0.0.1:6379> get Book.authors-7 \"[4]\" 127.0.0.1:6379> get Book.authors-10 \"[5]\" 127.0.0.1:6379> Thus, we have obtained the associated object id collections that the 4 Book objects can get through their respective many-to-many association Book.authors. Undoubtedly, before the data in Redis expires, executing the Java/Kotlin code above again will directly return the associated data from Redis without generating the second SQL statement. Step 3: Convert associated object id to associated object via object cache Such operations have been discussed in detail in Object Cache, so they are not repeated here. This article focuses on association cache. caution In the cache configuration, if association cache is enabled for an association property but object cache is not enabled for its associated object type, an exception will be thrown. info Previously in Object Fetcher, we saw that Jimmer only needs one SQL statement to query all associated objects based on a batch of current objects, but here two SQL statements are needed, please view: The difference compared to not enabling cache Finally, Jimmer concatenates the 3 steps results as the final data returned to the user: [ { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 51, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] }, { \"id\": 4, \"name\": \"Effective TypeScript\", \"edition\": 1, \"price\": 73, \"authors\": [...omit...] }, { \"id\": 7, \"name\": \"Programming TypeScript\", \"edition\": 1, \"price\": 47.5, \"authors\": [...omit...] }, { \"id\": 10, \"name\": \"GraphQL in Action\", \"edition\": 1, \"price\": 80, \"authors\": [...omit...] } ]","s":"Many-to-Many: Book.authors","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#many-to-many-bookauthors","p":17},{"i":30,"t":"caution To use Jimmer's automatic cache invalidation, triggers need to be enabled first.","s":"Cache Invalidation","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#cache-invalidation","p":17},{"i":32,"t":"Modify the foreign key STORE_ID of the BOOK table, Jimmer automatically deletes the many-to-one association cache Book.store and the one-to-many association cache BookStore.books. If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK /* Old value: 1, New value: 2 */ set STORE_ID = 2 where ID = 7; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(table) // Old value: 1L, New value: 2L .set(table.store().id, 2L) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { // Old value: 1L, New value: 2L set(table.store.id, 2L) where(table.id eq 7L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book-7] Delete data from redis: [Book.store-7] ❶ Delete data from redis: [BookStore.books-1] ❷ Delete data from redis: [BookStore.books-2] ❸ ❶ For the Book object with id 7, its many-to-one association cache Book.store is deleted. ❷ For the BookStore object with id 1 (old value before modification), its one-to-many association cache BookStore.books is deleted. ❸ For the BookStore object with id 2 (new value before modification), its one-to-many association cache BookStore.books is deleted.","s":"One-to-Many: BookStore.books","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#one-to-many-bookstorebooks-1","p":17},{"i":34,"t":"Inserting data into the join table BOOK_AUTHOR_MAPPING automatically deletes the many-to-many association caches Book.authors and Author.books. note Deleting data from the join table can achieve the same effect. Here insertion is used to demonstrate the effect. If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: insert into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values(10, 3); If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .save(10L, 3L); sqlClient .getAssociations(Book::authors) .save(10L, 3L); Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book.authors-10] ❶ Delete data from redis: [Author.books-3] ❷ ❶ For the Book object with id 10, its many-to-many association cache Book.authors is deleted. ❷ For the Author object with id 3, its many-to-many association cache Author.books is deleted.","s":"Many-to-Many: Book.authors","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#many-to-many-bookauthors-1","p":17},{"i":36,"t":"If associated objects support logical deletion, association caching is still supported by default. warning However, once the logical deletion is ignored or reversed, association caching will be ignored.","s":"Notes on Logical Deletion","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#notes-on-logical-deletion","p":17},{"i":38,"t":"caution In previous articles on object cache, association cache, and calculated cache, we have discussed in detail how Jimmer automatically deletes affected caches when data is modified. So here we will not repeat the discussion of how Jimmer intelligently invalidates affected caches. The focus of this article is how Jimmer ensures cache deletion operations issued can definitely succeed. Whether it is the fully automatic invalidation of object cache and association cache, or the user assisted invalidation of calculated cache, the cache consistency of Jimmer is driven by triggers. Jimmer triggers are divided into BinLog triggers and Transaction triggers. For different situations, Jimmer adopts different strategies to ensure cache consistency, that is, to ensure that cache invalidation operations must succeed.","s":"Cache Consistency","u":"/jimmer-doc/docs/cache/consistency","h":"","p":37},{"i":40,"t":"When trigger-type is BINLOG_ONLY or BOTH, Jimmer uses the BinLog trigger to invalidate caches. In this case, developers respond to messaging queue notifications, process them simply and then call Jimmer's BinLog API (this user code is very simple, and its complexity can be ignored). Calling the BinLog API initiates all trigger callbacks, including cache invalidation. Take Kafka as an example, make sure to commit the consumption progress after successfully calling the BinLog API, cache invalidation can be guaranteed to eventually succeed.","s":"Consistency of BinLog Trigger (Recommended)","u":"/jimmer-doc/docs/cache/consistency","h":"#consistency-of-binlog-trigger-recommended","p":37},{"i":42,"t":"When trigger-type is TRANSACTION_ONLY, Jimmer will be forced to use the Transaction trigger to invalidate caches. For Transaction triggers: Only modifying the database through Jimmer's own API can trigger all callback behaviors. All trigger callbacks complete before the transaction is committed. If a simple implementation of direct cache invalidation is adopted, any exception during cache invalidation will cause the transaction to be rolled back. Obviously, this implementation is not reasonable. Therefore, when trigger-type is TRANSACTION_ONLY, the cache invalidation operations perceived by the user will be delayed, they will not be executed immediately, but are stored in the JIMMER_TRANS_CACHE_OPERATOR table. caution Jimmer will automatically create the JIMMER_TRANS_CACHE_OPERATOR table. However, the default org.babyfish.jimmer.sql.dialect.DefaultDialect does not support this operation and will throw an exception. Therefore, if cache consistency needs to be driven by transaction trigger, don't use the default DefaultDialect, please explicitly specify the database dialect. Modifications to the JIMMER_TRANS_CACHE_OPERATOR table and business tables belong to the same database local transaction, either both succeed or both fail. After the transaction commits successfully, Jimmer will immediately execute a Flush operation. The so-called Flush operation is to query cache invalidation operations that have not yet been executed from the JIMMER_TRANS_CACHE_OPERATOR table, execute the actual cache invalidation operation, and delete related records if successful. For the Flush operation executed immediately after transaction commit: If successful, it's best to have good real-time. This should be the case most of the time. Even if it fails, it doesn't matter. Jimmer will periodically execute Flush operations to ensure related cache invalidation eventually succeed. The interval of Flush operations is controlled by the global SpringBoot configuration item jimmer.transaction-cache-operator-fixed-delay, which is specified in milliseconds and defaults to 5000.","s":"Consistency of Transaction Trigger","u":"/jimmer-doc/docs/cache/consistency","h":"#consistency-of-transaction-trigger","p":37},{"i":44,"t":"Calculated cache refers to mapping the current object id to the calculated value of the user-defined complex calculated property.","s":"Calculated Cache","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"","p":43},{"i":46,"t":"In the Complex Calculated Properties article, we discussed complex calculated properties in detail. caution This article focuses on calculated cache and does not repeat the introduction to complex calculated properties. Please read complex calculated properties before reading this article. In this article, we will add cache support for the calculated property BookStore.avgPrice defined in complex calculated properties. info To simplify the documentation, this article only discusses BookStore.avgPrice and does not discuss the other association-based calculated property BookStore.newestBooks. Readers can read and run the following official examples: jimmer-examples/java/jimmer-sql jimmer-examples/java/jimmer-sql-graphql jimmer-examples/kotlin/jimmer-sql-kt jimmer-examples/kotlin/jimmer-sql-graphql-kt","s":"Calculated Property Recap","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#calculated-property-recap","p":43},{"i":48,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...omit code... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { ...omit code... } @Override public Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { ...omit code... } @Override public Cache createResolverCache(ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(1), Duration.ofHours(1) ); } private Cache createPropCache( ImmutableProp prop, Duration caffeineDuration, Duration redisDuration ) { return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...omit code... override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = ...omit code... override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = ...omit code... override fun createResolverCache(prop: ImmutableProp): Cache<*, *> = return createPropCache( prop, Duration.ofMinutes(1), Duration.ofHours(1) ) private fun createPropCache( prop: ImmutableProp, duration: Duration): Cache = ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() } }","s":"Enable Calculated Cache","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#enable-calculated-cache","p":43},{"i":50,"t":"Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; List stores = sqlClient .createQuery(table) .select( table.fetch( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .avgPrice() ) ) .execute(); System.out.println(stores); val stores = sqlClient .createQuery(BookStore::class) { select( table.fetchBy { allScalarFields() avgPrice() } ) } .execute() println(stores) Step 1: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ The query in the code is implemented here to obtain some BookStore objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. Step 2: Convert current object id to calculated value via calculated cache The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return two aggregate root objects. The object fetcher in the code contains the calculated property BookStore.avgPrice The primary keys ID of these 2 BOOK_STOREs are 1 and 2. Jimmer first looks up the data in Redis with keys BookStore.avgPrice-1 and BookStore.avgPrice-2. Suppose the data corresponding to these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* (empty array) So the following SQL is executed to compute the calculated property: select tb_1_.ID, avg(tb_2_.PRICE) from BOOK_STORE tb_1_ left join BOOK tb_2_ on tb_1_.ID = tb_2_.STORE_ID where tb_1_.ID in ( ? /* 1 */, ? /* 2 */ ) group by tb_1_.ID Jimmer will put the query results into Redis, so we can view this data in Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* 1) \"BookStore.avgPrice-2\" 2) \"BookStore.avgPrice-1\" 127.0.0.1:6379> get BookStore.avgPrice-1 \"58.5\" 127.0.0.1:6379> get BookStore.avgPrice-2 \"80.333333\" 127.0.0.1:6379> Thus, the two BookStore objects can obtain the average price of their respective books through their calculated property BookStore.avgPrice. Undoubtedly, before the data in Redis expires, executing the Java/Kotlin code above again will directly return the calculated data from Redis without generating the second SQL statement. Finally, Jimmer concatenates the results of the 3 steps as the final data returned to the user: [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"avgPrice\":58.5 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"avgPrice\":80.333333 } ]","s":"Usage","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#usage","p":43},{"i":53,"t":"info Unlike the fully automatic cache invalidation of object cache and association cache, maintaining the consistency of calculated cache requires user assistance. This is because calculated properties introduce custom calculation rules that the ORM framework cannot understand. For the calculated property BookStore.avgPrice, the following two cases will both invalidate the calculated cache: Modifying the STORE_ID foreign key field of the BOOK record will affect the avgPrice cache data of the two bookstores corresponding to the old and new values. Modifying the PRICE field of the BOOK record will invalidate the avgPrice cache data of the bookstore it belongs to. In the Complex Calculated Properties article, a class BookStoreAvgPriceResolver is defined to support the calculated property BookStore.avgPrice. The code is as follows: Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.TransientResolver; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { @Override public Map resolve(Collection ids) { ...omit code... } @Override public BigDecimal getDefaultValue() { ...omit code... } } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.KTransientResolver import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver( ...omit... ) : KTransientResolver { override fun resolve(ids: Collection): Map { ...omit code... } override fun getDefaultValue(): BigDecimal = ...omit code... } We need to override the following two methods in this class: Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.TransientResolver; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { // Constructor inject sqlClient private final JSqlClient sqlClient; ...other code omitted... @Override Collection getAffectedSourceIds(@NotNull EntityEvent e) { // TODO } @Override Collection getAffectedSourceIds(@NotNull AssociationEvent e) { // TODO } } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.KTransientResolver import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver( // Constructor inject sqlClient private val sqlClient: KSqlClient ) : KTransientResolver { ...other code omitted... override fun getAffectedSourceIds(e: EntityEvent<*>): Collection<*>? { // TODO } override fun getAffectedSourceIds(e: AssociationEvent): Collection<*>? { // TODO } } These two methods are the built-in trigger response methods of TransientResolver that are executed automatically when the database changes. They are responsible for automatically clearing the computed cache when the database changes. Next, let's implement these two methods.","s":"Responding to Triggers","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#responding-to-triggers","p":43},{"i":55,"t":"Users can change the association between BOOK_STORE and BOOK by modifying the STORE_ID foreign key of the BOOK table. This will inevitably affect BookStore.avgPrice of some bookstores. tip If watching for changes to the Book.store one-to-many association, the old and new values before and after the modification are two parent objects that need to be considered separately, making the code slightly more cumbersome. Luckily, the entity model in this example has the reverse one-to-many association BookStore.books. When listening for changes to BookStore.books, we only need to consider the id of the current BookStore object, simplifying the code. Implement getAffectedSourceIds(AssociationEvent) as follows: Java Kotlin @Override public Collection getAffectedSourceIds(AssociationEvent e) { if (sqlClient.getCaches().isAffectedBy(e) && ❶ e.getImmutableProp() == BookStoreProps.BOOKS.unwrap() ❷ ) { return Collections.singletonList(e.getSourceId()); ❸ } return null; } override fun getAffectedSourceIds(e: AssociationEvent): Collection<*>? { if (sqlClient.caches.isAffectedBy(e) && ❶ e.immutableProp == BookProps.BOOKS ❷ ) { return listOf(e.sourceId) ❸ } return null } ❶ If the trigger type is set to BOTH, any modification-caused trigger event notifications will be executed twice. note The 1st time: e.connection is non-null, indicating this is a notification from the Transaction trigger. The 2nd time: e.connection is null, indicating this is a notification from the BinLog trigger. However, the cache consistency maintenance work only needs to be done once, no need to do it twice. sqlClient.caches.isAffectedBy(e) can solve this problem, so that even if the trigger type is set to BOTH, the code here will only execute once. caution No matter whether Jimmer's trigger type is set to BOTH or not, it is recommended to include this check as a disciplinary measure. ❷ If the BookStore.books one-to-many association is modified ❹ Then the sourceId of this association modification event (i.e. the BookStore id) needs to have the computed property cache BookStore.avgPrice cleared. Now let's verify the effect of modifying Book.store: If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK /* Old value: 1, New value: 2 */ set STORE_ID = 2 where ID = 7; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(table) // Old value: 1L, New value: 2L .set(table.store().id, 2L) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { // Old value: 1L, New value: 2L set(table.store.id, 2L) where(table.id eq 7L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book-7] Delete data from redis: [Book.store-7] Delete data from redis: [BookStore.avgPrice-1] ❶ Delete data from redis: [BookStore.books-1] Delete data from redis: [BookStore.avgPrice-2] ❷ Delete data from redis: [BookStore.books-2] ❶ The calculated cache BookStore.avgPrice-1 of the parent object referenced by the old foreign key 1 is deleted. ❷ The calculated cache BookStore.avgPrice-2 of the parent object referenced by the new foreign key 2 is deleted.","s":"When BOOK.STORE_ID is modified","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#when-bookstore_id-is-modified","p":43},{"i":57,"t":"Users can also modify the price of books, which will inevitably affect BookStore.avgPrice of the bookstore it belongs to. Implement getAffectedSourceIds(EntityEvent): Java Kotlin @Override public Collection getAffectedSourceIds(EntityEvent e) { if (sqlClient().getCaches().isAffectedBy(e) && ❶ !e.isEvict() && ❷ e.getImmutableType().getJavaClass() == Book.class) { ❸ Ref storeRef = e.getUnchangedRef(BookProps.STORE); ❹ if (storeRef != null && storeRef.getValue() != null && e.isChanged(BookProps.PRICE)) { ❺ return Collections.singletonList(storeRef.getValue().id()); ❻ } } return null; } override fun getAffectedSourceIds(e: EntityEvent<*>): Collection<*>? { if (sqlClient.caches.isAffectedBy(e) && ❶ !e.isEvict && ❷ e.getImmutableType().javaClass == Book::class.java ❸ ) { val store = e.getUnchangedRef(Book::store)?.value ❹ if (store !== null && e.isChanged(Book::price)) { ❺ return listOf(store.id) ❻ } } return null } ❶ If the trigger type is set to BOTH, any modification-caused trigger event notifications will be executed twice. note The 1st time: e.connection is non-null, indicating this is a notification from the Transaction trigger. The 2nd time: e.connection is null, indicating this is a notification from the BinLog trigger. However, the cache consistency maintenance work only needs to be done once, no need to do it twice. sqlClient.caches.isAffectedBy(e) can solve this problem, so that even if the trigger type is set to BOTH, the code here will only execute once. caution No matter whether Jimmer's trigger type is set to BOTH or not, it is recommended to include this check as a disciplinary measure. ❷ There are two reasons for Jimmer's event callbacks, whether it's EntityEvent or AssociationEvent. Explicitly know that the database has been modified In this case, isEvict() returns false. Users can access any property of EntityEvent/AssociationEvent. In the process of automatic cache eviction with cascading effect, the cache of an object/association needs to be evicted In this case, isEvict() returns true. Except for EntityEvent.id/AssociationEvent.sourceId, the event object does not support any other properties like EntityEvent.newEntity, AssociationEvent.attachedTargetId. Here, we need to explicitly determine if the user has modified the PRICE field of the BOOK table, so we must check isEvict() is false. warning Whether to check e.isEvict() must be decided on a case-by-case basis. ❸ Confirm that the current event was triggered because an object of type Book was modified. ❹ ❺ e.getUnchangedRef(BookProps.STORE)/e.getUnchangedRef(Book::store) returns a Ref wrapper object containing the unchanged associated object (only id property) or null, if the Book.store association based on foreign key was not modified. info If the returned Ref wrapper object itself is null, it means this property was modified rather than being Unchanged. If the returned Ref wrapper object is non-null but its internal value is null, it means this property was not modified and its value has remained null all along. Ultimately, we expect the BOOK.STORE_ID foreign key field was not modified and has remained non-null. tip We don't need to consider the case where the foreign key field was modified here, because the other method we discussed earlier, getAffectedSourceIds(AssociationEvent), will properly handle that case. ❻ If all the above conditions are met, then the computed property cache BookStore.avgPrice of the BookStore parent object that the price-modified Book belongs to needs to be cleared. Now let's verify the effect of modifying Book.price: If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK set PRICE = PRICE + 1 where ID = 7; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(table) .set(table.price(), table.price().plus(BigDecimal.ONE)) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { set(table.price, table.price + BigDecimal.ONE) where(table.id eq 7L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [BookStore.avgPrice-1] ❶ Delete data from redis: [Book-7] ❶ The calculated cache BookStore.avgPrice-1 of the parent object referenced by the foreign key is deleted.","s":"Modifying BOOK.PRICE","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#modifying-bookprice","p":43},{"i":59,"t":"Features represented by permission systems allow different users to see different data. Therefore, Jimmer uses multi-view cache to allow different users to see different caches.","s":"Multi-view Cache","u":"/jimmer-doc/docs/cache/multiview-cache/","h":"","p":58},{"i":62,"t":"Using multi-view caches is relatively strict and the following three conditions must be met at the same time: The properties that need multi-view cache must be explicitly specified. Cache is multi-layered. Multiple Binder objects must be specified for the ChainCacheBuilder used to build the cache instance, i.e. LoadingBinder/KLoadingBinder or SimpleBinder/KSimpleBinder. For multi-view caches, all Binder objects must implement the LoadingBinder.Parameterized/KLoadingBinder.Parameterized or SimpleBinder.Parameterized/KSimpleBinder.Parameterized interface. Otherwise, the final cache created by ChainCacheBuilder is a single-view cache. The filtering rules for association properties and the calculation rules for calculated properties must be cache friendly. For association properties, all global filters that affect their associated objects must be cache friendly filters. If any one filter is not cache friendly, it may cause the all affected properties to be unable to use cache. For user-defined cache filters, the CacheableFilter/KCacheableFilter interface must be implemented. For the @LogicalDeleted, its useMultiViewCache property must be configured as true (this will cause its built-in global filter to implement the CacheableFilter/KCacheableFilter interface). For calculated properties, the getParameterMapRef method of TransientResolver/KTransientResolver must not return null. The object fetch cannot use property-level filters. If these prerequisite conditions are not fully met, even if cache is specified for association or calculated properties, Jimmer will abandon them. Although the reasons have been explained in detail in previous documents, troubleshooting such issues during actual development is inconvenient. To quickly inform developers of the fact that property-level cache did not take effect and the reason, Jimmer defines a callback interface as follows: package org.babyfish.jimmer.sql.cache; import org.babyfish.jimmer.meta.ImmutableProp; public interface CacheAbandonedCallback { void abandoned(ImmutableProp prop, Reason reason); enum Reason { CACHEABLE_FILTER_REQUIRED, PARAMETERIZED_CACHE_REQUIRED, FIELD_FILTER_USED } } This callback interface tells developers that although cache is specified for a property, it is not adopted by Jimmer, and the reason. Its abandoned method has two parameters: prop: Which property does not adopt the cache configured by the user. reason: The reason why the cache of this property is not adopted. There are three possible values: CACHEABLE_FILTER_REQUIRED: The associated objects are affected by some global filters, but not all filters implement the CacheableFilter/KCacheableFilter interface. PARAMETERIZED_CACHE_REQUIRED: The getParameters method of some CacheableFilter/KCacheableFilter objects affecting the association properties or the getParameterMapRef method of TransientResolver/KTransientResolver implementing the calculated properties returns a Map of non-zero length, but the cache configured for that property by the developer is not a multi-view cache. FIELD_FILTER_USED: The developer uses property-level filters for the property in object fetchers. Developers can implement the CacheAbandonedCallback interface themselves, create an object, and register it with SqlClient. There is no limit on the number of registered callback objects.","s":"CacheAbandonedCallback","u":"/jimmer-doc/docs/cache/multiview-cache/abandoned-callback","h":"#cacheabandonedcallback","p":60},{"i":64,"t":"There are two ways to register CacheAbandonedCallback for Jimmer: Using Spring Boot Starter Just decorate the implementation class of CacheAbandonedCallback with @Component: Java Kotlin @Component public class MyCallback implements CacheAbandonedCallback { ...omit code... } @Component class MyCallback : CacheAbandonedCallback { ...omit code... } Using underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .addCacheAbandonedCallback( new CacheAbandonedCallback() { ...omit code... } ) ...omit other configuration... .build(); val sqlClient = newKSqlClient { addCacheAbandonedCallback( object: CacheAbandonedCallback { ...omit code... } ) ...omit other configuration... }","s":"Registering Callback","u":"/jimmer-doc/docs/cache/multiview-cache/abandoned-callback","h":"#registering-callback","p":60},{"i":66,"t":"If no callback implementation is registered by the user, the Spring Boot Starter will register a default callback implementation by default, outputting the reason why the cache is not adopted as a warning log, for example: !!!Jimmer warning!!! Property-level cache is abandoned. Property: `com.yourcompany.yourproject.model.BookStore.books` Reason: CACHEABLE_FILTER_REQUIRED","s":"Default Behavior of Spring Boot Starter","u":"/jimmer-doc/docs/cache/multiview-cache/abandoned-callback","h":"#default-behavior-of-spring-boot-starter","p":60},{"i":70,"t":"Up to now, the caches we have introduced are all single-view caches, where all clients see the same cached data. However, often times, different clients will see different persistent data, which is usually caused by permission systems. Since different clients will see different persistent data, we naturally also expect different clients to see different cache data, that is, the cache provides different views for different clients. Multi-view cache solves this problem very well by allowing different clients to see different caches. caution Unlike previous discussions where cache can be categorized into object cache, association cache and calculated cache, multi-view cache is not adding a new category to the existing taxonomy, but rather another dimension of characteristics. Except for object cache, both association cache and calculated cache can be combined with multi-view cache. Single-view Cache Multi-view Cache Object Cache Object Cache NA Association Cache Single-view Association Cache Multi-view Association Cache Calculated Cache Single-view Calculated Cache Multi-view Calculated Cache info We can refer to association cache and calculated cache together as property cache. Therefore, this table can also be interpreted as property cache can be multi-viewed.","s":"Concepts","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#concepts","p":68},{"i":72,"t":"Multi-view cache is caused by user defined global filters. info As long as an entity is applied with a user defined global filter, all association caches targeting it calculated caches relying on these association caches need to be multi-viewed. For example, if an user defined global filter is added to Book, then properties like: Association properties targeting Book, such as BookStore.books, Author.books Calculated properties relying on the above association properties, such as BookStore.avgPrice, BookStore.newestBooks will be sensitive to the filter, that is, different filtering conditions will result in different data seen by different clients. caution These filter-sensitive properties either do not support cache or support multi-view cache. Configuring single-view cache for them will be considered invalid and the cache configuration will be ignored. Don't worry. Jimmer will tell developers why cache is abandoned.","s":"Scenarios","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#scenarios","p":68},{"i":74,"t":"SubKey is an important concept for multi-view cache and a prerequisite for subsequent documentation. Let's first take a look at the structure of single-view cache Key Value Book-10 {\"id\":10,\"name\":\"GraphQL in Action\",...} Book.authors-1 [1,2] BookStore.avgPrice-2 80.333333 Here we list examples of object cache, association cache and calculated cache. Although the cache types are different, the cache structures are unified simple KV structures. Now let's take a look at an example of multi-view cache: Key SubKey Value BookStore.books-1 {} [6,5,4,3,2,1,9,8,7] {\"tenant\":\"a\"} [5,3,1,9,7] {\"tenant\":\"b\"} [6,4,2,8] {\"module\":\"x\"} [6,5,3,2,9,8] {\"module\":\"x\",\"tenant\":\"a\"} [5,3,9] {\"module\":\"x\",\"tenant\":\"b\"} [6,2,8] {\"module\":\"y\"} [4,1,7] {\"module\":\"y\",\"tenant\":\"a\"} [1,7] {\"module\":\"y\",\"tenant\":\"b\"} [4] BookStore.books-2 {} [12,11,10] {\"tenant\":\"a\"} [11] {\"tenant\":\"b\"} [12,10] {\"module\":\"x\"} [12,11] {\"module\":\"x\",\"tenant\":\"a\"} [11] {\"module\":\"x\",\"tenant\":\"b\"} [12] {} [10] {\"tenant\":\"a\"} [] {\"tenant\":\"b\"} [10] Multi-view cache is no longer a simple KV structure, but a nested two-level KV structure. tip For Redis, this structure is Redis Hashes. In this case, the SubKey in the table is the Hash Key in Redis. Obviously, compared to single-view cache, multi-view cache splits the data into finer granularity by sub key, allowing different clients to see different data. Key The Key in multi-view cache is no different from the key in single-view cache, representing a specific entity property, decided by Jimmer. SubKey The key characteristic of multi-view cache. The permission system allows different clients to have different sub keys, eventually extracting different data from the cache. info In Jimmer, SubKey must be the JSON-serialized string of java.util.SortedMap. This SortedMap must use the default sorting rule without custom Comparator. This is very important. For example, SubKey can only be {\"module\":\"x\",\"tenant\":\"a\"}, not {tenant:\"a\", \"module\":\"x\"} which is different but equivalent. This ensures there is no redundant information internally in multi-view cache. Multi-view cache is only for property cache, i.e. association cache and calculated cache. So association properties and complex calculated properties must specify sub key for their multi-view caches.","s":"SubKey","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#subkey","p":68},{"i":76,"t":"For association properties, the necessity of multi-view cache must be caused by the associated entity being affected by user defined global filters. Supporting multi-view cache by merely implementing the Filter/KFilter interface is not enough. The CacheableFilter/KCacheableFilter interface must be implemented. Java Kotlin CacheableFilter.java package org.babyfish.jimmer.sql.filter; public interface CacheableFilter

extends Filter

{ SortedMap getParameters(); ...other code omitted... } KCacheableFilter.kt package org.babyfish.jimmer.sql.kt.filter interface KCacheableFilter : KFilter { fun getParameters(): SortedMap? ...other code omitted... } Users need to implement the getParameters() method to contribute part of the information to sub key. info When multiple CacheableFilter/KCacheableFilter affect the associated entity, the data returned by the getParameters() method of each filter object is merged together as the SubKey.","s":"SubKey of Association Properties","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#subkey-of-association-properties","p":68},{"i":78,"t":"Implementing complex calculated properties requires implementing the TransientResolver/KTransientResolver interface. Java Kotlin TransientResolver.java package org.babyfish.jimmer.sql; import org.babyfish.jimmer.lang.Ref; import java.util.SortedMap; public interface TransientResolver { default Ref> getParameterMapRef() { return Ref.empty(); } ...other code omitted... } KTransientResolver.kt package org.babyfish.jimmer.sql.kt import org.babyfish.jimmer.lang.Ref interface KTransientResolver : TransientResolver { override fun getParameterMapRef(): Ref?>? = Ref.empty() ...other code omitted... } This method returns the Ref which is the wrapper of SortedMap. If Ref itself is null, it means getting sub key is difficult and multi-view cache cannot be applied to the calculated property. info In this case, Jimmer will tell developers why cache is abandoned. Otherwise, the internal value of Ref represents the sub key of the current calculated property. info When invalidating cache, Jimmer will automatically delete invalid cached by key. Cached items of multi-view cache are always deleted as a whole based on Key rather than partially based on Key + SubKey, to maximize the relative simplicity of multi-view cache.","s":"SubKey of Complex Calculated Properties","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#subkey-of-complex-calculated-properties","p":68},{"i":83,"t":"In the User defined Filters documentation, we introduced that custom global filters need to implement the Filter/KFilter interface. However, ordinary filters defined using this interface are not cache-friendly. Taking the Book entity as an example, if a cache-unfriendly global filter is set for it, it will cause all the following filter-sensitive properties Association properties targeting Book, such as BookStore.books, Author.books Calculated properties relying on the above association properties, such as BookStore.avgPrice, BookStore.newestBooks to become uncacheable. Jimmer uses the CacheableFilter/KCacheableFilter interface to define cache-friendly filters: Java Kotlin CacheableFilter.java package org.babyfish.jimmer.sql.filter; import org.babyfish.jimmer.sql.ast.table.Props; import org.babyfish.jimmer.sql.event.EntityEvent; import java.util.SortedMap; public interface CacheableFilter

extends Filter

{ SortedMap getParameters(); boolean isAffectedBy(EntityEvent e); } KCacheableFilter.kt package org.babyfish.jimmer.sql.kt.filter import org.babyfish.jimmer.sql.event.EntityEvent import java.util.* interface KCacheableFilter : KFilter { fun getParameters(): SortedMap? fun isAffectedBy(e: EntityEvent<*>): Boolean } This interface inherits from Filter/KFilter and adds two new methods: getParameters: The sub key fragment contributed by this filter for multi-view cache. isAffectedBy: Accepts an event that the filtered entity is modified, and judges whether the filtering fields depended on by the current filter are changed. info An entity type allows being processed by multiple global filters: If any one of them is cache-unfriendly, it will cause all filter-sensitive properties to become uncacheable. Therefore, these global filters must either all be cache-unfriendly Filter/KFilter, or all be cache-friendly CacheableFilter/KCacheableFilter. Mixing them together makes no sense. If such meaningless mixing occurs accidentally, Jimmer will tell why cache is abandoned. When all global filters are cache-friendly, the data returned by the getParameters() method of all CacheableFilter/KCacheableFilter objects is merged together as the SubKey of the multi-view cache. For example, if an entity is processed by two global filters at the same time. One is the filter implied by logical delete, denoted as a; the other one is a user-defined filter, denoted as b. Assume a's getParameters() returns {\"logicalDeleted\":false} b's getParameters() returns {\"tenant\":\"a\"} Then the final SubKey in multi-view cache will be {\"logicalDeleted\":false,\"tenant\":\"a\"}","s":"Basic Concepts","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#basic-concepts","p":80},{"i":85,"t":"In the User-defined Filters documentation, we defined a super type TenantAware for entities. Let's review its code again: Java Kotlin TenantAware.java @MappedSuperclass public interface TenantAware { String tenant(); } TenantAware.kt @MappedSuperclass interface TenantAware { val tenant: String } Any entity type that needs to support multiple tenants can inherit TenantAware, such as Book: Java Kotlin Book.java @Entity public interface Book extends TenantAware { ...code omitted... } Book.kt @Entity interface Book : TenantAware { ...code omitted... } Assume there is an object of type TenantProvider in the Spring context. Its Java method get() and Kotlin property tenant are used to extract the tenant from the identity information of the current operator. Define the following filter: Java Kotlin @Component public class TenantFilter implements CacheableFilter { private final TenantProvider tenantProvider; public TenantFilter(TenantProvider tenantProvider) { this.tenantProvider = tenantProvider; } @Override public void filter(FilterArgs args) { String tenant = tenantProvider.get(); if (tenant != null) { args.where(args.getTable().tenant().eq(tenant)); } } @Override public SortedMap getParameters() { String tenant = tenantProvider.get(); if (tenant == null) { return null; } SortedMap map = new TreeMap<>(); map.put(\"tenant\", tenant); return map; } @Override public boolean isAffectedBy(EntityEvent e) { return e.isChanged(TenantAwareProps.TENANT) } } @Component class TenantFilter( private val tenantProvider: TenantProvider ) : KCacheableFilter { override fun filter(args: KFilterArgs) { tenantProvider.tenant?.let { args.apply { where(table.tenant.eq(it)) } } } override fun getParameters(): SortedMap? = tenantProvider.tenant?.let { sortedMapOf(\"tenant\" to it) } override fun isAffectedBy(e: EntityEvent<*>): Boolean = e.isChanged(TenantAware::tenant) }","s":"Define Cache-friendly Filters","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#define-cache-friendly-filters","p":80},{"i":88,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...code omitted... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { ...code omitted... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( prop == BookStoreProps.BOOKS.unwrap() || prop == AuthorProps.BOOKS.unwrap() prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } @Override public Cache createResolverCache(ImmutableProp prop) { return createPropCache( prop == BookStoreProps.AVG_PRICE.unwrap() || prop == BookStoreProps.NEWEST_BOOKS.unwrap() prop, Duration.ofMinutes(1), Duration.ofHours(1) ); } private Cache createPropCache( boolean isMultiviewCache, ImmutableProp prop, Duration caffeineDuration, Duration redisDuration ) { if (isMultiView) { return new ChainCacheBuilder() .add( CaffeineHashBinder .forProp(prop) .maximumSize(128) .duration(caffeineDuration) .build() ) .add( RedisHashBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...code omitted... override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = ...code omitted... override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( prop === BookStore::books.toImmutableProp() || prop === Author::books.toImmutableProp(), prop, Duration.ofMinutes(1), Duration.ofHours(1) ) override fun createResolverCache(prop: ImmutableProp): Cache<*, *> = createPropCache( prop === BookStore::avgPrice.toImmutableProp() || prop === BookStore::newestBooks.toImmutableProp(), prop, Duration.ofMinutes(1), Duration.ofHours(1) ) private fun createPropCache( isMultiView: Boolean, prop: ImmutableProp, caffeineDuration: Duration, redisDuration: Duration ): Cache { if (isMultiView) { return ChainCacheBuilder() .add( CaffeineHashBinder .forProp(prop) .maximumSize(128) .duration(caffeineDuration) .build() ) .add( RedisHashBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() } } } The RedisHashBinder class in the above code is a very important implementation that utilizes Redis' support for multi-view cache. The underlying storage structure corresponds to Redis Hashes, i.e. nested Hash structures. Cache Style Is Multi-view Abstract API Built-in Impl Cache with self-loading (usually first-level cache technologies like Guava, Caffeine) Single-view LoadingBinder CaffeineValueBinder Multi-view LoadingBinder.Parameterized None Cache without self-loading (usually second-level cache technologies like Redis) Single-view SimpleBinder RedisValueBinder Multi-view SimpleBinder.Parameterized RedisHashBinder RedisHashBinder","s":"Simple Approach","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#simple-approach","p":80},{"i":90,"t":"In the above code, the createAssociatedIdListCache method judges the prop parameter to decide whether to build multi-view cache or single-view cache. However, tip For association properties, whether multi-view cache needs to be built can be determined solely by whether the target entity is filtered. Jimmer provides better support for this. Developers only need to replace the super interface CacheFactory/KCacheFactory with the super class AbstractCacheFactory/AbstractKCacheFactory to inherit a member called getFilterState/filterState which can help us determine whether to build multi-view cache. Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new AbstractCacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...code omitted... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( getFilterState().isAffectedBy(prop.getTargetType()), prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( getFilterState().isAffectedBy(prop.getTargetType()), prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } @Override public Cache createResolverCache(ImmutableProp prop) { return createPropCache( prop == BookStoreProps.AVG_PRICE.unwrap() || prop == BookStoreProps.NEWEST_BOOKS.unwrap() prop, Duration.ofSeconds(1), Duration.ofHours(24) ); } private Cache createPropCache( boolean isMultiviewCache, ImmutableProp prop, Duration duration ) { ...code omitted... } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: AbstractKCacheFactory() { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...code omitted... override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( filterState.isAffectedBy(prop.targetType), prop, Duration.ofMinutes(5), Duration.ofHours(5) ) override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( filterState.isAffectedBy(prop.targetType), prop, Duration.ofMinutes(5), Duration.ofHours(5) ) override fun createResolverCache(prop: ImmutableProp): Cache<*, *> = createPropCache( prop === BookStore::avgPrice.toImmutableProp() || prop === BookStore::newestBooks.toImmutableProp(), prop, Duration.ofHours(1), Duration.ofHours(24) ) private fun createPropCache( isMultiView: Boolean, prop: ImmutableProp, caffeineDuration: Duration, redisDuration: Duration ): Cache { ...code omitted... } } } info Unfortunately, this method can only simplify the construction of association caches, i.e. simplify the createAssociatedIdCache and createAssociatedIdListCache methods. For calculated properties, since the framework is unaware of the internal logic used by user-defined calculated properties, it cannot simplify them. Users need to decide whether to build multi-view caches based on their own business characteristics.","s":"Better Approach","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#better-approach","p":80},{"i":92,"t":"We have defined the getParameters method in TenantFilter. All affected association properties will automatically specify SubKey for their association caches. However, unfortunately, due to the introduction of user-defined calculation rules that the framework cannot understand, developers must manually specify SubKey for the TransientResolver implementation of calculated properties. Java Kotlin BookStoreAvgPriceResolver.java @Component public class BookStoreAvgPriceResolver implements TransientResolver { private final JSqlClient sqlClient; @Override public Ref> getParameterMapRef() { return sqlClient .getFilters() .getTargetParameterMapRef(BookStoreProps.BOOKS); } ...code omitted... } BookStoreAvgPriceResolver.kt @Component class BookStoreAvgPriceResolver( private val sqlClient: KSqlClient ) : KTransientResolver { override fun getParameterMapRef(): Ref?>? { return sqlClient .filters .getTargetParameterMapRef(BookStore::books) } ...code omitted... } Obviously, the calculated property BookStore.avgPrice is actually determined by the association property BookStore.books and changes with it. Therefore, whatever SubKey the association property BookStore.books specifies for the multi-view cache system in the current invocation context, the calculated property BookStore.avgPrice should specify the same one. note BookStore.avgPrice is also affected by Book.price. It changes when Book.price changes. However, Book.price is a non-associative property of the object, so it must be irrelevant to the multi-view cache system. The getParameterMapRef method does not need to consider it here.","s":"SubKey of Calculated Properties","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#subkey-of-calculated-properties","p":80},{"i":94,"t":"Now that we have made the association property BookStore.books and the calculated property BookStore.avgPrice support multi-view caching, let's use object fetchers to query them: Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; List stores = sqlClient .createQuery(table) .select( table.fetch( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .books( ❶ Fetchers.BOOK_FETCHER .allScalarFields() ) .avgPrice() ❷ ) ) .execute(); System.out.println(stores); val stores = sqlClient .createQuery(BookStore::class) { select( table.fetchBy { allScalarFields() books { ❶ allScalarFields() } avgPrice() ❷ } ) } .execute() println(stores)","s":"Usage","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#usage","p":80},{"i":96,"t":"Assume the current tenant name is a, the execution process is as follows: First step: Query aggregate root First query the aggregate root object by executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ Here the query in the code is implemented to get some BookStore objects. Such objects directly queried by the user are called aggregate root objects. Second step: Query BookStore.books in ❶ through association cache The above code will get a series of aggregate root objects. If using the official example data, it will get two aggregate root objects with ID of 1 and 2 for BOOK_STORE. Jimmer first looks up the data from Redis. The keys looked up are BookStore.books-1 and BookStore.books-2. Assume the data for these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.books-* (empty array) So the following SQL is executed to complete the associated property BookStore.books: SQL: select, tb_1_.STORE_ID, tb_1_.ID from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and tb_1_.TENANT = ? /* a */ order by tb_1_.NAME asc, tb_1_.EDITION desc info The filter condition tb_1_.TENANT = 'a' comes from the user filter TenantFilter. Jimmer will put the query result into Redis. So we can view the data from Redis: 127.0.0.1:6379> keys BookStore.books-* 1) \"BookStore.books-2\" 2) \"BookStore.books-1\" 127.0.0.1:6379> hgetall BookStore.books-1 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"[5,3,1,9,7]\" 127.0.0.1:6379> hgetall BookStore.books-2 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"[11]\" info Jimmer uses Redis Hash for multi-perspective cache. So hgetall instead of get is needed. Redis Hash is a nested KV structure: The outer Redis Key, e.g. BookStore.books-1 and BookStore.books-2, is no different from single-perspective cache. The inner Hash Key, also called SubKey in Jimmer, is provided by global filters. Here, {\"tenant\":\"a\"} is provided by TenantProvider, indicating the cached value is not the id set of all associated objects, but the id set of associated objects visible to tenant a. tip Undoubtedly, executing the above Java/Kotlin code again with the same tenant identity before data expiration in Redis, it will directly return associated data from Redis without generating related SQL. Third step: Convert id set to associated objects In the previous step we got the id set of associated objects corresponding to associated property BookStore.books, representing the associated objects visible to tenant a. Now we can use the object cache of Book to convert the Book id set into Book object set. This step is very simple without further discussion. Fourth step: Query BookStore.avgPrice in ❷ through computation cache The above code will get a series of aggregate root objects. If using the official example data, it will get two aggregate root objects with ID of 1 and 2 for BOOK_STORE. Jimmer first looks up the data from Redis. The keys looked up are BookStore.avgPrice-1 and BookStore.avgPrice-2. Assume the data for these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* (empty array) So the following SQL is executed to compute the calculation property: select tb_1_.ID, avg(tb_2_.PRICE) from BOOK_STORE tb_1_ left join BOOK tb_2_ on tb_1_.ID = tb_2_.STORE_ID where tb_1_.ID in ( ? /* 1 */, ? /* 2 */ ) and tb_1_.TENANT = ? /* a */ group by tb_1_.ID info The filter condition tb_1_.TENANT = 'a' comes from the user filter TenantFilter. Jimmer will put the query result into Redis. So we can view the data from Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* 1) \"BookStore.avgPrice-2\" 2) \"BookStore.avgPrice-1\" 127.0.0.1:6379> hgetall BookStore.avgPrice-1 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"53.1\" 127.0.0.1:6379> hgetall BookStore.avgPrice-2 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"81\" info Jimmer uses Redis Hash for multi-perspective cache. So hgetall instead of get is needed. Redis Hash is a nested KV structure: The outer Redis Key, e.g. BookStore.avgPrice-1 and BookStore.avgPrice-2, is no different from single-perspective cache. The inner Hash Key, also called SubKey in Jimmer, is provided by global filters. Here, {\"tenant\": \"a\"} is provided by TenantProvider, indicating the cached value is not the average price of all associated objects, but the average price of associated objects visible to tenant a. tip Undoubtedly, executing the above Java/Kotlin code again with the same tenant identity before data expiration in Redis, it will directly return associated data from Redis without generating related SQL. Finally, Jimmer concatenates the results of the 4 steps and returns them to the user. [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81 } ], \"avgPrice\":81 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":5, \"name\":\"Effective TypeScript\", \"edition\":2, \"price\":69 }, { \"id\":3, ...omitted... }, { \"id\":1, ...omitted... }, { \"id\":9, ...omitted... }, { \"id\":7, ...omitted... } ], \"avgPrice\":53.1 } ]","s":"Execute with one tenant identity","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#execute-with-one-tenant-identity","p":80},{"i":98,"t":"The query execution process with tenant a has been discussed. Similarly, we can execute multiple times using different tenant identities to leave cache data in Redis from the following perspectives: tenant = null tenant = \"a\" tenant = \"b\" info For the official example, TenantProvider is implemented based on HTTP request header and has swagger UI support. It's easy to execute three times with three different user identities. Among them, tenant = null corresponds to the unauthorized/logout state in swagger UI. Open redis-cli, we can verify the data in Redis: 127.0.0.1:6379> keys BookStore.books-* 1) \"BookStore.books-2\" 2) \"BookStore.books-1\" 127.0.0.1:6379> hgetall BookStore.books-1 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"[6,4,2,8]\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"[5,3,1,9,7]\" 5) \"{}\" 6) \"[6,5,4,3,2,1,9,8,7]\" 127.0.0.1:6379> hgetall BookStore.books-2 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"[12,10]\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"[11]\" 5) \"{}\" 6) \"[12,11,10]\" 127.0.0.1:6379> keys BookStore.avgPrice-* 1) \"BookStore.avgPrice-2\" 2) \"BookStore.avgPrice-1\" 127.0.0.1:6379> hgetall BookStore.avgPrice-1 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"65.25\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"53.1\" 5) \"{}\" 6) \"58.500000\" 127.0.0.1:6379> hgetall BookStore.avgPrice-2 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"80\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"81\" 5) \"{}\" 6) \"80.333333\" tip Readers can take a close look at these redis-cli commands and easily find that the data of sub key {\"tenant\":\"a\"} merged with the data of sub key {\"tenant\":\"b\"} is exactly the data of SubKey {}. The data returned to the user in the 3 calls is: tenant=null tenant=a tenant=b [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80, }, { \"id\":11, ...omitted... }, { \"id\":10, ...omitted... } ], \"avgPrice\":80.333333 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, \"price\":88 }, { \"id\":5, ...omitted... }, { \"id\":4, ...omitted... }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51 }, { \"id\":2, ...omitted... }, { \"id\":1, ...omitted... }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48 }, { \"id\":8, ...omitted... }, { \"id\":7, ...omitted... } ], \"avgPrice\":58.5 } ] [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81 } ], \"avgPrice\":81 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":5, \"name\":\"Effective TypeScript\", \"edition\":2, \"price\":69 }, { \"id\":3, ...omitted... }, { \"id\":1, ...omitted... }, { \"id\":9, ...omitted... }, { \"id\":7, ...omitted... } ], \"avgPrice\":53.1 } ] [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80 }, { \"id\":10, ...omitted... } ], \"avgPrice\":80 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, \"price\":88 }, { \"id\":4, ...omitted... }, { \"id\":2, ...omitted... }, { \"id\":8, ...omitted... } ], \"avgPrice\":65.25 } ]","s":"Execute repeatedly with multiple tenant identities","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#execute-repeatedly-with-multiple-tenant-identities","p":80},{"i":100,"t":"Now let's modify the property Book.tenant of the Book object with id 6 from \"b\" to \"a\". Since Book-6 belongs to BookStore-1, it is foreseeable that the multi-view caches corresponding to the properties BookStore.books-1 and BookStore.avgPrice-1 will definitely be invalidated. If BinLog trigger is enabled, modifying the database in any way can lead to Jimmer's cache consistency involvement. For example, directly executing the following SQL in SQL IDE: update BOOK set TENANT = 'a' where ID = 6; If only Transaction trigger is enabled, the database must be modified using Jimmer's API: Java Kotlin sqlClient.save( Immutables.createBook(draft -> { draft.setId(6L); draft.setTenant(\"a\"); }) ); sqlClient.save( Book { id = 6L tenant = \"a\" } ) No matter which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book-6] ❶ Delete data from redis: [Author.books-3] ❷ Delete data from redis: [BookStore.books-1] ❸ Delete data from redis: [BookStore.avgPrice-1] ❹ ❶ Update object cache of modified entity ❷ Any association property targeting Book must be affected, of course including Author.books According to existing database data, the affected Author object id is 3 ❸ Any association property targeting Book must be affected, of course including BookStore.books According to existing database data, the affected BookStore object id is 1 ❹ The calculated cache BookStore.avgPrice of BookStore object with id 1 is also affected. This is the most amazing characteristic. Although the framework is unaware of the calculation rule used by users in calculated properties, in the Calculated Cache documentation, we discussed the following code in the BookStoreAvgPriceResolver class: Java Kotlin @EventListener public void onAssociationChange(AssociationEvent e) { if (sqlClient.getCaches().isAffectedBy(e) && e.isChanged(BookStoreProps.BOOKS) ) { ...code omitted... } } @EventListener fun onAssociationChange(e: AssociationEvent) { if (sqlClient.caches.isAffectedBy(e) && e.isChanged(BookStore::books) ) { ...code omitted... } } If you have forgotten the specific logic of this code, you can review the Calculated Cache documentation. Just focus on the highlighted line. Here, this calculated property cares about changes to the association property BookStore.books. tip Modifying the association field between tables is not the only way to trigger association change events. Modifying the filtered field in associated objects that affects global filters, like TENANT here, can also trigger association change events. This is a very important characteristic of Jimmer's trigger mechanism! It is obvious that ❸ has already sensed the change of association property BookStore.books, so it will further lead to the invalidation of the calculated cache here.","s":"Cache Invalidation","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#cache-invalidation","p":80},{"i":103,"t":"To enable cache, you first need to implement the CacheFactory/KCacheFactory interface, which is defined as follows: Java Kotlin CacheFactory.java package org.babyfish.jimmer.sql.cache; import org.babyfish.jimmer.meta.ImmutableProp; import org.babyfish.jimmer.meta.ImmutableType; import org.jetbrains.annotations.NotNull; import org.jetbrains.annotations.Nullable; import java.util.List; public interface CacheFactory { @Nullable default Cache createObjectCache(@NotNull ImmutableType type) { return null; } @Nullable default Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return null; } @Nullable default Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { return null; } @Nullable default Cache createResolverCache(@NotNull ImmutableProp prop) { return null; } } KCacheFactory.kt package org.babyfish.jimmer.sql.kt.cache import org.babyfish.jimmer.meta.ImmutableProp import org.babyfish.jimmer.sql.cache.Cache import org.babyfish.jimmer.sql.cache.CacheFactory interface KCacheFactory : CacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = null override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = null override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = null override fun createResolverCache(prop: ImmutableProp): Cache<*, *>? = null } info For Kotlin, in order to generate better code when overriding createAssociatedIdListCache, please implement the org.babyfish.jimmer.sql.kt.cache.KCacheFactory interface. Otherwise, the return type of the override method generated by the IDE will be Cache<*, MutableList<*>> instead of the expected Cache<*, List<*>>. Jimmer calls this interface to initialize caches for types and properties. Users implement this interface to answer: createObjectCache: Enable object cache The parameter specifies an entity type. If you want to enable object cache for it, create and return the cache; otherwise, return null. Object cache refers to mapping id to entity object. info This entity object is orphaned, without associated properties. One-to-one/many-to-one associations based on foreign keys are an exception, they can hold associated objects with only the id property, because the id of the associated object is actually the foreign key field of the current table. createAssociatedIdCache and createAssociatedIdListCache: Enable association cache Both createAssociatedIdCache and createAssociatedIdListCache are used to enable association cache. The only difference between them is: createAssociatedIdCache: For one-to-one or many-to-one associations. createAssociatedIdListCache: For one-to-many or many-to-many associations. The parameter specifies an association property. If you want to enable association cache for it, create and return the cache; otherwise return null. Association cache refers to mapping id to associated id or associated id collection. createResolverCache: Enable calculated cache The parameter specifies a complex calculated property. If you want to enable calculated cache for it, create and return the cache; otherwise, return null. Computed cache refers to mapping id to calculated result.","s":"CacheFactory Interface","u":"/jimmer-doc/docs/cache/enable-cache","h":"#cachefactory-interface","p":101},{"i":105,"t":"The return type of all methods of the CacheFactory interface is org.babyfish.jimmer.sql.cache.Cache. Users do not need to directly implement Cache, but need to use org.babyfish.jimmer.sql.cache.chain.ChainCacheBuilder to build multi-level caches. In theory, ChainCacheBuilder supports caches of any number of levels. However, in most projects, two levels of cache are sufficient, for example: Java Kotlin return new CacheFactory() { @Override @Nullable public Cache createObjectCache(@NotNull ImmutableType type) { return new ChainCacheBuilder<>() .add( ❶ CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(Duration.ofSeconds(10)) .build() ) .add( ❷ RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(10)) .build() ) ) .build(); } }; return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ChainCacheBuilder() .add( ❶ CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(Duration.ofSeconds(10)) .build() ) .add( ❷ RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(10)) .build() ) ) .build() } ❶ Indicates first level cache based on Caffeine in-process JVM cache. ❷ Indicates second level cache based on Redis remote cache. As we can see, ChainCacheBuilder uses chain programming style. Calling the add method multiple times can build multi-level caches. The ChainCacheBuilder.add method is defined as follows: public class ChainCacheBuilder { public ChainCacheBuilder add(LoadingBinder binder) { ❶ ...omit code... return this; } public ChainCacheBuilder add(LoadingBinder.Parameterized binder) { ❷ ...omit code... return this; } public ChainCacheBuilder add(SimpleBinder binder) { ❸ ...omit code... return this; } ...omit other code... } ❶ org.babyfish.jimmer.sql.cache.chain.LoadingBinder is an interface. Any cache technology that automatically loads values on first access to a key can be adapted through this interface. Almost all in-process JVM caches have automatic loading capabilities, such as Caffeine or Guava Cache used in the above code. ❷ The code is only used by multi-view caches. Readers can ignore it for now. ❸ org.babyfish.jimmer.sql.cache.chain.SimpleBinder is an interface. Any cache technology without automatic value loading behavior can be adapted through this interface. Almost all remote caches do not have automatic loading capabilities, such as Redis used in the above code. tip Any cache technology can be adapted to the abstract interfaces LoadingBinder or SimpleBinder. Therefore, in Jimmer's multi-level cache architecture, no assumptions or restrictions are made on the choice of cache technology at any level. If using Jimmer's SpringBoot Starter, you can use the following three cache technology adapter classes, as in the code above: Jimmer's built-in adapter classes Implemented Interface Supports Multi-view Cache org.babyfish.jimmer.spring.cache.CaffeineBinder org.babyfish.jimmer.sql.cache.chain.LoadingBinder No org.babyfish.jimmer.spring.cache.RedisValueBinder org.babyfish.jimmer.sql.cache.chain.SimpleBinder No org.babyfish.jimmer.spring.cache.RedisHashBinder org.babyfish.jimmer.sql.cache.chain.SimpleBinder.Parameterized Yes note Multi-view caches will be explained in a subsequent article. Please ignore them for now.","s":"Multi-level Cache Architecture","u":"/jimmer-doc/docs/cache/enable-cache","h":"#multi-level-cache-architecture","p":101},{"i":107,"t":"Now we have introduced the CacheFactory interface and multi-level cache architecture, but there is one last step to enable cache. The last step is to register CacheFactory for Jimmer.","s":"Configuring CacheFactory","u":"/jimmer-doc/docs/cache/enable-cache","h":"#configuring-cachefactory","p":101},{"i":109,"t":"If using SpringBoot Starter, just let CacheFactory be managed by Spring. Java Kotlin @Bean public CacheFactory cacheFactory() { return new CacheFactory() { ...omit code... }; } @Bean fun cacheFactory(): KCacheFactory = object: KCacheFactory { ...omit code... }","s":"SpringBoot Configuration","u":"/jimmer-doc/docs/cache/enable-cache","h":"#springboot-configuration","p":101},{"i":111,"t":"Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setCacheFactory( new CacheFactory() { ...omit code... } ) ...omit other configuration... .build(); val sqlClient = newKSqlClient { setCacheFactory( object: KCacheFactory { ...omit code... } ) ...omit other configuration... }","s":"Underlying API Configuration","u":"/jimmer-doc/docs/cache/enable-cache","h":"#underlying-api-configuration","p":101},{"i":113,"t":"Earlier we mentioned that if using Jimmer's SpringBoot Starter, you can use the ready-made org.babyfish.jimmer.spring.cache.RedisValueBinder without having to adapt Redis yourself. note RedisHashBinder is related to multi-view caches and will not be discussed in this article. To build RedisValueBinder, you need a RedisOperations. Jimmer's SpringBoot Stater provides the org.babyfish.jimmer.spring.cache.RedisCaches class whose static method RedisCaches.cacheRedisTemplate can quickly build this RedisOperations object. An example of the helper method RedisCaches.cacheRedisTemplate is as follows: Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override @Nullable public Cache createObjectCache(@NotNull ImmutableType type) { return new ChainCacheBuilder() .add( CaffeineValueBinder .forProp() .maximumSize(1024) .duration(RedisCaches.ofMinutes(24)) .bind() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build(); } @Override @Nullable public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ); } @Override @Nullable public Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5), ); } @Override @Nullable public Cache createResolverCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } private Cache createPropCache( ImmutableProp prop, Duration caffeineDuration Duration redisDuration ) { return new ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ChainCacheBuilder() .add( CaffeineValueBinder .forObject(type) .maximumSize(1024) .duration(Duration.ofHours(1)) .build() ) .add( RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build() override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ) override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ) override fun createResolverCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ) private fun createPropCache( type: ImmutableType, caffeineDuration: Duration, redisDuration: Duration ): Cache<*, *> = ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() } }","s":"Redis Cache Helper APIs","u":"/jimmer-doc/docs/cache/enable-cache","h":"#redis-cache-helper-apis","p":101},{"i":115,"t":"This section introduces the global configurations supported by Jimmer.","s":"Configuration","u":"/jimmer-doc/docs/configuration/","h":"","p":114},{"i":117,"t":"SqlClient supports two configurations: DefaultBatchSize and DefaultListBatchSize. If not configured, the default values are 128 and 16. These two configurations provide default values for the batchSize in Object Fetcher. Their effects have been described in detail in Object Fetcher, so this article only explains the configuration without repeating the explanation of their effects. There are two ways to set these configurations: Use Spring Boot Starter Don't use Spring Boot Starter","s":"Batch Control","u":"/jimmer-doc/docs/configuration/batch-size","h":"","p":116},{"i":119,"t":"jimmer: default-batch-size: 256 default-list-batch-size: 32","s":"Use Spring Boot Starter","u":"/jimmer-doc/docs/configuration/batch-size","h":"#use-spring-boot-starter","p":116},{"i":121,"t":"Java Kotlin @Bean public JSqlClient sqlClient() { return JSqlClient .newBuilder() .setConnectionManager(...) .setDialect(new H2Dialect()) .setExecutor(...) .addScalarProvider(...) .setDefaultBatchSize(256) .setDefaultListBatchSize(32) .build(); } @Bean fun sqlClient(): KSqlClient = newKSqlClient { setConnectionManager { ... } setDialect(H2Dialect()) setExecutor { ... } addScalarProvider { ... } setDefaultBatchSize(256) setDefaultListBatchSize(32) }","s":"Don't use Spring Boot Starter","u":"/jimmer-doc/docs/configuration/batch-size","h":"#dont-use-spring-boot-starter","p":116},{"i":123,"t":"This configuration is explained in Cache Section/Multiview Cache/Cache Abandoned Reason. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Cache Abandoned Reason","u":"/jimmer-doc/docs/configuration/cache-abandoned","h":"","p":122},{"i":126,"t":"In Jimmer, all executable statements and instructions support two execution modes: Execute based on the JDBC connection specified by the user Executed by Jimmer automatically determining based on a JDBC connection Here, take Executable (Java) or KExecutable (Kotlin) interface as an example Java Kotlin Executable.java package org.babyfish.jimmer.sql.ast; import java.sql.Connection; public interface Executable { R execute(); R execute(Connection con); } KExecutable.kt package org.babyfish.jimmer.sql.kt import java.sql.Connection interface KExecutable { fun execute(con: Connection? = null): R } execute(Connection): Execute on the JDBC connection specified by the user. Take query as an example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select(book) .execute(con); val books = sqlClient .createQuery(Book::class) { select(table) } .execute(con) info For this usage, no special configuration of SqlClient is required. execute() or execute(null): Determined by Jimmer to execute on a JDBC connection. Take query as an example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { select(table) } .execute() info For this usage, ConnectionManager must be configured for SqlClient. Otherwise it will cause exceptions. Undoubtedly, the 2nd approach is more in line with the requirements of business system development, so it is recommended. So it is strongly recommended to configure ConnectionManager for SqlClient.","s":"Concept","u":"/jimmer-doc/docs/configuration/connection-manager","h":"#concept","p":124},{"i":128,"t":"Java Kotlin javax.sql.DataSource dataSource = ...; JSqlClient sqlClient = JSqlClient .newBuilder() .setConnectionManager( ConnectionManager .simpleConnectionManager(dataSource) ) .build(); val dataSource: javax.sql.DataSource = ... val sqlClient = newKSqlClient { setConnectionManager { dataSource.connection.use { proceed(it) } } } danger This way is only responsible for getting connections from DataSource and has no transaction management mechanism. However, transactions are very important in actual projects. Therefore, except for learning and trying, it is not recommended to use this approach in actual projects.","s":"Simple ConnectionManager","u":"/jimmer-doc/docs/configuration/connection-manager","h":"#simple-connectionmanager","p":124},{"i":130,"t":"This topic has been discussed in detail in Spring Section/Integrate Spring Transaction. This article will not repeat the explanation. tip Letting Jimmer be managed by Spring transaction is the recommended usage.","s":"ConnectionManager managed by Spring transaction","u":"/jimmer-doc/docs/configuration/connection-manager","h":"#connectionmanager-managed-by-spring-transaction","p":124},{"i":132,"t":"This configuration is explained in Mapping Section/Base Mapping/Naming Strategy. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Default Naming Strategy","u":"/jimmer-doc/docs/configuration/default-database-stragegy","h":"","p":131},{"i":135,"t":"Admittedly, Jimmer's strongly typed SQL DSL can expose problems as much as possible at compile time, and most errors can be prevented before testing. But this is not enough. The strongly typed SQL DSL can only improve the reliability of the entity model -> business code link, but cannot guarantee the reliability of the database structure -> entity model link. There is also a derived problem. If developers get reliable applications in the test environment, how to ensure that the application remains reliable after being transplanted to the production environment? Database validation is a very important feature that is used to verify the consistency between the database structure and the entity model definition. info Validation Rules Verify that table names, column names, sequence names are consistent with definitions in the entity model. Verify that the nullity of columns is consistent with the definitions of properties in the entity model. If a property is decorated with @OneToOne(inputNotNull = true) or @ManyToOne(inputNotNull = true), the nullity of the property itself is ignored. it is considered that the corresponding foreign key in the data cannot be null. For the id property of each entity in the entity model, verify that the database has a primary key constraint that exactly matches. For true foreign keys defined in the entity model (see True and False Foreign Keys), verify that the database has exactly matching foreign key constraints.","s":"Function Introduction","u":"/jimmer-doc/docs/configuration/database-validation","h":"#function-introduction","p":133},{"i":137,"t":"There are two ways to start validation: Use Spring Boot Starter Modify application.yml (or application.properties) jimmer: database-validation-mode: ERROR Use underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseValidationMode( DatabaseValidationMode.ERROR ) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseValidationMode( DatabaseValidationMode.ERROR ) ...Omit other configurations... } DatabaseValidationMode is an enum type with three values: NONE: Don't validate database structure, this is the default behavior. WARNING: Validate database structure, if the database structure is inconsistent with the entity model definition, it does not prevent the program from running, just prints warning information in the log. ERROR: Validate database structure, if the database structure is inconsistent with the entity model definition, an exception will be thrown to prevent the program from running.","s":"Enable Validation","u":"/jimmer-doc/docs/configuration/database-validation","h":"#enable-validation","p":133},{"i":139,"t":"Entity types must correspond to a table in the database, whether the table name is explicitly configured by the developer via @Table or automatically determined by the naming strategy. Association properties based on join tables must correspond to a real join table in the database, whether the table name is explicitly configured by the developer via @JoinTable or automatically determined by the naming strategy. The ID whose auto growth strategy is SEQUENCE must correspond to a sequence in the database, whether the sequence name is explicitly configured by the developer via @GeneratedValue or automatically determined by the naming strategy . When the program starts, Jimmer needs to query the database metadata to verify whether these tables or sequences exist. And if they exist, whether their internal structures are correct (for tables). However, since database often support multiple sub-databases, and sub-databases can authorize each other, the JDBC connection may see tables with the same name in different database users, such as db1.BOOK, db2.BOOK, and db3.BOOK. This is called table conflict. Of course, Jimmer can extract the database name from the JDBC connection metadata, for example, extract \"db1\" from jdbc:mysql://localhost:3306/db1, and first look for table information in the automatically extracted sub-database for verification. However, this method is not always valid. As long as the specified table cannot be found in the current sub-database, it will look for it in other sub-databases, which may lead to table conflict issues. To solve this problem, the following two methods are available: Specify strict table names or sequence names, for example: Change @Table(name = \"BOOK\") to @Table(name = \"db1.BOOK\"). Change @JoinTable(name = \"BOOK_AUTHOR_MAPPING\") to @JoinTable(name = \"db1.BOOK_AUTHOR_MAPPING\"). Change @GeneratedValue(sequenceName = \"BOOK_ID_SEQ\") to @GeneratedValue(sequenceName = \"db1.BOOK_ID_SEQ\"). Explicitly specify the sub-database name used for validation, which can be divided into two methods: There are two ways to start validation Use Spring Boot Starter Modify application.yml (or application.properties) jimmer: database-validation: mode: ERROR catalog: db1 info jimmer.database-validation-mode and jimmer.database-validation.mode are equivalent Use underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseValidationMode( DatabaseValidationMode.ERROR ) .setDatabaseValidationCatalog(\"db1\") ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseValidationMode( DatabaseValidationMode.ERROR ) setDatabaseValidationCatalog(\"db1\") ...Omit other configurations... } Similarly, schema can also be specified, for example: Direct configuration: @Table(name = \"mydatabase.myschema.BOOK\") Configure in SpringBoot's application.yml file jimmer: database-validation: mode: ERROR catalog: mydatabase schema: myschema Underlying API configuration Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseValidationMode( DatabaseValidationMode.ERROR ) .setDatabaseValidationCatalog(\"mydatabase\") setDatabaseValidationSchema(\"myschema\") ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseValidationMode( DatabaseValidationMode.ERROR ) setDatabaseValidationCatalog(\"mydatabase\") setDatabaseValidationSchema(\"myschema\") ...Omit other configurations... }","s":"Resolve Table Conflicts","u":"/jimmer-doc/docs/configuration/database-validation","h":"#resolve-table-conflicts","p":133},{"i":141,"t":"Sometimes developers are developing a new feature that is incomplete and cannot be verified. Developers will naturally not run unfinished features and expect unfinished parts not to verify the database structure. For this, Jimmer provides the annotation @org.babyfish.jimmer.sql.DatabaseValidationIgnore. This annotation has the following two usages: Annotate entity interfaces to indicate that the entire entity does not need to be verified. Annotate entity properties to indicate that specific properties do not need to be verified.","s":"Temporarily ignore partial validation","u":"/jimmer-doc/docs/configuration/database-validation","h":"#temporarily-ignore-partial-validation","p":133},{"i":143,"t":"This configuration is explained in Mapping Section/Advanced Mapping/Enum Mapping/Don't explicitly use @EnumType. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Default Enum Strategy","u":"/jimmer-doc/docs/configuration/default-enum-strategy","h":"","p":142},{"i":146,"t":"If using Jimmer to build backend systems, developers have three ways to solve the DTO Explosion Description Where object shapes are restricted Client experience Solution 1 Use Jimmer to build GraphQL services Client side Good Solution 2 Use Jimmer to build REST services, shapes specified by client Client side Bad Solution 3 Use Jimmer to build REST services, shapes enumerated by server Server side Good Let's discuss the three cases separately:","s":"Basic Concepts","u":"/jimmer-doc/docs/client/api","h":"#basic-concepts","p":144},{"i":148,"t":"Use Jimmer to build GraphQL services Server: Develop GraphQL Backend with Jimmer Client: Many client frameworks to choose from. Using my graphql-ts-client can get the ultimate TypeScript experience caution Jimmer itself supports recursive query of self-associated properties, but so far, the GraphQL protocol does not support this feature, which means the feature will be lost.","s":"Solution 1 (GraphQL)","u":"/jimmer-doc/docs/client/api","h":"#solution-1-graphql","p":144},{"i":150,"t":"Use Jimmer to build REST services, shapes specified by client This approach actually gives REST the capabilities of GraphQL. The client passes a string, and the server parses it into a Fetcher via org.babyfish.jimmer.sql.fetcher.compiler.FetcherCompiler Java Kotlin BookController.java @GetMapping(\"/book/{id}\") public Book findBookById( @PathVariable long id, @RequestParam(required = false) String fetcherCode ) { Fetcher fetcher = FetcherCompiler.compile(fetcherCode, Book.class); return bookRepository.findNullable(id, fetcher); } BookController.kt @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long, @RequestParam(required = false) fetcherCode: String? ): Book? = bookRepository.findNullable( id, FetcherCompiler.compile(fetcherCode, Book::class.java) ) When calling, specify the fetcherCode parameter, for example { id name authors { id firstName lastName } } or { id, name, authors { id, firstName, lastName }} info To learn how to express more complex object fetcher in string code, refer to the toString() method of object fetcher. caution Although this approach can give REST capabilities similar to GraphQL, which is very flexible, it only facilitates server-side writing. The client will get a messy type system, so it is not recommended. If due to some historical constraints, the client uses JavaScript, not TypeScript, and there is no foreseeable hope of any improvement, then consider this usage.","s":"Solution 2 (Not Recommended)","u":"/jimmer-doc/docs/client/api","h":"#solution-2-not-recommended","p":144},{"i":152,"t":"Use Jimmer to build REST services, shapes enumerated by server This usage is more in line with the original intention of the REST protocol, and it is also easier to manage permissions (although the previous two usages are flexible, permission control is very difficult), and it is also the topic to be discussed in this article. info The case discussed here is when the server API returns dynamic entities (recommended), not DTOs. Let's look at a contradiction first Jimmer uses dynamic entities. As long as the root entity types are the same, any data structure shape can be expressed with the same Java/Kotlin type. The client needs to see rich data types. The shapes returned by the same entity type in different HTTP interfaces are different. This contradiction is essentially the difference in awareness of DTO Explosion Server perspective is producer perspective. From the producer's point of view, DTO explosion is a very annoying problem, which means that their own development costs will also increase dramatically. Therefore, Jimmer uses dynamic entities combined with object fetchers to eliminate DTO explosions on the server side. Client perspective is consumer perspective. From the consumer's point of view, DTO explosion is beneficial, each business scenario has an accurate return type, which is very nice to use. (Difficult to implement? What does that have to do with me?) Therefore, Jimmer server can automatically generate client code to (such as TypeScript) restore the DTO explosion eliminated on the server side on the client side. tip The server eliminates DTO explosions, and the client restores DTO explosions. This is the fundamental value of Jimmer's automatic sever-client integration, and it is also the essential difference between Jimmer and any other technology that automatically generates client code. Only by letting the server and client use completely different programming models can both sides get the ultimate development experience at the same time.","s":"Solution 3 (Topic of This Article)","u":"/jimmer-doc/docs/client/api","h":"#solution-3-topic-of-this-article","p":144},{"i":155,"t":"Previously we discussed that using Jimmer to build REST services with shapes enumerated by the server is the topic to be discussed in this article. To use this development approach, you need to use the @org.babyfish.jimmer.client.FetchBy annotation to decorate dynamic entity types in REST API return types, to mark specific shapes of dynamic objects for the client. tip @FetchBy does not simply decorate the return value of the REST API, but is used to decorate type references. Its declaration code is as follows package org.babyfish.jimmer.client; import java.lang.annotation.*; @Documented @Retention(RetentionPolicy.RUNTIME) @Target(ElementType.TYPE_USE) public @interface FetchBy { ...omitted... } Therefore, the return type of the REST API is very flexible. You can use it to decorate Jimmer entity types anywhere (including generic parameters), for example @FetchBy(\"...\") Book List<@FetchBy(\"...\") Book> Page<@FetchBy(\"...\") Book> Tuple2<@FetchBy(\"...\") BookStore, @FetchBy(\"...\") Author> Map> Java Kotlin BookController.java @GetMapping(\"/books\") public Page< @FetchBy(\"SIMPLE_FETCHER\") Book ❶ > findBookById( @RequestParam(defaultValue = \"0\") int pageIndex, @RequestParam(defaultValue = \"5\") int pageSize, @RequestParam(defaultValue = \"name asc, edition desc\") String sortCode ) { return bookRepository.findBooks( PageRequest.of(pageIndex, pageSize, SortUtils.toSort(sortCode)), SIMPLE_FETCHER ❷ ); } @GetMapping(\"book/{id}\") @Nullable public @FetchBy(\"COMPLEX_FETCHER\") Book ❸ findComplexBook( @PathVariable(\"id\") long id ) { return bookRepository.findNullable( id, COMPLEX_FETCHER ❹ ); } private static final Fetcher SIMPLE_FETCHER = ❺ Fetchers.BOOK_FETCHER .allScalarFields() .tenant(false); private static final Fetcher COMPLEX_FETCHER = ❻ Fetchers.BOOK_FETCHER .allScalarFields() .tenant(false) .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .avgPrice() ) .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ); BookController.kt @GetMapping(\"/books\") fun findBooks( @RequestParam(defaultValue = \"0\") pageIndex: Int, @RequestParam(defaultValue = \"5\") pageSize: Int, @RequestParam(defaultValue = \"name asc, edition desc\") sortCode: String ): Page< @FetchBy(\"SIMPLE_FETCHER\") Book ❶ > = bookRepository.findBooks( PageRequest.of(pageIndex, pageSize, SortUtils.toSort(sortCode)), name, storeName, authorName, SIMPLE_FETCHER ❷ ) @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long, ): @FetchBy(\"COMPLEX_FETCHER\") Book? = ❸ bookRepository.findNullable( id, COMPLEX_FETCHER ❹ ) companion object { private val SIMPLE_FETCHER = ❺ newFetcher(Book::class).by { allScalarFields() tenant(false) } private val COMPLEX_FETCHER = ❻ newFetcher(Book::class).by { allScalarFields() tenant(false) store { allScalarFields() avgPrice() } authors { allScalarFields() } } } ❶ Promise externally that the shape of each Book object in the paged object returned by GET /books is expressed by the static constant SIMPLE_FETCHER ❷ Internal implementation, GET /books uses static constant SIMPLE_FETCHER internally to query data caution ❶ as external commitment and ❷ as internal implementation must be consistent ❸ Promise externally that if GET /book/{id} returns non-null, its shape is expressed by the static constant COMPLEX_FETCHER ❹ Internal implementation, GET /book/{id} uses static constant COMPLEX_FETCHER internally to query data caution ❸ as external commitment and ❹ as internal implementation must be consistent ❺ and ❻, declare object shapes as static constants. With the decoration of @FetchBy, Jimmer understands the specific shape of each object's externally returned data, so it can generate code for the client, including TypeScript. info In this example, the class annotated with @FetchBy and the class declaring object shapes with static constants are the same class. If not, you can use the ownerType parameter of @FetchBy, for example @FetchBy(value = \"COMPLEX_FETCHER\", ownerType = FetcherConstants.class)","s":"Declare @FetchBy","u":"/jimmer-doc/docs/client/api","h":"#declare-fetchby","p":144},{"i":157,"t":"The following configuration can be declared in application.yml or application.properties to download related client code jimmer: ...other configurations omitted... client: ts: path: /ts.zip ❶ java-feign: path: /java-feign.zip ❷ Currently, Jimmer supports generating two types of client code, TypeScript and Java Feign Client code required by Spring Cloud ❶ Can download Web client required TypeScript code through http://localhost:8080/ts.zip ❷ Can download Spring Cloud required Java Feign Client code through http://localhost:8080/java-feign.zip Next we discuss the TypeScript code. Start the service, download http://localhost:8080/ts.zip, decompress it. Let the root directory after decompression be ${ts_root}: Let's take a look at ${ts_root}/model/dto/BookDto.ts first BookDto.ts export type BookDto = { 'BookService/SIMPLE_FETCHER': { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, }, 'BookService/COMPLEX_FETCHER': { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, readonly store?: { readonly id: number, readonly name: string, readonly website?: string, readonly avgPrice: number }, readonly authors: ReadonlyArray<{ readonly id: number, readonly firstName: string, readonly lastName: string, readonly gender: Gender }> } } info It is obvious that the DTO explosion eliminated on the server side is restored on the client side. Let's also take a look at ${ts_root}/services/BookService.ts import type { BookDto } from '../model/dto'; import type { Page } from '../model/static'; export class BookService { async findBooks( options: BookServiceOptions['findBooks'] ): Promise< Page< BookDto['BookService/SIMPLE_FETCHER'] > > { ...code omitted... } async findBookById( options: BookServiceOptions['findBookById'] ): Promise< BookDto['BookService/COMPLEX_FETCHER'] | undefined > { ...code omitted... } ...other code omitted... } export type BookServiceOptions = { 'findBooks': { readonly pageIndex: number, readonly pageSize: number, readonly sortCode: string }, 'findBookById': { readonly id: number } } info It is obvious that the return type of each business scenario is accurately defined.","s":"Generate Client Code","u":"/jimmer-doc/docs/client/api","h":"#generate-client-code","p":144},{"i":159,"t":"Create project First create a typescript based react project yarn create react-app my-web-app --template typescript Automatically generate client code Obviously, it is impossible to require client developers to manually download server code, decompress it, and replace local code every time changes occur on the server side. So we need to write a small script to automatically complete the download, decompression and replacement of the latest TypeScript code. Add folder scripts under project root, and add file generate-api.js under it. This file is executed by nodejs and is tooling code for development, not the code of the client itself. scripts/generate-api.js const http = require('http'); const fs = require('fs'); const fse = require('fs-extra'); const uuid = require('uuid'); const tempDir = require('temp-dir'); const AdmZip = require('adm-zip'); const sourceUrl = \"http://localhost:8080/ts.zip\"; const tmpFilePath = tempDir + \"/\" + uuid.v4() + \".zip\"; const generatePath = \"src/__generated\"; console.log(\"Downloading \" + sourceUrl + \"...\"); const tmpFile = fs.createWriteStream(tmpFilePath); const request = http.get(sourceUrl, (response) => { response.pipe(tmpFile); tmpFile.on(\"finish\", () => { tmpFile.close(); console.log(\"File save success: \", tmpFilePath); // Remove generatePath if it exists if (fs.existsSync(generatePath)) { console.log(\"Removing existing generatePath...\"); fse.removeSync(generatePath); console.log(\"Existing generatePath removed.\"); } // Unzip the file using adm-zip console.log(\"Unzipping the file...\"); const zip = new AdmZip(tmpFilePath); zip.extractAllTo(generatePath, true); console.log(\"File unzipped successfully.\"); // Remove the temporary file console.log(\"Removing temporary file...\"); fs.unlink(tmpFilePath, (err) => { if (err) { console.error(\"Error while removing temporary file:\", err); } else { console.log(\"Temporary file removed.\"); } }); }); }); Here, adm-zip needs to be installed separately yarn add adm-zip --dev Modify project's package.json and add the following code under its \"scripts\" field { ...other code omitted... \"scripts\": { ...other code omitted... \"api\": \"node scripts/generate-api.js\" } ...other code omitted... } So every time the server team notifies that REST API changes have occurred, just execute yarn api simply to refresh the local TypeScript client code caution This method is only suitable when the web team is very small in size. If there are many web developers, it is more recommended to implement secondary development on the CI environment to achieve the following: Each time the server code on a specific branch is committed, the CI environment compiles and starts the service, then downloads the ts code, decompresses it, and commits it to git. Finally, web engineers can simply pull the latest code from git. Create Global API Object The generated TypeScript code has a __generated/Api.ts file that needs to be instantiated into a global variable and configured properly. Under src, create ApiInstance.ts and export the global variable api src/ApiInstance.ts import { Api } from \"../__generated\"; const BASE_URL = \"http://localhost:8080\"; // Export global variable `api` export const api = new Api(async({uri, method, body}) => { const response = await fetch(`${BASE_URL}${uri}`, { body: body !== undefined ? JSON.stringify(body) : undefined, headers: { 'content-type': 'application/json;charset=UTF-8', ...other important HTTP headers, e.g. Authorization... } }); if (response.status !== 200) { throw response.json(); } const text = await response.text(); if (text.length === 0) { return null; } return JSON.parse(text); }); Call REST APIs Now we can call REST APIs based on global variable api. info The following examples are based on use-immer and TanStack/Query. Being proficient in or quickly mastering various remote request libraries is the basic literacy of web front-end engineers, so the details are not elaborated here. Experience api.bookService.findBooks const [options, setOptions] = useImmer< // RequestOf is a TypeScript helper class generated by Jimmer, // used to extract parameter types of any REST API RequestOf< typeof api.bookService.findBooks > >(() => { return { pageIndex: 0, pageSize: 10, sortCode: \"name asc\" }; }); const { isLoading, // If `data` is not `undefined`, its type must be // `Page` data, error, refetch } = useQuery({ queryKey: [\"Books\", options], // The type of `data` is determined here queryFn: () => api.bookService.findBooks(options) }); If request succeeds, the type of data is Page. Where BookDto['BookService/SIMPLE_FETCHER'] is defined as { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, } Experience api.bookService.findBookById In the following code, assume id is the current React primary key parameter const { // If `data` is not `undefined`, its type must be // `BookDto['BookService/COMPLEX_FETCHER']` data, isLoading, error } = useQuery({ queryKey: [\"book/detail\", id], queryFn: () => api.bookService.findBookById({id: id!}), enabled: id !== undefined }); If request succeeds and data is not null, its type is BookDto['BookService/COMPLEX_FETCHER']. This type is defined as: { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, readonly store?: { readonly id: number, readonly name: string, readonly website?: string, readonly avgPrice: number }, readonly authors: ReadonlyArray<{ readonly id: number, readonly firstName: string, readonly lastName: string, readonly gender: Gender }> } tip It can be seen that any REST API call will return strict data type definitions, and these strict type definitions will also affect the React UI template code in tsx files. This will give full play to the advantages of TypeScript, providing good IDE intelligence, and ensuring all problems are discovered at compile time, thus having a good development experience.","s":"Develop Web Client Project","u":"/jimmer-doc/docs/client/api","h":"#develop-web-client-project","p":144},{"i":161,"t":"Although @FetchBy combined with Jimmer's dynamic entities can restore DTO type definitions in client code, one situation still needs to be carefully considered: the returned data type differs greatly from the underlying entity model. For example: Java Kotlin ActiveAuthorInfo.java @lombok.Data public class ActiveAuthorInfo { private Author raw; private List stores; } ActiveAuthorInfo.kt data class ActiveAuthorInfo( val raw: Author, val stores: List ) In this example, ActiveAuthorInfo represents a very active author, containing the original information of the author raw, and the collection of all bookstores selling his/her books. The corresponding HTTP service interface is: Java Kotlin AuthorController.java @GetMapping(\"/authors/mostActive\") public List findMostActiveAuthorInfos( @RequestParam(defaultValue = \"10\") int limit ) { ...omitted... } AuthorController.kt @GetMapping(\"/authors/mostActive\") fun findMostActiveAuthorInfos( @RequestParam(defaultValue = \"10\") limit: Int ): List { ...omitted... } Obviously, this data structure differs greatly from the underlying entity model. In the entity model, there is an association between BookStore and Book, and there is also an association between Book and Author, but there is no association between BookStore and Author. tip In some cases, the data required by the client may contain multiple entity objects that have no direct ORM association, but only a certain business-level correlation. If such business-level correlations are not generic at all, then defining complex calculated properties for entities is not a good choice either. At this point, we can break the stereotypical thinking of the entity object graph and use custom data to represent the return results, just like ActiveAuthorInfo here. However, ActiveAuthorInfo is not a purely custom user data type, it mixes the use of Jimmer entities internally. Let's call it a hybrid type. The @FetchBy annotation can be used to decorate the fields of this hybrid type, for example: Java Kotlin ActiveAuthorInfo.java @lombok.Data public class ActiveAuthorInfo { private @FetchBy(\"AUTHOR_FETCHER\") Author raw; private List<@FetchBy(\"STORE_FETCHER\") BookStore> stores; private static final Fetcher AUTHOR_FETCHER = Fetchers.AUTHOR_FETCHER .firstName() .lastName(); private static final Fetcher STORE_FETCHER = Fetchers.AUTHOR_FETCHER.name(); } ActiveAuthorInfo.kt data class ActiveAuthorInfo( val raw: @FetchBy(\"AUTHOR_FETCHER\") Author, val stores: List<@FetchBy(\"STORE_FETCHER\") BookStore> ) { companion object { private val AUTHOR_FETCHER = newFetcher(Author::class) { firstName() lastName() } private val STORE_FETCHER = new Fetcher(BookStore::class) { name() } } } Finally, the TypeScript related types generated for ActiveAuthorInfo are as follows (for convenience, the code of multiple TypeScript files is mixed here): export interface ActiveAuthorInfo { readonly raw: AuthorDto['ActiveAuthorInfo/AUTHOR_FETCHER']; readonly stores: ReadonlyArray< BookStoreDto['ActiveAuthorInfo/STORE_FETCHER'] >; } export type AuthorDto { 'ActiveAuthorInfo/AUTHOR_FETCHER': { readonly id: number, readonly firstName: string, readonly lastName: string }, ...other DTO types omitted... } export type BookStoreDto { 'ActiveAuthorInfo/STORE_FETCHER': { readonly id: number, readonly name: string }, ...other DTO types omitted... }","s":"Integrate with Custom Data","u":"/jimmer-doc/docs/client/api","h":"#integrate-with-custom-data","p":144},{"i":163,"t":"This part is actually unrelated to ORM. However, since generate client api is provided, this part of the functionality must also be provided to make it a complete solution.","s":"Generate Client Errors","u":"/jimmer-doc/docs/client/error","h":"","p":162},{"i":165,"t":"We need to define special Java/Kotlin business exceptions that can be directly translated into data that the client can understand. How do we define this special type of business exception? There are two extreme choices: Share one business exception class across the entire application, with built-in error codes that the client can understand Define a business exception class for each business error Obviously, both of the above solutions are unsuitable. The first option is too coarse-grained, with globally maintained error codes that are difficult to maintain. The second option is too fine-grained, requiring the definition of too many exception classes. So, Jimmer chooses a compromise: dividing business exceptions into multiple families, with each family using one set of Error Codes. Jimmer uses enums to define exception families, where the enum also serves as the error code for that family, e.g.","s":"Exception Families","u":"/jimmer-doc/docs/client/error","h":"#exception-families","p":162},{"i":167,"t":"Java Kotlin UserInfoErrorCode.java package com.example.business.error; import org.babyfish.jimmer.error.ErrorFamily; @ErrorFamily public enum UserInfoErrorCode { ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } UserInfoErrorCode.kt package com.example.business.error import org.babyfish.jimmer.error.ErrorFamily @ErrorFamily enum class UserInfoErrorCode { ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } The @org.babyfish.jimmer.error.ErrorFamily annotation indicates that this enum represents a family of business exceptions, and the enum itself serves as the error code for this family. The @ErrorFamily annotation will be processed by Jimmer's precompiler info Here, the precompiler refers to Annotation Processor for Java, and KSP for Kotlin. This part of the code has been discussed in Overview/Get Started/Generate Code, so it won't be repeated here. The precompiler will generate the following exception class based on this enum: info For enums used to declare exception families, you can choose to use ErrorCode or Error as a special suffix. If there is such a special suffix, the exception class name = enum name without the suffix + Exception Otherwise, exception class name = enum name + Exception So here the generated exception name is UserInfoException After compilation by Jimmer, the following exception class will be generated. Java Kotlin UserInfoException.java public abstract class UserInfoException extends CodeBasedException { ❶ private UserInfoException(String message, Throwable cause) { super(message, cause); } @Override public abstract UserInfoErrorCode getCode(); ❷ public static UserInfoException illegalUserName(@NotNull String message) { ❸ return new IllegalUserName( message, null ); } public static UserInfoException illegalUserName( ❹ @NotNull String message, @Nullable Throwable cause ) { return new IllegalUserName( message, cause ); } public static UserInfoException passwordTooShort(@NotNull String message) { ❺ return new PasswordTooShort( message, null ); } public static UserInfoException passwordTooShort( ❻ @NotNull String message, @Nullable Throwable cause ) { return new PasswordTooShort( message, cause ); } public static UserInfoException passwordsNotSame(@NotNull String message) { ❼ return new PasswordsNotSame( message, null ); } public static UserInfoException passwordsNotSame( ❽ @NotNull String message, @Nullable Throwable cause ) { return new PasswordsNotSame( message, cause ); } public static class IllegalUserName extends UserInfoException { public IllegalUserName(String message, Throwable cause) { super(message, cause); } @Override public UserInfoErrorCode getCode() { return UserInfoErrorCode.ILLEGAL_USER_NAME; ❾ } @Override public Map getFields() { return Collections.emptyMap(); } } public static class PasswordTooShort extends UserInfoException { public PasswordTooShort(String message, Throwable cause) { super(message, cause); } @Override public UserInfoErrorCode getCode() { return UserInfoErrorCode.PASSWORD_TOO_SHORT; ❿ } @Override public Map getFields() { return Collections.emptyMap(); } } public static class PasswordsNotSame extends UserInfoException { public PasswordsNotSame(String message, Throwable cause) { super(message, cause); } @Override public UserInfoErrorCode getCode() { return UserInfoErrorCode.PASSWORDS_NOT_SAME; ⓫ } @Override public Map getFields() { return Collections.emptyMap(); } } } UserInfoException.kt public abstract class UserInfoException private constructor( message: String, cause: Throwable? = null, ) : CodeBasedException(message, cause) { ❶ public abstract override val code: UserInfoErrorCode ❷ public companion object { @JvmStatic public fun illegalUserName( ❸❹ message: String, cause: Throwable? = null ): UserInfoException = IllegalUserName( message, cause ) @JvmStatic public fun passwordTooShort( ❺❻ message: String, cause: Throwable? = null ): UserInfoException = PasswordTooShort( message, cause ) @JvmStatic public fun passwordsNotSame( ❼❽ message: String, cause: Throwable? = null ): UserInfoException = PasswordsNotSame( message, cause ) } public class IllegalUserName( message: String, cause: Throwable? = null, ) : UserInfoException(message, cause) { public override val code: UserInfoErrorCode get() = UserInfoErrorCode.ILLEGAL_USER_NAME ❾ public override val fields: Map get() = emptyMap() } public class PasswordTooShort( message: String, cause: Throwable? = null, ) : UserInfoException(message, cause) { public override val code: UserInfoErrorCode get() = UserInfoErrorCode.PASSWORD_TOO_SHORT ❿ public override val fields: Map get() = emptyMap() } public class PasswordsNotSame( message: String, cause: Throwable? = null, ) : UserInfoException(message, cause) { public override val code: UserInfoErrorCode get() = UserInfoErrorCode.PASSWORDS_NOT_SAME ⓫ public override val fields: Map get() = emptyMap() } } ❶ Exceptions based on enum error codes must inherit from org.babyfish.jimmer.error.CodeBasedException ❷ The error code type for this family of exceptions is UserInfoErrorCode ❸❹ Static method to construct exception with error code ILLEGAL_USER_NAME ❺❻ Static method to construct exception with error code PASSWORD_TOO_SHORT ❼❽ Static method to construct exception with error code PASSWORDS_NOT_SAME ❾ Exception class UserInfoException.IllegalUserName has error code ILLEGAL_USER_NAME ❿ Exception class UserInfoException.PasswordTooShort has error code PASSWORD_TOO_SHORT ⓫ Exception class UserInfoException.PasswordsNotSame has error code PASSWORDS_NOT_SAME","s":"Define Exception Families","u":"/jimmer-doc/docs/client/error","h":"#define-exception-families","p":162},{"i":169,"t":"Additional fields can be added to any error code. For example, ILLEGAL_USER_NAME indicates an illegal username, i.e. the username contains illegal characters. We can add the field illegalChars for it. Java Kotlin UserInfoErrorCode.java @ErrorFamily public enum UserInfoErrorCode { @ErrorField(name = \"illegalChars\", type = Character.class, list = true) ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } UserInfoErrorCode.kt @ErrorFamily enum class UserInfoErrorCode { @ErrorField(name = \"illegalChars\", type = Char::class, list = true) ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } The generated code is as follows: Java Kotlin UserInfoException.java public abstract class UserInfoException extends CodeBasedException { public static UserInfoException illegalUserName( @NotNull String message, @NotNull List illegalChars ) { ...omit code... } public static UserInfoException illegalUserName( @NotNull String message, @Nullable Throwable cause, @NotNull List illegalChars ) { ...omit code... } public static class IllegalUserName extends UserInfoException { @NotNull private final List illegalChars; public IllegalUserName( String message, Throwable cause, @NotNull List illegalChars ) { super(message, cause); this.illegalChars = illegalChars; } @Override public Map getFields() { return Collections.singletonMap(\"illegalChars\", illegalChars); } @NotNull public List getIllegalChars() { return illegalChars; } ...omit other code... } ...omit other code... } UserInfoException.kt public abstract class UserInfoException private constructor( message: String, cause: Throwable? = null, ) : CodeBasedException(message, cause) { ❶ public abstract override val code: UserInfoErrorCode ❷ public companion object { @JvmStatic public fun illegalUserName( message: String, cause: Throwable? = null, illegalChars: List, ): UserInfoException = ...omit code... ...omit other code... } public class IllegalUserName( message: String, cause: Throwable? = null, public val illegalChars: List, ) : UserInfoException(message, cause) { public override val fields: Map get() = mapOf( \"illegalChars\" to illegalChars ) ...omit other code... } }","s":"Add Fields to Error Codes","u":"/jimmer-doc/docs/client/error","h":"#add-fields-to-error-codes","p":162},{"i":172,"t":"Java Kotlin UserController.java package com.example.service; import org.babyfish.jimmer.client.ThrowsAll; @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode.class) public void registerUser(@RequestBody RegisterUserInput input) { ...omit code... } UserController.kt package com.example.service import import org.babyfish.jimmer.client.ThrowsAll @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode::class) fun registerUser(@RequestBody input: RegisterUserInput) { ...omit code... } info The @org.babyfish.jimmer.client.ThrowsAll annotation allows the REST API to throw all exceptions in the family.","s":"Allow To Throw All Exceptions Of Family","u":"/jimmer-doc/docs/client/error","h":"#allow-to-throw-all-exceptions-of-family","p":162},{"i":174,"t":"Let's locate another business exception family: Java Kotlin PlatformErrorCode.java @ErrorFamily public enum PlatformErrorCode { PERMISSION_DENIED, DATA_IS_FROZEN, SERVICE_IS_SUSPENDED, } PlatformErrorCode.kt @ErrorFamily enum class PlatformErrorCode { PERMISSION_DENIED, DATA_IS_FROZEN, SERVICE_IS_SUSPENDED } To be able to declare that a REST API can only throw some of the exceptions in this family, define the following annotation: Java Kotlin ThrowsPlatformError.java @Documented @Retention(RetentionPolicy.RUNTIME) @Target(ElementType.METHOD) public @interface ThrowsPlatformError { PlatformErrorCode[] value(); } ThrowsPlatformError.kt @Retention(AnnotationRetention.RUNTIME) @Target(AnnotationTarget.FUNCTION) annotation class ThrowsPlatformError( val value: Array ) This annotation satisfies the following 5 conditions: Retention is configured as RUNTIME, i.e. reflectable at runtime Target is configured as METHOD or FUNCTION (kotlin), can be used to decorate methods Has a property named value The value property is of array type The array element type of value is an enum decorated with @ErrorFamily. tip If an annotation satisfies all the above conditions, it can be used to decorate REST APIs to declare the exceptions that can be thrown. Just like how we use @ThrowsAll. Java Kotlin UserController.java @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode.class) @ThrowsPlatformError({PlatformErrorCode.SERVICE_IS_SUSPENDED}) public void registerUser(@RequestBody RegisterUserInput input) { ...omit code... } UserController.kt @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode::class) @ThrowsPlatformError([PlatformErrorCode.SERVICE_IS_SUSPENDED]) fun registerUser(@RequestBody input: RegisterUserInput) { ...omit code... }","s":"Allow To Throw Some Exceptions Of Family","u":"/jimmer-doc/docs/client/error","h":"#allow-to-throw-some-exceptions-of-family","p":162},{"i":177,"t":"Java Kotlin UserController.java @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode.class) @ThrowsPlatformError({PlatformErrorCode.SERVICE_IS_SUSPENDED}) public void registerUser(@RequestBody RegisterUserInput input) { if (...some condition...) { throw PlatformException.serviceIsSuspended( \"The service is suspended\" ); } ...omit other code... } UserController.kt @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode::class) @ThrowsPlatformError([PlatformErrorCode.SERVICE_IS_SUSPENDED]) fun registerUser(@RequestBody input: RegisterUserInput) { if (...some condition...) { throw PlatformException.serviceIsSuspended( \"The service is suspended\" ) } ...omit other code... } caution The kinds of exceptions thrown internally must not exceed those declared externally.","s":"Throw Exceptions","u":"/jimmer-doc/docs/client/error","h":"#throw-exceptions","p":162},{"i":179,"t":"tip As long as Jimmer's Spring Boot Starter is used, no extra work is required. Any exception inherited from CodeBasedException thrown by the service will be automatically translated. The translation result is: { \"family\":\"USER_INFO_ERROR_CODE\", \"code\":\"ILLEGAL_USER_NAME\", \"illegalChars\": [\"&\", \"`\", \"@\"] } To facilitate development and testing, you can configure in application.yml or application.properties: jimmer: error-translator: debug-info-supported: true This configuration will include information useful for locating issues during development and testing in the HTTP response. Since the content is quite long, please click the button below to view the result. View Result warning This configuration is only for assisting development and testing, and must NOT be enabled in production environments! For example, enable this switch in application-dev.yml and application-test.yml, but absolutely do NOT enable it in application-prod.yml.","s":"Write Exception Messages to HTTP Responses","u":"/jimmer-doc/docs/client/error","h":"#write-exception-messages-to-http-responses","p":162},{"i":182,"t":"export type AllErrors = ❶ { readonly family: \"PLATFORM_ERROR_CODE\", ❷ readonly code: \"SERVICE_IS_SUSPENDED\" ❸ } | { readonly family: \"USER_INFO_ERROR_CODE\", readonly code: \"ILLEGAL_USER_NAME\", readonly \"illegalChars\": ReadonlyArray ❹ } | { readonly family: \"USER_INFO_ERROR_CODE\", readonly code: \"PASSWORDS_NOT_SAME\" } | { readonly family: \"USER_INFO_ERROR_CODE\", readonly code: \"PASSWORD_TOO_SHORT\" } | ...omit other code... ; export type ApiErrors = { ❺ \"userController\": { ❻ \"registerUser\": AllErrors & ( ❼ { readonly family: 'USER_INFO_ERROR_CODE', readonly code: 'ILLEGAL_USER_NAME', readonly [key:string]: any } | { readonly family: 'USER_INFO_ERROR_CODE', readonly code: 'PASSWORD_TOO_SHORT', readonly [key:string]: any } | { readonly family: 'USER_INFO_ERROR_CODE', readonly code: 'PASSWORDS_NOT_SAME', readonly [key:string]: any } | { readonly family: 'PLATFORM_ERROR_CODE', readonly code: 'SERVICE_IS_SUSPENDED', readonly [key:string]: any } ), ...omit other code... }, \"bookController\": { ...omit code... }, ...omit other code... }; ❶ AllErrors defines all error types caution Only REST APIs that explicitly declare exceptions that may be thrown via annotations in Java/Kotlin code will be used to generate TypeScript code. For example, in the Java/Kotlin code above, we defined the error codes PlatformError.PERMISSION_DENIED and PlatformErrorCode.DATA_IS_FROZEN, but they have not yet been declared as throwable by any REST API using @ThrowsAll or custom @ThrowsPlatformError. So they will not be defined in AllErrors. ❷ The enum name decorated with @ErrorFamily is the family field in client code, used to identify which family the error belongs to ❸ The enum variable name is the code field in client code, used to identify which specific error it is ❹ The server uses @ErrorField (can repeat) to declare arbitrary additional fields for an error code (only one here), so all additional fields are generated here tip ❶ AllErrors defines all errors, never duplicated. ApiErrors at ❺ refers to errors, may have duplicates. Because different REST APIs may declare throwing the same error code. So additional fields are always declared in AllErrors, not in ApiErrors. This is the fundamental reason AllErrors and ApiErrors are separated. ❺ Errors that each REST API may throw ❻ Errors that userController module may throw ❼ Errors that userController.registerUser API may throw","s":"Generated TypeScript Code","u":"/jimmer-doc/docs/client/error","h":"#generated-typescript-code","p":162},{"i":184,"t":"The above TypeScript code is quite lengthy, and considering some readers may not have TypeScript background knowledge, here are some IDE auto-complete screenshots: Under global type ApiErrors, there are two options: userController and bookController ApiErrors[\"userController\"] has three options: login, logout and registerUser For ApiErrors[\"userController\"][\"registerUser\"], the family field has two options: USER_INFO_ERROR_CODE and PLATFORM_ERROR_CODE Once family is determined as UserInfoErrorCode, the code field has three options: ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT and PASSWORDS_NOT_SAME Once code is determined as ILLEGAL_USER_NAME, the additional illegalChars field can be used","s":"TypeScript IDE Effects","u":"/jimmer-doc/docs/client/error","h":"#typescript-ide-effects","p":162},{"i":186,"t":"In the OnDissociate article, we know there are 5 dissociation modes: NONE (default) LAX CHECK SET_NULL DELETE For pseudo foreign key (please refer to Real and Fake Foreign Keys) associative properties, when its dissociation mode is NONE: If the global configuration jimmer.default-dissociation-action-checkable is true (default), it is equivalent to CHECK. If the global configuration jimmer.default-dissociation-action-checkable is false, it is equivalent to NONE.","s":"Default Dissociation Mode","u":"/jimmer-doc/docs/configuration/dissociate-action-checking","h":"","p":185},{"i":188,"t":"Different databases have vastly different SQL support, so Jimmer uses dialect configuration to adapt to different databases.","s":"Dialect","u":"/jimmer-doc/docs/configuration/dialect","h":"","p":187},{"i":190,"t":"If using the Spring Boot Starter provided by Jimmer, there are two ways: Configure application.yml or application.properties jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect Provide global dialect Bean Java Kotlin @Bean public Dialect dialect() { return new MySqlDialect(); } @Bean fun dialect(): Dialect = MySqlDialect() info If both methods above are used (not recommended), the second method takes precedence If not using the Spring Boot Starter provided by Jimmer Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect(new MySqlDialect()) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDialect(MySqlDialect()) ...Omit other configurations... }","s":"Set Dialect","u":"/jimmer-doc/docs/configuration/dialect","h":"#set-dialect","p":187},{"i":192,"t":"org.babyfish.jimmer.sql.dialect.DefaultDialect This is the default dialect used by Jimmer when no dialect is specified, so there is no need to specify it explicitly. warning The default configuration can only be used for learning simple demos in the initial stage, and can never be used in actual projects. The following situations will cause exceptions: Operations on Jimmer in the code will generate SQL that depends on specific database products, rather than perfect cross-database SQL When the type of trigger is set to TRANSACTION_ONLY and cache is used, Jimmer will automatically create the JIMMER_TRANS_CACHE_OPERATOR table at startup. DefaultDialect does not support this operation, please refer to Cache Consistency org.babyfish.jimmer.sql.dialect.H2Dialect org.babyfish.jimmer.sql.dialect.MySql5Dialect org.babyfish.jimmer.sql.dialect.MySqlDialect org.babyfish.jimmer.sql.dialect.PostgresDialect org.babyfish.jimmer.sql.dialect.OracleDialect org.babyfish.jimmer.sql.dialect.TiDBDialect org.babyfish.jimmer.sql.dialect.SQLiteDialect Because TiDB is a distributed database that does not support foreign key constraints, true foreign keys are not supported by this dialect. Please refer to True and False Foreign Keys Apart from this, TiDBDialect has no difference with MySqlDialect. For other databases, users can extend dialects by themselves. But the database needs to support multi-column in expressions, such as where (a, b) in ((3, 4), (8, 13)) Or where (a, b) in (select x, y from ...) note Currently, multi-column in expressions are highly dependent features of Jimmer, and Microsoft Sql Server does not support this feature for the time being. So Microsoft Sql Server is not supported for now.","s":"Dialect List","u":"/jimmer-doc/docs/configuration/dialect","h":"#dialect-list","p":187},{"i":194,"t":"This configuration is explained in Mutation Section/Save Command/Enum Mapping/Associated Id Checking. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Associated Id Checking","u":"/jimmer-doc/docs/configuration/id-only-target-checking-level","h":"","p":193},{"i":196,"t":"caution This article only explains how to enable the relevant options. As for what these options are used for, please refer to Query Chapter/DSL Expression/IN LIST/Optimization, this article will not repeat it.","s":"In List Predicate Optimization","u":"/jimmer-doc/docs/configuration/in-list-optimization","h":"","p":195},{"i":198,"t":"Two ways to enable: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-padding-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListPaddingEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListPaddingEnabled(true) // ...omitted other configurations... }","s":"Enable Padding Optimization","u":"/jimmer-doc/docs/configuration/in-list-optimization","h":"#enable-padding-optimization","p":195},{"i":200,"t":"Two ways to enable: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-to-any-equality-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListToAnyEqualityEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListToAnyEqualityEnabled(true) // ...omitted other configurations... }","s":"Enable Any Equality Optimization","u":"/jimmer-doc/docs/configuration/in-list-optimization","h":"#enable-any-equality-optimization","p":195},{"i":202,"t":"This configuration is explained in Spring Section/SpringCloud and Remote Association/Enable Jimmer to Support Microservices. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Microservice","u":"/jimmer-doc/docs/configuration/micro-service","h":"","p":201},{"i":204,"t":"This configuration is explained in Mutation Section/Save Command/Pessimistic Lock. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Pessimistic Lock","u":"/jimmer-doc/docs/configuration/save-command-pessimistic-lock","h":"","p":203},{"i":206,"t":"This configuration is explained in Mutation Section/Trigger/Set Trigger Type. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Trigger Type","u":"/jimmer-doc/docs/configuration/trigger-type","h":"","p":205},{"i":208,"t":"In Jimmer, each data source corresponds to a sqlClient object (whose type is JSqlClient or KSqlClient). For the most classic single data source case, one sqlClient object is sufficient. Even the Jimmer Spring Boot Starter can automatically create a single sqlClient object. For multiple data sources, developers need to manually create multiple sqlClient objects. For the Jimmer Spring Boot Starter, the support for multiple data sources falls into two cases: Distributed Transaction Mode Local Transaction Mode","s":"Multiple DataSources","u":"/jimmer-doc/docs/configuration/multi-datasources","h":"","p":207},{"i":210,"t":"Here, distributed transactions refer to using Spring's support for JTA transactions. In this mode, simply create multiple sqlClient objects. Java Kotlin import org.springframework.beans.factory.annotation.Qualifier; import org.babyfish.jimmer.spring.SpringClients; @configuration public class SqlClientConfig { @Bean public JSqlClient sqlClient1( ApplicationContext ctx, @Qualifier(\"ds1\") DataSource dataSource ) { return SqlClients.java(ctx, dataSource, null); } @Bean public JSqlClient sqlClient2( ApplicationContext ctx, @Qualifier(\"ds2\") DataSource dataSource ) { return SqlClients.java(ctx, dataSource, null); } } import org.springframework.beans.factory.annotation.Qualifier import org.babyfish.jimmer.spring.SpringClients @configuration class SqlClientConfig { @Bean public fun sqlClient1( ctx: ApplicationContext, @Qualifier(\"ds1\") dataSource: DataSource ): KSqlClient = SqlClients.kotlin(ctx, dataSource) @Bean public fun sqlClient2( ctx: ApplicationContext, @Qualifier(\"ds2\") dataSource: DataSource ): KSqlClient = SqlClients.kotlin(ctx, dataSource) } Then, developers can freely use any of the sqlClient objects. Even if two data sources are operated within a transaction, the JTA transaction will ensure consistency between them.","s":"Distributed Transaction Mode","u":"/jimmer-doc/docs/configuration/multi-datasources","h":"#distributed-transaction-mode","p":207},{"i":212,"t":"Local transactions are slightly different, let's first look at the code: Java Kotlin import org.springframework.beans.factory.annotation.Qualifier; import org.springframework.transaction.support.PlatformTransactionManager; import org.babyfish.jimmer.spring.SpringClients; import org.babyfish.jimmer.spring.transaction.JimmerTransactionManager; import org.babyfish.jimmer.spring.transaction.TransactionalSqlClients; @configuration public class SqlClientConfig { @Bean public PlatformTransactionManager tm1( ❶ ApplicationContext ctx, @Qualifier(\"ds1\") DataSource dataSource ) { return new JimmerTransactionManager( SqlClients.java(ctx, dataSource, null) ); } @Bean public PlatformTransactionManager tm2( ❷ ApplicationContext ctx, @Qualifier(\"ds2\") DataSource dataSource ) { return new JimmerTransactionManager( SqlClients.java(ctx, dataSource, null) ); } @Bean public JSqlClient sqlClient() { ❸ return TransactionalSqlClients.java(); } } import org.springframework.beans.factory.annotation.Qualifier import org.springframework.transaction.support.PlatformTransactionManager import org.babyfish.jimmer.spring.SpringClients import org.babyfish.jimmer.spring.transaction.JimmerTransactionManager import org.babyfish.jimmer.spring.transaction.TransactionalSqlClients @configuration public class SqlClientConfig { @Bean fun tm1( ctx: ApplicationContext, @Qualifier(\"ds1\") dataSource: DataSource ): PlatformTransactionManager = ❶ JimmerTransactionManager( SqlClients.kotlin(ctx, dataSource, null) ) @Bean fun tm2( ctx: ApplicationContext, @Qualifier(\"ds2\") dataSource: DataSource ): PlatformTransactionManager = ❷ JimmerTransactionManager( SqlClients.kotlin(ctx, dataSource, null) ) @Bean public JSqlClient sqlClient() = ❸ TransactionalSqlClients.kotlin() } ❶ Create the first transaction manager based on the first DataSource, note that: The transaction manager type is org.babyfish.jimmer.spring.transaction.JimmerTransactionManager. Although the internal code creates a sqlClient object, it is not exposed to the Spring context, but is held and hidden by the transaction manager. ❷ Create the second transaction manager based on the second DataSource, same as ❶, no need to repeat. ❸ Create a sqlClient proxy and expose it to the Spring context for developers to inject and use. For any business method that needs to operate Jimmer, the annotation @Transactional(\"tm1\") or @Transactional(\"tm2\") must be used, so that Jimmer can be told which JimmerTransactionManager the current business method is using. Otherwise, using the ❸ sqlClient proxy will result in the following exception: The transactional sql client is used, however, there is no AOP transaction, or the transaction manager is not \"org.babyfish.jimmer.spring.transaction.JimmerTransactionManager\" Once Jimmer understands that the current thread is using one of the transaction managers from ❶ and ❷, the ❸ sqlClient proxy will use the internal sqlClient of the corresponding JimmerTransactionManager from ❶ or ❷ to provide services for the user. That is, in the local transaction mode, although multiple sqlClient objects can be created, the business method must explicitly specify which data source to use through the Spring annotation @Transactional(transactionManagerRef).","s":"Local Transaction Mode","u":"/jimmer-doc/docs/configuration/multi-datasources","h":"#local-transaction-mode","p":207},{"i":214,"t":"This section introduces how to quickly create GraphQL services with Jimmer.","s":"GraphQL","u":"/jimmer-doc/docs/graphql/","h":"","p":213},{"i":216,"t":"For ORM, it is important to print generated SQL in logs.","s":"SQL Log","u":"/jimmer-doc/docs/configuration/sql-log","h":"","p":215},{"i":218,"t":"There are two ways to enable SQL logs: When using Spring Boot Starter, there are two ways to configure: Modify application.yml (or application.properties) jimmer: show-sql: true Configure global Bean Java Kotlin @Bean public Executor executor() { return Executor.log(); } @Bean fun executor(): Executor = Executor.log() info If both methods above are used (not recommended), the second method takes precedence. Use underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) ...Omit other configurations... } The actual printed logs are as follows: jimmer> sql: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? order by tb_1_.NAME asc, tb_1_.EDITION desc limit ?, ?, variables: [%graphql%, 0, 10], purpose: QUERY caution If only the SQL log is turned on, the above log will not wrap. The log has three parts: sql: The SQL statement being executed variables: The JDBC parameters associated with sql, which is an array whose length is the same as the number of \"?\" characters in sql. purpose: The reason why the SQL is executed, which is an enum with the following values: QUERY: Query directly executed by developers UPDATE: Operations performed by developers via update statements DELETE: Operations performed by developers via delete statements LOAD: Query executed automatically by Jimmer to get the value of associated properties or calculated properties in object fetcher. EXPORT: The user initiates a query to other microservices, and its object fetcher contains remote associations pointing to the current service. Jimmer automatically exposes the data of this service. MUTATE: Operations specified by developers via save commands EVICT: In some cases, the cache that should be cleared cannot be determined solely based on the event information of Jimmer triggers. Jimmer will automatically execute some queries to accurately determine which caches should be cleared.","s":"Enable SQL Log","u":"/jimmer-doc/docs/configuration/sql-log","h":"#enable-sql-log","p":215},{"i":220,"t":"In the previous example, the SQL log is printed in one line, which is poorly readable. Therefore, the SQL needs to be formatted. There are two implementation methods: When using Spring Boot Starter Modify application.yml (or application.properties) jimmer: show-sql: true pretty-sql: true When using underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) .setSqlFormatter(SqlFormatter.PRETTY) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) setSqlFormatter(SqlFormatter.PRETTY) ...Omit other configurations... } The log output is as follows: Execute SQL===> Purpose: QUERY SQL: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ ❶ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 0 */ ❷, ? /* 10 */ ❸ JDBC response status: success Time cost: 8ms <===Execute SQL In this mode: The SQL statement will be automatically formatted, automatically wrapped, and automatically indented. ❶ ❷ ❸ Unlike the previous example, all JDBC parameters are not printed together, but injected into the original SQL as comments. Other information will be printed, such as whether SQL execution is successful, total execution time of SQL. For insert, update, delete operations, the number of affected rows will also be printed.","s":"Pretty SQL","u":"/jimmer-doc/docs/configuration/sql-log","h":"#pretty-sql","p":215},{"i":222,"t":"In the previous examples, the JDBC parameters in the SQL logs were inserted after the JDBC parameter placeholders ? as comment, e.g. ? /* %graphql% */. Perhaps you want the parameters to be inlined into the SQL statement directly, making it look as if no JDBC parameters were used. This way, the SQL statement in the logs can be copied directly into a SQL IDE to execute. There are two ways to achieve this Using Spring Boot Starter: Modify application.yml (or application.properties): jimmer: show-sql: true pretty-sql: true inline-sql-variables: true Using low-level API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) .setSqlFormatter(SqlFormatter.INLINE_PRETTY) ...other configs omitted... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) setSqlFormatter(SqlFormatter.INLINE_PRETTY) ...other configs omitted... } The log output is as follows: Execute SQL===> Purpose: QUERY SQL: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like '%graphql%' ❶ order by tb_1_.NAME asc, tb_1_.EDITION desc limit 0 ❷, 10 ❸ JDBC response status: success Time cost: 8ms <===Execute SQL In this mode, we can see the parameters at ❶ ❷ ❸ are directly inlined. info This only affects the logs. The actual SQL executed still uses JDBC parameters.","s":"Inline SQL Parameters","u":"/jimmer-doc/docs/configuration/sql-log","h":"#inline-sql-parameters","p":215},{"i":224,"t":"In addition to coding, developers often need to troubleshoot issues. Whether it is a functional error or a performance issue, the developer needs to investigate it. If the SQL log only prints JDBC information centered on SQL, the user cannot associate the SQL log with the application code, which is not conducive to users troubleshooting. Jimmer provides a configuration option that if specified, before executing SQL, it will check the stack trace information of the current thread. However, these stack traces contain too much information, including infrastructure call frames represented by jdk, jdbc driver, jimmer and spring, while the business-related information that developers care about will be overwhelmed in the ocean of information. This configuration type is java.util.Collection allowing developers to specify multiple packages or class prefixes. Jimmer will use them to filter the stack trace information. If a call frame can pass the filter, Jimmer will consider it related to user business and include it in the callback parameter before execution. For SQL log printing, call frames that can pass the filter will appear in the print output to help users troubleshoot issues. There are two implementation methods: When using Spring Boot Starter Modify application.yml (or application.properties) jimmer: show-sql: true pretty-sql: true executor-context-prefixes: - com.example.business When using underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) .setSqlFormatter(SqlFormatter.PRETTY) .setExecutorContextPrefixes( Collections.singleton( \"com.example.business\" ) ) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) setSqlFormatter(SqlFormatter.PRETTY) setExecutorContextPrefixes( listOf( \"com.example.business\" ) ) ...Omit other configurations... } The log output is as follows: Execute SQL===> --- Business related stack trace information --- ❶ com.example.business.BookService.findBooks(BookService.java:55) ❷ Purpose: QUERY SQL: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 0 */, ? /* 10 */ JDBC response status: success Time cost: 9ms <===Execute SQL At ❶ and ❷, the stack trace information of the thread executing the SQL operation is printed. tip However, a large amount of stack trace information is not blindly printed, only what users care about is printed.","s":"Embed Stack Trace","u":"/jimmer-doc/docs/configuration/sql-log","h":"#embed-stack-trace","p":215},{"i":227,"t":"In the Spring section, we discussed how to implement REST services with Jimmer and automatically generate client code like TypeScript. In addition, Jimmer also supports another development mode to build GraphQL services, which is what this article series will discuss. caution So far, the GraphQL protocol does not support recursive queries for self-associated properties. Therefore, it is not possible to expose functionality like recursive queries in object fetchers through GraphQL. This is a functionality sacrifice that must currently be accepted when using GraphQL. Jimmer's support for GraphQL is based on Spring GraphQL. So the project needs to import both the Jimmer and Spring GraphQL Spring Boot starters, for example: Maven Gradle pom.xml ...other code omitted... org.babyfish.jimmer jimmer-spring-boot-starter ${jimmer.version} org.springframework.boot spring-boot-starter-graphql ${spring.boot.version} ...other dependencies omitted... ...other code omitted... build.gradle dependencies { implementation \"org.babyfish.jimmer:jimmer-spring-boot-starter:${jimmerVersion}\" implementation 'org.springframework.boot:spring-boot-starter-graphql' ...other dependencies omitted... } info If the Jimmer entity types are also defined in the GraphQL project rather than in a separate project, the preprocessor (Annotation Processor for Java, KSP for Kotlin) should also be configured in the build script. This has already been discussed in detail in the Generate Code article and will not be repeated here. Spring GraphQL is a Schema-First rather than Code-First approach. Therefore, developers need to create the file src/main/resources/graphql/schema.graphqls in the project and define the GraphQL schema in it. This file is a requirement of Spring GraphQL. The GraphQL schema content is a standard language that is unrelated to Jimmer, so this article will not explain it. Please refer to the GraphQL Schema in the example.","s":"Concepts","u":"/jimmer-doc/docs/graphql/concept","h":"#concepts","p":225},{"i":229,"t":"caution In the current version, there is a limitation that when providing GraphQL services, simple calculated properties based on SQL should NOT be used.","s":"Notes","u":"/jimmer-doc/docs/graphql/concept","h":"#notes","p":225},{"i":232,"t":"In previous documents, we have introduced how to map enums, and how to use @Serialized to map JSON. However, sometimes neither of these methods can meet our requirements. In this case, we can use ScalarProvider. tip ScalarProvider is the most low-level SPI of Jimmer for custom data types. The Enum Mapping and JSON Mapping we discussed before are actually Jimmer's built-in implementations of ScalarProvider. Multiple ScalarProvider can be registered for SqlClient. Each ScalarProvider tells Jimmer how to handle a custom data type. There are two types of ScalarProvider: Global Define the mapping rules between Java/Kotlin types and database types globally and uniformly. Any entity definition that contains properties of this type will be uniformly handled by the global ScalarProvider. note Global ScalarProvider can only handle non-collection types, such as: classes, interfaces, enums, etc. It cannot handle collection types like: Array, Collection, Map, etc. Property level For a specific entity property, define the mapping rules between Java/Kotlin types and database types. note Property-level ScalarProvider can handle any non-built-in types of Jimmer, including collection types such as: Array, Collection, Map. If the mapped property type is a collection type, the property needs to be annotated with @org.babyfish.jimmer.Scalar. tip The @Serialized annotation discussed in JSON Mapping can annotate both the return type of properties and entity properties. This is because the more low-level ScalarProvider has two types. ScalarProvider is an SPI interface provided by Jimmer, which is defined as follows: ScalarProvider package org.babyfish.jimmer.sql.runtime; import java.util.function.Consumer; public abstract class ScalarProvider { protected ScalarProvider(Class scalarType, Class sqlType) { ❸ ...Omitted code... } protected ScalarProvider() { ❹ ...Omitted code... } public abstract T toScalar(S sqlValue); ❺ public abstract S toSql(T scalarValue); ❻ public Collection getHandledProps() { ❼ return null; } } ❶ Generic parameter T: Data type in Java/Kotlin; ❷ Generic parameter S: Data type in the database; ❸ Constructor that explicitly specifies the types represented by T and S; This constructor is usually used to define ScalarProvider with higher generality and reusability. ❹ Constructor that does not need to explicitly specify the types represented by T and S; It requires derived classes to explicitly specify generic parameters T and S so that Jimmer can automatically analyze the types represented by T and S. Otherwise, an exception will occur. This constructor is usually used to define ScalarProvider corresponding to specific types without requiring generality and reusability. ❺ Method toScalar: Convert non-null data read from the database to Java data; ❻ Method toSql: Convert non-null Java data to data acceptable to the database; ❼ If you want to define a property-level ScalarProvider, one option (there are other options) is to override the getHandledProps method in the derived class;","s":"Basic Concepts","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#basic-concepts","p":230},{"i":234,"t":"For example, the current database does not support the UUID type, which can be handled as follows:","s":"Global ScalarProvider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#global-scalarprovider","p":230},{"i":236,"t":"Java Kotlin UUIDScalarProvider.java public class UUIDScalarProvider extends AbstractScalarProvider { @Override public UUID toScalar(String sqlValue) { return UUID.fromString(sqlValue); } @Override public String toSql(UUID scalarValue) { return scalarValue.toString(); } } UUIDScalarProvider.kt class UUIDScalarProvider : ScalarProvider { override fun toScalar(sqlValue: String): UUID = UUID.fromString(sqlValue) override fun toSql(scalarValue: UUID): String = scalarValue.toString() }","s":"Define ScalarProvider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#define-scalarprovider","p":230},{"i":238,"t":"There are two ways for Jimmer to register ScalarProvider: Use Spring Boot Starter Just let the derived classes of ScalarProvider be managed by Spring. There are two options: Modify the above UUIDScalarProvider class and annotate it with spring's @Component Java Kotlin UUIDScalarProvider.java @Component public class UUIDScalarProvider extends AbstractScalarProvider { ...Omitted code... } UUIDScalarProvider.kt @Component class UUIDScalarProvider : ScalarProvider { ...Omitted code... } Use Spring's @Bean method to register the UUIDScalaProvider object to Spring Java Kotlin @Bean public UUIDScalarProvider uuidScalarProvider() { return new UUIDScalarProvider(); } @Bean fun uuidScalarProvider(): UUIDScalarProvider = UnitTestIdGenerator() Use underlying API Java Kotlin @Bean public JSqlClient sqlClient() { return JSqlClient .newBuilder() .addScalarProvider(new UUIDScalarProvider()) ...Omit other configurations... .build(); } @Bean fun sqlClient() : KSqlClient = newKSqlClient { addScalarProvider(UUIDScalarProvider()) ...Omit other configurations... }","s":"Register Scalar Provider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#register-scalar-provider","p":230},{"i":240,"t":"The only difference between property-level ScalarProvider and global ScalarProvider is that it only applies to specific properties, not all properties. So the most important data conversion methods toScalar and toSql in property-level ScalarProvider have exactly the same user code implementation, only the registration method is different. Therefore, here we assume there is a user-defined type Location and its corresponding ScalarProvider implementation class is LocationScalarProvider. Specific implementation is omitted.","s":"Property level ScalarProvider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#property-level-scalarprovider","p":230},{"i":242,"t":"Java Kotlin @Bean public JSqlClient sqlClient() { return JSqlClient .newBuilder() .setScalarProvider( FlightProps.SOURCE_LOCATION new LocationScalarProvider() ) .setScalarProvider( FlightProps.TARGET_LOCATION new LocationScalarProvider() ) ...Omit other configurations... .build(); } @Bean fun sqlClient() : KSqlClient = newKSqlClient { setScalarProvider( Flight::sourceLocation LocationScalarProvider() ) setScalarProvider( Flight::targetLocation LocationScalarProvider() ) ...Omit other configurations... } That is, except for the Flight.sourceLocation and Flight.targetLocation properties, LocationScalarProvider does not affect any other properties of type Location.","s":"Non-Spring registration","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#non-spring-registration","p":230},{"i":244,"t":"The above method is intuitive, but it is manually registered. Can Spring's automatic registration method be used to register property-level ScalarProvider? Of course. Just override the getHandledProps method of ScalarProvider, and you can use the method of registering global ScalarProvider to register property-level ScalarProvider. For example: Java Kotlin LocationScalarProvider.java @Component public class LocationScalarProvider extends AbstractScalarProvider { @Override public Collection getHandledProps() { return Arrays.asList( FlightProps.SOURCE_LOCATION, FlightProps.TARGET_LOCATION ); } ...Omit other code... } LocationScalarProvider.kt @Component class LocationScalarProvider : ScalarProvider { override fun getHandledProps(): Collection = listOf( Flight::sourceLocation.toImmutableProp(), Flight::targetLocation.toImmutableProp() ) ...Omit other code... }","s":"Spring registration","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#spring-registration","p":230},{"i":246,"t":"In this section, we introduce how to map a relational database to entity model. For readers with ORM experience (especially JPA), you can skim through quickly. Major differences from JPA: Basic Mapping: Nullability Advanced Mapping: View Properties Calculated Properties Remote Associations Key Key is very important for Save Command OnDissociate For readers without ORM experience, you'll have to read slowly. This process is tedious but required for any ORM. All powerful and cool ORM capabilities are built on top of these mappings. To avoid extended tedium for ORM beginners, a suggestion - initially only read the basic mappings, enough to understand most of the docs. Come back for advanced mappings when needed.","s":"Mapping","u":"/jimmer-doc/docs/mapping/","h":"","p":245},{"i":248,"t":"In this series of articles, we will introduce advanced mappings.","s":"Advanced mapping","u":"/jimmer-doc/docs/mapping/advanced/","h":"","p":247},{"i":251,"t":"Without Jimmer's support, implementing GraphQL queries requires two types of work: Query aggregate roots This is work that needs to be done when developing any data service, whether it's a GraphQL service, REST service, or even a service using other custom protocols. Developers only need to query and return standalone aggregate root objects without considering their association properties. So this is a relatively simple development task. For Spring GraphQL, just add the @QueryMapping annotation to the query methods in controller classes. Query association properties and calculated properties This is the bulk of the work required to implement GraphQL queries, requiring consideration of all current object associations and batch loading. There is some workload involved. In other words, it is precisely because the server undertakes these responsibilities that using GraphQL feels free, convenient and powerful on the client side. For Spring GraphQL, some schemes are provided for querying association properties, such as @SchemaMapping Batch Loading @BatchMapping When using Jimmer to implement GraphQL queries, developers only need to focus on querying aggregate roots, just ensuring that these aggregate roots have simple scalar fields. This is because tip All association properties and calculated properties of entity objects are automatically mapped to GraphQL fields by Jimmer without any development. caution So far, the GraphQL protocol does not support recursive queries for self-associated properties. Therefore, it is not possible to expose functionality like recursive queries in object fetchers through GraphQL. This is a functionality sacrifice that must currently be accepted when using GraphQL.","s":"Feature Description","u":"/jimmer-doc/docs/graphql/query","h":"#feature-description","p":249},{"i":254,"t":"Java Kotlin BookStoreService.java package com.example.business; import org.springframework.graphql.data.method.annotation.Argument; import org.springframework.graphql.data.method.annotation.QueryMapping; import org.springframework.stereotype.Controller; ...Omit other imports... @Controller public class BookStoreService { private final JSqlClient sqlClient; public BookStoreService(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @QueryMapping public List bookStores( @Argument @Nullable String name ) { BookStoreTable table = Tables.BOOK_STORE_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .select(table) .execute(); } } BookStoreService.kt package com.example.business import org.springframework.graphql.data.method.annotation.Argument import org.springframework.graphql.data.method.annotation.QueryMapping import org.springframework.stereotype.Controller ...Omit other imports... @Controller class BookStoreService( private val sqlClient: KSqlClient ) { @QueryMapping fun bookStores( @Argument name: String? ): List = sqlClient .createQuery(BookStore::class) { where(table.name `ilike?` name) select(table) } .execute() } Unlike previous REST services, this example does not use object fetchers, returning the simplest orphan objects (orphan objects contain neither associated properties nor calculated properties). Although we return orphan objects here, if the client's GraphQL request contains associated objects, Jimmer will still automatically load the required associated properties. However, there is a problem with this approach: in non-cache mode, unnecessary properties will also be queried, which has performance issues. We will introduce another approach with optimization capability later.","s":"1. Simplest Implementation","u":"/jimmer-doc/docs/graphql/query","h":"#1-simplest-implementation","p":249},{"i":256,"t":"To avoid querying unnecessary non-associated properties in non-cache mode, Jimmer can create a Fetcher object based on graphql.schema.DataFetchingEnvironment and use this Fetcher to query the database with the object as a parameter. tip In non-cache mode, not querying unnecessary non-associated properties is the essential difference between Jimmer GraphQL and other GraphQL implementations in the Java ecosystem. Java Kotlin BookStoreService.java package com.example.business; import org.springframework.graphql.data.method.annotation.Argument; import graphql.schema.DataFetchingEnvironment; import org.babyfish.jimmer.spring.graphql.DataFetchingEnvironments; import org.springframework.graphql.data.method.annotation.QueryMapping; import org.springframework.stereotype.Controller; ...Omit other imports... @Controller public class BookStoreService { private final JSqlClient sqlClient; public BookStoreService(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @QueryMapping public List bookStores( @Argument @Nullable String name, DataFetchingEnvironment env ) { BookStoreTable table = Tables.BOOK_STORE_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .select( table.fetch( DataFetchingEnvironments.createQuery( BookStore.class, env ) ) ) .execute(); } } BookStoreService.kt package com.example.business import org.springframework.graphql.data.method.annotation.Argument import graphql.schema.DataFetchingEnvironment import org.babyfish.jimmer.spring.graphql.toFetcher import org.springframework.graphql.data.method.annotation.QueryMapping import org.springframework.stereotype.Controller ...Omit other imports... @Controller class BookStoreService( private val sqlClient: KSqlClient ) { @QueryMapping fun bookStores( @Argument name: String?, env: DataFetchingEnvironment ): List = sqlClient .createQuery(BookStore::class) { where(table.name `ilike?` name) select( table.fetch( env.toFetcher() ) ) } .execute() }","s":"2. Optimize Performance","u":"/jimmer-doc/docs/graphql/query","h":"#2-optimize-performance","p":249},{"i":258,"t":"In the accompanying example, the GraphQL related projects are: Language Example Java jimmer-examples/java/jimmer-sql-graphql Kotlin jimmer-examples/kotlin/jimmer-sql-graphql-kt Select any project, open and start it. Finally, use the browser to visit http://localhost:8080/graphiql note Be careful, it's /graphiql, not /graphql Execute the request: query { bookStores { id name avgPrice ❶ books { ❷ id name edition price authors { ❸ id firstName fullName gender } } } } ❶ Query calculated property BookStore.avgPrice ❷ Query association property BookStore.books ❸ Query association property Book.authors The return result is: { \"data\":{ \"bookStores\":[ { \"id\":2, \"name\":\"MANNING\", \"avgPrice\":80.333333, \"books\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"fullName\":\"Samer Buna\", \"gender\":\"MALE\" } ] }, { \"id\":11, ...omitted... }, { \"id\":12, ...omitted... } ] }, { \"id\":1, \"name\":\"O'REILLY\", \"avgPrice\":58.5, \"books\":[ { \"id\":4, \"name\":\"Effective TypeScript\", \"edition\":1, \"price\":73, \"authors\":[ { \"id\":3, \"firstName\":\"Dan\", \"fullName\":\"Dan Vanderkam\", \"gender\":\"MALE\" } ] }, { \"id\":5, ...omitted... }, { \"id\":6, ...omitted... }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"fullName\":\"Alex Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"fullName\":\"Eve Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"fullName\":\"Alex Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"fullName\":\"Eve Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"fullName\":\"Alex Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"fullName\":\"Eve Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":7, \"name\":\"Programming TypeScript\", \"edition\":1, \"price\":47.5, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"fullName\":\"Boris Cherny\", \"gender\":\"MALE\" } ] }, { \"id\":8, \"name\":\"Programming TypeScript\", \"edition\":2, \"price\":45, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"fullName\":\"Boris Cherny\", \"gender\":\"MALE\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"fullName\":\"Boris Cherny\", \"gender\":\"MALE\" } ] } ] } ] } }","s":"Running Effect","u":"/jimmer-doc/docs/graphql/query","h":"#running-effect","p":249},{"i":260,"t":"In this article, you will learn about Jimmer's calculated properties and annotations: org.babyfish.jimmer.sql.Formula Simple calculated properties, can be Java/Kotlin expressions or SQL expressions org.babyfish.jimmer.sql.Transient Complex calculated properties, with the following features: Not only can simple values be calculated, but associated calculated values can also be calculated. That is, calculated properties can be associated properties Any complex calculation rules can be used, for example, using OLAP systems unrelated to the current relational database for calculation caution Calculated properties should only be defined when a calculated metric belongs to an entity. If a calculated metric does not belong to any entity, it should be designed as a global Service API.","s":"Calculated Properties","u":"/jimmer-doc/docs/mapping/advanced/calculated/","h":"","p":259},{"i":263,"t":"In GraphQL, GraphQLObjects returned by queries are dynamic objects of arbitrary shapes. However, if mutation operations accept object parameters, they must be GraphQLInputs, which are static objects of fixed shapes. See GraphQLInput to learn more. Take the GraphQL declaration file in the example schema.graphqls as an example: type Book implements CommonEntity { ❶ id: Long! name: String! edition: Int! price: BigDecimal! store: BookStore authors: [Author!]! createdTime: LocalDateTime! modifiedTime: LocalDateTime! tenant: String! } input BookInput { ❷ id: Long name: String! edition: Int price: BigDecimal! storeId: Long authorIds: [Long!]! } ...other code omitted... ❶ Types declared with the type keyword are dynamic types used to express arbitrary data structures, used as GraphQL output types ❷ Types declared with the input keyword are static types used to express fixed data structures, used as GraphQL input types","s":"Introduction to GraphQL Input","u":"/jimmer-doc/docs/graphql/mutation","h":"#introduction-to-graphql-input","p":261},{"i":265,"t":"Jimmer Input DTOs are introduced in great detail in Save Command/Input DTO, which will not be repeated here. Jimmer provides two ways to define Input DTOs: Automatically generate Input DTOs using the DTO language Manually define Input DTOs based on MapStruct Using the DTO language can achieve our goal very efficiently, so this article adopts this approach. In the project where the entity is defined, create the directory src/main/dto Under src/main/dto, create subdirectories com/yourcompany/yourproject/model according to the package path where the entities are located Under the directory created in the previous step, create the file Book.dto. The file must have the same name as the entity class and the extension must be dto Edit this file and use the DTO language to define various DTO shapes for the Book entity Book.dto input BookInput { #allScalars(Book) id(store) id(authors) as authorIds } ...other DTO definitions omitted... After compilation, the following Input DTO will be generated automatically: Java Kotlin BookInput.java @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookInput implements Input { ❶ @Nullable private Long id; private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; private List authorIds; @Override public Book toEntity() { ❷ ...omitted... } ...other members omitted... } BookInput.kt @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookInput( val id: Long? = null, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val storeId: Long? = null, val authorIds: List = emptyList() ): Input { ❶ override fun toEntity(): Book = ❷ ...omitted... ...other members omitted... } ❶ The BookInput class implements the interface org.babyfish.jimmer.Input, which supports the toEntity method to convert the current Input DTO object to a Jimmer dynamic entity object. ❷ Implements the Input.toEntity method","s":"Define Jimmer Input DTO","u":"/jimmer-doc/docs/graphql/mutation","h":"#define-jimmer-input-dto","p":261},{"i":267,"t":"Java Kotlin BookStoreService.java package com.example.business; import org.springframework.graphql.data.method.annotation.Argument; import org.springframework.graphql.data.method.annotation.MutationMapping; import org.springframework.stereotype.Controller; ...other imports omitted... @Controller public class BookStoreService { private final BookStoreRepository bookStoreRepository; public BookStoreService(BookStoreRepository bookStoreRepository) { this.bookStoreRepository = bookStoreRepository; } @MutationMapping ❶ @Transactional public Book saveBook( @Argument BookInput input ❷ ) { // `save(input)` is shorthand for `save(input.toEntity())` return bookRepository.save(input); ❸ } } BookStoreService.kt package com.example.business import org.springframework.graphql.data.method.annotation.Argument import org.springframework.graphql.data.method.annotation.MutationMapping import org.springframework.stereotype.Controller ...other imports omitted... @Controller class BookStoreService( private val bookStoreRepository: BookStoreRepository ) { @MutationMapping ❶ @Transactional fun saveBook( @Argument input: BookInput ❷ ): Book = // `save(input)` is shorthand for `save(input.toEntity())` bookRepository.save(input) ❸ } ❶ Use annotation @org.springframework.graphql.data.method.annotation.MutationMapping ❷ Use the static Input DTO type BookInput to allow users to pass only data structures of specified shapes to conform to GraphQLInput ❸ Save command to save arbitrary data structures in one line Here bookRepository.save(input) is actually shorthand for bookRepository.save(input.toEntity()). tip No matter how simple or relatively complex the data structure defined by the BookInput type, it can be saved in one line. This is the core value of the save command feature.","s":"Implement GraphQL mutation","u":"/jimmer-doc/docs/graphql/mutation","h":"#implement-graphql-mutation","p":261},{"i":269,"t":"Embedded properties (Composite properties) merge multiple columns in the database into an integral whole, map them to a non-entity custom type, and then use this custom type to declare a property for the entity.","s":"Embedded Properties","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"","p":268},{"i":272,"t":"First, define a composite type: Java Kotlin FullName.java @Embeddable public interface FullName { String firstName(); String lastName(); } FullName.kt @Embeddable interface FullName { val firstName: String val lastName: String } caution Types defined by @Embeddable are not entity types. They must not declare id properties or association properties, otherwise compilation errors will occur. Then we can use it in another entity: Java Kotlin Author.java @Entity public interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); FullName name(); } Author.kt @Entity interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: FullName } info Unlike JPA/Hibernate, when using composite types in entities, @Embedded is not required. In fact, Jimmer does not provide the @Embedded annotation at all. The table structure corresponding to Author is: create table author( id bigint unsigned not null auto_increment primary key, first_name varchar(20) not null, last_name varchar(20) not null ) engine=innodb;","s":"Basic Usage","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#basic-usage","p":268},{"i":274,"t":"org.babyfish.jimmer.sql.PropOverride can be used to override column names of composite type properties: Define composite type Point: Java Kotlin Point.java @Embeddable public interface Point { int x(); int y(); } Point.kt @Embeddable interface Point { val x: Int val y: Int } Define composite type Rect and override column names of Point type: Java Kotlin Rect.java @Embeddable public interface Rect { @PropOverride(prop = \"x\", columnName = \"`LEFT`\") @PropOverride(prop = \"y\", columnName = \"`TOP`\") Point leftTop(); @PropOverride(prop = \"x\", columnName = \"`RIGHT`\") @PropOverride(prop = \"y\", columnName = \"BOTTOM\") Point rightBottom(); } Rect.kt @Embeddable interface Rect { @PropOverride(prop = \"x\", columnName = \"`LEFT`\") @PropOverride(prop = \"y\", columnName = \"`TOP`\") val leftTop: Point @PropOverride(prop = \"x\", columnName = \"`RIGHT`\") @PropOverride(prop = \"y\", columnName = \"BOTTOM\") val rightBottom: Point } Define entity type Transition and override column names of Rect type: Java Kotlin Transition.java @Entity public interface Transition { @Id long id(); int millis(); Rect source(); @PropOverride(prop = \"leftTop.x\", columnName = \"TARGET_LEFT\") @PropOverride(prop = \"leftTop.y\", columnName = \"TARGET_TOP\") @PropOverride(prop = \"rightBottom.x\", columnName = \"TARGET_RIGHT\") @PropOverride(prop = \"rightBottom.y\", columnName = \"TARGET_BOTTOM\") Rect target(); } Transition.kt @Entity interface Transition { @Id val id: Long val millis: Int val source: Rect @PropOverride(prop = \"leftTop.x\", columnName = \"TARGET_LEFT\") @PropOverride(prop = \"leftTop.y\", columnName = \"TARGET_TOP\") @PropOverride(prop = \"rightBottom.x\", columnName = \"TARGET_RIGHT\") @PropOverride(prop = \"rightBottom.y\", columnName = \"TARGET_BOTTOM\") val target: Rect } The table structure corresponding to Transition is: create table transition( id bigint unsigned not null auto_increment primary key, millis int not null, `LEFT` int not null, `TOP` int not null, `RIGHT` int not null, bottom int not null, target_left int not null, target_top int not null, target_right int not null, target_bottom int not null ) engine=innodb;","s":"Override Column Names","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#override-column-names","p":268},{"i":276,"t":"warning Using composite types as primary/foreign keys, that is, primary keys and foreign keys are composed of multiple columns, makes the system more complex without much benefit. Therefore, unless compatibility with legacy database design is required, the system should avoid such usage to keep primary/foreign keys simple. Let's first define a composite type: Java Kotlin UniqueId.java @Embeddable public interface UniqueId { @columnName(\"UNIQUE_ID_DAY_NO\") int dayNo(); @columnName(\"UNIQUE_ID_SEQ_NO\") int sequenceNo(); } UniqueId.kt @Embeddable interface UniqueId { @columnName(\"UNIQUE_ID_DAY_NO\") val dayNo: Int @columnName(\"UNIQUE_ID_SEQ_NO\") val sequenceNo: Int }","s":"As Primary/Foreign Keys","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#as-primaryforeign-keys","p":268},{"i":278,"t":"Java Kotlin Book.java @Entity public interface Book { @Id UniqueId id(); ...Omit other code... } Book.kt @Entity interface Book { @Id val id: UniqueId ...Omit other code... } Since Book.id does not override column names of UniqueId type using @PropOverride, the column names configured in UniqueId are used. The corresponding DDL is: create table book( unique_id_day_no int not null, unique_id_seq_no int not null, ...Omit other columns... ) engine=innodb; alter table book add constraint pk_book primary key(unique_id_day_no, unique_id_seq_no);","s":"As Primary Key","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#as-primary-key","p":268},{"i":280,"t":"Java Kotlin Chapter.java @Entity public interface Chapter { @ManyToOne @JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ) @JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) Book book(); ...Omit other code... } Chapter.kt @Entity interface Chapter { @ManyToOne @JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ) @JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) val book: Book ...Omit other code... } caution Different from all the examples we have covered before, here the referencedColumnName of the @JoinColumn annotation is specified. When the foreign key consists of multiple columns, multiple @JoinColumn annotations must be used, where each @JoinColumn must specify referencedColumnName. If the foreign key is real, the corresponding constraint is: alter table chapter add constraint fk_chapter__book foreign key( book_id_day_no, book_id_seq_id ) references book( unique_id_day_no, unique_id_seq_no );","s":"Referenced by @JoinColumn","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#referenced-by-joincolumn","p":268},{"i":282,"t":"Java Kotlin Book.java @Entity public interface Book { @Id UniqueId id(); @ManyToMany @JoinTable( joinColumns = { @JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ), @JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) } ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @Id val id: UniqueId @ManyToMany @JoinTable( joinColumns = [ JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ), JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) ] ) val authors: List ...Omit other code... } If the foreign key is real, the DDL of the join table is: create table book_author_mapping( book_id_day_no int not null, book_id_seq_id int not null, author_id bigint not null ) engine=innodb; alter table book_author_mapping add constraint pk_book_author_mapping primary key( book_id_day_no, book_id_seq_id, author_id ); alter table book_author_mapping add constraint fk_book_author_mapping__book foreign key( book_id_day_no, book_id_seq_id ) references book( unique_id_day_no, unique_id_seq_no ); alter table book_author_mapping add constraint fk_book_author_mapping__author foreign key(author_id) references author(id);","s":"Referenced by @JoinTable","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#referenced-by-jointable","p":268},{"i":285,"t":"Through the content related to Association Mapping, it is not difficult to find that all associations are based on @JoinColumn and @JoinTable (may be omitted). Although Jimmer supports fake foreign keys (foreign keys in the developer's mind but without corresponding foreign key constraints in the database), all the association mappings we have discussed so far are based on 3NF design of relational databases. However, you may be handed over a legacy database containing non-normalized database designs, such as: create table book( id bigint unsigned not null auto_increment primary key, author_ids varchar(100), ...Omit other columns... ) engine=innodb; Here, author_ids is a string column whose data is the ids of all Author objects associated with the current Book concatenated together with commas, e.g. 1, 5, 100, 206. Obviously, this is a non-structural design that does not satisfy 3NF of relational databases. note For Postgres that supports array types, using arrays would be a better choice, but for better generality of this example, string concatenation is still used here without utilizing database-specific features.","s":"Non-Structural Design Example","u":"/jimmer-doc/docs/mapping/advanced/join-sql","h":"#non-structural-design-example","p":283},{"i":287,"t":"To support such non-structural designs, Jimmer provides the @org.babyfish.jimmer.sql.JoinSql annotation. info @JoinSql must and can only be used together with @ManyToMany. Next, create an SQL function (MySQL is used as example here): create function concatenation_string_contains( self varchar(100), id bigint ) returns boolean begin if self is null then return false; end if; return self regexp concat('(^|\\\\,)\\\\s*', id, '\\\\s*(\\\\,|$)'); end; This function assumes that the parameter self is in the format of multiple numbers concatenated by commas, and determines whether it contains the parameter id. For example: concatenation_string_contains('100, 200, 300', 200) returns true concatenation_string_contains('100, 200, 300', 201) returns false Now we can map the non-structural many-to-many association: Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinSql( \"concatenation_string_contains(\" + \" %alias.author_ids, \" + \" %target_alias.id\" + \")\" ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinSql( \"concatenation_string_contains(\" + \" %alias.author_ids, \" + \" %target_alias.id\" + \")\" ) val authors: List ...Omit other code... } The SQL expression used in @JsonSql represents the join condition, where: concatenation_string_contains: The SQL function we defined earlier %alias: A special token defined by Jimmer representing the alias of the current table (book table in this example) %target_alias: A special token defined by Jimmer representing the alias of the target table (author table in this example) caution ORM automatically generates SQL (which is very important for dynamic queries, especially for ORMs like Jimmer that first proposed the Dynamic Join concept), and users cannot interfere with the aliases of tables in the final SQL. So using %alias and %target_alias here is the only way. It is worth mentioning that if you want to define a bidirectional many-to-many association, since Book.authors has already used @JoinSql, the other end Author.books does not need to use @JoinSql again. As before, use mappedBy to indicate that it is the inverse property. Java Kotlin Author.java @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ...Omit other code... } Author.kt @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...Omit other code... }","s":"Non-Structural Association","u":"/jimmer-doc/docs/mapping/advanced/join-sql","h":"#non-structural-association","p":283},{"i":289,"t":"warning Unless legacy database compatibility is required, do not perform non-structural design and map it with @JoinSql, because non-structural many-to-many associations have many limitations: Cannot be used as Remote Association Cannot participate in Dynamic Join Optimization Cannot use Association Cache Cannot be saved as part of data structure by Save Command. In fact, if the data structure to be saved contains non-structural associations, it will cause exceptions.","s":"Precautions","u":"/jimmer-doc/docs/mapping/advanced/join-sql","h":"#precautions","p":283},{"i":291,"t":"Jimmer handles enums in two ways: Map to string: A choice with better understandability and traceability, also the default option. Map to integer: A choice with better performance-first. Jimmer provides two annotations for enums: org.babyfish.jimmer.sql.EnumType: Decorate enum types, optional Specify mapping method, map to string or ordinal position to integer org.babyfish.jimmer.sql.EnumItem: Decorate enum items, optional Override the mapped string value or integer value for some enum item","s":"Enum Mapping","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"","p":290},{"i":293,"t":"Java Kotlin Gender.java @EnumType(EnumType.Strategy.NAME) public enum Gender { MALE, FEMALE } Gender.kt @EnumType(EnumType.Strategy.NAME) enum class Gender { MALE, FEMALE } Here, the parameter of @EnumType is specified as \"NAME\", indicating mapping to string. By default, the mapped string values of the two enum items are the same as their names, i.e. \"MALE\" and \"FEMALE\". If you expect the mapped strings to be different from the enum item names, you can decorate the enum items with @EnumItem. Java Kotlin Gender.java @EnumType(EnumType.Strategy.NAME) public enum Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE } Gender.kt @EnumType(EnumType.Strategy.NAME) enum class Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE }","s":"Map to String","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#map-to-string","p":290},{"i":295,"t":"Java Kotlin Gender.java @EnumType(EnumType.Strategy.ORDINAL) public enum Gender { MALE, FEMALE } Gender.kt @EnumType(EnumType.Strategy.ORDINAL) enum class Gender { MALE, FEMALE } Here, the parameter of @EnumType is specified as \"ORDINAL\", indicating mapping to integer. By default, the mapped integer values of the two enum items are the same as their ordinal, i.e. 0 and 1. If you expect the mapped integers to be different from the enum items' ordinal, you can decorate the enum items with @EnumItem. Java Kotlin Gender.java @EnumType(EnumType.Strategy.ORDINAL) public enum Gender { @EnumItem(ordinal = 100) MALE, @EnumItem(ordinal = 200) FEMALE } Gender.kt @EnumType(EnumType.Strategy.ORDINAL) enum class Gender { @EnumItem(ordinal = 100) MALE, @EnumItem(ordinal = 200) FEMALE }","s":"Map to Integer","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#map-to-integer","p":290},{"i":297,"t":"You can also avoid specifying the @EnumType annotation for enum types, that is, not explicitly indicate whether an enum type should be mapped to string or integer. In this case, Jimmer will refer to the default global configuration. info The default value of this global configuration is \"NAME\". If you need \"ORDINAL\", please override the global configuration. Next, we show how to override the global configuration: When using SpringBoot Add configuration item jimmer.default-enum-strategy in application.yml or application.properties and set its value to \"ORDINAL\" When not using SpringBoot Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultEnumStrategy(EnumType.Strategy.ORDINAL) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDefaultEnumStrategy(EnumType.Strategy.ORDINAL) ...Omit other configurations... }","s":"Do Not Explicitly Use @EnumType","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#do-not-explicitly-use-enumtype","p":290},{"i":299,"t":"The serialization of a type to JSON and its storage in the database are two independent matters. The content described above focuses on how Jimmer handles enum mapping in the database, which is unrelated to JSON. By default, Jackson converts enums to its name, so when generating the TypeScript Client, Jimmer maps the enum according to its name. Java Kotlin enum Gender { MAN, WOMAN } enum class Gender { MAN, WOMAN } The generated TypeScript code is as follows: export const GenderEnum_CONSTANTS = [ 'MAN', 'WOMAN' ] as const; export type GenderEnum = typeof GenderEnum_CONSTANTS[number]; //usage export type PersonDto = { gender: GenderEnum; } If you want to customize the JSON serialization, you need to use the @JsonValue annotation from Jackson. Java Kotlin enum Gender { MAN, WOMAN; @JsonValue public String getValue() { return name().toLowerCase(); } } enum class Gender { MAN, WOMAN; @JsonValue fun getValue(): String { return name().toLowerCase(); } } When detects the presence of annotations like @JsonValue, Jimmer not knowing how the enum will be converted during JSON serialization, so jimmer will translates the enum type to a string. The generated TypeScript code in this case is as follows: export type PersonDto = { gender: string; }","s":"Work with TypeScript Client and Jackson","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#work-with-typescript-client-and-jackson","p":290},{"i":301,"t":"Simple formula properties are properties declared with @org.babyfish.jimmer.sql.Formula. There are two usages: Formula properties based on Java/Kotlin calculation Formula properties based on SQL calculation note Simple formula properties are designed for simple and fast calculations. For complex calculations, use Complex Formula Properties instead. In Define Entity, we defined two fields for Author: firstName and lastName. Next, let's add a new property fullName to Author: fullName = firstName + ' ' + lastName Then we use two different ways, Java/Kotlin-based calculation and SQL-based calculation, to implement Author.fullName.","s":"Formula","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"","p":300},{"i":304,"t":"Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { @Formula(dependencies = {\"firstName\", \"lastName\"}) default String fullName() { return firstName() + ' ' + lastName(); } ...Omit other properties... } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { @Formula(dependencies = [\"firstName\", \"lastName\"]) val fullName: String get() = \"$firstName $lastName\" ...Omit other properties... } It is easy to see that Java/Kotlin-based simple formula properties have the following characteristics: The property is not abstract (requires default keyword in Java) and directly provides calculation logic implementation. @Formula's dependencies is specified, indicating that this property depends on Author.firstName and Author.lastName. That is, the dynamic entity must ensure the presence of both firstName and lastName properties to calculate fullName. The usage is: Java Kotlin Author author = authorRepository.findNullable( 1L, Fetchers.AUTHOR_FETCHER // Query id (implicit + forced) and fullName .fullName() ); System.out.println(author); val author = authorRepository.findNullable( 1L, newFetcher(Author::class).by { // Query id (implicit + forced) and fullName fullName() } ); println(author) The executed SQL is: select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR as tb_1_ where tb_1_.ID = ? fullName is a formula property without corresponding field in the database, but depends on firstName and lastName. So this SQL queries FIRST_NAME and LAST_NAME to make its dependent properties present. Next, let's see what is printed: {\"id\":1,\"fullName\":\"Eve Procello\"} We can see that after Jackson serialization (the toString method of entity objects is a shortcut for serialization), there is only fullName but no firstName and lastName. This is because the object fetcher causes firstName and lastName to be indirectly fetched due to fetching fullName, but they are not directly fetched. In this case, although the dynamic object has firstName and lastName, they are marked as invisible to Jackson and will not appear in the Jackson serialization result. note If the object fetcher directly fetches firstName and lastName, they will definitely appear in the serialization result. Readers can try it themselves, no need to repeat here.","s":"Depending on simple properties","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#depending-on-simple-properties","p":300},{"i":306,"t":"Suppose there is an Embeddable type Java Kotlin NameInfo.java @Embeddable public interface NameInfo { String firstName(); String lastName(); } NameInfo.kt @Embeddable interface NameInfo { val firstName: String val lastName: String } If an entity uses this Embeddable type, then the entity properties can depend on its internal properties, for example Java Kotlin Author.java @Entity public interface Author { NameInfo nameInfo(); @Formula(dependencies = {\"nameInfo.firstName\", \"nameInfo.lastName\"}) // or it can be written as: @Formula(dependencies = \"nameInfo\") default String fullName() { return nameInfo().firstName() + ' ' + nameInfo().lastName(); } ...other properties omitted... } Author.kt @Entity interface Author { val nameInfo: NameInfo @Formula(dependencies = [\"nameInfo.firstName\", \"nameInfo.lastName\"]) // or it can be written as: @Formula(dependencies = [\"nameInfo\"]) ...other properties omitted... val fullName: String get() = \"${nameInfo.firstName} ${nameInfo.lastName}\" } info The usage and execution effect are completely the same as above, no need to repeat.","s":"Depending on embedded object","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#depending-on-embedded-object","p":300},{"i":308,"t":"Java Kotlin Book.java @Entity public interface Book { @ManyToMany List authors(); @Formula(dependencies = \"authors\") default int authorCount() { return authors().size(); } @Formula(dependencies = {\"authors.firstName\", \"authors.lastName\"}) default List authorNames() { return authors() .stream() .map(author -> author.firstName() + ' ' + author.lastName()) .collect(Collectors.toList()); } ...other properties omitted... } Book.kt @Entity public interface Book { @ManyToMany val authors: List @Formula(dependencies = \"authors\") val authorCount: Int get() = authors.size @Formula(dependencies = [\"authors.firstName\", \"authors.lastName\"]) val authorNames: List get() = authors.map { \"${it.firstName} ${it.lastName}\" } ...other properties omitted... } Execute the following code Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .name() .edition() .authorCount() .authorNames() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition().desc()) select( table.fetchBy { name() edition() authorCount() authorNames() } ) } .execute() Execute, generating two SQL statements select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, from BOOK tb_1_ where tb_1_.NAME = ? /* Learning GraphQL */ order by tb_1_.EDITION desc select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ? /* 3 */, ? /* 2 */, ? /* 1 */ ) order by tb_1_.FIRST_NAME asc, tb_1_.LAST_NAME asc The obtained data is as follows [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"authorCount\":2, \"authorNames\":[\"Alex Banks\",\"Eve Procello\"] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"authorCount\":2, \"authorNames\":[\"Alex Banks\",\"Eve Procello\"] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"authorCount\":2, \"authorNames\":[\"Alex Banks\",\"Eve Procello\"] } ]","s":"Depending on association properties","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#depending-on-association-properties","p":300},{"i":310,"t":"Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { @Formula(sql = \"concat(%alias.FIRST_NAME, ' ', %alias.LAST_NAME)\") String fullName(); ...Omit other properties... } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { @Formula(sql = \"concat(%alias.FIRST_NAME, ' ', %alias.LAST_NAME)\") val fullName: String ...Omit other properties... } It is easy to see that SQL-based simple formula properties have the following characteristics: The property is abstract. @Formula's sql is specified as an SQL expression with a special token %alias Users cannot know the alias of the current table in the final SQL in advance, so Jimmer stipulates here that %alias represents the actual table column name. The usage is: Java Kotlin Author author = authorRepository.findNullable( 1L, Fetchers.AUTHOR_FETCHER // Query id (implicit + forced) and fullName .fullName() ); System.out.println(author); val author = authorRepository.findNullable( 1L, newFetcher(Author::class).by { // Query id (implicit + forced) and fullName fullName() } ); println(author) The generated SQL is: select tb_1_.ID, /* Here, `%alias` in @Formula.sql is replaced with `tb_1_` */ concat(tb_1_.FIRST_NAME, ' ', tb_1_.LAST_NAME) from AUTHOR as tb_1_ where tb_1_.ID = ? The final printed result is: {\"id\":1,\"fullName\":\"Eve Procello\"}","s":"2. SQL-based Calculation","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#2-sql-based-calculation","p":300},{"i":312,"t":"Compared with Java/Kotlin-based simple formula, SQL-based simple formula has one disadvantage and one advantage: Disadvantage: If the object fetcher fetches firstName, lastName and fullName at the same time, it will cause the final SQL to query three columns: tb_1_.FIRST_NAME, tb_1_.LAST_NAME and concat(tb_1_.FIRST_NAME, ' ', tb_1_.LAST_NAME). Obviously, the returned data contains redundancy and is wasteful. Advantage: Java/Kotlin-based formula properties can only be used as fields to be fetched by object fetchers, and cannot be used by SQL DSL. SQL-based formula properties will be generated into the strongly typed SQL DSL API by the code generator, available for SQL DSL, such as: Java's where(table.fullName().eq(\"Eve Procello\")) or Kotlin's where(table.fullName eq \"Eve Procello\") tip Among all formula properties, only SQL-based simple formula properties can be used by SQL DSL. It is recommended to use databases that support function indexes and use them in combination with function indexes. Therefore, it is recommended to carefully consider whether @Formula formula properties should be based on Java/Kotlin calculation or SQL calculation.","s":"Comparison","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#comparison","p":300},{"i":314,"t":"Jimmer supports JSON properties. In Java/Kotlin entity types, such properties can be declared as any type other than java.lang.Object and kotlin.Any. In the database, the information stored in the corresponding column is JSON. info JSON properties are simple properties, not association properties. According to the current implementation, the corresponding column type in Postgres should be jsonb, and the corresponding column type in other databases should be string. Jimmer provides org.babyfish.jimmer.sql.Serialized. There are two ways to use JSON mapping: Global JSON mapping If the property type is a custom class rather than an array, collection, or Map, decorate this class with @Serialized. This way, any properties of the this type in all entities will become JSON properties. Property-level JSON mapping The current property can be decorated with @Serialized. Properties of array, collection, or map types must use property-level mapping; however, global mapping is better for custom types.","s":"JSON Mapping","u":"/jimmer-doc/docs/mapping/advanced/json","h":"","p":313},{"i":316,"t":"First, define a custom class and decorate it with @Serialized: Java Kotlin UserType.java @Serialized public class UserType { ...Omit members, can contain any info... ...As long as Json serialization/deserialization is supported... } UserType.kt @Serialized data class UserType( ...Omit parameters, can contain any info... ...As long as Json serialization/deserialization is supported... ) Then UserType can be used to define properties for any entity: Java Kotlin Book.java @Entity public interface Book { UserType userData(); ...Omit other types... } Book.kt @Entity interface Book { val userData: UserType ...Omit other types... }","s":"Global JSON Mapping","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#global-json-mapping","p":313},{"i":318,"t":"Just decorate the property with @Serialized: Java Kotlin Book.java @Entity public interface Book { @Serialized List> userData1(); @Serialized Map> userData2(); ...Omit other types... } Book.kt @Entity interface Book { @Serialized val userData1: List> @Serialized val userData2: Map> ...Omit other types... }","s":"Property-level JSON Mapping","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#property-level-json-mapping","p":313},{"i":321,"t":"Developers can configure the ObjectMapper for JSON serialization/deserialization of properties decorated with @Serialized. Java Kotlin ObjectMapper mapper1 = ...omitted...; ObjectMapper mapper2 = ...omitted...; ObjectMapper mapper3 = ...omitted...; JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultSerializedTypeObjectMapper(mapper1) ❶ .setSerializedTypeObjectMapper(MetaConfig.class, mapper2) ❷ .setSerializedTypePropMapper(TopicProps.TAGS, mapper3) ❸ ...Omit other configurations... .build(); val mapper1: ObjectMapper = ...omitted... val mapper2: ObjectMapper = ...omitted... val mapper3: ObjectMapper = ...omitted... val sqlClient = newKSqlClient { setDefaultSerializedTypeObjectMapper(mapper1) ❶ setSerializedTypeObjectMapper(MetaConfig::class, mapper2) ❷ setSerializedTypePropMapper(Topic::tags, mapper3) ❸ ...Omit other configurations... } ❶ Set default ObjectMapper to mapper1 Equivalent to setSerializedTypeObjectMapper(Object.class, mapper1) ❷ For any property whose return type is MetaConfig or its subclass, use mapper2 ❸ Explicitly set ObjectMapper for Topic.tags to mapper3 If the set property is not decorated with @Serialized, an exception will be thrown Configuration precedence: ❸ > ❷ > ❶","s":"Use Low-level API","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#use-low-level-api","p":313},{"i":323,"t":"If using the Spring Boot Starter, the SqlClient is created automatically, but users can change the configuration before SqlClient is created via Customizer/KCustomizer: Java Kotlin @Component public class SerializationCustomizer implements Customizer { @Override public void customize(JSqlClient.Builder builder) { builder .setDefaultSerializedTypeObjectMapper(...omitted...) .setSerializedTypeObjectMapper(MetaConfig.class, ...omitted...) .setSerializedTypePropMapper(TopicProps.TAGS, ...omitted...); } } @Component class SerializationCustomizer : KCustomizer { override fun customize(dsl: KSqlClientDsl) { dsl .setDefaultSerializedTypeObjectMapper(...omitted...) .setSerializedTypeObjectMapper(MetaConfig::class, ...omitted...) .setSerializedTypePropMapper(Topic::tags, ...omitted...); } }","s":"Use Spring Boot Starter","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#use-spring-boot-starter","p":313},{"i":326,"t":"info @org.babyfish.jimmer.sql.Key is used together with Save Command in mutation section. Initially, people used business fields directly as the primary key of tables. This is the most straightforward and easy to use approach, but it has the following problems: Unstable primary key Since the primary key itself is a business field, it can be modified, which leads to an unstable primary key. Although the foreign keys that reference it in the database can use on update cascade to keep consistency, an unstable primary key will cause many problems for systems outside the database, such as caches. Even if a unified solution to the primary key instability problem can be abstracted at the technical level, it is not recommended, because it makes the system difficult to understand. High cost of multi-table joins Since the primary key itself is a business field, its type is likely to be a relatively long string type rather than a numeric type, and it may even be a composite primary key composed of multiple columns, which leads to high cost of multi-table joins. To solve the above problems, people learned to use data without business meaning as the primary key, such as Auto numbering by database Sequence value by database UUID Snowflake ID To enable idempotent saves for save commands, Jimmer introduces two concepts: Id and Key @Id: Primary key @Key: Business primary key If Id itself is a business attribute (not recommended), no need to specify Key, because Id itself already represents the uniqueness constraint at the business level. If Id has no business meaning (recommended), then Key represents what the uniqueness constraint is at the business level. See the following example: Java Kotlin @Entity public interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key @ManyToOne @Nullable TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } @Entity interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List } Here, the Id of the TreeNode entity uses auto numbering and has no business meaning. Therefore, to better match save commands, key is specified here, consisting of two properties: name and parent. The corresponding DDL is: create table TREE_NODE( ID bigint not null, NAME varchar(20) not null, PARENT_ID bigint ); alter table TREE_NODE add constraint PK_TREE_NODE primary key(ID); alter table TREE_NODE add constraint UQ_TREE_NODE unique(NAME, PARENT_ID); The name and parent properties of the entity type decorated with @Key correspond to the UNIQUE constraint (or UNIQUE INDEX) composed of the NAME and PARENT_ID columns in the database. This uniqueness constraint can be analogized to file systems. File systems allow directories or files with the same name, but do not allow the same name if the parent directory is specified. info Through this example, we see: Key can consist of multiple properties Foreign keys can be part of Key Let's take another look at another example where the properties that make up Key are all properties based on foreign keys: Java Kotlin @Entity public interface OrderItem { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key @ManyToOne Order order(); @Key @ManyToOne Product product(); int quantity(); // Snapshot of `product.price` BigDecimal unitPrice(); } @Entity interface OrderItem { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key @ManyToOne val order: Order @Key @ManyToOne val product: Product val quantity: Int // Snapshot of `product.price` val unitPrice: BigDecimal } This article only introduces the configuration of Key. For how to use it further, please refer to Save Command.","s":"Concept","u":"/jimmer-doc/docs/mapping/advanced/key","h":"#concept","p":324},{"i":328,"t":"Jimmer supports logical deletion, which hides deleted data instead of actually deleting it. The unique constraint defined by @Key is only for non-hidden data, not all data in the table, so unique constraint cannot be simply defined by the columns of @key. When the logical deletion flag is datetime Java Kotlin Book.java @Entity public interface Book { @Key String name(); @LogicalDeleted(\"now\") @Nullable LocalDateTime deletedTime(); ...other code omitted... } Book.kt @Entity interface Book { @Key val name: String @LogicalDeleted(\"now\") val deletedTime: LocalDateTime? ...other code omitted... } In this case, combine the columns corresponding to @Key (for this example, NAME) and the logical deletion flag column (for this example, DELETED_TIME) to define the uniqueness constraint, e.g.: alter table BOOK add constraint UQ_BOOK unique(NAME, DELETED_TIME); When the logical deletion flag is other type Java Kotlin Book.java @Entity public interface Book { @Key String name(); @LogicalDeleted(\"true\") boolean deleted(); ...other code omitted... } Book.kt @Entity interface Book { @Key val name: String @LogicalDeleted(\"true\") val deleted: Boolean ...other code omitted... } In this case, combining the @Key columns and the logical deletion flag column is no longer a viable approach. Using a conditional unique index is the only option. caution Unfortunately, not all databases support conditional indexes, and the syntax for creating conditional index varies between databases. Here, PostgresSQL is used as an example: create unique index BOOK_KEY_INDEX on BOOK(NAME) where DELETED = false;","s":"Multi-version support","u":"/jimmer-doc/docs/mapping/advanced/key","h":"#multi-version-support","p":324},{"i":330,"t":"Configuration specified by the annotation @Key is called static configuration. Sometimes, different businesses may have different requirements for @Key. Therefore, @Key configurations can be dynamically overridden at runtime. Java Kotlin sqlClient .getEntities() .saveCommand(book) .setKeyProps(BookProps.NAME, BookProps.EDITION) .execute(); sqlClient.save(book) { .setKeyProps(Book::name, Book::edition) }","s":"Dynamic Overrides","u":"/jimmer-doc/docs/mapping/advanced/key","h":"#dynamic-overrides","p":324},{"i":333,"t":"Jimmer entities can use @org.babyfish.jimmer.sql.Transient to define a property unrelated to the database table structure. Java Kotlin BookStore.java package com.example.model; import org.babyfish.jimmer.sql.*; public interface BookStore { ...Omit other properties... @Transient Object customData(); } BookStore.kt package com.example.model import org.babyfish.jimmer.sql.* interface BookStore { ...Omit other properties... @Transient val customData: Any? } Here, no parameters are specified for the @Transient annotation, so the current data is just custom user data unrelated to any ORM behavior. caution Only when parameters are specified for the @Transient annotation will the current property be a complex calculation property. So what are the parameters of the @Transient annotation? Jimmer provides an interface for complex calculation properties: Java: org.babyfish.jimmer.sql.TransientResolver Kotlin: org.babyfish.jimmer.sql.kt.KTransientResolver This interface allows users to customize the data calculation process. Users develop a class that implements this interface and have it managed by Spring. How to implement this class will be explained in detail later, but for the purpose of expression here, let's assume the user class that implements this interface is CustomerDataResolver. The @Transient annotation parameters should be written as: If the project is a single project where entity classes can reference this class, then @Transient(CustomerDataResolver.class) or @Transient(CustomerDataResolver::class). If the project has multiple subprojects where entity classes cannot reference this class, then @Transient(ref = \"customerDataResolver\"). Where the string \"customerDataResolver\" represents the name of this object in the Spring context.","s":"@Transient Annotation","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#transient-annotation","p":331},{"i":335,"t":"In this section, we will add a calculation property BookStore.avgPrice to BookStore with the type java.math.BigDecimal.","s":"Scalar Calculation: BookStore.avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#scalar-calculation-bookstoreavgprice","p":331},{"i":337,"t":"Each complex calculation property corresponds to a TransientResolver implementation class. Before defining the calculation property BookStore.avgPrice, let's first define BookStoreAvgPriceResolver: Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.TransientResolver; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { @Override public Map resolve(Collection ids) { To be implemented later } @Override public BigDecimal getDefaultValue() { return BigDecimal.ZERO; } } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.KTransientResolver import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver : KTransientResolver { override fun resolve(ids: Collection): Map { To be implemented later } override fun getDefaultValue(): BigDecimal = BigDecimal.ZERO } The base interface TransientResolver/KTransientResolver has two generic parameters: The 1st generic parameter: The type of the id property of the entity to which the calculation property belongs. In this example, BookStore.avgPrice to be defined belongs to the BookStore entity whose id type is long, so the generic parameter here is Long. The 2nd generic parameter: The return data type of the calculation property. In this example, the type of BookStore.avgPrice to be defined is BigDecimal, so the generic parameter here is BigDecimal. resolve is a method of the base interface that must be implemented for users to complete calculation through it. info The parameter type of the resolve method is Collection instead of Long; its return type is Map. This is very important. It means that BookStore.avgPrice is not calculated one by one against BookStore.id, but is calculated in batches against multiple BookStore.id at a time. This is designed to prevent the N+1 problem caused by calculation properties. This design is almost the same as MappedBatchLoader in the GraphQL field, which is the standard programming model for all similar domains. getDefaultValue is an optional method of the base interface to implement. For the resolve method, if the length of the returned Map is less than the length of the ids parameter collection passed in, it means some data does not have calculation results. The calculation value corresponding to each such data is considered null. However, if the calculation property (BookStore.avgPrice in this example) is non-null, it will cause problems. Users can override getDefaultValue() to return a non-null default value to resolve this issue. caution For calculation properties that do not allow null, TransientResolver must: Either ensure the keySet of the Map returned by the resolve method contains all parameters Or override getDefaultValue to return a non-null default value","s":"Define Resolver for avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-resolver-for-avgprice","p":331},{"i":339,"t":"Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.ast.tuple.Tuple2; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { private final JSqlClient sqlClient; // Constructor injection public BookStoreAvgPriceResolver(JSqlClient sqlClient) { this.sqlClient = bookStoreRepository; } @Override public Map resolve(Collection ids) { return Tuple2.toMap( sqlClient .createQuery(table) .where(table.storeId().in(storeIds)) ❶ .groupBy(table.storeId()) ❷ .select( table.storeId(), table.price().avg() ❸ ) .execute() ); } ...Omit other methods... } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.* import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver( // Constructor injection private val sqlClient: KSqlClient ) : KTransientResolver { override fun resolve(ids: Collection): Map = sqlClient .createQuery(Book::class) { where(table.store.id valueIn storeIds) ❶ groupBy(table.store.id) ❷ select( table.store.id, avg(table.price).asNonNull() ❸ ) } .execute() .associateBy({it._1}) { it._2 } ...Omit other functions... } ❶ Filter the foreign key STORE_ID in the BOOK table to limit the query scope. Only calculate the average price of books under the bookstores that need calculation at the moment, not all bookstores in the database. ❷ Group by the foreign key STORE_ID in the BOOK table. ❸ Calculate the average of book prices within each group. avg: Calculate the average of Book.price within the group. note In the Kotlin code there is an asNonNull(). According to SQL standards, if the aggregate function avg is not used with group, its return value can be null without original data. So in Kotlin avg is defined to return a nullable type. However, when the aggregate function avg is used with group, it cannot return null. So asNonNull() is called to get a non-null expression.","s":"Implement Resolver for avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#implement-resolver-for-avgprice","p":331},{"i":341,"t":"Now that the BookStoreAvgPriceResolver class is complete, we can add the calculation property avgPrice to the BookStore entity: Java Kotlin BookStore.java package com.example.model; import com.example.business.resolver.BookStoreAvgPriceResolver; ❶ import org.babyfish.jimmer.sql.*; public interface BookStore { ...Omit other properties... @Transient(BookStoreAvgPriceResolver.class) ❷ BigDecimal avgPrice(); } BookStore.kt package com.example.model import com.example.business.resolver.BookStoreAvgPriceResolver ❶ import org.babyfish.jimmer.sql.* interface BookStore { ...Omit other properties... @Transient(BookStoreAvgPriceResolver::class) ❷ val avgPrice: BigDecimal } If it is a single project, the BookStoreAvgPriceResolver class can be referenced here. Define the calculation property BookStore.avgPrice, and specify the class introduced at ❶ for its @Transient annotation to tell Jimmer the calculation rule for the calculation property. caution If it is a multi-project where the code structure has been split, the import statement at ❶ is invalid. In this case, ❷ must be @Transient(ref = \"bookStoreAvgPriceResolver\"). That is, use the name of this object in the Spring context.","s":"Define avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-avgprice","p":331},{"i":343,"t":"Java Kotlin List stores = bookStoreRepository.findAll( Fetchers.BOOK_STORE_FETCHER .name() .avgPrice() ); System.out.println(stores); val stores = bookStoreRepository.findAll( newFetcher(BookStore::class).by { name() avgPrice() } ) println(stores) Printed result: [ { \"id\":2, \"name\":\"MANNING\", \"avgPrice\":80.333333333333 }, { \"id\":1, \"name\":\"O'REILLY\", \"avgPrice\":57.944444444444 } ] Executed SQL: /* Step 1: Query aggregate root objects, i.e. BookStore */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ /* Step 2: Calculate `avgPrice` property for BookStore objects with id 1 and 2 */ select tb_1_.STORE_ID, avg(tb_1_.PRICE) from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 2 */, ? /* 1 */ ) group by tb_1_.STORE_ID","s":"Fetch avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#fetch-avgprice","p":331},{"i":346,"t":"In the previous section we demonstrated the calculation property BookStore.avgPrice, which is obviously a non-associative property. In this section, we will add a calculation property BookStore.newestBooks to BookStore with the type java.util.List, which is clearly an association property. To explain why this example needs to add a calculation property BookStore.newestBooks, let's first look at the characteristics of the original association property BookStore.books: Java Kotlin Book store = bookStoreRepository.findNullable( 1L, Fetchers.BOOK_STORE_FETCHER .name() .books( Fetchers.BOOK_FETCHER .name() .edition() ) ); System.out.println(store); val store = bookStoreRepository.findNullable( 1L, newFetcher(BookStore::class).by { name() books { name() edition() } } ) println(store) The query result is: { \"id\":1, \"name\":\"O'REILLY\", \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3 }, { \"id\":5, \"name\":\"Effective TypeScript\", \"edition\":2 }, { \"id\":4, \"name\":\"Effective TypeScript\", \"edition\":1 }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3 }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2 }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1 }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3 }, { \"id\":8, \"name\":\"Programming TypeScript\", \"edition\":2 }, { \"id\":7, \"name\":\"Programming TypeScript\", \"edition\":1 } ] } We can see that in the original BookStore.books association, there are many books with the same name in the bookstore. For example, there are a total of three books named \"Effective TypeScript\", with different edition values: 3, 2, 1. Now we want to create a new calculation property BookStore.newestBooks through calculation. It ensures that the returned book collection has no duplicate name problem. For each unique book name, only the book with the highest edition, i.e. the maximum edition, is taken.","s":"Clarify Requirements","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#clarify-requirements","p":331},{"i":348,"t":"Each complex calculation property corresponds to a TransientResolver implementation class. Before defining the calculation property BookStore.newestBooks, let's first define BookStoreNewestBooksResolver: Java Kotlin BookStoreNewestBooksResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.springframework.stereotype.Component; @Component public class BookStoreNewestBooksResolver implements TransientResolver> { ❶ @Override public Map> resolve(Collection ids) { ❷ ...To be implemented later... } @Override public List getDefaultValue() { Collections.emptyList(); } package com.example.business.resolver import org.babyfish.jimmer.sql.kt.* import org.springframework.stereotype.Component @Component class BookStoreNewestBooksResolver : KTransientResolver> { ❶ override fun resolve(ids: Collection): Map> { ❷ ...To be implemented later... } override fun getDefaultValue(): List = emptyList() } ❶ The base interface TransientResolver/KTransientResolver has two generic parameters: The 1st generic parameter: The type of the id property of the entity to which the calculation property belongs. In this example, BookStore.newestBooks to be defined belongs to the BookStore entity whose id type is long, so the generic parameter here is Long. The 2nd generic parameter: The return data type of the calculation property. In this example, the type of BookStore.newestBooks to be defined is List. Since it is a collection type, the generic parameter contains List here. Book is an entity type. Jimmer stipulates that the entity type here needs to be replaced with its id type, and Book.id is of type long. In summary, the 2nd generic parameter is List. ❷ resolve is a method of the base interface that must be implemented for users to complete calculation through it. info The parameter type of the resolve method is Collection instead of Long; its return type is Map>. This is very important. It means that BookStore.newestBooks is not calculated one by one against BookStore.id, but is calculated in batches against multiple BookStore.id at a time. This is designed to prevent the N+1 problem caused by calculation properties. This design is almost the same as MappedBatchLoader in the GraphQL field, which is the standard programming model for all similar domains. ❸ getDefaultValue is an optional method of the base interface to implement. For the resolve method, if the length of the returned Map is less than the length of the ids parameter collection passed in, it means some data does not have calculation results. The calculation value corresponding to each such data is considered null. However, if the calculation property (BookStore.newestBooks in this example) is non-null, it will cause problems. Users can override getDefaultValue() to return a non-null default value to resolve this issue. caution If calculation properties do not allow null, for their TransientResolver implementations: Either ensure the keySet of the Map returned by the resolve method contains all parameters Or override getDefaultValue to return a non-null default value","s":"Define Resolver for newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-resolver-for-newestbooks","p":331},{"i":350,"t":"Java Kotlin package com.example.business.resolver; import java.util.Collections; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.ast.tuple.Tuple2; import org.springframework.stereotype.Component; @Component public class BookStoreNewestBooksResolver implements TransientResolver> { private final JSqlClient sqlClient; // Constructor injection public BookStoreAvgPriceResolver(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Override public Map> resolve(Collection ids) { return Tuple2.toMultiMap( sqlClient .createQuery(table) .where( Expression.tuple( ❶ table.name(), table.edition() ).in( sqlClient.createSubQuery(table) ❷ .where(table.storeId().in(ids)) ❸ .groupBy(table.name()) ❹ .select( table.name(), table.edition().max() ❺ ) ) ) .select( table.storeId(), table.id() ) .execute() ); } ...Omit other code... } package com.example.business.resolver import org.babyfish.jimmer.sql.kt.* import org.springframework.stereotype.Component @Component class BookStoreNewestBooksResolver( // Constructor injection private val sqlClient: KSqlClient ) : KTransientResolver> { override fun resolve(ids: Collection): Map> = sqlClient .createQuery(Book::class) { where( tuple( ❶ table.name, table.edition ) valueIn subQuery(Book::class) { ❷ where(table.store.id valueIn storeIds) ❸ groupBy(table.name) ❹ select( table.name, max(table.edition).asNonNull() ❺ ) } ) select( table.store.id, table.id ) } .execute() .groupBy({it._1}) { it._2 } ...Omit other code... } ❶ Book.name and Book.edition form an SQL tuple. ❷ The tuple has two columns of type String and int. The subquery also has two columns of type String and int. The two match perfectly and can use the in operator. ❸ Limit the query scope to only calculate the latest version of books that need to be queried at the moment, not all bookstores in the database. Imposing calculation scope limiting conditions on the subquery performs better than imposing them on the parent query. ❹ Group by book name, so books of the same name must belong to the same group. ❺ For each group of books with the same name, find the maximum edition.","s":"Implement Resolver for newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#implement-resolver-for-newestbooks","p":331},{"i":352,"t":"Now that the BookStoreNewestBooksResolver class is complete, we can add the calculation property newestBooks to the BookStore entity: Java Kotlin package com.example.model; import com.example.business.resolver.BookStoreNewestBooksResolver; ❶ import org.babyfish.jimmer.sql.*; public interface BookStore { ...Omit other properties... @Transient(BookStoreNewestBooksResolver.class) ❷ List newestBooks(); } package com.example.model import com.example.business.resolver.BookStoreNewestBooksResolver ❶ import org.babyfish.jimmer.sql.* interface BookStore { ...Omit other properties... @Transient(BookStoreNewestBooksResolver::class) ❷ val newestBooks: List } If it is a single project, the BookStoreNewestBooksResolver class can be referenced here. Define the calculation property BookStore.newestBooks, and specify the class introduced at ❶ for its @Transient annotation to tell Jimmer the calculation rule for the calculation property. caution If it is a multi-project where the code structure has been split, the import statement at ❶ is invalid. In this case, ❷ must be @Transient(ref = \"bookStoreNewestBooksResolver\"). That is, use the name of this object in the Spring context.","s":"Define newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-newestbooks","p":331},{"i":354,"t":"Java Kotlin List stores = bookStoreRepository.findAll( Fetchers.BOOK_STORE_FETCHER .name() .newestBooks( ❶ ❷ Fetchers.BOOK_FETCHER allScalarFields() .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ); System.out.println(stores); val stores = bookStoreRepository.findAll( newFetcher(BookStore::class).by { name() newestBooks { ❶ ❷ allScalarFields() authors { allScalarFields() } } } ) println(stores) Fetch the calculation property BookStore.newestBooks The calculation property itself is also an association property, so the shape of its associated objects can be controlled by a deeper child fetcher. The printed result is: [ { \"id\":2, \"name\":\"MANNING\", \"newestBooks\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, // This edition is max, no duplicate names \"price\":80, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] } ] }, { \"id\":1, \"name\":\"O'REILLY\", \"newestBooks\":[ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, // This edition is max, no duplicate names \"price\":51, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, // This edition is max, no duplicate names \"price\":88, \"authors\":[ { \"id\":3, \"firstName\":\"Dan\", \"lastName\":\"Vanderkam\", \"gender\":\"MALE\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, // This edition is max, no duplicate names \"price\":48, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\", \"gender\":\"MALE\" } ] } ] } ] The generated SQL is: /* Step 1: Query aggregate root objects, i.e. BookStore */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ /* Step 2: For BookStore objects with id 1 and 2, calculate id sets of all Books that `newestBooks` can associate to */ select tb_1_.STORE_ID, tb_1_.ID from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( select tb_3_.NAME, max(tb_3_.EDITION) from BOOK tb_3_ where tb_3_.STORE_ID in ( ? /* 2 */, ? /* 1 */ ) group by tb_3_.NAME ) /* Step 3: For associated Book ids, query non-associative fields */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.ID in (?, ?, ?, ?) /* Step 4: For associated Books, query associable Authors */ select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) tip This example shows that when the calculation property itself is also an association property, the shape of its associated objects can be controlled by a deeper child fetcher. Since there is a deeper child fetcher, of course both native ORM association properties and other calculation association properties can be included. That is, in the process of querying complex data structures by object fetchers, the fetching tasks of ORM association properties and calculation association properties can be arbitrarily mixed. The fetching task of ORM association properties is actually SQL operations. (At least before we introduce cache, it can be considered so) As mentioned earlier, Jimmer does not impose any restrictions on the calculation methods of calculation properties. You can even use any technology other than SQL, such as OLAP technologies, to implement the calculation process (this documentation focuses on Jimmer itself, so examples also use Jimmer to implement the calculation process). That is, the fetching task of calculation properties is not necessarily SQL operations. Therefore, the functionality provided by object fetchers is actually an arbitrary mix of SQL and non-SQL operations.","s":"Fetch newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#fetch-newestbooks","p":331},{"i":356,"t":"Logical deletion, also known as soft deletion, means data is not actually deleted. Instead, data is hidden to give the illusion of deletion. This leaves room for recovering from accidental operations.","s":"Logical Deletion","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/","h":"","p":355},{"i":359,"t":"Jimmer supports join table filters, with two usage scenarios:","s":"Two Scenarios","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#two-scenarios","p":357},{"i":361,"t":"Java Kotlin @Entity public interface Shop { @Id long id(); String name(); @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", readonly = true ) List customers(); @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"VIP\" ) ) List vipCustomers(); @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"ORDINARY\" ) ) List ordinaryCustomers(); } @Entity interface Shop { @Id val id: Long val name: String @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", readonly = true ) val customers: List @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"VIP\" ) ) val vipCustomers: List @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"ORDINARY\" ) ) val ordinaryCustomers: List } In this example, Shop.customers, Shop.vipCustomers, and Shop.ordinaryCustomers share the same join table create table SHOP_CUSTOMER_MAPPING( SHOP_ID bigint not null, CUSTOMER_ID bigint not null, MAPPING_TYPE varchar(8) not null ); // Whether the primary key of the join table contains // the filter column depends on the specific case. // In this example, a mapping between a `Shop` and `Customer` // cannot be both \"VIP\" and \"ORDINARY\" at the same time. // So the primary key does not contain `MAPPING_TYPE`. alter table SHOP_CUSTOMER_MAPPING add constraint pk_SHOP_CUSTOMER_MAPPING primary key(SHOP_ID, CUSTOMER_ID); alter table SHOP_CUSTOMER_MAPPING add constraint fk_SHOP_CUSTOMER_MAPPING__SHOP foreign key(SHOP_ID) references SHOP(ID); alter table SHOP_CUSTOMER_MAPPING add constraint fk_SHOP_CUSTOMER_MAPPING__CUSTOMER foreign key(CUSTOMER_ID) references CUSTOMER(ID); alter table SHOP_CUSTOMER_MAPPING add constraint fk_SHOP_CUSTOMER_MAPPING__MAPPING_TYPE check(MAPPING_TYPE in ('VIP', 'ORDINARY')); The table stores data like below: SHOP_ID CUSTOMER_ID MAPPING_TYPE 21 3176 VIP 21 1087 ORDINARY 21 9155 ORDINARY 40 8347 VIP 40 4365 ORDINARY 40 3478 ORDINARY Where Shop.vipCustomers corresponds to two rows, Shop.ordinaryCustomers to four rows, and Shop.customers can see all rows: Shop.customers = Shop.vipCustomers + Shop.ordinaryCustomers We can see that Shop.customers is not a base association, but the union of other associations. Let's call it a union association. caution Union associations cannot be directly modified, so readonly = true must be declared. Actually, the union association Shop.customers has an equivalent alternative syntax: Java Kotlin @ManyToMany @JoinTable( ...other params omitted..., filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = {\"VIP\", \"ORDINARY\"} ) ) List customers(); @ManyToMany @JoinTable( ...other params omitted..., filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = {\"VIP\", \"ORDINARY\"} ) ) val customers: List Finally, let's look at the difference in JOIN behavior between these three associations: Shop.customers Java Kotlin ShopTable table = Tables.SHOP_TABLE; List shopIds = sqlClient .create(table) .where( table .asTableEx() .customers() .name().eq(\"Smith\") ) .select(table.id()) .distinct() .execute(); val shopIds = sqlClient .create(Shop::class) { where( table .asTableEx() .customers .name eq \"Smith\" ) select(table.id()) } .distinct() .execute(); The generated SQL is: select distinct tb_1_.ID, tb_1_.NAME from SHOP tb_1_ inner join SHOP_CUSTOMER_MAPPING tb_2_ on tb_1_.ID = tb_2_.SHOP_ID inner join CUSTOMER tb_3_ on tb_2_.CUSTOMER_ID = tb_3_.ID where tb_3_.NAME = ? /* Smith */ Shop.vipCustomers Java Kotlin ShopTable table = Tables.SHOP_TABLE; List shopIds = sqlClient .create(table) .where( table .asTableEx() .vipCustomers() .name().eq(\"Smith\") ) .select(table.id()) .distinct() .execute(); val shopIds = sqlClient .create(Shop::class) { where( table .asTableEx() .vipCustomers .name eq \"Smith\" ) select(table.id()) } .distinct() .execute(); The generated SQL is: select distinct tb_1_.ID, tb_1_.NAME from SHOP tb_1_ inner join SHOP_CUSTOMER_MAPPING tb_2_ on tb_1_.ID = tb_2_.SHOP_ID and tb_2_.MAPPING_TYPE = ? /* VIP */ and tb_2_.type = ? inner join CUSTOMER tb_3_ on tb_2_.CUSTOMER_ID = tb_3_.ID where tb_3_.NAME = ? /* Smith */ Shop.ordinaryCustomers Java Kotlin ShopTable table = Tables.SHOP_TABLE; List shopIds = sqlClient .create(table) .where( table .asTableEx() .ordinaryCustomers() .name().eq(\"Smith\") ) .select(table.id()) .distinct() .execute(); val shopIds = sqlClient .create(Shop::class) { where( table .asTableEx() .ordinaryCustomers .name eq \"Smith\" ) select(table.id()) } .distinct() .execute(); The generated SQL is: select distinct tb_1_.ID, tb_1_.NAME from SHOP tb_1_ inner join SHOP_CUSTOMER_MAPPING tb_2_ on tb_1_.ID = tb_2_.SHOP_ID and tb_2_.MAPPING_TYPE = ? /* ORDINARY */ and tb_2_.type = ? inner join CUSTOMER tb_3_ on tb_2_.CUSTOMER_ID = tb_3_.ID where tb_3_.NAME = ? /* Smith */","s":"1. Multiple associations between same entity types","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#1-multiple-associations-between-same-entity-types","p":357},{"i":363,"t":"A common case is when a project has many kinds of data, and each kind of data can be tagged with multiple Tags. Tag Java Kotlin @Entity public interface Tag { @Id long id(); String name(); ...other properties omitted... } @Entity interface Tag { @Id val id: Long val name: String ...other properties omitted... } BookStore Java Kotlin @Entity public interface BookStore { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK_STORE\", ) ) List tags(); ...other properties omitted... } @Entity interface BookStore { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK_STORE\", ) ) val tags: List ...other properties omitted... } Book Java Kotlin @Entity public interface Book { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK\", ) ) List tags(); ...other properties omitted... } @Entity interface Book { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK\", ) ) val tags: List ...other properties omitted... } Author Java Kotlin @Entity public interface Author { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"AUTHOR\", ) ) List tags(); ...other properties omitted... } @Entity interface Author { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"AUTHOR\", ) ) val tags: List ...other properties omitted... } For the join table SOURCE_TAG_MAPPING, although the foreign key TAG_ID references the TAG table, the other foreign key SOURCE_ID does not have a fixed target - it could reference BOOK_STORE, BOOK or AUTHOR. Therefore we cannot add a foreign key constraint on SOURCE_ID. create table SOURCE_TAG_MAPPING( SOURCE_ID bigint not null, TAG_ID bigint not null, SOURCE_TYPE varchar(10) not null ); // Whether the primary key contains the filter column // depends on the specific case. // In this example, `SOURCE_ID` of different types could be equal, // so the primary key constraint needs to contain `SOURCE_TYPE`. alter table SOURCE_TAG_MAPPING add constraint pk_SHOP_CUSTOMER_MAPPING primary key(SOURCE_ID, TAG_ID, SOURCE_TYPE); // `SOURCE_ID` could reference `BOOK_STORE`, `BOOK` or `AUTHOR`, // so we cannot add a foreign key constraint alter table SOURCE_TAG_MAPPING add constraint fk_SOURCE_TAG_MAPPING__TAG primary key(TAG_ID) references TAG(ID); alter table SOURCE_TAG_MAPPING add constraint ck_SOURCE_TAG_MAPPING__SOURCE_TYPE check(SOURCE_TYPE in ('BOOK_STORE', 'BOOK', 'AUTHOR')); Since SOURCE_ID cannot have a foreign key constraint, it is a fake foreign key. That's why in the code above: @JoinTable( joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), ...other params omitted... ) Sample data could look like: SOURCE_ID TARGET_ID SOURCE_TYPE 9 2 BOOK_STORE 9 4 BOOK_STORE 86 3 BOOK 86 4 BOOK 781 1 AUTHOR 781 3 AUTHOR","s":"2. Multiple associations between different entity types","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#2-multiple-associations-between-different-entity-types","p":357},{"i":365,"t":"Both one-to-many and many-to-many can use join tables, so we can merge their join tables into one table. But please note: caution It is strongly recommended to only use this pattern when the database supports conditional indexes. That is, do not use this pattern on databases without conditional index support like MySQL.","s":"Mixing One-to-Many and Many-to-Many","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#mixing-one-to-many-and-many-to-many","p":357},{"i":367,"t":"Java Kotlin @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", readonly = true ) List authors(); @Nullable @ManyToOne @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"PRIMARY\" ) ) Author primaryAuthor(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"SECONDARY\" ) ) List secondaryAuthors(); ...other properties omitted... } @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", readonly = true ) val authors: List @Nullable @ManyToOne @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"PRIMARY\" ) ) val primaryAuthor: Author? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"SECONDARY\" ) ) val secondaryAuthors: List ...other properties omitted... } Clearly: authors (many-to-many) = primaryAuthor (many-to-one) + secondaryAuthors (many-to-many)","s":"Define Associations","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#define-associations","p":357},{"i":369,"t":"create table BOOK_AUTHOR_MAPPING( BOOK_ID bigint not null, AUTHOR_ID bigint not null, MAPPING_TYPE varchar(9) not null ); // Whether the primary key contains the filter column depends on the specific case. // In this example, a mapping between an `Author` and a `Book` // cannot be both \"PRIMARY\" and \"SECONDARY\" at the same time. // So the primary key constraint does not contain `MAPPING_TYPE`. alter table BOOK_AUTHOR_MAPPING add constraint pk_BOOK_AUTHOR_MAPPING primary key(BOOK_ID, AUTHOR_ID); alter table BOOK_AUTHOR_MAPPING add constraint fk_BOOK_AUTHOR_MAPPING__BOOK foreign key(BOOK_ID) references BOOK(ID); alter table BOOK_AUTHOR_MAPPING add constraint fk_BOOK_AUTHOR_MAPPING__BOOK foreign key(AUTHOR_ID) references AUTHOR(ID); alter table BOOK_AUTHOR_MAPPING add constraint ck_BOOK_AUTHOR_MAPPING__MAPPING_TYPE check(MAPPING_TYPE in ('PRIMARY', 'SECONDARY')); // Syntax for conditional indexes may differ slightly between databases, // here is an example in Postgres create unique index BOOK_AUTHOR_MAPPING__PRIMARY_INDEX on BOOK_AUTHOR_MAPPING(AUTHOR_ID) when MAPPING_TYPE = 'PRIMARY'; The when clause is very important, indicating this is a conditional index. Syntax for conditional indexes may differ slightly between databases, here is an example in Postgres. See https://www.postgresql.org/docs/current/indexes-partial.html for more details. When MAPPING_TYPE is \"PRIMARY\", a unique index is added on the AUTHOR_ID foreign key to ensure each Book has maximum one primary Author. That is, to ensure Book.primaryAuthor is a many-to-one association. Otherwise, there is no uniqueness constraint, so each Book can have any number of secondary Authors. That is, Book.secondaryAuthors remains a many-to-many association.","s":"Conditional Indexes","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#conditional-indexes","p":357},{"i":372,"t":"org.babyfish.jimmer.sql.MappedSuperclass is used to provide abstract super types that can be inherited by entities. The super type itself is not an entity, but can be inherited by multiple entity types to avoid duplicate declaration of the same properties in multiple entities. Let's look at an example. First define the super type: Java Kotlin BaseEntity.java @MappedSuperclass public interface BaseEntity { LocalDateTime createdTime(); @ManyToOne User createdBy(); LocalDateTime modifiedTime(); @ManyToOne User modifiedBy(); } BaseEntity.kt @MappedSuperclass interface BaseEntity { val createdTime: LocalDateTime @ManyToOne val createdBy: User val modifiedTime: LocalDateTime @ManyToOne val modifiedBy: User } Other entities can inherit it: BookStore Java Kotlin BookStore.java @Entity public interface BookStore extends BaseEntity { ...Omit other code... } BookStore.kt @Entity interface BookStore : BaseEntity { ...Omit other code... } Book Java Kotlin Book.java @Entity public interface Book extends BaseEntity { ...Omit other code... } Book.kt @Entity interface Book : BaseEntity { ...Omit other code... } Author Java Kotlin Author.java @Entity public interface Author extends BaseEntity { ...Omit other code... } Author.kt @Entity interface Author : BaseEntity { ...Omit other code... }","s":"Basic Usage","u":"/jimmer-doc/docs/mapping/advanced/mapped-super-class","h":"#basic-usage","p":370},{"i":374,"t":"Types decorated with MappedSuperclass support multiple inheritance. Other types can inherit from multiple MappedSuperclass super types. Add a new abstract interface TenantAware to be inherited by all multi-tenant entities: Java Kotlin TenantAware.java @MappedSuperclass public interface TenantAware { String tenant(); } TenantAware.kt interface TenantAware { val tenant: String } Java Kotlin Book.java @Entity public interface Book extends BaseEntity, TenantAware { ...Omit other code... } Book.kt @Entity interface Book : BaseEntity, TenantAware { ...Omit other code... } Modify Book to inherit not only BaseEntity but also TenantAware. tip The role of @MapperSuperclass is not just to reduce duplicate code, it can also cooperate with two other functions: Global Filters Interceptors When used in cooperation with them, multiple inheritance can provide good flexibility.","s":"Multiple Inheritance","u":"/jimmer-doc/docs/mapping/advanced/mapped-super-class","h":"#multiple-inheritance","p":370},{"i":377,"t":"@org.babyfish.jimmer.sql.OnDissociate is used together with Modification/Save Command and Modification/Delete Command Modification/Save Command Existing data structure in database Data structure expected to be saved by user +-BookStore(id=2) | +-----Book(id=10) | +-----Book(id=11) | \\-----Book(id=12) +-BookStore(id=2) | +-----Book(id=10) | | | | | \\-----Book(id=9) This means: The association between BookStore-2 and Book-10 remains unchanged The association between BookStore-2 and Book-9 needs to be created BookStore-2 needs to be disassociated from Book-11 and Book-12. Modification/Delete Command This is easy to understand. Child objects need to be disassociated before deleting the parent object. @OnDissociate can only be used on foreign key based many-to-one associations, for example: Java Kotlin Book.java @Entity public interface Book { @Null @ManyToOne @OnDissociate(DissociateAction.SET_NULL) BookStore store(); ... } Book.kt @Entity interface Book { @ManyToOne @OnDissociate(DissociateAction.SET_NULL) val store: BookStore? ... } info Although disassociation of child objects is caused by a one-to-many association (or inverse one-to-one) (that is, the parent object abandons some child objects. The one-to-many association here is BookStore.books), the disassociation mode is configured for the inverse many-to-one association (here Book.store). This design is to maintain similarity with configuring cascade properties of foreign keys in database DDLs. For Jimmer, a one-to-many association must be bidirectional, so the many-to-one association that is the mirror image of a known one-to-many association is always known. So there is no problem with this design.","s":"Concepts","u":"/jimmer-doc/docs/mapping/advanced/on-dissociate","h":"#concepts","p":375},{"i":379,"t":"The parameter of the OnDissociate annotation in the above code is called the dissociation mode: There are 5 modes for child object dissociation operations Mode Description NONE (Default) Depends on global configuration jimmer.default-dissociate-action-checking If jimmer.default-dissociate-action-checking is true (default) or the foreign key upon which the current association is based is real (foreign key constraint exists in database, see Real and Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-checking is false and the foreign key upon which the current association is based is fake (no corresponding foreign key constraint in database, see Real and Fake Foreign Keys), treated as LAX. LAX Dissociation operation performs no action. If the foreign key is real (see Real and Fake Foreign Keys), when parent object is deleted: If cascade delete behavior is configured for the database foreign key (on cascade set null or on delete delete), database automatically clears the foreign key of dissociated child objects or automatically deletes the dissociated child objects Although database-level cascade modification performs better than ORM-level cascade modification, the ORM is unaware of this. Use with caution in projects requiring cache consistency Otherwise, database reports an error and the save command is terminated If the foreign key is fake (see Real and Fake Foreign Keys), when parent object is deleted, no additional behavior occurs, allowing dangling issues with child object foreign key values Even if fake foreign key values are invalid dangling values, jimmer queries won't error - the query system will return null for parent objects rather than error due to non-existent parent CHECK Does not support dissociation operations. Throws exception to prevent operation if current parent object in database has child objects that need to be dissociated. SET_NULL Sets the foreign key of dissociated child objects to null. This mode requires that the child object's foreign key property is nullable; otherwise attempting this configuration will cause an exception. DELETE Deletes the dissociated child objects. This article only introduces the configuration of OnDissociate. For how to use it further, please refer to Save Command/Dissociation Operations and Delete Commands.","s":"Dissociation Modes","u":"/jimmer-doc/docs/mapping/advanced/on-dissociate","h":"#dissociation-modes","p":375},{"i":381,"t":"Configuration specified by the annotation @OnDissociate is called static configuration. Sometimes, different businesses may have different requirements for dissociation operations. Therefore, dissociation configurations can be dynamically overridden at runtime. Modification/Save Command Java Kotlin sqlClient .getEntities() .saveCommand(book) .setDissociateAction(BookProps.STORE, DissociateAction.SET_NULL) .execute(); sqlClient.save(book) { .setDissociateAction(Book::store, DissociateAction.SET_NULL) } Modification/Delete Command Java Kotlin DeleteResult result = sqlClient .getEntities() .deleteCommand(BookStore.class, 1L) .configure(it -> it .setDissociateAction( BookProps.STORE, DissociateAction.SET_NULL ) ) .execute(); val result = sqlClient .entities .delete(BookStore::class, 1L) { setDissociateAction( Book::store, DissociateAction.SET_NULL ) }","s":"Dynamic Overrides","u":"/jimmer-doc/docs/mapping/advanced/on-dissociate","h":"#dynamic-overrides","p":375},{"i":383,"t":"To enable logical deletion support for an entity, add a flag property annotated with org.babyfish.jimmer.sql.LogicalDeleted to indicate whether the data is normal or already deleted. Once a logical deletion property is configured for an entity: By default, when developers call APIs to delete an entity object, Jimmer will NOT actually delete the data with SQL delete statements. Instead, it will use update statements to set the logical deletion property of the entity to \"already deleted\". Other cases: Even if an entity has a logical deletion property, Jimmer also provides APIs for developers to forcibly truly delete objects by passing additional parameters. By default, all SQL queries against the entity will be automatically appended with a where logicalDeleteFlag <> already deleted condition to create the illusion that some data has been deleted. info This doc only covers the mapping configuration of the logical deletion flag field. For how to use the logical deletion functionality, see Global Filters / Logical Deletion.","s":"Entity Table","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"","p":382},{"i":385,"t":"The logical deletion flag property can be one of the following types: boolean: must be non-null int: must be non-null enum: must be non-null long/Long：either null or non-null UUID: either null or non-null date: must be nullable Type Code Deleted State Initialized State boolean Java Kotlin @LogicalDeleted(\"true\") boolean deleted(); @LogicalDeleted(\"true\") val deleted: Boolean true false Java Kotlin @LogicalDeleted(\"false\") val active: Boolean; @LogicalDeleted(\"false\") val active: Boolean false true int Java Kotlin @Default(\"0\") @LogicalDeleted(\"1\") int state(); @Default(\"0\") @LogicalDeleted(\"1\") val state: Int 1 0 Enum Java Kotlin @Default(\"INITIALIZED\") @LogicalDeleted(\"DELETED\") State state(); @Default(\"INITIALIZED\") @LogicalDeleted(\"DELETED\") val state: State DELETED INITIALIZED ✩ long Java Kotlin @LogicalDeleted long deletedMillis(); @LogicalDeleted val deletedMillis: Long Current milliseconds 0L ✩ Nullable Long Java Kotlin @LogicalDeleted Long deletedMillis(); @LogicalDeleted val deletedMillis: Long? Current milliseconds null ✩ UUID Java Kotlin @LogicalDeleted UUID deletedData(); @LogicalDeleted val deletedData: UUID Random UUID UUID with all bytes as 0 ✩ Nullable UUID Java Kotlin @Nullable @LogicalDeleted UUID deletedData(); @LogicalDeleted val deletedData: UUID? Random UUID null Nullable LocalDateTime ✩ Java Kotlin @Nullable @LogicalDeleted(\"now\") UUID deletedTime(); @LogicalDeleted(\"now\") val deletedTime: LocalDateTime? Current time null Java Kotlin @Nullable @LogicalDeleted(\"null\") UUID createdTime(); @LogicalDeleted(\"null\") val createdTime: LocalDateTime? null Current time Where ✩ in the first or second column indicates that the current configuration method supports multi-version data to be discussed in the next section. info Supporting logical deletion but not considering multi-version data issues is a less mature consideration. Therefore, it is recommended to use the logical deletion configuration that supports multi-version data. Current milliseconds, the default behavior is System.currentMillis(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedLongGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @LogicalDeleted(generatedType = YourGenerator.class) @LogicalDeleted(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework Random UUID, the default behavior is UUID.randomUUID(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedUUIDGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @LogicalDeleted(generatedType = YourGenerator.class) @LogicalDeleted(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework","s":"Usage","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"#usage","p":382},{"i":387,"t":"Logical deletion does not actually delete data, it only hides the data. This means that data appears in multiple versions. This issue is also described in Key / Multi-version Support. Take the example of long type logical deletion that supports multiple versions Java Kotlin @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); @LogicalDeleted long deletedMillis(); BigDecimal price(); @ManyToOne BookStore store(); } @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: String @LogicalDeleted val deletedMillis: Long val price: BigDecimal @ManyToOne val store: BookStore } Although the Key of the Book object is name and edition, because the deletedMillis property is the logical deletion flag, the non-primary key UNIQUE constraint at the database level should be: alter table BOOK add constraint uq_key_BOOK unique(NAME, EDITION, DELETED_MILLIS); If the table input is as follows: ID NAME EDITION PRICE STORE_ID DELETED_MILLIS 1027 SQL in Action 1 49.99 23 0 1026 SQL in Action 1 55.99 22 1708796420956 1025 SQL in Action 1 47.99 23 1708234681901 3131 SQL in Action 2 59.99 23 0 3130 SQL in Action 2 53.99 22 1708722582793 3129 SQL in Action 2 58.99 23 1708664484823 There are 4 associated data records hidden, leaving only two valid data records: ID NAME EDITION PRICE STORE_ID DELETED_MILLIS 1027 SQL in Action 1 49.99 23 0 3131 SQL in Action 2 59.99 23 0","s":"Multi-Version Data","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"#multi-version-data","p":382},{"i":389,"t":"If an entity is logically deleted, what effect does it have on associations based on middle tables (using the @JoinTable annotation)? If the middle table also supports logical deletion, that is, the logicalDeletedFilter of the @JoinTable annotation is specified, the middle table records related to the logically deleted entity will also be logically deleted. In [the next document] (./join-table), we will discuss in detail the logical deletion of middle tables. If the deletedWhenEndpointIsLogicallyDeleted of the @JoinTable annotation is set to true, the middle table records related to the logically deleted entity will be physically deleted. If neither of the above two conditions is met, the middle table records related to the logically deleted entity will not be processed at all.","s":"Effects on Middle Tables","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"#effects-on-middle-tables","p":382},{"i":391,"t":"View properties do not maintain their own data, they are just another representation of another attribute (called original attribute) of their owning entity type. View properties and original properties share the same underlying data, the only difference is that the returned data format is different from the original attribute. In this article, you will learn about these annotations: org.babyfish.jimmer.sql.IdView org.babyfish.jimmer.sql.ManyToManyView","s":"View Properties","u":"/jimmer-doc/docs/mapping/advanced/view/","h":"","p":390},{"i":393,"t":"caution Remote association is a product of combining Jimmer with microservice architecture. It will be introduced in detail in Spring Cloud and Remote Association. The purpose of this article is not to systematically explain remote associations, just to introduce the mapping configuration required for remote associations.","s":"Remote Association","u":"/jimmer-doc/docs/mapping/advanced/remote","h":"","p":392},{"i":395,"t":"The @Entity annotation has an optional parameter microServiceName whose default value is \"\". Association properties involve two entity types. Since associations must point from the source to the target (self association properties are special, the source and target overlap): If the microServiceName of the source entity and target entity of the association property are equal, then this association is a local association (All entities in the examples before this article use the default microServiceName, so they are local associations). If the microServiceName of the source entity and target entity of the association property are not equal, then this association is a remote association. For example: Owning side (required): Book.authors Java Kotlin Book.java @Entity(microServiceName = \"book-service\") public interface Book { @ManyToMany List authors(); ...Omit other code... } Book.kt @Entity(microServiceName = \"book-service\") interface Book { @ManyToMany val authors: List ...Omit other code... } Inverse side (optional): Author.authors Java Kotlin Author.java @Entity(microServiceName = \"author-service\") public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ...Omit other code... } Author.kt @Entity(microServiceName = \"author-service\") interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...Omit other code... } Here, the microservice name of Book is book-service, and the microservice name of Author is author-service. The two are not equal, so Book.authors and Author.books are remote associations.","s":"@Entity","u":"/jimmer-doc/docs/mapping/advanced/remote","h":"#entity","p":392},{"i":397,"t":"As a super type, MappedSuperclass has two usages: Can contain association properties, but must belong to the same microservice Java Kotlin BookServiceCommonEntity.java @MappedSuperclass(microServiceName = \"book-service\") public interface BookServiceCommonEntity { LocalDateTime createdTime(); @ManyToOne User createdBy(); LocalDateTime modifiedTime(); @ManyToOne User modifiedBy(); } BookServiceCommonEntity.kt @MappedSuperclass(microServiceName = \"book-service\") interface BookServiceCommonEntity { val createdTime: LocalDateTime @ManyToOne val createdBy: User val modifiedTime: LocalDateTime @ManyToOne val modifiedBy: User } Here BookServiceCommonEntity contains association properties createdBy and modifiedBy, but only Entity or other MappedSuperclass belonging to the microservice \"book-service\" can inherit it. Can span any microservices, but must not contain association properties Java Kotlin CommonEntity.java @MappedSuperclass(acrossMicroServices = true) public interface CommonEntity { LocalDateTime createdTime(); LocalDateTime modifiedTime(); } CommonEntity.kt @MappedSuperclass(acrossMicroServices = true) interface CommonEntity { val createdTime: LocalDateTime val modifiedTime: LocalDateTime } Here CommonEntity can span any microservices. Any Entity or other MappedSuperclass under any microservice can inherit it, but it itself does not contain any association properties.","s":"@MappedSuperclass","u":"/jimmer-doc/docs/mapping/advanced/remote","h":"#mappedsuperclass","p":392},{"i":399,"t":"In this series of articles, we will introduce base mappings.","s":"Base mapping","u":"/jimmer-doc/docs/mapping/base/","h":"","p":398},{"i":401,"t":"To enable logical deletion for the middle table, the property needs to be specified for the org.babyfish.jimmer.sql.JoinTable annotation to indicate whether the data is normal or has been deleted. Once a logical deletion attribute is configured for the middle table, when any entity on either end is logically deleted, all related middle table records will be logically deleted. All JOIN operations for the current association will be automatically added with the condition and logical deletion flag <> already deleted to give the illusion that some associations have been deleted.","s":"Join Table","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","h":"","p":400},{"i":403,"t":"The logical deletion flag attribute can be one of the following types: boolean: must be non-null int: must be non-null enum: must be non-null long/Long: can be null or non-null UUID: must be non-null Date: must be nullable Type Code Deleted State Initialized State boolean Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED\", type = boolean.class, value = \"true\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED\", type = boolean.class, value = \"true\" ) ) val authors: List true false Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"ACTIVE\", type = boolean.class, value = \"false\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"ACTIVE\", type = boolean.class, value = \"false\" ) ) val authors: List false true int Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = int.class, value = \"1\", initializedValue = \"0\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = int.class, value = \"1\", initializedValue = \"0\" ) ) val authors: List 1 0 Enum Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = State.class, value = \"DELETED\", initializedValue = \"INITIALIZED\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = State.class, value = \"DELETED\", initializedValue = \"INITIALIZED\" ) ) val authors: List DELETED INITIALIZED ✩ long Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) val authors: List Current milliseconds 0L ✩ Nullable Long Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = Long.class, nullable = true ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = Long.class, nullable = true ) ) val authors: List Current milliseconds null ✩ UUID Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class ) ) val authors: List Random UUID UUID with all bytes as 0 ✩ Nullable UUID Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class, nullable = true ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class, nullable = true ) ) val authors: List Random UUID null Nullable LocalDateTime ✩ Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_TIME\", type = LocalDateTime.class, nullable = true, value = \"now\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_TIME\", type = LocalDateTime.class, nullable = true, value = \"now\" ) ) val authors: List Current Time null Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"CREATED_TIME\", type = LocalDateTime.class, nullable = true, value = \"null\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"CREATED_TIME\", type = LocalDateTime.class, nullable = true, value = \"null\" ) ) val authors: List null Current Time Where ✩ in the first or second column indicates that the current configuration method supports multi-version data to be discussed in the next section. info Supporting logical deletion without considering multi-version data issues is less mature. Therefore, it is recommended to use the logical deletion configuration that supports multi-version data. Current milliseconds, the default behavior is System.currentMillis(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedLongGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @JoinTable.LogicalDeletedFilter(generatedType = YourGenerator.class) @JoinTable.LogicalDeletedFilter(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework Random UUID, the default behavior is UUID.randomUUID(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedUUIDGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @JoinTable.LogicalDeletedFilter(generatedType = YourGenerator.class) @JoinTable.LogicalDeletedFilter(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework","s":"Usage","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","h":"#usage","p":400},{"i":405,"t":"Logical deletion does not actually delete data, it only hides it. This means that data appears in multiple versions. Take the configuration that supports multi-version data as an example: Java Kotlin @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) List authors(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\",| logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) val authors: List For example, the BOOK_AUTHOR_MAPPING table has three columns, all as part of the primary key alter table BOOK_AUTHOR_MAPPING add pk_BOOK_AUTHOR_MAPPING primary key( BOOK_ID, AUTHOR_ID, DELETED_MILLIS ); If the table input is as follows: BOOK_ID AUTHOR_ID DELETED_MILLIS 97 23 0 97 23 1708796420956 97 23 1708234681901 249 11 0 249 11 1708722582793 249 11 1708664484823 There are 4 associated data records hidden, leaving only two valid data records: BOOK_ID AUTHOR_ID DELETED_MILLIS 97 23 0 249 11 0","s":"Multi-Version Data","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","h":"#multi-version-data","p":400},{"i":407,"t":"Here, you will learn about the most important capability of ORM: entity relationship mapping. You will learn about these annotations: org.babyfish.jimmer.sql.OneToOne org.babyfish.jimmer.sql.ManyToOne org.babyfish.jimmer.sql.OneToMany org.babyfish.jimmer.sql.ManyToMany org.babyfish.jimmer.sql.JoinColumn org.babyfish.jimmer.sql.JoinTable caution For associations, the type of the basic properties in the entity type should be the associated object, not the associated Id. If you want to define associated Id properties, please First complete the association mapping according to this chapter Then add associated Id properties according to IdView","s":"Association Mapping","u":"/jimmer-doc/docs/mapping/base/association/","h":"","p":406},{"i":409,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToOne annotation to declare many-to-one association properties. There are two ways to implement many-to-one associations: based on foreign key and based on join table.","s":"Many To One","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","h":"","p":408},{"i":411,"t":"Java Kotlin Book.java @Entity public interface Book { @ManyToOne BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne val store: BookStore ...Omit other code... } Here @JoinColumn is not used together to explicitly specify the foreign key column name. Jimmer will deduce the column name corresponding to the store property based on the naming strategy. If the default naming strategy is not overridden by the user, the foreign key column name of the store property is STORE_ID. So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") val store: BookStore ...Omit other code... } The foreign key can be real or fake. Fake foreign keys are discussed in subsequent documents. Here we assume the foreign key is real, so the corresponding constraint in the database is: // If foreign key pointing to associated entity is real, // create foreign key constraint alter table BOOK add constraint FK_BOOK__BOOK_STORE foreign key(STORE_ID) references BOOK_STORE(ID);","s":"1. Based on Foreign Key","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","h":"#1-based-on-foreign-key","p":408},{"i":413,"t":"Java Kotlin Book.java @Entity public interface Book { @Nullable @ManyToOne @JoinTable BookStore store(); ... } Book.kt @Entity interface Book { @Nullable @ManyToOne @JoinTable val store: BookStore? ... } Here, no properties are specified for @JoinTable. Jimmer will deduce the column names corresponding to the store property based on the naming strategy. If the default naming strategy is not overridden by the user, the deduced join table information is: Join table name: BOOK_BOOK_STORE_MAPPING Join table foreign key column pointing to current entity: BOOK_ID Join table foreign key column pointing to associated entity: STORE_ID So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @Null @ManyToOne @JoinTable( name = \"BOOK_BOOK_STORE_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"STORE_ID\" ) BookStore store(); ... } Book.kt @Entity interface Book { @ManyToOne @JoinTable( name = \"BOOK_BOOK_STORE_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"STORE_ID\" ) val store: BookStore? ... } The join table BOOK_BOOK_STORE_MAPPING is defined as: create table BOOK_BOOK_STORE_MAPPING( BOOK_ID bigint not null, STORE_ID bigint not null ); alter table BOOK_STORE_MAPPING add constraint PK_BOOK_STORE_MAPPING primary(BOOK_ID, STORE_ID); // If foreign key pointing to current entity is real, // create foreign key constraint alter table BOOK_BOOK_STORE_MAPPING add constraint FK_BOOK_BOOK_STORE_MAPPING__BOOK foreign key(BOOK_ID) references BOOK(ID); // If foreign key pointing to associated entity is real, // create foreign key constraint alter table BOOK_BOOK_STORE_MAPPING add constraint FK_BOOK_BOOK_STORE_MAPPING__STORE foreign key(STORE_ID) references BOOK_STORE(ID); // This constraint is very important. // Otherwise this join table expresses a many-to-many association // rather than a many-to-one association alter table BOOK_BOOK_STORE_MAPPING add constraint UQ_BOOK_BOOK_STORE_MAPPING__BOOK_ID unique(BOOK_ID); The join table has only two foreign keys, both non-null. The join table maintains the association by inserting and deleting data, never storing null data itself. The join table has no corresponding ORM entity and does not need an independent primary key. The two foreign keys combined can serve as the primary key. By default, the join table represents a many-to-many association. To degrade it to a many-to-one association, a unique constraint must be specified for the foreign key BOOK_ID pointing to the current entity. caution Unless for compatibility with existing database design, many-to-one associations are recommended to use foreign keys directly instead of join tables. Once a many-to-one association is mapped using a join table, the Jimmer association property must be nullable, because the database cannot guarantee that any entity must have corresponding data in the join table.","s":"2. Based on Join Table","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","h":"#2-based-on-join-table","p":408},{"i":415,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToMany annotation to declare many-to-many association properties. Many-to-many supports bidirectional association. For bidirectional associations, one side must be the owning side, and the other side must be the inverse side. Owning side (required): The actual mapping between the database and association properties to implement unidirectional many-to-many association. Inverse side (optional): If a unidirectional association already exists, the inverse side can be configured as a mirror of the owning side to form a bidirectional association. Let's assume there are two entity types Book and Author, and establish a bidirectional many-to-many association between them. info Different from JPA/Hibernate, the owning side and inverse side can be chosen arbitrarily. Both can be used to persist associations. The example in this article chooses: Owning side (required): Book.authors Inverse side (optional): Author.books","s":"Many To Many","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"","p":414},{"i":417,"t":"Java Kotlin Book.java @Entity public interface Book { @ManyToMany List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany val authors: List ...Omit other code... } Many-to-many associations must be implemented based on a join table, even if the @JoinTable annotation is not used in the above code, it is actually equivalent to using the annotation. If no properties are specified for @JoinTable, and even @JoinTable itself is omitted (like the previous code), Jimmer will deduce the column names corresponding to the authors property based on the naming strategy. If the default naming strategy is not overridden by the user, the deduced join table information is: Join table name: BOOK_AUTHOR_MAPPING Join table foreign key column pointing to current entity: BOOK_ID Join table foreign key column pointing to associated entity: AUTHOR_ID So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List ...Omit other code... } The join table BOOK_AUTHOR_MAPPING is defined as: create table BOOK_AUTHOR_MAPPING( BOOK_ID bigint not null, AUTHOR_ID bigint not null ); alter table AUTHOR_MAPPING add constraint PK_AUTHOR_MAPPING primary(BOOK_ID, AUTHOR_ID); // If foreign key pointing to current entity is real, // create foreign key constraint alter table BOOK_AUTHOR_MAPPING add constraint FK_BOOK_AUTHOR_MAPPING__BOOK foreign key(BOOK_ID) references BOOK(ID); // If foreign key pointing to associated entity is real, // create foreign key constraint alter table BOOK_AUTHOR_MAPPING add constraint FK_BOOK_AUTHOR_MAPPING__AUTHOR foreign key(AUTHOR_ID) references AUTHOR(ID); The join table has only two foreign keys, both non-null. The join table maintains the association by inserting and deleting data, never storing null data itself. The join table has no corresponding ORM entity and does not need an independent primary key. The two foreign keys combined can serve as the primary key. caution Note The @ManyToMany association property must be non-null. If an object requires fetching its many-to-many association properties, then for the current object that has no corresponding associated object, the value of this property is a collection of length 0 rather than null.","s":"Owning Side","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"#owning-side","p":414},{"i":419,"t":"The configuration of the inverse side is very simple, just specify that Author.books is the mirror of Book.authors. In the following code: Left: The owning side discussed in the previous section Right: The inverse side association Author.books introduced in this section, which is the mirror of Book.authors Here, @ManyToMany(mappedBy = \"store\") indicates that the current property Authors.books is the mirror of Book.authors. Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List ...Omit other code... } Java Kotlin Author.java @Entity public interface Author { // `mappedBy` indicates `Author.books` // is the mirror of `Book.authors` @ManyToMany(mappedBy = \"authors\") List books(); ...Omit other code... } Author.kt @Entity interface Author { // `mappedBy` indicates `Author.books` // is the mirror of `Book.authors` @ManyToMany(mappedBy = \"authors\") val books: List ...Omit other code... } caution Note: Once the mappedBy property of @ManyToMany is specified, @JoinTable must not be used. Like the @ManyToMany association property on the owning side, the @ManyToMany association on the inverse side must also be non-null for the same reason.","s":"Inverse Side","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"#inverse-side","p":414},{"i":421,"t":"For the many-to-many association discussed in this article, no business fields other than the two foreign keys can be defined on the join table. If you want to define more other business fields in the join table of the many-to-many association, please refer to ManyToManyView.","s":"If business fields need to be added to the join table","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"#if-business-fields-need-to-be-added-to-the-join-table","p":414},{"i":423,"t":"Through the discussion of Association Mapping, we know that association mapping requires a lot of foreign keys. There are two types of foreign keys in Jimmer: Real foreign key: There is a corresponding foreign key constraint in the database. Fake foreign key: It is a foreign key in the developer's mind, but there is no corresponding foreign key constraint in the database. info When saving data: Real foreign keys rely on the ability of relational databases themselves to ensure referential integrity. Fake foreign keys rely on additional checks inserted by the ORM in the upper layer code to ensure referential integrity. This difference is transparent to the user. The user only needs to configure the authenticity of the foreign key without modifying the business code.","s":"Real and Fake Foreign Keys","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"","p":422},{"i":425,"t":"Association property based on foreign key Java Kotlin Book.java @Entity public interface Book { @ManyToOne @JoinColumn(foreignKeyType = ForeignKeyType.REAL) BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(foreignKeyType = ForeignKeyType.REAL) val store: BookStore ...Omit other code... } Association property based on join table Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( joinColumns = {@JoinColumn(foreignKeyType = ForeignKeyType.REAL)}, inverseJoinColumns = {@JoinColumn(foreignKeyType = ForeignKeyType.REAL)} ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( joinColumns = [JoinColumn(foreignKeyType = ForeignKeyType.REAL)], inverseJoinColumns = [JoinColumn(foreignKeyType = ForeignKeyType.REAL)] ) val authors: List ...Omit other code... } info Different from previous examples: Configure JoinTable.joinColumns instead of JoinTable.joinColumnName If the foreign key has only one column and the authenticity does not need to be explicitly specified, joinColumnName is a simplified configuration. Otherwise, joinColumns should be used. Configure JoinTable.inverseJoinColumns instead of JoinTable.inverseJoinColumnName If the foreign key has only one column and the authenticity does not need to be explicitly specified, inverseJoinColumnName is a simplified configuration. Otherwise, inverseJoinColumns should be used. caution If the database dialect does not support foreign keys (e.g. org.babyfish.jimmer.sql.dialect.TiDBDialect), real foreign keys cannot be explicitly specified. This is because TiDB, as a distributed relational database, does not support foreign key constraints.","s":"Explicitly specify real foreign key","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"#explicitly-specify-real-foreign-key","p":422},{"i":427,"t":"Association property based on foreign key Java Kotlin Book.java @Entity public interface Book { @ManyToOne @Nullable @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) val store: BookStore? ...Omit other code... } Association property based on join table Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( joinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE), inverseJoinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( joinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE), inverseJoinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) ) val authors: List ...Omit other code... }","s":"Explicitly specify fake foreign key","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"#explicitly-specify-fake-foreign-key","p":422},{"i":429,"t":"To avoid explicitly specifying the authenticity of foreign keys, use @JoinColumn(foreignKeyType = ForeignKeyType.AUTO). Since ForeignKeyType.AUTO is the default configuration for the @JoinColumn annotation, an even better choice is to make no configuration at all. Therefore, the code is no different from the sample code in Association Mapping, so there is no need for sample code here. If the authenticity of the foreign key is not explicitly specified, whether the foreign key is real or fake is automatically determined by the following two steps: If the database dialect does not support foreign keys (e.g. org.babyfish.jimmer.sql.dialect.TiDBDialect), it is determined to be a fake foreign key. At this point, the judgment is completed and it returns early without executing step 2. If step 1 cannot complete the determination, check Jimmer's global configuration is-foreign-key-enabled-by-default. If this configuration is true, it is determined to be a real foreign key; otherwise, it is determined to be a fake foreign key. The default value of this configuration is true. Users can override it to false: When using SpringBoot Modify application.yml or application.properties and set jimmer.is-foreign-key-enabled-by-default to false When not using SpringBoot Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setForeignKeyEnabledByDefault(false) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setForeignKeyEnabledByDefault(false) ...Omit other configurations... }","s":"Do not explicitly specify the authenticity of foreign keys","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"#do-not-explicitly-specify-the-authenticity-of-foreign-keys","p":422},{"i":431,"t":"Unlike JPA, Jimmer does not support unidirectional one-to-many associations. One-to-many associations can only exist as mirrors of many-to-one associations. That is, one-to-many associations necessarily imply bidirectional associations. In the following code: Left: Book.store discussed in Many To One Right: BookStore.books to be discussed in this article, which is the mirror of Book.store Java Kotlin Book.java @Entity public interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") val store: BookStore ...Omit other code... } Java Kotlin BookStore.java @Entity public interface BookStore { // `mappedBy` indicates `BookStore.books` // is the mirror of `Book.store` @OneToMany(mappedBy = \"store\") @Nullable List books(); ...Omit other code... } BookStore.kt @Entity interface BookStore { // `mappedBy` indicates `BookStore.books` // is the mirror of `Book.store` @OneToMany(mappedBy = \"store\") val books: List? ...Omit other code... } caution @OneToMany associations are merely mirrors of @ManyToOne associations. @JoinColumn and @JoinTable must not be used. The @OneToMany association property must be non-null. If the parent object is queried and its one-to-many association property needs to be fetched, then for the parent object that has no corresponding child objects, the value of this property is a collection of length 0 rather than null.","s":"One To Many","u":"/jimmer-doc/docs/mapping/base/association/one-to-many","h":"","p":430},{"i":434,"t":"Before introducing IdView, we need to first introduce a concept: short associations. Before introducing short associations, let's first look at a normal association Java Kotlin Book book = bookRepository.findNullable( 1L, Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) .authors( Fetchers.AUTHOR_FETCHER .firstName() .lastName() ) ); System.out.println(book); val book = bookRepository.findNullable( 1L, newFetcher(Book::class).by { allScalarFields() store { allScalarFields() } authors { firstName() lastName() } } ); System.out.println(book); In this code: Fetches associated BookStore object via store association property of Book, expecting to get all non-associative properties of associated object Fetches associated Author objects via authors association property of Book, expecting id (implicit + mandatory), firstName and lastName of associated objects The output is: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] } Here, associated objects BookStore and Author on aggregate root Book have properties other than id, with relatively complete information. More importantly, non-id properties of course also include associated properties, so this data structure can be nested multiple levels or even recursive. This kind of association can also be called a \"long association\". info However, not all cases require such a deep data structure. In actual projects, sometimes only a very simple UI is needed, like below: Book Form Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit In this UI: Book.store is a many-to-one association, rendered as a dropdown selector Book.authors is a many-to-many association, rendered as a multiple dropdown selector Of course, if there are too many options, a dropdown list is no longer a reasonable design. In this case, improve it to a popup dialog with pagination. But these UI details are unimportant and irrelevant to the current topic. It is obvious that at this point, the user only cares about the id of the associated object, and has no interest in other properties of the associated object. That is, we want the associated object to only have the id property To allow aggregate roots to be associated with some objects that only have id, we can improve the code. Java Kotlin Book book = bookRepository.findNullable( 1L, Fetchers.BOOK_FETCHER .allScalarFields() .store() // no args means id only .authors() // no args means id only ); System.out.println(book); val book = bookRepository.findNullable( 1L, newFetcher(Book::class).by { allScalarFields() store() // no args means id only authors() // no args means id only } ); System.out.println(book); This time, we get a data structure like this: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ // Only has id property \"id\":1 }, \"authors\":[ { // Only has id property \"id\":1 }, { // Only has id property \"id\":2 } ] } note In Hibernate, this kind of object with only id property is called a proxy object. However, associated objects with only id are not as simple as just the id of the association. Let's look at the same data expressed with associated ids instead of associated objects: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"storeId\": 1, \"authorIds\":[1, 2] } It is obvious that for short association use cases, associated ids or their collections are simpler than associated objects or their collections with only id.","s":"Basic Concepts: Short Associations","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#basic-concepts-short-associations","p":432},{"i":436,"t":"Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"Book Form","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"","p":432},{"i":438,"t":"ADO.NET EF Core is Microsoft's ORM. Let's look at its design: https://learn.microsoft.com/en-us/ef/core/modeling/relationships?tabs=fluent-api%2Cfluent-api-simple-key%2Csimple-key public class Post { public int PostId { get; set; } public string Title { get; set; } public string Content { get; set; } public int BlogId { get; set; } public Blog Blog { get; set; } } It's easy to see that: Associated object: public Blog Blog { get; set; } Associated id: public int BlogId { get; set; } They coexist. Jimmer learns from this design of ADO.NET EF Core and provides the @IdView property.","s":"Microsoft's Solution","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#microsofts-solution","p":432},{"i":441,"t":"IdView properties are declared with @org.babyfish.jimmer.sql.IdView: Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface Book { ...other properties omitted... @ManyToOne @Nullable BookStore store(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) List authors(); @IdView // View of store id Long storeId(); // View of all author ids in authors collection @IdView(\"authors\") List authorIds(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Book { ...other properties omitted... @ManyToOne val store: BookStore? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) val authors: List @IdView // View of store id val storeId: Long? // View of all author ids in authors collection @IdView(\"authors\") val authorIds: List } Where: Book.storeId: View of the id of associated Book.store object. Since storeId itself ends with Id, the parameter of @IdView annotation can be omitted. Jimmer infers the original association property to be Book.store. Nullability of original association property and IdView property must be consistent. In this example, Book.store property can be null, i.e. annotated with @Nullable in Java, or returns BookStore? in Kotlin. Therefore, Book.storeId must also be nullable, i.e. returns Long instead of long in Java, or returns Long? instead of Long in Kotlin. Otherwise it would cause compile error. Book.authorIds: View of ids of all Author objects in associated Book.authors collection. authorIds itself does not end with Id, so the parameter of @IdView annotation must be specified to explicitly indicate its original association is Book.authors. This is required in this case due to irregular noun pluralization in English.","s":"Declaring View Properties","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#declaring-view-properties","p":432},{"i":443,"t":"The emphasis on the word \"view\" above is intentional. IdView properties do not have their own data, they are just views of original association properties. info IdView properties and original association properties are linked. Setting one necessarily affects the other. Setting view property affects original property: Java Kotlin // Set view property Book book = Immutables.createBook(draft -> { draft.setStoreId(10L); draft.setAuthorIds(Arrays.asList(100L, 101L)); }); // Print original property System.out.println(\"Store: \" + book.store()); System.out.println(\"Authors:\" + book.authors()); // Set view property val book = Book { storeId = 10L authorIds = listOf(100L, 101L) } // Print original property println(\"Store: $book.store}\") println(\"Authors: ${book.authors}\") Prints: Store: {\"id\":10} Authors: [{\"id\":100},{\"id\":101}] Setting original property affects view property: Java Kotlin // Set original property Book book = Immutables.createBook(draft -> { draft.applyStore(store -> { store.setId(10L).storeName(\"TURING\") }); draft.addIntoAuthors(author -> { author.setId(101L); author.setFirstName(\"Fabrice\"); author.setLastName(\"Marguerie\"); }); draft.addIntoAuthors(author -> { author.setId(101L); author.setFirstName(\"Steve\"); author.setLastName(\"Eichert\"); }); }); // Print view property System.out.println(\"StoreId: \" + book.storeId()); System.out.println(\"AuthorIds:\" + book.authorIds()); // Set original property val book = Book { store { id = 10L name = \"TURING\" } authors().addBy { id = 100L; firstName = \"Fabrice\" lastName = \"Marguerie\" } authors().addBy { id = 101L firstName = \"Steve\" lastName = \"Eichert\" } } // Print view property println(\"Store: $book.storeId}\") println(\"Authors: ${book.authorIds}\") Prints: StoreId: 10 AuthorIds: [100, 101] tip This shows that view properties and original properties are highly unified. Jimmer is still a ORM framework that is core-associated-object-oriented. View properties are just syntactic sugar. Except for the impact on ObjectFetcher to be explained below, view properties do not affect ORM and core logic at all.","s":"Essence of View Properties","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#essence-of-view-properties","p":432},{"i":445,"t":"Java Kotlin Book book = bookRepository.findNullable( 1L, Fetchers.BOOK_FETCHER .allScalarFields() .storeId() .authorIds() ); System.out.println(book); val book = bookRepository.findNullable( 1L, newFetcher(Book::class).by { allScalarFields() storeId() authorIds() } ); System.out.println(book); Prints: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"storeId\": 1, \"authorIds\":[1, 2] } tip For Jimmer dynamic entities, original association properties and view properties are absolutely consistent. Either both can be accessed, or both are missing. Whether choosing to fetch the original association property or choosing to fetch the IdView view property does not affect the underlying execution logic of Jimmer, including the ultimately generated SQL. The only difference brought by different choices is that the Jackson visibility flag of original association properties and view properties are different. That is, properties fetched directly will be serialized by Jackson, while properties not fetched directly will be ignored. Here is the English translation of the file, with the code indentation preserved:","s":"Fetching IdView Properties","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#fetching-idview-properties","p":432},{"i":447,"t":"caution Without the assistance of DTOs, hope that the entity itself can express associated ids, is the only scenario where it is appropriate to use @IdView. Other features make no assumptions about whether an association property has a corresponding @IdView property. Using associated IDs in the SQL DSL Even if an entity's one-to-one or many-to-one association property does not have a corresponding @IdView property, you can still use associated id expressions in the SQL DSL, for example: Java Kotlin where(table.storeId().eq(2L)); where(table.storeId eq 2L) Of course, if you are not satisfied with the auto-generated name for the associated id (e.g., storeId here), you can provide an @IdView property to change its name. Using associated ids in the DTO language The DTO language does not require @IdView properties at all. Even if an entity's associated property already has a corresponding @IdView property, it is not recommended to use it in the DTO language, as this is a fragile assumption. Once that @IdView property is removed, the DTO code cannot be correctly compiled until it is synchronized with the change. The DTO language should directly use the association properties, for example: export yourpackage.Book -> package yourpackage.dto input BookInput { allScalarFields() id(store) // as storeId id(authors) as authorIds } specification BookSpecification { like/i(name) associatedIdIn(store) as storeIds associatedIdNotIn(store) as excludedStoreIds }","s":"Do Not Abuse","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#do-not-abuse","p":432},{"i":449,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.OneToOne annotation to declare one-to-one association properties. One-to-one supports bidirectional association. For bidirectional associations, one side must be the owning side and the other side must be the inverse side: Owning side (required): The actual mapping between the database and association properties to implement unidirectional one-to-one association. Inverse side (optional): If a unidirectional association already exists, the inverse side can be configured as a mirror of the owning side to form a bidirectional association. Let's assume there are two entity types Customer and Address, and establish a bidirectional one-to-one association between them. info Unlike JPA/Hibernate, the owning side and inverse side can be chosen arbitrarily. Both can be used to persist associations. The example in this article chooses: Owning side (required): Customer.address Inverse side (optional): Address.customer","s":"One To One","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"","p":448},{"i":451,"t":"There are two ways to implement a one-to-one association: based on foreign key and based on join table.","s":"Owning Side","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#owning-side","p":448},{"i":453,"t":"Java Kotlin Customer.java @Entity public interface Customer { @OneToOne Address address(); ...Omit other code... } Customer.kt @Entity interface Customer { @OneToOne val address: Address ...Omit other code... } Here @JoinColumn is not used together to explicitly specify the foreign key column name. Jimmer will deduce the column name corresponding to the address property based on the naming strategy. If the default naming strategy is not overridden by the user, the foreign key column name of the address property is ADDRESS_ID. So the previous code is equivalent to: Therefore, the above code is equivalent to the following: Java Kotlin Customer.java @Entity public interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") Address address(); ...Omit other code... } Customer.kt @Entity interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") val address: Address ...Omit other code... } The foreign key can be real or fake. Fake foreign keys are discussed in subsequent documents. Here we assume the foreign key is real, so the corresponding constraint in the database is: // If foreign key pointing to associated entity is real, create foreign key constraint alter table CUSTOMER add constraint FK_CUSTOMER__ADDRESS foreign key(ADDRESS_ID) references ADDRESS(ID);","s":"1. Based on Foreign Key","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#1-based-on-foreign-key","p":448},{"i":455,"t":"Java Kotlin Customer.java @Entity public interface Customer { @Nullable @OneToOne @JoinTable Address address(); ... } Customer.kt @Entity interface Customer { @OneToOne @JoinTable val address: Address? ... } Here, no properties are specified for @JoinTable. Jimmer will deduce the column names corresponding to the address property based on the naming strategy. If the default naming strategy is not overridden by the user, the deduced join table information is: Join table name: CUSTOMER_ADDRESS_MAPPING Join table foreign key column pointing to current entity: CUSTOMER_ID Join table foreign key column pointing to associated entity: ADDRESS_ID So the previous code is equivalent to: Java Kotlin Customer.java @Entity public interface Customer { @Nullable @OneToOne @JoinTable( name = \"CUSTOMER_ADDRESS_MAPPING\", joinColumnName = \"CUSTOMER_ID\", inverseJoinColumnName = \"ADDRESS_ID\" ) Address address(); ... } Customer.kt @Entity interface Customer { @OneToOne @JoinTable( name = \"CUSTOMER_ADDRESS_MAPPING\", joinColumnName = \"CUSTOMER_ID\", inverseJoinColumnName = \"ADDRESS_ID\" ) val address: Address? ... } The join table CUSTOMER_ADDRESS_MAPPING is defined as follows: create table CUSTOMER_ADDRESS_MAPPING( CUSTOMER_ID bigint not null, ADDRESS_ID bigint not null ); alter table ADDRESS_MAPPING add constraint PK_ADDRESS_MAPPING primary(CUSTOMER_ID, ADDRESS_ID); // If foreign key pointing to current entity is real, // create foreign key constraint alter table CUSTOMER_ADDRESS_MAPPING add constraint FK_CUSTOMER_ADDRESS_MAPPING__CUSTOMER foreign key(CUSTOMER_ID) references CUSTOMER(ID); // If foreign key pointing to associated entity is real, // create foreign key constraint alter table CUSTOMER_ADDRESS_MAPPING add constraint FK_CUSTOMER_ADDRESS_MAPPING__ADDRESS foreign key(ADDRESS_ID) references ADDRESS(ID); // These two constraints are very important. // Otherwise this join table expresses a many-to-many association // rather than a one-to-one association alter table CUSTOMER_ADDRESS_MAPPING add constraint UQ_CUSTOMER_ADDRESS_MAPPING__CUSTOMER_ID unique(CUSTOMER_ID); alter table CUSTOMER_ADDRESS_MAPPING add constraint UQ_CUSTOMER_ADDRESS_MAPPING__ADDRESS_ID unique(ADDRESS_ID); The join table has only two foreign keys, both non-null. The join table maintains the association by inserting and deleting data, never storing null data itself. The join table has no corresponding ORM entity and does not need an independent primary key. The two foreign keys combined can serve as the primary key. By default, the join table represents a many-to-many association. To degrade it to a one-to-one association, a unique constraint must be specified for each foreign key of the join table. caution Unless for compatibility with existing database design, one-to-one associations are recommended to directly use foreign keys instead of join tables. Once a one-to-one association is mapped using a join table, the Jimmer association property must be nullable, because the database cannot guarantee that any entity must have corresponding data in the join table.","s":"2. Based on Join Table","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#2-based-on-join-table","p":448},{"i":457,"t":"The configuration of the inverse side is very simple: just specify that Address.customer is the mirror of Customer.address. In the following code: Left: The owning side discussed in the previous section Right: The inverse side association Address.customer introduced in this section, which is the mirror of Customer.address Here, @OneToOne(mappedBy = \"address\") indicates that the current property Address.customer is the mirror of Customer.address. Java Kotlin Customer.java @Entity public interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") Address address(); ...Omit other code... } Customer.kt @Entity interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") val address: Address ...Omit other code... } Java Kotlin Address.java @Entity public interface Address { // `mappedBy` indicates `Address.customer` // is the mirror of `Customer.address` @OneToOne(mappedBy = \"address\") @Nullable Customer customer(); ...Omit other code... } Address.kt @Entity interface Address { // `mappedBy` indicates `Address.customer` // is the mirror of `Customer.address` @OneToOne(mappedBy = \"address\") val customer: Customer? ...Omit other code... } caution Once the mappedBy property of @OneToOne is specified, annotations like @JoinColumn and @JoinTable must not be used. The one-to-one association property as the inverse side must be nullable.","s":"Inverse Side","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#inverse-side","p":448},{"i":460,"t":"In Basic Mapping/Associative Mapping, we learned about the classic associative mappings in ORM, including one-to-one, many-to-one, one-to-many and many-to-many. However, there is one scenario that makes the choice of mapping mode very tangled. To show this scenario, let's start with a familiar scenario.","s":"Limitations of classic ORM associations","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#limitations-of-classic-orm-associations","p":458},{"i":462,"t":"Let's look at a piece of DDL create table book( ...omit... )engine=innodb;; create table author( ...omit... ) engine=innodb; create table book_author_mapping( book_id bigint unsigned not null, author_id bigint unsigned not null ) engine=innodb; alter table book_author_mapping add constraint pk_book_author_mapping primary key(book_id, author_id) ; alter table book_author_mapping add constraint fk_book_author_mapping__book foreign key(book_id) references book(id) on delete cascade ; alter table book_author_mapping add constraint fk_book_author_mapping__author foreign key(author_id) references author(id) on delete cascade ; In this piece of DDL, book_author_mapping table is very special, it only has two foreign keys, one pointing to book table, and one pointing to author table. This kind of subtable with only two foreign keys is used to express the many-to-many association between two parent tables. ORM's many-to-many mapping will hide the intermediate table, that is, the intermediate table does not correspond to a Java/Kotlin entity type. Therefore, the intermediate table does not need an independent primary key, but directly uses the two foreign keys as a combined primary key. info In addition to the two associative foreign keys, the intermediate table must not have any other fields, which is a limitation of many-to-many associations in ORM. The corresponding many-to-many association in ORM is as follows: Owning side: Book.authors Java Kotlin Book.java @Entity public interface Book { @ManyToMany List authors(); ...other code omitted... } Book.kt @Entity interface Book { @ManyToMany val authors: List ...other code omitted... } Inverse side (optional): Author.books Java Kotlin Author.java @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ...other code omitted... } Author.kt @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...other code omitted... }","s":"Undisputed many-to-many association","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#undisputed-many-to-many-association","p":458},{"i":464,"t":"Let's look at the second scenario, first, look at a piece of DDL create table order_( ...omit... ) engine=innodb; create table product( ...omit... ) engine=innodb; create table order_item( id bigint unsigned not null auto_increment primary key, order_id bigint unsigned not null, product_id bigint unsigned not null, quantity int not null, unit_price numeric(10, 2) not null ) engine=innodb; alter table order_item add constraint business_key_order_item unique(order_id, product_id) ; alter table order_item add constraint fk_order_item__order foreign key(order_id) references order_(id) ; alter table order_item add constraint fk_order_item__product foreign key(product_id) references product(id) ; This is a classic order - order item - product association. Among them, order-item looks a bit like the intermediate table of many-to-many, because it has two foreign keys: order_id pointing to the order_ table and product_id pointing to the product table. However, order-item is not an intermediate table, because it has other business fields, quantity representing quantity of goods, and unit_price representing a snapshot of the price of goods at the time of order. Fortunately, for the classic order - order item - product association, it is more intuitive to think of order_item as an independent entity, with two many-to-one associations pointing to order_ and product respectively; Rather than viewing order-item as a join table and thinking there is a many-to-many relationship between order_ and product. It is precisely because order_item is regarded as an independent entity that order_item uses an independent primary key. We can map these three tables in ORM using two many-to-one associations OrderItem.order and OrderItem.product Java Kotlin OrderItem.java @Entity public interface OrderItem { @ManyToOne Order order(); @ManyToOne Product product(); int quantity(); BigDecimal unitPrice(); ...other code omitted... } OrderItem.kt @Entity interface OrderItem { @ManyToOne val order: Order @ManyToOne val product: Product val quantity: Int val unitPrice: BigDecimal ...other code omitted... } Order.items In such systems, it is often necessary to get the detail list according to the order, so we define a one-to-many property Order.items as a mirror of OrderItem.order. Java Kotlin Order.java @Entity @Table(name = \"ORDER_\") public interface Order { @OneToMany(mappedBy = \"order\") List items(); ...other code omitted... } Order.kt @Entity @Table(name = \"ORDER_\") interface Order { @OneToMany(mappedBy = \"order\") val items: List ...other code omitted... } Do not provide Product.items In such systems, it is rarely necessary to get the detail list based on the product (if starting the analysis from the product side, it is usually a complex query rather than a simple association), so a one-way OrderItem.product association is sufficient. So there is no need to show the code for the Product entity.","s":"Undisputed double many-to-one association","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#undisputed-double-many-to-one-association","p":458},{"i":466,"t":"In the previous text, we showed two business scenarios Scenario 1: The intermediate table book_author_mapping is very clean, with only two foreign key fields, and is naturally mapped to a many-to-many association Scenario 2: order_item looks like an intermediate table but is not an intermediate table, because in addition to the two foreign keys it also needs to have other business fields. Fortunately, people will choose to treat OrderItem as an independent entity and use two many-to-one associations to string the three entity types together. Next, let's look at scenario 3, first look at the DDL: create table student( ...omit... )engine=innodb;; create table course( ...omit... ) engine=innodb; create table learning_link ( id bigint unsigned not null auto_increment primary key, student_id bigint unsigned not null, course_id bigint unsigned not null, score int ) engine=innodb; alter table learning_link add constraint pk_student_course_mapping primary key(student_id, course_id) ; alter table learning_link add constraint fk_student_course_mapping__student foreign key(student_id) references student(id) on delete cascade ; alter table learning_link add constraint fk_student_course_mapping__course foreign key(course_id) references course(id) on delete cascade ; This piece of DDL represents the elective course system in schools. There is a many-to-many relationship between students and elective courses. For students, it is of course very important to know which courses they have chosen For schools, it is also very important to know which students have chosen each course, because teacher resources and teaching venues need to be arranged based on this information That is, for the student entity and the course entity, associating with each other and querying each other is an important and high frequency operation. Therefore, abstracting bidirectional many-to-many associations between student and course is a very good choice. Unfortunately, the elective relationship table learning_link has a score field that can be null, null indicating that the exam has not yet taken place, non-null indicating the score after the exam. Because of the existence of this field, the intermediate table is no longer clean, and cannot be simply mapped to the classic ORM many-to-many association. That is, this is not a simple scenario 1. Of course, we can handle this problem using the method of scenario 2, treating learning_link as an independent entity, and using two many-to-one associations to string the three entity types together. However, for a large part of the upper layer business, what they really care about is only the mutual association between student and course, and they don't care about the score field of the learning_link table. (That is, the non-foreign key business field learning_link.score of the intermediate table is far less important than the relevant fields in scenario 2). In this case, scenario 2's solution will bring a higher cognitive burden, and scenario 1's way of thinking is obviously simpler. info This scenario is actually the most tangled scenario in classic ORM, which cannot be simply mapped to many-to-many associations, while hoping that some upper layer business can adopt the many-to-many mentality to simplify the problem. @ManyToManyView is a powerful tool designed for such scenarios.","s":"The controversial, tangled scenario","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#the-controversial-tangled-scenario","p":458},{"i":468,"t":"For the discussed scenario 3 above, Jimmer gave a two-step solution. Basic association mapping: First, treat learning_link as an independent entity according to scenario 2, and provide two many-to-one associations pointing to student and course respectively; Conversely, student and course also use one-to-many associations to reference learning_link. That is, use two bidirectional one-to-many associations to string the three entity types together. Use @ManyToManyView: Then, on the basis of the first step, use @ManyToManyView to quickly simulate the effect of scenario 1.","s":"Getting Started with ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#getting-started-with-manytomanyview","p":458},{"i":470,"t":"LearningLink.student and LearningLink.course Java Kotlin LearningLink.java @Entity public interface LearningLink { @ManyToOne Student student(); ① @ManyToOne Course course(); ② Integer score(); ...other code omitted... } LearningLink.kt @Entity interface LearningLink { @ManyToOne val student: Student ① @ManyToOne val course: Course ② val score: Int? ...other code omitted... } Where ① and ② will be referenced by subsequent code Student.learningLinks Java Kotlin Student.java @Entity public interface Student { @OneToMany(mappedBy = \"student\") List learningLinks(); ③ ...other code omitted... } Student.kt @Entity interface Student { @OneToMany(mappedBy = \"student\") val learningLinks: List ③ ...other code omitted... } Where ③ will be referenced by subsequent code Course.learningLinks Java Kotlin Course.java @Entity public interface Course { @OneToMany(mappedBy = \"course\") List learningLinks(); ④ ...other code omitted... } Course.kt @Entity interface Course { @OneToMany(mappedBy = \"course\") val learningLinks: List ④ ...other code omitted... } Where ④ will be referenced by subsequent code","s":"Basic relationship mapping","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#basic-relationship-mapping","p":458},{"i":472,"t":"Simulate many-to-many association: Student.courses Java Kotlin Student.java @Entity public interface Student { @ManyToManyView( prop = \"learningLinks\", ❶ -> ③ deeperProp = \"course\" ❷ -> ② ) List courses(); // The one-to-many association `learningLinks` // has been declared in step 1 @OneToMany(mappedBy = \"student\") List learningLinks(); ③ ...other code omitted... } Student.kt @Entity interface Student { @ManyToManyView( prop = \"learningLinks\", ❶ -> ③ deeperProp = \"course\" ❷ -> ② ) val courses: List // The one-to-many association `learningLinks` // has been declared in step 1 @OneToMany(mappedBy = \"student\") val learningLinks: List ③ ...other code omitted... } The current property Student.courses can be obtained in two steps: ❶ prop = \"learningLinks\" First, get all LearningLink objects through another property of the current entity Student.learningLinks ③ ❷ deeperProp = \"course\" For each LearningLink object obtained in the previous step, Course can be further obtained through the LearningLink.course property ② tip Since the LearningLink entity has only one many-to-one association pointing to the Course entity, there is no ambiguity, so deeperProp = \"course\" can be omitted here Simulate many-to-many association: Course.students Java Kotlin Course.java @Entity public interface Course { @ManyToManyView( prop = \"learningLinks\", ❶ -> ④ deeperProp = \"student\" ❷ -> ① ) List students(); // The one-to-many association `learningLinks` has been declared in step 1 @OneToMany(mappedBy = \"course\") List learningLinks(); ④ ...other code omitted... } Course.kt @Entity interface Course { @ManyToManyView( prop = \"learningLinks\", ❶ -> ④ deeperProp = \"student\" ❷ -> ① ) val students: List // The one-to-many association `learningLinks` has been declared in step 1 @OneToMany(mappedBy = \"course\") val learningLinks: List ④ ...other code omitted... } The current property Course.students can be obtained in two steps: ❶ prop = \"learningLinks\" First, get all LearningLink objects through another property of the current entity Course.learningLinks ④ ❷ deeperProp = \"student\" For each LearningLink object obtained in the previous step, Student can be further obtained through the LearningLink.student property ① tip Since the LearningLink entity has only one many-to-one association pointing to the Student entity, there is no ambiguity, so deeperProp = \"student\" can be omitted here","s":"Using @ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#using-manytomanyview","p":458},{"i":474,"t":"The property declared by @ManyToManyView does not maintain its own data, it is only a view of the original property, which proxies and wraps the collection returned by the original property. Take the Java example in this article Student side as an example (the Course side is the same). Original association property: List learningLinks(); View association property: List courses(); You can understand the ManyToManyView view property with this pseudocode: @Override public List courses() { return new ListProxy<>( this.learningLinks(), LearningLink::course ); } The view association property returns a proxy collection that wraps the collection of the original property and transforms the elements of the original collection. It is obvious that the two are essentially the same and share the same data. When constructing entity objects, only the original property can be set, not the view property. This is different from @IdView. For @IdView, both the original property and the view property can be set. Whether it is the original property or the view property, the preprocessor will generate code to match them, so both can be used in object fetchers and strongly typed SQL DSL.","s":"The essence of @ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#the-essence-of-manytomanyview","p":458},{"i":476,"t":"In addition to boolean, number, string, UUID, date, and enumeration, scalar properties also support other types, including: Array types JSON types Custom types info Enum types are not discussed in this article, please refer to Enum Mapping","s":"More Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"","p":475},{"i":478,"t":"warning To use array types, the underlying database must support array types Java Kotlin @Entity public interface Book { @Id long id(); String[] tags(); } @Entity interface Book { @Id val id: Long val tags: Array } For Postgres, you need to specify the data element type in SQL, for example: Java Kotlin @Entity public interface Book { @Id long id(); @Column(sqlElementType = \"text\") String[] tags(); } @Entity interface Book { @Id val id: Long @Column(sqlElementType = \"text\") val tags: Array }","s":"Array Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"#array-types","p":475},{"i":480,"t":"You can use Jackson to support scalar properties of any type, whether it's a custom Java/Kotlin type, a collection type, or even a mix of the two. Just use the @org.babyfish.jimmer.sql.Serialized annotation, and you can use the JSON type. Here, the usage is demonstrated using a collection type as an example: Java Kotlin @Entity public interface Book { @Id long id(); @Serialized Map>> data(); } @Entity interface Book { @Id val id: Long @Serialized val data: Map>> } So what SQL type does the JSON type correspond to? If the database supports the JSON or JSONB type, use that type Otherwise, please use the string type For Postgres, it supports operations on the internal structure of JSON, please see JSON Operations in Postgres. How should Jimmer implement such operations? Jimmer's SQL DSL can mix in Native SQL expressions, please see Native Expressions, this article will not repeat it. Note: caution JSON Operations in Postgres use ?, which happens to be the parameter for JDBC, please use ?? instead.","s":"JSON Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"#json-types","p":475},{"i":482,"t":"If the JSON type still cannot meet your requirements (e.g., you expect to map some Postgres-specific types), you can use ScalarProvider to customize types. Please refer to ScalarProvider, this article will not repeat it.","s":"Custom Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"#custom-types","p":475},{"i":484,"t":"Jimmer handles the issue of whether entity object properties can be null in a very strict way. Even for Java developers, it requires thinking about whether each property can be null in the same way as Kotlin developers. caution Explicitly stating whether each property of the entity object allows null is very important for Jimmer and affects many features.","s":"Nullity","u":"/jimmer-doc/docs/mapping/base/nullity","h":"","p":483},{"i":487,"t":"Kotlin supports null safety. Declaring entity properties as T for non-null and T? for nullable according to Kotlin's own way.","s":"Kotlin","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#kotlin","p":483},{"i":489,"t":"Whether a property is null in Java is determined by the following rules: If the property type is boolean, char, byte, short, int, long, float or double, then it is non-null. If the property type is Boolean, Character, Byte, Short, Integer, Long, Float or Double, then it is nullable. Otherwise If the property is decorated by any annotation simply named Nullable or Null, then it is nullable. Otherwise, the default is non-null. note It is recommended to use org.jetbrains.annotations.Nullable, because Although recognizable annotations are not restricted, if an annotation not included by default in the Jimmer annotation processor is used, its dependency needs to be added to the annotation processor, which is troublesome after all. org.jetbrains.annotations.Nullable is supported by Intellij.","s":"Java","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#java","p":483},{"i":491,"t":"info A series of concepts not explained yet will appear here. They will all be explained in subsequent documents. Here is just a simple list of precautions. Please ignore these terms for now. This document does not provide related examples either. Come back and check after you understand all subsequent concepts. The @Id property must be non-null. Very different from JPA/Hibernate. JPA/Hibernate recommends declaring the id property as a nullable type, e.g. Long instead of long in Java, so that the absence of id and the need for automatic allocation can be expressed when saving data. Jimmer must declare the id property as a non-null type, e.g. long instead of Long in Java. Jimmer relies on the dynamism of the entity objects themselves to express the absence of the id property. One-to-many and many-to-many properties must be non-null. One-to-many and many-to-many properties are represented by collections of length 0 instead of null when there is no data. One-to-one and many-to-one properties must be nullable when any of the following conditions is met: Mapping based on join table, rather than foreign key Mapping based on pseudo foreign key, rather than real foreign key info A \"pseudo foreign key\" refers to a foreign key in the developer's mind, but there is no corresponding foreign key constraint in the database. Remote association As the mirror side of @OneToOne association If the associated entity has global filters applied, then for one-to-one/many-to-one associations must be nullable even if they are directly based on foreign keys, unless all of the following conditions are met: All global filters applied to the associated entity implement the AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter interface. All global filters applied to the associated entity are also applied to the current entity.","s":"Precautions","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#precautions","p":483},{"i":493,"t":"As mentioned before, due to some query scenarios, one-to-one and many-to-one properties based on foreign keys must be declared as nullable. However, when saving data, developers may not expect users to modify the foreign key fields in the database to null. In this case, inputNotNull of @OneToOne or @ManyToOne can be set to true, for example: @OneToOne(inputNotNull = true) @ManyToOne(inputNotNull = true) If inputNotNull is configured for an associated property, it will be given priority consideration in database validation to verify that the foreign key field in the database cannot be null.","s":"inputNotNull","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#inputnotnull","p":483},{"i":495,"t":"In this section, we will introduce all the capabilities in Jimmer related to modifying the database. There are two groundbreaking capabilities: Save Command One statement to save complex data of arbitrary shape, find DIFF to change database, like React/Vue. Triggers Awareness of data changes whether via Jimmer's own capabilities or integrating with existing CDC solutions. This enables automatic Caching invalidation.","s":"Modification","u":"/jimmer-doc/docs/mutation/","h":"","p":494},{"i":498,"t":"The @Entity annotation is used to decorate immutable interfaces to represent ORM entities. Java Kotlin Book.java @Entity public interface Book { ...Omit other code... } Book.kt @Entity interface Book { ...Omit other code... } info Why are entity types interfaces instead of classes? Jimmer entities have dynamic shapes and immutability, which are not simple POJOs with intricate internal workings that cannot be accomplished manually or with lombok assistance. So Jimmer lets developers write interfaces that are implemented at compile time by preprocessors (AnnotationProcessor for Java, KSP for Kotlin).","s":"@Entity","u":"/jimmer-doc/docs/mapping/base/basic","h":"#entity","p":496},{"i":500,"t":"The @Table annotation specifies the table name for the entity. If @Table annotation is not used, e.g. Java Kotlin BookStore.java @Entity public interface BookStore { ...Omit other code... } BookStore.kt @Entity interface BookStore { ...Omit other code... } Jimmer will deduce the table name corresponding to the BookStore interface based on the naming strategy. If the default naming strategy is not overridden by the user, the table name for interface BookStore is BOOK_STORE. So the previous code is equivalent to: Java Kotlin BookStore.java @Entity @Table(name = \"BOOK_STORE\") public interface BookStore { ...Omit other code... } BookStore.kt @Entity @Table(name = \"BOOK_STORE\") interface BookStore { ...Omit other code... }","s":"@Table","u":"/jimmer-doc/docs/mapping/base/basic","h":"#table","p":496},{"i":502,"t":"The @Column annotation specifies the database column for ordinary non-associative properties. If @Column annotation is not used, e.g. Java Kotlin Author.java @Entity public interface BookStore { String firstName(); ...Omit other code... } Author.kt @Entity interface Author { val firstName: String ...Omit other code... } Jimmer will deduce the column name corresponding to the firstName property based on the naming strategy. If the default naming strategy is not overridden by the user, the column name for property firstName is FIRST_NAME. So the previous code is equivalent to: Java Kotlin Author.java @Entity public interface BookStore { @Column(name = \"FIRST_NAME\") String firstName(); ...Omit other code... } Author.kt @Entity interface Author { @Column(name = \"FIRST_NAME\") val firstName: String ...Omit other code... } caution @Column is only used to explicitly specify column names for non-associative properties. For foreign key column names of many-to-one or one-to-one association properties, they must be specified through @JoinColumn. See Association Mapping for more.","s":"@Column","u":"/jimmer-doc/docs/mapping/base/basic","h":"#column","p":496},{"i":504,"t":"Declare a property as the id property, as follows Java Kotlin Book.java @Entity public interface Book { @Id long id(); } Book.kt @Entity interface Book { @Id val id: Long } caution The id field must be non-null (for Java, long is used here instead of Long) Unlike JPA, which encourages declaring the id as a nullable type, Jimmer does not use this method to express not specifying the id during data insertion. The dynamism of Jimmer objects themselves can easily express this problem. See Nullity for details.","s":"@Id","u":"/jimmer-doc/docs/mapping/base/basic","h":"#id","p":496},{"i":506,"t":"In the previous example, the primary key property decorated with @Id is a business field that must be specified when inserting data. However, more often, we expect that the primary key property itself has no business meaning, so that it can be unspecified when inserting data and automatically generated instead. The automatic id generation strategies are: Database autoincrement Database sequence UUID Snowflake ID @GeneratedValue works with @Id to specify auto growth strategy for Id.","s":"@GeneratedValue","u":"/jimmer-doc/docs/mapping/base/basic","h":"#generatedvalue","p":496},{"i":508,"t":"Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long }","s":"Database autoincrement","u":"/jimmer-doc/docs/mapping/base/basic","h":"#database-autoincrement","p":496},{"i":510,"t":"Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) val id: Long } Here, the sequence name in the database is not specified through the sequenceName of @GeneratorValue. Jimmer will deduce the sequence name based on the naming strategy. If the default naming strategy is not overridden by the user, the sequence name here is BOOK_ID_SEQ. So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue( strategy = GenerationType.SEQUENCE, sequenceName = \"BOOK_ID_SEQ\" ) long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue( strategy = GenerationType.SEQUENCE, sequenceName = \"BOOK_ID_SEQ\" ) val id: Long }","s":"Database sequence","u":"/jimmer-doc/docs/mapping/base/basic","h":"#database-sequence","p":496},{"i":512,"t":"Setting the generatorType property of @GeneratedValue to org.babyfish.jimmer.sql.meta.UUIDIdGenerator can be used to randomly generate UUIDs Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(generatorType = UUIDIdGenerator.class) UUID id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(generatorType = UUIDIdGenerator::class) val id: UUID }","s":"UUID","u":"/jimmer-doc/docs/mapping/base/basic","h":"#uuid","p":496},{"i":514,"t":"When the above Id growth strategies cannot meet the requirements, a custom Id generation strategy can be defined. Jimmer provides an UserIdGenerator interface UserIdGenerator.java package org.babyfish.jimmer.sql.meta; public interface UserIdGenerator extends IdGenerator { T generate(Class entityType); } Users can implement this interface to implement any Id generation algorithm, including snowflake ID. MyGenerator.java package com.mycompany.myproject.common; public class MyIdGenerator implements UserIdGenerator { @Override public Long generate(Class entityType) { return ...Omit custom id generation logic... } } Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(generateType = MyIdGenerator.class) Long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(generateType = MyIdGenerator::class) val id: Long } caution The user-implemented Id generation class MyIdGenerator itself does not have generic parameters, but generic parameters must be specified for the super interface UserIdGenerator. The type of the decorated Id property must be consistent with this generic parameter, otherwise an exception will be thrown.","s":"Custom IdGenerator","u":"/jimmer-doc/docs/mapping/base/basic","h":"#custom-idgenerator","p":496},{"i":517,"t":"In previous chapters, we have introduced simple entity mapping and association mapping (one-to-one, many-to-one, one-to-many, many-to-many). From these contents, we understand that @Table(name = \"...\") can be used to explicitly specify the table name for an entity. @GeneratedValue(..., sequenceName = \"...\") can be used to explicitly specify the sequence name required to generate the id (if using sequence generation strategy). @Column(name = \"...\") can be used to explicitly specify the column name for ordinary columns. @JoinColumn(name = \"...\") can be used to explicitly specify the column name for foreign key columns. @JoinTable(name = \"...\") can be used to explicitly specify the join table name and all its column names for association properties based on join tables. However, in order to improve development efficiency, it is impossible to use these annotations too much. In most cases, the default name deduction behavior should work, and these annotations should only be used in code in a few cases. For a given class or property, how to automatically determine the identifier name in the database if the user does not use such annotations is called the naming strategy, which is a customizable Java interface: package org.babyfish.jimmer.sql.meta; import org.babyfish.jimmer.meta.ImmutableProp; import org.babyfish.jimmer.meta.ImmutableType; public interface DatabaseNamingStrategy { String tableName(ImmutableType type); String sequenceName(ImmutableType type); String columnName(ImmutableProp prop); String foreignKeyColumnName(ImmutableProp prop); String middleTableName(ImmutableProp prop); String middleTableBackRefColumnName(ImmutableProp prop); String middleTableTargetRefColumnName(ImmutableProp prop); } Among them, ImmutableType and ImmutableProp are the types used by Jimmer metadata and can be intuitively understood by analogy with Class and Field in JVM reflection API. The role of each method is: tableName: Given an entity type, what is its table name? sequenceName: Given an entity type whose ID growth strategy is sequence, what is its sequence name? columnName: Given a non-associative property, what is its column name? foreignKeyColumnName: Given an association property based on foreign key, what is its column name? middleTableName: Given an association property based on join table, what is its join table name? middleTableBackRefColumnName: Given an association property based on join table, what is the column name of the foreign key pointing to the current entity in the join table? middleTableTargetRefColumnName: Given an association property based on join table, what is the column name of the foreign key pointing to the associated entity in the join table?","s":"Naming Strategy Interface","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#naming-strategy-interface","p":515},{"i":519,"t":"In most cases, developers do not need to implement this interface directly. Jimmer's built-in org.babyfish.jimmer.sql.runtime.DefaultDatabaseNamingStrategy class already implements this interface. The DefaultDatabaseNamingStrategy class has two static fields: UPPER_CASE: The generated database identifier names are all uppercase. info If the user does not do any configuration, this is the default naming strategy for Jimmer. LOWER_CASE: The generated database identifier names are all lowercase. Some databases, such as MySQL, can be configured for case sensitivity. So it is very likely that you will be handling a MySQL database that is configured to be case sensitive with most table and column names in lowercase. In this case, you need to override the default strategy with this strategy. tip Even if neither UPPER_CASE nor LOWER_CASE meets your requirements and you need to implement your own strategy, you can also consider inheriting this default strategy instead of implementing from scratch. Before introducing the behavior of the default strategy, let's first introduce a character transformation rule: snake case. The so-called snake case refers to converting alternating case text into underscore-concatenated text, e.g. the snake case of class name BookStore is BOOK_STORE, and the snake case of property name firstName is FIRST_NAME. Considering case issues, we define two functions u_snake and l_snake with the following behaviors: u_snake(\"BookStore\") -> \"BOOK_STORE\" l_snake(\"BookStore\") -> \"book_store\" u_snake(\"firstName\") -> \"FIRST_NAME\" l_snake(\"firstName\") -> \"first_name\" With the conventions of u_snake and l_snake, it is easy to describe the behavior of DefaultDatabaseNamingStrategy: note ClassName below refers to the SimpleName of the Java class, not the QualifiedName.","s":"Default Naming Strategy","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#default-naming-strategy","p":515},{"i":521,"t":"tableName Rule: u_snake(ClassName) Example: BookStore -> BOOK_STORE sequenceName Rule: u_snake(ClassName)_ID_SEQ Example: BookStore -> BOOK_STORE_ID_SEQ columnName Rule: u_snake(ClassName) Example: firstName -> FIRST_NAME foreignKeyColumnName Rule: u_snake(ClassName)_ID Example: parentNode -> PARENT_NODE_ID middleTableName Rule: u_snake(SourceClassName)_u_snake(TargetClassName)_MAPPING Example: Book::authors -> BOOK_AUTHOR_MAPPING middleTableBackRefColumnName Rule: u_snake(SourceClassName)_ID Example: Book::authors -> BOOK_ID middleTableTargetRefColumnName Rule: u_snake(TargetClassName)_ID Example: Book::authors -> AUTHOR_ID","s":"UPPER_CASE","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#upper_case","p":515},{"i":523,"t":"tableName Rule: l_snake(ClassName) Example: BookStore -> book_store sequenceName Rule: l_snake(ClassName)_id_seq Example: BookStore -> book_store_id_seq columnName Rule: l_snake(ClassName) Example: firstName -> first_name foreignKeyColumnName Rule: l_snake(ClassName)_id Example: parentNode -> parent_node_id middleTableName Rule: l_snake(SourceClassName)_l_snake(TargetClassName)_mapping Example: Book::authors -> book_author_mapping middleTableBackRefColumnName Rule: l_snake(SourceClassName)_id Example: Book::authors -> book_id middleTableTargetRefColumnName Rule: l_snake(TargetClassName)_id Example: Book::authors -> author_id","s":"LOWER_CASE","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#lower_case","p":515},{"i":525,"t":"Now let's demonstrate how to override the default DefaultDatabaseNamingStrategy.UPPER_CASE with DefaultDatabaseNamingStrategy.LOWER_CASE.","s":"Override Strategy","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#override-strategy","p":515},{"i":527,"t":"Java Kotlin @Bean public DatabaseNamingStrategy databaseNamingStrategy() { return DefaultDatabaseNamingStrategy.LOWER_CASE; } @Bean fun databaseNamingStrategy(): DatabaseNamingStrategy = DefaultDatabaseNamingStrategy.LOWER_CASE","s":"When using SpringBoot","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#when-using-springboot","p":515},{"i":529,"t":"Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseNamingStrategy( DefaultDatabaseNamingStrategy.LOWER_CASE ) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseNamingStrategy( DefaultDatabaseNamingStrategy.LOWER_CASE ) ...Omit other configurations... }","s":"When not using SpringBoot","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#when-not-using-springboot","p":515},{"i":532,"t":"The delete command deletes objects by id or id collection. API Category Language Delete by Id Delete by Id Collection Low Level API Java Full API JSqlClient.getEntities().delete JSqlClient.getEntities().deleteCommand Shortcut API JSqlClient.deleteById Full API JSqlClient.getEntities().deleteAll JSqlClient.getEntities().deleteAllCommand Shortcut API JSqlClient.deleteByIds Kotlin Full API KSqlClient.entities.delete Shortcut API KSqlClient.deleteById Full API KSqlClient.entities.deleteAll Shortcut API KSqlClient.deleteByIds Spring Data API Java JRepository.deleteById JRepository.deleteByIds JRepository.deleteAllById Kotlin KRepository.deleteById KRepository.deleteByIds KRepository.deleteAllById Necessary Explanations: In the Java low-level API there are two methods ending in Command: deleteCommand and deleteAllCommand. These two methods create commands but do not execute them immediately. After the user does more configuration on the command, calling execute executes it. Take deleteCommand as an example: DeleteResult result = sqlClient .getEntities() .deleteCommand(BookStore.class, 1L) ❶ .setDissociateAction(BookProps.STORE, DissociateAction.SET_NULL) ❷ .execute(); ❸ ❶ Create the command, but do not execute it. ❷ Configure the command, can be chained with multiple configurations (here only one configuration is demoed) info The effect of this configuration will be explained later, readers can ignore it for now. ❸ Finally execute it. Kotlin does not need such a design, because its delete method supports an optional Lambda parameter for configuration. Simply execute with the necessary configuration: val result = sqlClient .entities .delete(BookStore::class, 1L) { setDissociateAction(Book::store, DissociateAction.SET_NULL) } In the Spring Data API we can find two methods with the same functionality but different names: deleteByIds and deleteAllById. deleteByIds: A method consistent in style with the Jimmer low-level shortcut API. deleteAllById: A required method when inheriting org.springframework.data.repository.CrudRepository, can be understood as an alias of deleteByIds. The delete command supports two types of operations: Logical delete: Does not actually delete data, just marks the logical delete field of the object as \"deleted\". Physical delete: Actually deletes data. All the above APIs support an optional parameter of type DeleteMode through Java method overloading or Kotlin default parameters. This parameter type is an enum with three possible values: AUTO: Does not explicitly specify whether the current operation is logical delete or physical delete If the deleted entity type has a logical delete field, perform logical delete. Otherwise, perform physical delete. LOGICAL: Explicitly specifies that the current operation is logical delete If the deleted entity type has a logical delete field, perform logical delete. Otherwise, throw an exception indicating that the current entity does not support logical delete. PHYSICAL: Explicitly specifies that the current operation is physical delete Regardless of whether the deleted entity type has a logical delete field, perform physical delete.","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/delete-command","h":"#basic-concepts","p":530},{"i":534,"t":"Assuming the entity has a logical delete field, for example: Java Kotlin Book.java @Entity public interface Book { @LogicalDeleted(\"true\") boolean isDeleted(); ...other code omitted... } Book.kt @Entity interface Book { @LogicalDeleted(\"true\") val isDeleted: Boolean ...other code omitted... } Then the following three behaviors: sqlClient.deleteById(Book.class, 1L) sqlClient.deleteById(Book.class, 1L, DeleteMode.AUTO) sqlClient.deleteById(Book.class, 1L, DeleteMode.LOGICAL) have the same function, they all represent logical delete, and generate the following sql: update BOOK set DELETED = ? /* true */ where ID in(?/* 1L*/)","s":"Logical Delete","u":"/jimmer-doc/docs/mutation/delete-command","h":"#logical-delete","p":530},{"i":536,"t":"If the entity does not have a logical delete field, or the delete mode is explicitly specified as DeleteMode.PHYSICAL, physical delete is performed.","s":"Physical Delete","u":"/jimmer-doc/docs/mutation/delete-command","h":"#physical-delete","p":530},{"i":538,"t":"Java Kotlin DeleteResult result = sqlClient .getEntities() .deleteAll(Book.class, Arrays.asList(1L, 2L, 3L, 4L)); System.out.println( \"Affected row count: \" + result.getTotalAffectedRowCount() + \"\\nAffected row count of table 'BOOK': \" + result.getAffectedRowCount(AffectedTable.of(Book.class)) + \"\\nAffected row count of middle table 'BOOK_AUTHOR_MAPPING': \" + result.getAffectedRowCount(AffectedTable.of(BookProps.AUTHORS)) ); val result = sqlClient .entities .deleteAll(Book::class, listOf(1L, 2L, 3L, 4L)) println( \"\"\"Affected row count: |${result.totalAffectedRowCount} |Affected row count of table 'BOOK': |${result.affectedRowCount(Book::class)} |Affected row count of middle table 'BOOK_AUTHOR_MAPPING': |${result.affectedRowCount(Book::authors)} \"\"\".trimMargin() ) The finally generated SQL is: delete from BOOK_AUTHOR_MAPPING where BOOK_ID in(?, ?, ?, ?) delete from BOOK where ID in(?, ?, ?, ?)","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/delete-command","h":"#basic-usage","p":530},{"i":540,"t":"From the above discussion we can see that the delete command may cause data in many-to-many association middle tables to be deleted, which is a relatively simple case. For one-to-one or one-to-many associations directly based on foreign keys, the situation to be handled is a little more complex. Java Kotlin DeleteResult result = sqlClient .getEntities() .delete(BookStore.class, 1L); System.out.println( \"Affected row count: \" + result.getTotalAffectedRowCount() + \"\\nAffected row count of table 'BOOK_STORE': \" + result.getAffectedRowCount(AffectedTable.of(BookStore.class)) + \"\\nAffected row count of table 'BOOK': \" + result.getAffectedRowCount(AffectedTable.of(Book.class)) + \"\\nAffected row count of middle table 'BOOK_AUTHOR_MAPPING': \" + result.getAffectedRowCount(AffectedTable.of(BookProps.AUTHORS)) ); val result = sqlClient .entities .delete(BookStore::class, 1L) println( \"\"\"Affected row count: |${result.totalAffectedRowCount} |Affected row count of table 'BOOK_STORE': |${result.affectedRowCount(BookStore::class)} |Affected row count of table 'BOOK': |${result.affectedRowCount(Book::class)} |Affected row count of middle table 'BOOK_AUTHOR_MAPPING': |${result.affectedRowCount(Book::authors)} \"\"\".trimMargin() ) This code deletes a BookStore object. Because the BookStore object has a one-to-many association BookStore.books, if the object being deleted already has some associated objects in the database, Jimmer will discard those objects. The one-to-many association BookStore.books is not a mapping based on a middle table, but a mapping based on a foreign key. How will Jimmer discard those Book objects? Unlike JPA, Jimmer does not allow direct use of @OneToMany for association mapping. @OneToMany must use the mappedBy property. See @OneToMany to learn more. This means that through the one-to-many association BookStore.books we can certainly find the corresponding many-to-one association Book.store. Next, Jimmer will refer to the @OnDissociate annotation on the many-to-one association property Book.store. There are 5 modes for child object dissociation operations Mode Description NONE (Default) Depends on global configuration jimmer.default-dissociate-action-checking If jimmer.default-dissociate-action-checking is true (default) or the foreign key upon which the current association is based is real (foreign key constraint exists in database, see Real and Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-checking is false and the foreign key upon which the current association is based is fake (no corresponding foreign key constraint in database, see Real and Fake Foreign Keys), treated as LAX. LAX Dissociation operation performs no action. If the foreign key is real (see Real and Fake Foreign Keys), when parent object is deleted: If cascade delete behavior is configured for the database foreign key (on cascade set null or on delete delete), database automatically clears the foreign key of dissociated child objects or automatically deletes the dissociated child objects Although database-level cascade modification performs better than ORM-level cascade modification, the ORM is unaware of this. Use with caution in projects requiring cache consistency Otherwise, database reports an error and the save command is terminated If the foreign key is fake (see Real and Fake Foreign Keys), when parent object is deleted, no additional behavior occurs, allowing dangling issues with child object foreign key values Even if fake foreign key values are invalid dangling values, jimmer queries won't error - the query system will return null for parent objects rather than error due to non-existent parent CHECK Does not support dissociation operations. Throws exception to prevent operation if current parent object in database has child objects that need to be dissociated. SET_NULL Sets the foreign key of dissociated child objects to null. This mode requires that the child object's foreign key property is nullable; otherwise attempting this configuration will cause an exception. DELETE Deletes the dissociated child objects.","s":"Dissociate Mode","u":"/jimmer-doc/docs/mutation/delete-command","h":"#dissociate-mode","p":530},{"i":542,"t":"If the foreign key corresponding to Book.store is configured by the @OnDissociate annotation as SET_NULL, the following SQL is executed: update BOOK set STORE_ID = null where STORE_ID in(?) where the parameter is the id of the deleted object. Thus, the foreign keys of these discarded objects are set to null. Otherwise, first execute: select ID from BOOK where STORE_ID in(?) where the parameter is the id of the deleted object. Thus, the ids of these discarded objects are obtained. If the query does not return any data, skip the subsequent steps. If the foreign key corresponding to Book.store is configured by @OnDissociate as DELETE, use the new delete command to delete these discarded objects. This is actually the automatic recursive execution capability of the delete command. Otherwise, throw an exception. The above discussed situations all require the developer to use the @OnDissociate annotation on the Book.store property. However, you can also choose not to use the @OnDissociate annotation, but dynamically specify the dissociateAction configuration for the delete command. Java Kotlin DeleteResult result = sqlClient .getEntities() .deleteCommand(BookStore.class, 1L) .configure(it -> it .setDissociateAction( BookProps.STORE, DissociateAction.SET_NULL ) ) .execute(); val result = sqlClient .entities .delete(BookStore::class, 1L) { setDissociateAction( Book::store, DissociateAction.SET_NULL ) } Here, calling the command's setDissociateAction method dynamically has the same effect as using the @OnDissociate annotation statically on the Book.store property and specifying cascade delete. info If the last parameter of the setDissociateAction method is DissociateAction.SET_NULL, the associated property being set must be nullable, otherwise it will cause an exception. If dissociation rules are configured dynamically for the save command and also configured statically in the entity interface through the @OnDissociate annotation, the dynamic configuration takes precedence.","s":"Dissociation Examples","u":"/jimmer-doc/docs/mutation/delete-command","h":"#dissociation-examples","p":530},{"i":544,"t":"caution In recent months, the save instruction has undergone a major restructuring, so there hasn't been time to update all the documentation in this directory. Apart from new features, the new version of the save instruction has made minimal changes to existing functionality, and it remains largely consistent with the description in this directory. However, the new version of the save instruction generates SQL with much higher performance than described here. The good news is that this historically significant restructuring of Jimmer has finally been completed and stabilized, so all the content in this directory will be updated soon. tip One statement to save complex data of arbitrary shape, find DIFF to change database, like React/Vue Save commands are a very powerful capability of Jimmer that can greatly simplify the development difficulty of persisting complex data structures. If object fetchers enable output data to be in any shape, then save commands allow input data to also be in any shape. For readers familiar with web frontend technologies, this can be analogized to Virtual DOM diff in React or Vue. tip Save command require developers to completely change their thinking pattern Fundamental difference in thinking The traditional thinking pattern: Manually compare the data structure to be saved with existing data in the database, and execute INSERT, UPDATE or DELETE on the changed parts The thinking pattern for save command: Accept the data structure passed from client as a whole and just save it. Jimmer will handle everything (automatically compare the data structure to be saved with existing data in the database, and execute INSERT, UPDATE or DELETE on the changed parts) Old habits should be replaced by better methods In the traditional development mode, developers like to do one thing: query an object first, then modify some of its properties, and finally save the modified object. Although Jimmer also allows developers to do this, it is recommended to use a more performant approach, please refer to Incomplete Object. Calling a save command only takes one line of code, but hides countless details internally that documentation cannot exhaustively enumerate. Therefore, save commands have a dedicated sample project: Java: jimmer-examples/java/save-command Kotlin: jimmer-examples/kotlin/save-command-kt Simply open either one in an IDE, and run the unit tests.","s":"Save Command","u":"/jimmer-doc/docs/mutation/save-command/","h":"","p":543},{"i":546,"t":"Although Jimmer entities are not POJOs, Jackson serialization can be supported by org.babyish.jimmer.jackson.ImmutableModule. tip If using the Jimmer Spring Boot Starter, this ImmutableModule will be automatically registered without user intervention. However, sometimes we need to customize the Jackson serialization behavior of certain properties. We give two examples here. Snowflake ID Data Masking","s":"JSON Converter","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"","p":545},{"i":548,"t":"Snowflake IDs lead to very large int64 values that unfortunately cannot be represented by JavaScript's number type. Therefore, we have no choice but to serialize such id properties as strings.","s":"1. Snowflake ID","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#1-snowflake-id","p":545},{"i":550,"t":"Java Kotlin @Entity @public interface Book { @Id @GeneratedValue(generatorType = SnowflakeIdGenerator.class) @JsonConverter(LongToStringConverter.class) long id(); String name(); ...Omit other properties... } @Entity @public interface Book { @Id @GeneratedValue(generatorType = SnowflakeIdGenerator.class) @JsonConverter(LongToStringConverter.class) long id(); String name(); ...Omit other properties... } Where SnowflakeIdGenerator is a user-provided distributed snowflake ID generator implementation, which is not the focus of our discussion. Here, we discuss the highlighted line: @org.babyfish.jimmer.jackson.JsonConverter indicates custom Jackson serialization/deserialization behavior for the Book.id property. org.babyfish.jimmer.jackson.LongToStringConverter means serialize/deserialize the long value as a String. LongToStringConverter is a built-in Converter in Jimmer. Here we show its source code to quickly understand how to customize Converter. package org.babyfish.jimmer.jackson; public class LongToStringConverter implements Converter { // How to serialize @Override public String output(Long value) { return Long.toString(value); } // How to deserialize @Override public Long input(String jsonValue) { return Long.parseLong(jsonValue); } } tip Note: Jimmer annotations rather than Jackson annotations are used here, because: This is not only an adjustment of the serialization framework Jackson, but also a useful adjustment of Automatic client/server integration DTO language No need to consider null values ​​inside Converter, null values ​​will never be passed as an argument to any Converter method. Here, bypassing ORM, we demonstrate the effect by simulating data. Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(1546434604146774987L); draft.setName(\"SQL in Action\"); }); System.out.println(book); val book = Book { id = 1546434604146774987L name = \"SQL in Action\" } println(book) Since the toString of Jimmer entities is Jackson serialization, we can print directly and observe the results of Jackson serialization: { \"id\": \"1546434604146774987\", \"name\": \"SQL in Action\" } We can see that the serialized id is a string rather than a number, thus avoiding the problem that JavaScript clients cannot parse large numbers.","s":"Usage","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#usage","p":545},{"i":552,"t":"info @IdView properties is advanced mapping content that will be explained later. Readers can skip this section for now and come back later. Java Kotlin @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); @IdView(\"authors\") List bookIds(); ...Omit other properties... } @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List @IdView(\"authors\") val bookIds: List ...Omit other properties... } Here, the bookIds property is not an ordinary List collection, but the collection of ids of all associated Book objects. Because the Book.id property has already been annotated with @JsonConverter, there is no need to specify any annotations for the bookIds property here to give it this capability. Similarly, bypassing ORM, demonstrate the effect through simulated data. Java Kotlin Author author = Immutables.createAuthor(draft -> { draft.setBookIds( Arrays.asList( 1546434604146774987L, 1546434604146774988L ) ); }); System.out.println(book); val book = Book { bookIds = listOf( 1546434604146774987L, 1546434604146774988L ) } println(book) Since the toString of Jimmer entities is Jackson serialization, we can print directly and observe the results of Jackson serialization: { \"bookIds\": [ \"1546434604146774987\", \"1546434604146774988\" ] } We can see that all elements of the serialized bookIds property are strings rather than numbers, thus avoiding the problem that JavaScript clients cannot parse large numbers.","s":"Automatically Applied to IdView Properties","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#automatically-applied-to-idview-properties","p":545},{"i":554,"t":"info DTO is advanced mapping content that will be explained later. Readers can skip this section for now and come back later. In the src/main/dto directory, create any file with the extension .dto and edit its code as follows export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { id name } After compiling the project, the generated Java/Kotlin type is: Java Kotlin @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookView { private String id; private String name; ...Omit other properties... } @GeneratedBy(file = \"/src/main/dto/Book.dto\") class BookView( val id: String, val name: String ) { ...Omit other properties... } We can see that the type of the id property in the automatically generated DTO type is String instead of long. Finally, we verify the conversion from entity to DTO object as follows Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(1546434604146774987L); draft.setName(\"SQL in Action\"); }); System.out.println(new BookView(book)); val book = Book { id = 1546434604146774987L name = \"SQL in Action\" } println(BookView(book)) The output is as follows BookView( id = \"1546434604146774987\", name = \"SQL in Action\" )","s":"Automatically Applied to DTO","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#automatically-applied-to-dto","p":545},{"i":557,"t":"Assume the User entity has a phone property representing the user's phone number. We now perform data masking on this property. For example, displaying the phone number as 135****6792. info Data masking is not simply a page rendering feature. It must ensure that real data is not returned in the HTTP requests themselves. There is no built-in Converter available for this requirement. We need to customize the Converter as follows: Java Kotlin public class UserPhoneConverter implements Converter { @Override public String output(String value) { return value.substring(0, 3) + \"****\" + value.substring(7); } } class UserPhoneConverter : Converter { override fun output(value: String): String = \"${value.substring(0,3)}****${value.substring(7)}\" } Then modify the User entity simply Java Kotlin @Entity public interface User { @JsonConverter(UserPhoneConverter.class) String phone(); } @Entity interface User { @JsonConverter(UserPhoneConverter.class) val phone: String }","s":"Usage","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#usage-1","p":545},{"i":559,"t":"In the above example, the UserPhoneConverter only overrides the output method without overriding the input method. Because the default implementation of the input method is to throw an UnsupportedOperationException exception, deserialization is not supported. However, in actual projects, Input DTO can be generated based on entity objects to complete data entry. In this case, the client should enter the exact phone number. Therefore, we can override the input method as follows. Java Kotlin @Override public String input(String value) { return value; } override fun input(value: String): String = value","s":"Support Input","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#support-input","p":545},{"i":563,"t":"Any entity object will be intercepted by interceptors before being saved by save commands (whether inserted or updated). At this point, users have an opportunity to modify the data to be saved, especially to assign values to some missing properties. If interceptors are used to assign values to missing properties (which is also the recommended usage), it is somewhat similar to default values at the database level, but with the following differences: Database default values can only provide business-irrelevant default value rules. Interceptors can provide default values based on business context-related information, such as the user's identity information in the permission system. Users can provide default values that are closely combined with the business based on such business context information, which cannot be achieved by database-level default values.","s":"Concept","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#concept","p":561},{"i":565,"t":"Draft interceptors work with Save Command to adjust data before objects are saved. If most entity tables have the four fields created_time, modified_time, created_by and modified_by, a super class can be provided as follows: Java Kotlin @MappedSuperclass public interface BaseEntity { LocalDateTime createdTime(); LocalDateTime modifiedTime(); @Nullable @ManyToOne @OnDissociate(DissociateAction.SET_NULL) User creator(); @Nullable @ManyToOne @OnDissociate(DissociateAction.SET_NULL) User editor(); } @MappedSuperclass interface BaseEntity { val createdTime: LocalDateTime val modifiedTime: LocalDateTime @ManyToOne @OnDissociate(DissociateAction.SET_NULL) val createdBy: User? @ManyToOne @OnDissociate(DissociateAction.SET_NULL) val modifiedBy: User? } All entities that need these fields can derive from this superclass. note The @OnDissociate(DissociateAction.SET_NULL) here is to prevent deletion operations on associated User data from being blocked due to these two foreign keys. When associated User is deleted, these two foreign keys are automatically cleared. tip Of course, user can directly intercept the entity type (decorated with @Entity), rather than an abstract type (decorated with @MappedSupperClass). However, if an abstract type is intercepted, the save operations of all derived entity types will be intercepted, which can greatly improve the flexibility of the system, especially when the abstract type supports multiple inheritance. Therefore, the example in this article chooses to intercept the abstract type instead of the entity type.","s":"Define Intercepted Data Format","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#define-intercepted-data-format","p":561},{"i":567,"t":"Assume there is a service class called UserService whose Java method getCurrentUserId() or Kotlin property currentUserId returns the id of the currently logged in user. The interceptor must implement the org.babyfish.jimmer.sql.DraftInterceptor interface. If using Spring management (two ways of using DraftHandler will be introduced below), the code is: Java Kotlin @Component public class BaseEntityDraftInterceptor implements DraftInterceptor { private final UserService userService; public BaseEntityDraftInterceptor(UserService userService) { this.userService = userService; } @Override public void beforeSave(BaseEntityDraft draft, @Nullable BaseEntity original) { if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.MODIFIED_TIME)) { draft.setModifiedTime(LocalDateTime.now()); } if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.EDITOR)) { draft.applyModifiedBy(user -> { user.setId(userService.getCurrentUserId()); }); } if (original == null) { if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.CREATED_TIME)) { draft.setCreatedTime(LocalDateTime.now()); } if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.CREATOR)) { draft.applyCreatedBy(user -> { user.setId(userService.getCurrentUserId()); }); } } } } @Component class BaseEntityDraftInterceptor( private val userService: UserService ) : DraftInterceptor { override fun beforeSave(draft: BaseEntityDraft, original: BaseEntity?) { if (!isLoaded(draft, BaseEntity::modifiedTime)) { draft.modifiedTime = LocalDateTime.now() } if (!isLoaded(draft, BaseEntity::modifiedBy)) { draft.modifiedBy { id = userService.currentUserId } } if (original === null) { if (!isLoaded(draft, BaseEntity::createdTime)) { draft.createdTime = LocalDateTime.now() } if (!isLoaded(draft, BaseEntity::createdBy)) { draft.createdBy { id = userService.currentUserId } } } } } The beforeSave method is called before an object is saved, where the user can make final adjustments to the data to be saved. If the isNew parameter is true, it means the subsequent operation is an insert; otherwise, it is an update. warning Please do not modify properties decorated with @Id or @Key in the beforeSave method.","s":"Define Interceptor","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#define-interceptor","p":561},{"i":569,"t":"It was mentioned above that if the current operation is UPDATE, the original parameter of the beforeSave method is non-null, representing the old value in the database. original is a Jimmer dynamic object. By default, only the id and key properties are loaded and accessible. However, can we control the format of the original object to allow more properties to be accessed? The DraftInterceptor interface provides another default method dependencies() which returns a collection of properties to indicate that in addition to the id property and key property, which other properties of the original object need to be loaded. Java Kotlin @Component public class BaseEntityDraftInterceptor implements DraftInterceptor { @Override public void beforeSave( BaseEntityDraft draft, // The format of `original` is controlled by `dependencies()` @Nullable BaseEntity original ) { ...implementation is omitted... } @Override public Collection> dependencies() { return Arrays.asList( BaseEntityProps.CREATED_BY, BaseEntityProps.MODIFIED_BY ); } } @Component class BaseEntityDraftInterceptor( private val userService: UserService ) : DraftInterceptor { override fun beforeSave( draft: BaseEntityDraft, // The format of `original` is controlled by `dependencies()` original: BaseEntity? ) { ...implementation is omitted... } override fun dependencies(): Collection> = listOf( BaseEntityProps.CREATED_BY, BaseEntityProps.MODIFIED_BY ) } tip The returned property collection does not need to contain the id property and key property, because they are always loaded.","s":"Controlling the format of the original parameter","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#controlling-the-format-of-the-original-parameter","p":561},{"i":572,"t":"In the above, the class BaseEntityDraftInterceptor is decorated with @Component, obviously a Spring-managed object. info If using Spring Boot Starter and ensuring the interceptor is Spring-managed, then Jimmer will register it automatically without additional configuration. Otherwise, it must be manually registered.","s":"Using Jimmer Spring Starter","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#using-jimmer-spring-starter","p":561},{"i":574,"t":"If jimmer spring starter is not used, attaching the interceptor to the SqlClient object makes it take effect: Java Kotlin @Bean public JSqlClient sqlClient( List> interceptors, ...other params omitted... ) { return JSqlClient .newBuilder() .addDraftInterceptors(interceptors) ...other config omitted... .build(); } @Bean fun sqlClient( interceptors: List>, ...other params omitted... ): KSqlClient = newKSqlClient { addDraftInterceptors(interceptors) ...other config omitted... } tip Although only one DraftInterceptor is demoed in this article, there may be many in an actual project. So here a collection is used for Spring to inject all DraftInterceptor instances.","s":"Not Using Jimmer Spring Starter","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#not-using-jimmer-spring-starter","p":561},{"i":576,"t":"Assume Book inherits from BaseEntity, then it can be used like: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"59\")); draft.applyStore(store -> store.setId(2L)); }); sqlClient.getEntities().save(book); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"59\") store().id = 2 } sqlClient.entities.save(book) If the above save command finally results in an insert operation, the generated SQL is: insert into BOOK( CREATED_TIME, MODIFIED_TIME, CREATED_BY, MODIFIED_BY, NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ?, ?, ?, ?, ? ) Where the assignment behavior for CREATED_TIME, MODIFIED_TIME, CREATED_BY and MODIFIED_BY is automatically added by the interceptor. If the above save command finally results in an update operation, the generated SQL is: update BOOK set MODIFIED_TIME = ?, MODIFIED_TIME, PRICE = ?, STORE_ID = ? where ID = ? Where the assignment behavior for MODIFIED_TIME and MODIFIED_BY is automatically added by the interceptor.","s":"Final Usage","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#final-usage","p":561},{"i":579,"t":"First, the association table is hidden by the object model, with no direct corresponding entity type. This problem has been explained in Query Association Table, so I won't repeat it here. In addition, in the Save Command section, we introduced the save command. It can compare the existing data structure in the database with the new data structure the user wants to save. If a relation property based on the association table has changed, the association table will be modified. Admittedly, the Save Command feature is very powerful, and modifying the association table is just a very small part of its capabilities. However, sometimes we just need a simple way to insert or delete data directly from the association table, we don't need the full capabilities of the Save Command. Jimmer allows developers to directly insert and delete data from the association table in a simpler way.","s":"Overview","u":"/jimmer-doc/docs/mutation/associations","h":"#overview","p":577},{"i":581,"t":"Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .save(12L, 3L); sqlClient .getAssociations(Book::authors) .save(12L, 3L) The generated SQL is: insert into BOOK_AUTHOR_MAPPING( BOOK_ID, AUTHOR_ID ) values (?, ?) This example shows how to use the association property Book.authors to operate the association table. Similarly, we can achieve the same goal through the association property Authors.books: Java Kotlin sqlClient .getAssociations(AuthorProps.BOOKS) .save(3L, 12L); sqlClient .getAssociations(Author::books) .save(3L, 12L) Note that compared to the previous example, the parameter order of the save method is different due to the different association direction. The generated SQL is: insert into BOOK_AUTHOR_MAPPING( AUTHOR_ID, BOOK_ID ) values (?, ?) It's easy to see that the order of the insert statement columns is also different.","s":"Insert Association","u":"/jimmer-doc/docs/mutation/associations","h":"#insert-association","p":577},{"i":583,"t":"For bidirectional associations, reverse can be used to switch between forward and reverse associations: Java Kotlin Associations bookToAuthor = sqlClient .getAssociations(BookProps.AUTHORS); Associations authorToBook = sqlClient .getAssociations(AuthorProps.BOOKS); Associations authorToBook2 = bookToAuthor.reverse(); Associations bookToAuthor2 = authorToBook.reverse(); val bookToAuthor = sqlClient.getAssociations( Book::authors ) val authorToBook = sqlClient.getAssociations( Author::books ) val authorToBook2 = bookToAuthor.reverse() val bookToAuthor2 = authorToBook.reverse() In this code: bookToAuthor and bookToAuthor2 are completely equivalent. authorToBook and authorToBook2 are completely equivalent.","s":"Reverse Conversion","u":"/jimmer-doc/docs/mutation/associations","h":"#reverse-conversion","p":577},{"i":585,"t":"Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .saveAll( Arrays.asList( new Tuple2<>(10L, 1L), new Tuple2<>(11L, 1L), new Tuple2<>(12L, 1L), new Tuple2<>(10L, 3L), new Tuple2<>(11L, 3L), new Tuple2<>(12L, 3L) ) ); sqlClient .getAssociations( Book::authors ) .saveAll( listOf( Tuple2(10L, 1L), Tuple2(11L, 1L), Tuple2(12L, 1L), Tuple2(10L, 3L), Tuple2(11L, 3L), Tuple2(12L, 3L) ) ) Here there are 3 books, two authors, and 6 total combination ways. The saveAll method inserts all 6 combinations into the association table, generating the following SQL: insert into BOOK_AUTHOR_MAPPING( BOOK_ID, AUTHOR_ID ) values (?, ?), (?, ?), (?, ?), (?, ?), (?, ?), (?, ?) The above approach is very cumbersome. For 3 * 2 = 6 it is still acceptable, but what about 7 * 9 = 63? Should we really construct 63 tuples? Jimmer-sql provides a shorthand syntax: Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) // Save cartesian product of two id sets .saveAll( Arrays.asList( 10L, 11L, 12L ), Arrays.asList( 1L, 3L ) ); sqlClient .getAssociations( Book::authors ) // Save cartesian product of two id sets .saveAll( listOf(10L, 11L, 12L), listOf(1L, 3L) ) The above saveAll method takes two collection parameters and inserts the cartesian product of the two collections into the association table, so its functionality is the same as the previous example.","s":"Bulk Insert","u":"/jimmer-doc/docs/mutation/associations","h":"#bulk-insert","p":577},{"i":587,"t":"Inserting id tuples that already exist into the association table will cause errors, as it violates uniqueness constraints. To solve this problem, existence checks can be performed. Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .saveAllCommand( Arrays.asList( 10L, 11L, 12L ), Arrays.asList( 1L, 3L ) ) .checkExistence() .execute(); sqlClient .getAssociations( Book::authors ) .saveAll( listOf(10L, 11L, 12L), listOf(1L, 3L), checkExistence = true ) Here checkExistence() indicates that it will first check which data to be inserted already exists, and then only insert data that does not exist. The generated SQL statements are: Check which data to be inserted already exists: select BOOK_ID, AUTHOR_ID from BOOK_AUTHOR_MAPPING where (BOOK_ID, AUTHOR_ID) in( (?, ?), (?, ?), (?, ?) ) Using the results of the previous query, the data that really needs to be inserted can be calculated. Skip this step if no data needs to be inserted; otherwise, execute this step. Here, assuming it is determined that only two rows of data really need to be inserted, the generated SQL is: insert into BOOK_AUTHOR_MAPPING( BOOK_ID, AUTHOR_ID ) values (?, ?), (?, ?) info Some databases support UPSERT (such as Postgres' insert into ... on conflict ...), which will be supported before Jimmer-1.0.0","s":"Check Existence","u":"/jimmer-doc/docs/mutation/associations","h":"#check-existence","p":577},{"i":589,"t":"Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .delete(12L, 3L); sqlClient .getAssociations( Book::authors ) .delete(12L, 3L) The generated SQL is: delete from BOOK_AUTHOR_MAPPING where (BOOK_ID, AUTHOR_ID) in ( (?, ?) )","s":"Delete Association","u":"/jimmer-doc/docs/mutation/associations","h":"#delete-association","p":577},{"i":591,"t":"Similar to bulk insert, there are two ways to bulk delete: Java Kotlin sqlClient .getAssociations( BookTableEx.claBookProps.AUTHORS) .deleteAll( Arrays.asList( new Tuple2<>(10L, 1L), new Tuple2<>(11L, 1L), new Tuple2<>(12L, 1L), new Tuple2<>(10L, 3L), new Tuple2<>(11L, 3L), new Tuple2<>(12L, 3L), ) ); sqlClient .getAssociations( Book::authors ) .deleteAll( listOf( Tuple2(10L, 1L), Tuple2(11L, 1L), Tuple2(12L, 1L), Tuple2(10L, 3L), Tuple2(11L, 3L), Tuple2(12L, 3L) ) ) Or: Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .deleteAll( Arrays.asList(10L, 11L, 12L), Arrays.asList(1L, 3L) ); sqlClient .getAssociations( Book::authors ) .deleteAll( listOf(10L, 11L, 12L), listOf(1L, 3L) ) The generated SQL is: delete from BOOK_AUTHOR_MAPPING where (BOOK_ID, AUTHOR_ID) in ( (?, ?), (?, ?) )","s":"Bulk Delete","u":"/jimmer-doc/docs/mutation/associations","h":"#bulk-delete","p":577},{"i":593,"t":"caution Please do not abuse this feature. This feature is only suitable for simple insertion and deletion of association tables. It is recommended to only use it when facing the simplest incremental operations. Let's look at an example. If comparison with existing data in the database is needed, this feature is obviously not the optimal choice, and the code will be very cumbersome, as follows: Java Kotlin Inappropriate Usage Example public void setAuthors(long bookId, Collection authorIds) { // Get old author ids AssociationTable table = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List oldAuthorIds = sqlClient .createAssociationQuery(table) .where(table.source().id().eq(bookId)) .select(table.target().id()) .execute(); // Delete `oldAuthorIds - authorIds` List detachedAuthorIds = new ArrayList<>(oldAuthorIds); detachedAuthorIds.removeAll(authorIds); sqlClient.getAssociations(BookProps.AUTHORS).deleteAll( Collections.singleton(bookId), detachedAuthorIds ); // Insert `authorIds - oldAuthorIds` List attachedAuthorIds = new ArrayList<>(authorIds); attachedAuthorIds.removeAll(oldAuthorIds); sqlClient.getAssociations(BookProps.AUTHORS).saveAll( Collections.singleton(bookId), attachedAuthorIds ); } Inappropriate Usage Example fun setAuthors(bookId: Long, authorIds: Collection) { // Get old author ids val oldAuthorIds = sqlClient.queries.forList(Book::authors) { where(table.source.id eq bookId) select(table.target.id) }.execute().toSet() // Delete `oldAuthorIds - authorIds` sqlClient .getAssociations(Book::authors) .deleteAll(listOf(bookId), oldAuthorIds - authorIds) // Insert `authorIds - oldAuthorIds` sqlClient .getAssociations(Book::authors) .saveAll(listOf(bookId), authorIds - oldAuthorIds) } It is obvious that dealing with it this way is very cumbersome. tip When the business scenario is no longer simple addition or deletion, Save Command is a better choice, as follows: Java Kotlin Better Usage Example public void setAuthors(long bookId, Collection authorIds) { sqlClient.save( Immutables.createBook(book -> { book.setId(bookId); book.setAuthorIds(authorIds); }) ); } Better Usage Example fun setAuthors(bookId: Long, authorIds: Collection) { sqlClient.save( Book { id = bookId authorIds = authorIds } ) }","s":"Notes","u":"/jimmer-doc/docs/mutation/associations","h":"#notes","p":577},{"i":596,"t":"The owned side only has @OneToMany or @OneToOne objects with mappedBy. Taking @OneToMany as an example: Java Kotlin @Entity public interface BookStore { @OneToMany(mappedBy = true) List books(); } @Entity interface BookStore { @OneToMany(mappedBy = true) val books: List } This association has a special functionality: Automatically sets reverse associations for child objects Configures whether different parent objects can snatch for child objects","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#basic-concepts","p":594},{"i":598,"t":"Assume we have the following entity: Java Kotlin TreeNode.java @Entity public interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key @ManyToOne @Nullable TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } TreeNode.kt @Entity interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List } The @Key properties of TreeNode are name and parent. Apart from explicitly accepting the persistence mode for wild objects, the object being saved needs to either: Specify the TreeNode.id property Specify both TreeNode.name and TreeNode.parent properties However, the following code works normally: Java Kotlin TreeNode rootNode = Immutables.createTreeNode(root -> { root.setName(\"Root\"); root.setParent(null); root.addIntoChildNodes(child -> { child.setName(\"Child-1\"); // For non-root objects, no need to specify the `parent` property }); root.addIntoChildNodes(child -> { child.setName(\"Child-2\"); // For non-root objects, no need to specify the `parent` property }); }); sqlClient .saveCommand(rootNode) .setTargetTransferModeAll(TargetTransferMode.ALLOWED) .execute(); val rootNode = TreeNode { name = \"Root\" parent = null childNodes().addBy { name = \"Child-1\" // For non-root objects, // no need to specify the `parent` property } childNodes().addBy { name = \"Child-2\" // For non-root objects, // no need to specify the `parent` property } } sqlClient.save(rootNode) { setTargetTransferModeAll(TargetTransferMode.ALLOWED) } The setTargetTransferModeAll(TargetTransferMode.ALLOWED) is not the focus here, readers can ignore it for now. Here, although the root object (Root) has both name and parent properties specified, for non-root objects (Child-1, Child-2), only the name property is specified, while the parent property is not. The TreeNode.childNodes property is the reverse association of the TreeNode.parent property. info For the owning side of many-to-one (or one-to-one) associations (here TreeNode.parent), once child objects are specified for the parent object through its inverse one-to-many (or one-to-one) association (here TreeNode.childNodes), the parent object reference for each child object in the collection will be automatically set. In this example, the object tree that the user originally expected to save was: { \"name\":\"Root\", \"parent\":null, \"childNodes\":[ {\"name\":\"Child-1\"}, {\"name\":\"Child-2\"} ] } Assuming the database assigns auto-number 100 to the root element after insertion, Jimmer will automatically adjust this tree to: { \"id\": 100, \"name\":\"Root\", \"parent\":null, \"childNodes\":[ { \"name\":\"Child-1\", \"parent\": {\"id\": 100} }, { \"name\":\"Child-2\", \"parent\": {\"id\": 100} } ] } As you can see, once the parent object is saved, the TreeNode.parent property of all child objects will be automatically set. That is, when the id property is not specified: From Jimmer's perspective, both name and parent properties of all TreeNode objects are specified, meaning all @Key properties are specified From the user's perspective, only the root object needs to specify both name and parent properties, while all other objects only need to specify the name property The above example will generate three SQL statements: Query whether the root object exists based on @Key: Purpose: COMMAND(NULL_NOT_DISTINCT_REQUIRED) select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.PARENT_ID is null and tb_1_.NAME = ? /* Root */ Here, the database's own UPSERT capability is not used, instead an additional query is made to determine whether the subsequent operation should be INSERT or UPDATE. This is because the database's own UPSERT capability relies on unique constraints (or unique indexes), and here, the parent property of the root object being saved is null, and not all databases have the ability to define null behavior for unique constraints. Therefore, by default, if the @Key property of the object being saved is null, Jimmer will give up using the database's own UPSERT capability, execute an additional query to determine whether the subsequent operation should be INSERT or UPDATE, and report QueryReason.NULL_NOT_DISTINCT_REQUIRED to developers. info Some databases, such as Postgres, can define null behavior for unique constraints. How to solve this problem in such databases is not the focus of this article, please refer to the documentation comments of QueryReason.NULL_NOT_DISTINCT_REQUIRED to learn more. Assuming the above query determines that the object being saved does not exist in the database, simply insert the root object: insert into TREE_NODE(NAME, PARENT_ID) values(?, ?) /* batch-0: [Root, DbNull{type=long}] */ Save child objects (assuming the id is known to be 100 after saving the root object): merge into TREE_NODE( NAME, PARENT_ID ) key( NAME, PARENT_ID ) values(?, ?) /* batch-0: [Child-1, 100] */ /* batch-1: [Child-2, 100] */","s":"1. Automatically Setting Reverse Associations for Child Objects","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#1-automatically-setting-reverse-associations-for-child-objects","p":594},{"i":601,"t":"Let's look at an example first: Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setId(12L); }); draft.addIntoBooks(book -> { book.setId(1L); }); }); sqlClient.save(store); val store = BookStore { name = \"MANNING\" books().addBy { id = 12L } books().addBy { id = 1L } } sqlClient.save(store) Executing this code will generate the following SQL and result in an exception: Saving the root object BookStore: merge into BOOK_STORE( NAME ) key(NAME) values(?) /* batch-0: [MANNING] */ Saving the child objects Book: Purpose: COMMAND(TARGET_NOT_TRANSFERABLE) select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.ID = any(? /* [12, 1] */) Strangely, even though the id property of child objects is specified (which usually means Jimmer will utilize the database's own UPSERT capability), Jimmer still tries to determine whether the subsequent operation should be INSERT or UPDATE through a query, rather than using the database's own UPSERT capability. More importantly, Jimmer reports QueryReason.TARGET_NOT_TRANSFERABLE. Finally, the above code will result in the following exception: Save error caused by the path: \".books\": Can the move the child object whose type is \"org.doc.j.model.Book\" and id is \"1\" to another parent object because the property \"org.doc.j.model.BookStore.books\" does not support target transfer Book.store is a many-to-one association, a Book object can only belong to one BookStore object and cannot belong to multiple BookStore objects simultaneously. Therefore, saving the data structure through the inverse one-to-many association BookStore.books establishes an association between the current BookStore parent object and another existing Book object. If the Book object already belongs to another parent object, it will cause the current parent object to snatch for the child object from other parent objects. In other words, the child object migrates between different parent objects. If this is expected behavior by the developers, then there's no problem. However, if this is not expected behavior, it may lead to unintended oversights. By default, Jimmer adopts a conservative strategy that prohibits child objects from transfering between different parent objects. In this example, attempting to associate BookStore(MANNING) with Book(12) and Book(1), Jimmer executes an additional query with QueryReason.TARGET_NOT_TRANSFERABLE to check if any child objects are transfering between different parent objects. Book(12) already belongs to BookStore(MANNING), no transfer occurs, no problem Book(1) doesn't belong to BookStore(MANNING) but belongs to BookStore(O'REILLY), transfer occurs, therefore an exception is thrown. The default behavior is very conservative. While it prevents competition for child objects between different parent objects (if developers consider such unintended competition harmful to business), it leads to additional queries and doesn't fully utilize the database's own UPSERT capability, resulting in suboptimal performance. If you believe better performance is more important than this conservative defensive behavior, Jimmer provides additional configuration to change this behavior.","s":"Conservative Default Behavior","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#conservative-default-behavior","p":594},{"i":603,"t":"To prioritize performance and remove these restrictions, there are two methods: Save command level configuration, which can be divided into two types: Precise configuration, removing restrictions for specific associations: Java Kotlin BookStore store = ...omitted...; sqlClient .saveCommand(store) .setTargetTransferMode( BookStoreProps.BOOKS, TargetTransferMode.ALLOWED ) .execute(); val store = BookStore {...omitted...} sqlClient.save(store) { setTargetTransferMode( BookStore::books, TargetTransferMode.ALLOWED ) } Blind configuration, removing restrictions for all associations: Java Kotlin BookStore store = ...omitted...; sqlClient .saveCommand(store) .setTargetTransferModeAll( TargetTransferMode.ALLOWED ) .execute(); val store = BookStore {...omitted...} sqlClient.save(store) { setTargetTransferModeAll( TargetTransferMode.ALLOWED ) } Whether precise or blind configuration, the last parameter is the TargetTransferMode enum, which has three values: ALLOWED: Allows child object transfer and tries to use the database's own UPSERT capability whenever possible NOT_ALLOWED: Prohibits child object transfer, initiates additional queries with QueryReason.TARGET_NOT_TRANSFERABLE for verification. If child object transfer occurs, throws an exception AUTO (default): Current configuration is invalid, refers to lower priority configuration For precise configuration, refers to blind configuration For blind configuration, refers to global configuration Global configuration, which can be divided into two types: Global configuration based on Jimmer API: Java Kotlin JSqlClient sqlCient = JSqlClient .newBuilder() .setTargetTransferable(true) ...other configurations omitted... .build(); val sqlClient = sqlClient { setTargetTransferable(true) ...other configurations omitted... } Global configuration based on Spring Boot if using Jimmer's spring-boot-starter: Using application.yml as an example: jimmer: target-transferable: true ...other configurations omitted... Once Jimmer is configured through any of the above methods to not restrict child object transfer for the BookStore.books association, modify the code as follows: Java Kotlin Book.java public interface Book { @ManyToOne @Nullable // Not related to the current discussion, // please ignore for now @OnDissociate(DissociateAction.SET_NULL) BookStore store(); ...other code omitted... } Book.kt public interface Book { @ManyToOne // Not related to the current discussion, // please ignore for now @OnDissociate(DissociateAction.SET_NULL) val store: BookStore? ...other code omitted... } Re-executing the code will generate the following SQL: Saving the root object: merge into BOOK_STORE( NAME ) key(NAME) values(?) /* batch-0: [MANNING] */ Establishing associations between root object and child objects: merge into BOOK( ID, STORE_ID ) key(ID) values(?, ?) /* batch-0: [12, 2] */ /* batch-1: [1, 2] */ Breaking associations between root object and no longer needed child objects: update BOOK set STORE_ID = null where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [2, [12, 1]] */ info To demonstrate performance-priority scenarios to users, the examples jimmer-examples/java/save-command and jimmer-examples/kotlin/save-command-kt both use global configuration to allow child object transfer.","s":"Overriding Default Behavior Without Restrictions","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#overriding-default-behavior-without-restrictions","p":594},{"i":606,"t":"The usage of the delete statement is: Java Kotlin BookTable book = Tables.BOOK_TABLE; int affectedRowCount = sqlClient .createDelete(book) .where(book.name().eq(\"Learning GraphQL\")) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createDelete(Book::class) { where(table.name eq \"Learning GraphQL\") } .execute() println(\"Affected row count: $affectedRowCount\") The generated SQL is: delete from BOOK as tb_1_ where tb_1_.NAME = ?","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/delete-statement","h":"#basic-usage","p":604},{"i":608,"t":"The delete statement usage below supports JOIN clauses, as follows: Java Kotlin BookTable book = Tables.BOOK_TABLE; int affectedRowCount = sqlClient .createDelete(book) .where(book.store().name().eq(\"MANNING\")) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createDelete(Book::class) { where(table.store.name eq \"MANNING\") } .execute() println(\"Affected row count: $affectedRowCount\") The finally generated SQL is: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? delete from BOOK_AUTHOR_MAPPING where BOOK_ID in(?, ?, ?) delete from BOOK where ID in(?, ?, ?) note If JOIN is used in a delete statement, Jimmer will translate it into select + delete. First use the select statement with join clause to query the ids of the data to be deleted, then use Delete Command to delete the data. This scheme is valid for any database.","s":"Using JOIN","u":"/jimmer-doc/docs/mutation/delete-statement","h":"#using-join","p":604},{"i":611,"t":"Association objects can be classified from two perspectives, with two types of associations from each perspective, totaling 4 types Classification by association object shape Short Association Only modifies the association relationship between the current object and other objects, without further saving the associated objects. The recursive saving behavior is terminated and will not continue deeper. Long Association Not only modifies the association relationship between the current object and other objects but also further saves the associated objects. The recursive saving behavior will not be terminated and will continue deeper. Classification by save order Forward Association Associated objects are saved earlier than the current object, which is actually based on foreign keys (whether true or false). For example: Book.store in this tutorial. Backward Association Associated objects are saved later than the current object, including two situations The inverse association of forward associations. For example: BookStore.books in this tutorial Associations based on intermediate tables. For example: Book.authors and Author.books in this tutorial","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#basic-concepts","p":609},{"i":614,"t":"A short association means only modifying the association itself between the current object and other objects, with no interest in modifying the associated objects. Typically, UI design will use radio buttons (association reference) or checkboxes (association collection). Book Form Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit Where: Radio buttons correspond to many-to-one association Book.store Checkboxes correspond to many-to-many association Book.authors note In real projects, when there is a lot of data to choose from, it might not be suitable to design as a dropdown UI. In this case, an object selector with filtering conditions and pagination capabilities can be used instead of a dropdown, which is a common workaround. Since users only want to modify the association between the current object and other objects, without further modifying the associated objects, the UI cannot have multiple levels of association nesting. This is why it's called a short association. When passing any shaped data structure as a parameter to the save command, there are two methods to specify short associations: Use Id-Only objects as associated objects Use Key-Only objects as associated objects with special configuration enabled 1.1.1. Using Id-Only Objects as Associated Objects​ Make associated objects have only the id property Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"39.9\")); // Associated object has only id property draft.setStoreId(2L); draft.addIntoAuthors(author -> { // Associated object has only id property author.setId(4L); }); draft.addIntoAuthors(author -> { // Associated object has only id property author.setId(5L); }); }); sqlClient.save(book); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"39.9\") // Associated object has only id property storeId = 2L authors().addBy { // Associated object has only id property id = 4L } authors().addBy { // Associated object has only id property id = 5L } } sqlClient.save(book) note The hardcoding of the data structure being saved here is only for demonstration. In actual projects, the data structure being saved is submitted by the frontend interface. Of course, if the user has defined the authorIds property according to the Mapping/Advanced Mapping/View Properties/IdView article, the above code can be simplified, for example: Java Kotlin Book book = ImmutableObjects.createBook(draft -> { draft.setAuthorIds(Arrays.asList(4L, 5L)); }); val book = Book { authorIds = listOf(4L, 5L) } However, this is not mandatory. To make the example more universal, we don't assume that users have defined IdView properties for entity types. All subsequent documentation will follow this approach without further reminders. Assuming the current database is H2, the generated SQL would be: Save the aggregate root. merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 39.9, 2] */ Since Book.store is a many-to-one relationship directly based on foreign key (STORE_ID), the association between the current object and BookStore(2) object will be automatically created by the execution of this SQL. If there are Author objects associated with the current object (newly inserted data is Book(100)) other than just Author(4) and Author(5), break the associations with those other objects. delete from BOOK_AUTHOR_MAPPING where BOOK_ID = ? /* 100 */ and not ( AUTHOR_ID = any(? /* [4, 5] */) ) This step is called unhooking, which will be introduced in subsequent documentation. Readers can ignore this for now. Establish associations between the object (newly inserted data is Book(100)) and the two objects Author(4) and Author(5) merge into BOOK_AUTHOR_MAPPING tb_1_ using(values(?, ?)) tb_2_( BOOK_ID, AUTHOR_ID ) on tb_1_.BOOK_ID = tb_2_.BOOK_ID and tb_1_.AUTHOR_ID = tb_2_.AUTHOR_ID when not matched then insert(BOOK_ID, AUTHOR_ID) values(tb_2_.BOOK_ID, tb_2_.AUTHOR_ID) /* batch-0: [100, 4] */ /* batch-1: [100, 5] */ info Through this example, it's not hard to see that short associations only create or destroy the association relationships between the current object and other objects, without further saving the associated objects. Short associations always assume that the referenced objects exist. If the referenced objects (in this example, BookStore(2), Author(4), and Author(5)) don't exist, it will cause an exception! 1.1.2. Using Key-Only Objects as Associated Objects with Special Configuration Enabled​ In the code below, assume: The key property for the BookStore type is name View The key properties for the Author type are firstName and lastName In actual business scenarios, this uniqueness constraint might not be reasonable, but let's assume this for the sake of simplifying the example. View Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"39.9\")); draft.applyStore(store -> { // Associated object has only key property, i.e., `BookStore.name` store.setName(\"MANNING\"); }); draft.addIntoAuthors(author -> { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` author.setFirstName(\"Boris\").setLastName(\"Cherny\"); }); draft.addIntoAuthors(author -> { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` author.setFirstName(\"Samer\").setLastName(\"Buna\"); }); }); sqlClient .saveCommand(book) .setKeyOnlyAsReference(BookProps.STORE) .setKeyOnlyAsReference(BookProps.AUTHORS) .execute(); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"39.9\") store { // Associated object has only key property, i.e., `BookStore.name` name = \"MANNING\" } authors().addBy { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` firstName = \"Boris\" lastName = \"Cherny\" } authors().addBy { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` firstName = \"Samer\" lastName = \"Buna\" } } sqlClient.save(book) { setKeyOnlyAsReference(Book::store) setKeyOnlyAsReference(Book::authors) } info By default, key-only associated objects are treated as long associations However, developers can treat key-only associated objects as short associations by calling the setKeyOnlyAsReference method. Here, setKeyOnlyAsReference is called twice to explicitly configure the associations Book.store and Book.authors. In fact, you can also call setKeyOnlyAsReferenceAll once to blindly configure all associations. Compared to Kotlin, the Java API is slightly less convenient for advanced configuration of save commands. First call the saveCommand method to create a save command without executing it immediately, then call the execute method to actually execute it after completing the advanced configuration.","s":"1.1. Short Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#11-short-association","p":609},{"i":616,"t":"Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"Book Form","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"","p":609},{"i":618,"t":"A long association means not only modifying the association itself between the current object and other objects but also further modifying the associated objects. Typically, orders and order items are the best examples of such scenarios. The UI design will use embedded tables, for example: Purchaser Schneewittchen Purchaser Province Province City City Address Address Order Items Commodity Quantity Unit price Item price Delete Timeless Vitamin C Plus E 10 Percent Ferulic Acid Serum Serum Unisex 1 oz 14.69 29.38 Olaplex No. 4 Bond Maintenance Shampoo 30 30 Add Total price:59.379999999999995 Submit Since users not only want to modify the association between the current object and other objects but also want to further modify the associated objects, and the associated objects can contain deeper associations, theoretically, the UI can have multiple levels of association nesting. This is why it's called a long association. note Although designers will intentionally avoid nesting deeper embedded tables within embedded tables to maintain UI simplicity, there are still scenarios in real projects where maintaining multi-level nested associations in the UI is necessary, such as: The form itself is a tree structure, which is saved as a whole after editing. Visual UI design, because UI components themselves are tree structures, after users perform a series of visual drag-and-drop designs, the UI component tree is saved as a whole. Jimmer can directly save long association data structures of any shape. If we call a long association data structure with unknown depth a complex form, the save command is designed for complex forms. Here's an example: Java Kotlin Order order = Immutables.createOrder(draft -> { draft.setCustomerId(1L); draft.setProvince(\"Prenzlauer Berg\"); draft.setCity(\"Berlin\"); draft.setAddress(\"Brandenburgische Straße 9, Prenzlauer Berg, Berlin, Germany\"); draft.addIntoItems(item -> { item.setProductId(8L); // Property neither id nor key item.setQuantity(2); }); draft.addIntoItems(item -> { item.setProductId(9L); // Property neither id nor key item.setQuantity(1); }); }); sqlClient.save(order); val order = Order { customerId = 1L province = \"Prenzlauer Berg\" city = \"Berlin\" address = \"Brandenburgische Straße 9, Prenzlauer Berg, Berlin, Germany\" items().addBy { productId = 8L // Property neither id nor key quantity = 2 } items().addBy { productId = 9L // Property neither id nor key quantity = 1 } } sqlClient.save(order) In this example, we can see many short associations, such as Order.customer, OrderItem.product, but these are not the focus here. Here, we should focus on the association Order.items, which is clearly a long association. This operation generates two SQL statements: Insert the root object Order insert into order_( PROVINCE, CITY, ADDRESS, CUSTOMER_ID ) values(?, ?, ?, ?) /*batch-0: [Prenzlauer Berg, Berlin, Brandenburgische Straße 9, Prenzlauer Berg, Berlin, Germany, 1] */ Insert all child objects OrderItem insert into ORDER_ITEM( ORDER_ID, PRODUCT_ID, QUANTITY ) values(?, ?, ?) /* batch-0: [100, 8, 2] */ /* batch-1: [100, 9, 1] */ info As we can see, long associations not only modify the association relationship between the current object and other objects but also cause the associated objects to be saved. If the associated objects also have long associations, they will be saved recursively until there are no more association properties or until a short association is encountered.","s":"1.2. Long Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#12-long-association","p":609},{"i":621,"t":"Forward association is based on foreign keys (whether true or false). Its working mode is to save the associated objects first, then save the root object. Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.9\")); draft.applyStore(store -> { store.setName(\"TURING\"); store.setWebsite(\"https://www.turing.com\"); }); }); sqlClient.save(book); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") store { name = \"TURING\" website = \"https://www.turing.com\" } } sqlClient.save(book) Taking H2 as an example, it generates two SQL statements: First save the associated object BookStore merge into BOOK_STORE( NAME, WEBSITE ) key(NAME) values(?, ?) /* batch-0: [TURING, https://www.turing.com] */ Then save the current object Book merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 100] */ caution When discussing forward associations in work communication, it's recommended to use expressions like \"current object/associated object\" rather than \"parent object/child object\". This is because, for forward associations, the parent-child relationship at the ORM level is completely opposite to that at the database modeling level, which can easily cause confusion and misunderstanding.","s":"2.1. Forward Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#21-forward-association","p":609},{"i":623,"t":"Other associations, such as: Inverse associations of forward associations (like BookStore.books in this tutorial) Associations based on intermediate tables (like Book.authors and Author.books in this tutorial) can all be categorized as backward associations, which are more common scenarios. The working mode of backward associations is easier to understand: save the current object first, then save the associated objects. Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.setWebsite(\"https://www.turing.com\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"RUST programming\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.9\")); }); }); sqlClient .saveCommand(store) // Please ignore this configuration for now .setTargetTransferModeAll(TargetTransferMode.ALLOWED) .execute(); val store = BookStore { name = \"TURING\" website = \"https://www.turing.com\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"RUST programming\" edition = 2 price = BigDecimal(\"39.9\") } } sqlClient.save(store) { // Please ignore this configuration for now setTargetTransferModeAll(TargetTransferMode.ALLOWED) } Taking H2 as an example, it generates three SQL statements: First save the current object BookStore merge into BOOK_STORE( NAME, WEBSITE ) key( NAME ) values(?, ?) /* batch-0: [TURING, https://www.turing.com] */ Then save the associated objects Book merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 100] */ /* batch-1: [RUST programming, 2, 39.9, 100] */ The third SQL statement is not relevant to the topic being discussed here, so it's omitted info Backward associations have richer functionality than forward associations. This tutorial will focus on discussing backward associations.","s":"2.2. Backward Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#22-backward-association","p":609},{"i":625,"t":"The save command is used to store data structures of any complexity. To facilitate discussion, we need to establish a basic classification of data structure shapes.","s":"Data Classification","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"","p":624},{"i":627,"t":"Jimmer entities support two types of property representation: @Id: A property that must be defined for any Jimmer entity type. It serves as a technical unique identifier, known in the industry as a Surrogate Id. @Key: Multiple properties that Jimmer recommends defining for entity types. They serve as business-level unique identifiers, known in the industry as Natural Id. In this series of articles, all entities have both @Id and @Key properties defined, with the Id property using the database's auto-increment strategy. Here's an example using Book: Java Kotlin Book.java @Entity public interface Book { @Id ❶ @GeneratedValue(strategy = GenerationType.IDENTITY) ❷ long id(); @Key ❸ String name(); @Key ❸ int edition(); BigDecimal price(); ...other properties omitted... } Book.kt @Entity interface Book { @Id ❶ @GeneratedValue(strategy = GenerationType.IDENTITY) ❷ val id: Long @Key ❸ val name: String @Key ❸ val edition: Int val price: BigDecimal ...other properties omitted... } ❶ Id property, i.e., Surrogate Id ❷ Id property uses database auto-numbering as the auto-increment strategy ❸ Key property, i.e., Natural Id","s":"Entity Definition","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#entity-definition","p":624},{"i":629,"t":"An object is called a wild object if neither its @Id property (Book.id in this article) nor its @Key properties (Book.name and Book.edition in this article) are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setPrice(new BigDecimal(\"59.9\")); }); val book = Book { price = BigDecimal(\"59.9\") } When we say @Key properties are not specified, this includes two situations: The entity type doesn't define any @Key properties (not discussed in this article) Although the entity type defines @Key properties, these properties are not specified in the object caution Jimmer does not recommend wild objects. Although API parameters can be adjusted to save wild objects, this will ultimately compromise idempotency.","s":"1. Wild Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#1-wild-objects","p":624},{"i":631,"t":"An object is called an id-specified object if its @Id property (Book.id in this article) is specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(17L); ...other settings omitted... }); val book = Book { id = 17L ...other settings omitted... } Jimmer supports UPSERT operations, where users don't explicitly specify insert or update, letting Jimmer make the determination. When saving an id-specified object in UPSERT mode, Jimmer uses the @Id property to determine whether corresponding data already exists in the database, ultimately deciding whether to insert or update.","s":"2. Id-specified Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#2-id-specified-objects","p":624},{"i":633,"t":"An object is called a key-specified object if its @Id property (Book.id in this article) is not specified, but its @Key properties (Book.name and Book.edition in this article) are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(2); ...setting other properties except id... }); val book = Book { name = \"GraphQL in Action\" edition = 1 ...setting other properties except id... } note In the code above, the omitted parts do not include setting the @Id property, because once the @Id property is set, it should be an id-specified object, not a key-specified object. Jimmer supports UPSERT operations, where users don't explicitly specify insert or update, letting Jimmer make the determination. When saving a key-specified object in UPSERT mode, Jimmer uses the @Key properties to determine whether corresponding data already exists in the database, ultimately deciding whether to insert or update.","s":"3. Key-specified Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#3-key-specified-objects","p":624},{"i":635,"t":"An id-specified object is called an id-only object if no properties other than id are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(17L); }); val book = Book { id = 17L } In hierarchical data structures, any object can have deeper associated objects. If an associated object is an id-only object, it indicates that only the association relationship is being modified, without further creating or modifying the associated object.","s":"4. Id-only Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#4-id-only-objects","p":624},{"i":637,"t":"A key-specified object is called a key-only object if no properties other than key properties are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(2); }); val book = Book { name = \"GraphQL in Action\" edition = 1 } In hierarchical data structures, any object can have deeper associated objects. If an associated object is a key-only object, it indicates that only the association relationship is being modified, without further creating or modifying the associated object.","s":"5. Key-only Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#5-key-only-objects","p":624},{"i":639,"t":"Although the underlying save commands are very powerful, there is still some way to go before exposing data persistence APIs externally. The documents in this section discuss how to expose data persistence APIs externally.","s":"Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/","h":"","p":638},{"i":641,"t":"When saving associated objects using the association mode AssociatedSaveMode.REPLACE, there is an important concept: dissociation operation.","s":"Dissociation Operations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"","p":640},{"i":643,"t":"Existing Database Structure User's Expected Data Structure +-Food | | | +-----Meat(ignore child nodes) | \\-----Bread(ignore child nodes) +-Food | +-----Drinks(ignore child nodes) | | | \\-----Bread(ignore child nodes) For Bread, it exists in both old and new data structures, corresponding to an UPDATE operation For Drinks, it doesn't exist in the old data structure but exists in the new data, corresponding to an INSERT operation For Meat, it exists in the old data structure but not in the new data, corresponding to an operation called dissociation operation. Dissociation applies to two types of associations: Middle table associations Obviously, middle table associations refer to associations like Book.authors and Author.books in this tutorial. Their dissociation operation is very simple, just deleting the association in the middle table, without affecting the associated objects themselves. Child table associations Child table associations refer to inverse associations based on foreign keys (whether real or fake), such as BookStore.books in this tutorial. Their dissociation operation is relatively complex. Developers can control specific dissociation behavior through configuration. Next, let's discuss these two types of dissociation operations.","s":"Concept","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#concept","p":640},{"i":645,"t":"We've already demonstrated this simplest form of dissociation when introducing the REPLACE save mode for associated objects. Therefore, we won't repeat it here.","s":"Dissociating Middle Table Associations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#dissociating-middle-table-associations","p":640},{"i":647,"t":"Child table associations refer to inverse associations based on foreign keys (whether real or fake), such as BookStore.books. Their dissociation operation is relatively complex. Developers can configure the dissociation mode for properties corresponding to foreign keys (such as Book.store here) to achieve different dissociation behaviors.","s":"Dissociating Child Table Associations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#dissociating-child-table-associations","p":640},{"i":649,"t":"There are 5 modes for child object dissociation operations Mode Description NONE (Default) Depends on global configuration jimmer.default-dissociate-action-checking If jimmer.default-dissociate-action-checking is true (default) or the foreign key upon which the current association is based is real (foreign key constraint exists in database, see Real and Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-checking is false and the foreign key upon which the current association is based is fake (no corresponding foreign key constraint in database, see Real and Fake Foreign Keys), treated as LAX. LAX Dissociation operation performs no action. If the foreign key is real (see Real and Fake Foreign Keys), when parent object is deleted: If cascade delete behavior is configured for the database foreign key (on cascade set null or on delete delete), database automatically clears the foreign key of dissociated child objects or automatically deletes the dissociated child objects Although database-level cascade modification performs better than ORM-level cascade modification, the ORM is unaware of this. Use with caution in projects requiring cache consistency Otherwise, database reports an error and the save command is terminated If the foreign key is fake (see Real and Fake Foreign Keys), when parent object is deleted, no additional behavior occurs, allowing dangling issues with child object foreign key values Even if fake foreign key values are invalid dangling values, jimmer queries won't error - the query system will return null for parent objects rather than error due to non-existent parent CHECK Does not support dissociation operations. Throws exception to prevent operation if current parent object in database has child objects that need to be dissociated. SET_NULL Sets the foreign key of dissociated child objects to null. This mode requires that the child object's foreign key property is nullable; otherwise attempting this configuration will cause an exception. DELETE Deletes the dissociated child objects. There are two ways to configure dissociation mode: Static configuration using annotations on entities, which is global. Dynamic configuration in code, which can override static configuration but only affects the current save command. Taking SET_NULL as an example: Static entity-based configuration (chosen in most cases, used by the majority of business logic) Java Kotlin Book.java @Entity public interface Book { @OnDissociate(DissociateAction.SET_NULL) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity interface Book { @OnDissociate(DissociateAction.SET_NULL) @ManyToOne val store: BookStore? ...omitted other code... } Dynamic save command-based configuration (only for individual save commands, used by very few businesses with special requirements) Java Kotlin sqlClient .getEntities() .saveCommand(book) .setDissociateAction( BookProps.STORE, DissociateAction.SET_NULL ) .execute(); sqlClient.save(book) { setDissociateAction( Book::store, DissociateAction.SET_NULL ) }","s":"Dissociation Modes","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#dissociation-modes","p":640},{"i":651,"t":"Next, let's explain various dissociation modes through saving data structures containing one-to-many association BookStore.books. Here's the save code: Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"O'REILLY\"); draft.addIntoBooks(book -> { book.setName(\"Learning GraphQL\"); book.setEdition(3); book.setPrice(new BigDecimal(\"51.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Learning GraphQL\"); book.setEdition(4); book.setPrice(new BigDecimal(\"43.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Effective TypeScript\"); book.setEdition(3); book.setPrice(new BigDecimal(\"88.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Effective TypeScript\"); book.setEdition(4); book.setPrice(new BigDecimal(\"85.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming TypeScript\"); book.setEdition(3); book.setPrice(new BigDecimal(\"48.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming TypeScript\"); book.setEdition(4); book.setPrice(new BigDecimal(\"47.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"GraphQL in Action\"); book.setEdition(3); book.setPrice(new BigDecimal(\"80.9\")); }); draft.addIntoBooks(book -> { book.setName(\"GraphQL in Action\"); book.setEdition(4); book.setPrice(new BigDecimal(\"81.9\")); }); }) ); sqlClient.saveEntities( stores, // This parameter can be omitted, for the `save` method, // AssociatedSaveMode defaults to REPLACE AssociatedSaveMode.REPLACE ); val stores = listOf( BookStore { name = \"O'REILLY\" books().addBy { name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"51.9\") } books().addBy { name = \"Learning GraphQL\" edition = 4 price = BigDecimal(\"32.9\") } books().addBy { name = \"Effective TypeScript\" edition = 3 price = BigDecimal(\"88.9\") } books().addBy { name = \"Effective TypeScript\" edition = 4 price = BigDecimal(\"85.9\") } books().addBy { name = \"Programming TypeScript\" edition = 3 price = BigDecimal(\"48.9\") } books().addBy { name = \"Programming TypeScript\" edition = 4 price = BigDecimal(\"47.9\") } }, BookStore { name = \"MANNING\" books().addBy { name = \"GraphQL in Action\" edition = 3 price = BigDecimal(\"80.9\") } books().addBy { name = \"GraphQL in Action\" edition = 4 price = BigDecimal(\"81.9\") } } ) sqlClient.saveEntities( stores, // This parameter can be omitted, for the `save` method, // AssociatedSaveMode defaults to REPLACE AssociatedSaveMode.REPLACE ) Comparison between old and new objects: Existing Database Data Data User Wants to Save --+-O'REILLY | +---Learn GraphQL(edition = 1) | +---Learn GraphQL(edition = 2) | +---Learn GraphQL(edition = 3) | | | +---Effective TypeScript(edition = 1) | +---Effective TypeScript(edition = 2) | +---Effective TypeScript(edition = 3) | | | +---Programming TypeScript(edition = 1) | +---Programming TypeScript(edition = 2) | \\---Programming TypeScript(edition = 3) --+-O'REILLY | | | | | +---Learn GraphQL(edition = 3) | +---Learn GraphQL(edition = 4) | | | | | +---Effective TypeScript(edition = 3) | +---Effective TypeScript(edition = 4) | | | | | +---Programming TypeScript(edition = 3) | \\---Programming TypeScript(edition = 4) --+-MANNING | +---GraphQL in Action(edition = 1) | +---GraphQL in Action(edition = 2) | \\---GraphQL in Action(edition = 3) --+-MANNING | | | | | +---GraphQL in Action(edition = 3) | \\---GraphQL in Action(edition = 4) info Among them, the 8 associated objects that are no longer needed, i.e., the 8 objects that need to be dissociated, are highlighted. So, how will Jimmer dissociate these associated objects? In fact, different dissociation configurations will lead to different dissociation behaviors.","s":"Save Code","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#save-code","p":640},{"i":653,"t":"NONE's behavior is not fixed, but depends on the global configuration jimmer.default-dissociate-action-check: If jimmer.default-dissociate-action-check is true (default) or if the current association is based on a real foreign key (foreign key constraint exists in database, see Real vs Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-check is false and the current association is based on a fake foreign key (no corresponding foreign key constraint in database, see Real vs Fake Foreign Keys), treated as LAX.","s":"1. NONE (Default)","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#1-none-default","p":640},{"i":655,"t":"Dissociate mode LAX means the dissociation operation does nothing. Associated save mode AssociatedSaveMode.REPLACE means unnecessary associations need to be discarded. Clearly, these two rules conflict. In this case, AssociatedSaveMode.REPLACE takes precedence, LAX is ignored, and it's ultimately treated as CHECK. Therefore, we cannot demonstrate LAX through this article. To understand how LAX works, please see Delete Command.","s":"2. LAX","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#2-lax","p":640},{"i":657,"t":"CHECK mode does not allow dissociating associated objects. Jimmer will check if there are objects that need to be dissociated, and if they exist, throws an exception. The dissociate mode can be set either through the entity definition or through the save command. Here, we set the dissociate mode for Book.store through entity configuration: Java Kotlin Book.java @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) public interface Book { @OnDissociate(DissociateAction.CHECK) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) interface Book { @OnDissociate(DissociateAction.CHECK) @ManyToOne val store: BookStore? ...omitted other code... } To demonstrate simpler SQL generation, let's assume sqlClient's targetTransferable feature is enabled, which was previously discussed, see here Running the save code from before will generate three SQL statements: Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Saving associations and associated objects is also not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key udpate /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ Check if there are objects that need to be dissociated (if any exist, throws exception to prevent save command) select tb_1_.ID from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and (tb_1_.STORE_ID, tb_1_.ID) not in ( (? /* 1 */, ? /* 3 */), (? /* 1 */, ? /* 100 */), (? /* 1 */, ? /* 6 */), (? /* 1 */, ? /* 101 */), (? /* 1 */, ? /* 9 */), (? /* 1 */, ? /* 102 */), (? /* 2 */, ? /* 12 */), (? /* 2 */, ? /* 103 */) ) limit ? /* 1 */ After this SQL check, some Book objects that will be dissociated are found through the saved BookStore objects' Book.authors property. However, they do not agree to be dissociated and throw the following exception: Save error caused by the path: \".books\": Cannot dissociate child objects because the dissociation action of the many-to-one property \"com.yourcommany.yourproject.model.Book.store\" is not configured as \"set null\" or \"cascade\". There are two ways to resolve this issue: Decorate the many-to-one property \"com.yourcommany.yourproject.model.Bookstore\" by @org.babyfish.jimmer.sql.OnDissociate whose argument is `DissociateAction.SET_NULL` or `DissociateAction.DELETE`, or use save command's runtime configuration to override it","s":"3. CHECK","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#3-check","p":640},{"i":659,"t":"SET_NULL mode achieves dissociation by setting the associated object's foreign key property to null. caution SET_NULL mode requires that the foreign key-based property (here Book.store) must be nullable, otherwise it will cause a compilation error The dissociate mode can be set either through the entity definition or through the save command. Here, we set the dissociate mode for Book.store through entity configuration: Java Kotlin Book.java @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) public interface Book { @OnDissociate(DissociateAction.SET_NULL) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) interface Book { @OnDissociate(DissociateAction.SET_NULL) @ManyToOne val store: BookStore? ...omitted other code... } To demonstrate simpler SQL generation, let's assume sqlClient's targetTransferable feature is enabled, which was previously discussed, see here Running the save code from before will generate three SQL statements: Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Saving associations and associated objects is also not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key udpate /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ Set foreign keys to null for all objects being dissociated H2 MySQL Postgres update BOOK set STORE_ID = null where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ update BOOK set STORE_ID = null where STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and (STORE_ID, ID) not in ( (? /* 1 */, ? /* 3 */), (? /* 1 */, ? /* 100 */), (? /* 1 */, ? /* 6 */), (? /* 1 */, ? /* 101 */), (? /* 1 */, ? /* 9 */), (? /* 1 */, ? /* 102 */), (? /* 2 */, ? /* 12 */), (? /* 2 */, ? /* 103 */) ) update BOOK set STORE_ID = null where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ We can see significant differences between databases: H2 and Postgres use batched simple SQL MySQL uses a single complex SQL info This is because H2 and Postgres support the =any(array) syntax, while MySQL does not.","s":"4. SET_NULL","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#4-set_null","p":640},{"i":661,"t":"DELETE mode achieves dissociation by deleting the associated objects. info Here when saving BookStore, we perform dissociation on the BookStore.books association, where DELETE mode indicates we want to delete unnecessary Book objects. However, since the Book entity has a deeper association Book.authors, we need to consider how to dissociate Author objects before deleting Book objects. In fact, if objects that need to be deleted due to dissociation have deeper associations, it evolves into a recursive deletion problem. This behavior is detailed in Delete Command, which we won't discuss here. Therefore, to simplify the discussion, we'll temporarily ignore the Author entity and assume the current system only has BookStore and Book entity types. The dissociate mode can be set either through the entity definition or through the save command. Here, we set the dissociate mode for Book.store through entity configuration: Java Kotlin Book.java @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) public interface Book { @OnDissociate(DissociateAction.DELETE) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) interface Book { @OnDissociate(DissociateAction.DELETE) @ManyToOne val store: BookStore? ...omitted other code... } To demonstrate simpler SQL generation, let's assume sqlClient's targetTransferable feature is enabled, which was previously discussed, see here Running the save code from before will generate three SQL statements: Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Saving associations and associated objects is also not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key udpate /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ Delete all objects that need to be dissociated H2 MySQL Postgres delete from BOOK where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ delete from BOOK where STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and (STORE_ID, ID) not in ( (? /* 1 */, ? /* 3 */), (? /* 1 */, ? /* 100 */), (? /* 1 */, ? /* 6 */), (? /* 1 */, ? /* 101 */), (? /* 1 */, ? /* 9 */), (? /* 1 */, ? /* 102 */), (? /* 2 */, ? /* 12 */), (? /* 2 */, ? /* 103 */) ) delete from BOOK where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ We can see significant differences between databases: H2 and Postgres use batched simple SQL MySQL uses a single complex SQL info This is because H2 and Postgres support the =any(array) syntax, while MySQL does not.","s":"5. DELETE","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#5-delete","p":640},{"i":663,"t":"caution This is a very crude solution, only for learning or very simple projects. Limitation: Can only save single table data, cannot persist complex data structures. Functionality: Resolves security issue (this issue is discussed in previous doc). Advantage: No need to define Input DTOs. Disadvantage: Does not resolve API ambiguity issue (this issue is discussed in previous doc). Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody Book book ) { if (!ImmutableObjects.isLonely(book)) { throw new IllegalArgumentException(\"The input object is too complex\"); } bookRepository.save(book); } @PutMapping(\"/book\") fun saveBook( @RequestBody book: Book ) { if (!isLonely(book)) { throw IllegalArgumentException(\"The input object is too complex\") } bookRepository.save(input) } This example directly uses the Jimmer dynamic object as the parameter, without restricting the complexity of the passed data structure. But we added a validation to throw an exception if the parameter is not a lonely object, to ensure security. isLonely is used to determine if a dynamic object is just a lonely object. A lonely object can only have two kinds of properties: Scalar properties Association properties based on foreign keys, but can only be assigned null or associated objects with only id property. It is easy to see that the validation in the above code ensures all insert or update operations can only apply to one table. If the developer thinks: Restricting functionality to only modifying one table achieves the security limit needed The other API ambiguity issue is acceptable Then this is indeed a very crude but usable solution.","s":"Lonely Form","u":"/jimmer-doc/docs/mutation/save-command/input-dto/lonely","h":"","p":662},{"i":666,"t":"In the previous article, we introduced how to control the save mode of aggregate root objects. This article will discuss how to control the save mode of associated objects. Associated objects support the following save modes: Association Save Mode Applicable Scope Accept Wild Objects Description APPEND All associations Yes Unconditionally perform INSERT operation on associated objects APPEND_IF_ABSENT All associations No First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, ignore the operation and do nothing Otherwise, insert the associated object note Jimmer will try to utilize the database's native UPSERT capability to combine these two steps. If not possible, it will inform the user why UPDATE All associations Yes If the id property of the associated object is specified, update the associated object by id Otherwise, update the associated object by key MERGE All associations No First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, update it Otherwise, insert the associated object note Jimmer will try to utilize the database's native UPSERT capability to combine these two steps. If not possible, it will inform the user why REPLACE Post associations No Based on MERGE, perform dissociate operation on no longer needed associated objects VIOLENTLY_REPLACE Post associations Yes Make Jimmer no longer search for changes in associations (or association collections) by id or key, but execute the following two operations First delete all old associations and related objects of the current object Then reinsert all associated objects and rebuild associations with the current object This is a very aggressive association update approach with the following pros and cons Pros: Accepts wild associated objects, no longer requires associated objects to either specify id or key Cons: If there are many associated objects, in most cases, this is a low-performance solution If associated objects have deeper associations, the deletion in step 1 may cause too deep cascade deletion, leading to loss of too much data","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#basic-concepts","p":664},{"i":668,"t":"You can set the AssociatedSaveMode for save commands in two ways Set parameters for the save method (this is the simpler choice) Call configuration methods on the save command (this is the more powerful choice) info Jimmer's API design only allows users to choose one of these methods, preventing confusion from having both methods appear simultaneously","s":"Methods with Specified Association Mode","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#methods-with-specified-association-mode","p":664},{"i":670,"t":"Many save methods support this, for example For save, saveEntities and saveInputs, the default AssociatedSaveMode is REPLACE. Now, let's modify it to MERGE. save Java Kotlin Book book = ...omitted...; sqlClient.save(book, AssociatedSaveMode.MERGE); val book = Book { ...omitted... } sqlCient.save(book, AssociatedSaveMode.MERGE); saveEntities Java Kotlin List books = ...omitted...; sqlClient.saveEntities(books, AssociatedSaveMode.MERGE); val books = listOf(...omitted...) sqlCient.saveEntities(books, AssociatedSaveMode.MERGE); saveInputs Java Kotlin List inputs = ...omitted...; sqlClient.saveInputs(inputs, AssociatedSaveMode.MERGE); val inputs = listOf(...omitted...) sqlCient.saveInputs(inputs, AssociatedSaveMode.MERGE); Here, the BookInput class is not an entity type, but rather an automatically generated Input DTO type by Jimmer. This related content hasn't been introduced before, please ignore it for now. Besides save, saveEntities and saveInputs, Jimmer has other shortcut methods, such as insert, insertEntities, insertInputs insertIfAbsent, mergeEntitiesIfAbsent, mergeInputsIfAbsent update, updateEntities, updateInputs merge, mergeEntities, mergeInputs Taking insert, insertEntities and insertInputs as examples, the default AssociatedSaveMode is APPEND. Now, let's modify it to MERGE. insert Java Kotlin Book book = ...omitted...; sqlClient.insert(book, AssociatedSaveMode.MERGE); val book = Book { ...omitted... } sqlCient.insert(book, AssociatedSaveMode.MERGE); insertEntities Java Kotlin List books = ...omitted...; sqlClient.insertEntities(books, AssociatedSaveMode.MERGE); val books = listOf(...omitted...) sqlCient.insertEntities(books, AssociatedSaveMode.MERGE); insertInputs Java Kotlin List inputs = ...omitted...; sqlClient.insertInputs(inputs, AssociatedSaveMode.MERGE); val inputs = listOf(...omitted...) sqlCient.insertInputs(inputs, AssociatedSaveMode.MERGE);","s":"Setting Save Method Parameters","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#setting-save-method-parameters","p":664},{"i":672,"t":"Besides setting save method parameters, we can also modify AssociatedSaveMode by calling configuration methods on the save command. Precisely set AssociatedSaveMode for specific associations Java Kotlin Book book = ...omitted...; sqlClient .saveCommand(book) .setAssociatedMode( BookProps.AUTHORS, AssociatedSaveMode.MERGE ) .execute(); val book = Book { ...omitted... } sqlCient.save(book) { setAssociatedMode( Book::authors, AssociatedSaveMode.MERGE ) } Java Calls the saveCommand method instead of save method, indicating creation of a save command without immediate execution. After configuration with setAssociatedMode, finally calls the execute method to actually execute. Kotlin The syntax is relatively concise, still calling the save method that can directly execute save commands, just with a lambda for additional configuration. Blindly set AssociatedSaveMode for all associations Java Kotlin Book book = ...omitted...; sqlClient .saveCommand(book) .setAssociatedModeAll( AssociatedSaveMode.MERGE ) .execute(); val book = Book { ...omitted... } sqlCient.save(book) { setAssociatedModeAll( AssociatedSaveMode.MERGE ) } Java Calls the saveCommand method instead of save method, indicating creation of a save command without immediate execution. After configuration with setAssociatedModeAll, finally calls the execute method to actually execute. Kotlin The syntax is relatively concise, still calling the save method that can directly execute save commands, just with a lambda for additional configuration. info Obviously, for specific associations, precise configuration has higher priority than blind configuration.","s":"Calling Save Instruction Configuration Methods","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#calling-save-instruction-configuration-methods","p":664},{"i":674,"t":"Unconditionally perform INSERT operations on associated objects Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform INSERT operations on 4 associated objects Assuming after the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */","s":"1. APPEND","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#1-append","p":664},{"i":676,"t":"First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, ignore the operation and do nothing Otherwise, insert the associated object note Jimmer will try to utilize the database's native UPSERT capabilities to combine these two steps. If this is not possible, it will inform the user of the reason Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND_IF_ABSENT ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND_IF_ABSENT ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform INSERT_IF_ABSENT operations on 4 associated objects Assuming: The key for Book objects is Book.name and Book.edition, and the Book entity is annotated with @KeyUniqueConstraint (For MySQL, @KeyUniqueConstraint(noMoreUniqueConstraints = true) is needed) After the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: H2 Mysql Postgres merge into BOOK tb_1_ using(values(?, ?, ?, ?)) tb_2_( NAME, EDITION, PRICE, STORE_ID ) on tb_1_.NAME = tb_2_.NAME and tb_1_.EDITION = tb_2_.EDITION when not matched then insert( NAME, EDITION, PRICE, STORE_ID ) values( tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID ) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert ignore into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do nothing returning ID /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */","s":"2. APPEND_IF_ABSENT","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#2-append_if_absent","p":664},{"i":678,"t":"If the id property of the associated object is specified, update the associated object by id Otherwise, update the associated object by key Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.UPDATE ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.UPDATE ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform INSERT operations on 4 associated objects Assuming after the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: update BOOK set PRICE = ?, STORE_ID = ? where NAME = ? and EDITION = ? /* batch-0: [49.9, 2, SQL in Action, 1] */ /* batch-1: [39.9, 2, LINQ in Action, 1] */ /* batch-2: [44.02, 100, C++ Primer, 5] */ /* batch-3: [71.99, 100, Programming RUST, 1] */","s":"3. UPDATE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#3-update","p":664},{"i":680,"t":"First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, update it Otherwise, insert it note Jimmer will try to utilize the database's native UPSERT capabilities to combine these two steps. If this is not possible, it will inform the user of the reason Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.MERGE ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.MERGE ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform MERGE operations on 4 associated objects Assuming: The key for Book objects is Book.name and Book.edition, and the Book entity is annotated with @KeyUniqueConstraint (For MySQL, @KeyUniqueConstraint(noMoreUniqueConstraints = true) is needed) After the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key(NAME, EDITION) values( ?, ?, ?, ? ) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key update /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */","s":"4. MERGE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#4-merge","p":664},{"i":682,"t":"The MERGE mode performs INSERT or UPDATE operations on associated objects, so after saving, the number of associated objects either remains the same or increases, but never decreases. The REPLACE mode does not have this characteristic because REPLACE performs dissociate operations on no-longer-needed associated objects in addition to the MERGE functionality. The dissociate operation removes associations that the current object no longer needs, for example: Existing Database Structure User's Expected Data Structure +-Food | | | +-----Meat(ignore child nodes) | \\-----Bread(ignore child nodes) +-Food | +-----Drinks(ignore child nodes) | | | \\-----Bread(ignore child nodes) For Bread, it exists in both old and new data structures, corresponding to an UPDATE operation For Drinks, it doesn't exist in the old data structure but exists in the new data, corresponding to an INSERT operation For Meat, it exists in the old data structure but not in the new data, corresponding to an operation called dissociation operation. info The dissociate operation will be explained in detail in subsequent tutorials, so this article provides a highly simplified example Java Kotlin List books = Arrays.asList( Immutables.createBook(book -> { book.setId(1L); book.addIntoAuthors(author -> author.setId(2L)); book.addIntoAuthors(author -> author.setId(3L)); }), Immutables.createBook(book -> { book.setId(2L); book.addIntoAuthors(author -> author.setId(2L)); book.addIntoAuthors(author -> author.setId(4L)); }) ); sqlClient.saveEntities( books, // This parameter can be removed because for the `saveEntities` method, // `AssociatedSaveMode.REPLACE` is the default behavior AssociatedSaveMode.REPLACE ); val books = listOf( Book { id = 1L authors().addBy { id = 2L } authors().addBy { id = 3L } }, Book { id = 2L authors().addBy { id = 2L } authors().addBy { id = 4L } } ) sqlClient.saveEntities( books, // This parameter can be removed because for the `saveEntities` method, // `AssociatedSaveMode.REPLACE` is the default behavior AssociatedSaveMode.REPLACE ) Assuming the existing database structure is shown in the left column of the table below: Existing Database Structure Desired Data Structure to Save --+-Book(1) | +---Author(1) | \\---Author(2) --+-Book(2) | +---Author(1) | \\---Author(2) --+-Book(1) | | | +---Author(2) | \\---Author(3) --+-Book(2) | | | +---Author(2) | \\---Author(4) Obviously, there should be 4 behaviors: Dissociate operations specific to REPLACE: Dissociate the association between Book-1 and Author-1 Dissociate the association between Book-2 and Author-1 Capabilities inherited from MERGE: Create a new association between Book-1 and Author-3 Create a new association between Book-2 and Author-4 Finally, two SQL statements will be generated: The dissociate operation specific to REPLACE mode, removing old associations: H2 Mysql Postgres delete from BOOK_AUTHOR_MAPPING where BOOK_ID = ? and not (AUTHOR_ID = any(?)) /* batch-0: [1, [2, 3]] */ /* batch-1: [2, [2, 4]] */ delete from BOOK_AUTHOR_MAPPING where BOOK_ID in ( ? /* 1 */, ? /* 2 */ ) and (BOOK_ID, AUTHOR_ID) not in ( (? /* 1 */, ? /* 2 */), (? /* 1 */, ? /* 3 */), (? /* 2 */, ? /* 2 */), (? /* 2 */, ? /* 4 */) ) delete from BOOK_AUTHOR_MAPPING where BOOK_ID = ? and not (AUTHOR_ID = any(?)) /* batch-0: [1, [2, 3]] */ /* batch-1: [2, [2, 4]] */ The purpose of this SQL is: For Book-1, delete its associations with Authors other than Author-2 and Author-3 In this case, it means dissociating Book-1 from Author-1 For Book-2, delete its associations with Authors other than Author-2 and Author-4 In this case, it means dissociating Book-2 from Author-1 We can see significant differences between different databases: H2 and Postgres use simple batched SQL MySQL uses a single complex SQL statement info This is because H2 and Postgres support the =any(array) syntax, while MySQL does not. Capabilities inherited by REPLACE mode from MERGE mode to establish new associations H2 Mysql Postgres merge into BOOK_AUTHOR_MAPPING tb_1_ using(values(?, ?)) tb_2_( BOOK_ID, AUTHOR_ID ) on tb_1_.BOOK_ID = tb_2_.BOOK_ID and tb_1_.AUTHOR_ID = tb_2_.AUTHOR_ID when not matched then insert(BOOK_ID, AUTHOR_ID) values(tb_2_.BOOK_ID, tb_2_.AUTHOR_ID) /* batch-0: [1, 2] */ /* batch-1: [1, 3] */ /* batch-2: [2, 2] */ /* batch-3: [2, 3] */ insert ignore into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values(?, ?) /* batch-0: [1, 2] */ /* batch-1: [1, 3] */ /* batch-2: [2, 2] */ /* batch-3: [2, 3] */ insert into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values(?, ?) on conflict(BOOK_ID, AUTHOR_ID) do nothing /* batch-0: [1, 2] */ /* batch-1: [1, 3] */ /* batch-2: [2, 2] */ /* batch-3: [2, 3] */ The REPLACE mode integrates INSERT, UPDATE, and DELETE operations into one, expecting to replace all associated relationships completely (if the association relationship is a deep long association, then it's replacing an entire subtree). However, REPLACE mode has one limitation: it expects objects to either have an id or a key. Because it expects to cleverly find the parts where the new and old data structures have changed through id and key, thereby minimizing the impact range of INSERT, UPDATE, and DELETE operations to achieve maximum performance. tip If readers are familiar with the web domain, it's not hard to see that this is the same principle as specifying the key attribute when using loop rendering in React. In fact, the save command design was inspired by React.","s":"5. REPLACE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#5-replace","p":664},{"i":684,"t":"We've dissucess REPLACE, however, what should we do when dealing with wild objects, i.e., associated objects that have neither id nor key? In this case, we can use the VIOLENTLY_REPLACE mode. Once this mode is adopted, Jimmer no longer looks for changes in associations (or association collections) based on id or key, but performs the following two operations: First, delete all old associations and related objects of the current object Then reinsert all associated objects and rebuild associations with the current object Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.VIOLENTLY_REPLACE ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.VIOLENTLY_REPLACE ) To demonstrate simpler SQL generation, let's assume that the targetTransferable feature of sqlClient is enabled, which was previously introduced, please refer to here Three SQL statements will be generated: Perform UPSERT (insert or update) operations on the two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Delete all old associated objects Assuming after saving the root objects in the previous SQL The id of MANNING is 2 The id of AMAZON is 100 delete from BOOK where STORE_ID in ( ? /* 2 */, ? /* 100 */ ) info If there are other tables in the database that reference the BOOK table through foreign keys, a simple DELETE statement cannot delete all associated objects. To simplify the discussion, let's assume this scenario doesn't exist. Create all new associations and associated objects Assuming after saving the root objects in the previous SQL The id of MANNING is 2 The id of AMAZON is 100 insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ Not comparing old and new data in detail, but simply deleting associated objects and rebuilding them is a very violent mode with the following disadvantages: If there are many associated objects, in most cases, this is a low-performance solution If the associated objects have deeper associations, the deletion behavior in step 1 may lead to too deep cascade deletion, resulting in the loss of too much data caution Therefore, it is not recommended, please use with caution","s":"6. VIOLENTLY_REPLACE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#6-violently_replace","p":664},{"i":686,"t":"The save command provides not only save, saveEntities, and saveInputs methods, but also other shortcut methods for various application scenarios. Different save commands have different default values for AssociatedSaveMode, please refer to this table: Method Default AssociatedSaveMode save REPLACE saveEntities saveInputs insert APPEND insertEntities insertInputs insertIfAbsent APPEND_IF_ABSENT insertEntitiesIfAbsent insertInputsIfAbsent update UPDATE updateEntities updateInputs merge MERGE mergeEntities mergeInputs","s":"Default Mode","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#default-mode","p":664},{"i":688,"t":"Jimmer provides DTO language. Developers can use this language to quickly define the shape of the Input DTO to be saved. After compilation: The corresponding Java/Kotlin Input DTO classes will be generated automatically The mutual conversion logic between Input DTOs and entities will be generated automatically The object fetcher that matches its shape will be automatically generated. (This feature is unrelated to input DTOs, so it is not discussed in this article) Developers use the auto-generated Input DTOs as method parameters, and persist them in one line of code (Internal logic: Call the auto-generated conversion logic to convert the Input DTO to a dynamic entity object, then directly persist using the save command). info This is the most efficient way to eliminate the pain of Input DTO explosion.","s":"Using DTO Language","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"","p":687},{"i":690,"t":"This article focuses on explaining how to save static DTO types, not a systematic introduction to DTO language. Please refer to Object/DTO conversion/DTO Language to know more. Assume the fully qualified name of the Book class is com.yourcompany.yourproject.model.Book. You can: In the project where entity is defined, create directory src/main/dto Under src/main/dto, create subdirectories following the package path of the entity, i.e. com/yourcompany/yourproject/model Under the directory created in previous step, create the file Book.dto. The file must have the same name as the entity class and the extension must be dto. Edit this file and use DTO language to define various DTO shapes for the Book entity: Book.dto input BookInput { #allScalars(Book) id(store) authors { #allScalars(Author) -id } } input SimpleBookInput { ... } ...Other Input DTO shapes omitted... info Input DTO shapes used as input parameters must be decorated with the input modifier. The specific reasons are elaborated in Object/DTO conversion/DTO Language and not repeated here.","s":"Defining DTO Shape","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#defining-dto-shape","p":687},{"i":692,"t":"Jimmer is responsible for compiling dto files and automatically generating DTO types conforming to these shapes. caution If Java/Kotlin source files other than dto files are modified, directly clicking the Run button in IDE can trigger recompilation of dto files. However, if no Java/Kotlin files other than dto files are modified, simply clicking the Run button in IDE will not trigger dto file recompilation unless rebuild is explicitly triggered! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle Take BookInput in the above code as an example. After successful compilation of this dto file, the following DTO types will be auto-generated: Java Kotlin BookInput.java package com.yourcompany.yourproject.model.dto; import com.yourcompany.yourproject.model.Book; import org.babyfish.jimmer.Input; @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookInput implements Input { @Nullable private Long id; ❶ private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; ❷ private List authors; ❸ public BookInput(Book book) { ❹ ... } @Override public Book toEntity() { ❺ ... } @Data public static class TargetOf_authors { private String firstName; private String lastName; private Gender gender; ...Other members omitted... } ...Other members omitted... } BookInput.kt package com.yourcompany.yourproject.model.dto import com.yourcompany.yourproject.model.Book import org.babyfish.jimmer.Input @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookInput( val id: Long? = null, ❶ val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val storeId: Long? = null, ❷ val authors: List = emptyList() ❸ ): Input { constructor(book: Book) : this(...) ❹ override fun toEntity(): Book = ... ❺ data class TargetOf_authors( val firstName: String, val lastName: String, val gender: Gender ) { ...Other members omitted... } ...Other members omitted... } ❶ If the id is designated some auto-generation strategy, it is not required. This is also a feature of save commands, see details in Mutation/Save Command/Save Mode/Summary. info For Jimmer entities, id cannot be null. Missing id (i.e. not assigning it) represents the object does not have an id. For Input DTOs, static POJO types do not have the concept of missing properties. null represents missing id. This seems contradictory, but can be handled simply: If Input DTO's id is null, the converted entity object will not have an id (although id of entity cannot be assigned null, dynamic objects allow unspecified properties). ❷ Explicitly specifies this Input DTO wants to edit the entity's many-to-one association Book.store using the short association mode. ❸ Explicitly specifies this Input DTO wants to edit the entity's many-to-many association Book.authors using the long association mode. The type of associated objects is also fixed to the nested Input DTO type BookInput.TargetOf_authors. ❹ Convert dynamic entity to static Input DTO ❺ Convert static Input DTO to dynamic entity","s":"Auto-Generated DTO Types","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#auto-generated-dto-types","p":687},{"i":694,"t":"The DTO language generates relatively complete code, so we can quickly expose HTTP APIs to persist data: Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody BookInput input ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input); } @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input) }","s":"HTTP API","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#http-api","p":687},{"i":696,"t":"In real projects, we often face the problem that entities may have many properties, and Relatively more properties need to be specified during insertion Relatively fewer properties need to be specified during modification The Book entity we consistently use as example has few properties and is inconvenient to demonstrate this. So I make up an entity type Product with more properties: Java Kotlin Product.java @Entity public interface Product { ...Many entity properties, omitted... } Product.kt @Entity interface Product { ...Many entity properties, omitted... } For insertion which requires specifying relatively more properties, define CreateProductInput. For modification which requires specifying relatively fewer properties, define UpdateProductInput. So the Product.dto code looks like: input CreateProductInput { ...More properties, omitted... } input UpdateProductInput { ...Fewer properties, omitted... } After compilation, CreateProductInput and UpdateProductInput Java/Kotlin classes will be auto-generated. So we can quickly implement the following two HTTP APIs: Java Kotlin @PostMapping(\"/product\") public void createProduct( // `CreateProductInput` has relatively more properties @RequestBody CreateProductInput input ) { productRepository.insert(input); } @PutMapping(\"/product\") public void updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody UpdateProductInput input ) { productRepository.update(input); } @PostMapping(\"/product\") fun createProduct( // `CreateProductInput` has relatively more properties @RequestBody input: CreateProductInput ) { productRepository.insert(input) } @PutMapping(\"/product\") fun updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody input: UpdateProductInput ) { productRepository.update(input) } tip As you can see, no matter how many different Input DTO types need to be defined for the same entity according to project requirements, we can quickly generate Input DTO types and related data conversion logic using DTO language, then persist in one line of code calling save commands. Even if the project is more complex, e.g. people with different identities can edit data structures of different shapes, this pattern can still be applied repeatedly to handle such scenarios easily.","s":"Best Practices","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#best-practices","p":687},{"i":700,"t":"Association id checking is a feature that only applies to short associationslong associations As we learned before, save commands can persist arbitrary data shapes, and any object can further hold associated objects. If the id of an associated object is specified, but the object it represents does not exist in the database, how does Jimmer handle this scenario? First, for long associations Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(3L); draft.addIntoAuthors(author -> author.setId(1L)); // ❶ draft.addIntoAuthors(author -> author.setId(2L)); // ❷ draft.addIntoAuthors(author -> { // ❸ author.setId(1000L); author.setFirstName(\"Svetlana\"); author.setLastName(\"Isakova\"); author.setGender(Gender.FEMALE); }); }) ); sqlClient.update( Book { id = 3L authors().addBy { id = 1L } // ❶ authors().addBy { id = 2L } // ❷ authors().addBy { // ❸ id = 1000L firstName = \"Svetlana\" lastName = \"Isakova\" gender = Gender.FEMALE } } ) This example mixes long associations and short associations. ❶ ❷ They are short associations, specifying invalid ids will lead to errors. ❸ This is a long association, even if an invalid id is specified, Jimmer will automatically create the associated object. The generated SQL is: // Check if associated object exists select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR tb_1_ where tb_1_.ID = ? /* 1000 */ // Associated object does not exist, create it insert into AUTHOR(ID, FIRST_NAME, LAST_NAME, GENDER) values (? /* 1000 */, ? /* Svetlana */, ? /* Isakova */, ? /* F */) // Query current `Book` and `Author` mapping select AUTHOR_ID from BOOK_AUTHOR_MAPPING where BOOK_ID = ? /* 3 */ // Map current `Book` with the newly created `Author` insert into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values (? /* 3 */, ? /* 1000 */) info Therefore, association id checking is a topic that only makes sense for short associations. In the following examples of this article, all discussions are about short associations.","s":"For Short Associations Only","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#for-short-associations-only","p":697},{"i":702,"t":"To discuss the id checking problem of short associations, we first define a concept for associated properties: the target foreign key. For associations based on join tables, the foreign key in the join table that points to the target entity table is the target foreign key. For examples: The target foreign key for Book.authors is the AUTHOR_ID field in the BOOK_AUTHOR_MAPPING table. The target foreign key for Author.books is the BOOK_ID field in the BOOK_AUTHOR_MAPPING table. For associations based on foreign keys, whether the foreign key is fake or not (please refer to Fake Foreign Keys), the foreign key of the association itself is the target foreign key. For example: The target foreign key for Book.store is the STORE_ID field in the BOOK table. If neither of the above two cases apply, the association is considered to not have a target foreign key. Properties without a target foreign key are the ones with mappedBy specified for one-to-one or one-to-many mappings. That is, properties decorated with @OneToOne(mappedBy = \"...\") or @OneToMany(mappedBy=\"...\"). For example: There is no target foreign key for BookStore.books. Summary Association Column of target foreign key Table of target foreign key Book.authors AUTHOR_ID BOOK_AUTHOR_MAPPING Author.books BOOK_ID BOOK_AUTHOR_MAPPING Book.store STORE_ID BOOK BookStore.books NA NA","s":"Concept Definition: Target Foreign Key","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#concept-definition-target-foreign-key","p":697},{"i":704,"t":"Users can configure whether to check the ids of short associated objects. Here, let's not discuss how to configure for now, but look at whether enabling this configuration has any impact on Jimmer's behavior. Properties without target foreign keys Take BookStore.books as an example. The code to save a short association is: Java Kotlin sqlClient.update( Immutables.createBookStore(draft -> { draft.setId(2L); draft.addIntoBooks(book -> book.setId(8L)); draft.addIntoBooks(book -> book.setId(9L)); draft.addIntoBooks(book -> book.setId(1000L)); draft.addIntoBooks(book -> book.setId(1001L)); }) ); sqlClient.update( BookStore { id = 2L books().addBy { id = 8L } books().addBy { id = 9L } books().addBy { id = 1000L } books().addBy { id = 1001L } } ); Without checking Properties without a target foreign key will automatically ignore associated objects with illegal ids. For example: update book set store_id = 2 where id in(1, 2, 1000, 10001) If 1000 and 10001 are ids that do not exist in the database, this update statement will only affect the two existing records, and the two non-existing records will be naturally ignored. With checking Jimmer will execute the following query to check all short associated ids: select tb_1_.ID from BOOK tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */, ? /* 1000 */, ? /* 1001 */ ) If ids 1000 and 1001 do not exist in the database, the following exception will be thrown: Save error caused by the path: \".books\": Illegal ids: [1000, 1001] Properties with target foreign keys Take Book.store as an example. The code to save a short association is: Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(10L); draft.applyStore(store -> store.setId(321L)); }) ); sqlClient.update( Book { id = 10L store { id = 321L } } ); Assume id 321 does not exist for BookStore in the database. Without checking If the foreign key is fake, there is no real foreign key constraint in the database, and Jimmer will allow BOOK.STORE_ID to be modified to an illegal value. If the foreign key is real, there is a real foreign key constraint in the database, and the underlying database will throw an error eventually. With checking Regardless of whether the foreign key is fake or not, Jimmer will execute the following query to check the short associated id: select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID in ( ? /* 321 */ ) Once the query returns no data, the following exception will be thrown: Save error caused by the path: \".store\": Illegal ids: [321] Summary Real target foreign key Fake target foreign key No target foreign keys Without checking Error from database Save wrong data Ignore invalid operations With checking Error from Jimmer Error from Jimmer Error from Jimmer info As you can see, for properties with a real target foreign key, exceptions will be thrown regardless of whether Jimmer's short association id checking is enabled. Without checking, the database throws the error. Advantage: Avoid an extra SQL query Disadvantage: Less control over the exception message and type. With checking, Jimmer throws the error. Advantage: clear exception message and type. Disadvantage: An extra SQL query. tip It is recommended to turn on this checking mechanism for all properties if your project does not have extreme performance requirements, in order to get ideal exception information (we will introduce how to configure it later).","s":"Checking Mechanism","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#checking-mechanism","p":697},{"i":706,"t":"Users can configure whether to check associated ids for properties. There are global configuration and command-level configuration.","s":"Configuration","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#configuration","p":697},{"i":708,"t":"The global configuration provides three levels: NONE FAKE ALL The behaviors are: Real target foreign key Fake target foreign key No target foreign keys NONE No checking No checking No checking FAKE No checking Checking Checking ALL Checking Checking Checking There are two ways to configure globally: Via Spring Boot Starter configuration Modify application.yml (or application.properties) and add the following: jimmer: id-only-target-checking-level: ALL Via low-level API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setIdOnlyTargetCheckingLevel(IdOnlyTargetCheckingLevel.ALL) ...other configurations omitted... .build(); val sqlClient = newKSqlClient { setIdOnlyTargetCheckingLevel(IdOnlyTargetCheckingLevel.ALL) ...other configurations omitted... }","s":"Global Configuration","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#global-configuration","p":697},{"i":710,"t":"The command-level configuration can override the global configuration, but only affects the current save command. There are three features for command-level configuration: Explicitly specify properties to check Java Kotlin Book book = ... sqlClient .getEntities() .saveCommand(book) .setAutoIdOnlyTargetChecking(BookProps.STORE) .setAutoIdOnlyTargetChecking(BookProps.AUTHORS) .execute(); val book = ... sqlClient.save(book) { setAutoIdOnlyTargetChecking(Book::store) setAutoIdOnlyTargetChecking(Book::authors) } info If the global configuration already enables checking, no need to adjust the save command like this. Specify all properties to check Java Kotlin Book book = ... sqlClient .getEntities() .saveCommand(book) .setAutoIdOnlyTargetCheckingAll() .execute(); val book = ... sqlClient.save(book) { setAutoIdOnlyTargetCheckingAll() } info If the global configuration already enables checking, no need to adjust the save command like this. Negative configuration, explicitly specify properties to not check Java Kotlin Book book = ... sqlClient .getEntities() .saveCommand(book) .setAutoIdOnlyTargetCheckingAll() .setAutoIdOnlyTargetChecking(BookProps.STORE, false) .execute(); val book = ... sqlClient.save(book) { setAutoIdOnlyTargetCheckingAll() setAutoIdOnlyTargetChecking(Book::authors, false) }","s":"Command-Level Configuration","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#command-level-configuration","p":697},{"i":712,"t":"In this article we discuss: The problem of using dynamic entities as method parameters Solutions Comparison with GraphQLInput","s":"Problem","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"","p":711},{"i":714,"t":"Up to this point, we have systematically explained all the capabilities of save command. Now we know that no matter what shape the data structure to be saved is, we can persist it to the database in one line of code calling save command, with all internal details hidden. This is a very convenient low-level capability. However, how should the upper layer APIs of business systems be designed? Should we directly accept dynamic objects via @RequestBody? Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody Book book ) { bookRepository.save(book); } @PutMapping(\"/book\") fun saveBook( @RequestBody book: Book ) { bookRepository.save(book) } This code can work, allowing HTTP clients to submit data structures of arbitrary shapes. This seems to be an extremely powerful capability. However, this approach has two problems: Security issue API ambiguity","s":"Problem of Dynamic Entities Parameters","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#problem-of-dynamic-entities-parameters","p":711},{"i":716,"t":"The client is granted too much power, being able to submit very deep and wide tree-shaped data structures that far exceed its allowed scope of modification under current security policies. This is a huge security vulnerability. For example, the client can totally submit data like: { \"name\": \"SQL in Motion\", \"edition\": 1, \"price\": 41.99, \"store\":{ \"name\": \"MANNING\", \"location\": { \"city\": \"Vancouver\", \"country\": \"Canada\", ... } }, \"authors\":[ { \"firstName\": \"Ben\", \"lastName\": \"Brumm\", \"job\":{ \"company\": { \"name\": \"IBM\" }, \"title\": \"Senior HR Manager\", ... } ... } ] } Assume your intention in providing this HTTP API is that only the BOOK, BOOK_STORE, AUTHOR and BOOK_AUTHOR_MAPPING tables can be affected. However, now the scope of data submitted by the client is too large, with far greater destructive power than you anticipated. In the above example, there are at least 4 unexpected destructions: .store.location.city is modified from New York to Vancouver .store.location.country is modified from USA to Canada .authors[0].job.company is modified from NAB to IBM .authors[0].job.title is modified from Senior Business Analyst to Senior HR Manager warning Using @RequestBody to directly accept dynamic objects as input parameters in external APIs is very dangerous and will lead to serious security issues. Therefore, save commands must be sealed internally as a low-level capability, and their raw capabilities must absolutely not be directly exposed through HTTP APIs.","s":"Security Issue","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#security-issue","p":711},{"i":718,"t":"Using dynamic objects as parameters leads to ambiguity in the API. Client developers do not know which fields are decided automatically by the business system and which must be specified by themselves, so they do not know how to invoke the API properly. This issue is especially obvious for insert operations. Unlike update operations which can modify just a few properties, insert operations often need to specify many properties, otherwise exceptions will occur. Client developers are unclear about exactly which properties must be specified to avoid errors.","s":"API Ambiguity","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#api-ambiguity","p":711},{"i":720,"t":"To resolve this issue, Jimmer provides three solutions: Lonely Form caution This is a very crude solution, only for learning or very simple projects. This solution only handles data persistence operations on a single table, and only resolves the security issue rather than the API ambiguity issue. It is also the only solution that does not require defining Input DTOs. Auto-Generated Input DTOs via DTO Language This solution quickly auto-generates Input DTOs with very little cost. It is a complete and extremely convenient solution, so is the recommended approach. Its huge convenience advantage will be introduced later. info All built-in examples use this solution. Manual Input DTOs via MapStruct This solution requires developers to manually create Input DTOs and handle conversion to dynamic objects. It is absolutely flexible, but requires a lot of work from developers.","s":"Solutions","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#solutions","p":711},{"i":722,"t":"The above introduces three solutions. Among them, although the latter two solutions differ greatly, they share one commonality - relying on Input DTOs. Comparing Jimmer's Input DTOs with GraphQLInput: Similarities In GraphQL, query results are GraphQLObjects, i.e. dynamic objects of arbitrary shapes. However, if mutation operations accept object parameters, they must be GraphQLInputs, i.e. static objects of fixed shapes. GraphQLInput has exactly the same idea as InputDTO here, which is the inevitable design to resolve security issues - different routes leading to the same destination. Differences GraphQLInput is just a protocol, merely constraining that object parameters for modification operations must be static objects of fixed shapes. The benefit is not limiting specific implementation technologies, but the downside is the persistence business logic needs to be implemented by developers for every specific GraphQLInput shape. Tedious work still exists objectively, and developers can truly feel the pain of Input DTO explosion. Jimmer's InputDTO is just an alternative representation of the dynamic entity to address security issues. Once the user finishes converting Input DTO to dynamic entity, the huge convenience of persisting arbitrary shaped data structures in one line of code via save commands can still be enjoyed. If developers adopt the Auto-Generated Input DTOs via DTO Language solution, Input DTO classes will be auto-generated, and the conversion logic between Input DTOs and dynamic entities will also be auto-generated. Thus the pain of Input DTO explosion no longer exists. So this is the recommended solution.","s":"Comparison with GraphQLInput","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#comparison-with-graphqlinput","p":711},{"i":724,"t":"caution Not recommended for Kotlin. This solution is based on MapStruct, which relies on apt. Kotlin has deprecated kapt in favor of ksp. So as Kotlin evolves, using kapt may cause more and more problems in the future.","s":"Using MapStruct","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"","p":723},{"i":726,"t":"Let's look at an example InputDTO (for simplicity, Java version uses Lombok): Java Kotlin BookInput.java @Data public class BookInput { @Nullable private Long id; ❶ private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; ❷ private List authors; ❸ @Data public static class AuthorItem { private String firstName; private String lastName; private Gender gender; } } BookInput.kt data class BookInput( val id: Long? = null, ❶ val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, ❷ val authors: List ❸ ) { data class AuthorItem( val firstName: String, val lastName: String, val gender: Gender ) } ❶ If the id is designated some auto-generation strategy, it is not required. This is also a feature of save commands, see details in Save Modes/Summary. info For Jimmer entities, id cannot be null. Missing id (i.e. not assigning it) represents the object does not have an id. For Input DTOs, static POJO types do not have the concept of missing properties. null represents missing id. This seems contradictory and difficult to convert between. Don't worry, Jimmer provides automated solutions, discussed later. ❷ Explicitly specifies this Input DTO wants to edit the entity's many-to-one association Book.store using the short association mode. ❸ Explicitly specifies this Input DTO wants to edit the entity's many-to-many association Book.authors using the long association mode. The type of associated objects is also fixed to the nested Input DTO type BookInput.AuthorItem.","s":"Define Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#define-input-dto","p":723},{"i":728,"t":"Jimmer extends MapStruct which can be used to handle conversions between dynamic entities and static Input DTOs. How to use the relevant extensions is detailed in Object/DTO Conversion/MapStruct, this article will not repeat it. Define the BookInputMapper interface: Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); ...Other mapstruct configurations omitted... } BookInputMapper.kt @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(BookInput input): Book ...Other mapstruct configurations omitted... } info MapStruct's annotation processor needs to be used to generate the implementation class for this interface at compile time. Details are explained in Object Section/DTO Mapping/MapStruct and not repeated here.","s":"MapStruct Converter","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#mapstruct-converter","p":723},{"i":730,"t":"Java Kotlin private static final BookInputMapper BOOK_INPUT_MAPPER = Mappers.getMapper(BookInputMapper.class); @PutMapping(\"/book\") public void saveBook( @RequestBody BookInput input ) { bookRepository.save( BOOK_INPUT_MAPPER.toBook(input) ); } @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ) { bookRepository.save( BOOK_INPUT_MAPPER.toBook(input) ) companion object { private val BOOK_INPUT_MAPPER = Mappers.getMapper(BookInputMapper::class.java) } } In this example, MapStruct is used to convert BookInput to Book entity and directly persist it. info For Jimmer entities, Book.id cannot be null. Missing id (i.e. not assigning it) represents the object does not have an id. For Input DTO, static POJO type, BookInput.id being null represents missing id. Jimmer has built-in extensions to MapStruct that will not assign BookInput.id to Book.id if it is null, so there are no issues.","s":"HTTP API","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#http-api","p":723},{"i":732,"t":"To better integrate with Jimmer, developers can make BookInput implement the org.babyfish.jimmer.Input interface: public interface Input { E toEntity(); } Dynamic objects will never implement this interface. It should be implemented by user-defined static POJO classes. Its functionality is simple: convert the current static POJO to a dynamic object. Make BookInput implement Input: Java Kotlin BookInput.java @Data public class BookInput implements Input { private static final Converter CONVERTER = Mappers.getMapper(Converter.class); ...Private fields omitted... @Override public Book toEntity() { return CONVERTER.toBook(this); } @Mapper interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); ...Other mapstruct configurations omitted... } ...AuthorItem definition omitted... } BookInput.kt data class BookInput( ... ) : Input { override fun toEntity(): Book = CONVERTER.toBook(this) @Mapper internal interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(input: BookInput): Book ...Other mapstruct configurations omitted... } companion object { @JvmStatic private val CONVERTER = Mappers.getMapper(Converter::class.java) } ...AuthorItem definition omitted... } info In this improved example, the previously introduced BookInputMapper is replaced by BookInput.Converter, so the previous BookInputMapper can be deleted. Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody BookInput input ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input); } @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input) } info Leveraging the Input interface to change coding style is recommended but not mandatory.","s":"Improvement","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#improvement","p":723},{"i":734,"t":"In real projects, we often face the problem that entities may have many properties, and Relatively more properties need to be specified during insertion Relatively fewer properties need to be specified during modification The Book entity we consistently use as example has few properties and is inconvenient to demonstrate this. So I make up an entity type Product with more properties: Java Kotlin Product.java @Entity public interface Product { ...Many entity properties, omitted... } Product.kt @Entity interface Product { ...Many entity properties, omitted... } For insertion which requires specifying relatively more properties, define CreateProductInput: Java Kotlin CreateProductInput.java @Data public class CreateProductInput implements Input { ...More fields, omitted... @Override public Product toEntity() { ... } } CreateProductInput.kt data class CreateProductInput( ...More fields, omitted... ) : Input { override fun toEntity(): Product { ... } } For modification which requires specifying relatively fewer properties, define UpdateProductInput: Java Kotlin UpdateProductInput.java @Data public class UpdateProductInput implements Input { ...Fewer fields, omitted... @Override public Product toEntity() { ... } } UpdateProductInput.kt data class UpdateProductInput( ...Fewer fields, omitted... ) : Input { override fun toEntity(): Product { ... } } Finally, provide two HTTP APIs: Java Kotlin @PostMapping(\"/product\") public void createProduct( // `CreateProductInput` has relatively more properties @RequestBody CreateProductInput input ) { productRepository.insert(input); } @PutMapping(\"/product\") public void updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody UpdateProductInput input ) { productRepository.update(input); } @PostMapping(\"/product\") fun createProduct( // `CreateProductInput` has relatively more properties @RequestBody input: CreateProductInput ) { productRepository.insert(input) } @PutMapping(\"/product\") fun updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody input: UpdateProductInput ) { productRepository.update(input) } tip As you can see, no matter how many different Input DTO types need to be defined for the same entity according to project requirements, we can always use MapStruct to convert them into the uniform dynamic entity type, then persist in one line of code calling save commands. Even if the project is more complex, e.g. people with different identities can edit data structures of different shapes, this pattern can still be applied repeatedly to handle such scenarios easily.","s":"Best Practices","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#best-practices","p":723},{"i":736,"t":"Input DTO is used for data input, so it provides powerful control over nullable properties in the objects submitted by the client, and standardizes this capability.","s":"Handle Null Values","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"","p":735},{"i":739,"t":"One of the most important features of Jimmer entities is the strict distinction between unknown data (not specifying object properties) and no data (setting object properties to null). Let's temporarily set aside the concept of Input DTO and review the differences when directly saving data using Jimmer entities. Setting nullable property to null Java Kotlin Book book = BookDraft.$.produce(draft -> { draft.setId(12L); draft.setName(\"TURING\"); draft.setStoreId(null); }); sqlClient.update(book); val book = Book { id = 12L name = \"TURING\" storeId = null } sqlClient.update(book); The following SQL is generated: update BOOK set NAME = ?, /* TURING */ STORE_ID = ? /* */ where ID = ? /* 12 */` As you can see, by explicitly setting the object's property to null and executing the save command with an update operation, the value in the database will be updated to null. Not specifying nullable property at all Java Kotlin Book book = BookDraft.$.produce(draft -> { draft.setId(12L); draft.setName(\"TURING\"); // `storeId` is not specified }); sqlClient.update(book); val book = Book { id = 12L name = \"TURING\" // `storeId` is not specified } sqlClient.update(book); The following SQL is generated: update BOOK set NAME = ? /* TURING */ /* `STORE_ID` is not updated */ where ID = ? /* 12 */` As you can see, by not setting the object's property and executing the save command with an update operation, the value in the database will not be updated. info This distinction is very important. In the subsequent content of this article, we will no longer discuss what SQL statements the ORM generated because we only need to focus on what the entity object obtained from the conversion of the Input DTO is.","s":"Review: Directly Saving Entity Objects","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#review-directly-saving-entity-objects","p":735},{"i":741,"t":"Now, let's define an Input DTO: input BookUpdateInput { id! name id(store) } For more details on the DTO language, please refer to the relevant chapter. Here, we focus on the Java/Kotlin code automatically generated by the Jimmer pre-compiler based on this DTO code. The generated code is as follows: Java Kotlin BookUpdateInput.java @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookUpdateInput implements Input { private long id; private String name; @Nullable private Long storeId; @Override public Book toEntity() { ...omitted... } ...other members omitted... } BookUpdateInput.kt @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookUpdateInput( val id: Long, val name: String, val storeId: Long? = null ) { override fun toEntity(): Book = ...omitted... ...other members omitted... } In the original entity, the associated property Book.store is nullable. The DTO code does not change this here, so in the generated classes, the field storeId is also nullable. If the storeId property of the BookUpdateInput object uploaded by the user is null, is the user's intention to update the corresponding foreign key STORE_ID in the database to null, or not to update it at all? In fact, both of these intentions are common. For a long time, developers have been very casual about the conventions for these two behaviors, and even if the API documentation mentions such details, the format is also very casual. This has led to difficulties in communication and understanding and has caused lasting damage to the industry. Input DTO provides a standardized definition for this issue, aiming to handle different intentions in a standardized manner.","s":"Issues Faced by Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#issues-faced-by-input-dto","p":735},{"i":743,"t":"To solve the problem raised above, the DTO language specifies that if a DTO property satisfies both of the following conditions: It is defined in an input type It allows null values Then, a modifier representing the null handling mode can be added to the DTO property: it can be fixed, static, dynamic, or fuzzy. For convenience in the subsequent discussion, let's assume that the following Web Controller exists: Java Kotlin @RestController public class BookController { @PutMapping(\"/book\") public void update( @RequestBody BookUpdateInput input ) { Book book = input.toEntity(); System.out.println(book); ...subsequent code omitted... } ...other members omitted... } @RestController class BookController { @PutMapping(\"/book\") fun update( @RequestBody input: BookUpdateInput ) { val book = input.toEntity() println(book) ...subsequent code omitted... } ...other members omitted... } Here, we convert the Input DTO object uploaded by the user into a Jimmer entity and print it out. We only need to focus on the print result, as mentioned earlier, we only need to focus on what the entity object obtained from the conversion of the Input DTO is, and we do not need to discuss what SQL statements the ORM will generate. Therefore, the subsequent code is not important and is omitted.","s":"4 Ways to Handle Nullable Properties","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#4-ways-to-handle-nullable-properties","p":735},{"i":745,"t":"DTO code example: input BookUpdateInput { id! name fixed id(store) } This mode can also be called the super static mode. It does not allow the user to submit an Input DTO without specifying certain properties. Even if they want a property to be null, they need to explicitly specify it. If the property of the Input DTO is null, the corresponding property of the obtained Jimmer entity object will also be set to null, effectively modifying the corresponding field in the database to null. Two ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' This request will be rejected, HTTP error code 400, parameter error. If you check the Java log, you will see the following error: Resolved [org.springframework.http.converter.HttpMessageNotReadableException: JSON parse error: Cannot construct instance of `org.doc.j.model.dto.BookUpdateInput$Builder`, problem: An object whose type is \"org.doc.j.model.dto.BookUpdateInput\" cannot be deserialized by Jackson. The current type is fixed input DTO so that all JSON properties must be specified explicitly, however, the property \"storeId\" is not specified by JSON explicitly. Please either explicitly specify the property as null in the JSON, or specify the current input properties as static, dynamic or fuzzy in the DTO language] tip If developer use the Automatic TypeScript Generation feature in Jimmer, the generated typeScript code will require web developers to provide the storeId property for the BookUpdateInput object, otherwise client code cannot be compiled successfully.","s":"1. fixed","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#1-fixed","p":735},{"i":747,"t":"DTO code example: input BookUpdateInput { id! name static id(store) } When submitting an Input DTO, the user can either set the storeId property to null or not specify it at all. Regardless of the user's choice, the behavior remains the same: the corresponding property of the obtained Jimmer entity object will definitely be set to null, effectively modifying the corresponding field in the database to null. Two ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. info The effects of the two operations are the same, and the final effect is only affected by the DTO shape, regardless of whether the user specified the DTO property or not.","s":"2. static","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#2-static","p":735},{"i":749,"t":"DTO code example: input BookUpdateInput { id! name dynamic id(store) } If the user chooses to set the storeId property of the DTO to null, then the storeId property of the final obtained Jimmer entity object will also be null, effectively modifying the corresponding field in the database to null. If the user does not set the storeId property of the DTO at all, then the storeId property of the final obtained Jimmer entity object will also not be set, so the corresponding field in the database will not be updated. Two ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", // There is no storeId property here } That is, subsequent operations will not update the corresponding field in the database. info The two ways of submitting data correspond to two completely different behaviors, suitable for professional client teams to have flexible control over the service behavior.","s":"3. dynamic","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#3-dynamic","p":735},{"i":751,"t":"warning This mode sacrifices functionality for conservativeness and safety, and is the only mode with incomplete functionality. DTO code example: input BookUpdateInput { id! name fuzzy id(store) } If the user sets the storeId property of the DTO object to a non-null value, then the storeId property of the final obtained Jimmer entity object will be set accordingly, effectively modifying the corresponding field in the database to the specified value. Otherwise (whether the storeId property of the DTO object is set to null or not specified at all), the storeId property of the final obtained Jimmer entity object will not be set, so the corresponding field in the database will not be updated. Three ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", // There is no storeId property here } That is, subsequent operations will not update the corresponding field in the database. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", // There is no storeId property here } That is, subsequent operations will not update the corresponding field in the database. Submit an Input DTO with the storeId property set to a non-null value The previous two ways cannot modify the corresponding field in the database unless a non-null value is specified, as follows: curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": 2 }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":3 } info This mode sacrifices the ability to modify the corresponding field in the database to null in exchange for absolute conservativeness and safety. It is particularly suitable for client teams with less experience.","s":"4. fuzzy","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#4-fuzzy","p":735},{"i":753,"t":"In the examples above, the keywords fixed, static, dynamic, and fuzzy were used to modify the nullable properties of the Input DTO. Field-level control is the most fine-grained. However, if there are many nullable properties in the Input DTO, configuring them one by one may be cumbersome. Jimmer provides configuration methods with a broader scope of influence: Input type level dynamic input XxxInput { fixed nullableProp1 static nullableProp2 nullableProp3 fuzzy nullableProp4 nullableProp5 } Here, the null handling mode is not declared for nullableProp3 and nullableProp5, and they will share the configuration at the input type level (in this case, dynamic). Precompiler level If no configuration is found at the input type level, refer to the global configuration parameter jimmer.dto.defaultNullableInputModifier of the precompiler (for Java, it is APT; for Kotlin, it is KSP). Java(Maven) Java(Gradle) Kotlin(Gradle.kts) org.apache.maven.plugins maven-compiler-plugin 3.13.0 -Ajimmer.dto.defaultNullableInputModifier=fixed tasks.withType().configureEach { options.compilerArgs.add(\"-Ajimmer.dto.defaultNullableInputModifier=fixed\") } ksp { arg(\"jimmer.dto.defaultNullableInputModifier\", \"fixed\") } Final default mode If no configuration is provided at the precompiler level either, the final default is static. info Configurations at different levels may conflict, and the priorities among them are: Input property level config > Input type level config > Precompiler global config > Final default static","s":"Higher-Level Configurations","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#higher-level-configurations","p":735},{"i":755,"t":"caution For the fixed and dynamic modes, Jimmer requires the server-side to use Jackson for deserialization. Therefore, if you plan to use the fixed or dynamic mode, please: Add @RequestBody If you carefully look at the examples in this article, you will notice that @RequestBody was used there. Do not replace the Jackson Message Converter enabled by default in Spring Boot. In fact, not only the Input DTOs using the fixed or dynamic mode discussed in this article have this requirement; if the user needs to use the serialization/deserialization of Jimmer entities themselves, Jackson is also required. Jackson is carefully designed to strike the perfect balance between functionality and performance. Therefore, Jimmer regards Jackson as an essential infrastructure.","s":"Caveats","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#caveats","p":735},{"i":758,"t":"The result returned by a save command is an object, e.g. SimpleSaveResult/KSimpleSaveResult for the save method that saves a single object. The result supports the following behaviors: originalEntity property: Returns the original parameter passed to the save method by the developer. modifiedEntity property: A data structure identical in shape to originalEntity, with the differences: If originalEntity contains some objects without id properties that rely on id generation strategies (e.g. auto increment, sequence, UUID, snowflake id etc.), the corresponding objects in modifiedEntity will necessarily have the id property set to the value automatically assigned by the database/application. If some objects belong to entity types with optimistic locking fields, the version properties of the corresponding objects in modifiedEntity will have the latest version number after modification. info modifiedEntity is discussed many times in previous docs, so is not elaborated here. totalAffectedRowCount property: The execution of a save command may modify multiple tables in the database. This property summarizes the total number of affected rows across all modified tables. getAffectedRowCountMap property: A map of affected tables and their affected row counts. getAffectedRowCount method, taking a parameter to get the affected row count of the specified table. Accepts two kinds of parameters: Entity type: Gets affected row count of the table corresponding to this entity type. Association property based on join table: Gets affected row count of the join table corresponding to this association property. Let's look at some examples of the totalAffectedRowCount property and getAffectedRowCount method: Java Kotlin SimpleSaveResult result = sqlClient.update( Immutables.createBook(draft -> { draft.setId(3L); draft.setPrice(new BigDecimal(\"59.9\")); draft.addIntoAuthors(author -> author.setId(1L)); draft.addIntoAuthors(author -> author.setId(3L)); draft.addIntoAuthors(author -> { author.setId(1000L); // does not exist, created automatically author.setFirstName(\"Svetlana\"); author.setLastName(\"Isakova\"); author.setGender(Gender.FEMALE); }); }) ); System.out.println( \"Total affected row count: \" + result.getTotalAffectedRowCount() ); System.out.println( \"Affected row count for entity table BOOK: \" + result.getAffectedRowCount(Book.class) ); System.out.println( \"Affected row count for entity table AUTHOR: \" + result.getAffectedRowCount(Author.class) ); System.out.println( \"Affected row count for join table BOOK_AUTHOR_MAPPING: \" + result.getAffectedRowCount(BookProps.AUTHORS) ); val result = sqlClient.update( Book { id = 3L price = BigDecimal(\"59.9\")) authors().addBy { id = 1L } authors().addBy { id = 3L } authors().addBy { id = 1000L // does not exist, created automatically firstName = \"Svetlana\" lastName = \"Isakova\" gender = Gender.FEMALE } } ); println( \"Total affected row count: \" + result.totalAffectedRowCount ) println( \"Affected row count for entity table BOOK: \" + result.getAffectedRowCount(Book::class) ) println( \"Affected row count for entity table AUTHOR: \" + result.getAffectedRowCount(Author::class) ) println( \"Affected row count for join table BOOK_AUTHOR_MAPPING: \" + result.getAffectedRowCount(Book::authors) ) tip The code getAffectedRowCount(BookProps.AUTHORS) is equivalent to getAffectedRowCount(AuthorProps.BOOKS) The printed result is: Total affected row count: 5 Affected row count for entity table BOOK: 1 Affected row count for entity table AUTHOR: 1 Affected row count for join table BOOK_AUTHOR_MAPPING: 3 The explanation is: The affected row count for table BOOK is 1: The price of the aggregate root object Book(id=3L) is modified. The affected row count for table AUTHOR is 1: The associated object Author(id=1000L) does not exist and is created automatically. The affected row count for table BOOK_AUTHOR_MAPPING is 3: Dissociation between Book(id=3L) and Author(id=2L) (For dissociation operations on join tables, this is deleting the association). New association between Book(id=3L) and Author(id=3L). New association between Book(id=3L) and Author(id=1000L).","s":"Save Command Result","u":"/jimmer-doc/docs/mutation/save-command/other","h":"#save-command-result","p":756},{"i":761,"t":"In daily project development, there is a very challenging issue: translating database constraint violation errors into user-friendly error messages. Based on constraints that cannot be simply validated through input validation, databases have three types of constraints that are difficult to handle when violated: Primary key constraints Unique constraints (or unique indexes) Foreign key constraints To standardize across different database products, the SQL standard specifies that errors caused by constraint violations have the category code 23 (integrity constraint violation). All related error states begin with 23. However, standardization ends there. For more detailed issues, such as: Which constraint was violated How to get the table name and column name from the database dictionary based on the constraint name Most importantly, which data row modification action caused the exception Different database products behave inconsistently and lack clear APIs to obtain this information. To provide users with clear error descriptions, many business projects adopt a simple but crude method: pre-checking through queries However, this pre-checking approach has many disadvantages: Developers need to write various pre-checking code repeatedly, leading to high development costs Only suitable for simple single-record DML modifications, completely unsuitable for advanced operations like save commands that recursively save deep data structures in batch Poor performance, as errors are rare events, and pre-checking every time is wasteful Therefore, Jimmer adopts the following strategy: Uses post-investigation approach, directly modifying the database first, and if constraint violation errors are reported, investigating the cause afterward During error investigation, uses queries to gather as much information as possible, reporting: The path of the illegal object in the saved data structure The entity type and related properties that caused the error The specific object and related data that caused the error Allows users to customize exception translators to further translate Jimmer's investigated exceptions into end-user friendly messages info The database error investigation can occur due to either root object save failure or associated object save failure. Jimmer treats both cases equally, without distinction. However, to simplify the documentation, the examples in this article demonstrate saving relatively simple objects, avoiding deep data structures (in fact, if saving deep associated objects fails, it will be investigated the same way).","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#basic-concepts","p":759},{"i":763,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(100L); draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"59.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(7L); // Exists draft.setName(\"LINQ in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }) ); sqlClient.insertEntities(books); val books = listOf( Book { id = 100L name = \"SQL in Action\" edition = 1 price = BigDecimal(\"59.9\") storeId = 2L }, Book { id = 7L // Exists name = \"LINQ in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L } ) sqlClient.insertEntities(books) This code will generate the following two SQL statements: Batch insert data insert into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) /* batch-0: [100, SQL in Action, 1, 59.9, 2] */ /* batch-1: [7, LINQ in Action, 3, 49.9, 2] */ Here, inserting the second record will cause an id conflict Investigate the cause of the constraint violation Most Databases Postgres Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK tb_1_ where tb_1_.ID = ? /* 7 */ Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK tb_1_ where tb_1_.ID = any(? /* [100, 7] */) For most databases, the original JDBC exception information from the batch SQL can determine which record violated the constraint, so only the problematic record is investigated For Postgres, the original JDBC exception information from the batch SQL cannot determine which record violated the constraint, so all records are investigated Either way, Jimmer can investigate and identify the problem. Finally, Jimmer will throw an exception based on the investigation results: org.babyfish.jimmer.sql.exception.SaveException$NotUnique: Save error caused by the path: \"\": Cannot save the entity, the value of the id property \"com.yourcompany.yourpoject.model.Book.id\" is \"7\" which already exists","s":"Checking for Id Conflicts","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#checking-for-id-conflicts","p":759},{"i":765,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(11L); draft.setName(\"GraphQL in Action\"); draft.setEdition(4); }), Immutables.createBook(draft -> { draft.setId(12L); draft.setName(\"GraphQL in Action\"); // `name + edition` exists draft.setEdition(1); // `name + edition` exists }) ); sqlClient.updateEntities(books); val books = listOf( Book { id = 11L name = \"GraphQL in Action\" edition = 4 }, Book { id = 12 name = \"GraphQL in Action\" // `name + edition` exists edition = 1 // `name + edition` exists } ) sqlClient.updateEntities(books) This code will generate the following two SQL statements: Batch update data update BOOK set NAME = ?, EDITION = ? where ID = ? /* batch-0: [GraphQL in Action, 4, 11] */ /* batch-1: [GraphQL in Action, 1, 12] */ Here, modifying the second record will cause a conflict with the combination of name and edition Investigate the cause of the constraint violation Most Databases Postgres Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) select tb_1_.ID from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) = ( ? /* GraphQL in Action */, ? /* 4 */ ) Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( (? /* GraphQL in Action */, ? /* 4 */), (? /* GraphQL in Action */, ? /* 1 */) ) For most databases, the original JDBC exception information from the batch SQL can determine which record violated the constraint, so only the problematic record is investigated For Postgres, the original JDBC exception information from the batch SQL cannot determine which record violated the constraint, so all records are investigated Either way, Jimmer can investigate and identify the problem. Finally, Jimmer will throw an exception based on the investigation results: #lighlight-next-line org.babyfish.jimmer.sql.exception.SaveException$NotUnique: Save error caused by the path: \"\": Cannot save the entity, the value of the key properties \"[ com.yourcompany.yourproject.model.Book.name, com.yourcompany.yourproject.Book.edition ]\" are \"Tuple2( _1=GraphQL in Action, _2=1 )\" which already exists info In the Mapping/Advanced Mapping/Key article, we introduced that entities can be configured with multiple unique constraints (or unique indexes) (in fact, this documentation has not been modified yet). If an entity has more than one unique constraint (or unique index), Jimmer will investigate them one by one. I'll translate the document while maintaining the technical terms as requested.","s":"Checking for Key Conflicts","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#checking-for-key-conflicts","p":759},{"i":767,"t":"In save commands, associations are divided into long associations and short associations. For long associations, if the associated object doesn't exist, Jimmer will automatically create it first, so there is no issue of non-existent associated objects. For short associations, Jimmer assumes that the associated object must exist, and problems will arise if the associated object doesn't exist. Therefore, this issue is specific to short associations. In the following examples, all associated objects are id-only objects. In Mapping/Basic Mapping/Real and Fake Foreign Keys, we introduced that Jimmer supports both real and fake foreign keys. Only real foreign keys involve database constraint violation issues, so we'll discuss them separately.","s":"Checking the Existence of Associated Objects","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"","p":759},{"i":769,"t":"For fake foreign keys, there are no foreign key constraints in the database. If the specified associated object doesn't exist, meaning the association ID is invalid, the database has no opinion on this. Therefore, by default, Jimmer doesn't check whether the associated object exists for fake foreign keys, allowing users to save invalid dangling values. Although this is unrelated to the main topic of this article, we'll still explain it. Users can configure the save command to make Jimmer verify the existence of associated objects beforehand. info Assume Book.store is a fake foreign key Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(8L); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(9L); draft.setStoreId(999L); // Invalid associated id }) ); sqlClient .saveEntitiesCommand(books) .setMode(SaveMode.UPDATE_ONLY) .setAutoIdOnlyTargetChecking( BookProps.STORE ) .execute(); val books = listOf( Book { id = 8L storeId = 2L }, Book { id = 9L storeId = 999L // Invalid associated id } ) sqlClient.updateEntities(books) { setAutoIdOnlyTargetChecking( Book::store ) } Here, the setAutoIdOnlyTargetChecking method is used to set which short associations need to be verified beforehand. Before saving the data, Jimmer will verify the association IDs through a query select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID = any(? /* [2, 999] */) Finally, it throws the following exception org.babyfish.jimmer.sql.exception.SaveException$IllegalTargetId: Save error caused by the path: \".store\": Cannot save the entity, the associated id of the reference property \"com.yourcompany.yourproject.model.Book.store\" is \"999\" but there is no corresponding associated object in the database","s":"Fake Foreign Keys","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#fake-foreign-keys","p":759},{"i":771,"t":"For real foreign keys, there are foreign key constraints in the database. If the specified associated object doesn't exist, meaning the association ID is invalid, the database will report a constraint violation error. Without any user configuration, if an error occurs, Jimmer will automatically analyze the error reported by the database to identify the invalid association ID. info Assume Book.store is a real foreign key Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(8L); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(9L); draft.setStoreId(999L); // Invalid associated id }) ); sqlClient.updateEntities(books); val books = listOf( Book { id = 8L storeId = 2L }, Book { id = 9L storeId = 999L // Invalid associated id } ) sqlClient.updateEntities(books) This code will generate two SQL statements Batch update data update BOOK set STORE_ID = ? where ID = ? /* batch-0: [2, 8] */ /* batch-1: [999, 9] */ Here, modifying the second record will cause a foreign key constraint violation on the STORE_ID column. Investigate the cause of the constraint violation Most Databases Postgres Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID = ? /* 999 */ Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID = any(? /* [2, 999] */) For most databases, the original JDBC exception information thrown by the batch SQL can determine which record violated the constraint, so only the erroneous record is investigated For Postgres, the original JDBC exception information thrown by the batch SQL cannot determine which record violated the constraint, so all records are investigated Either way, Jimmer can investigate the problem. Finally, Jimmer will throw an exception based on the investigation results org.babyfish.jimmer.sql.exception.SaveException$IllegalTargetId: Save error caused by the path: \".store\": Cannot save the entity, the associated id of the reference property \"com.yourcompany.yourproject.model.Book.store\" is \"999\" but there is no corresponding associated object in the database tip As you can see, although the automatic error investigation mechanism for real foreign keys and the manual checking mechanism for fake foreign keys are completely different, they produce exactly the same exception information.","s":"Real Foreign Keys","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#real-foreign-keys","p":759},{"i":774,"t":"As mentioned earlier, Jimmer investigates database-reported constraint violations and throws exceptions org.babyfish.jimmer.sql.exception.SaveException.NotUnique Violation of primary key constraint, unique constraint, or unique index org.babyfish.jimmer.sql.exception.SaveException.IllegalTargetId Illegal association ID These two exceptions not only provide detailed error messages but also offer rich APIs to obtain various information. However, this is far from enough. In real projects, we must display easy-to-understand information for end users. Indeed, we can catch and handle exceptions after each save command call. However, Jimmer supports more powerful unified exception translation. Jimmer provides an exception translation interface ExceptionTranslator, the code is as follows ExceptionTranslator.java package org.babyfish.jimmer.sql.runtime; public interface ExceptionTranslator { /** * Translate the exception. * *

If the exception is not known how to be translated, * return null or the original argument.

*/ @Nullable Exception translate(@NotNull E exception, @NotNull Args args); interface Args { ...omitted... } } Users can implement this interface through classes (note: lambda expressions cannot be used) and specify generic type parameter for the interface, for example: Translate SaveException.NotUnique exception Java Kotlin public class NotUniqueExceptionTranslator extends ExceptionTranslator< SaveException.NotUnique > { ...omitted... } class NotUniqueExceptionTranslator : ExceptionTranslator< SaveException.NotUnique > { ...omitted... } Translate SaveException.IllegalTargetId exception Java Kotlin public class IllegalTargetIdExceptionTranslator extends ExceptionTranslator< SaveException.IllegalTargetId > { ...omitted... } class IllegalTargetIdExceptionTranslator : ExceptionTranslator< SaveException.IllegalTargetId > { ...omitted... } You can even translate other JDBC exceptions that Jimmer is not interested in Java Kotlin public class SQLExceptionTranslator extends ExceptionTranslator< java.sql.SQLException > { ...omitted... } class SQLExceptionTranslator : ExceptionTranslator< java.sql.SQLException > { ...omitted... }","s":"Exception Translation Interface","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#exception-translation-interface","p":759},{"i":776,"t":"Just writing a class to implement this interface is useless; you must create an object and register it to Jimmer take effect. Jimmer provides two registration methods, taking the NotUniqueExceptionTranslator mentioned above as an example: Global registration, which can be divided into two types Not using Jimmer's spring starter Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .addExceptionTranslator( new NotUniqueExceptionTranslator() ) ...other configurations omitted... .build(); val sqlClient = sqlClient { addExceptionTranslator( NotUniqueExceptionTranslator() ) ...other configurations omitted... } Using Jimmer's spring starter Java Kotlin @Component public class NotUniqueExceptionTranslator extends ExceptionTranslator { ...omitted... } @Component class NotUniqueExceptionTranslator : ExceptionTranslator { ...omitted... } Register for specific save commands Java Kotlin Book book = ...omitted...; sqlClient .saveCommand(book) .addExceptionTranslator( new NotUniqueExceptionTranslator() ) .execute() val book: Book = ...omitted... sqlClient.save(book) { addExceptionTranslator( new NotUniqueExceptionTranslator() ) }","s":"Multiple Registration Methods","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#multiple-registration-methods","p":759},{"i":778,"t":"Finally, let's show how to implement the translate method Translate SaveException.NotUnique exception Java Kotlin @Component public class NotUniqueExceptionTranslator extends ExceptionTranslator { @Override public @Nullable Exception translate( @NotNull SaveException.NotUnique exception, @NotNull Args args ) { if (exception.isMatched(BookProps.ID)) { return new IllegalArgumentException( \"Book with ID \" + exception.getValue(BookProps.ID) + \" already exists\" ); } if (exception.isMatched(BookProps.NAME, BookProps.EDITION)) { return new IllegalArgumentException( \"Book with name \" + exception.getValue(BookProps.NAME) + \" and edition \" + exception.getValue(BookProps.EDITION) + \" already exists\" ); } //No processing needed, can also be written as `return exception` return null; } } @Component class NotUniqueExceptionTranslator : ExceptionTranslator { override fun translate( exception: NotUnique, args: ExceptionTranslator.Args ): Exception? = when { exception.isMatched(Book::id) -> throw IllegalArgumentException( \"Book with ID ${exception[Book::id]} already exists\" ) exception.isMatched(Book::name, Book::edition) -> throw IllegalArgumentException( \"Book with name ${ exception[Book::id] } and edition ${ exception[Book::edition] } already exists\" ) else -> null //No processing needed, can also be written as `exception` } } Translate SaveException.IllegalTargetId exception Java Kotlin @Component public class IllegalTargetIdExceptionTranslator extends ExceptionTranslator { @Override public @Nullable Exception translate( @NotNull SaveException.IllegalTargetId exception, @NotNull Args args ) { if (exception.getProp() == BookProps.STORE.unwrap()) { throw new IllegalArgumentException( \"Cannot set invalid associated store ID for book: \" + exception.getTargetIds() ); } // No processing needed, can also be written as `return exception` return null; } } @Component class IllegalTargetIdExceptionTranslator : ExceptionTranslator { override fun translate( exception: IllegalTargetId, args: ExceptionTranslator.Args ): Exception? = when { exception.prop == BookProps.STORE.unwrap() -> throw IllegalArgumentException( \"Cannot set invalid associated store ID for book: ${ exception.targetIds }\" ) else -> null //No processing needed, can also be written as `exception` } }","s":"Implementing the translate Method","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#implementing-the-translate-method","p":759},{"i":780,"t":"Save commands support both optimistic lock and pessimistic lock.","s":"Optimistic/Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"","p":779},{"i":782,"t":"Jimmer supports optimistic lock via the @org.babyfish.jimmer.sql.Version annotation.","s":"Optimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#optimistic-lock","p":779},{"i":784,"t":"Modify BookStore Java Kotlin BookStore.java @Entity public interface BookStore { @Version int version(); ...other properties omitted... } BookStore.kt @Entity public interface BookStore { @Version val version: Int ...other properties omitted... } Modify Book Java Kotlin Book.java @Entity public interface Book { @Version int version(); ...other properties omitted... } Book.kt @Entity public interface Book { @Version val version: Int ...other properties omitted... }","s":"Modify Entity Types","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#modify-entity-types","p":779},{"i":786,"t":"Characteristics of optimistic lock: When inserting objects (whether explicitly doing INSERT, or UPSERT determined to be INSERT), the version of the object will be inserted into the database. For example: Java Kotlin BookStore savedData = sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"44.99\")); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); }); }) ).getModifiedEntity(); System.out.println(savedData); val savedData = sqlClient.save( BookStore { name = \"TURING\" books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") } } ).modifiedEntity println(savedData) tip For INSERT operations, if the version of the object is not assigned, Jimmer will automatically insert 0. If you cannot ascertain whether a UPSERT save command will ultimately be determined as INSERT or UPDATE, you should insist on specifying the version property. The following example assumes we know for sure the save will be determined as INSERT rather than UPDATE, so the version properties are not specified. No ids are specified so jimmer determines their existence by their key properties. Assuming none of the objects exist, 3 new records will be inserted. No version properties are specified, so they are filled with 0 automatically. The final printed result will be (formatted for readability): { \"id\":100, \"name\":\"TURING\", \"version\":0, \"books\":[ { \"id\":100, \"name\":\"Introduction to Algorithms\", \"edition\":3, \"price\":44.99, \"version\":0, \"store\":{ \"id\":100 } }, { \"id\":101, \"name\":\"The Pragmatic Programmer\", \"edition\":2, \"price\":39.99, \"version\":0, \"store\":{ \"id\":100 } } ] } info Of course, if the user specifies version for these objects, the specified values rather than 0 will be inserted. When modifying objects (whether explicitly doing UPDATE, or UPSERT determined to be UPDATE), Jimmer will compare the version passed by the user and the existing version in the database for each object. If they differ, an exception will be thrown. Let's modify the code a bit and execute again: Java Kotlin BookStore savedData = sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.setVersion(0); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"54.99\")); book.setVersion(0); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); // illegal version book.setVersion(9999); }); }) ).getModifiedEntity(); System.out.println(savedData); val savedData = sqlClient.save( BookStore { name = \"TURING\" version = 0 books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") version = 0 } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") // illegal version version = 9999 } } ).modifiedEntity println(savedData) caution For UPDATE operations, if the version of the object is not assigned, Jimmer will throw an exception. If you cannot determine whether a UPSERT save command will ultimately be INSERT or UPDATE, you should insist on specifying the version property. Execute, since data already exists, the 3 objects will be updated. Obviously, the last book's version 9999 is illegal. The above code will result in the following exception: Exception Type: org.babyfish.jimmer.sql.runtime.SaveException Exception Code: org.babyfish.jimmer.sql.runtime.SaveErrorCode.ILLEGAL_VERSION Exception Message: Save error caused by the path: \".books\": Cannot update the entity whose type is \"org.doc.j.model.Book\", id is \"101\" and version is \"9999\" Let's modify the code again to use the correct version for all objects: Java Kotlin BookStore savedData = sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.setVersion(0); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"54.99\")); book.setVersion(0); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); book.setVersion(0); }); }) ).getModifiedEntity(); System.out.println(savedData); val savedData = sqlClient.save( BookStore { name = \"TURING\" version = 0 books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") version = 0 } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") version = 0 } } ).modifiedEntity println(savedData) The final printed result will be (formatted for readability): { \"id\":100, \"name\":\"TURING\", \"version\":1, \"books\":[ { \"id\":100, \"name\":\"Introduction to Algorithms\", \"edition\":3, \"price\":54.99, \"version\":1, \"store\":{ \"id\":100 } }, { \"id\":101, \"name\":\"The Pragmatic Programmer\", \"edition\":2, \"price\":39.99, \"version\":1, \"store\":{ \"id\":100 } } ] } info As you can see, the version is incremented by 1 automatically after data modification. In real projects, the version number of optimistic lock is often a hidden field in the form UI. If the form UI does not automatically redirect to other UI after saving, but keeps the UI unchanged to support multiple submissions, the hidden field should be updated with such return info after each successful save.","s":"Demo","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#demo","p":779},{"i":788,"t":"Unlike optimistic lock, pessimistic locks are very short-lived, only valid within a single jdbc transaction. Normally, Jimmer generates some query SQL to aid save command execution, such as: Determining whether a UPSERT should ultimately be INSERT or UPDATE Determining which associated objects need to be dissociated Next, we compare the differences in these query SQL between using and not using pessimistic lock. info In the previous examples, to demonstrate optimistic lock, we assumed the BookStore and Book types both defined a version property. In the following examples to demonstrate pessimistic lock, we no longer make that assumption.","s":"Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#pessimistic-lock","p":779},{"i":790,"t":"Java Kotlin sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"44.99\")); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); }); }) ); sqlClient.save( BookStore { name = \"TURING\" books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") } } ) This generates 6 SQL statements: Check if the book store exists select tb_1_.ID, tb_1_.NAME from BOOK_STORE tb_1_ where tb_1_.NAME = ? /* TURING */ Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 1st book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* Introduction to Algorithms */ and tb_1_.EDITION = ? /* 3 */ Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 2nd book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* The Pragmatic Programmer */ and tb_1_.EDITION = ? /* 2 */ Determine INSERT or UPDATE based on previous query insert or update, omitted info These query statements are used to make conditional judgments to determine how to generate subsequent SQL. However, without pessimistic lock, the conditions and assumptions made via these queries can potentially be invalidated by concurrent operations, leading to exceptions when executing subsequent SQL. To avoid such concurrency issues, pessimistic lock can be enabled. Next we discuss how to implement pessimistic lock.","s":"Without Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#without-pessimistic-lock","p":779},{"i":792,"t":"There are two ways to enable pessimistic lock: Global configuration There are two ways to enable pessimistic lock globally: Via Spring Boot Starter configuration Modify application.yml (or application.properties): jimmer: default-lock-mode: PESSIMISTIC Via low-level API configuration Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultLockMode(LockMode.PESSIMISTIC) ...other configurations omitted... .build(); val sqlClient = newKSqlClient { setDefaultLockMode(LockMode.PESSIMISTIC) } warning This change modifies the global setting, and the original default value OPTIMISTIC is compromised. This means that unless a specific save command is set to optimistic locking mode, the optimistic locking functionality described earlier disappears. Therefore, in most cases, global configuration is not recommended, and the command-level configuration that will be introduced later is more recommended. Command-level configuration Unlike global configuration affecting all save commands, command-level configuration only affects the current save command. info If pessimistic lock is already enabled globally, no need for command-level configuration. Calling setLockMode(LockMode) on the save command enables pessimistic lock: Java Kotlin sqlClient .getEntities() .saveCommand( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"44.99\")); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); }); }) ) .setLockMode(LockMode.PESSIMISTIC) .execute(); sqlClient.save( BookStore { name = \"TURING\" books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") } } ) { setLockMode(LockMode.PESSIMISTIC) } Once pessimistic lock is enabled, the generated query statements will change significantly: Check if the book store exists select tb_1_.ID, tb_1_.NAME from BOOK_STORE tb_1_ where tb_1_.NAME = ? /* TURING */ for update Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 1st book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* Introduction to Algorithms */ and tb_1_.EDITION = ? /* 3 */ for update Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 2nd book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* The Pragmatic Programmer */ and tb_1_.EDITION = ? /* 2 */ for update Determine INSERT or UPDATE based on previous query insert or update, omitted","s":"Enabling Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#enabling-pessimistic-lock","p":779},{"i":795,"t":"The usage of the update statement is: Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .where(author.firstName().eq(\"Dan\")) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) where(table.firstName eq \"Dan\") } .execute() println(\"Affected row count: $affectedRowCount\") The finally generated SQL is: update AUTHOR tb_1_ set FIRST_NAME = concat(tb_1_.FIRST_NAME, ?) where tb_1_.FIRST_NAME = ?","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/update-statement","h":"#basic-usage","p":793},{"i":797,"t":"By default, update statements do not support joins, which will cause exceptions: Java Kotlin AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .where( author .books() .name() .eq(\"Learning GraphQL\") ) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) where( table .books .name eq \"Learning GraphQL\" ) } .execute() println(\"Affected row count: $affectedRowCount\") The exception message is: Table joins for update statement is forbidden by the current dialect, but there is a join `'Author.books'`. When using MySQL or Postgres, update statements can use JOIN clauses.","s":"Using JOIN","u":"/jimmer-doc/docs/mutation/update-statement","h":"#using-join","p":793},{"i":799,"t":"First, MySQLDialect needs to be specified when creating SqlClient: Spring Boot configuration: Declare dialect in application.yml or application.properties, like this jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect Non-Spring Boot configuration: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect( new org.babyfish.jimmer.sql.dialect.MySqlDialect() ) ... .build(); val sqlClient = newKSqlClient { setDialect(org.babyfish.jimmer.sql.dialect.MySqlDialect()) } Then JOIN can be used in update: Java Kotlin AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .set( author.books().name(), author.books().name().concat(\"*\") ) .set( author.books().store().name(), author.books().store().name().concat(\"*\") ) .where( author.books().store().name().eq(\"MANNING\") ) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) set( table.books.name, concat(table.books.name, value(\"*\")) ) set( table.books.store.name, concat(table.books.store.name, value(\"*\")) ) where( table.books.store.name eq \"MANNING\" ) } .execute() println(\"Affected row count: $affectedRowCount\") The finally generated SQL for MySQL is: update AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID inner join BOOK as tb_3_ on tb_2_.BOOK_ID = tb_3_.ID inner join BOOK_STORE as tb_4_ on tb_3_.STORE_ID = tb_4_.ID set tb_1_.FIRST_NAME = concat(tb_1_.FIRST_NAME, ?), tb_3_.NAME = concat(tb_3_.NAME, ?), tb_4_.NAME = concat(tb_4_.NAME, ?) where tb_4_.NAME = ?","s":"MySQL","u":"/jimmer-doc/docs/mutation/update-statement","h":"#mysql","p":793},{"i":801,"t":"First, PostgresDialect needs to be specified when creating SqlClient: Spring Boot configuration: Declare dialect in application.yml or application.properties, like this jimmer: dialect: org.babyfish.jimmer.sql.dialect.PostgresDialect Non-Spring Boot configuration: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect( new org.babyfish.jimmer.sql.dialect.PostgresDialect() ) ... .build(); val sqlClient = newKSqlClient { setDialect(org.babyfish.jimmer.sql.dialect.PostgresDialect()) } Then JOIN can be used in update: Java Kotlin AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .where( author.books().store().name().eq(\"MANNING\") ) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) where( table.books.store.name eq \"MANNING\" ) } .execute() println(\"Affected row count: $affectedRowCount\") caution Unlike MySQL, using JOIN in update statements in Postgres has the following restrictions: JOIN can only be used in the where clause, not in the set clause. That is, Postgres still only allows modifying fields of the current table, supporting joins to other tables only for condition filtering. The join path can have multiple levels, such as author.books().store(), where books() is level 1 and store() is level 2. The join type of the first level must be inner join. The finally generated SQL for Postgres is: update AUTHOR tb_1_ set FIRST_NAME = concat(tb_1_.FIRST_NAME, ?) from BOOK_AUTHOR_MAPPING as tb_2_ ❶ inner join BOOK as tb_3_ ❷ on tb_2_.BOOK_ID = tb_3_.ID inner join BOOK_STORE as tb_4_ ❸ on tb_3_.STORE_ID = tb_4_.ID where tb_1_.ID = tb_2_.AUTHOR_ID ❹ and tb_4_.NAME = ? info The join path author.books().store() has two levels, books() is level 1 and store() is level 2. Level 1 books() involves two tables: BOOK_AUTHOR_MAPPING table at ❶, but the join condition is missing here, supplemented at ❹. BOOK table at ❷. Level 2 store() involves one table: BOOK_STORE table at ❸. As you can see, in the update statement of Postgres, table joins directly related to the main table cannot use the join + on syntax, they must be equivalently transformed into from + where. This is why Jimmer requires the join type of level 1 to be inner join for update statements in Postgres dialect.","s":"Postgres","u":"/jimmer-doc/docs/mutation/update-statement","h":"#postgres","p":793},{"i":803,"t":"In this series of articles, we thoroughly discuss the dynamicity and immutability of Jimmer objects: Dynamicity To support querying and saving any data shape, Jimmer entities are dynamic. Immutability To avoid circular references and allow entities to be directly JSON serialized for HTTP and understood by any language, Jimmer entities are immutable. tip The dynamicity and immutability of Jimmer objects underpin the entire Jimmer ecosystem.","s":"Object","u":"/jimmer-doc/docs/object/","h":"","p":802},{"i":806,"t":"Save instructions allow developers to save data structures of any shape, rather than save simple objects. By default, when AssociatedSaveMode is set to REPLACE, Jimmer will completely replace the existing data structure in the database with the structure being saved, as shown in the figure: Top right: Users pass in a data structure of any shape for Jimmer to write to the database. Top left: Query the existing data structure from the database to compare with the new data structure passed in by users. Whatever shape of data structure the user passes in, the same shape will be queried from the database, ensuring the shapes of old and new data structures are identical. Therefore, the querying and comparison costs are determined by the complexity of the user-provided data structure. Below:Compare the new and old data structures, find the DIFF and execute corresponding SQL operations to make them consistent: Orange parts: For entity objects that exist in both new and old data structures, modify data if scalar properties have changed Blue parts: For entity objects that exist in both new and old data structures, modify associations if they have changed Green parts: For entity objects that exist in the old data structure but not in the new one, decouple this object, clear associations and possibly delete data Red parts: For entity objects that exist in the new data structure but not in the old one, insert data and establish associations tip Unlike other ORMs, Jimmer doesn't require describing how data should be saved in the entity model Whether certain scalar properties need to be saved Taking JPA as an example, this is controlled throughColumn.insertable andColumn.updatable. Whether certain association properties need to be saved Taking JPA as an example, this is controlled throughOneToOne.cascade,ManyToOne.cascade,OenToMany.cascade andManyToOne.cascade. Jimmer adopts a completely different strategy - its entity objects are not POJOs and can flexibly control the shape of data structures. That is, entity objects have dynamic properties - not specifying a property for an entity object and setting an entity's property to null are completely different things. For any entity object, Jimmer will only save the specified properties while ignoring unspecified ones. Therefore, Jimmer doesn't need to consider data saving behavior during entity modeling, but rather describes the expected behavior at runtime through the data structure being saved itself, providing absolute flexibility.","s":"Introduction","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#introduction","p":804},{"i":809,"t":"Let's look at how Jimmer distinguishes between the following two requirements: Not updating a certain property of an object Updating a property of an object to null For traditional static language ORMs, this is a very tricky problem. However, Jimmer can easily distinguish between these two different behaviors. 1.1.1. Not Updating a Certain Property​ Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(8L); draft.setPrice(new BigDecimal(\"33.9\")); // `store` or `storeId` property not specified }) ); sqlClient.update( Book { id = 8L price = BigDecimal(\"33.9\") // `store` or `storeId` property not specified } ); Generates the following SQL: update BOOK set PRICE = ? /* 33.9 */ where ID = ? /* 8 */ As you can see, only the specified field PRICE is modified, while other unspecified fields (including STORE_ID) remain unchanged. 1.1.2. Updating a Property to Null​ Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(8L); draft.setPrice(BigDecimal(\"33.9\")) draft.setStore(null); // Can also be written as `draft.setStoreId(null)` }) ); sqlClient.update( Book { id = 8L price = BigDecimal(\"33.9\") store = null // Can also be written as `storeId = null` } ); Generates the following SQL: update BOOK set PRICE = ? /* 33.9 */ STORE_ID = ? /* */ where ID = ? /* 8 */","s":"1.1. Flexible Control Over Simple Property Modifications","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#11-flexible-control-over-simple-property-modifications","p":804},{"i":811,"t":"In real business projects, there's often a requirement to update only some properties of an entity, not all of them. However, in traditional ORM development patterns, developers rarely use ORM update statements for convenience. Instead, they often choose to query the object first, then modify it, and finally save it. Here's a JPA example: JPA Example EntityManager entityManager = ...obtain JPA session object from current transaction context, omitted... Book book = entityManager.find(Book.class, 8L); book.setStore(null); // In JPA, entities are mutable, setting association to null // Calling merge here is just for clarity, it can be omitted since JPA will modify the database when the transaction commits entityManager.merge(book); Actually, besides wanting to modify Book.store to null, this scenario has no interest in other properties of the object. Obviously, this is wasteful. If the entity object has many properties, it becomes even more apparent. Jimmer's entity objects don't require all properties to be specified, meaning Jimmer supports incomplete objects. Therefore, you can create from scratch an incomplete Book object, only specifying its id property and store property, and let Jimmer update it directly. Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(8L); draft.setStore(null); }) ); sqlClient.update( Book { id = 8L store = null } ); Generates the following SQL: update BOOK set STORE_ID = ? /* */ where ID = ? /* 8 */","s":"1.2. Using Incomplete Objects to Avoid Query-Before-Update","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#12-using-incomplete-objects-to-avoid-query-before-update","p":804},{"i":813,"t":"Through the single object case, we have gained a basic understanding of the flexibility of save commands. Next, let's introduce the control capabilities of save commands over association properties.","s":"2. Flexibility of Association Properties","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#2-flexibility-of-association-properties","p":804},{"i":815,"t":"In most ORMs, the cascade configuration of association properties determines whether to save associated objects when saving an object. Taking JPA as an example, this can be achieved through 4 configurations: OneToOne.cascade ManyToOne.cascade OneToMany.cascade ManyToMany.cascade However, deciding on these configurations is painful. No matter how they are configured, they solidify the behavioral patterns of the model at the entity modeling stage, making the entity design too tightly coupled with business requirements. Jimmer doesn't have similar configurations. The specific behavior depends on the format of the data structure being saved itself. For example: Only saving the BookStore object Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.setWebsite(\"https://www.amazon.com\"); }); sqlClient.save(store); val store = BookStore { name = \"AMAZON\" website = \"https://www.amazon.com\" } sqlCient.save(store) Saving the BookStore object while cascading to save related Book objects Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.setWebsite(\"https://www.amazon.com\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }); sqlClient.save(store); val store = BookStore { name = \"AMAZON\" website = \"https://www.amazon.com\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } sqlCient.save(store)","s":"2.1. Whether to Cascade Save Associated Properties","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#21-whether-to-cascade-save-associated-properties","p":804},{"i":817,"t":"ORM has an important concept: bidirectional associations. In this tutorial, Book.authors and Author.books are bidirectional associations of each other. Whether in JPA or Jimmer, both ends of a bidirectional association are divided into active and passive sides: Active side: The mappedBy property of the association annotation is not specified Passive side: The mappedBy property of the association annotation is specified However, there is a huge difference between Jimmer and JPA: In JPA, you must make the active side object act as the parent object and the passive side object act as the associated object. Otherwise, modifications will be ineffective. Choosing the active side for JPA bidirectional associations is also very painful, essentially solidifying the model's behavior pattern at the entity modeling stage, making entity design too tightly coupled with business requirements. In Jimmer, regardless of how you choose the active and passive sides, it has no impact on save commands. If the active side choice of bidirectional association is restricted by Jimmer (for example, when building bidirectional associations based on one-to-many and many-to-one associations, Jimmer requires the one-to-many association to be the passive side), define the bidirectional association according to Jimmer's requirements Otherwise, freely define bidirectional associations according to your preferences In Jimmer, you can freely manipulate bidirectional associations according to your preferences, for example: Saving a Book object and modifying its association with Author, i.e., implementing association modification through Book.authors Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"C++ Primer\"); draft.setEdition(5); draft.setPrice(new BigDecimal(\"44.02\")); draft.addIntoAuthors(author -> author.setId(10L)); draft.addIntoAuthors(author -> author.setId(11L)); draft.addIntoAuthors(author -> author.setId(12L)); }) sqlCient.save(book); val book = Book { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") authors().addBy { id = 10L } authors().addBy { id = 11L } authors().addBy { id = 12L } } sqlCient.save(book); Saving an Author object and modifying its association with Book, i.e., implementing association modification through Author.books Java Kotlin Author author = Immutables.createAuthor(draft -> { draft.setFirstName(\"Stanley\"); draft.setLastName(\"Lippman\"); draft.setGender(Gender.MALE); draft.addIntoBooks(book -> book.setId(40L)); draft.addIntoBooks(book -> book.setId(41L)); draft.addIntoBooks(book -> book.setId(42L)); draft.addIntoBooks(book -> book.setId(43L)); draft.addIntoBooks(book -> book.setId(44L)); draft.addIntoBooks(book -> book.setId(45L)); }); sqlClient.save(author); val author = Author { firstName = \"Stanley\" lastName = \"Lippman\" gender = Gender.MALE books().addBy { id = 40L } books().addBy { id = 41 } books().addBy { id = 42L } books().addBy { id = 43L } books().addBy { id = 44L } books().addBy { id = 45L } } sqlCient.save(author)","s":"2.2. Symmetry of Bidirectional Associations","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#22-symmetry-of-bidirectional-associations","p":804},{"i":819,"t":"Save commands are very flexible and can manifest as either very powerful advanced features or very simple basic features. It's all up to you. In daily project development, there are two distinctly different requirements: Full data replacement for complex forms Incremental modification for simple data In terms of development task complexity, one is very complex, and the other is very simple. However, Jimmer treats them equally and implements them quickly.","s":"3. Deciding Functionality Complexity","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#3-deciding-functionality-complexity","p":804},{"i":821,"t":"Complex forms usually include associations (such as orders and order details), and may even include recursive data structures (such as UI drag-and-drop systems, UML drawing tools). No matter how complex, viewing this data structure as a whole, it can be saved with a single command. To make the example representative, we'll use Input DTO that hasn't been explained yet. Although the related content hasn't been covered yet, readers can guess its purpose. Using Jimmer's DTO language, define a type called BookStoreInput. export com.yourcompany.yourproject.BookStore -> pacage com.yourcompany.yourproject.dto; input BookStoreInput { #allScalars books { #allScalars id(authors) as authorIds } } After Jimmer compilation, a Java or Kotlin class named BookStoreInput is automatically generated. BookStoreInput is similar to POJO, a highly static type used to regulate, restrict, and accept client HTTP request content. At the same time, this class can automatically transform into BookStore entity objects and related associated objects. Java Kotlin @PutMapping(\"/store\") public void saveBookStore( @RequestBody BookStoreInput input ) { sqlCient.save(input); } @PutMapping(\"/store\") fun saveBookStore( @RequestBody input: BookStoreInput ) { sqlCient.save(input); } Here, sqlClient.save(input) first converts the input DTO to BookStore entity objects and related associated objects, then directly saves the entire data structure, completing the full replacement of complex form data. The save command recursively processes objects at all levels in the entire data structure, comparing the data structure being saved with the existing data structure in the database, finding inconsistencies and making modifications. However, no matter how complex the internal details of this process are, it's transparent to users.","s":"3.1. Full Data Replacement for Complex Forms","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#31-full-data-replacement-for-complex-forms","p":804},{"i":823,"t":"Now, let's implement a very simple requirement: adding a book to a bookstore. Java Kotlin @PutMapping(\"/store/{storeId}/books/{bookId}\") public void addBook( @PathVariable long storeId, @PathVariable long bookId ) { sqlClient.update( Immutables.createBook( draft.setId(bookId); draft.setStoreId(storeId); ) ) } @PutMapping(\"/store/{storeId}/books/{bookId}\") fun addBook( @PathVariable storeId: Long, @PathVariable bookId: Long ) { sqlClient.update( Book { id = bookId storeId = storeId } ) } This is a very simple example, while the previous example was completely different, completing very complex work. info Save commands can manifest as either very powerful advanced features or very simple basic features. Everything is possible, depending entirely on how you use them.","s":"3.2. Incremental Modification for Simple Data","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#32-incremental-modification-for-simple-data","p":804},{"i":825,"t":"Save commands bring absolute flexibility to data saving operations, however, overly powerful flexibility often means compromising security. That is, the client can freely write arbitrary complex data structures to the server, even if this far exceeds its permission scope. For this, Jimmer adopts a divide-and-conquer approach: The save command itself serves as underlying support, accepting Jimmer's dynamic entities, providing absolute flexibility and unlimited possibilities. Introducing InputDTO, automatically generating static types similar to POJO, standardizing and limiting client behavior, and being responsible for accepting request data. Finally, it automatically transforms into an entity object tree, handled by the save command.","s":"Security","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#security","p":804},{"i":827,"t":"info The example code in this article uses a type called BookDraft, which is an interface type automatically generated by Jimmer based on the user-defined type Book. Readers can ignore this auto-generated interface for now. The later document Draft will introduce it.","s":"Dynamicity","u":"/jimmer-doc/docs/object/dynamic","h":"","p":826},{"i":830,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); }); val book = Book { name = \"Learning GraphQL\" } In this case, the JSON for the books object would be like follows {\"name\": \"Learning GraphQL\"}","s":"1. A few properties","u":"/jimmer-doc/docs/object/dynamic","h":"#1-a-few-properties","p":826},{"i":832,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.99\")); }); val book = Book { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") } In this case, the JSON for the books object would be like follows { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99 }","s":"2. More Properties","u":"/jimmer-doc/docs/object/dynamic","h":"#2-more-properties","p":826},{"i":834,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.99\")); draft.applyStore(store -> { store.setName(\"O'REILLY\"); store.setWebsite(\"https://www.oreilly.com/\"); }); }); val book = Book { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") store { name = \"O'REILLY\" website = \"https://www.oreilly.com/\" } } In this case, the JSON for the books object would be like follows { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99, \"store\": { \"name\": \"O'REILLY\", \"website\": \"https://www.oreilly.com/\" } }","s":"3. Include Association","u":"/jimmer-doc/docs/object/dynamic","h":"#3-include-association","p":826},{"i":836,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.99\")); draft.applyStore(store -> { store.setName(\"O'REILLY\"); store.setWebsite(\"https://www.oreilly.com/\"); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Eve\"); author.setLastName(\"Procello\"); author.setGender(Gender.FEMALE); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Alex\"); author.setLastName(\"Banks\"); author.setGender(Gender.MALE); }); }); val book = Book { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") store { name = \"O'REILLY\" website = \"https://www.oreilly.com/\" } authors().addBy { firstName = \"Eve\" setLastName = \"Procello\" gender = Gender.FEMALE } authors().addBy { firstName = \"Alex\" lastName = \"Banks\" gender = Gender.MALE } } In this case, the JSON for the books object would be like follows { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99, \"store\": { \"name\": \"O'REILLY\", \"website\": \"https://www.oreilly.com/\" }, \"authors\": [ { \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender:\" \"FEMALE\" }, { \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender:\" \"MALE\" } ] }","s":"4. More Associations (Larger Breadth)","u":"/jimmer-doc/docs/object/dynamic","h":"#4-more-associations-larger-breadth","p":826},{"i":838,"t":"Here is the translation to English: Unlike the previous examples, here we choose BookStore as the aggregate root for the data structure, rather than Book. Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"O'REILLY\"); draft.setWebsite(\"https://www.oreilly.com/\"); draft.addIntoBooks(book -> { book.setName(\"Learning GraphQL\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.99\")); book.addIntoAuthors(author -> { author.setFirstName(\"Eve\"); author.setLastName(\"Procello\"); author.setGender(Gender.FEMALE); }); book.addIntoAuthors(author -> { author.setFirstName(\"Alex\"); author.setLastName(\"Banks\"); author.setGender(Gender.MALE); }); }); }); val store = BookStore { name = \"O'REILLY\" website = \"https://www.oreilly.com/\" books().addBy { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") authors().addBy { firstName = \"Eve\" setLastName = \"Procello\" gender = Gender.FEMALE } authors().addBy { firstName = \"Alex\" lastName = \"Banks\" gender = Gender.MALE } } } In this case, the JSON for the store object would be like follows { \"name\": \"O'REILLY\", \"website\": \"https://www.oreilly.com/\", \"books\": [ { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99, \"authors\": [ { \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender:\" \"FEMALE\" }, { \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender:\" \"MALE\" } ] } ] }","s":"5. Deeper Associations (Larger Depth)","u":"/jimmer-doc/docs/object/dynamic","h":"#5-deeper-associations-larger-depth","p":826},{"i":840,"t":"Dynamic object may lack any property, or in other words, dynamic object are not required to have all properties set. caution In dynamic object, missing properties and properties set to null are completely different things. Missing property: The value of the property of the object is unknown, the current business is not interested in it Property set to null: The value of the property of the object is known, it really is nothing In static POJOs, the two are actually indistinguishable. What's worse, developers often intentionally or unintentionally confuse the two by taking advantage of Java's lack of null safety. The concept of dynamic object is very important and key to understanding Jimmer! For missing properties: Using code to access them directly will result in an exception org.babyfish.jimmer.UnloadedException note If the reader has Hibernate experience, think of this as org.hibernate.LazyInitializationException. In Jackson serialization, they will be automatically ignored. info This requires some configuration for Jackson. Since this detail is very important, it has been made into a separate document. Please refer to Work with Jackson.","s":"Characteristics of Dynamic Objects","u":"/jimmer-doc/docs/object/dynamic","h":"#characteristics-of-dynamic-objects","p":826},{"i":842,"t":"Dynamicity is an intrinsic characteristic of Jimmer objects and is universally applicable. Both the ORM framework itself and developers can easily build dynamic objects for each other to use. Jimmer creates dynamic objects and returns them to developers That is, query data structures of any shape. This feature is called object fetchers. Developers create dynamic objects and pass them to Jimmer That is, save data structures of any shape. This feature is called save commands.","s":"Interaction with ORM","u":"/jimmer-doc/docs/object/dynamic","h":"#interaction-with-orm","p":826},{"i":844,"t":"Jimmer creates dynamic objects and returns them to developers Java Kotlin Your browser does not support the video tag. Your browser does not support the video tag. info Compare to GraphQL GraphQL is based on HTTP services, which can only be experienced if it crosses the boundaries of HTTP services. In Jimmer, this is the underlying API for ORM, and you can use this capability in any code logic. Until now, the GraphQL protocol does not support recursive queries on self-associated properties with infinite depth; And Jimmer supports","s":"Object Fetchers","u":"/jimmer-doc/docs/object/dynamic","h":"#object-fetchers","p":826},{"i":846,"t":"Developers create dynamic objects and pass them to Jimmer Save instructions allow developers to save data structures of any shape, rather than save simple objects. By default, when AssociatedSaveMode is set to REPLACE, Jimmer will completely replace the existing data structure in the database with the structure being saved, as shown in the figure: Top right: Users pass in a data structure of any shape for Jimmer to write to the database. Top left: Query the existing data structure from the database to compare with the new data structure passed in by users. Whatever shape of data structure the user passes in, the same shape will be queried from the database, ensuring the shapes of old and new data structures are identical. Therefore, the querying and comparison costs are determined by the complexity of the user-provided data structure. Below:Compare the new and old data structures, find the DIFF and execute corresponding SQL operations to make them consistent: Orange parts: For entity objects that exist in both new and old data structures, modify data if scalar properties have changed Blue parts: For entity objects that exist in both new and old data structures, modify associations if they have changed Green parts: For entity objects that exist in the old data structure but not in the new one, decouple this object, clear associations and possibly delete data Red parts: For entity objects that exist in the new data structure but not in the old one, insert data and establish associations tip Unlike other ORMs, Jimmer doesn't require describing how data should be saved in the entity model Whether certain scalar properties need to be saved Taking JPA as an example, this is controlled throughColumn.insertable andColumn.updatable. Whether certain association properties need to be saved Taking JPA as an example, this is controlled throughOneToOne.cascade,ManyToOne.cascade,OenToMany.cascade andManyToOne.cascade. Jimmer adopts a completely different strategy - its entity objects are not POJOs and can flexibly control the shape of data structures. That is, entity objects have dynamic properties - not specifying a property for an entity object and setting an entity's property to null are completely different things. For any entity object, Jimmer will only save the specified properties while ignoring unspecified ones. Therefore, Jimmer doesn't need to consider data saving behavior during entity modeling, but rather describes the expected behavior at runtime through the data structure being saved itself, providing absolute flexibility.","s":"Save Commands","u":"/jimmer-doc/docs/object/dynamic","h":"#save-commands","p":826},{"i":848,"t":"Immutability is used to ensure that the data structure represented by Jimmer objects never contains circular references.","s":"Immutability","u":"/jimmer-doc/docs/object/immutable/","h":"","p":847},{"i":850,"t":"Jimmer supports triggers that allow users to listen for database changes. tip Triggers can notify changes not only to objects, but also to associations.","s":"Trigger","u":"/jimmer-doc/docs/mutation/trigger","h":"","p":849},{"i":853,"t":"BinLog Trigger This is the default trigger type. It does not affect the SQL generated by Jimmer itself, has higher performance, is triggered after transaction commit, can listen to database changes caused by any reason, including data changes not caused by Jimmer API. However, it requires the database to support binlog/CDC. Transaction Trigger This trigger does not requires the database to support binlog/CDC, it is triggered before transaction commit. However, It can only listener to the data changes caused by current Jimmer application, and will generate additional query statements during the modification process to simulate the trigger, which has some impact on modification performance. info Its working mechanism is similar to Alibaba Seata's AT mode The differences between the two triggers are as follows: BinLog Trigger Transaction Trigger Trigger Time After transaction commit Before transaction commit Performance High Low Database changes listened Changes caused by any reason Only changes caused by calling current application's Jimmer API Database Requirements Support and enable binlog/CDC No requirements Working Principle Use third-party technology to push database binlog changes to message queue, Jimmer application listens to message queue Any Jimmer modification API automatically implants additional SQL queries to find data changes, similar to Alibaba Seata's AT mode Apart from the differences in this table, the notification data provided by the two triggers to the user is exactly the same.","s":"Trigger Classification","u":"/jimmer-doc/docs/mutation/trigger","h":"#trigger-classification","p":849},{"i":855,"t":"BinLog Trigger The BinLog trigger is triggered after transaction commit, facing the immutable facts. That is, the BinLog trigger has no impact on the original transaction, and is allowed to perform time-consuming operations. So it is suitable to execute multiple tasks in its handling logic, especially these tasks: Cache invalidation Heterogeneous data source synchronization Send messages to other microservices asynchronously Transaction Trigger The Transaction trigger is triggered before transaction commit, and its handling logic is injected directly into the current transaction. If an exception occurs in its event handling logic, it will cause the current transaction to fail; if its handling logic cannot complete quickly, it will cause the current transaction to hold resources for a long time. Therefore, the Transaction trigger is suitable for appending more modification behaviors in the current transaction without compromising atomicity. It is suitable for implementing business logic with strong generality through additional modifications when the database changes.","s":"Recommended Usage","u":"/jimmer-doc/docs/mutation/trigger","h":"#recommended-usage","p":849},{"i":858,"t":"Before discussing setting the trigger type, let's see how developers use triggers: sqlClient.getTriggers() or sqlClient.getTriggers(false): Returns BinLog trigger first, if not exists, returns Transaction trigger. sqlClient.getTriggers(true): Explicitly returns Transaction trigger, throws exception if not exists. To affect the trigger type that can be obtained by sqlClient.getTriggers() afterwards, you need to specify TriggerType when building SqlClient. TriggerType has three possible values: BINLOG_ONLY: Only supports BinLog trigger, this is the default configuration. sqlClient.getTriggers() and sqlClient.getTriggers(false) return BinLog trigger object sqlClient.getTriggers(true) will throw an exception, cannot return Transaction trigger object TRANSACTION_ONLY: Only supports Transaction trigger. No matter what the parameter of sqlClient.getTriggers is, it will return the same Transaction trigger object. BOTH: Supports both BinLog trigger and Transaction trigger. sqlClient.getTriggers() and sqlClient.getTriggers(false) return BinLog trigger object sqlClient.getTriggers(true) returns Transaction trigger object Here is a table to compare the three cases: Trigger Type getTriggers(false) getTriggers(true) BINLOG_ONLY Dedicated binlog triggers object Throw exception TRANSACTION_ONLY Shared transaction triggers object BOTH Dedicated binlog triggers object Dedicated transaction triggers object","s":"Concept","u":"/jimmer-doc/docs/mutation/trigger","h":"#concept","p":849},{"i":860,"t":"Q: Why is BINLOG_ONLY the default mode? A: Transaction triggers implant additional queries in all save operations to simulate triggers, which impacts performance, so it is disabled by default. Q: In TRANSACTION_ONLY mode, why do the two different trigger APIs share the same object? A: Jimmer's built-in cache consistency strategy must be driven by sqlClient.getTriggers(false), which developers cannot change. The purpose is to allow cache consistency maintenance work to not affect the modification transaction, and only start execution after transaction commit. Thus, the original transaction will not be elongated and can end quickly to release lock resources. However, not all database products support binlog/CDC. In this case, getTriggers(false) returns the transaction trigger object, masquerading as the BinLog trigger object, taking over cache consistency maintenance work that should have been handled by the BinLog trigger. That is to say, TRANSACTION_ONLY is designed for databases that do not support binlog/CDC, this is the only reason to use this mode. Q: In BOTH mode, there are two different trigger API objects, does this mean there are two chances to handle any modification? A: Yes, and this is an important feature. Unlike Jimmer's built-in cache consistency mechanism which must be driven by sqlClient.getTriggers(false), the user's business code does not have this limitation. Developers can freely decide whether an event handling logic should be registered to sqlClient.getTriggers(false) or sqlClient.getTriggers(true), or registered to both at the same time. If the developer's event handling logic contains some additional modifications that must participate in the atomic scope of the current transaction, sqlClient.getTriggers(true) should be chosen. If the developer's event handling logic does not need to participate in the current transaction, sqlClient.getTriggers(false) should be chosen to allow the current transaction to end as soon as possible and release lock resources as soon as possible. If the developer's event handling logic contains both of the above cases, it should be split into two and registered to the two triggers respectively. caution If the developer registers the same event callback for two types of triggers, then this callback will indeed be executed twice each time an event is notified. At this point, distinguishing between the two calls is very important. The parameter of the callback method is an object that can obtain the JDBC connection object. Whether its value is null can be used as a criterion to distinguish between the two: Non-null: First callback, caused by transaction trigger Null: Second callback, caused by binlog trigger Q: For databases that do not support binlog/CDC, isn't it impossible to do cache cleanup after transaction commit? A: Not exactly, it can be achieved if the developer is willing to optimize. Admittedly, such databases cannot support binlog triggers, and using transaction triggers to get data change notifications within the transaction lifetime is the only feasible method. However, it is not necessary to perform cache cleanup immediately after receiving the notification, because the cache cleanup work on remote caches like redis has network communication costs and risks of communication failure. Doing so will elongate or even fail the local transaction. Jimmer's cache system supports custom CacheOperator. By customizing CacheOperator, users can override the cache deletion behavior, record the cache deletion tasks but not execute them immediately, and perform the actual cache cleanup after the transaction is committed. Unreliable approach Customize CacheOperator and do not immediately clear the cache, but use ThreadLocal to record the keys of the caches to be deleted. Collectively clean up the cache in Spring's AfterCommit event. Reliable approach Customize CacheOperator and do not immediately clear the cache, but use a local event table in the same database to record the keys of the caches to be deleted. In Spring's AfterCommit event, take data from the local event table, clean up the cache, and if successful, delete the data in the local event table. Use a polling service to cover failures in step 2. tip Fortunately, for trigger type TRANSACTION_ONLY, Jimmer's Spring Boot Starter has already implemented this. Please refer to Cache Consistency/Transaction Trigger","s":"Q & A","u":"/jimmer-doc/docs/mutation/trigger","h":"#q--a","p":849},{"i":862,"t":"If using the Jimmer Spring Boot Starter, setting the trigger type is very simple. Just add a configuration in application.properties or application.yml. Its name is jimmer.trigger-type, and its value is BINLOG_ONLY | TRANSACTION_ONLY | BOTH.","s":"Using Jimmer Spring Boot Starter","u":"/jimmer-doc/docs/mutation/trigger","h":"#using-jimmer-spring-boot-starter","p":849},{"i":864,"t":"Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setTriggerType(TriggerType.BOTH) ...other config omitted... .build(); javax.sql.DataSource dataSource = ...; val sqlClient = newKSqlClient { setTriggerType(TriggerType.BOTH) ...other config omitted... }","s":"Not Using Jimmer Spring Boot Starter","u":"/jimmer-doc/docs/mutation/trigger","h":"#not-using-jimmer-spring-boot-starter","p":849},{"i":866,"t":"Unlike Transaction triggers, BinLog triggers require third-party technologies to push database binlog changes to the message queue, and applications need to listen to the message queue. Therefore, just specifying TriggerType as BINLOG_ONLY (default behavior) or BOTH when building the SqlClient object is not enough. There are many choices for the message queue, such as Kafka and RabbitMQ; there are also many choices for third-party technologies to push database binlog incrementally to the message queue, such as MaxWell, Debezium, Canal and DataBus. Jimmer does not restrict such choices. But to simplify the discussion, this article assumes Kafka is used as the message queue, and Maxwell (For MySQL) and Debezium (For postgres) are used as the push technologies. caution Because Debezium itself is a kafka-connector, using Debezium inevitably leads to Kafka being the message queue.","s":"BinLog Trigger Development Work","u":"/jimmer-doc/docs/mutation/trigger","h":"#binlog-trigger-development-work","p":849},{"i":868,"t":"Before development, the environment needs to be installed first, including the database, Kafka, and Maxwell or Debezium. Maxwell Enter the local directory corresponding to jimmer-examples/env-with-cache/maxwell after git clone. Execute bash ./install.sh Debezium Enter the local directory corresponding to jimmer-examples/env-with-cache/debezium after git clone. Execute bash ./install.sh","s":"Create External Environment","u":"/jimmer-doc/docs/mutation/trigger","h":"#create-external-environment","p":849},{"i":870,"t":"Whether choosing different databases (MySQL or Postgres), or choosing different push technologies (Maxwell or Debezium), there will be differences in the listening code. But in any case, the user code is quite similar, divided into the following 4 steps: Listen to the message queue and get the message body string. Use ObjectMapper.readTree for weakly typed parsing of the message text. info So-called weakly typed parsing means the resulting type is JsonNode, unrelated to business system types. Observe the content of the JsonNode and extract: Table name, referred to as tableName The sub-JsonNode of the old data before modification, referred to as oldJsonNode For insert operations, oldJsonNode is null The sub-JsonNode of the new data after modification, referred to as newJsonNode For delete operations, newJsonNode is null info The differences in listening code caused by different choices of database and push technology are reflected in this step. However, it is not difficult after observing the message content for inserts, updates, and deletes. Call JSqlClient.getBinLog().accept or KSqlClient.binLog.accept with tableName, oldJsonNode and newJsonNode. The following examples demonstrate MySQL + Maxwell and Postgres + Debezium respectively. MySQL + Maxwell For MySQL + Maxwell, the message format is typically like: { \"database\":\"jimmer_demo\", \"table\":\"book\", \"type\":\"update\", \"ts\":1688592724, \"xid\":11790, \"commit\":true, \"data\":{ \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store_id\":1, \"tenant\":\"a\", \"created_time\":\"2023-07-05 20:21:00\", \"modified_time\":\"2023-07-05 20:21:00\" }, \"old\":{ \"store_id\":2 } } After a little observation (it is recommended to look at the messages for insert, update, and delete), it is not difficult to implement the following message listening code: Java Kotlin MaxwellListener.java @Component public class MaxwellListener { private static final ObjectMapper MAPPER = new ObjectMapper(); private final Caches caches; public MaxwellListener(JSqlClient sqlClient) { this.caches = sqlClient.getCaches(); } @KafkaListener(topics = \"maxwell\") public void onMaxwellEvent( String json, Acknowledgment acknowledgment ) throws JsonProcessingException { JsonNode node = MAPPER.readTree(json); String tableName = node.get(\"table\").asText(); String type = node.get(\"type\").asText(); JsonNode data = node.get(\"data\"); switch (type) { case \"insert\": binLog.accept(tableName, null, data); break; case \"update\": binLog.accept(tableName, node.get(\"old\"), data); break; case \"delete\": binLog.accept(tableName, data, null); break; } acknowledgment.acknowledge(); } } MaxwellListener.kt @Component class MaxwellListener(sqlClient: KSqlClient) { private val caches: KCaches = sqlClient.caches @KafkaListener(topics = [\"maxwell\"]) fun onMaxwellEvent( json: String, acknowledgment: Acknowledgment ) { val node = MAPPER.readTree(json) val tableName = node[\"table\"].asText() val type = node[\"type\"].asText() val data = node[\"data\"] when (type) { \"insert\" -> binLog.accept(tableName, null, data) \"update\" -> binLog.accept(tableName, node[\"old\"], data) \"delete\" -> binLog.accept(tableName, data, null) } acknowledgment.acknowledge() } companion object { private val MAPPER = ObjectMapper() } } Postgres + Debezium For Postgres + Debezium, the message format is typically: { \"before\": { \"id\": 10, \"name\": \"GraphQL in Action\", \"edition\": 1, \"price\": \"H0A=\", \"store_id\": 1, \"tenant\": \"b\", \"created_time\": 1688590805971294, \"modified_time\": 1688590805971294 }, \"after\": { ...omitted... }, \"source\": { \"table\": \"book\", ...omitted... }, ...omitted... } We find some difficulties here, not all data can be directly recognized and converted by Jimmer's BinLog mapping mechanism: Properties of BigDecimal type (NUMERIC(M[, D]) in Postgres) like Book.price are displayed as Base64 encoded (H0A= in this example). This Base64 string is the info processed by org.apache.kafka.connect.data.Decimal Properties of LocalDateTime type (TIMESTAMP in Postgres) are displayed as numbers info Debezium's documentation will explain in detail how its various connectors process certain special data, such as how pg-connector handles decimal. The various connectors in Debezium also provide rich configurations, some of which can be used to change the default data handling method, such as changing how decimal data is handled, to avoid similar problems. However, Debezium's connectors usually serve all systems, and will not deliberately \"pamper\" a particular application. We cannot assume its configuration will always ensure output that Jimmer can understand directly. The examples that come with Jimmer deliberately do not configure the Debezium connector, letting it output kafka-connector specific data to demonstrate how Jimmer solves this problem, same as this article. Java Kotlin DebeziumCustomizer.java package ...omitted...; import org.apache.kafka.connect.data.Decimal; import org.apache.kafka.connect.data.Schema; import org.babyfish.jimmer.sql.runtime.Customizer; ...other imports omitted... @Component public class DebeziumCustomizer implements Customizer { private static final Schema BOOK_PRICE_SCHEMA = // Postgres `BOOK.PRICE` is `NUMERIC(10, 2)`, precision is 2 Decimal.schema(2); @Override public void customize(JSqlClient.Builder builder) { builder.setBinLogPropReader( ❶ LocalDateTime.class, (prop, jsonNode) -> { return Instant.ofEpochMilli( jsonNode.asLong() / 1000 ).atZone(ZoneId.systemDefault()).toLocalDateTime(); } ); builder.setBinLogPropReader( BookProps.PRICE, ❷ (prop, jsonNode) -> { byte[] bytes = Base64.getDecoder().decode(jsonNode.asText()); return Decimal.toLogical(BOOK_PRICE_SCHEMA, bytes); } ); } } DebeziumCustomizer.kt package ...omitted... import org.apache.kafka.connect.data.Decimal import org.apache.kafka.connect.data.Schema import org.babyfish.jimmer.sql.kt.cfg.KCustomizer ...other imports omitted... @Component class DebeziumCustomizer : KCustomizer { override fun customize(dsl: KSqlClientDsl) { dsl.setBinLogPropReader( LocalDateTime::class ❶ ) { _, jsonNode -> Instant.ofEpochMilli( jsonNode.asLong() / 1000 ).atZone(ZoneId.systemDefault()).toLocalDateTime() } dsl.setBinLogPropReader( Book::price ❷ ) { _, jsonNode -> Decimal.toLogical( BOOK_PRICE_SCHEMA, Base64.getDecoder().decode(jsonNode.asText()) ) } } companion object { private val BOOK_PRICE_SCHEMA = // Postgres `BOOK.PRICE` is `NUMERIC(10, 2)`, precision is 2 Decimal.schema(2) } } setBinLogPropReader allows developers to customize how to parse properties in the message that cannot be directly recognized, with two usages: ❶ Given the return type, specify how a type of properties should be parsed ❷ Precisely define how a certain property should be parsed After solving these problems, the message listening code is easy to implement: Java Kotlin DebeziumListener.java @Component public class DebeziumListener { private static final ObjectMapper MAPPER = new ObjectMapper(); private final BinLog binLog; public DebeziumListener(JSqlClient sqlClient) { this.binLog = sqlClient.getBinLog(); } @KafkaListener(topicPattern = \"debezium\\\\..*\") public void onDebeziumEvent( @Payload(required = false) String json, Acknowledgment acknowledgment ) throws JsonProcessingException { if (json != null) { // Debezium sends empty msg after delete msg JsonNode node = MAPPER.readTree(json); String tableName = node.get(\"source\").get(\"table\").asText(); binLog.accept( tableName, node.get(\"before\"), node.get(\"after\") ); } acknowledgment.acknowledge(); } } DebeziumListener.kt @Component class DebeziumListener(sqlClient: KSqlClient) { private val binLog: BinLog = sqlClient.binLog @KafkaListener(topicPattern = \"\"\"debezium\\..*\"\"\") fun onDebeziumEvent( @Payload(required = false) json: String?, acknowledgment: Acknowledgment ) { if (json !== null) { val node: JsonNode = MAPPER.readTree(json) val tableName: String = node[\"source\"][\"table\"].asText() binLog.accept( tableName, node[\"before\"], node[\"after\"] ) } acknowledgment.acknowledge() } companion object { private val MAPPER = ObjectMapper() } }","s":"Listen to Message Queue","u":"/jimmer-doc/docs/mutation/trigger","h":"#listen-to-message-queue","p":849},{"i":872,"t":"If using BinLog trigger, please enable it first as described above.","s":"Usage Examples","u":"/jimmer-doc/docs/mutation/trigger","h":"#usage-examples","p":849},{"i":874,"t":"Using Jimmer Spring Boot Starter If using the Jimmer Spring Boot Starter, trigger events will be sent as Spring events. So use @org.springframework.context.event.EventListener to handle Spring events: Java Kotlin DatabaseListener.java @Component public class DatabaseListener { @EventListener public void onEntityChanged(EntityEvent e) { if (e.getImmutableType().getJavaClass() == Book.class) { System.out.println(\"The object `Book` is changed\"); System.out.println(\"\\told: \" + e.getOldEntity()); System.out.println(\"\\tnew: \" + e.getNewEntity()); } } @EventListener public void onAssociationChanged(AssociationEvent e) { if (e.isChanged(BookProps.STORE)) { System.out.println(\"The many-to-one association `Book.store` is changed\"); System.out.println(\"\\tbook id: \" + e.getSourceId()); System.out.println(\"\\tdetached book store id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book store id: \" + e.getAttachedTargetId()); } else if (e.isChanged(BookStoreProps.BOOKS)) { System.out.println(\"The one-to-many association `BookStore.books` is changed\"); System.out.println(\"\\tbook store id: \" + e.getSourceId()); System.out.println(\"\\tdetached book id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book id: \" + e.getAttachedTargetId()); } } } DatabaseListener.kt @Component class DatabaseListener { @EventListener fun onEntityChanged(e: EntityEvent<*>) { if (e.ImmutableType.javaClass == Book::class.java) { println(\"The object `Book` is changed\") println(\"\\told: ${e.oldEntity}\") println(\"\\tnew: ${e.newEntity}\") } } @EventListener fun onAssociationChanged(e: AssociationEvent) { if (e.isChanged(Book::store)) { println(\"The many-to-one association `Book.store` is changed\") println(\"\\tbook id: ${e.sourceId}\") println(\"\\tdetached book store id: ${e.detachedTargetId}\") println(\"\\tattached book store id: ${e.attachedTargetId}\") } else if (e.isChanged(BookStore::books)) { println(\"The one-to-many association `BookStore.books` is changed\") println(\"\\tbook store id: ${e.sourceId}\") println(\"\\tdetached book id: ${e.detachedTargetId}\") println(\"\\tattached book id: ${e.attachedTargetId}\") } } } Using Low Level API If not using the Jimmer Spring Boot starter, need to manually register event handler code: Java Kotlin sqlClient.getTriggers().addEntityListener(Book.class, e -> { System.out.println(\"The object `Book` is changed\"); System.out.println(\"\\told: \" + e.getOldEntity()); System.out.println(\"\\tnew: \" + e.getNewEntity()); }); sqlClient.getTriggers().addAssociationListener(BookProps.STORE, e -> { System.out.println(\"The many-to-one association `Book.store` is changed\"); System.out.println(\"\\tbook id: \" + e.getSourceId()); System.out.println(\"\\tdetached book store id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book store id: \" + e.getAttachedTargetId()); }); sqlClient.getTriggers().addAssociationListener(BookStoreProps.BOOKS, e -> { System.out.println(\"The one-to-many association `BookStore.books` is changed\"); System.out.println(\"\\tbook store id: \" + e.getSourceId()); System.out.println(\"\\tdetached book id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book id: \" + e.getAttachedTargetId()); }); sqlClient.triggers.addEntityListener(Book::class) { println(\"The object `Book` is changed\") println(\"\\told: ${e.oldEntity}\") println(\"\\tnew: ${e.newEntity}\") } sqlClient.triggers.addAssociationListener(Book::store) { println(\"The many-to-one association `Book.store` is changed\") println(\"\\tbook id: ${e.sourceId}\") println(\"\\tdetached book store id: ${e.detachedTargetId}\") println(\"\\tattached book store id: ${e.attachedTargetId}\") } sqlClient.triggers.addAssociationListener(BookStore::books) { println(\"The one-to-many association `BookStore.books` is changed\") println(\"\\tbook store id: ${e.sourceId}\") println(\"\\tdetached book id: ${e.detachedTargetId}\") println(\"\\tattached book id: ${e.attachedTargetId}\") } Where sqlClient.getTriggers() or sqlClient.triggers is used to register handler logic to the default trigger. Can also replace sqlClient.getTriggers() or sqlClient.triggers with sqlClient.getTriggers(true) to register handler logic to the Transaction trigger.","s":"Register Handler Logic","u":"/jimmer-doc/docs/mutation/trigger","h":"#register-handler-logic","p":849},{"i":876,"t":"Now we trigger events to experience triggers. The BinLog trigger can listen to database changes caused by any reason, even if the database is modified by bypassing the application using any other means. For example, you can directly execute: update BOOK set STORE_ID = 2 where ID = 7; However, to send events to the Transaction trigger, the database must be modified through Jimmer's API, for example: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(book) .set(table.store().id(), 2L) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { set(table.store.id, 2L) where(table.id eq 7L) } .execute() The output is: The object `Book` is changed ❶ old: {\"id\":7,\"name\":\"Programming TypeScript\",\"edition\":1,\"price\":47.50,\"store\":{\"id\":1}} new: {\"id\":7,\"name\":\"Programming TypeScript\",\"edition\":1,\"price\":47.50,\"store\":{\"id\":2}} The many-to-one association `Book.store` is changed ❷ book id: 7 detached book store id: 1 attached book store id: 2 The one-to-many association `BookStore.books` is changed ❸ book store id: 1 detached book id: 7 attached book id: null The one-to-many association `BookStore.books` is changed ❹ book store id: 2 detached book id: null attached book id: 7 Where: ❶ Represents object change event ❷, ❸ and ❹ Represent association change events tip Jimmer triggers can not only simply convert table changes into object change events, but also convert foreign key changes and middle table changes into association change events.","s":"Experience Triggers","u":"/jimmer-doc/docs/mutation/trigger","h":"#experience-triggers","p":849},{"i":878,"t":"Unlike other ORMs, Jimmer uses immutable objects as entity objects.","s":"Reason","u":"/jimmer-doc/docs/object/immutable/reason","h":"","p":877},{"i":881,"t":"ORMs are often accompanied by a very headache problem: circular references. Data structures containing circular references cannot be simply JSON serialized, which is a fatal flaw for HTTP API design. In fact, this problem can be solved, for example, advanced features of JSON serialization libraries (such as Jackson) can serialize data structures containing circular references. But this is meaningless, because the serialized result contains special extended content, which cannot be understood by client programming languages. As an ORM, Jimmer of course allows users to define bidirectional associations between entity types, which is a powerful capability of ORM. However, when instantiating objects, once the developer has determined the type of the aggregate root, the data structure created can only be a unidirectional tree with the aggregate root object as the starting point. That is, bidirectional associations can be defined between entity types, keeping the possibilities of both directions. When instantiating objects, choose to use one of the association directions according to business characteristics. tip Jimmer entity-related data structures never contain circular references, so they can be directly involved in JSON serialization and then transmitted via HTTP protocols, while ensuring the simplicity of HTTP transmitted data to ensure that any programming language can understand. This brings great simplification to application development.","s":"Forbid Circular References","u":"/jimmer-doc/docs/object/immutable/reason","h":"#forbid-circular-references","p":877},{"i":883,"t":"Java Kotlin TreeNode aggregateRoot = Immutables.createTreeNode(aggregateRootDraft -> aggregateRootDraft .setName(\"Aggregate root\") .addIntoChildNodes(childDraft -> childDraft .setName(\"Child\") // Throw CircularReferenceException .setParent(aggregateRootDraft) ) ); val aggregateRoot = TreeNode { val that = this name = \"Aggregate root\" childNodes().addBy { name = \"Child\" // Throw CircularReferenceException parent = that } } info The above code uses an interface called TreeNode, which is the interface type automatically generated by Jimmer based on the user-defined type TreeNode. Readers can ignore this auto-generated interface for now, later documentation Draft will introduce it. tip This code will cause an exception: org.babyfish.jimmer.CircularReferenceException. Jimmer objects are immutable objects. Users can neither build circular references when creating objects, nor form circular references through subsequent modifications. This quality will be preserved forever.","s":"Incorrect Demo","u":"/jimmer-doc/docs/object/immutable/reason","h":"#incorrect-demo","p":877},{"i":885,"t":"In addition to ensuring absolutely no circular references between objects, immutable objects have many other benefits, including: Multi-thread safety, which is easy to understand and needs no explanation. For collection containers that rely on hashCode, such as Set and Map, object immutability is desperately needed. Once mutable objects are held by hashCode sensitive collection containers like Set or Map (as Key), developers must be very careful to ensure that the data shared by these containers is stable. If a mistake is accidentally made, it usually takes debug tracking to find the problem, which often wastes time and affects efficiency. (In fact, hashCode sensitive collection containers holding mutable objects is a common behavior, and it can also be said that most Java code is not strict, developers just avoid this problem.) In actual development, there are some other situations where objects are held for a long time. Although not dependent on hashCode, problems can also arise from holding objects for a long time, such as: Using data persisted in WebSession for a long time Using first-level cache, that is, using process-local cache in JVM memory to persist some data for a long time Careful developers certainly do not want references in WebSession or Cache that persist data for a long time to share data structures with references leaked to user code, which would lead to uncontrollable mutual interference. Therefore, when performing read/write operations on data structures persisted in WebSession or JVM internal Cache, careful developers will copy mutable data structures once before saving or returning them. Among them, copying when writing is still acceptable, but copying every time when reading is expensive. It can be seen that Using mutable objects, whether it is necessary to copy objects to ensure necessary security depends on the developer's ability to foresee risks. This requires developers to have some experience and be cautious by nature. However, even if the risks are foreseen, there is no objective standard for the solution. Being too strict will lead to too many unnecessary copies and waste, and being too loose will lead to insufficient copying and bugs (the more team members, the easier to make mistakes). Moreover, for data of a certain volume, there are often disputes within the team about the strictness of this protection mechanism, which is highly subjective. Using immutable objects, the data structure is only copied in part when it is \"modified\" (Here the \"modified\" is pseudo-modification, not real modification of the current data, which will be discussed in detail in subsequent documents. Jimmer/Immer internally optimizes this: the modified object will be copied, and from its parent object to the root node, all ancestor nodes will also be copied, while all other unchanged branches still share and reuse the original) to get a new aggregate root reference, and simply share the original reference in all other cases. It has a very strict, indisputable objectivity. tip Undoubtedly, development based on objective laws is bound to be superior to development based on subjective feelings, which is very important.","s":"Other benefits","u":"/jimmer-doc/docs/object/immutable/reason","h":"#other-benefits","p":877},{"i":887,"t":"Java has supported immutable record types since Java 14, and Kotlin's data classes can easily implement immutable classes, even supporting copy functions. However, they are designed for simple immutable objects, and have problems dealing with complex deep data structure. The reason why deep, complex immutable objects are difficult to handle is not how to create a brand new data structure from scratch, which is very simple for any programming language. The real difficulty is wanting to make some local adjustments to an existing data structure and build a new data structure. This is very difficult for current Java and Kotlin, please see First define an immutable tree node Java Kotlin TreeNode.java record TreeNode( String name, List childNodes ) {} TreeNode.java data class TreeNode( val name: String, val childNodes: List ) Prepare an old object Java Kotlin var oldTreeNode = ...blabla... val oldTreeNode = ...blabla... Let's implement three data change operations in order from simple to complex to create a brand new object Change the name property of the root node Java Kotlin TreeNode newTreeNode = new TreeNode( \"Hello\", // Set root node name oldTreeNode.childNodes() ); val newTreeNode = oldTreeNode.copy( name = \"Hello\" // Set root node name ); This case is very simple, and the problems of Java/Kotlin are not obvious yet. Change the name property of the first level child node Breadcrumb conditions: Position of first level child node: pos1 Java Kotlin TreeNode newTreeNode = new TreeNode( oldTreeNode.name(), IntStream .range(0, oldTreeNode.childNodes().size()) .mapToObj(index1 -> { TreeNode oldChild1 = oldTreeNode.childNodes().get(index1); if (index1 != pos1) { return oldChild1; } return new TreeNode( \"Hello\", // Set name of first level child node oldChild1.childNodes() ); }) .toList() ); val newTreeNode = oldTreeNode.copy( childNodes = oldTreeNode .childNodes .mapIndexed { index1, child1 -> if (index1 == pos1) { child1.copy( name = \"Hello\" // Set name of first level child node ) } else { child1 } } ) Change the name property of the second level child node Breadcrumb conditions: Position of first level child node: pos1 Position of second level child node: pos2 Java Kotlin TreeNode newTreeNode = new TreeNode( oldTreeNode.name(), IntStream .range(0, oldTreeNode.childNodes().size()) .mapToObj(index1 -> { TreeNode oldChild1 = oldTreeNode.childNodes().get(index1); if (index1 != pos1) { return oldChild1; } return new TreeNode( oldChild1.name(), IntStream .range(0, oldChild1.childNodes().size()) .mapToObj(index2 -> { TreeNode oldChild2 = oldChild1.childNodes().get(index2); if (index2 != pos2) { return oldChild2; } else { return new TreeNode( \"Hello\", // Set name of second level child node oldChild2.childNodes() ); } }) .toList() ); }) .toList() ); val newTreeNode = oldTreeNode.copy( childNodes = oldTreeNode .childNodes .mapIndexed { index1, child1 -> if (index1 == pos1) { child1.copy( childNodes = child1 .childNodes .mapIndexed { index2, child2 -> if (index2 == pos2) { child2.copy( name = \"Hello\" // Set name of second level child node ) } else { child2 } } ) } else { child1 } } ) info It can be seen that as long as the object tree has some depth, creating a new immutable object based on another immutable object (i.e. secondary \"modification\") will be a nightmare.","s":"Current Situation","u":"/jimmer-doc/docs/object/immutable/current-situation","h":"","p":886},{"i":890,"t":"The save command supports 5 save modes that control how the aggregate root itself is saved: UPSERT: This is the default mode. It first queries to check if the aggregate root object being saved exists: If it doesn't exist: Executes an INSERT statement If it exists: Executes an UPDATE statement INSERT_ONLY: Unconditionally executes an INSERT statement INSERT_IF_ABSENT: If the data already exists, ignores the operation Otherwise, inserts the data UPDATE_ONLY: Unconditionally executes an UPDATE statement NON_IDEMPOTENT_UPSERT: If the object's @Id property or @Key properties are specified, performs behavior equivalent to UPSERT Otherwise, performs an INSERT operation note This behavior is equivalent to JPA's merge or Hibernate's saveOrUpdate, but it is not recommended in Jimmer. caution Save modes only affect the aggregate root object, not other associated objects. For associated objects, please refer to Associated Object Save Mode.","s":"Save Modes","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#save-modes","p":888},{"i":892,"t":"INSERT_ONLY means unconditionally inserting data Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List allocatedIds = sqlClient .saveEntities( books, SaveMode.INSERT_ONLY ) .getItems() .stream() .map(item -> item.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(\"Allocated ids: \" + allocatedIds); val books = listOf( Book { name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val allocatedIds = sqlClient .saveEntities( books, SaveMode.INSERT_ONLY ) .items .map { it.modifiedEntity.id } println(\"Allocated ids: $allocatedIds\") INSERT_ONLY works very simply - it inserts unconditionally without any checks. The generated batch operation SQL is as follows: insert into BOOK(NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?) /* batch-0: SQL in Action, 3, 49.9, 2 */ /* batch-1: [LINQ in Action, 2, 39.9, 2 */ In this example, since the id property's corresponding column uses database auto-numbering, after the batch insertion is complete, the ids allocated by the database for all data will be returned. The print result will be: Allocated ids: [100, 101]","s":"1. INSERT_ONLY","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#1-insert_only","p":888},{"i":894,"t":"UPDATE_ONLY means unconditionally updating data, and it has two scenarios: For Id-Specified objects, modify data according to id For Key-Specified objects, modify data according to key","s":"2. UPDATE_ONLY","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#2-update_only","p":888},{"i":896,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(3L); // Matched draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(100L); // Not matched draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); BatchSaveResult result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ); System.out.println(\"Affected row count: \" + result.getTotalAffectedRowCount()); val books = listOf( Book { id = 3L name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { id = 100L name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ) println(\"Affected row count: ${result.totalAffectedRowCount}\") Since the object's id property is specified, the object is updated based on its id. The generated batch operation SQL is as follows: update BOOK set NAME = ?, EDITION = ?, PRICE = ?, STORE_ID = ? where ID = ? /* batch-0: [SQL in Action, 3, 49.9, 2, 3] * /* batch-1: [LINQ in Action, 2, 39.9, 2, 100] */ This batch operation attempts to modify two records. Assuming the database only has one matching record, the print result will be 1.","s":"Updating Data by ID","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#updating-data-by-id","p":888},{"i":898,"t":"Assume the Book entity is defined as follows: Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); ...other properties that are neither id nor key omitted... } Book.kt @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: Int ...other properties that are neither id nor key omitted... } Here Book.name and Book.edition are annotated with @Key. Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { // Id is not specified draft.setName(\"Learning GraphQL\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { // Id is not specified draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); BatchSaveResult result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ); for (MutationResultItem item : result.getItems()) { if (ImmutableObjects.isLoaded(item.getModifiedEntity(), BookProps.ID)) { System.out.println(\"Data is updated, updated id is \" + item.getModifiedEntity().id()); } else { System.out.println(\"Data is not updated\"); } } val books = listOf( Book { // Id is not specified name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { // Id is not specified name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ) for (item in result.item) { if (isLoaded(item.modifiedEntity, Book::id)) { println(\"Data is updated, updated id is ${item.isModified}\") } else { println(\"Data is not updated\") } } Since the object's id property is not specified, the object is updated based on its key. The generated batch operation SQL is as follows: update BOOK set PRICE = ?, STORE_ID = ? where NAME = ? and EDITION = ? /* batch-0: [49.9, 2, Learning GraphQL, 3] */ /* batch-1: [39.9, 2, LINQ in Action, 2] */ The print result will be: Data is updated, updated id is 3 Data is not updated","s":"Updating Data by Key","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#updating-data-by-key","p":888},{"i":900,"t":"UPSERT means first checking if the data exists - if it exists then update it, otherwise insert it For Id-Specified objects, existence is determined by id, then deciding between INSERT or UPDATE For Key-Specified objects, existence is determined by key, then deciding between INSERT or UPDATE","s":"3. UPSERT","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#3-upsert","p":888},{"i":902,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(3L); draft.setName(\"Learning GraphQL\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(100L); draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); sqlClient .saveEntities( books, SaveMode.UPSERT ); val books = listOf( Book { id = 3L name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { id = 100L name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) sqlClient.save( books, SaveMode.UPSERT ) Jimmer prioritizes using the database's native UPSERT capabilities, so it generates different SQL for different databases Database Generated SQL H2 merge into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) key(ID) values( ?, ?, ?, ?, ? ) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ MySQL insert into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) on duplicate key update NAME = values(NAME), EDITION = values(EDITION), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Postgres insert into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) on conflict(ID) do update set NAME = excluded.NAME, EDITION = excluded.EDITION, PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */","s":"Determining Data Existence by Id","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#determining-data-existence-by-id","p":888},{"i":904,"t":"If the object's id is not specified, for example: Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"Kotlin in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List ids = sqlClient .saveEntities( books, SaveMode.UPSERT ) .getItems() .stream().map(it -> it.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(ids); val books = listOf( Book { name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"GraphQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L }, Book { name = \"Kotlin in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val ids = sqlClient.save( books, SaveMode.UPSERT ).items.map{ it.id } println(ids) By default, Jimmer tries to use the database's native UPSERT capabilities whenever possible. However, in this case, it cannot achieve this (we'll discuss how to solve this issue shortly). In this situation, Jimmer will first execute a query, then based on the query results, determine which data should be INSERTed and which should be UPDATEd. This results in three SQL statements: Query, with reason provided Purpose: COMMAND(KEY_UNIQUE_CONSTRAINT_REQUIRED) SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( (? /* Learning GraphQL */, ? /* 3 */), (? /* GraphQL in Action */, ? /* 3 */), (? /* LINQ in Action */, ? /* 2 */), (? /* Kotlin in Action */, ? /* 2 */) ) info Jimmer prints KEY_UNIQUE_CONSTRAINT_REQUIRED in the logs, which is called QueryReason. Jimmer prioritizes using the database's native UPSERT capabilities, and if it cannot do so resulting in a query, it provides the QueryReason to help users investigate and find solutions. INSERT operation for non-existing data insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) /* batch-0: [LINQ in Action, 2, 39.9, 2] */ /* batch-1: [Kotlin in Action, 2, 39.9, 2] */ UPDATE operation for existing data update BOOK set PRICE = ?, STORE_ID = ? where ID = ? /* batch-0: [49.9, 2, 3] */ /* batch-1: [49.9, 2, 12] */ The printed result is: [3, 12, 100, 101] Where: 3 and 12 represent the ids of updated data 100 and 101 represent new ids assigned by the database for inserted data","s":"Determining Data Existence by Key","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#determining-data-existence-by-key","p":888},{"i":906,"t":"In the previous example, Jimmer executed a query and provided the QueryReason KEY_UNIQUE_CONSTRAINT_REQUIRED. Jimmer provides detailed documentation comments for all QueryReasons, see QueryReason for details. For KEY_UNIQUE_CONSTRAINT_REQUIRED specifically, it indicates the need for: Creating a unique constraint for Book.name and Book.edition properties: alter table book add constraint uq_book__name_edition unique(name, edition); This is because the database's UPSERT functionality depends on unique constraints (or unique indexes) Informing Jimmer through the @KeyUniqueConstraint annotation that the properties modified by @Key have corresponding unique constraints (or unique indexes) in the database Java Kotlin Book.java @Entity @KeyUniqueConstraint public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); ...omitting other properties that are neither id nor key... } Book.kt @Entity @KeyUniqueConstraint public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: Int ...omitting other properties that are neither id nor key... } caution For MySQL, you need: @KeyUniqueConstraint(noMoreUniqueConstraints = true) Once these two improvements are made, when running the previous example again, Jimmer will no longer execute a select statement but instead directly utilize the database's native UPSERT capabilities Database Generated SQL H2 merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [GraphQL in Action, 3, 49.9, 2] */ /* batch-2: [LINQ in Action, 2, 39.9, 2] */ /* batch-3: [Kotlin in Action, 2, 39.9, 2] */ MySQL insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?) on duplicate key update /* fake update to return all ids */ ID = last_insert_id(ID), NAME = values(NAME), EDITION = values(EDITION), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [GraphQL in Action, 3, 49.9, 2] */ /* batch-2: [LINQ in Action, 2, 39.9, 2] */ /* batch-3: [Kotlin in Action, 2, 39.9, 2] */ Postgres insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) on conflict( NAME, EDITION ) do update set NAME = excluded.NAME, EDITION = excluded.EDITION, PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [GraphQL in Action, 3, 49.9, 2] */ /* batch-2: [LINQ in Action, 2, 39.9, 2] */ /* batch-3: [Kotlin in Action, 2, 39.9, 2] */ info If you are using MySQL, there are two points to note: Unlike Postgres which can explicitly specify columns used for determining data existence through on conflict(NAME, EDITION), MySQL is special in that its on duplicate key cannot explicitly specify which columns are used for determining data existence. Therefore, when an insert ... on duplicate key statement doesn't insert the id field, MySQL will determine data existence based on all fields participating in unique constraints, even if these fields belong to multiple different unique constraints. Thus, you must add an additional parameter noMoreUniqueConstraints to the annotation, like: @KeyUniqueConstraint(noMoreUniqueConstraints = true) noMoreUniqueConstraints = true tells Jimmer that the table corresponding to the entity has only one unique constraint (or unique index). Users need to be responsible for their commitment. The SQL generated for MySQL includes: /* fake update to return all ids */ ID = last_insert_id(ID) This is a relatively tricky technique. If the data is updated, it returns the existing id of the updated data; otherwise, it returns the id assigned by the database for automatically inserted data. Apart from utilizing the database's native UPSERT capabilities, the functionality is exactly the same as the previous example, and the printed result will not change at all, as shown below: [3, 12, 100, 101] Where: 3 and 12 represent the ids of updated data 100 and 101 represent new ids assigned by the database for inserted data","s":"Improved Key-based Determination","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#improved-key-based-determination","p":888},{"i":908,"t":"Check if data exists in the database based on id or key. If it doesn't exist, insert it; otherwise, ignore the operation.","s":"4. INSERT_IF_ABSENT","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#4-insert_if_absent","p":888},{"i":910,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(3L); // Matched draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(100L); // Not matched draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); BatchSaveResult result = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ); System.out.println(\"Affected row count: \" + result.getTotalAffectedRowCount()); val books = listOf( Book { id = 3L // Matched name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { id = 100L // Not matched name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val result = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ) println(\"Affected row count: ${result.totalAffectedRowCount}\") Jimmer will prioritize using the database's native capabilities for INSERT_IF_ABSENT operations, generating different SQL for different databases: Database Generated SQL H2 merge into BOOK tb_1_ using(values(?, ?, ?, ?, ?)) tb_2_( ID, NAME, EDITION, PRICE, STORE_ID ) on tb_1_.ID = tb_2_.ID when not matched then insert(ID, NAME, EDITION, PRICE, STORE_ID) values (tb_2_.ID, tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID) /* batch-0: [3, SQL in Action, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ MySQL insert ignore into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Postgres insert into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) on conflict(ID) do nothing /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Assuming one record is inserted and one is ignored, the output will be: 1","s":"Check Data Existence by Id","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#check-data-existence-by-id","p":888},{"i":912,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List ids = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ) .getItems() .stream() .map(it -> it.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(ids); val books = listOf( Book { name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val ids = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ) .items .map { it.originalEntity.id } println(ids) info In this case, Jimmer will try to utilize the database's native capabilities for INSERT_IF_ABSENT operations whenever possible. If this isn't possible, Jimmer will perform a query to determine whether to proceed with insertion or ignore the operation, and will inform developers of the query reason. However, the scenario where a query is needed for determination has already been discussed in the previous UPSERT section. To simplify this article, let's assume no query is needed and we can directly use the database's native INSERT_IF_ABSENT capability. Jimmer generates different SQL for different databases: Database Generated SQL H2 merge into BOOK tb_1_ using(values(?, ?, ?, ?, ?)) tb_2_( ID, NAME, EDITION, PRICE, STORE_ID ) on tb_1_.NAME = tb_2_.NAME and tb_1_.EDITION = tb_2_.EDITION when not matched then insert(ID, NAME, EDITION, PRICE, STORE_ID) values (tb_2_.ID, tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID) /* batch-0: [3, SQL in Action, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ MySQL insert ignore into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Postgres insert into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) on conflict( NAME, EDITION ) do nothing returning ID /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ The output will be: [3, 100] Where: The first record already exists, so the insert operation is ignored, and the existing ID is 3 The second record doesn't exist, so insertion is performed with a new auto-generated ID of 100","s":"Check Data Existence by Key","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#check-data-existence-by-key","p":888},{"i":914,"t":"We've already demonstrated four modes: INSERT_ONLY, UPDATE_ONLY, UPSERT, and INSERT_IF_ABSENT. In the previous examples, the saved objects were either Id-specified or Key-specified objects. Now, let's discuss saving Wild objects, which have neither id nor key. Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List ids = sqlClient .saveEntities( books, // Default SaveMode.UPSERT ) .getItems() .stream() .map(it -> it.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(ids); val books = listOf( Book { price = BigDecimal(\"49.9\") storeId = 2L }, Book { price = BigDecimal(\"39.9\") storeId = 2L } ) val ids = sqlClient .saveEntities( books, // Default SaveMode.UPSERT ) .items .map { it.originalEntity.id } println(ids) This code will result in the following exception (formatted for readability): Save error caused by the path: \"\": Cannot save illegal entity object whose type is \"com.yourproject.model.Book\", entity with neither id nor key cannot be accepted. There are 3 ways to fix this problem: 1. Specify the id property \"id\" for save objects; 2. Use the annotation \"org.babyfish.jimmer.sql.Key\" to decorate some scalar or foreign key properties in entity type, or call \"setKeyProps\" of the save command, to specify the key properties of \"com.yourproject.model.Book\", and finally specified the values of key properties of saved objects; 3. Specify the aggregate-root save mode of the save command to \"INSERT_ONLY(function changed)\", \"INSERT_IF_ABSTENT(function changed)\", or \"NON_IDEMPOTENT_UPSERT\" To save wild objects, you can use NON_IDEMPOTENT_UPSERT, which provides the following functionality: If the saved object is a wild object, it's equivalent to INSERT_ONLY mode, which is a non-idempotent operation Otherwise, it's equivalent to UPSERT mode, which is an idempotent operation caution This behavior is equivalent to JPA's merge or Hibernate's saveOrUpdate. However, this mode may mix idempotent and non-idempotent operations, so it's not recommended.","s":"5. NON_IDEMPOTENT_UPSERT","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#5-non_idempotent_upsert","p":888},{"i":916,"t":"Jimmer provides various save methods, many of which are equivalent: Save a single entity object Original Method Equivalent Shortcut Method save(entity, SaveMode.UPSERT) save(entity) save(entity, SaveMode.INSERT_ONLY) insert(entity) save(entity, SaveMode.UPDATE_ONLY) update(entity) save(entity, SaveMode.INSERT_IF_ABSENT) insertIfAbsent(entity) Save a single InputDTO object Original Method Equivalent Shortcut Method save(inputDTO, SaveMode.UPSERT) save(inputDTO) save(inputDTO, SaveMode.INSERT_ONLY) insert(inputDTO) save(inputDTO, SaveMode.UPDATE_ONLY) update(inputDTO) save(inputDTO, SaveMode.INSERT_IF_ABSENT) insertIfAbsent(inputDTO) Batch save multiple entity objects Original Method Equivalent Shortcut Method saveEntities(entities, SaveMode.UPSERT) saveEntities(entities) saveEntities(entities, SaveMode.INSERT_ONLY) insertEntities(entities) saveEntities(entities, SaveMode.UPDATE_ONLY) updateEntities(entities) saveEntities(entities, SaveMode.INSERT_IF_ABSENT) insertEntitiesIfAbsent(entities) Batch save multiple InputDTO objects Original Method Equivalent Shortcut Method saveInputs(inputDTOs, SaveMode.UPSERT) saveInputs(inputDTOs) saveInputs(inputDTOs, SaveMode.INSERT_ONLY) insertInputs(inputDTOs) saveInputs(inputDTOs, SaveMode.UPDATE_ONLY) updateInputs(inputDTOs) saveInputs(inputDTOs, SaveMode.INSERT_IF_ABSENT) insertInputsIfAbsent(inputDTOs)","s":"Various Save Methods","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#various-save-methods","p":888},{"i":918,"t":"To better demonstrate Jimmer's batch modification features, all examples in this article use the saveEntities method to save multiple objects, rather than using the save method to save a single object. These examples flexibly adjust the format of the objects being saved to demonstrate different functionalities. However, for each specific example, all objects saved by the saveEntities method have the same format. What happens if you try to use the saveEntities method to save multiple objects with different formats? Jimmer will first group these objects by format, then apply all the above functionalities to each group.","s":"Batch Saving Objects of Different Formats","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#batch-saving-objects-of-different-formats","p":888},{"i":920,"t":"Jimmer objects are dynamic and not all properties of an object need to be initialized. It allows missing some properties. Accessing an unspecified property directly in code will cause an exception. Unspecified properties are automatically ignored in JSON serialization without exceptions. JSON serialization is mentioned here, referring to jackson. jimmer-core defines a jackson module: org.babyfish.jimmer.jackson.ImmutableModule which can add the ability of serialize/deserialize jimmer immutable objects for jackson. There are two cases: Using Spring Boot Starter In this case, Jimmer has already registered ImmutableModule to Spring as below: // Internal Jimmer code, not user code @ConditionalOnMissingBean(ImmutableModule.class) @Bean public ImmutableModule immutableModule() { return new ImmutableModule(); } Therefore, the default ObjectMapper of Spring can already serialize/deserialize Jimmer dynamic objects, and most serialization/deserialization work is done automatically by Spring during HTTP interaction, so no extra development is required. caution The default JSON handling library in Spring is jackson. Don't replace it. Using low level API Java Kotlin ObjectMapper mapper = new ObjectMapper() .registerModule(new ImmutableModule()); TreeNode treeNode = Immutables.createTreeNode( draft -> draft.setName(\"Root Node\") ); // Serialize String json = mapper.writeValueAsString(treeNode); // Deserialize TreeNode deserializedTreeNode = mapper.readValue(json, TreeNode.class); val mapper = ObjectMapper() .registerModule(ImmutableModule()) val treeNode = TreeNode { name = \"Root Node\" } // Serialize val json = mapper.writeValueAsString(treeNode) // Deserialize val deserializedTreeNode = mapper.readValue(json, TreeNode::class.java) tip For serialization, there is a handy way which is the toString method of jimmer objects.","s":"Working with Jackson","u":"/jimmer-doc/docs/object/jackson","h":"","p":919},{"i":922,"t":"Jimmer provides a series of static tool methods for operating on dynamic objects or their Drafts. info For brevity, this article only lists the strongly typed usages. There are also weakly typed versions of these refactoring methods.","s":"Tool Methods","u":"/jimmer-doc/docs/object/tool","h":"","p":921},{"i":925,"t":"Purpose: Determine if a property of a dynamic object is loaded Java Kotlin if (ImmutableObjects.isLoaded(book, BookProps.AUTHORS)) { ... } if (isLoaded(book, Book::authors)) { ... }","s":"isLoaded","u":"/jimmer-doc/docs/object/tool","h":"#isloaded","p":921},{"i":927,"t":"Purpose: Dynamically get a property of an object Exception: The property of the object is in an unloaded state Java Kotlin List authors = ImmutableObjects.get(book, BookProps.AUTHORS); val authors = get(book, Book::authors)","s":"get","u":"/jimmer-doc/docs/object/tool","h":"#get","p":921},{"i":929,"t":"Purpose: Check if a dynamic object is only set with an id property Precondition: The object type is annotated with @Entity and is an ORM entity with an id Java Kotlin if (ImmutableObjects.isIdOnly(book)) { ... } if (isIdOnly(book)) { ... }","s":"isIdOnly","u":"/jimmer-doc/docs/object/tool","h":"#isidonly","p":921},{"i":931,"t":"Purpose: Construct an object of the given type and set its id property Precondition: The object type is annotated with @Entity and is an ORM entity with an id Java Kotlin Book book = ImmutableObjects.makeIdOnly(Book.class, 1L); val book = makeIdOnly(Book::class, 1L) tip For Kotlin, the id parameter must be non-null, and the return value is also non-null. To accept a possibly null id and directly return null when id is null, call makeNullableIdOnly Java's makeIdOnly is actually equivalent to Kotlin's makeNullableIdOnly.","s":"makeIdOnly","u":"/jimmer-doc/docs/object/tool","h":"#makeidonly","p":921},{"i":933,"t":"Purpose: Check if an object is only set with an id property. I.e. no associated properties are set to non-null (including unset and set to null). info If the object is an ORM entity, it is an exception if a one-to-one or many-to-one property based directly on a foreign key is set to an associated object with only an id. Java Kotlin if (ImmutableObjects.isLonely(book)) { ... } if (isLonely(book)) { ... }","s":"isLonely","u":"/jimmer-doc/docs/object/tool","h":"#islonely","p":921},{"i":935,"t":"Purpose: Create a new object based on an existing object. The new object copies all non-associated properties from the old object, but all associated properties remain unset. info For ORM entities, special handling is performed for one-to-one and many-to-one properties based directly on foreign keys. These are set to associated objects with only ids or null. Java Kotlin Book lonelyBook = ImmutableObjects.toLonely(book); val lonelyBook = toLonely(book)","s":"toLonely","u":"/jimmer-doc/docs/object/tool","h":"#tolonely","p":921},{"i":937,"t":"Purpose: Create a new object based on an existing object. The new object only copies the id property from the old object. Precondition: The object type is annotated with @Entity and is an ORM entity with an id Java Kotlin Book lonelyBook = ImmutableObjects.toIdOnly(book); val lonelyBook = toIdOnly(book) Or Java Kotlin List lonelyBooks = ImmutableObjects.toIdOnly(books); val lonelyBooks = toIdOnly(books)","s":"toIdOnly","u":"/jimmer-doc/docs/object/tool","h":"#toidonly","p":921},{"i":939,"t":"Purpose: Shortcut for JSON deserialization Java Kotlin Book book = ImmutableObjects.fromObject( Book.class, \"{\\\"id\\\":1,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"authorIds\\\":[2,1]}\" ); val book = fromString( Book::class, \"\"\"{\"id\":1,\"name\":\"Learning GraphQL\",\"authorIds\":[2,1]}\"\"\" )","s":"fromString","u":"/jimmer-doc/docs/object/tool","h":"#fromstring","p":921},{"i":942,"t":"Purpose: Dynamically set Draft properties Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.set(draft, BookProps.AUTHOR_IDS, Arrays.asList(1L, 3L)); }); val newBook = Book(book) { set(draft, Book::authorIds, listOf(1L, 3L)) }","s":"set","u":"/jimmer-doc/docs/object/tool","h":"#set","p":921},{"i":944,"t":"Purpose: Unload a Draft property, i.e. mark a property as unloaded Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.unload(draft, BookProps.AUTHOR_IDS); }); val newBook = Book(book) { unload(draft, Book::authorIds) }","s":"unload","u":"/jimmer-doc/docs/object/tool","h":"#unload","p":921},{"i":946,"t":"Purpose: Show a property Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.show(draft, BookProps.AUTHOR_IDS); }); val newBook = Book(book) { show(draft, Book::authorIds) }","s":"show","u":"/jimmer-doc/docs/object/tool","h":"#show","p":921},{"i":948,"t":"Purpose: Hide a property Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.hide(draft, BookProps.AUTHOR_IDS); }); val newBook = Book(book) { hide(draft, Book::authorIds) }","s":"hide","u":"/jimmer-doc/docs/object/tool","h":"#hide","p":921},{"i":950,"t":"Even if entity objects support dynamism to express arbitrary data structures, conversion between entities and DTOs is still unavoidable. Jimmer provides dynamic entities that can solve a large part of the DTO explosion problem very well. Therefore, generally speaking, it is not necessary to define output DTO types to express query results. However, not all DTO types can be eliminated. Input DTO objects are hard to remove. For example, in GraphQL, although dynamic GraphQLObject data is returned for the client from the output perspective, static GraphQLInput data submitted by the client is accepted from the input perspective. Why does the GraphQL protocol define GraphQLInput as a static type? Because API explicitness and system security are very important requirements, please refer to Problems with dynamic objects as input parameters. The problems faced by the GraphQL protocol are also faced by Jimmer, which must provide a complete solution. As a comprehensive solution, Jimmer is not limited to ORM itself, but considers the whole project. To solve this problem, it provides two ways: DTO Language A solution tailored for Jimmer with extremely high development efficiency. DTO Language is designed for that part of the DTO types that cannot be eliminated, with the goal of making them extremely cheap. MapStruct A solution that combines the MapStruct framework and can implement arbitrarily complex conversion logic.","s":"DTO conversion","u":"/jimmer-doc/docs/object/view/","h":"","p":949},{"i":952,"t":"In previous documents we have seen that When the user defines the Book type, the example code can use the BookDraft type When the user defines the TreeNode type, the example code can use the TreeNodeDraft type These types ending in Draft that correspond one-to-one with user-defined types are called Draft types.","s":"Draft","u":"/jimmer-doc/docs/object/draft","h":"","p":951},{"i":955,"t":"The user first defines an immutable data interface. Here, the ORM entity annotation @Entity is not needed, the non-ORM annotation @Immutable can achieve the demo purpose. Java Kotlin TreeNode.java package yourpackage; import javax.validation.constraints.Null; import java.util.List; import org.babyfish.jimmer.Immutable; @Immutable public interface TreeNode { String name(); @Null TreeNode parent(); List childNodes(); } TreeNode.kt package yourpackage import org.babyfish.jimmer.Immutable @Immutable interface TreeNode { val name: String val parent: TreeNode? val childNodes: List }","s":"Define TreeNode","u":"/jimmer-doc/docs/object/draft","h":"#define-treenode","p":951},{"i":957,"t":"To automatically generate TreeNodeDraft, the preprocessor needs to be enabled: Java: Use AnnotationProcessor jimmer-apt Kotlin: Use KSP jimmer-ksp info How to use jimmer-apt/jimmer-ksp and how to handle possible issues are introduced in great detail in Generate Code. This article will not repeat it. Java Kotlin TreeNodeDraft.java package org.babyfish.jimmer.example.core.model; import java.util.List; import org.babyfish.jimmer.DraftConsumer; import org.babyfish.jimmer.lang.OldChain; public interface TreeNodeDraft extends TreeNode, Draft { TreeNodeDraft.Producer $ = Producer.INSTANCE; @OldChain TreeNodeDraft setName(String name); TreeNodeDraft parent(); TreeNodeDraft parent(boolean autoCreate); @OldChain TreeNodeDraft setParent(TreeNode parent); @OldChain TreeNodeDraft applyParent(DraftConsumer block); @OldChain TreeNodeDraft applyParent(TreeNode base, DraftConsumer block); List childNodes(boolean autoCreate); @OldChain TreeNodeDraft setChildNodes(List childNodes); @OldChain TreeNodeDraft addIntoChildNodes(DraftConsumer block); @OldChain TreeNodeDraft addIntoChildNodes(TreeNode base, DraftConsumer block); class Producer { private Producer() {} public TreeNode produce( DraftConsumer block ) { return produce(null, block); } public TreeNode produce( TreeNode base, DraftConsumer block ) { ...omit... } ...other code omitted... } ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { public override var name: String public override var parent: TreeNode? public override var childNodes: List public fun parent(): TreeNodeDraft public fun childNodes(): MutableList public object `$` { ...other code omitted... public fun produce( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): TreeNode { ...omit code... } } ...other code omitted... } public fun ImmutableCreator.`by`( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): TreeNode = TreeNodeDraft.`$`.produce(base, block) public fun MutableList.addBy( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): MutableList { add(TreeNodeDraft.`$`.produce(base, block) as TreeNodeDraft) return this } public fun TreeNode.copy(block: TreeNodeDraft.() -> Unit): TreeNode = TreeNodeDraft.`$`.produce(this, block) You can use it like this: Create a brand new object from scratch Java Kotlin TreeNode oldTreeNode = Immutables.createTreeNode(treeNodeDraft -> { ...omitted... }); val oldTreeNode = TreeNode { ...omitted... } Based on an existing object, make some \"changes\" and create a new object Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(oldTreeNode, treeNodeDraft -> { ...omitted... }); val newTreeNode = TreeNode(oldTreeNode) { ...omitted... } or val newTreeNode = oldTreeNode.copy { ...省略... }","s":"Generate TreeNodeDraft","u":"/jimmer-doc/docs/object/draft","h":"#generate-treenodedraft","p":951},{"i":959,"t":"TreeNode.name is a scalar property. TreeNodeDraft will define a setter method/writable property like below: Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft setName(String name); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { // var, not val public override var name: String ...other code omitted... } Developers can use this method to set the name property of the draft proxy: Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft.setName(\"Root Node\"); }); val treeNode = TreeNode { name = \"Root Node\" }","s":"Scalar properties","u":"/jimmer-doc/docs/object/draft","h":"#scalar-properties","p":951},{"i":961,"t":"TreeNode.parent is an association property. Its type is an object, not a collection. In ORM terms, it is a one-to-one or many-to-one association. TreeNodeDraft defines multiple methods for it:","s":"Reference associations","u":"/jimmer-doc/docs/object/draft","h":"#reference-associations","p":951},{"i":963,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { TreeNodeDraft parent(); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { public fun parent(): TreeNodeDraft ...other code omitted... } info Note that the return type of this method is TreeNodeDraft rather than TreeNode. That is, if the reference association of the draft object has been set and set to non-null, this method will definitely return the draft object. This allows the user to directly modify deeper associated objects. Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(treeNode, draft -> { draft.parent().setName(\"Daddy\"); draft.parent().parent().setName(\"Grandpa\"); }); @DslScope var newTreeNode = TreeNode(treeNode) { parent().name = \"Daddy\" parent().parent().name = \"Grandpa\" }","s":"Override getter parent()","u":"/jimmer-doc/docs/object/draft","h":"#override-getter-parent","p":951},{"i":965,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { TreeNode parent(boolean autoCreate); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { // This getter is equivalent to Java's `parent(false)` override fun parent: TreeNode // This function is equivalent to Java's `parent(true)` public fun parent(): TreeNodeDraft ...other code omitted... } Java's parent(false) and Kotlin's parent have two issues: Accessing it will cause an exception if the parent property of the draft object is not set If the parent property of the draft object is set to null, accessing it will return null, and null does not support further modification parent(true) can resolve the above issues. If either of the above situations is met, it will automatically create and set an associated object, then allow the user to modify it. This is a very useful feature, especially when creating objects from scratch. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(/* No `base` here */ draft -> { draft.parent(true).setName(\"Daddy\"); draft.parent(true).parent(true).setName(\"Grandpa\"); }); val treeNode = TreeNode /* No `base` here */ { parent().setName(\"Daddy\"); parent().parent().setName(\"Grandpa\"); }","s":"Add getter parent(boolean)","u":"/jimmer-doc/docs/object/draft","h":"#add-getter-parentboolean","p":951},{"i":967,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft setParent(TreeNode parent); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode, Draft { // var, not val public var parent: TreeNode ...other code omitted... } This setter allows the user to replace the entire associated object. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft.setParent( Immutables.createTreeNode(daddyDraft -> { daddyDraft.setName(\"Daddy\") }) ) }); val treeNode = TreeNode { parent = TreeNode { name = \"Daddy\" } }","s":"Add setParent","u":"/jimmer-doc/docs/object/draft","h":"#add-setparent","p":951},{"i":969,"t":"info This feature only applies to Java. Kotlin code is already concise enough and does not need this method to simplify the code. TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft applyParent( DraftConsumer block ); @OldChain TreeNodeDraft applyParent( TreeNode base, DraftConsumer block ); ...other code omitted... } These two setters are used to simplify the code. Since the two methods are highly similar in usage, only the first one is used as an example: More verbose writing: TreeNode oldTreeNode = Immutables.createTreeNode(draft -> { draft.setParent( Immutables.createTreeNode(daddyDraft -> { daddyDraft.setName(\"Daddy\") }) ) }); More concise writing: TreeNode oldTreeNode = Immutables.createTreeNode(draft -> { draft.applyParent(daddyDraft -> { daddyDraft.setName(\"Daddy\") }) }); The two are completely equivalent.","s":"Add lambda-based applyParent","u":"/jimmer-doc/docs/object/draft","h":"#add-lambda-based-applyparent","p":951},{"i":971,"t":"TreeNode.childNodes is an association property whose type is a collection rather than an object. In ORM terms, it is a one-to-many or many-to-many association. TreeNodeDraft defines multiple methods for it:","s":"Collection associations","u":"/jimmer-doc/docs/object/draft","h":"#collection-associations","p":951},{"i":973,"t":"For both Java and Kotlin, TreeNodeDraft cannot override the return type of childNodes() method. From a syntactic point of view, it can only inherit the childNodes() method of TreeNode. Java Kotlin List childNodes(); var childNodes: List caution Although the return type defined in the TreeNode interface is List, after being inherited by the TreeNodeDraft interface, its return type should be understood as List. info If the collection association of the draft object has been set, all elements in the returned collection are drafts. This allows the user to directly modify deeper associated objects in the collection. Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(treeNode, draft -> { ((TreeNodeDraft) draft .childNodes().get(0) ).setName(\"Son\"); ((TreeNodeDraft) draft .childNodes().get(0) .childNodes().get(0) ).setName(\"Grandson\"); }); val newTreeNode = TreeNode(treeNode) { (childNodes[0] as TreeNodeDraft) .name = \"Son\" (childNodes[0].childNodes[0] as TreeNodeDraft) .name = \"Son\" } danger The two forced type conversions in the above code significantly impair the developer experience. Therefore, this usage is not recommended in actual projects. To achieve the same purpose, the childNodes(boolean) method introduced below is more recommended.","s":"Inherit getter childNodes()","u":"/jimmer-doc/docs/object/draft","h":"#inherit-getter-childnodes","p":951},{"i":975,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { List childNodes(boolean autoCreate); ...other code omitted... } childNodes(false) is equivalent to childNodes(), and accessing it will cause an exception if the childNodes property of the draft object is not set. childNodes(true) will resolve this problem by automatically creating and setting a collection if the collection association property has not yet been set, then allowing the user to modify that collection. TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode, Draft { override var childNodes: List fun childNodes(): MutableList ...other code omitted... } The getter of the childNodes property is equivalent to Java's childNodes(false). Accessing it will cause an exception if this mutable proxy property is not set. The childNodes() function is equivalent to Java's childNodes(true). It automatically creates the property if not set, allowing the user to modify the collection. Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(treeNode, draft -> { draft .childNodes(false) .get(0) .setName(\"Son\"); draft .childNodes(false) .get(0) .childNodes(false) .get(0) .setName(\"Grandson\"); }); tip Indeed, when the parameter is true, childNodes(boolean) can automatically create the collection when the childNodes property is not specified. However, when the parameter is false, it is also very useful. Because the return type of this method is List instead of List, the developer-unfriendly code in the previous example will no longer exist. val newTreeNode = TreeNode(treeNode) { childNodes()[0].name = \"Son\" childNodes()[0].childNodes()[0].name = \"Grandson\" }","s":"Add getter childNodes(boolean)","u":"/jimmer-doc/docs/object/draft","h":"#add-getter-childnodesboolean","p":951},{"i":977,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft setChildNodes(List childNodes); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode, Draft { // var, not val override var childNodes: List ...other code omitted... } This setter allows the user to replace the entire associated collection. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft.setChildNodes( Arrays.asList( Immutables.createTreeNode(childDraft -> { childDraft.setName(\"Eldest son\") }), Immutables.createTreeNode(childDraft -> { childDraft.setName(\"Second son\") }) ) ) }); val treeNode = TreeNode { childNodes = listOf( TreeNode { name = \"Eldest son\" }, TreeNode { name = \"Second son\" } ) } info Somewhat cumbersome, the addIntoChildNodes to be introduced below is more recommended.","s":"Add setChildNodes","u":"/jimmer-doc/docs/object/draft","h":"#add-setchildnodes","p":951},{"i":979,"t":"In the example above, we used setChildNodes to replace the entire collection, but we can also choose to add collection elements one by one, rather than replacing the entire collection at one time. The generated code is: Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft addIntoChildNodes( DraftConsumer block ); @OldChain TreeNodeDraft addIntoChildNodes( TreeNode base, DraftConsumer block ); ...other code omitted... } TreeNodeDraft.java @DslScope public interface TreeNodeDraft : TreeNode, Draft { public fun childNodes(): MutableList ...other code omitted... } public fun MutableList.addBy( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): MutableList { ...omit... return this; } You should use it like this: Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft .addIntoChildNodes(childDraft -> childDraft.setName(\"Eldest son\") ) .addIntoChildNodes(childDraft -> childDraft.setName(\"Second son\") ) }); val treeNode = TreeNode { childNodes().addBy { name = \"Eldest son\" } childNodes().addBy { name = \"Second son\" } } info This approach implicitly contains a feature that the childNodes property of the draft object is not set and the collection is automatically created, i.e. it contains a built-in childNodes(true). Obviously, this approach is simpler than using the setter to replace the entire collection, so it is more recommended.","s":"Add addIntoChildNodes","u":"/jimmer-doc/docs/object/draft","h":"#add-addintochildnodes","p":951},{"i":982,"t":"Jimmer extends MapStruct to support using mapstruct to complete the mutual conversion between Jimmer dynamic entity objects and static DTO objects.","s":"Introduction","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#introduction","p":980},{"i":984,"t":"Jimmer's entity objects are dynamic (similar to scalar attribute lazy loading introduced in Hibernate 3), which is a pattern that earlier versions of MapStruct did not consider. After communicating with MapStruct, MapStruct will support this behavior starting from 1.6.0. caution Therefore, please use 1.6.0 or higher version of MapStruct whenever possible.","s":"Notes","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#notes","p":980},{"i":986,"t":"Unlike DTO Language which pursues fast development but supports fixed conversion logic, mapstruct can implement arbitrarily complex conversion logic. Unlike DTO Language which directly generates brand new DTO types, mapstruct can integrate existing DTO types.","s":"Advantages","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#advantages","p":980},{"i":988,"t":"DTO Language is more recommended for the following reasons: Non-negligible development costs DTO Language is a solution tailored for Jimmer with development efficiency that cannot be compared when combined with any other technical solutions. Not very suitable for Output DTO The DTO types automatically generated by the DTO language have built-in Object Fetchers, so they can be used as query output types (although not recommended), please refer to: Object Fetcher/DTO Query Spring Data/Query DTO However, manually defined DTO types do not have corresponding Object Fetcher definitions, and only support mutual conversion with dynamic entities. Although Object Fetchers can be manually defined for this, there is a risk that the DTO and Object Fetcher shapes will be inconsistent. So it is not suitable as Output DTO. Kotlin risks mapstruct is based on apt (Annotation Processor). Therefore, this requires using kapt in Kotlin, which will significantly reduce the compilation speed of Kotlin projects. Kotlin has deprecated kapt in favor of ksp. Therefore, using kapt may encounter problems in the future as Kotlin evolves.","s":"Disadvantages","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#disadvantages","p":980},{"i":990,"t":"For converting static POJOs to Jimmer dynamic objects, MapStruct does not know how to build Jimmer objects. So Jimmer's own preprocessor (Java's jimmer-apt or Kotlin's jimmer-ksp) generates some MapStruct-oriented code in Draft, allowing MapStruct to build Jimmer objects through its Builder mode. Jimmer extends MapStruct's Annotation Processor. This extension allows MapStruct to utilize the capabilities reserved for MapStruct in the generated Draft to build Jimmer objects. This extension is called jimmer-mapstruct-apt For Java, jimmer-mapstruct-apt is included in jimmer-apt For Kotlin, jimmer-ksp and jimmer-mapstruct-apt must be used together in the maven or gradle configuration file. If you use Gradle plugin Jimmer, the plugin will automatically configure it for you when you have the MapStruct kapt dependency. Java(Maven) Java(Gradle) Kotlin(Maven) Kotlin(Gradle.kts) Java(Gradle Plugin) Kotlin(Gradle Plugin) pom.xml ...omit other code... ➀ org.projectlombok lombok ${lombok.version} ➊ org.mapstruct mapstruct ${mapstruct.version} ...omit other dependencies... org.apache.maven.plugins maven-compiler-plugin 3.10.1 ➁ org.projectlombok lombok ${lombok.version} ➋ org.babyfish.jimmer jimmer-apt ${jimmer.version} ➌ org.mapstruct mapstruct-processor ${mapstruct.version} ...omit other code... build.gradle dependencies { implementation \"org.projectlombok:lombok:${lombok.version}\" ➀ implementation \"org.mapstruct:mapstruct:${mapstructVersion}\" ➊ annotationProcessor \"org.projectlombok:lombok:${lombok.version}\" ➁ annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" ➋ annotationProcessor \"org.mapstruct:mapstruct-processor:${mapstructVersion}\" ➌ ...omit other dependencies... } pom.xml ...omit other code... src/main/kotlin src/test/kotlin ➊ org.mapstruct mapstruct ${mapstruct.version} ...omit other dependencies... org.jetbrains.kotlin kotlin-maven-plugin ${kotlin.version} compile compile compile test-compile test-compile test-compile ksp org.mapstruct ➌ mapstruct-processor ${mapstruct.version} org.babyfish.jimmer ⓐ jimmer-mapstruct-apt ${jimmer.version} com.dyescape kotlin-maven-symbol-processing 1.3 org.babyfish.jimmer ➋ jimmer-ksp ${jimmer.version} ...omit other code... build.gradle.kts plugins { id(\"com.google.devtools.ksp\") version \"1.7.10-1.0.6\" kotlin(\"kapt\") version \"1.7.10\" ...omit other plugins... } dependencies { implementation(\"org.mapstruct:mapstruct:${mapstructVersion}\") ➊ ksp(\"org.babyfish.jimmer:jimmer-ksp:${jimmerVersion}\") ➋ kapt(\"org.mapstruct:mapstruct-processor:${mapstructVersion}\") ➌ kapt(\"org.babyfish.jimmer:jimmer-mapstruct-apt:${jimmerVersion}\") ⓐ ...omit other dependencies... } kotlin { sourceSets.main { kotlin.srcDir(\"build/generated/ksp/main/kotlin\") } } build.gradle plugins { id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...omit other plugins... } jimmer { version = \"${jimmerVersion}\" ...omit other configurations... } dependencies { implementation \"org.projectlombok:lombok:${lombok.version}\" ➀ implementation \"org.mapstruct:mapstruct:${mapstructVersion}\" ➊ annotationProcessor \"org.projectlombok:lombok:${lombok.version}\" ➁ annotationProcessor \"org.mapstruct:mapstruct-processor:${mapstructVersion}\" ➍ // there's no need to add org.babyfish.jimmer:jimmer-apt to dependencies manually // when mapstruct-processor dependency is detected，the gradle plugin will add jimmer-apt to dependencies automatically ...omit other dependencies... } build.gradle.kts plugins { id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" id(\"com.google.devtools.ksp\") version \"1.7.10+\" kotlin(\"kapt\") version \"1.7.10\" ...omit other plugins... } jimmer { version = \"${jimmerVersion}\" ...omit other configurations... } dependencies { implementation(\"org.mapstruct:mapstruct:${mapstructVersion}\") ➊ kapt(\"org.mapstruct:mapstruct-processor:${mapstructVersion}\") ➌ ...omit other dependencies... } In this example, we assume static POJOs are written in Java using lombok. Language Location Description Java and Kotlin ➊ Introduce mapstruct dependency for user code to use mapstruct annotations ➋ Use Jimmer's preprocessor to generate related source code for dynamic types, Java uses jimmer-apt, Kotlin uses jimmer-ksp ➌ Use mapstruct's annotation processor to generate source code (introduced later) Java only ➀ Introduce lombok dependency for user code to use lombok annotations ➁ Use Lombok preprocessor to modify static POJO class code, e.g. add getters, setters Kotlin only ⓐ Use jimmer-mapstruct-apt to extend ➌","s":"Dependencies and Preprocessors","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#dependencies-and-preprocessors","p":980},{"i":992,"t":"Java Kotlin BookInput.java @Data public class BookInput { @Nullable private Long id; private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; private List authorIds; } BookInput.java data class BookInput( val id: Long? = null, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, val authorIds: List ) note The @Nullable annotation is used in the Java POJO code only to improve readability and has no functional effect Three properties of this POJO need to be explained: BookInput.id Here, BookInput.id is allowed to be null. This is necessary, for example, the id does not need to be specified when inserting data. The dynamic property Book.id of the entity object does not allow null (Jimmer prohibits id from being null, please refer to Mapping/Basic Mapping/@Id) The two contradict each other, so how to convert BookInput to Book? tip Jimmer agrees that if the property of the POJO can be null while the corresponding property of the dynamic object cannot be null, the corresponding property of the dynamic object will not be assigned and will remain missing. BookInput.storeId This is obviously an associated id for the dynamic entity object property Book.store. This kind of dynamic object property is defined as an associated object, but in the POJO it is defined as an associated id, called a short association. BookInput.authorIds This is obviously a collection of associated ids, for the dynamic entity object property Book.authors. This kind of dynamic object property is defined as an associated objects, but in the POJO it is defined as an associated ids, called a short association. The other properties are exactly the same as the original entity definition and need no explanation.","s":"Define POJO","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#define-pojo","p":980},{"i":994,"t":"The most important thing when using mapstruct is to define the Mapper, as follows Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); } BookInputMapper.java @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(input: BookInput): Book } This Mapper provides a toBook method to convert a BookInput object to a Book object. BookInput.id, BookInput.id, BookInput.name and BookInput.price are all non-associated properties that mapstruct can handle well. note The issue that BookInput.id can be null while Book.id cannot be null has been discussed before, so it won't be repeated here. The key is how BookInput.storeId and BookInput.authorIds should be mapped, which falls into two cases: The entity defines @IdView properties The entity does not define @IdView properties","s":"Define Mapper","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#define-mapper","p":980},{"i":996,"t":"If the entity type defines @IdView properties, for example: Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface Book { ...omit other properties... @ManyToOne @Nullable BookStore store(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) List authors(); @IdView // id view of associated object store Long storeId(); // id view of all objects in associated collection authors @IdView(\"authors\") List authorIds(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Book { ...omit other properties... @ManyToOne val store: BookStore? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) val authors: List @IdView // id view of associated object store val storeId: Long? // id view of all objects in associated collection authors @IdView(\"authors\") val authorIds: List } In this case, the entity object and POJO correspond completely, and the Mapper does not need any modification.","s":"If the entity defines @IdView properties","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#if-the-entity-defines-idview-properties","p":980},{"i":998,"t":"If the entity type does not define @IdView properties, the Mapper needs to be modified: Convert BookInput.storeId to a BookStore object with only the id, then assign it to Book.store Convert BookInput.authorIds to a collection of Author objects with only ids, then assign it to Book.authors Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") Book toBook(BookInput input); @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") BookStore toBookStore(Long id); @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") Author toAuthor(Long id); } BookInputMapper.java @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") fun toBook(input: BookInput): Book @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") fun toBookStore(id: Long?): BookStore @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") fun toAuthor(id: Long?): Author } Since mapstruct also supports @Mapping(target = \"store.id\", source = \"storeId\"), the following syntax can also be used to simplify the code: Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store.id\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") Book toBook(BookInput input); @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") Author toAuthor(Long id); } BookInputMapper.java @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store.id\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") fun toBook(input: BookInput): Book @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") fun toAuthor(id: Long?): Author }","s":"If the entity does not define @IdView properties","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#if-the-entity-does-not-define-idview-properties","p":980},{"i":1000,"t":"Now we can convert BookInput to Book: Java Kotlin BookInput input = ...omit...; BookInputMapper mapper = Mappers.getMapper(BookInputMapper.class); Book book = mapper.toBook(input); val input: BookInput = ...omit... val mapper = Mappers.getMapper(BookInputMapper::class.java) val book = mapper.toBook(input)","s":"Usage","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#usage","p":980},{"i":1002,"t":"Jimmer provides a simple interface, org.babyfish.jimmer.Input public interface Input { E toEntity(); } Dynamic objects will never implement this interface, this interface should be implemented by user-defined static POJO classes. Its function is very simple, just convert the current static POJO to a dynamic object. This interface can provide convenience at the syntax level. Whether it is the underlying save command or the top-level spring-data base interface JRepository/KRepository, its sava method directly accepts Input parameters, without the user having to call the Mapper to complete the conversion. If you want this convenience at the syntax level, you can choose to have the POJO implement this interface by modifying the BookInput code as follows: Java Kotlin BookInput.java @Data public class BookInput implements Input { ❶ private static final Converter CONVERTER = Mappers.getMapper(Converter.class); ...omit private fields... @Override public Book toEntity() { ❷ return CONVERTER.toBook(this); } @Mapper interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); ...omit other mapstruct configuration... } } BookInput.kt data class BookInput( ...omit... ): Input { ❶ override fun toEntity(): Book = ❷ CONVERTER.toBook(this) @Mapper internal interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(input: BookInput): Book ...omit other mapstruct configuration... } companion object { @JvmStatic private val CONVERTER = Mappers.getMapper(Converter::class.java) } } ❶ BookInput class implements interface org.babyfish.jimmer.Input ❷ Implement Input.toEntity method, use MapStruct to convert the current static Input DTO object to the dynamic Book entity object. This is the only function of this class.","s":"Make POJO implement Input interface","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#make-pojo-implement-input-interface","p":980},{"i":1004,"t":"In order to solve the inconvenience of secondary \"modification\" (creating a new immutable object based on another immutable object) of complex immutable objects in the current JVM ecosystem, some immutable object frameworks were born: Immutables FreeBuilder Arrow-Kt(Kotlin) Kopyk(Kotlin) MuteKt(Kotlin) Jimmer is an ORM framework, and handling deep data structures is a core issue for ORM, so Jimmer must do similar work. Jimmer needs to provide elegant dual language support for both Java and Kotlin at the same time. None of the above solutions can meet this requirement, so Jimmer did not use any of them, but chose to transplant immer from the JavaScript/TypeScript field. Next, we will demonstrate the power of immutable objects transplanted from immer in three steps: Define immutable types Create an immutable data structure from scratch Based on an existing data structure, create a new data structure according to some desired modifications. This last step is where the core value of immer lies. Please pay close attention.","s":"Solution","u":"/jimmer-doc/docs/object/immutable/solution","h":"","p":1003},{"i":1006,"t":"To demonstrate this feature, there is no need for the @Entity annotation on ORM entities, the non-ORM @Immutable is sufficient. Java Kotlin TreeNode.java package yourpackage; import java.util.List; import org.babyfish.jimmer.Immutable; @Immutable public interface TreeNode { String name(); List childNodes(); } TreeNode.kt package yourpackage import org.babyfish.jimmer.Immutable @Immutable interface TreeNode { val name: String val childNodes: List }","s":"1. Define immutable type","u":"/jimmer-doc/docs/object/immutable/solution","h":"#1-define-immutable-type","p":1003},{"i":1008,"t":"Java Kotlin TreeNode treeNode = Immutables.createTreeNode(root -> { root.setName(\"Root\").addIntoChildNodes(food -> { food .setName(\"Food\") .addIntoChildNodes(drink -> { drink .setName(\"Drink\") .addIntoChildNodes(cocacola -> { cocacola.setName(\"Cocacola\"); }) .addIntoChildNodes(fanta -> { fanta.setName(\"Fanta\"); }); ; }); ; }); }); val treeNode = TreeNode { name = \"Root\" childNodes().addBy { name = \"Food\" childNodes().addBy { name = \"Drinks\" childNodes().addBy { name = \"Cocacola\" } childNodes().addBy { name = \"Fanta\" } } } }","s":"2. Create data structure from scratch","u":"/jimmer-doc/docs/object/immutable/solution","h":"#2-create-data-structure-from-scratch","p":1003},{"i":1010,"t":"Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode( treeNode, // existing data root -> { root .childNodes(false).get(0) // Food .childNodes(false).get(0) // Drink .childNodes(false).get(0) // Cocacola .setName(\"Cocacola plus\"); } ); // Show that `newTreeNode` reflects the developer's desired modifications // Note that this does not affect the existing `treeNode` at all System.out.println(\"treeNode:\" + treeNode); System.out.println(\"newTreeNode:\" + newTreeNode); /* * val newTreeNode = treeNode.copy { * ... * } * * is actually shorthand for * * val newTreeNode = TreeNode(treeNode) { * ... * } */ val newTreeNode = treeNode.copy { childNodes()[0] // Food .childNodes()[0] // Drinks .childNodes()[0] // Cocacola .name += \" plus\" } // Show that `newTreeNode` reflects the developer's desired modifications // Note that this does not affect the existing `treeNode` at all println(\"treeNode: $treeNode\") println(\"newTreeNode: $newTreeNode\") Output (the actual printed output is compact, but is formatted here for readability) treeNode: { \"name\":\"Root\", \"childNodes\":[ { \"name\":\"Food\", \"childNodes\":[ { \"name\":\"Drink\", \"childNodes\":[ {\"name\":\"Coco Cola\"}, {\"name\":\"Fanta\"} ] } ] } ] } newTreeNode: { \"name\":\"Root\", \"childNodes\":[ { \"name\":\"Food\", \"childNodes\":[ { \"name\":\"Drink\", \"childNodes\":[ {\"name\":\"Coco Cola plus\"}, {\"name\":\"Fanta\"} ] } ] } ] } As you can see, treeNode is unaffected, and newTreeNode reflects the user's desired modifications. This transplant is a powerful complement to the JVM ecosystem. This framework is named Jimmer, paying tribute to immer. info The sample code above uses a type called TreeNodeDraft, which is the interface type automatically generated by Jimmer based on the user-defined type TreeNode. Readers can ignore this auto-generated interface for now, later documentation Draft will introduce it.","s":"3. Create new data based on existing data","u":"/jimmer-doc/docs/object/immutable/solution","h":"#3-create-new-data-based-on-existing-data","p":1003},{"i":1012,"t":"In this series of articles, we will introduce: Jimmer's positioning and existing pain points The revolutionary nature of Jimmer The examples that come with the project How to create a Jimmer project from scratch Jimmer's performance advantages","s":"Introduction ★","u":"/jimmer-doc/docs/overview/","h":"","p":1011},{"i":1014,"t":"Previous documents have discussed in detail the dynamic and immutable properties of Jimmer entities. This introduces a new feature: visibility.","s":"Visibility","u":"/jimmer-doc/docs/object/visibility","h":"","p":1013},{"i":1016,"t":"For Jimmer entities, although properties are mostly independent, in some cases multiple properties share private data and thus affect each other. We call this entanglement between properties. These cases include: Java/Kotlin-based calculated properties (review details) Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { String firstName(); String lastName(); @Formula(dependencies = {\"firstName\", \"lastName\"}) default String fullName() { return firstName() + ' ' + lastName(); } ...Omit other properties... } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { val firstName: String val lastName: String @Formula(dependencies = [\"firstName\", \"lastName\"]) val fullName: String get() = \"$firstName $lastName\" ...Omit other properties... } Author.fullName has no private data, it depends on Author.firstName and Author.lastName. Although Author.fullName is defined as a calculated property, it can also be considered a view property from another perspective. If treating Author.firstName and Author.lastName as original properties, then Author.fullName can be considered a view property based on them. @IdView view properties (review details) Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface Book { ...Omit other properties... @ManyToOne @Nullable BookStore store(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) List authors(); @IdView // View of associated object store's id Long storeId(); // View of ids of all objects in associated collection authors @IdView(\"authors\") List authorIds(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Book { ...Omit other properties... @ManyToOne val store: BookStore? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) val authors: List @IdView // View of associated object store's id val storeId: Long? // View of ids of all objects in associated collection authors @IdView(\"authors\") val authorIds: List } Book.store is the original property, Book.storeId is the view property based on it Book.authors is the original property, Book.authorIds is the view property based on it @ManyToManyView view properties (review details) Java Kotlin Student.java @Entity public interface Student { // In step 1, already declared one-to-many association `learningLinks` @OneToMany(mappedBy = \"student\") List learningLinks(); @ManyToManyView( prop = \"learningLinks\", deeperProp = \"course\" ) List courses(); ...Omit other code... } Student.kt @Entity interface Student { @OneToMany(mappedBy = \"student\") val learningLinks: List @ManyToManyView( prop = \"learningLinks\", deeperProp = \"course\" ) val courses: List ...Omit other code... } Student.learningLinks is the original property, Student.courses is the view property based on it. The commonality in the examples above is that there are original properties and view properties. The original properties have their own private data, while the view properties have none. The view properties just observe the values of the original properties from a different perspective. From an internal implementation perspective, a view property actually shares private data with the original property. This means knowing one value necessarily reveals partial information about the other's value. Hence they can be metaphorically described as entangled properties.","s":"Entangled Properties","u":"/jimmer-doc/docs/object/visibility","h":"#entangled-properties","p":1013},{"i":1018,"t":"We introduced entangled properties, with original properties and view properties. The real data is held by the original properties, while the view properties only observe. When using an object fetcher to fetch a view property, the internal logic will translate it into fetching the original property, for example: Fetching Author.fullName is translated internally into fetching Author.firstName and Author.lastName Fetching Book.storeId is translated internally into fetching Book.store Fetching Book.authorIds is translated internally into fetching Book.authors Fetching Student.courses is translated internally into fetching Student.learningLinks Let's take Book.authorIds and Book.authors to demonstrate how object fetchers handle original properties and view properties differently: Fetch the original property Java Kotlin Book book = sqlClient.findById( Fetchers.BOOK_FETCHER .allScalarFields() .authors(), // Associated objects with only id 1L ); System.out.println(book); val book = sqlClient.findById( newFetcher(Book::class).by { allScalarFields() authors() // Associated objects with only id }, 1L ) println(book) The authors() in the fetcher has no arguments, indicating it fetches a collection of author objects with only id properties. The result is (manually formatted for readability): { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] } Fetch the view property Java Kotlin Book book = sqlClient.findById( Fetchers.BOOK_FETCHER .allScalarFields() .authorIds(), // Associated ids, not objects 1L ); System.out.println(book); val book = sqlClient.findById( newFetcher(Book::class).by { allScalarFields() authorIds() // Associated ids, not objects }, 1L ) println(book) This time the result is (manually formatted for readability): { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authorIds\":[ 2, 1 ] } Although the returned data is equivalent, the formats are completely different. We said earlier that when an object fetcher fetches a view property, it translates internally into fetching the original property. Since this is the case, the underlying logic should be exactly the same. Where does this difference come from?","s":"Object Fetchers and Entangled Properties","u":"/jimmer-doc/docs/object/visibility","h":"#object-fetchers-and-entangled-properties","p":1013},{"i":1020,"t":"The question above is, with identical underlying logic, why do two queries with the same logic return data in different formats? Jimmer can control the visibility of each property, making it shown or hidden. Unlike dynamic where a property can be loaded or unloaded, visibility is an orthogonal feature, completely unrelated to dynamism. Visibility only affects Jackson serialization of objects (including their own toString behavior), deciding whether a property is serialized. Other than that, it does not impact any other behavior of the object. So the previous examples can be easily explained: First query: Book.authors is shown, Book.authorIds is hidden Second query: Book.authors is hidden, Book.authorIds is shown tip Only when both conditions below are met will a property participate in Jackson serialization Dynamism: the property is set Visibility: the property is shown See tool methods for how to control visibility of Jimmer object properties yourself","s":"Property Visibility","u":"/jimmer-doc/docs/object/visibility","h":"#property-visibility","p":1013},{"i":1022,"t":"Not only can Jimmer bring you powerful features, but it can also bring you ultimate performance. The source code for benchmarking is here, using H2 in-memory database, no environment preparation needed to run directly.","s":"Benchmark Report","u":"/jimmer-doc/docs/overview/benchmark","h":"","p":1021},{"i":1025,"t":"The x-axis indicates the number of data objects queried from the database each time. The y-axis indicates the number of operations per second. Chart Data Show native JDBC metrics Framework Data count Ops/s JDBC(ColIndex) 10 662071 JDBC(ColName) 10 345169 Jimmer(Java) 10 315312 Jimmer(Kotlin) 10 309029 EasyQuery 10 206634 MyBatis 10 68743 Exposed 10 92494 JPA(Hibernate) 10 90542 JPA(EclipseLink) 10 64230 JOOQ 10 69408 Nutz 10 76904 ObjectiveSQL 10 56245 Spring Data JDBC 10 20494 Ktorm 10 19152 JDBC(ColIndex) 20 453226 JDBC(ColName) 20 238107 Jimmer(Java) 20 224179 Jimmer(Kotlin) 20 230622 EasyQuery 20 135063 MyBatis 20 43940 Exposed 20 66934 JPA(Hibernate) 20 59926 JPA(EclipseLink) 20 33421 JOOQ 20 39737 Nutz 20 39501 ObjectiveSQL 20 29975 Spring Data JDBC 20 10704 Ktorm 20 9520 JDBC(ColIndex) 50 259484 JDBC(ColName) 50 125589 Jimmer(Java) 50 132673 Jimmer(Kotlin) 50 128315 EasyQuery 50 92230 MyBatis 50 20050 Exposed 50 26693 JPA(Hibernate) 50 25893 JPA(EclipseLink) 50 13634 JOOQ 50 18373 Nutz 50 16639 ObjectiveSQL 50 12455 Spring Data JDBC 50 4146 Ktorm 50 4385 JDBC(ColIndex) 100 130991 JDBC(ColName) 100 72424 Jimmer(Java) 100 77044 Jimmer(Kotlin) 100 74499 EasyQuery 100 45502 MyBatis 100 10541 Exposed 100 19483 JPA(Hibernate) 100 13096 JPA(EclipseLink) 100 6802 JOOQ 100 8145 Nutz 100 8903 ObjectiveSQL 100 6251 Spring Data JDBC 100 2229 Ktorm 100 2091 JDBC(ColIndex) 200 77725 JDBC(ColName) 200 33068 Jimmer(Java) 200 41474 Jimmer(Kotlin) 200 36656 EasyQuery 200 28085 MyBatis 200 5310 Exposed 200 10008 JPA(Hibernate) 200 6900 JPA(EclipseLink) 200 3238 JOOQ 200 4186 Nutz 200 4374 ObjectiveSQL 200 3470 Spring Data JDBC 200 1025 Ktorm 200 1063 JDBC(ColIndex) 500 32109 JDBC(ColName) 500 16234 Jimmer(Java) 500 16371 Jimmer(Kotlin) 500 16870 EasyQuery 500 11666 MyBatis 500 2137 Exposed 500 3894 JPA(Hibernate) 500 2491 JPA(EclipseLink) 500 1361 JOOQ 500 1707 Nutz 500 2040 ObjectiveSQL 500 1259 Spring Data JDBC 500 447 Ktorm 500 427 JDBC(ColIndex) 1000 16188 JDBC(ColName) 1000 8346 Jimmer(Java) 1000 8831 Jimmer(Kotlin) 1000 7932 EasyQuery 1000 4427 MyBatis 1000 1048 Exposed 1000 2082 JPA(Hibernate) 1000 1207 JPA(EclipseLink) 1000 650 JOOQ 1000 832 Nutz 1000 957 ObjectiveSQL 1000 559 Spring Data JDBC 1000 197 Ktorm 1000 168","s":"Operations Per Second","u":"/jimmer-doc/docs/overview/benchmark","h":"#operations-per-second","p":1021},{"i":1027,"t":"The x-axis indicates the number of data objects queried from the database each time. The y-axis indicates the operation time (microseconds) for each operation. Chart Data Framework Data count Time(μs) JDBC(ColIndex) 10 2 JDBC(ColName) 10 3 Jimmer(Java) 10 3 Jimmer(Kotlin) 10 3 EasyQuery 10 5 MyBatis 10 15 Exposed 10 11 JPA(Hibernate) 10 11 JPA(EclipseLink) 10 16 JOOQ 10 14 Nutz 10 13 ObjectiveSQL 10 18 Spring Data JDBC 10 49 Ktorm 10 52 JDBC(ColIndex) 20 2 JDBC(ColName) 20 4 Jimmer(Java) 20 4 Jimmer(Kotlin) 20 4 EasyQuery 20 7 MyBatis 20 23 Exposed 20 15 JPA(Hibernate) 20 17 JPA(EclipseLink) 20 30 JOOQ 20 25 Nutz 20 25 ObjectiveSQL 20 33 Spring Data JDBC 20 93 Ktorm 20 105 JDBC(ColIndex) 50 4 JDBC(ColName) 50 8 Jimmer(Java) 50 8 Jimmer(Kotlin) 50 8 EasyQuery 50 11 MyBatis 50 50 Exposed 50 37 JPA(Hibernate) 50 39 JPA(EclipseLink) 50 73 JOOQ 50 54 Nutz 50 60 ObjectiveSQL 50 80 Spring Data JDBC 50 241 Ktorm 50 228 JDBC(ColIndex) 100 8 JDBC(ColName) 100 14 Jimmer(Java) 100 13 Jimmer(Kotlin) 100 13 EasyQuery 100 22 MyBatis 100 95 Exposed 100 51 JPA(Hibernate) 100 76 JPA(EclipseLink) 100 147 JOOQ 100 123 Nutz 100 112 ObjectiveSQL 100 160 Spring Data JDBC 100 449 Ktorm 100 478 JDBC(ColIndex) 200 13 JDBC(ColName) 200 30 Jimmer(Java) 200 24 Jimmer(Kotlin) 200 27 EasyQuery 200 36 MyBatis 200 188 Exposed 200 100 JPA(Hibernate) 200 145 JPA(EclipseLink) 200 309 JOOQ 200 239 Nutz 200 229 ObjectiveSQL 200 288 Spring Data JDBC 200 976 Ktorm 200 941 JDBC(ColIndex) 500 31 JDBC(ColName) 500 62 Jimmer(Java) 500 61 Jimmer(Kotlin) 500 59 EasyQuery 500 86 MyBatis 500 468 Exposed 500 257 JPA(Hibernate) 500 401 JPA(EclipseLink) 500 735 JOOQ 500 586 Nutz 500 490 ObjectiveSQL 500 794 Spring Data JDBC 500 2237 Ktorm 500 2342 JDBC(ColIndex) 1000 62 JDBC(ColName) 1000 120 Jimmer(Java) 1000 113 Jimmer(Kotlin) 1000 126 EasyQuery 1000 226 MyBatis 1000 954 Exposed 1000 480 JPA(Hibernate) 1000 829 JPA(EclipseLink) 1000 1538 JOOQ 1000 1202 Nutz 1000 1045 ObjectiveSQL 1000 1789 Spring Data JDBC 1000 5076 Ktorm 1000 5952 note Since Spring removed support for OpenJPA, this benchmark test does not include JPA(OpenJPA).","s":"Operation Time","u":"/jimmer-doc/docs/overview/benchmark","h":"#operation-time","p":1021},{"i":1029,"t":"Disable cache for all frameworks Turn off logs for all frameworks For all frameworks, open and close connections/sessions each time, no sharing; rely on connection pools to ensure performance. Use Spring's connection management mechanism. The implementation is slightly different due to the different APIs of different frameworks. Some use DataSourceUtils's getConnection and releaseConnection Some use TransactionAwareDataSourceProxy But the end result is the same Do not use transactions Exposed is special in that its API can only work with transactions, so there is a fake transaction implementation for it. Use embedded H2 database to compress database overhead as much as possible, highlighting the performance of the ORM itself, i.e. the performance of mapping.","s":"Implementation Principles","u":"/jimmer-doc/docs/overview/benchmark","h":"#implementation-principles","p":1021},{"i":1031,"t":"A common view: the performance of the ORM itself is not important. In actual projects, the database is not an in-memory database, so the time consumed by the ORM itself is negligible compared to the time consumed by the database. Rebuttal: After the release of Java 19, virtual threads are supported. The faster the ORM completes the mapping, the more virtual threads the JVM can schedule, which can increase system throughput.","s":"Value","u":"/jimmer-doc/docs/overview/benchmark","h":"#value","p":1021},{"i":1033,"t":"There are two programming styles in JDBC for reading values from java.sql.ResultSet JDBC(ColIndex), i.e. reading by column index, rs.getString(1) JDBC(ColName), reading by column name: rs.getString(\"VALUE_1\") JDBC(ColIndex) is faster than JDBC(ColName), so Jimmer itself also uses JDBC(ColIndex) as the underlying means of accessing ResultSet, providing the possibility of exceeding the performance metrics of JDBC(ColName). Now let's focus on discussing the two cases in the charts (select native JDBC metrics): Querying 10 rows of data each time, the OPS of JDBC(ColName) and Jimmer(Java) are close. In this scenario, the performance of Jimmer and JDBC(ColName) is similar. The test code of JDBC(ColName) directly hardcodes the SQL, while Jimmer needs to dynamically construct the SQL using the DSL mechanism, from which perspective Jimmer should be slower. However, the process of Jimmer converting ResultSet to objects is faster than JDBC(ColName), canceling each other out. So the performance is similar. Of course, the SQL statement used in Benchmark is not complex. If more complex SQL is used, the hardcoded SQL JDBC(ColName) will be faster, which is also an area Jimmer can optimize in subsequent versions. Querying 1000 rows of data each time, Jimmer's ops are significantly higher than JDBC(ColName)'s OPS. In this case, the performance advantage of Jimmer converting ResultSet to objects is fully demonstrated. Even if Jimmer slowed down due to dynamically generating SQL using DSL, the overall result is still faster than JDBC(ColName). The main reasons why Jimmer converts ResultSet to objects so fast are: Use JDBC(ColIndex) at the bottom layer Do not use Java reflection to dynamically set properties for objects. At compile time, Jimmer generates a modifiable DraftImpl class for each immutable entity type, which provides a generic __set(PropId propId, Object value) method to achieve dynamic setting of object properties similar to Java reflection. At the same time, the compiler assigns each property an integer as id. The __set method in the DraftImpl class uses a switch statement internally to identify the passed property id. For example, the generated Java code is: @Override public void __set(PropId prop, Object value) { int __propIndex = prop.asIndex(); switch (__propIndex) { case -1: __set(prop.asName(), value); return; case 0: setId((Long)value); break; case 1: setName((String)value); break; case 2: setEdition((Integer)value); break; ...Omitted... } } Modern compilers have sufficient optimization for such integer-based switch statements, so it can be considered that Jimmer's dynamic assignment of entity objects is not much slower than the hardcoded JDBC test code. These two reasons are the most important reasons why Jimmer's object mapping performance is so high.","s":"Why so fast?","u":"/jimmer-doc/docs/overview/benchmark","h":"#why-so-fast","p":1021},{"i":1035,"t":"To help readers better understand the key features, let's first introduce Jimmer's fundamental design philosophy","s":"Key Features ✦","u":"/jimmer-doc/docs/overview/key-features","h":"","p":1034},{"i":1037,"t":"The core concept of Jimmer is to read and write data structures of arbitrary shapes as a whole, rather than simply processing entity objects. Jimmer entity objects are not POJOs, and can easily express data structures of arbitrary shapes. Data structures of any shape can be processed as a whole for: Reading: Jimmer creates this infinitely flexible data structure and passes it to you Writing: You create this infinitely flexible data structure and pass it to Jimmer Since Jimmer's design philosophy is to read and write data structures of arbitrary shapes rather than processing simple objects, how does it differ from technologies with similar capabilities? Here is the English translation of the provided table: Comparison Description GraphQL GraphQL only focuses on querying data structures of arbitrary shapes; Jimmer not only does this but also focuses on how to write data structures of arbitrary shapes GraphQL does not support recursive queries based on self-referencing properties, Jimmer does JPA In JPA, to control the shape of the data structure being saved, properties must be configured with insertable, updatable, or cascade (for associated properties). Regardless of the configuration, the saved data structure is fixed; Jimmer entities are not POJOs, their data structure shapes are ever-changing, no prior planning and design is needed, any business scenario can construct the data structure it needs and save it directly For queries, JPA's EntityGraphQL is very complex; Jimmer provides two methods to achieve similar functionality: controlling the format of returned entity objects, or generating DTOs through a cost-effective way and querying directly. Either way is much simpler than EntityGraph In JPA, if you need to use a DTO object to query only part of the properties, the DTO must be a simple object without any associations. That is, it loses the most valuable capability of ORM, degrading from ORM to OM; Jimmer's automatically generated DTOs support arbitrarily complex hierarchical relationships, Jimmer is currently the only ORM that supports nested projections based on DTO In JPA, updating an object results in all updatable columns being modified. For simplicity, developers rarely use update, instead choosing to first query the complete object, modify some properties, and finally save the entire object; Jimmer can construct and directly save incomplete objects JPA's EntityGraphQL does not support recursive queries based on self-referencing properties, Jimmer does MongoDB In MongoDB, each document structure is a data island. Although MongoDB's data structure is weakly typed, from a business perspective, which data islands exist and the internal hierarchical structure of each data island need to be designed and agreed upon in advance. Once the design and agreement are completed, the format of the entire data view is fixed and must be processed from a fixed perspective; In Jimmer, the shape of the data structure does not need to be designed in advance, any business scenario can freely plan a data structure format, and read and write the corresponding data structure as a whole. tip Based on this core concept, Jimmer will bring you convenience that was previously unattainable in any technology stack, freeing you from dealing with tedious details and allowing you to focus on quickly implementing complex business logic.","s":"Design Philosophy","u":"/jimmer-doc/docs/overview/key-features","h":"#design-philosophy","p":1034},{"i":1039,"t":"Based on the aforementioned core concept, Jimmer provides the following features: Convenient query API, robust Java DSL, elegant Kotlin DSL Dynamic querying is designed for multi-table queries DSL supports mixing native SQL expressions to use non-standard database-specific capabilities Extends SQL capabilities, easily supporting advanced features that are costly to implement with native SQL Advanced SQL optimization capabilities Automatic removal of unnecessary table joins Automatic merging of logically equivalent table joins Automatic merging of logically equivalent implicit subqueries Paginated query can automatically generate and optimize count query DTO language and corresponding compile-time code generator, making DTOs extremely cost-effective Output DTO, used as return for complex queries Input DTO, used as parameter for complex saves Specification DTO, used as parameter for complex queries The DTO supported by the ORM itself can be seamlessly integrated without introducing additional logic into business code Query arbitrary graph structures No \"N + 1\" problem Objects at any level can be incomplete Can recursively query self-referencing properties Can return either entities directly or output DTOs Save arbitrary graph structures Merge data using the database's native upsert capabilities Multiple objects at each level are handled using batch DML operations Automatically translates constraint violation exceptions Saved objects at any level can be incomplete Can save either entities directly or input DTOs This section has undergone a major upgrade, and the documentation is actively being restructured. Please refer to the save-command examples in the accompanying examples. Powerful caching Multi-layer caching, technology for each cache layer can be freely chosen Not just object caching (associations, computed values, multiple views) Automatically maintains cache consistency Rapid support for GraphQL Client contracts based on document comments (OpenAPI, TypeScript)","s":"Key features","u":"/jimmer-doc/docs/overview/key-features","h":"#key-features","p":1034},{"i":1041,"t":"When developing with Jimmer, there is a note of caution that needs attention. Please refer to here","s":"Notes","u":"/jimmer-doc/docs/overview/key-features","h":"#notes","p":1034},{"i":1044,"t":"Jimmer heavily relies on the precompilation technology in the JVM ecosystem: For Java, it's APT, i.e., Annotation Processor Tool For Kotlin, it's KSP, i.e., Kotlin Symbol Processing info Some code generated by APT/KSP is necessary for using Jimmer. Therefore, if you open any Java/Kotlin project from the official examples in IntelliJ, you will find that some code that should have been automatically generated is missing. For this, you can choose any of the following methods: First, execute the ./mvnw install (for Java examples only) or ./gradlew build command in the directory of the project you want to open from the command line to complete the code generation, then open the project with IntelliJ. Open the project directly with IntelliJ, ignore the IDE errors temporarily, and after the dependencies are downloaded, run the project's main method or unit test (save-command/save-command-kt demonstrates features using unit tests). All IDE errors will automatically disappear, and the application will start correctly.","s":"Basic Concepts","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#basic-concepts","p":1042},{"i":1046,"t":"Java (Maven) Java (Gradle) Kotlin (Gradle.kts) Java (Gradle Plugin) Kotlin (Gradle Plugin) pom.xml ...other code omitted... org.apache.maven.plugins maven-compiler-plugin 3.10.1 org.babyfish.jimmer jimmer-apt ${jimmer.version} ...other code omitted... dependencies { ...other dependencies omitted... annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" } plugins { // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10-1.0.6\" ...other plugins omitted... } dependencies { // Apply Jimmer's KSP code generator ksp(\"org.babyfish.jimmer:jimmer-ksp:${jimmerVersion}\") ...other dependencies omitted... } // Add generated code to compile path. // Gradle build works without this, but IntelliJ won't find generated code. kotlin { sourceSets.main { kotlin.srcDir(\"build/generated/ksp/main/kotlin\") } } build.gradle plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } build.gradle.kts plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10+\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } info The first three: Standard configurations The last two: Community-provided Gradle plugin for further simplifying configurations note KSP only supports gradle, It has been proven that KSP's third-party Maven plug-in support cannot keep up with the version iteration of 'kotlin/KSP' itself, and often encounters many problems during the upgrade process. Eventually, Jimmer dropped Maven support for Kotlin and asked Kotlin developers to use Gradle. For all projects in the official examples: All Java examples have both pom.xml and build.gradle, i.e., they support both Maven and Gradle. When opening these projects for the first time, IntelliJ will ask you how you want to open them, and you can make your choice. If you want to switch the opening method, exit IntelliJ, delete the hidden directory .idea in the project, and then open the project with IntelliJ again and reselect the method. All Kotlin examples only have the build.gradle.kts file, i.e., they only support Gradle. The reason has been explained earlier. IntelliJ has some rash over-optimization measures for integrating annotation processors introduced via Maven, resulting in a better development experience when using Gradle with the IDE than with Maven.","s":"How to Use","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#how-to-use","p":1042},{"i":1048,"t":"Business projects are rarely a single project, but more often split into multiple subprojects using build tools like Maven and Gradle. So, in which subprojects should we use the configurations mentioned earlier? Subproject Type Usage Notes Projects defining entities Generate necessary code based on entity definitions, such as Draft, SQL DSL, Fetcher Projects defining DTO files under src/main/dto Generate DTO classes based on the DTO language code For Java, unless the current subproject has entity definitions, you need to find any class and annotate it with @EnableDtoGeneration Projects using Spring Web annotations Automatically generate OpenAPI documentation and TypeScript code, writing Java/Kotlin documentation comments into the documentation and client code; support for remote exceptions","s":"Where to Use","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#where-to-use","p":1042},{"i":1050,"t":"Since Jimmer is a compile-time framework, and considering that not all users are familiar with apt and ksp, it's necessary to mention an important detail. Apt/Ksp are standard technologies in the industry, and Java IDEs provide support for them. In most cases, your modifications will include changes to Java or Kotlin code, such as changes in entity types or Web Controller*(Jimmer has its own implementations for OpenAPI and TypeScript generation)*. In this case, you only need to click the IDE's Run or Debug button once, without requiring a full compilation, to trigger all pre-compilation behaviors, the automatically generated source code and resource files will update automatically. In rare cases, if you only modify DTO files, meaning there are no Java or Kotlin source code changes within the same project except for the DTO files, you have three options: Use the companion DTO plugin Perform a full compilation using maven or gradle commands, or the IDE's Rebuild button, which can achieve this purpose Delete the affected project's compilation output directory, then click the IDE's Run or Debug button`","s":"Notes","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#notes","p":1042},{"i":1052,"t":"Unlike the Kotlin API, the Java API cannot avoid to directly use automatically generate types in user code. Let's compare the following: Feature Java Kotlin Draft Use the generated type BookDraft Use the original entity type Book Book book = BookDraft.$.produce(b -> { b.setName(\"SQL\"); b.addIntoAuthors(a -> { a.setName(\"Jessica\"); }); b.addIntoAuthors(a -> { a.setName(\"Bob\"); }); }); val book = Book { name = \"SQL in Action\" authors().addBy { name = \"Jessica\" } authors().addBy { name = \"Bob\" } } SQL DSL Use the generated type BookTable Use the original entity type Book BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.storeId().isNull()) .orderBy(table.name()) .select(table) .execute(); List books = sqlClient .createQuery(Book::class) { where(table.storeId.isNull()) orderBy(table.name) select(table) } .execute() Fetcher Use the generated types BookFetcher, BookStoreFetcher, and AuthorFetcher Use the original entity type Book Fetcher fetcher = BookFetcher.$ .allScalarFields() .store( BookStoreFetcher.$ .allScalarFields() ) .authors( AuthorFetcher.$ .allScalarFields() ) val fetcher = newFetcher(Book::class).by { allScalarFields() store { allScalarFields() } authors { allScalarFields() } } As you can see, the abstraction capabilities of Java and Kotlin are different, resulting in different effects that the API design can achieve: For Kotlin, regardless of the scenario, you only need to use the original entity type Book. For Java, you have to use the types automatically generated by the Annotation Processor, such as BookDraft, BookTable, BookFetcher, etc. In the above Java code, .$ appears frequently, $ are static read-only fields of these classes. Actually, using $ is the simplest way. However, considering that some Java developers have subjective biases against $, for Java subprojects defining entity types, Jimmer's APT also generate four summary types: Objects class Tables interface TableExes interface Fetchers interface The package where these four types reside is the common package for all entities. These four types provide another coding style for Java code by defining static constants, and the two styles are compared as follows: Style Accepting $ Style Not Accepting $ BookDraft.$.produce Immutables.createBook BookTable.$ Tables.BOOK_TABLE BookTableEx.$ TableExes.BOOK_TABLE_EX BookFetcher.$ Fetchers.BOOK_FETCHER Additionally, Tables, TableExes, and Fetchers are interfaces, and you can use the implements statement to further simplify the code (since IntelliJ does not support static imports well, implementing interfaces that define constants is still a recommended technique). For example: public interface FetcherConstants implements Fetchers { Fetcher BOOK_DETAIL_FETCHER = BOOK_FETCHER .allScalarFields() .store( BOOK_STORE_FETCHER .allScalarFields() ) .authors { AUTHOR_FETCHER .allScalarFields() }; }","s":"Two Styles of Java Code","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#two-styles-of-java-code","p":1042},{"i":1054,"t":"Java projects often use Lombok. By default, if the project does not have any APT other than Lombok, you only need to import the Lombok dependency. However, once you introduce other APT configurations (not necessarily Jimmer's APT, but any other APT), you must explicitly configure Lombok's APT. Java(Maven) Java(Gradle) Java(Gradle Plugin) pom.xml ...omitted other code... org.apache.maven.plugins maven-compiler-plugin 3.10.1 org.projectlombok lombok ${lombok.version} org.babyfish.jimmer jimmer-apt ${jimmer.version} ...omitted other code... build.gradle dependencies { ...omitted other dependencies... annotationProcessor \"org.projectlombok:lombok:${lombokVersion}\" annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" } build.gradle plugins { id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...省略其它插件... } jimmer { version = ... } dependencies { ...omitted other dependencies... annotationProcessor \"org.projectlombok:lombok:${lombokVersion}\" }","s":"Integration with Lombok","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#integration-with-lombok","p":1042},{"i":1056,"t":"In this section, we will introduce the various queries in Jimmer without considering Cache. There are three groundbreaking capabilities: Object Fetcher One statement to query data structure of arbitrary shape, like GraphQL Dynamic Join This addresses a huge gap in the JVM ecosystem, enabling easy complex dynamic queries Smart Paging Users only focus on querying the raw data, row count queries are auto-generated and optimized for convenience","s":"Query","u":"/jimmer-doc/docs/query/","h":"","p":1055},{"i":1059,"t":"When facing a new framework, the first reaction of developers is to look for examples and quick start guides. Examples: Quick Preview/Standard Examples Get started: Quick Preview/Get Started However, if you observe the documentation structure carefully, you will find that their positions in the directory structure are not particularly front. Why is that? Because Jimmer is a revolutionary technology, providing a completely new technical solution at a time when developers thought the technology ecosystem for accessing RDBMS from the JVM was already solidified and couldn't possibly undergo a major transformation. Therefore, it is necessary to first discuss these changes and clearly explain the incredible benefits they will bring to real-world projects. This field already has a plethora of choices (to the point of being over-served), and if the new technical solution's approach and methodology are similar to previous works, it would not bring about a ground-breaking change and cliff-like efficiency boost to real-world project development. Instead, it would simply be adding another choice to the already numerous choices. In that case, there would be no need to develop an entirely new project, as it would only add confusion to the industry. In summary, it is recommended to understand Jimmer's innovations and the significant benefits they will bring before looking at the standard examples and quick start guide; attempting to understand them with your previous path to success and psychological expectations may be counter-productive at first.","s":"Where are the Examples and Getting started?","u":"/jimmer-doc/docs/overview/welcome","h":"#where-are-the-examples-and-getting-started","p":1057},{"i":1061,"t":"The chapters of this documentation are divided into two types: Tutorial chapters marked with a ★ symbol. Introduction/Overview The most important article, marked with a ✦ symbol. It discusses Jimmer's innovations, introduces all its features, and provides rich, concise demonstrations. Quick Preview A quick preview of Jimmer's three most basic introductory features: Querying any shape Saving any shape Arbitrary dynamic queries. This chapter only includes these 3 core capabilities and does not cover other advanced features. Showcase For any framework, some features can be demonstrated with code and do not require extensive explanations to aid understanding. All such features that can be easily demonstrated with code and do not require much explanation are listed in this chapter. Other chapters. The remaining chapters should be treated as reference books, not tutorials. These chapters delve into the details of various features, including advanced ones.","s":"About This Documentation","u":"/jimmer-doc/docs/overview/welcome","h":"#about-this-documentation","p":1057},{"i":1063,"t":"Welcome to join the Jimmer community, Discord Link: https://discord.gg/PmgR5mpY3E","s":"Discussion","u":"/jimmer-doc/docs/overview/welcome","h":"#discussion","p":1057},{"i":1065,"t":"How Jimmer solves the dynamic join problem will be discussed in subsequent docs. This article first introduces the join style in Jimmer.","s":"Association Path Chaining","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","h":"","p":1064},{"i":1067,"t":"Firstly, Jimmer does not support cartesian products which is exists in theoretical and should be carefully avoided in actual projects. Thus, Jimmer's SQL DSL does not need to support multiple from clauses. All cross-table operations are unified as join. In Jimmer, all table joins are implicit, formed by association paths of arbitrary length, and are considered as multiple table joins. For example: Java Kotlin public List findBooksByStoreCityName(@Nullable String storeCityName) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( storeCityName != null && !storeCityName.isEmpty(), table.store().city().name().eq(name) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); } fun findBooksByStoreCityName(name: storeCityName?): List = sqlClient .createQuery(Book::class) { storeCityName?.takeIf { it.isNotEmpty() }?.let { where(table.store.city.name eq it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute() info In the above code, table.store().city() in Java or table.store.city in Kotlin is the association path. The association path length is unlimited. Each association reference corresponds to a SQL join operation. from BOOK tb_1_ inner join BOOK_STORE tb_2_ // `.store` on tb_1_.STORE_ID = tb_2_.ID inner join CITY tb_3_ // `.city` on tb_2_.CITY_ID = tb_3_.ID For findBooksByStoreCityName(null), the generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc For findBooksByStoreCityName(\"ChengDu\"), the generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ // `.store` on tb_1_.STORE_ID = tb_2_.ID inner join CITY tb_3_ // `.city` on tb_2_.CITY_ID = tb_3_.ID where // `.name eq \"ChengDu\"` tb_3_.NAME = ? /* ChengDu */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Basic Concepts","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","h":"#basic-concepts","p":1064},{"i":1069,"t":"The association paths .store and .city in the above example represent inner joins. It's also easy to express outer joins, taking left outer join as an example: Java Kotlin table.store().city(JoinType.LEFT) table.store.`city?` caution To fully leverage Kotlin's strengths and optimize its developer experience, Jimmer provides slightly different APIs for Java and Kotlin with the same essence. However, outer joins are the only exception where Java and Kotlin APIs behave differently: Java DSL Use JoinType to represent join type, can be INNER (default), LEFT, RIGHT or FULL Kotlin DSL DSL properties same as entity properties represent inner join DSL properties with a ? suffix compared to entity properties represent left outer join That is, Kotlin DSL does not support RIGHT and FULL. This sacrifice is a careful trade-off to gain null safety integration in Kotlin, which is more important. This detail will be discussed in Kotlin Join Features.","s":"Outer Joins","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","h":"#outer-joins","p":1064},{"i":1071,"t":"We will introduce the following contents: Problems of other solutions Chain-style association paths Merge conflict table joins Optimizing unnecessary join Pagination safety Weak join Kotlin table join special features","s":"Dynamic JOIN","u":"/jimmer-doc/docs/query/dynamic-join/","h":"","p":1070},{"i":1075,"t":"Jimmer provides dynamic entities that can solve a large part of the DTO explosion problem very well. Therefore, generally speaking, it is not necessary to define output DTO types to express query results. However, not all DTO types can be eliminated. Input DTO objects are hard to remove. For example, in GraphQL, although dynamic GraphQLObject data is returned for the client from the output perspective, static GraphQLInput data submitted by the client is accepted from the input perspective. Why does the GraphQL protocol define GraphQLInput as a static type? Because API explicitness and system security are very important requirements, please refer to Problems with dynamic objects as input parameters. The problems faced by the GraphQL protocol are also faced by Jimmer, which must provide a complete solution. tip The DTO language is designed for that part of the DTO types that cannot be eliminated, with the goal of making them extremely cheap.","s":"1.1. Pain Point","u":"/jimmer-doc/docs/object/view/dto-language","h":"#11-pain-point","p":1072},{"i":1077,"t":"As a comprehensive solution, Jimmer is not limited to ORM itself, but considers the whole project. To solve this problem, it provides the DTO language. The DTO language is a very powerful feature provided by Jimmer, and is a concept highly similar to Object Fetcher, but at an earlier stage during compilation. The DTO language is used to quickly define the shape of data structures. Based on these shapes, DTOs can be compile-time Generate specific static DTO types corresponding to specific data structures Generate mutual conversion logic between DTO static objects and Jimmer dynamic objects Generate Object Fetchers that match perfectly with the DTO shape definitions Using the DTO language to quickly build DTO types is a solution tailored for Jimmer with extremely high development efficiency, much faster than using mapstruct, and is the recommended approach.","s":"1.2. Solution","u":"/jimmer-doc/docs/object/view/dto-language","h":"#12-solution","p":1072},{"i":1079,"t":"The application scenarios of the DTO language: Serve as return results in query APIs (optional, not recommended, don't use unnecessarily) Serve as input parameters in save APIs (required) Serve as input parameters in super QBE queries (optional, recommended)","s":"1.3. Application Scenarios","u":"/jimmer-doc/docs/object/view/dto-language","h":"#13-application-scenarios","p":1072},{"i":1081,"t":"The code of the DTO language is reflected in files with the extension dto. Once compilation is complete, these files have no value. So these files cannot be packaged into src/main/resources, but should be placed in the src/main/dto directory. Therefore, the first thing is to create a dto subdirectory under src/main. tip Jimmer does not require the src/main/dto directory to be in the project where the entity type is located. In fact, you can create this directory in any project that can legally access the entity. Jimmer only requires using jimmer-apt or jimmer-ksp in projects containing dto files. They are responsible for compiling dto files and generating related code. For Java projects, in addition to jimmer-apt, it may be necessary to add an extra configuration. Please refer to Notes.","s":"2. Create File","u":"/jimmer-doc/docs/object/view/dto-language","h":"#2-create-file","p":1072},{"i":1083,"t":"Multiple dto files can be defined under the src/main/dto directory, with each file corresponding to an original entity. Assuming there is a Jimmer entity type whose full type name is com.yourcompany.yourproject.Book, and this class is decorated with @org.babyfish.jimmer.sql.Entity (DTO language only supports Entity types), there are two ways to create dto files. Not using export statement In this case, the dto file directory needs to correspond to the original entity package, and the name needs to correspond to the original entity name: Under the src/main/dto directory, create the directory com/yourcompany/yourproject, that is, create a directory consistent with the package name In the directory created in the previous step, create a new file Book.dto. This file must have the same name as the class and have the extension dto Using export statement The exportstatement is important, so we will explain it separately in a chapter.","s":"2.1. Two ways to create files","u":"/jimmer-doc/docs/object/view/dto-language","h":"#21-two-ways-to-create-files","p":1072},{"i":1085,"t":"In this case, the dto file directory and name are arbitrary, because we will use the export statement inside the file to define which original entity the dto file corresponds to. Since there is no requirement for the dto file directory, it is recommended to create the dto file directly under src/main/dto Although there is no requirement for the dto file name either, for the maintainability of the project, it is still recommended that the file name adopts the name of the original entity, which is Book.dto in this case The first line of code in the dto file is the export statement export com.yourcompany.yourproject.Book ...subsequent code... After the DTO file is compiled, more Java/Kotlin types will be generated automatically. Their default package name is: entity package name + .dto. If you use the export statement, you can further define the package where the generated code is located, for example: export com.yourcompany.yourproject.Book -> package com.yourcompany.yourproject.mydto Users can edit the Book.dto file to define any number of DTO types with Book as the aggregate root. Here we first define a DTO type: Book.dto ...export statement omitted if any... BookView { ...omitted... } info The first line of code in the dto file may be the export statement. For simplicity, export statements are omitted in subsequent sections. After compilation, the Java/Kotlin type BookView will be generated. Assuming the default value of the package where the generated code is located has not been changed, the generated code is as follows: Java Kotlin BookView.java package com.yourcompany.yourproject.dto; import com.yourcompany.yourproject.Book; import org.babyfish.jimmer.View; public class BookView implements View { ...omitted... } BookView.kt package com.yourcompany.yourproject.dto import com.yourcompany.yourproject.Book import org.babyfish.jimmer.View open class BookView( ...omitted... ) : View { ...omitted... }","s":"2.2 Export statement","u":"/jimmer-doc/docs/object/view/dto-language","h":"#22-export-statement","p":1072},{"i":1087,"t":"warning For Java projects (Kotlin developers please ignore): If the current project is not the project that defines the entity, you need to decorate any class in the current project with @org.babyfish.jimmer.sql.EnableDtoGeneration. Otherwise, the DTO file will not be compiled. dto files are compiled by Jimmer's Annotation Processor (Java) or Ksp (Kotlin). Therefore, if you are using an IDE like Intellij to develop projects, then In addition to dto files, if other Java/Kotlin files are modified, clicking the run button in the IDE directly can cause recompilation of dto files However, if no other Java/Kotlin files are modified except dto files, simply clicking the run button in the IDE does not cause dto files to be recompiled unless explicitly rebuilding! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle","s":"2.3. Notes","u":"/jimmer-doc/docs/object/view/dto-language","h":"#23-notes","p":1072},{"i":1089,"t":"It was mentioned earlier that the DTO language has three use cases: Serve as return values in query APIs (optional, not recommended, don't use unnecessarily) Serve as input parameters in save APIs (required) Serve as input parameters in super QBE queries (optional, recommended) So, the DTO language can define three types of DTOs: view: Neither uses the input keyword nor the specification keyword, which can be understood as Output DTO. input: Declared with the input keyword, which can be understood as Input DTO. specification: Declared with the specification keyword. It is not closely related to DTO itself, but can be used as a query parameter to support super QBE queries. Book.dto BookView { ...omitted... } AnotherBookView { ...omitted... } input BookInput { ...omitted... } input AnotherBookInput { ...omitted... } specification BookSpecification { ...omitted... } specification AnotherBookSpecification { ...omitted... } This means: BookView and AnotherBookView are used as query outputs. The generated Java/Kotlin types implement the org.babyfish.jimmer.View interface note It is recommended that output DTOs end with View BookInput and AnotherBookInput are used as save command inputs. The generated Java/Kotlin types implement the org.babyfish.jimmer.Input interface note It is recommended that input DTOs end with Input BookSpecification and AnotherBookSpecification are used as query parameters to support super QBE queries. The generated Java/Kotlin types implement the org.babyfish.jimmer.Specification interface note It is recommended that query parameter DTOs end with Specification","s":"3. view, input and specification","u":"/jimmer-doc/docs/object/view/dto-language","h":"#3-view-input-and-specification","p":1072},{"i":1091,"t":"For view and input, their generated Java/Kotlin types can convert between entities, with the following capabilities: Constructor taking original entity type as parameter: Convert Jimmer dynamic entity object to static DTO object toEntity(): Convert static DTO object to Jimmer dynamic entity object Take BookView as an example: Java Kotlin Book entity = ...omitted...; // Entity -> DTO BookView dto = new BookView(entity); // DTO -> Entity Book anotherEntity = dto.toEntity(); val entity: Book = ...omitted... // Entity -> DTO val dto = BookView(entity) // DTO -> Entity val anotherEntity: Book = dto.toEntity()","s":"3.1 Common functionalities of view and input","u":"/jimmer-doc/docs/object/view/dto-language","h":"#31-common-functionalities-of-view-and-input","p":1072},{"i":1093,"t":"Compared with Output DTO, Input DTO has the following differences: If the entity ID property is configured with auto-increment strategy, the id property in the input DTO is nullable. Here is the translation into English: info The reason for this design is that saving the object does not necessarily require the id property when the entity's id property has an auto-increment strategy. However, this does not mean Jimmer will simply assume like other ORMs such as JPA that lacking an id property means an insert operation while having an id property means an update operation. Jimmer has smarter strategies in this regard, please refer to Save Commands/Save Modes. This article will not repeat the details. If the developer does not accept this default behavior, there are two ways to write the DTO code: Make the DTO type have no id property at all input BookInput { #allScalars(this) -id } Make the DTO type's id property non-nullable input BookInput { #allScalars(this) id! } The input DTO can only define savable properties, such as simple properties, ordinary ORM associations, and id-view properties. Unsavable properties such as transient properties, formula properties, computed properties, and remote associations cannot be defined, otherwise it will cause compilation errors. Input DTO provides comprehensive and powerful support for nullable properties. tip For properties that are allowed to be null in the original entity, how to map them through Input DTO is a complex topic. Jimmer provides comprehensive and powerful support. Please refer to Modification/Save Command/Input DTO/Handle Null Values.","s":"3.2 input-specific functionalities","u":"/jimmer-doc/docs/object/view/dto-language","h":"#32-input-specific-functionalities","p":1072},{"i":1095,"t":"The role of specification is similar to input, used to decorate input types, but specification does not provide the ability to convert between entity objects, but is used as a query parameter to support super QBE queries. tip Super QBE Query is a very powerful feature of Jimmer that is not explained here. Please refer to the relevant section.","s":"3.3 specification-specific functionalities","u":"/jimmer-doc/docs/object/view/dto-language","h":"#33-specification-specific-functionalities","p":1072},{"i":1097,"t":"Attributes can be defined for DTO types to map properties in the original entity type, for example: Book.dto BookView { id name edition } This means that the DTO only maps the three properties of the entity: id, name and edition, as follows: Java Kotlin BookView.java public class BookView implements View { private long id; private String name; private String edition; public BookView(Book book) { ...omitted... } @Override public Book toEntity() { ...omitted... } ...other members omitted... } BookView.kt open class BookView( val id: Long = 0, val name: String = \"\", val edition: Int = 0 ) : View { constructor(book: Book): this(...omitted...) override fun toEntity(): Book { ...omitted... } ...other members omitted... }","s":"4. Simple properties","u":"/jimmer-doc/docs/object/view/dto-language","h":"#4-simple-properties","p":1072},{"i":1099,"t":"The DTO language supports a special macro property, #allScalars, which represents mapping all scalar properties in the entity. Book.dto BookView { #allScalars } According to the definition of the Book type in the official example: The scalar properties of Book itself are id, name, edition, and price Book inherits TenantAware, and the TenantAware interface defines the tenant property Book also inherits CommonEntity (multiple inheritance), and CommonEntity interface defines the createdTime and modifiedTime properties #allScalars means automatically mapping all scalar properties of the entity, including inherited ones. If this is not the behavior you want, then You can use allScalars(Book) to indicate mapping only the scalar properties defined by the Book type itself, excluding inherited properties. You can also use allScalars(TenantAware) and allScalars(CommonEntity) to indicate properties of specific super types. tip For the current type Book, #allScalars(Book) can also be written as #allScalars(this). In fact, #allScalars supports multiple parameters, for example: Macro Expression Automatically Mapped Attributes #allScalars createdTime, modifiedTime, tenant, id, name, edition, price #allScalars(this) id, name, edition, price #allScalars(TenantAware) tenant #allScalars(CommonEntity) createdTime, modifiedTime #allScalars(this, TenantAware) tenant, id, name, edition, price #allScalars(this, CommonEntity) createdTime, modifiedTime, id, name, edition, price #allScalars(TenantAware, CommonEntity) createdTime, modifiedTime, tenant #allScalars(this, TenantAware, CommonEntity) createdTime, modifiedTime, tenant, id, name, edition, price info If the #allScalars macro is used, it must be defined as the first property, otherwise it will cause compile errors. If parameters are specified for the #allScalars macro, each parameter must be the current entity or its base type, otherwise it will cause compile errors.","s":"5. allScalars","u":"/jimmer-doc/docs/object/view/dto-language","h":"#5-allscalars","p":1072},{"i":1101,"t":"The #allScalars macro mentioned above will batch map multiple properties. Negative properties can remove some properties. Book.dto BookView { #allScalars -tenant } Similar to above, if we understand according to the inheritance relationship of the Book type in the official example, #allScalars will add the properties createdTime, modifiedTime, tenant, id, name, edition and price. -tenant removes the tenant property from it, finally adding the properties createdTime, modifiedTime, id, name, edition and price. info What is specified by the negative property is not the property name of the entity, but the name of the corresponding property in the DTO. Here the two are the same and there is no difference. The Renaming section later will reveal the difference between the two. It is not difficult to find that for this example, there is another equivalent writing: Book.dto BookView { // Exclude `TenantAware` #allScalars(Book, CommonEntity) }","s":"6. Negative Attributes","u":"/jimmer-doc/docs/object/view/dto-language","h":"#6-negative-attributes","p":1072},{"i":1103,"t":"By default: All properties in specification are null by default. Otherwise, the nullability of DTO properties is the same as the nullability of original properties in entities. We can use ? or ! to modify DTO properties to change the nullability of DTO properties.","s":"7. Nullability","u":"/jimmer-doc/docs/object/view/dto-language","h":"#7-nullability","p":1072},{"i":1105,"t":"We can use ? to modify DTO properties to make them nullable. warning If the original property in the entity is already nullable, it will cause compile errors. For example: Book.dto input UpdateBookInput { #allScalars price? } You can even apply ? to allScalars to make all automatically mapped non-associative properties nullable: Book.dto input UpdateBookInput { #allScalars? } Specification types do not allow ? warning Since all properties in specification are nullable by default, specifying the modifier ? for properties within specification will cause compile errors. When the original property in the entity does not allow null For non-nullable original properties in an entity, if the corresponding property in the DTO object is null, the original property in the entity object will not be assigned after converting the DTO object to the entity object. When the original property in the entity allows null tip For properties that are allowed to be null in the original entity, how to map them through Input DTO is a complex topic. Jimmer provides comprehensive and powerful support. Due to length limitations, this issue forms a separate article. Please refer to Modification/Save Command/Input DTO/Handle Null Values.","s":"7.1. ?","u":"/jimmer-doc/docs/object/view/dto-language","h":"#71-","p":1072},{"i":1107,"t":"We can use ! to modify DTO properties to make them non-null. warning If the original property in the entity is already non-null, it will cause compile errors. Its use is limited and can only be used in the following three cases: Modify the id property in input type If the id property is configured with auto-increment strategy, the corresponding input DTO type will make the id property nullable. However, this behavior does not always meet user expectations. You can use ! to modify the id property in the input type to make it non-null, for example: Book.dto input BookUpdateInfo { #allScalars id! } warning Using ? to modify other properties will cause compile errors. If input is modified by the unsafe keyword, any nullable entity property can be converted to non-null, for example: Book.dto unsafe input BookUpdateInfo { #allScalars store! { ...omitted... } } info For an entity object, if the corresponding value of this property is null, when using the Input DTO constructor to convert it to an Input DTO object, an exception will occur because the corresponding property in DTO does not allow null. This is the meaning of the unsafe keyword. For specification, since all properties are null by default, any nullable entity property can be converted to non-null, for example: Book.dto specification BookSpecification { #allScalars edition! }","s":"7.2. !","u":"/jimmer-doc/docs/object/view/dto-language","h":"#72-","p":1072},{"i":1109,"t":"The as keyword can be used to set aliases for properties so that entity property names are different from DTO property names. as has two usages, it can precisely set an alias for a single property, and it can also vaguely set aliases for multiple properties.","s":"8. Renaming","u":"/jimmer-doc/docs/object/view/dto-language","h":"#8-renaming","p":1072},{"i":1111,"t":"Book.dto BookView { name as bookName }","s":"8.1. Renaming a single property","u":"/jimmer-doc/docs/object/view/dto-language","h":"#81-renaming-a-single-property","p":1072},{"i":1113,"t":"Assume there is an entity type called Robot: Robot.dto OrderView { as (^ -> oldSystem) { ❶ prop1 prop2 } as ($ -> ForNewSystem) { ❷ prop3 prop4 } } Where: ❶ Adds the prefix oldSystem to prop1 and prop2, where ^ indicates the start position ❷ Adds the suffix ForNewSystem to prop3 and prop4, where $ indicates the end position The generated RobotView class is as follows: Java Kotlin BookView.java public class RobotView implements View { private String oldSystemProp1; private String oldSystemProp2; private String prop3ForNewSystem; private String prop4ForNewSystem; ...other members omitted... } BookView.kt open class RobotView( val oldSystemProp1 = \"\", val oldSystemProp2 = \"\", val prop3ForNewSystem = \"\", val prop4ForNewSystem = \"\" ) : View { ...other members omitted... } You can define most properties in the as() {...} block, of course including #allScalars, for example: Robot.dto RobotView { as(^ -> robot) { #allScalars } } Below are all the usages of the as() {...} block: Code Example Description as(^ -> prefix) Add prefix as(^prefix ->) Remove prefix as(^prefix -> newPrefix) Replace prefix as($ -> suffix) Add suffix as($suffix ->) Remove suffix as($suffix -> newSuffix) Replace suffix as(infix -> ) Remove any content as(infix -> newInfix) Replace any content caution ^ and $ cannot appear at the same time, because it means precise renaming of a single property, which duplicates existing functionality.","s":"8.2. Renaming multiple properties","u":"/jimmer-doc/docs/object/view/dto-language","h":"#82-renaming-multiple-properties","p":1072},{"i":1115,"t":"By default, enum type properties in entities are still enum types after being mapped to DTO properties. You can map enum types to numbers or strings: Map to numbers AuthorView { #allScalars gender -> { MALE: 100 FEMALE: 101 } } The following code will be generated: Java Kotlin BookView.java public class AuthorView implements View { private int gender; ...other members omitted... } BookView.kt open class RobotView( val gender: Int, ...other members omitted... ) : View { ...other members omitted... } Map to strings AuthorView { #allScalars gender -> { MALE: \"Male\" FEMALE: \"Female\" } } The following code will be generated: Java Kotlin BookView.java public class AuthorView implements View { private String gender; ...other members omitted... } BookView.kt open class RobotView( val gender: String, ...other members omitted... ) : View { ...other members omitted... }","s":"9. Enum Mapping","u":"/jimmer-doc/docs/object/view/dto-language","h":"#9-enum-mapping","p":1072},{"i":1117,"t":"The handling of association properties is a very powerful feature of the DTO language with three usages: Direct use Recursive association Call id function Call flat function","s":"10. Association Attributes","u":"/jimmer-doc/docs/object/view/dto-language","h":"#10-association-attributes","p":1072},{"i":1119,"t":"Basic usage Robot.dto input CompositeBookInput { #allScalars(Book) store { #allScalars(BookStore) -id } authors { #allScalars(Author) -id } } The generated code is: Java Kotlin CompositeBookInput.java public class CompositeBookInput implements Input { @Nullable private Long id; private String name; private int edition; private BigDecimal price; private TargetOf_store store; private List authors; public static class TargetOf_store implements Input { private String name; @Nullable private String website; ...other members omitted... } public static class TargetOf_authors implements Input { private String firstName; private String lastName; private Gender gender; ...other members omitted... } ...other members omitted... } CompositeBookInput.kt open class CompositeBookInput( val id: Long? = null, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val store: TargetOf_store? = null, val authors: List = emptyList(), ) : Input { open class TargetOf_store( val name: String = \"\", val website: String? = null, ) : Input { ...other members omitted... } open class TargetOf_authors( public val firstName: String = \"\", public val lastName: String = \"\", public val gender: Gender, ) : Input { ...other members omitted... } ...other members omitted... } Renaming If you want to rename association properties, the as clause should be before the association definition block, for example: Book.dto input CompositeBookInput { authors as authorList { ...omitted... } ...omitted... }","s":"10.1. Ordinary Association","u":"/jimmer-doc/docs/object/view/dto-language","h":"#101-ordinary-association","p":1072},{"i":1121,"t":"For recursively associative properties in entities, such as TreeNode.parent or TreeNode.childNodes in the attached example, the corresponding associative property in the DTO can be marked as recursive using an asterisk *. TreeNode.dto TreeNodeView { #allScalars childNodes* }","s":"10.2 Recursive Association","u":"/jimmer-doc/docs/object/view/dto-language","h":"#102-recursive-association","p":1072},{"i":1123,"t":"Here is the translation into English: For short associations@IdView@IdView Therefore, the DTO language supports the id function on associated properties to achieve the same purpose: Book.dto BookView { id(store) id(authors) as authorIds ...omitted... } This code has the exact same function as the previous example, but no longer assumes the entity type always declares @IdView properties, which is a better solution.","s":"10.3. id Function","u":"/jimmer-doc/docs/object/view/dto-language","h":"#103-id-function","p":1072},{"i":1125,"t":"For view and input, the flat function can only be used for referential associations (one-to-one or many-to-one), not collection associations (one-to-many or many-to-many). It is used to promote the properties of associated DTOs to the current DTO type to obtain a flattened object without associations. For specification, the flat function does not have the above restrictions and can be used for collection associations. Please check (../../query/super_qbe). Take the TreeNode entity in the official example (in fact, this example is wrong, we will discuss this issue later): TreeNode.dto FlatTreeNodeView { #allScalars(TreeNode) flat(parent) { #allScalars(TreeNode) } } As mentioned above, this example is wrong, because the aggregate root and the associated object both have the id and name properties. Unconditionally extracting the properties of the associated object to the aggregate root will inevitably lead to name conflicts, eventually causing DTO language compilation errors. The right approach is to combine it with the user's multi-property fuzzy renaming as(...) {} block. Let's look at a new example: TreeNode.dto FlatTreeNodeView { #allScalars(TreeNode) // id, name flat(parent) { as(^ -> parent) { // parentId, parentName #allScalars(TreeNode) } } } Thus, we get a flattened DTO type with 4 properties: id, name, parentId and parentName. You can even nest the flat function to convert multi-level associations into flattened objects: TreeNode.dto FlatTreeNodeView { #allScalars(TreeNode) flat(parent) { as(^ -> parent) { #allScalars(TreeNode) } flat(grandParent) { as(^ -> parent) { #allScalars(TreeNode) } } } } Thus, we get a flattened DTO type with 6 properties: id, name, parentId, parentName, grandParentId, and grandParentName. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(cola -> { cola.setId(4L); cola.setName(\"Coca cola\"); cola.applyParent(drinks -> { drinks.setId(3L); drinks.setName(\"Drinks\"); drinks.applyParent(food -> { food.setId(2L); food.setName(\"Food\"); }) }) }); // Convert hierarchical Entity to flattened DTO FlatTreeNodeView view = new FlatTreeNodeView(treeNode); System.out.println(view); val treeNode = TreeNode { id = 4L name = \"Coca cola\" parent { id = 3L name = \"Drinks\" parent { id = 2L name = \"Food\" } } } // Convert hierarchical Entity to flattened DTO val view = FlatTreeNodeView(treeNode) println(view) The print result is (formatted here for readability): com.yourcompany.yourproject.FlatTreeNodeView( id = 4, name = Coco cola, parentId = 3, parentName = Drinks, grandParentId = 2, grandParentName = \"Food\" ) The flat solution also has drawbacks. For output DTOs, the flat solution is controversial and is not recommended to be blindly adopted. Please refer to Controversy over whether output DTOs should use flat mode","s":"10.4. flat Function","u":"/jimmer-doc/docs/object/view/dto-language","h":"#104-flat-function","p":1072},{"i":1128,"t":"In the examples we have discussed before, all DTO properties are mapped from entity properties and become mapped properties. In addition to mapped properties, DTO types also support mapping custom properties: BookInput.dto BookInput { #allScalars(Author)? - id remark: String } Here, BookInput has a custom field remark. info The difference between custom properties and mapped properties is that custom properties require type definitions.","s":"11.1 Introduction to Custom Fields","u":"/jimmer-doc/docs/object/view/dto-language","h":"#111-introduction-to-custom-fields","p":1072},{"i":1130,"t":"Custom fields can be defined as built-in types, which are types built into the DTO language that do not require import via import. Primitive and boxed types DTO Language Type Generated Java Type Generated Kotlin Type Boolean boolean Boolean Boolean? Boolean Boolean? Char char Char Char? Character Char? Byte byte Byte Byte? Byte Byte? Short short Short Short? Short Short? Int int Int Int? Integer Int? Long long Long Long? Long Long? Float float Float Float? Float Float? Double double Double Double? Double Double? Any and String types DTO Language Type Generated Java Type Generated Kotlin Type Any Object Any String String String Array types DTO Language Type Generated Java Type Generated Kotlin Type Array boolean[] BooleanArray Array Boolean[] Array Array char[] CharArray Array Character[] Array Array byte[] ByteArray Array Byte[] Array Array short[] ShortArray Array Short[] Array Array int[] IntArray Array Integer[] Array Array long[] LongArray Array Long[] Array Array float[] FloatArray Array Float[] Array Array double[] DoubleArray Array Double[] Array Array UserType[] Array Array UserType[] Array Array<*> Object[] Array<*> Collection types DTO Language Type Generated Java Type Generated Kotlin Type Iterable Iterable Iterable MutableIterable Iterable MutableIterable Collection Collection Collection MutableCollection Collection MutableCollection List List List MutableList List MutableList Set Set Set MutableSet Set MutableSet Map Map Map MutableMap Map Mutable","s":"11.2 Built-in Types","u":"/jimmer-doc/docs/object/view/dto-language","h":"#112-built-in-types","p":1072},{"i":1132,"t":"Except for generic class types (arrays and collections) in built-in types, other generic class types support using in or out to modify generic parameters, for example: DTO Language Type Generated Java Type Generated Kotlin Type UserType1 UserType1 UserType1 UserType1 UserType1 UserType1 UserType1 UserType1 UserType1","s":"11.3 Generic Parameter Modifiers","u":"/jimmer-doc/docs/object/view/dto-language","h":"#113-generic-parameter-modifiers","p":1072},{"i":1134,"t":"Except for built-in types, other types must be fully qualified or imported at the beginning of the file when referenced, otherwise they will be considered to belong to the same package as the current entity. The DTO language supports various styles of import statements, for example: Single class import import java.time.LocalDateTime Single class renamed import import java.time.LocalDateTime as LDT Multi-class import import java.time.{ LocalDateTime, OffsetDataTime, ZonedDataTime } Multi-class renamed import import java.time.{ LocalDateTime as LDT, OffsetDataTime as ODT, ZonedDataTime as ZDT }","s":"11.4 Import Statements","u":"/jimmer-doc/docs/object/view/dto-language","h":"#114-import-statements","p":1072},{"i":1137,"t":"You can use annotations to decorate DTO types, mapped properties, and custom properties in the DTO language: BookInput.dto import org.babyfish.jimmer.client.Doc import javax.validation.constraints.Size @Doc(\"BookInput without associations\") ❶ BookInput { #allScalars @Size(min = 4, max = 20) ❷ name @Size(min = 10, max = 50) ❸ remark: String } Where: ❶ Decorates type ❷ Decorates mapped properties ❸ Decorates custom properties tip There is a detail to note: BookView ...import statements omitted... BookView { ...other properties omitted... @A authors @B { ...associated object properties omitted... } ...other DTO types omitted... } Where: @A decorates the authors property @B decorates the anonymous associated type","s":"12.1 Basic Usage","u":"/jimmer-doc/docs/object/view/dto-language","h":"#121-basic-usage","p":1072},{"i":1139,"t":"As mentioned above, the DTO language supports annotations to directly control the annotations of the generated DTO types. If a DTO property is not decorated by any annotation, the annotations of the corresponding property in the original entity will be copied (if the DTO property is mapped, not custom). Among them, any non-jimmer annotations under the org.babyfish.jimmer.client package will be copied to the generated DTO type, except for those.","s":"12.2 Annotation Replacement","u":"/jimmer-doc/docs/object/view/dto-language","h":"#122-annotation-replacement","p":1072},{"i":1141,"t":"The value parameter in annotations can be abbreviated, for example: @UserAnnotation(value = \"a\", value2 = \"b\", value3 = \"c\") can be abbreviated as: @UserAnnotation(\"a\", value2 = \"b\", value3 = \"c\") Unlike Java, no matter how many parameters an annotation has, the value parameter can be abbreviated, as long as the abbreviated property is configured first.","s":"12.3 value Parameter","u":"/jimmer-doc/docs/object/view/dto-language","h":"#123-value-parameter","p":1072},{"i":1143,"t":"There are some subtle differences between Java and Kotlin annotation syntax. The DTO language mixes the features of both, for example: @UserAnnotation( \"key1\", items = { @Item(\"subKey1\", description = \"Detail information for subKey1 ...\"), @Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), @Item(\"subKey3\", description = \"Detail information for subKey3 ...\") } ) @UserAnnotation( \"key1\", items = [ @Item(\"subKey1\", description = \"Detail information for subKey1 ...\"), @Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), @Item(\"subKey3\", description = \"Detail information for subKey3 ...\") ] ) @UserAnnotation( \"key1\", items = { Item(\"subKey1\", description = \"Detail information or subKey1 ...\"), Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), Item(\"subKey3\", description = \"Detail information for subKey3 ...\") } ) @UserAnnotation( \"key1\", items = [ Item(\"subKey1\", description = \"Detail information for subKey1 ...\"), Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), Item(\"subKey3\", description = \"Detail information for subKey3 ...\") ] ) The above four styles are equivalent. You can freely choose the style you like.","s":"12.4 Mixing Java and Kotlin Syntax","u":"/jimmer-doc/docs/object/view/dto-language","h":"#124-mixing-java-and-kotlin-syntax","p":1072},{"i":1145,"t":"DTO types are low-value information, and if different DTO types are allowed to reference each other, it would lead to a problem: the early effect is convenience, but the later effect is difficulty in maintenance. Therefore, Jimmer prohibits users from seeking reusability in low-value DTO types. However, sometimes there is indeed a need to find commonalities between different DTO types (especially for internal classes of DTO), in order to facilitate abstraction and design. For this purpose, the DTO language provides a compromise: DTO types are allowed to implement existing Java/Kotlin interfaces, provided that the abstract properties in the interface are a subset of the properties in the DTO and can be implemented by the DTO type. DTO code as follows export com.yourcompany.yourproject.model.Book -> com.yourcompany.yourproject.model.dto import com.yourcompany.yourcompany.common.{ Shape1, Shape2, Shape3, Shape4, Shape5, Shape6 } BookView implements Shape1, Shape2 { #allScalars store implements Shape3, Shape4 { #allScalars } authors implements Shape5, Shape6 { #allScalars } } Compiled, generates the following code Java Kotlin BookView.java package com.yourcompany.yourproject.dto; import com.yourcompany.yourproject.Book; import org.babyfish.jimmer.View; public class BookView implements View, Shape1, Shape2 { @Nullable private TargetOf_store store; private List authors; ...other members omitted... public static class TargetOf_store implements View, Shape3, Shape4 { ...members omitted... } public static class TargetOf_authors implements View, Shape5, Shape6 { ...members omitted... } } BookView.kt package com.yourcompany.yourproject.dto import com.yourcompany.yourproject.Book import org.babyfish.jimmer.View open class BookView( ...other properties omitted... store: TargetOf_store? = null, authors: List = emptyList() ) : View, Shape1, Shape2 { ...other members omitted... open class TargetOf_store( ...omitted... ): View, Shape3, Shape4 { ...omitted... } open class TargetOf_authors( ...omitted... ): View, Shape5, Shape6 { ...omitted... } } caution If a property in the DTO overrides an abstract property in the interface, then in the auto-generated Java/Kotlin type, that property will be annotated with @Override (Java) or override keyword (Kotlin). Apart from this, the DTO language does not perform much validation on interface implementation. If the user makes other mistakes, it will result in generating incorrect Java/Kotlin types, which will be handled by the Java/Kotlin compiler.","s":"13. Implementing Interfaces","u":"/jimmer-doc/docs/object/view/dto-language","h":"#13-implementing-interfaces","p":1072},{"i":1147,"t":"As mentioned earlier, the DTO language has two more powerful features that are not discussed in depth in this article due to length limitations, but have been separated into other documents. Here we emphasize them again: Handling Null Values in Input DTO Specification DTO, Super QBE","s":"12. Related Links","u":"/jimmer-doc/docs/object/view/dto-language","h":"#12-related-links","p":1072},{"i":1150,"t":"Jimmer is a bilingual Java/Kotlin framework It includes a revolutionary ORM Based on this ORM, it has built a comprehensive solution, including DTO language A more comprehensive and powerful caching mechanism, as well as highly automated cache consistency More powerful client documentation and code generation capabilities, including Jimmer's unique remote exceptions Quickly create GraphQL services Cross-microservice remote entity associations","s":"1. What is Jimmer","u":"/jimmer-doc/docs/overview/introduction","h":"#1-what-is-jimmer","p":1148},{"i":1153,"t":"In the current technology ecosystem, the technology system for accessing relational databases has significant flaws. Please see the image below. Static language ORM represented by JPA Brief description Dynamic language ORM represented by ActiveRecord (Ruby) Brief description Lightweight SQL Builder/Mapper represented by MyBatis Brief description","s":"Existing Pain Points","u":"/jimmer-doc/docs/overview/introduction","h":"#existing-pain-points","p":1148},{"i":1155,"t":"In the above, we have discussed three common solutions in the RDBMS accessing field, but no matter which one we choose, we cannot achieve convenience, flexibility, and code safety simultaneously. Why is this the case? info For the JVM ecosystem, POJO (like structure of other language) is the root cause of this problem. POJO lacks the necessary flexibility and expressiveness, yet it is used as the data model and core by almost all JVM frameworks, severely limiting technical innovation in the JVM ecosystem. Therefore, in Jimmer, ORM entity objects are not POJOs. Instead, they are a unique universal data object (to be introduced later), and this unique entity object underpins all of Jimmer's major innovations, serving as the foundation for the entire framework. note In fact, Jimmer entity objects can not only be applied in the ORM field but can also be used in almost any scenario where structured data maintenance is the purpose, enhancing the expressiveness of various technology stacks. Currently, Jimmer entities are only used in relational database access due to limited resources.","s":"Root Cause","u":"/jimmer-doc/docs/overview/introduction","h":"#root-cause","p":1148},{"i":1157,"t":"At the beginning of this document, we mentioned that the revolutionary ORM is only a part of Jimmer, and Jimmer's actual capabilities have already exceeded that of a mere ORM. Now, we present an overview of Jimmer's functionality and explain each part.","s":"3. Complete Functionality","u":"/jimmer-doc/docs/overview/introduction","h":"#3-complete-functionality","p":1148},{"i":1159,"t":"In information systems, there are two types of objects: Entities: Entity objects are globally unified, with rich associations between objects. Entity objects are often very close to the database and have extremely high stability. DTO: Input/output objects for specific business scenarios, usually a local fragment torn from the global entity relationship network, and the size and shape of this fragment are very flexible. The number of DTO types is enormous, and each business interface has unique requirements for the format of DTO objects, which may be similar but different, exhibiting a clear DTO explosion problem. Additionally, they are easily affected by changing requirements and are unstable. tip Entity types are the globally unified data storage model, less affected by changing requirements, relatively stable, and considered high-value types. DTO types, as the input/output for each business scenario, are relatively arbitrary, easily affected by changing requirements, and considered low-value types. Jimmer advocates that developers should concentrate their efforts on designing the high-value entity model; sometimes DTOs are not needed, and sometimes they are. Even when needed, they can be automatically generated in an extremely inexpensive way. Therefore, projects built on Jimmer have excellent resistance to changing requirements. 3.1.1. Jimmer Entity​ Jimmer entity definitions are very similar to JPA entities. See a quick demonstration As discussed earlier, Jimmer entities are not POJOs, so they are declared as interface instead of class. Then, who is responsible for implementing this interface? It's the Jimmer Precompiler in the diagram above (for Java, it's APT; for Kotlin, it's KSP). Jimmer entities support two important features: dynamism and immutability Dynamism Jimmer objects seek the best balance between static and dynamic languages, combining the advantages of both: Static language data objects have advantages such as high performance, spelling safety, type safety, and even null safety (if using Kotlin), and Jimmer entities inherit these advantages. Dynamic language data objects have a high degree of flexibility, and Jimmer entities inherit this advantage; each property can be missing (but unlike dynamic languages, properties cannot be added, as this would inevitably violate the characteristics of static languages, and Jimmer does not need this ability). For Jimmer, an object lacking a property (its value is unknown) and an object having a null value property (its value is known) are completely different scenarios. tip This balanced design allows Jimmer to enjoy the benefits of static languages while giving data structures tremendous flexibility. This absolute flexibility can be used to express both the output format of query operations and the input format of save operations. This gives Jimmer a new positioning: an ORM designed for data structures of any shape. All its features are for operating data structures of any shape, rather than simple entity objects. Immutability Jimmer objects are immutable objects. The benefits of immutable objects are multifaceted, and there are many related articles and discussions, so this document will not repeat them. tip Jimmer chooses immutable objects to ensure that data structures never contain circular references. This ensures that data structures formed by Jimmer entities and their associations can be directly serialized by Jackson without the need for any special serialization techniques or injecting additional information into the JSON, making it easily understandable by any programming language. However, immutable objects also have disadvantages. For example, if you have a very deep data structure, creating a new data structure based on it with some desired modifications would be very difficult, with the difficulty increasing rapidly as the depth increases. ORM deals with very deep data structures, and Java's records and Kotlin's data classes are not suitable for handling very deep data structures. The current JVM ecosystem lacks a solution that provides bilingual support for both Java and Kotlin while being adept at creating new immutable data structures based on existing deep data structures with desired modifications. Fortunately, the JavaScript/TypeScript world has a sufficiently powerful solution: immer, which can perfectly solve this problem. This solution works as follows: Open a temporary scope based on the existing immutable data structure. Within this scope, developers can obtain a draft data structure with the same shape and initial values as the original data structure, which can be modified at will, including modifying any deeply nested sub-objects. After the scope ends, the draft data structure will create a new data structure based on the collected modification operations. Unmodified local parts will be optimized and reuse the old objects. Immer perfectly combines the advantages of immutable and mutable objects, with simple code, powerful functionality, and excellent performance. Therefore, Jimmer chose to port immer to the JVM ecosystem, and the project name is also a tribute to it. See a quick demonstration Reference links: Dynamism, Immutability 3.1.2. Generated DTO Type​ As mentioned earlier, Jimmer entities strike the best balance between static and dynamic language data objects, with dynamism bringing tremendous flexibility and determining the positioning of the entire framework. Jimmer objects allow certain properties to be missing, and an object lacking a property (its value is unknown) is completely different from an object having a null property (its value is known). For Jackson serialization, missing properties will be automatically ignored, just as we showed earlier. If the server does not use the queried entity object itself but directly writes it to the HTTP Response, there is no need for a DTO, and using the entity object directly is convenient. If you directly access a non-existent property using Java/Kotlin code, it will cause an exception. See a quick demonstration If the server needs to access the queried entity object itself, this could introduce risks, although Jimmer entities still retain static language features in other aspects, such as spelling safety, type safety, and even null safety (if using Kotlin). For example, in JPA, since Hibernate 3, lazy configuration is no longer limited to associated properties but can also be used for scalar properties. Later, this evolved into the fetch parameter of the JPA @Basic annotation, please refer here. This has some similarity to the fact that any property in Jimmer objects can be missing, except that Jimmer generalizes this feature to any property. So, this exception in Jimmer is somewhat similar to org.hibernate.LazyInitializationException. So, this is not a new problem created by Jimmer, but rather an existing and accepted problem in the static language ORM ecosystem. However, it is undeniable that this does indeed undermine the safety of static languages. If you want to pursue 100% static language safety, using DTO objects is the only way. However, the current DTO mapping technology in the JVM ecosystem has significant flaws. Either you explicitly map properties (e.g., pure manual mapping and conversion), which is extremely labor-intensive, tedious, and error-prone. Or you implicitly map properties (e.g., using BeanUtils technology), which introduces new safety issues that cannot be detected at compile-time. Even if you use the powerful mapstruct, all you can do is choose between these two extremes. Therefore, Jimmer provides a DTO language, where users can write very simple code, and compiling the project will automatically generate various rich DTO type definitions. tip The design goals of the DTO language are: To make the process of generating DTO types simple enough so that DTO types are inexpensive. To be 100% compliant with static language safety, detecting and reporting all issues at compile-time. In any sub-project (not limited to entity definition sub-projects), developers can freely create files with the dto extension in the src/main/dto directory to automatically generate various DTO types at a low cost. See a quick demonstration These low-cost, rapidly generated DTO types can be converted to and from Jimmer entity objects; therefore, any two DTO types can be converted to each other using Jimmer entities as an intermediate medium. Reference links: DTO language","s":"3.1. Business Model","u":"/jimmer-doc/docs/overview/introduction","h":"#31-business-model","p":1148},{"i":1161,"t":"tip Fetcher is one of the three most fundamental core features of Jimmer (the other two are Save Command and SQL DSL). Jimmer is designed to query data structures of any shape, allowing you to control the format of queried data with the same granularity as GraphQL. First, let's get an initial impression of Jimmer's ability to control the shape of queried data structures through this animation (you don't need to look too closely, just get a general idea). View animation As mentioned earlier, you can directly use entity objects or the inexpensively generated DTO objects. Fetcher provides first-class support for querying both types of data objects. Let's demonstrate its usage through three scenarios: Querying partial objects A partial object refers to querying only a subset of an object's properties, containing less information than a single object. See a quick demonstration Including associated objects Select an entity as the aggregate root, not only querying the aggregate root object but also querying its associated objects, with no restrictions on depth or breadth. This level of granularity in format control is similar to GraphQL. See a quick demonstration Recursive queries If the entity contains a self-association property, you can perform recursive queries (as of now, GraphQL does not support recursive queries). See a quick demonstration info Users should actively use this feature to query data structures of any complexity, rather than writing business code to retrieve data from different parts and then combine them into a whole, because Fetcher has advantages that are difficult to replicate with business code: It can handle not only associated properties but also complex calculated properties. It can fully utilize Jimmer's associated property caching and calculated property caching to significantly optimize the performance of querying complex data structures. Entities support remote associations, i.e., ORM associations across microservice boundaries, with Jimmer automatically querying data from different microservices and assembling it into a single data structure. The entire deep-dive process is driven by breadth-first recursion to support batch query optimization. No work is required from developers, as the ORM itself has powerful capabilities that rival GraphQL. Therefore, whether you use Jimmer to build REST services or GraphQL services, query-related tasks are very simple. Quickly build REST services The server controls the shape of the returned objects. If an HTTP API needs to return data in a certain structure, developers have two choices: either use the entity type directly or use the DTO language to cheaply generate DTO types. Whichever choice is made, the client passively accepts the data format returned by the server. Even if the client needs many different data structure shapes, the impact on the Jimmer-based server is minimal. If developers choose to return entity objects directly instead of DTOs, the server does not have the DTO explosion problem, which is not a problem for the server; but for the client, this is very bad. Jimmer generates Open API documentation and TypeScript code for the client. If the server developer chooses to return entity objects directly, the @FetchBy annotation can be used to modify the return type of the Web method, which can define the DTO type for the client in the Open API and TypeScript code. Client DTO Quickly build GraphQL services Usually, providing GraphQL services is not a small task, and developers need to put a lot of effort into supporting the rich associations between GraphQL objects. However, implementing GraphQL based on Jimmer is very easy because the ORM itself already has capabilities similar to GraphQL. Developers only need to implement queries for the aggregate root objects of the GraphQL query API, and the rich associations between GraphQL objects are automatically implemented by Jimmer. Reference links Link Description Quick Preview/Query Any Shape Quick preview: Query any shape jimmer-examples/tree/main/java/jimmer-sql Example project, using Java and Jimmer to build REST services jimmer-examples/tree/main/kotlin/jimmer-sql-kt Example project, using Kotlin and Jimmer to build REST services jimmer-examples/tree/main/java/jimmer-sql-graphql Example project, using Java and Jimmer to build GraphQL services jimmer-examples/tree/main/kotlin/jimmer-sql-graphql-kt Example project, using Kotlin and Jimmer to build GraphQL services jimmer-examples/tree/main/java/jimmer-cloud Example project, using Java and Jimmer to support ORM remote association across microservice boundaries jimmer-examples/tree/main/kotlin/jimmer-cloud-kt Example project, using Kotlin and Jimmer to support ORM remote association across microservice boundaries","s":"3.2. Fetcher","u":"/jimmer-doc/docs/overview/introduction","h":"#32-fetcher","p":1148},{"i":1163,"t":"tip Save Command is one of Jimmer's three most fundamental core capabilities (the other two are Fetcher and SQL DSL). Save Command is designed specifically for complex forms. No matter how complex the form is, it essentially represents a data structure of any shape, and Jimmer allows developers to write data structures of any shape into the database with a single method call. No matter how complex the data structure provided by the user is, Jimmer will query a data structure of the same complexity from the database and find the differences (this is not the actual working mechanism, but it's fine to understand this functionality from the user's perspective), and execute insert, update, and delete statements to update the differences. View illustration However, if the client is allowed to upload entity objects representing data structures of any shape, the client will have unrestricted data modification capabilities, which would seriously compromise security. Therefore, Input DTOs must be generated using the DTO language, and then used as input parameters for the Web API. That is: Dynamic entities serve as the internal mechanism, allowing the Save Command to save data structures of any shape, providing functional support for unlimited possibilities. Input DTO acts as a security guard, strictly limiting the user's input format, and exposing only limited data entry capabilities. Next, we will demonstrate the basic usage of the Save Command through four cases: Save a standalone object This is the simplest case because a standalone object does not have any associated data. View quick demo Save short associations A short association refers to only changing the association relationship between the current object and other objects, without further modifying the associated objects. For the UI, a reference association (one-to-one and many-to-one) is represented as a single-selection menu; a collection association (one-to-many and many-to-many) is represented as a multi-selection menu . Common UI for Short Association View quick demo Save long associations A long association refers to not only changing the association relationship between the current object and other objects, but also further modifying the associated objects. For the UI, the forms can be diverse, with nested sub-tables being the most common (one-to-many) : Common UI for Long Association View quick demo Recursively save tree structures This example is a bit different, requiring a slight modification of the root node's data before saving. View quick demo Reference links Link Description Quick Preview/Query Any Shape Quick preview: Save any shape jimmer-examples/tree/main/java/save-command Example project, using Java and Jimmer to demonstrate various scenarios of Save Command jimmer-examples/tree/main/kotlin/save-command-kt Example project, using Kotlin and Jimmer to demonstrate various scenarios of Save Command jimmer-examples/tree/main/java/jimmer-sql Example project, using Java and Jimmer to build REST services jimmer-examples/tree/main/kotlin/jimmer-sql-kt Example project, using Kotlin and Jimmer to build REST services jimmer-examples/tree/main/java/jimmer-sql-graphql Example project, using Java and Jimmer to build GraphQL services jimmer-examples/tree/main/kotlin/jimmer-sql-graphql-kt Example project, using Kotlin and Jimmer to build GraphQL services","s":"3.3. Save Command","u":"/jimmer-doc/docs/overview/introduction","h":"#33-save-command","p":1148},{"i":1165,"t":"tip SQL DSL is one of Jimmer's three most fundamental core capabilities (the other two are Fetcher and Save Command). Jimmer's SQL DSL is designed for arbitrary complex dynamic SQL. Currently, there are dozens of SQL DSLs in the entire JVM ecosystem. Among them, the ORM-style QueryDSL and the NativeSQL-style JOOQ are the most well-known. What are the characteristics of Jimmer's SQL DSL? Jimmer's SQL DSL is designed from the ground up for arbitrary complex dynamic SQL, including two powerful capabilities: dynamic table joins and implicit subqueries. Native SQL is not conducive to building complex dynamic queries, and the purpose of Jimmer's SQL DSL is to provide a solution for this; while the strong type safety that all SQL DSLs can achieve is just a side effect. Intelligent paging support, where developers only need to use the DSL to construct a regular list query, and Jimmer automatically generates a total row count query and automatically combines it with the list query to complete the paging query. Jimmer's SQL DSL can embed native SQL expressions. Due to space limitations, this article only discusses the first point above. Let's get a basic understanding of Jimmer's SQL DSL through three small examples: Simple dynamic query A simple dynamic query to establish an initial impression. View quick demo Dynamic table join Dynamically add SQL conditions for the associated objects of reference association (one-to-one or many-to-one) properties. View quick demo Implicit subquery Jimmer supports more complete regular subqueries. However, some subqueries closely related to entity associations can be written as these simpler implicit subqueries. Dynamically add SQL conditions for the associated objects of collection association (one-to-many or many-to-many) properties. View quick demo tip In fact, users can also leverage the DTO language to write specification DTOs, allowing Jimmer to automatically generate query condition parameters and all the dynamic query behaviors you've seen above. This more convenient feature is called Super QBE, Here, we adopt this feature to replace all the features introduced above. View quick demo Reference links Link Description Quick Preview/Query Any Shape Quick preview: Arbitrary dynamic queries Dynamic Table Join Implicit Subquery Intelligent Paging Not shown in this article Native Expression Not shown in this article, how to embed native SQL fragments in a strongly-typed SQL DSL Dynamic Ordering Not shown in this article Super QBE Here, no links to relevant examples are provided because all examples involve using the SQL DSL.","s":"3.4. SQL DSL","u":"/jimmer-doc/docs/overview/introduction","h":"#34-sql-dsl","p":1148},{"i":1167,"t":"This feature is similar to the database's after-trigger, which notifies the application after a database change occurs. The trigger not only notifies developers of what changes have occurred to which entity objects, but also performs ORM mapping on the change event information to notify developers of what associated changes have occurred. The trigger lays a solid foundation for another feature: caching. Jimmer supports two different types of triggers: BinLog triggers and Transaction triggers BinLog Trigger Transaction Trigger (Default Off) Working Principle Discover data changes by integrating mature CDC solutions in the industry (e.g., maxwell, debezium) Discover database changes through Jimmer's capability Notification Timing After transaction commit Before transaction commit Advantages Can sense database changes caused by any reason, including database changes that bypass the system Either the original change and the new change caused by the trigger both succeed or both fail Disadvantages After the transaction is committed, there is a slight delay in the CDC service pushing Can only sense changes to the database caused by modifications through Jimmer in the current JVM process, and cannot handle changes caused by any other reasons The duration of the current transaction will be extended, and the unlock operation of related resources will also be delayed Will cause Jimmer's modification behavior to the database to require more additional queries internally Applicable Scenarios Most scenarios, including but not limited to: cache synchronization, data synchronization across heterogeneous systems Additional behavior that must participate in the same transaction as the main business logic Reference link: Trigger","s":"3.5 Trigger","u":"/jimmer-doc/docs/overview/introduction","h":"#35-trigger","p":1148},{"i":1169,"t":"Jimmer's caching capability is very powerful, with the following 3 features: Supports multi-level caching, and each level of caching allows users to choose their preferred technology. In the accompanying example, the first-level cache is Caffeine; the second-level cache is Redis Significantly increases the application scope of caching. No longer limited to the most common id->object caching, i.e., Object Cache, but also supports the following three types of caching: id->associated id caching, i.e., Association Cache Association caching can significantly improve the performance of navigating between associated objects, which is very helpful for Jimmer's core functionality of querying data structures of any complexity. id->computed result caching, i.e., Calculated Cache Calculated caching is designed for complex computed properties, avoiding repeated calculations for multiple queries, which is also very helpful for Jimmer's core functionality of querying data structures of any complexity. Can also be combined with the permission system. Since users with different identities see different data in the database, they should also see different cached data, i.e., Multi-View Cache Storing different data for users with different identities is very memory-intensive and should definitely not be used for JVM internal caching. For external caches like Redis, it should also be used with caution, only for very important data. info Q: Why has business system caching been mainly limited to object caching for a long time, lacking diversity? A: Without the underlying framework providing highly automated support for cache consistency, the cost of using business code to maintain other types of caching is too high. Highly automated cache consistency. Jimmer provides highly automated support for cache consistency, simply by enabling the Jimmer Trigger (whether it's the BinLog trigger or the Transaction trigger). For object cache and association cache, their consistency is fully automated and requires no intervention from developers. For calculated cache and multi-view cache, developers' assistance is needed, but what developers need to do is very simple. View the effect of cache consistency Reference link: Caching","s":"3.6. Cache","u":"/jimmer-doc/docs/overview/introduction","h":"#36-cache","p":1148},{"i":1171,"t":"Global filters add inherent SQL filtering conditions to entities in a plugin manner outside the SQL DSL system. The most common application scenario is row-based permission management. Global filters are very flexible and can easily integrate with any IoC framework (such as Spring), allowing free access to business context information and thus implementing filtering logic that is closely integrated with the business. Reference link: Global Filter","s":"3.7. Global Filter","u":"/jimmer-doc/docs/overview/introduction","h":"#37-global-filter","p":1148},{"i":1173,"t":"The Draft Interceptor is similar to the database's before-trigger, giving users one last chance to adjust the data that is about to be saved before the database change occurs. The Draft Interceptor is very flexible and can easily integrate with any IoC framework (such as Spring), allowing free access to business context information and thus implementing data adjustment logic that is closely integrated with the business. Reference link: Interceptor","s":"3.8. Draft Interceptor","u":"/jimmer-doc/docs/overview/introduction","h":"#38-draft-interceptor","p":1148},{"i":1175,"t":"Logical deletion refers to the fact that a business-level data deletion operation does not actually cause the data to be deleted from the database, but simply modifies a field of the data to mark it as \"deleted\". Logical deletion also provides a built-in Global Filter, which causes data marked as \"deleted\" to be excluded from any query and unaffected by any modification statement. Jimmer's logical deletion supports both entity tables and join tables. Reference link: Logical Deletion of Entity Tables, Logical Deletion of Join Tables","s":"3.9. Logical Deletion","u":"/jimmer-doc/docs/overview/introduction","h":"#39-logical-deletion","p":1148},{"i":1177,"t":"Jimmer entities support remote associations, i.e., ORM associations across microservice boundaries. When querying a specific complex data structure, if the shape of the data structure spans multiple microservices, Jimmer will automatically query data from different microservices and assemble it into a whole to return to the developer. note Remote Associations is just the first feature for microservice development in a limited time, aiming to prove to developers that the ORM technology system can still be very powerful in the microservice technology system. After Jimmer gradually matures and releases the official 1.0 version, more features will be added to the microservice technology system to abstract and simplify more tedious details in that system. Reference link: Remote Association Mapping, Remote Association Support","s":"3.10. Remote Associations","u":"/jimmer-doc/docs/overview/introduction","h":"#310-remote-associations","p":1148},{"i":1179,"t":"Next, we will introduce Jimmer's third-party ecosystem, which are all contributed by Jimmer users. We would like to express our sincere gratitude. DTO language IntelliJ plugin https://github.com/ClearPlume/jimmer-dto Entity model generation tool The following tools focus on generating entity models based on the database Project Type Language Support Project Address IntelliJ Plugin Java&Kotlin https://github.com/ClearPlume/jimmer-generator IntelliJ Plugin Java&Kotlin https://github.com/huyaro/CodeGenX Maven Plugin Java https://github.com/TokgoRonin/code-generator-jimmer Gradle Plugin Java&Kotlin https://github.com/Enaium/jimmer-gradle Model Designer Java&Kotlin https://pot-mot.github.io/jimmer-code-gen-doc Quarkus extension https://github.com/flynndi/quarkus-jimmer-extension Solon extension https://github.com/zengyufei/xm-jimmer-solon-plugin Gradle Plugin https://github.com/ArgonarioD/gradle-plugin-jimmer https://github.com/Enaium/jimmer-gradle","s":"4. Ecosystem","u":"/jimmer-doc/docs/overview/introduction","h":"#4-ecosystem","p":1148},{"i":1181,"t":"When developing with Jimmer, there is a note of caution that needs attention. Please refer to here","s":"5. Notes","u":"/jimmer-doc/docs/overview/introduction","h":"#5-notes","p":1148},{"i":1184,"t":"In order to take full advantage of Kotlin's language features and optimize its development experience, Jimmer provides different APIs for Java and Kotlin, but they are essentially the same. However, outer joins are the only exception. For this detail, the behaviors of Java API and Kotlin API are different: Java DSL Use JoinType to represent join type, which can be INNER (default), LEFT, RIGHT or FULL Kotlin DSL Properties with the same name as entity properties represent inner joins Properties with a ? after the entity properties name represent left joins That is, Kotlin DSL does not support RIGHT and FULL. This sacrifice is a careful trade-off, in exchange for a more important feature for Kotlin: perfectly combining Kotlin's null safety and SQL DSL.","s":"Dilemma","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#dilemma","p":1182},{"i":1186,"t":"The entity BookStore is defined as follows: @Entity interface BookStore { val name: String val website: String? // Omit other code } The precompiled code generates: public val KNonNullProps.name: KNonNullPropExpression get() = get(\"name\") public val KNullableProps.name: KNullablePropExpression get() = get(\"name\") public val KProps.website: KNullablePropExpression get() = get(\"website\") Please ignore the details of the generated code for now. We can see many types containing NonNull or Nullable. tip In Jimmer's Kotlin SQL DSL, almost all AST types have both NonNull and Nullable implementations. This means Kotlin SQL DSL has null safety features equivalent to Kotlin language itself. SQL-style query code has complete null safety self-checking capabilities. Let's look at a simple example first: val tuples = sqlClient .createQuery(BookStore::class) { select( table.name, table.website ❶ ) } .execute() for ((name, website) in books) { ❷ println(\"Length of name: ${name.length}\") // Compile error println(\"Length of website: ${website.length}\") ❸ } Since BookStore.website is nullable, the type of the second column selected at ❶ is String? instead of String. The final return type of the query is List>. ❷ Loops through each tuple queried, destructuring into variables name and website. Since tuples is of type List>, here website is of type String?. ❸ Performs .length operation on potentially null website, causing compile error. To fix this compile error, modify code at ❸ to change . to ?.: println(\"Length of website: ${website?.length}\")","s":"Getting Started with DSL's Null Safety","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#getting-started-with-dsls-null-safety","p":1182},{"i":1188,"t":"In the above, we learned the simplest null safety in SQL DSL through a very simple example. Now, let's combine null safety with table join operations:","s":"Null Safety in Table Joins","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#null-safety-in-table-joins","p":1182},{"i":1190,"t":"val tuples = sqlClient .createQuery(BookStore::class) { select( table.name, table.store.name ❶ ) } .execute() for ((name, storeName) in books) { ❷ println(\"Length of name: ${name.length}\") println(\"Length of storeName: ${storeName.length}\") ❸ } ❶ Uses inner join to get parent object's name. The final return type of the query is List>. ❷ Destructures into variables storeName of type String, non-nullable. So code at ❸ compiles.","s":"Inner Join","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#inner-join","p":1182},{"i":1192,"t":"Let's modify the code to change inner join to outer join: val tuples = sqlClient .createQuery(BookStore::class) { select( table.name, table.`store?`.name ❶ ) } .execute() for ((name, storeName) in books) { ❷ println(\"Length of name: ${name.length}\") // Compile error println(\"Length of storeName: ${storeName.length}\") ❸ } ❶ Uses left join to get parent object. The precompiled code in BookProps.kt includes: public val KProps.store: KNonNullTable get() = join(\"store\") public val KProps.`store?`: KNullableTable get() = outerJoin(\"store\") Unlike inner join store, outer join store? returns a table of type KNullableTable, i.e. nullable table. This is the effect of left join in SQL. The precompiled code in BookStoreProps.kt includes: public val KNonNullProps.name: KNonNullPropExpression get() = get(\"name\") ❹ public val KNullableProps.name: KNullablePropExpression get() = get(\"name\") ❺ The returned KNullableTable inherits from KNullableProps instead of KNonNullProps. So in the DSL, accessing name matches ❺ instead of ❹. That is, just BookStore.name being non-null is not enough, need to also consider if the table it is accessed from is non-null. Ultimately, Jimmer determines the second column in ❶ is String?, so the return type is List>. ❷ Destructures into storeName of type String?, nullable. This must cause compile error at ❸. To fix this compile error, modify code at ❸ to change . to ?.: println(\"Length of storeName: ${storeName?.length}\") ❸","s":"Left Join","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#left-join","p":1182},{"i":1194,"t":"In the previous doc, we discussed dynamic queries. In this section, we will explore the problems with dynamic table joins. Currently, other technologies that operate on SQL, whether ORM or non-ORM, have a blank area: they only consider dynamic where, and do not consider dynamic join. Dynamic JOIN is defined as: If some dynamic query conditions are for tables other than the current table. This means When the condition is met: First join to other tables through association properties, then add dynamic where conditions to the joined table When the condition is not met: Cannot join other tables through association properties","s":"Problems with Other Solutions","u":"/jimmer-doc/docs/query/dynamic-join/problem","h":"","p":1193},{"i":1196,"t":"Let's first look at the first scene, taking MyBatis oriented to native SQL as an example Define MyBatis Mapper interface @Mapper public interface BookMapper { List findBooks( @Nullable String name, @Nullable String storeName, @Nullable String storeWebsite ); } Here, all query parameters may be null, which is clearly a dynamic query. The last two query parameters: storeName and storeWebsite, their filtering conditions are not applied on the current table BOOK, but on the parent table BOOK_STORE. That is, when any of these two parameters is non-null, a JOIN to the BOOK_STORE table will be generated. This table join dynamically determined by the parameter value is referred to as dynamic JOIN in this article. Define MyBatis SQL mapping XML Here, ❶ is the dynamic JOIN. However, for developers, ❷ and ❸ are the purpose, and ❶ is the work that has to be done to support ❷ and ❸. Its judgment condition is a burden. You may have noticed that ❶ uses or. This is easy to understand. However, this is only the simplest dynamic connection between two tables. For deeper multi-table join operations, the complexity of dynamic table joins will increase dramatically!","s":"Scene-1","u":"/jimmer-doc/docs/query/dynamic-join/problem","h":"#scene-1","p":1193},{"i":1198,"t":"Let's take a look at the second scene. With the previous example as the basis, this example is decoupled from any business. The logic of this example is simple. The five tables A, B, C, D and E form a JOIN chain, and each table has a dynamic query condition. However, as you can see, the complexity of dynamic JOIN has become unacceptable.","s":"Scene-2","u":"/jimmer-doc/docs/query/dynamic-join/problem","h":"#scene-2","p":1193},{"i":1201,"t":"Let's review this piece of entity interface code: Java Kotlin @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); ...omit other code... } @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List ...omit other code... } The BOOK_AUTHOR_MAPPING table is used as an association table here. The BOOK table in the database has a corresponding Book entity interface in Java code. The AUTHOR table in the database has a corresponding Author entity interface in Java code. However, the BOOK_AUTHOR_MAPPING table in the database does not have a corresponding entity interface in Java code. That is, the association table is hidden from the object model.","s":"Association Tables Hidden by Object Model","u":"/jimmer-doc/docs/query/associations","h":"#association-tables-hidden-by-object-model","p":1199},{"i":1203,"t":"Jimmer provides an interesting feature that allows querying association tables directly even if they are hidden without corresponding entities. Java Kotlin AssociationTable association = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List> associations = sqlClient .createAssociationQuery(association) .where(association.source().id().eq(3L)) .select(association) .execute(); associations.forEach(System.out::println); val associations = sqlClient .queries .forList(Book::authors) { where(table.source.id eq 3L) select(table) } .execute() associations.forEach(::println) Here, createAssociationQuery in Java or queries.forList in Kotlin represents a query based on the association table instead of entity tables. tip The Java code demo here uses AssociationTable type with complex generic arguments to be compatible with Java 8. It is recommended to upgrade Java and use the var keyword. The generated SQL is: select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID from BOOK_AUTHOR_MAPPING as tb_1_ where tb_1_.BOOK_ID = ? /* 3 */ This is indeed a query based on the association table. The final printed result is (the original output is compact, formatted here for readability): Association{ source={ \"id\":3 }, target={ \"id\":1 } } Association{ source={ \"id\":3 }, target={ \"id\":2 } } The returned data is a list of Association objects: public class Association { public S source; public T target; // constructor and getter/setters } The Association represents association table entities that associate S type to T type. Association table entities are pseudo entities without ids. They only have two properties: source: The object (Book in this example) corresponding to the foreign key pointing to the owning side. target: The object (Author in this example) corresponding to the foreign key pointing to the target side. note In this example, object fetchers are not used to define the format of association pseudo entity objects (in fact association pseudo entity does not support object fetchers), so the source and target association properties only contain id property. Author also has a bidirectional many-to-many association Author.books, which is the mirror of Book.authors. Java Kotlin @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ... } @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ... } Association table queries can also be created based on Author.books, but source will represent Author and target will represent Book, reversed from the current example. In this example, we only query the association table itself, so source and target objects only contain ids. To get complete source and target objects, join tables and use tuples for return: Java Kotlin AssociationTable association = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List> tuples = sqlClient .createAssociationQuery(association) .where(association.source().id().eq(3L)) .select( association.source(), association.target() ) .execute(); tuples.forEach(System.out::println); val associations = sqlClient .queries .forList(Book::authors) { where(table.source.id eq 3L) select( table.source, table.target ) } .execute() associations.forEach(::println) The generated SQL is: select /* source() */ tb_1_.BOOK_ID, tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID, /* target() */ tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join BOOK as tb_2_ on tb_1_.BOOK_ID = tb_2_.ID inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID = ? /* 3 */ The final printed result is (formatted for readability): Tuple2{ _1={ \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } }, _2={ \"id\": 1, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" } } Tuple2{ _1={ \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } }, _2={ \"id\": 2, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"MALE\" } } caution The association pseudo entity Association is simple and special, does not support or need object fetchers. However, its association properties source and target can support object fetchers, such as: Kotlin select( table .source .fetchBy { allScalarFields() store { allScalarFields() } }, table.target )","s":"Querying Association Tables Directly","u":"/jimmer-doc/docs/query/associations","h":"#querying-association-tables-directly","p":1199},{"i":1205,"t":"Readers may think that association table queries exist to allow developers to write more performant queries. But this is not the case. Due to optimizations like phantom joins and half joins, whether association table queries are used or not, similar functionality and performance can be achieved. Using association table queries is completely up to user preference.","s":"Comparison with Entity Table Queries","u":"/jimmer-doc/docs/query/associations","h":"#comparison-with-entity-table-queries","p":1199},{"i":1207,"t":"In previous examples, we demoed top-level queries based on association tables. Here we demo an association table subquery. Java Kotlin BookTable table = Tables.BOOK_TABLE; AssociationTable association = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List books = sqlClient .createQuery(table) .where( table.id().in( sqlClient .createAssociationSubQuery(association) .where( association .target() ❶ .firstName().eq(\"Alex\") ) .select( association .source() ❷ .id() ) ) ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id valueIn subQueries.forList(Book::authors) { where( table .target ❶ .firstName eq \"Alex\" ) select( table .source ❷ .id ) } ) select(table) } .execute() Where: createAssociationSubQuery in Java and subQueries.forList in Kotlin create a subquery based on the association table, to find books that contain the author with firstName \"Alex\". ❶ association.target is a real JOIN that generates SQL JOIN to the AUTHOR table for condition check. ❷ association.source is a phantom join that does not generate a SQL join. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_2_.BOOK_ID from BOOK_AUTHOR_MAPPING as tb_2_ inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID where tb_3_.FIRST_NAME = ? )","s":"1. Use association table subquery to achieve a function","u":"/jimmer-doc/docs/query/associations","h":"#1-use-association-table-subquery-to-achieve-a-function","p":1199},{"i":1209,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().in(sqlClient .createSubQuery(author) .where(author.firstName().eq(\"Alex\")) .select( author.books().id() ❶ ) ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id valueIn subQuery(Author::class) { where(table.firstName eq \"Alex\") select( table.books.id ❶ ) } ) select(table) } .execute() ❶ author.books is a half join that only generates SQL JOIN from AUTHOR to the BOOK_AUTHOR_MAPPING table, without further join to the BOOK table. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME = ? ) Comparing the two SQLs, it's not hard to see they achieve the same functionality and performance. info Association table queries just provide developers with another query style, they are not irreplaceable. The same functionality and performance can be achieved with other means.","s":"2. Achieve the same functionality with entity table subquery","u":"/jimmer-doc/docs/query/associations","h":"#2-achieve-the-same-functionality-with-entity-table-subquery","p":1199},{"i":1212,"t":"All the joins we have discussed so far rely on the association properties between entities, which means table joins are always related to primary and foreign keys. However, sometimes we need to join two tables based on some business properties unrelated to primary and foreign keys. Although not frequently used, such relatively free table joins can be very useful when needed. For this scenario, you have two options: Use @JoinSql to declare a ManyToMany association unrelated to primary and foreign keys, then use the association property to perform the join info This approach is suitable when the corresponding join operation is needed by multiple business scenarios and has high reusability. Directly use the weak join explained in this article, without declaring any association properties between entities info This approach is suitable when the corresponding join operation is only needed by some individual business scenarios and you don't want to define a @JoinSql based association property in entities just for this purpose.","s":"The Problem to Solve","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","h":"#the-problem-to-solve","p":1210},{"i":1215,"t":"To use weak join: For Java, first implement the WeakJoin interface For Kotlin, implement the KWeakJoin abstract class Java Kotlin WeakJoin.java package org.babyfish.jimmer.sql.ast.table; import org.babyfish.jimmer.sql.ast.Predicate; public interface WeakJoin, TT extends Table> { Predicate on(ST source, TT target); } KWeakJoin.kt package org.babyfish.jimmer.sql.kt.ast.table abstract class KWeakJoin /* omit super types */ { abstract fun on( source: KNonNullTable, target: KNonNullTable ): KNonNullExpression ...other code omitted... } For Java, the generic type parameters of the WeakJoin interface should be the Table classes generated by the preprocessor for the current entity and target entity, e.g. WeakJoin For Kotlin, the generic type parameters of the KWeakJoin abstract class should be the current entity and target entity, e.g. KWeakJoin Developers need to customize a class to implement the custom table join condition: Java Kotlin private static class BookAuthorJoin implements WeakJoin { @Override public Predicate on(BookTable source, AuthorTable target) { return Predicate.and( source.businessProp1().eq(target.businessPropA()), source.businessProp2().eq(target.businessPropB()) ); } } private class BookAuthorJoin : KWeakJoin { override fun on( source: KNonNullTable, target: KNonNullTable ): KNonNullExpression = and( source.businessProp1 eq target.businessPropA, source.businessProp2 eq target.businessPropB ) } caution WeakJoin/WeakJoin is an interface, but implementation must be a class rather than a lambda expression. Do not use anonymous classes for implementation. Although anonymous classes can work, they violate the design intent here. If the class has no reuse value at all, it is recommended to define it as a private static nested class. The class itself does not have generic type parameters, but the generic parameters of the super interface/class must be explicitly specified. The reasons for the first two points will be explained later. Developers can even use NativeSQL expressions to build more arbitrary join conditions, e.g. (assuming MySQL is used here, calling the SQL function substr): Java Kotlin private static class BookAuthorJoin implements WeakJoin { @Override public Predicate on(BookTable source, AuthorTable target) { return Predicate.sql( \"substr(%e, 1, 5) = substr(%e, 1, 5)\", new Expression[] { source.code(), target.code() } ); } } private class BookAuthorJoin : KWeakJoin { override fun on( source: KNonNullTable, target: KNonNullTable ): KNonNullExpression = sql(Boolean::class, \"substr(%e, 1, 5) = substr(%e, 1, 5)\") { expression(source.code) expression(target.code) } } info Here, Predicate.sql in Java code and sql in Kotlin code are methods to mix native SQL snippets into the strongly typed Jimmer SQL DSL. We have never introduced these before, please refer to NativeSQL expressions.","s":"Define Join Condition","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","h":"#define-join-condition","p":1210},{"i":1217,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(table) .where( table .asTableEx() ❶ .weakJoin(BookAuthorJoin.class) ❷ .firstName().eq(\"Alex\") ) .select(table.id()) .distinct() .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() ❶ .weakJoin(BookAuthorJoin::class) ❷ .firstName eq \"Alex\" ) select(table.id) } .distinct() .execute(); ❶ Converts Table to TableEx using asTableEx caution The subsequent weakJoin is only supported by TableEx, not by Table. ❷ Calls weakJoin with the BookAuthorJoin class defined before as the join condition, joining to the author table Here, the return type of weakJoin is AuthorTable/KNonNullTable The following methods can be used to support outer join: Java: weakJoin(BookAuthorJoin.class, JoinType.LEFT) Kotlin: weakOuterJoin(BookAuthorJoin::class) info We have introduced a feature called Merge Conflict Join before. It is important that weakJoin is compatible with it. For the same join source, if weakJoin is called multiple times with the same WeakJoin class (the BookAuthorJoin class here), they can be merged into one join operation to avoid duplicate joins in the final SQL. This is why the BookAuthorJoin class cannot be implemented using lambda or anonymous classes, as mentioned earlier.","s":"Use the Join Condition","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","h":"#use-the-join-condition","p":1210},{"i":1220,"t":"In Problems with current solutions note There are two ways to solve this problem. This article demonstrates the first solution. Solve the problem in scenario 1: Java Kotlin List findBooks( @Nullable String name, @Nullable String storeName, @Nullable String storeWebsite ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null, () -> book.name().like(name) ) .whereIf( storeName != null, () -> table .store() ❶ .name() .like(storeName) ) .whereIf( storeWebsite != null, () -> table .store() ❷ .website() .like(storeWebsite) ) .select(book) .execute(); } fun findBooks( name: String? = null, storeName: String? = null, storeWebsite: String? = null ): List = sqlClient .createQuery(Book::class) { name?.let { where(table.name like it) } storeName?.let { where( table .store ❶ .name like it ) } storeWebsite?.let { where( table .store ❷ .website like it ) } select(table) } .execute() This is a typical dynamic query where all three query parameters are nullable. Specify name but storeName and storeWebsite are still null. In this case, the code at ❶ and ❷ will not execute. The final generated SQL does not contain any joins. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME = ? Specify name and storeName, but storeWebsite is still null. In this case, the join at ❶ takes effect but the code at ❷ does not execute. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.NAME = ? and tb_2_.NAME = ? Specify all parameters, name, storeName and storeWebsite are all non-null. In this case, both joins at ❶ and ❷ take effect. This situation is called join conflict. tip This conflict does not cause any problems. Conflicting joins are merged into one join. So in the final generated SQL, there will be no duplicate join operations. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.NAME = ? and tb_2_.NAME = ? and tb_2_.WEBSITE = ? Solve the problem in scenario 2: Java Kotlin List findDistinctIds( @Nullable Long aId, @Nullable Long bId, @Nullable Long cId, @Nullable Long dId, @Nullable Long eId ) { ATable table = Tables.A_TABLE; return sqlClient .createQuery(table) .whereIf( aId != null, () -> table.id().like(aId) ) .whereIf( bId != null, () -> table.asTableEx().bs().id().like(bId) ) .whereIf( cId != null, () -> table.asTableEx().bs().cs().id().like(cId) ) .whereIf( dId != null, () -> table.asTableEx().bs().cs().ds().id().like(dId) ) .whereIf( eId != null, () -> table.asTableEx().bs().cs().ds().es().id().like(eId) ) .select(book.id()) .distinct() .execute(); } fun findDistinctIds( aId: Long? = null, bId: Long? = null, cId: Long? = null, dId: Long? = null, eId: Long? = null ): List = sqlClient .createQuery(A::class) { aId?.let { where(table.id eq it) } bId?.let { where(table.asTableEx().bs.id eq it) } cId?.let { where(table.asTableEx().bs.cs.id eq it) } dId?.let { where(table.asTableEx().bs.cs.ds.id eq it) } eId?.let { where(table.asTableEx().bs.cs.ds.es.id eq it) } select(table.id) } .distinct() .execute() info Given the basics above, no need to list the generated SQL for different parameter combinations here. Just understand that the final SQL will not contain duplicate joins. asTableEx here is a concept to be introduced in later docs Pagination Safety. Please ignore it for now.","s":"Usage","u":"/jimmer-doc/docs/query/dynamic-join/merge","h":"#usage","p":1218},{"i":1222,"t":"Assume there are three join paths: a -> b -> c -> d -> e -> f -> g a -> b -> c -> h -> i -> j a -> x -> y -> z -> a -> b -> c -> d To eliminate conflicts, Jimmer first merges these paths into a tree: -+-a | +----+-b | | | \\----+-c | | | +----+-d | | | | | \\----+-e | | | | | \\----+-f | | | | | \\------g | | | \\----+-h | | | \\----+-i | | | \\------j | \\----+-x | \\----+-y | \\----+-z | \\----+-a | \\----+-b | \\----+-c | \\------d Then generate the join clause in the final SQL based on this tree. Another rule to note is join type. The method to create join objects takes a parameter to specify join type, e.g. left join: Java Kotlin book.store(JoinType.LEFT) book.`store?` The merge rules for join types: If join types of all conflicting join nodes are the same, the merge preserves that join type. Otherwise, the merge result is always inner join.","s":"Merge Rules","u":"/jimmer-doc/docs/query/dynamic-join/merge","h":"#merge-rules","p":1218},{"i":1225,"t":"First, let's look at how to use static ordering to understand the ordering concepts in Jimmer: Java Kotlin public List findBooks() { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(table.name()) .orderBy(table.edition().desc()) .orderBy(table.score().desc().nullsLast()) .select(table) .execute(); } fun findBooks(): List = sqlClient .createQuery(Book::class) { orderBy(table.name) orderBy(table.edition.desc()) orderBy(table.score.desc().nullsLast()) select(table) } .execute() caution nullsFirst/nullsLast requires database support, such as Oracle. For more databases that do not support this, use case expressions in common expressions.","s":"Static Ordering","u":"/jimmer-doc/docs/query/dynamic-order","h":"#static-ordering","p":1223},{"i":1226,"t":"There are two ways to use dynamic ordering: orderByIf Ordering specified by client","s":"Dynamic Ordering","u":"/jimmer-doc/docs/query/dynamic-order","h":"#dynamic-ordering","p":1223},{"i":1228,"t":"The usage of orderByIf is similar to whereIf. info Unlike where, the order of orderBy is very sensitive, so orderByIf is not as useful as whereIf. Still, Jimmer supports orderByIf since it's the simplest and most basic usage. orderByIf is actually the Java DSL API for dynamic ordering. Java DSL uses fluent style, orderByIf is provided to avoid breaking the fluent chaining. Kotlin DSL uses lambdas so arbitrary logic can be mixed in, hence Kotlin does not need orderByIf. Assume OrderMode is an enum with values NAME and PRICE, orderByIf can be used like: Java Kotlin public List findBooks(OrderMode orderMode) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderByIf(mode == OrderMode.NAME, table.name()) .orderByIf(mode == OrderMode.PRICE, table.price()) .select(table) .execute(); } fun findBooks(orderMode: OrderMode): List = sqlClient .createQuery(Book::class) { when (orderMode) { OrderMode.NAME -> orderBy(table.name) OrderMode.PRICE -> orderBy(table.price) } select(table) } .execute()","s":"orderByIf","u":"/jimmer-doc/docs/query/dynamic-order","h":"#orderbyif","p":1223},{"i":1230,"t":"Often, the UI allows users to dynamically sort by interacting with table components. That is, the client decides the ordering and the server passively accepts parameters to query according to the sorting requirements from client. The client can specify dynamic ordering by passing string parameters, which can be converted to List needed by Jimmer using the method makeOrders. makeOrders is defined as: Java Kotlin public class Order { public static List makeOrders(Props table, String ... codes) { ...implementation omitted... } ...other code omitted... } fun KProps<*>.makeOrders(vararg codes: String): List = ...implementation omitted... Where the first parameter table is the root table in the SQL DSL. makeOrders is very flexible to use, for example: Sort by multiple columns: Java Kotlin Order.makeOrders(table, \"name\", \"edition desc\") table.makeOrders(\"name\", \"edition desc\") Merge multiple parameters into one separated by , or ;: Java Kotlin Order.makeOrders(table, \"name, edition desc\") table.makeOrders(\"name, edition desc\") info In real projects, most cases would use the single parameter form since it's the simplest. Even supports sorting by reference associations (one-to-one, many-to-one): Java Kotlin Order.makeOrders(table, \"store.city.name; store.name; name\") table.makeOrders(\"store.city.name; store.name; name\") info All dynamic join features are valid for these implicit joins. Order.makeOrders can be used like: Java Kotlin public List findBooks(String sort) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(Order.makeOrders(table, sort)) .select(table) .execute(); } fun findBooks(sort: String): List = sqlClient .createQuery(Book::class) { orderBy(table.makeOrders(sort)) select(table) } .execute() If called as findBooks(\"store.name asc, name asc\"), the generated SQL would be: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID order by tb_2_.NAME asc, tb_1_.NAME desc As can be seen, implicit joins are built for sorting criteria involving associations.","s":"Client-specified Ordering","u":"/jimmer-doc/docs/query/dynamic-order","h":"#client-specified-ordering","p":1223},{"i":1232,"t":"In the above examples, we directly convert the sorting string from client into Jimmer SQL AST orders. However, when working with Spring Data, we may need to handle Sort from Spring Data. We can write the query like this, with Sort as parameter instead of string: Java Kotlin public List findBooks(Sort sort) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(table, SpringOrders.toOrders(sort)) .select(table) .execute(); } fun findBooks(sort: Sort): List = sqlClient .createQuery(Book::class) { orderBy(sort) select(table) } .execute() This code works as: Java: Jimmer Java API provides a utility class org.babyfish.jimmer.spring.repository.SpringOrders. Its static method toOrders converts the Spring Data Sort object into the Order array in Jimmer SQL DSL. SpringOrders.toOrders takes two parameters: table: The root table in SQL DSL sort: The Spring Data Sort object After SpringOrders.toOrders converts the Sort into Order array, orderBy can be used to sort. Kotlin: Jimmer Kotlin API extends the query object to directly support sorting by the Spring Data Sort. This shows how to convert a Spring Data Sort into ordering in Jimmer. To further simplify user code, Jimmer provides the utility class org.babyfish.jimmer.spring.model.SortUtils. Its static method toSort can convert the sorting string from client into a Spring Data Sort object. For example: Java Kotlin Sort sort = SortUtils.toSort(\"name asc, edition desc\"); var sort = SortUtils.toSort(\"name asc, edition desc\") That is: +------------------------+ | Client sorting string | +-----------+------------+ | SortUtils.toSort | \\|/ +------------------------+ | Spring Data Sort | +-----------+------------+ | Java: SpringOrders.toOrders, then orderBy Kotlin: Directly orderBy with Sort object | \\|/ +------------------------+ | Ordering in Jimmer AST | +------------------------+","s":"Handling Spring Data Sort","u":"/jimmer-doc/docs/query/dynamic-order","h":"#handling-spring-data-sort","p":1223},{"i":1235,"t":"Java API uses fluent style to build DSL, whereIf is provided to add conditional where clauses without breaking the fluent chaining. Kotlin API uses lambdas to build DSL, no special API is needed to support dynamic queries. Java Kotlin public List findBooks(@Nullable String name) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); } fun findBooks(name: String?): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute() Calling findBooks(null) generates: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc Calling findBooks(\"SQL in Action\") generates: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME = ? /* SQL in Action */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Basic Usage","u":"/jimmer-doc/docs/query/dynamic-where","h":"#basic-usage","p":1233},{"i":1237,"t":"Java developers please note that in the code: .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) Even if name is null, the second parameter table.name().eq(name) would still be evaluated. This is the behavior of most programming languages. For eq (or ne), passing in null does not cause problems. eq(null) would be automatically changed to isNull(), and ne(null) would become isNotNull(). However, for most other conditional expressions, using null would cause exceptions. tip Don't worry, if you accidentally make mistakes, the exception messages are very informative to guide you to use the correct approach introduced below. For greater than or equals ge, dynamic query conditions can be added like: .whereIf( minPrice != null, () -> table.price().ge(minPrice) ) Here, a lambda expression is used to delay the expression construction until the condition is met. For Kotlin there are no such issues, no precautions needed. Let's look at a more complete example: Java Kotlin public List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( minPrice != null, () -> table.price().ge(minPrice) ) .whereIf( maxPrice != null, () -> table.price().le(maxPrice) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); } fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } minPrice?.let { where(table.price ge it) } maxPrice?.let { where(table.price le it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute()","s":"Notes for Java Developers","u":"/jimmer-doc/docs/query/dynamic-where","h":"#notes-for-java-developers","p":1233},{"i":1239,"t":"So far, the dynamic queries are based on a single table. Consider a more complex scenario where some dynamic conditions are on other tables instead of the current table (that is, those tables need to be joined first before dynamic where conditions can be added). How can this be achieved? No other higher level SQL access solutions have elegantly solved this problem, it had been a blank in the domain. Jimmer perfectly solves this difficult problem (which is the very reason Jimmer was created). We will systematically discuss this in next doc. tip In next doc you will see the uniqueness of Jimmer SQL DSL, gaining a powerful capability no other solution in the industry supports.","s":"Multi-table Operations","u":"/jimmer-doc/docs/query/dynamic-where","h":"#multi-table-operations","p":1233},{"i":1241,"t":"Global filters are used to automatically add filtering conditions for an entity type. Most queries for the entity type will automatically have related where conditions added. This feature has the following application scenarios: Multi-perspective data. Querying data requires query conditions related to user identity, even if all query parameters except user identity are the same, different users will see different data. Multi-perspective data has a typical case: multi-tenancy. This document uses multi-tenancy as an example to explain custom global filters defined by users. Logical deletion Logical deletion is a built-in global filter in Jimmer and does not require user definition. note For users with Hibernate background knowledge, global filters are similar to org.hibernate.annotations.Where, org.hibernate.annotations.Filter and org.hibernate.annotations.FilterDef. The difference is that Jimmer's global filters have flexible registration methods and are very easy to be managed by IOC frameworks (such as Spring). Thus, global filters can directly obtain parameters from the IOC framework, such as user identity information, so developers do not need to pass parameters to filters before queries. caution After repeated consideration, currently global filters only affect the main table of the top-level query, and have no effect on tables obtained from join operations and tables in subqueries. This has no impact on object fetchers because object fetchers are not table Join operations. Jimmer provides some simple APIs to query entities (or collections of entities) by id (or collection of ids). These APIs are exceptional and are not affected by global filters.","s":"Global Filters","u":"/jimmer-doc/docs/query/global-filter/","h":"","p":1240},{"i":1243,"t":"Pagination safety is a feature designed for pagination, but table join functionality provides underlying support.","s":"Pagination Safety","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"","p":1242},{"i":1245,"t":"Here, we first introduce two types of associations: reference associations and collection associations. Associations decorated with @OneToOne or @ManyToOne are called reference associations. Associations decorated with @OneToMany or @ManyToMany are called collection associations. Please refer to the example: Association example","s":"Problems with Collection Associations","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#problems-with-collection-associations","p":1242},{"i":1247,"t":"If we call the entity object corresponding to the first table being queried the aggregate root object, reference associations and collection associations differ in: Joining tables via a reference association does not produce duplicate records of the current main object in the SQL query result. For example: select b.id as root_id, b.name as root_name, s.id as associated_id, s.name as associated_name from book b inner join book_store s on b.store_id = s.id where b.id = 1; The query result has no duplicate aggregate root objects: root_id root_name associated_id associated_name 1 Learning GraphQL 1 O'REILLY Joining tables via a collection association produces duplicate records of the current main object in the SQL query result: select b.id as root_id, b.name as root_name, a.id as associated_id, a.first_name as associated_first_name, a.last_name as associated_last_name from book b inner join book_author_mapping m on b.id = m.book_id inner join author a on m.author_id = a.id where b.id = 1; Query result may have duplicate aggregate root objects: root_id root_name associated_id associated_first_name associated_last_name 1 Learning GraphQL 1 Eve Procello 1 Learning GraphQL 2 Alex Banks","s":"Collection JOIN Causes Duplicate Results","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#collection-join-causes-duplicate-results","p":1242},{"i":1249,"t":"Table joins based on collection associations lead to duplicate data, which causes the following problems: Bugs if the developer forgets deduplication. Even if the developer does not forget deduplication, using java.util.LinkedHashSet for deduplication post factum is not ideal. Because the fact that the original database result contains duplicates cannot be altered, and extra network transfer and JVM data processing costs are incurred. Most importantly, unfriendly to pagination queries. Paginating table join results at the SQL level is often not what people want. More often, people want pagination applied on aggregate root objects. Take Hibernate for example. In this case, Hibernate has to abandon SQL-level pagination and use memory-level pagination instead. This performs very poorly that Hibernate logs a warning to alert developers. If you have experience with Hibernate, the log below would give you a headache: firstResult/maxResults specified with collection fetch; applying in memory tip Note that Jimmer's other feature Object Fetcher does not use table join to fetch collection associations, so it does not have this problem. Feel free to use it. In summary, using collection joins in top-level queries has obvious drawbacks, but it remains valuable to use collection joins in subqueries. Therefore, Jimmer SQL DSL has the following characteristics: info Table joins based on collection associations are prohibited in top-level queries. Table joins based on collection associations remain allowed in subqueries, update statements and delete statements.","s":"Harms of Duplicate Results","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#harms-of-duplicate-results","p":1242},{"i":1251,"t":"tip For collection associations, JOIN is actually not recommended. Implicit subqueries are more recommended. If you still want to JOIN collection association properties, please continue reading below.","s":"Implicit Subqueries","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#implicit-subqueries","p":1242},{"i":1253,"t":"There are two kinds of table objects in Jimmer SQL DSL, Table and TableEx. Table Features: Can only join via reference associations, cannot join via collection associations. Java type: org.babyfish.jimmer.sql.ast.table.Table Kotlin type: org.babyfish.jimmer.sql.kt.ast.table.KTable TableEx Features: Can join via any associations. Java type: org.babyfish.jimmer.sql.ast.table.TableEx Kotlin type: org.babyfish.jimmer.sql.kt.ast.table.KTableEx","s":"Table and TableEx","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#table-and-tableex","p":1242},{"i":1255,"t":"To implement strongly typed SQL DSL, Jimmer uses Annotation Processor (Java) or KSP (Kotlin) to generate SQL DSL related source code based on user-defined entity interfaces. Take the Book entity interface at the beginning of this article as an example. The following two types would be generated automatically: Java Kotlin Generated Java Code /* * BookTable.java */ package org.babyfish.jimmer.sql.example.model; import java.lang.Integer; import java.math.BigDecimal; import javax.persistence.criteria.JoinType; import org.babyfish.jimmer.sql.ast.Expression; import org.babyfish.jimmer.sql.ast.PropExpression; import org.babyfish.jimmer.sql.ast.table.Table; import org.babyfish.jimmer.sql.ast.table.spi.AbstractTableWrapper; public class BookTable extends AbstractTableWrapper { public BookTable(Table table) { super(table); } public Expression id() { return get(\"id\"); } public PropExpression.Str name() { return get(\"name\"); } public PropExpression.Num edition() { return get(\"edition\"); } public PropExpression.Num price() { return get(\"price\"); } public BookStoreTable store() { return join(\"store\"); } public BookStoreTable store(JoinType joinType) { return join(\"store\", joinType); } } /* * BookTableEx.java */ package org.babyfish.jimmer.sql.example.model; import javax.persistence.criteria.JoinType; import org.babyfish.jimmer.sql.ast.table.TableEx; public class BookTableEx extends BookTable implements TableEx { public BookTableEx(TableEx table) { super(table); } public AuthorTableEx authors() { return join(\"authors\"); } public AuthorTableEx authors(JoinType joinType) { return join(\"authors\", joinType); } } Generated Kotlin Code package org.babyfish.jimmer.example.kt.sql.model import java.math.BigDecimal import org.babyfish.jimmer.sql.ast.Selection import org.babyfish.jimmer.sql.kt.ast.expression.KNonNullPropExpression import org.babyfish.jimmer.sql.kt.ast.expression.KNullablePropExpression import org.babyfish.jimmer.sql.kt.ast.table.KNonNullTable import org.babyfish.jimmer.sql.kt.ast.table.KNonNullTableEx import org.babyfish.jimmer.sql.kt.ast.table.KNullableTable import org.babyfish.jimmer.sql.kt.ast.table.KNullableTableEx import org.babyfish.jimmer.sql.kt.ast.table.KTable import org.babyfish.jimmer.sql.kt.ast.table.KTableEx /* * Extension for Table */ public val KTable.id: KNullablePropExpression get() = get(\"id\") public val KNonNullTable.id: KNonNullPropExpression get() = get(\"id\") public val KTable.name: KNullablePropExpression get() = get(\"name\") public val KNonNullTable.name: KNonNullPropExpression get() = get(\"name\") public val KTable.edition: KNullablePropExpression get() = get(\"edition\") public val KNonNullTable.edition: KNonNullPropExpression get() = get(\"edition\") public val KTable.price: KNullablePropExpression get() = get(\"price\") public val KNonNullTable.price: KNonNullPropExpression get() = get(\"price\") public val KNullableTable.store: KNullableTable get() = join(\"store\") public val KNonNullTable.store: KNonNullTable get() = join(\"store\") public val KTable.`store?`: KNullableTable get() = outerJoin(\"store\") /* * Extension for TableEx */ public val KNullableTableEx.authors: KNullableTableEx get() = join(\"authors\") public val KNonNullTableEx.authors: KNonNullTableEx get() = join(\"authors\") public val KTableEx.`authors?`: KNullableTableEx get() = outerJoin(\"authors\") Observing the two auto-generated types, we can see: BookTableEx inherits BookTable. BookTable does not support collection associations, but supports regular fields and reference associations (which is store in this example). BookTableEx adds support for collection associations (which is authors in this example). Therefore, jimmer-sql API follows this pattern: Top-level queries can only be created based on Table. Subqueries, update statements and delete statements can be created based on either Table or TableEx. Next, we demonstrate the contrast between top-level queries and subqueries with examples.","s":"Generated Code","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#generated-code","p":1242},{"i":1257,"t":"So your code looks like: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where( table .name() // Can access regular field name .eq(\"Book Name\") ) .where( table .store() // Can also join reference association store .name() .eq(\"Store Name\") ) /* * However, cannot use \"table.authors()\" because `authors()` * is defined in `BookTableEx` instead of `BookTable`. * * That is, joining collection associations is prohibited * at compile time in top-level queries. */ .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .name // Can access regular field name eq \"Book Name\" ) where( table .store // Can also join reference association `store` .name eq \"Store Name\" ) /* * However, cannot use \"table.authors\" because the extension property `authors` * is defined on `TableEx` instead of `Table`. * * That is, joining collection associations is prohibited * at compile time in top-level queries. */ select(table) } .execute() info Java: createQuery takes parameter specified by user, can only be Table type. TableEx would error. Kotlin: createQuery creates table object automatically. The automatic variable table in lambda is inferred to Table instead of TableEx. The final generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.NAME = ? and tb_2_.NAME = ?","s":"Top-Level Queries Must Be Based on Table","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#top-level-queries-must-be-based-on-table","p":1242},{"i":1259,"t":"Unlike top-level queries, subqueries, update statements and delete statements allow TableEx. In the example below, Author.books is the same as Book.authors discussed above, which is also a many-to-many association. Java Kotlin BookTable table = Tables.BOOK_TABLE; // `author` used in subquery, use TableEx AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(table) .where(sqlClient .createSubQuery(author) .where( author // `author` is TableEx, // so collection association `books` is allowed .books() .eq(table), author.firstName().eq(\"Alex\") ) .exists() ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { // In parent query `table` is Table where( exists( wildSubQuery(Author::class) { // Subquery's `table` overrides parent's `table`, // and the Subquery's `table` is `TableEx` where( table // Subquery's `table` is TableEx, // so collection association `books` is allowed .books eq parentTable, table.firstName.eq(\"Alex\") ) } ) ) select(table) } .execute() info Java: createSubQuery takes parameter specified by user, not enforced but suggested to be TableEx type. Kotlin: wildSubQuery (or subQuery) creates table object automatically. The automatic variable table in lambda is inferred to TableEx instead of Table. The final generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where exists( select 1 from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and tb_2_.FIRST_NAME = ? )","s":"TableEx Allowed for Subqueries","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#tableex-allowed-for-subqueries","p":1242},{"i":1261,"t":"Prohibiting collection associations in top-level queries is reasonable in most cases, but not all cases. For example, the user does not query entire objects, but individual fields, and uses the SQL keyword distinct to offset the side effects of joining collection associations. This scenario is perfectly reasonable. Therefore, prohibiting collection associations in top-level queries is a soft constraint rather than a hard constraint. It can be easily overridden. Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(book) .where( book .asTableEx() ❶ .authors() .firstName() .ilike(\"A%\") ) .select(book.id()) .distinct() ❷ .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() ❶ .authors .firstName ilike \"A%\" ) select(table.id) } .distinct() ❷ .execute() info ❶ The developer informs Jimmer that they know what they are doing, asking Jimmer to allow joining collection associations. ❷ The developer takes responsibility for their own actions. If there are additional operations here, it should be distinct rather than pagination related. The final generated SQL: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID where lower(tb_3_.FIRST_NAME) like ?","s":"asTableEx","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#astableex","p":1242},{"i":1263,"t":"info Readers cannot find anything related to global filters in this doc, because the filter required for logical deletion is built-in and hidden by Jimmer.","s":"Logical Deletion","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"","p":1262},{"i":1265,"t":"Logical deletion, also known as soft deletion, means data is not actually deleted from the database. Instead, data is hidden to give the illusion of deletion. This leaves room for recovering from accidental operations. The mapping related to logical deletion is introduced in great detail in Mapping / Advanced Mapping / Logical Deletion, so all the details are not repeated here, just a brief recap: Java Kotlin Book.java @Entity public interface Book { @LogicalDeleted(\"true\") boolean isDeleted(); ...other code omitted... } Book.kt @Entity interface Book { @LogicalDeleted(\"true\") val isDeleted: Boolean ...other code omitted... }","s":"Mapping","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#mapping","p":1262},{"i":1268,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.DELETED, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.DELETED <> ? /* true */","s":"Filter root entity","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#filter-root-entity","p":1262},{"i":1270,"t":"Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(author) .select( author.fetch( Fetchers.AUTHOR_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ) ) .execute(); val authors = sqlClient .createQuery(Author::class) { select( table.fetchBy { allScalarFields() books { allScalarFields() } } ) } .execute() Without caching enabled, this generates two SQLs: Query root entity select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ Query associated objects, apply logical deletion filter select tb_2_.AUTHOR_ID, tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where tb_2_.AUTHOR_ID in ( ? /* 1 */, ? /* 2 */, ? /* 3 */, ? /* 4 */, ? /* 5 */ ) and tb_1_.DELETED <> ? /* true */","s":"Filter associated objects","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#filter-associated-objects","p":1262},{"i":1272,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .filters(cfg -> { ❶ cfg.setBehavior(LogicalDeletedBehavior.IGNORED); ❷ }) .createQuery(table) .select(table) .execute(); val books = sqlClient .filters { ❶ cfg.setBehavior(LogicalDeletedBehavior.IGNORED) } .createQuery(table) .select(table) .execute() ❶ Adjust filter config without affecting the current sqlClient, create a new temporary sqlClient ❷ Ignore soft deletion flag This time, the generated SQL no longer contains: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.DELETED, tb_1_.STORE_ID from BOOK tb_1_","s":"Ignore Logical Deletion Filter","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#ignore-logical-deletion-filter","p":1262},{"i":1274,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .filters(cfg -> { ❶ cfg.setBehavior(LogicalDeletedBehavior.REVERSED); ❷ }) .createQuery(table) .select(table) .execute(); val books = sqlClient .filters { ❶ cfg.setBehavior(LogicalDeletedBehavior.REVERSED) } .createQuery(table) .select(table) .execute() ❶ Adjust filter config without affecting the current sqlClient, create a new temporary sqlClient ❷ Reverse the soft deletion flag, i.e. query deleted data Executing again, the generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.DELETED, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.DELETED = ? /* true */ This time the filter condition is tb_1_.DELETED = true, which is the exact opposite of the default filtering rule - it queries already deleted data.","s":"Reverse Logical Deletion Filter","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#reverse-logical-deletion-filter","p":1262},{"i":1277,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; long count = sqlClient .createQuery(table) .where(table.name().ilike(\"graphql\")) .select( table .asTableEx().authors().id() .count(true) // distinct: true ) .fetchOne(); val count = sqlClient .createQuery(Book::class) { where(table.name.ilike(\"graphql\")) select( count( table.asTableEx().authors.id, distinct = true ) ) } .fetchOne() The generated SQL is: select count(distinct tb_2_.AUTHOR_ID) from BOOK tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where lower(tb_1_.NAME) like ? /* %graphql% */","s":"Aggregation","u":"/jimmer-doc/docs/query/group","h":"#aggregation","p":1275},{"i":1279,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List> tuples = sqlClient .createQuery(table) .groupBy(table.storeId()) ❶ .select( table.storeId(), ❷ table.price().avg() ❸ ) .execute(); val tuples: List> = sqlClient .createQuery(Book::class) { groupBy(table.store.id) ❶ select( table.store.id, ❷ avg(table.price).asNonNull() ❸ ) } .execute() ❶ Group by STORE_ID, the foreign key of BOOK table info Here Jimmer does not treat table.store as a join operation, but considers table.store.id as a whole as the foreign key field. Please see phantom joins. ❷ Grouping columns can be directly queried. ❸ Non-grouping columns can only be queried as parameters of aggregate functions. caution The Kotlin code has an extra function call: asNonNull(). In Jimmer Kotlin DSL, aggregate functions like avg (also sum, min, max) return Nullable types. For a table with no data, aggregating any column would return null without grouping. However this is not the case when used with grouping. After grouping, each group has at least one row internally, if the original field being aggregated is non-null itself, the result after aggregation would not be null. So here asNonNull() converts the Nullable expression to NonNull, such that execute() returns List>, same as the type explicitly specified for tuples in the first line. If asNonNull() is removed, execute() would return List>, causing compile error.","s":"Grouping","u":"/jimmer-doc/docs/query/group","h":"#grouping","p":1275},{"i":1281,"t":"Native SQL expressions are an important feature to leverage database-specific capabilities, as database products always have proprietary features.","s":"Native SQL Expressions","u":"/jimmer-doc/docs/query/native-sql","h":"","p":1280},{"i":1283,"t":"This example shows how to use regular expression matching in Oracle and HSQLDB: Java Kotlin AuthorTable table = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(table) .where( Predicate.sql( \"regexp_like(%e, %v)\", it -> it .expression(table.firstName()) .value(\"^Ste(v|ph)en$\") ) ) .select(table) .execute(); val authors = sqlClient .createQuery(Author::class) { where( sql(Boolean::class, \"regexp_like(%e, %v)\") { expression(table.firstName) value(\"^Ste(v|ph)en$\") } ) select(table) } .execute() info In the Java code, Predicate.sql is called to create a query condition based on native SQL. In fact, other expression types also support native SQL expressions. There are 5 sql functions: Predicate.sql(...) Expression.string().sql(...) Expression.numeric().sql(...) Expression.comparable().sql(...) Expression.any().sql(...) Kotlin does not have this issue, its API is unified. The first parameter of sql(...) is the SQL template string, which can contain special symbols %e and %v: %e: Expression, to embed an expression %v: Value, to embed a value The second parameter of sql(...) is optional, a lambda expression whose parameter is an object supporting two methods: expression(Expression): Embed an expression, corresponding to %e in SQL template. value(Object): Embed a value, corresponding to %v in SQL template. The final generated SQL is: select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR as tb_1_ where regexp_like(tb_1_.FIRST_NAME, ?)","s":"Example 1: Regular Expression Matching","u":"/jimmer-doc/docs/query/native-sql","h":"#example-1-regular-expression-matching","p":1280},{"i":1285,"t":"Let's look at another example using analytic functions: Java Kotlin List> tuples = sqlClient .createQuery(table) .select( table, Expression.numeric().sql( Integer.class, \"rank() over(order by %e desc)\", table.price() ), Expression.numeric().sql( Integer.class, \"rank() over(partition by %e order by %e desc)\", new Expression[] { table.storeId(), table.price() } ) ) .execute(); val tuples = sqlClient .createQuery(Author::class) { select( table, sql(Int::class, \"rank() over(order by %e desc)\") { expression(table.price) }, sql(\"rank() over(partition by %e order by %e desc)\") { expression(table.store.id) expression(table.price) } ) } .execute() Three columns are queried here: First column: Book object Second column: The rank of the book price among all books Third column: The rank of the book price within its store The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID, rank() over( order by tb_1_.PRICE desc ), rank() over( partition by tb_1_.STORE_ID order by tb_1_.PRICE desc ) from BOOK tb_1_","s":"Example 2: Analytic Functions","u":"/jimmer-doc/docs/query/native-sql","h":"#example-2-analytic-functions","p":1280},{"i":1287,"t":"Collection (one-to-many or many-to-many) associations often lead to the frequent use of subqueries in queries, and implicit subqueries greatly simplify such subqueries. For complete normal subqueries, see Normal Subqueries.","s":"Implicit Subquery","u":"/jimmer-doc/docs/query/implicit-subquery","h":"","p":1286},{"i":1289,"t":"Taking the many-to-many association Book.authors as an example, after compilation, Jimmer will generate the following code: Java Kotlin BookTable.java @GeneratedBy(type = Book.class) public class BookTable extends AbstractTypedTable implements BookProps { @Override public Predicate authors(Function block) { ...implementation logic omitted... } } fun KProps.authors( block: KNonNullTableEx.() -> KNonNullExpression? ): KNonNullExpression? = ...implementation logic omitted... Users can build implicit subqueries based on this authors method. The parameter of this method is a lambda expression whose parameter is the table object of the associated object. Users can return an SQL condition to filter the associated object.","s":"DSL Code generated by Jimmer","u":"/jimmer-doc/docs/query/implicit-subquery","h":"#dsl-code-generated-by-jimmer","p":1286},{"i":1291,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; public List findBooks(@Nullable String authorName) { return sqlClient .createQuery(table) .whereIf( authorName != null && !authorName.isEmpty(), table.authors(author -> { return Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ); }) ) .select(table) .execute(); } fun findBooks(authorName: String?): List = sqlClient.createQuery(Book::class) { authorName?.takeIf { it.isNotEmpty() }?.let { where += table.authors { or( firstName ilike it, lastName ilike it ) } } }.execute() When calling the above method and specifying a non-null parameter, for example findBooks(\"alex\"), the generated SQL is: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where exists( ➊ select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID ➋ and ( lower(tb_2_.FIRST_NAME) like ? /* %alex% */ ➌ or lower(tb_2_.LAST_NAME) like ? /* %alex% */ ➍ ) ) ➊ Implicit subqueries always use exists ➋ The SQL condition auto-generated by Jimmer for associating parent-child queries ➌ ➍ Conditions specified by users to filter associated objects tip The association condition between parent-child queries is auto-generated. Users only need to specify the filtering condition for the associated object. This is the fundamental difference between implicit subqueries and normal subqueries.","s":"Demo","u":"/jimmer-doc/docs/query/implicit-subquery","h":"#demo","p":1286},{"i":1293,"t":"Similar to the automatic merge of dynamic JOINs, multiple implicit subqueries for the same association can also be automatically merged. caution The merge rules for implicit subqueries are not as universal as dynamic JOINs. They are limited to within the same and, or, or not. For example: Java Kotlin BookTable table = Tables.BOOK_TABLE; public List findBooks( @Nullable String authorName, @Nullable Gender authorGender ) { return sqlClient .createQuery(table) .whereIf( authorName != null && !authorName.isEmpty(), table.authors(author -> { return Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ); }) ) .whereIf( authorGender != null, table.authors(author -> author.gender().eq(authorGender)) ) .select(table) .execute(); } fun findBooks(authorName: String?): List = sqlClient.createQuery(Book::class) { authorName?.takeIf { it.isNotEmpty() }?.let { where += table.authors { or( firstName ilike it, lastName ilike it ) } } authorGender?.let { where += table.authors { gender like it } } }.execute() The above example uses two implicit subqueries. However, when we specify both parameters as non-null, for example findBooks(\"alex\", Gender.MALE), there will only be one subquery in the final SQL, as follows: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where // Merge two implicit subqueries to one real sub query exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %alex% */ or lower(tb_2_.LAST_NAME) like ? /* %alex% */ ) and tb_2_.GENDER = ? /* M */ ) This is because within the same and, or or not, multiple implicit subqueries for the same association are automatically merged.","s":"Automatic Merge","u":"/jimmer-doc/docs/query/implicit-subquery","h":"#automatic-merge","p":1286},{"i":1297,"t":"In Jimmer SQL DSL, created join objects that are not used will be ignored. For example: Java Kotlin BookTable table = Tables.BOOK_TABLE; System.out.println(\"Unused join: \" + table.store()); List books = sqlClient .createQuery(table) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { println(\"Unused join: ${table.store}\") orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute() Although a JOIN object is created via table.store, since it is not used by the SQL DSL of the current query, this JOIN object will be ignored. Therefore, the final generated SQL will not contain any JOIN operations: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME = ?","s":"Basic Concepts","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#basic-concepts","p":1294},{"i":1299,"t":"In Problems with current solutions In the previous doc, we discussed solving these two scenarios by utilizing Jimmer SQL DSL's automatic merge of conflicting joins. Here, we use another approach to solve the same problems. Solve the problem in scenario 1: Java Kotlin List findBooks( @Nullable String name, @Nullable String storeName, @Nullable String storeWebsite ) { BookTable table = Tables.BOOK_TABLE; // Create JOIN object unconditionally first, // will be auto ignored if not used later, // so no useless JOIN BookStoreTable store = table.store(); return sqlClient .createQuery(table) .whereIf( name != null, () -> book.name().like(name) ) .whereIf( storeName != null, () -> store.name().like(storeName) ) .whereIf( storeWebsite != null, () -> store.website().like(storeWebsite) ) .select(book) .execute(); } fun findBooks( name: String? = null, storeName: String? = null, storeWebsite: String? = null ): List { return sqlClient .createQuery(Book::class) { // Create JOIN object unconditionally first, // will be auto ignored if not used later, // so no useless JOIN val store = table.store name?.let { where(table.name like it) } storeName?.let { where(store.name like it) } storeWebsite?.let { where(store.website like it) } select(table) } .execute() } If only name is specified, without storeName and storeWebsite, then store is a created but unused join object, thus ignored. The final generated SQL contains no joins. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME = ? If storeName and storeWebsite are specified, store will be used, leading to join operations in the final generated SQL. This is obvious so no example here. Solve the problem in scenario 2: Java Kotlin List findDistinctIds( @Nullable Long aId, @Nullable Long bId, @Nullable Long cId, @Nullable Long dId, @Nullable Long eId ) { ATable table = Tables.A_TABLE; // Create JOIN objects unconditionally first, // Not used join objects will be auto ignored, // so no useless JOIN objects BTableEx b = table.asTableEx().bs(); CTableEx c = b.cs(); DTableEx d = c.ds(); ETableEx e = d.es(); return sqlClient .createQuery(table) .whereIf( aId != null, () -> table.id().like(aId) ) .whereIf( bId != null, () -> b.id().like(bId) ) .whereIf( cId != null, () -> c.id().like(cId) ) .whereIf( dId != null, () -> d.id().like(dId) ) .whereIf( eId != null, () -> e.id().like(eId) ) .select(book.id()) .distinct() .execute(); } fun findDistinctIds( aId: Long? = null, bId: Long? = null, cId: Long? = null, dId: Long? = null, eId: Long? = null ): List { // Create JOIN object unconditionally first, // will be auto ignored if not used later, // so no useless JOIN val b = table.asTableEx().bs val c = b.cs val d = c.ds val e = d.es return sqlClient .createQuery(A::class) { aId?.let { where(table.id eq it) } bId?.let { where(b.id eq it) } cId?.let { where(c.id eq it) } dId?.let { where(d.id eq it) } eId?.let { where(e.id eq it) } select(table.id) } .distinct() .execute() } info Given the basics above, no need to list the generated SQL for different parameter combinations here. Just understand that the final SQL will not contain useless joins. When a JOIN object is used by the SQL DSL, it will be marked as \"used\" to prevent being ignored. This mark is transitive. For example: Marking d as \"used\" will naturally also mark c, b and table. asTableEx here (and various TableEx types in Java) is a concept to be introduced in later docs Pagination Safety. Please ignore it for now.","s":"Another Solution","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#another-solution","p":1294},{"i":1302,"t":"For foreign key based associations, there are two ways to filter on the associated id: Use the foreign key property directly Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .storeId() .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .storeId eq 2L ) select(table) } .execute() tip For one-to-one/many-to-one associations (like Book.store in this example), even if the user does not declare an @IdView property for the Book entity, the storeId property can still be used in SQL DSL. Join to the associated object first, then access the id property Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .store() .id() // only access id .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .store .id // only access id eq 2L ) select(table) } .execute() These two approaches are not equivalent: where(table.storeId().eq(2L)): Simply filter based on the foreign key field of the current table. where(table.store().id().eq(2L)): Actually join to the associated table first, then check the associated id value. They are not equivalent because: The foreign key may be fake, i.e. there is no corresponding foreign key constraint in the database. This will cause non-null pseudo foreign keys to be unable to fetch non-null associated objects through joining. The associated object may be affected by global filters, so it should be ignored even if it exists in the database. However, the two approaches are completely equivalent when all of the following conditions are met: The association is a one-to-one or many-to-one association based on foreign key, not through a join table or other reverse association mapping. The foreign key is real, i.e. there is a corresponding foreign key constraint in the database. See Real and Fake Foreign Keys. The associated object is not affected by global filters. Note this refers to either of: User-defined filters Logical deletion filters In this case, the id of the associated object is actually just the foreign key of the current table, so they are equivalent. info Developers should understand the difference between these two approaches and choose the right one according to the business needs. However, when the two approaches are equivalent, optimizing the second approach into the first one is very beneficial - this is called phantom join elimination. The equivalence of the two query methods is a precondition for phantom join elimination to take effect, so this will not be repeated below.","s":"Two ways to filter on associated ids","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#two-ways-to-filter-on-associated-ids","p":1294},{"i":1304,"t":"Phantom join elimination is only applicable to accessing the id property of associated objects, not other properties. Here, accessing the name property of the associated object is used as an example to demonstrate the inability to eliminate the join. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where(book.store().name().eq(\"MANNING\")) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.store.name eq \"MANNING\") select(table) } .execute() The generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ?","s":"Inapplicable Scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#inapplicable-scenarios","p":1294},{"i":1306,"t":"If only the id property of the associated object is accessed, phantom join elimination can be triggered. For example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .store() .id() // Access id only .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .store .id // Access id only eq 2L ) select(table) } .execute() This time, the generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.STORE_ID = ? We see no table join in the SQL, only a condition tb_1_.STORE_ID = ? based on the foreign key. The reason: For a many-to-one association mapped by foreign key, the parent table's id is actually the child table's own foreign key.","s":"Applicable scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#applicable-scenarios","p":1294},{"i":1308,"t":"Half joins are a concept similar to phantom joins, but for join table based associations.","s":"Half Joins","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#half-joins","p":1294},{"i":1310,"t":"For join table based associations, there are two ways to filter on the associated id: Check the foreign key field in the join table Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .asTableEx() .authorIds() .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authorIds eq 2L ) select(table) } .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. caution For one-to-many/many-to-many associations (like Book.authors in this example), *users must declare an @IdView property *for the Book entity to access the authorIds property in SQL DSL. Join to the associated object first, then access the id property Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .asTableEx() .authors() .id() // only access id .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authors .id // only access id eq 2L ) select(table) } .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. These two approaches are not equivalent: where(table.authorIds().eq(2L)): 1 join operation From the current table BOOK, join to BOOK_AUTHOR_MAPPING table and directly check the BOOK_AUTHOR_MAPPING.AUTHOR_ID field. where(table.authors().id().eq(2L)): 2 join operations Based on current table BOOK, join to BOOK_AUTHOR_MAPPING Based on join table BOOK_AUTHOR_MAPPING, join to AUTHOR Finally, check the AUTHOR.ID field. They are not equivalent because: The foreign key BOOK_AUTHOR_MAPPING.AUTHOR_ID may be fake, i.e. there is no corresponding foreign key constraint in the database. This will cause non-null pseudo foreign keys to be unable to fetch non-null associated objects through joining. The associated object may be affected by global filters, so it should be ignored even if it exists in the database. However, the two approaches are completely equivalent when all of the following conditions are met: The foreign key in the join table is real, i.e. there is a corresponding foreign key constraint in the database. See Real and Fake Foreign Keys. The associated object is not affected by global filters. Note this refers to either of: User-defined filters Logical deletion filters In this case, the id of the associated object is actually just the foreign key of the current table, so they are equivalent. info Developers should understand the difference between these two approaches and choose the right one according to the business needs. However, when the two approaches are equivalent, optimizing the second approach into the first one is very beneficial - this is called half join elimination. The equivalence of the two query methods is a precondition for half join elimination to take effect, so this will not be repeated below.","s":"Two ways to filter on associated ids","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#two-ways-to-filter-on-associated-ids-1","p":1294},{"i":1312,"t":"Half join elimination is only applicable to accessing the id property of associated objects, not other properties. Here, accessing the Author.firstName property of the associated object is used as an example to demonstrate the inability to eliminate the second join. Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(book) .where( book .asTableEx() .authors() .firstName() .eq(\"Alex\") ) .select(book.id()) .distinct() .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authors .firstName eq \"Alex\" ) select(table.id) } .distinct() .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. The generated SQL: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID where tb_3_.FIRST_NAME = ? We see join tables produce two SQL JOIN clauses: First step: Join to intermediate table inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID Second step: Join to target table inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID","s":"Inapplicable scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#inapplicable-scenarios-1","p":1294},{"i":1314,"t":"If only the id property of the associated object is accessed, half join elimination can be triggered. For example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(book) .where( book .asTableEx() .authors() .id() // Access id only .eq(2L) ) .select(book.id()) .distinct() .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authors .id // Access id only eq 2L ) select(table.id) } .distinct() .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. This time, the generated SQL: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where tb_2_.AUTHOR_ID = ? This time we only see one SQL JOIN clause instead of two. The reason: The target table's primary key is actually the foreign key from the intermediate table to the target table.","s":"Applicable scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#applicable-scenarios-1","p":1294},{"i":1317,"t":"tip One statement to query data structure of arbitrary shape, like GraphQL The object fetcher is an important feature of Jimmer that automatically fetches specified fields and assembles them into objects, saving a lot of time writing manual conversion logic. The object fetcher is similar to the following technologies, but more powerful: JPA's EntityGraph ADO.NET EntityFramework's include ActiveRecord's include Although the code to return entire objects in queries is simple, the default object format often does not meet development needs very well. It is easy to encounter two problems: Over fetching problem Object properties that we don't need are queried, causing waste, especially when there are many object fields. Take JPA as an example. The returned object by default is a complete object that contains non-associative properties that are not needed. This is a big problem for traditional ORMs (JPA's @Basic(fetch = FetchType.LAZY) is designed for LOB column, it cannot be used by any column). Under fetching problem The object properties we need have not been fetched and are in an unavailable unloaded state, causing the program to fail to run correctly. The object fetcher solves this problem very well by allowing users to specify properties to fetch, and then utilizing the characteristics of dynamic objects to make the returned objects from the query neither over fetched nor under fetched. By using the object fetcher, it is easy to specify the return format of queries, because dynamic objects can describe data structures of any shape. You can decide whether a certain business perspective needs to query some entities, associations, or even every properties.","s":"Concept","u":"/jimmer-doc/docs/query/object-fetcher/","h":"#concept","p":1315},{"i":1319,"t":"Java Kotlin Your browser does not support the video tag. Your browser does not support the video tag. info Compare to GraphQL GraphQL is based on HTTP services, which can only be experienced if it crosses the boundaries of HTTP services. In Jimmer, this is the underlying API for ORM, and you can use this capability in any code logic. Until now, the GraphQL protocol does not support recursive queries on self-associated properties with infinite depth; And Jimmer supports","s":"Examples","u":"/jimmer-doc/docs/query/object-fetcher/","h":"#examples","p":1315},{"i":1321,"t":"In last doc we introduced scalar property fetching. In this doc we discuss association fetching. ORM has two types of association properties: Reference association: Associated with a single object (or null), the property return type is an entity object, used to express one-to-one and many-to-one associations. info This article uses the many-to-one association property Book.store as an example. Collection association: Associated with multiple objects, the property return type is a list of entities, used to express one-to-many and many-to-many associations. info This article uses the many-to-many association property Book.authors as an example.","s":"Associations","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"","p":1320},{"i":1323,"t":"When fetching associated objects without any parameters, only the id property of the associated objects is returned.","s":"Fetch associated objects with only id","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#fetch-associated-objects-with-only-id","p":1320},{"i":1325,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store() ) ) .execute(); System.out.println(toJson(list)); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() store() } ) } .execute() Here, store() indicates fetching the associated object. We did not specify any parameters for store(), which means only the id property of the associated object is fetched. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.EDITION = ? Since the many-to-one association Book.store is based on a real foreign key, the foreign key STORE_ID of the current table BOOK is the id of the parent object. Because store() only fetches the id property of the associated object, no additional SQL query is required. The parent object with only the id property can be directly constructed from the foreign key in the current data. The returned value is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } }, ...other objects omitted... ]","s":"ManyToOne: Book.store","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytoone-bookstore","p":1320},{"i":1327,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER. .allScalarFields() .authors() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors() } ) } .execute() Here, authors() indicates fetching the associated objects. We did not specify any parameters for authors(), which means only the id property of the associated objects is fetched. Two SQLs are generated: Query for the Book objects themselves select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? Based on the Book.authors association, query for the Author associated objects with only id for all root objects queried in the previous step select tb_1_.BOOK_ID, /* batch-map key */ tb_1_.AUTHOR_ID /* batch-map value */ from BOOK_AUTHOR_MAPPING as tb_1_ where tb_1_.BOOK_ID in (?, ?, ?, ?) This example demonstrates: The query only needs the id of the associated objects, and no filters are used (filters will be explained later). Jimmer optimizes this case by only querying the BOOK_AUTHOR_MAPPING table instead of the AUTHOR table, because the middle table already contains the id of the associated objects. where tb_1_.BOOK_ID in (?, ?, ?, ?) is a batch query, because the first query returns 4 root objects. Jimmer uses batch queries to solve the N+1 problem, similar to DataLoader in GraphQL. When a batch becomes too large, jimmer-sql will split it into smaller batches. This will be explained in the BatchSize section. Jimmer queries the associated objects via separate SQL instead of using LEFT JOIN in the main query SQL to fetch associated objects. This is designed to avoid duplicate results when joining collection associations, which can be devastating for paged queries on aggregate roots. The printed result is (formatted for readability, original output is compact): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, \"authors\":[ {\"id\":1}, {\"id\":2} ] }, ...other objects omitted... ]","s":"ManyToMany: Book.authors","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytomany-bookauthors","p":1320},{"i":1329,"t":"When fetching associated objects, parameters can be specified to get associated objects with more information.","s":"Fetch complex associated objects","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#fetch-complex-associated-objects","p":1320},{"i":1331,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) ) ) .execute(); System.out.println(toJson(list)); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() store { allScalarFields() } } ) } .execute() Here, store(...) indicates fetching the associated object. We specify parameters for store(...) to fetch information other than id of the associated object. Two SQLs are generated: Query for Book objects select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.EDITION = ? Based on the Book.store association, query for relatively complete BookStore associated objects for all root objects queried in the previous step select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ where tb_1_.ID in (?, ?) where tb_1_.ID in (?, ?) is a batch query. The first query returns 4 root objects, but the foreign key values are deduplicated to only 2 values. The returned value is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null } }, ...other objects omitted... ]","s":"ManyToOne: Book.store","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytoone-bookstore-1","p":1320},{"i":1333,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER. .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors { allScalarFields() } } ) } .execute() Here, authors(...) indicates fetching the associated objects. We specify parameters for authors(...) to fetch information other than id of the associated objects. Two SQLs are generated: Query for the Book objects themselves select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? Based on the Book.authors association, query for relatively complete Author associated objects for all root objects queried in previous step select /* batch-map key */ tb_2_.BOOK_ID, /* batch-map value */ tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) This example shows: Information other than id is required for the associated objects, so both the BOOK_AUTHOR_MAPPING table and the AUTHOR table are queried, besides just the middle table. where tb_2_.BOOK_ID in (?, ?, ?, ?) is a batch query, because the first query returns 4 root objects. Jimmer uses batch queries to solve the N+1 problem, similar to DataLoader in GraphQL. Jimmer queries the associated objects via separate SQL instead of using LEFT JOIN in the main query SQL. This is designed to avoid duplicate results when joining collection associations, which can be devastating for paged queries on aggregate roots. The printed result is (formatted for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, \"authors\":[ { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" }, { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" } ] }, ...other objects omitted... ]","s":"ManyToMany: Book.authors","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytomany-bookauthors-1","p":1320},{"i":1335,"t":"In some cases, all fields defined in the table are needed. allTableFields can be used for this. allTableFields fetches all properties defined in the table, including all scalar properties (same as allScalarFields), one-to-one/many-to-one associations based on foreign keys. It does not include one-to-many, many-to-many associations, one-to-one/many-to-one associations based on middle tables, calculated properties or view properties. info allTableFields includes all one-to-one/many-to-one associations based on foreign keys, in addition to allScalarFields. The fetched associated objects only have the id property. Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allTableFields() ) ) .execute(); System.out.println(toJson(list)); val bookAllTableFields = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allTableFields() } ) } .execute() The result is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } } ...other objects omitted ] info In some cases, select(table.fetch(Fetchers.XXX_FETCHER.allTableFields())) is equivalent to select(table). The latter can be considered as shorthand for the former. The equivalence holds when associated objects are not affected by filters. The simple equivalent shorthand is: Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select(book) .execute(); System.out.println(toJson(list)); val bookAllScalarFields = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select(table) } .execute()","s":"Fetching all table fields","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#fetching-all-table-fields","p":1320},{"i":1338,"t":"For one-to-many/many-to-many associations, a large number of associated objects may impact application performance. The batchSize configuration is provided for management. The following example does not configure batchSize: Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER.allScalarFields() .authors(Fetchers.AUTHOR_FETCHER.allScalarFields()) ) ) .execute(); System.out.println(toJson(list)); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allTableFields() authors { allScalarFields() } } ) } .execute() The generated SQL is: # 1. Query book table to get all BOOK_ID select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ where tb_1_.EDITION = ? # 2. Use BOOK_ID from previous step to join query author table select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) In this example, no batchSize is configured so the default will be used. All BOOK_ID will be directly used in the in(...) list of the second query. The output is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"authors\": [ { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" }, { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" } ] }, ...omit other objects ] In the example above, we see the query: select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) Here, the in expression implements batch query to solve N+1 problem. If a batch is too large, it will be split into multiple batches based on batchSize configuration, such as: Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER.allScalarFields() .authors(Fetchers.AUTHOR_FETCHER.allScalarFields(), it -> it.batch(2)) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors({ batch(2) }) {} } ) } .execute() danger Here the batchSize for authors is set to 2. Such a small value would cause poor performance, it is only for demo purposes. Please do not use such small values in real projects. This would cause the in(?, ?, ?, ?) to be split into two in(?, ?), and the SQL to fetch associated objects would be split into two. select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?) select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?) In real projects, in most cases batchSize would not be configured like this at fetcher level. Instead, use the global configurations in SqlClient: JSqlClient.getDefaultBatchSize(): Default batchSize for one-to-one and many-to-one associations, default 128 JSqlClient.getDefaultListBatchSize(): Default batchSize for one-to-many and many-to-many associations, default 16 When creating SqlClient, the global configs can be changed: Using spring boot Add configuration into application.yml or application.properties jimmer: default-batch-size: 256 default-list-batch-size: 32 Using low-level API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultBatchSize(256) .setDefaultListBatchSize(32) .... build(); val sqlClient = newKSqlClient { setDefaultBatchSize(256) setDefaultListBatchSize(32) .... } caution No matter association-level batchSize or global batchSize, do not set above 1000 because Oracle database allows max 1000 values in in(...).","s":"BatchSize","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#batchsize","p":1320},{"i":1340,"t":"For collection associations, limit(limit, offset) can be specified during fetching to do pagination at association level. caution Association-level pagination and batch loading cannot coexist. Association-level pagination necessarily causes N+1 problem. Please use this feature cautiously! If association-level pagination is used, batchSize must be set to 1, otherwise exceptions would be thrown. This is designed to make it clear to developers and readers that the code has N+1 performance risk. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER.allScalarFields(), it -> it.batch(1).limit(/*limit*/ 10, /*offset*/ 90) ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors({ batch(1) limit(limit = 90, offset = 10) }) { allScalarFields() } } ) } .execute() Since association pagination cannot solve N+1 problem, multiple SQLs are generated For simplicity let's assume H2Dialect is used so different databases have the same paging SQL Query current Book objects select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? Paginated query on authors collection of the 1st Book object select tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID = ? limit ? offset ? Paginated query on authors collection of the 2nd Book object Same as above, omitted. Paginated query on authors collection of the 3rd Book object Same as above, omitted. Paginated query on authors collection of the 4th Book object Same as above, omitted.","s":"Pagination at Association Level","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#pagination-at-association-level","p":1320},{"i":1342,"t":"When fetching associations, filters can be specified to filter associated objects. Here for comparison, the query selects two columns, both are Book type. The Book.authors of the first column uses filter The Book.authors of the second column does not use filter Java Kotlin BookTable book = Tables.BOOK_TABLE; List> books = sqlClient .createQuery(book) .select( // First column book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER.allScalarFields(), // Use filter it -> it.filter(args -> { args.where(args.getTable().firstName().ilike(\"a\")); }) ) ), // Second column book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER.allScalarFields() // No filter used ) ) ) .execute(); val tuples: List> = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( // First column table.fetchBy { allScalarFields() authors({ // Use filter filter { where(table.firstName ilike \"a\") } }) { allScalarFields() } }, // Second column table.fetchBy { allScalarFields() authors { // No filter used allScalarFields() } } ) } .execute() Three SQLs are generated: Query the two Book objects needed for the tuple select /* For tuple._1 */ tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, /* For tuple._2 */ tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? For the authors association of the 4 Book objects in column 1, use filter select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID in (?, ?, ?, ?) and /* Use filter here */ lower(tb_3_.FIRST_NAME) like ? For the authors association of the 4 Book objects in column 2, no filter select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID in (?, ?, ?, ?) /* No filter here */ The printed result is (formatted for readability): Tuple2{ _1={ \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, // Filter used, incomplete collection \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" } ] }, _2={ \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, // No filter, complete collection \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" },{ \"id\":\"fd6bb6cf-336d-416c-8005-1ae11a6694b5\", \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"MALE\" } ] } } note Filters can not only filter associated objects, but also sort them. The principle is similar so not demonstrated here. caution For associations satisfying both below conditions, applying filters would cause exceptions: Many-to-one Not null After field filters are used, association cache for that field will be ignored. To use the association cache, global filters supporting multi-view cache can be used. A common mistake in real development (Java for example) is: filter(it -> args.getTable().firstName().ilike(\"a\")) This creates the condition expression but does not call args.where. Filter code not calling either args.where or args.orderBy is meaningless. The correct code is: filter(it -> args.where(args.getTable().firstName().ilike(\"a\")))","s":"Property-level Filters","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#property-level-filters","p":1320},{"i":1345,"t":"First, provide MappedSuperclass for all entities that need multi-tenancy management to inherit: Java Kotlin TenantAware.java @MappedSuperclass public interface TenantAware { String tenant(); } TenantAware.kt @MappedSuperclass interface TenantAware { val tenant: String } Any entity that needs multi-tenancy support can inherit TenantAware, such as Book: Java Kotlin Book.java @Entity public interface Book extends TenantAware { ...Other code omitted... } Book.kt @Entity interface Book : TenantAware { ...Other code omitted... } tip Certainly, it's possible to apply filters directly to entity types without defining the abstract type, this works fine. However, it is better to extract the abstract type from entities, so one filter can apply to multiple entity types. More importantly, MappedSuperclass supports multiple inheritance, i.e. entities can inherit from multiple supertypes. Multi-inheritance combined with global filters brings amazing flexibility.","s":"Provide Abstract Mapped Superclass","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#provide-abstract-mapped-superclass","p":1343},{"i":1347,"t":"Assume there is an object of type TenantProvider in the Spring context. Its Java method get() and Kotlin property tenant are used to extract the tenant of the current operator from identity info. Define the filter as follows: In Java, filter need to implement org.babyfish.jimmer.sql.filter.Filter. In Kotlin, filter need to implement org.babyfish.jimmer.sql.kt.filter.KFilter. If using Spring management, the code is: Java Kotlin @Component public class TenantFilter implements Filter { private final TenantProvider tenantProvider; public TenantFilter(TenantProvider tenantProvider) { this.tenantProvider = tenantProvider; } @Override public void filter(FilterArgs args) { String tenant = tenantProvider.get(); if (tenant != null) { args.where(args.getTable().tenant().eq(tenant)); } } } @Component class TenantFilter( private val tenantProvider: TenantProvider ) : KFilter { override fun filter(args: KFilterArgs) { tenantProvider.tenant?.let { args.apply { where(table.tenant.eq(it)) } } } } There are slight differences in filter definition between Java and Kotlin: In Java, the generic type of Filter is TenantAwareProps, which is part of the code auto-generated by the precompiler for the abstract type TenantAware. In Kotlin, the generic type of KFilter is the abstract type TenantAware itself. TenantFilter filters the abstract type TenantAware. For any entity that inherits the abstract interface TenantAware directly or indirectly, its queries will be handled by this filter, automatically adding a where condition. Inside TenantFilter, it first extracts the tenant of the current operator from identity info. If the tenant is non-null, use it to filter data, querying only data that matches the specified tenant.","s":"Define Filter","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#define-filter","p":1343},{"i":1349,"t":"In the above, the defined class TenantFilter is decorated with @Component, obviously a Spring-managed object. info If using Jimmer's Spring Boot Starter and ensuring the filter is Spring-managed, Jimmer will auto-register it without extra configuration. Otherwise, must manually register.","s":"Configure Filter in Spring","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#configure-filter-in-spring","p":1343},{"i":1351,"t":"In this case, the filter class does not need to be decorated with @Component, attach the filter to the SqlClient object for it to take effect: Java Kotlin JSqlClient sqlClient = JSqlBuilder .newBuilder() .addFilter(new CustomerFilter()) ...Other config omitted... .build(); val sqlClient = newKSqlClient { addFilters(new CustomerFilter()) ...Other config omitted... }","s":"Configure Filter Without Spring","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#configure-filter-without-spring","p":1343},{"i":1353,"t":"Filtering aggregate roots is the simplest use of global filters. Since Book entity inherits from TenantAware, its queries will be affected by this filter. Java Kotlin List books = sqlClient.getEntities.findAll(Book.class); val books = sqlClient.entities.findAll(Book::class); or Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select(book) .execute(); val books = SqlClient .createQuery(Book::class) { select(table) } .execute() The generated SQL: select tb_1_.ID, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.TENANT = ? Obviously, the query here is very simple without any query parameters. But the final SQL still filters on tb_1_.TENANT.","s":"Filter Aggregate Root Objects","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#filter-aggregate-root-objects","p":1343},{"i":1355,"t":"Not only aggregate roots can be filtered, associated objects can be filtered too: Java Kotlin List authors = sqlClient.getEntities.findAll( Fetchers.AUTHOR_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ); val books = sqlClient.entities.findAll( newFetcher(Author::class).by { allScalarFields() books { allScalarFields() } } ); or Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(author) .select( author.fetch( Fetchers.AUTHOR_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ) ) .execute(); val authors = SqlClient .createQuery(Author::class) { select( table.fetchBy { allScalarFields() books { allScalarFields() } } ) } .execute() This generates two SQL statements: Query aggregate roots: select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR as tb_1_ Query associated objects: select tb_2_.AUTHOR_ID, tb_1_.ID, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where tb_2_.AUTHOR_ID in (?, ?, ?, ?, ?) and tb_1_.TENANT = ?","s":"Filter Associated Objects","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#filter-associated-objects","p":1343},{"i":1357,"t":"Calling sqlClient.filters creates a new temporary SqlClient without affecting the current sqlClient, which can be used to disable filters: Java Kotlin JSqlClient tmpSqlClient = sqlClient.filters(it -> { it .disableByTypes(TenantFilter.class); }); val tmpSqlClient = sqlClient.filters { disableByTypes(TenantFilter::class) } Here we get a temporary tmpSqlClient. Queries created from it will ignore the filter we demonstrated above.","s":"Disable Filters","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#disable-filters","p":1343},{"i":1359,"t":"In addition to the basic Filter/KFilter interface, filter classes can also implement more interfaces, including: CacheableFilter/KCacheableFilter AssociationIntegrityAssuranceFilter/AssociationIntegrityAssuranceFilter ShardingFilter/KShardingFilter","s":"More filter interfaces","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#more-filter-interfaces","p":1343},{"i":1361,"t":"Global filters show different data to different users, and for any associated property that takes the filtered type as the target type, different users will naturally see different associations. This will lead to: These association properties cannot apply simple Association Cache Dependent calculated properties also cannot enable Calculated Cache To solve this problem, Jimmer supports Multi-View CacheCacheableFilterKCacheableFilterCache/Multi-view Cache/User Defined Cacheable Filters","s":"CacheableFilter","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#cacheablefilter","p":1343},{"i":1363,"t":"The full name of this interface is: Java: org.babyfish.jimmer.sql.filter.AssociationIntegrityAssuranceFilter

Kotlin: org.babyfish.jimmer.sql.kt.filter.KAssociationIntegrityAssuranceFilter Compared to the basic Filter/KFilter interface, this interface does not add any new methods, it is only used as a type identifier. For one-to-one/many-to-one association properties based on foreign keys, even if the field is set to a non-null type and has a real foreign key constraint, the associated object queried may still be null due to the filter. Therefore, Jimmer stipulates that if the associated entity of a one-to-one/many-to-one association property is affected by the filter, the association property must be declared as nullable. The AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter allows the user to make a commitment to the characteristics of the database data to break this restriction. First, let the filter class implement this interface Java Kotlin @Component public class TenantFilter implements AssociationIntegrityAssuranceFilter { ... } @Component class TenantFilter( ... ) : KAssociationIntegrityAssuranceFilter { ... } Then, let BookStore inherit TenantAware Java Kotlin @Entity public interface Book extends TenantAware { ... } @Entity interface Book : TenantAware { ... } Finally, let Book also inherit TenantAware, and define a non-null many-to-one association property Book.store Java Kotlin @Entity public interface Book extends TenantAware { @ManyToOne // Not null BookStore store(); ... } @Entity interface Book : TenantAware { val store: BookStore // NotNull ... } The following code analysis: Book and BookStore both inherit TenantAware, that is, both sides of the association are controlled by the filter TenantFilter TenantFilter implements the AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter interface. This interface is the user's commitment to the characteristics of the database data, committing that only objects that follow the same filtering rules will have associations. For this example, it means that only BookStore and Book objects belonging to the same tenant are associated, and BookStore and Book objects belonging to different tenants will never be associated. Only under the user's commitment can the many-to-one association Book.store be set to non-null. In summary, if the associated type of a one-to-one/many-to-one association property is affected by the filter, in order to set this property to non-null, the following two conditions must be met at the same time: All global filters applied to the associated entity implement the AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter interface. All global filters applied to the associated entity are also applied to the current entity.","s":"AssociationIntegrityAssuranceFilter","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#associationintegrityassurancefilter","p":1343},{"i":1365,"t":"The full name of this interface is: Java: org.babyfish.jimmer.sql.filter.ShardingFilter

Kotlin: org.babyfish.jimmer.sql.kt.filter.KShardingFilter Compared to the basic Filter/KFilter interface, this interface does not add any new methods, it is only used as a type identifier. Jimmer provides simple APIs to query entity/entities by id/ids. By default, these APIs are special - they ignore global filters. Queries by id ignoring filters are correct since ids uniquely identify objects. However, if sharding-jdbc is used at the JDBC level, and the field used as filter condition is the sharding field in sharding-jdbc, querying by id alone would cause sharding-jdbc to query multiple shards, which is disastrous. To solve this, make the filter implement ShardingFilter (Java) or KShardingFilter (Kotlin). These interfaces have no behaviors, just for type marking. Once a filter inherits ShardingFilter or KShardingFilter, these simple APIs will no longer ignore the filter. This ensures the final SQL contains the sharding field required by sharding-jdbc, querying only one shard instead of all shards.","s":"Sharding Filters","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#sharding-filters","p":1343},{"i":1367,"t":"When user-defined filters and cache are used together, a problem called \"multi-view cache\" is involved. Since we haven't introduced cache yet, we'll just make a brief note here. Please refer to Cache/Multi-view Cache for details.","s":"Multi-view Cache","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#multi-view-cache","p":1343},{"i":1369,"t":"We have introduced that object fetchers can flexibly control the shape of queried data structures, bringing tremendous flexibility for application development. We also know there are two completely equivalent ways to use them: Directly use object fetchers and return dynamic entity objects Use the DTO language to define output DTO shapes, auto-generate related Java/Kotlin types and entity conversion logic, as well as the object fetcher corresponding to the shape. Jimmer provides a Spring Boot Starter and is integrated with Spring Data. Object fetchers are also integrated into Spring Data. Relevant documentation links: Directly using object fetchers Use object fetchers in abstract queries Use object fetchers in complex queries @FetchBy annotation to auto-generate strictly typed client code Using DTO language Query DTO objects with Spring Data","s":"Working with Spring Data","u":"/jimmer-doc/docs/query/object-fetcher/spring-data","h":"","p":1368},{"i":1371,"t":"Previously we introduced using object fetchers to flexibly control the shape of queried data structures. Now we introduce an equivalent capability: querying DTO objects. Jimmer provides a DTO language tip This language is essentially another way to express object fetchers. Using this language, developers can quickly define various data structure shapes with an entity type as the aggregate root. The compiler will generate corresponding Java/Kotlin DTO classes for each defined shape. Each DTO type contains mutual conversion logic with the original dynamic type, and an object fetcher matching its own shape. In some cases, after the server queries data in a certain shape, it is not meant to be returned as an HTTP response, but rather used internally to drive subsequent complex business logic. This is an ideal scenario for this approach. caution Note that if the server queries data in a certain shape not for its own use, but directly as the HTTP response, it is more recommended to directly return the dynamic entity object and use the solutions in Generate Client Code to automatically generate client code with a great developer experience.","s":"Querying DTOs","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"","p":1370},{"i":1373,"t":"This article focuses on explaining how to query static DTO types, not a systematic introduction to the DTO language itself. Please refer to Object section/DTO Mapping/DTO Language for the complete DTO language. Assuming the fully qualified name of the Book class is com.yourcompany.yourproject.model.Book, you can In the project where the entity is defined, create the directory src/main/dto Under src/main/dto, create subdirectories following the package path of the entity type com/yourcompany/yourproject/model In the directory created in the previous step, create a file Book.dto. The file name must match the entity class name, and the extension must be dto Edit this file, use the DTO language to define various DTO shapes for the Book entity Book.dto BookDetailView { #allScalars store { #allScalars } authors { #allScalars } } SimpleBookView { ...omitted... } ...Omit definitions of other DTO shapes...","s":"Defining DTO Shapes","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#defining-dto-shapes","p":1370},{"i":1375,"t":"Jimmer is responsible for compiling dto files and automatically generating DTO types matching these shapes. caution If Java/Kotlin source code files other than dto files are modified, running the application directly from the IDE can trigger recompilation of dto files. However, if no Java/Kotlin files other than dto files are modified, simply clicking the run button in the IDE does not cause dto files to be recompiled unless explicitly rebuilding! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle Taking BookDetailView in the above code as an example, after the dto file is successfully compiled by Jimmer, the following DTO type will be automatically generated: Java Kotlin BookDetailView.java package com.yourcompany.yourproject.model.dto; import com.yourcompany.yourproject.model.Book; import org.babyfish.jimmer.View; @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookDetailView implements View { private long id; private String name; private int edition; private BigDecimal price; private TargetOf_store store; private List authors; public static class TargetOf_store implements View { private long id; private String name; @Nullable private String website; ...other members omitted... } public static class TargetOf_authors implements View { private long id; private String firstName; private String lastName; private Gender gender; ...other members omitted... } ...other members omitted... } BookDetailView.kt package com.yourcompany.yourproject.model.dto import com.yourcompany.yourproject.model.Book import org.babyfish.jimmer.View @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookDetailView( val id: Long = 0, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val store: TargetOf_store? = null, val authors: List = emptyList(), ) : View { data class TargetOf_store( val id: Long = 0, val name: String = \"\", val website: String? = null, ) : View { ...other members omitted... } data class TargetOf_authors( val id: Long = 0, public val firstName: String = \"\", public val lastName: String = \"\", public val gender: Gender, ) : View { ...other members omitted... } ...other members omitted... } info The generated DTO classes are in the dto subpackage of the entity package, not the entity package itself. For Java, it is assumed lombok is already in use.","s":"Auto-generated DTO Types","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#auto-generated-dto-types","p":1370},{"i":1378,"t":"Java Kotlin BookDetailView view = sqlClient.findNullable( BookDetailView.class, 1L ); System.out.println(view); val view = sqlClient.findNullable( BookDetailView::class, 1L ); println(view) The printed result is as follows (formatted manually for readability): BookDetailView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookDetailView.TargetOf_store( id=1, name=O'REILLY, website=null, version=0 ), authors=[ BookDetailView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookDetailView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) It's easy to see that although dynamic entity objects are no longer returned, the functionality is exactly the same as object fetchers. Why is this? The DTO types generated from the DTO language all contain object fetchers matching their own shapes, as follows: Java Kotlin BookDetailView.java @Data public class BookDetailView implements View { public static final ViewMetadata METADATA = new ViewMetadata( Fetchers.BOOK_FETCHER .name() .edition() .price() .store(TargetOf_store.METADATA.getFetcher()) .authors(TargetOf_authors.METADATA.getFetcher()), BookDetailView::new ); @Data public static class TargetOf_store implements View { public static final ViewMetadata METADATA = new ViewMetadata( Fetchers.BOOK_STORE_FETCHER .name() .website() .version(), TargetOf_store::new ); ...other members omitted... } @Data public static class TargetOf_authors implements View { public static final ViewMetadata METADATA = new ViewMetadata( Fetchers.AUTHOR_FETCHER .firstName() .lastName() .gender(), TargetOf_authors::new ); ...other members omitted... } ...other members omitted... } BookDetailView.kt @Data data class BookDetailView( ...omitted... ) : View { ...other members omitted... companion object { @JvmStatic public val METADATA: ViewMetadata = ViewMetadata( newFetcher(Book::class).by { name() edition() price() store(TargetOf_store.METADATA.fetcher) authors(TargetOf_authors.METADATA.fetcher) } ) { CompositeBookInput(it) } } @Data public static class TargetOf_store implements View { ...other members omitted... companion object { @JvmStatic val METADATA: ViewMetadata = ViewMetadata( newFetcher(BookStore::class).by { name() website() } ) { TargetOf_store(it) } } } @Data public static class TargetOf_authors implements View { ...other members omitted... companion object { @JvmStatic val METADATA: ViewMetadata = ViewMetadata( newFetcher(Author::class).by { firstName() lastName() gender() } ) { TargetOf_authors(it) } } } } tip This is why this article says at the beginning that the DTO language is essentially another way to express object fetchers.","s":"Using findById","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#using-findbyid","p":1370},{"i":1380,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.name()) .orderBy(table.edition().desc()) .select( table.fetch(BookDetailView.class) ) .execute() val books = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.name) orderBy(table.edition.desc()) select( table.fetch(BookDetailView::class) ) } .execute() Here we see that table.fetch(fetcher) in previous code is replaced with table.fetch(BookDetailView.class). tip All low-level query APIs can replace fetcher with viewType, again proving that the DTO language is essentially another way to express object fetchers, as stated at the beginning.","s":"Using Custom Queries","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#using-custom-queries","p":1370},{"i":1383,"t":"Scalar fields refer to all non-associative fields in a database table. Taking fetching the book name as an example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER.name() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name() } ) } .execute() note For Java, the Annotation processor will automatically generate a Fetcher class for each entity interface, which is BookFetcher in this example. The generated SQL is: select tb_1_.ID, tb_1_.NAME from BOOK as tb_1_ where tb_1_.EDITION = ? note The Java code does not call the id() method of BookFetcher, but we can see the SQL statement still queries the id property of the object. The id property is treated specially and will always be queried, not controlled by object fetchers. In fact, the auto-generated BookFetcher class does not even have an id() method, because it is not needed. The printed result is (original output is compact, formatted here for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\" }, ...Other objects omitted... ]","s":"Fetching Scalar Fields","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#fetching-scalar-fields","p":1381},{"i":1385,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER .name() .edition() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name() edition() } ) } .execute() info Object fetchers are immutable objects, each method call returns a new object fetcher. In the Java code above: Fetchers.BOOK_FETCHER Fetchers.BOOK_FETCHER.name() Fetchers.BOOK_FETCHER.name().edition() are three different object fetchers, each immutable. Object fetchers can be freely shared using static variables since they are immutable. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK as tb_1_ where tb_1_.EDITION = ? The printed result is (original output is compact, formatted here for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":1 }, ...Other objects omitted... ]","s":"Fetching Multiple Fields","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#fetching-multiple-fields","p":1381},{"i":1387,"t":"In some scenarios, fetching all non-associative fields is a very common operation, so allScalarFields() is provided to load all non-associative fields. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER.allScalarFields() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() } ) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? The printed result is (original output is compact, formatted here for readability): { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00 } // Other objects omitted info allScalarFields() only loads non-associative fields. In the example we can see it queries id, name, edition, price, but does not query the association properties store and authors. Fetching association properties will be covered in the next document.","s":"Fetching All Scalar Fields","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#fetching-all-scalar-fields","p":1381},{"i":1389,"t":"The previously discussed properties are positive properties that incrementally add fields to query. But in some cases, we only need to exclude some specific fields, while querying all other fields. This is when negative properties can be used to exclude unneeded fields. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .edition(false) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() edition(false) } ) } .execute() edition(false) uses false as a parameter, making it a negative property. The properties of allScalarFields() are id + name + edition + price edition(false) means -edition So in combination, the finally fetched properties are id + name + price info For positive properties, edition() and edition(true) are equivalent When most properties need to be fetched and only a few excluded, using allScalarFields with negative properties can be very useful The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? The printed result is (original output is compact, formatted here for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"price\":51.00 // `edition` is not here }, ...Other objects omitted... ]","s":"Negative Properties","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#negative-properties","p":1381},{"i":1392,"t":"tip One statement to query data structure of arbitrary shape, like GraphQL Before understanding object fetchers, it is necessary to first understand conventional property queries. For example, I need a SQL like this: select b.id, b.name, b.edition /* Don't need `b.price` and `b.store_id` */ from book b where b.edition = 3; In this SQL, we only query a part of columns. The corresponding Jimmer code is: Java Kotlin BookTable table = Tables.BOOK_TABLE; List> tuples = sqlClient .createQuery(book) .where(table.edition().eq(3)) .select( table.id(), table.name(), table.edition() ) .execute(); System.out.println(tuples); val tuples = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.id table.name table.edition ) } .execute() println(tuples) The printed output is (formatted for readability): [ { \"_1\" : 3, \"_2\" : \"Learning GraphQL\", \"_3\" : 3 } ...Other objects omitted ] info Since a part of object properties are queried, select(table) cannot be simply used. Instead, select(expr1, expr2, ..., expr3) is required. However, this results in tuples being returned instead of objects. In the tuples, the property order corresponds to the select() order. In the above example, the mapping in each tuple is: _1 -> id _2 -> name _3 -> edition If we want to return objects, one choice is to define a BookDTO type (assuming lombok is used for Java): Unlike the original Book entity type, BookDTO only contains the properties we need rather than all properties. Java Kotlin BookDTO.java @Data public class BookDTO { private long id; private String name; private int edition; } BookDTO.kt data class BookDTO( val id: Long, val name: String, val edition: Int ) There are two ways to convert the tuples to BookDTO objects: Keep previous code unchanged, first query Tuple3 collection, then convert using Stream API Use Jimmer's utility API to directly transform the query result Here we use the second approach: Java Kotlin BookTable table = Tables.BOOK_TABLE; List bookDTOs = sqlClient .createQuery(book) .where(table.edition().eq(3)) .select( table.id(), table.name(), table.edition() ) .map(tuple -> { BookDTO dto = new BookDTO(); dto.setId(tuple.get_1()); dto.setName(tuple.get_2()); dto.setEdition(tuple.get_3()); return dto; }); System.out.println(bookDTOs); val bookDTOs = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.id table.name table.edition ) } .map { BookDTO(it._1, it._2, it._3) } println(tuples) The result after conversion is the type we want: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"edition\" : 3 } ...Other objects omitted ] JPA and MyBatis make this kind of choice: JPA returns all scalar properties of an object by default. If you want to customize the returned properties, Either use HQL: select new BookDTO(...) from ... Or use query.unwrap(SQLQuery.class).setResultTransformer(Transformers.aliasToBean(DTO.class)) MyBatis needs to write a ResultMapper corresponding to the DTO. However, neither JPA nor MyBatis can avoid having to write an additional DTO class and take on the logic of transforming from the query structure to the DTO object themselves. info Unfortunately Query business often has diversity, and inevitable format diversity means more DTO types (as aggregate root types there may be format diversity issues, and as associated types of other DTOs it will be easier to lead to format diversity issues). This eventually leads to DTO explosion problem For JPA, this goes against the original intention of ORM: convenience Next, we'll use Jimmer's object fetcher to simplify this process.","s":"Why Introduce Object Fetchers","u":"/jimmer-doc/docs/query/object-fetcher/usage","h":"#why-introduce-object-fetchers","p":1390},{"i":1394,"t":"For each entity interface, Jimmer generates a corresponding Fetcher class. These Fetchers are object fetchers. Based on the fetched properties, object fetchers automatically package objects, eliminating the need to manually map and write additional DTO classes. note The Annotation processor will automatically generate a Fetcher class for each entity interface, which is BookFetcher in this example. Example 1: The query in the above example can be written as an object fetcher: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient.createQuery(table) .where(table.edition().eq(3)) .select( table.fetch( Fetchers.BOOK_FETCHER // id is implicit, mandatory .name() .edition() ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { // id is implicit, mandatory name edition } ) } .execute() println(books) As you can see, the return value is of type Book, no need for further mapping, which saves a lot of time for daily coding. The output is as follows: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"edition\" : 3 }, ...Other objects omitted... ] Example 2 We can modify the code a little, not fetching the book edition, but fetching the book price: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient.createQuery(table) .where(table.edition().eq(3)) .select( table.fetch( Fetchers.BOOK_FETCHER .name() .price() ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name price } ) } .execute() println(books) The JSON output now is: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"price\" : 51.00 }, ...Other objects omitted... ] Example 3 You can even query associated objects Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient.createQuery(table) .where(table.edition().eq(3)) .select( table.fetch( Fetchers.BOOK_FETCHER .name() .authors( Fetchers.AUTHOR_FETCHER .firstName() ) ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name authors { firstName } } ) } .execute(); println(books) The JSON output now is: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"authors\": [ { \"id\": 1, \"Eve\" }, { \"id\": 2, \"Alex\" }, ] }, ...Other objects omitted... ] tip With the dynamicity of Jimmer entities, there is no need to write additional DTOs to achieve diversified query business, just change the shape of the object fetcher. For the output data of the query, eliminating DTO explosion problem can greatly improve server-side productivity.","s":"Using Object Fetchers","u":"/jimmer-doc/docs/query/object-fetcher/usage","h":"#using-object-fetchers","p":1390},{"i":1396,"t":"When object fetchers are used to fetch association properties, they are similar to JPA's EntityGraph, but have the following differences: Object fetchers use batch-load strategy to load associated objects, not JPA's join-fetch concept. This is important because: Fetching collection associations does not break paginated queries like JPA's EntityGraph. More friendly to association cache and remote associations. JPA's EntityGraph only controls association properties, but object fetchers can control any properties, same as GraphQL, with precision down to each property. For infinite recursive structures caused by self-associated properties, object fetchers support recursive query.","s":"Differences from JPA EntityGraph","u":"/jimmer-doc/docs/query/object-fetcher/usage","h":"#differences-from-jpa-entitygraph","p":1390},{"i":1398,"t":"In this series of articles, we will introduce Jimmer's smart paging. Surprisingly simple Sufficiently optimized","s":"Smart Paging","u":"/jimmer-doc/docs/query/paging/","h":"","p":1397},{"i":1401,"t":"As page numbers increase, pagination query efficiency drops. To solve this, Jimmer supports reverse sorting optimization. Reverse sorting optimization takes effect only when the following prerequisites are met together: This feature does not apply to queries that only care about in-page data regardless of total row count before pagination, i.e. limit(limit, offset). It must be queries that care about both in-page data and total count. The template query must have explicit orderBy clause. The queried page data is late relative to all data before pagination. I.e. offset + pageSize / 2 > totalCount / 2 When all above conditions are met, Jimmer flips the sorting of the template query. Because a forward sorting query with relatively large page number and a reverse sorting query with relatively small page number are equivalent.","s":"Concept","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#concept","p":1399},{"i":1403,"t":"Let's look at an example. Java Kotlin public Page findBooks( int pageIndex, int pageSize ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .fetchPage(pageIndex, pageSize); } fun findBooks( pageIndex: Int, pageSize: Int ): Page = sqlClient .createQuery(Book::class) { orderBy(table.name.asc(), table.edition.desc()) select(table) } .fetchPage(pageIndex, pageSize) Assume there are 12 Book records total. pageSize is 2, so there are 6 pages. pageIndex has 5 possible values: 0, 1, 2, 3, 4, 5. 0, 1, 2: Data to query is early, use forward sorting pagination. 3, 4, 5: Data to query is late, use reverse sorting pagination. Next we demonstrate the difference between reverse and forward sorting pagination with pageIndex=2 and pageIndex=3 as examples.","s":"Example","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#example","p":1399},{"i":1405,"t":"Executing findBooks(2, 2) generates the forward sorting SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 2 */ offset ? /* 4 */ The result is: { \"rows\":[ { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81, \"store\":{ \"id\":2 } }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2 } } ], \"totalCount\":12, \"totalPage\":6 }","s":"Forward Sorting","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#forward-sorting","p":1399},{"i":1407,"t":"Executing findBooks(3, 2) generates the reverse sorting SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME desc, // Reversed: asc to desc tb_1_.EDITION asc // Reversed: desc to asc limit ? /* 2 */ offset ? /* 4 */ The result is: { \"rows\":[ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1 } }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1 } } ], \"totalCount\":12, \"totalPage\":6 }","s":"Reverse Sorting","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#reverse-sorting","p":1399},{"i":1410,"t":"Let's first look at an example (this query has no real business logic, just for demo): Java Kotlin BookTable book = Tables.BOOK_TABLE; List< Tuple5< String, Long, OffsetDateTime, String, Boolean > > tuples = sqlClient .createQuery(book) .select( Expression.string().value(\"String\"), Expression.numeric().value(3L), Expression.comparable().value(OffsetDateTime.now()), Expression.any().value(\"String\"), Expression.nullValue(Boolean.class) ) .execute(); val tuples = sqlClient .createQuery(Book::class) { select( value(\"String\"), value(3L), value(OffsetDateTime.now()), value(\"String\"), nullValue(Boolean::class) ) } .execute() The generated SQL is: select ?, ?, ?, ?, null from BOOK as tb_1_ Except for null, literals of other types all become JDBC parameters. caution As can be seen from this example, the value() method accepts many parameter types. Note that no matter what the value() parameter type is, it cannot be null, otherwise exceptions would be thrown. To create literal expressions for null, the nullValue() method must be used which requires the expression type to be specified. info For Java code, type-guided methods are used: Expression.string(), for string type. Expression.numeric(), for numeric types. Expression.comparable(), for comparable types, i.e. types extending java.lang.Comparable. Expression.any(), for other types. Kotlin does not have this issue, its API is unified. tip In most cases, developers do not need to manually create literal expressions. Take equality check in examples below for instance, the relatively tedious syntax: Java Kotlin where( book.name().eq( Expression.string().value(\"Java in Action\") ) ); where( table.name eq value(\"Java in Action\") ) Isn't this a bit tedious? Don't worry, it can be replaced with a more convenient form: Java Kotlin where(book.name().eq(\"Java in Action\")); where(table.name eq \"Java in Action\") It's easy to see other APIs provide overloaded versions to avoid making developers create literal expressions manually. But this can't cover 100% cases. In very rare cases, developers still need to create literal expressions manually.","s":"Literal Expressions","u":"/jimmer-doc/docs/query/expression","h":"#literal-expressions","p":1408},{"i":1412,"t":"Constant expressions are highly similar to literal expressions, let's look at an example (this query has no real business logic, just for demo): Java Kotlin BookTable book = Tables.BOOK_TABLE; List constants = sqlClient .createQuery(book) .select( Expression.constant(1) ) .execute(); val constants = sqlClient .createQuery(Book::class) { select( constant(1) ) } .execute() The generated SQL is: select 1 from BOOK as tb_1_ Unlike literal expressions that always use JDBC parameters, constant expressions directly hardcode the value into the SQL. To prevent SQL injection attacks, constant expressions only support numeric types, this is a hard constraint. info Although constant expressions have this hard constraint of only supporting numeric types to prevent SQL injection, they should still be strictly limited in real projects. The only reason constant expressions exist is that some databases support function-based indexes. Constant expressions can be useful if the SQL expressions defining such function indexes contain numeric constants. If your project does not have this scenario, never use constant expressions. Always use literal expressions. Incorrect use of constant expressions can have serious consequences. Erroneously planting unstable numeric variables as constant expressions into SQL will break the stability of the SQL string, eventually leading to extremely low hit rates of execution plan cache in the database, impacting performance.","s":"Constant Expressions","u":"/jimmer-doc/docs/query/expression","h":"#constant-expressions","p":1408},{"i":1414,"t":"Initially, Jimmer supported dynamic queries through whereIf: Java Kotlin public List findBooks( @Nullable String name, @Nullable Integer edition ) { BookTable table = BookTable.$; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), () -> table().name().ilike(name) ) .whereIf( edition != null, table().edition().eq(edition) ) .select(table) .execute(); } fun findBooks( name: String? = null, edition: Int? = null ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } edition?.let { where(table.edition eq it) } select(table) } .execute() Although whereIf has good readability, the code is relatively cumbersome. Later, Jimmer provided dynamic predicates, which simplified the above code to: Java Kotlin public List findBooks( @Nullable String name, @Nullable Integer edition ) { BookTable table = BookTable.$; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .where(table.edition().eqIf(edition)) .select(table) .execute(); } fun findBooks( name: String? = null, edition: Int? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.name `eq?` edition) select(table) } .execute() Here, ilikeIf, eqIf in Java and ilike?, eq? in Kotlin are called dynamic predicates. When the right operand is null or an empty string (string of length 0), the dynamic predicate does not create an expression and directly returns null. The where call can automatically ignore null, thereby achieving an equivalent dynamic query. info Compared to the initial whereIf, the value of dynamic predicates is not in simplifying the code but in accommodating more complex scenarios, such as or: Java Kotlin public List findBooksByNameOrPriceRange( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ) { BookTable table = BookTable.$; return sqlClient .createQuery(table) .where( Predicate.or( table.name().eqIf(name), table.price().betweenIf(minPrice, maxPrice) ) ) .select(table) .execute(); } fun findBooksByNameOrPriceRange( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null ): List = sqlClient .createQuery(Book::class) { where( or( table.name `eq?` name, table.price.`between?`(minPrice, maxPrice) ) ) select(table) } .execute() Here, all the arguments of or are dynamic predicates, meaning each argument of or can be null, and or can also ignore null arguments. Of course, if all arguments are null, then or itself will refuse to create any expression and directly return null. Here are all the static predicates and dynamic predicates in Jimmer: Static Predicate Dynamic Predicate (Java) Dynamic Predicate (Kotlin) eq eqIf `eq?` ne neIf `ne?` lt ltIf `lt?` le leIf `le?` gt gtIf `gt?` ge geIf `ge?` like likeIf `like?` ilike ilikeIf `ilike?` between betweenIf `between?` Q: Why does Jimmer provide two sets of predicates instead of just providing dynamic predicates? A: Because static predicates also handle null specially: eq: automatically converted to isNull() ne: automatically converted to isNotNull() Other static predicates: Java: Treats this as a bug in the user's code, requiring the user to either provide a non-null value or switch to a dynamic predicate. Kotlin: Prevents the user from providing potentially null values at compile-time. info We have clearly discussed the concept of dynamic predicates. To simplify subsequent discussions, the rest of this content will only demonstrate static predicates.","s":"Static Predicates vs Dynamic Predicates","u":"/jimmer-doc/docs/query/expression","h":"#static-predicates-vs-dynamic-predicates","p":1408},{"i":1416,"t":"Equals Java Kotlin where(book.name().eq(\"SQL in Action\")); where(table.name eq \"SQL in Action\") Not equals Java Kotlin where(book.name().ne(\"SQL in Action\")); where(table.name ne \"SQL in Action\") Greater than Java Kotlin where(book.price().gt(new BigDecimal(50))); where(table.price gt BigDecimal(50)) Greater than or equals Java Kotlin where(book.price().ge(new BigDecimal(50))); where(table.price ge BigDecimal(50)) Less than Java Kotlin where(book.price().lt(new BigDecimal(50))); where(table.price lt BigDecimal(50)) Less than or equals Java Kotlin where(book.price().le(new BigDecimal(50))); where(table.price le BigDecimal(50)) Between Java Kotlin where( book.price().between( new BigDecimal(40), new BigDecimal(50) ) ); where( table.price.between( BigDecimal(40), BigDecimal(50) ) ) Not Between Java Kotlin where( book.price().notBetween( new BigDecimal(40), new BigDecimal(50) ) ); where( table.price.notBetween( BigDecimal(40), BigDecimal(50) ) )","s":"Comparison","u":"/jimmer-doc/docs/query/expression","h":"#comparison","p":1408},{"i":1419,"t":"like: case sensitive Java Kotlin where(book.name().like(\"Ab\")); where(table.name like \"Ab\") The generated SQL condition is: where tb_1_.NAME like ? The corresponding JDBC parameter is: %Ab% ilike: case insensitive Java Kotlin where(book.name().ilike(\"Ab\")); where(table.name ilike \"Ab\") The generated SQL condition is: If ilike is supported by dialect where tb_1_.NAME ilike ? Otherwise where lower(tb_1_.NAME) like ? The corresponding JDBC parameter is: %ab%","s":"Case Sensitivity","u":"/jimmer-doc/docs/query/expression","h":"#case-sensitivity","p":1408},{"i":1421,"t":"LikeMode.ANYWHERE (default behavior without specifying): appears anywhere Java Kotlin where(book.name().like(\"Ab\", LikeMode.ANYWHERE)); where(table.name.like(\"Ab\", LikeMode.ANYWHERE)) The corresponding JDBC parameter is: %Ab% LikeMode.START: as prefix Java Kotlin where(book.name().like(\"Ab\", LikeMode.START)); where(table.name.like(\"Ab\", LikeMode.START)) The corresponding JDBC parameter is: Ab% LikeMode.END: as suffix Java Kotlin where(book.name().like(\"Ab\", LikeMode.END)); where(table.name.like(\"Ab\", LikeMode.END)) The corresponding JDBC parameter is: %Ab LikeMode.EXACT: exact match Java Kotlin where(book.name().like(\"Ab\", LikeMode.EXACT)); where(table.name.like(\"Ab\", LikeMode.EXACT)) The corresponding JDBC parameter is: Ab","s":"Match Modes","u":"/jimmer-doc/docs/query/expression","h":"#match-modes","p":1408},{"i":1423,"t":"Java Kotlin where(book.store().isNull()); where(table.store.isNull()) Java Kotlin where(book.store().isNotNull()); where(table.store.isNotNull())","s":"Null Check","u":"/jimmer-doc/docs/query/expression","h":"#null-check","p":1408},{"i":1426,"t":"Java Kotlin where( book.name().in( Arrays.asList( \"SQL in Action\", \"Java in Action\" ) ) ); where( table.name valueIn listOf( \"SQL in Action\", \"Java in Action\" ) ) The generated SQL condition is: where tb_1_.NAME in (?, ?)","s":"Single Column","u":"/jimmer-doc/docs/query/expression","h":"#single-column","p":1408},{"i":1428,"t":"Java Kotlin where( Expression.tuple( book.name(), book.edition() ).in( Arrays.asList( new Tuple2<>(\"SQL in Action\", 1), new Tuple2<>(\"SQL in Action\", 2), new Tuple2<>(\"Java in Action\", 1), new Tuple2<>(\"Java in Action\", 2) ) ) ); where( tuple( table.name, table.edition ) valueIn listOf( Tuple2(\"SQL in Action\", 1), Tuple2(\"SQL in Action\", 2), Tuple2(\"Java in Action\", 1), Tuple2(\"Java in Action\", 2) ) ) The generated SQL condition is: where (tb_1_.NAME, tb_1_.EDITION) in ( (?, ?), (?, ?), (?, ?), (?, ?) ) note Besides used with collections, in can also be used with subqueries. This will be covered in detail in docs about subqueries.","s":"Multiple Columns","u":"/jimmer-doc/docs/query/expression","h":"#multiple-columns","p":1408},{"i":1430,"t":"Jimmer provides 3 optimizations for the in list expression: Single value optimization Padding optimization Any equality optimization Single value optimization When the list length is 1, in(?) will be automatically rewritten as = ?, and not in(?) will be automatically rewritten as <> ?. For example: Java Kotlin where( Expression.tuple( book.name(), book.edition() ).in( Arrays.asList( new Tuple2<>(\"SQL in Action\", 1) ) ) ); where( tuple( table.name, table.edition ) valueIn listOf( Tuple2(\"SQL in Action\", 1) ) ) The generated SQL condition: where (tb_1_.NAME, tb_1_.EDITION) = (? /* SQL in Action */, ? /* 1 */) Padding optimization To support padding optimization, Jimmer provides a switch that can be enabled in two ways: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-padding-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListPaddingEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListPaddingEnabled(true) // ...omitted other configurations... } Once this switch is enabled, Jimmer will ensure that the list length is a power of 2 (2, 4, 6, 8, 16, 32, ...), thereby significantly reducing the diversity of SQL and increasing the diversity of database execution plan caching. For example: Java Kotlin where( Expression.tuple( book.name(), book.edition() ).in( Arrays.asList( new Tuple2<>(\"SQL in Action\", 1), new Tuple2<>(\"SQL in Action\", 2), new Tuple2<>(\"Java in Action\", 1) ) ) ); where( tuple( table.name, table.edition ) valueIn listOf( Tuple2(\"SQL in Action\", 1), Tuple2(\"SQL in Action\", 2), Tuple2(\"Java in Action\", 1) ) ) In this example, the list length is 3, which is not a power of 2. The nearest power of 2 to 3 is 4, so Jimmer will repeat the last item in the list, eventually making the list length 4. The generated SQL condition is as follows: where (tb_1_.NAME, tb_1_.EDITION) in ( // Original list (? /* SQL in Action */, ? /* 1 */), (? /* SQL in Action */, ? /* 2 */), (? /* Java in Action */, ? /* 1 */), // Repeat the last item in the original list // to make the list length a power of 2 (? /* Java in Action */, ? /* 1 */) ) Any equality optimization This optimization is better tested by the previously discussed padding optimization, but it has two limitations: Currently, it can only optimize single column in The database needs to support the = any(?) expression, i.e., the isAnyEqualityOfArraySupported() method of the implementation class of org.babyfish.jimmer.sql.dialect.Dialect needs to return true Currently, the dialects that support this behavior are: org.babyfish.jimmer.sql.dialect.H2Dialect org.babyfish.jimmer.sql.dialect.PostgresDialect For this, Jimmer provides a switch that can be enabled in two ways: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-to-any-equality-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListToAnyEqualityEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListToAnyEqualityEnabled(true) // ...omitted other configurations... } warning If the current org.babyfish.jimmer.sql.dialect.Dialect implementation class's isAnyEqualityOfArraySupported() method returns false (does not support this feature), this configuration will cause an exception, and the sqlClient cannot be created, and the application cannot start. Java Kotlin where( book.name().in( Arrays.asList( \"SQL in Action\", \"Java in Action\" ) ) ); where( table.name valueIn listOf( \"SQL in Action\", \"Java in Action\" ) ) The generated SQL condition: where tb_1_.NAME = any( ? /* [SQL in Action, Java in Action] */ ) Here, the entire list is treated as a whole and passed as an array-type parameter.","s":"Optimization","u":"/jimmer-doc/docs/query/expression","h":"#optimization","p":1408},{"i":1433,"t":"Java Kotlin where( Predicate.and( book.name().like(\"Ab\"), book.price().ge(new BigDecimal(40)), book.price().lt(new BigDecimal(60)) ) ); where( and( table.name like \"Ab\", table.price ge BigDecimal(40), table.price lt BigDecimal(60) ) ) note Note that when the logical AND expression is directly used as the where parameter, the following equivalent forms are more recommended: Use varargs version of where method Java Kotlin where( book.name().like(\"Ab\"), book.price().ge(new BigDecimal(40)), book.price().lt(new BigDecimal(60)) ); where( table.name like \"Ab\", table.price ge BigDecimal(40), table.price lt BigDecimal(60) ) Call where multiple times Java Kotlin q.where(book.name().like(\"Ab\")); q.where(book.price().ge(new BigDecimal(40))); q.where(book.price().lt(new BigDecimal(60))); where(table.name like \"Ab\") where(table.price ge BigDecimal(40)) where(table.price lt BigDecimal(60)) So directly using and would not be common in real projects.","s":"AND","u":"/jimmer-doc/docs/query/expression","h":"#and","p":1408},{"i":1435,"t":"Java Kotlin where( Predicate.or( book.name().like(\"Ab\"), book.price().ge(new BigDecimal(40)), book.price().le(new BigDecimal(60)) ) ); where( or( table.name like \"Ab\", table.price ge BigDecimal(40), table.price le BigDecimal(60) ) )","s":"OR","u":"/jimmer-doc/docs/query/expression","h":"#or","p":1408},{"i":1437,"t":"Java Kotlin where( book.name().like(\"Ab\").not() ); where( not(table.name like \"Ab\") ); It's not always necessary to call the not() function. Often there are shortcuts available, such as: .eq(value).not() can be simplified to .ne(value) .isNull().not() can be simplified to .isNotNull(value) .exists().not() can be simplified to .notExists() (exists will be introduced in subqueries) Even when developers explicitly use not(), the final SQL may not contain NOT. For example: Java Kotlin where( book.price().ge(new BigDecimal(40)).not() ); where( not(book.price ge BigDecimal(40)) ) The actual generated SQL is: where tb_1_1.PRICE < ? Jimmer-sql tries to avoid directly using NOT in SQL, but the final logic is equivalent to what you want.","s":"NOT","u":"/jimmer-doc/docs/query/expression","h":"#not","p":1408},{"i":1439,"t":"+ Java Kotlin select(book.price().plus(BigDecimal.TWO)); select(table.price + BigDecimal.TWO) - Java Kotlin select(book.price().minus(BigDecimal.TWO)); select(table.price - BigDecimal.TWO) * Java Kotlin select(book.price().times(BigDecimal.TWO)); select(table.price * BigDecimal.TWO) / Java Kotlin select(book.price().div(BigDecimal.TWO)); select(table.price / BigDecimal.TWO) % Java Kotlin select(book.price().rem(BigDecimal.TWO)); select(table.price % BigDecimal.TWO)","s":"Math Operations","u":"/jimmer-doc/docs/query/expression","h":"#math-operations","p":1408},{"i":1441,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List< Tuple6< Long, Long, BigDecimal, BigDecimal, BigDecimal, BigDecimal > > tuples = sqlClient .createQuery(book) .select( book.count(), book.id().count(/* distinct */ true), book.price().sum(), book.price().min(), book.price().max(), book.price().avg() ) .execute(); val tuples = sqlClient .createQuery(Book::class) { select( count(table), count(table.id, distinct = true), sum(table.price), min(table.price), max(table.price), avg(table.price) ); } .execute() The final generated SQL is: select count(tb_1_.ID), count(distinct tb_1_.ID), sum(tb_1_.PRICE), min(tb_1_.PRICE), max(tb_1_.PRICE), avg(tb_1_.PRICE) from BOOK as tb_1_","s":"Aggregate Functions","u":"/jimmer-doc/docs/query/expression","h":"#aggregate-functions","p":1408},{"i":1443,"t":"The Coalesce statement specifies a list of expressions and returns the first non-null value. Java Kotlin BookStoreTable store = Tables.BOOK_STORE_TABLE; List results = sqlClient .createQuery(store) .select( store.website() ❶ .coalesceBuilder() .or(store.name()) ❷ .or(\"Default Value\") ❸ .build() ) .execute(); var results = sqlClient .createQuery(BookStore::class) { select( table.website .coalesce() ❶ .or(table.name) ❷ .end() ) } tip In this example, the Kotlin code is different from the Java code. In Kotlin there is no expression ❸. The Kotlin API introduces null-safety for SQL, table.name is a non-null field, so Kotlin forces us to write end() to complete the expression. This means the expression ❸ in Java code will not be used. The generated SQL is: SQL for Java SQL for Kotlin select coalesce( tb_1_.WEBSITE, tb_1_.NAME, ? ) from BOOK_STORE as tb_1_ select coalesce( tb_1_.WEBSITE, tb_1_.NAME ) from BOOK_STORE as tb_1_ Specifically, if the SQL coalesce function has only two parameters, i.e. or() is called only once in the Java code above, there is a shortcut: Java Kotlin BookStoreTable store = Tables.BOOK_STORE_TABLE; List results = sqlClient .createQuery(store) .select( store.website().coalesce(store.name()) ) .execute(); var results = sqlClient .createQuery(BookStore::class) { select( table.website.coalesce(table.name) ) } The generated SQL is: select coalesce(tb_1_.WEBSITE, tb_1_.NAME) from BOOK_STORE as tb_1_ This form is actually the most common.","s":"Coalesce","u":"/jimmer-doc/docs/query/expression","h":"#coalesce","p":1408},{"i":1445,"t":"The Contact expression concatenates strings. This example concatenates firstName and lastName of authors with a space as separator: Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; List results = sqlClient .createQuery(author) .select( author .firstName() .concat( Expression.string().value(\" \"), author.lastName() ) ) .execute(); var fullNames = sqlClient .createQuery(Author::class) { select( concat( table.firstName, value(\" \"), table.lastName ) ) } .execute() The generated SQL is: select concat( tb_1_.FIRST_NAME, ?, tb_1_.LAST_NAME ) from AUTHOR as tb_1_","s":"Concat","u":"/jimmer-doc/docs/query/expression","h":"#concat","p":1408},{"i":1447,"t":"There are two types of case expressions, simple case and searched case.","s":"Case","u":"/jimmer-doc/docs/query/expression","h":"#case","p":1408},{"i":1449,"t":"For simple case, an expression is specified at the beginning. Each WHEN branch specifies an expected value to check if the expression matches that value. Java Kotlin BookTable book = Tables.BOOK_TABLE; List results = sqlClient .createQuery(book) .select( Expression.string() .caseBuilder(book.name()) .when(\"Java in Action\", \"Matched\") .when(\"SQL in Action\", \"Matched\") .otherwise(\"Not matched\") ) .execute(); val results = sqlClient .createQuery(Book::class) { select( case(table.name) .match(\"Kotlin in Action\", \"Matched\") .match(\"SQL in Action\", \"Matched\") .otherwise(\"Not matched\") ) } .execute() The generated SQL is: select case tb_1_.NAME when ? then ? when ? then ? else ? end from BOOK as tb_1_","s":"Simple Case","u":"/jimmer-doc/docs/query/expression","h":"#simple-case","p":1408},{"i":1451,"t":"For searched case, no expression is specified at the beginning. Each WHEN branch can specify an arbitrary complex conditional expression to check if any branch logic evaluates to true. Java Kotlin BookTable book = Tables.BOOK_TABLE; List results = sqlClient .createQuery(book) .select( Expression.string() .caseBuilder() .when( book.price().lt(new BigDecimal(30)), \"Cheap\" ) .when( book.price().gt(new BigDecimal(70)), \"Expensive\" ) .otherwise(\"Appropriate\") ) .execute(); val results = sqlClient .createQuery(Book::class) { select( case() .match(table.price lt BigDecimal(30), \"Cheap\") .match(table.price gt BigDecimal(70), \"Expensive\") .otherwise(\"Appropriate\") ) } .execute() The generated SQL is: select case when tb_1_.PRICE < ? then ? when tb_1_.PRICE > ? then ? else ? end from BOOK as tb_1_","s":"Searched Case","u":"/jimmer-doc/docs/query/expression","h":"#searched-case","p":1408},{"i":1453,"t":"Pagination queries have a problem - when the data volume is large, if the pagination range is too far back (i.e. offset is too large), performance issues can occur. Therefore, Jimmer supports deep pagination optimization. Set a threshold offset-optimizing-threshold for the pagination offset. Once the offset reaches this threshold, the implementation of the pagination query is changed.","s":"Deep Pagination Optimization","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"","p":1452},{"i":1455,"t":"Using Spring Boot Starter: Modify application.yml (or application.properties), add config item offset-optimizing-threshold: jimmer: offset-optimizing-threshold: 1000 Using low-level API: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setOffsetOptimizingThreshold(1000) ...Other config omitted... .build(); val sqlClient = newKSqlClient { setOffsetOptimizingThreshold(1000) ...Other config omitted... } info If this threshold is not set, the default is Integer.MAX_VALUE, meaning this feature is disabled.","s":"Set Threshold","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"#set-threshold","p":1452},{"i":1457,"t":"To discuss this feature, focusing on the data query instead of the count query is sufficient. Let's look at this simple pagination query: Java Kotlin public List findBooks(int limit, int offset) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .select(table) .limit(limit, offset) .execute(); } fun findBooks(limit: Int, offset: Int): List = sqlClient.createQuery(Book::class) { select(table) } .limit(limit, offset) .execute() Pagination query support differs for different dialects. Oracle is more complex. See Pagination/Usage#Dialects. To simplify discussion, assume using org.babyfish.jimmer.sql.H2Dialect. Pagination queries under it generate simple SQL: When offset is less than 1000, e.g. calling findBooks(10, 90), the generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ limit ? /* 10 */ offset ? /* 90 */ When offset is greater than or equal to 1000, e.g. calling findBooks(10, 1000), the generated SQL: select optimize_.ID, optimize_.NAME, optimize_.EDITION, optimize_.PRICE, optimize_.STORE_ID from ( select tb_1_.ID optimize_core_id_ from BOOK tb_1_ limit ? /* 10 */ offset ? /* 1000 */ ) optimize_core_ inner join BOOK optimize_ on optimize_.ID = optimize_core_.optimize_core_id_ As you can see, when offset is too large, Jimmer queries ids of the page first, then converts the ids to objects. This is useful when data volume is large.","s":"Effectiveness","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"#effectiveness","p":1452},{"i":1459,"t":"For some databases (e.g. MySQL), if data volume is large, performance is poor even when querying the first page (offset is 0). In this case, simply set offset-optimizing-threshold to 0 directly.","s":"Set to 0","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"#set-to-0","p":1452},{"i":1462,"t":"For data structures, frontends and backends have different preferences. Backends prefer structured data, while frontends prefer flattened data. For IdOnly objects, Jimmer provides the @IdView annotation to easily flatten IdOnly objects into a field.","s":"IdView","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#idview","p":1460},{"i":1464,"t":"In the example entity interface, two @IdView properties are added, which are view properties. The value of these properties will be automatically synchronized with the value of the corresponding associated object. For the IdView of a collection property, the corresponding association property needs to be specified manually. Java Kotlin @Entity public interface Book { ...Other properties omitted... @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); @IdView Long storeId(); @IdView(\"authors\") List authorIds(); } @Entity interface Book { ...Other properties omitted... @ManyToOne val store: BookStore? @ManyToMany val authors: List @IdView val storeId: Long? @IdView(\"authors\") val authorsIds: List }","s":"Modify the Example Entity Interface","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#modify-the-example-entity-interface","p":1460},{"i":1466,"t":"caution View properties need to be fetched manually. allScalarFields and allTableFields will not automatically fetch view properties. Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookWithIdViews = sqlClient .createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .storeId() .authorIds() ) ) .execute(); System.out.println(bookWithIdViews); var bookWithIdViews = sqlClient .createQuery(Book::class) { where(table.edition eq 3) select( table.fetchBy { allScalarFields storeId authorIds } ) } .execute() println(bookWithIdViews) The output is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"storeId\": 1, \"authorIds\": [1,2] } ...Other objects omitted ]","s":"Fetch @IdView Properties","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#fetch-idview-properties","p":1460},{"i":1468,"t":"In some scenarios, the join table of a many-to-many association contains not only the IDs of both sides, but also some other fields. A join table with additional fields besides the two IDs cannot be directly mapped to a ManyToMany association. We have no choice but to create three entity types: the original two entities and an intermediate entity. Each side entity has a one-to-many association pointing to the intermediate entity, and the intermediate entity has two many-to-one associations pointing to the two side entities. Fortunately, Jimmer provides @ManyToManyView to abstract a many-to-many association between the two side entities on top of this three-entity structure. To better demonstrate, instead of using books and authors, a more realistic example with students, courses, and learning_link tables is used.","s":"ManyToManyView","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#manytomanyview","p":1460},{"i":1470,"t":"For convenience, H2 database is used here. First create the table structure and initialize data with: drop table course if exists; drop table learning_link if exists; drop table student if exists; create table course( id identity(100, 1) not null, name varchar(50) not null, academic_credit integer not null ); create table student( id identity(100, 1) not null, name varchar(50) not null ); create table learning_link( id identity(100, 1) not null, student_id int not null, course_id int not null, score int null ); alter table learning_link add constraint fk_learning_link__student foreign key(student_id) references student(id) on delete cascade; alter table learning_link add constraint fk_learning_link__course foreign key(course_id) references course(id) on delete cascade; insert into student(id, name) values (1, 'John'), (2, 'Jane'), (3, 'Jack'), (4, 'Jill'), (5, 'Joe'); insert into course(id, name, academic_credit) values (1, 'Math', 100), (2, 'English', 100), (3, 'History', 100), (4, 'Science', 100), (5, 'Art', 100); insert into learning_link(student_id, course_id, score) values (1, 1, 100), (1, 2, 90), (1, 3, 80), (1, 4, 70), (1, 5, 60), (2, 1, 90), (2, 2, 80), (2, 3, 70), (2, 4, 60), (2, 5, 100), (3, 1, 80), (3, 2, 70), (3, 3, 60), (3, 4, 100), (3, 5, 90), (4, 1, 70), (4, 2, 60), (4, 3, 100), (4, 4, 90), (4, 5, 80), (5, 1, 60), (5, 2, 100), (5, 3, 90), (5, 4, 80), (5, 5, 70);","s":"Prepare Data","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#prepare-data","p":1460},{"i":1472,"t":"Student Java Kotlin @Entity public interface Student { @Id long id(); String name(); @OneToMany(mappedBy = \"student\") List learningLinks(); // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `course` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"course\") List courses(); } @Entity interface Student { @Id val id: Long val name: String @OneToMany(mappedBy = \"student\") val learningLinks: List // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `course` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"course\") val courses: List } Course Java Kotlin @Entity public interface Course { @Id long id(); String name(); int academicCredit(); @OneToMany(mappedBy = \"course\") List learningLinks(); // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `student` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"student\") List students(); } @Entity interface Course { @Id val id: Long val name: String val academicCredit: Int @OneToMany(mappedBy = \"course\") val learningLinks: List // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `student` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"student\") val students: List } Intermediate Entity LearningLink Java Kotlin @Entity public interface LearningLink { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); // Many-to-one, points to Student entity @ManyToOne @OnDissociate(DissociateAction.DELETE) Student student(); // Many-to-one, points to Course entity @ManyToOne @OnDissociate(DissociateAction.DELETE) Course course(); Integer score(); } @Entity interface LearningLink { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long // Many-to-one, points to Student entity @ManyToOne @OnDissociate(DissociateAction.DELETE) val student: Student // Many-to-one, points to Course entity @ManyToOne @OnDissociate(DissociateAction.DELETE) val course: Course val score: Int }","s":"Define Entities","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#define-entities","p":1460},{"i":1474,"t":"With the introduction of the intermediate entity, Student and Course entities are no longer directly associated. Although they can be indirectly associated through a Student->LearningLink->Course path, the path is too long. Besides, the intermediate LearningLink entity should be hidden as much as possible, only used when reading/writing scores. @ManyToManyView properties (e.g. Student.courses in this example) can be used in object fetchers to reduce the path length. For example, the following query gets all course names for the student with id 1: Java Kotlin Student student = sqlClient .findNullable( 1L, Fetchers.STUDENT_FETCHER .name() .courses( Fetchers.COURSE_FETCHER .name() ) ) System.out.println(student); val student = sqlClient .findNullable( 1L, newFetcher(Student::class).by { name() courses { name() } } ) println(student) The generated SQL is: Query Student select tb_1_.ID, tb_1_.NAME from STUDENT tb_1_ where tb_1_.ID = ? /* 1 */ Query LearningLink select tb_1_.STUDENT_ID, tb_1_.ID, tb_1_.COURSE_ID from LEARNING_LINK tb_1_ where tb_1_.STUDENT_ID in (? /* 1 */) Query Course select tb_1_.ID, tb_1_.NAME from COURSE tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */, ? /* 3 */, ? /* 4 */, ? /* 5 */ ) The output is: { \"id\": 1, \"name\": \"John\", \"courses\": [ { \"id\": 1, \"name\": \"Math\" }, { \"id\": 2, \"name\": \"English\" }, { \"id\": 3, \"name\": \"History\" }, { \"id\": 4, \"name\": \"Science\" }, { \"id\": 5, \"name\": \"Art\" } ] } With many-to-many view properties, associated objects can be operated as conveniently as if the intermediate entity did not exist at all.","s":"Fetch @ManyToManyView Properties","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#fetch-manytomanyview-properties","p":1460},{"i":1476,"t":"In the previous article, we mentioned that Jimmer can not only auto-generate count-query from data-query, but also auto-optimize the count-query. Since count-query only cares about total row count regardless of order and format, some table joins in the original data-query may not need to be copied over to count-query. Jimmer will auto-optimize count-query to copy over as few table joins as possible from the original data-query.","s":"Table Join Optimization","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"","p":1475},{"i":1478,"t":"Table joins used by the where clause cannot be optimized. That is, only table joins used solely by the select or order by clause of the top-level query can be optimized. Table joins based on collection associations (one-to-many, many-to-many) cannot be optimized. Collection associations lead to duplicate data, thus affecting row count. So these table joins must be copied to count-query and cannot be optimized. Table joins based on reference associations (one-to-one, many-to-one) may be optimized, if any of the following conditions is met: Join type is left outer join Although join type is inner join, the association is based on non-null real foreign key. So-called real foreign key means there is a foreign key constraint in the database. See Real vs Fake Foreign Keys. In summary, to determine whether a table join in the original data-query can be automatically removed in the count-query, use the following optimization rules: AND Is based on reference association, i.e. many-to-one or one-to-one Is used solely by select or orderBy clause of top-level query OR Is left outer join Association is non-null and foreign key constraint exists in database","s":"Optimization Rules","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"#optimization-rules","p":1475},{"i":1480,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; ConfigurableRootQuery query = sqlClient .createQuery(book) .where( book.price().between( new BigDecimal(20), new BigDecimal(30) ) ) .orderBy(book.store().name()) .orderBy(book.name()) .select(book); int rowCount = query.fetchUnlimitedCount(); val query = sqlClient.createQuery(Book::class) { where( table.price.between( BigDecimal(20), BigDecimal(30) ) ) orderBy(table.store.name) // α orderBy(table.name) select(table) } val rowCount = query.fetchUnlimitedCount() Note α: Although table.store() is only used by orderBy clause without being used by where clause, table.store() is inner join Book.store association is nullable So the optimization rules do not apply. The count-query still needs to retain table.store() and ultimately generates JOIN clause in SQL: select count(tb_1_.ID) from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ?","s":"Non-Optimizable Scenario","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"#non-optimizable-scenario","p":1475},{"i":1482,"t":"For the unoptimizable case discussed above, any of the following modifications will enable optimization: Change Book.store association to non-null Use left outer join Here we choose the second approach, left outer join: Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; ConfigurableRootQuery query = sqlClient .createQuery(book) .where( book.price().between( new BigDecimal(20), new BigDecimal(30) ) ) .orderBy(book.store(JoinType.LEFT).name()) .orderBy(book.name()) .select(book); int rowCount = query.fetchUnlimitedCount(); val query = sqlClient.createQuery(Book::class) { where( table.price.between( BigDecimal(20), BigDecimal(30) ) ) orderBy(table.`store?`.name) // α orderBy(table.name) select(table) } val rowCount = query.fetchUnlimitedCount() Now optimization can take effect. The final count-query generates SQL: select count(tb_1_.ID) from BOOK as tb_1_ where tb_1_.PRICE between ? and ?","s":"Optimizable Scenario","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"#optimizable-scenario","p":1475},{"i":1484,"t":"A common requirement is to handle self-associated property. From a database perspective, self-associated property means a table's foreign key references itself. From an object model perspective, it represents a tree. The difficulty of self-associated properties is that the object depth is uncontrollable, theoretically infinite. Jimmer provides great support for this.","s":"Recursive Query","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"","p":1483},{"i":1486,"t":"Define the entity interface: Java Kotlin @Entity public interface TreeNode { @Id @Column(name = \"NODE_ID\") long id(); String name(); @Null @ManyToOne TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } @Entity interface TreeNode { @Id @Column(name = \"NODE_ID\") val id: Long val name: String @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List } Prepare the database: create table tree_node( node_id bigint not null, name varchar(20) not null, parent_id bigint ); alter table tree_node add constraint pk_tree_node primary key(node_id); alter table tree_node add constraint uq_tree_node unique(parent_id, name); alter table tree_node add constraint fk_tree_node__parent foreign key(parent_id) references tree_node(node_id); insert into tree_node( node_id, name, parent_id ) values (1, 'Home', null), (2, 'Food', 1), (3, 'Drinks', 2), (4, 'Coca Cola', 3), (5, 'Fanta', 3), (6, 'Bread', 2), (7, 'Baguette', 6), (8, 'Ciabatta', 6), (9, 'Clothing', 1), (10, 'Woman', 9), (11, 'Casual wear', 10), (12, 'Dress', 11), (13, 'Miniskirt', 11), (14, 'Jeans', 11), (15, 'Formal wear', 10), (16, 'Suit', 15), (17, 'Shirt', 15), (18, 'Man', 9), (19, 'Casual wear', 18), (20, 'Jacket', 19), (21, 'Jeans', 19), (22, 'Formal wear', 18), (23, 'Suit', 22), (24, 'Shirt', 22) ;","s":"Model and Data Preparation","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#model-and-data-preparation","p":1483},{"i":1488,"t":"Top-down, fetch unlimited layers: Java Kotlin TreeNodeTable node = Tables.TREE_NODE_TABLE; List treeNodes = sqlClient .createQuery(node) .where(node.parentId().isNull()) .select( node.fetch( Fetchers.TREE_NODE_FETCHER .name() .recursiveChildNodes() ) ) .execute(); val treeNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*`() } ) } .execute() info Here, recursiveChildNodes in Java code and childNodes* in Kotlin code represent recursive queries. Jimmer automatically discovers self-associated properties in entities and generates such methods at compile time for users to invoke. Recursive queries do not require specifying the shape of associated objects because recursive queries are very special - the shape of associated objects is the shape of the current object itself. 6 SQL statements are generated: Query root nodes select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID is null Fetch layer 1 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?) Fetch layer 2 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?) Fetch layer 3 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?) Fetch layer 4 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?, ?, ?, ?, ?) Fetch layer 5 (This step does not query any data and the recursive query downstairs ends) select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?, ?, ?, ?, ?, ?) The printed result is (original compact, formatted for readability): { \"id\": 1, \"name\": \"Home\", \"childNodes\": [ { \"id\": 9, \"name\": \"Clothing\", \"childNodes\": [ { \"id\": 18, \"name\": \"Man\", \"childNodes\": [ { \"id\": 19, \"name\": \"Casual wear\", \"childNodes\": [ { \"id\": 20, \"name\": \"Jacket\", \"childNodes\": [] }, { \"id\": 21, \"name\": \"Jeans\", \"childNodes\": [] } ] }, { \"id\": 22, \"name\": \"Formal wear\", \"childNodes\": [ { \"id\": 24, \"name\": \"Shirt\", \"childNodes\": [] }, { \"id\": 23, \"name\": \"Suit\", \"childNodes\": [] } ] } ] }, { \"id\": 10, \"name\": \"Woman\", \"childNodes\": [ { \"id\": 11, \"name\": \"Casual wear\", \"childNodes\": [ { \"id\": 12, \"name\": \"Dress\", \"childNodes\": [] }, { \"id\": 14, \"name\": \"Jeans\", \"childNodes\": [] }, { \"id\": 13, \"name\": \"Miniskirt\", \"childNodes\": [] } ] }, { \"id\": 15, \"name\": \"Formal wear\", \"childNodes\": [ { \"id\": 17, \"name\": \"Shirt\", \"childNodes\": [] }, { \"id\": 16, \"name\": \"Suit\", \"childNodes\": [] } ] } ] } ] }, { \"id\": 2, \"name\": \"Food\", \"childNodes\": [ { \"id\": 6, \"name\": \"Bread\", \"childNodes\": [ { \"id\": 7, \"name\": \"Baguette\", \"childNodes\": [] }, { \"id\": 8, \"name\": \"Ciabatta\", \"childNodes\": [] } ] }, { \"id\": 3, \"name\": \"Drinks\", \"childNodes\": [ { \"id\": 4, \"name\": \"Coca Cola\", \"childNodes\": [] }, { \"id\": 5, \"name\": \"Fanta\", \"childNodes\": [] } ] } ] } ] }","s":"Unlimited Recursion","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#unlimited-recursion","p":1483},{"i":1490,"t":"Top-down, fetch two layers: Java Kotlin TreeNodeTable node = Tables.TREE_NODE_TABLE; List treeNodes = sqlClient .createQuery(node) .where(node.parentId().isNull()) .select( node.fetch( Fetchers.TREE_NODE_FETCHER .name() .recursiveChildNodes( it -> it.depth(2) ) ) ) .execute(); val treeNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { depth(2) } } ) } .execute() 3 SQLs are generated: Main query to fetch root nodes (layer 0) select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID is null Fetch layer 1 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?) Fetch layer 2 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?) The printed result is (original compact, formatted for readability): { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":9, \"name\":\"Clothing\", \"childNodes\":[ {\"id\":18,\"name\":\"Man\"}, {\"id\":10,\"name\":\"Woman\"} ] },{ \"id\":2, \"name\":\"Food\", \"childNodes\":[ {\"id\":6,\"name\":\"Bread\"}, {\"id\":3,\"name\":\"Drinks\"} ] } ] } info Note that the 4 marked objects do not show childNodes as [], but lack the childNodes property altogether. This indicates not knowing at all whether there are deeper child nodes, because the recursive process was prematurely terminated manually.","s":"Limited Depth","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#limited-depth","p":1483},{"i":1492,"t":"Top-down, fetch unlimited layers. But for the node named \"Clothing\", stop recursion. Java Kotlin TreeNodeTable node = Tables.TREE_NODE_TABLE; List treeNodes = sqlClient .createQuery(node) .where(node.parentId().isNull()) .select( node.fetch( Fetchers.TREE_NODE_FETCHER .name() .recursiveChildNodes( it -> it.recursive(args -> !args.getEntity().name().equals(\"Clothing\") ) ) ) ) .execute(); val treeNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { recursive { entity.name != \"Clothing\" } } } ) } .execute() In the above code, the parameter args of it.recursive(args) is an object providing two properties: args.getEntity(): The current node object. args.getDepth(): The current node depth. 0 for nodes obtained directly from the main query, incrementally increases with recursion depth. The return value decided by the user: A boolean variable that decides whether to recursively fetch for the current node. The above code means all nodes will be recursively fetched except the Clothing node. 4 SQLs are generated: Query root objects select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID is null Fetch layer 1 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?) Fetch layer 2 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where /* * Home node has two child nodes: * \"Food\" and \"Clothing\", * * However, \"Clothing is excluded by user, * so `in(?)` is used here, not `in(?, ?)` */ tb_1_.PARENT_ID in (?) Fetch layer 3 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?) Fetch layer 4 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?) The printed result is (original compact, formatted for readability): { \"id\":1, \"name\":\"Home\", \"childNodes\":[ {\"id\":9,\"name\":\"Clothing\"}, { \"id\":2, \"name\":\"Food\", \"childNodes\":[ { \"id\":6, \"name\":\"Bread\", \"childNodes\":[ {\"id\":7,\"name\":\"Baguette\",\"childNodes\":[]}, {\"id\":8,\"name\":\"Ciabatta\",\"childNodes\":[]} ] },{ \"id\":3, \"name\":\"Drinks\", \"childNodes\":[ {\"id\":4,\"name\":\"Coca Cola\",\"childNodes\":[]}, {\"id\":5,\"name\":\"Fanta\",\"childNodes\":[]} ] } ] } ] } info Note that the marked object does not show childNodes as [], but lack the childNodes property altogether. This indicates not knowing at all whether there are deeper child nodes, because the recursive process was prematurely terminated manually.","s":"Control Recursion Per Node","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#control-recursion-per-node","p":1483},{"i":1494,"t":"Jimmer supports recursive queries on multiple association properties, as below Java Kotlin Tree treeNode = sqlClient .findById( Fetchers.TREE_NODE_FETCHER .name() .recursiveParent() .recursiveChildNodes(), 10L ); val treeNodes = sqlClient .findById( newFetcher(TreeNode::class) { name() `parent*`() `childNodes*`() } ) This example performs recursive queries on two associated properties: parent: Starting from the current node, keep querying upwards for the parent node until the root node is queried childNodes: Starting from the current node, keep querying downwards for child nodes until the deepest child node is queried When executed, the following 6 SQL statements are generated: Query current node select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.NODE_ID = ? /* 10 */ Query first layer parent node upstairs select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.NODE_ID = ? /* 9 */ Query second layer parent node upstairs (This step will query the root node and the recursive query upstairs ends) select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.NODE_ID = ? /* 1 */ Query first layer child nodes downstairs select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE tb_1_ where tb_1_.PARENT_ID = ? /* 10 */ Query second layer child nodes downstairs select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE tb_1_ where tb_1_.PARENT_ID in ( ? /* 11 */, ? /* 15 */ ) Query third layer child nodes downstairs (This step does not query any data and the recursive query downstairs ends) select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE tb_1_ where tb_1_.PARENT_ID in ( ? /* 12 */, ? /* 13 */, ? /* 14 */, ? /* 16 */, ? /* 17 */ ) Finally, the query result is: { \"id\":10, \"name\":\"Woman\", \"parent\":{ // Recursive query upstairs \"id\":9, \"name\":\"Clothing\", \"parent\":{ \"id\":1, \"name\":\"Home\", \"parent\":null } }, \"childNodes\":[ // Recursive query downstairs { \"id\":11, \"name\":\"Casual wear\", \"childNodes\":[ { \"id\":12, \"name\":\"Dress\", \"childNodes\":[] }, { \"id\":13, \"name\":\"Miniskirt\", \"childNodes\":[] }, { \"id\":14, \"name\":\"Jeans\", \"childNodes\":[] } ] }, { \"id\":15, \"name\":\"Formal wear\", \"childNodes\":[ { \"id\":16, \"name\":\"Suit\", \"childNodes\":[] }, { \"id\":17, \"name\":\"Shirt\", \"childNodes\":[] } ] } ] } It is not difficult to see from the correct running of this example that the recursive path of the parent direction and the recursive path of the childNodes direction are completely independent. The recursive query upstairs and downstairs will not be mixed or alternate. Therefore, we can slightly correct the previous discussion on why recursive queries do not require specifying the associated object format: info Associated object format = All properties in the current object format that are not recursively queried (whether associated properties or not) + The currently recursively queried property (excluding other recursively queried properties)","s":"Recursion on Multiple Properties","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#recursion-on-multiple-properties","p":1483},{"i":1498,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().in(sqlClient .createSubQuery(author) .where(author.firstName().eq(\"Alex\")) .select(author.books().id()) ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id valueIn subQuery(Author::class) { where(table.firstName eq \"Alex\") select(table.books.id) } ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME = ? )","s":"IN expression based on single column","u":"/jimmer-doc/docs/query/sub-query","h":"#in-expression-based-on-single-column","p":1495},{"i":1500,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List newestBooks = sqlClient .createQuery(book) .where( Expression.tuple( book.name(), book.edition() ).in(sqlClient .createSubQuery(book) .groupBy(book.name()) .select( book.name(), book.edition().max() ) ) ) .select(book) .execute(); val newestBooks = sqlClient .createQuery(Book::class) { where( tuple( table.name, table.edition ) valueIn subQuery(Book::class) { groupBy(table.name) select( table.name, max(table.edition).asNonNull() ) } ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( select tb_2_.NAME, max(tb_2_.EDITION) from BOOK as tb_2_ group by tb_2_.NAME )","s":"IN expression based on multiple columns","u":"/jimmer-doc/docs/query/sub-query","h":"#in-expression-based-on-multiple-columns","p":1495},{"i":1502,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List newestBooks = sqlClient .createQuery(book) .where( book.price().gt(sqlClient .createSubQuery(book) .groupBy(book.name()) .select( book .price() .avg() .coalesce(BigDecimal.ZERO) ) ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.price gt subQuery(Book::class) { select( avg(table.price) .coalesce(BigDecimal.ZERO) ) } ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.PRICE > ( select coalesce(avg(tb_2_.PRICE), ?) from BOOK as tb_2_ )","s":"Treat subquery as simple value","u":"/jimmer-doc/docs/query/sub-query","h":"#treat-subquery-as-simple-value","p":1495},{"i":1504,"t":"Java Kotlin BookStoreTable store = Tables.BOOK_STORE_TABLE; BookTable book = Tables.BOOK_TABLE; MutableRootQuery query = sqlClient.createQuery(store); TypedSubQuery subQuery = sqlClient .createSubQuery(book) .where(book.store().eq(store)) .select( book .price() .avg() .coalesce(BigDecimal.ZERO) ); List> storeAvgPriceTuples = query .orderBy( subQuery.desc() ) .select( store, subQuery ) .execute(); val storeAvgPriceTuples = sqlClient .createQuery(BookStore::class) { val avgPriceSubQuery = subQuery(Book::class) { where(table.store eq parentTable) select(avg(table.price)) } orderBy( avgPriceSubQuery.desc() ) select( table, avgPriceSubQuery ) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE, ( select coalesce(avg(tb_2_.PRICE), ?) from BOOK as tb_2_ ) from BOOK_STORE as tb_1_ order by ( select coalesce(avg(tb_2_.PRICE), ?) from BOOK as tb_2_ ) desc","s":"Use subquery in select and orderBy clauses","u":"/jimmer-doc/docs/query/sub-query","h":"#use-subquery-in-select-and-orderby-clauses","p":1495},{"i":1506,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().eq(sqlClient .createSubQuery(author) .where( author.firstName().in( Arrays.asList(\"Alex\", \"Bill\") ) ) .select(author.books().id()) .any() ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id eq any( subQuery(Author::class) { where( table.firstName valueIn listOf( \"Alex\", \"Bill\" ) ) select(table.id) } ) ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID = any( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME in (?, ?) )","s":"Use ANY operator","u":"/jimmer-doc/docs/query/sub-query","h":"#use-any-operator","p":1495},{"i":1508,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().ne(sqlClient .createSubQuery(author) .where( author.firstName().in( Arrays.asList(\"Alex\", \"Bill\") ) ) .select(author.books().id()) .all() ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id ne all( subQuery(Author::class) { where( table.firstName valueIn listOf( \"Alex\", \"Bill\" ) ) select(table.id) } ) ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID = all( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME in (?, ?) )","s":"Use ALL operator","u":"/jimmer-doc/docs/query/sub-query","h":"#use-all-operator","p":1495},{"i":1510,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where(sqlClient .createSubQuery(author) .where( author.books().eq(book), author.firstName().eq(\"Alex\") ) .select(author) .exists() ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( exists( subQuery(Author::class) { where( table.books eq parentTable, table.firstName eq \"Alex\" ) select(table) } ) ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where exists ( select 1 from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_1_.ID = tb_3_.BOOK_ID and tb_2_.FIRST_NAME = ? ) info Note that in the final SQL, the selected column in the subquery is the constant 1, not what is specified in the Java/Kotlin code. This is because the exists operator only cares if the subquery can match data, not what columns are selected. Whatever you select in the Java/Kotlin code will be ignored.","s":"Use EXISTS operator","u":"/jimmer-doc/docs/query/sub-query","h":"#use-exists-operator","p":1495},{"i":1512,"t":"The last example in previous section is exists subquery where whatever is selected in Java code gets ignored. In that case, why specify the return type for exists subqueries in Java code? Therefore, jimmer-sql supports untyped subqueries (wild subqueries). Unlike normal subqueries, for wild subqueries the final select() call is no longer needed, i.e. no return type. Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where(sqlClient .createSubQuery(author) .where( author.books().eq(book), author.firstName().eq(\"Alex\") ) // No select here .exists() ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( exists( wildSubQuery(Author::class) { where( table.books eq parentTable, table.firstName eq \"Alex\" ) // No select here } ) ) select(table) } .execute() The final SQL remains the same: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where exists ( select 1 from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_1_.ID = tb_3_.BOOK_ID and tb_2_.FIRST_NAME = ? ) info The only value of untyped subqueries is when used with exists operator.","s":"Untyped Subqueries","u":"/jimmer-doc/docs/query/sub-query","h":"#untyped-subqueries","p":1495},{"i":1514,"t":"This section only enumerates the usage methods of the most important functions in Jimmer to allow readers to build a preliminary impression. Therefore, this section only provides the usage and reference links of relevant functions without in-depth discussion. In this section, we take a quick tour of the three most core features of Jimmer Query arbitrary data structures Save arbitrary data structures Implement arbitrarily complex dynamic queries","s":"Quick View ★","u":"/jimmer-doc/docs/quick-view/","h":"","p":1513},{"i":1517,"t":"Unlike native SQL, in the DSL provided by Jimmer, the select statement comes after where, orderBy, groupBy, having, etc. For example: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) ❶ .where(table.name().eq(\"SQL in Action\")) .orderBy(table.name().asc(), table.edition().desc()) .select(table) ❷ .limit(10, 100) .execute(); ❸ val books = sqlClient .createQuery(Book::class) { ❶ where(table.name eq \"SQL in Action\") orderBy(table.name.asc(), table.edition.desc()) select(table) ❷ } .limit(10, 100) .execute() ❸ tip Putting select after is not invented by Jimmer. This style was first brought to mainstream by LINQ introduced in C# 3.5. This style has innate advantages for building strongly typed DSL frameworks, so Jimmer naturally adopts it.","s":"Select-After Style","u":"/jimmer-doc/docs/query/usage","h":"#select-after-style","p":1515},{"i":1519,"t":"Now let's explain the code: ❶ Create the query, get a mutable query object. Operations targeting this object continue until ❷. A mutable query object means any operations like where, orderBy, groupBy, having directly modify the current query object. ❷ Call select, convert the mutable query object into an immutable one. Operations targeting this object continue until ❸. An immutable query object means any operations like distinct, limit, forUpdate, reselect, withoutSortingAndPaging, union, unionAll, minus, intersect, do not change the current object but create a new one. For example (to be concise, this pseudo-code uses Kotlin): val query = sqlClient.createQuery(Book::class) { where(...) orderBy(...) select(...) } val query1 = query.limit(10, 0); val query2 = query.limit(10, 1); val query3 = query.limit(10, 2); Here query is the original query, query1, query2, query3 are other queries created based on it. limit does not change query itself but creates new immutable query objects. Finally, query1, query2, query3 share the same filters, sorting and structure projection as query, only differing in paging range. They can coexist without interfering with each other. Also, the mutable query before select has no return type, while the immutable query after select has a return type. That is, select assigns the final return type to the query. ❸ Call execute to execute the query and return data. Before this step, no matter how the DSL is operated and tuned, no SQL operations will be executed. Besides execute, there are other methods to execute queries: fetchOne: Assume the query returns exactly one row, get that row. Throw exception if 0 or more rows are returned during actual execution. fetchOneOrNull: Assume the query returns 0 or 1 row, get that row or null. Throw exception if more rows are returned during actual execution. fetchOptional: Similar to fetchOneOrNull but returns java.util.Optional instead of null | T. caution This API only exists in Java API, not in Kotlin API since Kotlin does not need java.util.Optional. map: Execute directly and do an additional collection map operation at JVM level on top of the returned raw collection. forEach: If returning too much data to avoid materializing a large collection, forEach can be called with a callback to traverse all data. This is what people often refer to as cursor queries. count: Based on the original data query written by users, automatically generate the count aggregate query needed for paging, execute and get total rows before paging. info This is a smart and advanced operation, please see Paging. tip All the methods above to execute queries have two overloaded versions: Parameterless version (as shown in the example) utilizes Jimmer's connection management (usually integrating with Spring transaction management) to get JDBC connection and execute. Version with a parameter accepting a JDBC connection. In special cases developers can discard Jimmer's connection management (usually integrating with Spring transaction management) and execute on a specified JDBC connection. Now the process can be summarized as: +----------------------+ | ❶ createQuery | +-----------+----------+ | Mutable Query (Operations like where, orderBy directly modify the query) | | \\|/ +----------------------+ | ❷ select | +-----------+----------+ | Immutable Query (Operations like limit, distinct create new queries without modifying current one) | | \\|/ +----------------------+ | ❸ execute or others | +-----------+----------+ | \\|/ Execution Result (Result type is specified by ❷ select)","s":"Code Structure","u":"/jimmer-doc/docs/query/usage","h":"#code-structure","p":1515},{"i":1522,"t":"From the previous article, we know Jimmer SQL DSL is inherently designed for arbitrary complex dynamic queries, completely different from other frameworks' SQL DSLs that only provide strong typing experience. But there are two issues: With more and more parameters introduced in the previous article, the method signatures become less Java-friendly. We urgently need to encapsulate all the query parameters into one object. I'm really lazy. I want to achieve all the capabilities introduced in the previous article, but I don't want to write those code. I just want to write one line of code. Jimmer's built-in DTO language can quickly solve the above two problems.","s":"Can It Be Simpler","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#can-it-be-simpler","p":1520},{"i":1524,"t":"Since in the article Query Arbitrary Shape/Exposing Features/Return Output DTO, we have already had some understanding about the DTO language when introducing Output DTO, this article does not repeat it. Install the DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This step is not required but highly recommended) Create a new directory src/main/dto Create a file Book.dto under src/main/dto and write the code below: Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto specification BookSpecification { like/i(name) ge(price) // Default alias: minPrice le(price) // Default alias: maxPrice flat(store) { as(^ -> store) { like/i(name) like/i(website) } } flat(authors) { like/i(firstName, lastName) as authorName gender as authorGender } } ...Omit other DTO type definitions... info Different from the Output/Input DTO we discussed before, here the query Specification DTO uses the specification modifier. The QBE functions used extensively inside this Specification DTO are self-explanatory. As this article belongs to the quick tour section, we do not explain them in detail.","s":"Define Specification DTO","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#define-specification-dto","p":1520},{"i":1526,"t":"After compiling the project, Jimmer will automatically generate the following code: Java Kotlin BookSpecification.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class BookSpecification implements JSpecification { ❷ @Nullable private String name; @Nullable private BigDecimal minPrice; @Nullable private BigDecimal maxPrice; @Nullable private String storeName; @Nullable private String storeWebsite; @Nullable private String authorName; @Nullable private Gender authorGender; @Override public void applyTo(SpecificationArgs args) { ❸ ...Omit complex dynamic query logic... } ...Omit getters, setters, hashCode, equals, toString... } BookSpecification.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class BookSpecification( val name: String? = null, val minPrice: BigDecimal? = null, val maxPrice: BigDecimal? = null, val storeName: String? = null, val storeWebsite: String? = null, val authorName: String? = null, val authorGender: Gender? = null ) : KSpecification { ❷ override applyTo(args: KSpecificationArgs) { ❸ ...Omit complex dynamic query logic... } } ❶ Reminds developers that this class is auto-generated by Jimmer at compile time ❷ Interface implemented by the Specification DTO ❸ This class knows how to generate SQL predicates","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#generated-code","p":1520},{"i":1528,"t":"Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( BookSpecification specification, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(specification) .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( specification: BookSpecification, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(specification) select(table.fetch(table)) } .execute() } We can see that with only one line of code, complex dynamic queries can be achieved. It has the same capabilities as the last example in the previous article. No need to repeat here.","s":"Usage","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#usage","p":1520},{"i":1531,"t":"Although Jimmer entities are strongly typed, they are also dynamic and can express the ever-changing shape of data structures. Therefore, Jimmer supports ObjectFetcher, which can control the shape of the queried data structure and then uniformly return Jimmer entities. This is an extremely similar concept to GraphQL, but there are huge differences: GraphQL is an application layer protocol based on HTTP that can only expose this capability by building HTTP services, and only HTTP clients can enjoy this capability. For Jimmer, the ability to query arbitrary shapes is an inherent behavior of ORM that can be used programmed anywhere. You can use it to expose GraphQL services. As shown in the content of this section, you can also expose REST services. It can even be used within applications without crossing any remote boundaries.","s":"Basic Concepts","u":"/jimmer-doc/docs/quick-view/fetch/","h":"#basic-concepts","p":1529},{"i":1533,"t":"Java Kotlin Your browser does not support the video tag. Your browser does not support the video tag. info Compare to GraphQL GraphQL is based on HTTP services, which can only be experienced if it crosses the boundaries of HTTP services. In Jimmer, this is the underlying API for ORM, and you can use this capability in any code logic. Until now, the GraphQL protocol does not support recursive queries on self-associated properties with infinite depth; And Jimmer supports","s":"Demo","u":"/jimmer-doc/docs/quick-view/fetch/","h":"#demo","p":1529},{"i":1535,"t":"Jimmer supports strongly typed SQL DSL. tip Note that unlike most frameworks that use strongly typed DSLs, Jimmer's strongly typed DSL is not only for compile-time safety assurance and IDE intelligent prompt experience of SQL statements, but also for solving the problem of table joins and subqueries in native SQL. They are too cumbersome so jimmer gives them higher abstractions. After giving table joins and subqueries higher abstractions, building arbitrary complex dynamic queries with Jimmer becomes very easy. From the beginning, Jimmer is designed for easy construction of arbitrary complex dynamic queries. In addition, for the powerful non-sql-standard features owned by specific database products, Jimmer's SQL DSL can embed Native SQL fragments without the abstraction of the strongly typed DSL affecting developers' full use of the special features of the data. (This part of the function will not be introduced in the quick preview. Interested supervisors please check Query/Native Expressions)","s":"3. Arbitrary Dynamic Query","u":"/jimmer-doc/docs/quick-view/dsl/","h":"","p":1534},{"i":1537,"t":"Through the introduction of the previous article, we quickly previewed Jimmer's powerful ability to query arbitrary data structures at will. Jimmer entities are both strongly typed and dynamic. This dynamicity can easily express any data structure and return it directly. This eliminates DTO explosions However, for client developers, getting a dynamic data structure that is possible at all is a very painful thing. The client wants each query API to precisely define the type of its returned data format. To this end, Jimmer provides two methods, both of which can provide first-class API support for clients. Directly return dynamic entities As a comprehensive solution, Jimmer is not limited to ORM. It generates client code for HTTP clients. In the generated client code, precise DTO types are defined for each specific data structure. tip If the service itself does not use the query results, but directly as an HTTP Response, it is suitable to use this method. Jimmer supports a programming language called DTO that can quickly define DTO types for output data structures at extremely low cost. tip When any of the following is met, this method can be adopted. The query results are not intended to be returned directly as HTTP Response, but the service itself uses them. At this point, the business code that uses the query results does not want to get dynamic entities with slightly weaker compile-time safety (although Jimmer entities are still strongly typed). The front-end team does not accept multiple interrelated objects and requires all non-collection association attributes to be flat operated to form an ultra-large orphan object, which seems very stubborn. (This situation will be introduced in detail in related chapters, not discussed in depth here).","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/fetch/export/","h":"","p":1536},{"i":1539,"t":"The comparison is as below: Return Entities Directly Use DTO Language Similarities Both can present DTO type definitions for the return type of each API to client developers Both can generate online OpenApi docs and TypeScript RPC code Both can show information in code comments to clients Differences Directly return entities (Easy) Need to use DTO language to quickly generate DTO types Need @FetchBy annotation in RestController to supplement type info for entity types Directly develop RestController based on the generated DTO types (Easy) More oriented to external API exposure Both external exposure and internal use are applicable tip No matter how users choose, Jimmer can elegantly solve the DTO Explosion Problem with development costs unimaginable in other JVM stacks.","s":"Comparison","u":"/jimmer-doc/docs/quick-view/fetch/export/comparison","h":"","p":1538},{"i":1542,"t":"Pagination query is a very characteristic function of Jimmer, which can greatly improve development efficiency. Pagination requires executing two SQL queries: Query the total number of rows that meet the criteria, the result of which can calculate how many pages there are in total, and whether the user's page number is out of bounds. info For discussion purposes, Jimmer refers to this SQL as count-query. Query all data within the current page, the number of returned data rows does not exceed the page size, and skip all data from previous pages. info For discussion purposes, Jimmer refers to this SQL as data-query. tip Jimmer's feature: The developer only needs to write the data-query (actual data-query without limit and offset), and the framework automatically generates the count-query. Not only can Jimmer automatically generate count-query, it can also optimize count-query. This optimization will be discussed in next article.","s":"Features of Jimmer Pagination","u":"/jimmer-doc/docs/query/paging/usage","h":"#features-of-jimmer-pagination","p":1540},{"i":1544,"t":"When used with Spring Data, developers derive custom Repository interfaces from JRepository/KRepository, and there are two options for adding query methods to the custom interfaces: Declare abstract methods according to certain conventions, and let Jimmer automatically implement them. caution This usage is too simple, hiding all details, and is not suitable for discussing pagination here. You can check Spring Section/Spring Data Style/Abstract Methods to learn how to implement pagination queries in this way. Directly define default methods in the custom interface and implement the query logic yourself. Java Kotlin BookRepository.java import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; ...other imports omitted... public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page findBooks( Pageable pageable, @Nullable String name, @Nullable String storeName, ) { return sql() .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) ❶ .select(table) .fetchPage( ❷ pageable.getPageNumber(), pageable.getPageSize() SpringPageFactory.getInstance() ); } } BookRepository.kt import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable ...other imports omitted... interface BookRepository : KRepository { fun findBooks( pageable: Pageable, name: String? = null, storeName: String? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } storeName?.takeIf { it.isNotEmpty() }?.let { where(table.store.name eq it) } orderBy(pageable.sort) ❶ select(table) } .fetchSpringPage(pageable) ❷ } ❶ Since Spring Data's Pageable contains dynamic sorting, dynamic sorting needs to be applied. ❷ Pagination query, returns org.springframework.data.domain.Page type of object Jimmer pagination can use any Page object, whether it's Spring Data's Page, Jimmer's own Page, or even Page defined by third parties. Here, the Java code uses SpringPageFactory.getInstance() to request the current pagination operation to return Spring Data's Page. In fact, the Kotlin code can also use SpringPageFactory.getInstance() for the same purpose, but in Kotlin there is a more convenient extension method fetchSpringPage(). If we execute: Page page = bookRepository.findBooks( PageRequest.of( 1, 5, SortUtils.toSort(\"name asc, edition desc\") ), null, null ) caution In Spring Data, the page number of Pageable starts from 0 instead of 1, so this queries the second page. It will generate two SQL statements: count-query select count(tb_1_.ID) from BOOK tb_1_ data-query (assuming the database is H2) select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 5 */, ? /* 5 */ This example allows us to understand Jimmer's pagination functionality, but Jimmer's Spring API hides some details. Therefore, next we bypass Spring Data and explain more clearly from a lower level perspective.","s":"When Used with Spring Data","u":"/jimmer-doc/docs/query/paging/usage","h":"#when-used-with-spring-data","p":1540},{"i":1547,"t":"Since Spring Data is not used, naturally org.springframework.data.domain.Page cannot be used. For this, Jimmer defines org.babyfish.jimmer.Page with the following definition: Page.java package org.babyfish.jimmer; public class Page { private final List rows; private final int totalRowCount; private final int totalPageCount; ...Omit other fields... } It can be seen that Jimmer's own Page is much simpler than Spring Data's Page, the differences are: info org.springframework.data.domain.Page is designed for server-side paging so that the page must still maintain its previous state after being refreshed. A lot of information (such as tedious sort information) needs to be returned verbatim to the client, so it is very complex. org.babyfish.jimmer.Page is designed for rich client pages. Such client pages are stateful applications themselves, the server only needs to provide pure data services, so returning just the bare necessities is enough, hence very simple.","s":"Jimmer's Page object","u":"/jimmer-doc/docs/query/paging/usage","h":"#jimmers-page-object","p":1540},{"i":1549,"t":"Java Kotlin public Page findBooks( int pageIndex, int pageSize, @Nullable String name, @Nullable String storeName ) { return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .fetchPage(pageIndex, pageSize); } fun findBooks( pageIndex: Int, pageSize: Int, name: String? = null, storeName: String? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } storeName?.takeIf { it.isNotEmpty() }?.let { where(table.store.name eq it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .fetchPage(pageIndex, pageSize) The finally generated SQL is the same as the example discussed earlier with Spring Data, so I won't repeat it here.","s":"Implement Business Logic","u":"/jimmer-doc/docs/query/paging/usage","h":"#implement-business-logic","p":1540},{"i":1551,"t":"In the above examples, we discussed language differences between Java and Kotlin, as well as using or not using Spring Data. The underlying logic of these behaviors is the same, taking Java as an example: BookTable table = Tables.BOOK_TABLE; ConfigurableRootQuery query = ❶ sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(table.name().asc(), table.edition().desc()) int totalCount = query.fetchUnlimitedCount(); ❷ int totalPage = (totalCount + pageSize - 1) / pageSize; if (pageIndex >= totalPage) { return new Page(totalCount, totalPage, Collections.emptyList()); } List entities = query .limit(pageSize, pageIndex * pageSize) ❸ .execute(); ❹ return new Page<>( ❺ totalCount, totalPage, entities ) caution To simplify the discussion, this pseudocode does not consider reverse sorting optimization. ❶ Create the query, but do not execute it yet. I can call it the template query. ❷ Based on the original template query without modification, generate the count-query, then execute the count-query to get the total number of rows before pagination. Here the fetchUnlimitedCount method is a shortcut API, and its underlying logic is: public interface ConfigurableRootQuery, R> extends ... { default int fetchUnlimitedCount() { return count(null); } default int fetchUnlimitedCount(Connection con) { return reselect((q, t) -> q.select(t.count())) .withoutSortingAndPaging() .execute(con) .get(0) .intValue(); } } reselect((q, t) -> q.select(t.count())): The count-query does not query data, but queries COUNT withoutSortingAndPaging(): The count-query does not need the sorting clause order by nor the paging clause (such as H2's limit ? offset ?) tip Not only can Jimmer automatically generate count-query, it can also automatically optimize count-query, please refer to Join Optimization. ❸ limit(limit, offset): Based on the original template query without modification, generate the real data-query with pagination limits. ❹ Execute the data-query generated in ❸ to get the data within one page. ❺ Combine the data obtained in ❷ and ❹ into the page object and return it.","s":"Internal Mechanism","u":"/jimmer-doc/docs/query/paging/usage","h":"#internal-mechanism","p":1540},{"i":1553,"t":"This section discusses the SQL implementation of data-query with pagination limits under different databases. Consider the following single page data query: Java Kotlin List books = query .limit(/*limit*/ 10, /*offset*/ 90) .execute(); val books = query .limit(limit = 10, offset = 90) .execute() Here limit(limit, offset) sets the pagination range. Different databases have vastly different support for pagination queries. So when creating SqlClient, the dialect needs to be specified. Spring Data configuration method: Add a configuration in application.properties or application.yml called jimmer.dialect with value as the class name of the dialect class provided by Jimmer: jimmer: dialect: org.babyfish.jimmer.sql.dialect.H2Dialect Non-Spring Data configuration method: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect(new H2Dialect()) ...other code omitted... .build(); val sqlClient = newKSqlClient { setDialect(H2Dialect()) ...other code omitted... } Different dialects will use different SQL to implement the limit query:","s":"Dialects","u":"/jimmer-doc/docs/query/paging/usage","h":"#dialects","p":1540},{"i":1555,"t":"info Default behavior includes DefaultDialect, H2Dialect and PostgresDialect. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ? order by tb_2_.NAME asc, tb_1_.NAME asc limit ? offset ?","s":"Default Behavior","u":"/jimmer-doc/docs/query/paging/usage","h":"#default-behavior","p":1540},{"i":1557,"t":"select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ? order by tb_2_.NAME asc, tb_1_.NAME asc limit ?, ?","s":"MySqlDialect","u":"/jimmer-doc/docs/query/paging/usage","h":"#mysqldialect","p":1540},{"i":1559,"t":"When offset is not 0: select * from ( select core__.*, rownum rn__ from ( select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ? order by tb_2_.NAME asc, tb_1_.NAME asc ) core__ where rownum <= ? ❶ ) limited__ where rn__ > ? ❷ Where the variable at ❶ is limit + offset, and at ❷ is offset. When offset is 0: select core__.* from ( select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID core__ where rownum <= ? ❶ Where ❶ is the variable limit.","s":"OracleDialect","u":"/jimmer-doc/docs/query/paging/usage","h":"#oracledialect","p":1540},{"i":1561,"t":"The object fetcher defines the shape of the queried object, allowing the queried object to carry more associated objects. This feature can be used together with pagination. info After the paged query is completed, Jimmer launches queries for other association objects, only for objects within a single page. Take the Spring Data mode as an example. Now, let's modify the BookRepository we discussed earlier to support object fetchers: Java Kotlin BookRepository.java import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; ...other imports omitted... public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page findBooks( Pageable pageable, @Nullable Fetch fetcher, @Nullable String name, @Nullable String storeName ) { return sql() .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) .select( table.fetch(fetcher) ) .fetchPage( pageable.getPageNumber(), pageable.getPageSize(), SpringPageFactory.getInstance() ); } } BookRepository.kt import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable ...other imports omitted... interface BookRepository : KRepository { fun findBooks( pageable: Pageable, fetcher: Fetcher? = null, name: String? = null, storeName: String? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } storeName?.takeIf { it.isNotEmpty() }?.let { where(table.store.name eq it) } orderBy(pageable.sort) select( table.fetch(fetcher) ) } .fetchSpringPage(pageable) } If called as follows: Java Kotlin Page.java Page page = bookRepository.findBooks( PageRequest.of( 1, 5, SortUtils.toSort(\"name asc, edition desc\") ), Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ), null, null ); Page.kt val page = bookRepository.findBooks( PageRequest.of( 1, 5, SortUtils.toSort(\"name asc, edition desc\") ), newFetcher(Book::class).by { allScalarFields() store { allScalarFields() } authors { allScalarFields() } } ) It will generate the following 4 SQL statements: count-query select count(tb_1_.ID) from BOOK tb_1_ data-query (assuming the database is H2) select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 5 */, ? /* 5 */ Query the many-to-one association Book.store for the 5 paged objects select tb_1_.ID, tb_1_.NAME from BOOK_STORE tb_1_ where tb_1_.ID in ( ? /* 2 */, ? /* 1 */ ) info Although there are 5 paged objects, their foreign key STORE_ID only has two values. Query the many-to-many association Book.authors for the 5 paged objects select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ? /* 10 */, ? /* 3 */, ? /* 2 */, ? /* 1 */, ? /* 9 */ ) Finally, in the obtained pagination, each object conforms to the data structure of the object fetcher. { \"content\":[ // Current page { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\", \"website\":null }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81, \"store\":{ \"id\":2, \"name\":\"MANNING\", \"website\":null }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82, \"store\":{ \"id\":2, \"name\":\"MANNING\", \"website\":null }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] } ], \"totalPages\":3, // Total page count is 3 \"totalElements\":12, // Total row count before pagination is 12 ...Spring Data's Page object has too many properties, omitted... }","s":"Used with Object Fetcher","u":"/jimmer-doc/docs/query/paging/usage","h":"#used-with-object-fetcher","p":1540},{"i":1563,"t":"Super QBE is a very powerful feature that uses DTO Language to generate parameter types for complex queries and automatically implement query logic.","s":"Super QBE","u":"/jimmer-doc/docs/query/super_qbe","h":"","p":1562},{"i":1565,"t":"In any project that can access entity types, create the src/main/dto directory, and create the Book.dto file in this directory. For Java projects, if the current project is not the project that defines the entity type, you need to add the @EnableDtoGeneration annotation to any class in the current project. Add the following code to the head of the file: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.dto The above steps, as well as how to compile DTO files, are discussed in detail in DTO Language #2. Create File, and will not be repeated here.","s":"Create File","u":"/jimmer-doc/docs/query/super_qbe","h":"#create-file","p":1562},{"i":1567,"t":"...export statement omitted... specification BookSpecification { }","s":"Define Specification Type","u":"/jimmer-doc/docs/query/super_qbe","h":"#define-specification-type","p":1562},{"i":1569,"t":"After compilation, Java/Kotlin code like this will be generated: Java Kotlin BookSpecification.java package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.ast.query.specification.JSpecification; import org.babyfish.jimmer.sql.ast.query.specification.SpecificationArgs; ...other imports omitted... public class BookSpecification implements JSpecification { @Override public void applyTo(SpecificationArgs args) {} } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( // Now data class has no fields, will cause compile error ) : KSpecification { override fun applyTo(args: KSpecificationArgs) {} } info applyTo is a method specific to the compiled specification code. It dynamically adds where conditions to Jimmer queries according to the information of the current object. This method does not require user invocation (invoked by internal Jimmer behaviors), and users do not need to care about its internal code implementation. Just knowing what this method does is enough here. In subsequent discussions, we will gradually add properties to BookSpecification in the DTO file. Accordingly, for the automatically generated BookSpecification class, on the one hand, properties will be added synchronously, on the other hand, the code in the applyTo method will also grow.","s":"Compiled Code","u":"/jimmer-doc/docs/query/super_qbe","h":"#compiled-code","p":1562},{"i":1571,"t":"Use in queries Java Kotlin public List find( Specification specification ❶ ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(specification) ❷ .select(table) .execute(); } fun find( specification: Specification ❶ ): List = sqlClient.createQuery(Book::class) { where(specification) ❷ select(table) }.execute() ❶ The argument whose type is org.babyfish.jimmer.Specification type, which is used to generate dynamic SQL predicates. ❷ No matter how simple or complex the specification format is, it can be used with just a simple where statement. Use in Spring Data Repository Jimmer integrates Spring Data, so Spring Data Repository can be defined, please refer to Spring Data Style to learn more. Jimmer's Spring Data Repository has two query styles, abstract methods and default methods. The code using specification in default methods is the same as above, so let's look at an example of using specification in abstract query methods: Java Kotlin public interface BookRepository : JRepository { public List find( Specification specification ) } interface BookRepository : KRepository { fun find( specification: Specification ): List }","s":"Usage","u":"/jimmer-doc/docs/query/super_qbe","h":"#usage","p":1562},{"i":1574,"t":"...export statement omitted... specification BookSpecification { name } This maps entity properties to DTOs. The generated code is: Java Kotlin BookSpecification.java public class BookSpecification implements JSpecification { @Nullable private String name; ...getters and setters omitted... @Override public void applyTo(SpecificationArgs args) { ...omitted... } } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( val name: String? = null ) : KSpecification { override fun applyTo(args: KSpecificationArgs) { ...omitted... } }","s":"Map Attributes","u":"/jimmer-doc/docs/query/super_qbe","h":"#map-attributes","p":1562},{"i":1576,"t":"We find that in the generated code, the name field can be null, which is where the specialty of specification lies. tip Specifications are used as query parameters. To support dynamic queries, all properties are nullable by default unless explicitly specified as non-nullable using ! (see DTO Language #7. Nullability).","s":"Nullability","u":"/jimmer-doc/docs/query/super_qbe","h":"#nullability","p":1562},{"i":1578,"t":"Let the name field of BookSpecification be null Java Kotlin BookSpecification specification = new BookSpecification(); List books = bookRepository.find(specification); val specification = BookSpecification() val books = bookRepository.find(specification) Since specification.name is null, the generated SQL does not contain any where conditions. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME = ? info Such queries that do not specify relevant specification properties will inevitably lead to queries without any conditions. This example is only demonstrated once in this article. Make the name field of BookSpecification non-null Java Kotlin BookSpecification specification = new BookSpecification(); specification.setName(\"GraphQL in Action\"); List books = bookRepository.find(specification); val specification = BookSpecification( name = \"GraphQL in Action\" ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME = ? /* GraphQL in Action */","s":"Usage","u":"/jimmer-doc/docs/query/super_qbe","h":"#usage-1","p":1562},{"i":1581,"t":"In the code above, when specification.name is specified, the generated where condition is equality. Equality is not necessarily what we need. QBE functions can be applied to mapped properties to change the operator. Take like as an example: ...export statement omitted... specification BookSpecification { like(name) } The like function does not affect the properties of the generated BookSpecification class, but affects its applyTo method, whose internal implementation is the where condition addition logic that users do not need to care about. Execute: Java Kotlin BookSpecification specification = new BookSpecification(); specification.setName(\"GraphQL\"); List books = bookRepository.find(specification); val specification = BookSpecification( name = \"GraphQL\" ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME like ? /* %GraphQL% */","s":"Introduction to QBE Functions","u":"/jimmer-doc/docs/query/super_qbe","h":"#introduction-to-qbe-functions","p":1562},{"i":1583,"t":"like is a special one among all QBE functions, supporting 3 options: i: Case insensitive ^: Exact match at the beginning (Jimmer does not automatically add % before the parameter value) $: Exact match at the end (Jimmer does not automatically add % after the parameter value) If options are needed, / can be added after like, followed by the required options. Such as: like/i, like/^, like/$, like/i^, like/i$, and like/i^$. caution Although i, ^ and $ are optional, their order is fixed. Let's try case-insensitive like by modifying the DTO code as follows: ...export statement omitted... specification BookSpecification { like/i(name) } Execute the code above again, the following SQL is executed: Databases that do not support ilike: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ Databases that support ilike: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME ilike ? /* %graphql% */","s":"like Function Options","u":"/jimmer-doc/docs/query/super_qbe","h":"#like-function-options","p":1562},{"i":1585,"t":"In fact, in addition to like, speciation supports a large number of QBE functions covering common SQL judgments, as shown in the table below: QBE Function Original Entity Attribute Type (or Requirement) Generated DTO Class Attribute Type Remarks eq Any non-associative property Original type Equal, equivalent to not using any QBE function ne Any non-associative property Original type Not equal gt Any non-associative property Original type Greater than ge Any non-associative property Original type Greater than or equal to lt Any non-associative property Original type Less than le Any non-associative property Original type Less than or equal to like String String Fuzzy match notLike String String Fuzzy mismatch null Any property boolean is null judgment if DTO property is true notNull Any property boolean is not null judgment if DTO property is true valueIn Any non-associative property List in(...) valueNotIn Any non-associative property List not in(...) associatedIdEq Any associative property Type of associated entity's id property Associated id = ?. Note that it is equivalent to id (inherent DTO language function) associatedIdNe Any associative property Type of associated entity's id property Associated id <> ? associatedIdIn Any associative property List Associated id in(...) associatedIdNotIn Any associative property List Associated id not in(...)","s":"All QBE Functions","u":"/jimmer-doc/docs/query/super_qbe","h":"#all-qbe-functions","p":1562},{"i":1587,"t":"Modify the DTO code: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) le(price) } ge(price) will specify the default alias minPrice, le(price) will specify the default alias maxPrice, so the above code can also be written as: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) as minPrice le(price) as maxPrice } As you can see, some QBE functions have built-in default alias functionality. Assuming the original property name is Prop, the default alias behaviors of all QBE functions are as follows: QBE Function Default alias eq (or no QBE function specified) prop ne Not supported, no alias specified will cause compile error gt minPropExclusive ge minProp lt maxPropExclusive le maxProp like prop notLike Not supported, no alias specified will cause compile error valueIn Not supported, no alias specified will cause compile error valueNotIn Not supported, no alias specified will cause compile error associatedIdEq or id If the association is a reference (non-collection), propId; otherwise, compile error associatedIdNe If the association is a reference (non-collection), excludedPropId; otherwise, compile error associatedIdIn If the association is a reference (non-collection), propIds; otherwise, compile error associatedIdNotNull If the association is a reference (non-collection), excludedPropIds; otherwise, compile error The compiled code is: Java Kotlin BookSpecification.java public class BookSpecification implements JSpecification { @Nullable private String name; @Nullable private BigDecimal minPrice; @Nullable private BigDecimal maxPrice; ...getters and setters omitted... @Override public void applyTo(SpecificationArgs args) { ...omitted... } } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( val name: String? = null, val minPrice: BigDecimal? = null, val maxPrice: BigDecimal? = null ) : KSpecification { override fun applyTo(args: KSpecificationArgs) { ...omitted... } } Execute: Java Kotlin BookSpecification specification = new BookSpecification(); specification.setName(\"GraphQL\"); specification.setMinPrice(new BigDecimal(40)); specification.setMaxPrice(new BigDecimal(40)); List books = bookRepository.find(specification); val specification = BookSpecification( name = \"GraphQL\", minPrice = BigDecimal(40), maxPrice = BigDecimal(60) ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ and tb_1_.PRICE >= ? /* 40 */ and tb_1_.PRICE <= ? /* 60 */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Comprehensive Example","u":"/jimmer-doc/docs/query/super_qbe","h":"#comprehensive-example","p":1562},{"i":1589,"t":"In previous examples, all filtering rules are for fields of the current table. Now let's filter on associated objects. Modify the DTO file as follows: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) le(price) flat(store) { ❶ like/i(name) as storeName } flat(authors) { ❷ like/i(firstName) as authorName } } We find that the code above uses the flat function. The flat function is discussed in detail in DTO Language #10.4-flat function, and will not be repeated here. info Since specification serves as a parameter for complex queries, it is very likely to be HTTP GET parameters. Using the flat function to eliminate associations and generate flattened DTO objects is more beneficial for developing HTTP GET APIs based on Spring MVC. ❶ Book.store is a reference association ❷ Book.authors is a collection association The compiled code is: Java Kotlin BookSpecification.java public class BookSpecification implements JSpecification { @Nullable private String name; @Nullable private BigDecimal minPrice; @Nullable private BigDecimal maxPrice; @Nullable private String storeName; @Nullable private String authorName; ...getters and setters omitted... @Override public void applyTo(SpecificationArgs args) { ...omitted... } } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( val name: String? = null, val minPrice: BigDecimal? = null, val maxPrice: BigDecimal? = null, val storeName: String? = null, val authorName: String? = null ) : KSpecification { override fun applyTo(args: KSpecificationArgs) { ...omitted... } } Execute: Java Kotlin BookSpecification specification = new BookSpecification(); specification.setStoreName(\"MANNING\"); specification.setAuthorName(\"a\"); List books = bookRepository.find(specification); val specification = BookSpecification( storeName = \"MANNING\", authorName = \"a\" ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ /* ❶ */ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME ilike ? /* %manning% */ and exists( /* ❷ */ select 1 from AUTHOR tb_3_ inner join BOOK_AUTHOR_MAPPING tb_4_ on tb_3_.ID = tb_4_.AUTHOR_ID where tb_1_.ID = tb_4_.BOOK_ID and tb_3_.FIRST_NAME ilike ? /* %a% */ ) ❶ Book.store is a reference association that does not break pagination safety. So only dynamic JOIN is needed to apply the filtering condition represented by the storeName property of the DTO object. ❷ Book.authors is a collection association that breaks pagination safety. So subqueries must be used instead of dynamic JOIN to apply the filtering condition represented by the authorName property of the DTO object.","s":"Associated Objects","u":"/jimmer-doc/docs/query/super_qbe","h":"#associated-objects","p":1562},{"i":1591,"t":"In previous examples, Jimmer generates multiple where conditions according to each property of the DTO object, and the relationship between these conditions is logical AND. But can logical OR be supported? In addition, the entity type Author has the lastName property in addition to the firstName property. Mapping only firstName to authorName in the previous example does not seem reasonable. Is there a better way? The above two issues are the same issue. To solve this problem, Super QBE supports logical OR, also known as multi-property mapping. Modify the DTO code as follows: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) le(price) flat(store) { like/i(name) as storeName } flat(authors) { like/i(firstName, lastName) as authorName } } Here, the DTO property authorName maps two properties, firstName and lastName. This is called multi-property mapping. Multi-property mapping can only be used in specification and cannot be used in other types described in DTO Language. The types of multiple properties mapped by QBE functions must be completely consistent (but nullability is allowed to differ). For example, both firstName and lastName here are of type String. The DTO property of multi-property mapping must be aliased via as, otherwise compilation errors will occur. Not all QBE functions support multi-property mapping. QBE functions that support multi-property mapping are: eq ne null notNull valueIn associatedIdEq associatedIdIn Allowing all QBE functions to support multi-property mapping blindly would lead to ambiguous understanding. So there is this restriction. Repeating the query in the previous example generates the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME ilike ? /* %manning% */ and exists( select 1 from AUTHOR tb_3_ inner join BOOK_AUTHOR_MAPPING tb_4_ on tb_3_.ID = tb_4_.AUTHOR_ID where tb_1_.ID = tb_4_.BOOK_ID and ( tb_3_.FIRST_NAME ilike ? /* %a% */ or tb_3_.LAST_NAME ilike ? /* %a% */ ) ) It is not difficult to see that multi-property mapping is logical OR.","s":"Logical OR","u":"/jimmer-doc/docs/query/super_qbe","h":"#logical-or","p":1562},{"i":1594,"t":"Different from most ORM DSLs that only provide strong typing, Jimmer DSL aims to solve the low efficiency issue of native SQL under complex scenarios and offers a brand new abstraction. So Jimmer SQL DSL has essential differences from most other SQL DSLs (which is also the original motivation of the Jimmer project) Jimmer DSL can embed native SQL snippets and keeps connected with database-specific features. To quickly preview, this chapter only focuses on 1. For 2, readers who are interested can check Native Expressions.","s":"Jimmer SQL DSL","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#jimmer-sql-dsl","p":1592},{"i":1596,"t":"Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) ❶ .where(table.price().betweenIf(minPrice, maxPrice)) ❷ .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) ❶ where(table.price.`between?`(minPrice, maxPrice)) ❷ select(table.fetch(table)) } .execute() } Where the meaning of the fetcher parameter has been introduced in Quick Tour/Fetch Any Shape, this article does not repeat it and readers can ignore it. ❶ Different from the static predicate ilike, ilikeIf/ilike? is a dynamic predicate that decides whether to add the SQL condition based on parameters. If name is neither null nor empty string, the SQL condition name ilike :name will be added. ❷ Different from the static predicate between, betweenIf/between? is a dynamic predicate that decides whether to add the SQL condition based on parameters. There are four cases: If both minPrice and maxPrice are not null, the SQL condition price between :minPrice and :maxPrice will be added. If only minPrice is not null, the SQL condition name >= :minPrice will be added. If only maxPrice is not null, the SQL condition name <= :maxPrice will be added. If both minPrice and maxPrice are null, no SQL condition will be added. Now let's see the effects: When all three parameters are null: Java Kotlin List books = bookRepository.findBooks( null, // name null, // minPrice null, // maxPrice null ); val books = bookRepository.findBooks() No where condition will be generated and the SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ // No SQL predicates When all three parameters are not null: Java Kotlin List books = bookRepository.findBooks( \"GraphQL\", // name new BigDecimal(20), // minPrice new BigDecimal(50), // maxPrice null ); val books = bookRepository.findBooks( name = \"GraphQL\", minPrice = BigDecimal(20), maxPrice = BigDecimal(50) ) All where conditions will be generated and the SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ and (tb_1_.PRICE between ? /* 20 */ and ? /* 50 */)","s":"Dynamic Predicates","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#dynamic-predicates","p":1592},{"i":1599,"t":"In the previous examples, our dynamic SQL conditions are all applied to the current entity (Book). Next, we use the reference association (one-to-one or many-to-one) to get associated object and add SQL conditions for it. The many-to-one association Book.store is associated with the BookStore entity. Let us add dynamic SQL conditions for BookStore.name and BookStore.website. Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .where(table.price().betweenIf(minPrice, maxPrice)) .where(table.store().name().ilikeIf(storeName)) ❶ .where(table.store().website().ilikeIf(storeWebsite)) ❷ .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) ❶ where(table.store.name `ilike?` storeWebsite) ❷ select(table.fetch(table)) } .execute() } tip The path table.store() in Java code or table.store in Kotlin code is called a dynamic table join path, which is represented by the following SQL logic from BOOK b inner join BOOK_STORE s on b.STORE_ID = s.ID Here is the translation to English: You can also use outer join. The Java code is table.store(JoinType.LEFT), and the Kotlin code is table.storeId?. In fact, if the entity model is richer, you can write a longer path, such as 'table.store().city().province()'. Here, just for the quick preview, there is no need to build richer entity model to demonstrate a longer join path, and the shortest join path 'table.store()' is enough. ❶ When 'storeName' is neither null nor empty string Associate to the BookStore entity via the association Book.store Add the SQL condition to 'BookStore.name' ❷ When 'storeWebsite' is neither null nor empty string Associate to the BookStore entity via the association Book.store Add the SQL condition to 'BookStore.website'","s":"Define dynamic table joins","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#define-dynamic-table-joins","p":1592},{"i":1601,"t":"If both the storeName and storeWebsite parameters are null Java Kotlin List books = bookRepository.findBooks( null, null, null, null, // storeName null, // storeWebsite null ); val books = bookRepository.findBooks() This will cause the 'ilikeIf'/'ilike?' at ❶ and ❷ to be invalid, further causing 'table.store()'/'table.store' to be ignored. That is, although a table join is created, it is not used. tip If a table join is created in the DSL but is not actually used, the table join will be automatically ignored and there will be no corresponding SQL join in the generated SQL statement. Note: Jimmer does not have the concept of join fetch like JPA. The only purpose of a join is to be referenced by other SQL expressions, so any unused join objects will be ignored. The generated SQL statement is as follows select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ // No SQL table joins","s":"Ignore useless table joins","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#ignore-useless-table-joins","p":1592},{"i":1603,"t":"If both storeName and storeWebsite parameters are not null: Java Kotlin List books = bookRepository.findBooks( null, null, null, \"M\", // storeName \".com\", // storeWebsite null ); val books = bookRepository.findBooks( storeName = \"M\", storeWebsite = \".com\" ) This will make both ❶ and ❷ ilikeIf/ilike? effective, which further makes both table joins table.store()/table.store effective. That is, the table join is created and used multiple times. tip If conflicting table joins of the same association are created multiple times in DSL, all the conflicting joins will be automatically merged into one JOIN in the final SQL without duplicate JOINs. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ /* Multiple conflicting table joins are merged into one */ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where lower(tb_2_.NAME) like ? /* %m% */ and lower(tb_2_.WEBSITE) like ? /* %.com% */","s":"Merge Conflicting Table Joins","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#merge-conflicting-table-joins","p":1592},{"i":1606,"t":"In the previous examples, the dynamic table joins are created based on references (one-to-one or many-to-one). For collection associations (one-to-many or many-to-many), we can create implicit subqueries. Actually, we can also create dynamic table joins based on collection associations using special DSL syntax. But it is more recommended to create implicit subqueries based on collection associations. Next, we demonstrate related features using the many-to-many association Book.authors. Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName, @Nullable Gender authorGender, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .where(table.price().betweenIf(minPrice, maxPrice)) .where(table.store().name().ilikeIf(storeName)) .where(table.store().website().ilikeIf(storeWebsite)) .where( table.authors(author -> ❶ Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .where( table.authors(author -> ❷ author.gender().eqIf(authorGender) ) ) .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, authorName: String? = null, authorGender: String? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.name `ilike?` storeWebsite) where += table.authors { ❶ or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } where += table.authors { ❷ gender `eq?` authorGender } select(table.fetch(table)) } .execute() } The two SQL conditions based on lambda expressions at ❶ and ❷ are implicit subqueries. Actually these two implicit subqueries can be merged into one. But two subqueries are created on purpose here to demonstrate subsequent features. ❶ Create the subquery of associated Author objects through the many-to-many association Book.authors and check if Author's firstName or lastName property fuzzy matches the authorName parameter. ❷ Create the subquery of associated Author objects through the many-to-many association Book.authors and check if Author's gender property equals the authorGender parameter. tip If effective, implicit subqueries will eventually generate SQL exists statements. The subqueries in SQL exists usually have a condition for joining parent and child queries. However, from the above code, we can see that all the conditions in subqueries are applied to Author objects without the join condition. Actually, the join condition between parent and child queries is implicitly included by implicit subqueries. It is always generated automatically. So users only need to write conditions related to associated objects. Note: Here we are discussing implicit subqueries instead of normal subqueries (Jimmer also supports normal subqueries which are not included in the quick tour). The rules here do not apply to normal subqueries.","s":"Define implicit subqueries","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#define-implicit-subqueries","p":1592},{"i":1608,"t":"If both authorName and authorGender parameters are null: Java Kotlin List books = bookRepository.findBooks( null, null, null, null, null, null, // authorName null, // authorGender null ); val books = bookRepository.findBooks() The first implicit subquery will be ignored: Java Kotlin where( ⑤ table.authors(author -> ④ Predicate.or( ③ author.firstName().ilikeIf(authorName), ① author.lastName().ilikeIf(authorName) ② ) ) ) where += ⑤ table.authors { ④ or( ③ firstName `ilike?` authorName, ① lastName `ilike?` authorName ② ) } When authorName is null or empty string, At ① and ②, ilikeIf/ilike? will be ignored and return null As expressions at ① and ② are null, the or expression at ③ will become null the or expression at ③ being null will lead to no SQL conditions for the subquery, so the predicate based on implicit subquery at ④ is null. The expression at ④ being null make where at ⑤ become meaningless, so the whole operation will be ignored. That is, the first implicit subquery is ignored. Similarly, the second implicit subquery will also be ignored. The final SQL does not contain any subqueries: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ // No SQL sub queries","s":"Ignore useless subqueries","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#ignore-useless-subqueries","p":1592},{"i":1610,"t":"If both authorName and authorGender parameters are not null: Java Kotlin List books = bookRepository.findBooks( null, null, null, null, null, \"A\", // authorName Gender.MALE, // authorGender null ); val books = bookRepository.findBooks( authorName = \"A\", authorGender = Gender.MALE ) In this case, two implicit subqueries based on the same association (Book.authors) will take effect. tip If conflicting implicit subqueries of the same association are created multiple times in DSL, all the conflicting subqueries will be automatically merged into one subquery in the final SQL. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where /* Multiple conflicting implicit subqueries are merged into one */ exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where /* Parent-child query join condition implied by the implicit subquery */ tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) and tb_2_.GENDER = ? /* M */ ) There is a restriction on conflicting implicit subquery merges, multiple subqueries that are merged must be inside the same context of and, or, or not.","s":"Merge conflicting subqueries","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#merge-conflicting-subqueries","p":1592},{"i":1612,"t":"Through the previous chapters, we already have a basic impression of Jimmer. Now we can start practicing. In this series of articles, we will introduce how to create your own Jimmer project from scratch.","s":"Get Started","u":"/jimmer-doc/docs/quick-view/get-started/","h":"","p":1611},{"i":1614,"t":"Here is the English translation of the file, with the code indentation preserved:","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"","p":1613},{"i":1616,"t":"Jimmer can query data structures of any shape, with control over the queried data structure as fine-grained as GraphQL. Next, we will demonstrate its usage in three scenarios.","s":"Basic Usage","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#basic-usage","p":1613},{"i":1618,"t":"info A partial object refers to querying only part of an object's properties, with less information than an isolated object. Usage1: Query Entity Objects Usage2: Query DTOs Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch( Fetchers.BOOK_FETCHER .name() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"Learning GraphQL\" select( table.fetchBy { name() } ) } .execute() DTO代码 export yourpackage.Book -> package yourpackage.dto; BookView { id name } After compilation, Java/Kotlin type BookView will be automatically generated. Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"Learning GraphQL\" select( table.fetch(BookView::class) ) } .execute() Output Result [ {\"id\":10,\"name\":\"Learning GraphQL\"}, {\"id\":11,\"name\":\"Learning GraphQL\"}, {\"id\":12,\"name\":\"Learning GraphQL\"} ] Output Result [ BookView(id=10, name=Learning GraphQL), BookView(id=11, name=Learning GraphQL), BookView(id=12, name=Learning GraphQL) ]","s":"1. Query Partial Objects","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#1-query-partial-objects","p":1613},{"i":1620,"t":"info Select an entity as the aggregate root, and query not only the aggregate root object but also its associated objects, with no restrictions on depth or breadth. This level of control over the format is as fine-grained as GraphQL. Usage1: Query Entity Objects Usage2: Query DTOs Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"Learning GraphQL\" select( table.fetchBy { allScalarFields() store { allScalarFields() } authors { allScalarFields() } } ) } .execute() DTO Code export yourpackage.Book -> package yourpackage.dto; BookView { #allScalars store { #allScalars } authors { #allScalars } } After compilation, Java/Kotlin type BookView will be automatically generated. Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"GraphQL\" select( table.fetch(BookView::class) ) } .execute() Output Result [ { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 50, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null }, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] }, { \"id\": 2, \"name\": \"Learning GraphQL\", \"edition\": 2, \"price\": 55, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null }, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] }, { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null }, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] } ] Output Result [ BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookView.TargetOf_store( id=1, name=O'REILLY, website=null ), authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, store=BookView.TargetOf_store( id=1, name=O'REILLY, website=null ), authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, store=BookView.TargetOf_store( id=1, name=O'REILLY, website=null ), authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) ]","s":"2. Include Associated Objects","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#2-include-associated-objects","p":1613},{"i":1622,"t":"info If an entity contains Self-correlation properties, you can perform a recursive query. As of now, the GraphQL protocol does not support recursive queries. Usage1: Query Entity Objects Usage2: Query DTOs Query Code Java Kotlin TreeNode rootNode = sqlClient .findById( Fetchers.TREE_NODE_FETCHER .allScalarFields() // Recursion upwards .recursiveParent() ❶ // Recursion downward .recursiveChildNodes() ❷ 10L ); val rootNode = sqlClient .findById( newFetcher(TreeNode::class).by { allScalarFields() // Recursion upwards `parent*`() ❶ // Recursion downward `childNodes*`() ❷ } ) DTO代码 export yourpackage.TreeNode -> package yourpackage.dto; RecursiveTreeNodeView { id // Recursion upwards parent* ❶ // Recursion downward childNodes* ❷ } After compilation, Java/Kotlin type RecursiveTreeNodeView will be automatically generated. Query Code Java Kotlin RecursiveTreeNodeView rootNode = sqlClient .findById( RecursiveTreeNodeView.class, 10L ); val rootNode = sqlClient .findById( RecursiveTreeNodeView::class, 10L ); Output Result { \"id\": 10, \"name\": \"Woman\", \"parent\": { ❶ \"id\": 9, \"name\": \"Clothing\", ❶ \"parent\": { \"id\": 1, \"name\": \"Home\", \"parent\": null ❶ } }, \"childNodes\": [ ❷ { \"id\": 11, \"name\": \"Casual wear\", \"childNodes\": [ ❷ { \"id\": 12, \"name\": \"Dress\", \"childNodes\": [] ❷ }, { \"id\": 13, \"name\": \"Miniskirt\", \"childNodes\": [] ❷ }, { \"id\": 14, \"name\": \"Jeans\", \"childNodes\": [] ❷ } ] }, { \"id\": 15, \"name\": \"Formal wear\", \"childNodes\": [ ❷ { \"id\": 16, \"name\": \"Suit\", \"childNodes\": [] ❷ }, { \"id\": 17, \"name\": \"Shirt\", \"childNodes\": [] ❷ } ] } ] } Output Result RecursiveTreeNodeView( id=10, name=Woman, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=9, name=Clothing, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=1, name=Home, parent=null ❶ ) ), childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=11, name=Casual wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=12, name=Dress, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=13, name=Miniskirt, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=14, name=Jeans, childNodes=[] ❷ ) ] ), RecursiveTreeNodeView.TargetOf_childNodes( id=15, name=Formal wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=16, name=Suit, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=17, name=Shirt, childNodes=[] ❷ ) ] ) ] )","s":"3. Recursive Query","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#3-recursive-query","p":1613},{"i":1624,"t":"The above code is only intended to demonstrate Jimmer's powerful control over the format of the queried data through three scenarios and does not organize the code structure. In actual development, we must organize the code in some way, with data operation-level code placed in the Repository. caution The previous examples showed two usages: querying entity objects and querying DTO objects. To control the complexity of this document, the following sections will only discuss how to organize code for querying entity objects.","s":"Repository Code Style","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#repository-code-style","p":1613},{"i":1626,"t":"Now let's write a BookRepository for querying Book Java Kotlin BookRepository.java @Repository pubic class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Nullable public Book findBookById(long id) { return sqlClient.findById(Book.class, id); } public List findBooksByName(@Nullable String name) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().ilike(name) ) .select(table) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBookById(id: Long): Book? = sqlClient.findById(Book::class, id) fun findBooksByName(name: String?): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike name); } select(table) } .execute() } JSqlClient in Java code and KSqlClient in Kotlin code are the API entry points provided by Jimmer for Java and Kotlin developers. In actual projects, the object is a global object. This chapter document is used for quick preview and does not introduce details. Readers can ignore specific details for the time being and just know that sqlClient is the API entry point. The purpose of this article is to control the format of returned objects, not to introduce complex query conditions (this part of the content is introduced in Quick Preview/Arbitrary Dynamic Queries). So these two methods symbolically use Book.id and Book.name as filters. Jimmer is technically neutral, but using Spring-style code often serves to simplify explanation, so this example uses Spring-style writing. However, for convenience of non-Spring users to read, it deliberately does not use Jimmer support for Spring Data here, but uses the relatively primitive injection of sqlClient, which reduces interference from Spring to a minimum. Tables.BOOK_TABLE in Java code is code that Jimmer automatically generates at compile time. If there is an instance bookRepository of the above class, take findBookById as an example: Java Kotlin System.out.println(bookRepository.findBookById(1L)); println(bookRepository.findBookById(1L)); The output result is as follows: { \"id\" : 1, \"name\" : \"Learning GraphQL\", \"edition\" : 1, \"price\" : 50.00, \"store\" : { \"id\" : 1 } } The output format is fixed and does not match the topic “Query Any Data Structure Shape” we are discussing now, so we need to improve BookRepository.","s":"The Simplest Repository","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#the-simplest-repository","p":1613},{"i":1628,"t":"Let's make some minor improvements to the previous BookRepository class Java Kotlin BookRepository.java @Repository pubic class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Nullable public Book findBookById( long id, Fetcher fetcher ) { return sqlClient.findById( fetcher, id ); } public List findBooksByName( @Nullable String name, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().ilike(name) ) .select( table.fetch(fetcher) ) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBookById( id: Long, fetcher: Fetcher ): Book? = sqlClient.findById( fetcher, id ) fun findBooksByName( name: String? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike name); } select( table.fetch(fetcher) ) } .execute() } In this example, we add a parameter of type Fetcher for each query method, through which we can flexibly control the format of the queried object (i.e. the shape of the queried data structure). tip This is the recommended usage. The Repository is only responsible for filtering, sorting, paging and other operations, but does not control the format of the returned data. Instead, it exposes the control of the data format through the Fetcher parameter to Let the upper layer business logic decide.","s":"Improved Repository","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#improved-repository","p":1613},{"i":1631,"t":"The examples in this tutorial require the following four entity types: BookStore, Book, Author: Demonstrate various associations including one-to-many, many-to-one, many-to-many. TreeNode: Demonstrates infinite recursion (self-associated properties), include recursive queries and recursive saving.","s":"UML","u":"/jimmer-doc/docs/quick-view/get-started/create-database","h":"#uml","p":1629},{"i":1633,"t":"This tutorial uses MySQL. Create a new SQL file jimmer-demo.sql with the following code: create database jimmer_demo; use jimmer_demo; create table book_store( id bigint unsigned not null auto_increment primary key, name varchar(50) not null, website varchar(100) ) engine=innodb; ... create table book ( id bigint unsigned not null auto_increment primary key, name varchar(50) not null, edition integer not null, price numeric(10, 2) not null, store_id bigint unsigned ) engine=innodb; ... create table author( id bigint unsigned not null auto_increment primary key, first_name varchar(25) not null, last_name varchar(25) not null, gender char(1) not null, created_time datetime not null, modified_time datetime not null ) engine=innodb; ... /* Many-to-many relationship between entities requires join table in ORM implementation. This table stores many-to-many mapping between books and authors. It is a join table, not an entity table, so no corresponding entity in the UML diagram above. */ create table book_author_mapping( book_id bigint unsigned not null, author_id bigint unsigned not null ) engine=innodb; ... create table tree_node( node_id bigint unsigned not null auto_increment primary key, name varchar(20) not null, parent_id bigint unsigned ) engine=innodb; ... insert into book_store(id, name) values (1, 'O''REILLY'), (2, 'MANNING') ; insert into book(id, name, edition, price, store_id) values (1, 'Learning GraphQL', 1, 50, 1), (2, 'Learning GraphQL', 2, 55, 1), (3, 'Learning GraphQL', 3, 51, 1), (4, 'Effective TypeScript', 1, 73, 1), (5, 'Effective TypeScript', 2, 69, 1), (6, 'Effective TypeScript', 3, 88, 1), (7, 'Programming TypeScript', 1, 47.5, 1), (8, 'Programming TypeScript', 2, 45, 1), (9, 'Programming TypeScript', 3, 48, 1), (10, 'GraphQL in Action', 1, 80, 2), (11, 'GraphQL in Action', 2, 81, 2), (12, 'GraphQL in Action', 3, 80, 2) ; insert into author(id, first_name, last_name, gender, created_time, modified_time) values (1, 'Eve', 'Procello', 'F', now(), now()), (2, 'Alex', 'Banks', 'M', now(), now()), (3, 'Dan', 'Vanderkam', 'M', now(), now()), (4, 'Boris', 'Cherny', 'M', now(), now()), (5, 'Samer', 'Buna', 'M', now(), now()) ; insert into book_author_mapping(book_id, author_id) values (1, 1), (2, 1), (3, 1), (1, 2), (2, 2), (3, 2), (4, 3), (5, 3), (6, 3), (7, 4), (8, 4), (9, 4), (10, 5), (11, 5), (12, 5) ; insert into tree_node( node_id, name, parent_id ) values (1, 'Home', null), (2, 'Food', 1), (3, 'Drinks', 2), (4, 'Coca Cola', 3), (5, 'Fanta', 3), (6, 'Bread', 2), (7, 'Baguette', 6), (8, 'Ciabatta', 6), (9, 'Clothing', 1), (10, 'Woman', 9), (11, 'Casual wear', 10), (12, 'Dress', 11), (13, 'Miniskirt', 11), (14, 'Jeans', 11), (15, 'Formal wear', 10), (16, 'Suit', 15), (17, 'Shirt', 15), (18, 'Man', 9), (19, 'Casual wear', 18), (20, 'Jacket', 19), (21, 'Jeans', 19), (22, 'Formal wear', 18), (23, 'Suit', 22), (24, 'Shirt', 22) ; This SQL file shows: Entity tables - book_store, book, author, tree_node map to entities in UML Join table - book_author_mapping represents many-to-many mapping between Book and Author note This is a basic database structure. More fields will be added in later tutorials. See https://github.com/babyfish-ct/jimmer-examples/blob/main/env-with-cache/maxwell/jimmer-demo.sql for full SQL.","s":"Create SQL File","u":"/jimmer-doc/docs/quick-view/get-started/create-database","h":"#create-sql-file","p":1629},{"i":1634,"t":"Install Docker. Open a command line, navigate to the SQL file directory, and run: docker run \\ --name jimmer-demo-mysql \\ ... mysql \\ --lower_case_table_names=1 docker cp jimmer-demo.sql jimmer-demo-mysql:/var/jimmer-demo.sql docker exec jimmer-demo-mysql /bin/sh -c \\ 'mysql -uroot -p123456 findBooksByName( @RequestParam(name = \"name\", required = false) String name ) { return bookRepository.findBooksByName( name, SIMPLE_BOOK ❹ ); } /** * Simple Book DTO which can only access `id` and `name` of `Book` itself */ private static final Fetcher SIMPLE_BOOK = ❺ BOOK_FETCHER .name(); /** * Complex Book DTO which can access not only properties of `Book` itself, * but also associated `BookStore` and `Author` objects with names */ private static final Fetcher COMPLEX_BOOK = ❻ BOOK_FETCHER .allScalarFields() .store( BOOK_STORE_FETCHER.name() ) .authors( AUTHOR_FETCHER .firstName() .lastName() ); } BookController.kt @RestController class BookController( private val bookRepository: BookRepository ) { @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long ): @FetchBy(\"COMPLEX_BOOK\") Book = ❶ bookRepository.findBookById( id, COMPLEX_BOOK ❷ ) @GetMapping(\"/books\") fun findBooksByName( @RequestParam(required = false) name: String ): List< @FetchBy(\"SIMPLE_BOOK\") Book ❸ > = bookRepository.findBooksByName( name, SIMPLE_BOOK ❹ ) companion object { /** * Simple Book DTO which can only access `id` and `name` of `Book` itself */ val SIMPLE_BOOK = ❺ newFetcher(Book::class).by { name() } /** * Complex Book DTO which can access not only properties of `Book` itself, * but also associated `BookStore` and `Author` objects with names */ private val COMPLEX_BOOK = ❻ newFetcher(Book::class).by { allScalarFields() store { name() } authors { firstName() lastName() } } } } The focus is on the 6 numbered items: ❶ Declare that the exact shape of the Book object returned by the findBookById method is defined by the static variable COMPLEX_BOOK ❷ The internal implementation of the findBookById method needs to be consistent with the external declaration at ❶, querying the Book object in the shape of COMPLEX_BOOK ❸ Declare that the exact shape of each Book object in the List returned by the findBooksByName method is defined by the static variable SIMPLE_BOOK ❹ The internal implementation of the findBooksByName method needs to be consistent with the external declaration at ❸, querying the Book object in the shape of SIMPLE_BOOK ❺ The definition of the SIMPLE_BOOK shape is used both at ❸ as part of the external API declaration and at ❹ to control the shape of the returned data structure ❻ The definition of the COMPLEX_BOOK shape is used both at ❶ as part of the external API declaration and at ❷ to control the shape of the returned data structure","s":"Write RestController","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#write-restcontroller","p":1635},{"i":1641,"t":"To recognize the Jimmer-specific annotation @FetchBy, Jimmer gives OpenAPI/Swagger a set of highly distinctive implementations. Without using any other frameworks in the JVM ecosystem for automatically generating OpenAPI/Swagger, just modify application.yml (or application.properties) as follows: application.yml jimmer: ...Omit other configurations... client: openapi: path: /openapi.yml ui-path: /openapi.html properties: info: title: My Web Service description: | Restore the DTO explosion that was eliminated by server-side developers version: 1.0 Start the web project and access http://localhost:8080/openapi.html with a browser to see: Expand /books to see that each element in the returned collection is a relatively simple DTO object Expand /books/{id} to see that the return type is a relatively complex DTO type","s":"View API Documentation","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#view-api-documentation","p":1635},{"i":1643,"t":"Modify application.yml (or application.properties) to add support for TypeScript: application.yml jimmer: ...Omit other configurations... client: openapi: ...Omit openapi related configurations... ts: path: /ts.zip Start the web project, download http://localhost:8080/ts.zip, unzip it, and you can see the TypeScript client code defines BookController as follows: services/BookController.ts import type {Executor} from '../'; import type {BookDto} from '../model/dto/'; export class BookController { constructor(private executor: Executor) {} async findBookById(options: BookControllerOptions['findBookById']): Promise< BookDto['BookController/COMPLEX_BOOK'] > { ...Omit specific logic... } async findBooksByName(options: BookControllerOptions['findBooksByName']): Promise< ReadonlyArray< BookDto['BookController/SIMPLE_BOOK'] > > { ...Omit specific logic... } } export type BookControllerOptions = { 'findBookById': { readonly id: number }, 'findBooksByName': { readonly name?: string | undefined } } Where BookDto['BookController/COMPLEX_BOOK'] and BookDto['BookController/SIMPLE_BOOK'] are the restored DTO types in the TypeScript client code generated by Jimmer. You can open the model/dto/BookDto.ts file to view their definitions as follows: model/dto/BookDto.ts export type BookDto = { /** * Complex Book DTO which can access not only properties of `Book` itself, * but also associated `BookStore` and `Author` objects with names */ 'BookController/COMPLEX_BOOK': { readonly id: number; readonly name: string; readonly edition: number; readonly price: number; readonly store?: { readonly id: number; readonly name: string; } | null | undefined; readonly authors: ReadonlyArray<{ readonly id: number; readonly firstName: string; readonly lastName: string; }>; } /** * Simple Book DTO which can only access `id` and `name` of `Book` itself */ 'BookController/SIMPLE_BOOK': { readonly id: number; readonly name: string; } }","s":"Generate TypeScript","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#generate-typescript","p":1635},{"i":1645,"t":"Through the above demonstration, we see that the server side does not need to define any Java/Kotlin types related to DTOs, while the client sees that each specific business API automatically defines precise DTO return types. In this way, both the server side and the client side get the programming models they expect. This article focuses on demonstrating this powerful feature without discussing how to add textual descriptions to various parts of the API (e.g. types, API methods, API parameters, object properties). tip Jimmer provides the simplest solution to these issues. Java/Kotlin developers only need to write the most basic documentation comments, and all documentation comments are automatically copied to the client API. This feature is simple. Readers can experiment on their own without elaboration here.","s":"Document Comments","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#document-comments","p":1635},{"i":1647,"t":"If the associated object has only the id property, the associated id is better than the associated object. For example: Using the associated object will lead to a large number of objects with only the id property, making the results slightly redundant: { \"id\" : 1, \"name\" : \"Learning GraphQL\", \"edition\" : 1, \"price\" : 50.00, \"store\" : { \"id\" : 1 }, \"authors\" : [{ \"id\" : 1 }, { \"id\" : 2 }] } Using the associated id makes the results relatively concise: { \"id\" : 1, \"name\" : \"Learning GraphQL\", \"edition\" : 1, \"price\" : 50.00, \"storeId\" : 1, \"authorIds\" : [1, 2] } If you choose to directly return entities (rather than the DTO returns in the next article), and want to use associated ids, you need to add @IdView properties to the entities first: Java Kotlin @Entity public interface Book { @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); @Nullable @IdView Long storeId(); @IdView(\"authors\") List authorIds(); ...Omit other members... } @Entity interface Book { @ManyToOne val store: BookStore? @ManyToMany val authors: List @IdView val storeId: Long? @IdView(\"authors\") val authorIds: List ...Omit other members... } In the above example: The storeId property is not a brand new property. It is just a view of the store property, getting the id property of the associated object represented by the store property (or null). storeId and store share the same data. The authorIds property is not a brand new property either. It is just a view of the authors property, getting a list of id properties of all associated objects represented by the authors property. authorIds and authors share the same data. Now, write the REST Controller as follows: Java Kotlin BookController.java @RestController public class BookController implements Fetchers { private final BookRepository bookRepository; public BookController(BookRepository bookRepository) { this.bookRepository = bookRepository; } @Nullable @GetMapping(\"/book\") public @FetchBy(\"SHALLOW_BOOK\") Book findBookById( @PathVariable(\"id\") long id ) { return bookRepository.findBookById(id, SHALLOW_BOOK); } /** * Shallow Book DTO which can access * 1. All scalar properties of `Book` itself * 2. All associated ids, not associated objects. */ private static final Fetcher SHALLOW_BOOK = BOOK_FETCHER .allScalarFields() .storeId() .authorIds(); ...Omit other members... } BookController.kt @RestController class BookController( private val bookRepository: BookRepository ) { @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long ): @FetchBy(\"SHALLOW_BOOK\") Book = bookRepository.findBookById(id, SHALLOW_BOOK) ...Omit other members... companion object { /** * Shallow Book DTO which can access * 1. All scalar properties of `Book` itself * 2. All associated ids, not associated objects. */ val SHALLOW_BOOK = newFetcher(Book::class).by { allScalarFields() storeId() authorIds() } ...Omit other shape definitions... } }","s":"Flat Associated IDs","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#flat-associated-ids","p":1635},{"i":1650,"t":"Similar to JPA2.0 Criteria, QueryDsl, Fluent MyBatis, etc., Jimmer uses strongly typed DSLs to catch errors at compile-time rather than runtime. So some additional code needs to be generated at compile-time based on user-defined entities: Java users use Annotation Processor Kotlin users use KSP Java (Maven) Java (Gradle) Kotlin (Gradle.kts) Java (Gradle Plugin) Kotlin (Gradle Plugin) pom.xml ...other code omitted... org.apache.maven.plugins maven-compiler-plugin 3.10.1 org.babyfish.jimmer jimmer-apt ${jimmer.version} ...other code omitted... dependencies { ...other dependencies omitted... annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" } plugins { // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10-1.0.6\" ...other plugins omitted... } dependencies { // Apply Jimmer's KSP code generator ksp(\"org.babyfish.jimmer:jimmer-ksp:${jimmerVersion}\") ...other dependencies omitted... } // Add generated code to compile path. // Gradle build works without this, but IntelliJ won't find generated code. kotlin { sourceSets.main { kotlin.srcDir(\"build/generated/ksp/main/kotlin\") } } build.gradle plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } build.gradle.kts plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10+\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } info The first three: Standard configurations The last two: Community-provided Gradle plugin for further simplifying configurations note KSP only supports gradle, It has been proven that KSP's third-party Maven plug-in support cannot keep up with the version iteration of 'kotlin/KSP' itself, and often encounters many problems during the upgrade process. Eventually, Jimmer dropped Maven support for Kotlin and asked Kotlin developers to use Gradle. After this configuration, running Maven or Gradle will generate additional source code based on user-defined entities. caution The above only applies to simple projects without separation. For real projects with separate entity definition, generator (annotation processor/ksp) must be configured in the project that defines entity types. Jimmer data types require one of: @Immutable @Entity @MappedSuperclass @Embeddable The first is ORM-agnostic, the others are ORM-related. If entities use the ORM annotations (eg: @Entity), the generated code requires jimmer-sql while entity code itself only needs jimmer-core: Maven Java (Gradle Plugin) Kotlin (Gradle Plugin) Java (Gradle) Kotlin (Gradle.kts) pom.xml ...other code omitted... org.babyfish.jimmer jimmer-core ${jimmer.version} org.babyfish.jimmer jimmer-sql ${jimmer.version} provided ...other dependencies omitted... ...other code omitted... build.gradle jimmer { // Ensure that jimmer-sql is only depended upon during code generation and compilation. ormCompileOnly = true ...other configurations omitted... } ...other code omitted... build.gradle.kts jimmer { // Ensure that jimmer-sql-kotlin is only depended upon during code generation and compilation. ormCompileOnly = true ...other configurations omitted... } ...other code omitted... ...other code omitted... dependencies { ...other dependencies omitted... // User entity code implementation \"org.babyfish.jimmer:jimmer-core:${jimmerVersion}\" // Generated code compileOnly \"org.babyfish.jimmer:jimmer-sql:${jimmerVersion}\" } ...other code omitted... ...other code omitted... dependencies { ...other dependencies omitted... // User entity code implementation(\"org.babyfish.jimmer:jimmer-core:${jimmerVersion}\") // Generated code compileOnly(\"org.babyfish.jimmer:jimmer-sql:${jimmerVersion}\") } ...other code omitted...","s":"Code Generation","u":"/jimmer-doc/docs/quick-view/get-started/generate-code","h":"#code-generation","p":1648},{"i":1652,"t":"If generation succeeded, developers should see: Java Kotlin note Screenshots are from Gradle project. For Maven, top level directory is target instead of build. caution Normally IDE marks generated code directories with icon. But sometimes IntelliJ fails to do so, preventing use of generated code. In this case, right-click on directory, choose Mark Directory As -> Generated Sources Root. Generated code includes: Java Kotlin Description XXXDraft.java XXXDraft.kt Mutable proxy interface for immutable object, object implementation, and methods to create and \"modify\" objects XXXProps.java XXXProps.kt Typed SQL DSL XXXTable.java XXXTableEx.java XXXFetcher.java XXXFetcher.kt Object fetcher DSL defining shape of complex query results","s":"Verify Successful Generation","u":"/jimmer-doc/docs/quick-view/get-started/generate-code","h":"#verify-successful-generation","p":1648},{"i":1655,"t":"Use https://start.spring.io/ to create a Spring Boot project. You need to choose your preferred language - Java or Kotlin. The choice of language is important because Jimmer supports two different sets of APIs. Java API - Ensures maximum developer usage Kotlin API - APIs designed specifically for Kotlin to optimize the development experience","s":"Create a Spring Boot Project","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#create-a-spring-boot-project","p":1653},{"i":1657,"t":"Jimmer itself is highly neutral and can be used without Spring Boot. But it also provides great integration with Spring Boot. Users can choose to use it with or without Spring Boot. Different choices require adding different dependencies. groupId: org.babyfish.jimmer artifactId: Integrate with Spring Boot Standalone Usage Java jimmer-spring-boot-starter jimmer-sql Kotlin jimmer-sql-kotlin Compared to standalone usage, integrating with Spring Boot is simpler. So this tutorial will demonstrate the jimmer-spring-boot-starter. Modify build.gradle or pom.xml to add dependencies: Maven Gradle Gradle (Kts) Gradle Plugin Gradle Plugin (kts) pom.xml 0.9.25 org.babyfish.jimmer jimmer-spring-boot-starter ${jimmer.version} ...other dependencies omitted... ext { jimmerVersion = '0.9.25' } dependencies { implementation \"org.babyfish.jimmer:jimmer-spring-boot-starter:${jimmerVersion}\" ...other dependencies omitted... } val jimmerVersion = \"0.9.25\" dependencies { implementation(\"org.babyfish.jimmer:jimmer-spring-boot-starter:${jimmerVersion}\") ...other dependencies omitted... } build.gradle plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ... other plugins omitted ... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"0.9.25\" } build.gradle.kts plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" ... other plugins omitted ... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"0.9.25\" } info If you are using Gradle as your build tool, you can also use third-party Gradle plugin tech.argonariod.gradle-plugin-jimmer provided by the community to automatically identify the project type and add dependencies automatically. The tech.argonariod.gradle-plugin-jimmer gradle plugin is community-provided and maintained to simplify Jimmer project configuration, and it is not officially maintained by Jimmer. Repository URL: https://github.com/ArgonarioD/gradle-plugin-jimmer","s":"Add Dependencies","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#add-dependencies","p":1653},{"i":1659,"t":"If using Kotlin, you must modify the Spring Boot configuration file - this is very important. warning Kotlin projects must configure jimmer.language application.properties application.yml jimmer.language = kotlin jimmer: language: kotlin","s":"Additional Configuration Needed for Kotlin","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#additional-configuration-needed-for-kotlin","p":1653},{"i":1661,"t":"In addition to the required jimmer.language for Kotlin projects, there are other useful configurations. Here are a few basic configurations that work for both Java and Kotlin: Property Type Default Description jimmer.dialect string org.babyfish.jimmer.sql.dialect.DefaultDialect Database dialect class name jimmer.show-sql boolean false Print executed SQL if true jimmer.pretty-sql boolean false Ensure that the printed SQL is well-formatted (compact by default) jimmer.database-validation-mode NONE|WARNING|ERROR NONE Validate consistency between database schema and entity types. WARNING logs inconsistencies, ERROR throws errors. See Spring/Appendix for complete documentation on configurations. application.properties application.yml jimmer.dialect = org.babyfish.jimmer.sql.dialect.MySqlDialect jimmer.show-sql = true jimmer.pretty-sql = true jimmer.database-validation-mode = ERROR ...other configurations omitted... jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect show-sql: true pretty-sql: true database-validation-mode: ERROR ...other configurations omitted...","s":"Other Useful Configurations","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#other-useful-configurations","p":1653},{"i":1663,"t":"In addition to Jimmer, some other dependencies are required like spring-web, JDBC driver, etc. Modify build.gradle or pom.xml to add dependencies: Maven Gradle Gradle (Kts) org.springframework.boot spring-boot-starter-web mysql mysql-connector-java 8.0.30 runtime ...other dependencies omitted... dependencies { implementation 'org.springframework.boot:spring-boot-starter-web' runtimeOnly 'mysql:mysql-connector-java:8.0.30' ...other dependencies omitted... } dependencies { implementation(\"org.springframework.boot:spring-boot-starter-web\") runtimeOnly(\"mysql:mysql-connector-java:8.0.30\") ...other dependencies omitted... }","s":"Add Other Required Dependencies","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#add-other-required-dependencies","p":1653},{"i":1666,"t":"In the previous article, we introduced that the web service does not need to define DTO types, directly returns entities, and uses @FetchBy annotations to restore all DTO type definitions in automatically generated client code. However, what if a query result is not returned to the Web remote client, but the server itself uses it? Java Kotlin List books = bookRepository.findBooksByName( \"graphql\", Fetchers.BOOK_FETCHER ❶ .name() .edition() ); for (Book book : books) { System.out.println(\"--------\"); System.out.println(\"Id: \" + book.id()); System.out.println(\"Name: \" + book.name()); System.out.println(\"Edition: \" + book.edition()); System.out.println(\"Price:\" + book.price()); ❷ } val books = bookRepository.findBooksByName( \"graphql\", newFetcher(Book::class).by { ❶ name() edition() } ) for (book in books) { println(\"--------\") println(\"Id: ${book.id}\") println(\"Name: ${book.name}\") println(\"Edition: ${book.edition}\") println(\"Price: ${book.price}\") ❷ } Here, there is no web service or remote call, it is just a call within the same JVM ❶ Only queries three properties of the object: id (implicit), name and edition ❷ Access the unqueried price property of the book object. This erroneous access will cause an exception: Exception type: org.babyfish.jimmer.UnloadedException Exception message: The property \"com.yourcompany.yourproject.model.Book.price\" is unloaded It can be seen that it is not enough to only consider automatically defining DTO types in remote client APIs. When the JVM itself directly uses query results, if sufficient compile-time security is required, defining DTO types for Java/Kotlin will be inevitable and necessary to ensure better compile-time safety.","s":"Java/Kotlin Applications Use Query Results","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#javakotlin-applications-use-query-results","p":1664},{"i":1668,"t":"The mutual conversion between entity objects and DTO objects is a boring, labor-intensive and error-prone thing that is common pain point in information management software development. Although many frameworks are trying to mitigate this problem, development efficiency has remained unable to be improved qualitatively. In order to minimize the cost of DTO type creation, Jimmer introduces the DTO language, which supplements the Java/Kotlin type system and can quickly generate Java/Kotlin DTO type definitions at compile time. This article only provides a quick overview without detailed introduction. For complete information, please refer to DTO Language","s":"DTO Language","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#dto-language","p":1664},{"i":1670,"t":"A jimmer user provide Intellij plugins for the DTO language. For details, see https://github.com/ClearPlume/jimmer-dto Installing the DTO language plugin is not required, but you can get a better development experience after installation, so it is recommended to install.","s":"DTO Language Plugin","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#dto-language-plugin","p":1664},{"i":1672,"t":"For any Java/Kotlin project that needs to use the DTO language, create a subdirectory dto under its src/main directory. That is, src/main/dto is where DTO files are stored. Create a Book.dto file under src/main/dto and enter the following code: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto SimpleBookView { id name } ComplexBookView { #allScalars(this) store { id name } authors { id firstName lastName } } Compile the project (either use gradle/maven commands on the command line or click gradle/maven build on the right side of Intellij) to generate related DTO types","s":"Define DTO Files","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#define-dto-files","p":1664},{"i":1674,"t":"After compilation, the following two types SimpleBookView and ComplexView will be generated automatically. The code for each is as follows: SimpleBookView Java Kotlin SimpleBookView.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class SimpleBookView implements View { ❷ private long id; @NotNull private String name; public SimpleBookView(@NotNull Book base) { ❸ ...omitted... } @Override public Book toEntity() { ❹ ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... } SimpleBookView.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class SimpleBookView( val id: Long val name: String ) : View { ❷ constructor(base: Book): ❸ this(...omitted...) override fun toEntity(): Book = ❹ ...omitted... ...Omit other members... } ❶ Reminds users that this is code automatically generated by Jimmer ❷ Output DTO based on Book entity needs to implement View interface ❸ Converts entity to DTO ❹ Converts DTO to entity ComplexBookView Java Kotlin ComplexBookView.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class ComplexBookView implements View { ❷ private long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private TargetOf_store store; @NotNull private List authors; public ComplexBookView(@NotNull Book base) { ❸ ...omitted... } @Override public Book toEntity() { ❹ ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... public static class TargetOf_store implements View { ❺ private long id; @NotNull private String name; public TargetOf_store(@NotNull BookStore base) { ...omitted... } @Override public BookStore toEntity() { ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... } public static class TargetOf_authors implements View { ❻ private long id; @NotNull private String firstName; @NotNull private String lastName; public TargetOf_authors(@NotNull Author base) { ...omitted... } @Override public Author toEntity() { ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... } } ComplexBookView.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class ComplexBookView( val id: Long, val name: String, val edition: Int, val price: BigDecimal, val store: TargetOf_store?, val authors: List ) : View { ❷ constructor(base: Book): ❸ this(...omitted...) override fun toEntity(): Book = ❹ ...omitted... data class TargetOf_store( ❺ val id: Long, val name: String ) : View { constructor(base: BookStore): this(...omitted...) override fun toEntity(): BookStore = ...omitted... } data class TargetOf_authors( ❻ val id: Long, val firstName: String, val lastName: String ) : View { constructor(base: Author): this(...omitted...) override fun toEntity(): Author = ...omitted... } } ❶ Reminds users that this is code automatically generated by Jimmer ❷ Output DTO based on Book entity needs to implement View interface ❸ Converts entity to DTO ❹ Converts DTO to entity ❺ DTO definition of associated object referenced by many-to-one association Book.store ❻ DTO definition of associated object referenced by many-to-many association Book.authors","s":"View Generated DTOs","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#view-generated-dtos","p":1664},{"i":1677,"t":"In the Feature Introduction article, we wrote a BookRepository class Java Kotlin public class BookRepository { @Nullable public Book findBookById( long id, Fetcher fetcher ) { ...omitted... } public List findBooksByName( @Nullable String name, @Nullable Fetcher fetcher ) { ...omitted... } ...Omit other members... } BookRepository.kt class BookRepository( ...Omit other members... ) { fun findBookById( id: Long, fetcher: Fetcher ): Book? = ...omitted... fun findBooksByName( name: String? = null, fetcher: Fetcher? = null ): List = ...omitted... } Each query method adds a parameter of type Fetcher. We can use it to flexibly control the format of queried objects (that is, the shape of queried data structures). This is the recommended usage. The Repository is only responsible for filtering, sorting, paging and other operations, but does not control the format of the returned data. Instead, it exposes the control of the data format through the Fetcher parameter to allow upper layer business logic to decide.","s":"Review Old BookRepository","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#review-old-bookrepository","p":1664},{"i":1679,"t":"Now, this BookRepository no longer meets our requirements. Because we no longer want to query Jimmer entities, but want to query DTO types automatically generated by the DTO language, we need to modify it. However, we want BookRepository to still maintain the excellent quality of exposing shape control externally. The modified code is as follows. Java Kotlin @Component public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Nullable public > V findBookById( ❶ long id, Class viewType ❷ ) { return sqlClient.findById( viewType, ❸ id ); } public > List findBooksByName( ❹ @Nullable String name, Class viewType ❺ ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().ilike(name) ) .select( table.fetch(viewType) ❻ ) .execute(); } } BookRepository.kt @Component class BookRepository( private val sqlClient: KSqlClient ) { fun > findBookById( ❶ id: Long, viewType: KClass ❷ ): V? = sqlClient.findById( viewType, ❸ id ) fun > findBooksByName( ❹ name: String? = null, viewType: KClass ❺ ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } select( table.fetch(viewType) ❻ ) } .execute() } ❶ ❹: > in java or > in kotlin defines a generic parameter V representing any Output DTO type based on Book. For example: SimpleBookView and ComplexBookView generated above implement the View interface. ❷ ❺: Use the type of any DTO based on Book as a parameter. The return type varies with the change of the parameter type to achieve querying any DTO type and hand over the decision of the DTO type to the upper caller. ❸ ❻: Let Jimmer query data of the specified type tip The DTO type internally includes a Fetcher matching the shape. First, entity data structures matching the shape are queried through this Fetcher, and then automatically converted to DTO types.","s":"Write New BookRepository","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#write-new-bookrepository","p":1664},{"i":1681,"t":"Take bookRepository.findById as an example Query relatively simple SimpleBookView Java Kotlin System.out.println( bookRepository.findBookById( 1L, SimpleBookView.class ) ); println( bookRepository.findBookById( 1L, SimpleBookView::class ) ) Print output: SimpleBookView( id=1, name=Learning GraphQL ) Query relatively complex ComplexBookView Java Kotlin System.out.println( bookRepository.findBookById( 1L, ComplexBookView.class ) ); println( bookRepository.findBookById( 1L, ComplexBookView::class ) ) Print output: ComplexBookView( id=1, name=Learning GraphQL, edition=1, price=50.0, store=ComplexBookView.TargetOf_store( id=1, name=O'REILLY ), authors=[ ComplexBookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello ), ComplexBookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks ) ] )","s":"Try New BookRepository","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#try-new-bookrepository","p":1664},{"i":1683,"t":"Although the DTO language is more suitable for Java/Kotlin applications to use query results internally, you can also use them as return information for HTTP APIs without any difference from using ordinary POJOs. Java Kotlin BookController.java @RestController public class BookController implements Fetchers { private final BookRepository bookRepository; public BookController(BookRepository bookRepository) { this.bookRepository = bookRepository; } @Nullable @GetMapping(\"/book/{id}\") public ComplexBookView findBookById(@PathVariable(\"id\") long id) { return bookRepository.findBookById( id, ComplexBookView.class ); } @GetMapping(\"/books\") public List findBooksByName( @RequestParam(name = \"name\", required = false) String name ) { return bookRepository.findBooksByName( name, SimpleBookView.class ); } } BookController.kt @RestController class BookController( private val bookRepository: BookRepository ) { @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long ): ComplexBookView = bookRepository.findBookById( id, ComplexBookView::class ) @GetMapping(\"/books\") fun findBooksByName( @RequestParam(required = false) name: String ): List = bookRepository.findBooksByName( name, SimpleBookView::class ) }","s":"Write BookController","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#write-bookcontroller","p":1664},{"i":1685,"t":"In the previous article, we mentioned that Jimmer can copy the document comments in Java/Kotlin code to the client Api, whether it is OpenApi online documentation or generated TypeScript code. The method introduced in this article has the same functionality, but it needs to be explained that the types and properties in the DTO language support document comments like Java/Kotlin types, so the DTO language can override Java/Kotlin document comments. For example, the original entity definition is as follows Java Kotlin /** * The book entity */ @Entity public interface Book { /** * The name of book entity */ String name(); ...Omit other members... } /** * The book entity */ @Entity interface Book { /** * The name of book entity */ val price: BigDecimal ...Omit other members... } The document comments here are the original document comments. The DTO Language also supports document comments. For example: Book.Dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto /** * Simple book dto */ SimpleBookView { /** * The name of simple book dto */ name ...Omit other members... } ...Omit other DTO definitions... info The document comment of the DTO Language has higher priority. That is, the document comments in the DTO language can override the document comments of the original entity, finally it is used to generate OpenApi documentation or TypeScript code.","s":"Document Comments","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#document-comments","p":1664},{"i":1687,"t":"If the associated object only has the id property, the associated Id will be better than the associated object. For example: Using associated objects will lead to a large number of objects with only id properties, making the results slightly redundant: { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 50.00, \"store\": { \"id\": 1 }, \"authors\": [{ \"id\": 1 }, { \"id\": 2 }] } Using associated Ids makes the results relatively concise: { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 50.00, \"storeId\": 1, \"authorIds\": [1, 2] } If you choose to return DTO (instead of directly returning entities as in the previous article), you can define the following DTO code: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto ShallowBookView { #allScalars(this) id(store) id(authors) as authorIds } ...Omit other DTO definitions... After compilation, the following code is generated: Java Kotlin ShallowBookView.java @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class ShallowBookView implements View { private long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private Long storeId; @NotNull private List authorIds; ...Omit other members... } ShallowBookView.kt @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class ShallowBookView( val id: Long, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, val authorIds: List ): View { ...Omit other members... }","s":"Flat Association ID","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#flat-association-id","p":1664},{"i":1689,"t":"A large part of server development teams will deal with a type of frontend development team who do not accept data structures composed of associated multiple objects, and only want to accept a huge single object. So they require all non-collection associations to be flattened. That is: They do not accept structured return information: { \"prop1\": 1, \"prop2\": 2, \"a\": { \"prop1\": 3, \"prop2\": 4, \"b\": { \"prop1\": 5, \"prop2\": 6, } }, \"c\": { \"prop1\": 7, \"prop2\": 8, \"d\": { \"prop1\": 9, \"prop2\": 10, } } } Insist on asking for such flat data: { \"prop1\": 1, \"prop2\": 2, \"aProp1\": 3, \"aProp2\": 4, \"aBProp1\": 5, \"abProp2\": 6, \"cProp1\": 7, \"cProp2\": 8, \"cdProp1\": 9, \"cdProp2\": 10 } In fact, such flat non-structured data is a disaster for client programs that need state management. But such frontend teams only do UI rendering without state management, so they do not realize this problem and insist on it very much. When you can't argue but need to complete the task quickly, write DTO code as follows: Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto FlatBookView { #allScalars(this) flat(store) { ❶ as(^ -> store) { ❷ #allScalar(this) } } } ...Omit other DTO definitions... ❶ The flat function means to flatten the properties of the associated object pointed to by the Book.store one-to-many association to the current object. ❷ For the properties of the associated object, the property name needs to be changed after being flattened to the current object. Prefix the old property name with store. For example, name -> storeName. After compilation, the following code is generated: Java Kotlin FlatBookView.java @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class FlatBookView implements View { private long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private Long storeId; @Nullable private String storeName; @Nullable private String storeWebsite; ...Omit other members... } FlatBookView.kt @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class FlatBookView( val id: Long, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, val storeName: String?, val storeWebsite: String? ): View { ...Omit other members... } Here, the flattened properties are all nullable, because the Book.store association itself allows null.","s":"Flat Associated Objects","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#flat-associated-objects","p":1664},{"i":1691,"t":"To quickly preview Jimmer's main features, we need to provide several entities here as the basic assumption of all discussions in this section.","s":"Precondition","u":"/jimmer-doc/docs/quick-view/precondition","h":"","p":1690},{"i":1693,"t":"tip In Jimmer applications, the only thing that matters is the unified global ORM entity model. The global entity model is finalized with the database design, irrelevant to specific query/modification business logics' requirements for interaction formats, and relatively stable. As for what kind of DTO types each query/modification business needs to interact with, it is completely unimportant. Either no DTO is needed at all, e.g. Quick View/Query Arbitrary Shape/Exposing Features/Return Entities Directly. Or DTO types can be quickly generated through Object/DTO Conversion/DTO Language, making DTO extremely cheap. Only the relatively stable entity model is important. So Jimmer is good at handling changing requirements.","s":"Status of Entities","u":"/jimmer-doc/docs/quick-view/precondition","h":"#status-of-entities","p":1690},{"i":1695,"t":"Here we list three entity types: BookStore, Book, Author and TreeNode, as the basic assumptions for all discussions in the current section.","s":"UML Relationships Between Entities","u":"/jimmer-doc/docs/quick-view/precondition","h":"#uml-relationships-between-entities","p":1690},{"i":1698,"t":"Java Kotlin @Entity public interface BookStore { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); @Nullable String website(); @OneToMany(mappedBy = \"store\") List books(); } @Entity interface BookStore { @Id @@GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String val website: String? @OneToMany(mappedBy = \"store\") val books: List }","s":"BookStore","u":"/jimmer-doc/docs/quick-view/precondition","h":"#bookstore","p":1690},{"i":1700,"t":"Java Kotlin @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); BigDecimal price(); @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); } @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: Int val price: BigDecimal @ManyToOne val store: BookStore? @ManyToMany val authors: List }","s":"Book","u":"/jimmer-doc/docs/quick-view/precondition","h":"#book","p":1690},{"i":1702,"t":"Java Kotlin @Entity public interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) UUID id(); @Key String firstName(); @Key String lastName(); Gender gender(); @ManyToMany(mappedBy = \"authors\") List books(); } @Entity interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val firstName String @Key val lastName: String val gender: Gender @ManyToMany(mappedBy = \"authors\") val books: List } Where Gender is a very simple enum type Java Kotlin public enum Gender { MALE, FEMALE } enum class Gender { MALE, FEMALE }","s":"Author","u":"/jimmer-doc/docs/quick-view/precondition","h":"#author","p":1690},{"i":1704,"t":"The save directive is a very powerful capability of Jimmer. With just one function call, data structures of any shape can be saved. Whether the data structure to be saved is simple (such as a single object or even a mutilated object) or complex (an aggregate root object holds many associated objects through associative relationships, with unlimited depth and breadth), it can be saved into the database with one function call. tip Saving operations for single table records has never been the difficulty of application development. Even without using any ORM framework, it is very easy to achieve with direct use of JDBC. However, saving complex data structures is not so easy. Developers will have to query existing data structures from the database and compare them with the data structures to be saved, so as to discover multiple changed parts and convert them into corresponding INSERT, UPDATE and DELETE statements. This process is very cumbersome and error-prone. Therefore, from the very beginning, Jimmer focused on how to save complex data structures, rather than how to save a single entity object.","s":"2. Save Arbitrary Shape","u":"/jimmer-doc/docs/quick-view/save/","h":"","p":1703},{"i":1706,"t":"Jimmer's Two Usages Use Jimmer's Spring Boot Starter Directly use the underlying SqlClient Jimmer has complete sample projects. For how to use Jimmer's Spring Boot Starter, please refer to the examples. This article discusses using the underlying sqlClient directly without Spring.","s":"Final Usage","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"","p":1705},{"i":1708,"t":"SqlClient is the lowest-level API in Jimmer Java org.babyfish.jimmer.sql.JSqlClient Kotlin org.babyfish.jimmer.sql.kt.KSqlClient You need to create a global object of this type, which is the API entry point for all ORM behaviors of Jimmer. Multiple data sources require creating multiple global objects. However, here we discuss the most common case of a single data source, where one global object is sufficient. Since we are using the Jimmer Spring Boot Starter, in this case, please specify the following configuration in application.yml (or application.properties) Java Kotlin spring: datasource: driver-class-name: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/jimmer_demo username: root password: 123456 jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect show-sql: true pretty-sql: true database-validation-mode: ERROR spring: datasource: driver-class-name: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/jimmer_demo username: root password: 123456 jimmer: language: kotlin // This is important for kotlin dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect show-sql: true pretty-sql: true database-validation-mode: ERROR The Jimmer Spring Boot Starter will automatically create this global object Note that for Kotlin, in order to create KSqlClient instead of JSqlClient, you need to configure jimmer.language = kotlin in application.yml/application.properties. info Therefore, you can directly inject an object of type JSqlClient/KSqlClient anywhere. The subsequent code in this article will assume there is a sqlClient variable and use it, but it will not provide an explanation, as a detailed explanation has already been given here.","s":"SqlClient","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#sqlclient","p":1705},{"i":1710,"t":"Java Kotlin package com.example.model.repository; import org.babyfish.jimmer.sql.JSqlClient; import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.babyfish.jimmer.Page; import com.example.model.Book; import com.example.model.BookTable; public class BookRepository { private static final BookTable T = BookTable.$; private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } public Page findBooks( int pageIndex, // Starts from 0 int pageSize, @Nullable Fetcher fetcher, // e.g. \"name asc, edition desc\" @Nullable String sortCode, @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName, @Nullable Gender authorGender ) { return sqlClient .createQuery(T) .where(T.name().ilikeIf(name)) .where(T.price().betweenIf(minPrice, maxPrice)) .where(T.store().name().ilikeIf(storeName)) .where(T.store().website().ilikeIf(storeWebsite)) .where( T.authors(author -> Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .where(T.authors(author -> author.gender().eqIf(authorGender))) .orderBy( Order.makeOrders( T, sortCode != null ? sortCode : \"name asc, edition desc\" ) ) .select( T.fetch(fetcher) ) .fetchPage(pageIndex, pageSize); } } package com.example.model.repository import org.babyfish.jimmer.sql.kt.KSqlClient import org.babyfish.jimmer.sql.fetcher.Fetcher import org.babyfish.jimmer.Page import com.example.model.* class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( pageIndex: Int, // Starts from 0 pageSize: Int = 10, fetcher: Fetcher? = null, sortCode: String = \"name asc, edition desc\", name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, authorName: String? = null, authorGender: Gender? = null ): Page = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.website `ilike?` storeWebsite) where += table.authors { or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } where += table.authors { gender `eq?` authorGender } orderBy(table.makeOrders(sortCode)) select( table.fetch(fetcher) ) } .fetchPage(pageIndex, pageSize) } Users can create BookRepository objects and combine the parameters in various ways to test: Dynamic queries (including dynamic joins, implicit subqueries) Dynamic sorting Paged queries Details omitted here.","s":"Query","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#query","p":1705},{"i":1713,"t":"In the src/main/dto directory, create any file with extension dto and edit its code: export com.example.model.Book -> package com.example.model.dto input BookInput { #allScalars(this) id(store) // as storeId id(authors) as authorIds } Compile to generate the Java/Kotlin DTO type com.example.model.dto.BookInput: View Generated Code Then modify the BookRepository: Java Kotlin public class BookRepository { ...other members omitted... public long saveBook(BookInput input) { return sqlClient .save(input) .execute() .getModifiedEntity() // Return auto-generated id if `input.id` is null .getId(); } } class BookRepository { ...other members omitted... fun saveBook(input: BookInput): Long = sqlClient .save(input) .modifiedEntity // Return auto-generated id if `input.id` is null .id }","s":"Save Short Associations","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#save-short-associations","p":1705},{"i":1715,"t":"In the src/main/dto directory, create any file with extension dto and edit its code: export com.example.model.BookStore -> package com.example.model.dto input CompositeBookStoreInput { #allScalars(this) books { #allScalars(this) -id } } Compile to generate the Java/Kotlin DTO type com.example.model.dto.CompositeBookStoreInput: View Generated Code Then create the BookStoreRepository: Java Kotlin public class BookStoreRepository { public long saveBookStore(CompositeBookStoreInput input) { return sqlClient .save(input) .execute() .getModifiedEntity() // Return auto-generated id if `input.id` is null .getId(); } } class BookStoreRepository { fun saveBookStore(input: CompositeBookStoreInput): Long = sqlClient .save(input) .modifiedEntity // Return auto-generated id if `input.id` is null .id }","s":"Save Long Associations","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#save-long-associations","p":1705},{"i":1717,"t":"Modify the BookRepository: Java Kotlin public class BookRepository { ...other members omitted... public void deleteBook(long id) { sqlClient.deleteById(Book.class, id); } } class BookRepository { ...other members omitted... fun deleteBook(id: Long) { sqlClient.deleteById(Book::class, id) } }","s":"Delete","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#delete","p":1705},{"i":1719,"t":"In Save Any Shape/Feature Introduction, we introduced the powerful data saving capability of Jimmer, but also pointed out that for security reasons, Jimmer dynamic entities cannot be directly used as input parameters to directly expose this capability. To protect system security, DTO Language needs to be used to define Input DTO. Unlike Jimmer dynamic entities, InputDTO is static with fixed shape. Using Input DTO as the type constraint of the input parameters of remote APIs can solve security issues.","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/save/export/","h":"","p":1718},{"i":1721,"t":"Unlike ORMs like JPA/Hibernate, entities in Jimmer are defined as interfaces instead of classes. The reasons are discussed in Why Interfaces. Before defining entities, two concepts need to be introduced: Jimmer entities are not simple Java beans, but dynamic objects. That is, an unset property is completely different from a property set to null. Jimmer entities are immutable, so interfaces only have getters, no setters.","s":"Define Entities","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"","p":1720},{"i":1723,"t":"Assume the entity package is \"com.example.model\". Ignore associated properties first, entity definitions are: BookStore Java Kotlin BookStore.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface BookStore { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); @Nullable String website(); } BookStore.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface BookStore { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String val website: String? } Book Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import java.math.BigDecimal; @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); int edition(); BigDecimal price(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* import java.math.BigDecimal @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String val edition: Int val price: BigDecimal } Author Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String firstName(); String lastName(); /* * Gender is an enum defined later */ Gender gender(); } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val firstName: String val lastName: String /* * Gender is an enum defined later */ val gender: Gender } Where Gender is an enum with two options: MALE and FEMALE. ORMs can map enums to strings (default) or numbers. Although this example maps enum to string by default, the database has a check constraint limiting values to 'M' and 'F', not default 'MALE' and 'FEMALE'. So the enum needs to be configured as: Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.EnumItem; public enum Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE } Author.kt package com.example.model import org.babyfish.jimmer.sql.EnumItem enum class Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE } TreeNode Java Kotlin TreeNode.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface TreeNode { @Id @Column(name = \"NODE_ID\") @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); } TreeNode.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface TreeNode { @Id @Column(name = \"NODE_ID\") @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String } For Java, each getter can use the traditional Java bean get/is prefix like getName(), or omit it like name() in this example. note Breaking the Java bean convention of getter prefixes is enabled by Java 14 records, not Jimmer. The new style allows more concise immutable objects. Jimmer entities are very sensitive to nullability: For Kotlin, use language's own nullity. For Java: Primitives like boolean, char, byte, short, int, long, float, double are non-null. Boxed types like Boolean, Character, Byte, Short, Integer, Long, Float, Double are nullable. Other types are non-null by default. Add @Nullable to allow null. Annotations used in example: @Entity - Indicates entity type. @Id - Specifies ID property. @GeneratedValue - Specifies auto-generated ID, using database autoincrement here. Java/Kotlin interface short name is converted to table name using word1Word2...WordN -> WORD1_WORD2_..._WORDN. If mismatch, use @Table on interface. Similarly, property name is converted to column name. If mismatch, use @Column on property. note Note @Column can be used on non-foreign key fields, not just foreign keys discussed later. Entities have non-null ID like long, not nullable ID like Long, otherwise framework will report error. note JPA/Hibernate users note this difference in handling ID nullability.","s":"Define Non-Associated Fields","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#define-non-associated-fields","p":1720},{"i":1725,"t":"Modify Book.java/Book.kt to add store association: Java Kotlin Book.java package com.example.model; ...imports omitted... @Entity public interface Book { ...other properties omitted... @ManyToOne @Nullable BookStore store(); } Book.kt package com.example.model ...imports omitted... @Entity interface Book { ...other properties omitted... @ManyToOne val store: BookStore? } @ManyToOne declares one-to-many association, mapping foreign key to associated entity. Property name is converted to foreign key column like store -> STORE_ID, matching database. If mismatch, use @JoinColumn on property.","s":"One-to-Many Association Book.store","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#one-to-many-association-bookstore","p":1720},{"i":1727,"t":"Modify BookStore.java/BookStore.kt to add books association: Java Kotlin BookStore.java package com.example.model; ...imports omitted... @Entity public interface BookStore { ...other properties omitted... @OneToMany(mappedBy = \"store\") List books(); } BookStore.kt package com.example.model ...imports omitted... @Entity interface BookStore { ...other properties omitted... @OneToMany(mappedBy = \"store\") val books: List } @OneToMany declares one-to-many association. It does not map any database field, just mirrors @ManyToOne to make association bidirectional. Here, mappedBy = \"store\" means BookStore.books is mirror of Book.store. @Entity public interface BookStore { @OneToMany( mappedBy = \"store\" ) List books(); ... } @Entity public interface Book { @ManyToOne @Nullable BookStore store(); ... } The side with mappedBy is called the mirror side. Mirroring is optional, bidirectional association is not required. Unlike JPA/Hibernate, @OneToMany in Jimmer can only mirror @ManyToOne, always implying bidirection.","s":"One-to-Many Association BookStore.books","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#one-to-many-association-bookstorebooks","p":1720},{"i":1729,"t":"Modify Book.java/Book.kt to add authors association: Java Kotlin Book.java package com.example.model; ...imports omitted... @Entity public interface Book { ...other properties omitted... @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); } Book.kt package com.example.model ...imports omitted... @Entity interface Book { ...other properties omitted... @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List } @ManyToMany declares many-to-many association. There are two sides of many-to-many: owner and mirror. This is the owner side. For owner, @JoinTable can specify join table: name: Join table name (default based on entities) joinColumnName: FK to current entity (Book) inverseJoinColumnName: FK to target entity (Author) note Here @JoinTable uses all default values, so it can be omitted.","s":"Many-to-Many Association Book.authors","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#many-to-many-association-bookauthors","p":1720},{"i":1731,"t":"Modify Author.java/Author.kt to add books association: Java Kotlin Author.java package com.example.model; ...imports omitted... @Entity public interface Author { ...other properties omitted... @ManyToMany(mappedBy = \"authors\") List books(); } Author.kt package com.example.model ...imports omitted... @Entity interface Author { ...other properties omitted... @ManyToMany(mappedBy = \"authors\") val books: List } Here, mappedBy makes this the mirror side of the many-to-many mapping. @ManyToMany(mappedBy = \"authors\") means Author.books mirrors Book.authors. @Entity public interface Author { @ManyToMany( mappedBy = \"authors\" ) List books(); ... } @Entity public interface Book { @ManyToMany @JoinTable(...略...) List authors(); ... } Mirroring many-to-many is optional, bidirection association is optional. But if bidirectional, one side must be owner and the other one must be mirror. tip Unlike JPA/Hibernate, owner vs mirror does not affect save behavior in Jimmer. You can choose freely.","s":"Many-to-Many Association Author.books","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#many-to-many-association-authorbooks","p":1720},{"i":1733,"t":"Now we understand associations. Let's quickly complete TreeNode: Java Kotlin TreeNode.java package com.example.model; ...imports omitted... @Entity public interface TreeNode { ...other properties omitted... @ManyToOne @Nullable TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } TreeNode.kt package com.example.model ...imports omitted... @Entity interface TreeNode { ...other properties omitted... @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List }","s":"Complete TreeNode Definition","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#complete-treenode-definition","p":1720},{"i":1735,"t":"We've seen entities declared as interfaces, not classes. Why? Dynamicity Jimmer entities are not simple Java beans, but dynamic objects. Unset vs null property are totally different Accessing non-existent property throws UnloadedException Serializing with Jackson omits unset properties See Dynamic for details on dynamicity. Benefits of dynamicity Easily express arbitrary complex data structures. Entities can be partial object, complete object, or aggregate root of complex tree. Since data structure is flexible, ORM can query and save entire object graph in one go instead of individual entities. For querying, dynamic entity graphs can directly return from HTTP services without needing DTOs. Compared to dynamic language ORMs As discussed, Jimmer exploits dynamicity for flexibility unmatched by static language ORMs. But it rejects unsafety and unmaintainability of dynamic languages. Jimmer entities remain ordinary Java/Kotlin objects with all static typing, even null safety in Kotlin. note The only unsafety is UnloadedException when accessing unloaded properties, similar to LazyInitializationException in JPA/Hibernate. This is a necessary cost universally accepted in ORM. tip Jimmer finds the optimal balance between dynamic language flexibility and static language safety. Immutability We've seen entities only have getters, meaning they are immutable. Mutable object allows circular references which the most headache problem of business system, Immutable data avoids this risk. However, enjoying and leveraging the advantages of immutable objects while suppressing their disadvantages is not an easy thing, especially for scenarios like ORM where the object hierarchy is very deep. Luckily, in the JavaScript/TypeScript domain, there is a framework called immer that provides a perfect way to handle deep immutability. Jimmer ports immer to Java/Kotlin and makes it the foundational programming model for the entire ORM. The name \"Jimmer\" is also a tribute to immer. See Immutability/Solution for details on how to create and \"modify\" immutable objects. In summary, because Jimmer entities themselves are dynamic and immutable, they are not simple Java objects. Their types have complex internal implementations. Therefore, Jimmer chooses to have developers write interfaces, and generate implementations at compile-time using AnnotationProcessors (Java) or KSP (Kotlin).","s":"Why Interfaces","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#why-interfaces","p":1720},{"i":1738,"t":"Save instructions allow developers to save data structures of any shape, rather than save simple objects. By default, when AssociatedSaveMode is set to REPLACE, Jimmer will completely replace the existing data structure in the database with the structure being saved, as shown in the figure: Top right: Users pass in a data structure of any shape for Jimmer to write to the database. Top left: Query the existing data structure from the database to compare with the new data structure passed in by users. Whatever shape of data structure the user passes in, the same shape will be queried from the database, ensuring the shapes of old and new data structures are identical. Therefore, the querying and comparison costs are determined by the complexity of the user-provided data structure. Below:Compare the new and old data structures, find the DIFF and execute corresponding SQL operations to make them consistent: Orange parts: For entity objects that exist in both new and old data structures, modify data if scalar properties have changed Blue parts: For entity objects that exist in both new and old data structures, modify associations if they have changed Green parts: For entity objects that exist in the old data structure but not in the new one, decouple this object, clear associations and possibly delete data Red parts: For entity objects that exist in the new data structure but not in the old one, insert data and establish associations tip Unlike other ORMs, Jimmer doesn't require describing how data should be saved in the entity model Whether certain scalar properties need to be saved Taking JPA as an example, this is controlled throughColumn.insertable andColumn.updatable. Whether certain association properties need to be saved Taking JPA as an example, this is controlled throughOneToOne.cascade,ManyToOne.cascade,OenToMany.cascade andManyToOne.cascade. Jimmer adopts a completely different strategy - its entity objects are not POJOs and can flexibly control the shape of data structures. That is, entity objects have dynamic properties - not specifying a property for an entity object and setting an entity's property to null are completely different things. For any entity object, Jimmer will only save the specified properties while ignoring unspecified ones. Therefore, Jimmer doesn't need to consider data saving behavior during entity modeling, but rather describes the expected behavior at runtime through the data structure being saved itself, providing absolute flexibility.","s":"Concept","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#concept","p":1736},{"i":1740,"t":"The UI design for modifying data in an application can be divided into two styles: Fully Commit This type of UI often has complex forms and provides a final button. After editing, the user submits all the information in the form at once. Incremental Commit This type of UI does not have a submit button. Each time the user completes a local operation, the page automatically submits the changed part, which is a fragmented commit mode. The greatest value of the Save Command lies in simplifying the development of fully commit mode functionality. For the two different modes, the usage is different. Fully Commit Incremental Commit Jimmer automatically handles the internal details, comparing the new and old data to find all differences and executing the relevant modification operations (Jimmer's unique perspective) Use the Save Command (parameters are often complex data structures) Business code uses a combination of multiple simple operations to implement complex operations, and the user handles the internal details (the same as traditional methods). Comprehensively use multiple methods: Save Command (parameters are often relatively simple objects) Delete Command Update Statement Delete Statement Directly Modify Join Tables Developers need to analyze their business scenarios to determine whether the current modification operation is a fully commit or an incremental commit, and make the right choice accordingly, without abuse.","s":"Scenarios","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#scenarios","p":1736},{"i":1742,"t":"In actual development, the data to be saved is always submitted by the client and can be passively accepted by the server (for example, @RequestBody in Spring). However, to simplify the discussion here, we directly hard code the object to be saved, so the code for the saved parameters is relatively more. Save simple object Java Kotlin sqlClient.save( Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(4); draft.setPrice(new BigDecimal(\"59.9\")); }) ); sqlClient.save( Book { name = \"GraphQL in Action\" edition = 4 price = BigDecimal(\"59.9\") } ) note Here, the id property of the object to be saved is not specified. Jimmer will determine whether related data exists in the database according to the name and edition properties, so as to decide whether to INSERT or UPDATE. This is because in the entity definition, Book.name and Book.edition are annotated with @org.babyfish.jimmer.sql.Key. This article is just a quick preview and does not go deep into it. Interested parties can view Mapping Part/Advanced Mapping/Key and Mutation Part/Save Command. Save data structures formed by multiple objects Java Kotlin sqlClient.save( Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(4); draft.setPrice(new BigDecimal(\"59.9\")); draft.applyStore(store -> { store.setName(\"MANNING\"); store.setWebsite(\"https://www.manning.com\"); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Bob\"); author.setLastName(\"Rockefeller\"); author.setGender(Gender.MALE); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Eve\"); author.setLastName(\"Procello\"); author.setGender(Gender.FEMALE); }); }) ); sqlClient.save( Book { name = \"GraphQL in Action\" edition = 4 price = BigDecimal(\"59.9\") store { name = \"MANNING\" website = \"https://www.manning.com\" } authors().addBy { firstName = \"Bob\" lastName = \"Rockefeller\" gender = Gender.MALE } authors().addBy { firstName = \"Eve\" lastName = \"Procello\" gender = Gender.FEMALE } } );","s":"Demo","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#demo","p":1736},{"i":1744,"t":"In the previous text, we demonstrated two examples, one describing how to save a simple object, and the other describing how to save an aggregate root object and cascade save more associated objects. It is obvious that Jimmer's save directive can appear both simple and complex, depending on whether the data structure expressed by the dynamic entity passed by the user is simple or complex. Jimmer does not provide configuration cascade options for association properties like traditional ORM, because it is not necessary at all. The dynamic entity gives Jimmer's save capability unlimited possibilities, so there is no need to limit it to some fixed configuration. This absolute flexibility has many wonderful uses. For example, changing the price of book with id 100 to 60, the traditional ORM and Jimmer approaches are different: Traditional ORM (take JPA as an example) adopts find first and then modify, which is intuitive but wastes performance Book book = entityManager.find(Book.class, 100L); if (book != null) { book.setPrice(new BigDecimal(60)); // entityManager.merge(book); //Omit if the current JPA transaction context exists } Jimmer's approach, make up a mutilated object and directly update Java Kotlin boolean matched = sqlClient.update( Immutables.createBook(draft -> { draft.setId(100L); draft.setPrice(new BigDecimal(60)); // No other properties except `id` and `price` are specified // So no other properties except `price` will be affected }) ).getTotalAffectedRowCount() != 0; val matched = sqlClient.update( Book { id = 100L price = BigDecimal(60) // No other properties except `id` and `price` are specified // So no other properties except `price` will be affected } ).totalAffectedRowCount != 0","s":"Essential Difference from Other ORM","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#essential-difference-from-other-orm","p":1736},{"i":1746,"t":"The ability to save data structures of arbitrary shapes is too powerful so that it cannot be exposed directly, otherwise, it will lead to huge security vulnerabilities. For example: warning Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/book\") pubic int saveBook( @RequestBody Book book ) { return sqlClient .save(book) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @PutMapping(\"/book\") fun saveBook( @RequestBody book: Book ): Int = sqlClient .save(book) .totalAffectedRowCount } This method can work and is very powerful. The client can upload any data structure with Book as the aggregate root for the server to save. But this is also dangerous. You cannot limit the complexity of the data structure uploaded by the client. The client can arbitrarily modify associated data of any depth through this API. Even if you try to verify and limit the shape of the book parameter, it is still very easy to overlook and make mistakes. warning Therefore, the powerful Jimmer data saving capability can only be used as an underlying support internally in the service, and cannot expose this capability directly to remote clients by using dynamic entities as input parameters, because this will result in the security door wide open. To safely expose Jimmer's data saving capabilities, please continue reading the next article: Exposing Features","s":"Note: Cannot Expose Directly","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#note-cannot-expose-directly","p":1736},{"i":1749,"t":"A short association refers to only changing the association relationship between the current object and other objects, without further modifying the associated object. For the UI interface: Reference association (one-to-one and many-to-one) is rendered as a radio menu Collection association (one-to-many and many-to-many) is rendered as a multiple select menu For example: Book Form Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"What is Short Association","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#what-is-short-association","p":1747},{"i":1751,"t":"Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"Book Form","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"","p":1747},{"i":1753,"t":"Install DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This process is not required but highly recommended) Create a new directory src/main/dto Under src/main/dto, create a file Book.dto and write the following code: Book.dto input BookInputWithShortAssociations { #allScalars(this) id(store) //default alias storeId id(authors) as authorIds }","s":"Define Input DTO","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#define-input-dto","p":1747},{"i":1755,"t":"Java Kotlin BookInputWithShortAssociations.java @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookInputWithShortAssociations implements Input { @Nullable private Long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private Long storeId; @NotNull private List authorIds; ...Omit other methods... } BookInputWithShortAssociations.kt @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookInputWithShortAssociations( val id: Long?, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long? val authorIds: List ) : Input { ...Omit other methods... }","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#generated-code","p":1747},{"i":1757,"t":"Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/book\") public int saveBookInputWithShortAssociations( @RequestBody BookInputWithShortAssociations input ) { return sqlClient .save(input) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @PutMapping(\"/book\") fun saveBookInputWithShortAssociations( @RequestBody input: BookInputWithShortAssociations ): Int = sqlClient .save(input) .totalAffectedRowCount } It can be seen that no matter how the Input DTO changes, Jimmer still only needs one method call to complete data saving.","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#write-http-service","p":1747},{"i":1759,"t":"https://discord.gg/PmgR5mpY3E","s":"Discuss","u":"/jimmer-doc/docs/resource/discuss","h":"","p":1758},{"i":1762,"t":"Jimmer focuses only on the ORM itself and does not provide auxiliary tools, such as generating entity interface definitions based on the database structure. Enthusiastic people have contributed related tools, welcome everyone to actively contribute related tools, and submit PRs for me to include them in the list. As of now, the collected projects are:","s":"Ecosystem","u":"/jimmer-doc/docs/resource/ecosystem","h":"","p":1761},{"i":1764,"t":"IDE Project URL Intellij Plugin https://github.com/ClearPlume/jimmer-dto Supports any IDE that supports LSP https://github.com/Enaium/jimmer-dto-lsp","s":"DTO Language Syntax Highlighting Plugin","u":"/jimmer-doc/docs/resource/ecosystem","h":"#dto-language-syntax-highlighting-plugin","p":1761},{"i":1766,"t":"Project Type Tool Support Language Support Project URL Gradle Plugin Gradle Java & Kotlin https://github.com/ArgonarioD/gradle-plugin-jimmer Gradle Plugin Gradle Java & Kotlin https://github.com/Enaium/jimmer-gradle","s":"Simplify Project Configurations","u":"/jimmer-doc/docs/resource/ecosystem","h":"#simplify-project-configurations","p":1761},{"i":1768,"t":"Project Type Language Support Project URL Intellij Plugin Java & Kotlin https://github.com/ClearPlume/jimmer-generator Intellij Plugin Java & Kotlin https://github.com/huyaro/CodeGenX Maven Plugin Java https://github.com/TokgoRonin/code-generator-jimmer Gradle Plugin Java&Kotlin https://github.com/Enaium/jimmer-gradle Model Designer Java&Kotlin https://pot-mot.github.io/jimmer-code-gen-doc","s":"Generate Entity Definitions by Database","u":"/jimmer-doc/docs/resource/ecosystem","h":"#generate-entity-definitions-by-database","p":1761},{"i":1770,"t":"https://github.com/flynndi/quarkus-jimmer-extension","s":"Quarkus Extension","u":"/jimmer-doc/docs/resource/ecosystem","h":"#quarkus-extension","p":1761},{"i":1772,"t":"https://github.com/zengyufei/xm-jimmer-solon-plugin","s":"Solon Extension","u":"/jimmer-doc/docs/resource/ecosystem","h":"#solon-extension","p":1761},{"i":1774,"t":"Through the previous chapters: We learned about the three core functionalities of Jimmer and got a basic impression of it. We also went through a simple project to understand the basics of using Jimmer, including how to use its Annotation Processor (Java) / KSP (Kotlin). However, for a comprehensive solution, having rich examples is better. Jimmer provides a series standard examples: tip Combining the accompanying examples is the most efficient way to get familiar with Jimmer.","s":"Standard Examples","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"","p":1773},{"i":1776,"t":"Like JOOQ, JPA2.0 Criteria, QueryDSL, MyBatis-Flex, Fluent-MyBatis and other types of strong-typed SQL DSL implementations, Jimmer needs to generate more source code based on user code. For Java, it is annotation processor For Kotlin, it is ksp When a user opens the accompanying examples in an IDE (such as IntelliJ) for the first time, some classes that should have been automatically generated will be missing. info Don't panic, click the run button and all errors will disappear automatically.","s":"Prerequisites","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#prerequisites","p":1773},{"i":1778,"t":"The accompanying examples of Jimmer are very helpful for quickly mastering Jimmer. The root directory of all examples: https://github.com/babyfish-ct/jimmer-examples This project provides 5 examples, each with Java and Kotlin versions, for a total of 10 projects. Java Kotlin Description How to Run Importance java/jimmer-core java/jimmer-core-kt ORM-unrelated example demonstrating immer-style immutable objects Run main method ★★★★ java/jimmer-sql java/jimmer-sql-kt Use Jimmer to quickly build REST services. This example demonstrates most of Jimmer's capabilities and is the most important and fundamental example. Run main method Visit swagger page: http://localhost:8080/ui Download client TypeScript code: http://localhost:8080/ts.zip Notes ★★★★★ java/jimmer-sql-graphql java/jimmer-sql-graphql-kt Use Jimmer to quickly build GraphQL services Run main method Visit GraphiQL page: http://localhost:8080/graphiql Notes ★★ java/jimmer-cloud java/jimmer-cloud-kt Microservice project based on Spring Cloud, demonstrating Jimmer's remote associations Start the registry center by running the main method of the registry-center subproject Start all microservices by running the main method in store-service, book-service and author-service Wait about half a minute to ensure the registry center correctly identifies all microservices to avoid exceptions in subsequent swagger calls where some remote services cannot be recognized. Visit the swagger-ui of any of the following microservices store-service: http://localhost:7001/ui book-service: http://localhost:7002/ui author-service: http://localhost:7003/ui note After starting all projects locally, if there is a communication failure between the microservices and it persists after waiting for some time, please visit http://localhost:7000 to open the eureka registration center, add the hostnames of the various registered services to your local hosts file. ★ java/save-command kotlin/save-command-kt Dedicated example for save commands Run all unit tests ★★★ tip When getting started, the most important examples are jimmer-sql and jimmer-sql-kt. Open either of them according to your language preference: Java jimmer-examples/java/jimmer-sql Kotlin jimmer-examples/kotlin/jimmer-sql-kt","s":"Example Introduction","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#example-introduction","p":1773},{"i":1780,"t":"Non-cache mode is the default running mode for all examples. No external environment needs to be installed for them to run directly. If an example depends on a database, it will use the H2 in-memory database in non-cache mode, and automatically create the database at startup. As you can see, non-cache mode is very simple and ideal for quickly getting familiar with the examples.","s":"Non-Cache Mode","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#non-cache-mode","p":1773},{"i":1782,"t":"As introduced above, there are 10 accompanying examples, 4 of which can demonstrate Jimmer's caching and cache consistency. java/jimmer-sql and kotlin/jimmer-sql-kt java/jimmer-sql-graphql and kotlin/jimmer-sql-graphql-kt By default, caching is not used, and they run on embedded in-memory databases with automatic database initialization. This ensures no external environment installation is required. Just click the run button to demonstrate. You can also start them in cache mode by running the program with the spring-boot profile maxwell or debezium. These two spring profiles utilize the CDC push capabilities of maxwell or debezium to achieve Cache Consistency tip In fact, relying on CDC push services like maxwell or debezium is not the only way to achieve Cache Consistency. Even without the help of any external technology, Jimmer can also achieve this capability. Jimmer's own capability to capture data changes is called Transaction Trigger Pushing database changes to Jimmer via external CDC technology is called BinLog Trigger Please refer to Trigger Classification. BinLog Trigger has better performance and universality (even if the database is changed through other means that bypass Jimmer, such as directly modifying the data using a SQL IDE, it can also be intercepted), so it is the recommended solution. Therefore, although Transaction Trigger can achieve Cache Consistency without relying on any special external environment, the official examples still use BinLog Trigger to synchronize the cache, as this is the more recommended approach. So we need to set up CDC services like maxwell or debezium to push database changes to Jimmer. Enabling cache mode requires building an external environment. First, you need to install docker on your local machine. Install the external environment The accompanying examples support two external environments. Feel free to choose either one to experience Cache Consistency","s":"Cache Mode","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#cache-mode","p":1773},{"i":1784,"t":"Although Maxwell only supports MySQL, it is the simplest of all database change push technologies. So it has demonstrational value. Open the command line, enter the local directory corresponding to jimmer-examples/env-with-cache/maxwell, and execute bash ./install.sh After installation, docker host port usage is enabled as follows Container Name Port Description maxwell-demo-zookeeper 4000 Support Kafka, users do not use directly maxwell-demo-kafka 4100 The exposed address is localhost, that is, assuming the docker host is your local machine. If you want to use a remote server as the docker host, you need to modify the kafka installation command in install.sh and modify the spring-boot configuration file in the examples maxwell-demo-kafdrop 4101 A Kafka GUI tool, visit http://localhost:4101 with a browser maxwell-demo-mysql 4200 Database service in this mode maxwell-demo-maxwell NA Background service that pushes MySQL changes to Kafka maxwell-demo-redis 4400 Caching service in this mode","s":"Maxwell + MySQL","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#maxwell--mysql","p":1773},{"i":1786,"t":"Debezium supports many databases and has good versatility. The example uses it to support change propagation for Postgres. info Postgres is a great open source database. If your project is brand new without any historical baggage, consider trying Postgres. This is why Jimmer's examples use Debezium to support Postgres. Open the command line, enter the local directory corresponding to jimmer-examples/env-with-cache/debezium, and execute bash ./install.sh After installation, docker host port usage is enabled as follows Container Name Port Description debezium-demo-zookeeper 5000 Support Kafka, users do not use directly debezium-demo-kafka 5100 The exposed address is localhost, that is, assuming the docker host is your local machine. If you want to use a remote server as the docker host, you need to modify the kafka installation command in install.sh and modify the spring-boot configuration file in the examples debezium-demo-kafdrop 5101 A Kafka GUI tool, visit http://localhost:5101 with a browser debezium-demo-postgres 5200 Database service in this mode debezium-demo-connect 5300 Responsible for pushing Postgres changes to Kafka using kafka-connector. You can verify whether the pg-connector named debezium-connector is successfully installed by visiting http://localhost:5300/connectors debezium-demo-redis 5400 Caching service in this mode","s":"Debezium + Postgres","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#debezium--postgres","p":1773},{"i":1788,"t":"caution If both the Maxwell + MySQL and Debezium + Postgres external environments are installed, some containers may fail to start due to insufficient memory. For example, on my Mac, the default memory allocated to docker is 2GB. Installing and starting all of the above containers, plus a few other unrelated containers, led to insufficient memory. The problem was resolved after setting to 3GB.","s":"Notes","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#notes","p":1773},{"i":1793,"t":"A long association refers to not only changing the association relationship between the current object and other objects, but also further modifying the associated object. For the UI interface, it is usually manifested as nested parent-child forms (or even recursive trees). The forms are diverse, and sub-forms embedded in forms are quite common, as follows: Purchaser Schneewittchen Purchaser Province Province City City Address Address Order Items Commodity Quantity Unit price Item price Delete Timeless Vitamin C Plus E 10 Percent Ferulic Acid Serum Serum Unisex 1 oz 14.69 29.38 Olaplex No. 4 Bond Maintenance Shampoo 30 30 Add Total price:59.379999999999995 Submit info As long as developers are willing, the depth of this nested parent-child form structure can be more than two layers. In theory, the depth can be infinite, which is why it is called a long association.","s":"What is Long Association","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#what-is-long-association","p":1791},{"i":1795,"t":"In the current example in the entity definition, the more suitable example as a long association to save is the BookStore and its associated books collection. Install DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This process is not required but highly recommended) Create a new directory src/main/dto Under src/main/dto, create a file BookStore.dto and write the following code: BookStore.dto export org.doc.j.model.BookStore -> package org.doc.j.model.dto input BookStoreWithLongAssociation { #allScalars(this) books { // LongAssociation #allScalars(this) -id id(authors) as authorIds } }","s":"Write DTO","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#write-dto","p":1791},{"i":1797,"t":"After compilation, Jimmer will generate the following code: Java Kotlin BookStoreWithLongAssociation.java @GeneratedBy( file = \"/src/main/dto/BookStore.dto\" ) public class BookStoreWithLongAssociation implements Input { @Nullable private Long id; @NotNull private String name; @Nullable private String website; @NotNull private List books; ...Omit other methods... public static class TargetOf_books implements Input { @NotNull private String name; private int edition; @NotNull private BigDecimal price; @NotNull private List authorIds; ...Omit other methods... } } BookStoreWithLongAssociation.kt @GeneratedBy( file = \"/src/main/dto/BookStore.dto\" ) data class BookStoreWithLongAssociation( val id: Long? val name: String, val website: String?, val books: List ) : Input { ...Omit other methods... data class TargetOf_authors( val name: String, val edition: Int, val price: BigDecimal, val authorIds: List ) }","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#generated-code","p":1791},{"i":1799,"t":"Java Kotlin BookStoreController.java @RestController public class BookStoreController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/bookStore\") public int saveBookStoreWithLongAssociation( @RequestBody BookStoreWithLongAssociation input ) { return sqlClient .save(input) .getTotalAffectedRowCount(); } } BookStoreController.java class BookStoreController( private val sqlClient: KSqlClient ) { @PutMapping(\"/bookStore\") fun saveBookStoreWithLongAssociation( @RequestBody input: BookStoreWithLongAssociation ): Int = sqlClient .save(input) .totalAffectedRowCount } It can be seen that no matter how the Input DTO changes, Jimmer still only needs one method call to complete data saving.","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#write-http-service","p":1791},{"i":1804,"t":"Although Jimmer's data saving capability is designed for arbitrary complex data structures, in order to show how to safely expose the data saving capability step by step, this article only discusses saving a single object, and saving complex data structures will be described in subsequent articles. For more practical guidance, this article discusses two situations: Homogeneous change scenario: This is a relatively simple business scenario where the form structure of the INSERT operation and the UPDATE operation is consistent. Heterogeneous change scenario: This is a relatively complex business scenario where the form structures of the INSERT operation and the UPDATE operation are inconsistent. In addition, since the save directive only requires one function call, encapsulating it with Repository does not make much sense. In order to simplify unnecessary complexity, this article no longer defines Repository, but lets Controller use sqlClient directly.","s":"Overview","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#overview","p":1802},{"i":1807,"t":"Since we have some understanding of the DTO language in Query Arbitrary Shape/Exposing Features/Return Output DTO, this article will not repeat the discussion. Install DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This process is not required but highly recommended) Create a new directory src/main/dto Under src/main/dto, create a file Book.dto and write the following code: Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto input BookInput { #allScalars(this) } ...Omit other DTO definitions... info Unlike the Output DTO in Query Arbitrary Shape/Exposing Features, the input DTO here uses the input modifier","s":"Define Input DTO","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#define-input-dto","p":1802},{"i":1809,"t":"After compilation, Jimmer will automatically generate the following types: Java Kotlin BookInput.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class BookInput implements Input { ❷ @Nullable ❸ private Long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; public BookInput(@NotNull Book base) { ❹ ...omitted... } @Override public Book toEntity() { ❺ ...omitted... } ...Omit other members... } BookInput.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class BookInput( id: Long?, ❸ name: String, edition: Int, price: BigDecimal ) : Input { ❷ constructor(base: Book): ❹ this(...) override fun toEntity(): Book = ❺ ... } ❶ Remind developers that this class is automatically generated by Jimmer ❷ Unlike the Output DTO in Query Arbitrary Shape/Exposing Features/Return Output DTO, after using the input modifier in the DTO language, the generated class will implement the Input interface instead of the View interface. ❸ If an auto increment strategy (such as automatic change, sequence, UUID, snowflake ID) is configured for the id attribute of the original entity, using the input modifier in the DTO language will cause the id attribute of the DTO to be null. The final DTO object will be converted to an entity object through ❺ and then saved by Jimmer. If the id attribute of the DTO is null, then after conversion to the entity, the id attribute of the entity will be in an unspecified state. For save operations that do not explicitly specify INSERT mode or UPDATE mode: If the id attribute of the entity object is specified, judge whether it should be INSERT or UPDATE according to id If the id attribute of the entity object is not specified, judge whether it should be INSERT or UPDATE according to key (in this case name and edition) ❹ Convert entity to DTO ❺ Convert DTO to entity","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#generated-code","p":1802},{"i":1811,"t":"Since DTO can be converted to entities, you can program like this: Java Kotlin BookInput input = ...omitted...; sqlClient.save(input.toEntity()); val input: BookInput = ...omitted... sqlClient.save(input.toEntity()) In fact, Jimmer provides a more convenient way, so that even calling the toEntity method to convert the DTO to an entity is not necessary, so the code can be simplified to: Java Kotlin BookInput input = ...omitted...; sqlClient.save(input); val input: BookInput = ...omitted... sqlClient.save(input) Next, you can implement the Controller: Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/book\") public int saveBook( @RequestBody BookInput input ) { return sqlClient .save(input) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ): Int = sqlClient .save(input) .totalAffectedRowCount }","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#write-http-service","p":1802},{"i":1814,"t":"Here we assume that there are two types of book management roles: Provide two roles that can save books: Operator: Can only modify the price of existing books Administrator: Can create and edit all information of books For the Administrator role, the Web API for creating new books and the Web API for editing books need to be separated","s":"Requirements","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#requirements","p":1802},{"i":1816,"t":"Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto /** * Input for the `Operator` role to modify books, can only modify the `price` attribute */ input BookOperatorUpdateInput { id! // Override default behavior, id cannot be null price } /** * Input for the `Administrator` role to create new books, no id attribute */ input BookAdministratorCreateInput { #allScalars(this) -id // Creating new books does not need id } /** * Input for the `Administrator` role to modify books, id attribute cannot be null */ input BookAdministratorUpdateInput { #allScalars(this) id! // Override default behavior, id cannot be null } ...Omit other DTO definitions...","s":"Write DTO","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#write-dto","p":1802},{"i":1818,"t":"After compilation, the following three types are automatically generated: BookOperatorUpdateInput Java Kotlin BookOperatorUpdateInput /** * Input for the `Operator` role to modify books, can only modify the `price` attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookOperatorUpdateInput implements Input { private long id; @NotNull private BigDecimal price; ...Omit other methods... } BookOperatorUpdateInput /** * Input for the `Operator` role to modify books, can only modify the `price` attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookOperatorUpdateInput( val id: Long, val price: BigDecimal ) : Input { ...Omit other methods... } BookAdministratorCreateInput Java Kotlin BookAdministratorCreateInput /** * Input for the `Administrator` role to create new books, no id attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookAdministratorCreateInput implements Input { @NotNull private String name; private int edition; @NotNull private BigDecimal price; ...Omit other methods... } BookAdministratorCreateInput /** * Input for the `Administrator` role to create new books, no id attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookAdministratorCreateInput( val name: String, val edition: Int, val price: BigDecimal ) : Input { ...Omit other methods... } BookAdministratorUpdateInput Java Kotlin BookAdministratorUpdateInput /** * Input for the `Administrator` role to modify books, id attribute cannot be null */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookAdministratorUpdateInput implements Input { @NotNull private String name; private int edition; @NotNull private BigDecimal price; private long id; ...Omit other methods... } BookAdministratorUpdateInput /** * Input for the `Administrator` role to modify books, id attribute cannot be null */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookAdministratorUpdateInput( val name: String, val edition: Int, val price: BigDecimal, val id: Long ) : Input { ...Omit other methods... }","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#generated-code-1","p":1802},{"i":1820,"t":"Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Secured(\"ADMINISTRATOR\") @PostMapping(\"/book\") public int createBookByAdministrator( @RequestBody BookAdministratorCreateInput input ) { return sqlClient .insert(input) .getTotalAffectedRowCount(); } @Secured(\"OPERATOR\") @PutMapping(\"/book/byOperator\") public int updateBookByOperator( @RequestBody BookOperatorUpdateInput input ) { return sqlClient .update(input) .getTotalAffectedRowCount(); } @Secured(\"ADMINISTRATOR\") @PutMapping(\"/book\") public int updateBookByAdministrator( @RequestBody BookAdministratorUpdateInput input ) { return sqlClient .update(input) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @Secured(\"ADMINISTRATOR\") @PutMapping(\"/book\") fun createBookByAdministrator( @RequestBody input: BookAdministratorCreateInput ): Int = sqlClient .insert(input) .totalAffectedRowCount @Secured(\"OPERATOR\") @PutMapping(\"/book/byOperator\") fun createBookByAdministrator( @RequestBody input: BookOperatorUpdateInput ): Int = sqlClient .update(input) .totalAffectedRowCount @Secured(\"ADMINISTRATOR\") @PutMapping(\"/book/byOperator\") fun updateBookByAdministrator( @RequestBody input: BookAdministratorUpdateInput ): Int = sqlClient .update(input) .totalAffectedRowCount } It is not difficult to find that no matter how diversified the Input DTO parameters are, Jimmer completes the data saving with one method call.","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#write-http-service-1","p":1802},{"i":1823,"t":"There are two concepts in Jimmer Query multiple columns Query one object column and specify multiple properties of the queried objects They are completely different concepts","s":"1. Basic Query","u":"/jimmer-doc/docs/showcase/base","h":"","p":1822},{"i":1825,"t":"Java Kotlin BookTable table = BookTable.$; List> tuples = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.edition().desc()) .select( table.id(), table.name(), table.edition() ) .execute(); val tuples = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.edition.desc()) select( table.id, table.name, table.edition ) } .execute() In Jimmer, all queries except queries that return only one column are multi-column queries. This example queries three columns, so the return type is 'Tuple3'. The following data is obtained [ { \"_1\" : 12, \"_2\" : \"GraphQL in Action\", \"_3\" : 3 }, { \"_1\" : 11, \"_2\" : \"GraphQL in Action\", \"_3\" : 2 }, { \"_1\" : 10, \"_2\" : \"GraphQL in Action\", \"_3\" : 1 } ]","s":"Query multiple columns","u":"/jimmer-doc/docs/showcase/base","h":"#query-multiple-columns","p":1822},{"i":1827,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.edition().desc()) .select( table.fetch( BookTableFetcher.$ // `id()` is implicit and is always queried .name() .edition() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.edition.desc()) select( table.fetchBy { // `id()` is implicit and is always queried name() edition() } ) } .execute() The result is [ { \"id\" : 12, \"name\" : \"GraphQL in Action\", \"edition\" : 3 }, { \"id\" : 11, \"name\" : \"GraphQL in Action\", \"edition\" : 2 }, { \"id\" : 10, \"name\" : \"GraphQL in Action\", \"edition\" : 1 } ] It's easy to see that although this query has only one column, we can precisely control the format of this object. In this example, not all the properties of the Book object are queried ('price' and many-to-one association 'store' are not queried), because the Jimmer entity type 'Book' supports dynamic properties, the number of properties queried for the object does not affect the return type, and it is always of the 'Book' type. tip Jimmer entity objects are dynamic and can be typed uniformly to represent objects of any format (format is also called shape). Therefore, we do not need to use a multi-column query to control the return format under Jimmer, but we should use a single-column query to return a column of objects and flexibly control the object format. This results in Jimmer making less use of tuple-based multi-column queries and being more object-oriented.","s":"Specify properties of the queried object","u":"/jimmer-doc/docs/showcase/base","h":"#specify-properties-of-the-queried-object","p":1822},{"i":1829,"t":"Java Kotlin BookTable table = BookTable.$; List> tuples = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() ), Expression.numeric().sql( Integer.class, \"row_number() over(partition by %e order by %e desc)\", new Expression[] { table.storeId(), table.price() } ) ) .execute(); val tuples = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.edition.desc()) .select( table.fetchBy { allScalarFields() }, sql(Int::class, \"row_number() over(partition by %e order by %e desc)\") { expression(table.storeId) expression(table.price) } ) } .execute() The result is [ { \"_1\":{ \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80 }, \"_2\":3 }, { \"_1\":{ \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81 }, \"_2\":2 }, { \"_1\":{ \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82 }, \"_2\":1 } ] This example queries two columns The first column is the object type, and the object format is 'allScalarFields' (contains all non-associated attributes)* The second column is a native SQL expression that calls the underlying database parse function ('%e' indicates a DSL expression that is used to implant the native SQL code) It's clearly a combination of the two.","s":"Combine both","u":"/jimmer-doc/docs/showcase/base","h":"#combine-both","p":1822},{"i":1832,"t":"Java Kotlin BookStoreTable table = BookStoreTable.$; List stores = sqlClient .createQuery(table) .where(table.name().eq(\"MANNING\")) .select( table.fetch( BookStoreFetcher.$ .allScalarFields() .books( ❶ BookFetcher.$ .allScalarFields() .authors( ❷ AuthorFetcher.$ .allScalarFields() ) ) ) ) .execute(); val books = sqlClient .createQuery(BookStore::class) { where(table.name eq \"MANNING\") select( table.fetchBy { allScalarFields() books { ❶ allScalarFields() authors { ❷ allScalarFields() } } } ) } .execute() The result is [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ ❶ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80, \"authors\":[ ❷ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81, \"authors\":[ ❷ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82, \"authors\":[ ❷ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/fetch-association/deeper-association","h":"#query-dynamic-entities","p":1830},{"i":1834,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.BookStore -> package com.yourcompany.yourproject.model.dto BookStoreView { #allScalars(this) books { ❶ #allScalars(this) authors { ❷ #allScalars(this) } } } Compile the project, a java/kotlin class named BookStoreView will be automatically generated. Java Kotlin BookStoreTable table = BookStoreTable.$; List stores = sqlClient .createQuery(table) .where(table.name().eq(\"MANNING\")) .select( table.fetch(BookStoreView.class) ) .execute(); val stores = sqlClient .createQuery(BookStore::class) { where(table.name eq \"Learning GraphQL\") select( table.fetch(BookStoreView::class) ) } .execute() The result is [ BookStoreView( id=2, name=MANNING, website=null, books=[ BookStoreView.TargetOf_books( id=12, name=GraphQL in Action, edition=3, price=80.00, authors=[ BookStoreView.TargetOf_books.TargetOf_authors_2( id=5, firstName=Samer, lastName=Buna, gender=MALE ) ] ), BookStoreView.TargetOf_books( id=11, name=GraphQL in Action, edition=2, price=81.00, authors=[ BookStoreView.TargetOf_books.TargetOf_authors_2( id=5, firstName=Samer, lastName=Buna, gender=MALE ) ] ), BookStoreView.TargetOf_books( id=10, name=GraphQL in Action, edition=1, price=82.00, authors=[ BookStoreView.TargetOf_books.TargetOf_authors_2( id=5, firstName=Samer, lastName=Buna, gender=MALE ) ] ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/deeper-association","h":"#query-static-dto","p":1830},{"i":1837,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .authors( AuthorFetcher.$ .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() authors { allScalarFields() } } ) } .execute() The result is [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/fetch-association/associated-object","h":"#query-dynamic-entities","p":1835},{"i":1839,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars(this) authors { #allScalars(this) } } Compile the project, a java/kotlin class named BookView will be automatically generated. Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetch(BookView::class) ) } .execute() The result is [ BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/associated-object","h":"#query-static-dto","p":1835},{"i":1842,"t":"Unlike the previous example, here we only need to fetch the associated object id, not the entire associated object.","s":"2.4 Associated Id","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"","p":1841},{"i":1845,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .authors() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() authors() } ) } .execute() The result is [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] } ] This will lead to large numbers of objects that have only the id property (JPA users can understand them as entity proxies), although correct, this may not be the format preferred by developers. In the next section we discuss how to solve this problem.","s":"If there is no IdView property","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"#if-there-is-no-idview-property","p":1841},{"i":1847,"t":"In order to solve the above problem, we can add the @IdView property for entity interface, namely the associated id property. Java Kotlin @Entity public interface Book { @ManyToMany List authors(); @IdView(\"authors\") List authorIds(); ....省略其他属性... } @Entity interface Book { @ManyToMany val authors: List @IdView(\"authors\") val authorIds: List ....省略其他属性... } Here, the authorIds property is a view of the authors property, and they share data. So, it does not change the entity format, it just diversifies the expression. info This is just a case study, no in-depth discussion of the @IdView property. Please refer here for more details Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .authorIds() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() authorIds() } ) } .execute() The result is [ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authorIds\":[2, 1] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authorIds\":[2, 1] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authorIds\":[2, 1] } ]","s":"If there is IdView property","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"#if-there-is-idview-property","p":1841},{"i":1849,"t":"No need to define @IdView attributes in entities, create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars id(authors) as authorIds } Compile the project, a java/kotlin class named BookView will be automatically generated. Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetch(BookView::class) ) } .execute() The result is [ BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, authorIds=[2, 1] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, authorIds=[2, 1] ), BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, authorIds=[2, 1] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"#query-static-dto","p":1841},{"i":1851,"t":"So far, we've quickly demonstrated the following features Object Fetcher, i.e. querying arbitrarily shaped data structures, are what are shown in Fetch Association and Recursive Query. Conditions, especially Dynamic table join and Implicit subquery Sorting, including dynamic sorting Paging queries Now, let's combine all of the above features into a relatively powerful query Again, there are two ways to develop Query dynamic entities Query static DTOs","s":"7. Comprehensive Query","u":"/jimmer-doc/docs/showcase/comprehensive-query","h":"","p":1850},{"i":1853,"t":"Java Kotlin public class BookRepository { private static final BookTable T = BookTable.$; private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } public Page findBooks( int pageIndex, int pageSize, @Nullable String sortCode, @Nullable Fetcher fetcher, @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName ) { return sqlClient .createQuery(T) .where(T.name().ilikeIf(name)) .where(T.price().betweenIf(minPrice, maxPrice)) .where(T.store().name().ilikeIf(storeName)) .where(T.store().website().ilikeIf(storeWebsite)) .where( T.authors(author -> Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .orderBy( Order.makeOrders( T, sortCode != null ? sortCode : \"name asc, edition desc\" ) ) .select(T.fetch(fetcher)) .fetchPage(pageIndex, pageSize); } } class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( pageIndex: Int, pageSize: Int = 10, sortCode: String = \"name asc, edition desc\", fetcher: Fetcher? = null, name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, name: String? = null ): Page = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.website `ilike?` storeWebsite) where += table.authors { or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } orderBy(table.makeOrders(sortCode)) select(table.fetch(fetcher)) } .fetchPage(pageIndex, pageSize) } info Here, the 'findBooks' method has too many parameters. This doesn't matter to Kotlin, but it may not be a good design for Java. If your project is based on the Java language, you can choose to reduce the number of parameters in the Java language by distilling all or some of the parameters into an object. However, this does not provide substantial benefit to the example presentation here, therefore, we do not do so in order to maintain a high degree of consistency between the Java and Kotlin examples. The user can use it like this (considering that Java doesn't have a good way to simplify the invocation to a method with many parameters, just a demonstration the kotlin invocation) val bookRepository = ...Omitted... val page = bookRepository.findBooks( pageIndex = 1, pageSize = 2, name = \"GraphQL\", maxPrice = BigDecimal(60), authorName = \"alex\", fetcher = newFetcher(Book::class).by { allScalarFields() store { name() } authors { firstName() lastName() } } ) The result is Page{ rows=[ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50.00, \"store\":{\"id\":1,\"name\":\"O'REILLY\"}, \"authors\":[ {\"id\":2,\"firstName\":\"Alex\",\"lastName\":\"Banks\"}, {\"id\":1,\"firstName\":\"Eve\",\"lastName\":\"Procello\"} ] } ], totalRowCount=3, totalPageCount=2 }","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/comprehensive-query","h":"#query-dynamic-entities","p":1850},{"i":1855,"t":"Java Kotlin public class BookRepository { private static final BookTable T = BookTable.$; private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } public > Page findBooks( int pageIndex, int pageSize, @Nullable String sortCode, @Nullable Class viewType, @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName ) { return sqlClient .createQuery(T) .where(T.name().ilikeIf(name)) .where(T.price().betweenIf(minPrice, maxPrice)) .where(T.store().name().ilikeIf(storeName)) .where(T.store().website().ilikeIf(storeWebsite)) .where( T.authors(author -> Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .orderBy( Order.makeOrders( T, sortCode != null ? sortCode : \"name asc, edition desc\" ) ) .select(T.fetch(viewType)) .fetchPage(pageIndex, pageSize); } } class BookRepository( private val sqlClient: KSqlClient ) { fun > findBooks( pageIndex: Int, pageSize: Int = 10, sortCode: String = \"name asc, edition desc\", viewType: KClass, name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, name: String? = null ): Page = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.website `ilike?` storeWebsite) where += table.authors { or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } orderBy(table.makeOrders(sortCode)) select(table.fetch(viewType)) } .fetchPage(pageIndex, pageSize) } info Here, the 'findBooks' method has too many parameters. This doesn't matter to Kotlin, but it may not be a good design for Java. If your project is based on the Java language, you can choose to reduce the number of parameters in the Java language by distilling all or some of the parameters into an object. However, this does not provide substantial benefit to the example presentation here, therefore, we do not do so in order to maintain a high degree of consistency between the Java and Kotlin examples. To demonstrate the invocation, let's first use the DTO language to automatically generate a DTO type that implements the View interface. Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars store { id name } authors { id firstName lastName } } Compile the project, a java/kotlin class named BookView will be automatically generated. The user can use it like this (considering that Java doesn't have a good way to simplify the invocation to a method with many parameters, just a demonstration the kotlin invocation) val bookRepository = ...Omitted... val page = bookRepository.findBooks( name = \"GraphQL\", maxPrice = BigDecimal(60), authorName = \"alex\", viewType = BookView::class ) 得到如下结果 Page{ rows=[ BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookView.TargetOf_store(id=1, name=O'REILLY), authors=[ BookView.TargetOf_authors(id=2, firstName=Alex, lastName=Banks), BookView.TargetOf_authors(id=1, firstName=Eve, lastName=Procello) ] ) ], totalRowCount=3, totalPageCount=2 }","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/comprehensive-query","h":"#query-static-dto","p":1850},{"i":1857,"t":"Dynamic sorting refers to the sorting method being dynamically specified by the client.","s":"5.2 Dynamic Sorting","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"","p":1856},{"i":1859,"t":"The simplest way for the client to specify sorting is strings. The string formats supported by Jimmer are as follows: store.name asc, name asc, edition desc or store.name asc; name asc; edition desc Where store.name means first inner join the associated object BookStore through the Book.store property, and then sort by the name property of the associated object. The path length is unlimited, but the association type along the way needs to be one-to-one or many-to-one. Java Kotlin String sortCode = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy(Order.makeOrders(table, sortCode)) .select(table) .execute(); val sortCode: String = ...Omitted... val books = sqlClient .createQuery(Book::class) { orderBy(table.makeOrders(sortCode)) select(table) } .execute()","s":"Use Strings Directly","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#use-strings-directly","p":1856},{"i":1861,"t":"Sometimes, when developing in combination with Spring Data, org.springframework.data.domain.Sort may be used to represent dynamic sorting. At this point, developers need to perform two steps:","s":"Transfer via Spring Sort","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#transfer-via-spring-sort","p":1856},{"i":1863,"t":"The easiest uploading way for the client is still the string discussed earlier, like store.name asc, name asc, edition desc or store.name asc; name asc; edition desc. Therefore, first the string needs to be converted to the org.springframework.data.domain.Sort object. After importing the dependency org.babyfish.jimmer:jimmer-spring-boot-starter:$version, the static method org.babyfish.jimmer.spring.model.SortUtils.toSort can then be used, as follows: Java Kotlin String sortCode = ...Omitted...; Sort sort = SortUtils.toSort(sortCode); val sortCode: String = ...Omitted... val sort = SortUtils.toSort(sortCode)","s":"I. Convert string to Sort Object","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#i-convert-string-to-sort-object","p":1856},{"i":1865,"t":"After importing the dependency org.babyfish.jimmer:jimmer-spring-boot-starter:$version: Java: Use the utility method org.babyfish.jimmer.spring.repository.SpringOrders.toOrders to convert the org.springframework.data.domain.Sort object into a collection of ordering objects accepted by Jimmer. Kotlin: Directly use the orderBy extension function that accepts org.springframework.data.domain.Sort object. Java Kotlin org.springframework.data.domain.Sort sort = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy(SpringOrders.toOrders(table, sort)) .select(table) .execute(); val sort: org.springframework.data.domain.Sort = ...Omitted... val books = sqlClient .createQuery(Book::class) { orderBy(sort) select(table) } .execute()","s":"II. Sort using Sort object","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#ii-sort-using-sort-object","p":1856},{"i":1868,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy(table.name().asc()) .orderBy(table.edition().desc()) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { orderBy(table.name.asc()) orderBy(table.edition.desc()) select(table) } .execute()","s":"Multiple orderBy actions","u":"/jimmer-doc/docs/showcase/order-by/usage","h":"#multiple-orderby-actions","p":1866},{"i":1870,"t":"There is another way to write the equivalent of the above code Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy( table.name().asc(), table.edition().desc() ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { orderBy( table.name.asc(), table.edition.desc() ) select(table) } .execute() However, the previous way of writing is more conducive to the organization of the code structure, so the previous way of writing is more recommended.","s":"orderBy with multiple arguments","u":"/jimmer-doc/docs/showcase/order-by/usage","h":"#orderby-with-multiple-arguments","p":1866},{"i":1872,"t":"Java Kotlin BookTable table = BookTable.$; AuthorTableEx author = AuthorTableEx.$; List books = sqlClient .createQuery(table) .orderBy( sqlClient .createSubQuery(author) .where(author.books().eq(table)) .select(Expression.rowCount()) .desc() ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { orderBy( subQuery(Author::class) { where(table.books() eq parentTable) select(rowCount()) } .desc() ) select(table) } .execute()","s":"Sorting based on subqueries","u":"/jimmer-doc/docs/showcase/order-by/usage","h":"#sorting-based-on-subqueries","p":1866},{"i":1875,"t":"Java Kotlin BookTable book = BookTable.$; List newestBooks = sqlClient .createQuery(book) .where( Expression.tuple( book.name(), book.edition() ).in(sqlClient .createSubQuery(book) .groupBy(book.name()) .select( book.name(), book.edition().max() ) ) ) .select(book) .execute(); val newestBooks = sqlClient .createQuery(Book::class) { where( tuple( table.name, table.edition ) valueIn subQuery(Book::class) { groupBy(table.name) select( table.name, max(table.edition).asNonNull() ) } ) select(table) } .execute()","s":"标准子查询","u":"/jimmer-doc/docs/showcase/other-query","h":"#标准子查询","p":1873},{"i":1877,"t":"为了支持特有数据库产品特有的能力，Jimmer的SQL DSL支持嵌入Native SQL表达式。以正则表达式查询为例。 Java Kotlin AuthorTable table = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(table) .where( Predicate.sql( \"regexp_like(%e, %v)\", it -> it .expression(table.firstName()) .value(\"^Ste(v|ph)en$\") ) ) .select(table) .execute(); val authors = sqlClient .createQuery(Author::class) { where( sql(Boolean::class, \"regexp_like(%e, %v)\") { expression(table.firstName) value(\"^Ste(v|ph)en$\") } ) select(table) } .execute() Native SQL片段中的%e表示可以嵌入一个强类型的Jimmer DSL表达式。 Lambda中的expression(...)指定用于替换%e的表达式。 Native SQL片段中的%v表示可以嵌入一个字面量。 Lambda中的value(...)指定用于替换%v的字面量。","s":"Native SQL","u":"/jimmer-doc/docs/showcase/other-query","h":"#native-sql","p":1873},{"i":1881,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch( TreeNodeFetcher.$ .allScalarFields() .recursiveChildNodes( cfg -> cfg.depth(2) ) ) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { depth(2) } } ) } .execute() The currently queried aggregate roots are defined as the 0th layer. On this basis, query two layers of child objects downwards to obtain the following data: [ { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":2, \"name\":\"Food\", \"childNodes\":[ {\"id\":3,\"name\":\"Drinks\"}, {\"id\":6,\"name\":\"Bread\"} ] }, { \"id\":9, \"name\":\"Clothing\", \"childNodes\":[ {\"id\":10,\"name\":\"Woman\"}, {\"id\":18,\"name\":\"Man\"} ] } ] } ] info The deepest 4 objects do not have the childNodes property as [], but do not have the childNodes property at all. This means whether these 4 objects have subordinate objects is unknown, because the recursion process was prematurely terminated due to manual intervention.","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/depth","h":"#query-dynamic-entities","p":1879},{"i":1883,"t":"Restricting recursion depth for static DTOs will be provided in later versions, please wait for later versions.","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/depth","h":"#query-static-dto","p":1879},{"i":1886,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; TreeNode treeNode = sqlClient .findById( TreeNodeFetcher.$ .allScalarFields() .recursiveParent() ❶ .recursiveChildNodes() ❷, 10L ); val treeNode = sqlClient .findById( newFetcher(TreeNode::class).by { allScalarFields() `parent*`() ❶ `childNodes*`() ❷ }, 10L ) The result is { \"id\":10, \"name\":\"Woman\", \"parent\":{ ❶ \"id\":9, \"name\":\"Clothing\", \"parent\":{ ❶ \"id\":1, \"name\":\"Home\", \"parent\":null ❶ } }, \"childNodes\":[ ❷ { \"id\":11, \"name\":\"Casual wear\", \"childNodes\":[ ❷ { \"id\":12, \"name\":\"Dress\", \"childNodes\":[] ❷ }, { \"id\":13, \"name\":\"Miniskirt\", \"childNodes\":[] ❷ }, { \"id\":14, \"name\":\"Jeans\", \"childNodes\":[] ❷ } ] }, { \"id\":15, \"name\":\"Formal wear\", \"childNodes\":[ ❷ { \"id\":16, \"name\":\"Suit\", \"childNodes\":[] ❷ }, { \"id\":17, \"name\":\"Shirt\", \"childNodes\":[] ❷ } ] } ] }","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/multiple-props","h":"#query-dynamic-entities","p":1884},{"i":1888,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.TreeNode -> package com.yourcompany.yourproject.model.dto RecursiveTreeNodeView { #allScalars(this) parent* ❶ childNodes* ❷ } Compile the project, a java/kotlin class named RecursiveTreeNodeView will be automatically generated. Java Kotlin TreeNodeTable table = TreeNodeTable.$; RecursiveTreeNodeView treeNode = sqlClient .findById( RecursiveTreeNodeView.class, 10L ); val treeNode = sqlClient .findById( RecursiveTreeNodeView::class, 10L ) The result is RecursiveTreeNodeView( id=10, name=Woman, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=9, name=Clothing, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=1, name=Home, parent=null ❶ ) ), childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=11, name=Casual wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=12, name=Dress, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=13, name=Miniskirt, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=14, name=Jeans, childNodes=[] ❷ ) ] ), RecursiveTreeNodeView.TargetOf_childNodes( id=15, name=Formal wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=16, name=Suit, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=17, name=Shirt, childNodes=[] ❷ ) ] ) ] )","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/multiple-props","h":"#query-static-dto","p":1884},{"i":1891,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .store( ❶ BookStoreFetcher.$ .allScalarFields() ) .authors( ❷ AuthorFetcher.$ .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() store { ❶ allScalarFields() } authors { ❷ allScalarFields() } } ) } .execute() The result is [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ ❶ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ ❷ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ ❶ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ ❷ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store\":{ ❶ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ ❷ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/fetch-association/more-association","h":"#query-dynamic-entities","p":1889},{"i":1893,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars(this) store { ❶ #allScalars(this) } authors { ❷ #allScalars(this) } } Compile the project, a java/kotlin class named BookView will be automatically generated. Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetch(BookView::class) ) } .execute() The result is [ BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookView.TargetOf_store( ❶ id=1, name=O'REILLY, website=null ), authors=[ ❷ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, store=BookView.TargetOf_store( ❶ id=1, name=O'REILLY, website=null ), authors=[ ❷ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, store=BookView.TargetOf_store( ❶ id=1, name=O'REILLY, website=null ), authors=[ ❷ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/more-association","h":"#query-static-dto","p":1889},{"i":1895,"t":"In the past few months, save command has been undergoing a major restructuring, so it has not been written. The good news is that this historically significant restructuring of Jimmer has finally been completed and stabilized, so the content here will be completed soon.","s":"X. To be Continued...","u":"/jimmer-doc/docs/showcase/to-be-conitnued","h":"","p":1894},{"i":1899,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch( TreeNodeFetcher.$ .allScalarFields() .recursiveChildNodes(cfg -> { cfg.recursive(it -> { return !it.getEntity().name().equals(\"Clothing\"); }); }) ) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { recursive { entity.name != \"Clothing\" } } } ) } .execute() If the name of the current tree node is equal to Clothing, terminate the recursion, otherwise continue recursion. The result is as follows: [ { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":2, \"name\":\"Food\", \"childNodes\":[ { \"id\":3, \"name\":\"Drinks\", \"childNodes\":[ { \"id\":4, \"name\":\"Coca Cola\", \"childNodes\":[] }, { \"id\":5, \"name\":\"Fanta\", \"childNodes\":[] } ] }, { \"id\":6, \"name\":\"Bread\", \"childNodes\":[ { \"id\":7, \"name\":\"Baguette\", \"childNodes\":[] }, { \"id\":8, \"name\":\"Ciabatta\", \"childNodes\":[] } ] } ] }, {\"id\":9,\"name\":\"Clothing\"} ] } ] info The Clothing object does not have the childNodes property as [], but does not have the childNodes property at all. This means whether the Clothing object has subordinate objects is unknown, because the recursion process was prematurely terminated due to manual intervention.","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/node-control","h":"#query-dynamic-entities","p":1897},{"i":1901,"t":"Controlling whether each node recurses using static DTOs will be provided in later versions, please wait for later versions.","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/node-control","h":"#query-static-dto","p":1897},{"i":1905,"t":"Jimmer supports built-in Page objects org.babyfish.jimmer.Page org.springframework.data.domain.Page note In fact, Jimmer allows users to customize any Page object. However, this article does not discuss this issue, partly because this article is only a showcase page and does not want to go into depth, and on the other hand, these two built-in Page objects are usually sufficient. As far as these two built-in Page objects are concerned, the differences are as follows: org.springframework.data.domain.Page: Designed for server-side pages, in order for the page to remain in its previous state after refresh, a lot of information (such as cumbersome sorting information) needs to be returned to the client as is, so it is very complex. org.babyfish.jimmer.Page: For the design of rich client pages, this kind of client page itself is a stateful application, and the server side provide pure data services, and only return the most necessary information, so it is very simple.","s":"Two types of Page objects","u":"/jimmer-doc/docs/showcase/page","h":"#two-types-of-page-objects","p":1903},{"i":1907,"t":"Java Kotlin int pageIndex = ...Omitted...; // 从0开始 int pageSize = ...Omitted...; BookTable table = BookTable.$; org.babyfish.jimmer.Page page = sqlClient .createQuery(table) .orderBy(table.name().asc()) .orderBy(table.edition().desc()) .select(table) .fetchPage(pageIndex, pageSize); val pageIndex: Int = ...Omitted...; // Starts from 0 val pageSize: Int = ...Omitted...; val page: org.babyfish.jimmer.Page = sqlClient .createQuery(Book::class) { orderBy(table.name.asc()) orderBy(table.edition().desc()) select(table) } .fetchPage(pageIndex, pageSize) If pageIndex is 1 * (page 2) * and pageSize is 5, the result is Page{ rows=[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82.00, \"store\":{\"id\":2} }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, \"store\":{\"id\":1} }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55.00, \"store\":{\"id\":1} }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50.00, \"store\":{\"id\":1} }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48.00, \"store\":{\"id\":1} } ], totalRowCount=12, totalPageCount=3 }","s":"Using the page of Jimmer","u":"/jimmer-doc/docs/showcase/page","h":"#using-the-page-of-jimmer","p":1903},{"i":1909,"t":"After importing the dependency 'org.babyfish.jimmer:jimmer-spring-boot-starter:$version' Usage supported by both Java and Kotlin: Use SpringPageFactory.getInstance() as the third argument to fetchPage Kotlin-specific usage: Directly call the extension function fetchSpringPage. Java Kotlin int pageIndex = ...Omitted...; // 从0开始 int pageSize = ...Omitted...; BookTable table = BookTable.$; org.springframework.data.domain.Page page = sqlClient .createQuery(table) .orderBy(table.name().asc()) .orderBy(table.edition().desc()) .select(table) .fetchPage( pageIndex, pageSize, SpringPageFactory.getInstance() ); val pageIndex: Int = ...Omitted...; // Starts from 0 val pageSize: Int = ...Omitted...; val page: org.springframework.data.domain.Page = sqlClient .createQuery(Book::class) { orderBy(table.name.asc()) orderBy(table.edition().desc()) select(table) } .fetchSpringPage( pageIndex, pageSize ) If pageIndex is 1 * (page 2) * and pageSize is 5, the result is { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82, \"store\":{\"id\":2} }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{\"id\":1} }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{\"id\":1} }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store\":{\"id\":1} }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{\"id\":1} } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"numberOfElements\":5, \"first\":false, \"size\":5, \"number\":1, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"empty\":false }","s":"Using the page of Spring Data","u":"/jimmer-doc/docs/showcase/page","h":"#using-the-page-of-spring-data","p":1903},{"i":1912,"t":"Query all TreeNodes with parentId being null, i.e. root nodes. Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select(table) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select(table) } .execute() tip In the code above, parentId is automatically generated by Jimmer at compile time based on the many-to-one property TreeNode.parent, even if the developer does not define the @IdView property named parentId.","s":"IsNull判断","u":"/jimmer-doc/docs/showcase/where/associated-id","h":"#isnull判断","p":1910},{"i":1914,"t":"In fact, eq supports null parameters. When the parameter of eq is null, is null is rendered: caution Note: The eqIf of java and eq? of kotlin are different, null is considered a dynamic query and does not render any SQL condition. Java Kotlin @Nullable Long parentId = ...Omitted...; TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().eq(parentId)) .select(table) .execute(); val parentId: Long? = ...Omitted...; val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId eq parentId) select(table) } .execute()","s":"Judgment of any value","u":"/jimmer-doc/docs/showcase/where/associated-id","h":"#judgment-of-any-value","p":1910},{"i":1917,"t":"Java Kotlin @Nullable String name = ...Omitted...; @Nullable Integer edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), () -> table.name().ilike(name) ) .whereIf( edition != null, table.edition().eq(edition) ) .select(table) .execute(); val name: String? = ...Omitted... val edition: Int? = ...Omitted... val books = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } edition?.let { where(table.edition eq it) } select(table) } .execute() caution In the Java code, the first whereIf uses a lambda to pass in the expression. This is because in addition to eq and ne which can accept null values (translated to is null and is not null), other conditions (such as ilike here) do not accept null and treats it as a bug made by developers.","s":"Using whereIf","u":"/jimmer-doc/docs/showcase/where/dynamic-where","h":"#using-whereif","p":1915},{"i":1919,"t":"whereIf is not the only way to write dynamic queries. The above code can be replaced with another syntax. Java Kotlin @Nullable String name = ...Omitted...; @Nullable Integer edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .whereIf(table.edition().eqIf(edition)) .select(table) .execute(); val name: String? = ...Omitted... val edition: Int? = ...Omitted... val books = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.edition `eq?` edition) select(table) } .execute() tip Most SQL conditions (such as ilike here) do not accept null and treat it as a bug made by developers. (eq and ne are exceptions, as they render null as is null and not null) However, dynamic predicates (ilikeIf in Java and ilike? in Kotlin) are completely different, they accept null values and understand them as dynamic queries. That is, if the parameter is null or \"\", the current SQL condition is ignored.","s":"Using Dynamic Predicate","u":"/jimmer-doc/docs/showcase/where/dynamic-where","h":"#using-dynamic-predicate","p":1915},{"i":1921,"t":"Although whereIf has good readability, dynamic predicates can adapt to more complex scenarios (can be used in complex conditions, including multi-layer nested and, not, or structures). In the following text, we use dynamic predicates throughout.","s":"Comparison","u":"/jimmer-doc/docs/showcase/where/dynamic-where","h":"#comparison","p":1915},{"i":1923,"t":"The following three ways of writing are equivalent","s":"4.1 Base Usage","u":"/jimmer-doc/docs/showcase/where/usage","h":"","p":1922},{"i":1925,"t":"Java Kotlin String name = ...Omitted...; int edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().ilike(name)) .where(table.edition().eq(edition)) .select(table) .execute(); val name: String = ...Omitted... val edition: Int = ...Omitted... val books = sqlClient .createQuery(Book::class) { where(table.name ilike name) where(table.edition eq edition) select(table) } .execute()","s":"Use multiple filters","u":"/jimmer-doc/docs/showcase/where/usage","h":"#use-multiple-filters","p":1922},{"i":1927,"t":"Java Kotlin String name = ...Omitted...; int edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where( table.name().ilike(name), table.edition().eq(edition) ) .select(table) .execute(); val name: String = ...Omitted... val edition: Int = ...Omitted... val books = sqlClient .createQuery(Book::class) { where( table.name ilike name, table.edition eq edition ) select(table) } .execute();","s":"Filter with multiple arguments","u":"/jimmer-doc/docs/showcase/where/usage","h":"#filter-with-multiple-arguments","p":1922},{"i":1929,"t":"Java Kotlin String name = ...Omitted...; int edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where( Predicate.and( table.name().ilike(name), table.edition().eq(edition) ) ) .select(table) .execute(); val name: String = ...Omitted... val edition: Int = ...Omitted... val books = sqlClient .createQuery(Book::class) { where( and( table.name ilike name, table.edition eq edition ) ) select(table) } .execute()","s":"Logic And","u":"/jimmer-doc/docs/showcase/where/usage","h":"#logic-and","p":1922},{"i":1931,"t":"The above three ways are completely equivalent. However, there is no doubt that the first one is the easiest, so it is recommended.","s":"Suggestion","u":"/jimmer-doc/docs/showcase/where/usage","h":"#suggestion","p":1922},{"i":1933,"t":"Jimmer itself is highly neutral and does not couple with any container framework, but can easily integrate with any container framework. Since SpringBoot is extremely common, Jimmer has built-in SpringBoot Starter to simplify development.","s":"Spring","u":"/jimmer-doc/docs/spring/","h":"","p":1932},{"i":1935,"t":"Jimmer provides Spring Data Repository style APIs, so you can: Define Repository Declare simple queries through abstract methods Implement complex queries through default methods","s":"Spring Data","u":"/jimmer-doc/docs/spring/repository/","h":"","p":1934},{"i":1938,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch( TreeNodeFetcher.$ .allScalarFields() .recursiveChildNodes() ) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*`() } ) } .execute() The result is [ { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":2, \"name\":\"Food\", \"childNodes\":[ { \"id\":3, \"name\":\"Drinks\", \"childNodes\":[ { \"id\":4, \"name\":\"Coca Cola\", \"childNodes\":[] }, { \"id\":5, \"name\":\"Fanta\", \"childNodes\":[] } ] }, { \"id\":6, \"name\":\"Bread\", \"childNodes\":[ { \"id\":7, \"name\":\"Baguette\", \"childNodes\":[] }, { \"id\":8, \"name\":\"Ciabatta\", \"childNodes\":[] } ] } ] }, { \"id\":9, \"name\":\"Clothing\", \"childNodes\":[ { \"id\":10, \"name\":\"Woman\", \"childNodes\":[ { \"id\":11, \"name\":\"Casual wear\", \"childNodes\":[ { \"id\":12, \"name\":\"Dress\", \"childNodes\":[] }, { \"id\":13, \"name\":\"Miniskirt\", \"childNodes\":[] }, { \"id\":14, \"name\":\"Jeans\", \"childNodes\":[] } ] }, { \"id\":15, \"name\":\"Formal wear\", \"childNodes\":[ { \"id\":16, \"name\":\"Suit\", \"childNodes\":[] }, { \"id\":17, \"name\":\"Shirt\", \"childNodes\":[] } ] } ] }, { \"id\":18, \"name\":\"Man\", \"childNodes\":[ { \"id\":19, \"name\":\"Casual wear\", \"childNodes\":[ { \"id\":20, \"name\":\"Jacket\", \"childNodes\":[] }, { \"id\":21, \"name\":\"Jeans\", \"childNodes\":[] } ] }, { \"id\":22, \"name\":\"Formal wear\", \"childNodes\":[ { \"id\":23, \"name\":\"Suit\", \"childNodes\":[] }, { \"id\":24, \"name\":\"Shirt\", \"childNodes\":[] } ] } ] } ] } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/usage","h":"#query-dynamic-entities","p":1936},{"i":1940,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.TreeNode -> package com.yourcompany.yourproject.model.dto RecursiveTreeNodeView { #allScalars(this) childNodes* } Compile the project, a java/kotlin class named RecursiveTreeNodeView will be automatically generated. Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch(RecursiveTreeNodeView.class) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetch(RecursiveTreeNodeView::class) ) } .execute() The result is [ RecursiveTreeNodeView( id=1, name=Home, childNodes=[ RecursiveTreeNodeView( id=2, name=Food, childNodes=[ RecursiveTreeNodeView( id=3, name=Drinks, childNodes=[ RecursiveTreeNodeView( id=4, name=Coca Cola, childNodes=[] ), RecursiveTreeNodeView( id=5, name=Fanta, childNodes=[] ) ] ), RecursiveTreeNodeView( id=6, name=Bread, childNodes=[ RecursiveTreeNodeView( id=7, name=Baguette, childNodes=[] ), RecursiveTreeNodeView( id=8, name=Ciabatta, childNodes=[] ) ] ) ] ), RecursiveTreeNodeView( id=9, name=Clothing, childNodes=[ RecursiveTreeNodeView( id=10, name=Woman, childNodes=[ RecursiveTreeNodeView( id=11, name=Casual wear, childNodes=[ RecursiveTreeNodeView( id=12, name=Dress, childNodes=[] ), RecursiveTreeNodeView( id=13, name=Miniskirt, childNodes=[] ), RecursiveTreeNodeView( id=14, name=Jeans, childNodes=[] ) ] ), RecursiveTreeNodeView( id=15, name=Formal wear, childNodes=[ RecursiveTreeNodeView( id=16, name=Suit, childNodes=[] ), RecursiveTreeNodeView( id=17, name=Shirt, childNodes=[] ) ] ) ] ), RecursiveTreeNodeView( id=18, name=Man, childNodes=[ RecursiveTreeNodeView( id=19, name=Casual wear, childNodes=[ RecursiveTreeNodeView( id=20, name=Jacket, childNodes=[] ), RecursiveTreeNodeView( id=21, name=Jeans, childNodes=[] ) ] ), RecursiveTreeNodeView( id=22, name=Formal wear, childNodes=[ RecursiveTreeNodeView( id=23, name=Suit, childNodes=[] ), RecursiveTreeNodeView( id=24, name=Shirt, childNodes=[] ) ] ) ] ) ] ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/usage","h":"#query-static-dto","p":1936},{"i":1942,"t":"Jimmer has many configurations, some of which can be configured in Spring Boot's application.yml or application.properties. Such as: Property Type Default Value Description jimmer.language java | kotlin java Must be configured for Kotlin projects jimmer.dialect string Jimmer's default dialect Jimmer dialect class name jimmer.show-sql boolean false Whether to print SQL logs jimmer.pretty-sql boolean false Whether to format SQL jimmer.inline-sql-variables boolean false Whether to inline SQL parameters(This only affects the logs. The actual SQL executed still uses JDBC parameters) jimmer.executor-context-prefixes List [] Usually multiple package names or full class names, Jimmer judges whether the current stacktrace should be appended to the SQL logs jimmer.database-validation.mode NONE | WARNING | ERROR NONE Database validation mode jimmer.database-validation-mode Same as above Same as above Same as above jimmer.database-validation.catalog string Catalog of validated tables' database, configured when table name conflicts jimmer.database-validation.schema string Schema of validated tables' database, configured when table name conflicts jimmer.trigger-type BINLOG_ONLY | TRANSACTION_ONLY | BOTH BINLOG_ONLY Trigger type jimmer.id-only-target-checking-level NONE | FAKE | ALL NONE Whether to check short associated ids in save commands jimmer.save-command-pessimistic-lock boolean false Whether queries in save commands use pessimistic locks jimmer.default-enum-strategy NAME | ORDINAL NAME Default mapping mode for enums without explicit declaration jimmer.default-batch-size int 128 Default fetch size for non-collection properties jimmer.default-list-batch-size int 16 Default fetch size for collection properties jimmer.offset-optimizing-threshold int Integer.MAX_VALUE Offset threshold to enable deep paging optimization for paged queries jimmer.is-foreign-key-enabled-by-default boolean true Foreign keys without explicit declaration are treated as real foreign keys jimmer.transaction-cache-operator-fixed-delay int 5000 Retry interval for failed or excessive cache invalidation tasks when trigger type is TRANSACTION_ONLY (not relying on external CDC) jimmer.micro-service-name string Service name of current application if using remote associations jimmer.error-translator.disabled boolean false Whether to disable exception mapping in automatic front-end integration jimmer.error-translator.http-status int 500 Unified HTTP status of server exceptions on client side jimmer.error-translator.debug-info-supported boolean false Whether to include exception message etc. to help debugging in client errors, should be disabled in production jimmer.error-translator.debug-info-max-stack-trace-count int 0 Maximum number of stacktrace in exception information in client errors, should be disabled in production jimmer.client.ts.path string Download path of automatically generated TypeScript code, e.g. \"/ts.zip\" jimmer.client.ts.api-name string Api API name of automatically generated TypeScript code jimmer.client.ts.indent int 4 Indentation of automatically generated TypeScript code jimmer.client.ts.anonymous boolean false Whether to use anonymous style to avoid naming DTO types in automatically generated TypeScript code jimmer.client.ts.mutable boolean false By default, the Typescript generated by Jimmer serves the React ecosystem, so there are a lot of readonly modifiers in the TS type declarations. If this behavior is not desirable, please set this configuration to true jimmer.client.java-feign.path string Download path of automatically generated Spring Cloud Feign Java code, e.g. \"/java-feign.zip\" jimmer.client.java-feign.api-name string Api API name of automatically generated Spring Cloud Feign Java code jimmer.client.java-feign.indent int 4 Indentation of automatically generated Spring Cloud Feign Java code jimmer.client.java-feign.base-package string Top level package of automatically generated Spring Cloud Feign Java code","s":"Appendix","u":"/jimmer-doc/docs/spring/appendix","h":"","p":1941},{"i":1945,"t":"Java Kotlin @Nullable String storeName = ...Omitted...; @Nullable String storeWebsite = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.store().name().eqIf(storeName)) ❶ .where(table.store().website().eqIf(storeWebsite)) ❷ .select(table) .execute(); val storeName: String? = ...Omitted... val storeWebsite: String? = ...Omitted... val books = sqlClient .createQuery(Book::class) { where(table.store.name `eq?` storeName) ❶ where(table.store.website `eq?` storeWebsite) ❷ select(table) } .execute() info In the above code, Java's table.store() and Kotlin's table.store represent the inner join between the table defined by Book and the table defined by BookStore through the many-to-one association Book.store. That is, the following SQL logic is represented: from BOOK b inner join BOOK_STORE s on b.STORE_ID = s.ID In fact, if the entity model is richer, longer paths can be written, such as table.store().city().province(). Here, just for quick start guide and preview, it is unnecessary to build a richer entity model to demonstrate longer paths. The shortest table chain join path table.store() is enough.","s":"Usage","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#usage","p":1943},{"i":1948,"t":"If both storeName and storeWebsite are null, it will cause the dynamic table joins created at ❶ and ❷ to be unused. Unused table joins will be automatically ignored without rendering any actual SQL joins. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_","s":"All table joins do not take effect","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#all-table-joins-do-not-take-effect","p":1943},{"i":1950,"t":"If storeName is specified as non-null while storeWebsite remains null, the dynamic table join at ❶ takes effect, while the dynamic table join at ❷ is ignored. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? /* MANNING */","s":"Some table joins take effect","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#some-table-joins-take-effect","p":1943},{"i":1952,"t":"If both storeName and storeWebsite are specified as non-null, the dynamic table joins created at ❶ and ❷ will both take effect. tip Jimmer can automatically merge conflicting table joins. The two joins will be merged into one. Ultimately, only one SQL join will be rendered select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? /* MANNING */ and tb_2_.WEBSITE = ? /* https://www.manning.com */","s":"All table joins take effect","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#all-table-joins-take-effect","p":1943},{"i":1954,"t":"类似Java中table.store()或Kotlintable.store这样的连接路径，会被渲染成SQL的内连接，而非外连接，这是因为 info 内连接比外连接拥有更好的性能！ caution 为此，Jimmer不惜通过异常让默认情况下内连接而得到的表对象不支持isNull。 如果要对关联对象施加isNull，必须明确采用外连接操作，例如 Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parent(JoinType.LEFT).isNull()) .select(table) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.`parent?`.isNull()) select(table) } .execute() Java代码中的.parent(JoinType.LEFT)和Kotlin代码中的.parent?表示左连接。 其实，这种案例更适合上一文中的关联id条件 Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select(table) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select(table) } .execute()","s":"IsNull和外连接","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#isnull和外连接","p":1943},{"i":1956,"t":"Implicit subqueries can only be used for collection associations. This article discusses implicit subqueries through the many-to-many Book.authors.","s":"4.5 Implicit Subquery","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"","p":1955},{"i":1958,"t":"Java Kotlin @Nullable String authorName = ...Omitted...; @Nullable Gender authorGender = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where( table.authors(author -> ❶ Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .where( table.authors(author -> ❷ author.gender().eqIf(authorGender) ) ) .select(table) .execute(); val authorName: String? = ...Omitted... val authorGender: Gender? = ...Omitted... val books = sqlClient .createQuery(Book::class) { where += table.authors { ❶ or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } where += table.authors { ❷ gender `eq?` authorGender } select(table) } .execute() In fact, the two implicit subqueries in the code above can be merged into one, but in order to better demonstrate in the following text, they are deliberately written as two.","s":"Usage","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#usage","p":1955},{"i":1961,"t":"If both authorName and authorGender are null, it will cause the subqueries created at ❶ and ❷ to be invalid, and no actual SQL subqueries will be rendered. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_","s":"All subqueries are invalid","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#all-subqueries-are-invalid","p":1955},{"i":1963,"t":"If authorName is specified as non-null while authorGender remains null, the subquery at ❶ takes effect, while the subquery at ❷ is ignored. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) )","s":"Some subqueries take effect","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#some-subqueries-take-effect","p":1955},{"i":1965,"t":"If both authorName and authorGender are specified as non-null, the implicit subqueries created at ❶ and ❷ will both take effect. tip Jimmer can automatically merge conflicting implicit subqueries. The two implicit subqueries will be merged into one implicit subquery. Ultimately, only one SQL subquery will be rendered. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) and tb_2_.GENDER = ? /* M */ )","s":"All subqueries take effect","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#all-subqueries-take-effect","p":1955},{"i":1967,"t":"Jimmer integrates spring data and provides a base repository interface for Java and Kotlin users respectively. Java org.babyfish.jimmer.spring.repository.JRepository Kotlin org.babyfish.jimmer.spring.repository.KRepository This interface has two generic parameters E: Entity type ID: Entity ID type By inheriting this interface, developers can quickly implement various Repository BookStoreRepository Java Kotlin BookStoreRepository.java package com.example.repository; import com.example.model.BookStore; import org.babyfish.jimmer.spring.repository.JRepository; public interface BookRepository extends JRepository {} BookStoreRepository.kt package com.example.repository import com.example.model.BookStore import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository BookRepository Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; public interface BookRepository extends JRepository {} BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository AuthorRepository Java Kotlin AuthorRepository.java package com.example.repository; import com.example.model.Author; import org.babyfish.jimmer.spring.repository.JRepository; public interface AuthorRepository extends JRepository {} AuthorRepository.kt package com.example.repository import com.example.model.Author import org.babyfish.jimmer.spring.repository.KRepository interface AuthorRepository : KRepository TreeNodeRepository Java Kotlin TreeNodeRepository.java package com.example.repository; import com.example.model.TreeNode; import org.babyfish.jimmer.spring.repository.JRepository; public interface TreeNodeRepository extends JRepository {} TreeNodeRepository.kt package com.example.repository import com.example.model.TreeNode import org.babyfish.jimmer.spring.repository.KRepository interface TreeNodeRepository : KRepository note The rest is the same as spring-data. Just define the interface and Jimmer will automatically implement these interfaces and register them in Spring. However, there is one caveat: By default, the package of the custom Repository must be the same as the package of the SpringBoot main class or its subpackage. Otherwise, you need to use @org.babyfish.jimmer.spring.repository.EnableJimmerRepositories to annotate the SpringBoot main class or other Spring configuration class to explicitly specify the package where the custom Repository interface is located.","s":"Define Repository","u":"/jimmer-doc/docs/spring/repository/concept","h":"","p":1966},{"i":1969,"t":"Remote associations are Jimmer's first thoughts on microservice architecture. Through vertical splitting, entity types can be divided into different microservices, or in other words, divided into different databases. The associations (including one-to-one, many-to-one, one-to-many and many-to-many) between entity types belonging to different microservices are remote associations. tip Jimmer automatically implements automatic query of remote associated data. That is, if the object fetcher contains remote association properties of any depth, it will query different parts of the data across multiple microservices, and finally merge the query results of different parts into the data structure expected by the object fetcher as a whole return. No need for developers to implement remote queries and data splicing themselves.","s":"Remote Associations","u":"/jimmer-doc/docs/spring/spring-cloud","h":"","p":1968},{"i":1971,"t":"In this article, each entity is divided as follows: info BOOK_AUTHOR_MAPPING as the many-to-many association intermediate table, can be divided into either the book-service service or the author-service service. In this example, it is divided into the book-service service, the reason will be explained later. Solid arrows indicate foreign key references within the same database, whose validity can be freely chosen by developers. Dashed arrows indicate foreign key references across database boundaries, which must be pseudo foreign keys. To simplify the discussion, the database initialization scripts for the three services are as follows: Language Example Service (Subproject) Database Initialization SQL Java jimmer-examples/java/jimmer-cloud store-service jimmer-cloud/store-service/src/main/resources/store.sql book-service jimmer-cloud/book-service/src/main/resources/book.sql author-service jimmer-cloud/author-service/src/main/resources/author.sql Kotlin jimmer-examples/kotlin/jimmer-cloud-kt store-service jimmer-cloud-kt/store-service/src/main/resources/store.sql book-service jimmer-cloud-kt/book-service/src/main/resources/book.sql author-service jimmer-cloud-kt/author-service/src/main/resources/author.sql info The accompanying examples jimmer-examples/java/jimmer-cloud or jimmer-examples/kotlin/jimmer-cloud-kt use H2, each service will automatically initialize its own database after startup.","s":"Databases","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#databases","p":1968},{"i":1973,"t":"In a separate subproject (the accompanying examples are jimmer-examples/java/jimmer-cloud/model or jimmer-examples/kotlin/jimmer-cloud-kt/model), define all entity types. These entity types constitute the global model. Entity types belong to different microservices. Entities between different microservices constitute remote associations, which can actually be understood as the interaction contracts between entities belonging to different microservices. Java Kotlin BookStore.java @Entity(microServiceName = \"store-service\") public interface BookStore { @OneToMany(mappedBy = \"store\") List books(); ...other code omitted... } BookStore.kt @Entity(microServiceName = \"store-service\") interface BookStore { @OneToMany(mappedBy = \"store\") val books: List ...other code omitted... } Java Kotlin Book.java @Entity(microServiceName = \"book-service\") public interface Book { @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); ...other code omitted... } Book.kt @Entity(microServiceName = \"book-service\") interface Book { @ManyToOne val store: BookStore? @ManyToMany val authors: List ...other code omitted... } Java Kotlin Author.java @Entity(microServiceName = \"author-service\") public interface Book { @ManyToMany(mappedBy = \"authors\") List books(); ...other code omitted... } Author.kt @Entity(microServiceName = \"author-service\") interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...other code omitted... } The microServiceName of the @Entity annotation of the entity class is specified, so that it is clear which microservice each entity belongs to, i.e. which database. In this example, the entity types BookStore, Book and Author belong to the services store-service, book-service and author-service respectively. Here the microservice is the name of each service in the registry center, for spring-cloud it is the global configuration spring.application.name. The associations between entities belonging to different microservices are remote associations. BookStore.books and Book.store: BookStore belongs to store-service, while Book belongs to book-service Book.authors and Author.books: Book belongs to book-service, while Author belongs to author-service The many-to-one association Book.store must be nullable, because the remote association means its foreign key must reference data in another database, that is, it must be a pseudo foreign key. And in Jimmer, the field corresponding to a pseudo foreign key must be nullable. Please refer to Real and Pseudo Foreign Keys. For the bidirectional many-to-many association between books and authors, Book.authors is the owning side, while Author.books is the inverse side (mappedBy of @ManyToMany is configured). info Jimmer stipulates that the intermediate table of remote associations must belong to the microservice where the owning side entity belongs. Here the question left in the previous section is answered, why in this example the intermediate table BOOK_AUTHOR_MAPPING is defined in the book-service database instead of the author-service database.","s":"Entity Definition","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#entity-definition","p":1968},{"i":1975,"t":"Microservice applications need a registry center, which is a basic feature of microservice architecture, no explanation is needed in this article. In the accompanying examples, it is jimmer-examples/java/jimmer-cloud/registry-center or jimmer-examples/kotlin/jimmer-cloud-kt/registry-center","s":"Registry Center","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#registry-center","p":1968},{"i":1977,"t":"Since the implementations of the microservices store-service, book-service and author-service are highly similar, this document only explains how to implement store-service. note Although this document only explains store-service, to experience the effect of remote associations, all three services need to be fully implemented. Complete code can be found in the accompanying examples jimmer-examples/java/jimmer-cloud or jimmer-examples/kotlin/jimmer-cloud-kt.","s":"Implementing Services","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#implementing-services","p":1968},{"i":1979,"t":"Any microservice must enable Jimmer's microservice support. There are two ways: Use Spring Boot Starter Modify spring configuration file application.yml (or application.properties) spring: application: name: store-service jimmer: micro-service-name: ${spring.application.name} ...other configurations omitted... eureka: client: serviceUrl: defaultZone: http://localhost:7000/eureka/ Here, \"store-service\" is used both as the name of the current service in spring-cloud registry center and as the microservice configuration in Jimmer. When using low-level APIs Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setMicroServiceName(\"...\") ...other configurations omitted... .build(); val sqlClient = newKSqlClient { setMicroServiceName(\"...\") ...other configurations omitted... } Once jimmer.micro-service-name is configured, Jimmer knows which entity types belong to the current service (here is BookStore). Using Jimmer's ORM APIs to operate on the entity types belonging to the current microservice will execute correctly, just like everything explained in previous documents. Using Jimmer's ORM APIs to operate on entity types belonging to other microservices will throw exceptions. tip As long as each service ensures spring.application.name and jimmer.micro-service-name are the same, Jimmer will automatically implement automatic query of remote associated data without requiring developers to write any code.","s":"Enable Microservice Support in Jimmer","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#enable-microservice-support-in-jimmer","p":1968},{"i":1981,"t":"Java Kotlin BookStoreService.java @GetMapping(\"/store/{id}/detail\") public @FetchBy(\"COMPLEX_FETCHER\") BookStore findStoreDetail( @PathVariable(\"id\") long id ) { return storeRepository.findNullable(id, COMPLEX_FETCHER); } public static final Fetcher COMPLEX_FETCHER = Fetchers.BOOK_STORE_FETCHER ❶ .allScalarFields() .books( ❷ Fetchers.BOOK_FETCHER .allScalarFields() .authors( ❸ Fetchers.AUTHOR_FETCHER .allScalarFields() ) ); BookStoreService.kt @GetMapping(\"/store/{id}/detail\") fun findStoreDetail( @PathVariable(\"id\") id: Long ): @FetchBy(\"COMPLEX_FETCHER\") BookStore? = storeRepository.findNullable(id, COMPLEX_FETCHER) companion object { val COMPLEX_FETCHER = newFetcher(BookStore::class).by { ❶ allScalarFields() books { ❷ allScalarFields() authors { ❸ allScalarFields() } } } } ❶ Query root aggregate, queried directly from the database belonging to the current service store-service ❷ Query associated objects through remote association property BookStore.books Access remote microservice book-service indirectly to get data via HTTP protocol ❸ Query associated objects through remote association property Book.authors Access remote microservice author-service indirectly to get data via HTTP protocol tip Users only need to implement queries for root aggregate objects, queries for associated properties (including remote associations) are fully automated by Jimmer. Therefore, even without writing any Java/Kotlin code for the other two microservices book-service and author-service, as long as their configuration files are modified to support microservices, this method can still run correctly.","s":"Implement Business Query Logic","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#implement-business-query-logic","p":1968},{"i":1983,"t":"Assuming store-service is started on localhost with port 7001, accessing http://localhost:7001/store/1/detail will get the result: { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" }, { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" } ] }, { \"id\":2, ...omitted... }, { \"id\":3, ...omitted... }, { \"id\":4, \"name\":\"Effective TypeScript\", \"edition\":1, \"price\":73, \"authors\":[ { \"id\":3, \"firstName\":\"Dan\", \"lastName\":\"Vanderkam\", \"gender\":\"MALE\" } ] }, { \"id\":5, ...omitted... }, { \"id\":6, ...omitted... }, { \"id\":7, \"name\":\"Programming TypeScript\", \"edition\":1, \"price\":47.5, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\", \"gender\":\"MALE\" } ] }, { \"id\":8, ...omitted... }, { \"id\":9, ...omitted... } ] }","s":"Run Effects","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#run-effects","p":1968},{"i":1986,"t":"In Jimmer, all database operation APIs have two execution modes: Execute on a specified JDBC connection Execute without specifying a JDBC connection, but a ConnectionManager needs to be configured for Jimmer to teach Jimmer how to borrow and return connections. Please refer to here So Jimmer itself does not provide connection/transaction management capabilities, such management capabilities completely rely on user customization of ConnectionManager. ConnectionManager is the key to integrate Jimmer with the connection/transaction management capabilities of any IOC framework (of course including Spring).","s":"Integrate Spring Transaction","u":"/jimmer-doc/docs/spring/transaction","h":"#integrate-spring-transaction","p":1984},{"i":1988,"t":"If using the Spring Boot Starter provided by Jimmer, no extra work is needed. Jimmer will automatically integrate into Spring's transaction management mechanism.","s":"Using Spring Boot starter","u":"/jimmer-doc/docs/spring/transaction","h":"#using-spring-boot-starter","p":1984},{"i":1990,"t":"If using Spring only, without the Spring Boot Starter provided by Jimmer. You need to code by yourself to integrate Jimmer into Spring's transaction management mechanism. Developers need to create JSqlClient/KSqlClient and set its ConnectionManager. In ConnectionManager, use Spring's org.springframework.jdbc.datasource.DataSourceUtils to open and close connections. Java Kotlin Book.java @Bean public JSqlClient sqlClient(DataSource dataSource) { return JSqlClient.newBuilder() .setConnectionManager( new ConnectionManager() { @Override public R execute( Function block ) { Connection con = DataSourceUtils .getConnection(dataSource); try { return block.apply(con); } finally { DataSourceUtils .releaseConnection(con, dataSource); } } } ) ...Omit other configurations... .build(); } Book.kt @Bean fun sqlClient(dataSource: DataSource): KSqlClient = newKSqlClient { setConnectionManager { val con = DataSourceUtils .getConnection(dataSource) try { proceed(con) } finally { DataSourceUtils .releaseConnection(con, dataSource) } } ...Omit other configurations... } caution Don't use normal methods to borrow (dataSource.getConnection) and return (con.close) connections from the connection pool. You must use Spring's org.springframework.jdbc.datasource.DataSourceUtils, because this can be combined with Spring's transaction management mechanism.","s":"Not Using Spring Boot Starter","u":"/jimmer-doc/docs/spring/transaction","h":"#not-using-spring-boot-starter","p":1984},{"i":1992,"t":"Jimmer adopts minimalist design. The API entry point JSqlClient/KSqlClient exposes stateless APIs. Many database operation frameworks provide lightweight stateful wrappers for JDBC connections, such as JPA's EntityManager Hibernate's Session MyBatis's SqlSession. And they also provide stateful wrappers for database transactions, such as JPA's EntityManager.getTransaction() Hibernate's Session.getTransaction() MyBatis's SqlSession.commit() Jimmer doesn't have similar abstractions. The API entry point JSqlClient/KSqlClient exposes stateless APIs. JDBC connection is the only low-level dependency of Jimmer. tip This enables an important feature: Jimmer's transaction management is exactly the same as JdbcTemplate's transaction management. Jimmer doesn't need to provide any APIs like createNativeQuery For report queries that are not closely related to ORM, users expect to write complete Native SQL, then JdbcTemplate can be used directly, because Jimmer's transaction management is exactly the same as JdbcTemplate's. For Jimmer's ORM-style queries, inject Native SQL expressions in strongly typed SQL DSL.","s":"Work with JdbcTemplate","u":"/jimmer-doc/docs/spring/transaction","h":"#work-with-jdbctemplate","p":1984},{"i":1994,"t":"In the previous sections, we discussed the integration of Spring transactions in the single data source scenario. As for multiple data sources, please refer to this section.","s":"Multiple Data Sources","u":"/jimmer-doc/docs/spring/transaction","h":"#multiple-data-sources","p":1984},{"i":1996,"t":"Jimmer provides DTO language. tip Essentially, this language is another way to express object fetchers. Using this language, developers can quickly define multiple data structure shapes with an entity type as the aggregate root. The compiler will generate the corresponding Java/Kotlin DTO classes for each shape. Each DTO type contains the mutual conversion logic between itself and the original dynamic type, as well as an object fetcher that matches its own shape. In some cases, after the server queries data of a certain shape, it is not used as the return of an HTTP request, but is used by itself to drive subsequent complex business logic. This is an ideal scenario for using this approach. caution Note that if the data of a certain shape queried by the server is not for its own use, but to be directly returned as the HTTP request return value, it is more recommended to directly return the dynamic entity object and use the scheme in Generate Client Code to automatically generate client code with high development experience.","s":"Query DTO","u":"/jimmer-doc/docs/spring/repository/dto","h":"","p":1995},{"i":1998,"t":"This article focuses on how to query static DTO types, not a systematic introduction to the DTO language. Please refer to Object/DTO Conversion/DTO Language for a complete DTO language. Assume the fully qualified name of the Book class is com.yourcompany.yourproject.model.Book, you can In the project where the entity is defined, create a directory src/main/dto Under src/main/dto, create subdirectories com/yourcompany/yourproject/model according to the package path where the entity is located In the directory created in the previous step, create the file Book.dto. The file name must be the same as the entity class name, and the extension must be dto Edit this file and use the DTO language to define various DTO shapes of the Book entity Book.dto BookDetailView { #allScalars store { #allScalars } authors { #allScalars } } SimpleBookView { ...Omitted... } ...Omit other DTO shape definitions...","s":"Define DTO shape","u":"/jimmer-doc/docs/spring/repository/dto","h":"#define-dto-shape","p":1995},{"i":2000,"t":"Jimmer is responsible for compiling dto files and automatically generating DTO types that conform to these shapes. caution If files other than dto files are modified in addition to dto files, directly clicking the run button in the IDE may cause the dto file to be recompiled. However, if no other Java/Kotlin files are modified except for the dto file, simply clicking the run button in the IDE will not cause the dto file to be recompiled unless explicitly rebuilding! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle Take BookDetailView in the above code as an example. After this dto file is successfully compiled by Jimmer, the following DTO type will be automatically generated: Java Kotlin BookDetailView.java package com.yourcompany.yourproject.model.dto; import com.yourcompany.yourproject.model.Book; import org.babyfish.jimmer.View; @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookDetailView implements Input { private long id; private String name; private int edition; private BigDecimal price; private TargetOf_store store; private List authors; public static class TargetOf_store implements Input { private long id; private String name; @Nullable private String website; ...Omitted other members... } public static class TargetOf_authors implements Input { private long id; private String firstName; private String lastName; private Gender gender; ...Omitted other members... } ...Omitted other members... } BookDetailView.kt package com.yourcompany.yourproject.model.dto import com.yourcompany.yourproject.model.Book import org.babyfish.jimmer.View @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookDetailView( val id: Long = 0, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val store: TargetOf_store? = null, val authors: List = emptyList(), ) : Input { data class TargetOf_store( val id: Long = 0, val name: String = \"\", val website: String? = null, ) : Input { ...Omitted other members... } data class TargetOf_authors( val id: Long = 0, public val firstName: String = \"\", public val lastName: String = \"\", public val gender: Gender, ) : Input { ...Omitted other members... } ...Omitted other members... } info The generated DTO classes are not in the package where the entity is located, but in its dto subpackage. For Java, it is assumed that lombok has been used.","s":"Automatically generate DTO types","u":"/jimmer-doc/docs/spring/repository/dto","h":"#automatically-generate-dto-types","p":1995},{"i":2002,"t":"There are several ways to query DTO types: Use inherited methods from JRepository/KRepository Define abstract methods in custom Repository Define default methods in custom Repository (Which is actually the method of the underlying API to query DTO types)","s":"Query DTO types","u":"/jimmer-doc/docs/spring/repository/dto","h":"#query-dto-types","p":1995},{"i":2004,"t":"Java Kotlin public static void main(String[] args) { ApplicationContext ctx = SpringApplication.run(MyApp.class, args); BookRepository bookRepository = ctx.getBean(BookRepository.class); Book view = bookRepository .viwer(BookDetailView.class) .findNullable(1L); System.out.println(view); } fun main(args: Array) { val ctx = runApplication(*args) val bookRepository = ctx.getBean(BookRepository.class.java) val view = bookRepository .viwer(BookDetailView.class) .findNullable(1L) println(view) } Where viewer(BookDetailView.class) indicates that the following methods are used to query DTO objects instead of dynamic entity objects. The print result is as follows (Formatted manually for readability): BookDetailView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookDetailView.TargetOf_store( id=1, name=O'REILLY, website=null, version=0 ), authors=[ BookDetailView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookDetailView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) It is not difficult to find that although the query no longer returns dynamic entity objects, the function is exactly the same as the object fetcher. Why is this? In fact, an object fetcher is automatically generated inside the BookDetailView class. Jimmer uses it to query dynamic entity objects matching the shape from the database and automatically converts them to DTO objects. tip Related details have been discussed in detail in Object Fetcher/DTO Query. This article will not repeat. This is why this article says at the beginning that the DTO language is essentially another way to express object fetchers.","s":"Use inherited methods from Repository","u":"/jimmer-doc/docs/spring/repository/dto","h":"#use-inherited-methods-from-repository","p":1995},{"i":2006,"t":"There are two implementation plans: Intuitive but not recommended Java Kotlin BookRepository.java // Intuitive but not recommended public interface BookRepository extends JRepository { List findByNameLikeIgnoreCase( @Nullable String name ); } BookRepository.kt // Intuitive but not recommended interface BookRepository : KRepository { fun findByNameLikeIgnoreCase( name: String? = null ) : List } This approach is very simple, the abstract method no longer returns dynamic entities representing arbitrary data, just return the DTO type with fixed shape. Very easy to understand. caution However, this approach still has drawbacks and is not recommended. Recommended approach The above code is simple and intuitive, but violates one of the important values ​​that Jimmer has been trying to pursue: tip Do not solidify the shape of the data structure to be queried in the data layer, but let the upper layer business decide. Java Kotlin BookRepository.java public interface BookRepository extends JRepository { > List findByNameLikeIgnoreCase( @Nullable String name, Class viewType ); } BookRepository.kt interface BookRepository : KRepository { fun > findByNameLikeIgnoreCase( name: String? = null viewType: KClass ) : List } You can see: First, define a method-level generic parameter V, which must extend org.babyfish.jimmer.View (this is very important, otherwise Jimmer will remind developers to do so via exceptions). Then, use V to declare the parameter viewType of type Class or KClass, and hand over the decision-making power of the data structure shape to the caller. Finally, return results carrying the V type, such as V, List or Page. In this way, we can use it to query data structures of various shapes. Take Java as an example: bookRepository.findByNameLikeIgnoreCase(null, BookDetailView.class) bookRepository.findByNameLikeIgnoreCase(null, SimpleBookView.class) bookRepository.findByNameLikeIgnoreCase(null, DefaultBookView.class) Let's recall how we used object fetchers directly to achieve the same functionality before introducing the DTO type: Java Kotlin BookRepository.java public interface BookRepository extends JRepository { List findByNameLikeIgnoreCase( @Nullable String name, fetcher fetcher ); } BookRepository.kt interface BookRepository : KRepository { fun findByNameLikeIgnoreCase( name: String? = null viewType: Fetcher ) : List } tip Comparing the code using DTO with the code using object fetcher directly, it is not difficult to find that the two are doing the same thing in different ways. This confirms again what is said at the beginning of this article that the DTO language is essentially another way to express object fetchers.","s":"Define abstract methods in custom Repository","u":"/jimmer-doc/docs/spring/repository/dto","h":"#define-abstract-methods-in-custom-repository","p":1995},{"i":2008,"t":"Java Kotlin BookRepository.java public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default > List find( @Nullable String name, @Nullable String storeName, @Nullable String authorName, Class viewType ) { return sql() .createQuery(table) whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table.fetch(viewType)) .execute(); } } BookRepository.kt interface BookRepository : KRepository { fun > findByNameLikeIgnoreCase( name: String? = null viewType: KClass ) : List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(table.name) orderBy(table.edition.desc()) select(table.fetch(viewType)) } .execute() } Here we see table.fetch(fetcher) is replaced with table.fetch(viewType). In fact, viewType can also replace fetcher in other underlying query APIs. For example, sqlClient.findById(fetcher, 1L) can be replaced with sqlClient.find(viewType, 1L). tip All underlying query APIs can replace fetcher with viewType, which confirms again that the DTO language is essentially another way to express object fetchers, as stated at the beginning of this article.","s":"Define default methods in custom Repository","u":"/jimmer-doc/docs/spring/repository/dto","h":"#define-default-methods-in-custom-repository","p":1995},{"i":2010,"t":"Just like other Spring Data implementations, users can define abstract methods in the Repository interface. As long as the names, parameters and return values of these methods follow conventions, Jimmer implements them automatically. For example: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; public interface BookRepository extends JRepository { List findByNameOrderByEditionDesc( @Nullable String name ); List findByPriceBetweenOrderByName( @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ); long countByName(String name); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository { fun findByNameOrderByEditionDesc( name: String? ): List fun findByPriceBetweenOrderByName( minPrice: BigDecimal?, maxPrice: BigDecimal? ): List fun countByName(String name): Long } note There are various conventions for method names, but basic usage is similar to Spring Data JPA. So please refer to https://docs.spring.io/spring-data/jpa/docs/current/reference/html/#repository-query-keywords, this article will not repeat it.","s":"Simple Queries","u":"/jimmer-doc/docs/spring/repository/abstract","h":"","p":2009},{"i":2012,"t":"You may have noticed that in the above examples, many parameters can be null. In Jimmer, the automatically implemented abstract methods are inherently dynamic queries, that is, any query parameter can be null. Let's look at another more representative example, where the abstract method is defined as: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; public interface BookRepository extends JRepository { List findByNameLikeIgnoreCaseAndPriceBetween( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository { fun findByNameLikeIgnoreCaseAndPriceBetween( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null ): List } Each parameter of this method can be null, look at the 6 possible invocations: Not specify any parameters Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, null, null ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween() The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ Specify name Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( \"G\", null, null ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween(name = \"G\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where lower(tb_1_.NAME) like ? /* %g% */ Specify minPrice Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, new BigDecimal(40), null ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( minPrice = BigDecimal(40) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.PRICE >= ? /* 40 */ Specify maxPrice Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, null, new BigDecimal(60) ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( maxPrice = BigDecimal(60) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.PRICE <= ? /* 60 */ Specify both minPrice and maxPrice Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, new BigDecimal(40), new BigDecimal(60) ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, BigDecimal(40), BigDecimal(60) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where (tb_1_.PRICE between ? /* 40 */ and ? /* 60 */) Specify all parameters Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( \"G\", new BigDecimal(40), new BigDecimal(60) ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( \"G\", BigDecimal(40), BigDecimal(60) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where lower(tb_1_.NAME) like ? /* %g% */ and (tb_1_.PRICE between ? /* 40 */ and ? /* 60 */)","s":"Dynamic WHERE","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#dynamic-where","p":2009},{"i":2014,"t":"Users can not only apply filters to properties of the currently queried object, but also to properties of associated objects. For example: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; public interface BookRepository extends JRepository { // name -> `Book.name` // storeName -> `Book.store.name` List findByNameStartsWithAndStoreName( @Nullable String name, @Nullable String storeName ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository { // name -> `Book.name` // storeName -> `Book.store.name` fun findByNameStartsWithAndStoreName( name: String? = null, storeName: String? = null ): List } Here, storeName in findByNameStartWithAndStoreName actually refers to store.name. It means a join is performed through Book.store to BookStore first, then a condition is applied on BookStore.name. note JOIN will only be generated in the SQL if the storeName parameter is specified The association that can be used by the convention method must be a non-collection association (one-to-one, many-to-one) Let's see how to use it: Specify name parameter, no JOIN Java Kotlin List books = bookRepository .findByNameStartsWithAndStoreName(\"G\", null); val books = bookRepository .findByNameStartsWithAndStoreName(\"G\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME like ? /* G% */ Specify storeName parameter, JOIN generated Java Kotlin List books = bookRepository .findByNameStartsWithAndStoreName(null, \"MANNING\"); val books = bookRepository .findByNameStartsWithAndStoreName(null, \"MANNING\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? /* MANNING */","s":"Dynamic JOIN","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#dynamic-join","p":2009},{"i":2016,"t":"As long as the abstract method has a parameter of type org.springframework.data.domain.Sort, dynamic ordering can be achieved. For example: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Sort; public interface BookRepository extends JRepository { List findByNameLikeIgnoreCase( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. @Nullable String name, @Nullable Sort sort ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.springframework.data.domain.Sort interface BookRepository : KRepository { fun findByNameLikeIgnoreCase( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. name: String? = null, sort: Sort? = null ): List } To facilitate the top-level code to accept sorting strings from the frontend, Jimmer provides the utility class org.babyfish.jimmer.spring.model.SortUtils to convert the sorting string passed from the client to org.springframework.data.domain.Sort. It can be used like: Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ); val sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ) or Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); val sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); ORDER BY without JOIN Java Kotlin List books = bookRepository .findByName( null, SortUtils.toSort(\"name, edition desc\") ); val books = bookRepository .findByName( null, SortUtils.toSort(\"name, edition desc\") ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc ORDER BY requiring JOIN Java Kotlin List books = bookRepository .findByName( null, SortUtils.toSort(\"store.name, name, edition desc\") ); val books = bookRepository .findByName( null, SortUtils.toSort(\"store.name, name, edition desc\") ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID order by tb_2_.NAME asc, tb_1_.NAME asc, tb_1_.EDITION desc","s":"Dynamic ORDER BY","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#dynamic-order-by","p":2009},{"i":2018,"t":"To perform paged queries, the method needs: A parameter of type org.springframework.data.domain.Pageable Return org.springframework.data.domain.Page Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Pageable; import org.springframework.data.domain.Page; public interface BookRepository extends JRepository { Page findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. @Nullable String name, Pageable pageable ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.springframework.data.domain.Pageable import org.springframework.data.domain.Page interface BookRepository : KRepository { fun findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. name: String? = null, pageable: Pageable ): Page } It can be used like: Java Kotlin Page page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ); val page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ) The returned Page object is like: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2 } }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1 } }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1 } }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1 } }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1 } } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"numberOfElements\":5, \"first\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"number\":1, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before paging */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query data within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL paging */ limit ?, /* 5 (offset) */ ? /* 5 (limit) */","s":"Paged Queries","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#paged-queries","p":2009},{"i":2020,"t":"Object fetchers are one of Jimmer's signature features, allowing querying of arbitrary complex data structures instead of just simple entity objects. Adding a parameter of type org.babyfish.jimmer.sql.fetcher.Fetcher makes the abstract method capable of this. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Pageable; import org.springframework.data.domain.Page; public interface BookRepository extends JRepository { Page findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. @Nullable String name, Pageable pageable, @Nullable Fetcher fetcher ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.fetcher.Fetcher import org.springframework.data.domain.Pageable import org.springframework.data.domain.Page interface BookRepository : KRepository { fun findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. name: String? = null, pageable: Pageable, fetcher: Fetcher? = null ): Page } If no Fetcher is passed or a shape of simple objects is passed, the result will be necessarily similar to previous examples, no need to repeat. So let's just demonstrate querying a complex data structure: Java Kotlin Page page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_FETCHER .name() // associated object only queries id (implicit+mandatory) and name ) .authors( Fetchers.AUTHOR_FETCHER // associated object only queries id (implicit+mandatory), firstName and lastName .firstName().lastName() ) ); val page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), newFetcher(Book::class).by { allScalarFields() store { // associated object only queries id // (implicit+mandatory) and name name() } authors { // associated object only queries // id (implicit+mandatory), firstName and lastName firstName() lastName() } } ) The returned Page object is: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\" }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\" } ] } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"numberOfElements\":5, \"number\":1, \"first\":false, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before paging */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query aggregate root objects within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL paging */ limit ?, /* 5 (offset) */ ? /* 5 (limit) */ /* * Step 3: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.store` * * Note: * In current case, the foreign key `STORE_ID` will be queried, so finding parent * objects directly via foreign key. Although there are 5 rows of data, * the foreign keys only have two distinct values, so only two SQL params. */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ where tb_1_.ID in ( ?, ? /* actual param list: 2, 1 */ ) /* * Step 4: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.authors` */ select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ?, ?, ?, ?, ? /* actual param list: 10, 3, 2, 1, 9 */ ) tip Whether it is simple queries discussed in this article, or complex queries to be discussed in next article, as long as the query returns entity objects or their collections instead of simple column tuples, it is highly recommended to add a Fetcher parameter to make all object queries as powerful in data structure shaping as GraphQL. This brings great convenience to higher level business code.","s":"Object Fetchers","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#object-fetchers","p":2009},{"i":2022,"t":"In the previous document, we introduced adding abstract methods to custom Repository interfaces following certain conventions, which are implemented automatically by Jimmer. However, this approach has some issues: Results in very long method names Cannot implement complex query logic If developers add methods violating conventions, it leads to startup failures rather than compile time errors So Jimmer provides another approach that allows developers to write queries themselves and control all details. To maximize the safety of static languages, Jimmer provides a strongly typed SQL DSL, rather than weak, string-based solutions like Spring Data JPA's @Query. In Jimmer, query logic can be directly implemented in default methods of the Repository interface.","s":"Complex Queries","u":"/jimmer-doc/docs/spring/repository/default","h":"","p":2021},{"i":2024,"t":"Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; ❶ default List find(@Nullable String name) { return sql() ❷ .createQuery(table) .whereIf( ❸ StringUtils.hasText(name), table.name().ilike(name) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table) ❹ .execute(); ❺ } } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.kt.ast.expression.* interface BookRepository : KRepository { fun find(name: String? = null): List = sql ❷ .createQuery(Book::class) { ❶ name?.takeIf { it.isNotEmpty() }?.let { ❸ where(table.name ilike it) } orderBy(table.name) orderBy(table.edition.desc()) select(table) ❹ } .execute() ❺ } ❶ Java: The parent query is based on the table object Tables.BOOK, renamed to table for convenience. This rename applies to all default methods of the current interface, so declaring it as a static interface variable is appropriate. Kotlin: createQuery accepts a lambda expression which switches the meaning of this, so code inside the lambda can directly use the table variable. ❷ Java: The sql() method inherited from JRepository returns org.babyfish.jimmer.sql.JSqlClient, which is the total entry point for Java API of the SQL DSL. Kotlin: The sql property inherited from KRepository returns org.babyfish.jimmer.sql.kt.KSqlClient, which is the total entry point for Kotlin API of the SQL DSL. ❸ Only add the where condition when the query parameter is non-null and string length is non-zero. Obviously, this query is dynamic. ❹ The select statement is always at the end. Before select, the query has no return type; only after select can the return type of the query be determined. This is why select appears at the end. note The practice of putting select at the end is not originally invented by Jimmer, it was first introduced in C# linq. ❺ Between select and execute: In Java, the expression type is TypedRootQuery In Kotlin, the expression type is KTypedRootQuery But neither is List. This represents a query that is created but not yet executed. It needs to call execute to actually execute it to get the final result List. note The query is not executed immediately after creation, execute must be called to execute it. This is not a design flaw, but an important capability that the pagination query section will illustrate. execute is not the only execution method, in addition to execute, there are other execution methods: Method Return Type Note execute (as shown in this example) List Returns a list fetchOne T (cannot be null) Returns one record, throws exception if no data or multiple data fetchOneOrNull T (can be null) Returns one record, throws exception if multiple data fetchOptional (Java only) Optional wrapping of T or null Returns one record, throws exception if multiple data forEach No return Use when data volume is large, don't want to build collection, just iterate All these execution methods have two overloaded versions: Version without parameters (current example): Execute based on JDBC connection managed by Spring transaction. Should be called in most cases. Version with java.sql.Connection parameter: Execute based on the JDBC connection specified by the user. Usage: Do not specify parameter Java Kotlin List books = bookRepository .find(null); val books = bookRepository.find() The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc Specify parameter Java Kotlin List books = bookRepository.find(\"G\"); val books = bookRepository.find(\"G\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where lower(tb_1_.NAME) like ? /* %g% */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Dynamic WHERE","u":"/jimmer-doc/docs/spring/repository/default","h":"#dynamic-where","p":2021},{"i":2026,"t":"Next, add a storeName parameter to this query method to filter on the name property of BookStore associated via the Book.store property of the current Book. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default List find( @Nullable String name, @Nullable String storeName ) { return sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table) .execute(); } } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.kt.ast.expression.* interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null ): List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } orderBy(table.name) orderBy(table.edition.desc()) select(table) } .execute() } Where Java's table.store().name() or Kotlin's table.store.name means: Starting from the current queried object Book, join to the BookStore object via the association property Book.store, and finally apply filter condition on the BookStore.name property. Obviously, if the storeName parameter is not specified, the final SQL will not contain JOIN, no need to demonstrate. So let's demonstrate the case where the storeName parameter is specified. Java Kotlin List books = bookRepository.find(null, \"M\"); val books = bookRepository.find(storeName = \"M\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where lower(tb_2_.NAME) like ? order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Dynamic JOIN","u":"/jimmer-doc/docs/spring/repository/default","h":"#dynamic-join","p":2021},{"i":2028,"t":"Next, add an authorName parameter to this query method to filter on the firstName or lastName properties of Author associated via Book.authors property of the current Book. note Unfortunately, if you try to emulate the previous example's table.store.name by writing table.authors.firstName, you'll find there is no table.authors option in the IDE auto-complete of table. This is because Book.authors is a collection association (collective term for one-to-many and many-to-many associations). Blindly joining other objects via collection associations will lead to duplicate data in the query results. More importantly, this duplication is fatal for pagination queries to be shown later. For more details, please refer to Pagination Safety. If you read Pagination Safety, you'll know you can force connecting via collection associations using table.asTableEx().authors. However, this capability is not suitable for use here. In short, Jimmer's API will subtly hint that this should be implemented using subqueries rather than JOIN. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default List find( @Nullable String name, @Nullable String storeName, @Nullable String authorName ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; ❶ return sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) ❷ .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table) .execute(); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.kt.ast.expression.* interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null ): List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { ❶❷ where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(table.name) orderBy(table.edition.desc()) select(table) } .execute() } ❶ Java: The subquery is based on the global variable TableExes.AUTHOR_TABLE_EX, alias it to author for subsequent convenience. Here, the subquery is based on TableExes.AUTHOR_TABLE_EX rather than Tables.AUTHOR_TABLE so that select(table.books().id()) can compile. Please read query/Pagination Safety for more details. Kotlin: subQuery accepts a lambda expression where this is redefined, so table variable can be used directly inside, but note: Inside subquery lambda: table var represents KNonNullTableEx Outside subquery lambda, inside parent query lambda: table var represents KNonNullTable If need to reference parent query table inside subquery (not shown in this example, usually used for correlated subqueries): please use parentTable ❷ Create subquery Obviously, if the authorName parameter is not specified, the final SQL will not contain sub query, no need to demonstrate. So let's demonstrate the case where authorName is specified. Java Kotlin List books = bookRepository.find(null, null, \"A\"); val books = bookRepository.find(authorName = \"M\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Subqueries","u":"/jimmer-doc/docs/spring/repository/default","h":"#subqueries","p":2021},{"i":2030,"t":"So far, the sorting in our queries has been static. We expect to accept external parameters to achieve dynamic sorting. Add a parameter of type org.springframework.data.domain.Sort to the query method and use it to sort. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.spring.repository.SpringOrders; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Sort; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default List find( @Nullable String name, @Nullable String storeName, @Nullable String authorName, @Nullable Sort sort ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; return sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(SpringOrders.toOrders(table, sort)) .select(table) .execute(); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.spring.repository.orderBy import org.babyfish.jimmer.sql.kt.ast.expression.* import org.springframework.data.domain.Sort interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null, sort: Sort? = null ): List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(sort) select(table) } .execute() } For Java, org.babyfish.jimmer.spring.repository.SpringOrders.toOrders is needed to convert the Spring Data Sort object to the sorting accepted by Jimmer. For Kotlin, org.babyfish.jimmer.spring.repository.orderBy extends the capability of Jimmer's underlying SQL DSL, so the query object can sort based on the Spring Data Sort object. To facilitate the top-level code to accept sorting strings from the client, Jimmer provides the utility class org.babyfish.jimmer.spring.model.SortUtils to convert the string passed from the frontend to org.springframework.data.domain.Sort. It can be used like: Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ); val sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ) or Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); val sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); Now let's demonstrate the usage of dynamic sorting by specifying all other query parameters as null to focus on the sorting logic. Java Kotlin List books = bookRepository.find( null, null, null, SortUtils.toSort( \"store.name\", // This sort implies JOIN \"price desc\" ) ); val books = bookRepository.find( sort = SortUtils.toSort( \"store.name\", // This sort implies JOIN \"price desc\" ) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ /* Dynamic sort causes table join */ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID /* Dynamic sort */ order by tb_2_.NAME asc, tb_1_.PRICE desc","s":"Dynamic ORDER BY","u":"/jimmer-doc/docs/spring/repository/default","h":"#dynamic-order-by","p":2021},{"i":2032,"t":"Let's continue improving the example by adding pagination capability. To implement pagination, need: Replace the org.springframework.data.domain.Sort type parameter with org.springframework.data.domain.Pageable (Pageable contains Sort) Change return value from java.util.List to org.springframework.data.domain.Page Internally use specific APIs to achieve pagination in one statement Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.spring.repository.SpringOrders; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page find( ❶ @Nullable String name, @Nullable String storeName, @Nullable String authorName, Pageable pageable ❷ ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; return pager(pageable).execute( ❸ sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) ❹ .select(table) ); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.spring.repository.orderBy import org.babyfish.jimmer.sql.kt.ast.expression.* import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null, pageable: Pageable ❷ ): Page = ❶ sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(pageable.sort) ❹ select(table) } .fetchPage( ❸ pageable.pageNumber, pageable.pageSize ) } ❶ Return org.springframework.data.domain.Page rather than java.util.List ❷ Parameter becomes org.springframework.data.domain.Pageable ❸ Execute paged query Java Create a Pager object to paginate the original unexecuted query pager is a method inherited from base interface JRepository/KRepository The pager method has multiple overloaded versions, here the one called accepts a pagable object The pager method creates a Pager object, which has an execute method that accepts the unexecuted original query Kotlin Kotlin API provides the extension method fetchPage for KConfigurableRootQuery<*, E> types to implement paged queries ❹ Get sort object from pageable to perform dynamic sorting Now let's demonstrate the usage of paging query by specifying all other query parameters as null to focus on the pagination logic. Java Kotlin List books = bookRepository.find( null, null, null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ); val books = bookRepository.find( pageable = PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ) The returned Page object is: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2 } }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1 } }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1 } }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1 } }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1 } } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"numberOfElements\":5, \"first\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"number\":1, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before pagination */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query data within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL pagination */ limit ?, /* 5(offset) */ ? /* 5(limit) */","s":"Pagination","u":"/jimmer-doc/docs/spring/repository/default","h":"#pagination","p":2021},{"i":2034,"t":"Object fetchers are one of Jimmer's signature features, allowing querying of arbitrary complex data structures instead of just simple entity objects. To use it, need: Add a parameter of type org.babyfish.jimmer.sql.fetcher.Fetcher Change the select call of the top-level query from select(table) to select(table.fetch(fetcher)) Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.spring.repository.SpringOrders; import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page find( @Nullable String name, @Nullable String storeName, @Nullable String authorName, Pageable pageable, @Nullable Fetcher fetcher ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; return pager(pageable).execute( sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) .select( table.fetch(fetcher) ) ); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.spring.repository.orderBy import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.babyfish.jimmer.sql.kt.ast.expression.* import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null, pageable: Pageable, fetcher: Fetcher? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(pageable.sort) select( table.fetch(fetcher) ) } .fetchPage( pageable.pageNumber, pageable.pageSize ) } If no fetcher is passed or simple object shape is passed, the result will necessarily be similar to previous examples, no need to repeat. So let's just demonstrate querying a complex data structure directly. To focus on the object fetcher, all other query parameters are specified as null except the fetcher. Java Kotlin Page page = bookRepository .find( null, null, null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_FETCHER .name() // associated object only queries id (implicit+mandatory) and name ) .authors( Fetchers.AUTHOR_FETCHER // associated object only queries id (implicit+mandatory), firstName and lastName .firstName().lastName() ) ); val page = bookRepository .find( pageable = PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), fetcher = newFetcher(Book::class).by { allScalarFields() store { // associated object only queries // id (implicit+mandatory) and name name() } authors { // associated object only queries // id (implicit+mandatory), firstName and lastName firstName() lastName() } } ) The returned Page object is: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\" }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\" } ] } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"numberOfElements\":5, \"number\":1, \"first\":false, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before pagination */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query aggregate root objects within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL pagination */ limit ?, /* 5(offset) */ ? /* 5(limit) */ /* * Step 3: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.store` * * Note: * Here the foreign key `STORE_ID` of the 5 records will be queried, * so finding parent objects directly via foreign key. * Although there are 5 rows of data, the foreign keys only * have two distinct values, so only two SQL params. */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ where tb_1_.ID in ( ?/* 2 */, ?/* 1 */ ) /* * Step 4: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.authors` */ select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ?/* 10 */, ?/* 3 */, ?/* 2 */, ?/* 1 */, ?/* 9 */ ) tip Whether it is complex queries discussed in this article, or simple queries discussed in previous article, as long as the query returns entity objects or their collections rather than simple column tuples, it is highly recommended to add a Fetcher parameter to make all object queries as powerful in data structure shaping as GraphQL. 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3,134,1.425,139,1.576,143,1.733,156,2.012,166,2.174,182,1.774,192,1.943,208,2.923,219,1.9,227,2.83,238,1.915,247,2.566,251,3.35,257,2.345,271,3.561,333,2.783,337,2.368,368,2.12,377,3.327,378,2.271,381,3.298,393,2.39,430,3.418,432,5.958,458,2.924,474,3.281,490,3.681,543,3.757,586,2.984,609,3.871,610,2.924,611,3.026,615,3.327,617,3.387,620,2.58,674,2.45,824,3.484,894,4.686,905,3.451,921,4.069,933,2.745,949,5.459,976,2.984,1037,4.523,1289,7.191,1344,3.757,1348,5.174,1924,5.006,2108,5.628,3918,5.376,3924,5.967,3925,8.189,4018,9.35,4067,6.481,4068,6.481,4069,8.895]],["t/1981",[5,1.401,6,1.964,8,0.588,11,1.467,21,1.433,23,2.575,27,1.507,35,1.471,37,2.083,42,1.737,43,1.462,48,1.55,52,0.662,53,0.609,55,1.594,60,1.321,80,1.034,81,1.737,89,0.908,91,1.281,95,2.329,97,4.453,101,2.882,102,1.256,115,0.777,143,2.055,156,1.853,165,1.839,166,2.003,174,2.987,175,5.31,176,3.748,177,3.868,179,4.01,180,3.16,182,1.634,189,2.402,194,1.213,208,1.718,215,3.099,219,3.259,232,1.883,247,3.326,261,2.665,271,1.797,308,2.364,314,1.462,321,4.313,334,3.418,343,3.461,375,2.749,385,3.806,401,4.079,432,3.503,461,3.345,487,1.64,545,4.313,824,5.977,933,2.529,949,5.101,958,5.443,965,6.303,967,6.303,971,5.745,976,2.749,1022,9.566,1026,3.934,1027,3.345,1289,6.623,1440,6.969,1594,6.969,1924,4.611,2487,4.952,4070,8.401,4071,8.401]],["t/1983",[48,1.704,74,2.453,79,2.479,86,1.647,102,0.764,121,2.475,122,2.881,123,4.007,139,1.496,140,2.33,141,2.433,143,1.886,145,2.239,146,4.077,147,2.577,148,2.239,149,3.843,153,3.191,154,4.554,155,5.68,202,3.71,220,3.386,228,3.742,229,3.742,247,2.911,261,2.502,316,4.125,317,4.655,325,3.096,326,3.993,327,3.843,334,2.992,354,3.459,355,3.843,356,5.226,357,5.82,358,3.679,359,3.71,360,4.165,361,3.484,362,5.132,545,3.774,702,2.959,904,3.774,921,6.079,949,3.253,1457,5.87,1458,6.099,1459,5.516,1460,5.516,3365,5.87,3921,8.915]],["t/1986",[0,1.95,8,1.238,9,2.437,12,4.782,15,3.177,23,3.733,35,2.133,43,2.119,46,2.565,60,1.914,91,1.856,120,2.428,134,2.57,166,2.903,184,2.966,194,1.758,195,4.131,213,3.56,225,3.088,250,5.333,251,2.854,271,2.604,306,2.832,333,2.707,472,3.984,523,7.668,609,2.831,637,5.517,800,4.848,832,6.346,866,3.644,867,5.722,871,9.695,881,4.747,1805,6.684,1973,7.967,4072,7.967]],["t/1988",[8,1.162,9,2.846,14,1.129,44,2.69,194,2.053,238,1.906,250,5.015,526,5.056,609,3.859,610,4.559,611,4.719,809,6.547,832,5.487,881,5.543,1068,7.21]],["t/1990",[8,0.898,9,1.893,14,1.24,17,1.9,52,0.621,53,0.487,54,5.35,55,1.73,60,2.29,61,1.942,62,2.661,75,2.504,79,1.841,80,1.165,81,1.956,83,3.687,84,2.661,102,0.947,104,1.705,115,0.874,134,1.478,166,2.255,187,2.19,194,1.852,232,2.876,238,2.093,246,2.226,250,4.526,271,2.745,280,2.553,285,3.336,314,1.646,425,1.9,426,2.514,481,4.723,487,1.846,490,4.283,496,4.723,523,7.077,609,3.913,610,3.032,611,3.139,615,3.45,617,3.513,632,3.363,781,3.896,786,5.908,809,5.908,832,4.951,836,5.576,855,7.92,867,4.855,869,8.988,870,10.149,871,8.584,875,9.945,877,5.838,879,5.563,881,3.687,1549,4.51,2154,6.506,3126,6.189,3127,11.015,3128,9.529,3129,8.396,4072,6.189]],["t/1992",[3,1.161,8,1.213,9,2.954,14,0.771,15,2.533,22,2.717,29,2.418,35,1.701,43,2.273,84,3.675,95,1.874,133,1.74,156,2.142,165,2.125,184,3.181,194,1.402,195,3.293,197,2.077,204,3.824,206,2.521,227,3.013,238,2.439,250,5.567,251,3.861,333,2.159,368,3.036,390,4.048,407,4.47,437,3.052,443,5.514,474,3.423,479,2.159,489,4.629,490,3.841,496,4.806,523,5.662,553,8.06,694,3.542,729,3.865,730,3.542,780,6.013,786,4.47,790,5.917,832,5.695,867,4.942,873,4.332,884,3.052,885,5.144,973,3.222,976,3.177,990,4.533,1344,3.999,1413,4.683,1466,2.905,1498,5.514,1707,5.257,1780,4.718,2142,7.169,2634,8.06,2635,8.06,2972,6.622,3344,6.352,4073,6.9,4074,9.281,4075,9.281,4076,9.281,4077,10.488,4078,6.9]],["t/1994",[27,2.122,46,3.009,223,3.138,225,3.622,250,5.037,263,4.519,378,3.557,566,3.836,575,4.919,609,3.32,845,5.485,881,5.567,1292,6.359]],["t/1996",[3,1.819,5,1.435,8,0.722,9,2.064,14,1.371,17,2.731,27,1.94,28,2.47,44,1.951,49,1.566,52,0.499,53,0.531,60,2.542,80,1.674,89,1.115,95,1.951,97,3.356,126,2.48,156,2.275,159,2.021,165,2.976,168,1.895,179,3.499,180,2.757,187,2.388,193,2.717,203,2.966,206,2.678,213,3.976,247,3.826,257,2.653,263,3.264,265,2.449,282,6.483,352,2.592,374,3.766,401,2.592,453,1.999,502,2.604,508,2.569,530,2.999,566,2.771,589,3.796,620,3.846,624,4.83,629,3.796,643,3.58,674,3.652,872,3.73,887,2.743,903,3.73,943,2.959,946,4.63,947,4.2,953,5.145,981,3.016,984,3.011,987,4.673,1154,6.066,1378,3.705,1401,3.98,1437,6.366,1636,4.83,1980,5.23,2438,5.852,3592,6.749]],["t/1998",[3,1.274,5,1.004,14,0.846,15,2.778,46,2.243,49,1.886,79,1.992,89,1.501,95,1.528,102,1.253,139,1.428,140,1.628,143,1.474,225,2.7,234,3.612,249,3.296,261,1.749,284,2.34,308,2.996,336,4.902,368,2.475,378,2.652,383,3.46,385,4.824,425,3.288,453,2.691,454,4.902,477,2.605,511,3.427,618,4.896,619,4.64,702,3.045,801,4.108,821,2.676,933,4.65,943,3.635,946,3.825,1034,3.918,1041,5.253,1061,3.954,1079,4.781,1125,4.194,1214,4.986,1297,5.844,1375,4.204,1378,3.988,1401,4.108,1481,5.844,1482,4.029,1483,5.586,183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It will be introduced in detail in Spring Cloud and Remote Association.","s":"Remote Association","u":"/jimmer-doc/docs/mapping/advanced/remote","p":398},{"i":404,"t":"In this series of articles, we will introduce base mappings.","s":"Base mapping","u":"/jimmer-doc/docs/mapping/base/","p":404},{"i":406,"t":"Here, you will learn about the most important capability of ORM","s":"Association Mapping","u":"/jimmer-doc/docs/mapping/base/association/","p":406},{"i":408,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToOne annotation to declare many-to-one association properties.","s":"Many To One","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","p":408},{"i":414,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToMany annotation to declare many-to-many association properties.","s":"Many To Many","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","p":414},{"i":422,"t":"Limitations of classic ORM associations","s":"ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","p":422},{"i":439,"t":"Unlike JPA, Jimmer does not support unidirectional one-to-many associations. One-to-many associations can only exist as mirrors of many-to-one associations. That is, one-to-many associations necessarily imply bidirectional associations.","s":"One To Many","u":"/jimmer-doc/docs/mapping/base/association/one-to-many","p":439},{"i":441,"t":"Basic Concepts: Short Associations","s":"IdView","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","p":441},{"i":457,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.OneToOne annotation to declare one-to-one association properties.","s":"One To One","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","p":457},{"i":467,"t":"Through the discussion of Association Mapping, we know that association mapping requires a lot of foreign keys.","s":"Real and Fake Foreign Keys","u":"/jimmer-doc/docs/mapping/base/foreignkey","p":467},{"i":475,"t":"In addition to boolean, number, string, UUID, date, and enumeration, scalar properties also support other types, including:","s":"More Types","u":"/jimmer-doc/docs/mapping/base/more-type","p":475},{"i":483,"t":"Naming Strategy Interface","s":"Naming Strategy","u":"/jimmer-doc/docs/mapping/base/naming-strategy","p":483},{"i":498,"t":"In this section, we will introduce all the capabilities in Jimmer related to modifying the database.","s":"Modification","u":"/jimmer-doc/docs/mutation/","p":498},{"i":500,"t":"Jimmer handles the issue of whether entity object properties can be null in a very strict way. Even for Java developers, it requires thinking about whether each property can be null in the same way as Kotlin developers.","s":"Nullity","u":"/jimmer-doc/docs/mapping/base/nullity","p":500},{"i":511,"t":"@Entity","s":"Simple Mapping","u":"/jimmer-doc/docs/mapping/base/basic","p":511},{"i":530,"t":"Basic Usage","s":"Delete Statement","u":"/jimmer-doc/docs/mutation/delete-statement","p":530},{"i":535,"t":"In recent months, the save instruction has undergone a major restructuring, so there hasn't been time to update all the documentation in this directory.","s":"Save Command","u":"/jimmer-doc/docs/mutation/save-command/","p":535},{"i":538,"t":"Basic Concepts","s":"Delete Command","u":"/jimmer-doc/docs/mutation/delete-command","p":538},{"i":551,"t":"Although Jimmer entities are not POJOs, Jackson serialization can be supported by org.babyish.jimmer.jackson.ImmutableModule.","s":"JSON Converter","u":"/jimmer-doc/docs/mapping/base/json-converter","p":551},{"i":566,"t":"Concept","s":"Interceptor before save","u":"/jimmer-doc/docs/mutation/draft-interceptor","p":566},{"i":582,"t":"Overview","s":"Mutable Association Table","u":"/jimmer-doc/docs/mutation/associations","p":582},{"i":599,"t":"Basic Concepts","s":"Owner side","u":"/jimmer-doc/docs/mutation/save-command/association/owner","p":599},{"i":609,"t":"The save command is used to store data structures of any complexity. To facilitate discussion, we need to establish a basic classification of data structure shapes.","s":"Data Classification","u":"/jimmer-doc/docs/mutation/save-command/data-classification","p":609},{"i":623,"t":"Basic Concepts","s":"Associated Id Checking","u":"/jimmer-doc/docs/mutation/save-command/id-checking","p":623},{"i":637,"t":"Although the underlying save commands are very powerful, there is still some way to go before exposing data persistence APIs externally.","s":"Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/","p":637},{"i":639,"t":"This is a very crude solution, only for learning or very simple projects.","s":"Lonely Form","u":"/jimmer-doc/docs/mutation/save-command/input-dto/lonely","p":639},{"i":641,"t":"Basic Concepts","s":"Association classification","u":"/jimmer-doc/docs/mutation/save-command/association/classification","p":641},{"i":656,"t":"Jimmer provides DTO language.","s":"Using DTO Language","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","p":656},{"i":666,"t":"Not recommended for Kotlin.","s":"Using MapStruct","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","p":666},{"i":678,"t":"When saving associated objects using the association mode AssociatedSaveMode.REPLACE,","s":"Dissociation Operations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","p":678},{"i":700,"t":"In this article we discuss:","s":"Problem","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","p":700},{"i":712,"t":"Save Command Result","s":"Other Features","u":"/jimmer-doc/docs/mutation/save-command/other","p":712},{"i":715,"t":"Basic Concepts","s":"Associated Save Mode","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","p":715},{"i":738,"t":"Save commands support both optimistic lock and pessimistic lock.","s":"Optimistic/Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","p":738},{"i":752,"t":"Input DTO is used for data input, so it provides powerful control over nullable properties in the objects submitted by the client, and standardizes this capability.","s":"Handle Null Values","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","p":752},{"i":773,"t":"Introduction","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/save-command/usage","p":773},{"i":795,"t":"Basic Concepts","s":"Constraint Violation Error Handling","u":"/jimmer-doc/docs/mutation/save-command/investigation","p":795},{"i":815,"t":"In this series of articles, we thoroughly discuss the dynamicity and immutability of Jimmer objects:","s":"Object","u":"/jimmer-doc/docs/object/","p":815},{"i":817,"t":"Basic Usage","s":"Update Statement","u":"/jimmer-doc/docs/mutation/update-statement","p":817},{"i":826,"t":"Save Modes","s":"Save Mode of Aggregate-Root","u":"/jimmer-doc/docs/mutation/save-command/save-mode","p":826},{"i":857,"t":"Immutability is used to ensure that the data structure represented by Jimmer objects never contains circular references.","s":"Immutability","u":"/jimmer-doc/docs/object/immutable/","p":857},{"i":859,"t":"Java has supported immutable record types since Java 14, and Kotlin's data classes can easily implement immutable classes, even supporting copy functions. However, they are designed for simple immutable objects, and have problems dealing with complex deep data structure.","s":"Current Situation","u":"/jimmer-doc/docs/object/immutable/current-situation","p":859},{"i":861,"t":"Unlike other ORMs, Jimmer uses immutable objects as entity objects.","s":"Reason","u":"/jimmer-doc/docs/object/immutable/reason","p":861},{"i":870,"t":"Jimmer supports triggers that allow users to listen for database changes.","s":"Trigger","u":"/jimmer-doc/docs/mutation/trigger","p":870},{"i":898,"t":"The example code in this article uses a type called BookDraft, which is an interface type automatically generated by Jimmer based on the user-defined type Book.","s":"Dynamicity","u":"/jimmer-doc/docs/object/dynamic","p":898},{"i":919,"t":"Jimmer objects are dynamic and not all properties of an object need to be initialized. It allows missing some properties.","s":"Working with Jackson","u":"/jimmer-doc/docs/object/jackson","p":919},{"i":921,"t":"Even if entity objects support dynamism to express arbitrary data structures, conversion between entities and DTOs is still unavoidable.","s":"DTO conversion","u":"/jimmer-doc/docs/object/view/","p":921},{"i":923,"t":"Jimmer provides a series of static tool methods for operating on dynamic objects or their Drafts.","s":"Tool Methods","u":"/jimmer-doc/docs/object/tool","p":923},{"i":951,"t":"The sample code above uses a type called TreeNodeDraft, which is the interface type automatically generated by Jimmer based on the user-defined type TreeNode.","s":"Solution","u":"/jimmer-doc/docs/object/immutable/solution","p":951},{"i":959,"t":"In previous documents we have seen that","s":"Draft","u":"/jimmer-doc/docs/object/draft","p":959},{"i":988,"t":"In this series of articles, we will introduce:","s":"Introduction ★","u":"/jimmer-doc/docs/overview/","p":988},{"i":990,"t":"Not only can Jimmer bring you powerful features, but it can also bring you ultimate performance.","s":"Benchmark Report","u":"/jimmer-doc/docs/overview/benchmark","p":990},{"i":1003,"t":"Basic Concepts","s":"APT/KSP","u":"/jimmer-doc/docs/overview/apt-ksp","p":1003},{"i":1016,"t":"Previous documents have discussed in detail the dynamic and immutable properties of Jimmer entities. This introduces a new feature: visibility.","s":"Visibility","u":"/jimmer-doc/docs/object/visibility","p":1016},{"i":1024,"t":"To help readers better understand the key features, let's first introduce Jimmer's fundamental design philosophy","s":"Key Features ✦","u":"/jimmer-doc/docs/overview/key-features","p":1024},{"i":1032,"t":"Where are the Examples and Getting started?","s":"Before Reading","u":"/jimmer-doc/docs/overview/welcome","p":1032},{"i":1039,"t":"Introduction","s":"MapStruct","u":"/jimmer-doc/docs/object/view/mapstruct","p":1039},{"i":1062,"t":"We will introduce the following contents:","s":"Dynamic JOIN","u":"/jimmer-doc/docs/query/dynamic-join/","p":1062},{"i":1064,"t":"In this section, we will introduce the various queries in Jimmer without considering Cache.","s":"Query","u":"/jimmer-doc/docs/query/","p":1064},{"i":1066,"t":"1. Concepts","s":"DTO Language","u":"/jimmer-doc/docs/object/view/dto-language","p":1066},{"i":1142,"t":"Usage","s":"Merge Conflict Joins","u":"/jimmer-doc/docs/query/dynamic-join/merge","p":1142},{"i":1147,"t":"Dilemma","s":"Join Features Specific to Kotlin","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","p":1147},{"i":1158,"t":"1. What is Jimmer","s":"Overview ✦","u":"/jimmer-doc/docs/overview/introduction","p":1158},{"i":1192,"t":"How Jimmer solves the dynamic join problem will be discussed in subsequent docs. This article first introduces the join style in Jimmer.","s":"Association Path Chaining","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","p":1192},{"i":1198,"t":"In the previous doc, we discussed dynamic queries. In this section, we will explore the problems with dynamic table joins.","s":"Problems with Other Solutions","u":"/jimmer-doc/docs/query/dynamic-join/problem","p":1198},{"i":1204,"t":"Association Tables Hidden by Object Model","s":"Querying Association Tables","u":"/jimmer-doc/docs/query/associations","p":1204},{"i":1215,"t":"The Problem to Solve","s":"Weak Join","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","p":1215},{"i":1223,"t":"Basic Usage","s":"Dynamic Filtering","u":"/jimmer-doc/docs/query/dynamic-where","p":1223},{"i":1230,"t":"Static Ordering","s":"Dynamic Ordering","u":"/jimmer-doc/docs/query/dynamic-order","p":1230},{"i":1240,"t":"Usage","s":"Optimize Unnecessary Joins","u":"/jimmer-doc/docs/query/dynamic-join/optimization","p":1240},{"i":1261,"t":"Pagination safety is a feature designed for pagination, but table join functionality provides underlying support.","s":"Pagination Safety","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","p":1261},{"i":1281,"t":"Readers cannot find anything related to global filters in this doc, because the filter required for logical deletion is built-in and hidden by Jimmer.","s":"Logical Deletion","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","p":1281},{"i":1294,"t":"Global filters are used to automatically add filtering conditions for an entity type. Most queries for the entity type will automatically have related where conditions added.","s":"Global Filters","u":"/jimmer-doc/docs/query/global-filter/","p":1294},{"i":1296,"t":"Aggregation","s":"Aggregate & Group","u":"/jimmer-doc/docs/query/group","p":1296},{"i":1301,"t":"Native SQL expressions are an important feature to leverage database-specific capabilities, as database products always have proprietary features.","s":"Native SQL Expressions","u":"/jimmer-doc/docs/query/native-sql","p":1301},{"i":1307,"t":"Concept","s":"Object Fetcher","u":"/jimmer-doc/docs/query/object-fetcher/","p":1307},{"i":1312,"t":"Collection (one-to-many or many-to-many) associations often lead to the frequent use of subqueries in queries, and implicit subqueries greatly simplify such subqueries.","s":"Implicit Subquery","u":"/jimmer-doc/docs/query/implicit-subquery","p":1312},{"i":1320,"t":"Previously we introduced using object fetchers to flexibly control the shape of queried data structures.","s":"Querying DTOs","u":"/jimmer-doc/docs/query/object-fetcher/dto","p":1320},{"i":1331,"t":"Provide Abstract Mapped Superclass","s":"Custom Filters","u":"/jimmer-doc/docs/query/global-filter/user-filter","p":1331},{"i":1356,"t":"We have introduced that object fetchers can flexibly control the shape of queried data structures, bringing tremendous flexibility for application development.","s":"Working with Spring Data","u":"/jimmer-doc/docs/query/object-fetcher/spring-data","p":1356},{"i":1358,"t":"Fetching Scalar Fields","s":"Ordinary Properties","u":"/jimmer-doc/docs/query/object-fetcher/props","p":1358},{"i":1367,"t":"Why Introduce Object Fetchers","s":"Basic Usage","u":"/jimmer-doc/docs/query/object-fetcher/usage","p":1367},{"i":1374,"t":"Literal Expressions","s":"DSL Expressions","u":"/jimmer-doc/docs/query/expression","p":1374},{"i":1418,"t":"In this series of articles, we will introduce Jimmer's smart paging.","s":"Smart Paging","u":"/jimmer-doc/docs/query/paging/","p":1418},{"i":1420,"t":"Pagination queries have a problem - when the data volume is large, if the pagination range is too far back (i.e. offset is too large), performance issues can occur.","s":"Deep Pagination Optimization","u":"/jimmer-doc/docs/query/paging/deep-optimization","p":1420},{"i":1428,"t":"Concept","s":"Reverse Sorting Optimization","u":"/jimmer-doc/docs/query/paging/reverse-sorting","p":1428},{"i":1437,"t":"A common requirement is to handle self-associated property.","s":"Recursive Query","u":"/jimmer-doc/docs/query/object-fetcher/recursive","p":1437},{"i":1449,"t":"In the previous article, we mentioned that Jimmer can not only auto-generate count-query from data-query, but also auto-optimize the count-query.","s":"Table Join Optimization","u":"/jimmer-doc/docs/query/paging/unnecessary-join","p":1449},{"i":1457,"t":"In last doc we introduced scalar property fetching. In this doc we discuss association fetching.","s":"Associations","u":"/jimmer-doc/docs/query/object-fetcher/association","p":1457},{"i":1480,"t":"IdView","s":"View Properties","u":"/jimmer-doc/docs/query/object-fetcher/view","p":1480},{"i":1495,"t":"Select-After Style","s":"Overview","u":"/jimmer-doc/docs/query/usage","p":1495},{"i":1500,"t":"This section only enumerates the usage methods of the most important functions in Jimmer to allow readers to build a preliminary impression.","s":"Quick View ★","u":"/jimmer-doc/docs/quick-view/","p":1500},{"i":1502,"t":"Jimmer supports strongly typed SQL DSL.","s":"3. Arbitrary Dynamic Query","u":"/jimmer-doc/docs/quick-view/dsl/","p":1502},{"i":1504,"t":"Typed Subqueries","s":"Subqueries","u":"/jimmer-doc/docs/query/sub-query","p":1504},{"i":1522,"t":"Super QBE is a very powerful feature that uses DTO Language to generate parameter types for complex queries and automatically implement query logic.","s":"Super QBE","u":"/jimmer-doc/docs/query/super_qbe","p":1522},{"i":1552,"t":"Basic Concepts","s":"1. Query Arbitrary Shape","u":"/jimmer-doc/docs/quick-view/fetch/","p":1552},{"i":1557,"t":"The comparison is as below:","s":"Comparison","u":"/jimmer-doc/docs/quick-view/fetch/export/comparison","p":1557},{"i":1559,"t":"Through the introduction of the previous article, we quickly previewed Jimmer's powerful ability to query arbitrary data structures at will.","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/fetch/export/","p":1559},{"i":1561,"t":"Features of Jimmer Pagination","s":"Usage","u":"/jimmer-doc/docs/query/paging/usage","p":1561},{"i":1583,"t":"Can It Be Simpler","s":"Super QBE","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","p":1583},{"i":1592,"t":"Through the previous chapters, we already have a basic impression of Jimmer. Now we can start practicing.","s":"Get Started","u":"/jimmer-doc/docs/quick-view/get-started/","p":1592},{"i":1594,"t":"UML","s":"Create Database","u":"/jimmer-doc/docs/quick-view/get-started/create-database","p":1594},{"i":1600,"t":"Jimmer SQL DSL","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/dsl/feature","p":1600},{"i":1619,"t":"Enable Web API Analysis","s":"Directly Return Entities","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","p":1619},{"i":1632,"t":"Create a Spring Boot Project","s":"Create a Project","u":"/jimmer-doc/docs/quick-view/get-started/create-project","p":1632},{"i":1643,"t":"Code Generation","s":"Generate Code","u":"/jimmer-doc/docs/quick-view/get-started/generate-code","p":1643},{"i":1648,"t":"To quickly preview Jimmer's main features, we need to provide several entities here as the basic assumption of all discussions in this section.","s":"Precondition","u":"/jimmer-doc/docs/quick-view/precondition","p":1648},{"i":1661,"t":"The save directive is a very powerful capability of Jimmer. With just one function call, data structures of any shape can be saved.","s":"2. Save Arbitrary Shape","u":"/jimmer-doc/docs/quick-view/save/","p":1661},{"i":1663,"t":"In Save Any Shape/Feature Introduction, we introduced the powerful data saving capability of Jimmer,","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/save/export/","p":1663},{"i":1665,"t":"Here is the English translation of the file, with the code indentation preserved:","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/fetch/feature","p":1665},{"i":1681,"t":"Java/Kotlin Applications Use Query Results","s":"Return Output DTO","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","p":1681},{"i":1707,"t":"Unlike ORMs like JPA/Hibernate, entities in Jimmer are defined as interfaces instead of classes. The reasons are discussed in Why Interfaces.","s":"Define Entities","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","p":1707},{"i":1723,"t":"What is Short Association","s":"Save Short Associations","u":"/jimmer-doc/docs/quick-view/save/export/short","p":1723},{"i":1734,"t":"Jimmer's Two Usages","s":"Final Usage","u":"/jimmer-doc/docs/quick-view/get-started/usage","p":1734},{"i":1747,"t":"Through the previous chapters:","s":"Standard Examples","u":"/jimmer-doc/docs/quick-view/standard-demo","p":1747},{"i":1763,"t":"Concept","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/save/feature","p":1763},{"i":1774,"t":"What is Long Association","s":"Save Long Associations","u":"/jimmer-doc/docs/quick-view/save/export/long","p":1774},{"i":1784,"t":"https://discord.gg/PmgR5mpY3E","s":"Discuss","u":"/jimmer-doc/docs/resource/discuss","p":1784},{"i":1786,"t":"TODO","s":"Video","u":"/jimmer-doc/docs/resource/video","p":1786},{"i":1789,"t":"Jimmer focuses only on the ORM itself and does not provide auxiliary tools, such as generating entity interface definitions based on the database structure.","s":"Ecosystem","u":"/jimmer-doc/docs/resource/ecosystem","p":1789},{"i":1801,"t":"There are two concepts in Jimmer","s":"1. Basic Query","u":"/jimmer-doc/docs/showcase/base","p":1801},{"i":1811,"t":"Overview","s":"Save Aggregate Root","u":"/jimmer-doc/docs/quick-view/save/export/root","p":1811},{"i":1830,"t":"Query Dynamic Entities","s":"2.3 Deeper Association","u":"/jimmer-doc/docs/showcase/fetch-association/deeper-association","p":1830},{"i":1835,"t":"Query Dynamic Entities","s":"2.1 Associated Object","u":"/jimmer-doc/docs/showcase/fetch-association/associated-object","p":1835},{"i":1840,"t":"Unlike the previous example, here we only need to fetch the associated object id, not the entire associated object.","s":"2.4 Associated Id","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","p":1840},{"i":1850,"t":"So far, we've quickly demonstrated the following features","s":"7. Comprehensive Query","u":"/jimmer-doc/docs/showcase/comprehensive-query","p":1850},{"i":1856,"t":"Dynamic sorting refers to the sorting method being dynamically specified by the client.","s":"5.2 Dynamic Sorting","u":"/jimmer-doc/docs/showcase/order-by/dynamic","p":1856},{"i":1866,"t":"Query Dynamic Entities","s":"2.2 More Associations","u":"/jimmer-doc/docs/showcase/fetch-association/more-association","p":1866},{"i":1871,"t":"Two types of Page objects","s":"6. Paging Query","u":"/jimmer-doc/docs/showcase/page","p":1871},{"i":1879,"t":"Query Dynamic Entities","s":"3.2 Limit Depth","u":"/jimmer-doc/docs/showcase/recursive-query/depth","p":1879},{"i":1884,"t":"Multiple orderBy actions","s":"5.1 Basic Usage","u":"/jimmer-doc/docs/showcase/order-by/usage","p":1884},{"i":1891,"t":"标准子查询","s":"8. Other Queries","u":"/jimmer-doc/docs/showcase/other-query","p":1891},{"i":1896,"t":"Query Dynamic Entities","s":"3.2 Control Recursion Of Node","u":"/jimmer-doc/docs/showcase/recursive-query/node-control","p":1896},{"i":1901,"t":"In the past few months, save command has been undergoing a major restructuring, so it has not been written.","s":"X. To be Continued...","u":"/jimmer-doc/docs/showcase/to-be-conitnued","p":1901},{"i":1905,"t":"Query Dynamic Entities","s":"3.4 Multiple Properties","u":"/jimmer-doc/docs/showcase/recursive-query/multiple-props","p":1905},{"i":1910,"t":"IsNull判断","s":"4.3 Associated Id","u":"/jimmer-doc/docs/showcase/where/associated-id","p":1910},{"i":1915,"t":"Using whereIf","s":"4.2 Dynamic Conditions","u":"/jimmer-doc/docs/showcase/where/dynamic-where","p":1915},{"i":1922,"t":"Jimmer itself is highly neutral and does not couple with any container framework, but can easily integrate with any container framework.","s":"Spring","u":"/jimmer-doc/docs/spring/","p":1922},{"i":1924,"t":"Implicit subqueries can only be used for collection associations. This article discusses implicit subqueries through the many-to-many Book.authors.","s":"4.5 Implicit Subquery","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","p":1924},{"i":1935,"t":"The following three ways of writing are equivalent","s":"4.1 Base Usage","u":"/jimmer-doc/docs/showcase/where/usage","p":1935},{"i":1945,"t":"Usage","s":"4.4 Dynamic Table Join","u":"/jimmer-doc/docs/showcase/where/dynamic-join","p":1945},{"i":1957,"t":"Jimmer has many configurations, some of which can be configured in Spring Boot's application.yml or application.properties. Such as:","s":"Appendix","u":"/jimmer-doc/docs/spring/appendix","p":1957},{"i":1959,"t":"Jimmer provides Spring Data Repository style APIs, so you can:","s":"Spring Data","u":"/jimmer-doc/docs/spring/repository/","p":1959},{"i":1961,"t":"Query Dynamic Entities","s":"3.1 Basic usage","u":"/jimmer-doc/docs/showcase/recursive-query/usage","p":1961},{"i":1966,"t":"Jimmer integrates spring data and provides a base repository interface for Java and Kotlin users respectively.","s":"Define Repository","u":"/jimmer-doc/docs/spring/repository/concept","p":1966},{"i":1968,"t":"Jimmer provides DTO language.","s":"Query DTO","u":"/jimmer-doc/docs/spring/repository/dto","p":1968},{"i":1982,"t":"Integrate Spring Transaction","s":"Spring Transaction","u":"/jimmer-doc/docs/spring/transaction","p":1982},{"i":1993,"t":"Remote associations are Jimmer's first thoughts on microservice architecture.","s":"Remote Associations","u":"/jimmer-doc/docs/spring/spring-cloud","p":1993},{"i":2009,"t":"Just like other Spring Data implementations, users can define abstract methods in the Repository interface. As long as the names, parameters and return values of these methods follow conventions, Jimmer implements them automatically. For example:","s":"Simple Queries","u":"/jimmer-doc/docs/spring/repository/abstract","p":2009},{"i":2021,"t":"In the previous document, we introduced adding abstract methods to custom Repository interfaces following certain conventions, which are implemented automatically by Jimmer.","s":"Complex 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provides powerful cache support capabilities. Whether to use cache is completely transparent to developers Which caching technologies to use is decided by developers Not only does it support simple object cache, but also property-level cache, including association cache and calculated cache. Ultimately it provides the ability to cache arbitrary data structures, not just simple object cache. Features represented by permission systems allow different users to see different data. Therefore, Jimmer uses multi-view cache to allow different users to see different caches. Powerful cache consistency support. Developers can focus on modifying the database and Jimmer will automatically invalidate cache.","s":"Cache","u":"/jimmer-doc/docs/cache/","h":"","p":1},{"i":4,"t":"Here, we will introduce three types of cache Object Cache Association Cache Calculation Cache","s":"Cache type","u":"/jimmer-doc/docs/cache/cache-type/","h":"","p":3},{"i":6,"t":"Object cache refers to mapping id to entity object. This is the simplest and most basic cache.","s":"Object Cache","u":"/jimmer-doc/docs/cache/cache-type/object","h":"","p":5},{"i":8,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forObject(type) .maximumSize(1024) .duration(Duration.ofHours(1)) .build() ) .add( RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build(); } ...omit other code... }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ChainCacheBuilder() .add( CaffeineValueBinder .forObject(type) .maximumSize(1024) .duration(Duration.ofHours(1)) .build() ) .add( RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build() ...omit other code... } } If you don't want to support object cache for some entity types, just return null. Java Kotlin @Override public Cache createObjectCache(ImmutableType type) { if (type.getJavaClass() == SomeEntity.class) { return null; } ... } override fun createObjectCache(type: ImmutableType): Cache<*, *>? = if (type.javaClass === SomeEntity::class.java) { null } else { ... }","s":"Enabling Object Caching","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#enabling-object-caching","p":5},{"i":10,"t":"There are two usage patterns that can utilize the object cache: Query entity objects (or their collections) by id (or their collections) Use object fetchers to fetch any non-id fields of associated objects","s":"Using Object Cache","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#using-object-cache","p":5},{"i":12,"t":"Java Kotlin Map bookMap = sqlClient.findMapByIds( Book.class, Arrays.asList(1L, 2L, 3L, 4L, 999L) ); System.out.println(bookMap); val bookMap = sqlClient.findMapByIds( Book::class, listOf(1L, 2L, 3L, 4L, 999L) ) println(bookMap) Jimmer first looks up the data in the cache with keys Book-1, Book-2, Book-3, Book-4 and Book-999. Suppose the data corresponding to these keys cannot be found in the cache: 127.0.0.1:6379> keys Book-* (empty array) So the following SQL is executed to load data from the database: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */, ? /* 3 */, ? /* 4 */, ? /* 999 */ ) Jimmer will put the query results into the cache, so we can view this data in the cache: 127.0.0.1:6379> keys Book-* 1) \"Book-4\" 2) \"Book-2\" 3) \"Book-3\" 4) \"Book-1\" 5) \"Book-999\" 127.0.0.1:6379> get Book-1 \"{\\\"id\\\":1,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"edition\\\":1,\\\"price\\\":50.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-2 \"{\\\"id\\\":2,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"edition\\\":2,\\\"price\\\":55.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-3 \"{\\\"id\\\":3,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"edition\\\":3,\\\"price\\\":51.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-4 \"{\\\"id\\\":4,\\\"name\\\":\\\"Effective TypeScript\\\",\\\"edition\\\":1,\\\"price\\\":73.00,\\\"store\\\":{\\\"id\\\":1}}\" 127.0.0.1:6379> get Book-999 \"\" 127.0.0.1:6379> tip The non-existent data Book-999 is also cached with the special value . Undoubtedly, before the data in the cache expires, executing the Java/Kotlin code above again will directly return the data from the cache without any SQL being generated.","s":"Query Based on Id","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#query-based-on-id","p":5},{"i":14,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().like(\"GraphQL\")) .select( table.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .name() ) ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.name like \"GraphQL\") select( table.fetchBy { allScalarFields() store { name() } } ) } .execute() println(books) 1st SQL: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME like ? /* %GraphQL% */ The fuzzy query in the code is implemented here to obtain some Book objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. 2nd SQL: Fetch many-to-one association Book.store The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return 6 aggregate root objects. The object fetcher in the code contains the many-to-one association Book.store and expects to query non-id properties of the associated object (information that cannot be expressed by the foreign key of the current table), so Jimmer will query the associated object for all aggregate root objects. Fortunately, the associated attribute Book.store is based on a real foreign key. The foreign key itself represents the id of the parent object. There is no need to obtain the associated object id through additional queries or association cache. Suppose the foreign key STORE_ID of the 6 BOOK data has two distinct values after deduplication, 1 and 2. Jimmer first looks up the data in the cache with keys BookStore-1 and BookStore-2. Suppose the data corresponding to these keys cannot be found in the cache: 127.0.0.1:6379> keys BookStore-* (empty array) Then the following SQL is executed to load data from the database: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */ ) info We only need the ID and NAME fields, but here all fields are queried, which is different from what was discussed earlier in Object Fetcher. Please view: The difference compared to not enabling cache Jimmer will put the query results into the cache, so we can view this data in the cache: 127.0.0.1:6379> keys BookStore-* 1) \"BookStore-1\" 2) \"BookStore-2\" 127.0.0.1:6379> get BookStore-1 \"{\\\"id\\\":1,\\\"name\\\":\\\"O'REILLY\\\",\\\"website\\\":null}\" 127.0.0.1:6379> get BookStore-2 \"{\\\"id\\\":2,\\\"name\\\":\\\"MANNING\\\",\\\"website\\\":null}\" 127.0.0.1:6379> Undoubtedly, before the data in the cache expires, executing the Java/Kotlin code above again will directly return the associated data from the cache without generating the 2nd SQL statement. Finally, Jimmer concatenates the results of the two steps as the final data returned to the user: [ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" } }, { ...omit... }, { ...omit... }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\" } }, { ...omit... }, { ...omit... } ]","s":"Using Object Fetchers","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#using-object-fetchers","p":5},{"i":16,"t":"caution To use Jimmer's automatic cache invalidation, triggers need to be enabled first. If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK_STORE set WEBSITE = 'https://www.manning.com' where ID = 2; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; sqlClient .createUpdate(table) .set(table.website(), \"https://www.manning.com\") .where(table.id().eq(2L)) .execute(); sqlClient .createUpdate(BookStore::class) { set(table.website, \"https://www.manning.com\") where(table.id eq 2L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [BookStore-2]","s":"Cache Invalidation","u":"/jimmer-doc/docs/cache/cache-type/object","h":"#cache-invalidation","p":5},{"i":18,"t":"caution In previous articles on object cache, association cache, and calculated cache, we have discussed in detail how Jimmer automatically deletes affected caches when data is modified. So here we will not repeat the discussion of how Jimmer intelligently invalidates affected caches. The focus of this article is how Jimmer ensures cache deletion operations issued can definitely succeed. Whether it is the fully automatic invalidation of object cache and association cache, or the user assisted invalidation of calculated cache, the cache consistency of Jimmer is driven by triggers. Jimmer triggers are divided into BinLog triggers and Transaction triggers. For different situations, Jimmer adopts different strategies to ensure cache consistency, that is, to ensure that cache invalidation operations must succeed.","s":"Cache Consistency","u":"/jimmer-doc/docs/cache/consistency","h":"","p":17},{"i":20,"t":"When trigger-type is BINLOG_ONLY or BOTH, Jimmer uses the BinLog trigger to invalidate caches. In this case, developers respond to messaging queue notifications, process them simply and then call Jimmer's BinLog API (this user code is very simple, and its complexity can be ignored). Calling the BinLog API initiates all trigger callbacks, including cache invalidation. Take Kafka as an example, make sure to commit the consumption progress after successfully calling the BinLog API, cache invalidation can be guaranteed to eventually succeed.","s":"Consistency of BinLog Trigger (Recommended)","u":"/jimmer-doc/docs/cache/consistency","h":"#consistency-of-binlog-trigger-recommended","p":17},{"i":22,"t":"When trigger-type is TRANSACTION_ONLY, Jimmer will be forced to use the Transaction trigger to invalidate caches. For Transaction triggers: Only modifying the database through Jimmer's own API can trigger all callback behaviors. All trigger callbacks complete before the transaction is committed. If a simple implementation of direct cache invalidation is adopted, any exception during cache invalidation will cause the transaction to be rolled back. Obviously, this implementation is not reasonable. Therefore, when trigger-type is TRANSACTION_ONLY, the cache invalidation operations perceived by the user will be delayed, they will not be executed immediately, but are stored in the JIMMER_TRANS_CACHE_OPERATOR table. caution Jimmer will automatically create the JIMMER_TRANS_CACHE_OPERATOR table. However, the default org.babyfish.jimmer.sql.dialect.DefaultDialect does not support this operation and will throw an exception. Therefore, if cache consistency needs to be driven by transaction trigger, don't use the default DefaultDialect, please explicitly specify the database dialect. Modifications to the JIMMER_TRANS_CACHE_OPERATOR table and business tables belong to the same database local transaction, either both succeed or both fail. After the transaction commits successfully, Jimmer will immediately execute a Flush operation. The so-called Flush operation is to query cache invalidation operations that have not yet been executed from the JIMMER_TRANS_CACHE_OPERATOR table, execute the actual cache invalidation operation, and delete related records if successful. For the Flush operation executed immediately after transaction commit: If successful, it's best to have good real-time. This should be the case most of the time. Even if it fails, it doesn't matter. Jimmer will periodically execute Flush operations to ensure related cache invalidation eventually succeed. The interval of Flush operations is controlled by the global SpringBoot configuration item jimmer.transaction-cache-operator-fixed-delay, which is specified in milliseconds and defaults to 5000.","s":"Consistency of Transaction Trigger","u":"/jimmer-doc/docs/cache/consistency","h":"#consistency-of-transaction-trigger","p":17},{"i":24,"t":"Association cache refers to mapping the current object id to the associated object id or collection. Where: BookStore.books-*: One-to-many association cache Book.store-*: Many-to-one association cache Book.authors-*: Many-to-many association cache Author.books-*: Many-to-many association cache caution Unlike other association caches, there is one scenario that does not require using one-to-one or many-to-one association cache. If a one-to-one or many-to-one association is based on a real foreign key with a corresponding foreign key constraint in the database, then the foreign key itself is the associated object id, and association cache is not required. In other cases, Jimmer will use one-to-one or many-to-one association cache. These cases include: The referenced association property is reverse side That is, @OneToOne's mappedBy is configured. The referenced association property is based on a pseudo foreign key A pseudo foreign key means that it is conceptually a foreign key in the developer's mind, but there is no corresponding foreign key constraint in the database. The pseudo foreign key field may contain illegal values, the non-null value does not mean the associated object exists, so association cache is required to filter out valid associated objects. The referenced association property is based on a join table rather than a foreign key. When implementing GraphQL with Jimmer, Object Fetcher (GraphQL and Object Fetchers are homogenous functions) should not be used in aggregate root queries, but object fetcher were incorrectly used in aggregate root queries to obtain objects without foreign keys. However, the GraphQL request body contains many-to-one associations. In the official sample code included, the many-to-one association Book.store is based on a real foreign key, so its many-to-one cache will not be used. Therefore, the examples in this article use the one-to-many association BookStore.books and the many-to-many association Book.authors.","s":"Association Cache","u":"/jimmer-doc/docs/cache/cache-type/association","h":"","p":23},{"i":26,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...omit code... } // Map current object id to associated object id // Applies to one-to-one and many-to-one associations @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ); } // Map current object id to collection of associated object ids // Applies to one-to-many and many-to-many associations @Override public Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } private Cache createPropCache( ImmutableProp prop, Duration caffeineDuration, Duration redisDuration ) { return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } ...omit other code... }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...omit code... // Map current object id to associated object id // Applies to one-to-one and many-to-one associations override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ) // Map current object id to collection of associated object ids // Applies to one-to-many and many-to-many associations override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ) private fun createPropCache(prop: ImmutableProp, duration: Duration): Cache = ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() ...omit other code... } }","s":"Enabling Association Cache","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#enabling-association-cache","p":23},{"i":28,"t":"caution For collection type associations, if we use the field filter of object fetchers to implement association-level sorting, it will cause Jimmer to ignore association cache. To make full use of association cache while keeping the sorting of the associated object collection returned by the object fetcher query controllable, you can specify the default sorting statically on the entity. BookStore.books Java Kotlin BookStore.java @Entity public interface BookStore { @OneToMany( mappedBy = \"store\", orderedProps = { @OrderedProp(\"name\"), @OrderedProp(value = \"edition\", desc = true) } ) List books(); ...omit other code... } BookStore.kt @Entity interface BookStore { @OneToMany( mappedBy = \"store\", orderedProps = { @OrderedProp(\"name\"), @OrderedProp(value = \"edition\", desc = true) } ) val books : List ...omit other code... } Book.authors Java Kotlin Book.java @Entity public interface Book { @ManyToMany( orderedProps = { @OrderedProp(\"firstName\"), @OrderedProp(\"lastName\") } ) List authors(); ...omit other code... } Book.kt @Entity interface Book { @ManyToMany( orderedProps = { @OrderedProp(\"firstName\"), @OrderedProp(\"lastName\") } ) val authors : List ...omit other code... }","s":"Sorting Collection Associations","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#sorting-collection-associations","p":23},{"i":30,"t":"As mentioned at the beginning of this article, the examples here are based on the one-to-many association BookStore.books and the many-to-many association Book.authors.","s":"Usage","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#usage","p":23},{"i":32,"t":"Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; List stores = sqlClient .createQuery(table) .select( table.fetch( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ) ) .execute(); System.out.println(stores); val stores = sqlClient .createQuery(BookStore::class) { select( table.fetchBy { allScalarFields() books { allScalarFields() } } ) } .execute() println(stores) Step 1: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ The query in the code is implemented here to obtain some BookStore objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. Step 2: Convert current object id to associated object id via association cache The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return two aggregate root objects. The object fetcher in the code contains the one-to-many association BookStore.books The primary keys ID of these 2 BOOK_STOREs are 1 and 2. Jimmer first looks up the data in Redis with keys BookStore.books-1 and BookStore.books-2. Suppose the data corresponding to these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.books-* (empty array) So the following SQL is executed to load data from the database: select tb_1_.STORE_ID, tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 1 */, ? /* 2 */ ) order by tb_1_.NAME asc, tb_1_.EDITION desc Jimmer will put the results of the query into Redis, so we can view this data in Redis: 127.0.0.1:6379> keys BookStore.books-* 1) \"BookStore.books-2\" 2) \"BookStore.books-1\" 127.0.0.1:6379> get BookStore.books-1 \"[6,5,4,3,2,1,9,8,7]\" 127.0.0.1:6379> get BookStore.books-2 \"[12,11,10]\" 127.0.0.1:6379> Thus, the two BookStore objects can obtain the associated object id collections of their respective one-to-many associations BookStore.books. Undoubtedly, before the data in Redis expires, executing the Java/Kotlin code above again will directly return the associated data from Redis without generating the second SQL statement. Step 3: Convert associated object id to associated object via object cache Such operations have been discussed in detail in Object Cache, so they are not repeated here. This article focuses on association cache. caution In the cache configuration, if association cache is enabled for an association property but object cache is not enabled for its associated object type, an exception will be thrown. info Previously in Object Fetcher, we saw that Jimmer only needs one SQL statement to query all associated objects based on a batch of current objects, but here two SQL statements are needed, please view: The difference compared to not enabling cache Finally, Jimmer concatenates the results of the two steps as the final data returned to the user: [ { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, \"price\":88 }, { \"id\":5, ...omit... }, { \"id\":4, ...omit... }, { \"id\":3, ...omit... }, { \"id\":2, ...omit... }, { \"id\":1, ...omit... }, { \"id\":9, ...omit... }, { \"id\":8, ...omit... }, { \"id\":7, ...omit... } ] }, { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80 }, { \"id\":11, ...omit... }, { \"id\":10, ...omit... } ] } ]","s":"One-to-Many: BookStore.books","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#one-to-many-bookstorebooks","p":23},{"i":34,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.edition().eq(1)) .select( table.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition eq 1) select( table.fetchBy { allScalarFields() authors { allScalarFields() } } ) } .execute() println(books) Step 1: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ where tb_1_.EDITION = ? /* 1 */ The query in the code is implemented here to obtain some Book objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. Step 2: Convert current object id to associated object ids via association cache The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return 4 aggregate root objects. The object fetcher in the code contains the many-to-many association Book.authors The primary keys ID of these 4 BOOKs are 1, 4, 7 and 10. Jimmer first looks up the data in Redis with keys Book.authors-1, Book.authors-4, Book.authors-7 and Book.authors-10. Suppose the data corresponding to these keys cannot be found in Redis: 127.0.0.1:6379> keys Book.authors-* (empty array) So the following SQL is executed to load data from the database: select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID from BOOK_AUTHOR_MAPPING tb_1_ inner join AUTHOR tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID in ( ? /* 1 */, ? /* 4 */, ? /* 7 */, ? /* 10 */ ) order by tb_3_.FIRST_NAME asc, tb_3_.LAST_NAME asc note If no default sort is specified for the association property Book.authors via @ManyToMany.orderedProps, the join here will not appear. Jimmer will put the results of the query into Redis, so we can view this data in Redis: 127.0.0.1:6379> keys Book.authors-* 1) \"Book.authors-4\" 2) \"Book.authors-1\" 3) \"Book.authors-10\" 4) \"Book.authors-7\" 127.0.0.1:6379> get Book.authors-1 \"[2,1]\" 127.0.0.1:6379> get Book.authors-4 \"[3]\" 127.0.0.1:6379> get Book.authors-7 \"[4]\" 127.0.0.1:6379> get Book.authors-10 \"[5]\" 127.0.0.1:6379> Thus, we have obtained the associated object id collections that the 4 Book objects can get through their respective many-to-many association Book.authors. Undoubtedly, before the data in Redis expires, executing the Java/Kotlin code above again will directly return the associated data from Redis without generating the second SQL statement. Step 3: Convert associated object id to associated object via object cache Such operations have been discussed in detail in Object Cache, so they are not repeated here. This article focuses on association cache. caution In the cache configuration, if association cache is enabled for an association property but object cache is not enabled for its associated object type, an exception will be thrown. info Previously in Object Fetcher, we saw that Jimmer only needs one SQL statement to query all associated objects based on a batch of current objects, but here two SQL statements are needed, please view: The difference compared to not enabling cache Finally, Jimmer concatenates the 3 steps results as the final data returned to the user: [ { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 51, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] }, { \"id\": 4, \"name\": \"Effective TypeScript\", \"edition\": 1, \"price\": 73, \"authors\": [...omit...] }, { \"id\": 7, \"name\": \"Programming TypeScript\", \"edition\": 1, \"price\": 47.5, \"authors\": [...omit...] }, { \"id\": 10, \"name\": \"GraphQL in Action\", \"edition\": 1, \"price\": 80, \"authors\": [...omit...] } ]","s":"Many-to-Many: Book.authors","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#many-to-many-bookauthors","p":23},{"i":36,"t":"caution To use Jimmer's automatic cache invalidation, triggers need to be enabled first.","s":"Cache Invalidation","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#cache-invalidation","p":23},{"i":38,"t":"Modify the foreign key STORE_ID of the BOOK table, Jimmer automatically deletes the many-to-one association cache Book.store and the one-to-many association cache BookStore.books. If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK /* Old value: 1, New value: 2 */ set STORE_ID = 2 where ID = 7; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(table) // Old value: 1L, New value: 2L .set(table.store().id, 2L) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { // Old value: 1L, New value: 2L set(table.store.id, 2L) where(table.id eq 7L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book-7] Delete data from redis: [Book.store-7] ❶ Delete data from redis: [BookStore.books-1] ❷ Delete data from redis: [BookStore.books-2] ❸ ❶ For the Book object with id 7, its many-to-one association cache Book.store is deleted. ❷ For the BookStore object with id 1 (old value before modification), its one-to-many association cache BookStore.books is deleted. ❸ For the BookStore object with id 2 (new value before modification), its one-to-many association cache BookStore.books is deleted.","s":"One-to-Many: BookStore.books","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#one-to-many-bookstorebooks-1","p":23},{"i":40,"t":"Inserting data into the join table BOOK_AUTHOR_MAPPING automatically deletes the many-to-many association caches Book.authors and Author.books. note Deleting data from the join table can achieve the same effect. Here insertion is used to demonstrate the effect. If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: insert into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values(10, 3); If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .save(10L, 3L); sqlClient .getAssociations(Book::authors) .save(10L, 3L); Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book.authors-10] ❶ Delete data from redis: [Author.books-3] ❷ ❶ For the Book object with id 10, its many-to-many association cache Book.authors is deleted. ❷ For the Author object with id 3, its many-to-many association cache Author.books is deleted.","s":"Many-to-Many: Book.authors","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#many-to-many-bookauthors-1","p":23},{"i":42,"t":"If associated objects support logical deletion, association caching is still supported by default. warning However, once the logical deletion is ignored or reversed, association caching will be ignored.","s":"Notes on Logical Deletion","u":"/jimmer-doc/docs/cache/cache-type/association","h":"#notes-on-logical-deletion","p":23},{"i":44,"t":"Features represented by permission systems allow different users to see different data. Therefore, Jimmer uses multi-view cache to allow different users to see different caches.","s":"Multi-view Cache","u":"/jimmer-doc/docs/cache/multiview-cache/","h":"","p":43},{"i":47,"t":"Using multi-view caches is relatively strict and the following three conditions must be met at the same time: The properties that need multi-view cache must be explicitly specified. Cache is multi-layered. Multiple Binder objects must be specified for the ChainCacheBuilder used to build the cache instance, i.e. LoadingBinder/KLoadingBinder or SimpleBinder/KSimpleBinder. For multi-view caches, all Binder objects must implement the LoadingBinder.Parameterized/KLoadingBinder.Parameterized or SimpleBinder.Parameterized/KSimpleBinder.Parameterized interface. Otherwise, the final cache created by ChainCacheBuilder is a single-view cache. The filtering rules for association properties and the calculation rules for calculated properties must be cache friendly. For association properties, all global filters that affect their associated objects must be cache friendly filters. If any one filter is not cache friendly, it may cause the all affected properties to be unable to use cache. For user-defined cache filters, the CacheableFilter/KCacheableFilter interface must be implemented. For the @LogicalDeleted, its useMultiViewCache property must be configured as true (this will cause its built-in global filter to implement the CacheableFilter/KCacheableFilter interface). For calculated properties, the getParameterMapRef method of TransientResolver/KTransientResolver must not return null. The object fetch cannot use property-level filters. If these prerequisite conditions are not fully met, even if cache is specified for association or calculated properties, Jimmer will abandon them. Although the reasons have been explained in detail in previous documents, troubleshooting such issues during actual development is inconvenient. To quickly inform developers of the fact that property-level cache did not take effect and the reason, Jimmer defines a callback interface as follows: package org.babyfish.jimmer.sql.cache; import org.babyfish.jimmer.meta.ImmutableProp; public interface CacheAbandonedCallback { void abandoned(ImmutableProp prop, Reason reason); enum Reason { CACHEABLE_FILTER_REQUIRED, PARAMETERIZED_CACHE_REQUIRED, FIELD_FILTER_USED } } This callback interface tells developers that although cache is specified for a property, it is not adopted by Jimmer, and the reason. Its abandoned method has two parameters: prop: Which property does not adopt the cache configured by the user. reason: The reason why the cache of this property is not adopted. There are three possible values: CACHEABLE_FILTER_REQUIRED: The associated objects are affected by some global filters, but not all filters implement the CacheableFilter/KCacheableFilter interface. PARAMETERIZED_CACHE_REQUIRED: The getParameters method of some CacheableFilter/KCacheableFilter objects affecting the association properties or the getParameterMapRef method of TransientResolver/KTransientResolver implementing the calculated properties returns a Map of non-zero length, but the cache configured for that property by the developer is not a multi-view cache. FIELD_FILTER_USED: The developer uses property-level filters for the property in object fetchers. Developers can implement the CacheAbandonedCallback interface themselves, create an object, and register it with SqlClient. There is no limit on the number of registered callback objects.","s":"CacheAbandonedCallback","u":"/jimmer-doc/docs/cache/multiview-cache/abandoned-callback","h":"#cacheabandonedcallback","p":45},{"i":49,"t":"There are two ways to register CacheAbandonedCallback for Jimmer: Using Spring Boot Starter Just decorate the implementation class of CacheAbandonedCallback with @Component: Java Kotlin @Component public class MyCallback implements CacheAbandonedCallback { ...omit code... } @Component class MyCallback : CacheAbandonedCallback { ...omit code... } Using underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .addCacheAbandonedCallback( new CacheAbandonedCallback() { ...omit code... } ) ...omit other configuration... .build(); val sqlClient = newKSqlClient { addCacheAbandonedCallback( object: CacheAbandonedCallback { ...omit code... } ) ...omit other configuration... }","s":"Registering Callback","u":"/jimmer-doc/docs/cache/multiview-cache/abandoned-callback","h":"#registering-callback","p":45},{"i":51,"t":"If no callback implementation is registered by the user, the Spring Boot Starter will register a default callback implementation by default, outputting the reason why the cache is not adopted as a warning log, for example: !!!Jimmer warning!!! Property-level cache is abandoned. Property: `com.yourcompany.yourproject.model.BookStore.books` Reason: CACHEABLE_FILTER_REQUIRED","s":"Default Behavior of Spring Boot Starter","u":"/jimmer-doc/docs/cache/multiview-cache/abandoned-callback","h":"#default-behavior-of-spring-boot-starter","p":45},{"i":54,"t":"Calculated cache refers to mapping the current object id to the calculated value of the user-defined complex calculated property.","s":"Calculated Cache","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"","p":53},{"i":56,"t":"In the Complex Calculated Properties article, we discussed complex calculated properties in detail. caution This article focuses on calculated cache and does not repeat the introduction to complex calculated properties. Please read complex calculated properties before reading this article. In this article, we will add cache support for the calculated property BookStore.avgPrice defined in complex calculated properties. info To simplify the documentation, this article only discusses BookStore.avgPrice and does not discuss the other association-based calculated property BookStore.newestBooks. Readers can read and run the following official examples: jimmer-examples/java/jimmer-sql jimmer-examples/java/jimmer-sql-graphql jimmer-examples/kotlin/jimmer-sql-kt jimmer-examples/kotlin/jimmer-sql-graphql-kt","s":"Calculated Property Recap","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#calculated-property-recap","p":53},{"i":58,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...omit code... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { ...omit code... } @Override public Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { ...omit code... } @Override public Cache createResolverCache(ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(1), Duration.ofHours(1) ); } private Cache createPropCache( ImmutableProp prop, Duration caffeineDuration, Duration redisDuration ) { return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...omit code... override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = ...omit code... override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = ...omit code... override fun createResolverCache(prop: ImmutableProp): Cache<*, *> = return createPropCache( prop, Duration.ofMinutes(1), Duration.ofHours(1) ) private fun createPropCache( prop: ImmutableProp, duration: Duration): Cache = ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() } }","s":"Enable Calculated Cache","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#enable-calculated-cache","p":53},{"i":60,"t":"Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; List stores = sqlClient .createQuery(table) .select( table.fetch( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .avgPrice() ) ) .execute(); System.out.println(stores); val stores = sqlClient .createQuery(BookStore::class) { select( table.fetchBy { allScalarFields() avgPrice() } ) } .execute() println(stores) Step 1: Query aggregate root First, query the aggregate root object, executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ The query in the code is implemented here to obtain some BookStore objects. Such objects obtained by direct user queries are called aggregate root objects. caution Jimmer does not cache aggregate objects returned by user queries, because the consistency of such query results cannot be guaranteed. Even if cache them at the cost of sacrificing consistency is required, it is a business need of the user rather than the framework. Step 2: Convert current object id to calculated value via calculated cache The above code will return a series of aggregate root objects. If using the official sample data in the database, it will return two aggregate root objects. The object fetcher in the code contains the calculated property BookStore.avgPrice The primary keys ID of these 2 BOOK_STOREs are 1 and 2. Jimmer first looks up the data in Redis with keys BookStore.avgPrice-1 and BookStore.avgPrice-2. Suppose the data corresponding to these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* (empty array) So the following SQL is executed to compute the calculated property: select tb_1_.ID, avg(tb_2_.PRICE) from BOOK_STORE tb_1_ left join BOOK tb_2_ on tb_1_.ID = tb_2_.STORE_ID where tb_1_.ID in ( ? /* 1 */, ? /* 2 */ ) group by tb_1_.ID Jimmer will put the query results into Redis, so we can view this data in Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* 1) \"BookStore.avgPrice-2\" 2) \"BookStore.avgPrice-1\" 127.0.0.1:6379> get BookStore.avgPrice-1 \"58.5\" 127.0.0.1:6379> get BookStore.avgPrice-2 \"80.333333\" 127.0.0.1:6379> Thus, the two BookStore objects can obtain the average price of their respective books through their calculated property BookStore.avgPrice. Undoubtedly, before the data in Redis expires, executing the Java/Kotlin code above again will directly return the calculated data from Redis without generating the second SQL statement. Finally, Jimmer concatenates the results of the 3 steps as the final data returned to the user: [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"avgPrice\":58.5 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"avgPrice\":80.333333 } ]","s":"Usage","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#usage","p":53},{"i":63,"t":"info Unlike the fully automatic cache invalidation of object cache and association cache, maintaining the consistency of calculated cache requires user assistance. This is because calculated properties introduce custom calculation rules that the ORM framework cannot understand. For the calculated property BookStore.avgPrice, the following two cases will both invalidate the calculated cache: Modifying the STORE_ID foreign key field of the BOOK record will affect the avgPrice cache data of the two bookstores corresponding to the old and new values. Modifying the PRICE field of the BOOK record will invalidate the avgPrice cache data of the bookstore it belongs to. In the Complex Calculated Properties article, a class BookStoreAvgPriceResolver is defined to support the calculated property BookStore.avgPrice. The code is as follows: Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.TransientResolver; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { @Override public Map resolve(Collection ids) { ...omit code... } @Override public BigDecimal getDefaultValue() { ...omit code... } } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.KTransientResolver import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver( ...omit... ) : KTransientResolver { override fun resolve(ids: Collection): Map { ...omit code... } override fun getDefaultValue(): BigDecimal = ...omit code... } We need to override the following two methods in this class: Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.TransientResolver; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { // Constructor inject sqlClient private final JSqlClient sqlClient; ...other code omitted... @Override Collection getAffectedSourceIds(@NotNull EntityEvent e) { // TODO } @Override Collection getAffectedSourceIds(@NotNull AssociationEvent e) { // TODO } } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.KTransientResolver import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver( // Constructor inject sqlClient private val sqlClient: KSqlClient ) : KTransientResolver { ...other code omitted... override fun getAffectedSourceIds(e: EntityEvent<*>): Collection<*>? { // TODO } override fun getAffectedSourceIds(e: AssociationEvent): Collection<*>? { // TODO } } These two methods are the built-in trigger response methods of TransientResolver that are executed automatically when the database changes. They are responsible for automatically clearing the computed cache when the database changes. Next, let's implement these two methods.","s":"Responding to Triggers","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#responding-to-triggers","p":53},{"i":65,"t":"Users can change the association between BOOK_STORE and BOOK by modifying the STORE_ID foreign key of the BOOK table. This will inevitably affect BookStore.avgPrice of some bookstores. tip If watching for changes to the Book.store one-to-many association, the old and new values before and after the modification are two parent objects that need to be considered separately, making the code slightly more cumbersome. Luckily, the entity model in this example has the reverse one-to-many association BookStore.books. When listening for changes to BookStore.books, we only need to consider the id of the current BookStore object, simplifying the code. Implement getAffectedSourceIds(AssociationEvent) as follows: Java Kotlin @Override public Collection getAffectedSourceIds(AssociationEvent e) { if (sqlClient.getCaches().isAffectedBy(e) && ❶ e.getImmutableProp() == BookStoreProps.BOOKS.unwrap() ❷ ) { return Collections.singletonList(e.getSourceId()); ❸ } return null; } override fun getAffectedSourceIds(e: AssociationEvent): Collection<*>? { if (sqlClient.caches.isAffectedBy(e) && ❶ e.immutableProp == BookProps.BOOKS ❷ ) { return listOf(e.sourceId) ❸ } return null } ❶ If the trigger type is set to BOTH, any modification-caused trigger event notifications will be executed twice. note The 1st time: e.connection is non-null, indicating this is a notification from the Transaction trigger. The 2nd time: e.connection is null, indicating this is a notification from the BinLog trigger. However, the cache consistency maintenance work only needs to be done once, no need to do it twice. sqlClient.caches.isAffectedBy(e) can solve this problem, so that even if the trigger type is set to BOTH, the code here will only execute once. caution No matter whether Jimmer's trigger type is set to BOTH or not, it is recommended to include this check as a disciplinary measure. ❷ If the BookStore.books one-to-many association is modified ❹ Then the sourceId of this association modification event (i.e. the BookStore id) needs to have the computed property cache BookStore.avgPrice cleared. Now let's verify the effect of modifying Book.store: If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK /* Old value: 1, New value: 2 */ set STORE_ID = 2 where ID = 7; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(table) // Old value: 1L, New value: 2L .set(table.store().id, 2L) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { // Old value: 1L, New value: 2L set(table.store.id, 2L) where(table.id eq 7L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book-7] Delete data from redis: [Book.store-7] Delete data from redis: [BookStore.avgPrice-1] ❶ Delete data from redis: [BookStore.books-1] Delete data from redis: [BookStore.avgPrice-2] ❷ Delete data from redis: [BookStore.books-2] ❶ The calculated cache BookStore.avgPrice-1 of the parent object referenced by the old foreign key 1 is deleted. ❷ The calculated cache BookStore.avgPrice-2 of the parent object referenced by the new foreign key 2 is deleted.","s":"When BOOK.STORE_ID is modified","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#when-bookstore_id-is-modified","p":53},{"i":67,"t":"Users can also modify the price of books, which will inevitably affect BookStore.avgPrice of the bookstore it belongs to. Implement getAffectedSourceIds(EntityEvent): Java Kotlin @Override public Collection getAffectedSourceIds(EntityEvent e) { if (sqlClient().getCaches().isAffectedBy(e) && ❶ !e.isEvict() && ❷ e.getImmutableType().getJavaClass() == Book.class) { ❸ Ref storeRef = e.getUnchangedRef(BookProps.STORE); ❹ if (storeRef != null && storeRef.getValue() != null && e.isChanged(BookProps.PRICE)) { ❺ return Collections.singletonList(storeRef.getValue().id()); ❻ } } return null; } override fun getAffectedSourceIds(e: EntityEvent<*>): Collection<*>? { if (sqlClient.caches.isAffectedBy(e) && ❶ !e.isEvict && ❷ e.getImmutableType().javaClass == Book::class.java ❸ ) { val store = e.getUnchangedRef(Book::store)?.value ❹ if (store !== null && e.isChanged(Book::price)) { ❺ return listOf(store.id) ❻ } } return null } ❶ If the trigger type is set to BOTH, any modification-caused trigger event notifications will be executed twice. note The 1st time: e.connection is non-null, indicating this is a notification from the Transaction trigger. The 2nd time: e.connection is null, indicating this is a notification from the BinLog trigger. However, the cache consistency maintenance work only needs to be done once, no need to do it twice. sqlClient.caches.isAffectedBy(e) can solve this problem, so that even if the trigger type is set to BOTH, the code here will only execute once. caution No matter whether Jimmer's trigger type is set to BOTH or not, it is recommended to include this check as a disciplinary measure. ❷ There are two reasons for Jimmer's event callbacks, whether it's EntityEvent or AssociationEvent. Explicitly know that the database has been modified In this case, isEvict() returns false. Users can access any property of EntityEvent/AssociationEvent. In the process of automatic cache eviction with cascading effect, the cache of an object/association needs to be evicted In this case, isEvict() returns true. Except for EntityEvent.id/AssociationEvent.sourceId, the event object does not support any other properties like EntityEvent.newEntity, AssociationEvent.attachedTargetId. Here, we need to explicitly determine if the user has modified the PRICE field of the BOOK table, so we must check isEvict() is false. warning Whether to check e.isEvict() must be decided on a case-by-case basis. ❸ Confirm that the current event was triggered because an object of type Book was modified. ❹ ❺ e.getUnchangedRef(BookProps.STORE)/e.getUnchangedRef(Book::store) returns a Ref wrapper object containing the unchanged associated object (only id property) or null, if the Book.store association based on foreign key was not modified. info If the returned Ref wrapper object itself is null, it means this property was modified rather than being Unchanged. If the returned Ref wrapper object is non-null but its internal value is null, it means this property was not modified and its value has remained null all along. Ultimately, we expect the BOOK.STORE_ID foreign key field was not modified and has remained non-null. tip We don't need to consider the case where the foreign key field was modified here, because the other method we discussed earlier, getAffectedSourceIds(AssociationEvent), will properly handle that case. ❻ If all the above conditions are met, then the computed property cache BookStore.avgPrice of the BookStore parent object that the price-modified Book belongs to needs to be cleared. Now let's verify the effect of modifying Book.price: If BinLog trigger is enabled, modifying the database by any means can lead to Jimmer's cache consistency intervention. For example, directly execute the following SQL in the SQL IDE: update BOOK set PRICE = PRICE + 1 where ID = 7; If only Transaction trigger is enabled, Jimmer's API must be used to modify the database: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(table) .set(table.price(), table.price().plus(BigDecimal.ONE)) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { set(table.price, table.price + BigDecimal.ONE) where(table.id eq 7L) } .execute() Regardless of which way above is used to modify the data, you will see the following log output: Delete data from redis: [BookStore.avgPrice-1] ❶ Delete data from redis: [Book-7] ❶ The calculated cache BookStore.avgPrice-1 of the parent object referenced by the foreign key is deleted.","s":"Modifying BOOK.PRICE","u":"/jimmer-doc/docs/cache/cache-type/calculation","h":"#modifying-bookprice","p":53},{"i":70,"t":"Up to now, the caches we have introduced are all single-view caches, where all clients see the same cached data. However, often times, different clients will see different persistent data, which is usually caused by permission systems. Since different clients will see different persistent data, we naturally also expect different clients to see different cache data, that is, the cache provides different views for different clients. Multi-view cache solves this problem very well by allowing different clients to see different caches. caution Unlike previous discussions where cache can be categorized into object cache, association cache and calculated cache, multi-view cache is not adding a new category to the existing taxonomy, but rather another dimension of characteristics. Except for object cache, both association cache and calculated cache can be combined with multi-view cache. Single-view Cache Multi-view Cache Object Cache Object Cache NA Association Cache Single-view Association Cache Multi-view Association Cache Calculated Cache Single-view Calculated Cache Multi-view Calculated Cache info We can refer to association cache and calculated cache together as property cache. Therefore, this table can also be interpreted as property cache can be multi-viewed.","s":"Concepts","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#concepts","p":68},{"i":72,"t":"Multi-view cache is caused by user defined global filters. info As long as an entity is applied with a user defined global filter, all association caches targeting it calculated caches relying on these association caches need to be multi-viewed. For example, if an user defined global filter is added to Book, then properties like: Association properties targeting Book, such as BookStore.books, Author.books Calculated properties relying on the above association properties, such as BookStore.avgPrice, BookStore.newestBooks will be sensitive to the filter, that is, different filtering conditions will result in different data seen by different clients. caution These filter-sensitive properties either do not support cache or support multi-view cache. Configuring single-view cache for them will be considered invalid and the cache configuration will be ignored. Don't worry. Jimmer will tell developers why cache is abandoned.","s":"Scenarios","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#scenarios","p":68},{"i":74,"t":"SubKey is an important concept for multi-view cache and a prerequisite for subsequent documentation. Let's first take a look at the structure of single-view cache Key Value Book-10 {\"id\":10,\"name\":\"GraphQL in Action\",...} Book.authors-1 [1,2] BookStore.avgPrice-2 80.333333 Here we list examples of object cache, association cache and calculated cache. Although the cache types are different, the cache structures are unified simple KV structures. Now let's take a look at an example of multi-view cache: Key SubKey Value BookStore.books-1 {} [6,5,4,3,2,1,9,8,7] {\"tenant\":\"a\"} [5,3,1,9,7] {\"tenant\":\"b\"} [6,4,2,8] {\"module\":\"x\"} [6,5,3,2,9,8] {\"module\":\"x\",\"tenant\":\"a\"} [5,3,9] {\"module\":\"x\",\"tenant\":\"b\"} [6,2,8] {\"module\":\"y\"} [4,1,7] {\"module\":\"y\",\"tenant\":\"a\"} [1,7] {\"module\":\"y\",\"tenant\":\"b\"} [4] BookStore.books-2 {} [12,11,10] {\"tenant\":\"a\"} [11] {\"tenant\":\"b\"} [12,10] {\"module\":\"x\"} [12,11] {\"module\":\"x\",\"tenant\":\"a\"} [11] {\"module\":\"x\",\"tenant\":\"b\"} [12] {} [10] {\"tenant\":\"a\"} [] {\"tenant\":\"b\"} [10] Multi-view cache is no longer a simple KV structure, but a nested two-level KV structure. tip For Redis, this structure is Redis Hashes. In this case, the SubKey in the table is the Hash Key in Redis. Obviously, compared to single-view cache, multi-view cache splits the data into finer granularity by sub key, allowing different clients to see different data. Key The Key in multi-view cache is no different from the key in single-view cache, representing a specific entity property, decided by Jimmer. SubKey The key characteristic of multi-view cache. The permission system allows different clients to have different sub keys, eventually extracting different data from the cache. info In Jimmer, SubKey must be the JSON-serialized string of java.util.SortedMap. This SortedMap must use the default sorting rule without custom Comparator. This is very important. For example, SubKey can only be {\"module\":\"x\",\"tenant\":\"a\"}, not {tenant:\"a\", \"module\":\"x\"} which is different but equivalent. This ensures there is no redundant information internally in multi-view cache. Multi-view cache is only for property cache, i.e. association cache and calculated cache. So association properties and complex calculated properties must specify sub key for their multi-view caches.","s":"SubKey","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#subkey","p":68},{"i":76,"t":"For association properties, the necessity of multi-view cache must be caused by the associated entity being affected by user defined global filters. Supporting multi-view cache by merely implementing the Filter/KFilter interface is not enough. The CacheableFilter/KCacheableFilter interface must be implemented. Java Kotlin CacheableFilter.java package org.babyfish.jimmer.sql.filter; public interface CacheableFilter

extends Filter

{ SortedMap getParameters(); ...other code omitted... } KCacheableFilter.kt package org.babyfish.jimmer.sql.kt.filter interface KCacheableFilter : KFilter { fun getParameters(): SortedMap? ...other code omitted... } Users need to implement the getParameters() method to contribute part of the information to sub key. info When multiple CacheableFilter/KCacheableFilter affect the associated entity, the data returned by the getParameters() method of each filter object is merged together as the SubKey.","s":"SubKey of Association Properties","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#subkey-of-association-properties","p":68},{"i":78,"t":"Implementing complex calculated properties requires implementing the TransientResolver/KTransientResolver interface. Java Kotlin TransientResolver.java package org.babyfish.jimmer.sql; import org.babyfish.jimmer.lang.Ref; import java.util.SortedMap; public interface TransientResolver { default Ref> getParameterMapRef() { return Ref.empty(); } ...other code omitted... } KTransientResolver.kt package org.babyfish.jimmer.sql.kt import org.babyfish.jimmer.lang.Ref interface KTransientResolver : TransientResolver { override fun getParameterMapRef(): Ref?>? = Ref.empty() ...other code omitted... } This method returns the Ref which is the wrapper of SortedMap. If Ref itself is null, it means getting sub key is difficult and multi-view cache cannot be applied to the calculated property. info In this case, Jimmer will tell developers why cache is abandoned. Otherwise, the internal value of Ref represents the sub key of the current calculated property. info When invalidating cache, Jimmer will automatically delete invalid cached by key. Cached items of multi-view cache are always deleted as a whole based on Key rather than partially based on Key + SubKey, to maximize the relative simplicity of multi-view cache.","s":"SubKey of Complex Calculated Properties","u":"/jimmer-doc/docs/cache/multiview-cache/concept","h":"#subkey-of-complex-calculated-properties","p":68},{"i":82,"t":"To enable cache, you first need to implement the CacheFactory/KCacheFactory interface, which is defined as follows: Java Kotlin CacheFactory.java package org.babyfish.jimmer.sql.cache; import org.babyfish.jimmer.meta.ImmutableProp; import org.babyfish.jimmer.meta.ImmutableType; import org.jetbrains.annotations.NotNull; import org.jetbrains.annotations.Nullable; import java.util.List; public interface CacheFactory { @Nullable default Cache createObjectCache(@NotNull ImmutableType type) { return null; } @Nullable default Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return null; } @Nullable default Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { return null; } @Nullable default Cache createResolverCache(@NotNull ImmutableProp prop) { return null; } } KCacheFactory.kt package org.babyfish.jimmer.sql.kt.cache import org.babyfish.jimmer.meta.ImmutableProp import org.babyfish.jimmer.sql.cache.Cache import org.babyfish.jimmer.sql.cache.CacheFactory interface KCacheFactory : CacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = null override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = null override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = null override fun createResolverCache(prop: ImmutableProp): Cache<*, *>? = null } info For Kotlin, in order to generate better code when overriding createAssociatedIdListCache, please implement the org.babyfish.jimmer.sql.kt.cache.KCacheFactory interface. Otherwise, the return type of the override method generated by the IDE will be Cache<*, MutableList<*>> instead of the expected Cache<*, List<*>>. Jimmer calls this interface to initialize caches for types and properties. Users implement this interface to answer: createObjectCache: Enable object cache The parameter specifies an entity type. If you want to enable object cache for it, create and return the cache; otherwise, return null. Object cache refers to mapping id to entity object. info This entity object is orphaned, without associated properties. One-to-one/many-to-one associations based on foreign keys are an exception, they can hold associated objects with only the id property, because the id of the associated object is actually the foreign key field of the current table. createAssociatedIdCache and createAssociatedIdListCache: Enable association cache Both createAssociatedIdCache and createAssociatedIdListCache are used to enable association cache. The only difference between them is: createAssociatedIdCache: For one-to-one or many-to-one associations. createAssociatedIdListCache: For one-to-many or many-to-many associations. The parameter specifies an association property. If you want to enable association cache for it, create and return the cache; otherwise return null. Association cache refers to mapping id to associated id or associated id collection. createResolverCache: Enable calculated cache The parameter specifies a complex calculated property. If you want to enable calculated cache for it, create and return the cache; otherwise, return null. Computed cache refers to mapping id to calculated result.","s":"CacheFactory Interface","u":"/jimmer-doc/docs/cache/enable-cache","h":"#cachefactory-interface","p":80},{"i":84,"t":"The return type of all methods of the CacheFactory interface is org.babyfish.jimmer.sql.cache.Cache. Users do not need to directly implement Cache, but need to use org.babyfish.jimmer.sql.cache.chain.ChainCacheBuilder to build multi-level caches. In theory, ChainCacheBuilder supports caches of any number of levels. However, in most projects, two levels of cache are sufficient, for example: Java Kotlin return new CacheFactory() { @Override @Nullable public Cache createObjectCache(@NotNull ImmutableType type) { return new ChainCacheBuilder<>() .add( ❶ CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(Duration.ofSeconds(10)) .build() ) .add( ❷ RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(10)) .build() ) ) .build(); } }; return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ChainCacheBuilder() .add( ❶ CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(Duration.ofSeconds(10)) .build() ) .add( ❷ RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(10)) .build() ) ) .build() } ❶ Indicates first level cache based on Caffeine in-process JVM cache. ❷ Indicates second level cache based on Redis remote cache. As we can see, ChainCacheBuilder uses chain programming style. Calling the add method multiple times can build multi-level caches. The ChainCacheBuilder.add method is defined as follows: public class ChainCacheBuilder { public ChainCacheBuilder add(LoadingBinder binder) { ❶ ...omit code... return this; } public ChainCacheBuilder add(LoadingBinder.Parameterized binder) { ❷ ...omit code... return this; } public ChainCacheBuilder add(SimpleBinder binder) { ❸ ...omit code... return this; } ...omit other code... } ❶ org.babyfish.jimmer.sql.cache.chain.LoadingBinder is an interface. Any cache technology that automatically loads values on first access to a key can be adapted through this interface. Almost all in-process JVM caches have automatic loading capabilities, such as Caffeine or Guava Cache used in the above code. ❷ The code is only used by multi-view caches. Readers can ignore it for now. ❸ org.babyfish.jimmer.sql.cache.chain.SimpleBinder is an interface. Any cache technology without automatic value loading behavior can be adapted through this interface. Almost all remote caches do not have automatic loading capabilities, such as Redis used in the above code. tip Any cache technology can be adapted to the abstract interfaces LoadingBinder or SimpleBinder. Therefore, in Jimmer's multi-level cache architecture, no assumptions or restrictions are made on the choice of cache technology at any level. If using Jimmer's SpringBoot Starter, you can use the following three cache technology adapter classes, as in the code above: Jimmer's built-in adapter classes Implemented Interface Supports Multi-view Cache org.babyfish.jimmer.spring.cache.CaffeineBinder org.babyfish.jimmer.sql.cache.chain.LoadingBinder No org.babyfish.jimmer.spring.cache.RedisValueBinder org.babyfish.jimmer.sql.cache.chain.SimpleBinder No org.babyfish.jimmer.spring.cache.RedisHashBinder org.babyfish.jimmer.sql.cache.chain.SimpleBinder.Parameterized Yes note Multi-view caches will be explained in a subsequent article. Please ignore them for now.","s":"Multi-level Cache Architecture","u":"/jimmer-doc/docs/cache/enable-cache","h":"#multi-level-cache-architecture","p":80},{"i":86,"t":"Now we have introduced the CacheFactory interface and multi-level cache architecture, but there is one last step to enable cache. The last step is to register CacheFactory for Jimmer.","s":"Configuring CacheFactory","u":"/jimmer-doc/docs/cache/enable-cache","h":"#configuring-cachefactory","p":80},{"i":88,"t":"If using SpringBoot Starter, just let CacheFactory be managed by Spring. Java Kotlin @Bean public CacheFactory cacheFactory() { return new CacheFactory() { ...omit code... }; } @Bean fun cacheFactory(): KCacheFactory = object: KCacheFactory { ...omit code... }","s":"SpringBoot Configuration","u":"/jimmer-doc/docs/cache/enable-cache","h":"#springboot-configuration","p":80},{"i":90,"t":"Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setCacheFactory( new CacheFactory() { ...omit code... } ) ...omit other configuration... .build(); val sqlClient = newKSqlClient { setCacheFactory( object: KCacheFactory { ...omit code... } ) ...omit other configuration... }","s":"Underlying API Configuration","u":"/jimmer-doc/docs/cache/enable-cache","h":"#underlying-api-configuration","p":80},{"i":92,"t":"Earlier we mentioned that if using Jimmer's SpringBoot Starter, you can use the ready-made org.babyfish.jimmer.spring.cache.RedisValueBinder without having to adapt Redis yourself. note RedisHashBinder is related to multi-view caches and will not be discussed in this article. To build RedisValueBinder, you need a RedisOperations. Jimmer's SpringBoot Stater provides the org.babyfish.jimmer.spring.cache.RedisCaches class whose static method RedisCaches.cacheRedisTemplate can quickly build this RedisOperations object. An example of the helper method RedisCaches.cacheRedisTemplate is as follows: Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override @Nullable public Cache createObjectCache(@NotNull ImmutableType type) { return new ChainCacheBuilder() .add( CaffeineValueBinder .forProp() .maximumSize(1024) .duration(RedisCaches.ofMinutes(24)) .bind() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build(); } @Override @Nullable public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ); } @Override @Nullable public Cache> createAssociatedIdListCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5), ); } @Override @Nullable public Cache createResolverCache(@NotNull ImmutableProp prop) { return createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } private Cache createPropCache( ImmutableProp prop, Duration caffeineDuration Duration redisDuration ) { return new ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ChainCacheBuilder() .add( CaffeineValueBinder .forObject(type) .maximumSize(1024) .duration(Duration.ofHours(1)) .build() ) .add( RedisValueBinder .forObject(type) .redis(connectionFactory) .objectMapper(objectMapper) .duration(Duration.ofHours(24)) .build() ) .build() override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( prop, Duration.ofMinutes(10), Duration.ofHours(10) ) override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ) override fun createResolverCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( prop, Duration.ofMinutes(5), Duration.ofHours(5) ) private fun createPropCache( type: ImmutableType, caffeineDuration: Duration, redisDuration: Duration ): Cache<*, *> = ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() } }","s":"Redis Cache Helper APIs","u":"/jimmer-doc/docs/cache/enable-cache","h":"#redis-cache-helper-apis","p":80},{"i":95,"t":"If using Jimmer to build backend systems, developers have three ways to solve the DTO Explosion Description Where object shapes are restricted Client experience Solution 1 Use Jimmer to build GraphQL services Client side Good Solution 2 Use Jimmer to build REST services, shapes specified by client Client side Bad Solution 3 Use Jimmer to build REST services, shapes enumerated by server Server side Good Let's discuss the three cases separately:","s":"Basic Concepts","u":"/jimmer-doc/docs/client/api","h":"#basic-concepts","p":93},{"i":97,"t":"Use Jimmer to build GraphQL services Server: Develop GraphQL Backend with Jimmer Client: Many client frameworks to choose from. Using my graphql-ts-client can get the ultimate TypeScript experience caution Jimmer itself supports recursive query of self-associated properties, but so far, the GraphQL protocol does not support this feature, which means the feature will be lost.","s":"Solution 1 (GraphQL)","u":"/jimmer-doc/docs/client/api","h":"#solution-1-graphql","p":93},{"i":99,"t":"Use Jimmer to build REST services, shapes specified by client This approach actually gives REST the capabilities of GraphQL. The client passes a string, and the server parses it into a Fetcher via org.babyfish.jimmer.sql.fetcher.compiler.FetcherCompiler Java Kotlin BookController.java @GetMapping(\"/book/{id}\") public Book findBookById( @PathVariable long id, @RequestParam(required = false) String fetcherCode ) { Fetcher fetcher = FetcherCompiler.compile(fetcherCode, Book.class); return bookRepository.findNullable(id, fetcher); } BookController.kt @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long, @RequestParam(required = false) fetcherCode: String? ): Book? = bookRepository.findNullable( id, FetcherCompiler.compile(fetcherCode, Book::class.java) ) When calling, specify the fetcherCode parameter, for example { id name authors { id firstName lastName } } or { id, name, authors { id, firstName, lastName }} info To learn how to express more complex object fetcher in string code, refer to the toString() method of object fetcher. caution Although this approach can give REST capabilities similar to GraphQL, which is very flexible, it only facilitates server-side writing. The client will get a messy type system, so it is not recommended. If due to some historical constraints, the client uses JavaScript, not TypeScript, and there is no foreseeable hope of any improvement, then consider this usage.","s":"Solution 2 (Not Recommended)","u":"/jimmer-doc/docs/client/api","h":"#solution-2-not-recommended","p":93},{"i":101,"t":"Use Jimmer to build REST services, shapes enumerated by server This usage is more in line with the original intention of the REST protocol, and it is also easier to manage permissions (although the previous two usages are flexible, permission control is very difficult), and it is also the topic to be discussed in this article. info The case discussed here is when the server API returns dynamic entities (recommended), not DTOs. Let's look at a contradiction first Jimmer uses dynamic entities. As long as the root entity types are the same, any data structure shape can be expressed with the same Java/Kotlin type. The client needs to see rich data types. The shapes returned by the same entity type in different HTTP interfaces are different. This contradiction is essentially the difference in awareness of DTO Explosion Server perspective is producer perspective. From the producer's point of view, DTO explosion is a very annoying problem, which means that their own development costs will also increase dramatically. Therefore, Jimmer uses dynamic entities combined with object fetchers to eliminate DTO explosions on the server side. Client perspective is consumer perspective. From the consumer's point of view, DTO explosion is beneficial, each business scenario has an accurate return type, which is very nice to use. (Difficult to implement? What does that have to do with me?) Therefore, Jimmer server can automatically generate client code to (such as TypeScript) restore the DTO explosion eliminated on the server side on the client side. tip The server eliminates DTO explosions, and the client restores DTO explosions. This is the fundamental value of Jimmer's automatic sever-client integration, and it is also the essential difference between Jimmer and any other technology that automatically generates client code. Only by letting the server and client use completely different programming models can both sides get the ultimate development experience at the same time.","s":"Solution 3 (Topic of This Article)","u":"/jimmer-doc/docs/client/api","h":"#solution-3-topic-of-this-article","p":93},{"i":104,"t":"Previously we discussed that using Jimmer to build REST services with shapes enumerated by the server is the topic to be discussed in this article. To use this development approach, you need to use the @org.babyfish.jimmer.client.FetchBy annotation to decorate dynamic entity types in REST API return types, to mark specific shapes of dynamic objects for the client. tip @FetchBy does not simply decorate the return value of the REST API, but is used to decorate type references. Its declaration code is as follows package org.babyfish.jimmer.client; import java.lang.annotation.*; @Documented @Retention(RetentionPolicy.RUNTIME) @Target(ElementType.TYPE_USE) public @interface FetchBy { ...omitted... } Therefore, the return type of the REST API is very flexible. You can use it to decorate Jimmer entity types anywhere (including generic parameters), for example @FetchBy(\"...\") Book List<@FetchBy(\"...\") Book> Page<@FetchBy(\"...\") Book> Tuple2<@FetchBy(\"...\") BookStore, @FetchBy(\"...\") Author> Map> Java Kotlin BookController.java @GetMapping(\"/books\") public Page< @FetchBy(\"SIMPLE_FETCHER\") Book ❶ > findBookById( @RequestParam(defaultValue = \"0\") int pageIndex, @RequestParam(defaultValue = \"5\") int pageSize, @RequestParam(defaultValue = \"name asc, edition desc\") String sortCode ) { return bookRepository.findBooks( PageRequest.of(pageIndex, pageSize, SortUtils.toSort(sortCode)), SIMPLE_FETCHER ❷ ); } @GetMapping(\"book/{id}\") @Nullable public @FetchBy(\"COMPLEX_FETCHER\") Book ❸ findComplexBook( @PathVariable(\"id\") long id ) { return bookRepository.findNullable( id, COMPLEX_FETCHER ❹ ); } private static final Fetcher SIMPLE_FETCHER = ❺ Fetchers.BOOK_FETCHER .allScalarFields() .tenant(false); private static final Fetcher COMPLEX_FETCHER = ❻ Fetchers.BOOK_FETCHER .allScalarFields() .tenant(false) .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .avgPrice() ) .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ); BookController.kt @GetMapping(\"/books\") fun findBooks( @RequestParam(defaultValue = \"0\") pageIndex: Int, @RequestParam(defaultValue = \"5\") pageSize: Int, @RequestParam(defaultValue = \"name asc, edition desc\") sortCode: String ): Page< @FetchBy(\"SIMPLE_FETCHER\") Book ❶ > = bookRepository.findBooks( PageRequest.of(pageIndex, pageSize, SortUtils.toSort(sortCode)), name, storeName, authorName, SIMPLE_FETCHER ❷ ) @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long, ): @FetchBy(\"COMPLEX_FETCHER\") Book? = ❸ bookRepository.findNullable( id, COMPLEX_FETCHER ❹ ) companion object { private val SIMPLE_FETCHER = ❺ newFetcher(Book::class).by { allScalarFields() tenant(false) } private val COMPLEX_FETCHER = ❻ newFetcher(Book::class).by { allScalarFields() tenant(false) store { allScalarFields() avgPrice() } authors { allScalarFields() } } } ❶ Promise externally that the shape of each Book object in the paged object returned by GET /books is expressed by the static constant SIMPLE_FETCHER ❷ Internal implementation, GET /books uses static constant SIMPLE_FETCHER internally to query data caution ❶ as external commitment and ❷ as internal implementation must be consistent ❸ Promise externally that if GET /book/{id} returns non-null, its shape is expressed by the static constant COMPLEX_FETCHER ❹ Internal implementation, GET /book/{id} uses static constant COMPLEX_FETCHER internally to query data caution ❸ as external commitment and ❹ as internal implementation must be consistent ❺ and ❻, declare object shapes as static constants. With the decoration of @FetchBy, Jimmer understands the specific shape of each object's externally returned data, so it can generate code for the client, including TypeScript. info In this example, the class annotated with @FetchBy and the class declaring object shapes with static constants are the same class. If not, you can use the ownerType parameter of @FetchBy, for example @FetchBy(value = \"COMPLEX_FETCHER\", ownerType = FetcherConstants.class)","s":"Declare @FetchBy","u":"/jimmer-doc/docs/client/api","h":"#declare-fetchby","p":93},{"i":106,"t":"The following configuration can be declared in application.yml or application.properties to download related client code jimmer: ...other configurations omitted... client: ts: path: /ts.zip ❶ java-feign: path: /java-feign.zip ❷ Currently, Jimmer supports generating two types of client code, TypeScript and Java Feign Client code required by Spring Cloud ❶ Can download Web client required TypeScript code through http://localhost:8080/ts.zip ❷ Can download Spring Cloud required Java Feign Client code through http://localhost:8080/java-feign.zip Next we discuss the TypeScript code. Start the service, download http://localhost:8080/ts.zip, decompress it. Let the root directory after decompression be ${ts_root}: Let's take a look at ${ts_root}/model/dto/BookDto.ts first BookDto.ts export type BookDto = { 'BookService/SIMPLE_FETCHER': { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, }, 'BookService/COMPLEX_FETCHER': { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, readonly store?: { readonly id: number, readonly name: string, readonly website?: string, readonly avgPrice: number }, readonly authors: ReadonlyArray<{ readonly id: number, readonly firstName: string, readonly lastName: string, readonly gender: Gender }> } } info It is obvious that the DTO explosion eliminated on the server side is restored on the client side. Let's also take a look at ${ts_root}/services/BookService.ts import type { BookDto } from '../model/dto'; import type { Page } from '../model/static'; export class BookService { async findBooks( options: BookServiceOptions['findBooks'] ): Promise< Page< BookDto['BookService/SIMPLE_FETCHER'] > > { ...code omitted... } async findBookById( options: BookServiceOptions['findBookById'] ): Promise< BookDto['BookService/COMPLEX_FETCHER'] | undefined > { ...code omitted... } ...other code omitted... } export type BookServiceOptions = { 'findBooks': { readonly pageIndex: number, readonly pageSize: number, readonly sortCode: string }, 'findBookById': { readonly id: number } } info It is obvious that the return type of each business scenario is accurately defined.","s":"Generate Client Code","u":"/jimmer-doc/docs/client/api","h":"#generate-client-code","p":93},{"i":108,"t":"Create project First create a typescript based react project yarn create react-app my-web-app --template typescript Automatically generate client code Obviously, it is impossible to require client developers to manually download server code, decompress it, and replace local code every time changes occur on the server side. So we need to write a small script to automatically complete the download, decompression and replacement of the latest TypeScript code. Add folder scripts under project root, and add file generate-api.js under it. This file is executed by nodejs and is tooling code for development, not the code of the client itself. scripts/generate-api.js const http = require('http'); const fs = require('fs'); const fse = require('fs-extra'); const uuid = require('uuid'); const tempDir = require('temp-dir'); const AdmZip = require('adm-zip'); const sourceUrl = \"http://localhost:8080/ts.zip\"; const tmpFilePath = tempDir + \"/\" + uuid.v4() + \".zip\"; const generatePath = \"src/__generated\"; console.log(\"Downloading \" + sourceUrl + \"...\"); const tmpFile = fs.createWriteStream(tmpFilePath); const request = http.get(sourceUrl, (response) => { response.pipe(tmpFile); tmpFile.on(\"finish\", () => { tmpFile.close(); console.log(\"File save success: \", tmpFilePath); // Remove generatePath if it exists if (fs.existsSync(generatePath)) { console.log(\"Removing existing generatePath...\"); fse.removeSync(generatePath); console.log(\"Existing generatePath removed.\"); } // Unzip the file using adm-zip console.log(\"Unzipping the file...\"); const zip = new AdmZip(tmpFilePath); zip.extractAllTo(generatePath, true); console.log(\"File unzipped successfully.\"); // Remove the temporary file console.log(\"Removing temporary file...\"); fs.unlink(tmpFilePath, (err) => { if (err) { console.error(\"Error while removing temporary file:\", err); } else { console.log(\"Temporary file removed.\"); } }); }); }); Here, adm-zip needs to be installed separately yarn add adm-zip --dev Modify project's package.json and add the following code under its \"scripts\" field { ...other code omitted... \"scripts\": { ...other code omitted... \"api\": \"node scripts/generate-api.js\" } ...other code omitted... } So every time the server team notifies that REST API changes have occurred, just execute yarn api simply to refresh the local TypeScript client code caution This method is only suitable when the web team is very small in size. If there are many web developers, it is more recommended to implement secondary development on the CI environment to achieve the following: Each time the server code on a specific branch is committed, the CI environment compiles and starts the service, then downloads the ts code, decompresses it, and commits it to git. Finally, web engineers can simply pull the latest code from git. Create Global API Object The generated TypeScript code has a __generated/Api.ts file that needs to be instantiated into a global variable and configured properly. Under src, create ApiInstance.ts and export the global variable api src/ApiInstance.ts import { Api } from \"../__generated\"; const BASE_URL = \"http://localhost:8080\"; // Export global variable `api` export const api = new Api(async({uri, method, body}) => { const response = await fetch(`${BASE_URL}${uri}`, { body: body !== undefined ? JSON.stringify(body) : undefined, headers: { 'content-type': 'application/json;charset=UTF-8', ...other important HTTP headers, e.g. Authorization... } }); if (response.status !== 200) { throw response.json(); } const text = await response.text(); if (text.length === 0) { return null; } return JSON.parse(text); }); Call REST APIs Now we can call REST APIs based on global variable api. info The following examples are based on use-immer and TanStack/Query. Being proficient in or quickly mastering various remote request libraries is the basic literacy of web front-end engineers, so the details are not elaborated here. Experience api.bookService.findBooks const [options, setOptions] = useImmer< // RequestOf is a TypeScript helper class generated by Jimmer, // used to extract parameter types of any REST API RequestOf< typeof api.bookService.findBooks > >(() => { return { pageIndex: 0, pageSize: 10, sortCode: \"name asc\" }; }); const { isLoading, // If `data` is not `undefined`, its type must be // `Page` data, error, refetch } = useQuery({ queryKey: [\"Books\", options], // The type of `data` is determined here queryFn: () => api.bookService.findBooks(options) }); If request succeeds, the type of data is Page. Where BookDto['BookService/SIMPLE_FETCHER'] is defined as { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, } Experience api.bookService.findBookById In the following code, assume id is the current React primary key parameter const { // If `data` is not `undefined`, its type must be // `BookDto['BookService/COMPLEX_FETCHER']` data, isLoading, error } = useQuery({ queryKey: [\"book/detail\", id], queryFn: () => api.bookService.findBookById({id: id!}), enabled: id !== undefined }); If request succeeds and data is not null, its type is BookDto['BookService/COMPLEX_FETCHER']. This type is defined as: { readonly id: number, readonly name: string, readonly edition: number, readonly price: number, readonly store?: { readonly id: number, readonly name: string, readonly website?: string, readonly avgPrice: number }, readonly authors: ReadonlyArray<{ readonly id: number, readonly firstName: string, readonly lastName: string, readonly gender: Gender }> } tip It can be seen that any REST API call will return strict data type definitions, and these strict type definitions will also affect the React UI template code in tsx files. This will give full play to the advantages of TypeScript, providing good IDE intelligence, and ensuring all problems are discovered at compile time, thus having a good development experience.","s":"Develop Web Client Project","u":"/jimmer-doc/docs/client/api","h":"#develop-web-client-project","p":93},{"i":110,"t":"Although @FetchBy combined with Jimmer's dynamic entities can restore DTO type definitions in client code, one situation still needs to be carefully considered: the returned data type differs greatly from the underlying entity model. For example: Java Kotlin ActiveAuthorInfo.java @lombok.Data public class ActiveAuthorInfo { private Author raw; private List stores; } ActiveAuthorInfo.kt data class ActiveAuthorInfo( val raw: Author, val stores: List ) In this example, ActiveAuthorInfo represents a very active author, containing the original information of the author raw, and the collection of all bookstores selling his/her books. The corresponding HTTP service interface is: Java Kotlin AuthorController.java @GetMapping(\"/authors/mostActive\") public List findMostActiveAuthorInfos( @RequestParam(defaultValue = \"10\") int limit ) { ...omitted... } AuthorController.kt @GetMapping(\"/authors/mostActive\") fun findMostActiveAuthorInfos( @RequestParam(defaultValue = \"10\") limit: Int ): List { ...omitted... } Obviously, this data structure differs greatly from the underlying entity model. In the entity model, there is an association between BookStore and Book, and there is also an association between Book and Author, but there is no association between BookStore and Author. tip In some cases, the data required by the client may contain multiple entity objects that have no direct ORM association, but only a certain business-level correlation. If such business-level correlations are not generic at all, then defining complex calculated properties for entities is not a good choice either. At this point, we can break the stereotypical thinking of the entity object graph and use custom data to represent the return results, just like ActiveAuthorInfo here. However, ActiveAuthorInfo is not a purely custom user data type, it mixes the use of Jimmer entities internally. Let's call it a hybrid type. The @FetchBy annotation can be used to decorate the fields of this hybrid type, for example: Java Kotlin ActiveAuthorInfo.java @lombok.Data public class ActiveAuthorInfo { private @FetchBy(\"AUTHOR_FETCHER\") Author raw; private List<@FetchBy(\"STORE_FETCHER\") BookStore> stores; private static final Fetcher AUTHOR_FETCHER = Fetchers.AUTHOR_FETCHER .firstName() .lastName(); private static final Fetcher STORE_FETCHER = Fetchers.AUTHOR_FETCHER.name(); } ActiveAuthorInfo.kt data class ActiveAuthorInfo( val raw: @FetchBy(\"AUTHOR_FETCHER\") Author, val stores: List<@FetchBy(\"STORE_FETCHER\") BookStore> ) { companion object { private val AUTHOR_FETCHER = newFetcher(Author::class) { firstName() lastName() } private val STORE_FETCHER = new Fetcher(BookStore::class) { name() } } } Finally, the TypeScript related types generated for ActiveAuthorInfo are as follows (for convenience, the code of multiple TypeScript files is mixed here): export interface ActiveAuthorInfo { readonly raw: AuthorDto['ActiveAuthorInfo/AUTHOR_FETCHER']; readonly stores: ReadonlyArray< BookStoreDto['ActiveAuthorInfo/STORE_FETCHER'] >; } export type AuthorDto { 'ActiveAuthorInfo/AUTHOR_FETCHER': { readonly id: number, readonly firstName: string, readonly lastName: string }, ...other DTO types omitted... } export type BookStoreDto { 'ActiveAuthorInfo/STORE_FETCHER': { readonly id: number, readonly name: string }, ...other DTO types omitted... }","s":"Integrate with Custom Data","u":"/jimmer-doc/docs/client/api","h":"#integrate-with-custom-data","p":93},{"i":112,"t":"This section introduces the global configurations supported by Jimmer.","s":"Configuration","u":"/jimmer-doc/docs/configuration/","h":"","p":111},{"i":114,"t":"SqlClient supports two configurations: DefaultBatchSize and DefaultListBatchSize. If not configured, the default values are 128 and 16. These two configurations provide default values for the batchSize in Object Fetcher. Their effects have been described in detail in Object Fetcher, so this article only explains the configuration without repeating the explanation of their effects. There are two ways to set these configurations: Use Spring Boot Starter Don't use Spring Boot Starter","s":"Batch Control","u":"/jimmer-doc/docs/configuration/batch-size","h":"","p":113},{"i":116,"t":"jimmer: default-batch-size: 256 default-list-batch-size: 32","s":"Use Spring Boot Starter","u":"/jimmer-doc/docs/configuration/batch-size","h":"#use-spring-boot-starter","p":113},{"i":118,"t":"Java Kotlin @Bean public JSqlClient sqlClient() { return JSqlClient .newBuilder() .setConnectionManager(...) .setDialect(new H2Dialect()) .setExecutor(...) .addScalarProvider(...) .setDefaultBatchSize(256) .setDefaultListBatchSize(32) .build(); } @Bean fun sqlClient(): KSqlClient = newKSqlClient { setConnectionManager { ... } setDialect(H2Dialect()) setExecutor { ... } addScalarProvider { ... } setDefaultBatchSize(256) setDefaultListBatchSize(32) }","s":"Don't use Spring Boot Starter","u":"/jimmer-doc/docs/configuration/batch-size","h":"#dont-use-spring-boot-starter","p":113},{"i":120,"t":"This part is actually unrelated to ORM. However, since generate client api is provided, this part of the functionality must also be provided to make it a complete solution.","s":"Generate Client Errors","u":"/jimmer-doc/docs/client/error","h":"","p":119},{"i":122,"t":"We need to define special Java/Kotlin business exceptions that can be directly translated into data that the client can understand. How do we define this special type of business exception? There are two extreme choices: Share one business exception class across the entire application, with built-in error codes that the client can understand Define a business exception class for each business error Obviously, both of the above solutions are unsuitable. The first option is too coarse-grained, with globally maintained error codes that are difficult to maintain. The second option is too fine-grained, requiring the definition of too many exception classes. So, Jimmer chooses a compromise: dividing business exceptions into multiple families, with each family using one set of Error Codes. Jimmer uses enums to define exception families, where the enum also serves as the error code for that family, e.g.","s":"Exception Families","u":"/jimmer-doc/docs/client/error","h":"#exception-families","p":119},{"i":124,"t":"Java Kotlin UserInfoErrorCode.java package com.example.business.error; import org.babyfish.jimmer.error.ErrorFamily; @ErrorFamily public enum UserInfoErrorCode { ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } UserInfoErrorCode.kt package com.example.business.error import org.babyfish.jimmer.error.ErrorFamily @ErrorFamily enum class UserInfoErrorCode { ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } The @org.babyfish.jimmer.error.ErrorFamily annotation indicates that this enum represents a family of business exceptions, and the enum itself serves as the error code for this family. The @ErrorFamily annotation will be processed by Jimmer's precompiler info Here, the precompiler refers to Annotation Processor for Java, and KSP for Kotlin. This part of the code has been discussed in Overview/Get Started/Generate Code, so it won't be repeated here. The precompiler will generate the following exception class based on this enum: info For enums used to declare exception families, you can choose to use ErrorCode or Error as a special suffix. If there is such a special suffix, the exception class name = enum name without the suffix + Exception Otherwise, exception class name = enum name + Exception So here the generated exception name is UserInfoException After compilation by Jimmer, the following exception class will be generated. Java Kotlin UserInfoException.java public abstract class UserInfoException extends CodeBasedException { ❶ private UserInfoException(String message, Throwable cause) { super(message, cause); } @Override public abstract UserInfoErrorCode getCode(); ❷ public static UserInfoException illegalUserName(@NotNull String message) { ❸ return new IllegalUserName( message, null ); } public static UserInfoException illegalUserName( ❹ @NotNull String message, @Nullable Throwable cause ) { return new IllegalUserName( message, cause ); } public static UserInfoException passwordTooShort(@NotNull String message) { ❺ return new PasswordTooShort( message, null ); } public static UserInfoException passwordTooShort( ❻ @NotNull String message, @Nullable Throwable cause ) { return new PasswordTooShort( message, cause ); } public static UserInfoException passwordsNotSame(@NotNull String message) { ❼ return new PasswordsNotSame( message, null ); } public static UserInfoException passwordsNotSame( ❽ @NotNull String message, @Nullable Throwable cause ) { return new PasswordsNotSame( message, cause ); } public static class IllegalUserName extends UserInfoException { public IllegalUserName(String message, Throwable cause) { super(message, cause); } @Override public UserInfoErrorCode getCode() { return UserInfoErrorCode.ILLEGAL_USER_NAME; ❾ } @Override public Map getFields() { return Collections.emptyMap(); } } public static class PasswordTooShort extends UserInfoException { public PasswordTooShort(String message, Throwable cause) { super(message, cause); } @Override public UserInfoErrorCode getCode() { return UserInfoErrorCode.PASSWORD_TOO_SHORT; ❿ } @Override public Map getFields() { return Collections.emptyMap(); } } public static class PasswordsNotSame extends UserInfoException { public PasswordsNotSame(String message, Throwable cause) { super(message, cause); } @Override public UserInfoErrorCode getCode() { return UserInfoErrorCode.PASSWORDS_NOT_SAME; ⓫ } @Override public Map getFields() { return Collections.emptyMap(); } } } UserInfoException.kt public abstract class UserInfoException private constructor( message: String, cause: Throwable? = null, ) : CodeBasedException(message, cause) { ❶ public abstract override val code: UserInfoErrorCode ❷ public companion object { @JvmStatic public fun illegalUserName( ❸❹ message: String, cause: Throwable? = null ): UserInfoException = IllegalUserName( message, cause ) @JvmStatic public fun passwordTooShort( ❺❻ message: String, cause: Throwable? = null ): UserInfoException = PasswordTooShort( message, cause ) @JvmStatic public fun passwordsNotSame( ❼❽ message: String, cause: Throwable? = null ): UserInfoException = PasswordsNotSame( message, cause ) } public class IllegalUserName( message: String, cause: Throwable? = null, ) : UserInfoException(message, cause) { public override val code: UserInfoErrorCode get() = UserInfoErrorCode.ILLEGAL_USER_NAME ❾ public override val fields: Map get() = emptyMap() } public class PasswordTooShort( message: String, cause: Throwable? = null, ) : UserInfoException(message, cause) { public override val code: UserInfoErrorCode get() = UserInfoErrorCode.PASSWORD_TOO_SHORT ❿ public override val fields: Map get() = emptyMap() } public class PasswordsNotSame( message: String, cause: Throwable? = null, ) : UserInfoException(message, cause) { public override val code: UserInfoErrorCode get() = UserInfoErrorCode.PASSWORDS_NOT_SAME ⓫ public override val fields: Map get() = emptyMap() } } ❶ Exceptions based on enum error codes must inherit from org.babyfish.jimmer.error.CodeBasedException ❷ The error code type for this family of exceptions is UserInfoErrorCode ❸❹ Static method to construct exception with error code ILLEGAL_USER_NAME ❺❻ Static method to construct exception with error code PASSWORD_TOO_SHORT ❼❽ Static method to construct exception with error code PASSWORDS_NOT_SAME ❾ Exception class UserInfoException.IllegalUserName has error code ILLEGAL_USER_NAME ❿ Exception class UserInfoException.PasswordTooShort has error code PASSWORD_TOO_SHORT ⓫ Exception class UserInfoException.PasswordsNotSame has error code PASSWORDS_NOT_SAME","s":"Define Exception Families","u":"/jimmer-doc/docs/client/error","h":"#define-exception-families","p":119},{"i":126,"t":"Additional fields can be added to any error code. For example, ILLEGAL_USER_NAME indicates an illegal username, i.e. the username contains illegal characters. We can add the field illegalChars for it. Java Kotlin UserInfoErrorCode.java @ErrorFamily public enum UserInfoErrorCode { @ErrorField(name = \"illegalChars\", type = Character.class, list = true) ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } UserInfoErrorCode.kt @ErrorFamily enum class UserInfoErrorCode { @ErrorField(name = \"illegalChars\", type = Char::class, list = true) ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT, PASSWORDS_NOT_SAME } The generated code is as follows: Java Kotlin UserInfoException.java public abstract class UserInfoException extends CodeBasedException { public static UserInfoException illegalUserName( @NotNull String message, @NotNull List illegalChars ) { ...omit code... } public static UserInfoException illegalUserName( @NotNull String message, @Nullable Throwable cause, @NotNull List illegalChars ) { ...omit code... } public static class IllegalUserName extends UserInfoException { @NotNull private final List illegalChars; public IllegalUserName( String message, Throwable cause, @NotNull List illegalChars ) { super(message, cause); this.illegalChars = illegalChars; } @Override public Map getFields() { return Collections.singletonMap(\"illegalChars\", illegalChars); } @NotNull public List getIllegalChars() { return illegalChars; } ...omit other code... } ...omit other code... } UserInfoException.kt public abstract class UserInfoException private constructor( message: String, cause: Throwable? = null, ) : CodeBasedException(message, cause) { ❶ public abstract override val code: UserInfoErrorCode ❷ public companion object { @JvmStatic public fun illegalUserName( message: String, cause: Throwable? = null, illegalChars: List, ): UserInfoException = ...omit code... ...omit other code... } public class IllegalUserName( message: String, cause: Throwable? = null, public val illegalChars: List, ) : UserInfoException(message, cause) { public override val fields: Map get() = mapOf( \"illegalChars\" to illegalChars ) ...omit other code... } }","s":"Add Fields to Error Codes","u":"/jimmer-doc/docs/client/error","h":"#add-fields-to-error-codes","p":119},{"i":129,"t":"Java Kotlin UserController.java package com.example.service; import org.babyfish.jimmer.client.ThrowsAll; @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode.class) public void registerUser(@RequestBody RegisterUserInput input) { ...omit code... } UserController.kt package com.example.service import import org.babyfish.jimmer.client.ThrowsAll @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode::class) fun registerUser(@RequestBody input: RegisterUserInput) { ...omit code... } info The @org.babyfish.jimmer.client.ThrowsAll annotation allows the REST API to throw all exceptions in the family.","s":"Allow To Throw All Exceptions Of Family","u":"/jimmer-doc/docs/client/error","h":"#allow-to-throw-all-exceptions-of-family","p":119},{"i":131,"t":"Let's locate another business exception family: Java Kotlin PlatformErrorCode.java @ErrorFamily public enum PlatformErrorCode { PERMISSION_DENIED, DATA_IS_FROZEN, SERVICE_IS_SUSPENDED, } PlatformErrorCode.kt @ErrorFamily enum class PlatformErrorCode { PERMISSION_DENIED, DATA_IS_FROZEN, SERVICE_IS_SUSPENDED } To be able to declare that a REST API can only throw some of the exceptions in this family, define the following annotation: Java Kotlin ThrowsPlatformError.java @Documented @Retention(RetentionPolicy.RUNTIME) @Target(ElementType.METHOD) public @interface ThrowsPlatformError { PlatformErrorCode[] value(); } ThrowsPlatformError.kt @Retention(AnnotationRetention.RUNTIME) @Target(AnnotationTarget.FUNCTION) annotation class ThrowsPlatformError( val value: Array ) This annotation satisfies the following 5 conditions: Retention is configured as RUNTIME, i.e. reflectable at runtime Target is configured as METHOD or FUNCTION (kotlin), can be used to decorate methods Has a property named value The value property is of array type The array element type of value is an enum decorated with @ErrorFamily. tip If an annotation satisfies all the above conditions, it can be used to decorate REST APIs to declare the exceptions that can be thrown. Just like how we use @ThrowsAll. Java Kotlin UserController.java @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode.class) @ThrowsPlatformError({PlatformErrorCode.SERVICE_IS_SUSPENDED}) public void registerUser(@RequestBody RegisterUserInput input) { ...omit code... } UserController.kt @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode::class) @ThrowsPlatformError([PlatformErrorCode.SERVICE_IS_SUSPENDED]) fun registerUser(@RequestBody input: RegisterUserInput) { ...omit code... }","s":"Allow To Throw Some Exceptions Of Family","u":"/jimmer-doc/docs/client/error","h":"#allow-to-throw-some-exceptions-of-family","p":119},{"i":134,"t":"Java Kotlin UserController.java @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode.class) @ThrowsPlatformError({PlatformErrorCode.SERVICE_IS_SUSPENDED}) public void registerUser(@RequestBody RegisterUserInput input) { if (...some condition...) { throw PlatformException.serviceIsSuspended( \"The service is suspended\" ); } ...omit other code... } UserController.kt @PostMapping(\"/user\") @ThrowsAll(UserInfoErrorCode::class) @ThrowsPlatformError([PlatformErrorCode.SERVICE_IS_SUSPENDED]) fun registerUser(@RequestBody input: RegisterUserInput) { if (...some condition...) { throw PlatformException.serviceIsSuspended( \"The service is suspended\" ) } ...omit other code... } caution The kinds of exceptions thrown internally must not exceed those declared externally.","s":"Throw Exceptions","u":"/jimmer-doc/docs/client/error","h":"#throw-exceptions","p":119},{"i":136,"t":"tip As long as Jimmer's Spring Boot Starter is used, no extra work is required. Any exception inherited from CodeBasedException thrown by the service will be automatically translated. The translation result is: { \"family\":\"USER_INFO_ERROR_CODE\", \"code\":\"ILLEGAL_USER_NAME\", \"illegalChars\": [\"&\", \"`\", \"@\"] } To facilitate development and testing, you can configure in application.yml or application.properties: jimmer: error-translator: debug-info-supported: true This configuration will include information useful for locating issues during development and testing in the HTTP response. Since the content is quite long, please click the button below to view the result. View Result warning This configuration is only for assisting development and testing, and must NOT be enabled in production environments! For example, enable this switch in application-dev.yml and application-test.yml, but absolutely do NOT enable it in application-prod.yml.","s":"Write Exception Messages to HTTP Responses","u":"/jimmer-doc/docs/client/error","h":"#write-exception-messages-to-http-responses","p":119},{"i":139,"t":"export type AllErrors = ❶ { readonly family: \"PLATFORM_ERROR_CODE\", ❷ readonly code: \"SERVICE_IS_SUSPENDED\" ❸ } | { readonly family: \"USER_INFO_ERROR_CODE\", readonly code: \"ILLEGAL_USER_NAME\", readonly \"illegalChars\": ReadonlyArray ❹ } | { readonly family: \"USER_INFO_ERROR_CODE\", readonly code: \"PASSWORDS_NOT_SAME\" } | { readonly family: \"USER_INFO_ERROR_CODE\", readonly code: \"PASSWORD_TOO_SHORT\" } | ...omit other code... ; export type ApiErrors = { ❺ \"userController\": { ❻ \"registerUser\": AllErrors & ( ❼ { readonly family: 'USER_INFO_ERROR_CODE', readonly code: 'ILLEGAL_USER_NAME', readonly [key:string]: any } | { readonly family: 'USER_INFO_ERROR_CODE', readonly code: 'PASSWORD_TOO_SHORT', readonly [key:string]: any } | { readonly family: 'USER_INFO_ERROR_CODE', readonly code: 'PASSWORDS_NOT_SAME', readonly [key:string]: any } | { readonly family: 'PLATFORM_ERROR_CODE', readonly code: 'SERVICE_IS_SUSPENDED', readonly [key:string]: any } ), ...omit other code... }, \"bookController\": { ...omit code... }, ...omit other code... }; ❶ AllErrors defines all error types caution Only REST APIs that explicitly declare exceptions that may be thrown via annotations in Java/Kotlin code will be used to generate TypeScript code. For example, in the Java/Kotlin code above, we defined the error codes PlatformError.PERMISSION_DENIED and PlatformErrorCode.DATA_IS_FROZEN, but they have not yet been declared as throwable by any REST API using @ThrowsAll or custom @ThrowsPlatformError. So they will not be defined in AllErrors. ❷ The enum name decorated with @ErrorFamily is the family field in client code, used to identify which family the error belongs to ❸ The enum variable name is the code field in client code, used to identify which specific error it is ❹ The server uses @ErrorField (can repeat) to declare arbitrary additional fields for an error code (only one here), so all additional fields are generated here tip ❶ AllErrors defines all errors, never duplicated. ApiErrors at ❺ refers to errors, may have duplicates. Because different REST APIs may declare throwing the same error code. So additional fields are always declared in AllErrors, not in ApiErrors. This is the fundamental reason AllErrors and ApiErrors are separated. ❺ Errors that each REST API may throw ❻ Errors that userController module may throw ❼ Errors that userController.registerUser API may throw","s":"Generated TypeScript Code","u":"/jimmer-doc/docs/client/error","h":"#generated-typescript-code","p":119},{"i":141,"t":"The above TypeScript code is quite lengthy, and considering some readers may not have TypeScript background knowledge, here are some IDE auto-complete screenshots: Under global type ApiErrors, there are two options: userController and bookController ApiErrors[\"userController\"] has three options: login, logout and registerUser For ApiErrors[\"userController\"][\"registerUser\"], the family field has two options: USER_INFO_ERROR_CODE and PLATFORM_ERROR_CODE Once family is determined as UserInfoErrorCode, the code field has three options: ILLEGAL_USER_NAME, PASSWORD_TOO_SHORT and PASSWORDS_NOT_SAME Once code is determined as ILLEGAL_USER_NAME, the additional illegalChars field can be used","s":"TypeScript IDE Effects","u":"/jimmer-doc/docs/client/error","h":"#typescript-ide-effects","p":119},{"i":144,"t":"In Jimmer, all executable statements and instructions support two execution modes: Execute based on the JDBC connection specified by the user Executed by Jimmer automatically determining based on a JDBC connection Here, take Executable (Java) or KExecutable (Kotlin) interface as an example Java Kotlin Executable.java package org.babyfish.jimmer.sql.ast; import java.sql.Connection; public interface Executable { R execute(); R execute(Connection con); } KExecutable.kt package org.babyfish.jimmer.sql.kt import java.sql.Connection interface KExecutable { fun execute(con: Connection? = null): R } execute(Connection): Execute on the JDBC connection specified by the user. Take query as an example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select(book) .execute(con); val books = sqlClient .createQuery(Book::class) { select(table) } .execute(con) info For this usage, no special configuration of SqlClient is required. execute() or execute(null): Determined by Jimmer to execute on a JDBC connection. Take query as an example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { select(table) } .execute() info For this usage, ConnectionManager must be configured for SqlClient. Otherwise it will cause exceptions. Undoubtedly, the 2nd approach is more in line with the requirements of business system development, so it is recommended. So it is strongly recommended to configure ConnectionManager for SqlClient.","s":"Concept","u":"/jimmer-doc/docs/configuration/connection-manager","h":"#concept","p":142},{"i":146,"t":"Java Kotlin javax.sql.DataSource dataSource = ...; JSqlClient sqlClient = JSqlClient .newBuilder() .setConnectionManager( ConnectionManager .simpleConnectionManager(dataSource) ) .build(); val dataSource: javax.sql.DataSource = ... val sqlClient = newKSqlClient { setConnectionManager { dataSource.connection.use { proceed(it) } } } danger This way is only responsible for getting connections from DataSource and has no transaction management mechanism. However, transactions are very important in actual projects. Therefore, except for learning and trying, it is not recommended to use this approach in actual projects.","s":"Simple ConnectionManager","u":"/jimmer-doc/docs/configuration/connection-manager","h":"#simple-connectionmanager","p":142},{"i":148,"t":"This topic has been discussed in detail in Spring Section/Integrate Spring Transaction. This article will not repeat the explanation. tip Letting Jimmer be managed by Spring transaction is the recommended usage.","s":"ConnectionManager managed by Spring transaction","u":"/jimmer-doc/docs/configuration/connection-manager","h":"#connectionmanager-managed-by-spring-transaction","p":142},{"i":151,"t":"Admittedly, Jimmer's strongly typed SQL DSL can expose problems as much as possible at compile time, and most errors can be prevented before testing. But this is not enough. The strongly typed SQL DSL can only improve the reliability of the entity model -> business code link, but cannot guarantee the reliability of the database structure -> entity model link. There is also a derived problem. If developers get reliable applications in the test environment, how to ensure that the application remains reliable after being transplanted to the production environment? Database validation is a very important feature that is used to verify the consistency between the database structure and the entity model definition. info Validation Rules Verify that table names, column names, sequence names are consistent with definitions in the entity model. Verify that the nullity of columns is consistent with the definitions of properties in the entity model. If a property is decorated with @OneToOne(inputNotNull = true) or @ManyToOne(inputNotNull = true), the nullity of the property itself is ignored. it is considered that the corresponding foreign key in the data cannot be null. For the id property of each entity in the entity model, verify that the database has a primary key constraint that exactly matches. For true foreign keys defined in the entity model (see True and False Foreign Keys), verify that the database has exactly matching foreign key constraints.","s":"Function Introduction","u":"/jimmer-doc/docs/configuration/database-validation","h":"#function-introduction","p":149},{"i":153,"t":"There are two ways to start validation: Use Spring Boot Starter Modify application.yml (or application.properties) jimmer: database-validation-mode: ERROR Use underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseValidationMode( DatabaseValidationMode.ERROR ) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseValidationMode( DatabaseValidationMode.ERROR ) ...Omit other configurations... } DatabaseValidationMode is an enum type with three values: NONE: Don't validate database structure, this is the default behavior. WARNING: Validate database structure, if the database structure is inconsistent with the entity model definition, it does not prevent the program from running, just prints warning information in the log. ERROR: Validate database structure, if the database structure is inconsistent with the entity model definition, an exception will be thrown to prevent the program from running.","s":"Enable Validation","u":"/jimmer-doc/docs/configuration/database-validation","h":"#enable-validation","p":149},{"i":155,"t":"Entity types must correspond to a table in the database, whether the table name is explicitly configured by the developer via @Table or automatically determined by the naming strategy. Association properties based on join tables must correspond to a real join table in the database, whether the table name is explicitly configured by the developer via @JoinTable or automatically determined by the naming strategy. The ID whose auto growth strategy is SEQUENCE must correspond to a sequence in the database, whether the sequence name is explicitly configured by the developer via @GeneratedValue or automatically determined by the naming strategy . When the program starts, Jimmer needs to query the database metadata to verify whether these tables or sequences exist. And if they exist, whether their internal structures are correct (for tables). However, since database often support multiple sub-databases, and sub-databases can authorize each other, the JDBC connection may see tables with the same name in different database users, such as db1.BOOK, db2.BOOK, and db3.BOOK. This is called table conflict. Of course, Jimmer can extract the database name from the JDBC connection metadata, for example, extract \"db1\" from jdbc:mysql://localhost:3306/db1, and first look for table information in the automatically extracted sub-database for verification. However, this method is not always valid. As long as the specified table cannot be found in the current sub-database, it will look for it in other sub-databases, which may lead to table conflict issues. To solve this problem, the following two methods are available: Specify strict table names or sequence names, for example: Change @Table(name = \"BOOK\") to @Table(name = \"db1.BOOK\"). Change @JoinTable(name = \"BOOK_AUTHOR_MAPPING\") to @JoinTable(name = \"db1.BOOK_AUTHOR_MAPPING\"). Change @GeneratedValue(sequenceName = \"BOOK_ID_SEQ\") to @GeneratedValue(sequenceName = \"db1.BOOK_ID_SEQ\"). Explicitly specify the sub-database name used for validation, which can be divided into two methods: There are two ways to start validation Use Spring Boot Starter Modify application.yml (or application.properties) jimmer: database-validation: mode: ERROR catalog: db1 info jimmer.database-validation-mode and jimmer.database-validation.mode are equivalent Use underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseValidationMode( DatabaseValidationMode.ERROR ) .setDatabaseValidationCatalog(\"db1\") ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseValidationMode( DatabaseValidationMode.ERROR ) setDatabaseValidationCatalog(\"db1\") ...Omit other configurations... } Similarly, schema can also be specified, for example: Direct configuration: @Table(name = \"mydatabase.myschema.BOOK\") Configure in SpringBoot's application.yml file jimmer: database-validation: mode: ERROR catalog: mydatabase schema: myschema Underlying API configuration Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseValidationMode( DatabaseValidationMode.ERROR ) .setDatabaseValidationCatalog(\"mydatabase\") setDatabaseValidationSchema(\"myschema\") ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseValidationMode( DatabaseValidationMode.ERROR ) setDatabaseValidationCatalog(\"mydatabase\") setDatabaseValidationSchema(\"myschema\") ...Omit other configurations... }","s":"Resolve Table Conflicts","u":"/jimmer-doc/docs/configuration/database-validation","h":"#resolve-table-conflicts","p":149},{"i":157,"t":"Sometimes developers are developing a new feature that is incomplete and cannot be verified. Developers will naturally not run unfinished features and expect unfinished parts not to verify the database structure. For this, Jimmer provides the annotation @org.babyfish.jimmer.sql.DatabaseValidationIgnore. This annotation has the following two usages: Annotate entity interfaces to indicate that the entire entity does not need to be verified. Annotate entity properties to indicate that specific properties do not need to be verified.","s":"Temporarily ignore partial validation","u":"/jimmer-doc/docs/configuration/database-validation","h":"#temporarily-ignore-partial-validation","p":149},{"i":159,"t":"This configuration is explained in Mapping Section/Base Mapping/Naming Strategy. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Default Naming Strategy","u":"/jimmer-doc/docs/configuration/default-database-stragegy","h":"","p":158},{"i":161,"t":"This configuration is explained in Mapping Section/Advanced Mapping/Enum Mapping/Don't explicitly use @EnumType. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Default Enum Strategy","u":"/jimmer-doc/docs/configuration/default-enum-strategy","h":"","p":160},{"i":163,"t":"This configuration is explained in Cache Section/Multiview Cache/Cache Abandoned Reason. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Cache Abandoned Reason","u":"/jimmer-doc/docs/configuration/cache-abandoned","h":"","p":162},{"i":165,"t":"Different databases have vastly different SQL support, so Jimmer uses dialect configuration to adapt to different databases.","s":"Dialect","u":"/jimmer-doc/docs/configuration/dialect","h":"","p":164},{"i":167,"t":"If using the Spring Boot Starter provided by Jimmer, there are two ways: Configure application.yml or application.properties jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect Provide global dialect Bean Java Kotlin @Bean public Dialect dialect() { return new MySqlDialect(); } @Bean fun dialect(): Dialect = MySqlDialect() info If both methods above are used (not recommended), the second method takes precedence If not using the Spring Boot Starter provided by Jimmer Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect(new MySqlDialect()) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDialect(MySqlDialect()) ...Omit other configurations... }","s":"Set Dialect","u":"/jimmer-doc/docs/configuration/dialect","h":"#set-dialect","p":164},{"i":169,"t":"org.babyfish.jimmer.sql.dialect.DefaultDialect This is the default dialect used by Jimmer when no dialect is specified, so there is no need to specify it explicitly. warning The default configuration can only be used for learning simple demos in the initial stage, and can never be used in actual projects. The following situations will cause exceptions: Operations on Jimmer in the code will generate SQL that depends on specific database products, rather than perfect cross-database SQL When the type of trigger is set to TRANSACTION_ONLY and cache is used, Jimmer will automatically create the JIMMER_TRANS_CACHE_OPERATOR table at startup. DefaultDialect does not support this operation, please refer to Cache Consistency org.babyfish.jimmer.sql.dialect.H2Dialect org.babyfish.jimmer.sql.dialect.MySql5Dialect org.babyfish.jimmer.sql.dialect.MySqlDialect org.babyfish.jimmer.sql.dialect.PostgresDialect org.babyfish.jimmer.sql.dialect.OracleDialect org.babyfish.jimmer.sql.dialect.TiDBDialect org.babyfish.jimmer.sql.dialect.SQLiteDialect Because TiDB is a distributed database that does not support foreign key constraints, true foreign keys are not supported by this dialect. Please refer to True and False Foreign Keys Apart from this, TiDBDialect has no difference with MySqlDialect. For other databases, users can extend dialects by themselves. But the database needs to support multi-column in expressions, such as where (a, b) in ((3, 4), (8, 13)) Or where (a, b) in (select x, y from ...) note Currently, multi-column in expressions are highly dependent features of Jimmer, and Microsoft Sql Server does not support this feature for the time being. So Microsoft Sql Server is not supported for now.","s":"Dialect List","u":"/jimmer-doc/docs/configuration/dialect","h":"#dialect-list","p":164},{"i":171,"t":"In the OnDissociate article, we know there are 5 dissociation modes: NONE (default) LAX CHECK SET_NULL DELETE For pseudo foreign key (please refer to Real and Fake Foreign Keys) associative properties, when its dissociation mode is NONE: If the global configuration jimmer.default-dissociation-action-checkable is true (default), it is equivalent to CHECK. If the global configuration jimmer.default-dissociation-action-checkable is false, it is equivalent to NONE.","s":"Default Dissociation Mode","u":"/jimmer-doc/docs/configuration/dissociate-action-checking","h":"","p":170},{"i":173,"t":"This configuration is explained in Mutation Section/Save Command/Enum Mapping/Associated Id Checking. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Associated Id Checking","u":"/jimmer-doc/docs/configuration/id-only-target-checking-level","h":"","p":172},{"i":175,"t":"caution This article only explains how to enable the relevant options. As for what these options are used for, please refer to Query Chapter/DSL Expression/IN LIST/Optimization, this article will not repeat it.","s":"In List Predicate Optimization","u":"/jimmer-doc/docs/configuration/in-list-optimization","h":"","p":174},{"i":177,"t":"Two ways to enable: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-padding-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListPaddingEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListPaddingEnabled(true) // ...omitted other configurations... }","s":"Enable Padding Optimization","u":"/jimmer-doc/docs/configuration/in-list-optimization","h":"#enable-padding-optimization","p":174},{"i":179,"t":"Two ways to enable: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-to-any-equality-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListToAnyEqualityEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListToAnyEqualityEnabled(true) // ...omitted other configurations... }","s":"Enable Any Equality Optimization","u":"/jimmer-doc/docs/configuration/in-list-optimization","h":"#enable-any-equality-optimization","p":174},{"i":181,"t":"This configuration is explained in Spring Section/SpringCloud and Remote Association/Enable Jimmer to Support Microservices. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Microservice","u":"/jimmer-doc/docs/configuration/micro-service","h":"","p":180},{"i":183,"t":"This configuration is explained in Mutation Section/Save Command/Pessimistic Lock. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Pessimistic Lock","u":"/jimmer-doc/docs/configuration/save-command-pessimistic-lock","h":"","p":182},{"i":185,"t":"In Jimmer, each data source corresponds to a sqlClient object (whose type is JSqlClient or KSqlClient). For the most classic single data source case, one sqlClient object is sufficient. Even the Jimmer Spring Boot Starter can automatically create a single sqlClient object. For multiple data sources, developers need to manually create multiple sqlClient objects. For the Jimmer Spring Boot Starter, the support for multiple data sources falls into two cases: Distributed Transaction Mode Local Transaction Mode","s":"Multiple DataSources","u":"/jimmer-doc/docs/configuration/multi-datasources","h":"","p":184},{"i":187,"t":"Here, distributed transactions refer to using Spring's support for JTA transactions. In this mode, simply create multiple sqlClient objects. Java Kotlin import org.springframework.beans.factory.annotation.Qualifier; import org.babyfish.jimmer.spring.SpringClients; @configuration public class SqlClientConfig { @Bean public JSqlClient sqlClient1( ApplicationContext ctx, @Qualifier(\"ds1\") DataSource dataSource ) { return SqlClients.java(ctx, dataSource, null); } @Bean public JSqlClient sqlClient2( ApplicationContext ctx, @Qualifier(\"ds2\") DataSource dataSource ) { return SqlClients.java(ctx, dataSource, null); } } import org.springframework.beans.factory.annotation.Qualifier import org.babyfish.jimmer.spring.SpringClients @configuration class SqlClientConfig { @Bean public fun sqlClient1( ctx: ApplicationContext, @Qualifier(\"ds1\") dataSource: DataSource ): KSqlClient = SqlClients.kotlin(ctx, dataSource) @Bean public fun sqlClient2( ctx: ApplicationContext, @Qualifier(\"ds2\") dataSource: DataSource ): KSqlClient = SqlClients.kotlin(ctx, dataSource) } Then, developers can freely use any of the sqlClient objects. Even if two data sources are operated within a transaction, the JTA transaction will ensure consistency between them.","s":"Distributed Transaction Mode","u":"/jimmer-doc/docs/configuration/multi-datasources","h":"#distributed-transaction-mode","p":184},{"i":189,"t":"Local transactions are slightly different, let's first look at the code: Java Kotlin import org.springframework.beans.factory.annotation.Qualifier; import org.springframework.transaction.support.PlatformTransactionManager; import org.babyfish.jimmer.spring.SpringClients; import org.babyfish.jimmer.spring.transaction.JimmerTransactionManager; import org.babyfish.jimmer.spring.transaction.TransactionalSqlClients; @configuration public class SqlClientConfig { @Bean public PlatformTransactionManager tm1( ❶ ApplicationContext ctx, @Qualifier(\"ds1\") DataSource dataSource ) { return new JimmerTransactionManager( SqlClients.java(ctx, dataSource, null) ); } @Bean public PlatformTransactionManager tm2( ❷ ApplicationContext ctx, @Qualifier(\"ds2\") DataSource dataSource ) { return new JimmerTransactionManager( SqlClients.java(ctx, dataSource, null) ); } @Bean public JSqlClient sqlClient() { ❸ return TransactionalSqlClients.java(); } } import org.springframework.beans.factory.annotation.Qualifier import org.springframework.transaction.support.PlatformTransactionManager import org.babyfish.jimmer.spring.SpringClients import org.babyfish.jimmer.spring.transaction.JimmerTransactionManager import org.babyfish.jimmer.spring.transaction.TransactionalSqlClients @configuration public class SqlClientConfig { @Bean fun tm1( ctx: ApplicationContext, @Qualifier(\"ds1\") dataSource: DataSource ): PlatformTransactionManager = ❶ JimmerTransactionManager( SqlClients.kotlin(ctx, dataSource, null) ) @Bean fun tm2( ctx: ApplicationContext, @Qualifier(\"ds2\") dataSource: DataSource ): PlatformTransactionManager = ❷ JimmerTransactionManager( SqlClients.kotlin(ctx, dataSource, null) ) @Bean public JSqlClient sqlClient() = ❸ TransactionalSqlClients.kotlin() } ❶ Create the first transaction manager based on the first DataSource, note that: The transaction manager type is org.babyfish.jimmer.spring.transaction.JimmerTransactionManager. Although the internal code creates a sqlClient object, it is not exposed to the Spring context, but is held and hidden by the transaction manager. ❷ Create the second transaction manager based on the second DataSource, same as ❶, no need to repeat. ❸ Create a sqlClient proxy and expose it to the Spring context for developers to inject and use. For any business method that needs to operate Jimmer, the annotation @Transactional(\"tm1\") or @Transactional(\"tm2\") must be used, so that Jimmer can be told which JimmerTransactionManager the current business method is using. Otherwise, using the ❸ sqlClient proxy will result in the following exception: The transactional sql client is used, however, there is no AOP transaction, or the transaction manager is not \"org.babyfish.jimmer.spring.transaction.JimmerTransactionManager\" Once Jimmer understands that the current thread is using one of the transaction managers from ❶ and ❷, the ❸ sqlClient proxy will use the internal sqlClient of the corresponding JimmerTransactionManager from ❶ or ❷ to provide services for the user. That is, in the local transaction mode, although multiple sqlClient objects can be created, the business method must explicitly specify which data source to use through the Spring annotation @Transactional(transactionManagerRef).","s":"Local Transaction Mode","u":"/jimmer-doc/docs/configuration/multi-datasources","h":"#local-transaction-mode","p":184},{"i":193,"t":"In the User defined Filters documentation, we introduced that custom global filters need to implement the Filter/KFilter interface. However, ordinary filters defined using this interface are not cache-friendly. Taking the Book entity as an example, if a cache-unfriendly global filter is set for it, it will cause all the following filter-sensitive properties Association properties targeting Book, such as BookStore.books, Author.books Calculated properties relying on the above association properties, such as BookStore.avgPrice, BookStore.newestBooks to become uncacheable. Jimmer uses the CacheableFilter/KCacheableFilter interface to define cache-friendly filters: Java Kotlin CacheableFilter.java package org.babyfish.jimmer.sql.filter; import org.babyfish.jimmer.sql.ast.table.Props; import org.babyfish.jimmer.sql.event.EntityEvent; import java.util.SortedMap; public interface CacheableFilter

extends Filter

{ SortedMap getParameters(); boolean isAffectedBy(EntityEvent e); } KCacheableFilter.kt package org.babyfish.jimmer.sql.kt.filter import org.babyfish.jimmer.sql.event.EntityEvent import java.util.* interface KCacheableFilter : KFilter { fun getParameters(): SortedMap? fun isAffectedBy(e: EntityEvent<*>): Boolean } This interface inherits from Filter/KFilter and adds two new methods: getParameters: The sub key fragment contributed by this filter for multi-view cache. isAffectedBy: Accepts an event that the filtered entity is modified, and judges whether the filtering fields depended on by the current filter are changed. info An entity type allows being processed by multiple global filters: If any one of them is cache-unfriendly, it will cause all filter-sensitive properties to become uncacheable. Therefore, these global filters must either all be cache-unfriendly Filter/KFilter, or all be cache-friendly CacheableFilter/KCacheableFilter. Mixing them together makes no sense. If such meaningless mixing occurs accidentally, Jimmer will tell why cache is abandoned. When all global filters are cache-friendly, the data returned by the getParameters() method of all CacheableFilter/KCacheableFilter objects is merged together as the SubKey of the multi-view cache. For example, if an entity is processed by two global filters at the same time. One is the filter implied by logical delete, denoted as a; the other one is a user-defined filter, denoted as b. Assume a's getParameters() returns {\"logicalDeleted\":false} b's getParameters() returns {\"tenant\":\"a\"} Then the final SubKey in multi-view cache will be {\"logicalDeleted\":false,\"tenant\":\"a\"}","s":"Basic Concepts","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#basic-concepts","p":190},{"i":195,"t":"In the User-defined Filters documentation, we defined a super type TenantAware for entities. Let's review its code again: Java Kotlin TenantAware.java @MappedSuperclass public interface TenantAware { String tenant(); } TenantAware.kt @MappedSuperclass interface TenantAware { val tenant: String } Any entity type that needs to support multiple tenants can inherit TenantAware, such as Book: Java Kotlin Book.java @Entity public interface Book extends TenantAware { ...code omitted... } Book.kt @Entity interface Book : TenantAware { ...code omitted... } Assume there is an object of type TenantProvider in the Spring context. Its Java method get() and Kotlin property tenant are used to extract the tenant from the identity information of the current operator. Define the following filter: Java Kotlin @Component public class TenantFilter implements CacheableFilter { private final TenantProvider tenantProvider; public TenantFilter(TenantProvider tenantProvider) { this.tenantProvider = tenantProvider; } @Override public void filter(FilterArgs args) { String tenant = tenantProvider.get(); if (tenant != null) { args.where(args.getTable().tenant().eq(tenant)); } } @Override public SortedMap getParameters() { String tenant = tenantProvider.get(); if (tenant == null) { return null; } SortedMap map = new TreeMap<>(); map.put(\"tenant\", tenant); return map; } @Override public boolean isAffectedBy(EntityEvent e) { return e.isChanged(TenantAwareProps.TENANT) } } @Component class TenantFilter( private val tenantProvider: TenantProvider ) : KCacheableFilter { override fun filter(args: KFilterArgs) { tenantProvider.tenant?.let { args.apply { where(table.tenant.eq(it)) } } } override fun getParameters(): SortedMap? = tenantProvider.tenant?.let { sortedMapOf(\"tenant\" to it) } override fun isAffectedBy(e: EntityEvent<*>): Boolean = e.isChanged(TenantAware::tenant) }","s":"Define Cache-friendly Filters","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#define-cache-friendly-filters","p":190},{"i":198,"t":"Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new CacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...code omitted... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { ...code omitted... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( prop == BookStoreProps.BOOKS.unwrap() || prop == AuthorProps.BOOKS.unwrap() prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } @Override public Cache createResolverCache(ImmutableProp prop) { return createPropCache( prop == BookStoreProps.AVG_PRICE.unwrap() || prop == BookStoreProps.NEWEST_BOOKS.unwrap() prop, Duration.ofMinutes(1), Duration.ofHours(1) ); } private Cache createPropCache( boolean isMultiviewCache, ImmutableProp prop, Duration caffeineDuration, Duration redisDuration ) { if (isMultiView) { return new ChainCacheBuilder() .add( CaffeineHashBinder .forProp(prop) .maximumSize(128) .duration(caffeineDuration) .build() ) .add( RedisHashBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } return new ChainCacheBuilder<>() .add( CaffeineValueBinder .forObject(type) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: KCacheFactory { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...code omitted... override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = ...code omitted... override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( prop === BookStore::books.toImmutableProp() || prop === Author::books.toImmutableProp(), prop, Duration.ofMinutes(1), Duration.ofHours(1) ) override fun createResolverCache(prop: ImmutableProp): Cache<*, *> = createPropCache( prop === BookStore::avgPrice.toImmutableProp() || prop === BookStore::newestBooks.toImmutableProp(), prop, Duration.ofMinutes(1), Duration.ofHours(1) ) private fun createPropCache( isMultiView: Boolean, prop: ImmutableProp, caffeineDuration: Duration, redisDuration: Duration ): Cache { if (isMultiView) { return ChainCacheBuilder() .add( CaffeineHashBinder .forProp(prop) .maximumSize(128) .duration(caffeineDuration) .build() ) .add( RedisHashBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build(); } ChainCacheBuilder() .add( CaffeineValueBinder .forProp(prop) .maximumSize(512) .duration(caffeineDuration) .build() ) .add( RedisValueBinder .forProp(prop) .redis(connectionFactory) .objectMapper(objectMapper) .duration(redisDuration) .build() ) .build() } } } The RedisHashBinder class in the above code is a very important implementation that utilizes Redis' support for multi-view cache. The underlying storage structure corresponds to Redis Hashes, i.e. nested Hash structures. Cache Style Is Multi-view Abstract API Built-in Impl Cache with self-loading (usually first-level cache technologies like Guava, Caffeine) Single-view LoadingBinder CaffeineValueBinder Multi-view LoadingBinder.Parameterized None Cache without self-loading (usually second-level cache technologies like Redis) Single-view SimpleBinder RedisValueBinder Multi-view SimpleBinder.Parameterized RedisHashBinder RedisHashBinder","s":"Simple Approach","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#simple-approach","p":190},{"i":200,"t":"In the above code, the createAssociatedIdListCache method judges the prop parameter to decide whether to build multi-view cache or single-view cache. However, tip For association properties, whether multi-view cache needs to be built can be determined solely by whether the target entity is filtered. Jimmer provides better support for this. Developers only need to replace the super interface CacheFactory/KCacheFactory with the super class AbstractCacheFactory/AbstractKCacheFactory to inherit a member called getFilterState/filterState which can help us determine whether to build multi-view cache. Java Kotlin @Bean public CacheFactory cacheFactory( RedisConnectionFactory connectionFactory, ObjectMapper objectMapper ) { return new AbstractCacheFactory() { @Override public Cache createObjectCache(@NotNull ImmutableType type) { ...code omitted... } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( getFilterState().isAffectedBy(prop.getTargetType()), prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } @Override public Cache createAssociatedIdCache(@NotNull ImmutableProp prop) { return createPropCache( getFilterState().isAffectedBy(prop.getTargetType()), prop, Duration.ofMinutes(5), Duration.ofHours(5) ); } @Override public Cache createResolverCache(ImmutableProp prop) { return createPropCache( prop == BookStoreProps.AVG_PRICE.unwrap() || prop == BookStoreProps.NEWEST_BOOKS.unwrap() prop, Duration.ofSeconds(1), Duration.ofHours(24) ); } private Cache createPropCache( boolean isMultiviewCache, ImmutableProp prop, Duration duration ) { ...code omitted... } }; } @Bean fun cacheFactory( connectionFactory: RedisConnectionFactory, objectMapper: ObjectMapper ): KCacheFactory { return object: AbstractKCacheFactory() { override fun createObjectCache(type: ImmutableType): Cache<*, *>? = ...code omitted... override fun createAssociatedIdCache(prop: ImmutableProp): Cache<*, *>? = createPropCache( filterState.isAffectedBy(prop.targetType), prop, Duration.ofMinutes(5), Duration.ofHours(5) ) override fun createAssociatedIdListCache(prop: ImmutableProp): Cache<*, List<*>>? = createPropCache( filterState.isAffectedBy(prop.targetType), prop, Duration.ofMinutes(5), Duration.ofHours(5) ) override fun createResolverCache(prop: ImmutableProp): Cache<*, *> = createPropCache( prop === BookStore::avgPrice.toImmutableProp() || prop === BookStore::newestBooks.toImmutableProp(), prop, Duration.ofHours(1), Duration.ofHours(24) ) private fun createPropCache( isMultiView: Boolean, prop: ImmutableProp, caffeineDuration: Duration, redisDuration: Duration ): Cache { ...code omitted... } } } info Unfortunately, this method can only simplify the construction of association caches, i.e. simplify the createAssociatedIdCache and createAssociatedIdListCache methods. For calculated properties, since the framework is unaware of the internal logic used by user-defined calculated properties, it cannot simplify them. Users need to decide whether to build multi-view caches based on their own business characteristics.","s":"Better Approach","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#better-approach","p":190},{"i":202,"t":"We have defined the getParameters method in TenantFilter. All affected association properties will automatically specify SubKey for their association caches. However, unfortunately, due to the introduction of user-defined calculation rules that the framework cannot understand, developers must manually specify SubKey for the TransientResolver implementation of calculated properties. Java Kotlin BookStoreAvgPriceResolver.java @Component public class BookStoreAvgPriceResolver implements TransientResolver { private final JSqlClient sqlClient; @Override public Ref> getParameterMapRef() { return sqlClient .getFilters() .getTargetParameterMapRef(BookStoreProps.BOOKS); } ...code omitted... } BookStoreAvgPriceResolver.kt @Component class BookStoreAvgPriceResolver( private val sqlClient: KSqlClient ) : KTransientResolver { override fun getParameterMapRef(): Ref?>? { return sqlClient .filters .getTargetParameterMapRef(BookStore::books) } ...code omitted... } Obviously, the calculated property BookStore.avgPrice is actually determined by the association property BookStore.books and changes with it. Therefore, whatever SubKey the association property BookStore.books specifies for the multi-view cache system in the current invocation context, the calculated property BookStore.avgPrice should specify the same one. note BookStore.avgPrice is also affected by Book.price. It changes when Book.price changes. However, Book.price is a non-associative property of the object, so it must be irrelevant to the multi-view cache system. The getParameterMapRef method does not need to consider it here.","s":"SubKey of Calculated Properties","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#subkey-of-calculated-properties","p":190},{"i":204,"t":"Now that we have made the association property BookStore.books and the calculated property BookStore.avgPrice support multi-view caching, let's use object fetchers to query them: Java Kotlin BookStoreTable table = Tables.BOOK_STORE_TABLE; List stores = sqlClient .createQuery(table) .select( table.fetch( Fetchers.BOOK_STORE_FETCHER .allScalarFields() .books( ❶ Fetchers.BOOK_FETCHER .allScalarFields() ) .avgPrice() ❷ ) ) .execute(); System.out.println(stores); val stores = sqlClient .createQuery(BookStore::class) { select( table.fetchBy { allScalarFields() books { ❶ allScalarFields() } avgPrice() ❷ } ) } .execute() println(stores)","s":"Usage","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#usage","p":190},{"i":206,"t":"Assume the current tenant name is a, the execution process is as follows: First step: Query aggregate root First query the aggregate root object by executing the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ Here the query in the code is implemented to get some BookStore objects. Such objects directly queried by the user are called aggregate root objects. Second step: Query BookStore.books in ❶ through association cache The above code will get a series of aggregate root objects. If using the official example data, it will get two aggregate root objects with ID of 1 and 2 for BOOK_STORE. Jimmer first looks up the data from Redis. The keys looked up are BookStore.books-1 and BookStore.books-2. Assume the data for these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.books-* (empty array) So the following SQL is executed to complete the associated property BookStore.books: SQL: select, tb_1_.STORE_ID, tb_1_.ID from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and tb_1_.TENANT = ? /* a */ order by tb_1_.NAME asc, tb_1_.EDITION desc info The filter condition tb_1_.TENANT = 'a' comes from the user filter TenantFilter. Jimmer will put the query result into Redis. So we can view the data from Redis: 127.0.0.1:6379> keys BookStore.books-* 1) \"BookStore.books-2\" 2) \"BookStore.books-1\" 127.0.0.1:6379> hgetall BookStore.books-1 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"[5,3,1,9,7]\" 127.0.0.1:6379> hgetall BookStore.books-2 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"[11]\" info Jimmer uses Redis Hash for multi-perspective cache. So hgetall instead of get is needed. Redis Hash is a nested KV structure: The outer Redis Key, e.g. BookStore.books-1 and BookStore.books-2, is no different from single-perspective cache. The inner Hash Key, also called SubKey in Jimmer, is provided by global filters. Here, {\"tenant\":\"a\"} is provided by TenantProvider, indicating the cached value is not the id set of all associated objects, but the id set of associated objects visible to tenant a. tip Undoubtedly, executing the above Java/Kotlin code again with the same tenant identity before data expiration in Redis, it will directly return associated data from Redis without generating related SQL. Third step: Convert id set to associated objects In the previous step we got the id set of associated objects corresponding to associated property BookStore.books, representing the associated objects visible to tenant a. Now we can use the object cache of Book to convert the Book id set into Book object set. This step is very simple without further discussion. Fourth step: Query BookStore.avgPrice in ❷ through computation cache The above code will get a series of aggregate root objects. If using the official example data, it will get two aggregate root objects with ID of 1 and 2 for BOOK_STORE. Jimmer first looks up the data from Redis. The keys looked up are BookStore.avgPrice-1 and BookStore.avgPrice-2. Assume the data for these keys cannot be found in Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* (empty array) So the following SQL is executed to compute the calculation property: select tb_1_.ID, avg(tb_2_.PRICE) from BOOK_STORE tb_1_ left join BOOK tb_2_ on tb_1_.ID = tb_2_.STORE_ID where tb_1_.ID in ( ? /* 1 */, ? /* 2 */ ) and tb_1_.TENANT = ? /* a */ group by tb_1_.ID info The filter condition tb_1_.TENANT = 'a' comes from the user filter TenantFilter. Jimmer will put the query result into Redis. So we can view the data from Redis: 127.0.0.1:6379> keys BookStore.avgPrice-* 1) \"BookStore.avgPrice-2\" 2) \"BookStore.avgPrice-1\" 127.0.0.1:6379> hgetall BookStore.avgPrice-1 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"53.1\" 127.0.0.1:6379> hgetall BookStore.avgPrice-2 1) \"{\\\"tenant\\\":\\\"a\\\"}\" 2) \"81\" info Jimmer uses Redis Hash for multi-perspective cache. So hgetall instead of get is needed. Redis Hash is a nested KV structure: The outer Redis Key, e.g. BookStore.avgPrice-1 and BookStore.avgPrice-2, is no different from single-perspective cache. The inner Hash Key, also called SubKey in Jimmer, is provided by global filters. Here, {\"tenant\": \"a\"} is provided by TenantProvider, indicating the cached value is not the average price of all associated objects, but the average price of associated objects visible to tenant a. tip Undoubtedly, executing the above Java/Kotlin code again with the same tenant identity before data expiration in Redis, it will directly return associated data from Redis without generating related SQL. Finally, Jimmer concatenates the results of the 4 steps and returns them to the user. [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81 } ], \"avgPrice\":81 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":5, \"name\":\"Effective TypeScript\", \"edition\":2, \"price\":69 }, { \"id\":3, ...omitted... }, { \"id\":1, ...omitted... }, { \"id\":9, ...omitted... }, { \"id\":7, ...omitted... } ], \"avgPrice\":53.1 } ]","s":"Execute with one tenant identity","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#execute-with-one-tenant-identity","p":190},{"i":208,"t":"The query execution process with tenant a has been discussed. Similarly, we can execute multiple times using different tenant identities to leave cache data in Redis from the following perspectives: tenant = null tenant = \"a\" tenant = \"b\" info For the official example, TenantProvider is implemented based on HTTP request header and has swagger UI support. It's easy to execute three times with three different user identities. Among them, tenant = null corresponds to the unauthorized/logout state in swagger UI. Open redis-cli, we can verify the data in Redis: 127.0.0.1:6379> keys BookStore.books-* 1) \"BookStore.books-2\" 2) \"BookStore.books-1\" 127.0.0.1:6379> hgetall BookStore.books-1 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"[6,4,2,8]\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"[5,3,1,9,7]\" 5) \"{}\" 6) \"[6,5,4,3,2,1,9,8,7]\" 127.0.0.1:6379> hgetall BookStore.books-2 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"[12,10]\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"[11]\" 5) \"{}\" 6) \"[12,11,10]\" 127.0.0.1:6379> keys BookStore.avgPrice-* 1) \"BookStore.avgPrice-2\" 2) \"BookStore.avgPrice-1\" 127.0.0.1:6379> hgetall BookStore.avgPrice-1 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"65.25\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"53.1\" 5) \"{}\" 6) \"58.500000\" 127.0.0.1:6379> hgetall BookStore.avgPrice-2 1) \"{\\\"tenant\\\":\\\"b\\\"}\" 2) \"80\" 3) \"{\\\"tenant\\\":\\\"a\\\"}\" 4) \"81\" 5) \"{}\" 6) \"80.333333\" tip Readers can take a close look at these redis-cli commands and easily find that the data of sub key {\"tenant\":\"a\"} merged with the data of sub key {\"tenant\":\"b\"} is exactly the data of SubKey {}. The data returned to the user in the 3 calls is: tenant=null tenant=a tenant=b [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80, }, { \"id\":11, ...omitted... }, { \"id\":10, ...omitted... } ], \"avgPrice\":80.333333 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, \"price\":88 }, { \"id\":5, ...omitted... }, { \"id\":4, ...omitted... }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51 }, { \"id\":2, ...omitted... }, { \"id\":1, ...omitted... }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48 }, { \"id\":8, ...omitted... }, { \"id\":7, ...omitted... } ], \"avgPrice\":58.5 } ] [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81 } ], \"avgPrice\":81 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":5, \"name\":\"Effective TypeScript\", \"edition\":2, \"price\":69 }, { \"id\":3, ...omitted... }, { \"id\":1, ...omitted... }, { \"id\":9, ...omitted... }, { \"id\":7, ...omitted... } ], \"avgPrice\":53.1 } ] [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80 }, { \"id\":10, ...omitted... } ], \"avgPrice\":80 }, { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, \"price\":88 }, { \"id\":4, ...omitted... }, { \"id\":2, ...omitted... }, { \"id\":8, ...omitted... } ], \"avgPrice\":65.25 } ]","s":"Execute repeatedly with multiple tenant identities","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#execute-repeatedly-with-multiple-tenant-identities","p":190},{"i":210,"t":"Now let's modify the property Book.tenant of the Book object with id 6 from \"b\" to \"a\". Since Book-6 belongs to BookStore-1, it is foreseeable that the multi-view caches corresponding to the properties BookStore.books-1 and BookStore.avgPrice-1 will definitely be invalidated. If BinLog trigger is enabled, modifying the database in any way can lead to Jimmer's cache consistency involvement. For example, directly executing the following SQL in SQL IDE: update BOOK set TENANT = 'a' where ID = 6; If only Transaction trigger is enabled, the database must be modified using Jimmer's API: Java Kotlin sqlClient.save( Immutables.createBook(draft -> { draft.setId(6L); draft.setTenant(\"a\"); }) ); sqlClient.save( Book { id = 6L tenant = \"a\" } ) No matter which way above is used to modify the data, you will see the following log output: Delete data from redis: [Book-6] ❶ Delete data from redis: [Author.books-3] ❷ Delete data from redis: [BookStore.books-1] ❸ Delete data from redis: [BookStore.avgPrice-1] ❹ ❶ Update object cache of modified entity ❷ Any association property targeting Book must be affected, of course including Author.books According to existing database data, the affected Author object id is 3 ❸ Any association property targeting Book must be affected, of course including BookStore.books According to existing database data, the affected BookStore object id is 1 ❹ The calculated cache BookStore.avgPrice of BookStore object with id 1 is also affected. This is the most amazing characteristic. Although the framework is unaware of the calculation rule used by users in calculated properties, in the Calculated Cache documentation, we discussed the following code in the BookStoreAvgPriceResolver class: Java Kotlin @EventListener public void onAssociationChange(AssociationEvent e) { if (sqlClient.getCaches().isAffectedBy(e) && e.isChanged(BookStoreProps.BOOKS) ) { ...code omitted... } } @EventListener fun onAssociationChange(e: AssociationEvent) { if (sqlClient.caches.isAffectedBy(e) && e.isChanged(BookStore::books) ) { ...code omitted... } } If you have forgotten the specific logic of this code, you can review the Calculated Cache documentation. Just focus on the highlighted line. Here, this calculated property cares about changes to the association property BookStore.books. tip Modifying the association field between tables is not the only way to trigger association change events. Modifying the filtered field in associated objects that affects global filters, like TENANT here, can also trigger association change events. This is a very important characteristic of Jimmer's trigger mechanism! It is obvious that ❸ has already sensed the change of association property BookStore.books, so it will further lead to the invalidation of the calculated cache here.","s":"Cache Invalidation","u":"/jimmer-doc/docs/cache/multiview-cache/user-filter","h":"#cache-invalidation","p":190},{"i":212,"t":"This configuration is explained in Mutation Section/Trigger/Set Trigger Type. Therefore, this article will not repeat the explanation, it just serves as a link reference.","s":"Trigger Type","u":"/jimmer-doc/docs/configuration/trigger-type","h":"","p":211},{"i":215,"t":"In previous documents, we have introduced how to map enums, and how to use @Serialized to map JSON. However, sometimes neither of these methods can meet our requirements. In this case, we can use ScalarProvider. tip ScalarProvider is the most low-level SPI of Jimmer for custom data types. The Enum Mapping and JSON Mapping we discussed before are actually Jimmer's built-in implementations of ScalarProvider. Multiple ScalarProvider can be registered for SqlClient. Each ScalarProvider tells Jimmer how to handle a custom data type. There are two types of ScalarProvider: Global Define the mapping rules between Java/Kotlin types and database types globally and uniformly. Any entity definition that contains properties of this type will be uniformly handled by the global ScalarProvider. note Global ScalarProvider can only handle non-collection types, such as: classes, interfaces, enums, etc. It cannot handle collection types like: Array, Collection, Map, etc. Property level For a specific entity property, define the mapping rules between Java/Kotlin types and database types. note Property-level ScalarProvider can handle any non-built-in types of Jimmer, including collection types such as: Array, Collection, Map. If the mapped property type is a collection type, the property needs to be annotated with @org.babyfish.jimmer.Scalar. tip The @Serialized annotation discussed in JSON Mapping can annotate both the return type of properties and entity properties. This is because the more low-level ScalarProvider has two types. ScalarProvider is an SPI interface provided by Jimmer, which is defined as follows: ScalarProvider package org.babyfish.jimmer.sql.runtime; import java.util.function.Consumer; public abstract class ScalarProvider { protected ScalarProvider(Class scalarType, Class sqlType) { ❸ ...Omitted code... } protected ScalarProvider() { ❹ ...Omitted code... } public abstract T toScalar(S sqlValue); ❺ public abstract S toSql(T scalarValue); ❻ public Collection getHandledProps() { ❼ return null; } } ❶ Generic parameter T: Data type in Java/Kotlin; ❷ Generic parameter S: Data type in the database; ❸ Constructor that explicitly specifies the types represented by T and S; This constructor is usually used to define ScalarProvider with higher generality and reusability. ❹ Constructor that does not need to explicitly specify the types represented by T and S; It requires derived classes to explicitly specify generic parameters T and S so that Jimmer can automatically analyze the types represented by T and S. Otherwise, an exception will occur. This constructor is usually used to define ScalarProvider corresponding to specific types without requiring generality and reusability. ❺ Method toScalar: Convert non-null data read from the database to Java data; ❻ Method toSql: Convert non-null Java data to data acceptable to the database; ❼ If you want to define a property-level ScalarProvider, one option (there are other options) is to override the getHandledProps method in the derived class;","s":"Basic Concepts","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#basic-concepts","p":213},{"i":217,"t":"For example, the current database does not support the UUID type, which can be handled as follows:","s":"Global ScalarProvider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#global-scalarprovider","p":213},{"i":219,"t":"Java Kotlin UUIDScalarProvider.java public class UUIDScalarProvider extends AbstractScalarProvider { @Override public UUID toScalar(String sqlValue) { return UUID.fromString(sqlValue); } @Override public String toSql(UUID scalarValue) { return scalarValue.toString(); } } UUIDScalarProvider.kt class UUIDScalarProvider : ScalarProvider { override fun toScalar(sqlValue: String): UUID = UUID.fromString(sqlValue) override fun toSql(scalarValue: UUID): String = scalarValue.toString() }","s":"Define ScalarProvider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#define-scalarprovider","p":213},{"i":221,"t":"There are two ways for Jimmer to register ScalarProvider: Use Spring Boot Starter Just let the derived classes of ScalarProvider be managed by Spring. There are two options: Modify the above UUIDScalarProvider class and annotate it with spring's @Component Java Kotlin UUIDScalarProvider.java @Component public class UUIDScalarProvider extends AbstractScalarProvider { ...Omitted code... } UUIDScalarProvider.kt @Component class UUIDScalarProvider : ScalarProvider { ...Omitted code... } Use Spring's @Bean method to register the UUIDScalaProvider object to Spring Java Kotlin @Bean public UUIDScalarProvider uuidScalarProvider() { return new UUIDScalarProvider(); } @Bean fun uuidScalarProvider(): UUIDScalarProvider = UnitTestIdGenerator() Use underlying API Java Kotlin @Bean public JSqlClient sqlClient() { return JSqlClient .newBuilder() .addScalarProvider(new UUIDScalarProvider()) ...Omit other configurations... .build(); } @Bean fun sqlClient() : KSqlClient = newKSqlClient { addScalarProvider(UUIDScalarProvider()) ...Omit other configurations... }","s":"Register Scalar Provider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#register-scalar-provider","p":213},{"i":223,"t":"The only difference between property-level ScalarProvider and global ScalarProvider is that it only applies to specific properties, not all properties. So the most important data conversion methods toScalar and toSql in property-level ScalarProvider have exactly the same user code implementation, only the registration method is different. Therefore, here we assume there is a user-defined type Location and its corresponding ScalarProvider implementation class is LocationScalarProvider. Specific implementation is omitted.","s":"Property level ScalarProvider","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#property-level-scalarprovider","p":213},{"i":225,"t":"Java Kotlin @Bean public JSqlClient sqlClient() { return JSqlClient .newBuilder() .setScalarProvider( FlightProps.SOURCE_LOCATION new LocationScalarProvider() ) .setScalarProvider( FlightProps.TARGET_LOCATION new LocationScalarProvider() ) ...Omit other configurations... .build(); } @Bean fun sqlClient() : KSqlClient = newKSqlClient { setScalarProvider( Flight::sourceLocation LocationScalarProvider() ) setScalarProvider( Flight::targetLocation LocationScalarProvider() ) ...Omit other configurations... } That is, except for the Flight.sourceLocation and Flight.targetLocation properties, LocationScalarProvider does not affect any other properties of type Location.","s":"Non-Spring registration","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#non-spring-registration","p":213},{"i":227,"t":"The above method is intuitive, but it is manually registered. Can Spring's automatic registration method be used to register property-level ScalarProvider? Of course. Just override the getHandledProps method of ScalarProvider, and you can use the method of registering global ScalarProvider to register property-level ScalarProvider. For example: Java Kotlin LocationScalarProvider.java @Component public class LocationScalarProvider extends AbstractScalarProvider { @Override public Collection getHandledProps() { return Arrays.asList( FlightProps.SOURCE_LOCATION, FlightProps.TARGET_LOCATION ); } ...Omit other code... } LocationScalarProvider.kt @Component class LocationScalarProvider : ScalarProvider { override fun getHandledProps(): Collection = listOf( Flight::sourceLocation.toImmutableProp(), Flight::targetLocation.toImmutableProp() ) ...Omit other code... }","s":"Spring registration","u":"/jimmer-doc/docs/configuration/scala-provider","h":"#spring-registration","p":213},{"i":229,"t":"This section introduces how to quickly create GraphQL services with Jimmer.","s":"GraphQL","u":"/jimmer-doc/docs/graphql/","h":"","p":228},{"i":232,"t":"In the Spring section, we discussed how to implement REST services with Jimmer and automatically generate client code like TypeScript. In addition, Jimmer also supports another development mode to build GraphQL services, which is what this article series will discuss. caution So far, the GraphQL protocol does not support recursive queries for self-associated properties. Therefore, it is not possible to expose functionality like recursive queries in object fetchers through GraphQL. This is a functionality sacrifice that must currently be accepted when using GraphQL. Jimmer's support for GraphQL is based on Spring GraphQL. So the project needs to import both the Jimmer and Spring GraphQL Spring Boot starters, for example: Maven Gradle pom.xml ...other code omitted... org.babyfish.jimmer jimmer-spring-boot-starter ${jimmer.version} org.springframework.boot spring-boot-starter-graphql ${spring.boot.version} ...other dependencies omitted... ...other code omitted... build.gradle dependencies { implementation \"org.babyfish.jimmer:jimmer-spring-boot-starter:${jimmerVersion}\" implementation 'org.springframework.boot:spring-boot-starter-graphql' ...other dependencies omitted... } info If the Jimmer entity types are also defined in the GraphQL project rather than in a separate project, the preprocessor (Annotation Processor for Java, KSP for Kotlin) should also be configured in the build script. This has already been discussed in detail in the Generate Code article and will not be repeated here. Spring GraphQL is a Schema-First rather than Code-First approach. Therefore, developers need to create the file src/main/resources/graphql/schema.graphqls in the project and define the GraphQL schema in it. This file is a requirement of Spring GraphQL. The GraphQL schema content is a standard language that is unrelated to Jimmer, so this article will not explain it. Please refer to the GraphQL Schema in the example.","s":"Concepts","u":"/jimmer-doc/docs/graphql/concept","h":"#concepts","p":230},{"i":234,"t":"caution In the current version, there is a limitation that when providing GraphQL services, simple calculated properties based on SQL should NOT be used.","s":"Notes","u":"/jimmer-doc/docs/graphql/concept","h":"#notes","p":230},{"i":236,"t":"In this section, we introduce how to map a relational database to entity model. For readers with ORM experience (especially JPA), you can skim through quickly. Major differences from JPA: Basic Mapping: Nullability Advanced Mapping: View Properties Calculated Properties Remote Associations Key Key is very important for Save Command OnDissociate For readers without ORM experience, you'll have to read slowly. This process is tedious but required for any ORM. All powerful and cool ORM capabilities are built on top of these mappings. To avoid extended tedium for ORM beginners, a suggestion - initially only read the basic mappings, enough to understand most of the docs. Come back for advanced mappings when needed.","s":"Mapping","u":"/jimmer-doc/docs/mapping/","h":"","p":235},{"i":239,"t":"In GraphQL, GraphQLObjects returned by queries are dynamic objects of arbitrary shapes. However, if mutation operations accept object parameters, they must be GraphQLInputs, which are static objects of fixed shapes. See GraphQLInput to learn more. Take the GraphQL declaration file in the example schema.graphqls as an example: type Book implements CommonEntity { ❶ id: Long! name: String! edition: Int! price: BigDecimal! store: BookStore authors: [Author!]! createdTime: LocalDateTime! modifiedTime: LocalDateTime! tenant: String! } input BookInput { ❷ id: Long name: String! edition: Int price: BigDecimal! storeId: Long authorIds: [Long!]! } ...other code omitted... ❶ Types declared with the type keyword are dynamic types used to express arbitrary data structures, used as GraphQL output types ❷ Types declared with the input keyword are static types used to express fixed data structures, used as GraphQL input types","s":"Introduction to GraphQL Input","u":"/jimmer-doc/docs/graphql/mutation","h":"#introduction-to-graphql-input","p":237},{"i":241,"t":"Jimmer Input DTOs are introduced in great detail in Save Command/Input DTO, which will not be repeated here. Jimmer provides two ways to define Input DTOs: Automatically generate Input DTOs using the DTO language Manually define Input DTOs based on MapStruct Using the DTO language can achieve our goal very efficiently, so this article adopts this approach. In the project where the entity is defined, create the directory src/main/dto Under src/main/dto, create subdirectories com/yourcompany/yourproject/model according to the package path where the entities are located Under the directory created in the previous step, create the file Book.dto. The file must have the same name as the entity class and the extension must be dto Edit this file and use the DTO language to define various DTO shapes for the Book entity Book.dto input BookInput { #allScalars(Book) id(store) id(authors) as authorIds } ...other DTO definitions omitted... After compilation, the following Input DTO will be generated automatically: Java Kotlin BookInput.java @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookInput implements Input { ❶ @Nullable private Long id; private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; private List authorIds; @Override public Book toEntity() { ❷ ...omitted... } ...other members omitted... } BookInput.kt @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookInput( val id: Long? = null, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val storeId: Long? = null, val authorIds: List = emptyList() ): Input { ❶ override fun toEntity(): Book = ❷ ...omitted... ...other members omitted... } ❶ The BookInput class implements the interface org.babyfish.jimmer.Input, which supports the toEntity method to convert the current Input DTO object to a Jimmer dynamic entity object. ❷ Implements the Input.toEntity method","s":"Define Jimmer Input DTO","u":"/jimmer-doc/docs/graphql/mutation","h":"#define-jimmer-input-dto","p":237},{"i":243,"t":"Java Kotlin BookStoreService.java package com.example.business; import org.springframework.graphql.data.method.annotation.Argument; import org.springframework.graphql.data.method.annotation.MutationMapping; import org.springframework.stereotype.Controller; ...other imports omitted... @Controller public class BookStoreService { private final BookStoreRepository bookStoreRepository; public BookStoreService(BookStoreRepository bookStoreRepository) { this.bookStoreRepository = bookStoreRepository; } @MutationMapping ❶ @Transactional public Book saveBook( @Argument BookInput input ❷ ) { // `save(input)` is shorthand for `save(input.toEntity())` return bookRepository.save(input); ❸ } } BookStoreService.kt package com.example.business import org.springframework.graphql.data.method.annotation.Argument import org.springframework.graphql.data.method.annotation.MutationMapping import org.springframework.stereotype.Controller ...other imports omitted... @Controller class BookStoreService( private val bookStoreRepository: BookStoreRepository ) { @MutationMapping ❶ @Transactional fun saveBook( @Argument input: BookInput ❷ ): Book = // `save(input)` is shorthand for `save(input.toEntity())` bookRepository.save(input) ❸ } ❶ Use annotation @org.springframework.graphql.data.method.annotation.MutationMapping ❷ Use the static Input DTO type BookInput to allow users to pass only data structures of specified shapes to conform to GraphQLInput ❸ Save command to save arbitrary data structures in one line Here bookRepository.save(input) is actually shorthand for bookRepository.save(input.toEntity()). tip No matter how simple or relatively complex the data structure defined by the BookInput type, it can be saved in one line. This is the core value of the save command feature.","s":"Implement GraphQL mutation","u":"/jimmer-doc/docs/graphql/mutation","h":"#implement-graphql-mutation","p":237},{"i":245,"t":"In this series of articles, we will introduce advanced mappings.","s":"Advanced mapping","u":"/jimmer-doc/docs/mapping/advanced/","h":"","p":244},{"i":247,"t":"For ORM, it is important to print generated SQL in logs.","s":"SQL Log","u":"/jimmer-doc/docs/configuration/sql-log","h":"","p":246},{"i":249,"t":"There are two ways to enable SQL logs: When using Spring Boot Starter, there are two ways to configure: Modify application.yml (or application.properties) jimmer: show-sql: true Configure global Bean Java Kotlin @Bean public Executor executor() { return Executor.log(); } @Bean fun executor(): Executor = Executor.log() info If both methods above are used (not recommended), the second method takes precedence. Use underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) ...Omit other configurations... } The actual printed logs are as follows: jimmer> sql: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? order by tb_1_.NAME asc, tb_1_.EDITION desc limit ?, ?, variables: [%graphql%, 0, 10], purpose: QUERY caution If only the SQL log is turned on, the above log will not wrap. The log has three parts: sql: The SQL statement being executed variables: The JDBC parameters associated with sql, which is an array whose length is the same as the number of \"?\" characters in sql. purpose: The reason why the SQL is executed, which is an enum with the following values: QUERY: Query directly executed by developers UPDATE: Operations performed by developers via update statements DELETE: Operations performed by developers via delete statements LOAD: Query executed automatically by Jimmer to get the value of associated properties or calculated properties in object fetcher. EXPORT: The user initiates a query to other microservices, and its object fetcher contains remote associations pointing to the current service. Jimmer automatically exposes the data of this service. MUTATE: Operations specified by developers via save commands EVICT: In some cases, the cache that should be cleared cannot be determined solely based on the event information of Jimmer triggers. Jimmer will automatically execute some queries to accurately determine which caches should be cleared.","s":"Enable SQL Log","u":"/jimmer-doc/docs/configuration/sql-log","h":"#enable-sql-log","p":246},{"i":251,"t":"In the previous example, the SQL log is printed in one line, which is poorly readable. Therefore, the SQL needs to be formatted. There are two implementation methods: When using Spring Boot Starter Modify application.yml (or application.properties) jimmer: show-sql: true pretty-sql: true When using underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) .setSqlFormatter(SqlFormatter.PRETTY) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) setSqlFormatter(SqlFormatter.PRETTY) ...Omit other configurations... } The log output is as follows: Execute SQL===> Purpose: QUERY SQL: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ ❶ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 0 */ ❷, ? /* 10 */ ❸ JDBC response status: success Time cost: 8ms <===Execute SQL In this mode: The SQL statement will be automatically formatted, automatically wrapped, and automatically indented. ❶ ❷ ❸ Unlike the previous example, all JDBC parameters are not printed together, but injected into the original SQL as comments. Other information will be printed, such as whether SQL execution is successful, total execution time of SQL. For insert, update, delete operations, the number of affected rows will also be printed.","s":"Pretty SQL","u":"/jimmer-doc/docs/configuration/sql-log","h":"#pretty-sql","p":246},{"i":253,"t":"In the previous examples, the JDBC parameters in the SQL logs were inserted after the JDBC parameter placeholders ? as comment, e.g. ? /* %graphql% */. Perhaps you want the parameters to be inlined into the SQL statement directly, making it look as if no JDBC parameters were used. This way, the SQL statement in the logs can be copied directly into a SQL IDE to execute. There are two ways to achieve this Using Spring Boot Starter: Modify application.yml (or application.properties): jimmer: show-sql: true pretty-sql: true inline-sql-variables: true Using low-level API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) .setSqlFormatter(SqlFormatter.INLINE_PRETTY) ...other configs omitted... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) setSqlFormatter(SqlFormatter.INLINE_PRETTY) ...other configs omitted... } The log output is as follows: Execute SQL===> Purpose: QUERY SQL: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like '%graphql%' ❶ order by tb_1_.NAME asc, tb_1_.EDITION desc limit 0 ❷, 10 ❸ JDBC response status: success Time cost: 8ms <===Execute SQL In this mode, we can see the parameters at ❶ ❷ ❸ are directly inlined. info This only affects the logs. The actual SQL executed still uses JDBC parameters.","s":"Inline SQL Parameters","u":"/jimmer-doc/docs/configuration/sql-log","h":"#inline-sql-parameters","p":246},{"i":255,"t":"In addition to coding, developers often need to troubleshoot issues. Whether it is a functional error or a performance issue, the developer needs to investigate it. If the SQL log only prints JDBC information centered on SQL, the user cannot associate the SQL log with the application code, which is not conducive to users troubleshooting. Jimmer provides a configuration option that if specified, before executing SQL, it will check the stack trace information of the current thread. However, these stack traces contain too much information, including infrastructure call frames represented by jdk, jdbc driver, jimmer and spring, while the business-related information that developers care about will be overwhelmed in the ocean of information. This configuration type is java.util.Collection allowing developers to specify multiple packages or class prefixes. Jimmer will use them to filter the stack trace information. If a call frame can pass the filter, Jimmer will consider it related to user business and include it in the callback parameter before execution. For SQL log printing, call frames that can pass the filter will appear in the print output to help users troubleshoot issues. There are two implementation methods: When using Spring Boot Starter Modify application.yml (or application.properties) jimmer: show-sql: true pretty-sql: true executor-context-prefixes: - com.example.business When using underlying API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setExecutor(Executor.log()) .setSqlFormatter(SqlFormatter.PRETTY) .setExecutorContextPrefixes( Collections.singleton( \"com.example.business\" ) ) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setExecutor(Executor.log()) setSqlFormatter(SqlFormatter.PRETTY) setExecutorContextPrefixes( listOf( \"com.example.business\" ) ) ...Omit other configurations... } The log output is as follows: Execute SQL===> --- Business related stack trace information --- ❶ com.example.business.BookService.findBooks(BookService.java:55) ❷ Purpose: QUERY SQL: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 0 */, ? /* 10 */ JDBC response status: success Time cost: 9ms <===Execute SQL At ❶ and ❷, the stack trace information of the thread executing the SQL operation is printed. tip However, a large amount of stack trace information is not blindly printed, only what users care about is printed.","s":"Embed Stack Trace","u":"/jimmer-doc/docs/configuration/sql-log","h":"#embed-stack-trace","p":246},{"i":257,"t":"In this article, you will learn about Jimmer's calculated properties and annotations: org.babyfish.jimmer.sql.Formula Simple calculated properties, can be Java/Kotlin expressions or SQL expressions org.babyfish.jimmer.sql.Transient Complex calculated properties, with the following features: Not only can simple values be calculated, but associated calculated values can also be calculated. That is, calculated properties can be associated properties Any complex calculation rules can be used, for example, using OLAP systems unrelated to the current relational database for calculation caution Calculated properties should only be defined when a calculated metric belongs to an entity. If a calculated metric does not belong to any entity, it should be designed as a global Service API.","s":"Calculated Properties","u":"/jimmer-doc/docs/mapping/advanced/calculated/","h":"","p":256},{"i":260,"t":"Without Jimmer's support, implementing GraphQL queries requires two types of work: Query aggregate roots This is work that needs to be done when developing any data service, whether it's a GraphQL service, REST service, or even a service using other custom protocols. Developers only need to query and return standalone aggregate root objects without considering their association properties. So this is a relatively simple development task. For Spring GraphQL, just add the @QueryMapping annotation to the query methods in controller classes. Query association properties and calculated properties This is the bulk of the work required to implement GraphQL queries, requiring consideration of all current object associations and batch loading. There is some workload involved. In other words, it is precisely because the server undertakes these responsibilities that using GraphQL feels free, convenient and powerful on the client side. For Spring GraphQL, some schemes are provided for querying association properties, such as @SchemaMapping Batch Loading @BatchMapping When using Jimmer to implement GraphQL queries, developers only need to focus on querying aggregate roots, just ensuring that these aggregate roots have simple scalar fields. This is because tip All association properties and calculated properties of entity objects are automatically mapped to GraphQL fields by Jimmer without any development. caution So far, the GraphQL protocol does not support recursive queries for self-associated properties. Therefore, it is not possible to expose functionality like recursive queries in object fetchers through GraphQL. This is a functionality sacrifice that must currently be accepted when using GraphQL.","s":"Feature Description","u":"/jimmer-doc/docs/graphql/query","h":"#feature-description","p":258},{"i":263,"t":"Java Kotlin BookStoreService.java package com.example.business; import org.springframework.graphql.data.method.annotation.Argument; import org.springframework.graphql.data.method.annotation.QueryMapping; import org.springframework.stereotype.Controller; ...Omit other imports... @Controller public class BookStoreService { private final JSqlClient sqlClient; public BookStoreService(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @QueryMapping public List bookStores( @Argument @Nullable String name ) { BookStoreTable table = Tables.BOOK_STORE_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .select(table) .execute(); } } BookStoreService.kt package com.example.business import org.springframework.graphql.data.method.annotation.Argument import org.springframework.graphql.data.method.annotation.QueryMapping import org.springframework.stereotype.Controller ...Omit other imports... @Controller class BookStoreService( private val sqlClient: KSqlClient ) { @QueryMapping fun bookStores( @Argument name: String? ): List = sqlClient .createQuery(BookStore::class) { where(table.name `ilike?` name) select(table) } .execute() } Unlike previous REST services, this example does not use object fetchers, returning the simplest orphan objects (orphan objects contain neither associated properties nor calculated properties). Although we return orphan objects here, if the client's GraphQL request contains associated objects, Jimmer will still automatically load the required associated properties. However, there is a problem with this approach: in non-cache mode, unnecessary properties will also be queried, which has performance issues. We will introduce another approach with optimization capability later.","s":"1. Simplest Implementation","u":"/jimmer-doc/docs/graphql/query","h":"#1-simplest-implementation","p":258},{"i":265,"t":"To avoid querying unnecessary non-associated properties in non-cache mode, Jimmer can create a Fetcher object based on graphql.schema.DataFetchingEnvironment and use this Fetcher to query the database with the object as a parameter. tip In non-cache mode, not querying unnecessary non-associated properties is the essential difference between Jimmer GraphQL and other GraphQL implementations in the Java ecosystem. Java Kotlin BookStoreService.java package com.example.business; import org.springframework.graphql.data.method.annotation.Argument; import graphql.schema.DataFetchingEnvironment; import org.babyfish.jimmer.spring.graphql.DataFetchingEnvironments; import org.springframework.graphql.data.method.annotation.QueryMapping; import org.springframework.stereotype.Controller; ...Omit other imports... @Controller public class BookStoreService { private final JSqlClient sqlClient; public BookStoreService(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @QueryMapping public List bookStores( @Argument @Nullable String name, DataFetchingEnvironment env ) { BookStoreTable table = Tables.BOOK_STORE_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .select( table.fetch( DataFetchingEnvironments.createQuery( BookStore.class, env ) ) ) .execute(); } } BookStoreService.kt package com.example.business import org.springframework.graphql.data.method.annotation.Argument import graphql.schema.DataFetchingEnvironment import org.babyfish.jimmer.spring.graphql.toFetcher import org.springframework.graphql.data.method.annotation.QueryMapping import org.springframework.stereotype.Controller ...Omit other imports... @Controller class BookStoreService( private val sqlClient: KSqlClient ) { @QueryMapping fun bookStores( @Argument name: String?, env: DataFetchingEnvironment ): List = sqlClient .createQuery(BookStore::class) { where(table.name `ilike?` name) select( table.fetch( env.toFetcher() ) ) } .execute() }","s":"2. Optimize Performance","u":"/jimmer-doc/docs/graphql/query","h":"#2-optimize-performance","p":258},{"i":267,"t":"In the accompanying example, the GraphQL related projects are: Language Example Java jimmer-examples/java/jimmer-sql-graphql Kotlin jimmer-examples/kotlin/jimmer-sql-graphql-kt Select any project, open and start it. Finally, use the browser to visit http://localhost:8080/graphiql note Be careful, it's /graphiql, not /graphql Execute the request: query { bookStores { id name avgPrice ❶ books { ❷ id name edition price authors { ❸ id firstName fullName gender } } } } ❶ Query calculated property BookStore.avgPrice ❷ Query association property BookStore.books ❸ Query association property Book.authors The return result is: { \"data\":{ \"bookStores\":[ { \"id\":2, \"name\":\"MANNING\", \"avgPrice\":80.333333, \"books\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"fullName\":\"Samer Buna\", \"gender\":\"MALE\" } ] }, { \"id\":11, ...omitted... }, { \"id\":12, ...omitted... } ] }, { \"id\":1, \"name\":\"O'REILLY\", \"avgPrice\":58.5, \"books\":[ { \"id\":4, \"name\":\"Effective TypeScript\", \"edition\":1, \"price\":73, \"authors\":[ { \"id\":3, \"firstName\":\"Dan\", \"fullName\":\"Dan Vanderkam\", \"gender\":\"MALE\" } ] }, { \"id\":5, ...omitted... }, { \"id\":6, ...omitted... }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"fullName\":\"Alex Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"fullName\":\"Eve Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"fullName\":\"Alex Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"fullName\":\"Eve Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"fullName\":\"Alex Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"fullName\":\"Eve Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":7, \"name\":\"Programming TypeScript\", \"edition\":1, \"price\":47.5, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"fullName\":\"Boris Cherny\", \"gender\":\"MALE\" } ] }, { \"id\":8, \"name\":\"Programming TypeScript\", \"edition\":2, \"price\":45, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"fullName\":\"Boris Cherny\", \"gender\":\"MALE\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"fullName\":\"Boris Cherny\", \"gender\":\"MALE\" } ] } ] } ] } }","s":"Running Effect","u":"/jimmer-doc/docs/graphql/query","h":"#running-effect","p":258},{"i":269,"t":"Simple formula properties are properties declared with @org.babyfish.jimmer.sql.Formula. There are two usages: Formula properties based on Java/Kotlin calculation Formula properties based on SQL calculation note Simple formula properties are designed for simple and fast calculations. For complex calculations, use Complex Formula Properties instead. In Define Entity, we defined two fields for Author: firstName and lastName. Next, let's add a new property fullName to Author: fullName = firstName + ' ' + lastName Then we use two different ways, Java/Kotlin-based calculation and SQL-based calculation, to implement Author.fullName.","s":"Formula","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"","p":268},{"i":272,"t":"Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { @Formula(dependencies = {\"firstName\", \"lastName\"}) default String fullName() { return firstName() + ' ' + lastName(); } ...Omit other properties... } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { @Formula(dependencies = [\"firstName\", \"lastName\"]) val fullName: String get() = \"$firstName $lastName\" ...Omit other properties... } It is easy to see that Java/Kotlin-based simple formula properties have the following characteristics: The property is not abstract (requires default keyword in Java) and directly provides calculation logic implementation. @Formula's dependencies is specified, indicating that this property depends on Author.firstName and Author.lastName. That is, the dynamic entity must ensure the presence of both firstName and lastName properties to calculate fullName. The usage is: Java Kotlin Author author = authorRepository.findNullable( 1L, Fetchers.AUTHOR_FETCHER // Query id (implicit + forced) and fullName .fullName() ); System.out.println(author); val author = authorRepository.findNullable( 1L, newFetcher(Author::class).by { // Query id (implicit + forced) and fullName fullName() } ); println(author) The executed SQL is: select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR as tb_1_ where tb_1_.ID = ? fullName is a formula property without corresponding field in the database, but depends on firstName and lastName. So this SQL queries FIRST_NAME and LAST_NAME to make its dependent properties present. Next, let's see what is printed: {\"id\":1,\"fullName\":\"Eve Procello\"} We can see that after Jackson serialization (the toString method of entity objects is a shortcut for serialization), there is only fullName but no firstName and lastName. This is because the object fetcher causes firstName and lastName to be indirectly fetched due to fetching fullName, but they are not directly fetched. In this case, although the dynamic object has firstName and lastName, they are marked as invisible to Jackson and will not appear in the Jackson serialization result. note If the object fetcher directly fetches firstName and lastName, they will definitely appear in the serialization result. Readers can try it themselves, no need to repeat here.","s":"Depending on simple properties","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#depending-on-simple-properties","p":268},{"i":274,"t":"Suppose there is an Embeddable type Java Kotlin NameInfo.java @Embeddable public interface NameInfo { String firstName(); String lastName(); } NameInfo.kt @Embeddable interface NameInfo { val firstName: String val lastName: String } If an entity uses this Embeddable type, then the entity properties can depend on its internal properties, for example Java Kotlin Author.java @Entity public interface Author { NameInfo nameInfo(); @Formula(dependencies = {\"nameInfo.firstName\", \"nameInfo.lastName\"}) // or it can be written as: @Formula(dependencies = \"nameInfo\") default String fullName() { return nameInfo().firstName() + ' ' + nameInfo().lastName(); } ...other properties omitted... } Author.kt @Entity interface Author { val nameInfo: NameInfo @Formula(dependencies = [\"nameInfo.firstName\", \"nameInfo.lastName\"]) // or it can be written as: @Formula(dependencies = [\"nameInfo\"]) ...other properties omitted... val fullName: String get() = \"${nameInfo.firstName} ${nameInfo.lastName}\" } info The usage and execution effect are completely the same as above, no need to repeat.","s":"Depending on embedded object","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#depending-on-embedded-object","p":268},{"i":276,"t":"Java Kotlin Book.java @Entity public interface Book { @ManyToMany List authors(); @Formula(dependencies = \"authors\") default int authorCount() { return authors().size(); } @Formula(dependencies = {\"authors.firstName\", \"authors.lastName\"}) default List authorNames() { return authors() .stream() .map(author -> author.firstName() + ' ' + author.lastName()) .collect(Collectors.toList()); } ...other properties omitted... } Book.kt @Entity public interface Book { @ManyToMany val authors: List @Formula(dependencies = \"authors\") val authorCount: Int get() = authors.size @Formula(dependencies = [\"authors.firstName\", \"authors.lastName\"]) val authorNames: List get() = authors.map { \"${it.firstName} ${it.lastName}\" } ...other properties omitted... } Execute the following code Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .name() .edition() .authorCount() .authorNames() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition().desc()) select( table.fetchBy { name() edition() authorCount() authorNames() } ) } .execute() Execute, generating two SQL statements select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, from BOOK tb_1_ where tb_1_.NAME = ? /* Learning GraphQL */ order by tb_1_.EDITION desc select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ? /* 3 */, ? /* 2 */, ? /* 1 */ ) order by tb_1_.FIRST_NAME asc, tb_1_.LAST_NAME asc The obtained data is as follows [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"authorCount\":2, \"authorNames\":[\"Alex Banks\",\"Eve Procello\"] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"authorCount\":2, \"authorNames\":[\"Alex Banks\",\"Eve Procello\"] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"authorCount\":2, \"authorNames\":[\"Alex Banks\",\"Eve Procello\"] } ]","s":"Depending on association properties","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#depending-on-association-properties","p":268},{"i":278,"t":"Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { @Formula(sql = \"concat(%alias.FIRST_NAME, ' ', %alias.LAST_NAME)\") String fullName(); ...Omit other properties... } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { @Formula(sql = \"concat(%alias.FIRST_NAME, ' ', %alias.LAST_NAME)\") val fullName: String ...Omit other properties... } It is easy to see that SQL-based simple formula properties have the following characteristics: The property is abstract. @Formula's sql is specified as an SQL expression with a special token %alias Users cannot know the alias of the current table in the final SQL in advance, so Jimmer stipulates here that %alias represents the actual table column name. The usage is: Java Kotlin Author author = authorRepository.findNullable( 1L, Fetchers.AUTHOR_FETCHER // Query id (implicit + forced) and fullName .fullName() ); System.out.println(author); val author = authorRepository.findNullable( 1L, newFetcher(Author::class).by { // Query id (implicit + forced) and fullName fullName() } ); println(author) The generated SQL is: select tb_1_.ID, /* Here, `%alias` in @Formula.sql is replaced with `tb_1_` */ concat(tb_1_.FIRST_NAME, ' ', tb_1_.LAST_NAME) from AUTHOR as tb_1_ where tb_1_.ID = ? The final printed result is: {\"id\":1,\"fullName\":\"Eve Procello\"}","s":"2. SQL-based Calculation","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#2-sql-based-calculation","p":268},{"i":280,"t":"Compared with Java/Kotlin-based simple formula, SQL-based simple formula has one disadvantage and one advantage: Disadvantage: If the object fetcher fetches firstName, lastName and fullName at the same time, it will cause the final SQL to query three columns: tb_1_.FIRST_NAME, tb_1_.LAST_NAME and concat(tb_1_.FIRST_NAME, ' ', tb_1_.LAST_NAME). Obviously, the returned data contains redundancy and is wasteful. Advantage: Java/Kotlin-based formula properties can only be used as fields to be fetched by object fetchers, and cannot be used by SQL DSL. SQL-based formula properties will be generated into the strongly typed SQL DSL API by the code generator, available for SQL DSL, such as: Java's where(table.fullName().eq(\"Eve Procello\")) or Kotlin's where(table.fullName eq \"Eve Procello\") tip Among all formula properties, only SQL-based simple formula properties can be used by SQL DSL. It is recommended to use databases that support function indexes and use them in combination with function indexes. Therefore, it is recommended to carefully consider whether @Formula formula properties should be based on Java/Kotlin calculation or SQL calculation.","s":"Comparison","u":"/jimmer-doc/docs/mapping/advanced/calculated/formula","h":"#comparison","p":268},{"i":282,"t":"Embedded properties (Composite properties) merge multiple columns in the database into an integral whole, map them to a non-entity custom type, and then use this custom type to declare a property for the entity.","s":"Embedded Properties","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"","p":281},{"i":285,"t":"First, define a composite type: Java Kotlin FullName.java @Embeddable public interface FullName { String firstName(); String lastName(); } FullName.kt @Embeddable interface FullName { val firstName: String val lastName: String } caution Types defined by @Embeddable are not entity types. They must not declare id properties or association properties, otherwise compilation errors will occur. Then we can use it in another entity: Java Kotlin Author.java @Entity public interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); FullName name(); } Author.kt @Entity interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: FullName } info Unlike JPA/Hibernate, when using composite types in entities, @Embedded is not required. In fact, Jimmer does not provide the @Embedded annotation at all. The table structure corresponding to Author is: create table author( id bigint unsigned not null auto_increment primary key, first_name varchar(20) not null, last_name varchar(20) not null ) engine=innodb;","s":"Basic Usage","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#basic-usage","p":281},{"i":287,"t":"org.babyfish.jimmer.sql.PropOverride can be used to override column names of composite type properties: Define composite type Point: Java Kotlin Point.java @Embeddable public interface Point { int x(); int y(); } Point.kt @Embeddable interface Point { val x: Int val y: Int } Define composite type Rect and override column names of Point type: Java Kotlin Rect.java @Embeddable public interface Rect { @PropOverride(prop = \"x\", columnName = \"`LEFT`\") @PropOverride(prop = \"y\", columnName = \"`TOP`\") Point leftTop(); @PropOverride(prop = \"x\", columnName = \"`RIGHT`\") @PropOverride(prop = \"y\", columnName = \"BOTTOM\") Point rightBottom(); } Rect.kt @Embeddable interface Rect { @PropOverride(prop = \"x\", columnName = \"`LEFT`\") @PropOverride(prop = \"y\", columnName = \"`TOP`\") val leftTop: Point @PropOverride(prop = \"x\", columnName = \"`RIGHT`\") @PropOverride(prop = \"y\", columnName = \"BOTTOM\") val rightBottom: Point } Define entity type Transition and override column names of Rect type: Java Kotlin Transition.java @Entity public interface Transition { @Id long id(); int millis(); Rect source(); @PropOverride(prop = \"leftTop.x\", columnName = \"TARGET_LEFT\") @PropOverride(prop = \"leftTop.y\", columnName = \"TARGET_TOP\") @PropOverride(prop = \"rightBottom.x\", columnName = \"TARGET_RIGHT\") @PropOverride(prop = \"rightBottom.y\", columnName = \"TARGET_BOTTOM\") Rect target(); } Transition.kt @Entity interface Transition { @Id val id: Long val millis: Int val source: Rect @PropOverride(prop = \"leftTop.x\", columnName = \"TARGET_LEFT\") @PropOverride(prop = \"leftTop.y\", columnName = \"TARGET_TOP\") @PropOverride(prop = \"rightBottom.x\", columnName = \"TARGET_RIGHT\") @PropOverride(prop = \"rightBottom.y\", columnName = \"TARGET_BOTTOM\") val target: Rect } The table structure corresponding to Transition is: create table transition( id bigint unsigned not null auto_increment primary key, millis int not null, `LEFT` int not null, `TOP` int not null, `RIGHT` int not null, bottom int not null, target_left int not null, target_top int not null, target_right int not null, target_bottom int not null ) engine=innodb;","s":"Override Column Names","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#override-column-names","p":281},{"i":289,"t":"warning Using composite types as primary/foreign keys, that is, primary keys and foreign keys are composed of multiple columns, makes the system more complex without much benefit. Therefore, unless compatibility with legacy database design is required, the system should avoid such usage to keep primary/foreign keys simple. Let's first define a composite type: Java Kotlin UniqueId.java @Embeddable public interface UniqueId { @columnName(\"UNIQUE_ID_DAY_NO\") int dayNo(); @columnName(\"UNIQUE_ID_SEQ_NO\") int sequenceNo(); } UniqueId.kt @Embeddable interface UniqueId { @columnName(\"UNIQUE_ID_DAY_NO\") val dayNo: Int @columnName(\"UNIQUE_ID_SEQ_NO\") val sequenceNo: Int }","s":"As Primary/Foreign Keys","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#as-primaryforeign-keys","p":281},{"i":291,"t":"Java Kotlin Book.java @Entity public interface Book { @Id UniqueId id(); ...Omit other code... } Book.kt @Entity interface Book { @Id val id: UniqueId ...Omit other code... } Since Book.id does not override column names of UniqueId type using @PropOverride, the column names configured in UniqueId are used. The corresponding DDL is: create table book( unique_id_day_no int not null, unique_id_seq_no int not null, ...Omit other columns... ) engine=innodb; alter table book add constraint pk_book primary key(unique_id_day_no, unique_id_seq_no);","s":"As Primary Key","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#as-primary-key","p":281},{"i":293,"t":"Java Kotlin Chapter.java @Entity public interface Chapter { @ManyToOne @JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ) @JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) Book book(); ...Omit other code... } Chapter.kt @Entity interface Chapter { @ManyToOne @JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ) @JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) val book: Book ...Omit other code... } caution Different from all the examples we have covered before, here the referencedColumnName of the @JoinColumn annotation is specified. When the foreign key consists of multiple columns, multiple @JoinColumn annotations must be used, where each @JoinColumn must specify referencedColumnName. If the foreign key is real, the corresponding constraint is: alter table chapter add constraint fk_chapter__book foreign key( book_id_day_no, book_id_seq_id ) references book( unique_id_day_no, unique_id_seq_no );","s":"Referenced by @JoinColumn","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#referenced-by-joincolumn","p":281},{"i":295,"t":"Java Kotlin Book.java @Entity public interface Book { @Id UniqueId id(); @ManyToMany @JoinTable( joinColumns = { @JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ), @JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) } ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @Id val id: UniqueId @ManyToMany @JoinTable( joinColumns = [ JoinColumn( name = \"BOOK_ID_DAY_NO\", referencedColumnName = \"UNIQUE_ID_DAY_NO\" ), JoinColumn( name = \"BOOK_ID_SEQ_NO\", referencedColumnName = \"UNIQUE_ID_SEQ_NO\" ) ] ) val authors: List ...Omit other code... } If the foreign key is real, the DDL of the join table is: create table book_author_mapping( book_id_day_no int not null, book_id_seq_id int not null, author_id bigint not null ) engine=innodb; alter table book_author_mapping add constraint pk_book_author_mapping primary key( book_id_day_no, book_id_seq_id, author_id ); alter table book_author_mapping add constraint fk_book_author_mapping__book foreign key( book_id_day_no, book_id_seq_id ) references book( unique_id_day_no, unique_id_seq_no ); alter table book_author_mapping add constraint fk_book_author_mapping__author foreign key(author_id) references author(id);","s":"Referenced by @JoinTable","u":"/jimmer-doc/docs/mapping/advanced/embedded","h":"#referenced-by-jointable","p":281},{"i":298,"t":"Through the content related to Association Mapping, it is not difficult to find that all associations are based on @JoinColumn and @JoinTable (may be omitted). Although Jimmer supports fake foreign keys (foreign keys in the developer's mind but without corresponding foreign key constraints in the database), all the association mappings we have discussed so far are based on 3NF design of relational databases. However, you may be handed over a legacy database containing non-normalized database designs, such as: create table book( id bigint unsigned not null auto_increment primary key, author_ids varchar(100), ...Omit other columns... ) engine=innodb; Here, author_ids is a string column whose data is the ids of all Author objects associated with the current Book concatenated together with commas, e.g. 1, 5, 100, 206. Obviously, this is a non-structural design that does not satisfy 3NF of relational databases. note For Postgres that supports array types, using arrays would be a better choice, but for better generality of this example, string concatenation is still used here without utilizing database-specific features.","s":"Non-Structural Design Example","u":"/jimmer-doc/docs/mapping/advanced/join-sql","h":"#non-structural-design-example","p":296},{"i":300,"t":"To support such non-structural designs, Jimmer provides the @org.babyfish.jimmer.sql.JoinSql annotation. info @JoinSql must and can only be used together with @ManyToMany. Next, create an SQL function (MySQL is used as example here): create function concatenation_string_contains( self varchar(100), id bigint ) returns boolean begin if self is null then return false; end if; return self regexp concat('(^|\\\\,)\\\\s*', id, '\\\\s*(\\\\,|$)'); end; This function assumes that the parameter self is in the format of multiple numbers concatenated by commas, and determines whether it contains the parameter id. For example: concatenation_string_contains('100, 200, 300', 200) returns true concatenation_string_contains('100, 200, 300', 201) returns false Now we can map the non-structural many-to-many association: Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinSql( \"concatenation_string_contains(\" + \" %alias.author_ids, \" + \" %target_alias.id\" + \")\" ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinSql( \"concatenation_string_contains(\" + \" %alias.author_ids, \" + \" %target_alias.id\" + \")\" ) val authors: List ...Omit other code... } The SQL expression used in @JsonSql represents the join condition, where: concatenation_string_contains: The SQL function we defined earlier %alias: A special token defined by Jimmer representing the alias of the current table (book table in this example) %target_alias: A special token defined by Jimmer representing the alias of the target table (author table in this example) caution ORM automatically generates SQL (which is very important for dynamic queries, especially for ORMs like Jimmer that first proposed the Dynamic Join concept), and users cannot interfere with the aliases of tables in the final SQL. So using %alias and %target_alias here is the only way. It is worth mentioning that if you want to define a bidirectional many-to-many association, since Book.authors has already used @JoinSql, the other end Author.books does not need to use @JoinSql again. As before, use mappedBy to indicate that it is the inverse property. Java Kotlin Author.java @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ...Omit other code... } Author.kt @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...Omit other code... }","s":"Non-Structural Association","u":"/jimmer-doc/docs/mapping/advanced/join-sql","h":"#non-structural-association","p":296},{"i":302,"t":"warning Unless legacy database compatibility is required, do not perform non-structural design and map it with @JoinSql, because non-structural many-to-many associations have many limitations: Cannot be used as Remote Association Cannot participate in Dynamic Join Optimization Cannot use Association Cache Cannot be saved as part of data structure by Save Command. In fact, if the data structure to be saved contains non-structural associations, it will cause exceptions.","s":"Precautions","u":"/jimmer-doc/docs/mapping/advanced/join-sql","h":"#precautions","p":296},{"i":304,"t":"Jimmer handles enums in two ways: Map to string: A choice with better understandability and traceability, also the default option. Map to integer: A choice with better performance-first. Jimmer provides two annotations for enums: org.babyfish.jimmer.sql.EnumType: Decorate enum types, optional Specify mapping method, map to string or ordinal position to integer org.babyfish.jimmer.sql.EnumItem: Decorate enum items, optional Override the mapped string value or integer value for some enum item","s":"Enum Mapping","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"","p":303},{"i":306,"t":"Java Kotlin Gender.java @EnumType(EnumType.Strategy.NAME) public enum Gender { MALE, FEMALE } Gender.kt @EnumType(EnumType.Strategy.NAME) enum class Gender { MALE, FEMALE } Here, the parameter of @EnumType is specified as \"NAME\", indicating mapping to string. By default, the mapped string values of the two enum items are the same as their names, i.e. \"MALE\" and \"FEMALE\". If you expect the mapped strings to be different from the enum item names, you can decorate the enum items with @EnumItem. Java Kotlin Gender.java @EnumType(EnumType.Strategy.NAME) public enum Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE } Gender.kt @EnumType(EnumType.Strategy.NAME) enum class Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE }","s":"Map to String","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#map-to-string","p":303},{"i":308,"t":"Java Kotlin Gender.java @EnumType(EnumType.Strategy.ORDINAL) public enum Gender { MALE, FEMALE } Gender.kt @EnumType(EnumType.Strategy.ORDINAL) enum class Gender { MALE, FEMALE } Here, the parameter of @EnumType is specified as \"ORDINAL\", indicating mapping to integer. By default, the mapped integer values of the two enum items are the same as their ordinal, i.e. 0 and 1. If you expect the mapped integers to be different from the enum items' ordinal, you can decorate the enum items with @EnumItem. Java Kotlin Gender.java @EnumType(EnumType.Strategy.ORDINAL) public enum Gender { @EnumItem(ordinal = 100) MALE, @EnumItem(ordinal = 200) FEMALE } Gender.kt @EnumType(EnumType.Strategy.ORDINAL) enum class Gender { @EnumItem(ordinal = 100) MALE, @EnumItem(ordinal = 200) FEMALE }","s":"Map to Integer","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#map-to-integer","p":303},{"i":310,"t":"You can also avoid specifying the @EnumType annotation for enum types, that is, not explicitly indicate whether an enum type should be mapped to string or integer. In this case, Jimmer will refer to the default global configuration. info The default value of this global configuration is \"NAME\". If you need \"ORDINAL\", please override the global configuration. Next, we show how to override the global configuration: When using SpringBoot Add configuration item jimmer.default-enum-strategy in application.yml or application.properties and set its value to \"ORDINAL\" When not using SpringBoot Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultEnumStrategy(EnumType.Strategy.ORDINAL) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDefaultEnumStrategy(EnumType.Strategy.ORDINAL) ...Omit other configurations... }","s":"Do Not Explicitly Use @EnumType","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#do-not-explicitly-use-enumtype","p":303},{"i":312,"t":"The serialization of a type to JSON and its storage in the database are two independent matters. The content described above focuses on how Jimmer handles enum mapping in the database, which is unrelated to JSON. By default, Jackson converts enums to its name, so when generating the TypeScript Client, Jimmer maps the enum according to its name. Java Kotlin enum Gender { MAN, WOMAN } enum class Gender { MAN, WOMAN } The generated TypeScript code is as follows: export const GenderEnum_CONSTANTS = [ 'MAN', 'WOMAN' ] as const; export type GenderEnum = typeof GenderEnum_CONSTANTS[number]; //usage export type PersonDto = { gender: GenderEnum; } If you want to customize the JSON serialization, you need to use the @JsonValue annotation from Jackson. Java Kotlin enum Gender { MAN, WOMAN; @JsonValue public String getValue() { return name().toLowerCase(); } } enum class Gender { MAN, WOMAN; @JsonValue fun getValue(): String { return name().toLowerCase(); } } When detects the presence of annotations like @JsonValue, Jimmer not knowing how the enum will be converted during JSON serialization, so jimmer will translates the enum type to a string. The generated TypeScript code in this case is as follows: export type PersonDto = { gender: string; }","s":"Work with TypeScript Client and Jackson","u":"/jimmer-doc/docs/mapping/advanced/enum","h":"#work-with-typescript-client-and-jackson","p":303},{"i":314,"t":"Jimmer supports JSON properties. In Java/Kotlin entity types, such properties can be declared as any type other than java.lang.Object and kotlin.Any. In the database, the information stored in the corresponding column is JSON. info JSON properties are simple properties, not association properties. According to the current implementation, the corresponding column type in Postgres should be jsonb, and the corresponding column type in other databases should be string. Jimmer provides org.babyfish.jimmer.sql.Serialized. There are two ways to use JSON mapping: Global JSON mapping If the property type is a custom class rather than an array, collection, or Map, decorate this class with @Serialized. This way, any properties of the this type in all entities will become JSON properties. Property-level JSON mapping The current property can be decorated with @Serialized. Properties of array, collection, or map types must use property-level mapping; however, global mapping is better for custom types.","s":"JSON Mapping","u":"/jimmer-doc/docs/mapping/advanced/json","h":"","p":313},{"i":316,"t":"First, define a custom class and decorate it with @Serialized: Java Kotlin UserType.java @Serialized public class UserType { ...Omit members, can contain any info... ...As long as Json serialization/deserialization is supported... } UserType.kt @Serialized data class UserType( ...Omit parameters, can contain any info... ...As long as Json serialization/deserialization is supported... ) Then UserType can be used to define properties for any entity: Java Kotlin Book.java @Entity public interface Book { UserType userData(); ...Omit other types... } Book.kt @Entity interface Book { val userData: UserType ...Omit other types... }","s":"Global JSON Mapping","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#global-json-mapping","p":313},{"i":318,"t":"Just decorate the property with @Serialized: Java Kotlin Book.java @Entity public interface Book { @Serialized List> userData1(); @Serialized Map> userData2(); ...Omit other types... } Book.kt @Entity interface Book { @Serialized val userData1: List> @Serialized val userData2: Map> ...Omit other types... }","s":"Property-level JSON Mapping","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#property-level-json-mapping","p":313},{"i":321,"t":"Developers can configure the ObjectMapper for JSON serialization/deserialization of properties decorated with @Serialized. Java Kotlin ObjectMapper mapper1 = ...omitted...; ObjectMapper mapper2 = ...omitted...; ObjectMapper mapper3 = ...omitted...; JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultSerializedTypeObjectMapper(mapper1) ❶ .setSerializedTypeObjectMapper(MetaConfig.class, mapper2) ❷ .setSerializedTypePropMapper(TopicProps.TAGS, mapper3) ❸ ...Omit other configurations... .build(); val mapper1: ObjectMapper = ...omitted... val mapper2: ObjectMapper = ...omitted... val mapper3: ObjectMapper = ...omitted... val sqlClient = newKSqlClient { setDefaultSerializedTypeObjectMapper(mapper1) ❶ setSerializedTypeObjectMapper(MetaConfig::class, mapper2) ❷ setSerializedTypePropMapper(Topic::tags, mapper3) ❸ ...Omit other configurations... } ❶ Set default ObjectMapper to mapper1 Equivalent to setSerializedTypeObjectMapper(Object.class, mapper1) ❷ For any property whose return type is MetaConfig or its subclass, use mapper2 ❸ Explicitly set ObjectMapper for Topic.tags to mapper3 If the set property is not decorated with @Serialized, an exception will be thrown Configuration precedence: ❸ > ❷ > ❶","s":"Use Low-level API","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#use-low-level-api","p":313},{"i":323,"t":"If using the Spring Boot Starter, the SqlClient is created automatically, but users can change the configuration before SqlClient is created via Customizer/KCustomizer: Java Kotlin @Component public class SerializationCustomizer implements Customizer { @Override public void customize(JSqlClient.Builder builder) { builder .setDefaultSerializedTypeObjectMapper(...omitted...) .setSerializedTypeObjectMapper(MetaConfig.class, ...omitted...) .setSerializedTypePropMapper(TopicProps.TAGS, ...omitted...); } } @Component class SerializationCustomizer : KCustomizer { override fun customize(dsl: KSqlClientDsl) { dsl .setDefaultSerializedTypeObjectMapper(...omitted...) .setSerializedTypeObjectMapper(MetaConfig::class, ...omitted...) .setSerializedTypePropMapper(Topic::tags, ...omitted...); } }","s":"Use Spring Boot Starter","u":"/jimmer-doc/docs/mapping/advanced/json","h":"#use-spring-boot-starter","p":313},{"i":326,"t":"Jimmer entities can use @org.babyfish.jimmer.sql.Transient to define a property unrelated to the database table structure. Java Kotlin BookStore.java package com.example.model; import org.babyfish.jimmer.sql.*; public interface BookStore { ...Omit other properties... @Transient Object customData(); } BookStore.kt package com.example.model import org.babyfish.jimmer.sql.* interface BookStore { ...Omit other properties... @Transient val customData: Any? } Here, no parameters are specified for the @Transient annotation, so the current data is just custom user data unrelated to any ORM behavior. caution Only when parameters are specified for the @Transient annotation will the current property be a complex calculation property. So what are the parameters of the @Transient annotation? Jimmer provides an interface for complex calculation properties: Java: org.babyfish.jimmer.sql.TransientResolver Kotlin: org.babyfish.jimmer.sql.kt.KTransientResolver This interface allows users to customize the data calculation process. Users develop a class that implements this interface and have it managed by Spring. How to implement this class will be explained in detail later, but for the purpose of expression here, let's assume the user class that implements this interface is CustomerDataResolver. The @Transient annotation parameters should be written as: If the project is a single project where entity classes can reference this class, then @Transient(CustomerDataResolver.class) or @Transient(CustomerDataResolver::class). If the project has multiple subprojects where entity classes cannot reference this class, then @Transient(ref = \"customerDataResolver\"). Where the string \"customerDataResolver\" represents the name of this object in the Spring context.","s":"@Transient Annotation","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#transient-annotation","p":324},{"i":328,"t":"In this section, we will add a calculation property BookStore.avgPrice to BookStore with the type java.math.BigDecimal.","s":"Scalar Calculation: BookStore.avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#scalar-calculation-bookstoreavgprice","p":324},{"i":330,"t":"Each complex calculation property corresponds to a TransientResolver implementation class. Before defining the calculation property BookStore.avgPrice, let's first define BookStoreAvgPriceResolver: Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.TransientResolver; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { @Override public Map resolve(Collection ids) { To be implemented later } @Override public BigDecimal getDefaultValue() { return BigDecimal.ZERO; } } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.KTransientResolver import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver : KTransientResolver { override fun resolve(ids: Collection): Map { To be implemented later } override fun getDefaultValue(): BigDecimal = BigDecimal.ZERO } The base interface TransientResolver/KTransientResolver has two generic parameters: The 1st generic parameter: The type of the id property of the entity to which the calculation property belongs. In this example, BookStore.avgPrice to be defined belongs to the BookStore entity whose id type is long, so the generic parameter here is Long. The 2nd generic parameter: The return data type of the calculation property. In this example, the type of BookStore.avgPrice to be defined is BigDecimal, so the generic parameter here is BigDecimal. resolve is a method of the base interface that must be implemented for users to complete calculation through it. info The parameter type of the resolve method is Collection instead of Long; its return type is Map. This is very important. It means that BookStore.avgPrice is not calculated one by one against BookStore.id, but is calculated in batches against multiple BookStore.id at a time. This is designed to prevent the N+1 problem caused by calculation properties. This design is almost the same as MappedBatchLoader in the GraphQL field, which is the standard programming model for all similar domains. getDefaultValue is an optional method of the base interface to implement. For the resolve method, if the length of the returned Map is less than the length of the ids parameter collection passed in, it means some data does not have calculation results. The calculation value corresponding to each such data is considered null. However, if the calculation property (BookStore.avgPrice in this example) is non-null, it will cause problems. Users can override getDefaultValue() to return a non-null default value to resolve this issue. caution For calculation properties that do not allow null, TransientResolver must: Either ensure the keySet of the Map returned by the resolve method contains all parameters Or override getDefaultValue to return a non-null default value","s":"Define Resolver for avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-resolver-for-avgprice","p":324},{"i":332,"t":"Java Kotlin BookStoreAvgPriceResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.ast.tuple.Tuple2; import org.springframework.stereotype.Component; @Component public class BookStoreAvgPriceResolver implements TransientResolver { private final JSqlClient sqlClient; // Constructor injection public BookStoreAvgPriceResolver(JSqlClient sqlClient) { this.sqlClient = bookStoreRepository; } @Override public Map resolve(Collection ids) { return Tuple2.toMap( sqlClient .createQuery(table) .where(table.storeId().in(storeIds)) ❶ .groupBy(table.storeId()) ❷ .select( table.storeId(), table.price().avg() ❸ ) .execute() ); } ...Omit other methods... } BookStoreAvgPriceResolver.kt package com.example.business.resolver import org.babyfish.jimmer.sql.* import org.babyfish.jimmer.sql.kt.* import org.springframework.stereotype.Component @Component class BookStoreAvgPriceResolver( // Constructor injection private val sqlClient: KSqlClient ) : KTransientResolver { override fun resolve(ids: Collection): Map = sqlClient .createQuery(Book::class) { where(table.store.id valueIn storeIds) ❶ groupBy(table.store.id) ❷ select( table.store.id, avg(table.price).asNonNull() ❸ ) } .execute() .associateBy({it._1}) { it._2 } ...Omit other functions... } ❶ Filter the foreign key STORE_ID in the BOOK table to limit the query scope. Only calculate the average price of books under the bookstores that need calculation at the moment, not all bookstores in the database. ❷ Group by the foreign key STORE_ID in the BOOK table. ❸ Calculate the average of book prices within each group. avg: Calculate the average of Book.price within the group. note In the Kotlin code there is an asNonNull(). According to SQL standards, if the aggregate function avg is not used with group, its return value can be null without original data. So in Kotlin avg is defined to return a nullable type. However, when the aggregate function avg is used with group, it cannot return null. So asNonNull() is called to get a non-null expression.","s":"Implement Resolver for avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#implement-resolver-for-avgprice","p":324},{"i":334,"t":"Now that the BookStoreAvgPriceResolver class is complete, we can add the calculation property avgPrice to the BookStore entity: Java Kotlin BookStore.java package com.example.model; import com.example.business.resolver.BookStoreAvgPriceResolver; ❶ import org.babyfish.jimmer.sql.*; public interface BookStore { ...Omit other properties... @Transient(BookStoreAvgPriceResolver.class) ❷ BigDecimal avgPrice(); } BookStore.kt package com.example.model import com.example.business.resolver.BookStoreAvgPriceResolver ❶ import org.babyfish.jimmer.sql.* interface BookStore { ...Omit other properties... @Transient(BookStoreAvgPriceResolver::class) ❷ val avgPrice: BigDecimal } If it is a single project, the BookStoreAvgPriceResolver class can be referenced here. Define the calculation property BookStore.avgPrice, and specify the class introduced at ❶ for its @Transient annotation to tell Jimmer the calculation rule for the calculation property. caution If it is a multi-project where the code structure has been split, the import statement at ❶ is invalid. In this case, ❷ must be @Transient(ref = \"bookStoreAvgPriceResolver\"). That is, use the name of this object in the Spring context.","s":"Define avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-avgprice","p":324},{"i":336,"t":"Java Kotlin List stores = bookStoreRepository.findAll( Fetchers.BOOK_STORE_FETCHER .name() .avgPrice() ); System.out.println(stores); val stores = bookStoreRepository.findAll( newFetcher(BookStore::class).by { name() avgPrice() } ) println(stores) Printed result: [ { \"id\":2, \"name\":\"MANNING\", \"avgPrice\":80.333333333333 }, { \"id\":1, \"name\":\"O'REILLY\", \"avgPrice\":57.944444444444 } ] Executed SQL: /* Step 1: Query aggregate root objects, i.e. BookStore */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ /* Step 2: Calculate `avgPrice` property for BookStore objects with id 1 and 2 */ select tb_1_.STORE_ID, avg(tb_1_.PRICE) from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 2 */, ? /* 1 */ ) group by tb_1_.STORE_ID","s":"Fetch avgPrice","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#fetch-avgprice","p":324},{"i":339,"t":"In the previous section we demonstrated the calculation property BookStore.avgPrice, which is obviously a non-associative property. In this section, we will add a calculation property BookStore.newestBooks to BookStore with the type java.util.List, which is clearly an association property. To explain why this example needs to add a calculation property BookStore.newestBooks, let's first look at the characteristics of the original association property BookStore.books: Java Kotlin Book store = bookStoreRepository.findNullable( 1L, Fetchers.BOOK_STORE_FETCHER .name() .books( Fetchers.BOOK_FETCHER .name() .edition() ) ); System.out.println(store); val store = bookStoreRepository.findNullable( 1L, newFetcher(BookStore::class).by { name() books { name() edition() } } ) println(store) The query result is: { \"id\":1, \"name\":\"O'REILLY\", \"books\":[ { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3 }, { \"id\":5, \"name\":\"Effective TypeScript\", \"edition\":2 }, { \"id\":4, \"name\":\"Effective TypeScript\", \"edition\":1 }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3 }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2 }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1 }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3 }, { \"id\":8, \"name\":\"Programming TypeScript\", \"edition\":2 }, { \"id\":7, \"name\":\"Programming TypeScript\", \"edition\":1 } ] } We can see that in the original BookStore.books association, there are many books with the same name in the bookstore. For example, there are a total of three books named \"Effective TypeScript\", with different edition values: 3, 2, 1. Now we want to create a new calculation property BookStore.newestBooks through calculation. It ensures that the returned book collection has no duplicate name problem. For each unique book name, only the book with the highest edition, i.e. the maximum edition, is taken.","s":"Clarify Requirements","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#clarify-requirements","p":324},{"i":341,"t":"Each complex calculation property corresponds to a TransientResolver implementation class. Before defining the calculation property BookStore.newestBooks, let's first define BookStoreNewestBooksResolver: Java Kotlin BookStoreNewestBooksResolver.java package com.example.business.resolver; import org.babyfish.jimmer.sql.*; import org.springframework.stereotype.Component; @Component public class BookStoreNewestBooksResolver implements TransientResolver> { ❶ @Override public Map> resolve(Collection ids) { ❷ ...To be implemented later... } @Override public List getDefaultValue() { Collections.emptyList(); } package com.example.business.resolver import org.babyfish.jimmer.sql.kt.* import org.springframework.stereotype.Component @Component class BookStoreNewestBooksResolver : KTransientResolver> { ❶ override fun resolve(ids: Collection): Map> { ❷ ...To be implemented later... } override fun getDefaultValue(): List = emptyList() } ❶ The base interface TransientResolver/KTransientResolver has two generic parameters: The 1st generic parameter: The type of the id property of the entity to which the calculation property belongs. In this example, BookStore.newestBooks to be defined belongs to the BookStore entity whose id type is long, so the generic parameter here is Long. The 2nd generic parameter: The return data type of the calculation property. In this example, the type of BookStore.newestBooks to be defined is List. Since it is a collection type, the generic parameter contains List here. Book is an entity type. Jimmer stipulates that the entity type here needs to be replaced with its id type, and Book.id is of type long. In summary, the 2nd generic parameter is List. ❷ resolve is a method of the base interface that must be implemented for users to complete calculation through it. info The parameter type of the resolve method is Collection instead of Long; its return type is Map>. This is very important. It means that BookStore.newestBooks is not calculated one by one against BookStore.id, but is calculated in batches against multiple BookStore.id at a time. This is designed to prevent the N+1 problem caused by calculation properties. This design is almost the same as MappedBatchLoader in the GraphQL field, which is the standard programming model for all similar domains. ❸ getDefaultValue is an optional method of the base interface to implement. For the resolve method, if the length of the returned Map is less than the length of the ids parameter collection passed in, it means some data does not have calculation results. The calculation value corresponding to each such data is considered null. However, if the calculation property (BookStore.newestBooks in this example) is non-null, it will cause problems. Users can override getDefaultValue() to return a non-null default value to resolve this issue. caution If calculation properties do not allow null, for their TransientResolver implementations: Either ensure the keySet of the Map returned by the resolve method contains all parameters Or override getDefaultValue to return a non-null default value","s":"Define Resolver for newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-resolver-for-newestbooks","p":324},{"i":343,"t":"Java Kotlin package com.example.business.resolver; import java.util.Collections; import org.babyfish.jimmer.sql.*; import org.babyfish.jimmer.sql.ast.tuple.Tuple2; import org.springframework.stereotype.Component; @Component public class BookStoreNewestBooksResolver implements TransientResolver> { private final JSqlClient sqlClient; // Constructor injection public BookStoreAvgPriceResolver(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Override public Map> resolve(Collection ids) { return Tuple2.toMultiMap( sqlClient .createQuery(table) .where( Expression.tuple( ❶ table.name(), table.edition() ).in( sqlClient.createSubQuery(table) ❷ .where(table.storeId().in(ids)) ❸ .groupBy(table.name()) ❹ .select( table.name(), table.edition().max() ❺ ) ) ) .select( table.storeId(), table.id() ) .execute() ); } ...Omit other code... } package com.example.business.resolver import org.babyfish.jimmer.sql.kt.* import org.springframework.stereotype.Component @Component class BookStoreNewestBooksResolver( // Constructor injection private val sqlClient: KSqlClient ) : KTransientResolver> { override fun resolve(ids: Collection): Map> = sqlClient .createQuery(Book::class) { where( tuple( ❶ table.name, table.edition ) valueIn subQuery(Book::class) { ❷ where(table.store.id valueIn storeIds) ❸ groupBy(table.name) ❹ select( table.name, max(table.edition).asNonNull() ❺ ) } ) select( table.store.id, table.id ) } .execute() .groupBy({it._1}) { it._2 } ...Omit other code... } ❶ Book.name and Book.edition form an SQL tuple. ❷ The tuple has two columns of type String and int. The subquery also has two columns of type String and int. The two match perfectly and can use the in operator. ❸ Limit the query scope to only calculate the latest version of books that need to be queried at the moment, not all bookstores in the database. Imposing calculation scope limiting conditions on the subquery performs better than imposing them on the parent query. ❹ Group by book name, so books of the same name must belong to the same group. ❺ For each group of books with the same name, find the maximum edition.","s":"Implement Resolver for newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#implement-resolver-for-newestbooks","p":324},{"i":345,"t":"Now that the BookStoreNewestBooksResolver class is complete, we can add the calculation property newestBooks to the BookStore entity: Java Kotlin package com.example.model; import com.example.business.resolver.BookStoreNewestBooksResolver; ❶ import org.babyfish.jimmer.sql.*; public interface BookStore { ...Omit other properties... @Transient(BookStoreNewestBooksResolver.class) ❷ List newestBooks(); } package com.example.model import com.example.business.resolver.BookStoreNewestBooksResolver ❶ import org.babyfish.jimmer.sql.* interface BookStore { ...Omit other properties... @Transient(BookStoreNewestBooksResolver::class) ❷ val newestBooks: List } If it is a single project, the BookStoreNewestBooksResolver class can be referenced here. Define the calculation property BookStore.newestBooks, and specify the class introduced at ❶ for its @Transient annotation to tell Jimmer the calculation rule for the calculation property. caution If it is a multi-project where the code structure has been split, the import statement at ❶ is invalid. In this case, ❷ must be @Transient(ref = \"bookStoreNewestBooksResolver\"). That is, use the name of this object in the Spring context.","s":"Define newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#define-newestbooks","p":324},{"i":347,"t":"Java Kotlin List stores = bookStoreRepository.findAll( Fetchers.BOOK_STORE_FETCHER .name() .newestBooks( ❶ ❷ Fetchers.BOOK_FETCHER allScalarFields() .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ); System.out.println(stores); val stores = bookStoreRepository.findAll( newFetcher(BookStore::class).by { name() newestBooks { ❶ ❷ allScalarFields() authors { allScalarFields() } } } ) println(stores) Fetch the calculation property BookStore.newestBooks The calculation property itself is also an association property, so the shape of its associated objects can be controlled by a deeper child fetcher. The printed result is: [ { \"id\":2, \"name\":\"MANNING\", \"newestBooks\":[ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, // This edition is max, no duplicate names \"price\":80, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] } ] }, { \"id\":1, \"name\":\"O'REILLY\", \"newestBooks\":[ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, // This edition is max, no duplicate names \"price\":51, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":6, \"name\":\"Effective TypeScript\", \"edition\":3, // This edition is max, no duplicate names \"price\":88, \"authors\":[ { \"id\":3, \"firstName\":\"Dan\", \"lastName\":\"Vanderkam\", \"gender\":\"MALE\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, // This edition is max, no duplicate names \"price\":48, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\", \"gender\":\"MALE\" } ] } ] } ] The generated SQL is: /* Step 1: Query aggregate root objects, i.e. BookStore */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ /* Step 2: For BookStore objects with id 1 and 2, calculate id sets of all Books that `newestBooks` can associate to */ select tb_1_.STORE_ID, tb_1_.ID from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( select tb_3_.NAME, max(tb_3_.EDITION) from BOOK tb_3_ where tb_3_.STORE_ID in ( ? /* 2 */, ? /* 1 */ ) group by tb_3_.NAME ) /* Step 3: For associated Book ids, query non-associative fields */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.ID in (?, ?, ?, ?) /* Step 4: For associated Books, query associable Authors */ select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) tip This example shows that when the calculation property itself is also an association property, the shape of its associated objects can be controlled by a deeper child fetcher. Since there is a deeper child fetcher, of course both native ORM association properties and other calculation association properties can be included. That is, in the process of querying complex data structures by object fetchers, the fetching tasks of ORM association properties and calculation association properties can be arbitrarily mixed. The fetching task of ORM association properties is actually SQL operations. (At least before we introduce cache, it can be considered so) As mentioned earlier, Jimmer does not impose any restrictions on the calculation methods of calculation properties. You can even use any technology other than SQL, such as OLAP technologies, to implement the calculation process (this documentation focuses on Jimmer itself, so examples also use Jimmer to implement the calculation process). That is, the fetching task of calculation properties is not necessarily SQL operations. Therefore, the functionality provided by object fetchers is actually an arbitrary mix of SQL and non-SQL operations.","s":"Fetch newestBooks","u":"/jimmer-doc/docs/mapping/advanced/calculated/transient","h":"#fetch-newestbooks","p":324},{"i":350,"t":"info @org.babyfish.jimmer.sql.Key is used together with Save Command in mutation section. Initially, people used business fields directly as the primary key of tables. This is the most straightforward and easy to use approach, but it has the following problems: Unstable primary key Since the primary key itself is a business field, it can be modified, which leads to an unstable primary key. Although the foreign keys that reference it in the database can use on update cascade to keep consistency, an unstable primary key will cause many problems for systems outside the database, such as caches. Even if a unified solution to the primary key instability problem can be abstracted at the technical level, it is not recommended, because it makes the system difficult to understand. High cost of multi-table joins Since the primary key itself is a business field, its type is likely to be a relatively long string type rather than a numeric type, and it may even be a composite primary key composed of multiple columns, which leads to high cost of multi-table joins. To solve the above problems, people learned to use data without business meaning as the primary key, such as Auto numbering by database Sequence value by database UUID Snowflake ID To enable idempotent saves for save commands, Jimmer introduces two concepts: Id and Key @Id: Primary key @Key: Business primary key If Id itself is a business attribute (not recommended), no need to specify Key, because Id itself already represents the uniqueness constraint at the business level. If Id has no business meaning (recommended), then Key represents what the uniqueness constraint is at the business level. See the following example: Java Kotlin @Entity public interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key @ManyToOne @Nullable TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } @Entity interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List } Here, the Id of the TreeNode entity uses auto numbering and has no business meaning. Therefore, to better match save commands, key is specified here, consisting of two properties: name and parent. The corresponding DDL is: create table TREE_NODE( ID bigint not null, NAME varchar(20) not null, PARENT_ID bigint ); alter table TREE_NODE add constraint PK_TREE_NODE primary key(ID); alter table TREE_NODE add constraint UQ_TREE_NODE unique(NAME, PARENT_ID); The name and parent properties of the entity type decorated with @Key correspond to the UNIQUE constraint (or UNIQUE INDEX) composed of the NAME and PARENT_ID columns in the database. This uniqueness constraint can be analogized to file systems. File systems allow directories or files with the same name, but do not allow the same name if the parent directory is specified. info Through this example, we see: Key can consist of multiple properties Foreign keys can be part of Key Let's take another look at another example where the properties that make up Key are all properties based on foreign keys: Java Kotlin @Entity public interface OrderItem { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key @ManyToOne Order order(); @Key @ManyToOne Product product(); int quantity(); // Snapshot of `product.price` BigDecimal unitPrice(); } @Entity interface OrderItem { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key @ManyToOne val order: Order @Key @ManyToOne val product: Product val quantity: Int // Snapshot of `product.price` val unitPrice: BigDecimal } This article only introduces the configuration of Key. For how to use it further, please refer to Save Command.","s":"Concept","u":"/jimmer-doc/docs/mapping/advanced/key","h":"#concept","p":348},{"i":352,"t":"Jimmer supports logical deletion, which hides deleted data instead of actually deleting it. The unique constraint defined by @Key is only for non-hidden data, not all data in the table, so unique constraint cannot be simply defined by the columns of @key. When the logical deletion flag is datetime Java Kotlin Book.java @Entity public interface Book { @Key String name(); @LogicalDeleted(\"now\") @Nullable LocalDateTime deletedTime(); ...other code omitted... } Book.kt @Entity interface Book { @Key val name: String @LogicalDeleted(\"now\") val deletedTime: LocalDateTime? ...other code omitted... } In this case, combine the columns corresponding to @Key (for this example, NAME) and the logical deletion flag column (for this example, DELETED_TIME) to define the uniqueness constraint, e.g.: alter table BOOK add constraint UQ_BOOK unique(NAME, DELETED_TIME); When the logical deletion flag is other type Java Kotlin Book.java @Entity public interface Book { @Key String name(); @LogicalDeleted(\"true\") boolean deleted(); ...other code omitted... } Book.kt @Entity interface Book { @Key val name: String @LogicalDeleted(\"true\") val deleted: Boolean ...other code omitted... } In this case, combining the @Key columns and the logical deletion flag column is no longer a viable approach. Using a conditional unique index is the only option. caution Unfortunately, not all databases support conditional indexes, and the syntax for creating conditional index varies between databases. Here, PostgresSQL is used as an example: create unique index BOOK_KEY_INDEX on BOOK(NAME) where DELETED = false;","s":"Multi-version support","u":"/jimmer-doc/docs/mapping/advanced/key","h":"#multi-version-support","p":348},{"i":354,"t":"Configuration specified by the annotation @Key is called static configuration. Sometimes, different businesses may have different requirements for @Key. Therefore, @Key configurations can be dynamically overridden at runtime. Java Kotlin sqlClient .getEntities() .saveCommand(book) .setKeyProps(BookProps.NAME, BookProps.EDITION) .execute(); sqlClient.save(book) { .setKeyProps(Book::name, Book::edition) }","s":"Dynamic Overrides","u":"/jimmer-doc/docs/mapping/advanced/key","h":"#dynamic-overrides","p":348},{"i":356,"t":"Logical deletion, also known as soft deletion, means data is not actually deleted. Instead, data is hidden to give the illusion of deletion. This leaves room for recovering from accidental operations.","s":"Logical Deletion","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/","h":"","p":355},{"i":358,"t":"To enable logical deletion for the middle table, the property needs to be specified for the org.babyfish.jimmer.sql.JoinTable annotation to indicate whether the data is normal or has been deleted. Once a logical deletion attribute is configured for the middle table, when any entity on either end is logically deleted, all related middle table records will be logically deleted. All JOIN operations for the current association will be automatically added with the condition and logical deletion flag <> already deleted to give the illusion that some associations have been deleted.","s":"Join Table","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","h":"","p":357},{"i":360,"t":"The logical deletion flag attribute can be one of the following types: boolean: must be non-null int: must be non-null enum: must be non-null long/Long: can be null or non-null UUID: must be non-null Date: must be nullable Type Code Deleted State Initialized State boolean Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED\", type = boolean.class, value = \"true\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED\", type = boolean.class, value = \"true\" ) ) val authors: List true false Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"ACTIVE\", type = boolean.class, value = \"false\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"ACTIVE\", type = boolean.class, value = \"false\" ) ) val authors: List false true int Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = int.class, value = \"1\", initializedValue = \"0\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = int.class, value = \"1\", initializedValue = \"0\" ) ) val authors: List 1 0 Enum Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = State.class, value = \"DELETED\", initializedValue = \"INITIALIZED\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"STATE\", type = State.class, value = \"DELETED\", initializedValue = \"INITIALIZED\" ) ) val authors: List DELETED INITIALIZED ✩ long Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) val authors: List Current milliseconds 0L ✩ Nullable Long Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = Long.class, nullable = true ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = Long.class, nullable = true ) ) val authors: List Current milliseconds null ✩ UUID Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class ) ) val authors: List Random UUID UUID with all bytes as 0 ✩ Nullable UUID Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class, nullable = true ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_DATA\", type = UUID.class, nullable = true ) ) val authors: List Random UUID null Nullable LocalDateTime ✩ Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_TIME\", type = LocalDateTime.class, nullable = true, value = \"now\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"DELETED_TIME\", type = LocalDateTime.class, nullable = true, value = \"now\" ) ) val authors: List Current Time null Java Kotlin @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"CREATED_TIME\", type = LocalDateTime.class, nullable = true, value = \"null\" ) ) List authors(); @ManyToMany @JoinTable( ...Omit other arguments..., logicalDeletedFilter = JoinTable.LogicalDeletedFilter( columnName = \"CREATED_TIME\", type = LocalDateTime.class, nullable = true, value = \"null\" ) ) val authors: List null Current Time Where ✩ in the first or second column indicates that the current configuration method supports multi-version data to be discussed in the next section. info Supporting logical deletion without considering multi-version data issues is less mature. Therefore, it is recommended to use the logical deletion configuration that supports multi-version data. Current milliseconds, the default behavior is System.currentMillis(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedLongGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @JoinTable.LogicalDeletedFilter(generatedType = YourGenerator.class) @JoinTable.LogicalDeletedFilter(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework Random UUID, the default behavior is UUID.randomUUID(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedUUIDGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @JoinTable.LogicalDeletedFilter(generatedType = YourGenerator.class) @JoinTable.LogicalDeletedFilter(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework","s":"Usage","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","h":"#usage","p":357},{"i":362,"t":"Logical deletion does not actually delete data, it only hides it. This means that data appears in multiple versions. Take the configuration that supports multi-version data as an example: Java Kotlin @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) List authors(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\",| logicalDeletedFilter = @JoinTable.LogicalDeletedFilter( columnName = \"DELETED_MILLIS\", type = long.class ) ) val authors: List For example, the BOOK_AUTHOR_MAPPING table has three columns, all as part of the primary key alter table BOOK_AUTHOR_MAPPING add pk_BOOK_AUTHOR_MAPPING primary key( BOOK_ID, AUTHOR_ID, DELETED_MILLIS ); If the table input is as follows: BOOK_ID AUTHOR_ID DELETED_MILLIS 97 23 0 97 23 1708796420956 97 23 1708234681901 249 11 0 249 11 1708722582793 249 11 1708664484823 There are 4 associated data records hidden, leaving only two valid data records: BOOK_ID AUTHOR_ID DELETED_MILLIS 97 23 0 249 11 0","s":"Multi-Version Data","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/join-table","h":"#multi-version-data","p":357},{"i":364,"t":"To enable logical deletion support for an entity, add a flag property annotated with org.babyfish.jimmer.sql.LogicalDeleted to indicate whether the data is normal or already deleted. Once a logical deletion property is configured for an entity: By default, when developers call APIs to delete an entity object, Jimmer will NOT actually delete the data with SQL delete statements. Instead, it will use update statements to set the logical deletion property of the entity to \"already deleted\". Other cases: Even if an entity has a logical deletion property, Jimmer also provides APIs for developers to forcibly truly delete objects by passing additional parameters. By default, all SQL queries against the entity will be automatically appended with a where logicalDeleteFlag <> already deleted condition to create the illusion that some data has been deleted. info This doc only covers the mapping configuration of the logical deletion flag field. For how to use the logical deletion functionality, see Global Filters / Logical Deletion.","s":"Entity Table","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"","p":363},{"i":366,"t":"The logical deletion flag property can be one of the following types: boolean: must be non-null int: must be non-null enum: must be non-null long/Long：either null or non-null UUID: either null or non-null date: must be nullable Type Code Deleted State Initialized State boolean Java Kotlin @LogicalDeleted(\"true\") boolean deleted(); @LogicalDeleted(\"true\") val deleted: Boolean true false Java Kotlin @LogicalDeleted(\"false\") val active: Boolean; @LogicalDeleted(\"false\") val active: Boolean false true int Java Kotlin @Default(\"0\") @LogicalDeleted(\"1\") int state(); @Default(\"0\") @LogicalDeleted(\"1\") val state: Int 1 0 Enum Java Kotlin @Default(\"INITIALIZED\") @LogicalDeleted(\"DELETED\") State state(); @Default(\"INITIALIZED\") @LogicalDeleted(\"DELETED\") val state: State DELETED INITIALIZED ✩ long Java Kotlin @LogicalDeleted long deletedMillis(); @LogicalDeleted val deletedMillis: Long Current milliseconds 0L ✩ Nullable Long Java Kotlin @LogicalDeleted Long deletedMillis(); @LogicalDeleted val deletedMillis: Long? Current milliseconds null ✩ UUID Java Kotlin @LogicalDeleted UUID deletedData(); @LogicalDeleted val deletedData: UUID Random UUID UUID with all bytes as 0 ✩ Nullable UUID Java Kotlin @Nullable @LogicalDeleted UUID deletedData(); @LogicalDeleted val deletedData: UUID? Random UUID null Nullable LocalDateTime ✩ Java Kotlin @Nullable @LogicalDeleted(\"now\") UUID deletedTime(); @LogicalDeleted(\"now\") val deletedTime: LocalDateTime? Current time null Java Kotlin @Nullable @LogicalDeleted(\"null\") UUID createdTime(); @LogicalDeleted(\"null\") val createdTime: LocalDateTime? null Current time Where ✩ in the first or second column indicates that the current configuration method supports multi-version data to be discussed in the next section. info Supporting logical deletion but not considering multi-version data issues is a less mature consideration. Therefore, it is recommended to use the logical deletion configuration that supports multi-version data. Current milliseconds, the default behavior is System.currentMillis(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedLongGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @LogicalDeleted(generatedType = YourGenerator.class) @LogicalDeleted(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework Random UUID, the default behavior is UUID.randomUUID(), which is the behavior of the default org.babyfish.jimmer.sql.meta.LogicalDeletedUUIDGenerator. If this behavior is unsatisfactory, a custom class can be implemented that implements the LogicalDeletedValueGenerator interface, and configured with: @LogicalDeleted(generatedType = YourGenerator.class) @LogicalDeleted(generatedRef = YourGenerator.class), where generatorRef indicates the name of the object in the IOC container management framework","s":"Usage","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"#usage","p":363},{"i":368,"t":"Logical deletion does not actually delete data, it only hides the data. This means that data appears in multiple versions. This issue is also described in Key / Multi-version Support. Take the example of long type logical deletion that supports multiple versions Java Kotlin @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); @LogicalDeleted long deletedMillis(); BigDecimal price(); @ManyToOne BookStore store(); } @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: String @LogicalDeleted val deletedMillis: Long val price: BigDecimal @ManyToOne val store: BookStore } Although the Key of the Book object is name and edition, because the deletedMillis property is the logical deletion flag, the non-primary key UNIQUE constraint at the database level should be: alter table BOOK add constraint uq_key_BOOK unique(NAME, EDITION, DELETED_MILLIS); If the table input is as follows: ID NAME EDITION PRICE STORE_ID DELETED_MILLIS 1027 SQL in Action 1 49.99 23 0 1026 SQL in Action 1 55.99 22 1708796420956 1025 SQL in Action 1 47.99 23 1708234681901 3131 SQL in Action 2 59.99 23 0 3130 SQL in Action 2 53.99 22 1708722582793 3129 SQL in Action 2 58.99 23 1708664484823 There are 4 associated data records hidden, leaving only two valid data records: ID NAME EDITION PRICE STORE_ID DELETED_MILLIS 1027 SQL in Action 1 49.99 23 0 3131 SQL in Action 2 59.99 23 0","s":"Multi-Version Data","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"#multi-version-data","p":363},{"i":370,"t":"If an entity is logically deleted, what effect does it have on associations based on middle tables (using the @JoinTable annotation)? If the middle table also supports logical deletion, that is, the logicalDeletedFilter of the @JoinTable annotation is specified, the middle table records related to the logically deleted entity will also be logically deleted. In [the next document] (./join-table), we will discuss in detail the logical deletion of middle tables. If the deletedWhenEndpointIsLogicallyDeleted of the @JoinTable annotation is set to true, the middle table records related to the logically deleted entity will be physically deleted. If neither of the above two conditions is met, the middle table records related to the logically deleted entity will not be processed at all.","s":"Effects on Middle Tables","u":"/jimmer-doc/docs/mapping/advanced/logical-deleted/entity","h":"#effects-on-middle-tables","p":363},{"i":373,"t":"org.babyfish.jimmer.sql.MappedSuperclass is used to provide abstract super types that can be inherited by entities. The super type itself is not an entity, but can be inherited by multiple entity types to avoid duplicate declaration of the same properties in multiple entities. Let's look at an example. First define the super type: Java Kotlin BaseEntity.java @MappedSuperclass public interface BaseEntity { LocalDateTime createdTime(); @ManyToOne User createdBy(); LocalDateTime modifiedTime(); @ManyToOne User modifiedBy(); } BaseEntity.kt @MappedSuperclass interface BaseEntity { val createdTime: LocalDateTime @ManyToOne val createdBy: User val modifiedTime: LocalDateTime @ManyToOne val modifiedBy: User } Other entities can inherit it: BookStore Java Kotlin BookStore.java @Entity public interface BookStore extends BaseEntity { ...Omit other code... } BookStore.kt @Entity interface BookStore : BaseEntity { ...Omit other code... } Book Java Kotlin Book.java @Entity public interface Book extends BaseEntity { ...Omit other code... } Book.kt @Entity interface Book : BaseEntity { ...Omit other code... } Author Java Kotlin Author.java @Entity public interface Author extends BaseEntity { ...Omit other code... } Author.kt @Entity interface Author : BaseEntity { ...Omit other code... }","s":"Basic Usage","u":"/jimmer-doc/docs/mapping/advanced/mapped-super-class","h":"#basic-usage","p":371},{"i":375,"t":"Types decorated with MappedSuperclass support multiple inheritance. Other types can inherit from multiple MappedSuperclass super types. Add a new abstract interface TenantAware to be inherited by all multi-tenant entities: Java Kotlin TenantAware.java @MappedSuperclass public interface TenantAware { String tenant(); } TenantAware.kt interface TenantAware { val tenant: String } Java Kotlin Book.java @Entity public interface Book extends BaseEntity, TenantAware { ...Omit other code... } Book.kt @Entity interface Book : BaseEntity, TenantAware { ...Omit other code... } Modify Book to inherit not only BaseEntity but also TenantAware. tip The role of @MapperSuperclass is not just to reduce duplicate code, it can also cooperate with two other functions: Global Filters Interceptors When used in cooperation with them, multiple inheritance can provide good flexibility.","s":"Multiple Inheritance","u":"/jimmer-doc/docs/mapping/advanced/mapped-super-class","h":"#multiple-inheritance","p":371},{"i":378,"t":"@org.babyfish.jimmer.sql.OnDissociate is used together with Modification/Save Command and Modification/Delete Command Modification/Save Command Existing data structure in database Data structure expected to be saved by user +-BookStore(id=2) | +-----Book(id=10) | +-----Book(id=11) | \\-----Book(id=12) +-BookStore(id=2) | +-----Book(id=10) | | | | | \\-----Book(id=9) This means: The association between BookStore-2 and Book-10 remains unchanged The association between BookStore-2 and Book-9 needs to be created BookStore-2 needs to be disassociated from Book-11 and Book-12. Modification/Delete Command This is easy to understand. Child objects need to be disassociated before deleting the parent object. @OnDissociate can only be used on foreign key based many-to-one associations, for example: Java Kotlin Book.java @Entity public interface Book { @Null @ManyToOne @OnDissociate(DissociateAction.SET_NULL) BookStore store(); ... } Book.kt @Entity interface Book { @ManyToOne @OnDissociate(DissociateAction.SET_NULL) val store: BookStore? ... } info Although disassociation of child objects is caused by a one-to-many association (or inverse one-to-one) (that is, the parent object abandons some child objects. The one-to-many association here is BookStore.books), the disassociation mode is configured for the inverse many-to-one association (here Book.store). This design is to maintain similarity with configuring cascade properties of foreign keys in database DDLs. For Jimmer, a one-to-many association must be bidirectional, so the many-to-one association that is the mirror image of a known one-to-many association is always known. So there is no problem with this design.","s":"Concepts","u":"/jimmer-doc/docs/mapping/advanced/on-dissociate","h":"#concepts","p":376},{"i":380,"t":"The parameter of the OnDissociate annotation in the above code is called the dissociation mode: There are 5 modes for child object dissociation operations Mode Description NONE (Default) Depends on global configuration jimmer.default-dissociate-action-checking If jimmer.default-dissociate-action-checking is true (default) or the foreign key upon which the current association is based is real (foreign key constraint exists in database, see Real and Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-checking is false and the foreign key upon which the current association is based is fake (no corresponding foreign key constraint in database, see Real and Fake Foreign Keys), treated as LAX. LAX Dissociation operation performs no action. If the foreign key is real (see Real and Fake Foreign Keys), when parent object is deleted: If cascade delete behavior is configured for the database foreign key (on cascade set null or on delete delete), database automatically clears the foreign key of dissociated child objects or automatically deletes the dissociated child objects Although database-level cascade modification performs better than ORM-level cascade modification, the ORM is unaware of this. Use with caution in projects requiring cache consistency Otherwise, database reports an error and the save command is terminated If the foreign key is fake (see Real and Fake Foreign Keys), when parent object is deleted, no additional behavior occurs, allowing dangling issues with child object foreign key values Even if fake foreign key values are invalid dangling values, jimmer queries won't error - the query system will return null for parent objects rather than error due to non-existent parent CHECK Does not support dissociation operations. Throws exception to prevent operation if current parent object in database has child objects that need to be dissociated. SET_NULL Sets the foreign key of dissociated child objects to null. This mode requires that the child object's foreign key property is nullable; otherwise attempting this configuration will cause an exception. DELETE Deletes the dissociated child objects. This article only introduces the configuration of OnDissociate. For how to use it further, please refer to Save Command/Dissociation Operations and Delete Commands.","s":"Dissociation Modes","u":"/jimmer-doc/docs/mapping/advanced/on-dissociate","h":"#dissociation-modes","p":376},{"i":382,"t":"Configuration specified by the annotation @OnDissociate is called static configuration. Sometimes, different businesses may have different requirements for dissociation operations. Therefore, dissociation configurations can be dynamically overridden at runtime. Modification/Save Command Java Kotlin sqlClient .getEntities() .saveCommand(book) .setDissociateAction(BookProps.STORE, DissociateAction.SET_NULL) .execute(); sqlClient.save(book) { .setDissociateAction(Book::store, DissociateAction.SET_NULL) } Modification/Delete Command Java Kotlin DeleteResult result = sqlClient .getEntities() .deleteCommand(BookStore.class, 1L) .configure(it -> it .setDissociateAction( BookProps.STORE, DissociateAction.SET_NULL ) ) .execute(); val result = sqlClient .entities .delete(BookStore::class, 1L) { setDissociateAction( Book::store, DissociateAction.SET_NULL ) }","s":"Dynamic Overrides","u":"/jimmer-doc/docs/mapping/advanced/on-dissociate","h":"#dynamic-overrides","p":376},{"i":385,"t":"Jimmer supports join table filters, with two usage scenarios:","s":"Two Scenarios","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#two-scenarios","p":383},{"i":387,"t":"Java Kotlin @Entity public interface Shop { @Id long id(); String name(); @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", readonly = true ) List customers(); @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"VIP\" ) ) List vipCustomers(); @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"ORDINARY\" ) ) List ordinaryCustomers(); } @Entity interface Shop { @Id val id: Long val name: String @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", readonly = true ) val customers: List @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"VIP\" ) ) val vipCustomers: List @ManyToMany @JoinTable( name = \"SHOP_CUSTOMER_MAPPING\", joinColumnName = \"SHOP_ID\", inverseJoinColumnName = \"CUSTOMER_ID\", filter = JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"ORDINARY\" ) ) val ordinaryCustomers: List } In this example, Shop.customers, Shop.vipCustomers, and Shop.ordinaryCustomers share the same join table create table SHOP_CUSTOMER_MAPPING( SHOP_ID bigint not null, CUSTOMER_ID bigint not null, MAPPING_TYPE varchar(8) not null ); // Whether the primary key of the join table contains // the filter column depends on the specific case. // In this example, a mapping between a `Shop` and `Customer` // cannot be both \"VIP\" and \"ORDINARY\" at the same time. // So the primary key does not contain `MAPPING_TYPE`. alter table SHOP_CUSTOMER_MAPPING add constraint pk_SHOP_CUSTOMER_MAPPING primary key(SHOP_ID, CUSTOMER_ID); alter table SHOP_CUSTOMER_MAPPING add constraint fk_SHOP_CUSTOMER_MAPPING__SHOP foreign key(SHOP_ID) references SHOP(ID); alter table SHOP_CUSTOMER_MAPPING add constraint fk_SHOP_CUSTOMER_MAPPING__CUSTOMER foreign key(CUSTOMER_ID) references CUSTOMER(ID); alter table SHOP_CUSTOMER_MAPPING add constraint fk_SHOP_CUSTOMER_MAPPING__MAPPING_TYPE check(MAPPING_TYPE in ('VIP', 'ORDINARY')); The table stores data like below: SHOP_ID CUSTOMER_ID MAPPING_TYPE 21 3176 VIP 21 1087 ORDINARY 21 9155 ORDINARY 40 8347 VIP 40 4365 ORDINARY 40 3478 ORDINARY Where Shop.vipCustomers corresponds to two rows, Shop.ordinaryCustomers to four rows, and Shop.customers can see all rows: Shop.customers = Shop.vipCustomers + Shop.ordinaryCustomers We can see that Shop.customers is not a base association, but the union of other associations. Let's call it a union association. caution Union associations cannot be directly modified, so readonly = true must be declared. Actually, the union association Shop.customers has an equivalent alternative syntax: Java Kotlin @ManyToMany @JoinTable( ...other params omitted..., filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = {\"VIP\", \"ORDINARY\"} ) ) List customers(); @ManyToMany @JoinTable( ...other params omitted..., filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = {\"VIP\", \"ORDINARY\"} ) ) val customers: List Finally, let's look at the difference in JOIN behavior between these three associations: Shop.customers Java Kotlin ShopTable table = Tables.SHOP_TABLE; List shopIds = sqlClient .create(table) .where( table .asTableEx() .customers() .name().eq(\"Smith\") ) .select(table.id()) .distinct() .execute(); val shopIds = sqlClient .create(Shop::class) { where( table .asTableEx() .customers .name eq \"Smith\" ) select(table.id()) } .distinct() .execute(); The generated SQL is: select distinct tb_1_.ID, tb_1_.NAME from SHOP tb_1_ inner join SHOP_CUSTOMER_MAPPING tb_2_ on tb_1_.ID = tb_2_.SHOP_ID inner join CUSTOMER tb_3_ on tb_2_.CUSTOMER_ID = tb_3_.ID where tb_3_.NAME = ? /* Smith */ Shop.vipCustomers Java Kotlin ShopTable table = Tables.SHOP_TABLE; List shopIds = sqlClient .create(table) .where( table .asTableEx() .vipCustomers() .name().eq(\"Smith\") ) .select(table.id()) .distinct() .execute(); val shopIds = sqlClient .create(Shop::class) { where( table .asTableEx() .vipCustomers .name eq \"Smith\" ) select(table.id()) } .distinct() .execute(); The generated SQL is: select distinct tb_1_.ID, tb_1_.NAME from SHOP tb_1_ inner join SHOP_CUSTOMER_MAPPING tb_2_ on tb_1_.ID = tb_2_.SHOP_ID and tb_2_.MAPPING_TYPE = ? /* VIP */ and tb_2_.type = ? inner join CUSTOMER tb_3_ on tb_2_.CUSTOMER_ID = tb_3_.ID where tb_3_.NAME = ? /* Smith */ Shop.ordinaryCustomers Java Kotlin ShopTable table = Tables.SHOP_TABLE; List shopIds = sqlClient .create(table) .where( table .asTableEx() .ordinaryCustomers() .name().eq(\"Smith\") ) .select(table.id()) .distinct() .execute(); val shopIds = sqlClient .create(Shop::class) { where( table .asTableEx() .ordinaryCustomers .name eq \"Smith\" ) select(table.id()) } .distinct() .execute(); The generated SQL is: select distinct tb_1_.ID, tb_1_.NAME from SHOP tb_1_ inner join SHOP_CUSTOMER_MAPPING tb_2_ on tb_1_.ID = tb_2_.SHOP_ID and tb_2_.MAPPING_TYPE = ? /* ORDINARY */ and tb_2_.type = ? inner join CUSTOMER tb_3_ on tb_2_.CUSTOMER_ID = tb_3_.ID where tb_3_.NAME = ? /* Smith */","s":"1. Multiple associations between same entity types","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#1-multiple-associations-between-same-entity-types","p":383},{"i":389,"t":"A common case is when a project has many kinds of data, and each kind of data can be tagged with multiple Tags. Tag Java Kotlin @Entity public interface Tag { @Id long id(); String name(); ...other properties omitted... } @Entity interface Tag { @Id val id: Long val name: String ...other properties omitted... } BookStore Java Kotlin @Entity public interface BookStore { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK_STORE\", ) ) List tags(); ...other properties omitted... } @Entity interface BookStore { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK_STORE\", ) ) val tags: List ...other properties omitted... } Book Java Kotlin @Entity public interface Book { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK\", ) ) List tags(); ...other properties omitted... } @Entity interface Book { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"BOOK\", ) ) val tags: List ...other properties omitted... } Author Java Kotlin @Entity public interface Author { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"AUTHOR\", ) ) List tags(); ...other properties omitted... } @Entity interface Author { @ManyToMany @JoinTable( name = \"SOURCE_TAG_MAPPING\", joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), inverseJoinColumnName = \"TAG_ID\", filter = JoinTable.JoinTableFilter( columnName = \"SOURCE_TYPE\", type = String.class, values = \"AUTHOR\", ) ) val tags: List ...other properties omitted... } For the join table SOURCE_TAG_MAPPING, although the foreign key TAG_ID references the TAG table, the other foreign key SOURCE_ID does not have a fixed target - it could reference BOOK_STORE, BOOK or AUTHOR. Therefore we cannot add a foreign key constraint on SOURCE_ID. create table SOURCE_TAG_MAPPING( SOURCE_ID bigint not null, TAG_ID bigint not null, SOURCE_TYPE varchar(10) not null ); // Whether the primary key contains the filter column // depends on the specific case. // In this example, `SOURCE_ID` of different types could be equal, // so the primary key constraint needs to contain `SOURCE_TYPE`. alter table SOURCE_TAG_MAPPING add constraint pk_SHOP_CUSTOMER_MAPPING primary key(SOURCE_ID, TAG_ID, SOURCE_TYPE); // `SOURCE_ID` could reference `BOOK_STORE`, `BOOK` or `AUTHOR`, // so we cannot add a foreign key constraint alter table SOURCE_TAG_MAPPING add constraint fk_SOURCE_TAG_MAPPING__TAG primary key(TAG_ID) references TAG(ID); alter table SOURCE_TAG_MAPPING add constraint ck_SOURCE_TAG_MAPPING__SOURCE_TYPE check(SOURCE_TYPE in ('BOOK_STORE', 'BOOK', 'AUTHOR')); Since SOURCE_ID cannot have a foreign key constraint, it is a fake foreign key. That's why in the code above: @JoinTable( joinColumns = @joinColumn( name = \"SOURCE_ID\", foreignKeyType = ForeignKeyType.FAKE ), ...other params omitted... ) Sample data could look like: SOURCE_ID TARGET_ID SOURCE_TYPE 9 2 BOOK_STORE 9 4 BOOK_STORE 86 3 BOOK 86 4 BOOK 781 1 AUTHOR 781 3 AUTHOR","s":"2. Multiple associations between different entity types","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#2-multiple-associations-between-different-entity-types","p":383},{"i":391,"t":"Both one-to-many and many-to-many can use join tables, so we can merge their join tables into one table. But please note: caution It is strongly recommended to only use this pattern when the database supports conditional indexes. That is, do not use this pattern on databases without conditional index support like MySQL.","s":"Mixing One-to-Many and Many-to-Many","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#mixing-one-to-many-and-many-to-many","p":383},{"i":393,"t":"Java Kotlin @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", readonly = true ) List authors(); @Nullable @ManyToOne @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"PRIMARY\" ) ) Author primaryAuthor(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"SECONDARY\" ) ) List secondaryAuthors(); ...other properties omitted... } @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", readonly = true ) val authors: List @Nullable @ManyToOne @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"PRIMARY\" ) ) val primaryAuthor: Author? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\", filter = @JoinTable.JoinTableFilter( columnName = \"MAPPING_TYPE\", type = String.class, values = \"SECONDARY\" ) ) val secondaryAuthors: List ...other properties omitted... } Clearly: authors (many-to-many) = primaryAuthor (many-to-one) + secondaryAuthors (many-to-many)","s":"Define Associations","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#define-associations","p":383},{"i":395,"t":"create table BOOK_AUTHOR_MAPPING( BOOK_ID bigint not null, AUTHOR_ID bigint not null, MAPPING_TYPE varchar(9) not null ); // Whether the primary key contains the filter column depends on the specific case. // In this example, a mapping between an `Author` and a `Book` // cannot be both \"PRIMARY\" and \"SECONDARY\" at the same time. // So the primary key constraint does not contain `MAPPING_TYPE`. alter table BOOK_AUTHOR_MAPPING add constraint pk_BOOK_AUTHOR_MAPPING primary key(BOOK_ID, AUTHOR_ID); alter table BOOK_AUTHOR_MAPPING add constraint fk_BOOK_AUTHOR_MAPPING__BOOK foreign key(BOOK_ID) references BOOK(ID); alter table BOOK_AUTHOR_MAPPING add constraint fk_BOOK_AUTHOR_MAPPING__BOOK foreign key(AUTHOR_ID) references AUTHOR(ID); alter table BOOK_AUTHOR_MAPPING add constraint ck_BOOK_AUTHOR_MAPPING__MAPPING_TYPE check(MAPPING_TYPE in ('PRIMARY', 'SECONDARY')); // Syntax for conditional indexes may differ slightly between databases, // here is an example in Postgres create unique index BOOK_AUTHOR_MAPPING__PRIMARY_INDEX on BOOK_AUTHOR_MAPPING(AUTHOR_ID) when MAPPING_TYPE = 'PRIMARY'; The when clause is very important, indicating this is a conditional index. Syntax for conditional indexes may differ slightly between databases, here is an example in Postgres. See https://www.postgresql.org/docs/current/indexes-partial.html for more details. When MAPPING_TYPE is \"PRIMARY\", a unique index is added on the AUTHOR_ID foreign key to ensure each Book has maximum one primary Author. That is, to ensure Book.primaryAuthor is a many-to-one association. Otherwise, there is no uniqueness constraint, so each Book can have any number of secondary Authors. That is, Book.secondaryAuthors remains a many-to-many association.","s":"Conditional Indexes","u":"/jimmer-doc/docs/mapping/advanced/join-table-filter","h":"#conditional-indexes","p":383},{"i":397,"t":"View properties do not maintain their own data, they are just another representation of another attribute (called original attribute) of their owning entity type. View properties and original properties share the same underlying data, the only difference is that the returned data format is different from the original attribute. In this article, you will learn about these annotations: org.babyfish.jimmer.sql.IdView org.babyfish.jimmer.sql.ManyToManyView","s":"View Properties","u":"/jimmer-doc/docs/mapping/advanced/view/","h":"","p":396},{"i":399,"t":"caution Remote association is a product of combining Jimmer with microservice architecture. It will be introduced in detail in Spring Cloud and Remote Association. The purpose of this article is not to systematically explain remote associations, just to introduce the mapping configuration required for remote associations.","s":"Remote Association","u":"/jimmer-doc/docs/mapping/advanced/remote","h":"","p":398},{"i":401,"t":"The @Entity annotation has an optional parameter microServiceName whose default value is \"\". Association properties involve two entity types. Since associations must point from the source to the target (self association properties are special, the source and target overlap): If the microServiceName of the source entity and target entity of the association property are equal, then this association is a local association (All entities in the examples before this article use the default microServiceName, so they are local associations). If the microServiceName of the source entity and target entity of the association property are not equal, then this association is a remote association. For example: Owning side (required): Book.authors Java Kotlin Book.java @Entity(microServiceName = \"book-service\") public interface Book { @ManyToMany List authors(); ...Omit other code... } Book.kt @Entity(microServiceName = \"book-service\") interface Book { @ManyToMany val authors: List ...Omit other code... } Inverse side (optional): Author.authors Java Kotlin Author.java @Entity(microServiceName = \"author-service\") public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ...Omit other code... } Author.kt @Entity(microServiceName = \"author-service\") interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...Omit other code... } Here, the microservice name of Book is book-service, and the microservice name of Author is author-service. The two are not equal, so Book.authors and Author.books are remote associations.","s":"@Entity","u":"/jimmer-doc/docs/mapping/advanced/remote","h":"#entity","p":398},{"i":403,"t":"As a super type, MappedSuperclass has two usages: Can contain association properties, but must belong to the same microservice Java Kotlin BookServiceCommonEntity.java @MappedSuperclass(microServiceName = \"book-service\") public interface BookServiceCommonEntity { LocalDateTime createdTime(); @ManyToOne User createdBy(); LocalDateTime modifiedTime(); @ManyToOne User modifiedBy(); } BookServiceCommonEntity.kt @MappedSuperclass(microServiceName = \"book-service\") interface BookServiceCommonEntity { val createdTime: LocalDateTime @ManyToOne val createdBy: User val modifiedTime: LocalDateTime @ManyToOne val modifiedBy: User } Here BookServiceCommonEntity contains association properties createdBy and modifiedBy, but only Entity or other MappedSuperclass belonging to the microservice \"book-service\" can inherit it. Can span any microservices, but must not contain association properties Java Kotlin CommonEntity.java @MappedSuperclass(acrossMicroServices = true) public interface CommonEntity { LocalDateTime createdTime(); LocalDateTime modifiedTime(); } CommonEntity.kt @MappedSuperclass(acrossMicroServices = true) interface CommonEntity { val createdTime: LocalDateTime val modifiedTime: LocalDateTime } Here CommonEntity can span any microservices. Any Entity or other MappedSuperclass under any microservice can inherit it, but it itself does not contain any association properties.","s":"@MappedSuperclass","u":"/jimmer-doc/docs/mapping/advanced/remote","h":"#mappedsuperclass","p":398},{"i":405,"t":"In this series of articles, we will introduce base mappings.","s":"Base mapping","u":"/jimmer-doc/docs/mapping/base/","h":"","p":404},{"i":407,"t":"Here, you will learn about the most important capability of ORM: entity relationship mapping. You will learn about these annotations: org.babyfish.jimmer.sql.OneToOne org.babyfish.jimmer.sql.ManyToOne org.babyfish.jimmer.sql.OneToMany org.babyfish.jimmer.sql.ManyToMany org.babyfish.jimmer.sql.JoinColumn org.babyfish.jimmer.sql.JoinTable caution For associations, the type of the basic properties in the entity type should be the associated object, not the associated Id. If you want to define associated Id properties, please First complete the association mapping according to this chapter Then add associated Id properties according to IdView","s":"Association Mapping","u":"/jimmer-doc/docs/mapping/base/association/","h":"","p":406},{"i":409,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToOne annotation to declare many-to-one association properties. There are two ways to implement many-to-one associations: based on foreign key and based on join table.","s":"Many To One","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","h":"","p":408},{"i":411,"t":"Java Kotlin Book.java @Entity public interface Book { @ManyToOne BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne val store: BookStore ...Omit other code... } Here @JoinColumn is not used together to explicitly specify the foreign key column name. Jimmer will deduce the column name corresponding to the store property based on the naming strategy. If the default naming strategy is not overridden by the user, the foreign key column name of the store property is STORE_ID. So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") val store: BookStore ...Omit other code... } The foreign key can be real or fake. Fake foreign keys are discussed in subsequent documents. Here we assume the foreign key is real, so the corresponding constraint in the database is: // If foreign key pointing to associated entity is real, // create foreign key constraint alter table BOOK add constraint FK_BOOK__BOOK_STORE foreign key(STORE_ID) references BOOK_STORE(ID);","s":"1. Based on Foreign Key","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","h":"#1-based-on-foreign-key","p":408},{"i":413,"t":"Java Kotlin Book.java @Entity public interface Book { @Nullable @ManyToOne @JoinTable BookStore store(); ... } Book.kt @Entity interface Book { @Nullable @ManyToOne @JoinTable val store: BookStore? ... } Here, no properties are specified for @JoinTable. Jimmer will deduce the column names corresponding to the store property based on the naming strategy. If the default naming strategy is not overridden by the user, the deduced join table information is: Join table name: BOOK_BOOK_STORE_MAPPING Join table foreign key column pointing to current entity: BOOK_ID Join table foreign key column pointing to associated entity: STORE_ID So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @Null @ManyToOne @JoinTable( name = \"BOOK_BOOK_STORE_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"STORE_ID\" ) BookStore store(); ... } Book.kt @Entity interface Book { @ManyToOne @JoinTable( name = \"BOOK_BOOK_STORE_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"STORE_ID\" ) val store: BookStore? ... } The join table BOOK_BOOK_STORE_MAPPING is defined as: create table BOOK_BOOK_STORE_MAPPING( BOOK_ID bigint not null, STORE_ID bigint not null ); alter table BOOK_STORE_MAPPING add constraint PK_BOOK_STORE_MAPPING primary(BOOK_ID, STORE_ID); // If foreign key pointing to current entity is real, // create foreign key constraint alter table BOOK_BOOK_STORE_MAPPING add constraint FK_BOOK_BOOK_STORE_MAPPING__BOOK foreign key(BOOK_ID) references BOOK(ID); // If foreign key pointing to associated entity is real, // create foreign key constraint alter table BOOK_BOOK_STORE_MAPPING add constraint FK_BOOK_BOOK_STORE_MAPPING__STORE foreign key(STORE_ID) references BOOK_STORE(ID); // This constraint is very important. // Otherwise this join table expresses a many-to-many association // rather than a many-to-one association alter table BOOK_BOOK_STORE_MAPPING add constraint UQ_BOOK_BOOK_STORE_MAPPING__BOOK_ID unique(BOOK_ID); The join table has only two foreign keys, both non-null. The join table maintains the association by inserting and deleting data, never storing null data itself. The join table has no corresponding ORM entity and does not need an independent primary key. The two foreign keys combined can serve as the primary key. By default, the join table represents a many-to-many association. To degrade it to a many-to-one association, a unique constraint must be specified for the foreign key BOOK_ID pointing to the current entity. caution Unless for compatibility with existing database design, many-to-one associations are recommended to use foreign keys directly instead of join tables. Once a many-to-one association is mapped using a join table, the Jimmer association property must be nullable, because the database cannot guarantee that any entity must have corresponding data in the join table.","s":"2. Based on Join Table","u":"/jimmer-doc/docs/mapping/base/association/many-to-one","h":"#2-based-on-join-table","p":408},{"i":415,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.ManyToMany annotation to declare many-to-many association properties. Many-to-many supports bidirectional association. For bidirectional associations, one side must be the owning side, and the other side must be the inverse side. Owning side (required): The actual mapping between the database and association properties to implement unidirectional many-to-many association. Inverse side (optional): If a unidirectional association already exists, the inverse side can be configured as a mirror of the owning side to form a bidirectional association. Let's assume there are two entity types Book and Author, and establish a bidirectional many-to-many association between them. info Different from JPA/Hibernate, the owning side and inverse side can be chosen arbitrarily. Both can be used to persist associations. The example in this article chooses: Owning side (required): Book.authors Inverse side (optional): Author.books","s":"Many To Many","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"","p":414},{"i":417,"t":"Java Kotlin Book.java @Entity public interface Book { @ManyToMany List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany val authors: List ...Omit other code... } Many-to-many associations must be implemented based on a join table, even if the @JoinTable annotation is not used in the above code, it is actually equivalent to using the annotation. If no properties are specified for @JoinTable, and even @JoinTable itself is omitted (like the previous code), Jimmer will deduce the column names corresponding to the authors property based on the naming strategy. If the default naming strategy is not overridden by the user, the deduced join table information is: Join table name: BOOK_AUTHOR_MAPPING Join table foreign key column pointing to current entity: BOOK_ID Join table foreign key column pointing to associated entity: AUTHOR_ID So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List ...Omit other code... } The join table BOOK_AUTHOR_MAPPING is defined as: create table BOOK_AUTHOR_MAPPING( BOOK_ID bigint not null, AUTHOR_ID bigint not null ); alter table AUTHOR_MAPPING add constraint PK_AUTHOR_MAPPING primary(BOOK_ID, AUTHOR_ID); // If foreign key pointing to current entity is real, // create foreign key constraint alter table BOOK_AUTHOR_MAPPING add constraint FK_BOOK_AUTHOR_MAPPING__BOOK foreign key(BOOK_ID) references BOOK(ID); // If foreign key pointing to associated entity is real, // create foreign key constraint alter table BOOK_AUTHOR_MAPPING add constraint FK_BOOK_AUTHOR_MAPPING__AUTHOR foreign key(AUTHOR_ID) references AUTHOR(ID); The join table has only two foreign keys, both non-null. The join table maintains the association by inserting and deleting data, never storing null data itself. The join table has no corresponding ORM entity and does not need an independent primary key. The two foreign keys combined can serve as the primary key. caution Note The @ManyToMany association property must be non-null. If an object requires fetching its many-to-many association properties, then for the current object that has no corresponding associated object, the value of this property is a collection of length 0 rather than null.","s":"Owning Side","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"#owning-side","p":414},{"i":419,"t":"The configuration of the inverse side is very simple, just specify that Author.books is the mirror of Book.authors. In the following code: Left: The owning side discussed in the previous section Right: The inverse side association Author.books introduced in this section, which is the mirror of Book.authors Here, @ManyToMany(mappedBy = \"store\") indicates that the current property Authors.books is the mirror of Book.authors. Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List ...Omit other code... } Java Kotlin Author.java @Entity public interface Author { // `mappedBy` indicates `Author.books` // is the mirror of `Book.authors` @ManyToMany(mappedBy = \"authors\") List books(); ...Omit other code... } Author.kt @Entity interface Author { // `mappedBy` indicates `Author.books` // is the mirror of `Book.authors` @ManyToMany(mappedBy = \"authors\") val books: List ...Omit other code... } caution Note: Once the mappedBy property of @ManyToMany is specified, @JoinTable must not be used. Like the @ManyToMany association property on the owning side, the @ManyToMany association on the inverse side must also be non-null for the same reason.","s":"Inverse Side","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"#inverse-side","p":414},{"i":421,"t":"For the many-to-many association discussed in this article, no business fields other than the two foreign keys can be defined on the join table. If you want to define more other business fields in the join table of the many-to-many association, please refer to ManyToManyView.","s":"If business fields need to be added to the join table","u":"/jimmer-doc/docs/mapping/base/association/many-to-many","h":"#if-business-fields-need-to-be-added-to-the-join-table","p":414},{"i":424,"t":"In Basic Mapping/Associative Mapping, we learned about the classic associative mappings in ORM, including one-to-one, many-to-one, one-to-many and many-to-many. However, there is one scenario that makes the choice of mapping mode very tangled. To show this scenario, let's start with a familiar scenario.","s":"Limitations of classic ORM associations","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#limitations-of-classic-orm-associations","p":422},{"i":426,"t":"Let's look at a piece of DDL create table book( ...omit... )engine=innodb;; create table author( ...omit... ) engine=innodb; create table book_author_mapping( book_id bigint unsigned not null, author_id bigint unsigned not null ) engine=innodb; alter table book_author_mapping add constraint pk_book_author_mapping primary key(book_id, author_id) ; alter table book_author_mapping add constraint fk_book_author_mapping__book foreign key(book_id) references book(id) on delete cascade ; alter table book_author_mapping add constraint fk_book_author_mapping__author foreign key(author_id) references author(id) on delete cascade ; In this piece of DDL, book_author_mapping table is very special, it only has two foreign keys, one pointing to book table, and one pointing to author table. This kind of subtable with only two foreign keys is used to express the many-to-many association between two parent tables. ORM's many-to-many mapping will hide the intermediate table, that is, the intermediate table does not correspond to a Java/Kotlin entity type. Therefore, the intermediate table does not need an independent primary key, but directly uses the two foreign keys as a combined primary key. info In addition to the two associative foreign keys, the intermediate table must not have any other fields, which is a limitation of many-to-many associations in ORM. The corresponding many-to-many association in ORM is as follows: Owning side: Book.authors Java Kotlin Book.java @Entity public interface Book { @ManyToMany List authors(); ...other code omitted... } Book.kt @Entity interface Book { @ManyToMany val authors: List ...other code omitted... } Inverse side (optional): Author.books Java Kotlin Author.java @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ...other code omitted... } Author.kt @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...other code omitted... }","s":"Undisputed many-to-many association","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#undisputed-many-to-many-association","p":422},{"i":428,"t":"Let's look at the second scenario, first, look at a piece of DDL create table order_( ...omit... ) engine=innodb; create table product( ...omit... ) engine=innodb; create table order_item( id bigint unsigned not null auto_increment primary key, order_id bigint unsigned not null, product_id bigint unsigned not null, quantity int not null, unit_price numeric(10, 2) not null ) engine=innodb; alter table order_item add constraint business_key_order_item unique(order_id, product_id) ; alter table order_item add constraint fk_order_item__order foreign key(order_id) references order_(id) ; alter table order_item add constraint fk_order_item__product foreign key(product_id) references product(id) ; This is a classic order - order item - product association. Among them, order-item looks a bit like the intermediate table of many-to-many, because it has two foreign keys: order_id pointing to the order_ table and product_id pointing to the product table. However, order-item is not an intermediate table, because it has other business fields, quantity representing quantity of goods, and unit_price representing a snapshot of the price of goods at the time of order. Fortunately, for the classic order - order item - product association, it is more intuitive to think of order_item as an independent entity, with two many-to-one associations pointing to order_ and product respectively; Rather than viewing order-item as a join table and thinking there is a many-to-many relationship between order_ and product. It is precisely because order_item is regarded as an independent entity that order_item uses an independent primary key. We can map these three tables in ORM using two many-to-one associations OrderItem.order and OrderItem.product Java Kotlin OrderItem.java @Entity public interface OrderItem { @ManyToOne Order order(); @ManyToOne Product product(); int quantity(); BigDecimal unitPrice(); ...other code omitted... } OrderItem.kt @Entity interface OrderItem { @ManyToOne val order: Order @ManyToOne val product: Product val quantity: Int val unitPrice: BigDecimal ...other code omitted... } Order.items In such systems, it is often necessary to get the detail list according to the order, so we define a one-to-many property Order.items as a mirror of OrderItem.order. Java Kotlin Order.java @Entity @Table(name = \"ORDER_\") public interface Order { @OneToMany(mappedBy = \"order\") List items(); ...other code omitted... } Order.kt @Entity @Table(name = \"ORDER_\") interface Order { @OneToMany(mappedBy = \"order\") val items: List ...other code omitted... } Do not provide Product.items In such systems, it is rarely necessary to get the detail list based on the product (if starting the analysis from the product side, it is usually a complex query rather than a simple association), so a one-way OrderItem.product association is sufficient. So there is no need to show the code for the Product entity.","s":"Undisputed double many-to-one association","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#undisputed-double-many-to-one-association","p":422},{"i":430,"t":"In the previous text, we showed two business scenarios Scenario 1: The intermediate table book_author_mapping is very clean, with only two foreign key fields, and is naturally mapped to a many-to-many association Scenario 2: order_item looks like an intermediate table but is not an intermediate table, because in addition to the two foreign keys it also needs to have other business fields. Fortunately, people will choose to treat OrderItem as an independent entity and use two many-to-one associations to string the three entity types together. Next, let's look at scenario 3, first look at the DDL: create table student( ...omit... )engine=innodb;; create table course( ...omit... ) engine=innodb; create table learning_link ( id bigint unsigned not null auto_increment primary key, student_id bigint unsigned not null, course_id bigint unsigned not null, score int ) engine=innodb; alter table learning_link add constraint pk_student_course_mapping primary key(student_id, course_id) ; alter table learning_link add constraint fk_student_course_mapping__student foreign key(student_id) references student(id) on delete cascade ; alter table learning_link add constraint fk_student_course_mapping__course foreign key(course_id) references course(id) on delete cascade ; This piece of DDL represents the elective course system in schools. There is a many-to-many relationship between students and elective courses. For students, it is of course very important to know which courses they have chosen For schools, it is also very important to know which students have chosen each course, because teacher resources and teaching venues need to be arranged based on this information That is, for the student entity and the course entity, associating with each other and querying each other is an important and high frequency operation. Therefore, abstracting bidirectional many-to-many associations between student and course is a very good choice. Unfortunately, the elective relationship table learning_link has a score field that can be null, null indicating that the exam has not yet taken place, non-null indicating the score after the exam. Because of the existence of this field, the intermediate table is no longer clean, and cannot be simply mapped to the classic ORM many-to-many association. That is, this is not a simple scenario 1. Of course, we can handle this problem using the method of scenario 2, treating learning_link as an independent entity, and using two many-to-one associations to string the three entity types together. However, for a large part of the upper layer business, what they really care about is only the mutual association between student and course, and they don't care about the score field of the learning_link table. (That is, the non-foreign key business field learning_link.score of the intermediate table is far less important than the relevant fields in scenario 2). In this case, scenario 2's solution will bring a higher cognitive burden, and scenario 1's way of thinking is obviously simpler. info This scenario is actually the most tangled scenario in classic ORM, which cannot be simply mapped to many-to-many associations, while hoping that some upper layer business can adopt the many-to-many mentality to simplify the problem. @ManyToManyView is a powerful tool designed for such scenarios.","s":"The controversial, tangled scenario","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#the-controversial-tangled-scenario","p":422},{"i":432,"t":"For the discussed scenario 3 above, Jimmer gave a two-step solution. Basic association mapping: First, treat learning_link as an independent entity according to scenario 2, and provide two many-to-one associations pointing to student and course respectively; Conversely, student and course also use one-to-many associations to reference learning_link. That is, use two bidirectional one-to-many associations to string the three entity types together. Use @ManyToManyView: Then, on the basis of the first step, use @ManyToManyView to quickly simulate the effect of scenario 1.","s":"Getting Started with ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#getting-started-with-manytomanyview","p":422},{"i":434,"t":"LearningLink.student and LearningLink.course Java Kotlin LearningLink.java @Entity public interface LearningLink { @ManyToOne Student student(); ① @ManyToOne Course course(); ② Integer score(); ...other code omitted... } LearningLink.kt @Entity interface LearningLink { @ManyToOne val student: Student ① @ManyToOne val course: Course ② val score: Int? ...other code omitted... } Where ① and ② will be referenced by subsequent code Student.learningLinks Java Kotlin Student.java @Entity public interface Student { @OneToMany(mappedBy = \"student\") List learningLinks(); ③ ...other code omitted... } Student.kt @Entity interface Student { @OneToMany(mappedBy = \"student\") val learningLinks: List ③ ...other code omitted... } Where ③ will be referenced by subsequent code Course.learningLinks Java Kotlin Course.java @Entity public interface Course { @OneToMany(mappedBy = \"course\") List learningLinks(); ④ ...other code omitted... } Course.kt @Entity interface Course { @OneToMany(mappedBy = \"course\") val learningLinks: List ④ ...other code omitted... } Where ④ will be referenced by subsequent code","s":"Basic relationship mapping","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#basic-relationship-mapping","p":422},{"i":436,"t":"Simulate many-to-many association: Student.courses Java Kotlin Student.java @Entity public interface Student { @ManyToManyView( prop = \"learningLinks\", ❶ -> ③ deeperProp = \"course\" ❷ -> ② ) List courses(); // The one-to-many association `learningLinks` // has been declared in step 1 @OneToMany(mappedBy = \"student\") List learningLinks(); ③ ...other code omitted... } Student.kt @Entity interface Student { @ManyToManyView( prop = \"learningLinks\", ❶ -> ③ deeperProp = \"course\" ❷ -> ② ) val courses: List // The one-to-many association `learningLinks` // has been declared in step 1 @OneToMany(mappedBy = \"student\") val learningLinks: List ③ ...other code omitted... } The current property Student.courses can be obtained in two steps: ❶ prop = \"learningLinks\" First, get all LearningLink objects through another property of the current entity Student.learningLinks ③ ❷ deeperProp = \"course\" For each LearningLink object obtained in the previous step, Course can be further obtained through the LearningLink.course property ② tip Since the LearningLink entity has only one many-to-one association pointing to the Course entity, there is no ambiguity, so deeperProp = \"course\" can be omitted here Simulate many-to-many association: Course.students Java Kotlin Course.java @Entity public interface Course { @ManyToManyView( prop = \"learningLinks\", ❶ -> ④ deeperProp = \"student\" ❷ -> ① ) List students(); // The one-to-many association `learningLinks` has been declared in step 1 @OneToMany(mappedBy = \"course\") List learningLinks(); ④ ...other code omitted... } Course.kt @Entity interface Course { @ManyToManyView( prop = \"learningLinks\", ❶ -> ④ deeperProp = \"student\" ❷ -> ① ) val students: List // The one-to-many association `learningLinks` has been declared in step 1 @OneToMany(mappedBy = \"course\") val learningLinks: List ④ ...other code omitted... } The current property Course.students can be obtained in two steps: ❶ prop = \"learningLinks\" First, get all LearningLink objects through another property of the current entity Course.learningLinks ④ ❷ deeperProp = \"student\" For each LearningLink object obtained in the previous step, Student can be further obtained through the LearningLink.student property ① tip Since the LearningLink entity has only one many-to-one association pointing to the Student entity, there is no ambiguity, so deeperProp = \"student\" can be omitted here","s":"Using @ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#using-manytomanyview","p":422},{"i":438,"t":"The property declared by @ManyToManyView does not maintain its own data, it is only a view of the original property, which proxies and wraps the collection returned by the original property. Take the Java example in this article Student side as an example (the Course side is the same). Original association property: List learningLinks(); View association property: List courses(); You can understand the ManyToManyView view property with this pseudocode: @Override public List courses() { return new ListProxy<>( this.learningLinks(), LearningLink::course ); } The view association property returns a proxy collection that wraps the collection of the original property and transforms the elements of the original collection. It is obvious that the two are essentially the same and share the same data. When constructing entity objects, only the original property can be set, not the view property. This is different from @IdView. For @IdView, both the original property and the view property can be set. Whether it is the original property or the view property, the preprocessor will generate code to match them, so both can be used in object fetchers and strongly typed SQL DSL.","s":"The essence of @ManyToManyView","u":"/jimmer-doc/docs/mapping/advanced/view/many-to-many-view","h":"#the-essence-of-manytomanyview","p":422},{"i":440,"t":"Unlike JPA, Jimmer does not support unidirectional one-to-many associations. One-to-many associations can only exist as mirrors of many-to-one associations. That is, one-to-many associations necessarily imply bidirectional associations. In the following code: Left: Book.store discussed in Many To One Right: BookStore.books to be discussed in this article, which is the mirror of Book.store Java Kotlin Book.java @Entity public interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(name = \"STORE_ID\") val store: BookStore ...Omit other code... } Java Kotlin BookStore.java @Entity public interface BookStore { // `mappedBy` indicates `BookStore.books` // is the mirror of `Book.store` @OneToMany(mappedBy = \"store\") @Nullable List books(); ...Omit other code... } BookStore.kt @Entity interface BookStore { // `mappedBy` indicates `BookStore.books` // is the mirror of `Book.store` @OneToMany(mappedBy = \"store\") val books: List? ...Omit other code... } caution @OneToMany associations are merely mirrors of @ManyToOne associations. @JoinColumn and @JoinTable must not be used. The @OneToMany association property must be non-null. If the parent object is queried and its one-to-many association property needs to be fetched, then for the parent object that has no corresponding child objects, the value of this property is a collection of length 0 rather than null.","s":"One To Many","u":"/jimmer-doc/docs/mapping/base/association/one-to-many","h":"","p":439},{"i":443,"t":"Before introducing IdView, we need to first introduce a concept: short associations. Before introducing short associations, let's first look at a normal association Java Kotlin Book book = bookRepository.findNullable( 1L, Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) .authors( Fetchers.AUTHOR_FETCHER .firstName() .lastName() ) ); System.out.println(book); val book = bookRepository.findNullable( 1L, newFetcher(Book::class).by { allScalarFields() store { allScalarFields() } authors { firstName() lastName() } } ); System.out.println(book); In this code: Fetches associated BookStore object via store association property of Book, expecting to get all non-associative properties of associated object Fetches associated Author objects via authors association property of Book, expecting id (implicit + mandatory), firstName and lastName of associated objects The output is: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] } Here, associated objects BookStore and Author on aggregate root Book have properties other than id, with relatively complete information. More importantly, non-id properties of course also include associated properties, so this data structure can be nested multiple levels or even recursive. This kind of association can also be called a \"long association\". info However, not all cases require such a deep data structure. In actual projects, sometimes only a very simple UI is needed, like below: Book Form Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit In this UI: Book.store is a many-to-one association, rendered as a dropdown selector Book.authors is a many-to-many association, rendered as a multiple dropdown selector Of course, if there are too many options, a dropdown list is no longer a reasonable design. In this case, improve it to a popup dialog with pagination. But these UI details are unimportant and irrelevant to the current topic. It is obvious that at this point, the user only cares about the id of the associated object, and has no interest in other properties of the associated object. That is, we want the associated object to only have the id property To allow aggregate roots to be associated with some objects that only have id, we can improve the code. Java Kotlin Book book = bookRepository.findNullable( 1L, Fetchers.BOOK_FETCHER .allScalarFields() .store() // no args means id only .authors() // no args means id only ); System.out.println(book); val book = bookRepository.findNullable( 1L, newFetcher(Book::class).by { allScalarFields() store() // no args means id only authors() // no args means id only } ); System.out.println(book); This time, we get a data structure like this: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ // Only has id property \"id\":1 }, \"authors\":[ { // Only has id property \"id\":1 }, { // Only has id property \"id\":2 } ] } note In Hibernate, this kind of object with only id property is called a proxy object. However, associated objects with only id are not as simple as just the id of the association. Let's look at the same data expressed with associated ids instead of associated objects: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"storeId\": 1, \"authorIds\":[1, 2] } It is obvious that for short association use cases, associated ids or their collections are simpler than associated objects or their collections with only id.","s":"Basic Concepts: Short Associations","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#basic-concepts-short-associations","p":441},{"i":445,"t":"Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"Book Form","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"","p":441},{"i":447,"t":"ADO.NET EF Core is Microsoft's ORM. Let's look at its design: https://learn.microsoft.com/en-us/ef/core/modeling/relationships?tabs=fluent-api%2Cfluent-api-simple-key%2Csimple-key public class Post { public int PostId { get; set; } public string Title { get; set; } public string Content { get; set; } public int BlogId { get; set; } public Blog Blog { get; set; } } It's easy to see that: Associated object: public Blog Blog { get; set; } Associated id: public int BlogId { get; set; } They coexist. Jimmer learns from this design of ADO.NET EF Core and provides the @IdView property.","s":"Microsoft's Solution","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#microsofts-solution","p":441},{"i":450,"t":"IdView properties are declared with @org.babyfish.jimmer.sql.IdView: Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface Book { ...other properties omitted... @ManyToOne @Nullable BookStore store(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) List authors(); @IdView // View of store id Long storeId(); // View of all author ids in authors collection @IdView(\"authors\") List authorIds(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Book { ...other properties omitted... @ManyToOne val store: BookStore? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) val authors: List @IdView // View of store id val storeId: Long? // View of all author ids in authors collection @IdView(\"authors\") val authorIds: List } Where: Book.storeId: View of the id of associated Book.store object. Since storeId itself ends with Id, the parameter of @IdView annotation can be omitted. Jimmer infers the original association property to be Book.store. Nullability of original association property and IdView property must be consistent. In this example, Book.store property can be null, i.e. annotated with @Nullable in Java, or returns BookStore? in Kotlin. Therefore, Book.storeId must also be nullable, i.e. returns Long instead of long in Java, or returns Long? instead of Long in Kotlin. Otherwise it would cause compile error. Book.authorIds: View of ids of all Author objects in associated Book.authors collection. authorIds itself does not end with Id, so the parameter of @IdView annotation must be specified to explicitly indicate its original association is Book.authors. This is required in this case due to irregular noun pluralization in English.","s":"Declaring View Properties","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#declaring-view-properties","p":441},{"i":452,"t":"The emphasis on the word \"view\" above is intentional. IdView properties do not have their own data, they are just views of original association properties. info IdView properties and original association properties are linked. Setting one necessarily affects the other. Setting view property affects original property: Java Kotlin // Set view property Book book = Immutables.createBook(draft -> { draft.setStoreId(10L); draft.setAuthorIds(Arrays.asList(100L, 101L)); }); // Print original property System.out.println(\"Store: \" + book.store()); System.out.println(\"Authors:\" + book.authors()); // Set view property val book = Book { storeId = 10L authorIds = listOf(100L, 101L) } // Print original property println(\"Store: $book.store}\") println(\"Authors: ${book.authors}\") Prints: Store: {\"id\":10} Authors: [{\"id\":100},{\"id\":101}] Setting original property affects view property: Java Kotlin // Set original property Book book = Immutables.createBook(draft -> { draft.applyStore(store -> { store.setId(10L).storeName(\"TURING\") }); draft.addIntoAuthors(author -> { author.setId(101L); author.setFirstName(\"Fabrice\"); author.setLastName(\"Marguerie\"); }); draft.addIntoAuthors(author -> { author.setId(101L); author.setFirstName(\"Steve\"); author.setLastName(\"Eichert\"); }); }); // Print view property System.out.println(\"StoreId: \" + book.storeId()); System.out.println(\"AuthorIds:\" + book.authorIds()); // Set original property val book = Book { store { id = 10L name = \"TURING\" } authors().addBy { id = 100L; firstName = \"Fabrice\" lastName = \"Marguerie\" } authors().addBy { id = 101L firstName = \"Steve\" lastName = \"Eichert\" } } // Print view property println(\"Store: $book.storeId}\") println(\"Authors: ${book.authorIds}\") Prints: StoreId: 10 AuthorIds: [100, 101] tip This shows that view properties and original properties are highly unified. Jimmer is still a ORM framework that is core-associated-object-oriented. View properties are just syntactic sugar. Except for the impact on ObjectFetcher to be explained below, view properties do not affect ORM and core logic at all.","s":"Essence of View Properties","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#essence-of-view-properties","p":441},{"i":454,"t":"Java Kotlin Book book = bookRepository.findNullable( 1L, Fetchers.BOOK_FETCHER .allScalarFields() .storeId() .authorIds() ); System.out.println(book); val book = bookRepository.findNullable( 1L, newFetcher(Book::class).by { allScalarFields() storeId() authorIds() } ); System.out.println(book); Prints: { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"storeId\": 1, \"authorIds\":[1, 2] } tip For Jimmer dynamic entities, original association properties and view properties are absolutely consistent. Either both can be accessed, or both are missing. Whether choosing to fetch the original association property or choosing to fetch the IdView view property does not affect the underlying execution logic of Jimmer, including the ultimately generated SQL. The only difference brought by different choices is that the Jackson visibility flag of original association properties and view properties are different. That is, properties fetched directly will be serialized by Jackson, while properties not fetched directly will be ignored. Here is the English translation of the file, with the code indentation preserved:","s":"Fetching IdView Properties","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#fetching-idview-properties","p":441},{"i":456,"t":"caution Without the assistance of DTOs, hope that the entity itself can express associated ids, is the only scenario where it is appropriate to use @IdView. Other features make no assumptions about whether an association property has a corresponding @IdView property. Using associated IDs in the SQL DSL Even if an entity's one-to-one or many-to-one association property does not have a corresponding @IdView property, you can still use associated id expressions in the SQL DSL, for example: Java Kotlin where(table.storeId().eq(2L)); where(table.storeId eq 2L) Of course, if you are not satisfied with the auto-generated name for the associated id (e.g., storeId here), you can provide an @IdView property to change its name. Using associated ids in the DTO language The DTO language does not require @IdView properties at all. Even if an entity's associated property already has a corresponding @IdView property, it is not recommended to use it in the DTO language, as this is a fragile assumption. Once that @IdView property is removed, the DTO code cannot be correctly compiled until it is synchronized with the change. The DTO language should directly use the association properties, for example: export yourpackage.Book -> package yourpackage.dto input BookInput { allScalarFields() id(store) // as storeId id(authors) as authorIds } specification BookSpecification { like/i(name) associatedIdIn(store) as storeIds associatedIdNotIn(store) as excludedStoreIds }","s":"Do Not Abuse","u":"/jimmer-doc/docs/mapping/advanced/view/id-view","h":"#do-not-abuse","p":441},{"i":458,"t":"This chapter introduces how to use the @org.babyfish.jimmer.sql.OneToOne annotation to declare one-to-one association properties. One-to-one supports bidirectional association. For bidirectional associations, one side must be the owning side and the other side must be the inverse side: Owning side (required): The actual mapping between the database and association properties to implement unidirectional one-to-one association. Inverse side (optional): If a unidirectional association already exists, the inverse side can be configured as a mirror of the owning side to form a bidirectional association. Let's assume there are two entity types Customer and Address, and establish a bidirectional one-to-one association between them. info Unlike JPA/Hibernate, the owning side and inverse side can be chosen arbitrarily. Both can be used to persist associations. The example in this article chooses: Owning side (required): Customer.address Inverse side (optional): Address.customer","s":"One To One","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"","p":457},{"i":460,"t":"There are two ways to implement a one-to-one association: based on foreign key and based on join table.","s":"Owning Side","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#owning-side","p":457},{"i":462,"t":"Java Kotlin Customer.java @Entity public interface Customer { @OneToOne Address address(); ...Omit other code... } Customer.kt @Entity interface Customer { @OneToOne val address: Address ...Omit other code... } Here @JoinColumn is not used together to explicitly specify the foreign key column name. Jimmer will deduce the column name corresponding to the address property based on the naming strategy. If the default naming strategy is not overridden by the user, the foreign key column name of the address property is ADDRESS_ID. So the previous code is equivalent to: Therefore, the above code is equivalent to the following: Java Kotlin Customer.java @Entity public interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") Address address(); ...Omit other code... } Customer.kt @Entity interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") val address: Address ...Omit other code... } The foreign key can be real or fake. Fake foreign keys are discussed in subsequent documents. Here we assume the foreign key is real, so the corresponding constraint in the database is: // If foreign key pointing to associated entity is real, create foreign key constraint alter table CUSTOMER add constraint FK_CUSTOMER__ADDRESS foreign key(ADDRESS_ID) references ADDRESS(ID);","s":"1. Based on Foreign Key","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#1-based-on-foreign-key","p":457},{"i":464,"t":"Java Kotlin Customer.java @Entity public interface Customer { @Nullable @OneToOne @JoinTable Address address(); ... } Customer.kt @Entity interface Customer { @OneToOne @JoinTable val address: Address? ... } Here, no properties are specified for @JoinTable. Jimmer will deduce the column names corresponding to the address property based on the naming strategy. If the default naming strategy is not overridden by the user, the deduced join table information is: Join table name: CUSTOMER_ADDRESS_MAPPING Join table foreign key column pointing to current entity: CUSTOMER_ID Join table foreign key column pointing to associated entity: ADDRESS_ID So the previous code is equivalent to: Java Kotlin Customer.java @Entity public interface Customer { @Nullable @OneToOne @JoinTable( name = \"CUSTOMER_ADDRESS_MAPPING\", joinColumnName = \"CUSTOMER_ID\", inverseJoinColumnName = \"ADDRESS_ID\" ) Address address(); ... } Customer.kt @Entity interface Customer { @OneToOne @JoinTable( name = \"CUSTOMER_ADDRESS_MAPPING\", joinColumnName = \"CUSTOMER_ID\", inverseJoinColumnName = \"ADDRESS_ID\" ) val address: Address? ... } The join table CUSTOMER_ADDRESS_MAPPING is defined as follows: create table CUSTOMER_ADDRESS_MAPPING( CUSTOMER_ID bigint not null, ADDRESS_ID bigint not null ); alter table ADDRESS_MAPPING add constraint PK_ADDRESS_MAPPING primary(CUSTOMER_ID, ADDRESS_ID); // If foreign key pointing to current entity is real, // create foreign key constraint alter table CUSTOMER_ADDRESS_MAPPING add constraint FK_CUSTOMER_ADDRESS_MAPPING__CUSTOMER foreign key(CUSTOMER_ID) references CUSTOMER(ID); // If foreign key pointing to associated entity is real, // create foreign key constraint alter table CUSTOMER_ADDRESS_MAPPING add constraint FK_CUSTOMER_ADDRESS_MAPPING__ADDRESS foreign key(ADDRESS_ID) references ADDRESS(ID); // These two constraints are very important. // Otherwise this join table expresses a many-to-many association // rather than a one-to-one association alter table CUSTOMER_ADDRESS_MAPPING add constraint UQ_CUSTOMER_ADDRESS_MAPPING__CUSTOMER_ID unique(CUSTOMER_ID); alter table CUSTOMER_ADDRESS_MAPPING add constraint UQ_CUSTOMER_ADDRESS_MAPPING__ADDRESS_ID unique(ADDRESS_ID); The join table has only two foreign keys, both non-null. The join table maintains the association by inserting and deleting data, never storing null data itself. The join table has no corresponding ORM entity and does not need an independent primary key. The two foreign keys combined can serve as the primary key. By default, the join table represents a many-to-many association. To degrade it to a one-to-one association, a unique constraint must be specified for each foreign key of the join table. caution Unless for compatibility with existing database design, one-to-one associations are recommended to directly use foreign keys instead of join tables. Once a one-to-one association is mapped using a join table, the Jimmer association property must be nullable, because the database cannot guarantee that any entity must have corresponding data in the join table.","s":"2. Based on Join Table","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#2-based-on-join-table","p":457},{"i":466,"t":"The configuration of the inverse side is very simple: just specify that Address.customer is the mirror of Customer.address. In the following code: Left: The owning side discussed in the previous section Right: The inverse side association Address.customer introduced in this section, which is the mirror of Customer.address Here, @OneToOne(mappedBy = \"address\") indicates that the current property Address.customer is the mirror of Customer.address. Java Kotlin Customer.java @Entity public interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") Address address(); ...Omit other code... } Customer.kt @Entity interface Customer { @OneToOne @JoinColumn(name = \"ADDRESS_ID\") val address: Address ...Omit other code... } Java Kotlin Address.java @Entity public interface Address { // `mappedBy` indicates `Address.customer` // is the mirror of `Customer.address` @OneToOne(mappedBy = \"address\") @Nullable Customer customer(); ...Omit other code... } Address.kt @Entity interface Address { // `mappedBy` indicates `Address.customer` // is the mirror of `Customer.address` @OneToOne(mappedBy = \"address\") val customer: Customer? ...Omit other code... } caution Once the mappedBy property of @OneToOne is specified, annotations like @JoinColumn and @JoinTable must not be used. The one-to-one association property as the inverse side must be nullable.","s":"Inverse Side","u":"/jimmer-doc/docs/mapping/base/association/one-to-one","h":"#inverse-side","p":457},{"i":468,"t":"Through the discussion of Association Mapping, we know that association mapping requires a lot of foreign keys. There are two types of foreign keys in Jimmer: Real foreign key: There is a corresponding foreign key constraint in the database. Fake foreign key: It is a foreign key in the developer's mind, but there is no corresponding foreign key constraint in the database. info When saving data: Real foreign keys rely on the ability of relational databases themselves to ensure referential integrity. Fake foreign keys rely on additional checks inserted by the ORM in the upper layer code to ensure referential integrity. This difference is transparent to the user. The user only needs to configure the authenticity of the foreign key without modifying the business code.","s":"Real and Fake Foreign Keys","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"","p":467},{"i":470,"t":"Association property based on foreign key Java Kotlin Book.java @Entity public interface Book { @ManyToOne @JoinColumn(foreignKeyType = ForeignKeyType.REAL) BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(foreignKeyType = ForeignKeyType.REAL) val store: BookStore ...Omit other code... } Association property based on join table Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( joinColumns = {@JoinColumn(foreignKeyType = ForeignKeyType.REAL)}, inverseJoinColumns = {@JoinColumn(foreignKeyType = ForeignKeyType.REAL)} ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( joinColumns = [JoinColumn(foreignKeyType = ForeignKeyType.REAL)], inverseJoinColumns = [JoinColumn(foreignKeyType = ForeignKeyType.REAL)] ) val authors: List ...Omit other code... } info Different from previous examples: Configure JoinTable.joinColumns instead of JoinTable.joinColumnName If the foreign key has only one column and the authenticity does not need to be explicitly specified, joinColumnName is a simplified configuration. Otherwise, joinColumns should be used. Configure JoinTable.inverseJoinColumns instead of JoinTable.inverseJoinColumnName If the foreign key has only one column and the authenticity does not need to be explicitly specified, inverseJoinColumnName is a simplified configuration. Otherwise, inverseJoinColumns should be used. caution If the database dialect does not support foreign keys (e.g. org.babyfish.jimmer.sql.dialect.TiDBDialect), real foreign keys cannot be explicitly specified. This is because TiDB, as a distributed relational database, does not support foreign key constraints.","s":"Explicitly specify real foreign key","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"#explicitly-specify-real-foreign-key","p":467},{"i":472,"t":"Association property based on foreign key Java Kotlin Book.java @Entity public interface Book { @ManyToOne @Nullable @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) BookStore store(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToOne @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) val store: BookStore? ...Omit other code... } Association property based on join table Java Kotlin Book.java @Entity public interface Book { @ManyToMany @JoinTable( joinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE), inverseJoinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) ) List authors(); ...Omit other code... } Book.kt @Entity interface Book { @ManyToMany @JoinTable( joinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE), inverseJoinColumns = @JoinColumn(foreignKeyType = ForeignKeyType.FAKE) ) val authors: List ...Omit other code... }","s":"Explicitly specify fake foreign key","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"#explicitly-specify-fake-foreign-key","p":467},{"i":474,"t":"To avoid explicitly specifying the authenticity of foreign keys, use @JoinColumn(foreignKeyType = ForeignKeyType.AUTO). Since ForeignKeyType.AUTO is the default configuration for the @JoinColumn annotation, an even better choice is to make no configuration at all. Therefore, the code is no different from the sample code in Association Mapping, so there is no need for sample code here. If the authenticity of the foreign key is not explicitly specified, whether the foreign key is real or fake is automatically determined by the following two steps: If the database dialect does not support foreign keys (e.g. org.babyfish.jimmer.sql.dialect.TiDBDialect), it is determined to be a fake foreign key. At this point, the judgment is completed and it returns early without executing step 2. If step 1 cannot complete the determination, check Jimmer's global configuration is-foreign-key-enabled-by-default. If this configuration is true, it is determined to be a real foreign key; otherwise, it is determined to be a fake foreign key. The default value of this configuration is true. Users can override it to false: When using SpringBoot Modify application.yml or application.properties and set jimmer.is-foreign-key-enabled-by-default to false When not using SpringBoot Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setForeignKeyEnabledByDefault(false) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setForeignKeyEnabledByDefault(false) ...Omit other configurations... }","s":"Do not explicitly specify the authenticity of foreign keys","u":"/jimmer-doc/docs/mapping/base/foreignkey","h":"#do-not-explicitly-specify-the-authenticity-of-foreign-keys","p":467},{"i":476,"t":"In addition to boolean, number, string, UUID, date, and enumeration, scalar properties also support other types, including: Array types JSON types Custom types info Enum types are not discussed in this article, please refer to Enum Mapping","s":"More Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"","p":475},{"i":478,"t":"warning To use array types, the underlying database must support array types Java Kotlin @Entity public interface Book { @Id long id(); String[] tags(); } @Entity interface Book { @Id val id: Long val tags: Array } For Postgres, you need to specify the data element type in SQL, for example: Java Kotlin @Entity public interface Book { @Id long id(); @Column(sqlElementType = \"text\") String[] tags(); } @Entity interface Book { @Id val id: Long @Column(sqlElementType = \"text\") val tags: Array }","s":"Array Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"#array-types","p":475},{"i":480,"t":"You can use Jackson to support scalar properties of any type, whether it's a custom Java/Kotlin type, a collection type, or even a mix of the two. Just use the @org.babyfish.jimmer.sql.Serialized annotation, and you can use the JSON type. Here, the usage is demonstrated using a collection type as an example: Java Kotlin @Entity public interface Book { @Id long id(); @Serialized Map>> data(); } @Entity interface Book { @Id val id: Long @Serialized val data: Map>> } So what SQL type does the JSON type correspond to? If the database supports the JSON or JSONB type, use that type Otherwise, please use the string type For Postgres, it supports operations on the internal structure of JSON, please see JSON Operations in Postgres. How should Jimmer implement such operations? Jimmer's SQL DSL can mix in Native SQL expressions, please see Native Expressions, this article will not repeat it. Note: caution JSON Operations in Postgres use ?, which happens to be the parameter for JDBC, please use ?? instead.","s":"JSON Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"#json-types","p":475},{"i":482,"t":"If the JSON type still cannot meet your requirements (e.g., you expect to map some Postgres-specific types), you can use ScalarProvider to customize types. Please refer to ScalarProvider, this article will not repeat it.","s":"Custom Types","u":"/jimmer-doc/docs/mapping/base/more-type","h":"#custom-types","p":475},{"i":485,"t":"In previous chapters, we have introduced simple entity mapping and association mapping (one-to-one, many-to-one, one-to-many, many-to-many). From these contents, we understand that @Table(name = \"...\") can be used to explicitly specify the table name for an entity. @GeneratedValue(..., sequenceName = \"...\") can be used to explicitly specify the sequence name required to generate the id (if using sequence generation strategy). @Column(name = \"...\") can be used to explicitly specify the column name for ordinary columns. @JoinColumn(name = \"...\") can be used to explicitly specify the column name for foreign key columns. @JoinTable(name = \"...\") can be used to explicitly specify the join table name and all its column names for association properties based on join tables. However, in order to improve development efficiency, it is impossible to use these annotations too much. In most cases, the default name deduction behavior should work, and these annotations should only be used in code in a few cases. For a given class or property, how to automatically determine the identifier name in the database if the user does not use such annotations is called the naming strategy, which is a customizable Java interface: package org.babyfish.jimmer.sql.meta; import org.babyfish.jimmer.meta.ImmutableProp; import org.babyfish.jimmer.meta.ImmutableType; public interface DatabaseNamingStrategy { String tableName(ImmutableType type); String sequenceName(ImmutableType type); String columnName(ImmutableProp prop); String foreignKeyColumnName(ImmutableProp prop); String middleTableName(ImmutableProp prop); String middleTableBackRefColumnName(ImmutableProp prop); String middleTableTargetRefColumnName(ImmutableProp prop); } Among them, ImmutableType and ImmutableProp are the types used by Jimmer metadata and can be intuitively understood by analogy with Class and Field in JVM reflection API. The role of each method is: tableName: Given an entity type, what is its table name? sequenceName: Given an entity type whose ID growth strategy is sequence, what is its sequence name? columnName: Given a non-associative property, what is its column name? foreignKeyColumnName: Given an association property based on foreign key, what is its column name? middleTableName: Given an association property based on join table, what is its join table name? middleTableBackRefColumnName: Given an association property based on join table, what is the column name of the foreign key pointing to the current entity in the join table? middleTableTargetRefColumnName: Given an association property based on join table, what is the column name of the foreign key pointing to the associated entity in the join table?","s":"Naming Strategy Interface","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#naming-strategy-interface","p":483},{"i":487,"t":"In most cases, developers do not need to implement this interface directly. Jimmer's built-in org.babyfish.jimmer.sql.runtime.DefaultDatabaseNamingStrategy class already implements this interface. The DefaultDatabaseNamingStrategy class has two static fields: UPPER_CASE: The generated database identifier names are all uppercase. info If the user does not do any configuration, this is the default naming strategy for Jimmer. LOWER_CASE: The generated database identifier names are all lowercase. Some databases, such as MySQL, can be configured for case sensitivity. So it is very likely that you will be handling a MySQL database that is configured to be case sensitive with most table and column names in lowercase. In this case, you need to override the default strategy with this strategy. tip Even if neither UPPER_CASE nor LOWER_CASE meets your requirements and you need to implement your own strategy, you can also consider inheriting this default strategy instead of implementing from scratch. Before introducing the behavior of the default strategy, let's first introduce a character transformation rule: snake case. The so-called snake case refers to converting alternating case text into underscore-concatenated text, e.g. the snake case of class name BookStore is BOOK_STORE, and the snake case of property name firstName is FIRST_NAME. Considering case issues, we define two functions u_snake and l_snake with the following behaviors: u_snake(\"BookStore\") -> \"BOOK_STORE\" l_snake(\"BookStore\") -> \"book_store\" u_snake(\"firstName\") -> \"FIRST_NAME\" l_snake(\"firstName\") -> \"first_name\" With the conventions of u_snake and l_snake, it is easy to describe the behavior of DefaultDatabaseNamingStrategy: note ClassName below refers to the SimpleName of the Java class, not the QualifiedName.","s":"Default Naming Strategy","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#default-naming-strategy","p":483},{"i":489,"t":"tableName Rule: u_snake(ClassName) Example: BookStore -> BOOK_STORE sequenceName Rule: u_snake(ClassName)_ID_SEQ Example: BookStore -> BOOK_STORE_ID_SEQ columnName Rule: u_snake(ClassName) Example: firstName -> FIRST_NAME foreignKeyColumnName Rule: u_snake(ClassName)_ID Example: parentNode -> PARENT_NODE_ID middleTableName Rule: u_snake(SourceClassName)_u_snake(TargetClassName)_MAPPING Example: Book::authors -> BOOK_AUTHOR_MAPPING middleTableBackRefColumnName Rule: u_snake(SourceClassName)_ID Example: Book::authors -> BOOK_ID middleTableTargetRefColumnName Rule: u_snake(TargetClassName)_ID Example: Book::authors -> AUTHOR_ID","s":"UPPER_CASE","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#upper_case","p":483},{"i":491,"t":"tableName Rule: l_snake(ClassName) Example: BookStore -> book_store sequenceName Rule: l_snake(ClassName)_id_seq Example: BookStore -> book_store_id_seq columnName Rule: l_snake(ClassName) Example: firstName -> first_name foreignKeyColumnName Rule: l_snake(ClassName)_id Example: parentNode -> parent_node_id middleTableName Rule: l_snake(SourceClassName)_l_snake(TargetClassName)_mapping Example: Book::authors -> book_author_mapping middleTableBackRefColumnName Rule: l_snake(SourceClassName)_id Example: Book::authors -> book_id middleTableTargetRefColumnName Rule: l_snake(TargetClassName)_id Example: Book::authors -> author_id","s":"LOWER_CASE","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#lower_case","p":483},{"i":493,"t":"Now let's demonstrate how to override the default DefaultDatabaseNamingStrategy.UPPER_CASE with DefaultDatabaseNamingStrategy.LOWER_CASE.","s":"Override Strategy","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#override-strategy","p":483},{"i":495,"t":"Java Kotlin @Bean public DatabaseNamingStrategy databaseNamingStrategy() { return DefaultDatabaseNamingStrategy.LOWER_CASE; } @Bean fun databaseNamingStrategy(): DatabaseNamingStrategy = DefaultDatabaseNamingStrategy.LOWER_CASE","s":"When using SpringBoot","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#when-using-springboot","p":483},{"i":497,"t":"Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDatabaseNamingStrategy( DefaultDatabaseNamingStrategy.LOWER_CASE ) ...Omit other configurations... .build(); val sqlClient = newKSqlClient { setDatabaseNamingStrategy( DefaultDatabaseNamingStrategy.LOWER_CASE ) ...Omit other configurations... }","s":"When not using SpringBoot","u":"/jimmer-doc/docs/mapping/base/naming-strategy","h":"#when-not-using-springboot","p":483},{"i":499,"t":"In this section, we will introduce all the capabilities in Jimmer related to modifying the database. There are two groundbreaking capabilities: Save Command One statement to save complex data of arbitrary shape, find DIFF to change database, like React/Vue. Triggers Awareness of data changes whether via Jimmer's own capabilities or integrating with existing CDC solutions. This enables automatic Caching invalidation.","s":"Modification","u":"/jimmer-doc/docs/mutation/","h":"","p":498},{"i":501,"t":"Jimmer handles the issue of whether entity object properties can be null in a very strict way. Even for Java developers, it requires thinking about whether each property can be null in the same way as Kotlin developers. caution Explicitly stating whether each property of the entity object allows null is very important for Jimmer and affects many features.","s":"Nullity","u":"/jimmer-doc/docs/mapping/base/nullity","h":"","p":500},{"i":504,"t":"Kotlin supports null safety. Declaring entity properties as T for non-null and T? for nullable according to Kotlin's own way.","s":"Kotlin","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#kotlin","p":500},{"i":506,"t":"Whether a property is null in Java is determined by the following rules: If the property type is boolean, char, byte, short, int, long, float or double, then it is non-null. If the property type is Boolean, Character, Byte, Short, Integer, Long, Float or Double, then it is nullable. Otherwise If the property is decorated by any annotation simply named Nullable or Null, then it is nullable. Otherwise, the default is non-null. note It is recommended to use org.jetbrains.annotations.Nullable, because Although recognizable annotations are not restricted, if an annotation not included by default in the Jimmer annotation processor is used, its dependency needs to be added to the annotation processor, which is troublesome after all. org.jetbrains.annotations.Nullable is supported by Intellij.","s":"Java","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#java","p":500},{"i":508,"t":"info A series of concepts not explained yet will appear here. They will all be explained in subsequent documents. Here is just a simple list of precautions. Please ignore these terms for now. This document does not provide related examples either. Come back and check after you understand all subsequent concepts. The @Id property must be non-null. Very different from JPA/Hibernate. JPA/Hibernate recommends declaring the id property as a nullable type, e.g. Long instead of long in Java, so that the absence of id and the need for automatic allocation can be expressed when saving data. Jimmer must declare the id property as a non-null type, e.g. long instead of Long in Java. Jimmer relies on the dynamism of the entity objects themselves to express the absence of the id property. One-to-many and many-to-many properties must be non-null. One-to-many and many-to-many properties are represented by collections of length 0 instead of null when there is no data. One-to-one and many-to-one properties must be nullable when any of the following conditions is met: Mapping based on join table, rather than foreign key Mapping based on pseudo foreign key, rather than real foreign key info A \"pseudo foreign key\" refers to a foreign key in the developer's mind, but there is no corresponding foreign key constraint in the database. Remote association As the mirror side of @OneToOne association If the associated entity has global filters applied, then for one-to-one/many-to-one associations must be nullable even if they are directly based on foreign keys, unless all of the following conditions are met: All global filters applied to the associated entity implement the AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter interface. All global filters applied to the associated entity are also applied to the current entity.","s":"Precautions","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#precautions","p":500},{"i":510,"t":"As mentioned before, due to some query scenarios, one-to-one and many-to-one properties based on foreign keys must be declared as nullable. However, when saving data, developers may not expect users to modify the foreign key fields in the database to null. In this case, inputNotNull of @OneToOne or @ManyToOne can be set to true, for example: @OneToOne(inputNotNull = true) @ManyToOne(inputNotNull = true) If inputNotNull is configured for an associated property, it will be given priority consideration in database validation to verify that the foreign key field in the database cannot be null.","s":"inputNotNull","u":"/jimmer-doc/docs/mapping/base/nullity","h":"#inputnotnull","p":500},{"i":513,"t":"The @Entity annotation is used to decorate immutable interfaces to represent ORM entities. Java Kotlin Book.java @Entity public interface Book { ...Omit other code... } Book.kt @Entity interface Book { ...Omit other code... } info Why are entity types interfaces instead of classes? Jimmer entities have dynamic shapes and immutability, which are not simple POJOs with intricate internal workings that cannot be accomplished manually or with lombok assistance. So Jimmer lets developers write interfaces that are implemented at compile time by preprocessors (AnnotationProcessor for Java, KSP for Kotlin).","s":"@Entity","u":"/jimmer-doc/docs/mapping/base/basic","h":"#entity","p":511},{"i":515,"t":"The @Table annotation specifies the table name for the entity. If @Table annotation is not used, e.g. Java Kotlin BookStore.java @Entity public interface BookStore { ...Omit other code... } BookStore.kt @Entity interface BookStore { ...Omit other code... } Jimmer will deduce the table name corresponding to the BookStore interface based on the naming strategy. If the default naming strategy is not overridden by the user, the table name for interface BookStore is BOOK_STORE. So the previous code is equivalent to: Java Kotlin BookStore.java @Entity @Table(name = \"BOOK_STORE\") public interface BookStore { ...Omit other code... } BookStore.kt @Entity @Table(name = \"BOOK_STORE\") interface BookStore { ...Omit other code... }","s":"@Table","u":"/jimmer-doc/docs/mapping/base/basic","h":"#table","p":511},{"i":517,"t":"The @Column annotation specifies the database column for ordinary non-associative properties. If @Column annotation is not used, e.g. Java Kotlin Author.java @Entity public interface BookStore { String firstName(); ...Omit other code... } Author.kt @Entity interface Author { val firstName: String ...Omit other code... } Jimmer will deduce the column name corresponding to the firstName property based on the naming strategy. If the default naming strategy is not overridden by the user, the column name for property firstName is FIRST_NAME. So the previous code is equivalent to: Java Kotlin Author.java @Entity public interface BookStore { @Column(name = \"FIRST_NAME\") String firstName(); ...Omit other code... } Author.kt @Entity interface Author { @Column(name = \"FIRST_NAME\") val firstName: String ...Omit other code... } caution @Column is only used to explicitly specify column names for non-associative properties. For foreign key column names of many-to-one or one-to-one association properties, they must be specified through @JoinColumn. See Association Mapping for more.","s":"@Column","u":"/jimmer-doc/docs/mapping/base/basic","h":"#column","p":511},{"i":519,"t":"Declare a property as the id property, as follows Java Kotlin Book.java @Entity public interface Book { @Id long id(); } Book.kt @Entity interface Book { @Id val id: Long } caution The id field must be non-null (for Java, long is used here instead of Long) Unlike JPA, which encourages declaring the id as a nullable type, Jimmer does not use this method to express not specifying the id during data insertion. The dynamism of Jimmer objects themselves can easily express this problem. See Nullity for details.","s":"@Id","u":"/jimmer-doc/docs/mapping/base/basic","h":"#id","p":511},{"i":521,"t":"In the previous example, the primary key property decorated with @Id is a business field that must be specified when inserting data. However, more often, we expect that the primary key property itself has no business meaning, so that it can be unspecified when inserting data and automatically generated instead. The automatic id generation strategies are: Database autoincrement Database sequence UUID Snowflake ID @GeneratedValue works with @Id to specify auto growth strategy for Id.","s":"@GeneratedValue","u":"/jimmer-doc/docs/mapping/base/basic","h":"#generatedvalue","p":511},{"i":523,"t":"Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long }","s":"Database autoincrement","u":"/jimmer-doc/docs/mapping/base/basic","h":"#database-autoincrement","p":511},{"i":525,"t":"Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.SEQUENCE) val id: Long } Here, the sequence name in the database is not specified through the sequenceName of @GeneratorValue. Jimmer will deduce the sequence name based on the naming strategy. If the default naming strategy is not overridden by the user, the sequence name here is BOOK_ID_SEQ. So the previous code is equivalent to: Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue( strategy = GenerationType.SEQUENCE, sequenceName = \"BOOK_ID_SEQ\" ) long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue( strategy = GenerationType.SEQUENCE, sequenceName = \"BOOK_ID_SEQ\" ) val id: Long }","s":"Database sequence","u":"/jimmer-doc/docs/mapping/base/basic","h":"#database-sequence","p":511},{"i":527,"t":"Setting the generatorType property of @GeneratedValue to org.babyfish.jimmer.sql.meta.UUIDIdGenerator can be used to randomly generate UUIDs Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(generatorType = UUIDIdGenerator.class) UUID id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(generatorType = UUIDIdGenerator::class) val id: UUID }","s":"UUID","u":"/jimmer-doc/docs/mapping/base/basic","h":"#uuid","p":511},{"i":529,"t":"When the above Id growth strategies cannot meet the requirements, a custom Id generation strategy can be defined. Jimmer provides an UserIdGenerator interface UserIdGenerator.java package org.babyfish.jimmer.sql.meta; public interface UserIdGenerator extends IdGenerator { T generate(Class entityType); } Users can implement this interface to implement any Id generation algorithm, including snowflake ID. MyGenerator.java package com.mycompany.myproject.common; public class MyIdGenerator implements UserIdGenerator { @Override public Long generate(Class entityType) { return ...Omit custom id generation logic... } } Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(generateType = MyIdGenerator.class) Long id(); } Book.kt @Entity interface Book { @Id @GeneratedValue(generateType = MyIdGenerator::class) val id: Long } caution The user-implemented Id generation class MyIdGenerator itself does not have generic parameters, but generic parameters must be specified for the super interface UserIdGenerator. The type of the decorated Id property must be consistent with this generic parameter, otherwise an exception will be thrown.","s":"Custom IdGenerator","u":"/jimmer-doc/docs/mapping/base/basic","h":"#custom-idgenerator","p":511},{"i":532,"t":"The usage of the delete statement is: Java Kotlin BookTable book = Tables.BOOK_TABLE; int affectedRowCount = sqlClient .createDelete(book) .where(book.name().eq(\"Learning GraphQL\")) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createDelete(Book::class) { where(table.name eq \"Learning GraphQL\") } .execute() println(\"Affected row count: $affectedRowCount\") The generated SQL is: delete from BOOK as tb_1_ where tb_1_.NAME = ?","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/delete-statement","h":"#basic-usage","p":530},{"i":534,"t":"The delete statement usage below supports JOIN clauses, as follows: Java Kotlin BookTable book = Tables.BOOK_TABLE; int affectedRowCount = sqlClient .createDelete(book) .where(book.store().name().eq(\"MANNING\")) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createDelete(Book::class) { where(table.store.name eq \"MANNING\") } .execute() println(\"Affected row count: $affectedRowCount\") The finally generated SQL is: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? delete from BOOK_AUTHOR_MAPPING where BOOK_ID in(?, ?, ?) delete from BOOK where ID in(?, ?, ?) note If JOIN is used in a delete statement, Jimmer will translate it into select + delete. First use the select statement with join clause to query the ids of the data to be deleted, then use Delete Command to delete the data. This scheme is valid for any database.","s":"Using JOIN","u":"/jimmer-doc/docs/mutation/delete-statement","h":"#using-join","p":530},{"i":536,"t":"caution In recent months, the save instruction has undergone a major restructuring, so there hasn't been time to update all the documentation in this directory. Apart from new features, the new version of the save instruction has made minimal changes to existing functionality, and it remains largely consistent with the description in this directory. However, the new version of the save instruction generates SQL with much higher performance than described here. The good news is that this historically significant restructuring of Jimmer has finally been completed and stabilized, so all the content in this directory will be updated soon. tip One statement to save complex data of arbitrary shape, find DIFF to change database, like React/Vue Save commands are a very powerful capability of Jimmer that can greatly simplify the development difficulty of persisting complex data structures. If object fetchers enable output data to be in any shape, then save commands allow input data to also be in any shape. For readers familiar with web frontend technologies, this can be analogized to Virtual DOM diff in React or Vue. tip Save command require developers to completely change their thinking pattern Fundamental difference in thinking The traditional thinking pattern: Manually compare the data structure to be saved with existing data in the database, and execute INSERT, UPDATE or DELETE on the changed parts The thinking pattern for save command: Accept the data structure passed from client as a whole and just save it. Jimmer will handle everything (automatically compare the data structure to be saved with existing data in the database, and execute INSERT, UPDATE or DELETE on the changed parts) Old habits should be replaced by better methods In the traditional development mode, developers like to do one thing: query an object first, then modify some of its properties, and finally save the modified object. Although Jimmer also allows developers to do this, it is recommended to use a more performant approach, please refer to Incomplete Object. Calling a save command only takes one line of code, but hides countless details internally that documentation cannot exhaustively enumerate. Therefore, save commands have a dedicated sample project: Java: jimmer-examples/java/save-command Kotlin: jimmer-examples/kotlin/save-command-kt Simply open either one in an IDE, and run the unit tests.","s":"Save Command","u":"/jimmer-doc/docs/mutation/save-command/","h":"","p":535},{"i":540,"t":"The delete command deletes objects by id or id collection. API Category Language Delete by Id Delete by Id Collection Low Level API Java Full API JSqlClient.getEntities().delete JSqlClient.getEntities().deleteCommand Shortcut API JSqlClient.deleteById Full API JSqlClient.getEntities().deleteAll JSqlClient.getEntities().deleteAllCommand Shortcut API JSqlClient.deleteByIds Kotlin Full API KSqlClient.entities.delete Shortcut API KSqlClient.deleteById Full API KSqlClient.entities.deleteAll Shortcut API KSqlClient.deleteByIds Spring Data API Java JRepository.deleteById JRepository.deleteByIds JRepository.deleteAllById Kotlin KRepository.deleteById KRepository.deleteByIds KRepository.deleteAllById Necessary Explanations: In the Java low-level API there are two methods ending in Command: deleteCommand and deleteAllCommand. These two methods create commands but do not execute them immediately. After the user does more configuration on the command, calling execute executes it. Take deleteCommand as an example: DeleteResult result = sqlClient .getEntities() .deleteCommand(BookStore.class, 1L) ❶ .setDissociateAction(BookProps.STORE, DissociateAction.SET_NULL) ❷ .execute(); ❸ ❶ Create the command, but do not execute it. ❷ Configure the command, can be chained with multiple configurations (here only one configuration is demoed) info The effect of this configuration will be explained later, readers can ignore it for now. ❸ Finally execute it. Kotlin does not need such a design, because its delete method supports an optional Lambda parameter for configuration. Simply execute with the necessary configuration: val result = sqlClient .entities .delete(BookStore::class, 1L) { setDissociateAction(Book::store, DissociateAction.SET_NULL) } In the Spring Data API we can find two methods with the same functionality but different names: deleteByIds and deleteAllById. deleteByIds: A method consistent in style with the Jimmer low-level shortcut API. deleteAllById: A required method when inheriting org.springframework.data.repository.CrudRepository, can be understood as an alias of deleteByIds. The delete command supports two types of operations: Logical delete: Does not actually delete data, just marks the logical delete field of the object as \"deleted\". Physical delete: Actually deletes data. All the above APIs support an optional parameter of type DeleteMode through Java method overloading or Kotlin default parameters. This parameter type is an enum with three possible values: AUTO: Does not explicitly specify whether the current operation is logical delete or physical delete If the deleted entity type has a logical delete field, perform logical delete. Otherwise, perform physical delete. LOGICAL: Explicitly specifies that the current operation is logical delete If the deleted entity type has a logical delete field, perform logical delete. Otherwise, throw an exception indicating that the current entity does not support logical delete. PHYSICAL: Explicitly specifies that the current operation is physical delete Regardless of whether the deleted entity type has a logical delete field, perform physical delete.","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/delete-command","h":"#basic-concepts","p":538},{"i":542,"t":"Assuming the entity has a logical delete field, for example: Java Kotlin Book.java @Entity public interface Book { @LogicalDeleted(\"true\") boolean isDeleted(); ...other code omitted... } Book.kt @Entity interface Book { @LogicalDeleted(\"true\") val isDeleted: Boolean ...other code omitted... } Then the following three behaviors: sqlClient.deleteById(Book.class, 1L) sqlClient.deleteById(Book.class, 1L, DeleteMode.AUTO) sqlClient.deleteById(Book.class, 1L, DeleteMode.LOGICAL) have the same function, they all represent logical delete, and generate the following sql: update BOOK set DELETED = ? /* true */ where ID in(?/* 1L*/)","s":"Logical Delete","u":"/jimmer-doc/docs/mutation/delete-command","h":"#logical-delete","p":538},{"i":544,"t":"If the entity does not have a logical delete field, or the delete mode is explicitly specified as DeleteMode.PHYSICAL, physical delete is performed.","s":"Physical Delete","u":"/jimmer-doc/docs/mutation/delete-command","h":"#physical-delete","p":538},{"i":546,"t":"Java Kotlin DeleteResult result = sqlClient .getEntities() .deleteAll(Book.class, Arrays.asList(1L, 2L, 3L, 4L)); System.out.println( \"Affected row count: \" + result.getTotalAffectedRowCount() + \"\\nAffected row count of table 'BOOK': \" + result.getAffectedRowCount(AffectedTable.of(Book.class)) + \"\\nAffected row count of middle table 'BOOK_AUTHOR_MAPPING': \" + result.getAffectedRowCount(AffectedTable.of(BookProps.AUTHORS)) ); val result = sqlClient .entities .deleteAll(Book::class, listOf(1L, 2L, 3L, 4L)) println( \"\"\"Affected row count: |${result.totalAffectedRowCount} |Affected row count of table 'BOOK': |${result.affectedRowCount(Book::class)} |Affected row count of middle table 'BOOK_AUTHOR_MAPPING': |${result.affectedRowCount(Book::authors)} \"\"\".trimMargin() ) The finally generated SQL is: delete from BOOK_AUTHOR_MAPPING where BOOK_ID in(?, ?, ?, ?) delete from BOOK where ID in(?, ?, ?, ?)","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/delete-command","h":"#basic-usage","p":538},{"i":548,"t":"From the above discussion we can see that the delete command may cause data in many-to-many association middle tables to be deleted, which is a relatively simple case. For one-to-one or one-to-many associations directly based on foreign keys, the situation to be handled is a little more complex. Java Kotlin DeleteResult result = sqlClient .getEntities() .delete(BookStore.class, 1L); System.out.println( \"Affected row count: \" + result.getTotalAffectedRowCount() + \"\\nAffected row count of table 'BOOK_STORE': \" + result.getAffectedRowCount(AffectedTable.of(BookStore.class)) + \"\\nAffected row count of table 'BOOK': \" + result.getAffectedRowCount(AffectedTable.of(Book.class)) + \"\\nAffected row count of middle table 'BOOK_AUTHOR_MAPPING': \" + result.getAffectedRowCount(AffectedTable.of(BookProps.AUTHORS)) ); val result = sqlClient .entities .delete(BookStore::class, 1L) println( \"\"\"Affected row count: |${result.totalAffectedRowCount} |Affected row count of table 'BOOK_STORE': |${result.affectedRowCount(BookStore::class)} |Affected row count of table 'BOOK': |${result.affectedRowCount(Book::class)} |Affected row count of middle table 'BOOK_AUTHOR_MAPPING': |${result.affectedRowCount(Book::authors)} \"\"\".trimMargin() ) This code deletes a BookStore object. Because the BookStore object has a one-to-many association BookStore.books, if the object being deleted already has some associated objects in the database, Jimmer will discard those objects. The one-to-many association BookStore.books is not a mapping based on a middle table, but a mapping based on a foreign key. How will Jimmer discard those Book objects? Unlike JPA, Jimmer does not allow direct use of @OneToMany for association mapping. @OneToMany must use the mappedBy property. See @OneToMany to learn more. This means that through the one-to-many association BookStore.books we can certainly find the corresponding many-to-one association Book.store. Next, Jimmer will refer to the @OnDissociate annotation on the many-to-one association property Book.store. There are 5 modes for child object dissociation operations Mode Description NONE (Default) Depends on global configuration jimmer.default-dissociate-action-checking If jimmer.default-dissociate-action-checking is true (default) or the foreign key upon which the current association is based is real (foreign key constraint exists in database, see Real and Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-checking is false and the foreign key upon which the current association is based is fake (no corresponding foreign key constraint in database, see Real and Fake Foreign Keys), treated as LAX. LAX Dissociation operation performs no action. If the foreign key is real (see Real and Fake Foreign Keys), when parent object is deleted: If cascade delete behavior is configured for the database foreign key (on cascade set null or on delete delete), database automatically clears the foreign key of dissociated child objects or automatically deletes the dissociated child objects Although database-level cascade modification performs better than ORM-level cascade modification, the ORM is unaware of this. Use with caution in projects requiring cache consistency Otherwise, database reports an error and the save command is terminated If the foreign key is fake (see Real and Fake Foreign Keys), when parent object is deleted, no additional behavior occurs, allowing dangling issues with child object foreign key values Even if fake foreign key values are invalid dangling values, jimmer queries won't error - the query system will return null for parent objects rather than error due to non-existent parent CHECK Does not support dissociation operations. Throws exception to prevent operation if current parent object in database has child objects that need to be dissociated. SET_NULL Sets the foreign key of dissociated child objects to null. This mode requires that the child object's foreign key property is nullable; otherwise attempting this configuration will cause an exception. DELETE Deletes the dissociated child objects.","s":"Dissociate Mode","u":"/jimmer-doc/docs/mutation/delete-command","h":"#dissociate-mode","p":538},{"i":550,"t":"If the foreign key corresponding to Book.store is configured by the @OnDissociate annotation as SET_NULL, the following SQL is executed: update BOOK set STORE_ID = null where STORE_ID in(?) where the parameter is the id of the deleted object. Thus, the foreign keys of these discarded objects are set to null. Otherwise, first execute: select ID from BOOK where STORE_ID in(?) where the parameter is the id of the deleted object. Thus, the ids of these discarded objects are obtained. If the query does not return any data, skip the subsequent steps. If the foreign key corresponding to Book.store is configured by @OnDissociate as DELETE, use the new delete command to delete these discarded objects. This is actually the automatic recursive execution capability of the delete command. Otherwise, throw an exception. The above discussed situations all require the developer to use the @OnDissociate annotation on the Book.store property. However, you can also choose not to use the @OnDissociate annotation, but dynamically specify the dissociateAction configuration for the delete command. Java Kotlin DeleteResult result = sqlClient .getEntities() .deleteCommand(BookStore.class, 1L) .configure(it -> it .setDissociateAction( BookProps.STORE, DissociateAction.SET_NULL ) ) .execute(); val result = sqlClient .entities .delete(BookStore::class, 1L) { setDissociateAction( Book::store, DissociateAction.SET_NULL ) } Here, calling the command's setDissociateAction method dynamically has the same effect as using the @OnDissociate annotation statically on the Book.store property and specifying cascade delete. info If the last parameter of the setDissociateAction method is DissociateAction.SET_NULL, the associated property being set must be nullable, otherwise it will cause an exception. If dissociation rules are configured dynamically for the save command and also configured statically in the entity interface through the @OnDissociate annotation, the dynamic configuration takes precedence.","s":"Dissociation Examples","u":"/jimmer-doc/docs/mutation/delete-command","h":"#dissociation-examples","p":538},{"i":552,"t":"Although Jimmer entities are not POJOs, Jackson serialization can be supported by org.babyish.jimmer.jackson.ImmutableModule. tip If using the Jimmer Spring Boot Starter, this ImmutableModule will be automatically registered without user intervention. However, sometimes we need to customize the Jackson serialization behavior of certain properties. We give two examples here. Snowflake ID Data Masking","s":"JSON Converter","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"","p":551},{"i":554,"t":"Snowflake IDs lead to very large int64 values that unfortunately cannot be represented by JavaScript's number type. Therefore, we have no choice but to serialize such id properties as strings.","s":"1. Snowflake ID","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#1-snowflake-id","p":551},{"i":556,"t":"Java Kotlin @Entity @public interface Book { @Id @GeneratedValue(generatorType = SnowflakeIdGenerator.class) @JsonConverter(LongToStringConverter.class) long id(); String name(); ...Omit other properties... } @Entity @public interface Book { @Id @GeneratedValue(generatorType = SnowflakeIdGenerator.class) @JsonConverter(LongToStringConverter.class) long id(); String name(); ...Omit other properties... } Where SnowflakeIdGenerator is a user-provided distributed snowflake ID generator implementation, which is not the focus of our discussion. Here, we discuss the highlighted line: @org.babyfish.jimmer.jackson.JsonConverter indicates custom Jackson serialization/deserialization behavior for the Book.id property. org.babyfish.jimmer.jackson.LongToStringConverter means serialize/deserialize the long value as a String. LongToStringConverter is a built-in Converter in Jimmer. Here we show its source code to quickly understand how to customize Converter. package org.babyfish.jimmer.jackson; public class LongToStringConverter implements Converter { // How to serialize @Override public String output(Long value) { return Long.toString(value); } // How to deserialize @Override public Long input(String jsonValue) { return Long.parseLong(jsonValue); } } tip Note: Jimmer annotations rather than Jackson annotations are used here, because: This is not only an adjustment of the serialization framework Jackson, but also a useful adjustment of Automatic client/server integration DTO language No need to consider null values ​​inside Converter, null values ​​will never be passed as an argument to any Converter method. Here, bypassing ORM, we demonstrate the effect by simulating data. Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(1546434604146774987L); draft.setName(\"SQL in Action\"); }); System.out.println(book); val book = Book { id = 1546434604146774987L name = \"SQL in Action\" } println(book) Since the toString of Jimmer entities is Jackson serialization, we can print directly and observe the results of Jackson serialization: { \"id\": \"1546434604146774987\", \"name\": \"SQL in Action\" } We can see that the serialized id is a string rather than a number, thus avoiding the problem that JavaScript clients cannot parse large numbers.","s":"Usage","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#usage","p":551},{"i":558,"t":"info @IdView properties is advanced mapping content that will be explained later. Readers can skip this section for now and come back later. Java Kotlin @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); @IdView(\"authors\") List bookIds(); ...Omit other properties... } @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List @IdView(\"authors\") val bookIds: List ...Omit other properties... } Here, the bookIds property is not an ordinary List collection, but the collection of ids of all associated Book objects. Because the Book.id property has already been annotated with @JsonConverter, there is no need to specify any annotations for the bookIds property here to give it this capability. Similarly, bypassing ORM, demonstrate the effect through simulated data. Java Kotlin Author author = Immutables.createAuthor(draft -> { draft.setBookIds( Arrays.asList( 1546434604146774987L, 1546434604146774988L ) ); }); System.out.println(book); val book = Book { bookIds = listOf( 1546434604146774987L, 1546434604146774988L ) } println(book) Since the toString of Jimmer entities is Jackson serialization, we can print directly and observe the results of Jackson serialization: { \"bookIds\": [ \"1546434604146774987\", \"1546434604146774988\" ] } We can see that all elements of the serialized bookIds property are strings rather than numbers, thus avoiding the problem that JavaScript clients cannot parse large numbers.","s":"Automatically Applied to IdView Properties","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#automatically-applied-to-idview-properties","p":551},{"i":560,"t":"info DTO is advanced mapping content that will be explained later. Readers can skip this section for now and come back later. In the src/main/dto directory, create any file with the extension .dto and edit its code as follows export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { id name } After compiling the project, the generated Java/Kotlin type is: Java Kotlin @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookView { private String id; private String name; ...Omit other properties... } @GeneratedBy(file = \"/src/main/dto/Book.dto\") class BookView( val id: String, val name: String ) { ...Omit other properties... } We can see that the type of the id property in the automatically generated DTO type is String instead of long. Finally, we verify the conversion from entity to DTO object as follows Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(1546434604146774987L); draft.setName(\"SQL in Action\"); }); System.out.println(new BookView(book)); val book = Book { id = 1546434604146774987L name = \"SQL in Action\" } println(BookView(book)) The output is as follows BookView( id = \"1546434604146774987\", name = \"SQL in Action\" )","s":"Automatically Applied to DTO","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#automatically-applied-to-dto","p":551},{"i":563,"t":"Assume the User entity has a phone property representing the user's phone number. We now perform data masking on this property. For example, displaying the phone number as 135****6792. info Data masking is not simply a page rendering feature. It must ensure that real data is not returned in the HTTP requests themselves. There is no built-in Converter available for this requirement. We need to customize the Converter as follows: Java Kotlin public class UserPhoneConverter implements Converter { @Override public String output(String value) { return value.substring(0, 3) + \"****\" + value.substring(7); } } class UserPhoneConverter : Converter { override fun output(value: String): String = \"${value.substring(0,3)}****${value.substring(7)}\" } Then modify the User entity simply Java Kotlin @Entity public interface User { @JsonConverter(UserPhoneConverter.class) String phone(); } @Entity interface User { @JsonConverter(UserPhoneConverter.class) val phone: String }","s":"Usage","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#usage-1","p":551},{"i":565,"t":"In the above example, the UserPhoneConverter only overrides the output method without overriding the input method. Because the default implementation of the input method is to throw an UnsupportedOperationException exception, deserialization is not supported. However, in actual projects, Input DTO can be generated based on entity objects to complete data entry. In this case, the client should enter the exact phone number. Therefore, we can override the input method as follows. Java Kotlin @Override public String input(String value) { return value; } override fun input(value: String): String = value","s":"Support Input","u":"/jimmer-doc/docs/mapping/base/json-converter","h":"#support-input","p":551},{"i":568,"t":"Any entity object will be intercepted by interceptors before being saved by save commands (whether inserted or updated). At this point, users have an opportunity to modify the data to be saved, especially to assign values to some missing properties. If interceptors are used to assign values to missing properties (which is also the recommended usage), it is somewhat similar to default values at the database level, but with the following differences: Database default values can only provide business-irrelevant default value rules. Interceptors can provide default values based on business context-related information, such as the user's identity information in the permission system. Users can provide default values that are closely combined with the business based on such business context information, which cannot be achieved by database-level default values.","s":"Concept","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#concept","p":566},{"i":570,"t":"Draft interceptors work with Save Command to adjust data before objects are saved. If most entity tables have the four fields created_time, modified_time, created_by and modified_by, a super class can be provided as follows: Java Kotlin @MappedSuperclass public interface BaseEntity { LocalDateTime createdTime(); LocalDateTime modifiedTime(); @Nullable @ManyToOne @OnDissociate(DissociateAction.SET_NULL) User creator(); @Nullable @ManyToOne @OnDissociate(DissociateAction.SET_NULL) User editor(); } @MappedSuperclass interface BaseEntity { val createdTime: LocalDateTime val modifiedTime: LocalDateTime @ManyToOne @OnDissociate(DissociateAction.SET_NULL) val createdBy: User? @ManyToOne @OnDissociate(DissociateAction.SET_NULL) val modifiedBy: User? } All entities that need these fields can derive from this superclass. note The @OnDissociate(DissociateAction.SET_NULL) here is to prevent deletion operations on associated User data from being blocked due to these two foreign keys. When associated User is deleted, these two foreign keys are automatically cleared. tip Of course, user can directly intercept the entity type (decorated with @Entity), rather than an abstract type (decorated with @MappedSupperClass). However, if an abstract type is intercepted, the save operations of all derived entity types will be intercepted, which can greatly improve the flexibility of the system, especially when the abstract type supports multiple inheritance. Therefore, the example in this article chooses to intercept the abstract type instead of the entity type.","s":"Define Intercepted Data Format","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#define-intercepted-data-format","p":566},{"i":572,"t":"Assume there is a service class called UserService whose Java method getCurrentUserId() or Kotlin property currentUserId returns the id of the currently logged in user. The interceptor must implement the org.babyfish.jimmer.sql.DraftInterceptor interface. If using Spring management (two ways of using DraftHandler will be introduced below), the code is: Java Kotlin @Component public class BaseEntityDraftInterceptor implements DraftInterceptor { private final UserService userService; public BaseEntityDraftInterceptor(UserService userService) { this.userService = userService; } @Override public void beforeSave(BaseEntityDraft draft, @Nullable BaseEntity original) { if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.MODIFIED_TIME)) { draft.setModifiedTime(LocalDateTime.now()); } if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.EDITOR)) { draft.applyModifiedBy(user -> { user.setId(userService.getCurrentUserId()); }); } if (original == null) { if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.CREATED_TIME)) { draft.setCreatedTime(LocalDateTime.now()); } if (!ImmutableObjects.isLoaded(draft, BaseEntityProps.CREATOR)) { draft.applyCreatedBy(user -> { user.setId(userService.getCurrentUserId()); }); } } } } @Component class BaseEntityDraftInterceptor( private val userService: UserService ) : DraftInterceptor { override fun beforeSave(draft: BaseEntityDraft, original: BaseEntity?) { if (!isLoaded(draft, BaseEntity::modifiedTime)) { draft.modifiedTime = LocalDateTime.now() } if (!isLoaded(draft, BaseEntity::modifiedBy)) { draft.modifiedBy { id = userService.currentUserId } } if (original === null) { if (!isLoaded(draft, BaseEntity::createdTime)) { draft.createdTime = LocalDateTime.now() } if (!isLoaded(draft, BaseEntity::createdBy)) { draft.createdBy { id = userService.currentUserId } } } } } The beforeSave method is called before an object is saved, where the user can make final adjustments to the data to be saved. If the isNew parameter is true, it means the subsequent operation is an insert; otherwise, it is an update. warning Please do not modify properties decorated with @Id or @Key in the beforeSave method.","s":"Define Interceptor","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#define-interceptor","p":566},{"i":574,"t":"It was mentioned above that if the current operation is UPDATE, the original parameter of the beforeSave method is non-null, representing the old value in the database. original is a Jimmer dynamic object. By default, only the id and key properties are loaded and accessible. However, can we control the format of the original object to allow more properties to be accessed? The DraftInterceptor interface provides another default method dependencies() which returns a collection of properties to indicate that in addition to the id property and key property, which other properties of the original object need to be loaded. Java Kotlin @Component public class BaseEntityDraftInterceptor implements DraftInterceptor { @Override public void beforeSave( BaseEntityDraft draft, // The format of `original` is controlled by `dependencies()` @Nullable BaseEntity original ) { ...implementation is omitted... } @Override public Collection> dependencies() { return Arrays.asList( BaseEntityProps.CREATED_BY, BaseEntityProps.MODIFIED_BY ); } } @Component class BaseEntityDraftInterceptor( private val userService: UserService ) : DraftInterceptor { override fun beforeSave( draft: BaseEntityDraft, // The format of `original` is controlled by `dependencies()` original: BaseEntity? ) { ...implementation is omitted... } override fun dependencies(): Collection> = listOf( BaseEntityProps.CREATED_BY, BaseEntityProps.MODIFIED_BY ) } tip The returned property collection does not need to contain the id property and key property, because they are always loaded.","s":"Controlling the format of the original parameter","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#controlling-the-format-of-the-original-parameter","p":566},{"i":577,"t":"In the above, the class BaseEntityDraftInterceptor is decorated with @Component, obviously a Spring-managed object. info If using Spring Boot Starter and ensuring the interceptor is Spring-managed, then Jimmer will register it automatically without additional configuration. Otherwise, it must be manually registered.","s":"Using Jimmer Spring Starter","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#using-jimmer-spring-starter","p":566},{"i":579,"t":"If jimmer spring starter is not used, attaching the interceptor to the SqlClient object makes it take effect: Java Kotlin @Bean public JSqlClient sqlClient( List> interceptors, ...other params omitted... ) { return JSqlClient .newBuilder() .addDraftInterceptors(interceptors) ...other config omitted... .build(); } @Bean fun sqlClient( interceptors: List>, ...other params omitted... ): KSqlClient = newKSqlClient { addDraftInterceptors(interceptors) ...other config omitted... } tip Although only one DraftInterceptor is demoed in this article, there may be many in an actual project. So here a collection is used for Spring to inject all DraftInterceptor instances.","s":"Not Using Jimmer Spring Starter","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#not-using-jimmer-spring-starter","p":566},{"i":581,"t":"Assume Book inherits from BaseEntity, then it can be used like: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"59\")); draft.applyStore(store -> store.setId(2L)); }); sqlClient.getEntities().save(book); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"59\") store().id = 2 } sqlClient.entities.save(book) If the above save command finally results in an insert operation, the generated SQL is: insert into BOOK( CREATED_TIME, MODIFIED_TIME, CREATED_BY, MODIFIED_BY, NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ?, ?, ?, ?, ? ) Where the assignment behavior for CREATED_TIME, MODIFIED_TIME, CREATED_BY and MODIFIED_BY is automatically added by the interceptor. If the above save command finally results in an update operation, the generated SQL is: update BOOK set MODIFIED_TIME = ?, MODIFIED_TIME, PRICE = ?, STORE_ID = ? where ID = ? Where the assignment behavior for MODIFIED_TIME and MODIFIED_BY is automatically added by the interceptor.","s":"Final Usage","u":"/jimmer-doc/docs/mutation/draft-interceptor","h":"#final-usage","p":566},{"i":584,"t":"First, the association table is hidden by the object model, with no direct corresponding entity type. This problem has been explained in Query Association Table, so I won't repeat it here. In addition, in the Save Command section, we introduced the save command. It can compare the existing data structure in the database with the new data structure the user wants to save. If a relation property based on the association table has changed, the association table will be modified. Admittedly, the Save Command feature is very powerful, and modifying the association table is just a very small part of its capabilities. However, sometimes we just need a simple way to insert or delete data directly from the association table, we don't need the full capabilities of the Save Command. Jimmer allows developers to directly insert and delete data from the association table in a simpler way.","s":"Overview","u":"/jimmer-doc/docs/mutation/associations","h":"#overview","p":582},{"i":586,"t":"Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .save(12L, 3L); sqlClient .getAssociations(Book::authors) .save(12L, 3L) The generated SQL is: insert into BOOK_AUTHOR_MAPPING( BOOK_ID, AUTHOR_ID ) values (?, ?) This example shows how to use the association property Book.authors to operate the association table. Similarly, we can achieve the same goal through the association property Authors.books: Java Kotlin sqlClient .getAssociations(AuthorProps.BOOKS) .save(3L, 12L); sqlClient .getAssociations(Author::books) .save(3L, 12L) Note that compared to the previous example, the parameter order of the save method is different due to the different association direction. The generated SQL is: insert into BOOK_AUTHOR_MAPPING( AUTHOR_ID, BOOK_ID ) values (?, ?) It's easy to see that the order of the insert statement columns is also different.","s":"Insert Association","u":"/jimmer-doc/docs/mutation/associations","h":"#insert-association","p":582},{"i":588,"t":"For bidirectional associations, reverse can be used to switch between forward and reverse associations: Java Kotlin Associations bookToAuthor = sqlClient .getAssociations(BookProps.AUTHORS); Associations authorToBook = sqlClient .getAssociations(AuthorProps.BOOKS); Associations authorToBook2 = bookToAuthor.reverse(); Associations bookToAuthor2 = authorToBook.reverse(); val bookToAuthor = sqlClient.getAssociations( Book::authors ) val authorToBook = sqlClient.getAssociations( Author::books ) val authorToBook2 = bookToAuthor.reverse() val bookToAuthor2 = authorToBook.reverse() In this code: bookToAuthor and bookToAuthor2 are completely equivalent. authorToBook and authorToBook2 are completely equivalent.","s":"Reverse Conversion","u":"/jimmer-doc/docs/mutation/associations","h":"#reverse-conversion","p":582},{"i":590,"t":"Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .saveAll( Arrays.asList( new Tuple2<>(10L, 1L), new Tuple2<>(11L, 1L), new Tuple2<>(12L, 1L), new Tuple2<>(10L, 3L), new Tuple2<>(11L, 3L), new Tuple2<>(12L, 3L) ) ); sqlClient .getAssociations( Book::authors ) .saveAll( listOf( Tuple2(10L, 1L), Tuple2(11L, 1L), Tuple2(12L, 1L), Tuple2(10L, 3L), Tuple2(11L, 3L), Tuple2(12L, 3L) ) ) Here there are 3 books, two authors, and 6 total combination ways. The saveAll method inserts all 6 combinations into the association table, generating the following SQL: insert into BOOK_AUTHOR_MAPPING( BOOK_ID, AUTHOR_ID ) values (?, ?), (?, ?), (?, ?), (?, ?), (?, ?), (?, ?) The above approach is very cumbersome. For 3 * 2 = 6 it is still acceptable, but what about 7 * 9 = 63? Should we really construct 63 tuples? Jimmer-sql provides a shorthand syntax: Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) // Save cartesian product of two id sets .saveAll( Arrays.asList( 10L, 11L, 12L ), Arrays.asList( 1L, 3L ) ); sqlClient .getAssociations( Book::authors ) // Save cartesian product of two id sets .saveAll( listOf(10L, 11L, 12L), listOf(1L, 3L) ) The above saveAll method takes two collection parameters and inserts the cartesian product of the two collections into the association table, so its functionality is the same as the previous example.","s":"Bulk Insert","u":"/jimmer-doc/docs/mutation/associations","h":"#bulk-insert","p":582},{"i":592,"t":"Inserting id tuples that already exist into the association table will cause errors, as it violates uniqueness constraints. To solve this problem, existence checks can be performed. Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .saveAllCommand( Arrays.asList( 10L, 11L, 12L ), Arrays.asList( 1L, 3L ) ) .checkExistence() .execute(); sqlClient .getAssociations( Book::authors ) .saveAll( listOf(10L, 11L, 12L), listOf(1L, 3L), checkExistence = true ) Here checkExistence() indicates that it will first check which data to be inserted already exists, and then only insert data that does not exist. The generated SQL statements are: Check which data to be inserted already exists: select BOOK_ID, AUTHOR_ID from BOOK_AUTHOR_MAPPING where (BOOK_ID, AUTHOR_ID) in( (?, ?), (?, ?), (?, ?) ) Using the results of the previous query, the data that really needs to be inserted can be calculated. Skip this step if no data needs to be inserted; otherwise, execute this step. Here, assuming it is determined that only two rows of data really need to be inserted, the generated SQL is: insert into BOOK_AUTHOR_MAPPING( BOOK_ID, AUTHOR_ID ) values (?, ?), (?, ?) info Some databases support UPSERT (such as Postgres' insert into ... on conflict ...), which will be supported before Jimmer-1.0.0","s":"Check Existence","u":"/jimmer-doc/docs/mutation/associations","h":"#check-existence","p":582},{"i":594,"t":"Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .delete(12L, 3L); sqlClient .getAssociations( Book::authors ) .delete(12L, 3L) The generated SQL is: delete from BOOK_AUTHOR_MAPPING where (BOOK_ID, AUTHOR_ID) in ( (?, ?) )","s":"Delete Association","u":"/jimmer-doc/docs/mutation/associations","h":"#delete-association","p":582},{"i":596,"t":"Similar to bulk insert, there are two ways to bulk delete: Java Kotlin sqlClient .getAssociations( BookTableEx.claBookProps.AUTHORS) .deleteAll( Arrays.asList( new Tuple2<>(10L, 1L), new Tuple2<>(11L, 1L), new Tuple2<>(12L, 1L), new Tuple2<>(10L, 3L), new Tuple2<>(11L, 3L), new Tuple2<>(12L, 3L), ) ); sqlClient .getAssociations( Book::authors ) .deleteAll( listOf( Tuple2(10L, 1L), Tuple2(11L, 1L), Tuple2(12L, 1L), Tuple2(10L, 3L), Tuple2(11L, 3L), Tuple2(12L, 3L) ) ) Or: Java Kotlin sqlClient .getAssociations(BookProps.AUTHORS) .deleteAll( Arrays.asList(10L, 11L, 12L), Arrays.asList(1L, 3L) ); sqlClient .getAssociations( Book::authors ) .deleteAll( listOf(10L, 11L, 12L), listOf(1L, 3L) ) The generated SQL is: delete from BOOK_AUTHOR_MAPPING where (BOOK_ID, AUTHOR_ID) in ( (?, ?), (?, ?) )","s":"Bulk Delete","u":"/jimmer-doc/docs/mutation/associations","h":"#bulk-delete","p":582},{"i":598,"t":"caution Please do not abuse this feature. This feature is only suitable for simple insertion and deletion of association tables. It is recommended to only use it when facing the simplest incremental operations. Let's look at an example. If comparison with existing data in the database is needed, this feature is obviously not the optimal choice, and the code will be very cumbersome, as follows: Java Kotlin Inappropriate Usage Example public void setAuthors(long bookId, Collection authorIds) { // Get old author ids AssociationTable table = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List oldAuthorIds = sqlClient .createAssociationQuery(table) .where(table.source().id().eq(bookId)) .select(table.target().id()) .execute(); // Delete `oldAuthorIds - authorIds` List detachedAuthorIds = new ArrayList<>(oldAuthorIds); detachedAuthorIds.removeAll(authorIds); sqlClient.getAssociations(BookProps.AUTHORS).deleteAll( Collections.singleton(bookId), detachedAuthorIds ); // Insert `authorIds - oldAuthorIds` List attachedAuthorIds = new ArrayList<>(authorIds); attachedAuthorIds.removeAll(oldAuthorIds); sqlClient.getAssociations(BookProps.AUTHORS).saveAll( Collections.singleton(bookId), attachedAuthorIds ); } Inappropriate Usage Example fun setAuthors(bookId: Long, authorIds: Collection) { // Get old author ids val oldAuthorIds = sqlClient.queries.forList(Book::authors) { where(table.source.id eq bookId) select(table.target.id) }.execute().toSet() // Delete `oldAuthorIds - authorIds` sqlClient .getAssociations(Book::authors) .deleteAll(listOf(bookId), oldAuthorIds - authorIds) // Insert `authorIds - oldAuthorIds` sqlClient .getAssociations(Book::authors) .saveAll(listOf(bookId), authorIds - oldAuthorIds) } It is obvious that dealing with it this way is very cumbersome. tip When the business scenario is no longer simple addition or deletion, Save Command is a better choice, as follows: Java Kotlin Better Usage Example public void setAuthors(long bookId, Collection authorIds) { sqlClient.save( Immutables.createBook(book -> { book.setId(bookId); book.setAuthorIds(authorIds); }) ); } Better Usage Example fun setAuthors(bookId: Long, authorIds: Collection) { sqlClient.save( Book { id = bookId authorIds = authorIds } ) }","s":"Notes","u":"/jimmer-doc/docs/mutation/associations","h":"#notes","p":582},{"i":601,"t":"The owned side only has @OneToMany or @OneToOne objects with mappedBy. Taking @OneToMany as an example: Java Kotlin @Entity public interface BookStore { @OneToMany(mappedBy = true) List books(); } @Entity interface BookStore { @OneToMany(mappedBy = true) val books: List } This association has a special functionality: Automatically sets reverse associations for child objects Configures whether different parent objects can snatch for child objects","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#basic-concepts","p":599},{"i":603,"t":"Assume we have the following entity: Java Kotlin TreeNode.java @Entity public interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key @ManyToOne @Nullable TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } TreeNode.kt @Entity interface TreeNode { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List } The @Key properties of TreeNode are name and parent. Apart from explicitly accepting the persistence mode for wild objects, the object being saved needs to either: Specify the TreeNode.id property Specify both TreeNode.name and TreeNode.parent properties However, the following code works normally: Java Kotlin TreeNode rootNode = Immutables.createTreeNode(root -> { root.setName(\"Root\"); root.setParent(null); root.addIntoChildNodes(child -> { child.setName(\"Child-1\"); // For non-root objects, no need to specify the `parent` property }); root.addIntoChildNodes(child -> { child.setName(\"Child-2\"); // For non-root objects, no need to specify the `parent` property }); }); sqlClient .saveCommand(rootNode) .setTargetTransferModeAll(TargetTransferMode.ALLOWED) .execute(); val rootNode = TreeNode { name = \"Root\" parent = null childNodes().addBy { name = \"Child-1\" // For non-root objects, // no need to specify the `parent` property } childNodes().addBy { name = \"Child-2\" // For non-root objects, // no need to specify the `parent` property } } sqlClient.save(rootNode) { setTargetTransferModeAll(TargetTransferMode.ALLOWED) } The setTargetTransferModeAll(TargetTransferMode.ALLOWED) is not the focus here, readers can ignore it for now. Here, although the root object (Root) has both name and parent properties specified, for non-root objects (Child-1, Child-2), only the name property is specified, while the parent property is not. The TreeNode.childNodes property is the reverse association of the TreeNode.parent property. info For the owning side of many-to-one (or one-to-one) associations (here TreeNode.parent), once child objects are specified for the parent object through its inverse one-to-many (or one-to-one) association (here TreeNode.childNodes), the parent object reference for each child object in the collection will be automatically set. In this example, the object tree that the user originally expected to save was: { \"name\":\"Root\", \"parent\":null, \"childNodes\":[ {\"name\":\"Child-1\"}, {\"name\":\"Child-2\"} ] } Assuming the database assigns auto-number 100 to the root element after insertion, Jimmer will automatically adjust this tree to: { \"id\": 100, \"name\":\"Root\", \"parent\":null, \"childNodes\":[ { \"name\":\"Child-1\", \"parent\": {\"id\": 100} }, { \"name\":\"Child-2\", \"parent\": {\"id\": 100} } ] } As you can see, once the parent object is saved, the TreeNode.parent property of all child objects will be automatically set. That is, when the id property is not specified: From Jimmer's perspective, both name and parent properties of all TreeNode objects are specified, meaning all @Key properties are specified From the user's perspective, only the root object needs to specify both name and parent properties, while all other objects only need to specify the name property The above example will generate three SQL statements: Query whether the root object exists based on @Key: Purpose: COMMAND(NULL_NOT_DISTINCT_REQUIRED) select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.PARENT_ID is null and tb_1_.NAME = ? /* Root */ Here, the database's own UPSERT capability is not used, instead an additional query is made to determine whether the subsequent operation should be INSERT or UPDATE. This is because the database's own UPSERT capability relies on unique constraints (or unique indexes), and here, the parent property of the root object being saved is null, and not all databases have the ability to define null behavior for unique constraints. Therefore, by default, if the @Key property of the object being saved is null, Jimmer will give up using the database's own UPSERT capability, execute an additional query to determine whether the subsequent operation should be INSERT or UPDATE, and report QueryReason.NULL_NOT_DISTINCT_REQUIRED to developers. info Some databases, such as Postgres, can define null behavior for unique constraints. How to solve this problem in such databases is not the focus of this article, please refer to the documentation comments of QueryReason.NULL_NOT_DISTINCT_REQUIRED to learn more. Assuming the above query determines that the object being saved does not exist in the database, simply insert the root object: insert into TREE_NODE(NAME, PARENT_ID) values(?, ?) /* batch-0: [Root, DbNull{type=long}] */ Save child objects (assuming the id is known to be 100 after saving the root object): merge into TREE_NODE( NAME, PARENT_ID ) key( NAME, PARENT_ID ) values(?, ?) /* batch-0: [Child-1, 100] */ /* batch-1: [Child-2, 100] */","s":"1. Automatically Setting Reverse Associations for Child Objects","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#1-automatically-setting-reverse-associations-for-child-objects","p":599},{"i":606,"t":"Let's look at an example first: Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setId(12L); }); draft.addIntoBooks(book -> { book.setId(1L); }); }); sqlClient.save(store); val store = BookStore { name = \"MANNING\" books().addBy { id = 12L } books().addBy { id = 1L } } sqlClient.save(store) Executing this code will generate the following SQL and result in an exception: Saving the root object BookStore: merge into BOOK_STORE( NAME ) key(NAME) values(?) /* batch-0: [MANNING] */ Saving the child objects Book: Purpose: COMMAND(TARGET_NOT_TRANSFERABLE) select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.ID = any(? /* [12, 1] */) Strangely, even though the id property of child objects is specified (which usually means Jimmer will utilize the database's own UPSERT capability), Jimmer still tries to determine whether the subsequent operation should be INSERT or UPDATE through a query, rather than using the database's own UPSERT capability. More importantly, Jimmer reports QueryReason.TARGET_NOT_TRANSFERABLE. Finally, the above code will result in the following exception: Save error caused by the path: \".books\": Can the move the child object whose type is \"org.doc.j.model.Book\" and id is \"1\" to another parent object because the property \"org.doc.j.model.BookStore.books\" does not support target transfer Book.store is a many-to-one association, a Book object can only belong to one BookStore object and cannot belong to multiple BookStore objects simultaneously. Therefore, saving the data structure through the inverse one-to-many association BookStore.books establishes an association between the current BookStore parent object and another existing Book object. If the Book object already belongs to another parent object, it will cause the current parent object to snatch for the child object from other parent objects. In other words, the child object migrates between different parent objects. If this is expected behavior by the developers, then there's no problem. However, if this is not expected behavior, it may lead to unintended oversights. By default, Jimmer adopts a conservative strategy that prohibits child objects from transfering between different parent objects. In this example, attempting to associate BookStore(MANNING) with Book(12) and Book(1), Jimmer executes an additional query with QueryReason.TARGET_NOT_TRANSFERABLE to check if any child objects are transfering between different parent objects. Book(12) already belongs to BookStore(MANNING), no transfer occurs, no problem Book(1) doesn't belong to BookStore(MANNING) but belongs to BookStore(O'REILLY), transfer occurs, therefore an exception is thrown. The default behavior is very conservative. While it prevents competition for child objects between different parent objects (if developers consider such unintended competition harmful to business), it leads to additional queries and doesn't fully utilize the database's own UPSERT capability, resulting in suboptimal performance. If you believe better performance is more important than this conservative defensive behavior, Jimmer provides additional configuration to change this behavior.","s":"Conservative Default Behavior","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#conservative-default-behavior","p":599},{"i":608,"t":"To prioritize performance and remove these restrictions, there are two methods: Save command level configuration, which can be divided into two types: Precise configuration, removing restrictions for specific associations: Java Kotlin BookStore store = ...omitted...; sqlClient .saveCommand(store) .setTargetTransferMode( BookStoreProps.BOOKS, TargetTransferMode.ALLOWED ) .execute(); val store = BookStore {...omitted...} sqlClient.save(store) { setTargetTransferMode( BookStore::books, TargetTransferMode.ALLOWED ) } Blind configuration, removing restrictions for all associations: Java Kotlin BookStore store = ...omitted...; sqlClient .saveCommand(store) .setTargetTransferModeAll( TargetTransferMode.ALLOWED ) .execute(); val store = BookStore {...omitted...} sqlClient.save(store) { setTargetTransferModeAll( TargetTransferMode.ALLOWED ) } Whether precise or blind configuration, the last parameter is the TargetTransferMode enum, which has three values: ALLOWED: Allows child object transfer and tries to use the database's own UPSERT capability whenever possible NOT_ALLOWED: Prohibits child object transfer, initiates additional queries with QueryReason.TARGET_NOT_TRANSFERABLE for verification. If child object transfer occurs, throws an exception AUTO (default): Current configuration is invalid, refers to lower priority configuration For precise configuration, refers to blind configuration For blind configuration, refers to global configuration Global configuration, which can be divided into two types: Global configuration based on Jimmer API: Java Kotlin JSqlClient sqlCient = JSqlClient .newBuilder() .setTargetTransferable(true) ...other configurations omitted... .build(); val sqlClient = sqlClient { setTargetTransferable(true) ...other configurations omitted... } Global configuration based on Spring Boot if using Jimmer's spring-boot-starter: Using application.yml as an example: jimmer: target-transferable: true ...other configurations omitted... Once Jimmer is configured through any of the above methods to not restrict child object transfer for the BookStore.books association, modify the code as follows: Java Kotlin Book.java public interface Book { @ManyToOne @Nullable // Not related to the current discussion, // please ignore for now @OnDissociate(DissociateAction.SET_NULL) BookStore store(); ...other code omitted... } Book.kt public interface Book { @ManyToOne // Not related to the current discussion, // please ignore for now @OnDissociate(DissociateAction.SET_NULL) val store: BookStore? ...other code omitted... } Re-executing the code will generate the following SQL: Saving the root object: merge into BOOK_STORE( NAME ) key(NAME) values(?) /* batch-0: [MANNING] */ Establishing associations between root object and child objects: merge into BOOK( ID, STORE_ID ) key(ID) values(?, ?) /* batch-0: [12, 2] */ /* batch-1: [1, 2] */ Breaking associations between root object and no longer needed child objects: update BOOK set STORE_ID = null where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [2, [12, 1]] */ info To demonstrate performance-priority scenarios to users, the examples jimmer-examples/java/save-command and jimmer-examples/kotlin/save-command-kt both use global configuration to allow child object transfer.","s":"Overriding Default Behavior Without Restrictions","u":"/jimmer-doc/docs/mutation/save-command/association/owner","h":"#overriding-default-behavior-without-restrictions","p":599},{"i":610,"t":"The save command is used to store data structures of any complexity. To facilitate discussion, we need to establish a basic classification of data structure shapes.","s":"Data Classification","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"","p":609},{"i":612,"t":"Jimmer entities support two types of property representation: @Id: A property that must be defined for any Jimmer entity type. It serves as a technical unique identifier, known in the industry as a Surrogate Id. @Key: Multiple properties that Jimmer recommends defining for entity types. They serve as business-level unique identifiers, known in the industry as Natural Id. In this series of articles, all entities have both @Id and @Key properties defined, with the Id property using the database's auto-increment strategy. Here's an example using Book: Java Kotlin Book.java @Entity public interface Book { @Id ❶ @GeneratedValue(strategy = GenerationType.IDENTITY) ❷ long id(); @Key ❸ String name(); @Key ❸ int edition(); BigDecimal price(); ...other properties omitted... } Book.kt @Entity interface Book { @Id ❶ @GeneratedValue(strategy = GenerationType.IDENTITY) ❷ val id: Long @Key ❸ val name: String @Key ❸ val edition: Int val price: BigDecimal ...other properties omitted... } ❶ Id property, i.e., Surrogate Id ❷ Id property uses database auto-numbering as the auto-increment strategy ❸ Key property, i.e., Natural Id","s":"Entity Definition","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#entity-definition","p":609},{"i":614,"t":"An object is called a wild object if neither its @Id property (Book.id in this article) nor its @Key properties (Book.name and Book.edition in this article) are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setPrice(new BigDecimal(\"59.9\")); }); val book = Book { price = BigDecimal(\"59.9\") } When we say @Key properties are not specified, this includes two situations: The entity type doesn't define any @Key properties (not discussed in this article) Although the entity type defines @Key properties, these properties are not specified in the object caution Jimmer does not recommend wild objects. Although API parameters can be adjusted to save wild objects, this will ultimately compromise idempotency.","s":"1. Wild Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#1-wild-objects","p":609},{"i":616,"t":"An object is called an id-specified object if its @Id property (Book.id in this article) is specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(17L); ...other settings omitted... }); val book = Book { id = 17L ...other settings omitted... } Jimmer supports UPSERT operations, where users don't explicitly specify insert or update, letting Jimmer make the determination. When saving an id-specified object in UPSERT mode, Jimmer uses the @Id property to determine whether corresponding data already exists in the database, ultimately deciding whether to insert or update.","s":"2. Id-specified Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#2-id-specified-objects","p":609},{"i":618,"t":"An object is called a key-specified object if its @Id property (Book.id in this article) is not specified, but its @Key properties (Book.name and Book.edition in this article) are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(2); ...setting other properties except id... }); val book = Book { name = \"GraphQL in Action\" edition = 1 ...setting other properties except id... } note In the code above, the omitted parts do not include setting the @Id property, because once the @Id property is set, it should be an id-specified object, not a key-specified object. Jimmer supports UPSERT operations, where users don't explicitly specify insert or update, letting Jimmer make the determination. When saving a key-specified object in UPSERT mode, Jimmer uses the @Key properties to determine whether corresponding data already exists in the database, ultimately deciding whether to insert or update.","s":"3. Key-specified Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#3-key-specified-objects","p":609},{"i":620,"t":"An id-specified object is called an id-only object if no properties other than id are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setId(17L); }); val book = Book { id = 17L } In hierarchical data structures, any object can have deeper associated objects. If an associated object is an id-only object, it indicates that only the association relationship is being modified, without further creating or modifying the associated object.","s":"4. Id-only Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#4-id-only-objects","p":609},{"i":622,"t":"A key-specified object is called a key-only object if no properties other than key properties are specified. For example: Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(2); }); val book = Book { name = \"GraphQL in Action\" edition = 1 } In hierarchical data structures, any object can have deeper associated objects. If an associated object is a key-only object, it indicates that only the association relationship is being modified, without further creating or modifying the associated object.","s":"5. Key-only Objects","u":"/jimmer-doc/docs/mutation/save-command/data-classification","h":"#5-key-only-objects","p":609},{"i":626,"t":"Association id checking is a feature that only applies to short associationslong associations As we learned before, save commands can persist arbitrary data shapes, and any object can further hold associated objects. If the id of an associated object is specified, but the object it represents does not exist in the database, how does Jimmer handle this scenario? First, for long associations Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(3L); draft.addIntoAuthors(author -> author.setId(1L)); // ❶ draft.addIntoAuthors(author -> author.setId(2L)); // ❷ draft.addIntoAuthors(author -> { // ❸ author.setId(1000L); author.setFirstName(\"Svetlana\"); author.setLastName(\"Isakova\"); author.setGender(Gender.FEMALE); }); }) ); sqlClient.update( Book { id = 3L authors().addBy { id = 1L } // ❶ authors().addBy { id = 2L } // ❷ authors().addBy { // ❸ id = 1000L firstName = \"Svetlana\" lastName = \"Isakova\" gender = Gender.FEMALE } } ) This example mixes long associations and short associations. ❶ ❷ They are short associations, specifying invalid ids will lead to errors. ❸ This is a long association, even if an invalid id is specified, Jimmer will automatically create the associated object. The generated SQL is: // Check if associated object exists select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR tb_1_ where tb_1_.ID = ? /* 1000 */ // Associated object does not exist, create it insert into AUTHOR(ID, FIRST_NAME, LAST_NAME, GENDER) values (? /* 1000 */, ? /* Svetlana */, ? /* Isakova */, ? /* F */) // Query current `Book` and `Author` mapping select AUTHOR_ID from BOOK_AUTHOR_MAPPING where BOOK_ID = ? /* 3 */ // Map current `Book` with the newly created `Author` insert into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values (? /* 3 */, ? /* 1000 */) info Therefore, association id checking is a topic that only makes sense for short associations. In the following examples of this article, all discussions are about short associations.","s":"For Short Associations Only","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#for-short-associations-only","p":623},{"i":628,"t":"To discuss the id checking problem of short associations, we first define a concept for associated properties: the target foreign key. For associations based on join tables, the foreign key in the join table that points to the target entity table is the target foreign key. For examples: The target foreign key for Book.authors is the AUTHOR_ID field in the BOOK_AUTHOR_MAPPING table. The target foreign key for Author.books is the BOOK_ID field in the BOOK_AUTHOR_MAPPING table. For associations based on foreign keys, whether the foreign key is fake or not (please refer to Fake Foreign Keys), the foreign key of the association itself is the target foreign key. For example: The target foreign key for Book.store is the STORE_ID field in the BOOK table. If neither of the above two cases apply, the association is considered to not have a target foreign key. Properties without a target foreign key are the ones with mappedBy specified for one-to-one or one-to-many mappings. That is, properties decorated with @OneToOne(mappedBy = \"...\") or @OneToMany(mappedBy=\"...\"). For example: There is no target foreign key for BookStore.books. Summary Association Column of target foreign key Table of target foreign key Book.authors AUTHOR_ID BOOK_AUTHOR_MAPPING Author.books BOOK_ID BOOK_AUTHOR_MAPPING Book.store STORE_ID BOOK BookStore.books NA NA","s":"Concept Definition: Target Foreign Key","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#concept-definition-target-foreign-key","p":623},{"i":630,"t":"Users can configure whether to check the ids of short associated objects. Here, let's not discuss how to configure for now, but look at whether enabling this configuration has any impact on Jimmer's behavior. Properties without target foreign keys Take BookStore.books as an example. The code to save a short association is: Java Kotlin sqlClient.update( Immutables.createBookStore(draft -> { draft.setId(2L); draft.addIntoBooks(book -> book.setId(8L)); draft.addIntoBooks(book -> book.setId(9L)); draft.addIntoBooks(book -> book.setId(1000L)); draft.addIntoBooks(book -> book.setId(1001L)); }) ); sqlClient.update( BookStore { id = 2L books().addBy { id = 8L } books().addBy { id = 9L } books().addBy { id = 1000L } books().addBy { id = 1001L } } ); Without checking Properties without a target foreign key will automatically ignore associated objects with illegal ids. For example: update book set store_id = 2 where id in(1, 2, 1000, 10001) If 1000 and 10001 are ids that do not exist in the database, this update statement will only affect the two existing records, and the two non-existing records will be naturally ignored. With checking Jimmer will execute the following query to check all short associated ids: select tb_1_.ID from BOOK tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */, ? /* 1000 */, ? /* 1001 */ ) If ids 1000 and 1001 do not exist in the database, the following exception will be thrown: Save error caused by the path: \".books\": Illegal ids: [1000, 1001] Properties with target foreign keys Take Book.store as an example. The code to save a short association is: Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(10L); draft.applyStore(store -> store.setId(321L)); }) ); sqlClient.update( Book { id = 10L store { id = 321L } } ); Assume id 321 does not exist for BookStore in the database. Without checking If the foreign key is fake, there is no real foreign key constraint in the database, and Jimmer will allow BOOK.STORE_ID to be modified to an illegal value. If the foreign key is real, there is a real foreign key constraint in the database, and the underlying database will throw an error eventually. With checking Regardless of whether the foreign key is fake or not, Jimmer will execute the following query to check the short associated id: select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID in ( ? /* 321 */ ) Once the query returns no data, the following exception will be thrown: Save error caused by the path: \".store\": Illegal ids: [321] Summary Real target foreign key Fake target foreign key No target foreign keys Without checking Error from database Save wrong data Ignore invalid operations With checking Error from Jimmer Error from Jimmer Error from Jimmer info As you can see, for properties with a real target foreign key, exceptions will be thrown regardless of whether Jimmer's short association id checking is enabled. Without checking, the database throws the error. Advantage: Avoid an extra SQL query Disadvantage: Less control over the exception message and type. With checking, Jimmer throws the error. Advantage: clear exception message and type. Disadvantage: An extra SQL query. tip It is recommended to turn on this checking mechanism for all properties if your project does not have extreme performance requirements, in order to get ideal exception information (we will introduce how to configure it later).","s":"Checking Mechanism","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#checking-mechanism","p":623},{"i":632,"t":"Users can configure whether to check associated ids for properties. There are global configuration and command-level configuration.","s":"Configuration","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#configuration","p":623},{"i":634,"t":"The global configuration provides three levels: NONE FAKE ALL The behaviors are: Real target foreign key Fake target foreign key No target foreign keys NONE No checking No checking No checking FAKE No checking Checking Checking ALL Checking Checking Checking There are two ways to configure globally: Via Spring Boot Starter configuration Modify application.yml (or application.properties) and add the following: jimmer: id-only-target-checking-level: ALL Via low-level API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setIdOnlyTargetCheckingLevel(IdOnlyTargetCheckingLevel.ALL) ...other configurations omitted... .build(); val sqlClient = newKSqlClient { setIdOnlyTargetCheckingLevel(IdOnlyTargetCheckingLevel.ALL) ...other configurations omitted... }","s":"Global Configuration","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#global-configuration","p":623},{"i":636,"t":"The command-level configuration can override the global configuration, but only affects the current save command. There are three features for command-level configuration: Explicitly specify properties to check Java Kotlin Book book = ... sqlClient .getEntities() .saveCommand(book) .setAutoIdOnlyTargetChecking(BookProps.STORE) .setAutoIdOnlyTargetChecking(BookProps.AUTHORS) .execute(); val book = ... sqlClient.save(book) { setAutoIdOnlyTargetChecking(Book::store) setAutoIdOnlyTargetChecking(Book::authors) } info If the global configuration already enables checking, no need to adjust the save command like this. Specify all properties to check Java Kotlin Book book = ... sqlClient .getEntities() .saveCommand(book) .setAutoIdOnlyTargetCheckingAll() .execute(); val book = ... sqlClient.save(book) { setAutoIdOnlyTargetCheckingAll() } info If the global configuration already enables checking, no need to adjust the save command like this. Negative configuration, explicitly specify properties to not check Java Kotlin Book book = ... sqlClient .getEntities() .saveCommand(book) .setAutoIdOnlyTargetCheckingAll() .setAutoIdOnlyTargetChecking(BookProps.STORE, false) .execute(); val book = ... sqlClient.save(book) { setAutoIdOnlyTargetCheckingAll() setAutoIdOnlyTargetChecking(Book::authors, false) }","s":"Command-Level Configuration","u":"/jimmer-doc/docs/mutation/save-command/id-checking","h":"#command-level-configuration","p":623},{"i":638,"t":"Although the underlying save commands are very powerful, there is still some way to go before exposing data persistence APIs externally. The documents in this section discuss how to expose data persistence APIs externally.","s":"Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/","h":"","p":637},{"i":640,"t":"caution This is a very crude solution, only for learning or very simple projects. Limitation: Can only save single table data, cannot persist complex data structures. Functionality: Resolves security issue (this issue is discussed in previous doc). Advantage: No need to define Input DTOs. Disadvantage: Does not resolve API ambiguity issue (this issue is discussed in previous doc). Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody Book book ) { if (!ImmutableObjects.isLonely(book)) { throw new IllegalArgumentException(\"The input object is too complex\"); } bookRepository.save(book); } @PutMapping(\"/book\") fun saveBook( @RequestBody book: Book ) { if (!isLonely(book)) { throw IllegalArgumentException(\"The input object is too complex\") } bookRepository.save(input) } This example directly uses the Jimmer dynamic object as the parameter, without restricting the complexity of the passed data structure. But we added a validation to throw an exception if the parameter is not a lonely object, to ensure security. isLonely is used to determine if a dynamic object is just a lonely object. A lonely object can only have two kinds of properties: Scalar properties Association properties based on foreign keys, but can only be assigned null or associated objects with only id property. It is easy to see that the validation in the above code ensures all insert or update operations can only apply to one table. If the developer thinks: Restricting functionality to only modifying one table achieves the security limit needed The other API ambiguity issue is acceptable Then this is indeed a very crude but usable solution.","s":"Lonely Form","u":"/jimmer-doc/docs/mutation/save-command/input-dto/lonely","h":"","p":639},{"i":643,"t":"Association objects can be classified from two perspectives, with two types of associations from each perspective, totaling 4 types Classification by association object shape Short Association Only modifies the association relationship between the current object and other objects, without further saving the associated objects. The recursive saving behavior is terminated and will not continue deeper. Long Association Not only modifies the association relationship between the current object and other objects but also further saves the associated objects. The recursive saving behavior will not be terminated and will continue deeper. Classification by save order Forward Association Associated objects are saved earlier than the current object, which is actually based on foreign keys (whether true or false). For example: Book.store in this tutorial. Backward Association Associated objects are saved later than the current object, including two situations The inverse association of forward associations. For example: BookStore.books in this tutorial Associations based on intermediate tables. For example: Book.authors and Author.books in this tutorial","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#basic-concepts","p":641},{"i":646,"t":"A short association means only modifying the association itself between the current object and other objects, with no interest in modifying the associated objects. Typically, UI design will use radio buttons (association reference) or checkboxes (association collection). Book Form Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit Where: Radio buttons correspond to many-to-one association Book.store Checkboxes correspond to many-to-many association Book.authors note In real projects, when there is a lot of data to choose from, it might not be suitable to design as a dropdown UI. In this case, an object selector with filtering conditions and pagination capabilities can be used instead of a dropdown, which is a common workaround. Since users only want to modify the association between the current object and other objects, without further modifying the associated objects, the UI cannot have multiple levels of association nesting. This is why it's called a short association. When passing any shaped data structure as a parameter to the save command, there are two methods to specify short associations: Use Id-Only objects as associated objects Use Key-Only objects as associated objects with special configuration enabled 1.1.1. Using Id-Only Objects as Associated Objects​ Make associated objects have only the id property Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"39.9\")); // Associated object has only id property draft.setStoreId(2L); draft.addIntoAuthors(author -> { // Associated object has only id property author.setId(4L); }); draft.addIntoAuthors(author -> { // Associated object has only id property author.setId(5L); }); }); sqlClient.save(book); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"39.9\") // Associated object has only id property storeId = 2L authors().addBy { // Associated object has only id property id = 4L } authors().addBy { // Associated object has only id property id = 5L } } sqlClient.save(book) note The hardcoding of the data structure being saved here is only for demonstration. In actual projects, the data structure being saved is submitted by the frontend interface. Of course, if the user has defined the authorIds property according to the Mapping/Advanced Mapping/View Properties/IdView article, the above code can be simplified, for example: Java Kotlin Book book = ImmutableObjects.createBook(draft -> { draft.setAuthorIds(Arrays.asList(4L, 5L)); }); val book = Book { authorIds = listOf(4L, 5L) } However, this is not mandatory. To make the example more universal, we don't assume that users have defined IdView properties for entity types. All subsequent documentation will follow this approach without further reminders. Assuming the current database is H2, the generated SQL would be: Save the aggregate root. merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 39.9, 2] */ Since Book.store is a many-to-one relationship directly based on foreign key (STORE_ID), the association between the current object and BookStore(2) object will be automatically created by the execution of this SQL. If there are Author objects associated with the current object (newly inserted data is Book(100)) other than just Author(4) and Author(5), break the associations with those other objects. delete from BOOK_AUTHOR_MAPPING where BOOK_ID = ? /* 100 */ and not ( AUTHOR_ID = any(? /* [4, 5] */) ) This step is called unhooking, which will be introduced in subsequent documentation. Readers can ignore this for now. Establish associations between the object (newly inserted data is Book(100)) and the two objects Author(4) and Author(5) merge into BOOK_AUTHOR_MAPPING tb_1_ using(values(?, ?)) tb_2_( BOOK_ID, AUTHOR_ID ) on tb_1_.BOOK_ID = tb_2_.BOOK_ID and tb_1_.AUTHOR_ID = tb_2_.AUTHOR_ID when not matched then insert(BOOK_ID, AUTHOR_ID) values(tb_2_.BOOK_ID, tb_2_.AUTHOR_ID) /* batch-0: [100, 4] */ /* batch-1: [100, 5] */ info Through this example, it's not hard to see that short associations only create or destroy the association relationships between the current object and other objects, without further saving the associated objects. Short associations always assume that the referenced objects exist. If the referenced objects (in this example, BookStore(2), Author(4), and Author(5)) don't exist, it will cause an exception! 1.1.2. Using Key-Only Objects as Associated Objects with Special Configuration Enabled​ In the code below, assume: The key property for the BookStore type is name View The key properties for the Author type are firstName and lastName In actual business scenarios, this uniqueness constraint might not be reasonable, but let's assume this for the sake of simplifying the example. View Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"39.9\")); draft.applyStore(store -> { // Associated object has only key property, i.e., `BookStore.name` store.setName(\"MANNING\"); }); draft.addIntoAuthors(author -> { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` author.setFirstName(\"Boris\").setLastName(\"Cherny\"); }); draft.addIntoAuthors(author -> { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` author.setFirstName(\"Samer\").setLastName(\"Buna\"); }); }); sqlClient .saveCommand(book) .setKeyOnlyAsReference(BookProps.STORE) .setKeyOnlyAsReference(BookProps.AUTHORS) .execute(); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"39.9\") store { // Associated object has only key property, i.e., `BookStore.name` name = \"MANNING\" } authors().addBy { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` firstName = \"Boris\" lastName = \"Cherny\" } authors().addBy { // Associated object has only key properties, i.e., `Author.firstName` and `Author.lastName` firstName = \"Samer\" lastName = \"Buna\" } } sqlClient.save(book) { setKeyOnlyAsReference(Book::store) setKeyOnlyAsReference(Book::authors) } info By default, key-only associated objects are treated as long associations However, developers can treat key-only associated objects as short associations by calling the setKeyOnlyAsReference method. Here, setKeyOnlyAsReference is called twice to explicitly configure the associations Book.store and Book.authors. In fact, you can also call setKeyOnlyAsReferenceAll once to blindly configure all associations. Compared to Kotlin, the Java API is slightly less convenient for advanced configuration of save commands. First call the saveCommand method to create a save command without executing it immediately, then call the execute method to actually execute it after completing the advanced configuration.","s":"1.1. Short Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#11-short-association","p":641},{"i":648,"t":"Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"Book Form","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"","p":641},{"i":650,"t":"A long association means not only modifying the association itself between the current object and other objects but also further modifying the associated objects. Typically, orders and order items are the best examples of such scenarios. The UI design will use embedded tables, for example: Purchaser Schneewittchen Purchaser Province Province City City Address Address Order Items Commodity Quantity Unit price Item price Delete Timeless Vitamin C Plus E 10 Percent Ferulic Acid Serum Serum Unisex 1 oz 14.69 29.38 Olaplex No. 4 Bond Maintenance Shampoo 30 30 Add Total price:59.379999999999995 Submit Since users not only want to modify the association between the current object and other objects but also want to further modify the associated objects, and the associated objects can contain deeper associations, theoretically, the UI can have multiple levels of association nesting. This is why it's called a long association. note Although designers will intentionally avoid nesting deeper embedded tables within embedded tables to maintain UI simplicity, there are still scenarios in real projects where maintaining multi-level nested associations in the UI is necessary, such as: The form itself is a tree structure, which is saved as a whole after editing. Visual UI design, because UI components themselves are tree structures, after users perform a series of visual drag-and-drop designs, the UI component tree is saved as a whole. Jimmer can directly save long association data structures of any shape. If we call a long association data structure with unknown depth a complex form, the save command is designed for complex forms. Here's an example: Java Kotlin Order order = Immutables.createOrder(draft -> { draft.setCustomerId(1L); draft.setProvince(\"Prenzlauer Berg\"); draft.setCity(\"Berlin\"); draft.setAddress(\"Brandenburgische Straße 9, Prenzlauer Berg, Berlin, Germany\"); draft.addIntoItems(item -> { item.setProductId(8L); // Property neither id nor key item.setQuantity(2); }); draft.addIntoItems(item -> { item.setProductId(9L); // Property neither id nor key item.setQuantity(1); }); }); sqlClient.save(order); val order = Order { customerId = 1L province = \"Prenzlauer Berg\" city = \"Berlin\" address = \"Brandenburgische Straße 9, Prenzlauer Berg, Berlin, Germany\" items().addBy { productId = 8L // Property neither id nor key quantity = 2 } items().addBy { productId = 9L // Property neither id nor key quantity = 1 } } sqlClient.save(order) In this example, we can see many short associations, such as Order.customer, OrderItem.product, but these are not the focus here. Here, we should focus on the association Order.items, which is clearly a long association. This operation generates two SQL statements: Insert the root object Order insert into order_( PROVINCE, CITY, ADDRESS, CUSTOMER_ID ) values(?, ?, ?, ?) /*batch-0: [Prenzlauer Berg, Berlin, Brandenburgische Straße 9, Prenzlauer Berg, Berlin, Germany, 1] */ Insert all child objects OrderItem insert into ORDER_ITEM( ORDER_ID, PRODUCT_ID, QUANTITY ) values(?, ?, ?) /* batch-0: [100, 8, 2] */ /* batch-1: [100, 9, 1] */ info As we can see, long associations not only modify the association relationship between the current object and other objects but also cause the associated objects to be saved. If the associated objects also have long associations, they will be saved recursively until there are no more association properties or until a short association is encountered.","s":"1.2. Long Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#12-long-association","p":641},{"i":653,"t":"Forward association is based on foreign keys (whether true or false). Its working mode is to save the associated objects first, then save the root object. Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.9\")); draft.applyStore(store -> { store.setName(\"TURING\"); store.setWebsite(\"https://www.turing.com\"); }); }); sqlClient.save(book); val book = Book { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") store { name = \"TURING\" website = \"https://www.turing.com\" } } sqlClient.save(book) Taking H2 as an example, it generates two SQL statements: First save the associated object BookStore merge into BOOK_STORE( NAME, WEBSITE ) key(NAME) values(?, ?) /* batch-0: [TURING, https://www.turing.com] */ Then save the current object Book merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 100] */ caution When discussing forward associations in work communication, it's recommended to use expressions like \"current object/associated object\" rather than \"parent object/child object\". This is because, for forward associations, the parent-child relationship at the ORM level is completely opposite to that at the database modeling level, which can easily cause confusion and misunderstanding.","s":"2.1. Forward Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#21-forward-association","p":641},{"i":655,"t":"Other associations, such as: Inverse associations of forward associations (like BookStore.books in this tutorial) Associations based on intermediate tables (like Book.authors and Author.books in this tutorial) can all be categorized as backward associations, which are more common scenarios. The working mode of backward associations is easier to understand: save the current object first, then save the associated objects. Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.setWebsite(\"https://www.turing.com\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"RUST programming\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.9\")); }); }); sqlClient .saveCommand(store) // Please ignore this configuration for now .setTargetTransferModeAll(TargetTransferMode.ALLOWED) .execute(); val store = BookStore { name = \"TURING\" website = \"https://www.turing.com\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"RUST programming\" edition = 2 price = BigDecimal(\"39.9\") } } sqlClient.save(store) { // Please ignore this configuration for now setTargetTransferModeAll(TargetTransferMode.ALLOWED) } Taking H2 as an example, it generates three SQL statements: First save the current object BookStore merge into BOOK_STORE( NAME, WEBSITE ) key( NAME ) values(?, ?) /* batch-0: [TURING, https://www.turing.com] */ Then save the associated objects Book merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 100] */ /* batch-1: [RUST programming, 2, 39.9, 100] */ The third SQL statement is not relevant to the topic being discussed here, so it's omitted info Backward associations have richer functionality than forward associations. This tutorial will focus on discussing backward associations.","s":"2.2. Backward Association","u":"/jimmer-doc/docs/mutation/save-command/association/classification","h":"#22-backward-association","p":641},{"i":657,"t":"Jimmer provides DTO language. Developers can use this language to quickly define the shape of the Input DTO to be saved. After compilation: The corresponding Java/Kotlin Input DTO classes will be generated automatically The mutual conversion logic between Input DTOs and entities will be generated automatically The object fetcher that matches its shape will be automatically generated. (This feature is unrelated to input DTOs, so it is not discussed in this article) Developers use the auto-generated Input DTOs as method parameters, and persist them in one line of code (Internal logic: Call the auto-generated conversion logic to convert the Input DTO to a dynamic entity object, then directly persist using the save command). info This is the most efficient way to eliminate the pain of Input DTO explosion.","s":"Using DTO Language","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"","p":656},{"i":659,"t":"This article focuses on explaining how to save static DTO types, not a systematic introduction to DTO language. Please refer to Object/DTO conversion/DTO Language to know more. Assume the fully qualified name of the Book class is com.yourcompany.yourproject.model.Book. You can: In the project where entity is defined, create directory src/main/dto Under src/main/dto, create subdirectories following the package path of the entity, i.e. com/yourcompany/yourproject/model Under the directory created in previous step, create the file Book.dto. The file must have the same name as the entity class and the extension must be dto. Edit this file and use DTO language to define various DTO shapes for the Book entity: Book.dto input BookInput { #allScalars(Book) id(store) authors { #allScalars(Author) -id } } input SimpleBookInput { ... } ...Other Input DTO shapes omitted... info Input DTO shapes used as input parameters must be decorated with the input modifier. The specific reasons are elaborated in Object/DTO conversion/DTO Language and not repeated here.","s":"Defining DTO Shape","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#defining-dto-shape","p":656},{"i":661,"t":"Jimmer is responsible for compiling dto files and automatically generating DTO types conforming to these shapes. caution If Java/Kotlin source files other than dto files are modified, directly clicking the Run button in IDE can trigger recompilation of dto files. However, if no Java/Kotlin files other than dto files are modified, simply clicking the Run button in IDE will not trigger dto file recompilation unless rebuild is explicitly triggered! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle Take BookInput in the above code as an example. After successful compilation of this dto file, the following DTO types will be auto-generated: Java Kotlin BookInput.java package com.yourcompany.yourproject.model.dto; import com.yourcompany.yourproject.model.Book; import org.babyfish.jimmer.Input; @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookInput implements Input { @Nullable private Long id; ❶ private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; ❷ private List authors; ❸ public BookInput(Book book) { ❹ ... } @Override public Book toEntity() { ❺ ... } @Data public static class TargetOf_authors { private String firstName; private String lastName; private Gender gender; ...Other members omitted... } ...Other members omitted... } BookInput.kt package com.yourcompany.yourproject.model.dto import com.yourcompany.yourproject.model.Book import org.babyfish.jimmer.Input @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookInput( val id: Long? = null, ❶ val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val storeId: Long? = null, ❷ val authors: List = emptyList() ❸ ): Input { constructor(book: Book) : this(...) ❹ override fun toEntity(): Book = ... ❺ data class TargetOf_authors( val firstName: String, val lastName: String, val gender: Gender ) { ...Other members omitted... } ...Other members omitted... } ❶ If the id is designated some auto-generation strategy, it is not required. This is also a feature of save commands, see details in Mutation/Save Command/Save Mode/Summary. info For Jimmer entities, id cannot be null. Missing id (i.e. not assigning it) represents the object does not have an id. For Input DTOs, static POJO types do not have the concept of missing properties. null represents missing id. This seems contradictory, but can be handled simply: If Input DTO's id is null, the converted entity object will not have an id (although id of entity cannot be assigned null, dynamic objects allow unspecified properties). ❷ Explicitly specifies this Input DTO wants to edit the entity's many-to-one association Book.store using the short association mode. ❸ Explicitly specifies this Input DTO wants to edit the entity's many-to-many association Book.authors using the long association mode. The type of associated objects is also fixed to the nested Input DTO type BookInput.TargetOf_authors. ❹ Convert dynamic entity to static Input DTO ❺ Convert static Input DTO to dynamic entity","s":"Auto-Generated DTO Types","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#auto-generated-dto-types","p":656},{"i":663,"t":"The DTO language generates relatively complete code, so we can quickly expose HTTP APIs to persist data: Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody BookInput input ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input); } @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input) }","s":"HTTP API","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#http-api","p":656},{"i":665,"t":"In real projects, we often face the problem that entities may have many properties, and Relatively more properties need to be specified during insertion Relatively fewer properties need to be specified during modification The Book entity we consistently use as example has few properties and is inconvenient to demonstrate this. So I make up an entity type Product with more properties: Java Kotlin Product.java @Entity public interface Product { ...Many entity properties, omitted... } Product.kt @Entity interface Product { ...Many entity properties, omitted... } For insertion which requires specifying relatively more properties, define CreateProductInput. For modification which requires specifying relatively fewer properties, define UpdateProductInput. So the Product.dto code looks like: input CreateProductInput { ...More properties, omitted... } input UpdateProductInput { ...Fewer properties, omitted... } After compilation, CreateProductInput and UpdateProductInput Java/Kotlin classes will be auto-generated. So we can quickly implement the following two HTTP APIs: Java Kotlin @PostMapping(\"/product\") public void createProduct( // `CreateProductInput` has relatively more properties @RequestBody CreateProductInput input ) { productRepository.insert(input); } @PutMapping(\"/product\") public void updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody UpdateProductInput input ) { productRepository.update(input); } @PostMapping(\"/product\") fun createProduct( // `CreateProductInput` has relatively more properties @RequestBody input: CreateProductInput ) { productRepository.insert(input) } @PutMapping(\"/product\") fun updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody input: UpdateProductInput ) { productRepository.update(input) } tip As you can see, no matter how many different Input DTO types need to be defined for the same entity according to project requirements, we can quickly generate Input DTO types and related data conversion logic using DTO language, then persist in one line of code calling save commands. Even if the project is more complex, e.g. people with different identities can edit data structures of different shapes, this pattern can still be applied repeatedly to handle such scenarios easily.","s":"Best Practices","u":"/jimmer-doc/docs/mutation/save-command/input-dto/dto-lang","h":"#best-practices","p":656},{"i":667,"t":"caution Not recommended for Kotlin. This solution is based on MapStruct, which relies on apt. Kotlin has deprecated kapt in favor of ksp. So as Kotlin evolves, using kapt may cause more and more problems in the future.","s":"Using MapStruct","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"","p":666},{"i":669,"t":"Let's look at an example InputDTO (for simplicity, Java version uses Lombok): Java Kotlin BookInput.java @Data public class BookInput { @Nullable private Long id; ❶ private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; ❷ private List authors; ❸ @Data public static class AuthorItem { private String firstName; private String lastName; private Gender gender; } } BookInput.kt data class BookInput( val id: Long? = null, ❶ val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, ❷ val authors: List ❸ ) { data class AuthorItem( val firstName: String, val lastName: String, val gender: Gender ) } ❶ If the id is designated some auto-generation strategy, it is not required. This is also a feature of save commands, see details in Save Modes/Summary. info For Jimmer entities, id cannot be null. Missing id (i.e. not assigning it) represents the object does not have an id. For Input DTOs, static POJO types do not have the concept of missing properties. null represents missing id. This seems contradictory and difficult to convert between. Don't worry, Jimmer provides automated solutions, discussed later. ❷ Explicitly specifies this Input DTO wants to edit the entity's many-to-one association Book.store using the short association mode. ❸ Explicitly specifies this Input DTO wants to edit the entity's many-to-many association Book.authors using the long association mode. The type of associated objects is also fixed to the nested Input DTO type BookInput.AuthorItem.","s":"Define Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#define-input-dto","p":666},{"i":671,"t":"Jimmer extends MapStruct which can be used to handle conversions between dynamic entities and static Input DTOs. How to use the relevant extensions is detailed in Object/DTO Conversion/MapStruct, this article will not repeat it. Define the BookInputMapper interface: Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); ...Other mapstruct configurations omitted... } BookInputMapper.kt @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(BookInput input): Book ...Other mapstruct configurations omitted... } info MapStruct's annotation processor needs to be used to generate the implementation class for this interface at compile time. Details are explained in Object Section/DTO Mapping/MapStruct and not repeated here.","s":"MapStruct Converter","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#mapstruct-converter","p":666},{"i":673,"t":"Java Kotlin private static final BookInputMapper BOOK_INPUT_MAPPER = Mappers.getMapper(BookInputMapper.class); @PutMapping(\"/book\") public void saveBook( @RequestBody BookInput input ) { bookRepository.save( BOOK_INPUT_MAPPER.toBook(input) ); } @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ) { bookRepository.save( BOOK_INPUT_MAPPER.toBook(input) ) companion object { private val BOOK_INPUT_MAPPER = Mappers.getMapper(BookInputMapper::class.java) } } In this example, MapStruct is used to convert BookInput to Book entity and directly persist it. info For Jimmer entities, Book.id cannot be null. Missing id (i.e. not assigning it) represents the object does not have an id. For Input DTO, static POJO type, BookInput.id being null represents missing id. Jimmer has built-in extensions to MapStruct that will not assign BookInput.id to Book.id if it is null, so there are no issues.","s":"HTTP API","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#http-api","p":666},{"i":675,"t":"To better integrate with Jimmer, developers can make BookInput implement the org.babyfish.jimmer.Input interface: public interface Input { E toEntity(); } Dynamic objects will never implement this interface. It should be implemented by user-defined static POJO classes. Its functionality is simple: convert the current static POJO to a dynamic object. Make BookInput implement Input: Java Kotlin BookInput.java @Data public class BookInput implements Input { private static final Converter CONVERTER = Mappers.getMapper(Converter.class); ...Private fields omitted... @Override public Book toEntity() { return CONVERTER.toBook(this); } @Mapper interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); ...Other mapstruct configurations omitted... } ...AuthorItem definition omitted... } BookInput.kt data class BookInput( ... ) : Input { override fun toEntity(): Book = CONVERTER.toBook(this) @Mapper internal interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(input: BookInput): Book ...Other mapstruct configurations omitted... } companion object { @JvmStatic private val CONVERTER = Mappers.getMapper(Converter::class.java) } ...AuthorItem definition omitted... } info In this improved example, the previously introduced BookInputMapper is replaced by BookInput.Converter, so the previous BookInputMapper can be deleted. Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody BookInput input ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input); } @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ) { // `save(input)` is equivalent to `save(input.toEntity())` bookRepository.save(input) } info Leveraging the Input interface to change coding style is recommended but not mandatory.","s":"Improvement","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#improvement","p":666},{"i":677,"t":"In real projects, we often face the problem that entities may have many properties, and Relatively more properties need to be specified during insertion Relatively fewer properties need to be specified during modification The Book entity we consistently use as example has few properties and is inconvenient to demonstrate this. So I make up an entity type Product with more properties: Java Kotlin Product.java @Entity public interface Product { ...Many entity properties, omitted... } Product.kt @Entity interface Product { ...Many entity properties, omitted... } For insertion which requires specifying relatively more properties, define CreateProductInput: Java Kotlin CreateProductInput.java @Data public class CreateProductInput implements Input { ...More fields, omitted... @Override public Product toEntity() { ... } } CreateProductInput.kt data class CreateProductInput( ...More fields, omitted... ) : Input { override fun toEntity(): Product { ... } } For modification which requires specifying relatively fewer properties, define UpdateProductInput: Java Kotlin UpdateProductInput.java @Data public class UpdateProductInput implements Input { ...Fewer fields, omitted... @Override public Product toEntity() { ... } } UpdateProductInput.kt data class UpdateProductInput( ...Fewer fields, omitted... ) : Input { override fun toEntity(): Product { ... } } Finally, provide two HTTP APIs: Java Kotlin @PostMapping(\"/product\") public void createProduct( // `CreateProductInput` has relatively more properties @RequestBody CreateProductInput input ) { productRepository.insert(input); } @PutMapping(\"/product\") public void updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody UpdateProductInput input ) { productRepository.update(input); } @PostMapping(\"/product\") fun createProduct( // `CreateProductInput` has relatively more properties @RequestBody input: CreateProductInput ) { productRepository.insert(input) } @PutMapping(\"/product\") fun updateProduct( // `UpdateProductInput` has relatively fewer properties @RequestBody input: UpdateProductInput ) { productRepository.update(input) } tip As you can see, no matter how many different Input DTO types need to be defined for the same entity according to project requirements, we can always use MapStruct to convert them into the uniform dynamic entity type, then persist in one line of code calling save commands. Even if the project is more complex, e.g. people with different identities can edit data structures of different shapes, this pattern can still be applied repeatedly to handle such scenarios easily.","s":"Best Practices","u":"/jimmer-doc/docs/mutation/save-command/input-dto/mapstruct","h":"#best-practices","p":666},{"i":679,"t":"When saving associated objects using the association mode AssociatedSaveMode.REPLACE, there is an important concept: dissociation operation.","s":"Dissociation Operations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"","p":678},{"i":681,"t":"Existing Database Structure User's Expected Data Structure +-Food | | | +-----Meat(ignore child nodes) | \\-----Bread(ignore child nodes) +-Food | +-----Drinks(ignore child nodes) | | | \\-----Bread(ignore child nodes) For Bread, it exists in both old and new data structures, corresponding to an UPDATE operation For Drinks, it doesn't exist in the old data structure but exists in the new data, corresponding to an INSERT operation For Meat, it exists in the old data structure but not in the new data, corresponding to an operation called dissociation operation. Dissociation applies to two types of associations: Middle table associations Obviously, middle table associations refer to associations like Book.authors and Author.books in this tutorial. Their dissociation operation is very simple, just deleting the association in the middle table, without affecting the associated objects themselves. Child table associations Child table associations refer to inverse associations based on foreign keys (whether real or fake), such as BookStore.books in this tutorial. Their dissociation operation is relatively complex. Developers can control specific dissociation behavior through configuration. Next, let's discuss these two types of dissociation operations.","s":"Concept","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#concept","p":678},{"i":683,"t":"We've already demonstrated this simplest form of dissociation when introducing the REPLACE save mode for associated objects. Therefore, we won't repeat it here.","s":"Dissociating Middle Table Associations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#dissociating-middle-table-associations","p":678},{"i":685,"t":"Child table associations refer to inverse associations based on foreign keys (whether real or fake), such as BookStore.books. Their dissociation operation is relatively complex. Developers can configure the dissociation mode for properties corresponding to foreign keys (such as Book.store here) to achieve different dissociation behaviors.","s":"Dissociating Child Table Associations","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#dissociating-child-table-associations","p":678},{"i":687,"t":"There are 5 modes for child object dissociation operations Mode Description NONE (Default) Depends on global configuration jimmer.default-dissociate-action-checking If jimmer.default-dissociate-action-checking is true (default) or the foreign key upon which the current association is based is real (foreign key constraint exists in database, see Real and Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-checking is false and the foreign key upon which the current association is based is fake (no corresponding foreign key constraint in database, see Real and Fake Foreign Keys), treated as LAX. LAX Dissociation operation performs no action. If the foreign key is real (see Real and Fake Foreign Keys), when parent object is deleted: If cascade delete behavior is configured for the database foreign key (on cascade set null or on delete delete), database automatically clears the foreign key of dissociated child objects or automatically deletes the dissociated child objects Although database-level cascade modification performs better than ORM-level cascade modification, the ORM is unaware of this. Use with caution in projects requiring cache consistency Otherwise, database reports an error and the save command is terminated If the foreign key is fake (see Real and Fake Foreign Keys), when parent object is deleted, no additional behavior occurs, allowing dangling issues with child object foreign key values Even if fake foreign key values are invalid dangling values, jimmer queries won't error - the query system will return null for parent objects rather than error due to non-existent parent CHECK Does not support dissociation operations. Throws exception to prevent operation if current parent object in database has child objects that need to be dissociated. SET_NULL Sets the foreign key of dissociated child objects to null. This mode requires that the child object's foreign key property is nullable; otherwise attempting this configuration will cause an exception. DELETE Deletes the dissociated child objects. There are two ways to configure dissociation mode: Static configuration using annotations on entities, which is global. Dynamic configuration in code, which can override static configuration but only affects the current save command. Taking SET_NULL as an example: Static entity-based configuration (chosen in most cases, used by the majority of business logic) Java Kotlin Book.java @Entity public interface Book { @OnDissociate(DissociateAction.SET_NULL) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity interface Book { @OnDissociate(DissociateAction.SET_NULL) @ManyToOne val store: BookStore? ...omitted other code... } Dynamic save command-based configuration (only for individual save commands, used by very few businesses with special requirements) Java Kotlin sqlClient .getEntities() .saveCommand(book) .setDissociateAction( BookProps.STORE, DissociateAction.SET_NULL ) .execute(); sqlClient.save(book) { setDissociateAction( Book::store, DissociateAction.SET_NULL ) }","s":"Dissociation Modes","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#dissociation-modes","p":678},{"i":689,"t":"Next, let's explain various dissociation modes through saving data structures containing one-to-many association BookStore.books. Here's the save code: Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"O'REILLY\"); draft.addIntoBooks(book -> { book.setName(\"Learning GraphQL\"); book.setEdition(3); book.setPrice(new BigDecimal(\"51.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Learning GraphQL\"); book.setEdition(4); book.setPrice(new BigDecimal(\"43.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Effective TypeScript\"); book.setEdition(3); book.setPrice(new BigDecimal(\"88.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Effective TypeScript\"); book.setEdition(4); book.setPrice(new BigDecimal(\"85.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming TypeScript\"); book.setEdition(3); book.setPrice(new BigDecimal(\"48.9\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming TypeScript\"); book.setEdition(4); book.setPrice(new BigDecimal(\"47.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"GraphQL in Action\"); book.setEdition(3); book.setPrice(new BigDecimal(\"80.9\")); }); draft.addIntoBooks(book -> { book.setName(\"GraphQL in Action\"); book.setEdition(4); book.setPrice(new BigDecimal(\"81.9\")); }); }) ); sqlClient.saveEntities( stores, // This parameter can be omitted, for the `save` method, // AssociatedSaveMode defaults to REPLACE AssociatedSaveMode.REPLACE ); val stores = listOf( BookStore { name = \"O'REILLY\" books().addBy { name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"51.9\") } books().addBy { name = \"Learning GraphQL\" edition = 4 price = BigDecimal(\"32.9\") } books().addBy { name = \"Effective TypeScript\" edition = 3 price = BigDecimal(\"88.9\") } books().addBy { name = \"Effective TypeScript\" edition = 4 price = BigDecimal(\"85.9\") } books().addBy { name = \"Programming TypeScript\" edition = 3 price = BigDecimal(\"48.9\") } books().addBy { name = \"Programming TypeScript\" edition = 4 price = BigDecimal(\"47.9\") } }, BookStore { name = \"MANNING\" books().addBy { name = \"GraphQL in Action\" edition = 3 price = BigDecimal(\"80.9\") } books().addBy { name = \"GraphQL in Action\" edition = 4 price = BigDecimal(\"81.9\") } } ) sqlClient.saveEntities( stores, // This parameter can be omitted, for the `save` method, // AssociatedSaveMode defaults to REPLACE AssociatedSaveMode.REPLACE ) Comparison between old and new objects: Existing Database Data Data User Wants to Save --+-O'REILLY | +---Learn GraphQL(edition = 1) | +---Learn GraphQL(edition = 2) | +---Learn GraphQL(edition = 3) | | | +---Effective TypeScript(edition = 1) | +---Effective TypeScript(edition = 2) | +---Effective TypeScript(edition = 3) | | | +---Programming TypeScript(edition = 1) | +---Programming TypeScript(edition = 2) | \\---Programming TypeScript(edition = 3) --+-O'REILLY | | | | | +---Learn GraphQL(edition = 3) | +---Learn GraphQL(edition = 4) | | | | | +---Effective TypeScript(edition = 3) | +---Effective TypeScript(edition = 4) | | | | | +---Programming TypeScript(edition = 3) | \\---Programming TypeScript(edition = 4) --+-MANNING | +---GraphQL in Action(edition = 1) | +---GraphQL in Action(edition = 2) | \\---GraphQL in Action(edition = 3) --+-MANNING | | | | | +---GraphQL in Action(edition = 3) | \\---GraphQL in Action(edition = 4) info Among them, the 8 associated objects that are no longer needed, i.e., the 8 objects that need to be dissociated, are highlighted. So, how will Jimmer dissociate these associated objects? In fact, different dissociation configurations will lead to different dissociation behaviors.","s":"Save Code","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#save-code","p":678},{"i":691,"t":"NONE's behavior is not fixed, but depends on the global configuration jimmer.default-dissociate-action-check: If jimmer.default-dissociate-action-check is true (default) or if the current association is based on a real foreign key (foreign key constraint exists in database, see Real vs Fake Foreign Keys), treated as CHECK. If jimmer.default-dissociate-action-check is false and the current association is based on a fake foreign key (no corresponding foreign key constraint in database, see Real vs Fake Foreign Keys), treated as LAX.","s":"1. NONE (Default)","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#1-none-default","p":678},{"i":693,"t":"Dissociate mode LAX means the dissociation operation does nothing. Associated save mode AssociatedSaveMode.REPLACE means unnecessary associations need to be discarded. Clearly, these two rules conflict. In this case, AssociatedSaveMode.REPLACE takes precedence, LAX is ignored, and it's ultimately treated as CHECK. Therefore, we cannot demonstrate LAX through this article. To understand how LAX works, please see Delete Command.","s":"2. LAX","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#2-lax","p":678},{"i":695,"t":"CHECK mode does not allow dissociating associated objects. Jimmer will check if there are objects that need to be dissociated, and if they exist, throws an exception. The dissociate mode can be set either through the entity definition or through the save command. Here, we set the dissociate mode for Book.store through entity configuration: Java Kotlin Book.java @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) public interface Book { @OnDissociate(DissociateAction.CHECK) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) interface Book { @OnDissociate(DissociateAction.CHECK) @ManyToOne val store: BookStore? ...omitted other code... } To demonstrate simpler SQL generation, let's assume sqlClient's targetTransferable feature is enabled, which was previously discussed, see here Running the save code from before will generate three SQL statements: Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Saving associations and associated objects is also not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key udpate /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ Check if there are objects that need to be dissociated (if any exist, throws exception to prevent save command) select tb_1_.ID from BOOK tb_1_ where tb_1_.STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and (tb_1_.STORE_ID, tb_1_.ID) not in ( (? /* 1 */, ? /* 3 */), (? /* 1 */, ? /* 100 */), (? /* 1 */, ? /* 6 */), (? /* 1 */, ? /* 101 */), (? /* 1 */, ? /* 9 */), (? /* 1 */, ? /* 102 */), (? /* 2 */, ? /* 12 */), (? /* 2 */, ? /* 103 */) ) limit ? /* 1 */ After this SQL check, some Book objects that will be dissociated are found through the saved BookStore objects' Book.authors property. However, they do not agree to be dissociated and throw the following exception: Save error caused by the path: \".books\": Cannot dissociate child objects because the dissociation action of the many-to-one property \"com.yourcommany.yourproject.model.Book.store\" is not configured as \"set null\" or \"cascade\". There are two ways to resolve this issue: Decorate the many-to-one property \"com.yourcommany.yourproject.model.Bookstore\" by @org.babyfish.jimmer.sql.OnDissociate whose argument is `DissociateAction.SET_NULL` or `DissociateAction.DELETE`, or use save command's runtime configuration to override it","s":"3. CHECK","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#3-check","p":678},{"i":697,"t":"SET_NULL mode achieves dissociation by setting the associated object's foreign key property to null. caution SET_NULL mode requires that the foreign key-based property (here Book.store) must be nullable, otherwise it will cause a compilation error The dissociate mode can be set either through the entity definition or through the save command. Here, we set the dissociate mode for Book.store through entity configuration: Java Kotlin Book.java @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) public interface Book { @OnDissociate(DissociateAction.SET_NULL) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) interface Book { @OnDissociate(DissociateAction.SET_NULL) @ManyToOne val store: BookStore? ...omitted other code... } To demonstrate simpler SQL generation, let's assume sqlClient's targetTransferable feature is enabled, which was previously discussed, see here Running the save code from before will generate three SQL statements: Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Saving associations and associated objects is also not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key udpate /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ Set foreign keys to null for all objects being dissociated H2 MySQL Postgres update BOOK set STORE_ID = null where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ update BOOK set STORE_ID = null where STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and (STORE_ID, ID) not in ( (? /* 1 */, ? /* 3 */), (? /* 1 */, ? /* 100 */), (? /* 1 */, ? /* 6 */), (? /* 1 */, ? /* 101 */), (? /* 1 */, ? /* 9 */), (? /* 1 */, ? /* 102 */), (? /* 2 */, ? /* 12 */), (? /* 2 */, ? /* 103 */) ) update BOOK set STORE_ID = null where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ We can see significant differences between databases: H2 and Postgres use batched simple SQL MySQL uses a single complex SQL info This is because H2 and Postgres support the =any(array) syntax, while MySQL does not.","s":"4. SET_NULL","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#4-set_null","p":678},{"i":699,"t":"DELETE mode achieves dissociation by deleting the associated objects. info Here when saving BookStore, we perform dissociation on the BookStore.books association, where DELETE mode indicates we want to delete unnecessary Book objects. However, since the Book entity has a deeper association Book.authors, we need to consider how to dissociate Author objects before deleting Book objects. In fact, if objects that need to be deleted due to dissociation have deeper associations, it evolves into a recursive deletion problem. This behavior is detailed in Delete Command, which we won't discuss here. Therefore, to simplify the discussion, we'll temporarily ignore the Author entity and assume the current system only has BookStore and Book entity types. The dissociate mode can be set either through the entity definition or through the save command. Here, we set the dissociate mode for Book.store through entity configuration: Java Kotlin Book.java @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) public interface Book { @OnDissociate(DissociateAction.DELETE) @Nullable @ManyToOne BookStore store(); ...omitted other code... } Book.kt @Entity @KeyUniqueConstraint(noMoreUniqueConstraints = true) interface Book { @OnDissociate(DissociateAction.DELETE) @ManyToOne val store: BookStore? ...omitted other code... } To demonstrate simpler SQL generation, let's assume sqlClient's targetTransferable feature is enabled, which was previously discussed, see here Running the save code from before will generate three SQL statements: Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Saving associations and associated objects is also not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key udpate /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 51.9, 1] */ /* batch-1: [Learning GraphQL, 4, 43.9, 1] */ /* batch-2: [Effective TypeScript, 3, 88.9, 1] */ /* batch-3: [Effective TypeScript, 4, 85.9, 1] */ /* batch-4: [Programming TypeScript, 3, 48.9, 1] */ /* batch-5: [Programming TypeScript, 4, 47.9, 1] */ /* batch-6: [GraphQL in Action, 3, 80.9, 2] */ /* batch-7: [GraphQL in Action, 4, 81.9, 2] */ Delete all objects that need to be dissociated H2 MySQL Postgres delete from BOOK where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ delete from BOOK where STORE_ID in ( ? /* 1 */, ? /* 2 */ ) and (STORE_ID, ID) not in ( (? /* 1 */, ? /* 3 */), (? /* 1 */, ? /* 100 */), (? /* 1 */, ? /* 6 */), (? /* 1 */, ? /* 101 */), (? /* 1 */, ? /* 9 */), (? /* 1 */, ? /* 102 */), (? /* 2 */, ? /* 12 */), (? /* 2 */, ? /* 103 */) ) delete from BOOK where STORE_ID = ? and not ( ID = any(?) ) /* batch-0: [1, [3, 100, 6, 101, 9, 102]] */ /* batch-1: [2, [12, 103]] */ We can see significant differences between databases: H2 and Postgres use batched simple SQL MySQL uses a single complex SQL info This is because H2 and Postgres support the =any(array) syntax, while MySQL does not.","s":"5. DELETE","u":"/jimmer-doc/docs/mutation/save-command/association/dissociation","h":"#5-delete","p":678},{"i":701,"t":"In this article we discuss: The problem of using dynamic entities as method parameters Solutions Comparison with GraphQLInput","s":"Problem","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"","p":700},{"i":703,"t":"Up to this point, we have systematically explained all the capabilities of save command. Now we know that no matter what shape the data structure to be saved is, we can persist it to the database in one line of code calling save command, with all internal details hidden. This is a very convenient low-level capability. However, how should the upper layer APIs of business systems be designed? Should we directly accept dynamic objects via @RequestBody? Java Kotlin @PutMapping(\"/book\") public void saveBook( @RequestBody Book book ) { bookRepository.save(book); } @PutMapping(\"/book\") fun saveBook( @RequestBody book: Book ) { bookRepository.save(book) } This code can work, allowing HTTP clients to submit data structures of arbitrary shapes. This seems to be an extremely powerful capability. However, this approach has two problems: Security issue API ambiguity","s":"Problem of Dynamic Entities Parameters","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#problem-of-dynamic-entities-parameters","p":700},{"i":705,"t":"The client is granted too much power, being able to submit very deep and wide tree-shaped data structures that far exceed its allowed scope of modification under current security policies. This is a huge security vulnerability. For example, the client can totally submit data like: { \"name\": \"SQL in Motion\", \"edition\": 1, \"price\": 41.99, \"store\":{ \"name\": \"MANNING\", \"location\": { \"city\": \"Vancouver\", \"country\": \"Canada\", ... } }, \"authors\":[ { \"firstName\": \"Ben\", \"lastName\": \"Brumm\", \"job\":{ \"company\": { \"name\": \"IBM\" }, \"title\": \"Senior HR Manager\", ... } ... } ] } Assume your intention in providing this HTTP API is that only the BOOK, BOOK_STORE, AUTHOR and BOOK_AUTHOR_MAPPING tables can be affected. However, now the scope of data submitted by the client is too large, with far greater destructive power than you anticipated. In the above example, there are at least 4 unexpected destructions: .store.location.city is modified from New York to Vancouver .store.location.country is modified from USA to Canada .authors[0].job.company is modified from NAB to IBM .authors[0].job.title is modified from Senior Business Analyst to Senior HR Manager warning Using @RequestBody to directly accept dynamic objects as input parameters in external APIs is very dangerous and will lead to serious security issues. Therefore, save commands must be sealed internally as a low-level capability, and their raw capabilities must absolutely not be directly exposed through HTTP APIs.","s":"Security Issue","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#security-issue","p":700},{"i":707,"t":"Using dynamic objects as parameters leads to ambiguity in the API. Client developers do not know which fields are decided automatically by the business system and which must be specified by themselves, so they do not know how to invoke the API properly. This issue is especially obvious for insert operations. Unlike update operations which can modify just a few properties, insert operations often need to specify many properties, otherwise exceptions will occur. Client developers are unclear about exactly which properties must be specified to avoid errors.","s":"API Ambiguity","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#api-ambiguity","p":700},{"i":709,"t":"To resolve this issue, Jimmer provides three solutions: Lonely Form caution This is a very crude solution, only for learning or very simple projects. This solution only handles data persistence operations on a single table, and only resolves the security issue rather than the API ambiguity issue. It is also the only solution that does not require defining Input DTOs. Auto-Generated Input DTOs via DTO Language This solution quickly auto-generates Input DTOs with very little cost. It is a complete and extremely convenient solution, so is the recommended approach. Its huge convenience advantage will be introduced later. info All built-in examples use this solution. Manual Input DTOs via MapStruct This solution requires developers to manually create Input DTOs and handle conversion to dynamic objects. It is absolutely flexible, but requires a lot of work from developers.","s":"Solutions","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#solutions","p":700},{"i":711,"t":"The above introduces three solutions. Among them, although the latter two solutions differ greatly, they share one commonality - relying on Input DTOs. Comparing Jimmer's Input DTOs with GraphQLInput: Similarities In GraphQL, query results are GraphQLObjects, i.e. dynamic objects of arbitrary shapes. However, if mutation operations accept object parameters, they must be GraphQLInputs, i.e. static objects of fixed shapes. GraphQLInput has exactly the same idea as InputDTO here, which is the inevitable design to resolve security issues - different routes leading to the same destination. Differences GraphQLInput is just a protocol, merely constraining that object parameters for modification operations must be static objects of fixed shapes. The benefit is not limiting specific implementation technologies, but the downside is the persistence business logic needs to be implemented by developers for every specific GraphQLInput shape. Tedious work still exists objectively, and developers can truly feel the pain of Input DTO explosion. Jimmer's InputDTO is just an alternative representation of the dynamic entity to address security issues. Once the user finishes converting Input DTO to dynamic entity, the huge convenience of persisting arbitrary shaped data structures in one line of code via save commands can still be enjoyed. If developers adopt the Auto-Generated Input DTOs via DTO Language solution, Input DTO classes will be auto-generated, and the conversion logic between Input DTOs and dynamic entities will also be auto-generated. Thus the pain of Input DTO explosion no longer exists. So this is the recommended solution.","s":"Comparison with GraphQLInput","u":"/jimmer-doc/docs/mutation/save-command/input-dto/problem","h":"#comparison-with-graphqlinput","p":700},{"i":714,"t":"The result returned by a save command is an object, e.g. SimpleSaveResult/KSimpleSaveResult for the save method that saves a single object. The result supports the following behaviors: originalEntity property: Returns the original parameter passed to the save method by the developer. modifiedEntity property: A data structure identical in shape to originalEntity, with the differences: If originalEntity contains some objects without id properties that rely on id generation strategies (e.g. auto increment, sequence, UUID, snowflake id etc.), the corresponding objects in modifiedEntity will necessarily have the id property set to the value automatically assigned by the database/application. If some objects belong to entity types with optimistic locking fields, the version properties of the corresponding objects in modifiedEntity will have the latest version number after modification. info modifiedEntity is discussed many times in previous docs, so is not elaborated here. totalAffectedRowCount property: The execution of a save command may modify multiple tables in the database. This property summarizes the total number of affected rows across all modified tables. getAffectedRowCountMap property: A map of affected tables and their affected row counts. getAffectedRowCount method, taking a parameter to get the affected row count of the specified table. Accepts two kinds of parameters: Entity type: Gets affected row count of the table corresponding to this entity type. Association property based on join table: Gets affected row count of the join table corresponding to this association property. Let's look at some examples of the totalAffectedRowCount property and getAffectedRowCount method: Java Kotlin SimpleSaveResult result = sqlClient.update( Immutables.createBook(draft -> { draft.setId(3L); draft.setPrice(new BigDecimal(\"59.9\")); draft.addIntoAuthors(author -> author.setId(1L)); draft.addIntoAuthors(author -> author.setId(3L)); draft.addIntoAuthors(author -> { author.setId(1000L); // does not exist, created automatically author.setFirstName(\"Svetlana\"); author.setLastName(\"Isakova\"); author.setGender(Gender.FEMALE); }); }) ); System.out.println( \"Total affected row count: \" + result.getTotalAffectedRowCount() ); System.out.println( \"Affected row count for entity table BOOK: \" + result.getAffectedRowCount(Book.class) ); System.out.println( \"Affected row count for entity table AUTHOR: \" + result.getAffectedRowCount(Author.class) ); System.out.println( \"Affected row count for join table BOOK_AUTHOR_MAPPING: \" + result.getAffectedRowCount(BookProps.AUTHORS) ); val result = sqlClient.update( Book { id = 3L price = BigDecimal(\"59.9\")) authors().addBy { id = 1L } authors().addBy { id = 3L } authors().addBy { id = 1000L // does not exist, created automatically firstName = \"Svetlana\" lastName = \"Isakova\" gender = Gender.FEMALE } } ); println( \"Total affected row count: \" + result.totalAffectedRowCount ) println( \"Affected row count for entity table BOOK: \" + result.getAffectedRowCount(Book::class) ) println( \"Affected row count for entity table AUTHOR: \" + result.getAffectedRowCount(Author::class) ) println( \"Affected row count for join table BOOK_AUTHOR_MAPPING: \" + result.getAffectedRowCount(Book::authors) ) tip The code getAffectedRowCount(BookProps.AUTHORS) is equivalent to getAffectedRowCount(AuthorProps.BOOKS) The printed result is: Total affected row count: 5 Affected row count for entity table BOOK: 1 Affected row count for entity table AUTHOR: 1 Affected row count for join table BOOK_AUTHOR_MAPPING: 3 The explanation is: The affected row count for table BOOK is 1: The price of the aggregate root object Book(id=3L) is modified. The affected row count for table AUTHOR is 1: The associated object Author(id=1000L) does not exist and is created automatically. The affected row count for table BOOK_AUTHOR_MAPPING is 3: Dissociation between Book(id=3L) and Author(id=2L) (For dissociation operations on join tables, this is deleting the association). New association between Book(id=3L) and Author(id=3L). New association between Book(id=3L) and Author(id=1000L).","s":"Save Command Result","u":"/jimmer-doc/docs/mutation/save-command/other","h":"#save-command-result","p":712},{"i":717,"t":"In the previous article, we introduced how to control the save mode of aggregate root objects. This article will discuss how to control the save mode of associated objects. Associated objects support the following save modes: Association Save Mode Applicable Scope Accept Wild Objects Description APPEND All associations Yes Unconditionally perform INSERT operation on associated objects APPEND_IF_ABSENT All associations No First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, ignore the operation and do nothing Otherwise, insert the associated object note Jimmer will try to utilize the database's native UPSERT capability to combine these two steps. If not possible, it will inform the user why UPDATE All associations Yes If the id property of the associated object is specified, update the associated object by id Otherwise, update the associated object by key MERGE All associations No First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, update it Otherwise, insert the associated object note Jimmer will try to utilize the database's native UPSERT capability to combine these two steps. If not possible, it will inform the user why REPLACE Post associations No Based on MERGE, perform dissociate operation on no longer needed associated objects VIOLENTLY_REPLACE Post associations Yes Make Jimmer no longer search for changes in associations (or association collections) by id or key, but execute the following two operations First delete all old associations and related objects of the current object Then reinsert all associated objects and rebuild associations with the current object This is a very aggressive association update approach with the following pros and cons Pros: Accepts wild associated objects, no longer requires associated objects to either specify id or key Cons: If there are many associated objects, in most cases, this is a low-performance solution If associated objects have deeper associations, the deletion in step 1 may cause too deep cascade deletion, leading to loss of too much data","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#basic-concepts","p":715},{"i":719,"t":"You can set the AssociatedSaveMode for save commands in two ways Set parameters for the save method (this is the simpler choice) Call configuration methods on the save command (this is the more powerful choice) info Jimmer's API design only allows users to choose one of these methods, preventing confusion from having both methods appear simultaneously","s":"Methods with Specified Association Mode","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#methods-with-specified-association-mode","p":715},{"i":721,"t":"Many save methods support this, for example For save, saveEntities and saveInputs, the default AssociatedSaveMode is REPLACE. Now, let's modify it to MERGE. save Java Kotlin Book book = ...omitted...; sqlClient.save(book, AssociatedSaveMode.MERGE); val book = Book { ...omitted... } sqlCient.save(book, AssociatedSaveMode.MERGE); saveEntities Java Kotlin List books = ...omitted...; sqlClient.saveEntities(books, AssociatedSaveMode.MERGE); val books = listOf(...omitted...) sqlCient.saveEntities(books, AssociatedSaveMode.MERGE); saveInputs Java Kotlin List inputs = ...omitted...; sqlClient.saveInputs(inputs, AssociatedSaveMode.MERGE); val inputs = listOf(...omitted...) sqlCient.saveInputs(inputs, AssociatedSaveMode.MERGE); Here, the BookInput class is not an entity type, but rather an automatically generated Input DTO type by Jimmer. This related content hasn't been introduced before, please ignore it for now. Besides save, saveEntities and saveInputs, Jimmer has other shortcut methods, such as insert, insertEntities, insertInputs insertIfAbsent, mergeEntitiesIfAbsent, mergeInputsIfAbsent update, updateEntities, updateInputs merge, mergeEntities, mergeInputs Taking insert, insertEntities and insertInputs as examples, the default AssociatedSaveMode is APPEND. Now, let's modify it to MERGE. insert Java Kotlin Book book = ...omitted...; sqlClient.insert(book, AssociatedSaveMode.MERGE); val book = Book { ...omitted... } sqlCient.insert(book, AssociatedSaveMode.MERGE); insertEntities Java Kotlin List books = ...omitted...; sqlClient.insertEntities(books, AssociatedSaveMode.MERGE); val books = listOf(...omitted...) sqlCient.insertEntities(books, AssociatedSaveMode.MERGE); insertInputs Java Kotlin List inputs = ...omitted...; sqlClient.insertInputs(inputs, AssociatedSaveMode.MERGE); val inputs = listOf(...omitted...) sqlCient.insertInputs(inputs, AssociatedSaveMode.MERGE);","s":"Setting Save Method Parameters","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#setting-save-method-parameters","p":715},{"i":723,"t":"Besides setting save method parameters, we can also modify AssociatedSaveMode by calling configuration methods on the save command. Precisely set AssociatedSaveMode for specific associations Java Kotlin Book book = ...omitted...; sqlClient .saveCommand(book) .setAssociatedMode( BookProps.AUTHORS, AssociatedSaveMode.MERGE ) .execute(); val book = Book { ...omitted... } sqlCient.save(book) { setAssociatedMode( Book::authors, AssociatedSaveMode.MERGE ) } Java Calls the saveCommand method instead of save method, indicating creation of a save command without immediate execution. After configuration with setAssociatedMode, finally calls the execute method to actually execute. Kotlin The syntax is relatively concise, still calling the save method that can directly execute save commands, just with a lambda for additional configuration. Blindly set AssociatedSaveMode for all associations Java Kotlin Book book = ...omitted...; sqlClient .saveCommand(book) .setAssociatedModeAll( AssociatedSaveMode.MERGE ) .execute(); val book = Book { ...omitted... } sqlCient.save(book) { setAssociatedModeAll( AssociatedSaveMode.MERGE ) } Java Calls the saveCommand method instead of save method, indicating creation of a save command without immediate execution. After configuration with setAssociatedModeAll, finally calls the execute method to actually execute. Kotlin The syntax is relatively concise, still calling the save method that can directly execute save commands, just with a lambda for additional configuration. info Obviously, for specific associations, precise configuration has higher priority than blind configuration.","s":"Calling Save Instruction Configuration Methods","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#calling-save-instruction-configuration-methods","p":715},{"i":725,"t":"Unconditionally perform INSERT operations on associated objects Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform INSERT operations on 4 associated objects Assuming after the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */","s":"1. APPEND","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#1-append","p":715},{"i":727,"t":"First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, ignore the operation and do nothing Otherwise, insert the associated object note Jimmer will try to utilize the database's native UPSERT capabilities to combine these two steps. If this is not possible, it will inform the user of the reason Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND_IF_ABSENT ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.APPEND_IF_ABSENT ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform INSERT_IF_ABSENT operations on 4 associated objects Assuming: The key for Book objects is Book.name and Book.edition, and the Book entity is annotated with @KeyUniqueConstraint (For MySQL, @KeyUniqueConstraint(noMoreUniqueConstraints = true) is needed) After the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: H2 Mysql Postgres merge into BOOK tb_1_ using(values(?, ?, ?, ?)) tb_2_( NAME, EDITION, PRICE, STORE_ID ) on tb_1_.NAME = tb_2_.NAME and tb_1_.EDITION = tb_2_.EDITION when not matched then insert( NAME, EDITION, PRICE, STORE_ID ) values( tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID ) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert ignore into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do nothing returning ID /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */","s":"2. APPEND_IF_ABSENT","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#2-append_if_absent","p":715},{"i":729,"t":"If the id property of the associated object is specified, update the associated object by id Otherwise, update the associated object by key Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.UPDATE ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.UPDATE ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform INSERT operations on 4 associated objects Assuming after the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: update BOOK set PRICE = ?, STORE_ID = ? where NAME = ? and EDITION = ? /* batch-0: [49.9, 2, SQL in Action, 1] */ /* batch-1: [39.9, 2, LINQ in Action, 1] */ /* batch-2: [44.02, 100, C++ Primer, 5] */ /* batch-3: [71.99, 100, Programming RUST, 1] */","s":"3. UPDATE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#3-update","p":715},{"i":731,"t":"First check if the associated object exists in the database If the id property of the associated object is specified, check existence by id Otherwise, check existence by key Execute subsequent operations based on the check result If the associated object already exists, update it Otherwise, insert it note Jimmer will try to utilize the database's native UPSERT capabilities to combine these two steps. If this is not possible, it will inform the user of the reason Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.MERGE ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.MERGE ) To demonstrate simpler SQL generation, we assume that the targetTransferable feature of sqlClient is enabled, which was previously covered, see here Two SQL statements will be generated: Perform UPSERT (insert or update) operations on two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Perform MERGE operations on 4 associated objects Assuming: The key for Book objects is Book.name and Book.edition, and the Book entity is annotated with @KeyUniqueConstraint (For MySQL, @KeyUniqueConstraint(noMoreUniqueConstraints = true) is needed) After the previous SQL saves the root objects: The id of MANNING is 2 The id of AMAZON is 100 The following SQL is generated: H2 Mysql Postgres merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key(NAME, EDITION) values( ?, ?, ?, ? ) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on duplicate key update /* fake update to return all ids */ ID = last_insert_id(ID), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) on conflict( NAME, EDITION ) do update set PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */","s":"4. MERGE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#4-merge","p":715},{"i":733,"t":"The MERGE mode performs INSERT or UPDATE operations on associated objects, so after saving, the number of associated objects either remains the same or increases, but never decreases. The REPLACE mode does not have this characteristic because REPLACE performs dissociate operations on no-longer-needed associated objects in addition to the MERGE functionality. The dissociate operation removes associations that the current object no longer needs, for example: Existing Database Structure User's Expected Data Structure +-Food | | | +-----Meat(ignore child nodes) | \\-----Bread(ignore child nodes) +-Food | +-----Drinks(ignore child nodes) | | | \\-----Bread(ignore child nodes) For Bread, it exists in both old and new data structures, corresponding to an UPDATE operation For Drinks, it doesn't exist in the old data structure but exists in the new data, corresponding to an INSERT operation For Meat, it exists in the old data structure but not in the new data, corresponding to an operation called dissociation operation. info The dissociate operation will be explained in detail in subsequent tutorials, so this article provides a highly simplified example Java Kotlin List books = Arrays.asList( Immutables.createBook(book -> { book.setId(1L); book.addIntoAuthors(author -> author.setId(2L)); book.addIntoAuthors(author -> author.setId(3L)); }), Immutables.createBook(book -> { book.setId(2L); book.addIntoAuthors(author -> author.setId(2L)); book.addIntoAuthors(author -> author.setId(4L)); }) ); sqlClient.saveEntities( books, // This parameter can be removed because for the `saveEntities` method, // `AssociatedSaveMode.REPLACE` is the default behavior AssociatedSaveMode.REPLACE ); val books = listOf( Book { id = 1L authors().addBy { id = 2L } authors().addBy { id = 3L } }, Book { id = 2L authors().addBy { id = 2L } authors().addBy { id = 4L } } ) sqlClient.saveEntities( books, // This parameter can be removed because for the `saveEntities` method, // `AssociatedSaveMode.REPLACE` is the default behavior AssociatedSaveMode.REPLACE ) Assuming the existing database structure is shown in the left column of the table below: Existing Database Structure Desired Data Structure to Save --+-Book(1) | +---Author(1) | \\---Author(2) --+-Book(2) | +---Author(1) | \\---Author(2) --+-Book(1) | | | +---Author(2) | \\---Author(3) --+-Book(2) | | | +---Author(2) | \\---Author(4) Obviously, there should be 4 behaviors: Dissociate operations specific to REPLACE: Dissociate the association between Book-1 and Author-1 Dissociate the association between Book-2 and Author-1 Capabilities inherited from MERGE: Create a new association between Book-1 and Author-3 Create a new association between Book-2 and Author-4 Finally, two SQL statements will be generated: The dissociate operation specific to REPLACE mode, removing old associations: H2 Mysql Postgres delete from BOOK_AUTHOR_MAPPING where BOOK_ID = ? and not (AUTHOR_ID = any(?)) /* batch-0: [1, [2, 3]] */ /* batch-1: [2, [2, 4]] */ delete from BOOK_AUTHOR_MAPPING where BOOK_ID in ( ? /* 1 */, ? /* 2 */ ) and (BOOK_ID, AUTHOR_ID) not in ( (? /* 1 */, ? /* 2 */), (? /* 1 */, ? /* 3 */), (? /* 2 */, ? /* 2 */), (? /* 2 */, ? /* 4 */) ) delete from BOOK_AUTHOR_MAPPING where BOOK_ID = ? and not (AUTHOR_ID = any(?)) /* batch-0: [1, [2, 3]] */ /* batch-1: [2, [2, 4]] */ The purpose of this SQL is: For Book-1, delete its associations with Authors other than Author-2 and Author-3 In this case, it means dissociating Book-1 from Author-1 For Book-2, delete its associations with Authors other than Author-2 and Author-4 In this case, it means dissociating Book-2 from Author-1 We can see significant differences between different databases: H2 and Postgres use simple batched SQL MySQL uses a single complex SQL statement info This is because H2 and Postgres support the =any(array) syntax, while MySQL does not. Capabilities inherited by REPLACE mode from MERGE mode to establish new associations H2 Mysql Postgres merge into BOOK_AUTHOR_MAPPING tb_1_ using(values(?, ?)) tb_2_( BOOK_ID, AUTHOR_ID ) on tb_1_.BOOK_ID = tb_2_.BOOK_ID and tb_1_.AUTHOR_ID = tb_2_.AUTHOR_ID when not matched then insert(BOOK_ID, AUTHOR_ID) values(tb_2_.BOOK_ID, tb_2_.AUTHOR_ID) /* batch-0: [1, 2] */ /* batch-1: [1, 3] */ /* batch-2: [2, 2] */ /* batch-3: [2, 3] */ insert ignore into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values(?, ?) /* batch-0: [1, 2] */ /* batch-1: [1, 3] */ /* batch-2: [2, 2] */ /* batch-3: [2, 3] */ insert into BOOK_AUTHOR_MAPPING(BOOK_ID, AUTHOR_ID) values(?, ?) on conflict(BOOK_ID, AUTHOR_ID) do nothing /* batch-0: [1, 2] */ /* batch-1: [1, 3] */ /* batch-2: [2, 2] */ /* batch-3: [2, 3] */ The REPLACE mode integrates INSERT, UPDATE, and DELETE operations into one, expecting to replace all associated relationships completely (if the association relationship is a deep long association, then it's replacing an entire subtree). However, REPLACE mode has one limitation: it expects objects to either have an id or a key. Because it expects to cleverly find the parts where the new and old data structures have changed through id and key, thereby minimizing the impact range of INSERT, UPDATE, and DELETE operations to achieve maximum performance. tip If readers are familiar with the web domain, it's not hard to see that this is the same principle as specifying the key attribute when using loop rendering in React. In fact, the save command design was inspired by React.","s":"5. REPLACE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#5-replace","p":715},{"i":735,"t":"We've dissucess REPLACE, however, what should we do when dealing with wild objects, i.e., associated objects that have neither id nor key? In this case, we can use the VIOLENTLY_REPLACE mode. Once this mode is adopted, Jimmer no longer looks for changes in associations (or association collections) based on id or key, but performs the following two operations: First, delete all old associations and related objects of the current object Then reinsert all associated objects and rebuild associations with the current object Java Kotlin List stores = Arrays.asList( Immutables.createBookStore(draft -> { draft.setName(\"MANNING\"); draft.addIntoBooks(book -> { book.setName(\"SQL in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.9\")); }); draft.addIntoBooks(book -> { book.setName(\"LINQ in Action\"); book.setEdition(1); book.setPrice(new BigDecimal(\"39.9\")); }); }), Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }) ); sqlClient.saveEntities( stores, AssociatedSaveMode.VIOLENTLY_REPLACE ); val stores = listOf( BookStore { name = \"MANNING\" books().addBy { name = \"SQL in Action\" edition = 1 price = BigDecimal(\"49.9\") } books().addBy { name = \"LINQ in Action\" edition = 1 price = BigDecimal(\"39.9\") } }, BookStore { name = \"AMAZON\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } ) sqlClient.saveEntities( stores, AssociatedSaveMode.VIOLENTLY_REPLACE ) To demonstrate simpler SQL generation, let's assume that the targetTransferable feature of sqlClient is enabled, which was previously introduced, please refer to here Three SQL statements will be generated: Perform UPSERT (insert or update) operations on the two root objects Saving the root object is not the focus of this article, collapsed by default H2 Mysql Postgres merge into BOOK_STORE( NAME ) key(NAME) values( ? ) /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ TBD insert into BOOK_STORE( NAME ) values( ? ) on conflict( NAME ) do nothing returning ID /* batch-0: [MANNING] */ /* batch-1: [AMAZON] */ Assume MANNING exists with an id of 2 Assume AMAZON exists, after insertion, the database automatically assigns a new id of 100 Delete all old associated objects Assuming after saving the root objects in the previous SQL The id of MANNING is 2 The id of AMAZON is 100 delete from BOOK where STORE_ID in ( ? /* 2 */, ? /* 100 */ ) info If there are other tables in the database that reference the BOOK table through foreign keys, a simple DELETE statement cannot delete all associated objects. To simplify the discussion, let's assume this scenario doesn't exist. Create all new associations and associated objects Assuming after saving the root objects in the previous SQL The id of MANNING is 2 The id of AMAZON is 100 insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?) /* batch-0: [SQL in Action, 1, 49.9, 2] */ /* batch-1: [LINQ in Action, 1, 39.9, 2] */ /* batch-2: [C++ Primer, 5, 44.02, 100] */ /* batch-3: [Programming RUST, 1, 71.99, 100] */ Not comparing old and new data in detail, but simply deleting associated objects and rebuilding them is a very violent mode with the following disadvantages: If there are many associated objects, in most cases, this is a low-performance solution If the associated objects have deeper associations, the deletion behavior in step 1 may lead to too deep cascade deletion, resulting in the loss of too much data caution Therefore, it is not recommended, please use with caution","s":"6. VIOLENTLY_REPLACE","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#6-violently_replace","p":715},{"i":737,"t":"The save command provides not only save, saveEntities, and saveInputs methods, but also other shortcut methods for various application scenarios. Different save commands have different default values for AssociatedSaveMode, please refer to this table: Method Default AssociatedSaveMode save REPLACE saveEntities saveInputs insert APPEND insertEntities insertInputs insertIfAbsent APPEND_IF_ABSENT insertEntitiesIfAbsent insertInputsIfAbsent update UPDATE updateEntities updateInputs merge MERGE mergeEntities mergeInputs","s":"Default Mode","u":"/jimmer-doc/docs/mutation/save-command/association/associated-save-mode","h":"#default-mode","p":715},{"i":739,"t":"Save commands support both optimistic lock and pessimistic lock.","s":"Optimistic/Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"","p":738},{"i":741,"t":"Jimmer supports optimistic lock via the @org.babyfish.jimmer.sql.Version annotation.","s":"Optimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#optimistic-lock","p":738},{"i":743,"t":"Modify BookStore Java Kotlin BookStore.java @Entity public interface BookStore { @Version int version(); ...other properties omitted... } BookStore.kt @Entity public interface BookStore { @Version val version: Int ...other properties omitted... } Modify Book Java Kotlin Book.java @Entity public interface Book { @Version int version(); ...other properties omitted... } Book.kt @Entity public interface Book { @Version val version: Int ...other properties omitted... }","s":"Modify Entity Types","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#modify-entity-types","p":738},{"i":745,"t":"Characteristics of optimistic lock: When inserting objects (whether explicitly doing INSERT, or UPSERT determined to be INSERT), the version of the object will be inserted into the database. For example: Java Kotlin BookStore savedData = sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"44.99\")); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); }); }) ).getModifiedEntity(); System.out.println(savedData); val savedData = sqlClient.save( BookStore { name = \"TURING\" books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") } } ).modifiedEntity println(savedData) tip For INSERT operations, if the version of the object is not assigned, Jimmer will automatically insert 0. If you cannot ascertain whether a UPSERT save command will ultimately be determined as INSERT or UPDATE, you should insist on specifying the version property. The following example assumes we know for sure the save will be determined as INSERT rather than UPDATE, so the version properties are not specified. No ids are specified so jimmer determines their existence by their key properties. Assuming none of the objects exist, 3 new records will be inserted. No version properties are specified, so they are filled with 0 automatically. The final printed result will be (formatted for readability): { \"id\":100, \"name\":\"TURING\", \"version\":0, \"books\":[ { \"id\":100, \"name\":\"Introduction to Algorithms\", \"edition\":3, \"price\":44.99, \"version\":0, \"store\":{ \"id\":100 } }, { \"id\":101, \"name\":\"The Pragmatic Programmer\", \"edition\":2, \"price\":39.99, \"version\":0, \"store\":{ \"id\":100 } } ] } info Of course, if the user specifies version for these objects, the specified values rather than 0 will be inserted. When modifying objects (whether explicitly doing UPDATE, or UPSERT determined to be UPDATE), Jimmer will compare the version passed by the user and the existing version in the database for each object. If they differ, an exception will be thrown. Let's modify the code a bit and execute again: Java Kotlin BookStore savedData = sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.setVersion(0); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"54.99\")); book.setVersion(0); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); // illegal version book.setVersion(9999); }); }) ).getModifiedEntity(); System.out.println(savedData); val savedData = sqlClient.save( BookStore { name = \"TURING\" version = 0 books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") version = 0 } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") // illegal version version = 9999 } } ).modifiedEntity println(savedData) caution For UPDATE operations, if the version of the object is not assigned, Jimmer will throw an exception. If you cannot determine whether a UPSERT save command will ultimately be INSERT or UPDATE, you should insist on specifying the version property. Execute, since data already exists, the 3 objects will be updated. Obviously, the last book's version 9999 is illegal. The above code will result in the following exception: Exception Type: org.babyfish.jimmer.sql.runtime.SaveException Exception Code: org.babyfish.jimmer.sql.runtime.SaveErrorCode.ILLEGAL_VERSION Exception Message: Save error caused by the path: \".books\": Cannot update the entity whose type is \"org.doc.j.model.Book\", id is \"101\" and version is \"9999\" Let's modify the code again to use the correct version for all objects: Java Kotlin BookStore savedData = sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.setVersion(0); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"54.99\")); book.setVersion(0); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); book.setVersion(0); }); }) ).getModifiedEntity(); System.out.println(savedData); val savedData = sqlClient.save( BookStore { name = \"TURING\" version = 0 books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") version = 0 } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") version = 0 } } ).modifiedEntity println(savedData) The final printed result will be (formatted for readability): { \"id\":100, \"name\":\"TURING\", \"version\":1, \"books\":[ { \"id\":100, \"name\":\"Introduction to Algorithms\", \"edition\":3, \"price\":54.99, \"version\":1, \"store\":{ \"id\":100 } }, { \"id\":101, \"name\":\"The Pragmatic Programmer\", \"edition\":2, \"price\":39.99, \"version\":1, \"store\":{ \"id\":100 } } ] } info As you can see, the version is incremented by 1 automatically after data modification. In real projects, the version number of optimistic lock is often a hidden field in the form UI. If the form UI does not automatically redirect to other UI after saving, but keeps the UI unchanged to support multiple submissions, the hidden field should be updated with such return info after each successful save.","s":"Demo","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#demo","p":738},{"i":747,"t":"Unlike optimistic lock, pessimistic locks are very short-lived, only valid within a single jdbc transaction. Normally, Jimmer generates some query SQL to aid save command execution, such as: Determining whether a UPSERT should ultimately be INSERT or UPDATE Determining which associated objects need to be dissociated Next, we compare the differences in these query SQL between using and not using pessimistic lock. info In the previous examples, to demonstrate optimistic lock, we assumed the BookStore and Book types both defined a version property. In the following examples to demonstrate pessimistic lock, we no longer make that assumption.","s":"Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#pessimistic-lock","p":738},{"i":749,"t":"Java Kotlin sqlClient.save( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"44.99\")); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); }); }) ); sqlClient.save( BookStore { name = \"TURING\" books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") } } ) This generates 6 SQL statements: Check if the book store exists select tb_1_.ID, tb_1_.NAME from BOOK_STORE tb_1_ where tb_1_.NAME = ? /* TURING */ Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 1st book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* Introduction to Algorithms */ and tb_1_.EDITION = ? /* 3 */ Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 2nd book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* The Pragmatic Programmer */ and tb_1_.EDITION = ? /* 2 */ Determine INSERT or UPDATE based on previous query insert or update, omitted info These query statements are used to make conditional judgments to determine how to generate subsequent SQL. However, without pessimistic lock, the conditions and assumptions made via these queries can potentially be invalidated by concurrent operations, leading to exceptions when executing subsequent SQL. To avoid such concurrency issues, pessimistic lock can be enabled. Next we discuss how to implement pessimistic lock.","s":"Without Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#without-pessimistic-lock","p":738},{"i":751,"t":"There are two ways to enable pessimistic lock: Global configuration There are two ways to enable pessimistic lock globally: Via Spring Boot Starter configuration Modify application.yml (or application.properties): jimmer: default-lock-mode: PESSIMISTIC Via low-level API configuration Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultLockMode(LockMode.PESSIMISTIC) ...other configurations omitted... .build(); val sqlClient = newKSqlClient { setDefaultLockMode(LockMode.PESSIMISTIC) } warning This change modifies the global setting, and the original default value OPTIMISTIC is compromised. This means that unless a specific save command is set to optimistic locking mode, the optimistic locking functionality described earlier disappears. Therefore, in most cases, global configuration is not recommended, and the command-level configuration that will be introduced later is more recommended. Command-level configuration Unlike global configuration affecting all save commands, command-level configuration only affects the current save command. info If pessimistic lock is already enabled globally, no need for command-level configuration. Calling setLockMode(LockMode) on the save command enables pessimistic lock: Java Kotlin sqlClient .getEntities() .saveCommand( Immutables.createBookStore(draft -> { draft.setName(\"TURING\"); draft.addIntoBooks(book -> { book.setName(\"Introduction to Algorithms\"); book.setEdition(3); book.setPrice(new BigDecimal(\"44.99\")); }); draft.addIntoBooks(book -> { book.setName(\"The Pragmatic Programmer\"); book.setEdition(2); book.setPrice(new BigDecimal(\"39.99\")); }); }) ) .setLockMode(LockMode.PESSIMISTIC) .execute(); sqlClient.save( BookStore { name = \"TURING\" books().addBy { name = \"Introduction to Algorithms\" edition = 3; price = BigDecimal(\"44.99\") } books().addBy { name = \"The Pragmatic Programmer\" edition = 2 price = BigDecimal(\"39.99\") } } ) { setLockMode(LockMode.PESSIMISTIC) } Once pessimistic lock is enabled, the generated query statements will change significantly: Check if the book store exists select tb_1_.ID, tb_1_.NAME from BOOK_STORE tb_1_ where tb_1_.NAME = ? /* TURING */ for update Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 1st book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* Introduction to Algorithms */ and tb_1_.EDITION = ? /* 3 */ for update Determine INSERT or UPDATE based on previous query insert or update, omitted Check if the 2nd book exists select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where tb_1_.NAME = ? /* The Pragmatic Programmer */ and tb_1_.EDITION = ? /* 2 */ for update Determine INSERT or UPDATE based on previous query insert or update, omitted","s":"Enabling Pessimistic Lock","u":"/jimmer-doc/docs/mutation/save-command/lock","h":"#enabling-pessimistic-lock","p":738},{"i":753,"t":"Input DTO is used for data input, so it provides powerful control over nullable properties in the objects submitted by the client, and standardizes this capability.","s":"Handle Null Values","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"","p":752},{"i":756,"t":"One of the most important features of Jimmer entities is the strict distinction between unknown data (not specifying object properties) and no data (setting object properties to null). Let's temporarily set aside the concept of Input DTO and review the differences when directly saving data using Jimmer entities. Setting nullable property to null Java Kotlin Book book = BookDraft.$.produce(draft -> { draft.setId(12L); draft.setName(\"TURING\"); draft.setStoreId(null); }); sqlClient.update(book); val book = Book { id = 12L name = \"TURING\" storeId = null } sqlClient.update(book); The following SQL is generated: update BOOK set NAME = ?, /* TURING */ STORE_ID = ? /* */ where ID = ? /* 12 */` As you can see, by explicitly setting the object's property to null and executing the save command with an update operation, the value in the database will be updated to null. Not specifying nullable property at all Java Kotlin Book book = BookDraft.$.produce(draft -> { draft.setId(12L); draft.setName(\"TURING\"); // `storeId` is not specified }); sqlClient.update(book); val book = Book { id = 12L name = \"TURING\" // `storeId` is not specified } sqlClient.update(book); The following SQL is generated: update BOOK set NAME = ? /* TURING */ /* `STORE_ID` is not updated */ where ID = ? /* 12 */` As you can see, by not setting the object's property and executing the save command with an update operation, the value in the database will not be updated. info This distinction is very important. In the subsequent content of this article, we will no longer discuss what SQL statements the ORM generated because we only need to focus on what the entity object obtained from the conversion of the Input DTO is.","s":"Review: Directly Saving Entity Objects","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#review-directly-saving-entity-objects","p":752},{"i":758,"t":"Now, let's define an Input DTO: input BookUpdateInput { id! name id(store) } For more details on the DTO language, please refer to the relevant chapter. Here, we focus on the Java/Kotlin code automatically generated by the Jimmer pre-compiler based on this DTO code. The generated code is as follows: Java Kotlin BookUpdateInput.java @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookUpdateInput implements Input { private long id; private String name; @Nullable private Long storeId; @Override public Book toEntity() { ...omitted... } ...other members omitted... } BookUpdateInput.kt @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookUpdateInput( val id: Long, val name: String, val storeId: Long? = null ) { override fun toEntity(): Book = ...omitted... ...other members omitted... } In the original entity, the associated property Book.store is nullable. The DTO code does not change this here, so in the generated classes, the field storeId is also nullable. If the storeId property of the BookUpdateInput object uploaded by the user is null, is the user's intention to update the corresponding foreign key STORE_ID in the database to null, or not to update it at all? In fact, both of these intentions are common. For a long time, developers have been very casual about the conventions for these two behaviors, and even if the API documentation mentions such details, the format is also very casual. This has led to difficulties in communication and understanding and has caused lasting damage to the industry. Input DTO provides a standardized definition for this issue, aiming to handle different intentions in a standardized manner.","s":"Issues Faced by Input DTO","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#issues-faced-by-input-dto","p":752},{"i":760,"t":"To solve the problem raised above, the DTO language specifies that if a DTO property satisfies both of the following conditions: It is defined in an input type It allows null values Then, a modifier representing the null handling mode can be added to the DTO property: it can be fixed, static, dynamic, or fuzzy. For convenience in the subsequent discussion, let's assume that the following Web Controller exists: Java Kotlin @RestController public class BookController { @PutMapping(\"/book\") public void update( @RequestBody BookUpdateInput input ) { Book book = input.toEntity(); System.out.println(book); ...subsequent code omitted... } ...other members omitted... } @RestController class BookController { @PutMapping(\"/book\") fun update( @RequestBody input: BookUpdateInput ) { val book = input.toEntity() println(book) ...subsequent code omitted... } ...other members omitted... } Here, we convert the Input DTO object uploaded by the user into a Jimmer entity and print it out. We only need to focus on the print result, as mentioned earlier, we only need to focus on what the entity object obtained from the conversion of the Input DTO is, and we do not need to discuss what SQL statements the ORM will generate. Therefore, the subsequent code is not important and is omitted.","s":"4 Ways to Handle Nullable Properties","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#4-ways-to-handle-nullable-properties","p":752},{"i":762,"t":"DTO code example: input BookUpdateInput { id! name fixed id(store) } This mode can also be called the super static mode. It does not allow the user to submit an Input DTO without specifying certain properties. Even if they want a property to be null, they need to explicitly specify it. If the property of the Input DTO is null, the corresponding property of the obtained Jimmer entity object will also be set to null, effectively modifying the corresponding field in the database to null. Two ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' This request will be rejected, HTTP error code 400, parameter error. If you check the Java log, you will see the following error: Resolved [org.springframework.http.converter.HttpMessageNotReadableException: JSON parse error: Cannot construct instance of `org.doc.j.model.dto.BookUpdateInput$Builder`, problem: An object whose type is \"org.doc.j.model.dto.BookUpdateInput\" cannot be deserialized by Jackson. The current type is fixed input DTO so that all JSON properties must be specified explicitly, however, the property \"storeId\" is not specified by JSON explicitly. Please either explicitly specify the property as null in the JSON, or specify the current input properties as static, dynamic or fuzzy in the DTO language] tip If developer use the Automatic TypeScript Generation feature in Jimmer, the generated typeScript code will require web developers to provide the storeId property for the BookUpdateInput object, otherwise client code cannot be compiled successfully.","s":"1. fixed","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#1-fixed","p":752},{"i":764,"t":"DTO code example: input BookUpdateInput { id! name static id(store) } When submitting an Input DTO, the user can either set the storeId property to null or not specify it at all. Regardless of the user's choice, the behavior remains the same: the corresponding property of the obtained Jimmer entity object will definitely be set to null, effectively modifying the corresponding field in the database to null. Two ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. info The effects of the two operations are the same, and the final effect is only affected by the DTO shape, regardless of whether the user specified the DTO property or not.","s":"2. static","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#2-static","p":752},{"i":766,"t":"DTO code example: input BookUpdateInput { id! name dynamic id(store) } If the user chooses to set the storeId property of the DTO to null, then the storeId property of the final obtained Jimmer entity object will also be null, effectively modifying the corresponding field in the database to null. If the user does not set the storeId property of the DTO at all, then the storeId property of the final obtained Jimmer entity object will also not be set, so the corresponding field in the database will not be updated. Two ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":null } That is, subsequent operations will update the corresponding field in the database to null. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", // There is no storeId property here } That is, subsequent operations will not update the corresponding field in the database. info The two ways of submitting data correspond to two completely different behaviors, suitable for professional client teams to have flexible control over the service behavior.","s":"3. dynamic","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#3-dynamic","p":752},{"i":768,"t":"warning This mode sacrifices functionality for conservativeness and safety, and is the only mode with incomplete functionality. DTO code example: input BookUpdateInput { id! name fuzzy id(store) } If the user sets the storeId property of the DTO object to a non-null value, then the storeId property of the final obtained Jimmer entity object will be set accordingly, effectively modifying the corresponding field in the database to the specified value. Otherwise (whether the storeId property of the DTO object is set to null or not specified at all), the storeId property of the final obtained Jimmer entity object will not be set, so the corresponding field in the database will not be updated. Three ways for the client to submit data: Submit an Input DTO with the storeId property set to null curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": null }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", // There is no storeId property here } That is, subsequent operations will not update the corresponding field in the database. Submit an Input DTO without the storeId property curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\" }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", // There is no storeId property here } That is, subsequent operations will not update the corresponding field in the database. Submit an Input DTO with the storeId property set to a non-null value The previous two ways cannot modify the corresponding field in the database unless a non-null value is specified, as follows: curl -X 'PUT' \\ 'http://localhost:8080/book' \\ -H 'accept: */*' \\ -H 'Content-Type: application/json' \\ -d '{ \"id\": 12, \"name\": \"TURING\", \"storeId\": 2 }' The print result (the final Jimmer entity object obtained) is as follows: { \"id\":12, \"name\":\"TURING\", \"store\":3 } info This mode sacrifices the ability to modify the corresponding field in the database to null in exchange for absolute conservativeness and safety. It is particularly suitable for client teams with less experience.","s":"4. fuzzy","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#4-fuzzy","p":752},{"i":770,"t":"In the examples above, the keywords fixed, static, dynamic, and fuzzy were used to modify the nullable properties of the Input DTO. Field-level control is the most fine-grained. However, if there are many nullable properties in the Input DTO, configuring them one by one may be cumbersome. Jimmer provides configuration methods with a broader scope of influence: Input type level dynamic input XxxInput { fixed nullableProp1 static nullableProp2 nullableProp3 fuzzy nullableProp4 nullableProp5 } Here, the null handling mode is not declared for nullableProp3 and nullableProp5, and they will share the configuration at the input type level (in this case, dynamic). Precompiler level If no configuration is found at the input type level, refer to the global configuration parameter jimmer.dto.defaultNullableInputModifier of the precompiler (for Java, it is APT; for Kotlin, it is KSP). Java(Maven) Java(Gradle) Kotlin(Gradle.kts) org.apache.maven.plugins maven-compiler-plugin 3.13.0 -Ajimmer.dto.defaultNullableInputModifier=fixed tasks.withType().configureEach { options.compilerArgs.add(\"-Ajimmer.dto.defaultNullableInputModifier=fixed\") } ksp { arg(\"jimmer.dto.defaultNullableInputModifier\", \"fixed\") } Final default mode If no configuration is provided at the precompiler level either, the final default is static. info Configurations at different levels may conflict, and the priorities among them are: Input property level config > Input type level config > Precompiler global config > Final default static","s":"Higher-Level Configurations","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#higher-level-configurations","p":752},{"i":772,"t":"caution For the fixed and dynamic modes, Jimmer requires the server-side to use Jackson for deserialization. Therefore, if you plan to use the fixed or dynamic mode, please: Add @RequestBody If you carefully look at the examples in this article, you will notice that @RequestBody was used there. Do not replace the Jackson Message Converter enabled by default in Spring Boot. In fact, not only the Input DTOs using the fixed or dynamic mode discussed in this article have this requirement; if the user needs to use the serialization/deserialization of Jimmer entities themselves, Jackson is also required. Jackson is carefully designed to strike the perfect balance between functionality and performance. Therefore, Jimmer regards Jackson as an essential infrastructure.","s":"Caveats","u":"/jimmer-doc/docs/mutation/save-command/input-dto/null-handling","h":"#caveats","p":752},{"i":775,"t":"Save instructions allow developers to save data structures of any shape, rather than save simple objects. By default, when AssociatedSaveMode is set to REPLACE, Jimmer will completely replace the existing data structure in the database with the structure being saved, as shown in the figure: Top right: Users pass in a data structure of any shape for Jimmer to write to the database. Top left: Query the existing data structure from the database to compare with the new data structure passed in by users. Whatever shape of data structure the user passes in, the same shape will be queried from the database, ensuring the shapes of old and new data structures are identical. Therefore, the querying and comparison costs are determined by the complexity of the user-provided data structure. Below:Compare the new and old data structures, find the DIFF and execute corresponding SQL operations to make them consistent: Orange parts: For entity objects that exist in both new and old data structures, modify data if scalar properties have changed Blue parts: For entity objects that exist in both new and old data structures, modify associations if they have changed Green parts: For entity objects that exist in the old data structure but not in the new one, decouple this object, clear associations and possibly delete data Red parts: For entity objects that exist in the new data structure but not in the old one, insert data and establish associations tip Unlike other ORMs, Jimmer doesn't require describing how data should be saved in the entity model Whether certain scalar properties need to be saved Taking JPA as an example, this is controlled throughColumn.insertable andColumn.updatable. Whether certain association properties need to be saved Taking JPA as an example, this is controlled throughOneToOne.cascade,ManyToOne.cascade,OenToMany.cascade andManyToOne.cascade. Jimmer adopts a completely different strategy - its entity objects are not POJOs and can flexibly control the shape of data structures. That is, entity objects have dynamic properties - not specifying a property for an entity object and setting an entity's property to null are completely different things. For any entity object, Jimmer will only save the specified properties while ignoring unspecified ones. Therefore, Jimmer doesn't need to consider data saving behavior during entity modeling, but rather describes the expected behavior at runtime through the data structure being saved itself, providing absolute flexibility.","s":"Introduction","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#introduction","p":773},{"i":778,"t":"Let's look at how Jimmer distinguishes between the following two requirements: Not updating a certain property of an object Updating a property of an object to null For traditional static language ORMs, this is a very tricky problem. However, Jimmer can easily distinguish between these two different behaviors. 1.1.1. Not Updating a Certain Property​ Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(8L); draft.setPrice(new BigDecimal(\"33.9\")); // `store` or `storeId` property not specified }) ); sqlClient.update( Book { id = 8L price = BigDecimal(\"33.9\") // `store` or `storeId` property not specified } ); Generates the following SQL: update BOOK set PRICE = ? /* 33.9 */ where ID = ? /* 8 */ As you can see, only the specified field PRICE is modified, while other unspecified fields (including STORE_ID) remain unchanged. 1.1.2. Updating a Property to Null​ Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(8L); draft.setPrice(BigDecimal(\"33.9\")) draft.setStore(null); // Can also be written as `draft.setStoreId(null)` }) ); sqlClient.update( Book { id = 8L price = BigDecimal(\"33.9\") store = null // Can also be written as `storeId = null` } ); Generates the following SQL: update BOOK set PRICE = ? /* 33.9 */ STORE_ID = ? /* */ where ID = ? /* 8 */","s":"1.1. Flexible Control Over Simple Property Modifications","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#11-flexible-control-over-simple-property-modifications","p":773},{"i":780,"t":"In real business projects, there's often a requirement to update only some properties of an entity, not all of them. However, in traditional ORM development patterns, developers rarely use ORM update statements for convenience. Instead, they often choose to query the object first, then modify it, and finally save it. Here's a JPA example: JPA Example EntityManager entityManager = ...obtain JPA session object from current transaction context, omitted... Book book = entityManager.find(Book.class, 8L); book.setStore(null); // In JPA, entities are mutable, setting association to null // Calling merge here is just for clarity, it can be omitted since JPA will modify the database when the transaction commits entityManager.merge(book); Actually, besides wanting to modify Book.store to null, this scenario has no interest in other properties of the object. Obviously, this is wasteful. If the entity object has many properties, it becomes even more apparent. Jimmer's entity objects don't require all properties to be specified, meaning Jimmer supports incomplete objects. Therefore, you can create from scratch an incomplete Book object, only specifying its id property and store property, and let Jimmer update it directly. Java Kotlin sqlClient.update( Immutables.createBook(draft -> { draft.setId(8L); draft.setStore(null); }) ); sqlClient.update( Book { id = 8L store = null } ); Generates the following SQL: update BOOK set STORE_ID = ? /* */ where ID = ? /* 8 */","s":"1.2. Using Incomplete Objects to Avoid Query-Before-Update","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#12-using-incomplete-objects-to-avoid-query-before-update","p":773},{"i":782,"t":"Through the single object case, we have gained a basic understanding of the flexibility of save commands. Next, let's introduce the control capabilities of save commands over association properties.","s":"2. Flexibility of Association Properties","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#2-flexibility-of-association-properties","p":773},{"i":784,"t":"In most ORMs, the cascade configuration of association properties determines whether to save associated objects when saving an object. Taking JPA as an example, this can be achieved through 4 configurations: OneToOne.cascade ManyToOne.cascade OneToMany.cascade ManyToMany.cascade However, deciding on these configurations is painful. No matter how they are configured, they solidify the behavioral patterns of the model at the entity modeling stage, making the entity design too tightly coupled with business requirements. Jimmer doesn't have similar configurations. The specific behavior depends on the format of the data structure being saved itself. For example: Only saving the BookStore object Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.setWebsite(\"https://www.amazon.com\"); }); sqlClient.save(store); val store = BookStore { name = \"AMAZON\" website = \"https://www.amazon.com\" } sqlCient.save(store) Saving the BookStore object while cascading to save related Book objects Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"AMAZON\"); draft.setWebsite(\"https://www.amazon.com\"); draft.addIntoBooks(book -> { book.setName(\"C++ Primer\"); book.setEdition(5); book.setPrice(new BigDecimal(\"44.02\")); }); draft.addIntoBooks(book -> { book.setName(\"Programming RUST\"); book.setEdition(1); book.setPrice(new BigDecimal(\"71.99\")); }); }); sqlClient.save(store); val store = BookStore { name = \"AMAZON\" website = \"https://www.amazon.com\" books().addBy { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") } books().addBy { name = \"Programming RUST\" edition = 1 price = BigDecimal(\"71.99\") } } sqlCient.save(store)","s":"2.1. Whether to Cascade Save Associated Properties","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#21-whether-to-cascade-save-associated-properties","p":773},{"i":786,"t":"ORM has an important concept: bidirectional associations. In this tutorial, Book.authors and Author.books are bidirectional associations of each other. Whether in JPA or Jimmer, both ends of a bidirectional association are divided into active and passive sides: Active side: The mappedBy property of the association annotation is not specified Passive side: The mappedBy property of the association annotation is specified However, there is a huge difference between Jimmer and JPA: In JPA, you must make the active side object act as the parent object and the passive side object act as the associated object. Otherwise, modifications will be ineffective. Choosing the active side for JPA bidirectional associations is also very painful, essentially solidifying the model's behavior pattern at the entity modeling stage, making entity design too tightly coupled with business requirements. In Jimmer, regardless of how you choose the active and passive sides, it has no impact on save commands. If the active side choice of bidirectional association is restricted by Jimmer (for example, when building bidirectional associations based on one-to-many and many-to-one associations, Jimmer requires the one-to-many association to be the passive side), define the bidirectional association according to Jimmer's requirements Otherwise, freely define bidirectional associations according to your preferences In Jimmer, you can freely manipulate bidirectional associations according to your preferences, for example: Saving a Book object and modifying its association with Author, i.e., implementing association modification through Book.authors Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"C++ Primer\"); draft.setEdition(5); draft.setPrice(new BigDecimal(\"44.02\")); draft.addIntoAuthors(author -> author.setId(10L)); draft.addIntoAuthors(author -> author.setId(11L)); draft.addIntoAuthors(author -> author.setId(12L)); }) sqlCient.save(book); val book = Book { name = \"C++ Primer\" edition = 5 price = BigDecimal(\"44.02\") authors().addBy { id = 10L } authors().addBy { id = 11L } authors().addBy { id = 12L } } sqlCient.save(book); Saving an Author object and modifying its association with Book, i.e., implementing association modification through Author.books Java Kotlin Author author = Immutables.createAuthor(draft -> { draft.setFirstName(\"Stanley\"); draft.setLastName(\"Lippman\"); draft.setGender(Gender.MALE); draft.addIntoBooks(book -> book.setId(40L)); draft.addIntoBooks(book -> book.setId(41L)); draft.addIntoBooks(book -> book.setId(42L)); draft.addIntoBooks(book -> book.setId(43L)); draft.addIntoBooks(book -> book.setId(44L)); draft.addIntoBooks(book -> book.setId(45L)); }); sqlClient.save(author); val author = Author { firstName = \"Stanley\" lastName = \"Lippman\" gender = Gender.MALE books().addBy { id = 40L } books().addBy { id = 41 } books().addBy { id = 42L } books().addBy { id = 43L } books().addBy { id = 44L } books().addBy { id = 45L } } sqlCient.save(author)","s":"2.2. Symmetry of Bidirectional Associations","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#22-symmetry-of-bidirectional-associations","p":773},{"i":788,"t":"Save commands are very flexible and can manifest as either very powerful advanced features or very simple basic features. It's all up to you. In daily project development, there are two distinctly different requirements: Full data replacement for complex forms Incremental modification for simple data In terms of development task complexity, one is very complex, and the other is very simple. However, Jimmer treats them equally and implements them quickly.","s":"3. Deciding Functionality Complexity","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#3-deciding-functionality-complexity","p":773},{"i":790,"t":"Complex forms usually include associations (such as orders and order details), and may even include recursive data structures (such as UI drag-and-drop systems, UML drawing tools). No matter how complex, viewing this data structure as a whole, it can be saved with a single command. To make the example representative, we'll use Input DTO that hasn't been explained yet. Although the related content hasn't been covered yet, readers can guess its purpose. Using Jimmer's DTO language, define a type called BookStoreInput. export com.yourcompany.yourproject.BookStore -> pacage com.yourcompany.yourproject.dto; input BookStoreInput { #allScalars books { #allScalars id(authors) as authorIds } } After Jimmer compilation, a Java or Kotlin class named BookStoreInput is automatically generated. BookStoreInput is similar to POJO, a highly static type used to regulate, restrict, and accept client HTTP request content. At the same time, this class can automatically transform into BookStore entity objects and related associated objects. Java Kotlin @PutMapping(\"/store\") public void saveBookStore( @RequestBody BookStoreInput input ) { sqlCient.save(input); } @PutMapping(\"/store\") fun saveBookStore( @RequestBody input: BookStoreInput ) { sqlCient.save(input); } Here, sqlClient.save(input) first converts the input DTO to BookStore entity objects and related associated objects, then directly saves the entire data structure, completing the full replacement of complex form data. The save command recursively processes objects at all levels in the entire data structure, comparing the data structure being saved with the existing data structure in the database, finding inconsistencies and making modifications. However, no matter how complex the internal details of this process are, it's transparent to users.","s":"3.1. Full Data Replacement for Complex Forms","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#31-full-data-replacement-for-complex-forms","p":773},{"i":792,"t":"Now, let's implement a very simple requirement: adding a book to a bookstore. Java Kotlin @PutMapping(\"/store/{storeId}/books/{bookId}\") public void addBook( @PathVariable long storeId, @PathVariable long bookId ) { sqlClient.update( Immutables.createBook( draft.setId(bookId); draft.setStoreId(storeId); ) ) } @PutMapping(\"/store/{storeId}/books/{bookId}\") fun addBook( @PathVariable storeId: Long, @PathVariable bookId: Long ) { sqlClient.update( Book { id = bookId storeId = storeId } ) } This is a very simple example, while the previous example was completely different, completing very complex work. info Save commands can manifest as either very powerful advanced features or very simple basic features. Everything is possible, depending entirely on how you use them.","s":"3.2. Incremental Modification for Simple Data","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#32-incremental-modification-for-simple-data","p":773},{"i":794,"t":"Save commands bring absolute flexibility to data saving operations, however, overly powerful flexibility often means compromising security. That is, the client can freely write arbitrary complex data structures to the server, even if this far exceeds its permission scope. For this, Jimmer adopts a divide-and-conquer approach: The save command itself serves as underlying support, accepting Jimmer's dynamic entities, providing absolute flexibility and unlimited possibilities. Introducing InputDTO, automatically generating static types similar to POJO, standardizing and limiting client behavior, and being responsible for accepting request data. Finally, it automatically transforms into an entity object tree, handled by the save command.","s":"Security","u":"/jimmer-doc/docs/mutation/save-command/usage","h":"#security","p":773},{"i":797,"t":"In daily project development, there is a very challenging issue: translating database constraint violation errors into user-friendly error messages. Based on constraints that cannot be simply validated through input validation, databases have three types of constraints that are difficult to handle when violated: Primary key constraints Unique constraints (or unique indexes) Foreign key constraints To standardize across different database products, the SQL standard specifies that errors caused by constraint violations have the category code 23 (integrity constraint violation). All related error states begin with 23. However, standardization ends there. For more detailed issues, such as: Which constraint was violated How to get the table name and column name from the database dictionary based on the constraint name Most importantly, which data row modification action caused the exception Different database products behave inconsistently and lack clear APIs to obtain this information. To provide users with clear error descriptions, many business projects adopt a simple but crude method: pre-checking through queries However, this pre-checking approach has many disadvantages: Developers need to write various pre-checking code repeatedly, leading to high development costs Only suitable for simple single-record DML modifications, completely unsuitable for advanced operations like save commands that recursively save deep data structures in batch Poor performance, as errors are rare events, and pre-checking every time is wasteful Therefore, Jimmer adopts the following strategy: Uses post-investigation approach, directly modifying the database first, and if constraint violation errors are reported, investigating the cause afterward During error investigation, uses queries to gather as much information as possible, reporting: The path of the illegal object in the saved data structure The entity type and related properties that caused the error The specific object and related data that caused the error Allows users to customize exception translators to further translate Jimmer's investigated exceptions into end-user friendly messages info The database error investigation can occur due to either root object save failure or associated object save failure. Jimmer treats both cases equally, without distinction. However, to simplify the documentation, the examples in this article demonstrate saving relatively simple objects, avoiding deep data structures (in fact, if saving deep associated objects fails, it will be investigated the same way).","s":"Basic Concepts","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#basic-concepts","p":795},{"i":799,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(100L); draft.setName(\"SQL in Action\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"59.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(7L); // Exists draft.setName(\"LINQ in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }) ); sqlClient.insertEntities(books); val books = listOf( Book { id = 100L name = \"SQL in Action\" edition = 1 price = BigDecimal(\"59.9\") storeId = 2L }, Book { id = 7L // Exists name = \"LINQ in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L } ) sqlClient.insertEntities(books) This code will generate the following two SQL statements: Batch insert data insert into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) /* batch-0: [100, SQL in Action, 1, 59.9, 2] */ /* batch-1: [7, LINQ in Action, 3, 49.9, 2] */ Here, inserting the second record will cause an id conflict Investigate the cause of the constraint violation Most Databases Postgres Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK tb_1_ where tb_1_.ID = ? /* 7 */ Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK tb_1_ where tb_1_.ID = any(? /* [100, 7] */) For most databases, the original JDBC exception information from the batch SQL can determine which record violated the constraint, so only the problematic record is investigated For Postgres, the original JDBC exception information from the batch SQL cannot determine which record violated the constraint, so all records are investigated Either way, Jimmer can investigate and identify the problem. Finally, Jimmer will throw an exception based on the investigation results: org.babyfish.jimmer.sql.exception.SaveException$NotUnique: Save error caused by the path: \"\": Cannot save the entity, the value of the id property \"com.yourcompany.yourpoject.model.Book.id\" is \"7\" which already exists","s":"Checking for Id Conflicts","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#checking-for-id-conflicts","p":795},{"i":801,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(11L); draft.setName(\"GraphQL in Action\"); draft.setEdition(4); }), Immutables.createBook(draft -> { draft.setId(12L); draft.setName(\"GraphQL in Action\"); // `name + edition` exists draft.setEdition(1); // `name + edition` exists }) ); sqlClient.updateEntities(books); val books = listOf( Book { id = 11L name = \"GraphQL in Action\" edition = 4 }, Book { id = 12 name = \"GraphQL in Action\" // `name + edition` exists edition = 1 // `name + edition` exists } ) sqlClient.updateEntities(books) This code will generate the following two SQL statements: Batch update data update BOOK set NAME = ?, EDITION = ? where ID = ? /* batch-0: [GraphQL in Action, 4, 11] */ /* batch-1: [GraphQL in Action, 1, 12] */ Here, modifying the second record will cause a conflict with the combination of name and edition Investigate the cause of the constraint violation Most Databases Postgres Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) select tb_1_.ID from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) = ( ? /* GraphQL in Action */, ? /* 4 */ ) Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( (? /* GraphQL in Action */, ? /* 4 */), (? /* GraphQL in Action */, ? /* 1 */) ) For most databases, the original JDBC exception information from the batch SQL can determine which record violated the constraint, so only the problematic record is investigated For Postgres, the original JDBC exception information from the batch SQL cannot determine which record violated the constraint, so all records are investigated Either way, Jimmer can investigate and identify the problem. Finally, Jimmer will throw an exception based on the investigation results: #lighlight-next-line org.babyfish.jimmer.sql.exception.SaveException$NotUnique: Save error caused by the path: \"\": Cannot save the entity, the value of the key properties \"[ com.yourcompany.yourproject.model.Book.name, com.yourcompany.yourproject.Book.edition ]\" are \"Tuple2( _1=GraphQL in Action, _2=1 )\" which already exists info In the Mapping/Advanced Mapping/Key article, we introduced that entities can be configured with multiple unique constraints (or unique indexes) (in fact, this documentation has not been modified yet). If an entity has more than one unique constraint (or unique index), Jimmer will investigate them one by one. I'll translate the document while maintaining the technical terms as requested.","s":"Checking for Key Conflicts","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#checking-for-key-conflicts","p":795},{"i":803,"t":"In save commands, associations are divided into long associations and short associations. For long associations, if the associated object doesn't exist, Jimmer will automatically create it first, so there is no issue of non-existent associated objects. For short associations, Jimmer assumes that the associated object must exist, and problems will arise if the associated object doesn't exist. Therefore, this issue is specific to short associations. In the following examples, all associated objects are id-only objects. In Mapping/Basic Mapping/Real and Fake Foreign Keys, we introduced that Jimmer supports both real and fake foreign keys. Only real foreign keys involve database constraint violation issues, so we'll discuss them separately.","s":"Checking the Existence of Associated Objects","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"","p":795},{"i":805,"t":"For fake foreign keys, there are no foreign key constraints in the database. If the specified associated object doesn't exist, meaning the association ID is invalid, the database has no opinion on this. Therefore, by default, Jimmer doesn't check whether the associated object exists for fake foreign keys, allowing users to save invalid dangling values. Although this is unrelated to the main topic of this article, we'll still explain it. Users can configure the save command to make Jimmer verify the existence of associated objects beforehand. info Assume Book.store is a fake foreign key Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(8L); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(9L); draft.setStoreId(999L); // Invalid associated id }) ); sqlClient .saveEntitiesCommand(books) .setMode(SaveMode.UPDATE_ONLY) .setAutoIdOnlyTargetChecking( BookProps.STORE ) .execute(); val books = listOf( Book { id = 8L storeId = 2L }, Book { id = 9L storeId = 999L // Invalid associated id } ) sqlClient.updateEntities(books) { setAutoIdOnlyTargetChecking( Book::store ) } Here, the setAutoIdOnlyTargetChecking method is used to set which short associations need to be verified beforehand. Before saving the data, Jimmer will verify the association IDs through a query select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID = any(? /* [2, 999] */) Finally, it throws the following exception org.babyfish.jimmer.sql.exception.SaveException$IllegalTargetId: Save error caused by the path: \".store\": Cannot save the entity, the associated id of the reference property \"com.yourcompany.yourproject.model.Book.store\" is \"999\" but there is no corresponding associated object in the database","s":"Fake Foreign Keys","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#fake-foreign-keys","p":795},{"i":807,"t":"For real foreign keys, there are foreign key constraints in the database. If the specified associated object doesn't exist, meaning the association ID is invalid, the database will report a constraint violation error. Without any user configuration, if an error occurs, Jimmer will automatically analyze the error reported by the database to identify the invalid association ID. info Assume Book.store is a real foreign key Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(8L); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(9L); draft.setStoreId(999L); // Invalid associated id }) ); sqlClient.updateEntities(books); val books = listOf( Book { id = 8L storeId = 2L }, Book { id = 9L storeId = 999L // Invalid associated id } ) sqlClient.updateEntities(books) This code will generate two SQL statements Batch update data update BOOK set STORE_ID = ? where ID = ? /* batch-0: [2, 8] */ /* batch-1: [999, 9] */ Here, modifying the second record will cause a foreign key constraint violation on the STORE_ID column. Investigate the cause of the constraint violation Most Databases Postgres Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID = ? /* 999 */ Purpose: COMMAND(INVESTIGATE_CONSTRAINT_VIOLATION_ERROR) SQL: select tb_1_.ID from BOOK_STORE tb_1_ where tb_1_.ID = any(? /* [2, 999] */) For most databases, the original JDBC exception information thrown by the batch SQL can determine which record violated the constraint, so only the erroneous record is investigated For Postgres, the original JDBC exception information thrown by the batch SQL cannot determine which record violated the constraint, so all records are investigated Either way, Jimmer can investigate the problem. Finally, Jimmer will throw an exception based on the investigation results org.babyfish.jimmer.sql.exception.SaveException$IllegalTargetId: Save error caused by the path: \".store\": Cannot save the entity, the associated id of the reference property \"com.yourcompany.yourproject.model.Book.store\" is \"999\" but there is no corresponding associated object in the database tip As you can see, although the automatic error investigation mechanism for real foreign keys and the manual checking mechanism for fake foreign keys are completely different, they produce exactly the same exception information.","s":"Real Foreign Keys","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#real-foreign-keys","p":795},{"i":810,"t":"As mentioned earlier, Jimmer investigates database-reported constraint violations and throws exceptions org.babyfish.jimmer.sql.exception.SaveException.NotUnique Violation of primary key constraint, unique constraint, or unique index org.babyfish.jimmer.sql.exception.SaveException.IllegalTargetId Illegal association ID These two exceptions not only provide detailed error messages but also offer rich APIs to obtain various information. However, this is far from enough. In real projects, we must display easy-to-understand information for end users. Indeed, we can catch and handle exceptions after each save command call. However, Jimmer supports more powerful unified exception translation. Jimmer provides an exception translation interface ExceptionTranslator, the code is as follows ExceptionTranslator.java package org.babyfish.jimmer.sql.runtime; public interface ExceptionTranslator { /** * Translate the exception. * *

If the exception is not known how to be translated, * return null or the original argument.

*/ @Nullable Exception translate(@NotNull E exception, @NotNull Args args); interface Args { ...omitted... } } Users can implement this interface through classes (note: lambda expressions cannot be used) and specify generic type parameter for the interface, for example: Translate SaveException.NotUnique exception Java Kotlin public class NotUniqueExceptionTranslator extends ExceptionTranslator< SaveException.NotUnique > { ...omitted... } class NotUniqueExceptionTranslator : ExceptionTranslator< SaveException.NotUnique > { ...omitted... } Translate SaveException.IllegalTargetId exception Java Kotlin public class IllegalTargetIdExceptionTranslator extends ExceptionTranslator< SaveException.IllegalTargetId > { ...omitted... } class IllegalTargetIdExceptionTranslator : ExceptionTranslator< SaveException.IllegalTargetId > { ...omitted... } You can even translate other JDBC exceptions that Jimmer is not interested in Java Kotlin public class SQLExceptionTranslator extends ExceptionTranslator< java.sql.SQLException > { ...omitted... } class SQLExceptionTranslator : ExceptionTranslator< java.sql.SQLException > { ...omitted... }","s":"Exception Translation Interface","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#exception-translation-interface","p":795},{"i":812,"t":"Just writing a class to implement this interface is useless; you must create an object and register it to Jimmer take effect. Jimmer provides two registration methods, taking the NotUniqueExceptionTranslator mentioned above as an example: Global registration, which can be divided into two types Not using Jimmer's spring starter Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .addExceptionTranslator( new NotUniqueExceptionTranslator() ) ...other configurations omitted... .build(); val sqlClient = sqlClient { addExceptionTranslator( NotUniqueExceptionTranslator() ) ...other configurations omitted... } Using Jimmer's spring starter Java Kotlin @Component public class NotUniqueExceptionTranslator extends ExceptionTranslator { ...omitted... } @Component class NotUniqueExceptionTranslator : ExceptionTranslator { ...omitted... } Register for specific save commands Java Kotlin Book book = ...omitted...; sqlClient .saveCommand(book) .addExceptionTranslator( new NotUniqueExceptionTranslator() ) .execute() val book: Book = ...omitted... sqlClient.save(book) { addExceptionTranslator( new NotUniqueExceptionTranslator() ) }","s":"Multiple Registration Methods","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#multiple-registration-methods","p":795},{"i":814,"t":"Finally, let's show how to implement the translate method Translate SaveException.NotUnique exception Java Kotlin @Component public class NotUniqueExceptionTranslator extends ExceptionTranslator { @Override public @Nullable Exception translate( @NotNull SaveException.NotUnique exception, @NotNull Args args ) { if (exception.isMatched(BookProps.ID)) { return new IllegalArgumentException( \"Book with ID \" + exception.getValue(BookProps.ID) + \" already exists\" ); } if (exception.isMatched(BookProps.NAME, BookProps.EDITION)) { return new IllegalArgumentException( \"Book with name \" + exception.getValue(BookProps.NAME) + \" and edition \" + exception.getValue(BookProps.EDITION) + \" already exists\" ); } //No processing needed, can also be written as `return exception` return null; } } @Component class NotUniqueExceptionTranslator : ExceptionTranslator { override fun translate( exception: NotUnique, args: ExceptionTranslator.Args ): Exception? = when { exception.isMatched(Book::id) -> throw IllegalArgumentException( \"Book with ID ${exception[Book::id]} already exists\" ) exception.isMatched(Book::name, Book::edition) -> throw IllegalArgumentException( \"Book with name ${ exception[Book::id] } and edition ${ exception[Book::edition] } already exists\" ) else -> null //No processing needed, can also be written as `exception` } } Translate SaveException.IllegalTargetId exception Java Kotlin @Component public class IllegalTargetIdExceptionTranslator extends ExceptionTranslator { @Override public @Nullable Exception translate( @NotNull SaveException.IllegalTargetId exception, @NotNull Args args ) { if (exception.getProp() == BookProps.STORE.unwrap()) { throw new IllegalArgumentException( \"Cannot set invalid associated store ID for book: \" + exception.getTargetIds() ); } // No processing needed, can also be written as `return exception` return null; } } @Component class IllegalTargetIdExceptionTranslator : ExceptionTranslator { override fun translate( exception: IllegalTargetId, args: ExceptionTranslator.Args ): Exception? = when { exception.prop == BookProps.STORE.unwrap() -> throw IllegalArgumentException( \"Cannot set invalid associated store ID for book: ${ exception.targetIds }\" ) else -> null //No processing needed, can also be written as `exception` } }","s":"Implementing the translate Method","u":"/jimmer-doc/docs/mutation/save-command/investigation","h":"#implementing-the-translate-method","p":795},{"i":816,"t":"In this series of articles, we thoroughly discuss the dynamicity and immutability of Jimmer objects: Dynamicity To support querying and saving any data shape, Jimmer entities are dynamic. Immutability To avoid circular references and allow entities to be directly JSON serialized for HTTP and understood by any language, Jimmer entities are immutable. tip The dynamicity and immutability of Jimmer objects underpin the entire Jimmer ecosystem.","s":"Object","u":"/jimmer-doc/docs/object/","h":"","p":815},{"i":819,"t":"The usage of the update statement is: Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .where(author.firstName().eq(\"Dan\")) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) where(table.firstName eq \"Dan\") } .execute() println(\"Affected row count: $affectedRowCount\") The finally generated SQL is: update AUTHOR tb_1_ set FIRST_NAME = concat(tb_1_.FIRST_NAME, ?) where tb_1_.FIRST_NAME = ?","s":"Basic Usage","u":"/jimmer-doc/docs/mutation/update-statement","h":"#basic-usage","p":817},{"i":821,"t":"By default, update statements do not support joins, which will cause exceptions: Java Kotlin AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .where( author .books() .name() .eq(\"Learning GraphQL\") ) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) where( table .books .name eq \"Learning GraphQL\" ) } .execute() println(\"Affected row count: $affectedRowCount\") The exception message is: Table joins for update statement is forbidden by the current dialect, but there is a join `'Author.books'`. When using MySQL or Postgres, update statements can use JOIN clauses.","s":"Using JOIN","u":"/jimmer-doc/docs/mutation/update-statement","h":"#using-join","p":817},{"i":823,"t":"First, MySQLDialect needs to be specified when creating SqlClient: Spring Boot configuration: Declare dialect in application.yml or application.properties, like this jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect Non-Spring Boot configuration: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect( new org.babyfish.jimmer.sql.dialect.MySqlDialect() ) ... .build(); val sqlClient = newKSqlClient { setDialect(org.babyfish.jimmer.sql.dialect.MySqlDialect()) } Then JOIN can be used in update: Java Kotlin AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .set( author.books().name(), author.books().name().concat(\"*\") ) .set( author.books().store().name(), author.books().store().name().concat(\"*\") ) .where( author.books().store().name().eq(\"MANNING\") ) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) set( table.books.name, concat(table.books.name, value(\"*\")) ) set( table.books.store.name, concat(table.books.store.name, value(\"*\")) ) where( table.books.store.name eq \"MANNING\" ) } .execute() println(\"Affected row count: $affectedRowCount\") The finally generated SQL for MySQL is: update AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID inner join BOOK as tb_3_ on tb_2_.BOOK_ID = tb_3_.ID inner join BOOK_STORE as tb_4_ on tb_3_.STORE_ID = tb_4_.ID set tb_1_.FIRST_NAME = concat(tb_1_.FIRST_NAME, ?), tb_3_.NAME = concat(tb_3_.NAME, ?), tb_4_.NAME = concat(tb_4_.NAME, ?) where tb_4_.NAME = ?","s":"MySQL","u":"/jimmer-doc/docs/mutation/update-statement","h":"#mysql","p":817},{"i":825,"t":"First, PostgresDialect needs to be specified when creating SqlClient: Spring Boot configuration: Declare dialect in application.yml or application.properties, like this jimmer: dialect: org.babyfish.jimmer.sql.dialect.PostgresDialect Non-Spring Boot configuration: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect( new org.babyfish.jimmer.sql.dialect.PostgresDialect() ) ... .build(); val sqlClient = newKSqlClient { setDialect(org.babyfish.jimmer.sql.dialect.PostgresDialect()) } Then JOIN can be used in update: Java Kotlin AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; int affectedRowCount = sqlClient .createUpdate(author) .set( author.firstName(), author.firstName().concat(\"*\") ) .where( author.books().store().name().eq(\"MANNING\") ) .execute(); System.out.println(\"Affected row count: \" + affectedRowCount); val affectedRowCount = sqlClient .createUpdate(Author::class) { set( table.firstName, concat(table.firstName, value(\"*\")) ) where( table.books.store.name eq \"MANNING\" ) } .execute() println(\"Affected row count: $affectedRowCount\") caution Unlike MySQL, using JOIN in update statements in Postgres has the following restrictions: JOIN can only be used in the where clause, not in the set clause. That is, Postgres still only allows modifying fields of the current table, supporting joins to other tables only for condition filtering. The join path can have multiple levels, such as author.books().store(), where books() is level 1 and store() is level 2. The join type of the first level must be inner join. The finally generated SQL for Postgres is: update AUTHOR tb_1_ set FIRST_NAME = concat(tb_1_.FIRST_NAME, ?) from BOOK_AUTHOR_MAPPING as tb_2_ ❶ inner join BOOK as tb_3_ ❷ on tb_2_.BOOK_ID = tb_3_.ID inner join BOOK_STORE as tb_4_ ❸ on tb_3_.STORE_ID = tb_4_.ID where tb_1_.ID = tb_2_.AUTHOR_ID ❹ and tb_4_.NAME = ? info The join path author.books().store() has two levels, books() is level 1 and store() is level 2. Level 1 books() involves two tables: BOOK_AUTHOR_MAPPING table at ❶, but the join condition is missing here, supplemented at ❹. BOOK table at ❷. Level 2 store() involves one table: BOOK_STORE table at ❸. As you can see, in the update statement of Postgres, table joins directly related to the main table cannot use the join + on syntax, they must be equivalently transformed into from + where. This is why Jimmer requires the join type of level 1 to be inner join for update statements in Postgres dialect.","s":"Postgres","u":"/jimmer-doc/docs/mutation/update-statement","h":"#postgres","p":817},{"i":828,"t":"The save command supports 5 save modes that control how the aggregate root itself is saved: UPSERT: This is the default mode. It first queries to check if the aggregate root object being saved exists: If it doesn't exist: Executes an INSERT statement If it exists: Executes an UPDATE statement INSERT_ONLY: Unconditionally executes an INSERT statement INSERT_IF_ABSENT: If the data already exists, ignores the operation Otherwise, inserts the data UPDATE_ONLY: Unconditionally executes an UPDATE statement NON_IDEMPOTENT_UPSERT: If the object's @Id property or @Key properties are specified, performs behavior equivalent to UPSERT Otherwise, performs an INSERT operation note This behavior is equivalent to JPA's merge or Hibernate's saveOrUpdate, but it is not recommended in Jimmer. caution Save modes only affect the aggregate root object, not other associated objects. For associated objects, please refer to Associated Object Save Mode.","s":"Save Modes","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#save-modes","p":826},{"i":830,"t":"INSERT_ONLY means unconditionally inserting data Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List allocatedIds = sqlClient .saveEntities( books, SaveMode.INSERT_ONLY ) .getItems() .stream() .map(item -> item.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(\"Allocated ids: \" + allocatedIds); val books = listOf( Book { name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val allocatedIds = sqlClient .saveEntities( books, SaveMode.INSERT_ONLY ) .items .map { it.modifiedEntity.id } println(\"Allocated ids: $allocatedIds\") INSERT_ONLY works very simply - it inserts unconditionally without any checks. The generated batch operation SQL is as follows: insert into BOOK(NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?) /* batch-0: SQL in Action, 3, 49.9, 2 */ /* batch-1: [LINQ in Action, 2, 39.9, 2 */ In this example, since the id property's corresponding column uses database auto-numbering, after the batch insertion is complete, the ids allocated by the database for all data will be returned. The print result will be: Allocated ids: [100, 101]","s":"1. INSERT_ONLY","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#1-insert_only","p":826},{"i":832,"t":"UPDATE_ONLY means unconditionally updating data, and it has two scenarios: For Id-Specified objects, modify data according to id For Key-Specified objects, modify data according to key","s":"2. UPDATE_ONLY","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#2-update_only","p":826},{"i":834,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(3L); // Matched draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(100L); // Not matched draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); BatchSaveResult result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ); System.out.println(\"Affected row count: \" + result.getTotalAffectedRowCount()); val books = listOf( Book { id = 3L name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { id = 100L name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ) println(\"Affected row count: ${result.totalAffectedRowCount}\") Since the object's id property is specified, the object is updated based on its id. The generated batch operation SQL is as follows: update BOOK set NAME = ?, EDITION = ?, PRICE = ?, STORE_ID = ? where ID = ? /* batch-0: [SQL in Action, 3, 49.9, 2, 3] * /* batch-1: [LINQ in Action, 2, 39.9, 2, 100] */ This batch operation attempts to modify two records. Assuming the database only has one matching record, the print result will be 1.","s":"Updating Data by ID","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#updating-data-by-id","p":826},{"i":836,"t":"Assume the Book entity is defined as follows: Java Kotlin Book.java @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); ...other properties that are neither id nor key omitted... } Book.kt @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: Int ...other properties that are neither id nor key omitted... } Here Book.name and Book.edition are annotated with @Key. Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { // Id is not specified draft.setName(\"Learning GraphQL\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { // Id is not specified draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); BatchSaveResult result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ); for (MutationResultItem item : result.getItems()) { if (ImmutableObjects.isLoaded(item.getModifiedEntity(), BookProps.ID)) { System.out.println(\"Data is updated, updated id is \" + item.getModifiedEntity().id()); } else { System.out.println(\"Data is not updated\"); } } val books = listOf( Book { // Id is not specified name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { // Id is not specified name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val result = sqlClient .saveEntities( books, SaveMode.UPDATE_ONLY ) for (item in result.item) { if (isLoaded(item.modifiedEntity, Book::id)) { println(\"Data is updated, updated id is ${item.isModified}\") } else { println(\"Data is not updated\") } } Since the object's id property is not specified, the object is updated based on its key. The generated batch operation SQL is as follows: update BOOK set PRICE = ?, STORE_ID = ? where NAME = ? and EDITION = ? /* batch-0: [49.9, 2, Learning GraphQL, 3] */ /* batch-1: [39.9, 2, LINQ in Action, 2] */ The print result will be: Data is updated, updated id is 3 Data is not updated","s":"Updating Data by Key","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#updating-data-by-key","p":826},{"i":838,"t":"UPSERT means first checking if the data exists - if it exists then update it, otherwise insert it For Id-Specified objects, existence is determined by id, then deciding between INSERT or UPDATE For Key-Specified objects, existence is determined by key, then deciding between INSERT or UPDATE","s":"3. UPSERT","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#3-upsert","p":826},{"i":840,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(3L); draft.setName(\"Learning GraphQL\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(100L); draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); sqlClient .saveEntities( books, SaveMode.UPSERT ); val books = listOf( Book { id = 3L name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { id = 100L name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) sqlClient.save( books, SaveMode.UPSERT ) Jimmer prioritizes using the database's native UPSERT capabilities, so it generates different SQL for different databases Database Generated SQL H2 merge into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) key(ID) values( ?, ?, ?, ?, ? ) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ MySQL insert into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) on duplicate key update NAME = values(NAME), EDITION = values(EDITION), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Postgres insert into BOOK( ID, NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) on conflict(ID) do update set NAME = excluded.NAME, EDITION = excluded.EDITION, PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */","s":"Determining Data Existence by Id","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#determining-data-existence-by-id","p":826},{"i":842,"t":"If the object's id is not specified, for example: Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"Kotlin in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List ids = sqlClient .saveEntities( books, SaveMode.UPSERT ) .getItems() .stream().map(it -> it.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(ids); val books = listOf( Book { name = \"Learning GraphQL\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"GraphQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L }, Book { name = \"Kotlin in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val ids = sqlClient.save( books, SaveMode.UPSERT ).items.map{ it.id } println(ids) By default, Jimmer tries to use the database's native UPSERT capabilities whenever possible. However, in this case, it cannot achieve this (we'll discuss how to solve this issue shortly). In this situation, Jimmer will first execute a query, then based on the query results, determine which data should be INSERTed and which should be UPDATEd. This results in three SQL statements: Query, with reason provided Purpose: COMMAND(KEY_UNIQUE_CONSTRAINT_REQUIRED) SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( (? /* Learning GraphQL */, ? /* 3 */), (? /* GraphQL in Action */, ? /* 3 */), (? /* LINQ in Action */, ? /* 2 */), (? /* Kotlin in Action */, ? /* 2 */) ) info Jimmer prints KEY_UNIQUE_CONSTRAINT_REQUIRED in the logs, which is called QueryReason. Jimmer prioritizes using the database's native UPSERT capabilities, and if it cannot do so resulting in a query, it provides the QueryReason to help users investigate and find solutions. INSERT operation for non-existing data insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values( ?, ?, ?, ? ) /* batch-0: [LINQ in Action, 2, 39.9, 2] */ /* batch-1: [Kotlin in Action, 2, 39.9, 2] */ UPDATE operation for existing data update BOOK set PRICE = ?, STORE_ID = ? where ID = ? /* batch-0: [49.9, 2, 3] */ /* batch-1: [49.9, 2, 12] */ The printed result is: [3, 12, 100, 101] Where: 3 and 12 represent the ids of updated data 100 and 101 represent new ids assigned by the database for inserted data","s":"Determining Data Existence by Key","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#determining-data-existence-by-key","p":826},{"i":844,"t":"In the previous example, Jimmer executed a query and provided the QueryReason KEY_UNIQUE_CONSTRAINT_REQUIRED. Jimmer provides detailed documentation comments for all QueryReasons, see QueryReason for details. For KEY_UNIQUE_CONSTRAINT_REQUIRED specifically, it indicates the need for: Creating a unique constraint for Book.name and Book.edition properties: alter table book add constraint uq_book__name_edition unique(name, edition); This is because the database's UPSERT functionality depends on unique constraints (or unique indexes) Informing Jimmer through the @KeyUniqueConstraint annotation that the properties modified by @Key have corresponding unique constraints (or unique indexes) in the database Java Kotlin Book.java @Entity @KeyUniqueConstraint public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); ...omitting other properties that are neither id nor key... } Book.kt @Entity @KeyUniqueConstraint public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: Int ...omitting other properties that are neither id nor key... } caution For MySQL, you need: @KeyUniqueConstraint(noMoreUniqueConstraints = true) Once these two improvements are made, when running the previous example again, Jimmer will no longer execute a select statement but instead directly utilize the database's native UPSERT capabilities Database Generated SQL H2 merge into BOOK( NAME, EDITION, PRICE, STORE_ID ) key( NAME, EDITION ) values( ?, ?, ?, ? ) /* batch-0: [Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [GraphQL in Action, 3, 49.9, 2] */ /* batch-2: [LINQ in Action, 2, 39.9, 2] */ /* batch-3: [Kotlin in Action, 2, 39.9, 2] */ MySQL insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?) on duplicate key update /* fake update to return all ids */ ID = last_insert_id(ID), NAME = values(NAME), EDITION = values(EDITION), PRICE = values(PRICE), STORE_ID = values(STORE_ID) /* batch-0: [Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [GraphQL in Action, 3, 49.9, 2] */ /* batch-2: [LINQ in Action, 2, 39.9, 2] */ /* batch-3: [Kotlin in Action, 2, 39.9, 2] */ Postgres insert into BOOK( NAME, EDITION, PRICE, STORE_ID ) values(?, ?, ?, ?, ?) on conflict( NAME, EDITION ) do update set NAME = excluded.NAME, EDITION = excluded.EDITION, PRICE = excluded.PRICE, STORE_ID = excluded.STORE_ID returning ID /* batch-0: [Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [GraphQL in Action, 3, 49.9, 2] */ /* batch-2: [LINQ in Action, 2, 39.9, 2] */ /* batch-3: [Kotlin in Action, 2, 39.9, 2] */ info If you are using MySQL, there are two points to note: Unlike Postgres which can explicitly specify columns used for determining data existence through on conflict(NAME, EDITION), MySQL is special in that its on duplicate key cannot explicitly specify which columns are used for determining data existence. Therefore, when an insert ... on duplicate key statement doesn't insert the id field, MySQL will determine data existence based on all fields participating in unique constraints, even if these fields belong to multiple different unique constraints. Thus, you must add an additional parameter noMoreUniqueConstraints to the annotation, like: @KeyUniqueConstraint(noMoreUniqueConstraints = true) noMoreUniqueConstraints = true tells Jimmer that the table corresponding to the entity has only one unique constraint (or unique index). Users need to be responsible for their commitment. The SQL generated for MySQL includes: /* fake update to return all ids */ ID = last_insert_id(ID) This is a relatively tricky technique. If the data is updated, it returns the existing id of the updated data; otherwise, it returns the id assigned by the database for automatically inserted data. Apart from utilizing the database's native UPSERT capabilities, the functionality is exactly the same as the previous example, and the printed result will not change at all, as shown below: [3, 12, 100, 101] Where: 3 and 12 represent the ids of updated data 100 and 101 represent new ids assigned by the database for inserted data","s":"Improved Key-based Determination","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#improved-key-based-determination","p":826},{"i":846,"t":"Check if data exists in the database based on id or key. If it doesn't exist, insert it; otherwise, ignore the operation.","s":"4. INSERT_IF_ABSENT","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#4-insert_if_absent","p":826},{"i":848,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setId(3L); // Matched draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setId(100L); // Not matched draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); BatchSaveResult result = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ); System.out.println(\"Affected row count: \" + result.getTotalAffectedRowCount()); val books = listOf( Book { id = 3L // Matched name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { id = 100L // Not matched name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val result = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ) println(\"Affected row count: ${result.totalAffectedRowCount}\") Jimmer will prioritize using the database's native capabilities for INSERT_IF_ABSENT operations, generating different SQL for different databases: Database Generated SQL H2 merge into BOOK tb_1_ using(values(?, ?, ?, ?, ?)) tb_2_( ID, NAME, EDITION, PRICE, STORE_ID ) on tb_1_.ID = tb_2_.ID when not matched then insert(ID, NAME, EDITION, PRICE, STORE_ID) values (tb_2_.ID, tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID) /* batch-0: [3, SQL in Action, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ MySQL insert ignore into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Postgres insert into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) on conflict(ID) do nothing /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Assuming one record is inserted and one is ignored, the output will be: 1","s":"Check Data Existence by Id","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#check-data-existence-by-id","p":826},{"i":850,"t":"Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setName(\"SQL in Action\"); draft.setEdition(3); draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setName(\"LINQ in Action\"); draft.setEdition(2); draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List ids = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ) .getItems() .stream() .map(it -> it.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(ids); val books = listOf( Book { name = \"SQL in Action\" edition = 3 price = BigDecimal(\"49.9\") storeId = 2L }, Book { name = \"SQL in Action\" edition = 2 price = BigDecimal(\"39.9\") storeId = 2L } ) val ids = sqlClient .saveEntities( books, SaveMode.INSERT_IF_ABSENT ) .items .map { it.originalEntity.id } println(ids) info In this case, Jimmer will try to utilize the database's native capabilities for INSERT_IF_ABSENT operations whenever possible. If this isn't possible, Jimmer will perform a query to determine whether to proceed with insertion or ignore the operation, and will inform developers of the query reason. However, the scenario where a query is needed for determination has already been discussed in the previous UPSERT section. To simplify this article, let's assume no query is needed and we can directly use the database's native INSERT_IF_ABSENT capability. Jimmer generates different SQL for different databases: Database Generated SQL H2 merge into BOOK tb_1_ using(values(?, ?, ?, ?, ?)) tb_2_( ID, NAME, EDITION, PRICE, STORE_ID ) on tb_1_.NAME = tb_2_.NAME and tb_1_.EDITION = tb_2_.EDITION when not matched then insert(ID, NAME, EDITION, PRICE, STORE_ID) values (tb_2_.ID, tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID) /* batch-0: [3, SQL in Action, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ MySQL insert ignore into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ Postgres insert into BOOK(ID, NAME, EDITION, PRICE, STORE_ID) values(?, ?, ?, ?, ?) on conflict( NAME, EDITION ) do nothing returning ID /* batch-0: [3, Learning GraphQL, 3, 49.9, 2] */ /* batch-1: [100, LINQ in Action, 2, 39.9, 2] */ The output will be: [3, 100] Where: The first record already exists, so the insert operation is ignored, and the existing ID is 3 The second record doesn't exist, so insertion is performed with a new auto-generated ID of 100","s":"Check Data Existence by Key","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#check-data-existence-by-key","p":826},{"i":852,"t":"We've already demonstrated four modes: INSERT_ONLY, UPDATE_ONLY, UPSERT, and INSERT_IF_ABSENT. In the previous examples, the saved objects were either Id-specified or Key-specified objects. Now, let's discuss saving Wild objects, which have neither id nor key. Java Kotlin List books = Arrays.asList( Immutables.createBook(draft -> { draft.setPrice(new BigDecimal(\"49.9\")); draft.setStoreId(2L); }), Immutables.createBook(draft -> { draft.setPrice(new BigDecimal(\"39.9\")); draft.setStoreId(2L); }) ); List ids = sqlClient .saveEntities( books, // Default SaveMode.UPSERT ) .getItems() .stream() .map(it -> it.getModifiedEntity().id()) .collect(Collectors.toList()); System.out.println(ids); val books = listOf( Book { price = BigDecimal(\"49.9\") storeId = 2L }, Book { price = BigDecimal(\"39.9\") storeId = 2L } ) val ids = sqlClient .saveEntities( books, // Default SaveMode.UPSERT ) .items .map { it.originalEntity.id } println(ids) This code will result in the following exception (formatted for readability): Save error caused by the path: \"\": Cannot save illegal entity object whose type is \"com.yourproject.model.Book\", entity with neither id nor key cannot be accepted. There are 3 ways to fix this problem: 1. Specify the id property \"id\" for save objects; 2. Use the annotation \"org.babyfish.jimmer.sql.Key\" to decorate some scalar or foreign key properties in entity type, or call \"setKeyProps\" of the save command, to specify the key properties of \"com.yourproject.model.Book\", and finally specified the values of key properties of saved objects; 3. Specify the aggregate-root save mode of the save command to \"INSERT_ONLY(function changed)\", \"INSERT_IF_ABSTENT(function changed)\", or \"NON_IDEMPOTENT_UPSERT\" To save wild objects, you can use NON_IDEMPOTENT_UPSERT, which provides the following functionality: If the saved object is a wild object, it's equivalent to INSERT_ONLY mode, which is a non-idempotent operation Otherwise, it's equivalent to UPSERT mode, which is an idempotent operation caution This behavior is equivalent to JPA's merge or Hibernate's saveOrUpdate. However, this mode may mix idempotent and non-idempotent operations, so it's not recommended.","s":"5. NON_IDEMPOTENT_UPSERT","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#5-non_idempotent_upsert","p":826},{"i":854,"t":"Jimmer provides various save methods, many of which are equivalent: Save a single entity object Original Method Equivalent Shortcut Method save(entity, SaveMode.UPSERT) save(entity) save(entity, SaveMode.INSERT_ONLY) insert(entity) save(entity, SaveMode.UPDATE_ONLY) update(entity) save(entity, SaveMode.INSERT_IF_ABSENT) insertIfAbsent(entity) Save a single InputDTO object Original Method Equivalent Shortcut Method save(inputDTO, SaveMode.UPSERT) save(inputDTO) save(inputDTO, SaveMode.INSERT_ONLY) insert(inputDTO) save(inputDTO, SaveMode.UPDATE_ONLY) update(inputDTO) save(inputDTO, SaveMode.INSERT_IF_ABSENT) insertIfAbsent(inputDTO) Batch save multiple entity objects Original Method Equivalent Shortcut Method saveEntities(entities, SaveMode.UPSERT) saveEntities(entities) saveEntities(entities, SaveMode.INSERT_ONLY) insertEntities(entities) saveEntities(entities, SaveMode.UPDATE_ONLY) updateEntities(entities) saveEntities(entities, SaveMode.INSERT_IF_ABSENT) insertEntitiesIfAbsent(entities) Batch save multiple InputDTO objects Original Method Equivalent Shortcut Method saveInputs(inputDTOs, SaveMode.UPSERT) saveInputs(inputDTOs) saveInputs(inputDTOs, SaveMode.INSERT_ONLY) insertInputs(inputDTOs) saveInputs(inputDTOs, SaveMode.UPDATE_ONLY) updateInputs(inputDTOs) saveInputs(inputDTOs, SaveMode.INSERT_IF_ABSENT) insertInputsIfAbsent(inputDTOs)","s":"Various Save Methods","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#various-save-methods","p":826},{"i":856,"t":"To better demonstrate Jimmer's batch modification features, all examples in this article use the saveEntities method to save multiple objects, rather than using the save method to save a single object. These examples flexibly adjust the format of the objects being saved to demonstrate different functionalities. However, for each specific example, all objects saved by the saveEntities method have the same format. What happens if you try to use the saveEntities method to save multiple objects with different formats? Jimmer will first group these objects by format, then apply all the above functionalities to each group.","s":"Batch Saving Objects of Different Formats","u":"/jimmer-doc/docs/mutation/save-command/save-mode","h":"#batch-saving-objects-of-different-formats","p":826},{"i":858,"t":"Immutability is used to ensure that the data structure represented by Jimmer objects never contains circular references.","s":"Immutability","u":"/jimmer-doc/docs/object/immutable/","h":"","p":857},{"i":860,"t":"Java has supported immutable record types since Java 14, and Kotlin's data classes can easily implement immutable classes, even supporting copy functions. However, they are designed for simple immutable objects, and have problems dealing with complex deep data structure. The reason why deep, complex immutable objects are difficult to handle is not how to create a brand new data structure from scratch, which is very simple for any programming language. The real difficulty is wanting to make some local adjustments to an existing data structure and build a new data structure. This is very difficult for current Java and Kotlin, please see First define an immutable tree node Java Kotlin TreeNode.java record TreeNode( String name, List childNodes ) {} TreeNode.java data class TreeNode( val name: String, val childNodes: List ) Prepare an old object Java Kotlin var oldTreeNode = ...blabla... val oldTreeNode = ...blabla... Let's implement three data change operations in order from simple to complex to create a brand new object Change the name property of the root node Java Kotlin TreeNode newTreeNode = new TreeNode( \"Hello\", // Set root node name oldTreeNode.childNodes() ); val newTreeNode = oldTreeNode.copy( name = \"Hello\" // Set root node name ); This case is very simple, and the problems of Java/Kotlin are not obvious yet. Change the name property of the first level child node Breadcrumb conditions: Position of first level child node: pos1 Java Kotlin TreeNode newTreeNode = new TreeNode( oldTreeNode.name(), IntStream .range(0, oldTreeNode.childNodes().size()) .mapToObj(index1 -> { TreeNode oldChild1 = oldTreeNode.childNodes().get(index1); if (index1 != pos1) { return oldChild1; } return new TreeNode( \"Hello\", // Set name of first level child node oldChild1.childNodes() ); }) .toList() ); val newTreeNode = oldTreeNode.copy( childNodes = oldTreeNode .childNodes .mapIndexed { index1, child1 -> if (index1 == pos1) { child1.copy( name = \"Hello\" // Set name of first level child node ) } else { child1 } } ) Change the name property of the second level child node Breadcrumb conditions: Position of first level child node: pos1 Position of second level child node: pos2 Java Kotlin TreeNode newTreeNode = new TreeNode( oldTreeNode.name(), IntStream .range(0, oldTreeNode.childNodes().size()) .mapToObj(index1 -> { TreeNode oldChild1 = oldTreeNode.childNodes().get(index1); if (index1 != pos1) { return oldChild1; } return new TreeNode( oldChild1.name(), IntStream .range(0, oldChild1.childNodes().size()) .mapToObj(index2 -> { TreeNode oldChild2 = oldChild1.childNodes().get(index2); if (index2 != pos2) { return oldChild2; } else { return new TreeNode( \"Hello\", // Set name of second level child node oldChild2.childNodes() ); } }) .toList() ); }) .toList() ); val newTreeNode = oldTreeNode.copy( childNodes = oldTreeNode .childNodes .mapIndexed { index1, child1 -> if (index1 == pos1) { child1.copy( childNodes = child1 .childNodes .mapIndexed { index2, child2 -> if (index2 == pos2) { child2.copy( name = \"Hello\" // Set name of second level child node ) } else { child2 } } ) } else { child1 } } ) info It can be seen that as long as the object tree has some depth, creating a new immutable object based on another immutable object (i.e. secondary \"modification\") will be a nightmare.","s":"Current Situation","u":"/jimmer-doc/docs/object/immutable/current-situation","h":"","p":859},{"i":862,"t":"Unlike other ORMs, Jimmer uses immutable objects as entity objects.","s":"Reason","u":"/jimmer-doc/docs/object/immutable/reason","h":"","p":861},{"i":865,"t":"ORMs are often accompanied by a very headache problem: circular references. Data structures containing circular references cannot be simply JSON serialized, which is a fatal flaw for HTTP API design. In fact, this problem can be solved, for example, advanced features of JSON serialization libraries (such as Jackson) can serialize data structures containing circular references. But this is meaningless, because the serialized result contains special extended content, which cannot be understood by client programming languages. As an ORM, Jimmer of course allows users to define bidirectional associations between entity types, which is a powerful capability of ORM. However, when instantiating objects, once the developer has determined the type of the aggregate root, the data structure created can only be a unidirectional tree with the aggregate root object as the starting point. That is, bidirectional associations can be defined between entity types, keeping the possibilities of both directions. When instantiating objects, choose to use one of the association directions according to business characteristics. tip Jimmer entity-related data structures never contain circular references, so they can be directly involved in JSON serialization and then transmitted via HTTP protocols, while ensuring the simplicity of HTTP transmitted data to ensure that any programming language can understand. This brings great simplification to application development.","s":"Forbid Circular References","u":"/jimmer-doc/docs/object/immutable/reason","h":"#forbid-circular-references","p":861},{"i":867,"t":"Java Kotlin TreeNode aggregateRoot = Immutables.createTreeNode(aggregateRootDraft -> aggregateRootDraft .setName(\"Aggregate root\") .addIntoChildNodes(childDraft -> childDraft .setName(\"Child\") // Throw CircularReferenceException .setParent(aggregateRootDraft) ) ); val aggregateRoot = TreeNode { val that = this name = \"Aggregate root\" childNodes().addBy { name = \"Child\" // Throw CircularReferenceException parent = that } } info The above code uses an interface called TreeNode, which is the interface type automatically generated by Jimmer based on the user-defined type TreeNode. Readers can ignore this auto-generated interface for now, later documentation Draft will introduce it. tip This code will cause an exception: org.babyfish.jimmer.CircularReferenceException. Jimmer objects are immutable objects. Users can neither build circular references when creating objects, nor form circular references through subsequent modifications. This quality will be preserved forever.","s":"Incorrect Demo","u":"/jimmer-doc/docs/object/immutable/reason","h":"#incorrect-demo","p":861},{"i":869,"t":"In addition to ensuring absolutely no circular references between objects, immutable objects have many other benefits, including: Multi-thread safety, which is easy to understand and needs no explanation. For collection containers that rely on hashCode, such as Set and Map, object immutability is desperately needed. Once mutable objects are held by hashCode sensitive collection containers like Set or Map (as Key), developers must be very careful to ensure that the data shared by these containers is stable. If a mistake is accidentally made, it usually takes debug tracking to find the problem, which often wastes time and affects efficiency. (In fact, hashCode sensitive collection containers holding mutable objects is a common behavior, and it can also be said that most Java code is not strict, developers just avoid this problem.) In actual development, there are some other situations where objects are held for a long time. Although not dependent on hashCode, problems can also arise from holding objects for a long time, such as: Using data persisted in WebSession for a long time Using first-level cache, that is, using process-local cache in JVM memory to persist some data for a long time Careful developers certainly do not want references in WebSession or Cache that persist data for a long time to share data structures with references leaked to user code, which would lead to uncontrollable mutual interference. Therefore, when performing read/write operations on data structures persisted in WebSession or JVM internal Cache, careful developers will copy mutable data structures once before saving or returning them. Among them, copying when writing is still acceptable, but copying every time when reading is expensive. It can be seen that Using mutable objects, whether it is necessary to copy objects to ensure necessary security depends on the developer's ability to foresee risks. This requires developers to have some experience and be cautious by nature. However, even if the risks are foreseen, there is no objective standard for the solution. Being too strict will lead to too many unnecessary copies and waste, and being too loose will lead to insufficient copying and bugs (the more team members, the easier to make mistakes). Moreover, for data of a certain volume, there are often disputes within the team about the strictness of this protection mechanism, which is highly subjective. Using immutable objects, the data structure is only copied in part when it is \"modified\" (Here the \"modified\" is pseudo-modification, not real modification of the current data, which will be discussed in detail in subsequent documents. Jimmer/Immer internally optimizes this: the modified object will be copied, and from its parent object to the root node, all ancestor nodes will also be copied, while all other unchanged branches still share and reuse the original) to get a new aggregate root reference, and simply share the original reference in all other cases. It has a very strict, indisputable objectivity. tip Undoubtedly, development based on objective laws is bound to be superior to development based on subjective feelings, which is very important.","s":"Other benefits","u":"/jimmer-doc/docs/object/immutable/reason","h":"#other-benefits","p":861},{"i":871,"t":"Jimmer supports triggers that allow users to listen for database changes. tip Triggers can notify changes not only to objects, but also to associations.","s":"Trigger","u":"/jimmer-doc/docs/mutation/trigger","h":"","p":870},{"i":874,"t":"BinLog Trigger This is the default trigger type. It does not affect the SQL generated by Jimmer itself, has higher performance, is triggered after transaction commit, can listen to database changes caused by any reason, including data changes not caused by Jimmer API. However, it requires the database to support binlog/CDC. Transaction Trigger This trigger does not requires the database to support binlog/CDC, it is triggered before transaction commit. However, It can only listener to the data changes caused by current Jimmer application, and will generate additional query statements during the modification process to simulate the trigger, which has some impact on modification performance. info Its working mechanism is similar to Alibaba Seata's AT mode The differences between the two triggers are as follows: BinLog Trigger Transaction Trigger Trigger Time After transaction commit Before transaction commit Performance High Low Database changes listened Changes caused by any reason Only changes caused by calling current application's Jimmer API Database Requirements Support and enable binlog/CDC No requirements Working Principle Use third-party technology to push database binlog changes to message queue, Jimmer application listens to message queue Any Jimmer modification API automatically implants additional SQL queries to find data changes, similar to Alibaba Seata's AT mode Apart from the differences in this table, the notification data provided by the two triggers to the user is exactly the same.","s":"Trigger Classification","u":"/jimmer-doc/docs/mutation/trigger","h":"#trigger-classification","p":870},{"i":876,"t":"BinLog Trigger The BinLog trigger is triggered after transaction commit, facing the immutable facts. That is, the BinLog trigger has no impact on the original transaction, and is allowed to perform time-consuming operations. So it is suitable to execute multiple tasks in its handling logic, especially these tasks: Cache invalidation Heterogeneous data source synchronization Send messages to other microservices asynchronously Transaction Trigger The Transaction trigger is triggered before transaction commit, and its handling logic is injected directly into the current transaction. If an exception occurs in its event handling logic, it will cause the current transaction to fail; if its handling logic cannot complete quickly, it will cause the current transaction to hold resources for a long time. Therefore, the Transaction trigger is suitable for appending more modification behaviors in the current transaction without compromising atomicity. It is suitable for implementing business logic with strong generality through additional modifications when the database changes.","s":"Recommended Usage","u":"/jimmer-doc/docs/mutation/trigger","h":"#recommended-usage","p":870},{"i":879,"t":"Before discussing setting the trigger type, let's see how developers use triggers: sqlClient.getTriggers() or sqlClient.getTriggers(false): Returns BinLog trigger first, if not exists, returns Transaction trigger. sqlClient.getTriggers(true): Explicitly returns Transaction trigger, throws exception if not exists. To affect the trigger type that can be obtained by sqlClient.getTriggers() afterwards, you need to specify TriggerType when building SqlClient. TriggerType has three possible values: BINLOG_ONLY: Only supports BinLog trigger, this is the default configuration. sqlClient.getTriggers() and sqlClient.getTriggers(false) return BinLog trigger object sqlClient.getTriggers(true) will throw an exception, cannot return Transaction trigger object TRANSACTION_ONLY: Only supports Transaction trigger. No matter what the parameter of sqlClient.getTriggers is, it will return the same Transaction trigger object. BOTH: Supports both BinLog trigger and Transaction trigger. sqlClient.getTriggers() and sqlClient.getTriggers(false) return BinLog trigger object sqlClient.getTriggers(true) returns Transaction trigger object Here is a table to compare the three cases: Trigger Type getTriggers(false) getTriggers(true) BINLOG_ONLY Dedicated binlog triggers object Throw exception TRANSACTION_ONLY Shared transaction triggers object BOTH Dedicated binlog triggers object Dedicated transaction triggers object","s":"Concept","u":"/jimmer-doc/docs/mutation/trigger","h":"#concept","p":870},{"i":881,"t":"Q: Why is BINLOG_ONLY the default mode? A: Transaction triggers implant additional queries in all save operations to simulate triggers, which impacts performance, so it is disabled by default. Q: In TRANSACTION_ONLY mode, why do the two different trigger APIs share the same object? A: Jimmer's built-in cache consistency strategy must be driven by sqlClient.getTriggers(false), which developers cannot change. The purpose is to allow cache consistency maintenance work to not affect the modification transaction, and only start execution after transaction commit. Thus, the original transaction will not be elongated and can end quickly to release lock resources. However, not all database products support binlog/CDC. In this case, getTriggers(false) returns the transaction trigger object, masquerading as the BinLog trigger object, taking over cache consistency maintenance work that should have been handled by the BinLog trigger. That is to say, TRANSACTION_ONLY is designed for databases that do not support binlog/CDC, this is the only reason to use this mode. Q: In BOTH mode, there are two different trigger API objects, does this mean there are two chances to handle any modification? A: Yes, and this is an important feature. Unlike Jimmer's built-in cache consistency mechanism which must be driven by sqlClient.getTriggers(false), the user's business code does not have this limitation. Developers can freely decide whether an event handling logic should be registered to sqlClient.getTriggers(false) or sqlClient.getTriggers(true), or registered to both at the same time. If the developer's event handling logic contains some additional modifications that must participate in the atomic scope of the current transaction, sqlClient.getTriggers(true) should be chosen. If the developer's event handling logic does not need to participate in the current transaction, sqlClient.getTriggers(false) should be chosen to allow the current transaction to end as soon as possible and release lock resources as soon as possible. If the developer's event handling logic contains both of the above cases, it should be split into two and registered to the two triggers respectively. caution If the developer registers the same event callback for two types of triggers, then this callback will indeed be executed twice each time an event is notified. At this point, distinguishing between the two calls is very important. The parameter of the callback method is an object that can obtain the JDBC connection object. Whether its value is null can be used as a criterion to distinguish between the two: Non-null: First callback, caused by transaction trigger Null: Second callback, caused by binlog trigger Q: For databases that do not support binlog/CDC, isn't it impossible to do cache cleanup after transaction commit? A: Not exactly, it can be achieved if the developer is willing to optimize. Admittedly, such databases cannot support binlog triggers, and using transaction triggers to get data change notifications within the transaction lifetime is the only feasible method. However, it is not necessary to perform cache cleanup immediately after receiving the notification, because the cache cleanup work on remote caches like redis has network communication costs and risks of communication failure. Doing so will elongate or even fail the local transaction. Jimmer's cache system supports custom CacheOperator. By customizing CacheOperator, users can override the cache deletion behavior, record the cache deletion tasks but not execute them immediately, and perform the actual cache cleanup after the transaction is committed. Unreliable approach Customize CacheOperator and do not immediately clear the cache, but use ThreadLocal to record the keys of the caches to be deleted. Collectively clean up the cache in Spring's AfterCommit event. Reliable approach Customize CacheOperator and do not immediately clear the cache, but use a local event table in the same database to record the keys of the caches to be deleted. In Spring's AfterCommit event, take data from the local event table, clean up the cache, and if successful, delete the data in the local event table. Use a polling service to cover failures in step 2. tip Fortunately, for trigger type TRANSACTION_ONLY, Jimmer's Spring Boot Starter has already implemented this. Please refer to Cache Consistency/Transaction Trigger","s":"Q & A","u":"/jimmer-doc/docs/mutation/trigger","h":"#q--a","p":870},{"i":883,"t":"If using the Jimmer Spring Boot Starter, setting the trigger type is very simple. Just add a configuration in application.properties or application.yml. Its name is jimmer.trigger-type, and its value is BINLOG_ONLY | TRANSACTION_ONLY | BOTH.","s":"Using Jimmer Spring Boot Starter","u":"/jimmer-doc/docs/mutation/trigger","h":"#using-jimmer-spring-boot-starter","p":870},{"i":885,"t":"Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setTriggerType(TriggerType.BOTH) ...other config omitted... .build(); javax.sql.DataSource dataSource = ...; val sqlClient = newKSqlClient { setTriggerType(TriggerType.BOTH) ...other config omitted... }","s":"Not Using Jimmer Spring Boot Starter","u":"/jimmer-doc/docs/mutation/trigger","h":"#not-using-jimmer-spring-boot-starter","p":870},{"i":887,"t":"Unlike Transaction triggers, BinLog triggers require third-party technologies to push database binlog changes to the message queue, and applications need to listen to the message queue. Therefore, just specifying TriggerType as BINLOG_ONLY (default behavior) or BOTH when building the SqlClient object is not enough. There are many choices for the message queue, such as Kafka and RabbitMQ; there are also many choices for third-party technologies to push database binlog incrementally to the message queue, such as MaxWell, Debezium, Canal and DataBus. Jimmer does not restrict such choices. But to simplify the discussion, this article assumes Kafka is used as the message queue, and Maxwell (For MySQL) and Debezium (For postgres) are used as the push technologies. caution Because Debezium itself is a kafka-connector, using Debezium inevitably leads to Kafka being the message queue.","s":"BinLog Trigger Development Work","u":"/jimmer-doc/docs/mutation/trigger","h":"#binlog-trigger-development-work","p":870},{"i":889,"t":"Before development, the environment needs to be installed first, including the database, Kafka, and Maxwell or Debezium. Maxwell Enter the local directory corresponding to jimmer-examples/env-with-cache/maxwell after git clone. Execute bash ./install.sh Debezium Enter the local directory corresponding to jimmer-examples/env-with-cache/debezium after git clone. Execute bash ./install.sh","s":"Create External Environment","u":"/jimmer-doc/docs/mutation/trigger","h":"#create-external-environment","p":870},{"i":891,"t":"Whether choosing different databases (MySQL or Postgres), or choosing different push technologies (Maxwell or Debezium), there will be differences in the listening code. But in any case, the user code is quite similar, divided into the following 4 steps: Listen to the message queue and get the message body string. Use ObjectMapper.readTree for weakly typed parsing of the message text. info So-called weakly typed parsing means the resulting type is JsonNode, unrelated to business system types. Observe the content of the JsonNode and extract: Table name, referred to as tableName The sub-JsonNode of the old data before modification, referred to as oldJsonNode For insert operations, oldJsonNode is null The sub-JsonNode of the new data after modification, referred to as newJsonNode For delete operations, newJsonNode is null info The differences in listening code caused by different choices of database and push technology are reflected in this step. However, it is not difficult after observing the message content for inserts, updates, and deletes. Call JSqlClient.getBinLog().accept or KSqlClient.binLog.accept with tableName, oldJsonNode and newJsonNode. The following examples demonstrate MySQL + Maxwell and Postgres + Debezium respectively. MySQL + Maxwell For MySQL + Maxwell, the message format is typically like: { \"database\":\"jimmer_demo\", \"table\":\"book\", \"type\":\"update\", \"ts\":1688592724, \"xid\":11790, \"commit\":true, \"data\":{ \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store_id\":1, \"tenant\":\"a\", \"created_time\":\"2023-07-05 20:21:00\", \"modified_time\":\"2023-07-05 20:21:00\" }, \"old\":{ \"store_id\":2 } } After a little observation (it is recommended to look at the messages for insert, update, and delete), it is not difficult to implement the following message listening code: Java Kotlin MaxwellListener.java @Component public class MaxwellListener { private static final ObjectMapper MAPPER = new ObjectMapper(); private final Caches caches; public MaxwellListener(JSqlClient sqlClient) { this.caches = sqlClient.getCaches(); } @KafkaListener(topics = \"maxwell\") public void onMaxwellEvent( String json, Acknowledgment acknowledgment ) throws JsonProcessingException { JsonNode node = MAPPER.readTree(json); String tableName = node.get(\"table\").asText(); String type = node.get(\"type\").asText(); JsonNode data = node.get(\"data\"); switch (type) { case \"insert\": binLog.accept(tableName, null, data); break; case \"update\": binLog.accept(tableName, node.get(\"old\"), data); break; case \"delete\": binLog.accept(tableName, data, null); break; } acknowledgment.acknowledge(); } } MaxwellListener.kt @Component class MaxwellListener(sqlClient: KSqlClient) { private val caches: KCaches = sqlClient.caches @KafkaListener(topics = [\"maxwell\"]) fun onMaxwellEvent( json: String, acknowledgment: Acknowledgment ) { val node = MAPPER.readTree(json) val tableName = node[\"table\"].asText() val type = node[\"type\"].asText() val data = node[\"data\"] when (type) { \"insert\" -> binLog.accept(tableName, null, data) \"update\" -> binLog.accept(tableName, node[\"old\"], data) \"delete\" -> binLog.accept(tableName, data, null) } acknowledgment.acknowledge() } companion object { private val MAPPER = ObjectMapper() } } Postgres + Debezium For Postgres + Debezium, the message format is typically: { \"before\": { \"id\": 10, \"name\": \"GraphQL in Action\", \"edition\": 1, \"price\": \"H0A=\", \"store_id\": 1, \"tenant\": \"b\", \"created_time\": 1688590805971294, \"modified_time\": 1688590805971294 }, \"after\": { ...omitted... }, \"source\": { \"table\": \"book\", ...omitted... }, ...omitted... } We find some difficulties here, not all data can be directly recognized and converted by Jimmer's BinLog mapping mechanism: Properties of BigDecimal type (NUMERIC(M[, D]) in Postgres) like Book.price are displayed as Base64 encoded (H0A= in this example). This Base64 string is the info processed by org.apache.kafka.connect.data.Decimal Properties of LocalDateTime type (TIMESTAMP in Postgres) are displayed as numbers info Debezium's documentation will explain in detail how its various connectors process certain special data, such as how pg-connector handles decimal. The various connectors in Debezium also provide rich configurations, some of which can be used to change the default data handling method, such as changing how decimal data is handled, to avoid similar problems. However, Debezium's connectors usually serve all systems, and will not deliberately \"pamper\" a particular application. We cannot assume its configuration will always ensure output that Jimmer can understand directly. The examples that come with Jimmer deliberately do not configure the Debezium connector, letting it output kafka-connector specific data to demonstrate how Jimmer solves this problem, same as this article. Java Kotlin DebeziumCustomizer.java package ...omitted...; import org.apache.kafka.connect.data.Decimal; import org.apache.kafka.connect.data.Schema; import org.babyfish.jimmer.sql.runtime.Customizer; ...other imports omitted... @Component public class DebeziumCustomizer implements Customizer { private static final Schema BOOK_PRICE_SCHEMA = // Postgres `BOOK.PRICE` is `NUMERIC(10, 2)`, precision is 2 Decimal.schema(2); @Override public void customize(JSqlClient.Builder builder) { builder.setBinLogPropReader( ❶ LocalDateTime.class, (prop, jsonNode) -> { return Instant.ofEpochMilli( jsonNode.asLong() / 1000 ).atZone(ZoneId.systemDefault()).toLocalDateTime(); } ); builder.setBinLogPropReader( BookProps.PRICE, ❷ (prop, jsonNode) -> { byte[] bytes = Base64.getDecoder().decode(jsonNode.asText()); return Decimal.toLogical(BOOK_PRICE_SCHEMA, bytes); } ); } } DebeziumCustomizer.kt package ...omitted... import org.apache.kafka.connect.data.Decimal import org.apache.kafka.connect.data.Schema import org.babyfish.jimmer.sql.kt.cfg.KCustomizer ...other imports omitted... @Component class DebeziumCustomizer : KCustomizer { override fun customize(dsl: KSqlClientDsl) { dsl.setBinLogPropReader( LocalDateTime::class ❶ ) { _, jsonNode -> Instant.ofEpochMilli( jsonNode.asLong() / 1000 ).atZone(ZoneId.systemDefault()).toLocalDateTime() } dsl.setBinLogPropReader( Book::price ❷ ) { _, jsonNode -> Decimal.toLogical( BOOK_PRICE_SCHEMA, Base64.getDecoder().decode(jsonNode.asText()) ) } } companion object { private val BOOK_PRICE_SCHEMA = // Postgres `BOOK.PRICE` is `NUMERIC(10, 2)`, precision is 2 Decimal.schema(2) } } setBinLogPropReader allows developers to customize how to parse properties in the message that cannot be directly recognized, with two usages: ❶ Given the return type, specify how a type of properties should be parsed ❷ Precisely define how a certain property should be parsed After solving these problems, the message listening code is easy to implement: Java Kotlin DebeziumListener.java @Component public class DebeziumListener { private static final ObjectMapper MAPPER = new ObjectMapper(); private final BinLog binLog; public DebeziumListener(JSqlClient sqlClient) { this.binLog = sqlClient.getBinLog(); } @KafkaListener(topicPattern = \"debezium\\\\..*\") public void onDebeziumEvent( @Payload(required = false) String json, Acknowledgment acknowledgment ) throws JsonProcessingException { if (json != null) { // Debezium sends empty msg after delete msg JsonNode node = MAPPER.readTree(json); String tableName = node.get(\"source\").get(\"table\").asText(); binLog.accept( tableName, node.get(\"before\"), node.get(\"after\") ); } acknowledgment.acknowledge(); } } DebeziumListener.kt @Component class DebeziumListener(sqlClient: KSqlClient) { private val binLog: BinLog = sqlClient.binLog @KafkaListener(topicPattern = \"\"\"debezium\\..*\"\"\") fun onDebeziumEvent( @Payload(required = false) json: String?, acknowledgment: Acknowledgment ) { if (json !== null) { val node: JsonNode = MAPPER.readTree(json) val tableName: String = node[\"source\"][\"table\"].asText() binLog.accept( tableName, node[\"before\"], node[\"after\"] ) } acknowledgment.acknowledge() } companion object { private val MAPPER = ObjectMapper() } }","s":"Listen to Message Queue","u":"/jimmer-doc/docs/mutation/trigger","h":"#listen-to-message-queue","p":870},{"i":893,"t":"If using BinLog trigger, please enable it first as described above.","s":"Usage Examples","u":"/jimmer-doc/docs/mutation/trigger","h":"#usage-examples","p":870},{"i":895,"t":"Using Jimmer Spring Boot Starter If using the Jimmer Spring Boot Starter, trigger events will be sent as Spring events. So use @org.springframework.context.event.EventListener to handle Spring events: Java Kotlin DatabaseListener.java @Component public class DatabaseListener { @EventListener public void onEntityChanged(EntityEvent e) { if (e.getImmutableType().getJavaClass() == Book.class) { System.out.println(\"The object `Book` is changed\"); System.out.println(\"\\told: \" + e.getOldEntity()); System.out.println(\"\\tnew: \" + e.getNewEntity()); } } @EventListener public void onAssociationChanged(AssociationEvent e) { if (e.isChanged(BookProps.STORE)) { System.out.println(\"The many-to-one association `Book.store` is changed\"); System.out.println(\"\\tbook id: \" + e.getSourceId()); System.out.println(\"\\tdetached book store id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book store id: \" + e.getAttachedTargetId()); } else if (e.isChanged(BookStoreProps.BOOKS)) { System.out.println(\"The one-to-many association `BookStore.books` is changed\"); System.out.println(\"\\tbook store id: \" + e.getSourceId()); System.out.println(\"\\tdetached book id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book id: \" + e.getAttachedTargetId()); } } } DatabaseListener.kt @Component class DatabaseListener { @EventListener fun onEntityChanged(e: EntityEvent<*>) { if (e.ImmutableType.javaClass == Book::class.java) { println(\"The object `Book` is changed\") println(\"\\told: ${e.oldEntity}\") println(\"\\tnew: ${e.newEntity}\") } } @EventListener fun onAssociationChanged(e: AssociationEvent) { if (e.isChanged(Book::store)) { println(\"The many-to-one association `Book.store` is changed\") println(\"\\tbook id: ${e.sourceId}\") println(\"\\tdetached book store id: ${e.detachedTargetId}\") println(\"\\tattached book store id: ${e.attachedTargetId}\") } else if (e.isChanged(BookStore::books)) { println(\"The one-to-many association `BookStore.books` is changed\") println(\"\\tbook store id: ${e.sourceId}\") println(\"\\tdetached book id: ${e.detachedTargetId}\") println(\"\\tattached book id: ${e.attachedTargetId}\") } } } Using Low Level API If not using the Jimmer Spring Boot starter, need to manually register event handler code: Java Kotlin sqlClient.getTriggers().addEntityListener(Book.class, e -> { System.out.println(\"The object `Book` is changed\"); System.out.println(\"\\told: \" + e.getOldEntity()); System.out.println(\"\\tnew: \" + e.getNewEntity()); }); sqlClient.getTriggers().addAssociationListener(BookProps.STORE, e -> { System.out.println(\"The many-to-one association `Book.store` is changed\"); System.out.println(\"\\tbook id: \" + e.getSourceId()); System.out.println(\"\\tdetached book store id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book store id: \" + e.getAttachedTargetId()); }); sqlClient.getTriggers().addAssociationListener(BookStoreProps.BOOKS, e -> { System.out.println(\"The one-to-many association `BookStore.books` is changed\"); System.out.println(\"\\tbook store id: \" + e.getSourceId()); System.out.println(\"\\tdetached book id: \" + e.getDetachedTargetId()); System.out.println(\"\\tattached book id: \" + e.getAttachedTargetId()); }); sqlClient.triggers.addEntityListener(Book::class) { println(\"The object `Book` is changed\") println(\"\\told: ${e.oldEntity}\") println(\"\\tnew: ${e.newEntity}\") } sqlClient.triggers.addAssociationListener(Book::store) { println(\"The many-to-one association `Book.store` is changed\") println(\"\\tbook id: ${e.sourceId}\") println(\"\\tdetached book store id: ${e.detachedTargetId}\") println(\"\\tattached book store id: ${e.attachedTargetId}\") } sqlClient.triggers.addAssociationListener(BookStore::books) { println(\"The one-to-many association `BookStore.books` is changed\") println(\"\\tbook store id: ${e.sourceId}\") println(\"\\tdetached book id: ${e.detachedTargetId}\") println(\"\\tattached book id: ${e.attachedTargetId}\") } Where sqlClient.getTriggers() or sqlClient.triggers is used to register handler logic to the default trigger. Can also replace sqlClient.getTriggers() or sqlClient.triggers with sqlClient.getTriggers(true) to register handler logic to the Transaction trigger.","s":"Register Handler Logic","u":"/jimmer-doc/docs/mutation/trigger","h":"#register-handler-logic","p":870},{"i":897,"t":"Now we trigger events to experience triggers. The BinLog trigger can listen to database changes caused by any reason, even if the database is modified by bypassing the application using any other means. For example, you can directly execute: update BOOK set STORE_ID = 2 where ID = 7; However, to send events to the Transaction trigger, the database must be modified through Jimmer's API, for example: Java Kotlin BookTable table = Tables.BOOK_TABLE; sqlClient .createUpdate(book) .set(table.store().id(), 2L) .where(table.id().eq(7L)) .execute(); sqlClient .createUpdate(Book::class) { set(table.store.id, 2L) where(table.id eq 7L) } .execute() The output is: The object `Book` is changed ❶ old: {\"id\":7,\"name\":\"Programming TypeScript\",\"edition\":1,\"price\":47.50,\"store\":{\"id\":1}} new: {\"id\":7,\"name\":\"Programming TypeScript\",\"edition\":1,\"price\":47.50,\"store\":{\"id\":2}} The many-to-one association `Book.store` is changed ❷ book id: 7 detached book store id: 1 attached book store id: 2 The one-to-many association `BookStore.books` is changed ❸ book store id: 1 detached book id: 7 attached book id: null The one-to-many association `BookStore.books` is changed ❹ book store id: 2 detached book id: null attached book id: 7 Where: ❶ Represents object change event ❷, ❸ and ❹ Represent association change events tip Jimmer triggers can not only simply convert table changes into object change events, but also convert foreign key changes and middle table changes into association change events.","s":"Experience Triggers","u":"/jimmer-doc/docs/mutation/trigger","h":"#experience-triggers","p":870},{"i":899,"t":"info The example code in this article uses a type called BookDraft, which is an interface type automatically generated by Jimmer based on the user-defined type Book. Readers can ignore this auto-generated interface for now. The later document Draft will introduce it.","s":"Dynamicity","u":"/jimmer-doc/docs/object/dynamic","h":"","p":898},{"i":902,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); }); val book = Book { name = \"Learning GraphQL\" } In this case, the JSON for the books object would be like follows {\"name\": \"Learning GraphQL\"}","s":"1. A few properties","u":"/jimmer-doc/docs/object/dynamic","h":"#1-a-few-properties","p":898},{"i":904,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.99\")); }); val book = Book { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") } In this case, the JSON for the books object would be like follows { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99 }","s":"2. More Properties","u":"/jimmer-doc/docs/object/dynamic","h":"#2-more-properties","p":898},{"i":906,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.99\")); draft.applyStore(store -> { store.setName(\"O'REILLY\"); store.setWebsite(\"https://www.oreilly.com/\"); }); }); val book = Book { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") store { name = \"O'REILLY\" website = \"https://www.oreilly.com/\" } } In this case, the JSON for the books object would be like follows { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99, \"store\": { \"name\": \"O'REILLY\", \"website\": \"https://www.oreilly.com/\" } }","s":"3. Include Association","u":"/jimmer-doc/docs/object/dynamic","h":"#3-include-association","p":898},{"i":908,"t":"Java Kotlin Book book = Immutables.createBook(draft -> { draft.setName(\"Learning GraphQL\"); draft.setEdition(1); draft.setPrice(new BigDecimal(\"49.99\")); draft.applyStore(store -> { store.setName(\"O'REILLY\"); store.setWebsite(\"https://www.oreilly.com/\"); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Eve\"); author.setLastName(\"Procello\"); author.setGender(Gender.FEMALE); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Alex\"); author.setLastName(\"Banks\"); author.setGender(Gender.MALE); }); }); val book = Book { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") store { name = \"O'REILLY\" website = \"https://www.oreilly.com/\" } authors().addBy { firstName = \"Eve\" setLastName = \"Procello\" gender = Gender.FEMALE } authors().addBy { firstName = \"Alex\" lastName = \"Banks\" gender = Gender.MALE } } In this case, the JSON for the books object would be like follows { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99, \"store\": { \"name\": \"O'REILLY\", \"website\": \"https://www.oreilly.com/\" }, \"authors\": [ { \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender:\" \"FEMALE\" }, { \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender:\" \"MALE\" } ] }","s":"4. More Associations (Larger Breadth)","u":"/jimmer-doc/docs/object/dynamic","h":"#4-more-associations-larger-breadth","p":898},{"i":910,"t":"Here is the translation to English: Unlike the previous examples, here we choose BookStore as the aggregate root for the data structure, rather than Book. Java Kotlin BookStore store = Immutables.createBookStore(draft -> { draft.setName(\"O'REILLY\"); draft.setWebsite(\"https://www.oreilly.com/\"); draft.addIntoBooks(book -> { book.setName(\"Learning GraphQL\"); book.setEdition(1); book.setPrice(new BigDecimal(\"49.99\")); book.addIntoAuthors(author -> { author.setFirstName(\"Eve\"); author.setLastName(\"Procello\"); author.setGender(Gender.FEMALE); }); book.addIntoAuthors(author -> { author.setFirstName(\"Alex\"); author.setLastName(\"Banks\"); author.setGender(Gender.MALE); }); }); }); val store = BookStore { name = \"O'REILLY\" website = \"https://www.oreilly.com/\" books().addBy { name = \"Learning GraphQL\" edition = 1 price = BigDecimal(\"49.99\") authors().addBy { firstName = \"Eve\" setLastName = \"Procello\" gender = Gender.FEMALE } authors().addBy { firstName = \"Alex\" lastName = \"Banks\" gender = Gender.MALE } } } In this case, the JSON for the store object would be like follows { \"name\": \"O'REILLY\", \"website\": \"https://www.oreilly.com/\", \"books\": [ { \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 49.99, \"authors\": [ { \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender:\" \"FEMALE\" }, { \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender:\" \"MALE\" } ] } ] }","s":"5. Deeper Associations (Larger Depth)","u":"/jimmer-doc/docs/object/dynamic","h":"#5-deeper-associations-larger-depth","p":898},{"i":912,"t":"Dynamic object may lack any property, or in other words, dynamic object are not required to have all properties set. caution In dynamic object, missing properties and properties set to null are completely different things. Missing property: The value of the property of the object is unknown, the current business is not interested in it Property set to null: The value of the property of the object is known, it really is nothing In static POJOs, the two are actually indistinguishable. What's worse, developers often intentionally or unintentionally confuse the two by taking advantage of Java's lack of null safety. The concept of dynamic object is very important and key to understanding Jimmer! For missing properties: Using code to access them directly will result in an exception org.babyfish.jimmer.UnloadedException note If the reader has Hibernate experience, think of this as org.hibernate.LazyInitializationException. In Jackson serialization, they will be automatically ignored. info This requires some configuration for Jackson. Since this detail is very important, it has been made into a separate document. Please refer to Work with Jackson.","s":"Characteristics of Dynamic Objects","u":"/jimmer-doc/docs/object/dynamic","h":"#characteristics-of-dynamic-objects","p":898},{"i":914,"t":"Dynamicity is an intrinsic characteristic of Jimmer objects and is universally applicable. Both the ORM framework itself and developers can easily build dynamic objects for each other to use. Jimmer creates dynamic objects and returns them to developers That is, query data structures of any shape. This feature is called object fetchers. Developers create dynamic objects and pass them to Jimmer That is, save data structures of any shape. This feature is called save commands.","s":"Interaction with ORM","u":"/jimmer-doc/docs/object/dynamic","h":"#interaction-with-orm","p":898},{"i":916,"t":"Jimmer creates dynamic objects and returns them to developers Java Kotlin Your browser does not support the video tag. Your browser does not support the video tag. info Compare to GraphQL GraphQL is based on HTTP services, which can only be experienced if it crosses the boundaries of HTTP services. In Jimmer, this is the underlying API for ORM, and you can use this capability in any code logic. Until now, the GraphQL protocol does not support recursive queries on self-associated properties with infinite depth; And Jimmer supports","s":"Object Fetchers","u":"/jimmer-doc/docs/object/dynamic","h":"#object-fetchers","p":898},{"i":918,"t":"Developers create dynamic objects and pass them to Jimmer Save instructions allow developers to save data structures of any shape, rather than save simple objects. By default, when AssociatedSaveMode is set to REPLACE, Jimmer will completely replace the existing data structure in the database with the structure being saved, as shown in the figure: Top right: Users pass in a data structure of any shape for Jimmer to write to the database. Top left: Query the existing data structure from the database to compare with the new data structure passed in by users. Whatever shape of data structure the user passes in, the same shape will be queried from the database, ensuring the shapes of old and new data structures are identical. Therefore, the querying and comparison costs are determined by the complexity of the user-provided data structure. Below:Compare the new and old data structures, find the DIFF and execute corresponding SQL operations to make them consistent: Orange parts: For entity objects that exist in both new and old data structures, modify data if scalar properties have changed Blue parts: For entity objects that exist in both new and old data structures, modify associations if they have changed Green parts: For entity objects that exist in the old data structure but not in the new one, decouple this object, clear associations and possibly delete data Red parts: For entity objects that exist in the new data structure but not in the old one, insert data and establish associations tip Unlike other ORMs, Jimmer doesn't require describing how data should be saved in the entity model Whether certain scalar properties need to be saved Taking JPA as an example, this is controlled throughColumn.insertable andColumn.updatable. Whether certain association properties need to be saved Taking JPA as an example, this is controlled throughOneToOne.cascade,ManyToOne.cascade,OenToMany.cascade andManyToOne.cascade. Jimmer adopts a completely different strategy - its entity objects are not POJOs and can flexibly control the shape of data structures. That is, entity objects have dynamic properties - not specifying a property for an entity object and setting an entity's property to null are completely different things. For any entity object, Jimmer will only save the specified properties while ignoring unspecified ones. Therefore, Jimmer doesn't need to consider data saving behavior during entity modeling, but rather describes the expected behavior at runtime through the data structure being saved itself, providing absolute flexibility.","s":"Save Commands","u":"/jimmer-doc/docs/object/dynamic","h":"#save-commands","p":898},{"i":920,"t":"Jimmer objects are dynamic and not all properties of an object need to be initialized. It allows missing some properties. Accessing an unspecified property directly in code will cause an exception. Unspecified properties are automatically ignored in JSON serialization without exceptions. JSON serialization is mentioned here, referring to jackson. jimmer-core defines a jackson module: org.babyfish.jimmer.jackson.ImmutableModule which can add the ability of serialize/deserialize jimmer immutable objects for jackson. There are two cases: Using Spring Boot Starter In this case, Jimmer has already registered ImmutableModule to Spring as below: // Internal Jimmer code, not user code @ConditionalOnMissingBean(ImmutableModule.class) @Bean public ImmutableModule immutableModule() { return new ImmutableModule(); } Therefore, the default ObjectMapper of Spring can already serialize/deserialize Jimmer dynamic objects, and most serialization/deserialization work is done automatically by Spring during HTTP interaction, so no extra development is required. caution The default JSON handling library in Spring is jackson. Don't replace it. Using low level API Java Kotlin ObjectMapper mapper = new ObjectMapper() .registerModule(new ImmutableModule()); TreeNode treeNode = Immutables.createTreeNode( draft -> draft.setName(\"Root Node\") ); // Serialize String json = mapper.writeValueAsString(treeNode); // Deserialize TreeNode deserializedTreeNode = mapper.readValue(json, TreeNode.class); val mapper = ObjectMapper() .registerModule(ImmutableModule()) val treeNode = TreeNode { name = \"Root Node\" } // Serialize val json = mapper.writeValueAsString(treeNode) // Deserialize val deserializedTreeNode = mapper.readValue(json, TreeNode::class.java) tip For serialization, there is a handy way which is the toString method of jimmer objects.","s":"Working with Jackson","u":"/jimmer-doc/docs/object/jackson","h":"","p":919},{"i":922,"t":"Even if entity objects support dynamism to express arbitrary data structures, conversion between entities and DTOs is still unavoidable. Jimmer provides dynamic entities that can solve a large part of the DTO explosion problem very well. Therefore, generally speaking, it is not necessary to define output DTO types to express query results. However, not all DTO types can be eliminated. Input DTO objects are hard to remove. For example, in GraphQL, although dynamic GraphQLObject data is returned for the client from the output perspective, static GraphQLInput data submitted by the client is accepted from the input perspective. Why does the GraphQL protocol define GraphQLInput as a static type? Because API explicitness and system security are very important requirements, please refer to Problems with dynamic objects as input parameters. The problems faced by the GraphQL protocol are also faced by Jimmer, which must provide a complete solution. As a comprehensive solution, Jimmer is not limited to ORM itself, but considers the whole project. To solve this problem, it provides two ways: DTO Language A solution tailored for Jimmer with extremely high development efficiency. DTO Language is designed for that part of the DTO types that cannot be eliminated, with the goal of making them extremely cheap. MapStruct A solution that combines the MapStruct framework and can implement arbitrarily complex conversion logic.","s":"DTO conversion","u":"/jimmer-doc/docs/object/view/","h":"","p":921},{"i":924,"t":"Jimmer provides a series of static tool methods for operating on dynamic objects or their Drafts. info For brevity, this article only lists the strongly typed usages. There are also weakly typed versions of these refactoring methods.","s":"Tool Methods","u":"/jimmer-doc/docs/object/tool","h":"","p":923},{"i":927,"t":"Purpose: Determine if a property of a dynamic object is loaded Java Kotlin if (ImmutableObjects.isLoaded(book, BookProps.AUTHORS)) { ... } if (isLoaded(book, Book::authors)) { ... }","s":"isLoaded","u":"/jimmer-doc/docs/object/tool","h":"#isloaded","p":923},{"i":929,"t":"Purpose: Dynamically get a property of an object Exception: The property of the object is in an unloaded state Java Kotlin List authors = ImmutableObjects.get(book, BookProps.AUTHORS); val authors = get(book, Book::authors)","s":"get","u":"/jimmer-doc/docs/object/tool","h":"#get","p":923},{"i":931,"t":"Purpose: Check if a dynamic object is only set with an id property Precondition: The object type is annotated with @Entity and is an ORM entity with an id Java Kotlin if (ImmutableObjects.isIdOnly(book)) { ... } if (isIdOnly(book)) { ... }","s":"isIdOnly","u":"/jimmer-doc/docs/object/tool","h":"#isidonly","p":923},{"i":933,"t":"Purpose: Construct an object of the given type and set its id property Precondition: The object type is annotated with @Entity and is an ORM entity with an id Java Kotlin Book book = ImmutableObjects.makeIdOnly(Book.class, 1L); val book = makeIdOnly(Book::class, 1L) tip For Kotlin, the id parameter must be non-null, and the return value is also non-null. To accept a possibly null id and directly return null when id is null, call makeNullableIdOnly Java's makeIdOnly is actually equivalent to Kotlin's makeNullableIdOnly.","s":"makeIdOnly","u":"/jimmer-doc/docs/object/tool","h":"#makeidonly","p":923},{"i":935,"t":"Purpose: Check if an object is only set with an id property. I.e. no associated properties are set to non-null (including unset and set to null). info If the object is an ORM entity, it is an exception if a one-to-one or many-to-one property based directly on a foreign key is set to an associated object with only an id. Java Kotlin if (ImmutableObjects.isLonely(book)) { ... } if (isLonely(book)) { ... }","s":"isLonely","u":"/jimmer-doc/docs/object/tool","h":"#islonely","p":923},{"i":937,"t":"Purpose: Create a new object based on an existing object. The new object copies all non-associated properties from the old object, but all associated properties remain unset. info For ORM entities, special handling is performed for one-to-one and many-to-one properties based directly on foreign keys. These are set to associated objects with only ids or null. Java Kotlin Book lonelyBook = ImmutableObjects.toLonely(book); val lonelyBook = toLonely(book)","s":"toLonely","u":"/jimmer-doc/docs/object/tool","h":"#tolonely","p":923},{"i":939,"t":"Purpose: Create a new object based on an existing object. The new object only copies the id property from the old object. Precondition: The object type is annotated with @Entity and is an ORM entity with an id Java Kotlin Book lonelyBook = ImmutableObjects.toIdOnly(book); val lonelyBook = toIdOnly(book) Or Java Kotlin List lonelyBooks = ImmutableObjects.toIdOnly(books); val lonelyBooks = toIdOnly(books)","s":"toIdOnly","u":"/jimmer-doc/docs/object/tool","h":"#toidonly","p":923},{"i":941,"t":"Purpose: Shortcut for JSON deserialization Java Kotlin Book book = ImmutableObjects.fromObject( Book.class, \"{\\\"id\\\":1,\\\"name\\\":\\\"Learning GraphQL\\\",\\\"authorIds\\\":[2,1]}\" ); val book = fromString( Book::class, \"\"\"{\"id\":1,\"name\":\"Learning GraphQL\",\"authorIds\":[2,1]}\"\"\" )","s":"fromString","u":"/jimmer-doc/docs/object/tool","h":"#fromstring","p":923},{"i":944,"t":"Purpose: Dynamically set Draft properties Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.set(draft, BookProps.AUTHOR_IDS, Arrays.asList(1L, 3L)); }); val newBook = Book(book) { set(draft, Book::authorIds, listOf(1L, 3L)) }","s":"set","u":"/jimmer-doc/docs/object/tool","h":"#set","p":923},{"i":946,"t":"Purpose: Unload a Draft property, i.e. mark a property as unloaded Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.unload(draft, BookProps.AUTHOR_IDS); }); val newBook = Book(book) { unload(draft, Book::authorIds) }","s":"unload","u":"/jimmer-doc/docs/object/tool","h":"#unload","p":923},{"i":948,"t":"Purpose: Show a property Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.show(draft, BookProps.AUTHOR_IDS); }); val newBook = Book(book) { show(draft, Book::authorIds) }","s":"show","u":"/jimmer-doc/docs/object/tool","h":"#show","p":923},{"i":950,"t":"Purpose: Hide a property Java Kotlin Book newBook = Immutables.createBook(book, draft -> { DraftObjects.hide(draft, BookProps.AUTHOR_IDS); }); val newBook = Book(book) { hide(draft, Book::authorIds) }","s":"hide","u":"/jimmer-doc/docs/object/tool","h":"#hide","p":923},{"i":952,"t":"In order to solve the inconvenience of secondary \"modification\" (creating a new immutable object based on another immutable object) of complex immutable objects in the current JVM ecosystem, some immutable object frameworks were born: Immutables FreeBuilder Arrow-Kt(Kotlin) Kopyk(Kotlin) MuteKt(Kotlin) Jimmer is an ORM framework, and handling deep data structures is a core issue for ORM, so Jimmer must do similar work. Jimmer needs to provide elegant dual language support for both Java and Kotlin at the same time. None of the above solutions can meet this requirement, so Jimmer did not use any of them, but chose to transplant immer from the JavaScript/TypeScript field. Next, we will demonstrate the power of immutable objects transplanted from immer in three steps: Define immutable types Create an immutable data structure from scratch Based on an existing data structure, create a new data structure according to some desired modifications. This last step is where the core value of immer lies. Please pay close attention.","s":"Solution","u":"/jimmer-doc/docs/object/immutable/solution","h":"","p":951},{"i":954,"t":"To demonstrate this feature, there is no need for the @Entity annotation on ORM entities, the non-ORM @Immutable is sufficient. Java Kotlin TreeNode.java package yourpackage; import java.util.List; import org.babyfish.jimmer.Immutable; @Immutable public interface TreeNode { String name(); List childNodes(); } TreeNode.kt package yourpackage import org.babyfish.jimmer.Immutable @Immutable interface TreeNode { val name: String val childNodes: List }","s":"1. Define immutable type","u":"/jimmer-doc/docs/object/immutable/solution","h":"#1-define-immutable-type","p":951},{"i":956,"t":"Java Kotlin TreeNode treeNode = Immutables.createTreeNode(root -> { root.setName(\"Root\").addIntoChildNodes(food -> { food .setName(\"Food\") .addIntoChildNodes(drink -> { drink .setName(\"Drink\") .addIntoChildNodes(cocacola -> { cocacola.setName(\"Cocacola\"); }) .addIntoChildNodes(fanta -> { fanta.setName(\"Fanta\"); }); ; }); ; }); }); val treeNode = TreeNode { name = \"Root\" childNodes().addBy { name = \"Food\" childNodes().addBy { name = \"Drinks\" childNodes().addBy { name = \"Cocacola\" } childNodes().addBy { name = \"Fanta\" } } } }","s":"2. Create data structure from scratch","u":"/jimmer-doc/docs/object/immutable/solution","h":"#2-create-data-structure-from-scratch","p":951},{"i":958,"t":"Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode( treeNode, // existing data root -> { root .childNodes(false).get(0) // Food .childNodes(false).get(0) // Drink .childNodes(false).get(0) // Cocacola .setName(\"Cocacola plus\"); } ); // Show that `newTreeNode` reflects the developer's desired modifications // Note that this does not affect the existing `treeNode` at all System.out.println(\"treeNode:\" + treeNode); System.out.println(\"newTreeNode:\" + newTreeNode); /* * val newTreeNode = treeNode.copy { * ... * } * * is actually shorthand for * * val newTreeNode = TreeNode(treeNode) { * ... * } */ val newTreeNode = treeNode.copy { childNodes()[0] // Food .childNodes()[0] // Drinks .childNodes()[0] // Cocacola .name += \" plus\" } // Show that `newTreeNode` reflects the developer's desired modifications // Note that this does not affect the existing `treeNode` at all println(\"treeNode: $treeNode\") println(\"newTreeNode: $newTreeNode\") Output (the actual printed output is compact, but is formatted here for readability) treeNode: { \"name\":\"Root\", \"childNodes\":[ { \"name\":\"Food\", \"childNodes\":[ { \"name\":\"Drink\", \"childNodes\":[ {\"name\":\"Coco Cola\"}, {\"name\":\"Fanta\"} ] } ] } ] } newTreeNode: { \"name\":\"Root\", \"childNodes\":[ { \"name\":\"Food\", \"childNodes\":[ { \"name\":\"Drink\", \"childNodes\":[ {\"name\":\"Coco Cola plus\"}, {\"name\":\"Fanta\"} ] } ] } ] } As you can see, treeNode is unaffected, and newTreeNode reflects the user's desired modifications. This transplant is a powerful complement to the JVM ecosystem. This framework is named Jimmer, paying tribute to immer. info The sample code above uses a type called TreeNodeDraft, which is the interface type automatically generated by Jimmer based on the user-defined type TreeNode. Readers can ignore this auto-generated interface for now, later documentation Draft will introduce it.","s":"3. Create new data based on existing data","u":"/jimmer-doc/docs/object/immutable/solution","h":"#3-create-new-data-based-on-existing-data","p":951},{"i":960,"t":"In previous documents we have seen that When the user defines the Book type, the example code can use the BookDraft type When the user defines the TreeNode type, the example code can use the TreeNodeDraft type These types ending in Draft that correspond one-to-one with user-defined types are called Draft types.","s":"Draft","u":"/jimmer-doc/docs/object/draft","h":"","p":959},{"i":963,"t":"The user first defines an immutable data interface. Here, the ORM entity annotation @Entity is not needed, the non-ORM annotation @Immutable can achieve the demo purpose. Java Kotlin TreeNode.java package yourpackage; import javax.validation.constraints.Null; import java.util.List; import org.babyfish.jimmer.Immutable; @Immutable public interface TreeNode { String name(); @Null TreeNode parent(); List childNodes(); } TreeNode.kt package yourpackage import org.babyfish.jimmer.Immutable @Immutable interface TreeNode { val name: String val parent: TreeNode? val childNodes: List }","s":"Define TreeNode","u":"/jimmer-doc/docs/object/draft","h":"#define-treenode","p":959},{"i":965,"t":"To automatically generate TreeNodeDraft, the preprocessor needs to be enabled: Java: Use AnnotationProcessor jimmer-apt Kotlin: Use KSP jimmer-ksp info How to use jimmer-apt/jimmer-ksp and how to handle possible issues are introduced in great detail in Generate Code. This article will not repeat it. Java Kotlin TreeNodeDraft.java package org.babyfish.jimmer.example.core.model; import java.util.List; import org.babyfish.jimmer.DraftConsumer; import org.babyfish.jimmer.lang.OldChain; public interface TreeNodeDraft extends TreeNode, Draft { TreeNodeDraft.Producer $ = Producer.INSTANCE; @OldChain TreeNodeDraft setName(String name); TreeNodeDraft parent(); TreeNodeDraft parent(boolean autoCreate); @OldChain TreeNodeDraft setParent(TreeNode parent); @OldChain TreeNodeDraft applyParent(DraftConsumer block); @OldChain TreeNodeDraft applyParent(TreeNode base, DraftConsumer block); List childNodes(boolean autoCreate); @OldChain TreeNodeDraft setChildNodes(List childNodes); @OldChain TreeNodeDraft addIntoChildNodes(DraftConsumer block); @OldChain TreeNodeDraft addIntoChildNodes(TreeNode base, DraftConsumer block); class Producer { private Producer() {} public TreeNode produce( DraftConsumer block ) { return produce(null, block); } public TreeNode produce( TreeNode base, DraftConsumer block ) { ...omit... } ...other code omitted... } ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { public override var name: String public override var parent: TreeNode? public override var childNodes: List public fun parent(): TreeNodeDraft public fun childNodes(): MutableList public object `$` { ...other code omitted... public fun produce( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): TreeNode { ...omit code... } } ...other code omitted... } public fun ImmutableCreator.`by`( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): TreeNode = TreeNodeDraft.`$`.produce(base, block) public fun MutableList.addBy( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): MutableList { add(TreeNodeDraft.`$`.produce(base, block) as TreeNodeDraft) return this } public fun TreeNode.copy(block: TreeNodeDraft.() -> Unit): TreeNode = TreeNodeDraft.`$`.produce(this, block) You can use it like this: Create a brand new object from scratch Java Kotlin TreeNode oldTreeNode = Immutables.createTreeNode(treeNodeDraft -> { ...omitted... }); val oldTreeNode = TreeNode { ...omitted... } Based on an existing object, make some \"changes\" and create a new object Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(oldTreeNode, treeNodeDraft -> { ...omitted... }); val newTreeNode = TreeNode(oldTreeNode) { ...omitted... } or val newTreeNode = oldTreeNode.copy { ...省略... }","s":"Generate TreeNodeDraft","u":"/jimmer-doc/docs/object/draft","h":"#generate-treenodedraft","p":959},{"i":967,"t":"TreeNode.name is a scalar property. TreeNodeDraft will define a setter method/writable property like below: Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft setName(String name); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { // var, not val public override var name: String ...other code omitted... } Developers can use this method to set the name property of the draft proxy: Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft.setName(\"Root Node\"); }); val treeNode = TreeNode { name = \"Root Node\" }","s":"Scalar properties","u":"/jimmer-doc/docs/object/draft","h":"#scalar-properties","p":959},{"i":969,"t":"TreeNode.parent is an association property. Its type is an object, not a collection. In ORM terms, it is a one-to-one or many-to-one association. TreeNodeDraft defines multiple methods for it:","s":"Reference associations","u":"/jimmer-doc/docs/object/draft","h":"#reference-associations","p":959},{"i":971,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { TreeNodeDraft parent(); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { public fun parent(): TreeNodeDraft ...other code omitted... } info Note that the return type of this method is TreeNodeDraft rather than TreeNode. That is, if the reference association of the draft object has been set and set to non-null, this method will definitely return the draft object. This allows the user to directly modify deeper associated objects. Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(treeNode, draft -> { draft.parent().setName(\"Daddy\"); draft.parent().parent().setName(\"Grandpa\"); }); @DslScope var newTreeNode = TreeNode(treeNode) { parent().name = \"Daddy\" parent().parent().name = \"Grandpa\" }","s":"Override getter parent()","u":"/jimmer-doc/docs/object/draft","h":"#override-getter-parent","p":959},{"i":973,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { TreeNode parent(boolean autoCreate); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode { // This getter is equivalent to Java's `parent(false)` override fun parent: TreeNode // This function is equivalent to Java's `parent(true)` public fun parent(): TreeNodeDraft ...other code omitted... } Java's parent(false) and Kotlin's parent have two issues: Accessing it will cause an exception if the parent property of the draft object is not set If the parent property of the draft object is set to null, accessing it will return null, and null does not support further modification parent(true) can resolve the above issues. If either of the above situations is met, it will automatically create and set an associated object, then allow the user to modify it. This is a very useful feature, especially when creating objects from scratch. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(/* No `base` here */ draft -> { draft.parent(true).setName(\"Daddy\"); draft.parent(true).parent(true).setName(\"Grandpa\"); }); val treeNode = TreeNode /* No `base` here */ { parent().setName(\"Daddy\"); parent().parent().setName(\"Grandpa\"); }","s":"Add getter parent(boolean)","u":"/jimmer-doc/docs/object/draft","h":"#add-getter-parentboolean","p":959},{"i":975,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft setParent(TreeNode parent); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode, Draft { // var, not val public var parent: TreeNode ...other code omitted... } This setter allows the user to replace the entire associated object. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft.setParent( Immutables.createTreeNode(daddyDraft -> { daddyDraft.setName(\"Daddy\") }) ) }); val treeNode = TreeNode { parent = TreeNode { name = \"Daddy\" } }","s":"Add setParent","u":"/jimmer-doc/docs/object/draft","h":"#add-setparent","p":959},{"i":977,"t":"info This feature only applies to Java. Kotlin code is already concise enough and does not need this method to simplify the code. TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft applyParent( DraftConsumer block ); @OldChain TreeNodeDraft applyParent( TreeNode base, DraftConsumer block ); ...other code omitted... } These two setters are used to simplify the code. Since the two methods are highly similar in usage, only the first one is used as an example: More verbose writing: TreeNode oldTreeNode = Immutables.createTreeNode(draft -> { draft.setParent( Immutables.createTreeNode(daddyDraft -> { daddyDraft.setName(\"Daddy\") }) ) }); More concise writing: TreeNode oldTreeNode = Immutables.createTreeNode(draft -> { draft.applyParent(daddyDraft -> { daddyDraft.setName(\"Daddy\") }) }); The two are completely equivalent.","s":"Add lambda-based applyParent","u":"/jimmer-doc/docs/object/draft","h":"#add-lambda-based-applyparent","p":959},{"i":979,"t":"TreeNode.childNodes is an association property whose type is a collection rather than an object. In ORM terms, it is a one-to-many or many-to-many association. TreeNodeDraft defines multiple methods for it:","s":"Collection associations","u":"/jimmer-doc/docs/object/draft","h":"#collection-associations","p":959},{"i":981,"t":"For both Java and Kotlin, TreeNodeDraft cannot override the return type of childNodes() method. From a syntactic point of view, it can only inherit the childNodes() method of TreeNode. Java Kotlin List childNodes(); var childNodes: List caution Although the return type defined in the TreeNode interface is List, after being inherited by the TreeNodeDraft interface, its return type should be understood as List. info If the collection association of the draft object has been set, all elements in the returned collection are drafts. This allows the user to directly modify deeper associated objects in the collection. Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(treeNode, draft -> { ((TreeNodeDraft) draft .childNodes().get(0) ).setName(\"Son\"); ((TreeNodeDraft) draft .childNodes().get(0) .childNodes().get(0) ).setName(\"Grandson\"); }); val newTreeNode = TreeNode(treeNode) { (childNodes[0] as TreeNodeDraft) .name = \"Son\" (childNodes[0].childNodes[0] as TreeNodeDraft) .name = \"Son\" } danger The two forced type conversions in the above code significantly impair the developer experience. Therefore, this usage is not recommended in actual projects. To achieve the same purpose, the childNodes(boolean) method introduced below is more recommended.","s":"Inherit getter childNodes()","u":"/jimmer-doc/docs/object/draft","h":"#inherit-getter-childnodes","p":959},{"i":983,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { List childNodes(boolean autoCreate); ...other code omitted... } childNodes(false) is equivalent to childNodes(), and accessing it will cause an exception if the childNodes property of the draft object is not set. childNodes(true) will resolve this problem by automatically creating and setting a collection if the collection association property has not yet been set, then allowing the user to modify that collection. TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode, Draft { override var childNodes: List fun childNodes(): MutableList ...other code omitted... } The getter of the childNodes property is equivalent to Java's childNodes(false). Accessing it will cause an exception if this mutable proxy property is not set. The childNodes() function is equivalent to Java's childNodes(true). It automatically creates the property if not set, allowing the user to modify the collection. Java Kotlin TreeNode newTreeNode = Immutables.createTreeNode(treeNode, draft -> { draft .childNodes(false) .get(0) .setName(\"Son\"); draft .childNodes(false) .get(0) .childNodes(false) .get(0) .setName(\"Grandson\"); }); tip Indeed, when the parameter is true, childNodes(boolean) can automatically create the collection when the childNodes property is not specified. However, when the parameter is false, it is also very useful. Because the return type of this method is List instead of List, the developer-unfriendly code in the previous example will no longer exist. val newTreeNode = TreeNode(treeNode) { childNodes()[0].name = \"Son\" childNodes()[0].childNodes()[0].name = \"Grandson\" }","s":"Add getter childNodes(boolean)","u":"/jimmer-doc/docs/object/draft","h":"#add-getter-childnodesboolean","p":959},{"i":985,"t":"Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft setChildNodes(List childNodes); ...other code omitted... } TreeNodeDraft.kt @DslScope public interface TreeNodeDraft : TreeNode, Draft { // var, not val override var childNodes: List ...other code omitted... } This setter allows the user to replace the entire associated collection. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft.setChildNodes( Arrays.asList( Immutables.createTreeNode(childDraft -> { childDraft.setName(\"Eldest son\") }), Immutables.createTreeNode(childDraft -> { childDraft.setName(\"Second son\") }) ) ) }); val treeNode = TreeNode { childNodes = listOf( TreeNode { name = \"Eldest son\" }, TreeNode { name = \"Second son\" } ) } info Somewhat cumbersome, the addIntoChildNodes to be introduced below is more recommended.","s":"Add setChildNodes","u":"/jimmer-doc/docs/object/draft","h":"#add-setchildnodes","p":959},{"i":987,"t":"In the example above, we used setChildNodes to replace the entire collection, but we can also choose to add collection elements one by one, rather than replacing the entire collection at one time. The generated code is: Java Kotlin TreeNodeDraft.java public interface TreeNodeDraft extends TreeNode, Draft { @OldChain TreeNodeDraft addIntoChildNodes( DraftConsumer block ); @OldChain TreeNodeDraft addIntoChildNodes( TreeNode base, DraftConsumer block ); ...other code omitted... } TreeNodeDraft.java @DslScope public interface TreeNodeDraft : TreeNode, Draft { public fun childNodes(): MutableList ...other code omitted... } public fun MutableList.addBy( base: TreeNode? = null, block: TreeNodeDraft.() -> Unit ): MutableList { ...omit... return this; } You should use it like this: Java Kotlin TreeNode treeNode = Immutables.createTreeNode(draft -> { draft .addIntoChildNodes(childDraft -> childDraft.setName(\"Eldest son\") ) .addIntoChildNodes(childDraft -> childDraft.setName(\"Second son\") ) }); val treeNode = TreeNode { childNodes().addBy { name = \"Eldest son\" } childNodes().addBy { name = \"Second son\" } } info This approach implicitly contains a feature that the childNodes property of the draft object is not set and the collection is automatically created, i.e. it contains a built-in childNodes(true). Obviously, this approach is simpler than using the setter to replace the entire collection, so it is more recommended.","s":"Add addIntoChildNodes","u":"/jimmer-doc/docs/object/draft","h":"#add-addintochildnodes","p":959},{"i":989,"t":"In this series of articles, we will introduce: Jimmer's positioning and existing pain points The revolutionary nature of Jimmer The examples that come with the project How to create a Jimmer project from scratch Jimmer's performance advantages","s":"Introduction ★","u":"/jimmer-doc/docs/overview/","h":"","p":988},{"i":991,"t":"Not only can Jimmer bring you powerful features, but it can also bring you ultimate performance. The source code for benchmarking is here, using H2 in-memory database, no environment preparation needed to run directly.","s":"Benchmark Report","u":"/jimmer-doc/docs/overview/benchmark","h":"","p":990},{"i":994,"t":"The x-axis indicates the number of data objects queried from the database each time. The y-axis indicates the number of operations per second. Chart Data Show native JDBC metrics Framework Data count Ops/s JDBC(ColIndex) 10 662071 JDBC(ColName) 10 345169 Jimmer(Java) 10 315312 Jimmer(Kotlin) 10 309029 EasyQuery 10 206634 MyBatis 10 68743 Exposed 10 92494 JPA(Hibernate) 10 90542 JPA(EclipseLink) 10 64230 JOOQ 10 69408 Nutz 10 76904 ObjectiveSQL 10 56245 Spring Data JDBC 10 20494 Ktorm 10 19152 JDBC(ColIndex) 20 453226 JDBC(ColName) 20 238107 Jimmer(Java) 20 224179 Jimmer(Kotlin) 20 230622 EasyQuery 20 135063 MyBatis 20 43940 Exposed 20 66934 JPA(Hibernate) 20 59926 JPA(EclipseLink) 20 33421 JOOQ 20 39737 Nutz 20 39501 ObjectiveSQL 20 29975 Spring Data JDBC 20 10704 Ktorm 20 9520 JDBC(ColIndex) 50 259484 JDBC(ColName) 50 125589 Jimmer(Java) 50 132673 Jimmer(Kotlin) 50 128315 EasyQuery 50 92230 MyBatis 50 20050 Exposed 50 26693 JPA(Hibernate) 50 25893 JPA(EclipseLink) 50 13634 JOOQ 50 18373 Nutz 50 16639 ObjectiveSQL 50 12455 Spring Data JDBC 50 4146 Ktorm 50 4385 JDBC(ColIndex) 100 130991 JDBC(ColName) 100 72424 Jimmer(Java) 100 77044 Jimmer(Kotlin) 100 74499 EasyQuery 100 45502 MyBatis 100 10541 Exposed 100 19483 JPA(Hibernate) 100 13096 JPA(EclipseLink) 100 6802 JOOQ 100 8145 Nutz 100 8903 ObjectiveSQL 100 6251 Spring Data JDBC 100 2229 Ktorm 100 2091 JDBC(ColIndex) 200 77725 JDBC(ColName) 200 33068 Jimmer(Java) 200 41474 Jimmer(Kotlin) 200 36656 EasyQuery 200 28085 MyBatis 200 5310 Exposed 200 10008 JPA(Hibernate) 200 6900 JPA(EclipseLink) 200 3238 JOOQ 200 4186 Nutz 200 4374 ObjectiveSQL 200 3470 Spring Data JDBC 200 1025 Ktorm 200 1063 JDBC(ColIndex) 500 32109 JDBC(ColName) 500 16234 Jimmer(Java) 500 16371 Jimmer(Kotlin) 500 16870 EasyQuery 500 11666 MyBatis 500 2137 Exposed 500 3894 JPA(Hibernate) 500 2491 JPA(EclipseLink) 500 1361 JOOQ 500 1707 Nutz 500 2040 ObjectiveSQL 500 1259 Spring Data JDBC 500 447 Ktorm 500 427 JDBC(ColIndex) 1000 16188 JDBC(ColName) 1000 8346 Jimmer(Java) 1000 8831 Jimmer(Kotlin) 1000 7932 EasyQuery 1000 4427 MyBatis 1000 1048 Exposed 1000 2082 JPA(Hibernate) 1000 1207 JPA(EclipseLink) 1000 650 JOOQ 1000 832 Nutz 1000 957 ObjectiveSQL 1000 559 Spring Data JDBC 1000 197 Ktorm 1000 168","s":"Operations Per Second","u":"/jimmer-doc/docs/overview/benchmark","h":"#operations-per-second","p":990},{"i":996,"t":"The x-axis indicates the number of data objects queried from the database each time. The y-axis indicates the operation time (microseconds) for each operation. Chart Data Framework Data count Time(μs) JDBC(ColIndex) 10 2 JDBC(ColName) 10 3 Jimmer(Java) 10 3 Jimmer(Kotlin) 10 3 EasyQuery 10 5 MyBatis 10 15 Exposed 10 11 JPA(Hibernate) 10 11 JPA(EclipseLink) 10 16 JOOQ 10 14 Nutz 10 13 ObjectiveSQL 10 18 Spring Data JDBC 10 49 Ktorm 10 52 JDBC(ColIndex) 20 2 JDBC(ColName) 20 4 Jimmer(Java) 20 4 Jimmer(Kotlin) 20 4 EasyQuery 20 7 MyBatis 20 23 Exposed 20 15 JPA(Hibernate) 20 17 JPA(EclipseLink) 20 30 JOOQ 20 25 Nutz 20 25 ObjectiveSQL 20 33 Spring Data JDBC 20 93 Ktorm 20 105 JDBC(ColIndex) 50 4 JDBC(ColName) 50 8 Jimmer(Java) 50 8 Jimmer(Kotlin) 50 8 EasyQuery 50 11 MyBatis 50 50 Exposed 50 37 JPA(Hibernate) 50 39 JPA(EclipseLink) 50 73 JOOQ 50 54 Nutz 50 60 ObjectiveSQL 50 80 Spring Data JDBC 50 241 Ktorm 50 228 JDBC(ColIndex) 100 8 JDBC(ColName) 100 14 Jimmer(Java) 100 13 Jimmer(Kotlin) 100 13 EasyQuery 100 22 MyBatis 100 95 Exposed 100 51 JPA(Hibernate) 100 76 JPA(EclipseLink) 100 147 JOOQ 100 123 Nutz 100 112 ObjectiveSQL 100 160 Spring Data JDBC 100 449 Ktorm 100 478 JDBC(ColIndex) 200 13 JDBC(ColName) 200 30 Jimmer(Java) 200 24 Jimmer(Kotlin) 200 27 EasyQuery 200 36 MyBatis 200 188 Exposed 200 100 JPA(Hibernate) 200 145 JPA(EclipseLink) 200 309 JOOQ 200 239 Nutz 200 229 ObjectiveSQL 200 288 Spring Data JDBC 200 976 Ktorm 200 941 JDBC(ColIndex) 500 31 JDBC(ColName) 500 62 Jimmer(Java) 500 61 Jimmer(Kotlin) 500 59 EasyQuery 500 86 MyBatis 500 468 Exposed 500 257 JPA(Hibernate) 500 401 JPA(EclipseLink) 500 735 JOOQ 500 586 Nutz 500 490 ObjectiveSQL 500 794 Spring Data JDBC 500 2237 Ktorm 500 2342 JDBC(ColIndex) 1000 62 JDBC(ColName) 1000 120 Jimmer(Java) 1000 113 Jimmer(Kotlin) 1000 126 EasyQuery 1000 226 MyBatis 1000 954 Exposed 1000 480 JPA(Hibernate) 1000 829 JPA(EclipseLink) 1000 1538 JOOQ 1000 1202 Nutz 1000 1045 ObjectiveSQL 1000 1789 Spring Data JDBC 1000 5076 Ktorm 1000 5952 note Since Spring removed support for OpenJPA, this benchmark test does not include JPA(OpenJPA).","s":"Operation Time","u":"/jimmer-doc/docs/overview/benchmark","h":"#operation-time","p":990},{"i":998,"t":"Disable cache for all frameworks Turn off logs for all frameworks For all frameworks, open and close connections/sessions each time, no sharing; rely on connection pools to ensure performance. Use Spring's connection management mechanism. The implementation is slightly different due to the different APIs of different frameworks. Some use DataSourceUtils's getConnection and releaseConnection Some use TransactionAwareDataSourceProxy But the end result is the same Do not use transactions Exposed is special in that its API can only work with transactions, so there is a fake transaction implementation for it. Use embedded H2 database to compress database overhead as much as possible, highlighting the performance of the ORM itself, i.e. the performance of mapping.","s":"Implementation Principles","u":"/jimmer-doc/docs/overview/benchmark","h":"#implementation-principles","p":990},{"i":1000,"t":"A common view: the performance of the ORM itself is not important. In actual projects, the database is not an in-memory database, so the time consumed by the ORM itself is negligible compared to the time consumed by the database. Rebuttal: After the release of Java 19, virtual threads are supported. The faster the ORM completes the mapping, the more virtual threads the JVM can schedule, which can increase system throughput.","s":"Value","u":"/jimmer-doc/docs/overview/benchmark","h":"#value","p":990},{"i":1002,"t":"There are two programming styles in JDBC for reading values from java.sql.ResultSet JDBC(ColIndex), i.e. reading by column index, rs.getString(1) JDBC(ColName), reading by column name: rs.getString(\"VALUE_1\") JDBC(ColIndex) is faster than JDBC(ColName), so Jimmer itself also uses JDBC(ColIndex) as the underlying means of accessing ResultSet, providing the possibility of exceeding the performance metrics of JDBC(ColName). Now let's focus on discussing the two cases in the charts (select native JDBC metrics): Querying 10 rows of data each time, the OPS of JDBC(ColName) and Jimmer(Java) are close. In this scenario, the performance of Jimmer and JDBC(ColName) is similar. The test code of JDBC(ColName) directly hardcodes the SQL, while Jimmer needs to dynamically construct the SQL using the DSL mechanism, from which perspective Jimmer should be slower. However, the process of Jimmer converting ResultSet to objects is faster than JDBC(ColName), canceling each other out. So the performance is similar. Of course, the SQL statement used in Benchmark is not complex. If more complex SQL is used, the hardcoded SQL JDBC(ColName) will be faster, which is also an area Jimmer can optimize in subsequent versions. Querying 1000 rows of data each time, Jimmer's ops are significantly higher than JDBC(ColName)'s OPS. In this case, the performance advantage of Jimmer converting ResultSet to objects is fully demonstrated. Even if Jimmer slowed down due to dynamically generating SQL using DSL, the overall result is still faster than JDBC(ColName). The main reasons why Jimmer converts ResultSet to objects so fast are: Use JDBC(ColIndex) at the bottom layer Do not use Java reflection to dynamically set properties for objects. At compile time, Jimmer generates a modifiable DraftImpl class for each immutable entity type, which provides a generic __set(PropId propId, Object value) method to achieve dynamic setting of object properties similar to Java reflection. At the same time, the compiler assigns each property an integer as id. The __set method in the DraftImpl class uses a switch statement internally to identify the passed property id. For example, the generated Java code is: @Override public void __set(PropId prop, Object value) { int __propIndex = prop.asIndex(); switch (__propIndex) { case -1: __set(prop.asName(), value); return; case 0: setId((Long)value); break; case 1: setName((String)value); break; case 2: setEdition((Integer)value); break; ...Omitted... } } Modern compilers have sufficient optimization for such integer-based switch statements, so it can be considered that Jimmer's dynamic assignment of entity objects is not much slower than the hardcoded JDBC test code. These two reasons are the most important reasons why Jimmer's object mapping performance is so high.","s":"Why so fast?","u":"/jimmer-doc/docs/overview/benchmark","h":"#why-so-fast","p":990},{"i":1005,"t":"Jimmer heavily relies on the precompilation technology in the JVM ecosystem: For Java, it's APT, i.e., Annotation Processor Tool For Kotlin, it's KSP, i.e., Kotlin Symbol Processing info Some code generated by APT/KSP is necessary for using Jimmer. Therefore, if you open any Java/Kotlin project from the official examples in IntelliJ, you will find that some code that should have been automatically generated is missing. For this, you can choose any of the following methods: First, execute the ./mvnw install (for Java examples only) or ./gradlew build command in the directory of the project you want to open from the command line to complete the code generation, then open the project with IntelliJ. Open the project directly with IntelliJ, ignore the IDE errors temporarily, and after the dependencies are downloaded, run the project's main method or unit test (save-command/save-command-kt demonstrates features using unit tests). All IDE errors will automatically disappear, and the application will start correctly.","s":"Basic Concepts","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#basic-concepts","p":1003},{"i":1007,"t":"Java (Maven) Java (Gradle) Kotlin (Gradle.kts) Java (Gradle Plugin) Kotlin (Gradle Plugin) pom.xml ...other code omitted... org.apache.maven.plugins maven-compiler-plugin 3.10.1 org.babyfish.jimmer jimmer-apt ${jimmer.version} ...other code omitted... dependencies { ...other dependencies omitted... annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" } plugins { // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10-1.0.6\" ...other plugins omitted... } dependencies { // Apply Jimmer's KSP code generator ksp(\"org.babyfish.jimmer:jimmer-ksp:${jimmerVersion}\") ...other dependencies omitted... } // Add generated code to compile path. // Gradle build works without this, but IntelliJ won't find generated code. kotlin { sourceSets.main { kotlin.srcDir(\"build/generated/ksp/main/kotlin\") } } build.gradle plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } build.gradle.kts plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10+\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } info The first three: Standard configurations The last two: Community-provided Gradle plugin for further simplifying configurations note KSP only supports gradle, It has been proven that KSP's third-party Maven plug-in support cannot keep up with the version iteration of 'kotlin/KSP' itself, and often encounters many problems during the upgrade process. Eventually, Jimmer dropped Maven support for Kotlin and asked Kotlin developers to use Gradle. For all projects in the official examples: All Java examples have both pom.xml and build.gradle, i.e., they support both Maven and Gradle. When opening these projects for the first time, IntelliJ will ask you how you want to open them, and you can make your choice. If you want to switch the opening method, exit IntelliJ, delete the hidden directory .idea in the project, and then open the project with IntelliJ again and reselect the method. All Kotlin examples only have the build.gradle.kts file, i.e., they only support Gradle. The reason has been explained earlier. IntelliJ has some rash over-optimization measures for integrating annotation processors introduced via Maven, resulting in a better development experience when using Gradle with the IDE than with Maven.","s":"How to Use","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#how-to-use","p":1003},{"i":1009,"t":"Business projects are rarely a single project, but more often split into multiple subprojects using build tools like Maven and Gradle. So, in which subprojects should we use the configurations mentioned earlier? Subproject Type Usage Notes Projects defining entities Generate necessary code based on entity definitions, such as Draft, SQL DSL, Fetcher Projects defining DTO files under src/main/dto Generate DTO classes based on the DTO language code For Java, unless the current subproject has entity definitions, you need to find any class and annotate it with @EnableDtoGeneration Projects using Spring Web annotations Automatically generate OpenAPI documentation and TypeScript code, writing Java/Kotlin documentation comments into the documentation and client code; support for remote exceptions","s":"Where to Use","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#where-to-use","p":1003},{"i":1011,"t":"Since Jimmer is a compile-time framework, and considering that not all users are familiar with apt and ksp, it's necessary to mention an important detail. Apt/Ksp are standard technologies in the industry, and Java IDEs provide support for them. In most cases, your modifications will include changes to Java or Kotlin code, such as changes in entity types or Web Controller*(Jimmer has its own implementations for OpenAPI and TypeScript generation)*. In this case, you only need to click the IDE's Run or Debug button once, without requiring a full compilation, to trigger all pre-compilation behaviors, the automatically generated source code and resource files will update automatically. In rare cases, if you only modify DTO files, meaning there are no Java or Kotlin source code changes within the same project except for the DTO files, you have three options: Use the companion DTO plugin Perform a full compilation using maven or gradle commands, or the IDE's Rebuild button, which can achieve this purpose Delete the affected project's compilation output directory, then click the IDE's Run or Debug button`","s":"Notes","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#notes","p":1003},{"i":1013,"t":"Unlike the Kotlin API, the Java API cannot avoid to directly use automatically generate types in user code. Let's compare the following: Feature Java Kotlin Draft Use the generated type BookDraft Use the original entity type Book Book book = BookDraft.$.produce(b -> { b.setName(\"SQL\"); b.addIntoAuthors(a -> { a.setName(\"Jessica\"); }); b.addIntoAuthors(a -> { a.setName(\"Bob\"); }); }); val book = Book { name = \"SQL in Action\" authors().addBy { name = \"Jessica\" } authors().addBy { name = \"Bob\" } } SQL DSL Use the generated type BookTable Use the original entity type Book BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.storeId().isNull()) .orderBy(table.name()) .select(table) .execute(); List books = sqlClient .createQuery(Book::class) { where(table.storeId.isNull()) orderBy(table.name) select(table) } .execute() Fetcher Use the generated types BookFetcher, BookStoreFetcher, and AuthorFetcher Use the original entity type Book Fetcher fetcher = BookFetcher.$ .allScalarFields() .store( BookStoreFetcher.$ .allScalarFields() ) .authors( AuthorFetcher.$ .allScalarFields() ) val fetcher = newFetcher(Book::class).by { allScalarFields() store { allScalarFields() } authors { allScalarFields() } } As you can see, the abstraction capabilities of Java and Kotlin are different, resulting in different effects that the API design can achieve: For Kotlin, regardless of the scenario, you only need to use the original entity type Book. For Java, you have to use the types automatically generated by the Annotation Processor, such as BookDraft, BookTable, BookFetcher, etc. In the above Java code, .$ appears frequently, $ are static read-only fields of these classes. Actually, using $ is the simplest way. However, considering that some Java developers have subjective biases against $, for Java subprojects defining entity types, Jimmer's APT also generate four summary types: Objects class Tables interface TableExes interface Fetchers interface The package where these four types reside is the common package for all entities. These four types provide another coding style for Java code by defining static constants, and the two styles are compared as follows: Style Accepting $ Style Not Accepting $ BookDraft.$.produce Immutables.createBook BookTable.$ Tables.BOOK_TABLE BookTableEx.$ TableExes.BOOK_TABLE_EX BookFetcher.$ Fetchers.BOOK_FETCHER Additionally, Tables, TableExes, and Fetchers are interfaces, and you can use the implements statement to further simplify the code (since IntelliJ does not support static imports well, implementing interfaces that define constants is still a recommended technique). For example: public interface FetcherConstants implements Fetchers { Fetcher BOOK_DETAIL_FETCHER = BOOK_FETCHER .allScalarFields() .store( BOOK_STORE_FETCHER .allScalarFields() ) .authors { AUTHOR_FETCHER .allScalarFields() }; }","s":"Two Styles of Java Code","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#two-styles-of-java-code","p":1003},{"i":1015,"t":"Java projects often use Lombok. By default, if the project does not have any APT other than Lombok, you only need to import the Lombok dependency. However, once you introduce other APT configurations (not necessarily Jimmer's APT, but any other APT), you must explicitly configure Lombok's APT. Java(Maven) Java(Gradle) Java(Gradle Plugin) pom.xml ...omitted other code... org.apache.maven.plugins maven-compiler-plugin 3.10.1 org.projectlombok lombok ${lombok.version} org.babyfish.jimmer jimmer-apt ${jimmer.version} ...omitted other code... build.gradle dependencies { ...omitted other dependencies... annotationProcessor \"org.projectlombok:lombok:${lombokVersion}\" annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" } build.gradle plugins { id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...省略其它插件... } jimmer { version = ... } dependencies { ...omitted other dependencies... annotationProcessor \"org.projectlombok:lombok:${lombokVersion}\" }","s":"Integration with Lombok","u":"/jimmer-doc/docs/overview/apt-ksp","h":"#integration-with-lombok","p":1003},{"i":1017,"t":"Previous documents have discussed in detail the dynamic and immutable properties of Jimmer entities. This introduces a new feature: visibility.","s":"Visibility","u":"/jimmer-doc/docs/object/visibility","h":"","p":1016},{"i":1019,"t":"For Jimmer entities, although properties are mostly independent, in some cases multiple properties share private data and thus affect each other. We call this entanglement between properties. These cases include: Java/Kotlin-based calculated properties (review details) Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { String firstName(); String lastName(); @Formula(dependencies = {\"firstName\", \"lastName\"}) default String fullName() { return firstName() + ' ' + lastName(); } ...Omit other properties... } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { val firstName: String val lastName: String @Formula(dependencies = [\"firstName\", \"lastName\"]) val fullName: String get() = \"$firstName $lastName\" ...Omit other properties... } Author.fullName has no private data, it depends on Author.firstName and Author.lastName. Although Author.fullName is defined as a calculated property, it can also be considered a view property from another perspective. If treating Author.firstName and Author.lastName as original properties, then Author.fullName can be considered a view property based on them. @IdView view properties (review details) Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface Book { ...Omit other properties... @ManyToOne @Nullable BookStore store(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) List authors(); @IdView // View of associated object store's id Long storeId(); // View of ids of all objects in associated collection authors @IdView(\"authors\") List authorIds(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Book { ...Omit other properties... @ManyToOne val store: BookStore? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) val authors: List @IdView // View of associated object store's id val storeId: Long? // View of ids of all objects in associated collection authors @IdView(\"authors\") val authorIds: List } Book.store is the original property, Book.storeId is the view property based on it Book.authors is the original property, Book.authorIds is the view property based on it @ManyToManyView view properties (review details) Java Kotlin Student.java @Entity public interface Student { // In step 1, already declared one-to-many association `learningLinks` @OneToMany(mappedBy = \"student\") List learningLinks(); @ManyToManyView( prop = \"learningLinks\", deeperProp = \"course\" ) List courses(); ...Omit other code... } Student.kt @Entity interface Student { @OneToMany(mappedBy = \"student\") val learningLinks: List @ManyToManyView( prop = \"learningLinks\", deeperProp = \"course\" ) val courses: List ...Omit other code... } Student.learningLinks is the original property, Student.courses is the view property based on it. The commonality in the examples above is that there are original properties and view properties. The original properties have their own private data, while the view properties have none. The view properties just observe the values of the original properties from a different perspective. From an internal implementation perspective, a view property actually shares private data with the original property. This means knowing one value necessarily reveals partial information about the other's value. Hence they can be metaphorically described as entangled properties.","s":"Entangled Properties","u":"/jimmer-doc/docs/object/visibility","h":"#entangled-properties","p":1016},{"i":1021,"t":"We introduced entangled properties, with original properties and view properties. The real data is held by the original properties, while the view properties only observe. When using an object fetcher to fetch a view property, the internal logic will translate it into fetching the original property, for example: Fetching Author.fullName is translated internally into fetching Author.firstName and Author.lastName Fetching Book.storeId is translated internally into fetching Book.store Fetching Book.authorIds is translated internally into fetching Book.authors Fetching Student.courses is translated internally into fetching Student.learningLinks Let's take Book.authorIds and Book.authors to demonstrate how object fetchers handle original properties and view properties differently: Fetch the original property Java Kotlin Book book = sqlClient.findById( Fetchers.BOOK_FETCHER .allScalarFields() .authors(), // Associated objects with only id 1L ); System.out.println(book); val book = sqlClient.findById( newFetcher(Book::class).by { allScalarFields() authors() // Associated objects with only id }, 1L ) println(book) The authors() in the fetcher has no arguments, indicating it fetches a collection of author objects with only id properties. The result is (manually formatted for readability): { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] } Fetch the view property Java Kotlin Book book = sqlClient.findById( Fetchers.BOOK_FETCHER .allScalarFields() .authorIds(), // Associated ids, not objects 1L ); System.out.println(book); val book = sqlClient.findById( newFetcher(Book::class).by { allScalarFields() authorIds() // Associated ids, not objects }, 1L ) println(book) This time the result is (manually formatted for readability): { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authorIds\":[ 2, 1 ] } Although the returned data is equivalent, the formats are completely different. We said earlier that when an object fetcher fetches a view property, it translates internally into fetching the original property. Since this is the case, the underlying logic should be exactly the same. Where does this difference come from?","s":"Object Fetchers and Entangled Properties","u":"/jimmer-doc/docs/object/visibility","h":"#object-fetchers-and-entangled-properties","p":1016},{"i":1023,"t":"The question above is, with identical underlying logic, why do two queries with the same logic return data in different formats? Jimmer can control the visibility of each property, making it shown or hidden. Unlike dynamic where a property can be loaded or unloaded, visibility is an orthogonal feature, completely unrelated to dynamism. Visibility only affects Jackson serialization of objects (including their own toString behavior), deciding whether a property is serialized. Other than that, it does not impact any other behavior of the object. So the previous examples can be easily explained: First query: Book.authors is shown, Book.authorIds is hidden Second query: Book.authors is hidden, Book.authorIds is shown tip Only when both conditions below are met will a property participate in Jackson serialization Dynamism: the property is set Visibility: the property is shown See tool methods for how to control visibility of Jimmer object properties yourself","s":"Property Visibility","u":"/jimmer-doc/docs/object/visibility","h":"#property-visibility","p":1016},{"i":1025,"t":"To help readers better understand the key features, let's first introduce Jimmer's fundamental design philosophy","s":"Key Features ✦","u":"/jimmer-doc/docs/overview/key-features","h":"","p":1024},{"i":1027,"t":"The core concept of Jimmer is to read and write data structures of arbitrary shapes as a whole, rather than simply processing entity objects. Jimmer entity objects are not POJOs, and can easily express data structures of arbitrary shapes. Data structures of any shape can be processed as a whole for: Reading: Jimmer creates this infinitely flexible data structure and passes it to you Writing: You create this infinitely flexible data structure and pass it to Jimmer Since Jimmer's design philosophy is to read and write data structures of arbitrary shapes rather than processing simple objects, how does it differ from technologies with similar capabilities? Here is the English translation of the provided table: Comparison Description GraphQL GraphQL only focuses on querying data structures of arbitrary shapes; Jimmer not only does this but also focuses on how to write data structures of arbitrary shapes GraphQL does not support recursive queries based on self-referencing properties, Jimmer does JPA In JPA, to control the shape of the data structure being saved, properties must be configured with insertable, updatable, or cascade (for associated properties). Regardless of the configuration, the saved data structure is fixed; Jimmer entities are not POJOs, their data structure shapes are ever-changing, no prior planning and design is needed, any business scenario can construct the data structure it needs and save it directly For queries, JPA's EntityGraphQL is very complex; Jimmer provides two methods to achieve similar functionality: controlling the format of returned entity objects, or generating DTOs through a cost-effective way and querying directly. Either way is much simpler than EntityGraph In JPA, if you need to use a DTO object to query only part of the properties, the DTO must be a simple object without any associations. That is, it loses the most valuable capability of ORM, degrading from ORM to OM; Jimmer's automatically generated DTOs support arbitrarily complex hierarchical relationships, Jimmer is currently the only ORM that supports nested projections based on DTO In JPA, updating an object results in all updatable columns being modified. For simplicity, developers rarely use update, instead choosing to first query the complete object, modify some properties, and finally save the entire object; Jimmer can construct and directly save incomplete objects JPA's EntityGraphQL does not support recursive queries based on self-referencing properties, Jimmer does MongoDB In MongoDB, each document structure is a data island. Although MongoDB's data structure is weakly typed, from a business perspective, which data islands exist and the internal hierarchical structure of each data island need to be designed and agreed upon in advance. Once the design and agreement are completed, the format of the entire data view is fixed and must be processed from a fixed perspective; In Jimmer, the shape of the data structure does not need to be designed in advance, any business scenario can freely plan a data structure format, and read and write the corresponding data structure as a whole. tip Based on this core concept, Jimmer will bring you convenience that was previously unattainable in any technology stack, freeing you from dealing with tedious details and allowing you to focus on quickly implementing complex business logic.","s":"Design Philosophy","u":"/jimmer-doc/docs/overview/key-features","h":"#design-philosophy","p":1024},{"i":1029,"t":"Based on the aforementioned core concept, Jimmer provides the following features: Convenient query API, robust Java DSL, elegant Kotlin DSL Dynamic querying is designed for multi-table queries DSL supports mixing native SQL expressions to use non-standard database-specific capabilities Extends SQL capabilities, easily supporting advanced features that are costly to implement with native SQL Advanced SQL optimization capabilities Automatic removal of unnecessary table joins Automatic merging of logically equivalent table joins Automatic merging of logically equivalent implicit subqueries Paginated query can automatically generate and optimize count query DTO language and corresponding compile-time code generator, making DTOs extremely cost-effective Output DTO, used as return for complex queries Input DTO, used as parameter for complex saves Specification DTO, used as parameter for complex queries The DTO supported by the ORM itself can be seamlessly integrated without introducing additional logic into business code Query arbitrary graph structures No \"N + 1\" problem Objects at any level can be incomplete Can recursively query self-referencing properties Can return either entities directly or output DTOs Save arbitrary graph structures Merge data using the database's native upsert capabilities Multiple objects at each level are handled using batch DML operations Automatically translates constraint violation exceptions Saved objects at any level can be incomplete Can save either entities directly or input DTOs This section has undergone a major upgrade, and the documentation is actively being restructured. Please refer to the save-command examples in the accompanying examples. Powerful caching Multi-layer caching, technology for each cache layer can be freely chosen Not just object caching (associations, computed values, multiple views) Automatically maintains cache consistency Rapid support for GraphQL Client contracts based on document comments (OpenAPI, TypeScript)","s":"Key features","u":"/jimmer-doc/docs/overview/key-features","h":"#key-features","p":1024},{"i":1031,"t":"When developing with Jimmer, there is a note of caution that needs attention. Please refer to here","s":"Notes","u":"/jimmer-doc/docs/overview/key-features","h":"#notes","p":1024},{"i":1034,"t":"When facing a new framework, the first reaction of developers is to look for examples and quick start guides. Examples: Quick Preview/Standard Examples Get started: Quick Preview/Get Started However, if you observe the documentation structure carefully, you will find that their positions in the directory structure are not particularly front. Why is that? Because Jimmer is a revolutionary technology, providing a completely new technical solution at a time when developers thought the technology ecosystem for accessing RDBMS from the JVM was already solidified and couldn't possibly undergo a major transformation. Therefore, it is necessary to first discuss these changes and clearly explain the incredible benefits they will bring to real-world projects. This field already has a plethora of choices (to the point of being over-served), and if the new technical solution's approach and methodology are similar to previous works, it would not bring about a ground-breaking change and cliff-like efficiency boost to real-world project development. Instead, it would simply be adding another choice to the already numerous choices. In that case, there would be no need to develop an entirely new project, as it would only add confusion to the industry. In summary, it is recommended to understand Jimmer's innovations and the significant benefits they will bring before looking at the standard examples and quick start guide; attempting to understand them with your previous path to success and psychological expectations may be counter-productive at first.","s":"Where are the Examples and Getting started?","u":"/jimmer-doc/docs/overview/welcome","h":"#where-are-the-examples-and-getting-started","p":1032},{"i":1036,"t":"The chapters of this documentation are divided into two types: Tutorial chapters marked with a ★ symbol. Introduction/Overview The most important article, marked with a ✦ symbol. It discusses Jimmer's innovations, introduces all its features, and provides rich, concise demonstrations. Quick Preview A quick preview of Jimmer's three most basic introductory features: Querying any shape Saving any shape Arbitrary dynamic queries. This chapter only includes these 3 core capabilities and does not cover other advanced features. Showcase For any framework, some features can be demonstrated with code and do not require extensive explanations to aid understanding. All such features that can be easily demonstrated with code and do not require much explanation are listed in this chapter. Other chapters. The remaining chapters should be treated as reference books, not tutorials. These chapters delve into the details of various features, including advanced ones.","s":"About This Documentation","u":"/jimmer-doc/docs/overview/welcome","h":"#about-this-documentation","p":1032},{"i":1038,"t":"Welcome to join the Jimmer community, Discord Link: https://discord.gg/PmgR5mpY3E","s":"Discussion","u":"/jimmer-doc/docs/overview/welcome","h":"#discussion","p":1032},{"i":1041,"t":"Jimmer extends MapStruct to support using mapstruct to complete the mutual conversion between Jimmer dynamic entity objects and static DTO objects.","s":"Introduction","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#introduction","p":1039},{"i":1043,"t":"Jimmer's entity objects are dynamic (similar to scalar attribute lazy loading introduced in Hibernate 3), which is a pattern that earlier versions of MapStruct did not consider. After communicating with MapStruct, MapStruct will support this behavior starting from 1.6.0. caution Therefore, please use 1.6.0 or higher version of MapStruct whenever possible.","s":"Notes","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#notes","p":1039},{"i":1045,"t":"Unlike DTO Language which pursues fast development but supports fixed conversion logic, mapstruct can implement arbitrarily complex conversion logic. Unlike DTO Language which directly generates brand new DTO types, mapstruct can integrate existing DTO types.","s":"Advantages","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#advantages","p":1039},{"i":1047,"t":"DTO Language is more recommended for the following reasons: Non-negligible development costs DTO Language is a solution tailored for Jimmer with development efficiency that cannot be compared when combined with any other technical solutions. Not very suitable for Output DTO The DTO types automatically generated by the DTO language have built-in Object Fetchers, so they can be used as query output types (although not recommended), please refer to: Object Fetcher/DTO Query Spring Data/Query DTO However, manually defined DTO types do not have corresponding Object Fetcher definitions, and only support mutual conversion with dynamic entities. Although Object Fetchers can be manually defined for this, there is a risk that the DTO and Object Fetcher shapes will be inconsistent. So it is not suitable as Output DTO. Kotlin risks mapstruct is based on apt (Annotation Processor). Therefore, this requires using kapt in Kotlin, which will significantly reduce the compilation speed of Kotlin projects. Kotlin has deprecated kapt in favor of ksp. Therefore, using kapt may encounter problems in the future as Kotlin evolves.","s":"Disadvantages","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#disadvantages","p":1039},{"i":1049,"t":"For converting static POJOs to Jimmer dynamic objects, MapStruct does not know how to build Jimmer objects. So Jimmer's own preprocessor (Java's jimmer-apt or Kotlin's jimmer-ksp) generates some MapStruct-oriented code in Draft, allowing MapStruct to build Jimmer objects through its Builder mode. Jimmer extends MapStruct's Annotation Processor. This extension allows MapStruct to utilize the capabilities reserved for MapStruct in the generated Draft to build Jimmer objects. This extension is called jimmer-mapstruct-apt For Java, jimmer-mapstruct-apt is included in jimmer-apt For Kotlin, jimmer-ksp and jimmer-mapstruct-apt must be used together in the maven or gradle configuration file. If you use Gradle plugin Jimmer, the plugin will automatically configure it for you when you have the MapStruct kapt dependency. Java(Maven) Java(Gradle) Kotlin(Maven) Kotlin(Gradle.kts) Java(Gradle Plugin) Kotlin(Gradle Plugin) pom.xml ...omit other code... ➀ org.projectlombok lombok ${lombok.version} ➊ org.mapstruct mapstruct ${mapstruct.version} ...omit other dependencies... org.apache.maven.plugins maven-compiler-plugin 3.10.1 ➁ org.projectlombok lombok ${lombok.version} ➋ org.babyfish.jimmer jimmer-apt ${jimmer.version} ➌ org.mapstruct mapstruct-processor ${mapstruct.version} ...omit other code... build.gradle dependencies { implementation \"org.projectlombok:lombok:${lombok.version}\" ➀ implementation \"org.mapstruct:mapstruct:${mapstructVersion}\" ➊ annotationProcessor \"org.projectlombok:lombok:${lombok.version}\" ➁ annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" ➋ annotationProcessor \"org.mapstruct:mapstruct-processor:${mapstructVersion}\" ➌ ...omit other dependencies... } pom.xml ...omit other code... src/main/kotlin src/test/kotlin ➊ org.mapstruct mapstruct ${mapstruct.version} ...omit other dependencies... org.jetbrains.kotlin kotlin-maven-plugin ${kotlin.version} compile compile compile test-compile test-compile test-compile ksp org.mapstruct ➌ mapstruct-processor ${mapstruct.version} org.babyfish.jimmer ⓐ jimmer-mapstruct-apt ${jimmer.version} com.dyescape kotlin-maven-symbol-processing 1.3 org.babyfish.jimmer ➋ jimmer-ksp ${jimmer.version} ...omit other code... build.gradle.kts plugins { id(\"com.google.devtools.ksp\") version \"1.7.10-1.0.6\" kotlin(\"kapt\") version \"1.7.10\" ...omit other plugins... } dependencies { implementation(\"org.mapstruct:mapstruct:${mapstructVersion}\") ➊ ksp(\"org.babyfish.jimmer:jimmer-ksp:${jimmerVersion}\") ➋ kapt(\"org.mapstruct:mapstruct-processor:${mapstructVersion}\") ➌ kapt(\"org.babyfish.jimmer:jimmer-mapstruct-apt:${jimmerVersion}\") ⓐ ...omit other dependencies... } kotlin { sourceSets.main { kotlin.srcDir(\"build/generated/ksp/main/kotlin\") } } build.gradle plugins { id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...omit other plugins... } jimmer { version = \"${jimmerVersion}\" ...omit other configurations... } dependencies { implementation \"org.projectlombok:lombok:${lombok.version}\" ➀ implementation \"org.mapstruct:mapstruct:${mapstructVersion}\" ➊ annotationProcessor \"org.projectlombok:lombok:${lombok.version}\" ➁ annotationProcessor \"org.mapstruct:mapstruct-processor:${mapstructVersion}\" ➍ // there's no need to add org.babyfish.jimmer:jimmer-apt to dependencies manually // when mapstruct-processor dependency is detected，the gradle plugin will add jimmer-apt to dependencies automatically ...omit other dependencies... } build.gradle.kts plugins { id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" id(\"com.google.devtools.ksp\") version \"1.7.10+\" kotlin(\"kapt\") version \"1.7.10\" ...omit other plugins... } jimmer { version = \"${jimmerVersion}\" ...omit other configurations... } dependencies { implementation(\"org.mapstruct:mapstruct:${mapstructVersion}\") ➊ kapt(\"org.mapstruct:mapstruct-processor:${mapstructVersion}\") ➌ ...omit other dependencies... } In this example, we assume static POJOs are written in Java using lombok. Language Location Description Java and Kotlin ➊ Introduce mapstruct dependency for user code to use mapstruct annotations ➋ Use Jimmer's preprocessor to generate related source code for dynamic types, Java uses jimmer-apt, Kotlin uses jimmer-ksp ➌ Use mapstruct's annotation processor to generate source code (introduced later) Java only ➀ Introduce lombok dependency for user code to use lombok annotations ➁ Use Lombok preprocessor to modify static POJO class code, e.g. add getters, setters Kotlin only ⓐ Use jimmer-mapstruct-apt to extend ➌","s":"Dependencies and Preprocessors","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#dependencies-and-preprocessors","p":1039},{"i":1051,"t":"Java Kotlin BookInput.java @Data public class BookInput { @Nullable private Long id; private String name; private int edition; private BigDecimal price; @Nullable private Long storeId; private List authorIds; } BookInput.java data class BookInput( val id: Long? = null, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, val authorIds: List ) note The @Nullable annotation is used in the Java POJO code only to improve readability and has no functional effect Three properties of this POJO need to be explained: BookInput.id Here, BookInput.id is allowed to be null. This is necessary, for example, the id does not need to be specified when inserting data. The dynamic property Book.id of the entity object does not allow null (Jimmer prohibits id from being null, please refer to Mapping/Basic Mapping/@Id) The two contradict each other, so how to convert BookInput to Book? tip Jimmer agrees that if the property of the POJO can be null while the corresponding property of the dynamic object cannot be null, the corresponding property of the dynamic object will not be assigned and will remain missing. BookInput.storeId This is obviously an associated id for the dynamic entity object property Book.store. This kind of dynamic object property is defined as an associated object, but in the POJO it is defined as an associated id, called a short association. BookInput.authorIds This is obviously a collection of associated ids, for the dynamic entity object property Book.authors. This kind of dynamic object property is defined as an associated objects, but in the POJO it is defined as an associated ids, called a short association. The other properties are exactly the same as the original entity definition and need no explanation.","s":"Define POJO","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#define-pojo","p":1039},{"i":1053,"t":"The most important thing when using mapstruct is to define the Mapper, as follows Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); } BookInputMapper.java @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(input: BookInput): Book } This Mapper provides a toBook method to convert a BookInput object to a Book object. BookInput.id, BookInput.id, BookInput.name and BookInput.price are all non-associated properties that mapstruct can handle well. note The issue that BookInput.id can be null while Book.id cannot be null has been discussed before, so it won't be repeated here. The key is how BookInput.storeId and BookInput.authorIds should be mapped, which falls into two cases: The entity defines @IdView properties The entity does not define @IdView properties","s":"Define Mapper","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#define-mapper","p":1039},{"i":1055,"t":"If the entity type defines @IdView properties, for example: Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface Book { ...omit other properties... @ManyToOne @Nullable BookStore store(); @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) List authors(); @IdView // id view of associated object store Long storeId(); // id view of all objects in associated collection authors @IdView(\"authors\") List authorIds(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Book { ...omit other properties... @ManyToOne val store: BookStore? @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_id\" ) val authors: List @IdView // id view of associated object store val storeId: Long? // id view of all objects in associated collection authors @IdView(\"authors\") val authorIds: List } In this case, the entity object and POJO correspond completely, and the Mapper does not need any modification.","s":"If the entity defines @IdView properties","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#if-the-entity-defines-idview-properties","p":1039},{"i":1057,"t":"If the entity type does not define @IdView properties, the Mapper needs to be modified: Convert BookInput.storeId to a BookStore object with only the id, then assign it to Book.store Convert BookInput.authorIds to a collection of Author objects with only ids, then assign it to Book.authors Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") Book toBook(BookInput input); @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") BookStore toBookStore(Long id); @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") Author toAuthor(Long id); } BookInputMapper.java @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") fun toBook(input: BookInput): Book @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") fun toBookStore(id: Long?): BookStore @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") fun toAuthor(id: Long?): Author } Since mapstruct also supports @Mapping(target = \"store.id\", source = \"storeId\"), the following syntax can also be used to simplify the code: Java Kotlin BookInputMapper.java @Mapper public interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store.id\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") Book toBook(BookInput input); @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") Author toAuthor(Long id); } BookInputMapper.java @Mapper interface BookInputMapper { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) @Mapping(target = \"store.id\", source = \"storeId\") @Mapping(target = \"authors\", source = \"authorIds\") fun toBook(input: BookInput): Book @BeanMapping(ignoreByDefault = true) @Mapping(target = \"id\", source = \".\") fun toAuthor(id: Long?): Author }","s":"If the entity does not define @IdView properties","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#if-the-entity-does-not-define-idview-properties","p":1039},{"i":1059,"t":"Now we can convert BookInput to Book: Java Kotlin BookInput input = ...omit...; BookInputMapper mapper = Mappers.getMapper(BookInputMapper.class); Book book = mapper.toBook(input); val input: BookInput = ...omit... val mapper = Mappers.getMapper(BookInputMapper::class.java) val book = mapper.toBook(input)","s":"Usage","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#usage","p":1039},{"i":1061,"t":"Jimmer provides a simple interface, org.babyfish.jimmer.Input public interface Input { E toEntity(); } Dynamic objects will never implement this interface, this interface should be implemented by user-defined static POJO classes. Its function is very simple, just convert the current static POJO to a dynamic object. This interface can provide convenience at the syntax level. Whether it is the underlying save command or the top-level spring-data base interface JRepository/KRepository, its sava method directly accepts Input parameters, without the user having to call the Mapper to complete the conversion. If you want this convenience at the syntax level, you can choose to have the POJO implement this interface by modifying the BookInput code as follows: Java Kotlin BookInput.java @Data public class BookInput implements Input { ❶ private static final Converter CONVERTER = Mappers.getMapper(Converter.class); ...omit private fields... @Override public Book toEntity() { ❷ return CONVERTER.toBook(this); } @Mapper interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) Book toBook(BookInput input); ...omit other mapstruct configuration... } } BookInput.kt data class BookInput( ...omit... ): Input { ❶ override fun toEntity(): Book = ❷ CONVERTER.toBook(this) @Mapper internal interface Converter { @BeanMapping(unmappedTargetPolicy = ReportingPolicy.IGNORE) fun toBook(input: BookInput): Book ...omit other mapstruct configuration... } companion object { @JvmStatic private val CONVERTER = Mappers.getMapper(Converter::class.java) } } ❶ BookInput class implements interface org.babyfish.jimmer.Input ❷ Implement Input.toEntity method, use MapStruct to convert the current static Input DTO object to the dynamic Book entity object. This is the only function of this class.","s":"Make POJO implement Input interface","u":"/jimmer-doc/docs/object/view/mapstruct","h":"#make-pojo-implement-input-interface","p":1039},{"i":1063,"t":"We will introduce the following contents: Problems of other solutions Chain-style association paths Merge conflict table joins Optimizing unnecessary join Pagination safety Weak join Kotlin table join special features","s":"Dynamic JOIN","u":"/jimmer-doc/docs/query/dynamic-join/","h":"","p":1062},{"i":1065,"t":"In this section, we will introduce the various queries in Jimmer without considering Cache. There are three groundbreaking capabilities: Object Fetcher One statement to query data structure of arbitrary shape, like GraphQL Dynamic Join This addresses a huge gap in the JVM ecosystem, enabling easy complex dynamic queries Smart Paging Users only focus on querying the raw data, row count queries are auto-generated and optimized for convenience","s":"Query","u":"/jimmer-doc/docs/query/","h":"","p":1064},{"i":1069,"t":"Jimmer provides dynamic entities that can solve a large part of the DTO explosion problem very well. Therefore, generally speaking, it is not necessary to define output DTO types to express query results. However, not all DTO types can be eliminated. Input DTO objects are hard to remove. For example, in GraphQL, although dynamic GraphQLObject data is returned for the client from the output perspective, static GraphQLInput data submitted by the client is accepted from the input perspective. Why does the GraphQL protocol define GraphQLInput as a static type? Because API explicitness and system security are very important requirements, please refer to Problems with dynamic objects as input parameters. The problems faced by the GraphQL protocol are also faced by Jimmer, which must provide a complete solution. tip The DTO language is designed for that part of the DTO types that cannot be eliminated, with the goal of making them extremely cheap.","s":"1.1. Pain Point","u":"/jimmer-doc/docs/object/view/dto-language","h":"#11-pain-point","p":1066},{"i":1071,"t":"As a comprehensive solution, Jimmer is not limited to ORM itself, but considers the whole project. To solve this problem, it provides the DTO language. The DTO language is a very powerful feature provided by Jimmer, and is a concept highly similar to Object Fetcher, but at an earlier stage during compilation. The DTO language is used to quickly define the shape of data structures. Based on these shapes, DTOs can be compile-time Generate specific static DTO types corresponding to specific data structures Generate mutual conversion logic between DTO static objects and Jimmer dynamic objects Generate Object Fetchers that match perfectly with the DTO shape definitions Using the DTO language to quickly build DTO types is a solution tailored for Jimmer with extremely high development efficiency, much faster than using mapstruct, and is the recommended approach.","s":"1.2. Solution","u":"/jimmer-doc/docs/object/view/dto-language","h":"#12-solution","p":1066},{"i":1073,"t":"The application scenarios of the DTO language: Serve as return results in query APIs (optional, not recommended, don't use unnecessarily) Serve as input parameters in save APIs (required) Serve as input parameters in super QBE queries (optional, recommended)","s":"1.3. Application Scenarios","u":"/jimmer-doc/docs/object/view/dto-language","h":"#13-application-scenarios","p":1066},{"i":1075,"t":"The code of the DTO language is reflected in files with the extension dto. Once compilation is complete, these files have no value. So these files cannot be packaged into src/main/resources, but should be placed in the src/main/dto directory. Therefore, the first thing is to create a dto subdirectory under src/main. tip Jimmer does not require the src/main/dto directory to be in the project where the entity type is located. In fact, you can create this directory in any project that can legally access the entity. Jimmer only requires using jimmer-apt or jimmer-ksp in projects containing dto files. They are responsible for compiling dto files and generating related code. For Java projects, in addition to jimmer-apt, it may be necessary to add an extra configuration. Please refer to Notes.","s":"2. Create File","u":"/jimmer-doc/docs/object/view/dto-language","h":"#2-create-file","p":1066},{"i":1077,"t":"Multiple dto files can be defined under the src/main/dto directory, with each file corresponding to an original entity. Assuming there is a Jimmer entity type whose full type name is com.yourcompany.yourproject.Book, and this class is decorated with @org.babyfish.jimmer.sql.Entity (DTO language only supports Entity types), there are two ways to create dto files. Not using export statement In this case, the dto file directory needs to correspond to the original entity package, and the name needs to correspond to the original entity name: Under the src/main/dto directory, create the directory com/yourcompany/yourproject, that is, create a directory consistent with the package name In the directory created in the previous step, create a new file Book.dto. This file must have the same name as the class and have the extension dto Using export statement The exportstatement is important, so we will explain it separately in a chapter.","s":"2.1. Two ways to create files","u":"/jimmer-doc/docs/object/view/dto-language","h":"#21-two-ways-to-create-files","p":1066},{"i":1079,"t":"In this case, the dto file directory and name are arbitrary, because we will use the export statement inside the file to define which original entity the dto file corresponds to. Since there is no requirement for the dto file directory, it is recommended to create the dto file directly under src/main/dto Although there is no requirement for the dto file name either, for the maintainability of the project, it is still recommended that the file name adopts the name of the original entity, which is Book.dto in this case The first line of code in the dto file is the export statement export com.yourcompany.yourproject.Book ...subsequent code... After the DTO file is compiled, more Java/Kotlin types will be generated automatically. Their default package name is: entity package name + .dto. If you use the export statement, you can further define the package where the generated code is located, for example: export com.yourcompany.yourproject.Book -> package com.yourcompany.yourproject.mydto Users can edit the Book.dto file to define any number of DTO types with Book as the aggregate root. Here we first define a DTO type: Book.dto ...export statement omitted if any... BookView { ...omitted... } info The first line of code in the dto file may be the export statement. For simplicity, export statements are omitted in subsequent sections. After compilation, the Java/Kotlin type BookView will be generated. Assuming the default value of the package where the generated code is located has not been changed, the generated code is as follows: Java Kotlin BookView.java package com.yourcompany.yourproject.dto; import com.yourcompany.yourproject.Book; import org.babyfish.jimmer.View; public class BookView implements View { ...omitted... } BookView.kt package com.yourcompany.yourproject.dto import com.yourcompany.yourproject.Book import org.babyfish.jimmer.View open class BookView( ...omitted... ) : View { ...omitted... }","s":"2.2 Export statement","u":"/jimmer-doc/docs/object/view/dto-language","h":"#22-export-statement","p":1066},{"i":1081,"t":"warning For Java projects (Kotlin developers please ignore): If the current project is not the project that defines the entity, you need to decorate any class in the current project with @org.babyfish.jimmer.sql.EnableDtoGeneration. Otherwise, the DTO file will not be compiled. dto files are compiled by Jimmer's Annotation Processor (Java) or Ksp (Kotlin). Therefore, if you are using an IDE like Intellij to develop projects, then In addition to dto files, if other Java/Kotlin files are modified, clicking the run button in the IDE directly can cause recompilation of dto files However, if no other Java/Kotlin files are modified except dto files, simply clicking the run button in the IDE does not cause dto files to be recompiled unless explicitly rebuilding! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle","s":"2.3. Notes","u":"/jimmer-doc/docs/object/view/dto-language","h":"#23-notes","p":1066},{"i":1083,"t":"It was mentioned earlier that the DTO language has three use cases: Serve as return values in query APIs (optional, not recommended, don't use unnecessarily) Serve as input parameters in save APIs (required) Serve as input parameters in super QBE queries (optional, recommended) So, the DTO language can define three types of DTOs: view: Neither uses the input keyword nor the specification keyword, which can be understood as Output DTO. input: Declared with the input keyword, which can be understood as Input DTO. specification: Declared with the specification keyword. It is not closely related to DTO itself, but can be used as a query parameter to support super QBE queries. Book.dto BookView { ...omitted... } AnotherBookView { ...omitted... } input BookInput { ...omitted... } input AnotherBookInput { ...omitted... } specification BookSpecification { ...omitted... } specification AnotherBookSpecification { ...omitted... } This means: BookView and AnotherBookView are used as query outputs. The generated Java/Kotlin types implement the org.babyfish.jimmer.View interface note It is recommended that output DTOs end with View BookInput and AnotherBookInput are used as save command inputs. The generated Java/Kotlin types implement the org.babyfish.jimmer.Input interface note It is recommended that input DTOs end with Input BookSpecification and AnotherBookSpecification are used as query parameters to support super QBE queries. The generated Java/Kotlin types implement the org.babyfish.jimmer.Specification interface note It is recommended that query parameter DTOs end with Specification","s":"3. view, input and specification","u":"/jimmer-doc/docs/object/view/dto-language","h":"#3-view-input-and-specification","p":1066},{"i":1085,"t":"For view and input, their generated Java/Kotlin types can convert between entities, with the following capabilities: Constructor taking original entity type as parameter: Convert Jimmer dynamic entity object to static DTO object toEntity(): Convert static DTO object to Jimmer dynamic entity object Take BookView as an example: Java Kotlin Book entity = ...omitted...; // Entity -> DTO BookView dto = new BookView(entity); // DTO -> Entity Book anotherEntity = dto.toEntity(); val entity: Book = ...omitted... // Entity -> DTO val dto = BookView(entity) // DTO -> Entity val anotherEntity: Book = dto.toEntity()","s":"3.1 Common functionalities of view and input","u":"/jimmer-doc/docs/object/view/dto-language","h":"#31-common-functionalities-of-view-and-input","p":1066},{"i":1087,"t":"Compared with Output DTO, Input DTO has the following differences: If the entity ID property is configured with auto-increment strategy, the id property in the input DTO is nullable. Here is the translation into English: info The reason for this design is that saving the object does not necessarily require the id property when the entity's id property has an auto-increment strategy. However, this does not mean Jimmer will simply assume like other ORMs such as JPA that lacking an id property means an insert operation while having an id property means an update operation. Jimmer has smarter strategies in this regard, please refer to Save Commands/Save Modes. This article will not repeat the details. If the developer does not accept this default behavior, there are two ways to write the DTO code: Make the DTO type have no id property at all input BookInput { #allScalars(this) -id } Make the DTO type's id property non-nullable input BookInput { #allScalars(this) id! } The input DTO can only define savable properties, such as simple properties, ordinary ORM associations, and id-view properties. Unsavable properties such as transient properties, formula properties, computed properties, and remote associations cannot be defined, otherwise it will cause compilation errors. Input DTO provides comprehensive and powerful support for nullable properties. tip For properties that are allowed to be null in the original entity, how to map them through Input DTO is a complex topic. Jimmer provides comprehensive and powerful support. Please refer to Modification/Save Command/Input DTO/Handle Null Values.","s":"3.2 input-specific functionalities","u":"/jimmer-doc/docs/object/view/dto-language","h":"#32-input-specific-functionalities","p":1066},{"i":1089,"t":"The role of specification is similar to input, used to decorate input types, but specification does not provide the ability to convert between entity objects, but is used as a query parameter to support super QBE queries. tip Super QBE Query is a very powerful feature of Jimmer that is not explained here. Please refer to the relevant section.","s":"3.3 specification-specific functionalities","u":"/jimmer-doc/docs/object/view/dto-language","h":"#33-specification-specific-functionalities","p":1066},{"i":1091,"t":"Attributes can be defined for DTO types to map properties in the original entity type, for example: Book.dto BookView { id name edition } This means that the DTO only maps the three properties of the entity: id, name and edition, as follows: Java Kotlin BookView.java public class BookView implements View { private long id; private String name; private String edition; public BookView(Book book) { ...omitted... } @Override public Book toEntity() { ...omitted... } ...other members omitted... } BookView.kt open class BookView( val id: Long = 0, val name: String = \"\", val edition: Int = 0 ) : View { constructor(book: Book): this(...omitted...) override fun toEntity(): Book { ...omitted... } ...other members omitted... }","s":"4. Simple properties","u":"/jimmer-doc/docs/object/view/dto-language","h":"#4-simple-properties","p":1066},{"i":1093,"t":"The DTO language supports a special macro property, #allScalars, which represents mapping all scalar properties in the entity. Book.dto BookView { #allScalars } According to the definition of the Book type in the official example: The scalar properties of Book itself are id, name, edition, and price Book inherits TenantAware, and the TenantAware interface defines the tenant property Book also inherits CommonEntity (multiple inheritance), and CommonEntity interface defines the createdTime and modifiedTime properties #allScalars means automatically mapping all scalar properties of the entity, including inherited ones. If this is not the behavior you want, then You can use allScalars(Book) to indicate mapping only the scalar properties defined by the Book type itself, excluding inherited properties. You can also use allScalars(TenantAware) and allScalars(CommonEntity) to indicate properties of specific super types. tip For the current type Book, #allScalars(Book) can also be written as #allScalars(this). In fact, #allScalars supports multiple parameters, for example: Macro Expression Automatically Mapped Attributes #allScalars createdTime, modifiedTime, tenant, id, name, edition, price #allScalars(this) id, name, edition, price #allScalars(TenantAware) tenant #allScalars(CommonEntity) createdTime, modifiedTime #allScalars(this, TenantAware) tenant, id, name, edition, price #allScalars(this, CommonEntity) createdTime, modifiedTime, id, name, edition, price #allScalars(TenantAware, CommonEntity) createdTime, modifiedTime, tenant #allScalars(this, TenantAware, CommonEntity) createdTime, modifiedTime, tenant, id, name, edition, price info If the #allScalars macro is used, it must be defined as the first property, otherwise it will cause compile errors. If parameters are specified for the #allScalars macro, each parameter must be the current entity or its base type, otherwise it will cause compile errors.","s":"5. allScalars","u":"/jimmer-doc/docs/object/view/dto-language","h":"#5-allscalars","p":1066},{"i":1095,"t":"The #allScalars macro mentioned above will batch map multiple properties. Negative properties can remove some properties. Book.dto BookView { #allScalars -tenant } Similar to above, if we understand according to the inheritance relationship of the Book type in the official example, #allScalars will add the properties createdTime, modifiedTime, tenant, id, name, edition and price. -tenant removes the tenant property from it, finally adding the properties createdTime, modifiedTime, id, name, edition and price. info What is specified by the negative property is not the property name of the entity, but the name of the corresponding property in the DTO. Here the two are the same and there is no difference. The Renaming section later will reveal the difference between the two. It is not difficult to find that for this example, there is another equivalent writing: Book.dto BookView { // Exclude `TenantAware` #allScalars(Book, CommonEntity) }","s":"6. Negative Attributes","u":"/jimmer-doc/docs/object/view/dto-language","h":"#6-negative-attributes","p":1066},{"i":1097,"t":"By default: All properties in specification are null by default. Otherwise, the nullability of DTO properties is the same as the nullability of original properties in entities. We can use ? or ! to modify DTO properties to change the nullability of DTO properties.","s":"7. Nullability","u":"/jimmer-doc/docs/object/view/dto-language","h":"#7-nullability","p":1066},{"i":1099,"t":"We can use ? to modify DTO properties to make them nullable. warning If the original property in the entity is already nullable, it will cause compile errors. For example: Book.dto input UpdateBookInput { #allScalars price? } You can even apply ? to allScalars to make all automatically mapped non-associative properties nullable: Book.dto input UpdateBookInput { #allScalars? } Specification types do not allow ? warning Since all properties in specification are nullable by default, specifying the modifier ? for properties within specification will cause compile errors. When the original property in the entity does not allow null For non-nullable original properties in an entity, if the corresponding property in the DTO object is null, the original property in the entity object will not be assigned after converting the DTO object to the entity object. When the original property in the entity allows null tip For properties that are allowed to be null in the original entity, how to map them through Input DTO is a complex topic. Jimmer provides comprehensive and powerful support. Due to length limitations, this issue forms a separate article. Please refer to Modification/Save Command/Input DTO/Handle Null Values.","s":"7.1. ?","u":"/jimmer-doc/docs/object/view/dto-language","h":"#71-","p":1066},{"i":1101,"t":"We can use ! to modify DTO properties to make them non-null. warning If the original property in the entity is already non-null, it will cause compile errors. Its use is limited and can only be used in the following three cases: Modify the id property in input type If the id property is configured with auto-increment strategy, the corresponding input DTO type will make the id property nullable. However, this behavior does not always meet user expectations. You can use ! to modify the id property in the input type to make it non-null, for example: Book.dto input BookUpdateInfo { #allScalars id! } warning Using ? to modify other properties will cause compile errors. If input is modified by the unsafe keyword, any nullable entity property can be converted to non-null, for example: Book.dto unsafe input BookUpdateInfo { #allScalars store! { ...omitted... } } info For an entity object, if the corresponding value of this property is null, when using the Input DTO constructor to convert it to an Input DTO object, an exception will occur because the corresponding property in DTO does not allow null. This is the meaning of the unsafe keyword. For specification, since all properties are null by default, any nullable entity property can be converted to non-null, for example: Book.dto specification BookSpecification { #allScalars edition! }","s":"7.2. !","u":"/jimmer-doc/docs/object/view/dto-language","h":"#72-","p":1066},{"i":1103,"t":"The as keyword can be used to set aliases for properties so that entity property names are different from DTO property names. as has two usages, it can precisely set an alias for a single property, and it can also vaguely set aliases for multiple properties.","s":"8. Renaming","u":"/jimmer-doc/docs/object/view/dto-language","h":"#8-renaming","p":1066},{"i":1105,"t":"Book.dto BookView { name as bookName }","s":"8.1. Renaming a single property","u":"/jimmer-doc/docs/object/view/dto-language","h":"#81-renaming-a-single-property","p":1066},{"i":1107,"t":"Assume there is an entity type called Robot: Robot.dto OrderView { as (^ -> oldSystem) { ❶ prop1 prop2 } as ($ -> ForNewSystem) { ❷ prop3 prop4 } } Where: ❶ Adds the prefix oldSystem to prop1 and prop2, where ^ indicates the start position ❷ Adds the suffix ForNewSystem to prop3 and prop4, where $ indicates the end position The generated RobotView class is as follows: Java Kotlin BookView.java public class RobotView implements View { private String oldSystemProp1; private String oldSystemProp2; private String prop3ForNewSystem; private String prop4ForNewSystem; ...other members omitted... } BookView.kt open class RobotView( val oldSystemProp1 = \"\", val oldSystemProp2 = \"\", val prop3ForNewSystem = \"\", val prop4ForNewSystem = \"\" ) : View { ...other members omitted... } You can define most properties in the as() {...} block, of course including #allScalars, for example: Robot.dto RobotView { as(^ -> robot) { #allScalars } } Below are all the usages of the as() {...} block: Code Example Description as(^ -> prefix) Add prefix as(^prefix ->) Remove prefix as(^prefix -> newPrefix) Replace prefix as($ -> suffix) Add suffix as($suffix ->) Remove suffix as($suffix -> newSuffix) Replace suffix as(infix -> ) Remove any content as(infix -> newInfix) Replace any content caution ^ and $ cannot appear at the same time, because it means precise renaming of a single property, which duplicates existing functionality.","s":"8.2. Renaming multiple properties","u":"/jimmer-doc/docs/object/view/dto-language","h":"#82-renaming-multiple-properties","p":1066},{"i":1109,"t":"By default, enum type properties in entities are still enum types after being mapped to DTO properties. You can map enum types to numbers or strings: Map to numbers AuthorView { #allScalars gender -> { MALE: 100 FEMALE: 101 } } The following code will be generated: Java Kotlin BookView.java public class AuthorView implements View { private int gender; ...other members omitted... } BookView.kt open class RobotView( val gender: Int, ...other members omitted... ) : View { ...other members omitted... } Map to strings AuthorView { #allScalars gender -> { MALE: \"Male\" FEMALE: \"Female\" } } The following code will be generated: Java Kotlin BookView.java public class AuthorView implements View { private String gender; ...other members omitted... } BookView.kt open class RobotView( val gender: String, ...other members omitted... ) : View { ...other members omitted... }","s":"9. Enum Mapping","u":"/jimmer-doc/docs/object/view/dto-language","h":"#9-enum-mapping","p":1066},{"i":1111,"t":"The handling of association properties is a very powerful feature of the DTO language with three usages: Direct use Recursive association Call id function Call flat function","s":"10. Association Attributes","u":"/jimmer-doc/docs/object/view/dto-language","h":"#10-association-attributes","p":1066},{"i":1113,"t":"Basic usage Robot.dto input CompositeBookInput { #allScalars(Book) store { #allScalars(BookStore) -id } authors { #allScalars(Author) -id } } The generated code is: Java Kotlin CompositeBookInput.java public class CompositeBookInput implements Input { @Nullable private Long id; private String name; private int edition; private BigDecimal price; private TargetOf_store store; private List authors; public static class TargetOf_store implements Input { private String name; @Nullable private String website; ...other members omitted... } public static class TargetOf_authors implements Input { private String firstName; private String lastName; private Gender gender; ...other members omitted... } ...other members omitted... } CompositeBookInput.kt open class CompositeBookInput( val id: Long? = null, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val store: TargetOf_store? = null, val authors: List = emptyList(), ) : Input { open class TargetOf_store( val name: String = \"\", val website: String? = null, ) : Input { ...other members omitted... } open class TargetOf_authors( public val firstName: String = \"\", public val lastName: String = \"\", public val gender: Gender, ) : Input { ...other members omitted... } ...other members omitted... } Renaming If you want to rename association properties, the as clause should be before the association definition block, for example: Book.dto input CompositeBookInput { authors as authorList { ...omitted... } ...omitted... }","s":"10.1. Ordinary Association","u":"/jimmer-doc/docs/object/view/dto-language","h":"#101-ordinary-association","p":1066},{"i":1115,"t":"For recursively associative properties in entities, such as TreeNode.parent or TreeNode.childNodes in the attached example, the corresponding associative property in the DTO can be marked as recursive using an asterisk *. TreeNode.dto TreeNodeView { #allScalars childNodes* }","s":"10.2 Recursive Association","u":"/jimmer-doc/docs/object/view/dto-language","h":"#102-recursive-association","p":1066},{"i":1117,"t":"Here is the translation into English: For short associations@IdView@IdView Therefore, the DTO language supports the id function on associated properties to achieve the same purpose: Book.dto BookView { id(store) id(authors) as authorIds ...omitted... } This code has the exact same function as the previous example, but no longer assumes the entity type always declares @IdView properties, which is a better solution.","s":"10.3. id Function","u":"/jimmer-doc/docs/object/view/dto-language","h":"#103-id-function","p":1066},{"i":1119,"t":"For view and input, the flat function can only be used for referential associations (one-to-one or many-to-one), not collection associations (one-to-many or many-to-many). It is used to promote the properties of associated DTOs to the current DTO type to obtain a flattened object without associations. For specification, the flat function does not have the above restrictions and can be used for collection associations. Please check (../../query/super_qbe). Take the TreeNode entity in the official example (in fact, this example is wrong, we will discuss this issue later): TreeNode.dto FlatTreeNodeView { #allScalars(TreeNode) flat(parent) { #allScalars(TreeNode) } } As mentioned above, this example is wrong, because the aggregate root and the associated object both have the id and name properties. Unconditionally extracting the properties of the associated object to the aggregate root will inevitably lead to name conflicts, eventually causing DTO language compilation errors. The right approach is to combine it with the user's multi-property fuzzy renaming as(...) {} block. Let's look at a new example: TreeNode.dto FlatTreeNodeView { #allScalars(TreeNode) // id, name flat(parent) { as(^ -> parent) { // parentId, parentName #allScalars(TreeNode) } } } Thus, we get a flattened DTO type with 4 properties: id, name, parentId and parentName. You can even nest the flat function to convert multi-level associations into flattened objects: TreeNode.dto FlatTreeNodeView { #allScalars(TreeNode) flat(parent) { as(^ -> parent) { #allScalars(TreeNode) } flat(grandParent) { as(^ -> parent) { #allScalars(TreeNode) } } } } Thus, we get a flattened DTO type with 6 properties: id, name, parentId, parentName, grandParentId, and grandParentName. Java Kotlin TreeNode treeNode = Immutables.createTreeNode(cola -> { cola.setId(4L); cola.setName(\"Coca cola\"); cola.applyParent(drinks -> { drinks.setId(3L); drinks.setName(\"Drinks\"); drinks.applyParent(food -> { food.setId(2L); food.setName(\"Food\"); }) }) }); // Convert hierarchical Entity to flattened DTO FlatTreeNodeView view = new FlatTreeNodeView(treeNode); System.out.println(view); val treeNode = TreeNode { id = 4L name = \"Coca cola\" parent { id = 3L name = \"Drinks\" parent { id = 2L name = \"Food\" } } } // Convert hierarchical Entity to flattened DTO val view = FlatTreeNodeView(treeNode) println(view) The print result is (formatted here for readability): com.yourcompany.yourproject.FlatTreeNodeView( id = 4, name = Coco cola, parentId = 3, parentName = Drinks, grandParentId = 2, grandParentName = \"Food\" ) The flat solution also has drawbacks. For output DTOs, the flat solution is controversial and is not recommended to be blindly adopted. Please refer to Controversy over whether output DTOs should use flat mode","s":"10.4. flat Function","u":"/jimmer-doc/docs/object/view/dto-language","h":"#104-flat-function","p":1066},{"i":1122,"t":"In the examples we have discussed before, all DTO properties are mapped from entity properties and become mapped properties. In addition to mapped properties, DTO types also support mapping custom properties: BookInput.dto BookInput { #allScalars(Author)? - id remark: String } Here, BookInput has a custom field remark. info The difference between custom properties and mapped properties is that custom properties require type definitions.","s":"11.1 Introduction to Custom Fields","u":"/jimmer-doc/docs/object/view/dto-language","h":"#111-introduction-to-custom-fields","p":1066},{"i":1124,"t":"Custom fields can be defined as built-in types, which are types built into the DTO language that do not require import via import. Primitive and boxed types DTO Language Type Generated Java Type Generated Kotlin Type Boolean boolean Boolean Boolean? Boolean Boolean? Char char Char Char? Character Char? Byte byte Byte Byte? Byte Byte? Short short Short Short? Short Short? Int int Int Int? Integer Int? Long long Long Long? Long Long? Float float Float Float? Float Float? Double double Double Double? Double Double? Any and String types DTO Language Type Generated Java Type Generated Kotlin Type Any Object Any String String String Array types DTO Language Type Generated Java Type Generated Kotlin Type Array boolean[] BooleanArray Array Boolean[] Array Array char[] CharArray Array Character[] Array Array byte[] ByteArray Array Byte[] Array Array short[] ShortArray Array Short[] Array Array int[] IntArray Array Integer[] Array Array long[] LongArray Array Long[] Array Array float[] FloatArray Array Float[] Array Array double[] DoubleArray Array Double[] Array Array UserType[] Array Array UserType[] Array Array<*> Object[] Array<*> Collection types DTO Language Type Generated Java Type Generated Kotlin Type Iterable Iterable Iterable MutableIterable Iterable MutableIterable Collection Collection Collection MutableCollection Collection MutableCollection List List List MutableList List MutableList Set Set Set MutableSet Set MutableSet Map Map Map MutableMap Map Mutable","s":"11.2 Built-in Types","u":"/jimmer-doc/docs/object/view/dto-language","h":"#112-built-in-types","p":1066},{"i":1126,"t":"Except for generic class types (arrays and collections) in built-in types, other generic class types support using in or out to modify generic parameters, for example: DTO Language Type Generated Java Type Generated Kotlin Type UserType1 UserType1 UserType1 UserType1 UserType1 UserType1 UserType1 UserType1 UserType1","s":"11.3 Generic Parameter Modifiers","u":"/jimmer-doc/docs/object/view/dto-language","h":"#113-generic-parameter-modifiers","p":1066},{"i":1128,"t":"Except for built-in types, other types must be fully qualified or imported at the beginning of the file when referenced, otherwise they will be considered to belong to the same package as the current entity. The DTO language supports various styles of import statements, for example: Single class import import java.time.LocalDateTime Single class renamed import import java.time.LocalDateTime as LDT Multi-class import import java.time.{ LocalDateTime, OffsetDataTime, ZonedDataTime } Multi-class renamed import import java.time.{ LocalDateTime as LDT, OffsetDataTime as ODT, ZonedDataTime as ZDT }","s":"11.4 Import Statements","u":"/jimmer-doc/docs/object/view/dto-language","h":"#114-import-statements","p":1066},{"i":1131,"t":"You can use annotations to decorate DTO types, mapped properties, and custom properties in the DTO language: BookInput.dto import org.babyfish.jimmer.client.Doc import javax.validation.constraints.Size @Doc(\"BookInput without associations\") ❶ BookInput { #allScalars @Size(min = 4, max = 20) ❷ name @Size(min = 10, max = 50) ❸ remark: String } Where: ❶ Decorates type ❷ Decorates mapped properties ❸ Decorates custom properties tip There is a detail to note: BookView ...import statements omitted... BookView { ...other properties omitted... @A authors @B { ...associated object properties omitted... } ...other DTO types omitted... } Where: @A decorates the authors property @B decorates the anonymous associated type","s":"12.1 Basic Usage","u":"/jimmer-doc/docs/object/view/dto-language","h":"#121-basic-usage","p":1066},{"i":1133,"t":"As mentioned above, the DTO language supports annotations to directly control the annotations of the generated DTO types. If a DTO property is not decorated by any annotation, the annotations of the corresponding property in the original entity will be copied (if the DTO property is mapped, not custom). Among them, any non-jimmer annotations under the org.babyfish.jimmer.client package will be copied to the generated DTO type, except for those.","s":"12.2 Annotation Replacement","u":"/jimmer-doc/docs/object/view/dto-language","h":"#122-annotation-replacement","p":1066},{"i":1135,"t":"The value parameter in annotations can be abbreviated, for example: @UserAnnotation(value = \"a\", value2 = \"b\", value3 = \"c\") can be abbreviated as: @UserAnnotation(\"a\", value2 = \"b\", value3 = \"c\") Unlike Java, no matter how many parameters an annotation has, the value parameter can be abbreviated, as long as the abbreviated property is configured first.","s":"12.3 value Parameter","u":"/jimmer-doc/docs/object/view/dto-language","h":"#123-value-parameter","p":1066},{"i":1137,"t":"There are some subtle differences between Java and Kotlin annotation syntax. The DTO language mixes the features of both, for example: @UserAnnotation( \"key1\", items = { @Item(\"subKey1\", description = \"Detail information for subKey1 ...\"), @Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), @Item(\"subKey3\", description = \"Detail information for subKey3 ...\") } ) @UserAnnotation( \"key1\", items = [ @Item(\"subKey1\", description = \"Detail information for subKey1 ...\"), @Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), @Item(\"subKey3\", description = \"Detail information for subKey3 ...\") ] ) @UserAnnotation( \"key1\", items = { Item(\"subKey1\", description = \"Detail information or subKey1 ...\"), Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), Item(\"subKey3\", description = \"Detail information for subKey3 ...\") } ) @UserAnnotation( \"key1\", items = [ Item(\"subKey1\", description = \"Detail information for subKey1 ...\"), Item(\"subKey2\", description = \"Detail information for subKey2 ...\"), Item(\"subKey3\", description = \"Detail information for subKey3 ...\") ] ) The above four styles are equivalent. You can freely choose the style you like.","s":"12.4 Mixing Java and Kotlin Syntax","u":"/jimmer-doc/docs/object/view/dto-language","h":"#124-mixing-java-and-kotlin-syntax","p":1066},{"i":1139,"t":"DTO types are low-value information, and if different DTO types are allowed to reference each other, it would lead to a problem: the early effect is convenience, but the later effect is difficulty in maintenance. Therefore, Jimmer prohibits users from seeking reusability in low-value DTO types. However, sometimes there is indeed a need to find commonalities between different DTO types (especially for internal classes of DTO), in order to facilitate abstraction and design. For this purpose, the DTO language provides a compromise: DTO types are allowed to implement existing Java/Kotlin interfaces, provided that the abstract properties in the interface are a subset of the properties in the DTO and can be implemented by the DTO type. DTO code as follows export com.yourcompany.yourproject.model.Book -> com.yourcompany.yourproject.model.dto import com.yourcompany.yourcompany.common.{ Shape1, Shape2, Shape3, Shape4, Shape5, Shape6 } BookView implements Shape1, Shape2 { #allScalars store implements Shape3, Shape4 { #allScalars } authors implements Shape5, Shape6 { #allScalars } } Compiled, generates the following code Java Kotlin BookView.java package com.yourcompany.yourproject.dto; import com.yourcompany.yourproject.Book; import org.babyfish.jimmer.View; public class BookView implements View, Shape1, Shape2 { @Nullable private TargetOf_store store; private List authors; ...other members omitted... public static class TargetOf_store implements View, Shape3, Shape4 { ...members omitted... } public static class TargetOf_authors implements View, Shape5, Shape6 { ...members omitted... } } BookView.kt package com.yourcompany.yourproject.dto import com.yourcompany.yourproject.Book import org.babyfish.jimmer.View open class BookView( ...other properties omitted... store: TargetOf_store? = null, authors: List = emptyList() ) : View, Shape1, Shape2 { ...other members omitted... open class TargetOf_store( ...omitted... ): View, Shape3, Shape4 { ...omitted... } open class TargetOf_authors( ...omitted... ): View, Shape5, Shape6 { ...omitted... } } caution If a property in the DTO overrides an abstract property in the interface, then in the auto-generated Java/Kotlin type, that property will be annotated with @Override (Java) or override keyword (Kotlin). Apart from this, the DTO language does not perform much validation on interface implementation. If the user makes other mistakes, it will result in generating incorrect Java/Kotlin types, which will be handled by the Java/Kotlin compiler.","s":"13. Implementing Interfaces","u":"/jimmer-doc/docs/object/view/dto-language","h":"#13-implementing-interfaces","p":1066},{"i":1141,"t":"As mentioned earlier, the DTO language has two more powerful features that are not discussed in depth in this article due to length limitations, but have been separated into other documents. Here we emphasize them again: Handling Null Values in Input DTO Specification DTO, Super QBE","s":"12. Related Links","u":"/jimmer-doc/docs/object/view/dto-language","h":"#12-related-links","p":1066},{"i":1144,"t":"In Problems with current solutions note There are two ways to solve this problem. This article demonstrates the first solution. Solve the problem in scenario 1: Java Kotlin List findBooks( @Nullable String name, @Nullable String storeName, @Nullable String storeWebsite ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null, () -> book.name().like(name) ) .whereIf( storeName != null, () -> table .store() ❶ .name() .like(storeName) ) .whereIf( storeWebsite != null, () -> table .store() ❷ .website() .like(storeWebsite) ) .select(book) .execute(); } fun findBooks( name: String? = null, storeName: String? = null, storeWebsite: String? = null ): List = sqlClient .createQuery(Book::class) { name?.let { where(table.name like it) } storeName?.let { where( table .store ❶ .name like it ) } storeWebsite?.let { where( table .store ❷ .website like it ) } select(table) } .execute() This is a typical dynamic query where all three query parameters are nullable. Specify name but storeName and storeWebsite are still null. In this case, the code at ❶ and ❷ will not execute. The final generated SQL does not contain any joins. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME = ? Specify name and storeName, but storeWebsite is still null. In this case, the join at ❶ takes effect but the code at ❷ does not execute. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.NAME = ? and tb_2_.NAME = ? Specify all parameters, name, storeName and storeWebsite are all non-null. In this case, both joins at ❶ and ❷ take effect. This situation is called join conflict. tip This conflict does not cause any problems. Conflicting joins are merged into one join. So in the final generated SQL, there will be no duplicate join operations. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.NAME = ? and tb_2_.NAME = ? and tb_2_.WEBSITE = ? Solve the problem in scenario 2: Java Kotlin List findDistinctIds( @Nullable Long aId, @Nullable Long bId, @Nullable Long cId, @Nullable Long dId, @Nullable Long eId ) { ATable table = Tables.A_TABLE; return sqlClient .createQuery(table) .whereIf( aId != null, () -> table.id().like(aId) ) .whereIf( bId != null, () -> table.asTableEx().bs().id().like(bId) ) .whereIf( cId != null, () -> table.asTableEx().bs().cs().id().like(cId) ) .whereIf( dId != null, () -> table.asTableEx().bs().cs().ds().id().like(dId) ) .whereIf( eId != null, () -> table.asTableEx().bs().cs().ds().es().id().like(eId) ) .select(book.id()) .distinct() .execute(); } fun findDistinctIds( aId: Long? = null, bId: Long? = null, cId: Long? = null, dId: Long? = null, eId: Long? = null ): List = sqlClient .createQuery(A::class) { aId?.let { where(table.id eq it) } bId?.let { where(table.asTableEx().bs.id eq it) } cId?.let { where(table.asTableEx().bs.cs.id eq it) } dId?.let { where(table.asTableEx().bs.cs.ds.id eq it) } eId?.let { where(table.asTableEx().bs.cs.ds.es.id eq it) } select(table.id) } .distinct() .execute() info Given the basics above, no need to list the generated SQL for different parameter combinations here. Just understand that the final SQL will not contain duplicate joins. asTableEx here is a concept to be introduced in later docs Pagination Safety. Please ignore it for now.","s":"Usage","u":"/jimmer-doc/docs/query/dynamic-join/merge","h":"#usage","p":1142},{"i":1146,"t":"Assume there are three join paths: a -> b -> c -> d -> e -> f -> g a -> b -> c -> h -> i -> j a -> x -> y -> z -> a -> b -> c -> d To eliminate conflicts, Jimmer first merges these paths into a tree: -+-a | +----+-b | | | \\----+-c | | | +----+-d | | | | | \\----+-e | | | | | \\----+-f | | | | | \\------g | | | \\----+-h | | | \\----+-i | | | \\------j | \\----+-x | \\----+-y | \\----+-z | \\----+-a | \\----+-b | \\----+-c | \\------d Then generate the join clause in the final SQL based on this tree. Another rule to note is join type. The method to create join objects takes a parameter to specify join type, e.g. left join: Java Kotlin book.store(JoinType.LEFT) book.`store?` The merge rules for join types: If join types of all conflicting join nodes are the same, the merge preserves that join type. Otherwise, the merge result is always inner join.","s":"Merge Rules","u":"/jimmer-doc/docs/query/dynamic-join/merge","h":"#merge-rules","p":1142},{"i":1149,"t":"In order to take full advantage of Kotlin's language features and optimize its development experience, Jimmer provides different APIs for Java and Kotlin, but they are essentially the same. However, outer joins are the only exception. For this detail, the behaviors of Java API and Kotlin API are different: Java DSL Use JoinType to represent join type, which can be INNER (default), LEFT, RIGHT or FULL Kotlin DSL Properties with the same name as entity properties represent inner joins Properties with a ? after the entity properties name represent left joins That is, Kotlin DSL does not support RIGHT and FULL. This sacrifice is a careful trade-off, in exchange for a more important feature for Kotlin: perfectly combining Kotlin's null safety and SQL DSL.","s":"Dilemma","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#dilemma","p":1147},{"i":1151,"t":"The entity BookStore is defined as follows: @Entity interface BookStore { val name: String val website: String? // Omit other code } The precompiled code generates: public val KNonNullProps.name: KNonNullPropExpression get() = get(\"name\") public val KNullableProps.name: KNullablePropExpression get() = get(\"name\") public val KProps.website: KNullablePropExpression get() = get(\"website\") Please ignore the details of the generated code for now. We can see many types containing NonNull or Nullable. tip In Jimmer's Kotlin SQL DSL, almost all AST types have both NonNull and Nullable implementations. This means Kotlin SQL DSL has null safety features equivalent to Kotlin language itself. SQL-style query code has complete null safety self-checking capabilities. Let's look at a simple example first: val tuples = sqlClient .createQuery(BookStore::class) { select( table.name, table.website ❶ ) } .execute() for ((name, website) in books) { ❷ println(\"Length of name: ${name.length}\") // Compile error println(\"Length of website: ${website.length}\") ❸ } Since BookStore.website is nullable, the type of the second column selected at ❶ is String? instead of String. The final return type of the query is List>. ❷ Loops through each tuple queried, destructuring into variables name and website. Since tuples is of type List>, here website is of type String?. ❸ Performs .length operation on potentially null website, causing compile error. To fix this compile error, modify code at ❸ to change . to ?.: println(\"Length of website: ${website?.length}\")","s":"Getting Started with DSL's Null Safety","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#getting-started-with-dsls-null-safety","p":1147},{"i":1153,"t":"In the above, we learned the simplest null safety in SQL DSL through a very simple example. Now, let's combine null safety with table join operations:","s":"Null Safety in Table Joins","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#null-safety-in-table-joins","p":1147},{"i":1155,"t":"val tuples = sqlClient .createQuery(BookStore::class) { select( table.name, table.store.name ❶ ) } .execute() for ((name, storeName) in books) { ❷ println(\"Length of name: ${name.length}\") println(\"Length of storeName: ${storeName.length}\") ❸ } ❶ Uses inner join to get parent object's name. The final return type of the query is List>. ❷ Destructures into variables storeName of type String, non-nullable. So code at ❸ compiles.","s":"Inner Join","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#inner-join","p":1147},{"i":1157,"t":"Let's modify the code to change inner join to outer join: val tuples = sqlClient .createQuery(BookStore::class) { select( table.name, table.`store?`.name ❶ ) } .execute() for ((name, storeName) in books) { ❷ println(\"Length of name: ${name.length}\") // Compile error println(\"Length of storeName: ${storeName.length}\") ❸ } ❶ Uses left join to get parent object. The precompiled code in BookProps.kt includes: public val KProps.store: KNonNullTable get() = join(\"store\") public val KProps.`store?`: KNullableTable get() = outerJoin(\"store\") Unlike inner join store, outer join store? returns a table of type KNullableTable, i.e. nullable table. This is the effect of left join in SQL. The precompiled code in BookStoreProps.kt includes: public val KNonNullProps.name: KNonNullPropExpression get() = get(\"name\") ❹ public val KNullableProps.name: KNullablePropExpression get() = get(\"name\") ❺ The returned KNullableTable inherits from KNullableProps instead of KNonNullProps. So in the DSL, accessing name matches ❺ instead of ❹. That is, just BookStore.name being non-null is not enough, need to also consider if the table it is accessed from is non-null. Ultimately, Jimmer determines the second column in ❶ is String?, so the return type is List>. ❷ Destructures into storeName of type String?, nullable. This must cause compile error at ❸. To fix this compile error, modify code at ❸ to change . to ?.: println(\"Length of storeName: ${storeName?.length}\") ❸","s":"Left Join","u":"/jimmer-doc/docs/query/dynamic-join/kotlin-join","h":"#left-join","p":1147},{"i":1160,"t":"Jimmer is a bilingual Java/Kotlin framework It includes a revolutionary ORM Based on this ORM, it has built a comprehensive solution, including DTO language A more comprehensive and powerful caching mechanism, as well as highly automated cache consistency More powerful client documentation and code generation capabilities, including Jimmer's unique remote exceptions Quickly create GraphQL services Cross-microservice remote entity associations","s":"1. What is Jimmer","u":"/jimmer-doc/docs/overview/introduction","h":"#1-what-is-jimmer","p":1158},{"i":1163,"t":"In the current technology ecosystem, the technology system for accessing relational databases has significant flaws. Please see the image below. Static language ORM represented by JPA Brief description Dynamic language ORM represented by ActiveRecord (Ruby) Brief description Lightweight SQL Builder/Mapper represented by MyBatis Brief description","s":"Existing Pain Points","u":"/jimmer-doc/docs/overview/introduction","h":"#existing-pain-points","p":1158},{"i":1165,"t":"In the above, we have discussed three common solutions in the RDBMS accessing field, but no matter which one we choose, we cannot achieve convenience, flexibility, and code safety simultaneously. Why is this the case? info For the JVM ecosystem, POJO (like structure of other language) is the root cause of this problem. POJO lacks the necessary flexibility and expressiveness, yet it is used as the data model and core by almost all JVM frameworks, severely limiting technical innovation in the JVM ecosystem. Therefore, in Jimmer, ORM entity objects are not POJOs. Instead, they are a unique universal data object (to be introduced later), and this unique entity object underpins all of Jimmer's major innovations, serving as the foundation for the entire framework. note In fact, Jimmer entity objects can not only be applied in the ORM field but can also be used in almost any scenario where structured data maintenance is the purpose, enhancing the expressiveness of various technology stacks. Currently, Jimmer entities are only used in relational database access due to limited resources.","s":"Root Cause","u":"/jimmer-doc/docs/overview/introduction","h":"#root-cause","p":1158},{"i":1167,"t":"At the beginning of this document, we mentioned that the revolutionary ORM is only a part of Jimmer, and Jimmer's actual capabilities have already exceeded that of a mere ORM. Now, we present an overview of Jimmer's functionality and explain each part.","s":"3. Complete Functionality","u":"/jimmer-doc/docs/overview/introduction","h":"#3-complete-functionality","p":1158},{"i":1169,"t":"In information systems, there are two types of objects: Entities: Entity objects are globally unified, with rich associations between objects. Entity objects are often very close to the database and have extremely high stability. DTO: Input/output objects for specific business scenarios, usually a local fragment torn from the global entity relationship network, and the size and shape of this fragment are very flexible. The number of DTO types is enormous, and each business interface has unique requirements for the format of DTO objects, which may be similar but different, exhibiting a clear DTO explosion problem. Additionally, they are easily affected by changing requirements and are unstable. tip Entity types are the globally unified data storage model, less affected by changing requirements, relatively stable, and considered high-value types. DTO types, as the input/output for each business scenario, are relatively arbitrary, easily affected by changing requirements, and considered low-value types. Jimmer advocates that developers should concentrate their efforts on designing the high-value entity model; sometimes DTOs are not needed, and sometimes they are. Even when needed, they can be automatically generated in an extremely inexpensive way. Therefore, projects built on Jimmer have excellent resistance to changing requirements. 3.1.1. Jimmer Entity​ Jimmer entity definitions are very similar to JPA entities. See a quick demonstration As discussed earlier, Jimmer entities are not POJOs, so they are declared as interface instead of class. Then, who is responsible for implementing this interface? It's the Jimmer Precompiler in the diagram above (for Java, it's APT; for Kotlin, it's KSP). Jimmer entities support two important features: dynamism and immutability Dynamism Jimmer objects seek the best balance between static and dynamic languages, combining the advantages of both: Static language data objects have advantages such as high performance, spelling safety, type safety, and even null safety (if using Kotlin), and Jimmer entities inherit these advantages. Dynamic language data objects have a high degree of flexibility, and Jimmer entities inherit this advantage; each property can be missing (but unlike dynamic languages, properties cannot be added, as this would inevitably violate the characteristics of static languages, and Jimmer does not need this ability). For Jimmer, an object lacking a property (its value is unknown) and an object having a null value property (its value is known) are completely different scenarios. tip This balanced design allows Jimmer to enjoy the benefits of static languages while giving data structures tremendous flexibility. This absolute flexibility can be used to express both the output format of query operations and the input format of save operations. This gives Jimmer a new positioning: an ORM designed for data structures of any shape. All its features are for operating data structures of any shape, rather than simple entity objects. Immutability Jimmer objects are immutable objects. The benefits of immutable objects are multifaceted, and there are many related articles and discussions, so this document will not repeat them. tip Jimmer chooses immutable objects to ensure that data structures never contain circular references. This ensures that data structures formed by Jimmer entities and their associations can be directly serialized by Jackson without the need for any special serialization techniques or injecting additional information into the JSON, making it easily understandable by any programming language. However, immutable objects also have disadvantages. For example, if you have a very deep data structure, creating a new data structure based on it with some desired modifications would be very difficult, with the difficulty increasing rapidly as the depth increases. ORM deals with very deep data structures, and Java's records and Kotlin's data classes are not suitable for handling very deep data structures. The current JVM ecosystem lacks a solution that provides bilingual support for both Java and Kotlin while being adept at creating new immutable data structures based on existing deep data structures with desired modifications. Fortunately, the JavaScript/TypeScript world has a sufficiently powerful solution: immer, which can perfectly solve this problem. This solution works as follows: Open a temporary scope based on the existing immutable data structure. Within this scope, developers can obtain a draft data structure with the same shape and initial values as the original data structure, which can be modified at will, including modifying any deeply nested sub-objects. After the scope ends, the draft data structure will create a new data structure based on the collected modification operations. Unmodified local parts will be optimized and reuse the old objects. Immer perfectly combines the advantages of immutable and mutable objects, with simple code, powerful functionality, and excellent performance. Therefore, Jimmer chose to port immer to the JVM ecosystem, and the project name is also a tribute to it. See a quick demonstration Reference links: Dynamism, Immutability 3.1.2. Generated DTO Type​ As mentioned earlier, Jimmer entities strike the best balance between static and dynamic language data objects, with dynamism bringing tremendous flexibility and determining the positioning of the entire framework. Jimmer objects allow certain properties to be missing, and an object lacking a property (its value is unknown) is completely different from an object having a null property (its value is known). For Jackson serialization, missing properties will be automatically ignored, just as we showed earlier. If the server does not use the queried entity object itself but directly writes it to the HTTP Response, there is no need for a DTO, and using the entity object directly is convenient. If you directly access a non-existent property using Java/Kotlin code, it will cause an exception. See a quick demonstration If the server needs to access the queried entity object itself, this could introduce risks, although Jimmer entities still retain static language features in other aspects, such as spelling safety, type safety, and even null safety (if using Kotlin). For example, in JPA, since Hibernate 3, lazy configuration is no longer limited to associated properties but can also be used for scalar properties. Later, this evolved into the fetch parameter of the JPA @Basic annotation, please refer here. This has some similarity to the fact that any property in Jimmer objects can be missing, except that Jimmer generalizes this feature to any property. So, this exception in Jimmer is somewhat similar to org.hibernate.LazyInitializationException. So, this is not a new problem created by Jimmer, but rather an existing and accepted problem in the static language ORM ecosystem. However, it is undeniable that this does indeed undermine the safety of static languages. If you want to pursue 100% static language safety, using DTO objects is the only way. However, the current DTO mapping technology in the JVM ecosystem has significant flaws. Either you explicitly map properties (e.g., pure manual mapping and conversion), which is extremely labor-intensive, tedious, and error-prone. Or you implicitly map properties (e.g., using BeanUtils technology), which introduces new safety issues that cannot be detected at compile-time. Even if you use the powerful mapstruct, all you can do is choose between these two extremes. Therefore, Jimmer provides a DTO language, where users can write very simple code, and compiling the project will automatically generate various rich DTO type definitions. tip The design goals of the DTO language are: To make the process of generating DTO types simple enough so that DTO types are inexpensive. To be 100% compliant with static language safety, detecting and reporting all issues at compile-time. In any sub-project (not limited to entity definition sub-projects), developers can freely create files with the dto extension in the src/main/dto directory to automatically generate various DTO types at a low cost. See a quick demonstration These low-cost, rapidly generated DTO types can be converted to and from Jimmer entity objects; therefore, any two DTO types can be converted to each other using Jimmer entities as an intermediate medium. Reference links: DTO language","s":"3.1. Business Model","u":"/jimmer-doc/docs/overview/introduction","h":"#31-business-model","p":1158},{"i":1171,"t":"tip Fetcher is one of the three most fundamental core features of Jimmer (the other two are Save Command and SQL DSL). Jimmer is designed to query data structures of any shape, allowing you to control the format of queried data with the same granularity as GraphQL. First, let's get an initial impression of Jimmer's ability to control the shape of queried data structures through this animation (you don't need to look too closely, just get a general idea). View animation As mentioned earlier, you can directly use entity objects or the inexpensively generated DTO objects. Fetcher provides first-class support for querying both types of data objects. Let's demonstrate its usage through three scenarios: Querying partial objects A partial object refers to querying only a subset of an object's properties, containing less information than a single object. See a quick demonstration Including associated objects Select an entity as the aggregate root, not only querying the aggregate root object but also querying its associated objects, with no restrictions on depth or breadth. This level of granularity in format control is similar to GraphQL. See a quick demonstration Recursive queries If the entity contains a self-association property, you can perform recursive queries (as of now, GraphQL does not support recursive queries). See a quick demonstration info Users should actively use this feature to query data structures of any complexity, rather than writing business code to retrieve data from different parts and then combine them into a whole, because Fetcher has advantages that are difficult to replicate with business code: It can handle not only associated properties but also complex calculated properties. It can fully utilize Jimmer's associated property caching and calculated property caching to significantly optimize the performance of querying complex data structures. Entities support remote associations, i.e., ORM associations across microservice boundaries, with Jimmer automatically querying data from different microservices and assembling it into a single data structure. The entire deep-dive process is driven by breadth-first recursion to support batch query optimization. No work is required from developers, as the ORM itself has powerful capabilities that rival GraphQL. Therefore, whether you use Jimmer to build REST services or GraphQL services, query-related tasks are very simple. Quickly build REST services The server controls the shape of the returned objects. If an HTTP API needs to return data in a certain structure, developers have two choices: either use the entity type directly or use the DTO language to cheaply generate DTO types. Whichever choice is made, the client passively accepts the data format returned by the server. Even if the client needs many different data structure shapes, the impact on the Jimmer-based server is minimal. If developers choose to return entity objects directly instead of DTOs, the server does not have the DTO explosion problem, which is not a problem for the server; but for the client, this is very bad. Jimmer generates Open API documentation and TypeScript code for the client. If the server developer chooses to return entity objects directly, the @FetchBy annotation can be used to modify the return type of the Web method, which can define the DTO type for the client in the Open API and TypeScript code. Client DTO Quickly build GraphQL services Usually, providing GraphQL services is not a small task, and developers need to put a lot of effort into supporting the rich associations between GraphQL objects. However, implementing GraphQL based on Jimmer is very easy because the ORM itself already has capabilities similar to GraphQL. Developers only need to implement queries for the aggregate root objects of the GraphQL query API, and the rich associations between GraphQL objects are automatically implemented by Jimmer. Reference links Link Description Quick Preview/Query Any Shape Quick preview: Query any shape jimmer-examples/tree/main/java/jimmer-sql Example project, using Java and Jimmer to build REST services jimmer-examples/tree/main/kotlin/jimmer-sql-kt Example project, using Kotlin and Jimmer to build REST services jimmer-examples/tree/main/java/jimmer-sql-graphql Example project, using Java and Jimmer to build GraphQL services jimmer-examples/tree/main/kotlin/jimmer-sql-graphql-kt Example project, using Kotlin and Jimmer to build GraphQL services jimmer-examples/tree/main/java/jimmer-cloud Example project, using Java and Jimmer to support ORM remote association across microservice boundaries jimmer-examples/tree/main/kotlin/jimmer-cloud-kt Example project, using Kotlin and Jimmer to support ORM remote association across microservice boundaries","s":"3.2. Fetcher","u":"/jimmer-doc/docs/overview/introduction","h":"#32-fetcher","p":1158},{"i":1173,"t":"tip Save Command is one of Jimmer's three most fundamental core capabilities (the other two are Fetcher and SQL DSL). Save Command is designed specifically for complex forms. No matter how complex the form is, it essentially represents a data structure of any shape, and Jimmer allows developers to write data structures of any shape into the database with a single method call. No matter how complex the data structure provided by the user is, Jimmer will query a data structure of the same complexity from the database and find the differences (this is not the actual working mechanism, but it's fine to understand this functionality from the user's perspective), and execute insert, update, and delete statements to update the differences. View illustration However, if the client is allowed to upload entity objects representing data structures of any shape, the client will have unrestricted data modification capabilities, which would seriously compromise security. Therefore, Input DTOs must be generated using the DTO language, and then used as input parameters for the Web API. That is: Dynamic entities serve as the internal mechanism, allowing the Save Command to save data structures of any shape, providing functional support for unlimited possibilities. Input DTO acts as a security guard, strictly limiting the user's input format, and exposing only limited data entry capabilities. Next, we will demonstrate the basic usage of the Save Command through four cases: Save a standalone object This is the simplest case because a standalone object does not have any associated data. View quick demo Save short associations A short association refers to only changing the association relationship between the current object and other objects, without further modifying the associated objects. For the UI, a reference association (one-to-one and many-to-one) is represented as a single-selection menu; a collection association (one-to-many and many-to-many) is represented as a multi-selection menu . Common UI for Short Association View quick demo Save long associations A long association refers to not only changing the association relationship between the current object and other objects, but also further modifying the associated objects. For the UI, the forms can be diverse, with nested sub-tables being the most common (one-to-many) : Common UI for Long Association View quick demo Recursively save tree structures This example is a bit different, requiring a slight modification of the root node's data before saving. View quick demo Reference links Link Description Quick Preview/Query Any Shape Quick preview: Save any shape jimmer-examples/tree/main/java/save-command Example project, using Java and Jimmer to demonstrate various scenarios of Save Command jimmer-examples/tree/main/kotlin/save-command-kt Example project, using Kotlin and Jimmer to demonstrate various scenarios of Save Command jimmer-examples/tree/main/java/jimmer-sql Example project, using Java and Jimmer to build REST services jimmer-examples/tree/main/kotlin/jimmer-sql-kt Example project, using Kotlin and Jimmer to build REST services jimmer-examples/tree/main/java/jimmer-sql-graphql Example project, using Java and Jimmer to build GraphQL services jimmer-examples/tree/main/kotlin/jimmer-sql-graphql-kt Example project, using Kotlin and Jimmer to build GraphQL services","s":"3.3. Save Command","u":"/jimmer-doc/docs/overview/introduction","h":"#33-save-command","p":1158},{"i":1175,"t":"tip SQL DSL is one of Jimmer's three most fundamental core capabilities (the other two are Fetcher and Save Command). Jimmer's SQL DSL is designed for arbitrary complex dynamic SQL. Currently, there are dozens of SQL DSLs in the entire JVM ecosystem. Among them, the ORM-style QueryDSL and the NativeSQL-style JOOQ are the most well-known. What are the characteristics of Jimmer's SQL DSL? Jimmer's SQL DSL is designed from the ground up for arbitrary complex dynamic SQL, including two powerful capabilities: dynamic table joins and implicit subqueries. Native SQL is not conducive to building complex dynamic queries, and the purpose of Jimmer's SQL DSL is to provide a solution for this; while the strong type safety that all SQL DSLs can achieve is just a side effect. Intelligent paging support, where developers only need to use the DSL to construct a regular list query, and Jimmer automatically generates a total row count query and automatically combines it with the list query to complete the paging query. Jimmer's SQL DSL can embed native SQL expressions. Due to space limitations, this article only discusses the first point above. Let's get a basic understanding of Jimmer's SQL DSL through three small examples: Simple dynamic query A simple dynamic query to establish an initial impression. View quick demo Dynamic table join Dynamically add SQL conditions for the associated objects of reference association (one-to-one or many-to-one) properties. View quick demo Implicit subquery Jimmer supports more complete regular subqueries. However, some subqueries closely related to entity associations can be written as these simpler implicit subqueries. Dynamically add SQL conditions for the associated objects of collection association (one-to-many or many-to-many) properties. View quick demo tip In fact, users can also leverage the DTO language to write specification DTOs, allowing Jimmer to automatically generate query condition parameters and all the dynamic query behaviors you've seen above. This more convenient feature is called Super QBE, Here, we adopt this feature to replace all the features introduced above. View quick demo Reference links Link Description Quick Preview/Query Any Shape Quick preview: Arbitrary dynamic queries Dynamic Table Join Implicit Subquery Intelligent Paging Not shown in this article Native Expression Not shown in this article, how to embed native SQL fragments in a strongly-typed SQL DSL Dynamic Ordering Not shown in this article Super QBE Here, no links to relevant examples are provided because all examples involve using the SQL DSL.","s":"3.4. SQL DSL","u":"/jimmer-doc/docs/overview/introduction","h":"#34-sql-dsl","p":1158},{"i":1177,"t":"This feature is similar to the database's after-trigger, which notifies the application after a database change occurs. The trigger not only notifies developers of what changes have occurred to which entity objects, but also performs ORM mapping on the change event information to notify developers of what associated changes have occurred. The trigger lays a solid foundation for another feature: caching. Jimmer supports two different types of triggers: BinLog triggers and Transaction triggers BinLog Trigger Transaction Trigger (Default Off) Working Principle Discover data changes by integrating mature CDC solutions in the industry (e.g., maxwell, debezium) Discover database changes through Jimmer's capability Notification Timing After transaction commit Before transaction commit Advantages Can sense database changes caused by any reason, including database changes that bypass the system Either the original change and the new change caused by the trigger both succeed or both fail Disadvantages After the transaction is committed, there is a slight delay in the CDC service pushing Can only sense changes to the database caused by modifications through Jimmer in the current JVM process, and cannot handle changes caused by any other reasons The duration of the current transaction will be extended, and the unlock operation of related resources will also be delayed Will cause Jimmer's modification behavior to the database to require more additional queries internally Applicable Scenarios Most scenarios, including but not limited to: cache synchronization, data synchronization across heterogeneous systems Additional behavior that must participate in the same transaction as the main business logic Reference link: Trigger","s":"3.5 Trigger","u":"/jimmer-doc/docs/overview/introduction","h":"#35-trigger","p":1158},{"i":1179,"t":"Jimmer's caching capability is very powerful, with the following 3 features: Supports multi-level caching, and each level of caching allows users to choose their preferred technology. In the accompanying example, the first-level cache is Caffeine; the second-level cache is Redis Significantly increases the application scope of caching. No longer limited to the most common id->object caching, i.e., Object Cache, but also supports the following three types of caching: id->associated id caching, i.e., Association Cache Association caching can significantly improve the performance of navigating between associated objects, which is very helpful for Jimmer's core functionality of querying data structures of any complexity. id->computed result caching, i.e., Calculated Cache Calculated caching is designed for complex computed properties, avoiding repeated calculations for multiple queries, which is also very helpful for Jimmer's core functionality of querying data structures of any complexity. Can also be combined with the permission system. Since users with different identities see different data in the database, they should also see different cached data, i.e., Multi-View Cache Storing different data for users with different identities is very memory-intensive and should definitely not be used for JVM internal caching. For external caches like Redis, it should also be used with caution, only for very important data. info Q: Why has business system caching been mainly limited to object caching for a long time, lacking diversity? A: Without the underlying framework providing highly automated support for cache consistency, the cost of using business code to maintain other types of caching is too high. Highly automated cache consistency. Jimmer provides highly automated support for cache consistency, simply by enabling the Jimmer Trigger (whether it's the BinLog trigger or the Transaction trigger). For object cache and association cache, their consistency is fully automated and requires no intervention from developers. For calculated cache and multi-view cache, developers' assistance is needed, but what developers need to do is very simple. View the effect of cache consistency Reference link: Caching","s":"3.6. Cache","u":"/jimmer-doc/docs/overview/introduction","h":"#36-cache","p":1158},{"i":1181,"t":"Global filters add inherent SQL filtering conditions to entities in a plugin manner outside the SQL DSL system. The most common application scenario is row-based permission management. Global filters are very flexible and can easily integrate with any IoC framework (such as Spring), allowing free access to business context information and thus implementing filtering logic that is closely integrated with the business. Reference link: Global Filter","s":"3.7. Global Filter","u":"/jimmer-doc/docs/overview/introduction","h":"#37-global-filter","p":1158},{"i":1183,"t":"The Draft Interceptor is similar to the database's before-trigger, giving users one last chance to adjust the data that is about to be saved before the database change occurs. The Draft Interceptor is very flexible and can easily integrate with any IoC framework (such as Spring), allowing free access to business context information and thus implementing data adjustment logic that is closely integrated with the business. Reference link: Interceptor","s":"3.8. Draft Interceptor","u":"/jimmer-doc/docs/overview/introduction","h":"#38-draft-interceptor","p":1158},{"i":1185,"t":"Logical deletion refers to the fact that a business-level data deletion operation does not actually cause the data to be deleted from the database, but simply modifies a field of the data to mark it as \"deleted\". Logical deletion also provides a built-in Global Filter, which causes data marked as \"deleted\" to be excluded from any query and unaffected by any modification statement. Jimmer's logical deletion supports both entity tables and join tables. Reference link: Logical Deletion of Entity Tables, Logical Deletion of Join Tables","s":"3.9. Logical Deletion","u":"/jimmer-doc/docs/overview/introduction","h":"#39-logical-deletion","p":1158},{"i":1187,"t":"Jimmer entities support remote associations, i.e., ORM associations across microservice boundaries. When querying a specific complex data structure, if the shape of the data structure spans multiple microservices, Jimmer will automatically query data from different microservices and assemble it into a whole to return to the developer. note Remote Associations is just the first feature for microservice development in a limited time, aiming to prove to developers that the ORM technology system can still be very powerful in the microservice technology system. After Jimmer gradually matures and releases the official 1.0 version, more features will be added to the microservice technology system to abstract and simplify more tedious details in that system. Reference link: Remote Association Mapping, Remote Association Support","s":"3.10. Remote Associations","u":"/jimmer-doc/docs/overview/introduction","h":"#310-remote-associations","p":1158},{"i":1189,"t":"Next, we will introduce Jimmer's third-party ecosystem, which are all contributed by Jimmer users. We would like to express our sincere gratitude. DTO language IntelliJ plugin https://github.com/ClearPlume/jimmer-dto Entity model generation tool The following tools focus on generating entity models based on the database Project Type Language Support Project Address IntelliJ Plugin Java&Kotlin https://github.com/ClearPlume/jimmer-generator IntelliJ Plugin Java&Kotlin https://github.com/huyaro/CodeGenX Maven Plugin Java https://github.com/TokgoRonin/code-generator-jimmer Gradle Plugin Java&Kotlin https://github.com/Enaium/jimmer-gradle Model Designer Java&Kotlin https://pot-mot.github.io/jimmer-code-gen-doc Quarkus extension https://github.com/flynndi/quarkus-jimmer-extension Solon extension https://github.com/zengyufei/xm-jimmer-solon-plugin Gradle Plugin https://github.com/ArgonarioD/gradle-plugin-jimmer https://github.com/Enaium/jimmer-gradle","s":"4. Ecosystem","u":"/jimmer-doc/docs/overview/introduction","h":"#4-ecosystem","p":1158},{"i":1191,"t":"When developing with Jimmer, there is a note of caution that needs attention. Please refer to here","s":"5. Notes","u":"/jimmer-doc/docs/overview/introduction","h":"#5-notes","p":1158},{"i":1193,"t":"How Jimmer solves the dynamic join problem will be discussed in subsequent docs. This article first introduces the join style in Jimmer.","s":"Association Path Chaining","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","h":"","p":1192},{"i":1195,"t":"Firstly, Jimmer does not support cartesian products which is exists in theoretical and should be carefully avoided in actual projects. Thus, Jimmer's SQL DSL does not need to support multiple from clauses. All cross-table operations are unified as join. In Jimmer, all table joins are implicit, formed by association paths of arbitrary length, and are considered as multiple table joins. For example: Java Kotlin public List findBooksByStoreCityName(@Nullable String storeCityName) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( storeCityName != null && !storeCityName.isEmpty(), table.store().city().name().eq(name) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); } fun findBooksByStoreCityName(name: storeCityName?): List = sqlClient .createQuery(Book::class) { storeCityName?.takeIf { it.isNotEmpty() }?.let { where(table.store.city.name eq it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute() info In the above code, table.store().city() in Java or table.store.city in Kotlin is the association path. The association path length is unlimited. Each association reference corresponds to a SQL join operation. from BOOK tb_1_ inner join BOOK_STORE tb_2_ // `.store` on tb_1_.STORE_ID = tb_2_.ID inner join CITY tb_3_ // `.city` on tb_2_.CITY_ID = tb_3_.ID For findBooksByStoreCityName(null), the generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc For findBooksByStoreCityName(\"ChengDu\"), the generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ // `.store` on tb_1_.STORE_ID = tb_2_.ID inner join CITY tb_3_ // `.city` on tb_2_.CITY_ID = tb_3_.ID where // `.name eq \"ChengDu\"` tb_3_.NAME = ? /* ChengDu */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Basic Concepts","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","h":"#basic-concepts","p":1192},{"i":1197,"t":"The association paths .store and .city in the above example represent inner joins. It's also easy to express outer joins, taking left outer join as an example: Java Kotlin table.store().city(JoinType.LEFT) table.store.`city?` caution To fully leverage Kotlin's strengths and optimize its developer experience, Jimmer provides slightly different APIs for Java and Kotlin with the same essence. However, outer joins are the only exception where Java and Kotlin APIs behave differently: Java DSL Use JoinType to represent join type, can be INNER (default), LEFT, RIGHT or FULL Kotlin DSL DSL properties same as entity properties represent inner join DSL properties with a ? suffix compared to entity properties represent left outer join That is, Kotlin DSL does not support RIGHT and FULL. This sacrifice is a careful trade-off to gain null safety integration in Kotlin, which is more important. This detail will be discussed in Kotlin Join Features.","s":"Outer Joins","u":"/jimmer-doc/docs/query/dynamic-join/chain-style","h":"#outer-joins","p":1192},{"i":1199,"t":"In the previous doc, we discussed dynamic queries. In this section, we will explore the problems with dynamic table joins. Currently, other technologies that operate on SQL, whether ORM or non-ORM, have a blank area: they only consider dynamic where, and do not consider dynamic join. Dynamic JOIN is defined as: If some dynamic query conditions are for tables other than the current table. This means When the condition is met: First join to other tables through association properties, then add dynamic where conditions to the joined table When the condition is not met: Cannot join other tables through association properties","s":"Problems with Other Solutions","u":"/jimmer-doc/docs/query/dynamic-join/problem","h":"","p":1198},{"i":1201,"t":"Let's first look at the first scene, taking MyBatis oriented to native SQL as an example Define MyBatis Mapper interface @Mapper public interface BookMapper { List findBooks( @Nullable String name, @Nullable String storeName, @Nullable String storeWebsite ); } Here, all query parameters may be null, which is clearly a dynamic query. The last two query parameters: storeName and storeWebsite, their filtering conditions are not applied on the current table BOOK, but on the parent table BOOK_STORE. That is, when any of these two parameters is non-null, a JOIN to the BOOK_STORE table will be generated. This table join dynamically determined by the parameter value is referred to as dynamic JOIN in this article. Define MyBatis SQL mapping XML Here, ❶ is the dynamic JOIN. However, for developers, ❷ and ❸ are the purpose, and ❶ is the work that has to be done to support ❷ and ❸. Its judgment condition is a burden. You may have noticed that ❶ uses or. This is easy to understand. However, this is only the simplest dynamic connection between two tables. For deeper multi-table join operations, the complexity of dynamic table joins will increase dramatically!","s":"Scene-1","u":"/jimmer-doc/docs/query/dynamic-join/problem","h":"#scene-1","p":1198},{"i":1203,"t":"Let's take a look at the second scene. With the previous example as the basis, this example is decoupled from any business. The logic of this example is simple. The five tables A, B, C, D and E form a JOIN chain, and each table has a dynamic query condition. However, as you can see, the complexity of dynamic JOIN has become unacceptable.","s":"Scene-2","u":"/jimmer-doc/docs/query/dynamic-join/problem","h":"#scene-2","p":1198},{"i":1206,"t":"Let's review this piece of entity interface code: Java Kotlin @Entity public interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); ...omit other code... } @Entity interface Book { @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List ...omit other code... } The BOOK_AUTHOR_MAPPING table is used as an association table here. The BOOK table in the database has a corresponding Book entity interface in Java code. The AUTHOR table in the database has a corresponding Author entity interface in Java code. However, the BOOK_AUTHOR_MAPPING table in the database does not have a corresponding entity interface in Java code. That is, the association table is hidden from the object model.","s":"Association Tables Hidden by Object Model","u":"/jimmer-doc/docs/query/associations","h":"#association-tables-hidden-by-object-model","p":1204},{"i":1208,"t":"Jimmer provides an interesting feature that allows querying association tables directly even if they are hidden without corresponding entities. Java Kotlin AssociationTable association = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List> associations = sqlClient .createAssociationQuery(association) .where(association.source().id().eq(3L)) .select(association) .execute(); associations.forEach(System.out::println); val associations = sqlClient .queries .forList(Book::authors) { where(table.source.id eq 3L) select(table) } .execute() associations.forEach(::println) Here, createAssociationQuery in Java or queries.forList in Kotlin represents a query based on the association table instead of entity tables. tip The Java code demo here uses AssociationTable type with complex generic arguments to be compatible with Java 8. It is recommended to upgrade Java and use the var keyword. The generated SQL is: select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID from BOOK_AUTHOR_MAPPING as tb_1_ where tb_1_.BOOK_ID = ? /* 3 */ This is indeed a query based on the association table. The final printed result is (the original output is compact, formatted here for readability): Association{ source={ \"id\":3 }, target={ \"id\":1 } } Association{ source={ \"id\":3 }, target={ \"id\":2 } } The returned data is a list of Association objects: public class Association { public S source; public T target; // constructor and getter/setters } The Association represents association table entities that associate S type to T type. Association table entities are pseudo entities without ids. They only have two properties: source: The object (Book in this example) corresponding to the foreign key pointing to the owning side. target: The object (Author in this example) corresponding to the foreign key pointing to the target side. note In this example, object fetchers are not used to define the format of association pseudo entity objects (in fact association pseudo entity does not support object fetchers), so the source and target association properties only contain id property. Author also has a bidirectional many-to-many association Author.books, which is the mirror of Book.authors. Java Kotlin @Entity public interface Author { @ManyToMany(mappedBy = \"authors\") List books(); ... } @Entity interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ... } Association table queries can also be created based on Author.books, but source will represent Author and target will represent Book, reversed from the current example. In this example, we only query the association table itself, so source and target objects only contain ids. To get complete source and target objects, join tables and use tuples for return: Java Kotlin AssociationTable association = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List> tuples = sqlClient .createAssociationQuery(association) .where(association.source().id().eq(3L)) .select( association.source(), association.target() ) .execute(); tuples.forEach(System.out::println); val associations = sqlClient .queries .forList(Book::authors) { where(table.source.id eq 3L) select( table.source, table.target ) } .execute() associations.forEach(::println) The generated SQL is: select /* source() */ tb_1_.BOOK_ID, tb_2_.NAME, tb_2_.EDITION, tb_2_.PRICE, tb_2_.STORE_ID, /* target() */ tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join BOOK as tb_2_ on tb_1_.BOOK_ID = tb_2_.ID inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID = ? /* 3 */ The final printed result is (formatted for readability): Tuple2{ _1={ \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } }, _2={ \"id\": 1, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" } } Tuple2{ _1={ \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } }, _2={ \"id\": 2, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"MALE\" } } caution The association pseudo entity Association is simple and special, does not support or need object fetchers. However, its association properties source and target can support object fetchers, such as: Kotlin select( table .source .fetchBy { allScalarFields() store { allScalarFields() } }, table.target )","s":"Querying Association Tables Directly","u":"/jimmer-doc/docs/query/associations","h":"#querying-association-tables-directly","p":1204},{"i":1210,"t":"Readers may think that association table queries exist to allow developers to write more performant queries. But this is not the case. Due to optimizations like phantom joins and half joins, whether association table queries are used or not, similar functionality and performance can be achieved. Using association table queries is completely up to user preference.","s":"Comparison with Entity Table Queries","u":"/jimmer-doc/docs/query/associations","h":"#comparison-with-entity-table-queries","p":1204},{"i":1212,"t":"In previous examples, we demoed top-level queries based on association tables. Here we demo an association table subquery. Java Kotlin BookTable table = Tables.BOOK_TABLE; AssociationTable association = AssociationTable.of(BookTableEx.class, BookTableEx::authors); List books = sqlClient .createQuery(table) .where( table.id().in( sqlClient .createAssociationSubQuery(association) .where( association .target() ❶ .firstName().eq(\"Alex\") ) .select( association .source() ❷ .id() ) ) ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id valueIn subQueries.forList(Book::authors) { where( table .target ❶ .firstName eq \"Alex\" ) select( table .source ❷ .id ) } ) select(table) } .execute() Where: createAssociationSubQuery in Java and subQueries.forList in Kotlin create a subquery based on the association table, to find books that contain the author with firstName \"Alex\". ❶ association.target is a real JOIN that generates SQL JOIN to the AUTHOR table for condition check. ❷ association.source is a phantom join that does not generate a SQL join. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_2_.BOOK_ID from BOOK_AUTHOR_MAPPING as tb_2_ inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID where tb_3_.FIRST_NAME = ? )","s":"1. Use association table subquery to achieve a function","u":"/jimmer-doc/docs/query/associations","h":"#1-use-association-table-subquery-to-achieve-a-function","p":1204},{"i":1214,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().in(sqlClient .createSubQuery(author) .where(author.firstName().eq(\"Alex\")) .select( author.books().id() ❶ ) ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id valueIn subQuery(Author::class) { where(table.firstName eq \"Alex\") select( table.books.id ❶ ) } ) select(table) } .execute() ❶ author.books is a half join that only generates SQL JOIN from AUTHOR to the BOOK_AUTHOR_MAPPING table, without further join to the BOOK table. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME = ? ) Comparing the two SQLs, it's not hard to see they achieve the same functionality and performance. info Association table queries just provide developers with another query style, they are not irreplaceable. The same functionality and performance can be achieved with other means.","s":"2. Achieve the same functionality with entity table subquery","u":"/jimmer-doc/docs/query/associations","h":"#2-achieve-the-same-functionality-with-entity-table-subquery","p":1204},{"i":1217,"t":"All the joins we have discussed so far rely on the association properties between entities, which means table joins are always related to primary and foreign keys. However, sometimes we need to join two tables based on some business properties unrelated to primary and foreign keys. Although not frequently used, such relatively free table joins can be very useful when needed. For this scenario, you have two options: Use @JoinSql to declare a ManyToMany association unrelated to primary and foreign keys, then use the association property to perform the join info This approach is suitable when the corresponding join operation is needed by multiple business scenarios and has high reusability. Directly use the weak join explained in this article, without declaring any association properties between entities info This approach is suitable when the corresponding join operation is only needed by some individual business scenarios and you don't want to define a @JoinSql based association property in entities just for this purpose.","s":"The Problem to Solve","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","h":"#the-problem-to-solve","p":1215},{"i":1220,"t":"To use weak join: For Java, first implement the WeakJoin interface For Kotlin, implement the KWeakJoin abstract class Java Kotlin WeakJoin.java package org.babyfish.jimmer.sql.ast.table; import org.babyfish.jimmer.sql.ast.Predicate; public interface WeakJoin, TT extends Table> { Predicate on(ST source, TT target); } KWeakJoin.kt package org.babyfish.jimmer.sql.kt.ast.table abstract class KWeakJoin /* omit super types */ { abstract fun on( source: KNonNullTable, target: KNonNullTable ): KNonNullExpression ...other code omitted... } For Java, the generic type parameters of the WeakJoin interface should be the Table classes generated by the preprocessor for the current entity and target entity, e.g. WeakJoin For Kotlin, the generic type parameters of the KWeakJoin abstract class should be the current entity and target entity, e.g. KWeakJoin Developers need to customize a class to implement the custom table join condition: Java Kotlin private static class BookAuthorJoin implements WeakJoin { @Override public Predicate on(BookTable source, AuthorTable target) { return Predicate.and( source.businessProp1().eq(target.businessPropA()), source.businessProp2().eq(target.businessPropB()) ); } } private class BookAuthorJoin : KWeakJoin { override fun on( source: KNonNullTable, target: KNonNullTable ): KNonNullExpression = and( source.businessProp1 eq target.businessPropA, source.businessProp2 eq target.businessPropB ) } caution WeakJoin/WeakJoin is an interface, but implementation must be a class rather than a lambda expression. Do not use anonymous classes for implementation. Although anonymous classes can work, they violate the design intent here. If the class has no reuse value at all, it is recommended to define it as a private static nested class. The class itself does not have generic type parameters, but the generic parameters of the super interface/class must be explicitly specified. The reasons for the first two points will be explained later. Developers can even use NativeSQL expressions to build more arbitrary join conditions, e.g. (assuming MySQL is used here, calling the SQL function substr): Java Kotlin private static class BookAuthorJoin implements WeakJoin { @Override public Predicate on(BookTable source, AuthorTable target) { return Predicate.sql( \"substr(%e, 1, 5) = substr(%e, 1, 5)\", new Expression[] { source.code(), target.code() } ); } } private class BookAuthorJoin : KWeakJoin { override fun on( source: KNonNullTable, target: KNonNullTable ): KNonNullExpression = sql(Boolean::class, \"substr(%e, 1, 5) = substr(%e, 1, 5)\") { expression(source.code) expression(target.code) } } info Here, Predicate.sql in Java code and sql in Kotlin code are methods to mix native SQL snippets into the strongly typed Jimmer SQL DSL. We have never introduced these before, please refer to NativeSQL expressions.","s":"Define Join Condition","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","h":"#define-join-condition","p":1215},{"i":1222,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(table) .where( table .asTableEx() ❶ .weakJoin(BookAuthorJoin.class) ❷ .firstName().eq(\"Alex\") ) .select(table.id()) .distinct() .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() ❶ .weakJoin(BookAuthorJoin::class) ❷ .firstName eq \"Alex\" ) select(table.id) } .distinct() .execute(); ❶ Converts Table to TableEx using asTableEx caution The subsequent weakJoin is only supported by TableEx, not by Table. ❷ Calls weakJoin with the BookAuthorJoin class defined before as the join condition, joining to the author table Here, the return type of weakJoin is AuthorTable/KNonNullTable The following methods can be used to support outer join: Java: weakJoin(BookAuthorJoin.class, JoinType.LEFT) Kotlin: weakOuterJoin(BookAuthorJoin::class) info We have introduced a feature called Merge Conflict Join before. It is important that weakJoin is compatible with it. For the same join source, if weakJoin is called multiple times with the same WeakJoin class (the BookAuthorJoin class here), they can be merged into one join operation to avoid duplicate joins in the final SQL. This is why the BookAuthorJoin class cannot be implemented using lambda or anonymous classes, as mentioned earlier.","s":"Use the Join Condition","u":"/jimmer-doc/docs/query/dynamic-join/weak-join","h":"#use-the-join-condition","p":1215},{"i":1225,"t":"Java API uses fluent style to build DSL, whereIf is provided to add conditional where clauses without breaking the fluent chaining. Kotlin API uses lambdas to build DSL, no special API is needed to support dynamic queries. Java Kotlin public List findBooks(@Nullable String name) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); } fun findBooks(name: String?): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute() Calling findBooks(null) generates: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc Calling findBooks(\"SQL in Action\") generates: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME = ? /* SQL in Action */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Basic Usage","u":"/jimmer-doc/docs/query/dynamic-where","h":"#basic-usage","p":1223},{"i":1227,"t":"Java developers please note that in the code: .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) Even if name is null, the second parameter table.name().eq(name) would still be evaluated. This is the behavior of most programming languages. For eq (or ne), passing in null does not cause problems. eq(null) would be automatically changed to isNull(), and ne(null) would become isNotNull(). However, for most other conditional expressions, using null would cause exceptions. tip Don't worry, if you accidentally make mistakes, the exception messages are very informative to guide you to use the correct approach introduced below. For greater than or equals ge, dynamic query conditions can be added like: .whereIf( minPrice != null, () -> table.price().ge(minPrice) ) Here, a lambda expression is used to delay the expression construction until the condition is met. For Kotlin there are no such issues, no precautions needed. Let's look at a more complete example: Java Kotlin public List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( minPrice != null, () -> table.price().ge(minPrice) ) .whereIf( maxPrice != null, () -> table.price().le(maxPrice) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); } fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } minPrice?.let { where(table.price ge it) } maxPrice?.let { where(table.price le it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute()","s":"Notes for Java Developers","u":"/jimmer-doc/docs/query/dynamic-where","h":"#notes-for-java-developers","p":1223},{"i":1229,"t":"So far, the dynamic queries are based on a single table. Consider a more complex scenario where some dynamic conditions are on other tables instead of the current table (that is, those tables need to be joined first before dynamic where conditions can be added). How can this be achieved? No other higher level SQL access solutions have elegantly solved this problem, it had been a blank in the domain. Jimmer perfectly solves this difficult problem (which is the very reason Jimmer was created). We will systematically discuss this in next doc. tip In next doc you will see the uniqueness of Jimmer SQL DSL, gaining a powerful capability no other solution in the industry supports.","s":"Multi-table Operations","u":"/jimmer-doc/docs/query/dynamic-where","h":"#multi-table-operations","p":1223},{"i":1232,"t":"First, let's look at how to use static ordering to understand the ordering concepts in Jimmer: Java Kotlin public List findBooks() { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(table.name()) .orderBy(table.edition().desc()) .orderBy(table.score().desc().nullsLast()) .select(table) .execute(); } fun findBooks(): List = sqlClient .createQuery(Book::class) { orderBy(table.name) orderBy(table.edition.desc()) orderBy(table.score.desc().nullsLast()) select(table) } .execute() caution nullsFirst/nullsLast requires database support, such as Oracle. For more databases that do not support this, use case expressions in common expressions.","s":"Static Ordering","u":"/jimmer-doc/docs/query/dynamic-order","h":"#static-ordering","p":1230},{"i":1233,"t":"There are two ways to use dynamic ordering: orderByIf Ordering specified by client","s":"Dynamic Ordering","u":"/jimmer-doc/docs/query/dynamic-order","h":"#dynamic-ordering","p":1230},{"i":1235,"t":"The usage of orderByIf is similar to whereIf. info Unlike where, the order of orderBy is very sensitive, so orderByIf is not as useful as whereIf. Still, Jimmer supports orderByIf since it's the simplest and most basic usage. orderByIf is actually the Java DSL API for dynamic ordering. Java DSL uses fluent style, orderByIf is provided to avoid breaking the fluent chaining. Kotlin DSL uses lambdas so arbitrary logic can be mixed in, hence Kotlin does not need orderByIf. Assume OrderMode is an enum with values NAME and PRICE, orderByIf can be used like: Java Kotlin public List findBooks(OrderMode orderMode) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderByIf(mode == OrderMode.NAME, table.name()) .orderByIf(mode == OrderMode.PRICE, table.price()) .select(table) .execute(); } fun findBooks(orderMode: OrderMode): List = sqlClient .createQuery(Book::class) { when (orderMode) { OrderMode.NAME -> orderBy(table.name) OrderMode.PRICE -> orderBy(table.price) } select(table) } .execute()","s":"orderByIf","u":"/jimmer-doc/docs/query/dynamic-order","h":"#orderbyif","p":1230},{"i":1237,"t":"Often, the UI allows users to dynamically sort by interacting with table components. That is, the client decides the ordering and the server passively accepts parameters to query according to the sorting requirements from client. The client can specify dynamic ordering by passing string parameters, which can be converted to List needed by Jimmer using the method makeOrders. makeOrders is defined as: Java Kotlin public class Order { public static List makeOrders(Props table, String ... codes) { ...implementation omitted... } ...other code omitted... } fun KProps<*>.makeOrders(vararg codes: String): List = ...implementation omitted... Where the first parameter table is the root table in the SQL DSL. makeOrders is very flexible to use, for example: Sort by multiple columns: Java Kotlin Order.makeOrders(table, \"name\", \"edition desc\") table.makeOrders(\"name\", \"edition desc\") Merge multiple parameters into one separated by , or ;: Java Kotlin Order.makeOrders(table, \"name, edition desc\") table.makeOrders(\"name, edition desc\") info In real projects, most cases would use the single parameter form since it's the simplest. Even supports sorting by reference associations (one-to-one, many-to-one): Java Kotlin Order.makeOrders(table, \"store.city.name; store.name; name\") table.makeOrders(\"store.city.name; store.name; name\") info All dynamic join features are valid for these implicit joins. Order.makeOrders can be used like: Java Kotlin public List findBooks(String sort) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(Order.makeOrders(table, sort)) .select(table) .execute(); } fun findBooks(sort: String): List = sqlClient .createQuery(Book::class) { orderBy(table.makeOrders(sort)) select(table) } .execute() If called as findBooks(\"store.name asc, name asc\"), the generated SQL would be: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID order by tb_2_.NAME asc, tb_1_.NAME desc As can be seen, implicit joins are built for sorting criteria involving associations.","s":"Client-specified Ordering","u":"/jimmer-doc/docs/query/dynamic-order","h":"#client-specified-ordering","p":1230},{"i":1239,"t":"In the above examples, we directly convert the sorting string from client into Jimmer SQL AST orders. However, when working with Spring Data, we may need to handle Sort from Spring Data. We can write the query like this, with Sort as parameter instead of string: Java Kotlin public List findBooks(Sort sort) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(table, SpringOrders.toOrders(sort)) .select(table) .execute(); } fun findBooks(sort: Sort): List = sqlClient .createQuery(Book::class) { orderBy(sort) select(table) } .execute() This code works as: Java: Jimmer Java API provides a utility class org.babyfish.jimmer.spring.repository.SpringOrders. Its static method toOrders converts the Spring Data Sort object into the Order array in Jimmer SQL DSL. SpringOrders.toOrders takes two parameters: table: The root table in SQL DSL sort: The Spring Data Sort object After SpringOrders.toOrders converts the Sort into Order array, orderBy can be used to sort. Kotlin: Jimmer Kotlin API extends the query object to directly support sorting by the Spring Data Sort. This shows how to convert a Spring Data Sort into ordering in Jimmer. To further simplify user code, Jimmer provides the utility class org.babyfish.jimmer.spring.model.SortUtils. Its static method toSort can convert the sorting string from client into a Spring Data Sort object. For example: Java Kotlin Sort sort = SortUtils.toSort(\"name asc, edition desc\"); var sort = SortUtils.toSort(\"name asc, edition desc\") That is: +------------------------+ | Client sorting string | +-----------+------------+ | SortUtils.toSort | \\|/ +------------------------+ | Spring Data Sort | +-----------+------------+ | Java: SpringOrders.toOrders, then orderBy Kotlin: Directly orderBy with Sort object | \\|/ +------------------------+ | Ordering in Jimmer AST | +------------------------+","s":"Handling Spring Data Sort","u":"/jimmer-doc/docs/query/dynamic-order","h":"#handling-spring-data-sort","p":1230},{"i":1243,"t":"In Jimmer SQL DSL, created join objects that are not used will be ignored. For example: Java Kotlin BookTable table = Tables.BOOK_TABLE; System.out.println(\"Unused join: \" + table.store()); List books = sqlClient .createQuery(table) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { println(\"Unused join: ${table.store}\") orderBy(table.name.asc(), table.edition.desc()) select(table) } .execute() Although a JOIN object is created via table.store, since it is not used by the SQL DSL of the current query, this JOIN object will be ignored. Therefore, the final generated SQL will not contain any JOIN operations: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME = ?","s":"Basic Concepts","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#basic-concepts","p":1240},{"i":1245,"t":"In Problems with current solutions In the previous doc, we discussed solving these two scenarios by utilizing Jimmer SQL DSL's automatic merge of conflicting joins. Here, we use another approach to solve the same problems. Solve the problem in scenario 1: Java Kotlin List findBooks( @Nullable String name, @Nullable String storeName, @Nullable String storeWebsite ) { BookTable table = Tables.BOOK_TABLE; // Create JOIN object unconditionally first, // will be auto ignored if not used later, // so no useless JOIN BookStoreTable store = table.store(); return sqlClient .createQuery(table) .whereIf( name != null, () -> book.name().like(name) ) .whereIf( storeName != null, () -> store.name().like(storeName) ) .whereIf( storeWebsite != null, () -> store.website().like(storeWebsite) ) .select(book) .execute(); } fun findBooks( name: String? = null, storeName: String? = null, storeWebsite: String? = null ): List { return sqlClient .createQuery(Book::class) { // Create JOIN object unconditionally first, // will be auto ignored if not used later, // so no useless JOIN val store = table.store name?.let { where(table.name like it) } storeName?.let { where(store.name like it) } storeWebsite?.let { where(store.website like it) } select(table) } .execute() } If only name is specified, without storeName and storeWebsite, then store is a created but unused join object, thus ignored. The final generated SQL contains no joins. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME = ? If storeName and storeWebsite are specified, store will be used, leading to join operations in the final generated SQL. This is obvious so no example here. Solve the problem in scenario 2: Java Kotlin List findDistinctIds( @Nullable Long aId, @Nullable Long bId, @Nullable Long cId, @Nullable Long dId, @Nullable Long eId ) { ATable table = Tables.A_TABLE; // Create JOIN objects unconditionally first, // Not used join objects will be auto ignored, // so no useless JOIN objects BTableEx b = table.asTableEx().bs(); CTableEx c = b.cs(); DTableEx d = c.ds(); ETableEx e = d.es(); return sqlClient .createQuery(table) .whereIf( aId != null, () -> table.id().like(aId) ) .whereIf( bId != null, () -> b.id().like(bId) ) .whereIf( cId != null, () -> c.id().like(cId) ) .whereIf( dId != null, () -> d.id().like(dId) ) .whereIf( eId != null, () -> e.id().like(eId) ) .select(book.id()) .distinct() .execute(); } fun findDistinctIds( aId: Long? = null, bId: Long? = null, cId: Long? = null, dId: Long? = null, eId: Long? = null ): List { // Create JOIN object unconditionally first, // will be auto ignored if not used later, // so no useless JOIN val b = table.asTableEx().bs val c = b.cs val d = c.ds val e = d.es return sqlClient .createQuery(A::class) { aId?.let { where(table.id eq it) } bId?.let { where(b.id eq it) } cId?.let { where(c.id eq it) } dId?.let { where(d.id eq it) } eId?.let { where(e.id eq it) } select(table.id) } .distinct() .execute() } info Given the basics above, no need to list the generated SQL for different parameter combinations here. Just understand that the final SQL will not contain useless joins. When a JOIN object is used by the SQL DSL, it will be marked as \"used\" to prevent being ignored. This mark is transitive. For example: Marking d as \"used\" will naturally also mark c, b and table. asTableEx here (and various TableEx types in Java) is a concept to be introduced in later docs Pagination Safety. Please ignore it for now.","s":"Another Solution","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#another-solution","p":1240},{"i":1248,"t":"For foreign key based associations, there are two ways to filter on the associated id: Use the foreign key property directly Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .storeId() .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .storeId eq 2L ) select(table) } .execute() tip For one-to-one/many-to-one associations (like Book.store in this example), even if the user does not declare an @IdView property for the Book entity, the storeId property can still be used in SQL DSL. Join to the associated object first, then access the id property Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .store() .id() // only access id .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .store .id // only access id eq 2L ) select(table) } .execute() These two approaches are not equivalent: where(table.storeId().eq(2L)): Simply filter based on the foreign key field of the current table. where(table.store().id().eq(2L)): Actually join to the associated table first, then check the associated id value. They are not equivalent because: The foreign key may be fake, i.e. there is no corresponding foreign key constraint in the database. This will cause non-null pseudo foreign keys to be unable to fetch non-null associated objects through joining. The associated object may be affected by global filters, so it should be ignored even if it exists in the database. However, the two approaches are completely equivalent when all of the following conditions are met: The association is a one-to-one or many-to-one association based on foreign key, not through a join table or other reverse association mapping. The foreign key is real, i.e. there is a corresponding foreign key constraint in the database. See Real and Fake Foreign Keys. The associated object is not affected by global filters. Note this refers to either of: User-defined filters Logical deletion filters In this case, the id of the associated object is actually just the foreign key of the current table, so they are equivalent. info Developers should understand the difference between these two approaches and choose the right one according to the business needs. However, when the two approaches are equivalent, optimizing the second approach into the first one is very beneficial - this is called phantom join elimination. The equivalence of the two query methods is a precondition for phantom join elimination to take effect, so this will not be repeated below.","s":"Two ways to filter on associated ids","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#two-ways-to-filter-on-associated-ids","p":1240},{"i":1250,"t":"Phantom join elimination is only applicable to accessing the id property of associated objects, not other properties. Here, accessing the name property of the associated object is used as an example to demonstrate the inability to eliminate the join. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where(book.store().name().eq(\"MANNING\")) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.store.name eq \"MANNING\") select(table) } .execute() The generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ?","s":"Inapplicable Scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#inapplicable-scenarios","p":1240},{"i":1252,"t":"If only the id property of the associated object is accessed, phantom join elimination can be triggered. For example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .store() .id() // Access id only .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .store .id // Access id only eq 2L ) select(table) } .execute() This time, the generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.STORE_ID = ? We see no table join in the SQL, only a condition tb_1_.STORE_ID = ? based on the foreign key. The reason: For a many-to-one association mapped by foreign key, the parent table's id is actually the child table's own foreign key.","s":"Applicable scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#applicable-scenarios","p":1240},{"i":1254,"t":"Half joins are a concept similar to phantom joins, but for join table based associations.","s":"Half Joins","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#half-joins","p":1240},{"i":1256,"t":"For join table based associations, there are two ways to filter on the associated id: Check the foreign key field in the join table Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .asTableEx() .authorIds() .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authorIds eq 2L ) select(table) } .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. caution For one-to-many/many-to-many associations (like Book.authors in this example), *users must declare an @IdView property *for the Book entity to access the authorIds property in SQL DSL. Join to the associated object first, then access the id property Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .where( book .asTableEx() .authors() .id() // only access id .eq(2L) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authors .id // only access id eq 2L ) select(table) } .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. These two approaches are not equivalent: where(table.authorIds().eq(2L)): 1 join operation From the current table BOOK, join to BOOK_AUTHOR_MAPPING table and directly check the BOOK_AUTHOR_MAPPING.AUTHOR_ID field. where(table.authors().id().eq(2L)): 2 join operations Based on current table BOOK, join to BOOK_AUTHOR_MAPPING Based on join table BOOK_AUTHOR_MAPPING, join to AUTHOR Finally, check the AUTHOR.ID field. They are not equivalent because: The foreign key BOOK_AUTHOR_MAPPING.AUTHOR_ID may be fake, i.e. there is no corresponding foreign key constraint in the database. This will cause non-null pseudo foreign keys to be unable to fetch non-null associated objects through joining. The associated object may be affected by global filters, so it should be ignored even if it exists in the database. However, the two approaches are completely equivalent when all of the following conditions are met: The foreign key in the join table is real, i.e. there is a corresponding foreign key constraint in the database. See Real and Fake Foreign Keys. The associated object is not affected by global filters. Note this refers to either of: User-defined filters Logical deletion filters In this case, the id of the associated object is actually just the foreign key of the current table, so they are equivalent. info Developers should understand the difference between these two approaches and choose the right one according to the business needs. However, when the two approaches are equivalent, optimizing the second approach into the first one is very beneficial - this is called half join elimination. The equivalence of the two query methods is a precondition for half join elimination to take effect, so this will not be repeated below.","s":"Two ways to filter on associated ids","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#two-ways-to-filter-on-associated-ids-1","p":1240},{"i":1258,"t":"Half join elimination is only applicable to accessing the id property of associated objects, not other properties. Here, accessing the Author.firstName property of the associated object is used as an example to demonstrate the inability to eliminate the second join. Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(book) .where( book .asTableEx() .authors() .firstName() .eq(\"Alex\") ) .select(book.id()) .distinct() .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authors .firstName eq \"Alex\" ) select(table.id) } .distinct() .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. The generated SQL: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID where tb_3_.FIRST_NAME = ? We see join tables produce two SQL JOIN clauses: First step: Join to intermediate table inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID Second step: Join to target table inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID","s":"Inapplicable scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#inapplicable-scenarios-1","p":1240},{"i":1260,"t":"If only the id property of the associated object is accessed, half join elimination can be triggered. For example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(book) .where( book .asTableEx() .authors() .id() // Access id only .eq(2L) ) .select(book.id()) .distinct() .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() .authors .id // Access id only eq 2L ) select(table.id) } .distinct() .execute() note The asTableEx here has no substantial function, it will be introduced in the next doc Pagination Safety. Please ignore it for now. This time, the generated SQL: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where tb_2_.AUTHOR_ID = ? This time we only see one SQL JOIN clause instead of two. The reason: The target table's primary key is actually the foreign key from the intermediate table to the target table.","s":"Applicable scenarios","u":"/jimmer-doc/docs/query/dynamic-join/optimization","h":"#applicable-scenarios-1","p":1240},{"i":1262,"t":"Pagination safety is a feature designed for pagination, but table join functionality provides underlying support.","s":"Pagination Safety","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"","p":1261},{"i":1264,"t":"Here, we first introduce two types of associations: reference associations and collection associations. Associations decorated with @OneToOne or @ManyToOne are called reference associations. Associations decorated with @OneToMany or @ManyToMany are called collection associations. Please refer to the example: Association example","s":"Problems with Collection Associations","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#problems-with-collection-associations","p":1261},{"i":1266,"t":"If we call the entity object corresponding to the first table being queried the aggregate root object, reference associations and collection associations differ in: Joining tables via a reference association does not produce duplicate records of the current main object in the SQL query result. For example: select b.id as root_id, b.name as root_name, s.id as associated_id, s.name as associated_name from book b inner join book_store s on b.store_id = s.id where b.id = 1; The query result has no duplicate aggregate root objects: root_id root_name associated_id associated_name 1 Learning GraphQL 1 O'REILLY Joining tables via a collection association produces duplicate records of the current main object in the SQL query result: select b.id as root_id, b.name as root_name, a.id as associated_id, a.first_name as associated_first_name, a.last_name as associated_last_name from book b inner join book_author_mapping m on b.id = m.book_id inner join author a on m.author_id = a.id where b.id = 1; Query result may have duplicate aggregate root objects: root_id root_name associated_id associated_first_name associated_last_name 1 Learning GraphQL 1 Eve Procello 1 Learning GraphQL 2 Alex Banks","s":"Collection JOIN Causes Duplicate Results","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#collection-join-causes-duplicate-results","p":1261},{"i":1268,"t":"Table joins based on collection associations lead to duplicate data, which causes the following problems: Bugs if the developer forgets deduplication. Even if the developer does not forget deduplication, using java.util.LinkedHashSet for deduplication post factum is not ideal. Because the fact that the original database result contains duplicates cannot be altered, and extra network transfer and JVM data processing costs are incurred. Most importantly, unfriendly to pagination queries. Paginating table join results at the SQL level is often not what people want. More often, people want pagination applied on aggregate root objects. Take Hibernate for example. In this case, Hibernate has to abandon SQL-level pagination and use memory-level pagination instead. This performs very poorly that Hibernate logs a warning to alert developers. If you have experience with Hibernate, the log below would give you a headache: firstResult/maxResults specified with collection fetch; applying in memory tip Note that Jimmer's other feature Object Fetcher does not use table join to fetch collection associations, so it does not have this problem. Feel free to use it. In summary, using collection joins in top-level queries has obvious drawbacks, but it remains valuable to use collection joins in subqueries. Therefore, Jimmer SQL DSL has the following characteristics: info Table joins based on collection associations are prohibited in top-level queries. Table joins based on collection associations remain allowed in subqueries, update statements and delete statements.","s":"Harms of Duplicate Results","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#harms-of-duplicate-results","p":1261},{"i":1270,"t":"tip For collection associations, JOIN is actually not recommended. Implicit subqueries are more recommended. If you still want to JOIN collection association properties, please continue reading below.","s":"Implicit Subqueries","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#implicit-subqueries","p":1261},{"i":1272,"t":"There are two kinds of table objects in Jimmer SQL DSL, Table and TableEx. Table Features: Can only join via reference associations, cannot join via collection associations. Java type: org.babyfish.jimmer.sql.ast.table.Table Kotlin type: org.babyfish.jimmer.sql.kt.ast.table.KTable TableEx Features: Can join via any associations. Java type: org.babyfish.jimmer.sql.ast.table.TableEx Kotlin type: org.babyfish.jimmer.sql.kt.ast.table.KTableEx","s":"Table and TableEx","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#table-and-tableex","p":1261},{"i":1274,"t":"To implement strongly typed SQL DSL, Jimmer uses Annotation Processor (Java) or KSP (Kotlin) to generate SQL DSL related source code based on user-defined entity interfaces. Take the Book entity interface at the beginning of this article as an example. The following two types would be generated automatically: Java Kotlin Generated Java Code /* * BookTable.java */ package org.babyfish.jimmer.sql.example.model; import java.lang.Integer; import java.math.BigDecimal; import javax.persistence.criteria.JoinType; import org.babyfish.jimmer.sql.ast.Expression; import org.babyfish.jimmer.sql.ast.PropExpression; import org.babyfish.jimmer.sql.ast.table.Table; import org.babyfish.jimmer.sql.ast.table.spi.AbstractTableWrapper; public class BookTable extends AbstractTableWrapper { public BookTable(Table table) { super(table); } public Expression id() { return get(\"id\"); } public PropExpression.Str name() { return get(\"name\"); } public PropExpression.Num edition() { return get(\"edition\"); } public PropExpression.Num price() { return get(\"price\"); } public BookStoreTable store() { return join(\"store\"); } public BookStoreTable store(JoinType joinType) { return join(\"store\", joinType); } } /* * BookTableEx.java */ package org.babyfish.jimmer.sql.example.model; import javax.persistence.criteria.JoinType; import org.babyfish.jimmer.sql.ast.table.TableEx; public class BookTableEx extends BookTable implements TableEx { public BookTableEx(TableEx table) { super(table); } public AuthorTableEx authors() { return join(\"authors\"); } public AuthorTableEx authors(JoinType joinType) { return join(\"authors\", joinType); } } Generated Kotlin Code package org.babyfish.jimmer.example.kt.sql.model import java.math.BigDecimal import org.babyfish.jimmer.sql.ast.Selection import org.babyfish.jimmer.sql.kt.ast.expression.KNonNullPropExpression import org.babyfish.jimmer.sql.kt.ast.expression.KNullablePropExpression import org.babyfish.jimmer.sql.kt.ast.table.KNonNullTable import org.babyfish.jimmer.sql.kt.ast.table.KNonNullTableEx import org.babyfish.jimmer.sql.kt.ast.table.KNullableTable import org.babyfish.jimmer.sql.kt.ast.table.KNullableTableEx import org.babyfish.jimmer.sql.kt.ast.table.KTable import org.babyfish.jimmer.sql.kt.ast.table.KTableEx /* * Extension for Table */ public val KTable.id: KNullablePropExpression get() = get(\"id\") public val KNonNullTable.id: KNonNullPropExpression get() = get(\"id\") public val KTable.name: KNullablePropExpression get() = get(\"name\") public val KNonNullTable.name: KNonNullPropExpression get() = get(\"name\") public val KTable.edition: KNullablePropExpression get() = get(\"edition\") public val KNonNullTable.edition: KNonNullPropExpression get() = get(\"edition\") public val KTable.price: KNullablePropExpression get() = get(\"price\") public val KNonNullTable.price: KNonNullPropExpression get() = get(\"price\") public val KNullableTable.store: KNullableTable get() = join(\"store\") public val KNonNullTable.store: KNonNullTable get() = join(\"store\") public val KTable.`store?`: KNullableTable get() = outerJoin(\"store\") /* * Extension for TableEx */ public val KNullableTableEx.authors: KNullableTableEx get() = join(\"authors\") public val KNonNullTableEx.authors: KNonNullTableEx get() = join(\"authors\") public val KTableEx.`authors?`: KNullableTableEx get() = outerJoin(\"authors\") Observing the two auto-generated types, we can see: BookTableEx inherits BookTable. BookTable does not support collection associations, but supports regular fields and reference associations (which is store in this example). BookTableEx adds support for collection associations (which is authors in this example). Therefore, jimmer-sql API follows this pattern: Top-level queries can only be created based on Table. Subqueries, update statements and delete statements can be created based on either Table or TableEx. Next, we demonstrate the contrast between top-level queries and subqueries with examples.","s":"Generated Code","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#generated-code","p":1261},{"i":1276,"t":"So your code looks like: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where( table .name() // Can access regular field name .eq(\"Book Name\") ) .where( table .store() // Can also join reference association store .name() .eq(\"Store Name\") ) /* * However, cannot use \"table.authors()\" because `authors()` * is defined in `BookTableEx` instead of `BookTable`. * * That is, joining collection associations is prohibited * at compile time in top-level queries. */ .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { where( table .name // Can access regular field name eq \"Book Name\" ) where( table .store // Can also join reference association `store` .name eq \"Store Name\" ) /* * However, cannot use \"table.authors\" because the extension property `authors` * is defined on `TableEx` instead of `Table`. * * That is, joining collection associations is prohibited * at compile time in top-level queries. */ select(table) } .execute() info Java: createQuery takes parameter specified by user, can only be Table type. TableEx would error. Kotlin: createQuery creates table object automatically. The automatic variable table in lambda is inferred to Table instead of TableEx. The final generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.NAME = ? and tb_2_.NAME = ?","s":"Top-Level Queries Must Be Based on Table","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#top-level-queries-must-be-based-on-table","p":1261},{"i":1278,"t":"Unlike top-level queries, subqueries, update statements and delete statements allow TableEx. In the example below, Author.books is the same as Book.authors discussed above, which is also a many-to-many association. Java Kotlin BookTable table = Tables.BOOK_TABLE; // `author` used in subquery, use TableEx AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(table) .where(sqlClient .createSubQuery(author) .where( author // `author` is TableEx, // so collection association `books` is allowed .books() .eq(table), author.firstName().eq(\"Alex\") ) .exists() ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { // In parent query `table` is Table where( exists( wildSubQuery(Author::class) { // Subquery's `table` overrides parent's `table`, // and the Subquery's `table` is `TableEx` where( table // Subquery's `table` is TableEx, // so collection association `books` is allowed .books eq parentTable, table.firstName.eq(\"Alex\") ) } ) ) select(table) } .execute() info Java: createSubQuery takes parameter specified by user, not enforced but suggested to be TableEx type. Kotlin: wildSubQuery (or subQuery) creates table object automatically. The automatic variable table in lambda is inferred to TableEx instead of Table. The final generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where exists( select 1 from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and tb_2_.FIRST_NAME = ? )","s":"TableEx Allowed for Subqueries","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#tableex-allowed-for-subqueries","p":1261},{"i":1280,"t":"Prohibiting collection associations in top-level queries is reasonable in most cases, but not all cases. For example, the user does not query entire objects, but individual fields, and uses the SQL keyword distinct to offset the side effects of joining collection associations. This scenario is perfectly reasonable. Therefore, prohibiting collection associations in top-level queries is a soft constraint rather than a hard constraint. It can be easily overridden. Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookIds = sqlClient .createQuery(book) .where( book .asTableEx() ❶ .authors() .firstName() .ilike(\"A%\") ) .select(book.id()) .distinct() ❷ .execute(); val bookIds = sqlClient .createQuery(Book::class) { where( table .asTableEx() ❶ .authors .firstName ilike \"A%\" ) select(table.id) } .distinct() ❷ .execute() info ❶ The developer informs Jimmer that they know what they are doing, asking Jimmer to allow joining collection associations. ❷ The developer takes responsibility for their own actions. If there are additional operations here, it should be distinct rather than pagination related. The final generated SQL: select distinct tb_1_.ID from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID inner join AUTHOR as tb_3_ on tb_2_.AUTHOR_ID = tb_3_.ID where lower(tb_3_.FIRST_NAME) like ?","s":"asTableEx","u":"/jimmer-doc/docs/query/dynamic-join/table-ex","h":"#astableex","p":1261},{"i":1282,"t":"info Readers cannot find anything related to global filters in this doc, because the filter required for logical deletion is built-in and hidden by Jimmer.","s":"Logical Deletion","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"","p":1281},{"i":1284,"t":"Logical deletion, also known as soft deletion, means data is not actually deleted from the database. Instead, data is hidden to give the illusion of deletion. This leaves room for recovering from accidental operations. The mapping related to logical deletion is introduced in great detail in Mapping / Advanced Mapping / Logical Deletion, so all the details are not repeated here, just a brief recap: Java Kotlin Book.java @Entity public interface Book { @LogicalDeleted(\"true\") boolean isDeleted(); ...other code omitted... } Book.kt @Entity interface Book { @LogicalDeleted(\"true\") val isDeleted: Boolean ...other code omitted... }","s":"Mapping","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#mapping","p":1281},{"i":1287,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.DELETED, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.DELETED <> ? /* true */","s":"Filter root entity","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#filter-root-entity","p":1281},{"i":1289,"t":"Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(author) .select( author.fetch( Fetchers.AUTHOR_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ) ) .execute(); val authors = sqlClient .createQuery(Author::class) { select( table.fetchBy { allScalarFields() books { allScalarFields() } } ) } .execute() Without caching enabled, this generates two SQLs: Query root entity select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ Query associated objects, apply logical deletion filter select tb_2_.AUTHOR_ID, tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where tb_2_.AUTHOR_ID in ( ? /* 1 */, ? /* 2 */, ? /* 3 */, ? /* 4 */, ? /* 5 */ ) and tb_1_.DELETED <> ? /* true */","s":"Filter associated objects","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#filter-associated-objects","p":1281},{"i":1291,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .filters(cfg -> { ❶ cfg.setBehavior(LogicalDeletedBehavior.IGNORED); ❷ }) .createQuery(table) .select(table) .execute(); val books = sqlClient .filters { ❶ cfg.setBehavior(LogicalDeletedBehavior.IGNORED) } .createQuery(table) .select(table) .execute() ❶ Adjust filter config without affecting the current sqlClient, create a new temporary sqlClient ❷ Ignore soft deletion flag This time, the generated SQL no longer contains: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.DELETED, tb_1_.STORE_ID from BOOK tb_1_","s":"Ignore Logical Deletion Filter","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#ignore-logical-deletion-filter","p":1281},{"i":1293,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .filters(cfg -> { ❶ cfg.setBehavior(LogicalDeletedBehavior.REVERSED); ❷ }) .createQuery(table) .select(table) .execute(); val books = sqlClient .filters { ❶ cfg.setBehavior(LogicalDeletedBehavior.REVERSED) } .createQuery(table) .select(table) .execute() ❶ Adjust filter config without affecting the current sqlClient, create a new temporary sqlClient ❷ Reverse the soft deletion flag, i.e. query deleted data Executing again, the generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.DELETED, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.DELETED = ? /* true */ This time the filter condition is tb_1_.DELETED = true, which is the exact opposite of the default filtering rule - it queries already deleted data.","s":"Reverse Logical Deletion Filter","u":"/jimmer-doc/docs/query/global-filter/logical-deleted","h":"#reverse-logical-deletion-filter","p":1281},{"i":1295,"t":"Global filters are used to automatically add filtering conditions for an entity type. Most queries for the entity type will automatically have related where conditions added. This feature has the following application scenarios: Multi-perspective data. Querying data requires query conditions related to user identity, even if all query parameters except user identity are the same, different users will see different data. Multi-perspective data has a typical case: multi-tenancy. This document uses multi-tenancy as an example to explain custom global filters defined by users. Logical deletion Logical deletion is a built-in global filter in Jimmer and does not require user definition. note For users with Hibernate background knowledge, global filters are similar to org.hibernate.annotations.Where, org.hibernate.annotations.Filter and org.hibernate.annotations.FilterDef. The difference is that Jimmer's global filters have flexible registration methods and are very easy to be managed by IOC frameworks (such as Spring). Thus, global filters can directly obtain parameters from the IOC framework, such as user identity information, so developers do not need to pass parameters to filters before queries. caution After repeated consideration, currently global filters only affect the main table of the top-level query, and have no effect on tables obtained from join operations and tables in subqueries. This has no impact on object fetchers because object fetchers are not table Join operations. Jimmer provides some simple APIs to query entities (or collections of entities) by id (or collection of ids). These APIs are exceptional and are not affected by global filters.","s":"Global Filters","u":"/jimmer-doc/docs/query/global-filter/","h":"","p":1294},{"i":1298,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; long count = sqlClient .createQuery(table) .where(table.name().ilike(\"graphql\")) .select( table .asTableEx().authors().id() .count(true) // distinct: true ) .fetchOne(); val count = sqlClient .createQuery(Book::class) { where(table.name.ilike(\"graphql\")) select( count( table.asTableEx().authors.id, distinct = true ) ) } .fetchOne() The generated SQL is: select count(distinct tb_2_.AUTHOR_ID) from BOOK tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where lower(tb_1_.NAME) like ? /* %graphql% */","s":"Aggregation","u":"/jimmer-doc/docs/query/group","h":"#aggregation","p":1296},{"i":1300,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List> tuples = sqlClient .createQuery(table) .groupBy(table.storeId()) ❶ .select( table.storeId(), ❷ table.price().avg() ❸ ) .execute(); val tuples: List> = sqlClient .createQuery(Book::class) { groupBy(table.store.id) ❶ select( table.store.id, ❷ avg(table.price).asNonNull() ❸ ) } .execute() ❶ Group by STORE_ID, the foreign key of BOOK table info Here Jimmer does not treat table.store as a join operation, but considers table.store.id as a whole as the foreign key field. Please see phantom joins. ❷ Grouping columns can be directly queried. ❸ Non-grouping columns can only be queried as parameters of aggregate functions. caution The Kotlin code has an extra function call: asNonNull(). In Jimmer Kotlin DSL, aggregate functions like avg (also sum, min, max) return Nullable types. For a table with no data, aggregating any column would return null without grouping. However this is not the case when used with grouping. After grouping, each group has at least one row internally, if the original field being aggregated is non-null itself, the result after aggregation would not be null. So here asNonNull() converts the Nullable expression to NonNull, such that execute() returns List>, same as the type explicitly specified for tuples in the first line. If asNonNull() is removed, execute() would return List>, causing compile error.","s":"Grouping","u":"/jimmer-doc/docs/query/group","h":"#grouping","p":1296},{"i":1302,"t":"Native SQL expressions are an important feature to leverage database-specific capabilities, as database products always have proprietary features.","s":"Native SQL Expressions","u":"/jimmer-doc/docs/query/native-sql","h":"","p":1301},{"i":1304,"t":"This example shows how to use regular expression matching in Oracle and HSQLDB: Java Kotlin AuthorTable table = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(table) .where( Predicate.sql( \"regexp_like(%e, %v)\", it -> it .expression(table.firstName()) .value(\"^Ste(v|ph)en$\") ) ) .select(table) .execute(); val authors = sqlClient .createQuery(Author::class) { where( sql(Boolean::class, \"regexp_like(%e, %v)\") { expression(table.firstName) value(\"^Ste(v|ph)en$\") } ) select(table) } .execute() info In the Java code, Predicate.sql is called to create a query condition based on native SQL. In fact, other expression types also support native SQL expressions. There are 5 sql functions: Predicate.sql(...) Expression.string().sql(...) Expression.numeric().sql(...) Expression.comparable().sql(...) Expression.any().sql(...) Kotlin does not have this issue, its API is unified. The first parameter of sql(...) is the SQL template string, which can contain special symbols %e and %v: %e: Expression, to embed an expression %v: Value, to embed a value The second parameter of sql(...) is optional, a lambda expression whose parameter is an object supporting two methods: expression(Expression): Embed an expression, corresponding to %e in SQL template. value(Object): Embed a value, corresponding to %v in SQL template. The final generated SQL is: select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR as tb_1_ where regexp_like(tb_1_.FIRST_NAME, ?)","s":"Example 1: Regular Expression Matching","u":"/jimmer-doc/docs/query/native-sql","h":"#example-1-regular-expression-matching","p":1301},{"i":1306,"t":"Let's look at another example using analytic functions: Java Kotlin List> tuples = sqlClient .createQuery(table) .select( table, Expression.numeric().sql( Integer.class, \"rank() over(order by %e desc)\", table.price() ), Expression.numeric().sql( Integer.class, \"rank() over(partition by %e order by %e desc)\", new Expression[] { table.storeId(), table.price() } ) ) .execute(); val tuples = sqlClient .createQuery(Author::class) { select( table, sql(Int::class, \"rank() over(order by %e desc)\") { expression(table.price) }, sql(\"rank() over(partition by %e order by %e desc)\") { expression(table.store.id) expression(table.price) } ) } .execute() Three columns are queried here: First column: Book object Second column: The rank of the book price among all books Third column: The rank of the book price within its store The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID, rank() over( order by tb_1_.PRICE desc ), rank() over( partition by tb_1_.STORE_ID order by tb_1_.PRICE desc ) from BOOK tb_1_","s":"Example 2: Analytic Functions","u":"/jimmer-doc/docs/query/native-sql","h":"#example-2-analytic-functions","p":1301},{"i":1309,"t":"tip One statement to query data structure of arbitrary shape, like GraphQL The object fetcher is an important feature of Jimmer that automatically fetches specified fields and assembles them into objects, saving a lot of time writing manual conversion logic. The object fetcher is similar to the following technologies, but more powerful: JPA's EntityGraph ADO.NET EntityFramework's include ActiveRecord's include Although the code to return entire objects in queries is simple, the default object format often does not meet development needs very well. It is easy to encounter two problems: Over fetching problem Object properties that we don't need are queried, causing waste, especially when there are many object fields. Take JPA as an example. The returned object by default is a complete object that contains non-associative properties that are not needed. This is a big problem for traditional ORMs (JPA's @Basic(fetch = FetchType.LAZY) is designed for LOB column, it cannot be used by any column). Under fetching problem The object properties we need have not been fetched and are in an unavailable unloaded state, causing the program to fail to run correctly. The object fetcher solves this problem very well by allowing users to specify properties to fetch, and then utilizing the characteristics of dynamic objects to make the returned objects from the query neither over fetched nor under fetched. By using the object fetcher, it is easy to specify the return format of queries, because dynamic objects can describe data structures of any shape. You can decide whether a certain business perspective needs to query some entities, associations, or even every properties.","s":"Concept","u":"/jimmer-doc/docs/query/object-fetcher/","h":"#concept","p":1307},{"i":1311,"t":"Java Kotlin Your browser does not support the video tag. Your browser does not support the video tag. info Compare to GraphQL GraphQL is based on HTTP services, which can only be experienced if it crosses the boundaries of HTTP services. In Jimmer, this is the underlying API for ORM, and you can use this capability in any code logic. Until now, the GraphQL protocol does not support recursive queries on self-associated properties with infinite depth; And Jimmer supports","s":"Examples","u":"/jimmer-doc/docs/query/object-fetcher/","h":"#examples","p":1307},{"i":1313,"t":"Collection (one-to-many or many-to-many) associations often lead to the frequent use of subqueries in queries, and implicit subqueries greatly simplify such subqueries. For complete normal subqueries, see Normal Subqueries.","s":"Implicit Subquery","u":"/jimmer-doc/docs/query/implicit-subquery","h":"","p":1312},{"i":1315,"t":"Taking the many-to-many association Book.authors as an example, after compilation, Jimmer will generate the following code: Java Kotlin BookTable.java @GeneratedBy(type = Book.class) public class BookTable extends AbstractTypedTable implements BookProps { @Override public Predicate authors(Function block) { ...implementation logic omitted... } } fun KProps.authors( block: KNonNullTableEx.() -> KNonNullExpression? ): KNonNullExpression? = ...implementation logic omitted... Users can build implicit subqueries based on this authors method. The parameter of this method is a lambda expression whose parameter is the table object of the associated object. Users can return an SQL condition to filter the associated object.","s":"DSL Code generated by Jimmer","u":"/jimmer-doc/docs/query/implicit-subquery","h":"#dsl-code-generated-by-jimmer","p":1312},{"i":1317,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; public List findBooks(@Nullable String authorName) { return sqlClient .createQuery(table) .whereIf( authorName != null && !authorName.isEmpty(), table.authors(author -> { return Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ); }) ) .select(table) .execute(); } fun findBooks(authorName: String?): List = sqlClient.createQuery(Book::class) { authorName?.takeIf { it.isNotEmpty() }?.let { where += table.authors { or( firstName ilike it, lastName ilike it ) } } }.execute() When calling the above method and specifying a non-null parameter, for example findBooks(\"alex\"), the generated SQL is: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where exists( ➊ select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID ➋ and ( lower(tb_2_.FIRST_NAME) like ? /* %alex% */ ➌ or lower(tb_2_.LAST_NAME) like ? /* %alex% */ ➍ ) ) ➊ Implicit subqueries always use exists ➋ The SQL condition auto-generated by Jimmer for associating parent-child queries ➌ ➍ Conditions specified by users to filter associated objects tip The association condition between parent-child queries is auto-generated. Users only need to specify the filtering condition for the associated object. This is the fundamental difference between implicit subqueries and normal subqueries.","s":"Demo","u":"/jimmer-doc/docs/query/implicit-subquery","h":"#demo","p":1312},{"i":1319,"t":"Similar to the automatic merge of dynamic JOINs, multiple implicit subqueries for the same association can also be automatically merged. caution The merge rules for implicit subqueries are not as universal as dynamic JOINs. They are limited to within the same and, or, or not. For example: Java Kotlin BookTable table = Tables.BOOK_TABLE; public List findBooks( @Nullable String authorName, @Nullable Gender authorGender ) { return sqlClient .createQuery(table) .whereIf( authorName != null && !authorName.isEmpty(), table.authors(author -> { return Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ); }) ) .whereIf( authorGender != null, table.authors(author -> author.gender().eq(authorGender)) ) .select(table) .execute(); } fun findBooks(authorName: String?): List = sqlClient.createQuery(Book::class) { authorName?.takeIf { it.isNotEmpty() }?.let { where += table.authors { or( firstName ilike it, lastName ilike it ) } } authorGender?.let { where += table.authors { gender like it } } }.execute() The above example uses two implicit subqueries. However, when we specify both parameters as non-null, for example findBooks(\"alex\", Gender.MALE), there will only be one subquery in the final SQL, as follows: select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where // Merge two implicit subqueries to one real sub query exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %alex% */ or lower(tb_2_.LAST_NAME) like ? /* %alex% */ ) and tb_2_.GENDER = ? /* M */ ) This is because within the same and, or or not, multiple implicit subqueries for the same association are automatically merged.","s":"Automatic Merge","u":"/jimmer-doc/docs/query/implicit-subquery","h":"#automatic-merge","p":1312},{"i":1321,"t":"Previously we introduced using object fetchers to flexibly control the shape of queried data structures. Now we introduce an equivalent capability: querying DTO objects. Jimmer provides a DTO language tip This language is essentially another way to express object fetchers. Using this language, developers can quickly define various data structure shapes with an entity type as the aggregate root. The compiler will generate corresponding Java/Kotlin DTO classes for each defined shape. Each DTO type contains mutual conversion logic with the original dynamic type, and an object fetcher matching its own shape. In some cases, after the server queries data in a certain shape, it is not meant to be returned as an HTTP response, but rather used internally to drive subsequent complex business logic. This is an ideal scenario for this approach. caution Note that if the server queries data in a certain shape not for its own use, but directly as the HTTP response, it is more recommended to directly return the dynamic entity object and use the solutions in Generate Client Code to automatically generate client code with a great developer experience.","s":"Querying DTOs","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"","p":1320},{"i":1323,"t":"This article focuses on explaining how to query static DTO types, not a systematic introduction to the DTO language itself. Please refer to Object section/DTO Mapping/DTO Language for the complete DTO language. Assuming the fully qualified name of the Book class is com.yourcompany.yourproject.model.Book, you can In the project where the entity is defined, create the directory src/main/dto Under src/main/dto, create subdirectories following the package path of the entity type com/yourcompany/yourproject/model In the directory created in the previous step, create a file Book.dto. The file name must match the entity class name, and the extension must be dto Edit this file, use the DTO language to define various DTO shapes for the Book entity Book.dto BookDetailView { #allScalars store { #allScalars } authors { #allScalars } } SimpleBookView { ...omitted... } ...Omit definitions of other DTO shapes...","s":"Defining DTO Shapes","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#defining-dto-shapes","p":1320},{"i":1325,"t":"Jimmer is responsible for compiling dto files and automatically generating DTO types matching these shapes. caution If Java/Kotlin source code files other than dto files are modified, running the application directly from the IDE can trigger recompilation of dto files. However, if no Java/Kotlin files other than dto files are modified, simply clicking the run button in the IDE does not cause dto files to be recompiled unless explicitly rebuilding! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle Taking BookDetailView in the above code as an example, after the dto file is successfully compiled by Jimmer, the following DTO type will be automatically generated: Java Kotlin BookDetailView.java package com.yourcompany.yourproject.model.dto; import com.yourcompany.yourproject.model.Book; import org.babyfish.jimmer.View; @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookDetailView implements View { private long id; private String name; private int edition; private BigDecimal price; private TargetOf_store store; private List authors; public static class TargetOf_store implements View { private long id; private String name; @Nullable private String website; ...other members omitted... } public static class TargetOf_authors implements View { private long id; private String firstName; private String lastName; private Gender gender; ...other members omitted... } ...other members omitted... } BookDetailView.kt package com.yourcompany.yourproject.model.dto import com.yourcompany.yourproject.model.Book import org.babyfish.jimmer.View @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookDetailView( val id: Long = 0, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val store: TargetOf_store? = null, val authors: List = emptyList(), ) : View { data class TargetOf_store( val id: Long = 0, val name: String = \"\", val website: String? = null, ) : View { ...other members omitted... } data class TargetOf_authors( val id: Long = 0, public val firstName: String = \"\", public val lastName: String = \"\", public val gender: Gender, ) : View { ...other members omitted... } ...other members omitted... } info The generated DTO classes are in the dto subpackage of the entity package, not the entity package itself. For Java, it is assumed lombok is already in use.","s":"Auto-generated DTO Types","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#auto-generated-dto-types","p":1320},{"i":1328,"t":"Java Kotlin BookDetailView view = sqlClient.findNullable( BookDetailView.class, 1L ); System.out.println(view); val view = sqlClient.findNullable( BookDetailView::class, 1L ); println(view) The printed result is as follows (formatted manually for readability): BookDetailView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookDetailView.TargetOf_store( id=1, name=O'REILLY, website=null, version=0 ), authors=[ BookDetailView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookDetailView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) It's easy to see that although dynamic entity objects are no longer returned, the functionality is exactly the same as object fetchers. Why is this? The DTO types generated from the DTO language all contain object fetchers matching their own shapes, as follows: Java Kotlin BookDetailView.java @Data public class BookDetailView implements View { public static final ViewMetadata METADATA = new ViewMetadata( Fetchers.BOOK_FETCHER .name() .edition() .price() .store(TargetOf_store.METADATA.getFetcher()) .authors(TargetOf_authors.METADATA.getFetcher()), BookDetailView::new ); @Data public static class TargetOf_store implements View { public static final ViewMetadata METADATA = new ViewMetadata( Fetchers.BOOK_STORE_FETCHER .name() .website() .version(), TargetOf_store::new ); ...other members omitted... } @Data public static class TargetOf_authors implements View { public static final ViewMetadata METADATA = new ViewMetadata( Fetchers.AUTHOR_FETCHER .firstName() .lastName() .gender(), TargetOf_authors::new ); ...other members omitted... } ...other members omitted... } BookDetailView.kt @Data data class BookDetailView( ...omitted... ) : View { ...other members omitted... companion object { @JvmStatic public val METADATA: ViewMetadata = ViewMetadata( newFetcher(Book::class).by { name() edition() price() store(TargetOf_store.METADATA.fetcher) authors(TargetOf_authors.METADATA.fetcher) } ) { CompositeBookInput(it) } } @Data public static class TargetOf_store implements View { ...other members omitted... companion object { @JvmStatic val METADATA: ViewMetadata = ViewMetadata( newFetcher(BookStore::class).by { name() website() } ) { TargetOf_store(it) } } } @Data public static class TargetOf_authors implements View { ...other members omitted... companion object { @JvmStatic val METADATA: ViewMetadata = ViewMetadata( newFetcher(Author::class).by { firstName() lastName() gender() } ) { TargetOf_authors(it) } } } } tip This is why this article says at the beginning that the DTO language is essentially another way to express object fetchers.","s":"Using findById","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#using-findbyid","p":1320},{"i":1330,"t":"Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.name()) .orderBy(table.edition().desc()) .select( table.fetch(BookDetailView.class) ) .execute() val books = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.name) orderBy(table.edition.desc()) select( table.fetch(BookDetailView::class) ) } .execute() Here we see that table.fetch(fetcher) in previous code is replaced with table.fetch(BookDetailView.class). tip All low-level query APIs can replace fetcher with viewType, again proving that the DTO language is essentially another way to express object fetchers, as stated at the beginning.","s":"Using Custom Queries","u":"/jimmer-doc/docs/query/object-fetcher/dto","h":"#using-custom-queries","p":1320},{"i":1333,"t":"First, provide MappedSuperclass for all entities that need multi-tenancy management to inherit: Java Kotlin TenantAware.java @MappedSuperclass public interface TenantAware { String tenant(); } TenantAware.kt @MappedSuperclass interface TenantAware { val tenant: String } Any entity that needs multi-tenancy support can inherit TenantAware, such as Book: Java Kotlin Book.java @Entity public interface Book extends TenantAware { ...Other code omitted... } Book.kt @Entity interface Book : TenantAware { ...Other code omitted... } tip Certainly, it's possible to apply filters directly to entity types without defining the abstract type, this works fine. However, it is better to extract the abstract type from entities, so one filter can apply to multiple entity types. More importantly, MappedSuperclass supports multiple inheritance, i.e. entities can inherit from multiple supertypes. Multi-inheritance combined with global filters brings amazing flexibility.","s":"Provide Abstract Mapped Superclass","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#provide-abstract-mapped-superclass","p":1331},{"i":1335,"t":"Assume there is an object of type TenantProvider in the Spring context. Its Java method get() and Kotlin property tenant are used to extract the tenant of the current operator from identity info. Define the filter as follows: In Java, filter need to implement org.babyfish.jimmer.sql.filter.Filter. In Kotlin, filter need to implement org.babyfish.jimmer.sql.kt.filter.KFilter. If using Spring management, the code is: Java Kotlin @Component public class TenantFilter implements Filter { private final TenantProvider tenantProvider; public TenantFilter(TenantProvider tenantProvider) { this.tenantProvider = tenantProvider; } @Override public void filter(FilterArgs args) { String tenant = tenantProvider.get(); if (tenant != null) { args.where(args.getTable().tenant().eq(tenant)); } } } @Component class TenantFilter( private val tenantProvider: TenantProvider ) : KFilter { override fun filter(args: KFilterArgs) { tenantProvider.tenant?.let { args.apply { where(table.tenant.eq(it)) } } } } There are slight differences in filter definition between Java and Kotlin: In Java, the generic type of Filter is TenantAwareProps, which is part of the code auto-generated by the precompiler for the abstract type TenantAware. In Kotlin, the generic type of KFilter is the abstract type TenantAware itself. TenantFilter filters the abstract type TenantAware. For any entity that inherits the abstract interface TenantAware directly or indirectly, its queries will be handled by this filter, automatically adding a where condition. Inside TenantFilter, it first extracts the tenant of the current operator from identity info. If the tenant is non-null, use it to filter data, querying only data that matches the specified tenant.","s":"Define Filter","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#define-filter","p":1331},{"i":1337,"t":"In the above, the defined class TenantFilter is decorated with @Component, obviously a Spring-managed object. info If using Jimmer's Spring Boot Starter and ensuring the filter is Spring-managed, Jimmer will auto-register it without extra configuration. Otherwise, must manually register.","s":"Configure Filter in Spring","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#configure-filter-in-spring","p":1331},{"i":1339,"t":"In this case, the filter class does not need to be decorated with @Component, attach the filter to the SqlClient object for it to take effect: Java Kotlin JSqlClient sqlClient = JSqlBuilder .newBuilder() .addFilter(new CustomerFilter()) ...Other config omitted... .build(); val sqlClient = newKSqlClient { addFilters(new CustomerFilter()) ...Other config omitted... }","s":"Configure Filter Without Spring","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#configure-filter-without-spring","p":1331},{"i":1341,"t":"Filtering aggregate roots is the simplest use of global filters. Since Book entity inherits from TenantAware, its queries will be affected by this filter. Java Kotlin List books = sqlClient.getEntities.findAll(Book.class); val books = sqlClient.entities.findAll(Book::class); or Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select(book) .execute(); val books = SqlClient .createQuery(Book::class) { select(table) } .execute() The generated SQL: select tb_1_.ID, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.TENANT = ? Obviously, the query here is very simple without any query parameters. But the final SQL still filters on tb_1_.TENANT.","s":"Filter Aggregate Root Objects","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#filter-aggregate-root-objects","p":1331},{"i":1343,"t":"Not only aggregate roots can be filtered, associated objects can be filtered too: Java Kotlin List authors = sqlClient.getEntities.findAll( Fetchers.AUTHOR_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ); val books = sqlClient.entities.findAll( newFetcher(Author::class).by { allScalarFields() books { allScalarFields() } } ); or Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(author) .select( author.fetch( Fetchers.AUTHOR_FETCHER .allScalarFields() .books( Fetchers.BOOK_FETCHER .allScalarFields() ) ) ) .execute(); val authors = SqlClient .createQuery(Author::class) { select( table.fetchBy { allScalarFields() books { allScalarFields() } } ) } .execute() This generates two SQL statements: Query aggregate roots: select tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR as tb_1_ Query associated objects: select tb_2_.AUTHOR_ID, tb_1_.ID, tb_1_.TENANT, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.BOOK_ID where tb_2_.AUTHOR_ID in (?, ?, ?, ?, ?) and tb_1_.TENANT = ?","s":"Filter Associated Objects","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#filter-associated-objects","p":1331},{"i":1345,"t":"Calling sqlClient.filters creates a new temporary SqlClient without affecting the current sqlClient, which can be used to disable filters: Java Kotlin JSqlClient tmpSqlClient = sqlClient.filters(it -> { it .disableByTypes(TenantFilter.class); }); val tmpSqlClient = sqlClient.filters { disableByTypes(TenantFilter::class) } Here we get a temporary tmpSqlClient. Queries created from it will ignore the filter we demonstrated above.","s":"Disable Filters","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#disable-filters","p":1331},{"i":1347,"t":"In addition to the basic Filter/KFilter interface, filter classes can also implement more interfaces, including: CacheableFilter/KCacheableFilter AssociationIntegrityAssuranceFilter/AssociationIntegrityAssuranceFilter ShardingFilter/KShardingFilter","s":"More filter interfaces","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#more-filter-interfaces","p":1331},{"i":1349,"t":"Global filters show different data to different users, and for any associated property that takes the filtered type as the target type, different users will naturally see different associations. This will lead to: These association properties cannot apply simple Association Cache Dependent calculated properties also cannot enable Calculated Cache To solve this problem, Jimmer supports Multi-View CacheCacheableFilterKCacheableFilterCache/Multi-view Cache/User Defined Cacheable Filters","s":"CacheableFilter","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#cacheablefilter","p":1331},{"i":1351,"t":"The full name of this interface is: Java: org.babyfish.jimmer.sql.filter.AssociationIntegrityAssuranceFilter

Kotlin: org.babyfish.jimmer.sql.kt.filter.KAssociationIntegrityAssuranceFilter Compared to the basic Filter/KFilter interface, this interface does not add any new methods, it is only used as a type identifier. For one-to-one/many-to-one association properties based on foreign keys, even if the field is set to a non-null type and has a real foreign key constraint, the associated object queried may still be null due to the filter. Therefore, Jimmer stipulates that if the associated entity of a one-to-one/many-to-one association property is affected by the filter, the association property must be declared as nullable. The AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter allows the user to make a commitment to the characteristics of the database data to break this restriction. First, let the filter class implement this interface Java Kotlin @Component public class TenantFilter implements AssociationIntegrityAssuranceFilter { ... } @Component class TenantFilter( ... ) : KAssociationIntegrityAssuranceFilter { ... } Then, let BookStore inherit TenantAware Java Kotlin @Entity public interface Book extends TenantAware { ... } @Entity interface Book : TenantAware { ... } Finally, let Book also inherit TenantAware, and define a non-null many-to-one association property Book.store Java Kotlin @Entity public interface Book extends TenantAware { @ManyToOne // Not null BookStore store(); ... } @Entity interface Book : TenantAware { val store: BookStore // NotNull ... } The following code analysis: Book and BookStore both inherit TenantAware, that is, both sides of the association are controlled by the filter TenantFilter TenantFilter implements the AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter interface. This interface is the user's commitment to the characteristics of the database data, committing that only objects that follow the same filtering rules will have associations. For this example, it means that only BookStore and Book objects belonging to the same tenant are associated, and BookStore and Book objects belonging to different tenants will never be associated. Only under the user's commitment can the many-to-one association Book.store be set to non-null. In summary, if the associated type of a one-to-one/many-to-one association property is affected by the filter, in order to set this property to non-null, the following two conditions must be met at the same time: All global filters applied to the associated entity implement the AssociationIntegrityAssuranceFilter/KAssociationIntegrityAssuranceFilter interface. All global filters applied to the associated entity are also applied to the current entity.","s":"AssociationIntegrityAssuranceFilter","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#associationintegrityassurancefilter","p":1331},{"i":1353,"t":"The full name of this interface is: Java: org.babyfish.jimmer.sql.filter.ShardingFilter

Kotlin: org.babyfish.jimmer.sql.kt.filter.KShardingFilter Compared to the basic Filter/KFilter interface, this interface does not add any new methods, it is only used as a type identifier. Jimmer provides simple APIs to query entity/entities by id/ids. By default, these APIs are special - they ignore global filters. Queries by id ignoring filters are correct since ids uniquely identify objects. However, if sharding-jdbc is used at the JDBC level, and the field used as filter condition is the sharding field in sharding-jdbc, querying by id alone would cause sharding-jdbc to query multiple shards, which is disastrous. To solve this, make the filter implement ShardingFilter (Java) or KShardingFilter (Kotlin). These interfaces have no behaviors, just for type marking. Once a filter inherits ShardingFilter or KShardingFilter, these simple APIs will no longer ignore the filter. This ensures the final SQL contains the sharding field required by sharding-jdbc, querying only one shard instead of all shards.","s":"Sharding Filters","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#sharding-filters","p":1331},{"i":1355,"t":"When user-defined filters and cache are used together, a problem called \"multi-view cache\" is involved. Since we haven't introduced cache yet, we'll just make a brief note here. Please refer to Cache/Multi-view Cache for details.","s":"Multi-view Cache","u":"/jimmer-doc/docs/query/global-filter/user-filter","h":"#multi-view-cache","p":1331},{"i":1357,"t":"We have introduced that object fetchers can flexibly control the shape of queried data structures, bringing tremendous flexibility for application development. We also know there are two completely equivalent ways to use them: Directly use object fetchers and return dynamic entity objects Use the DTO language to define output DTO shapes, auto-generate related Java/Kotlin types and entity conversion logic, as well as the object fetcher corresponding to the shape. Jimmer provides a Spring Boot Starter and is integrated with Spring Data. Object fetchers are also integrated into Spring Data. Relevant documentation links: Directly using object fetchers Use object fetchers in abstract queries Use object fetchers in complex queries @FetchBy annotation to auto-generate strictly typed client code Using DTO language Query DTO objects with Spring Data","s":"Working with Spring Data","u":"/jimmer-doc/docs/query/object-fetcher/spring-data","h":"","p":1356},{"i":1360,"t":"Scalar fields refer to all non-associative fields in a database table. Taking fetching the book name as an example: Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER.name() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name() } ) } .execute() note For Java, the Annotation processor will automatically generate a Fetcher class for each entity interface, which is BookFetcher in this example. The generated SQL is: select tb_1_.ID, tb_1_.NAME from BOOK as tb_1_ where tb_1_.EDITION = ? note The Java code does not call the id() method of BookFetcher, but we can see the SQL statement still queries the id property of the object. The id property is treated specially and will always be queried, not controlled by object fetchers. In fact, the auto-generated BookFetcher class does not even have an id() method, because it is not needed. The printed result is (original output is compact, formatted here for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\" }, ...Other objects omitted... ]","s":"Fetching Scalar Fields","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#fetching-scalar-fields","p":1358},{"i":1362,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER .name() .edition() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name() edition() } ) } .execute() info Object fetchers are immutable objects, each method call returns a new object fetcher. In the Java code above: Fetchers.BOOK_FETCHER Fetchers.BOOK_FETCHER.name() Fetchers.BOOK_FETCHER.name().edition() are three different object fetchers, each immutable. Object fetchers can be freely shared using static variables since they are immutable. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION from BOOK as tb_1_ where tb_1_.EDITION = ? The printed result is (original output is compact, formatted here for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":1 }, ...Other objects omitted... ]","s":"Fetching Multiple Fields","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#fetching-multiple-fields","p":1358},{"i":1364,"t":"In some scenarios, fetching all non-associative fields is a very common operation, so allScalarFields() is provided to load all non-associative fields. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER.allScalarFields() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() } ) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? The printed result is (original output is compact, formatted here for readability): { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00 } // Other objects omitted info allScalarFields() only loads non-associative fields. In the example we can see it queries id, name, edition, price, but does not query the association properties store and authors. Fetching association properties will be covered in the next document.","s":"Fetching All Scalar Fields","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#fetching-all-scalar-fields","p":1358},{"i":1366,"t":"The previously discussed properties are positive properties that incrementally add fields to query. But in some cases, we only need to exclude some specific fields, while querying all other fields. This is when negative properties can be used to exclude unneeded fields. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .edition(false) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() edition(false) } ) } .execute() edition(false) uses false as a parameter, making it a negative property. The properties of allScalarFields() are id + name + edition + price edition(false) means -edition So in combination, the finally fetched properties are id + name + price info For positive properties, edition() and edition(true) are equivalent When most properties need to be fetched and only a few excluded, using allScalarFields with negative properties can be very useful The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? The printed result is (original output is compact, formatted here for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"price\":51.00 // `edition` is not here }, ...Other objects omitted... ]","s":"Negative Properties","u":"/jimmer-doc/docs/query/object-fetcher/props","h":"#negative-properties","p":1358},{"i":1369,"t":"tip One statement to query data structure of arbitrary shape, like GraphQL Before understanding object fetchers, it is necessary to first understand conventional property queries. For example, I need a SQL like this: select b.id, b.name, b.edition /* Don't need `b.price` and `b.store_id` */ from book b where b.edition = 3; In this SQL, we only query a part of columns. The corresponding Jimmer code is: Java Kotlin BookTable table = Tables.BOOK_TABLE; List> tuples = sqlClient .createQuery(book) .where(table.edition().eq(3)) .select( table.id(), table.name(), table.edition() ) .execute(); System.out.println(tuples); val tuples = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.id table.name table.edition ) } .execute() println(tuples) The printed output is (formatted for readability): [ { \"_1\" : 3, \"_2\" : \"Learning GraphQL\", \"_3\" : 3 } ...Other objects omitted ] info Since a part of object properties are queried, select(table) cannot be simply used. Instead, select(expr1, expr2, ..., expr3) is required. However, this results in tuples being returned instead of objects. In the tuples, the property order corresponds to the select() order. In the above example, the mapping in each tuple is: _1 -> id _2 -> name _3 -> edition If we want to return objects, one choice is to define a BookDTO type (assuming lombok is used for Java): Unlike the original Book entity type, BookDTO only contains the properties we need rather than all properties. Java Kotlin BookDTO.java @Data public class BookDTO { private long id; private String name; private int edition; } BookDTO.kt data class BookDTO( val id: Long, val name: String, val edition: Int ) There are two ways to convert the tuples to BookDTO objects: Keep previous code unchanged, first query Tuple3 collection, then convert using Stream API Use Jimmer's utility API to directly transform the query result Here we use the second approach: Java Kotlin BookTable table = Tables.BOOK_TABLE; List bookDTOs = sqlClient .createQuery(book) .where(table.edition().eq(3)) .select( table.id(), table.name(), table.edition() ) .map(tuple -> { BookDTO dto = new BookDTO(); dto.setId(tuple.get_1()); dto.setName(tuple.get_2()); dto.setEdition(tuple.get_3()); return dto; }); System.out.println(bookDTOs); val bookDTOs = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.id table.name table.edition ) } .map { BookDTO(it._1, it._2, it._3) } println(tuples) The result after conversion is the type we want: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"edition\" : 3 } ...Other objects omitted ] JPA and MyBatis make this kind of choice: JPA returns all scalar properties of an object by default. If you want to customize the returned properties, Either use HQL: select new BookDTO(...) from ... Or use query.unwrap(SQLQuery.class).setResultTransformer(Transformers.aliasToBean(DTO.class)) MyBatis needs to write a ResultMapper corresponding to the DTO. However, neither JPA nor MyBatis can avoid having to write an additional DTO class and take on the logic of transforming from the query structure to the DTO object themselves. info Unfortunately Query business often has diversity, and inevitable format diversity means more DTO types (as aggregate root types there may be format diversity issues, and as associated types of other DTOs it will be easier to lead to format diversity issues). This eventually leads to DTO explosion problem For JPA, this goes against the original intention of ORM: convenience Next, we'll use Jimmer's object fetcher to simplify this process.","s":"Why Introduce Object Fetchers","u":"/jimmer-doc/docs/query/object-fetcher/usage","h":"#why-introduce-object-fetchers","p":1367},{"i":1371,"t":"For each entity interface, Jimmer generates a corresponding Fetcher class. These Fetchers are object fetchers. Based on the fetched properties, object fetchers automatically package objects, eliminating the need to manually map and write additional DTO classes. note The Annotation processor will automatically generate a Fetcher class for each entity interface, which is BookFetcher in this example. Example 1: The query in the above example can be written as an object fetcher: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient.createQuery(table) .where(table.edition().eq(3)) .select( table.fetch( Fetchers.BOOK_FETCHER // id is implicit, mandatory .name() .edition() ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { // id is implicit, mandatory name edition } ) } .execute() println(books) As you can see, the return value is of type Book, no need for further mapping, which saves a lot of time for daily coding. The output is as follows: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"edition\" : 3 }, ...Other objects omitted... ] Example 2 We can modify the code a little, not fetching the book edition, but fetching the book price: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient.createQuery(table) .where(table.edition().eq(3)) .select( table.fetch( Fetchers.BOOK_FETCHER .name() .price() ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name price } ) } .execute() println(books) The JSON output now is: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"price\" : 51.00 }, ...Other objects omitted... ] Example 3 You can even query associated objects Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient.createQuery(table) .where(table.edition().eq(3)) .select( table.fetch( Fetchers.BOOK_FETCHER .name() .authors( Fetchers.AUTHOR_FETCHER .firstName() ) ) ) .execute(); System.out.println(books); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { name authors { firstName } } ) } .execute(); println(books) The JSON output now is: [ { \"id\" : 3, \"name\" : \"Learning GraphQL\", \"authors\": [ { \"id\": 1, \"Eve\" }, { \"id\": 2, \"Alex\" }, ] }, ...Other objects omitted... ] tip With the dynamicity of Jimmer entities, there is no need to write additional DTOs to achieve diversified query business, just change the shape of the object fetcher. For the output data of the query, eliminating DTO explosion problem can greatly improve server-side productivity.","s":"Using Object Fetchers","u":"/jimmer-doc/docs/query/object-fetcher/usage","h":"#using-object-fetchers","p":1367},{"i":1373,"t":"When object fetchers are used to fetch association properties, they are similar to JPA's EntityGraph, but have the following differences: Object fetchers use batch-load strategy to load associated objects, not JPA's join-fetch concept. This is important because: Fetching collection associations does not break paginated queries like JPA's EntityGraph. More friendly to association cache and remote associations. JPA's EntityGraph only controls association properties, but object fetchers can control any properties, same as GraphQL, with precision down to each property. For infinite recursive structures caused by self-associated properties, object fetchers support recursive query.","s":"Differences from JPA EntityGraph","u":"/jimmer-doc/docs/query/object-fetcher/usage","h":"#differences-from-jpa-entitygraph","p":1367},{"i":1376,"t":"Let's first look at an example (this query has no real business logic, just for demo): Java Kotlin BookTable book = Tables.BOOK_TABLE; List< Tuple5< String, Long, OffsetDateTime, String, Boolean > > tuples = sqlClient .createQuery(book) .select( Expression.string().value(\"String\"), Expression.numeric().value(3L), Expression.comparable().value(OffsetDateTime.now()), Expression.any().value(\"String\"), Expression.nullValue(Boolean.class) ) .execute(); val tuples = sqlClient .createQuery(Book::class) { select( value(\"String\"), value(3L), value(OffsetDateTime.now()), value(\"String\"), nullValue(Boolean::class) ) } .execute() The generated SQL is: select ?, ?, ?, ?, null from BOOK as tb_1_ Except for null, literals of other types all become JDBC parameters. caution As can be seen from this example, the value() method accepts many parameter types. Note that no matter what the value() parameter type is, it cannot be null, otherwise exceptions would be thrown. To create literal expressions for null, the nullValue() method must be used which requires the expression type to be specified. info For Java code, type-guided methods are used: Expression.string(), for string type. Expression.numeric(), for numeric types. Expression.comparable(), for comparable types, i.e. types extending java.lang.Comparable. Expression.any(), for other types. Kotlin does not have this issue, its API is unified. tip In most cases, developers do not need to manually create literal expressions. Take equality check in examples below for instance, the relatively tedious syntax: Java Kotlin where( book.name().eq( Expression.string().value(\"Java in Action\") ) ); where( table.name eq value(\"Java in Action\") ) Isn't this a bit tedious? Don't worry, it can be replaced with a more convenient form: Java Kotlin where(book.name().eq(\"Java in Action\")); where(table.name eq \"Java in Action\") It's easy to see other APIs provide overloaded versions to avoid making developers create literal expressions manually. But this can't cover 100% cases. In very rare cases, developers still need to create literal expressions manually.","s":"Literal Expressions","u":"/jimmer-doc/docs/query/expression","h":"#literal-expressions","p":1374},{"i":1378,"t":"Constant expressions are highly similar to literal expressions, let's look at an example (this query has no real business logic, just for demo): Java Kotlin BookTable book = Tables.BOOK_TABLE; List constants = sqlClient .createQuery(book) .select( Expression.constant(1) ) .execute(); val constants = sqlClient .createQuery(Book::class) { select( constant(1) ) } .execute() The generated SQL is: select 1 from BOOK as tb_1_ Unlike literal expressions that always use JDBC parameters, constant expressions directly hardcode the value into the SQL. To prevent SQL injection attacks, constant expressions only support numeric types, this is a hard constraint. info Although constant expressions have this hard constraint of only supporting numeric types to prevent SQL injection, they should still be strictly limited in real projects. The only reason constant expressions exist is that some databases support function-based indexes. Constant expressions can be useful if the SQL expressions defining such function indexes contain numeric constants. If your project does not have this scenario, never use constant expressions. Always use literal expressions. Incorrect use of constant expressions can have serious consequences. Erroneously planting unstable numeric variables as constant expressions into SQL will break the stability of the SQL string, eventually leading to extremely low hit rates of execution plan cache in the database, impacting performance.","s":"Constant Expressions","u":"/jimmer-doc/docs/query/expression","h":"#constant-expressions","p":1374},{"i":1380,"t":"Initially, Jimmer supported dynamic queries through whereIf: Java Kotlin public List findBooks( @Nullable String name, @Nullable Integer edition ) { BookTable table = BookTable.$; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), () -> table().name().ilike(name) ) .whereIf( edition != null, table().edition().eq(edition) ) .select(table) .execute(); } fun findBooks( name: String? = null, edition: Int? = null ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } edition?.let { where(table.edition eq it) } select(table) } .execute() Although whereIf has good readability, the code is relatively cumbersome. Later, Jimmer provided dynamic predicates, which simplified the above code to: Java Kotlin public List findBooks( @Nullable String name, @Nullable Integer edition ) { BookTable table = BookTable.$; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .where(table.edition().eqIf(edition)) .select(table) .execute(); } fun findBooks( name: String? = null, edition: Int? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.name `eq?` edition) select(table) } .execute() Here, ilikeIf, eqIf in Java and ilike?, eq? in Kotlin are called dynamic predicates. When the right operand is null or an empty string (string of length 0), the dynamic predicate does not create an expression and directly returns null. The where call can automatically ignore null, thereby achieving an equivalent dynamic query. info Compared to the initial whereIf, the value of dynamic predicates is not in simplifying the code but in accommodating more complex scenarios, such as or: Java Kotlin public List findBooksByNameOrPriceRange( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ) { BookTable table = BookTable.$; return sqlClient .createQuery(table) .where( Predicate.or( table.name().eqIf(name), table.price().betweenIf(minPrice, maxPrice) ) ) .select(table) .execute(); } fun findBooksByNameOrPriceRange( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null ): List = sqlClient .createQuery(Book::class) { where( or( table.name `eq?` name, table.price.`between?`(minPrice, maxPrice) ) ) select(table) } .execute() Here, all the arguments of or are dynamic predicates, meaning each argument of or can be null, and or can also ignore null arguments. Of course, if all arguments are null, then or itself will refuse to create any expression and directly return null. Here are all the static predicates and dynamic predicates in Jimmer: Static Predicate Dynamic Predicate (Java) Dynamic Predicate (Kotlin) eq eqIf `eq?` ne neIf `ne?` lt ltIf `lt?` le leIf `le?` gt gtIf `gt?` ge geIf `ge?` like likeIf `like?` ilike ilikeIf `ilike?` between betweenIf `between?` Q: Why does Jimmer provide two sets of predicates instead of just providing dynamic predicates? A: Because static predicates also handle null specially: eq: automatically converted to isNull() ne: automatically converted to isNotNull() Other static predicates: Java: Treats this as a bug in the user's code, requiring the user to either provide a non-null value or switch to a dynamic predicate. Kotlin: Prevents the user from providing potentially null values at compile-time. info We have clearly discussed the concept of dynamic predicates. To simplify subsequent discussions, the rest of this content will only demonstrate static predicates.","s":"Static Predicates vs Dynamic Predicates","u":"/jimmer-doc/docs/query/expression","h":"#static-predicates-vs-dynamic-predicates","p":1374},{"i":1382,"t":"Equals Java Kotlin where(book.name().eq(\"SQL in Action\")); where(table.name eq \"SQL in Action\") Not equals Java Kotlin where(book.name().ne(\"SQL in Action\")); where(table.name ne \"SQL in Action\") Greater than Java Kotlin where(book.price().gt(new BigDecimal(50))); where(table.price gt BigDecimal(50)) Greater than or equals Java Kotlin where(book.price().ge(new BigDecimal(50))); where(table.price ge BigDecimal(50)) Less than Java Kotlin where(book.price().lt(new BigDecimal(50))); where(table.price lt BigDecimal(50)) Less than or equals Java Kotlin where(book.price().le(new BigDecimal(50))); where(table.price le BigDecimal(50)) Between Java Kotlin where( book.price().between( new BigDecimal(40), new BigDecimal(50) ) ); where( table.price.between( BigDecimal(40), BigDecimal(50) ) ) Not Between Java Kotlin where( book.price().notBetween( new BigDecimal(40), new BigDecimal(50) ) ); where( table.price.notBetween( BigDecimal(40), BigDecimal(50) ) )","s":"Comparison","u":"/jimmer-doc/docs/query/expression","h":"#comparison","p":1374},{"i":1385,"t":"like: case sensitive Java Kotlin where(book.name().like(\"Ab\")); where(table.name like \"Ab\") The generated SQL condition is: where tb_1_.NAME like ? The corresponding JDBC parameter is: %Ab% ilike: case insensitive Java Kotlin where(book.name().ilike(\"Ab\")); where(table.name ilike \"Ab\") The generated SQL condition is: If ilike is supported by dialect where tb_1_.NAME ilike ? Otherwise where lower(tb_1_.NAME) like ? The corresponding JDBC parameter is: %ab%","s":"Case Sensitivity","u":"/jimmer-doc/docs/query/expression","h":"#case-sensitivity","p":1374},{"i":1387,"t":"LikeMode.ANYWHERE (default behavior without specifying): appears anywhere Java Kotlin where(book.name().like(\"Ab\", LikeMode.ANYWHERE)); where(table.name.like(\"Ab\", LikeMode.ANYWHERE)) The corresponding JDBC parameter is: %Ab% LikeMode.START: as prefix Java Kotlin where(book.name().like(\"Ab\", LikeMode.START)); where(table.name.like(\"Ab\", LikeMode.START)) The corresponding JDBC parameter is: Ab% LikeMode.END: as suffix Java Kotlin where(book.name().like(\"Ab\", LikeMode.END)); where(table.name.like(\"Ab\", LikeMode.END)) The corresponding JDBC parameter is: %Ab LikeMode.EXACT: exact match Java Kotlin where(book.name().like(\"Ab\", LikeMode.EXACT)); where(table.name.like(\"Ab\", LikeMode.EXACT)) The corresponding JDBC parameter is: Ab","s":"Match Modes","u":"/jimmer-doc/docs/query/expression","h":"#match-modes","p":1374},{"i":1389,"t":"Java Kotlin where(book.store().isNull()); where(table.store.isNull()) Java Kotlin where(book.store().isNotNull()); where(table.store.isNotNull())","s":"Null Check","u":"/jimmer-doc/docs/query/expression","h":"#null-check","p":1374},{"i":1392,"t":"Java Kotlin where( book.name().in( Arrays.asList( \"SQL in Action\", \"Java in Action\" ) ) ); where( table.name valueIn listOf( \"SQL in Action\", \"Java in Action\" ) ) The generated SQL condition is: where tb_1_.NAME in (?, ?)","s":"Single Column","u":"/jimmer-doc/docs/query/expression","h":"#single-column","p":1374},{"i":1394,"t":"Java Kotlin where( Expression.tuple( book.name(), book.edition() ).in( Arrays.asList( new Tuple2<>(\"SQL in Action\", 1), new Tuple2<>(\"SQL in Action\", 2), new Tuple2<>(\"Java in Action\", 1), new Tuple2<>(\"Java in Action\", 2) ) ) ); where( tuple( table.name, table.edition ) valueIn listOf( Tuple2(\"SQL in Action\", 1), Tuple2(\"SQL in Action\", 2), Tuple2(\"Java in Action\", 1), Tuple2(\"Java in Action\", 2) ) ) The generated SQL condition is: where (tb_1_.NAME, tb_1_.EDITION) in ( (?, ?), (?, ?), (?, ?), (?, ?) ) note Besides used with collections, in can also be used with subqueries. This will be covered in detail in docs about subqueries.","s":"Multiple Columns","u":"/jimmer-doc/docs/query/expression","h":"#multiple-columns","p":1374},{"i":1396,"t":"Jimmer provides 3 optimizations for the in list expression: Single value optimization Padding optimization Any equality optimization Single value optimization When the list length is 1, in(?) will be automatically rewritten as = ?, and not in(?) will be automatically rewritten as <> ?. For example: Java Kotlin where( Expression.tuple( book.name(), book.edition() ).in( Arrays.asList( new Tuple2<>(\"SQL in Action\", 1) ) ) ); where( tuple( table.name, table.edition ) valueIn listOf( Tuple2(\"SQL in Action\", 1) ) ) The generated SQL condition: where (tb_1_.NAME, tb_1_.EDITION) = (? /* SQL in Action */, ? /* 1 */) Padding optimization To support padding optimization, Jimmer provides a switch that can be enabled in two ways: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-padding-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListPaddingEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListPaddingEnabled(true) // ...omitted other configurations... } Once this switch is enabled, Jimmer will ensure that the list length is a power of 2 (2, 4, 6, 8, 16, 32, ...), thereby significantly reducing the diversity of SQL and increasing the diversity of database execution plan caching. For example: Java Kotlin where( Expression.tuple( book.name(), book.edition() ).in( Arrays.asList( new Tuple2<>(\"SQL in Action\", 1), new Tuple2<>(\"SQL in Action\", 2), new Tuple2<>(\"Java in Action\", 1) ) ) ); where( tuple( table.name, table.edition ) valueIn listOf( Tuple2(\"SQL in Action\", 1), Tuple2(\"SQL in Action\", 2), Tuple2(\"Java in Action\", 1) ) ) In this example, the list length is 3, which is not a power of 2. The nearest power of 2 to 3 is 4, so Jimmer will repeat the last item in the list, eventually making the list length 4. The generated SQL condition is as follows: where (tb_1_.NAME, tb_1_.EDITION) in ( // Original list (? /* SQL in Action */, ? /* 1 */), (? /* SQL in Action */, ? /* 2 */), (? /* Java in Action */, ? /* 1 */), // Repeat the last item in the original list // to make the list length a power of 2 (? /* Java in Action */, ? /* 1 */) ) Any equality optimization This optimization is better tested by the previously discussed padding optimization, but it has two limitations: Currently, it can only optimize single column in The database needs to support the = any(?) expression, i.e., the isAnyEqualityOfArraySupported() method of the implementation class of org.babyfish.jimmer.sql.dialect.Dialect needs to return true Currently, the dialects that support this behavior are: org.babyfish.jimmer.sql.dialect.H2Dialect org.babyfish.jimmer.sql.dialect.PostgresDialect For this, Jimmer provides a switch that can be enabled in two ways: If you are using the Jimmer Spring Boot Starter, modify application.yml (or application.properties) as follows: application.yml jimmer: in-list-to-any-equality-enabled: true If you are not using the Jimmer Spring Boot Starter, you need to call the following API when creating the sqlClient: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setInListToAnyEqualityEnabled(true) // ...omitted other configurations... .build(); val sqlClient = newKSqlClient { setInListToAnyEqualityEnabled(true) // ...omitted other configurations... } warning If the current org.babyfish.jimmer.sql.dialect.Dialect implementation class's isAnyEqualityOfArraySupported() method returns false (does not support this feature), this configuration will cause an exception, and the sqlClient cannot be created, and the application cannot start. Java Kotlin where( book.name().in( Arrays.asList( \"SQL in Action\", \"Java in Action\" ) ) ); where( table.name valueIn listOf( \"SQL in Action\", \"Java in Action\" ) ) The generated SQL condition: where tb_1_.NAME = any( ? /* [SQL in Action, Java in Action] */ ) Here, the entire list is treated as a whole and passed as an array-type parameter.","s":"Optimization","u":"/jimmer-doc/docs/query/expression","h":"#optimization","p":1374},{"i":1399,"t":"Java Kotlin where( Predicate.and( book.name().like(\"Ab\"), book.price().ge(new BigDecimal(40)), book.price().lt(new BigDecimal(60)) ) ); where( and( table.name like \"Ab\", table.price ge BigDecimal(40), table.price lt BigDecimal(60) ) ) note Note that when the logical AND expression is directly used as the where parameter, the following equivalent forms are more recommended: Use varargs version of where method Java Kotlin where( book.name().like(\"Ab\"), book.price().ge(new BigDecimal(40)), book.price().lt(new BigDecimal(60)) ); where( table.name like \"Ab\", table.price ge BigDecimal(40), table.price lt BigDecimal(60) ) Call where multiple times Java Kotlin q.where(book.name().like(\"Ab\")); q.where(book.price().ge(new BigDecimal(40))); q.where(book.price().lt(new BigDecimal(60))); where(table.name like \"Ab\") where(table.price ge BigDecimal(40)) where(table.price lt BigDecimal(60)) So directly using and would not be common in real projects.","s":"AND","u":"/jimmer-doc/docs/query/expression","h":"#and","p":1374},{"i":1401,"t":"Java Kotlin where( Predicate.or( book.name().like(\"Ab\"), book.price().ge(new BigDecimal(40)), book.price().le(new BigDecimal(60)) ) ); where( or( table.name like \"Ab\", table.price ge BigDecimal(40), table.price le BigDecimal(60) ) )","s":"OR","u":"/jimmer-doc/docs/query/expression","h":"#or","p":1374},{"i":1403,"t":"Java Kotlin where( book.name().like(\"Ab\").not() ); where( not(table.name like \"Ab\") ); It's not always necessary to call the not() function. Often there are shortcuts available, such as: .eq(value).not() can be simplified to .ne(value) .isNull().not() can be simplified to .isNotNull(value) .exists().not() can be simplified to .notExists() (exists will be introduced in subqueries) Even when developers explicitly use not(), the final SQL may not contain NOT. For example: Java Kotlin where( book.price().ge(new BigDecimal(40)).not() ); where( not(book.price ge BigDecimal(40)) ) The actual generated SQL is: where tb_1_1.PRICE < ? Jimmer-sql tries to avoid directly using NOT in SQL, but the final logic is equivalent to what you want.","s":"NOT","u":"/jimmer-doc/docs/query/expression","h":"#not","p":1374},{"i":1405,"t":"+ Java Kotlin select(book.price().plus(BigDecimal.TWO)); select(table.price + BigDecimal.TWO) - Java Kotlin select(book.price().minus(BigDecimal.TWO)); select(table.price - BigDecimal.TWO) * Java Kotlin select(book.price().times(BigDecimal.TWO)); select(table.price * BigDecimal.TWO) / Java Kotlin select(book.price().div(BigDecimal.TWO)); select(table.price / BigDecimal.TWO) % Java Kotlin select(book.price().rem(BigDecimal.TWO)); select(table.price % BigDecimal.TWO)","s":"Math Operations","u":"/jimmer-doc/docs/query/expression","h":"#math-operations","p":1374},{"i":1407,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List< Tuple6< Long, Long, BigDecimal, BigDecimal, BigDecimal, BigDecimal > > tuples = sqlClient .createQuery(book) .select( book.count(), book.id().count(/* distinct */ true), book.price().sum(), book.price().min(), book.price().max(), book.price().avg() ) .execute(); val tuples = sqlClient .createQuery(Book::class) { select( count(table), count(table.id, distinct = true), sum(table.price), min(table.price), max(table.price), avg(table.price) ); } .execute() The final generated SQL is: select count(tb_1_.ID), count(distinct tb_1_.ID), sum(tb_1_.PRICE), min(tb_1_.PRICE), max(tb_1_.PRICE), avg(tb_1_.PRICE) from BOOK as tb_1_","s":"Aggregate Functions","u":"/jimmer-doc/docs/query/expression","h":"#aggregate-functions","p":1374},{"i":1409,"t":"The Coalesce statement specifies a list of expressions and returns the first non-null value. Java Kotlin BookStoreTable store = Tables.BOOK_STORE_TABLE; List results = sqlClient .createQuery(store) .select( store.website() ❶ .coalesceBuilder() .or(store.name()) ❷ .or(\"Default Value\") ❸ .build() ) .execute(); var results = sqlClient .createQuery(BookStore::class) { select( table.website .coalesce() ❶ .or(table.name) ❷ .end() ) } tip In this example, the Kotlin code is different from the Java code. In Kotlin there is no expression ❸. The Kotlin API introduces null-safety for SQL, table.name is a non-null field, so Kotlin forces us to write end() to complete the expression. This means the expression ❸ in Java code will not be used. The generated SQL is: SQL for Java SQL for Kotlin select coalesce( tb_1_.WEBSITE, tb_1_.NAME, ? ) from BOOK_STORE as tb_1_ select coalesce( tb_1_.WEBSITE, tb_1_.NAME ) from BOOK_STORE as tb_1_ Specifically, if the SQL coalesce function has only two parameters, i.e. or() is called only once in the Java code above, there is a shortcut: Java Kotlin BookStoreTable store = Tables.BOOK_STORE_TABLE; List results = sqlClient .createQuery(store) .select( store.website().coalesce(store.name()) ) .execute(); var results = sqlClient .createQuery(BookStore::class) { select( table.website.coalesce(table.name) ) } The generated SQL is: select coalesce(tb_1_.WEBSITE, tb_1_.NAME) from BOOK_STORE as tb_1_ This form is actually the most common.","s":"Coalesce","u":"/jimmer-doc/docs/query/expression","h":"#coalesce","p":1374},{"i":1411,"t":"The Contact expression concatenates strings. This example concatenates firstName and lastName of authors with a space as separator: Java Kotlin AuthorTable author = Tables.AUTHOR_TABLE; List results = sqlClient .createQuery(author) .select( author .firstName() .concat( Expression.string().value(\" \"), author.lastName() ) ) .execute(); var fullNames = sqlClient .createQuery(Author::class) { select( concat( table.firstName, value(\" \"), table.lastName ) ) } .execute() The generated SQL is: select concat( tb_1_.FIRST_NAME, ?, tb_1_.LAST_NAME ) from AUTHOR as tb_1_","s":"Concat","u":"/jimmer-doc/docs/query/expression","h":"#concat","p":1374},{"i":1413,"t":"There are two types of case expressions, simple case and searched case.","s":"Case","u":"/jimmer-doc/docs/query/expression","h":"#case","p":1374},{"i":1415,"t":"For simple case, an expression is specified at the beginning. Each WHEN branch specifies an expected value to check if the expression matches that value. Java Kotlin BookTable book = Tables.BOOK_TABLE; List results = sqlClient .createQuery(book) .select( Expression.string() .caseBuilder(book.name()) .when(\"Java in Action\", \"Matched\") .when(\"SQL in Action\", \"Matched\") .otherwise(\"Not matched\") ) .execute(); val results = sqlClient .createQuery(Book::class) { select( case(table.name) .match(\"Kotlin in Action\", \"Matched\") .match(\"SQL in Action\", \"Matched\") .otherwise(\"Not matched\") ) } .execute() The generated SQL is: select case tb_1_.NAME when ? then ? when ? then ? else ? end from BOOK as tb_1_","s":"Simple Case","u":"/jimmer-doc/docs/query/expression","h":"#simple-case","p":1374},{"i":1417,"t":"For searched case, no expression is specified at the beginning. Each WHEN branch can specify an arbitrary complex conditional expression to check if any branch logic evaluates to true. Java Kotlin BookTable book = Tables.BOOK_TABLE; List results = sqlClient .createQuery(book) .select( Expression.string() .caseBuilder() .when( book.price().lt(new BigDecimal(30)), \"Cheap\" ) .when( book.price().gt(new BigDecimal(70)), \"Expensive\" ) .otherwise(\"Appropriate\") ) .execute(); val results = sqlClient .createQuery(Book::class) { select( case() .match(table.price lt BigDecimal(30), \"Cheap\") .match(table.price gt BigDecimal(70), \"Expensive\") .otherwise(\"Appropriate\") ) } .execute() The generated SQL is: select case when tb_1_.PRICE < ? then ? when tb_1_.PRICE > ? then ? else ? end from BOOK as tb_1_","s":"Searched Case","u":"/jimmer-doc/docs/query/expression","h":"#searched-case","p":1374},{"i":1419,"t":"In this series of articles, we will introduce Jimmer's smart paging. Surprisingly simple Sufficiently optimized","s":"Smart Paging","u":"/jimmer-doc/docs/query/paging/","h":"","p":1418},{"i":1421,"t":"Pagination queries have a problem - when the data volume is large, if the pagination range is too far back (i.e. offset is too large), performance issues can occur. Therefore, Jimmer supports deep pagination optimization. Set a threshold offset-optimizing-threshold for the pagination offset. Once the offset reaches this threshold, the implementation of the pagination query is changed.","s":"Deep Pagination Optimization","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"","p":1420},{"i":1423,"t":"Using Spring Boot Starter: Modify application.yml (or application.properties), add config item offset-optimizing-threshold: jimmer: offset-optimizing-threshold: 1000 Using low-level API: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setOffsetOptimizingThreshold(1000) ...Other config omitted... .build(); val sqlClient = newKSqlClient { setOffsetOptimizingThreshold(1000) ...Other config omitted... } info If this threshold is not set, the default is Integer.MAX_VALUE, meaning this feature is disabled.","s":"Set Threshold","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"#set-threshold","p":1420},{"i":1425,"t":"To discuss this feature, focusing on the data query instead of the count query is sufficient. Let's look at this simple pagination query: Java Kotlin public List findBooks(int limit, int offset) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .select(table) .limit(limit, offset) .execute(); } fun findBooks(limit: Int, offset: Int): List = sqlClient.createQuery(Book::class) { select(table) } .limit(limit, offset) .execute() Pagination query support differs for different dialects. Oracle is more complex. See Pagination/Usage#Dialects. To simplify discussion, assume using org.babyfish.jimmer.sql.H2Dialect. Pagination queries under it generate simple SQL: When offset is less than 1000, e.g. calling findBooks(10, 90), the generated SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ limit ? /* 10 */ offset ? /* 90 */ When offset is greater than or equal to 1000, e.g. calling findBooks(10, 1000), the generated SQL: select optimize_.ID, optimize_.NAME, optimize_.EDITION, optimize_.PRICE, optimize_.STORE_ID from ( select tb_1_.ID optimize_core_id_ from BOOK tb_1_ limit ? /* 10 */ offset ? /* 1000 */ ) optimize_core_ inner join BOOK optimize_ on optimize_.ID = optimize_core_.optimize_core_id_ As you can see, when offset is too large, Jimmer queries ids of the page first, then converts the ids to objects. This is useful when data volume is large.","s":"Effectiveness","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"#effectiveness","p":1420},{"i":1427,"t":"For some databases (e.g. MySQL), if data volume is large, performance is poor even when querying the first page (offset is 0). In this case, simply set offset-optimizing-threshold to 0 directly.","s":"Set to 0","u":"/jimmer-doc/docs/query/paging/deep-optimization","h":"#set-to-0","p":1420},{"i":1430,"t":"As page numbers increase, pagination query efficiency drops. To solve this, Jimmer supports reverse sorting optimization. Reverse sorting optimization takes effect only when the following prerequisites are met together: This feature does not apply to queries that only care about in-page data regardless of total row count before pagination, i.e. limit(limit, offset). It must be queries that care about both in-page data and total count. The template query must have explicit orderBy clause. The queried page data is late relative to all data before pagination. I.e. offset + pageSize / 2 > totalCount / 2 When all above conditions are met, Jimmer flips the sorting of the template query. Because a forward sorting query with relatively large page number and a reverse sorting query with relatively small page number are equivalent.","s":"Concept","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#concept","p":1428},{"i":1432,"t":"Let's look at an example. Java Kotlin public Page findBooks( int pageIndex, int pageSize ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .fetchPage(pageIndex, pageSize); } fun findBooks( pageIndex: Int, pageSize: Int ): Page = sqlClient .createQuery(Book::class) { orderBy(table.name.asc(), table.edition.desc()) select(table) } .fetchPage(pageIndex, pageSize) Assume there are 12 Book records total. pageSize is 2, so there are 6 pages. pageIndex has 5 possible values: 0, 1, 2, 3, 4, 5. 0, 1, 2: Data to query is early, use forward sorting pagination. 3, 4, 5: Data to query is late, use reverse sorting pagination. Next we demonstrate the difference between reverse and forward sorting pagination with pageIndex=2 and pageIndex=3 as examples.","s":"Example","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#example","p":1428},{"i":1434,"t":"Executing findBooks(2, 2) generates the forward sorting SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 2 */ offset ? /* 4 */ The result is: { \"rows\":[ { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81, \"store\":{ \"id\":2 } }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2 } } ], \"totalCount\":12, \"totalPage\":6 }","s":"Forward Sorting","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#forward-sorting","p":1428},{"i":1436,"t":"Executing findBooks(3, 2) generates the reverse sorting SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME desc, // Reversed: asc to desc tb_1_.EDITION asc // Reversed: desc to asc limit ? /* 2 */ offset ? /* 4 */ The result is: { \"rows\":[ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1 } }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1 } } ], \"totalCount\":12, \"totalPage\":6 }","s":"Reverse Sorting","u":"/jimmer-doc/docs/query/paging/reverse-sorting","h":"#reverse-sorting","p":1428},{"i":1438,"t":"A common requirement is to handle self-associated property. From a database perspective, self-associated property means a table's foreign key references itself. From an object model perspective, it represents a tree. The difficulty of self-associated properties is that the object depth is uncontrollable, theoretically infinite. Jimmer provides great support for this.","s":"Recursive Query","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"","p":1437},{"i":1440,"t":"Define the entity interface: Java Kotlin @Entity public interface TreeNode { @Id @Column(name = \"NODE_ID\") long id(); String name(); @Null @ManyToOne TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } @Entity interface TreeNode { @Id @Column(name = \"NODE_ID\") val id: Long val name: String @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List } Prepare the database: create table tree_node( node_id bigint not null, name varchar(20) not null, parent_id bigint ); alter table tree_node add constraint pk_tree_node primary key(node_id); alter table tree_node add constraint uq_tree_node unique(parent_id, name); alter table tree_node add constraint fk_tree_node__parent foreign key(parent_id) references tree_node(node_id); insert into tree_node( node_id, name, parent_id ) values (1, 'Home', null), (2, 'Food', 1), (3, 'Drinks', 2), (4, 'Coca Cola', 3), (5, 'Fanta', 3), (6, 'Bread', 2), (7, 'Baguette', 6), (8, 'Ciabatta', 6), (9, 'Clothing', 1), (10, 'Woman', 9), (11, 'Casual wear', 10), (12, 'Dress', 11), (13, 'Miniskirt', 11), (14, 'Jeans', 11), (15, 'Formal wear', 10), (16, 'Suit', 15), (17, 'Shirt', 15), (18, 'Man', 9), (19, 'Casual wear', 18), (20, 'Jacket', 19), (21, 'Jeans', 19), (22, 'Formal wear', 18), (23, 'Suit', 22), (24, 'Shirt', 22) ;","s":"Model and Data Preparation","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#model-and-data-preparation","p":1437},{"i":1442,"t":"Top-down, fetch unlimited layers: Java Kotlin TreeNodeTable node = Tables.TREE_NODE_TABLE; List treeNodes = sqlClient .createQuery(node) .where(node.parentId().isNull()) .select( node.fetch( Fetchers.TREE_NODE_FETCHER .name() .recursiveChildNodes() ) ) .execute(); val treeNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*`() } ) } .execute() info Here, recursiveChildNodes in Java code and childNodes* in Kotlin code represent recursive queries. Jimmer automatically discovers self-associated properties in entities and generates such methods at compile time for users to invoke. Recursive queries do not require specifying the shape of associated objects because recursive queries are very special - the shape of associated objects is the shape of the current object itself. 6 SQL statements are generated: Query root nodes select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID is null Fetch layer 1 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?) Fetch layer 2 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?) Fetch layer 3 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?) Fetch layer 4 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?, ?, ?, ?, ?) Fetch layer 5 (This step does not query any data and the recursive query downstairs ends) select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?, ?, ?, ?, ?, ?) The printed result is (original compact, formatted for readability): { \"id\": 1, \"name\": \"Home\", \"childNodes\": [ { \"id\": 9, \"name\": \"Clothing\", \"childNodes\": [ { \"id\": 18, \"name\": \"Man\", \"childNodes\": [ { \"id\": 19, \"name\": \"Casual wear\", \"childNodes\": [ { \"id\": 20, \"name\": \"Jacket\", \"childNodes\": [] }, { \"id\": 21, \"name\": \"Jeans\", \"childNodes\": [] } ] }, { \"id\": 22, \"name\": \"Formal wear\", \"childNodes\": [ { \"id\": 24, \"name\": \"Shirt\", \"childNodes\": [] }, { \"id\": 23, \"name\": \"Suit\", \"childNodes\": [] } ] } ] }, { \"id\": 10, \"name\": \"Woman\", \"childNodes\": [ { \"id\": 11, \"name\": \"Casual wear\", \"childNodes\": [ { \"id\": 12, \"name\": \"Dress\", \"childNodes\": [] }, { \"id\": 14, \"name\": \"Jeans\", \"childNodes\": [] }, { \"id\": 13, \"name\": \"Miniskirt\", \"childNodes\": [] } ] }, { \"id\": 15, \"name\": \"Formal wear\", \"childNodes\": [ { \"id\": 17, \"name\": \"Shirt\", \"childNodes\": [] }, { \"id\": 16, \"name\": \"Suit\", \"childNodes\": [] } ] } ] } ] }, { \"id\": 2, \"name\": \"Food\", \"childNodes\": [ { \"id\": 6, \"name\": \"Bread\", \"childNodes\": [ { \"id\": 7, \"name\": \"Baguette\", \"childNodes\": [] }, { \"id\": 8, \"name\": \"Ciabatta\", \"childNodes\": [] } ] }, { \"id\": 3, \"name\": \"Drinks\", \"childNodes\": [ { \"id\": 4, \"name\": \"Coca Cola\", \"childNodes\": [] }, { \"id\": 5, \"name\": \"Fanta\", \"childNodes\": [] } ] } ] } ] }","s":"Unlimited Recursion","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#unlimited-recursion","p":1437},{"i":1444,"t":"Top-down, fetch two layers: Java Kotlin TreeNodeTable node = Tables.TREE_NODE_TABLE; List treeNodes = sqlClient .createQuery(node) .where(node.parentId().isNull()) .select( node.fetch( Fetchers.TREE_NODE_FETCHER .name() .recursiveChildNodes( it -> it.depth(2) ) ) ) .execute(); val treeNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { depth(2) } } ) } .execute() 3 SQLs are generated: Main query to fetch root nodes (layer 0) select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID is null Fetch layer 1 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?) Fetch layer 2 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?) The printed result is (original compact, formatted for readability): { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":9, \"name\":\"Clothing\", \"childNodes\":[ {\"id\":18,\"name\":\"Man\"}, {\"id\":10,\"name\":\"Woman\"} ] },{ \"id\":2, \"name\":\"Food\", \"childNodes\":[ {\"id\":6,\"name\":\"Bread\"}, {\"id\":3,\"name\":\"Drinks\"} ] } ] } info Note that the 4 marked objects do not show childNodes as [], but lack the childNodes property altogether. This indicates not knowing at all whether there are deeper child nodes, because the recursive process was prematurely terminated manually.","s":"Limited Depth","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#limited-depth","p":1437},{"i":1446,"t":"Top-down, fetch unlimited layers. But for the node named \"Clothing\", stop recursion. Java Kotlin TreeNodeTable node = Tables.TREE_NODE_TABLE; List treeNodes = sqlClient .createQuery(node) .where(node.parentId().isNull()) .select( node.fetch( Fetchers.TREE_NODE_FETCHER .name() .recursiveChildNodes( it -> it.recursive(args -> !args.getEntity().name().equals(\"Clothing\") ) ) ) ) .execute(); val treeNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { recursive { entity.name != \"Clothing\" } } } ) } .execute() In the above code, the parameter args of it.recursive(args) is an object providing two properties: args.getEntity(): The current node object. args.getDepth(): The current node depth. 0 for nodes obtained directly from the main query, incrementally increases with recursion depth. The return value decided by the user: A boolean variable that decides whether to recursively fetch for the current node. The above code means all nodes will be recursively fetched except the Clothing node. 4 SQLs are generated: Query root objects select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID is null Fetch layer 1 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?) Fetch layer 2 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where /* * Home node has two child nodes: * \"Food\" and \"Clothing\", * * However, \"Clothing is excluded by user, * so `in(?)` is used here, not `in(?, ?)` */ tb_1_.PARENT_ID in (?) Fetch layer 3 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?) Fetch layer 4 select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE as tb_1_ where tb_1_.PARENT_ID in (?, ?, ?, ?) The printed result is (original compact, formatted for readability): { \"id\":1, \"name\":\"Home\", \"childNodes\":[ {\"id\":9,\"name\":\"Clothing\"}, { \"id\":2, \"name\":\"Food\", \"childNodes\":[ { \"id\":6, \"name\":\"Bread\", \"childNodes\":[ {\"id\":7,\"name\":\"Baguette\",\"childNodes\":[]}, {\"id\":8,\"name\":\"Ciabatta\",\"childNodes\":[]} ] },{ \"id\":3, \"name\":\"Drinks\", \"childNodes\":[ {\"id\":4,\"name\":\"Coca Cola\",\"childNodes\":[]}, {\"id\":5,\"name\":\"Fanta\",\"childNodes\":[]} ] } ] } ] } info Note that the marked object does not show childNodes as [], but lack the childNodes property altogether. This indicates not knowing at all whether there are deeper child nodes, because the recursive process was prematurely terminated manually.","s":"Control Recursion Per Node","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#control-recursion-per-node","p":1437},{"i":1448,"t":"Jimmer supports recursive queries on multiple association properties, as below Java Kotlin Tree treeNode = sqlClient .findById( Fetchers.TREE_NODE_FETCHER .name() .recursiveParent() .recursiveChildNodes(), 10L ); val treeNodes = sqlClient .findById( newFetcher(TreeNode::class) { name() `parent*`() `childNodes*`() } ) This example performs recursive queries on two associated properties: parent: Starting from the current node, keep querying upwards for the parent node until the root node is queried childNodes: Starting from the current node, keep querying downwards for child nodes until the deepest child node is queried When executed, the following 6 SQL statements are generated: Query current node select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.NODE_ID = ? /* 10 */ Query first layer parent node upstairs select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.NODE_ID = ? /* 9 */ Query second layer parent node upstairs (This step will query the root node and the recursive query upstairs ends) select tb_1_.NODE_ID, tb_1_.NAME, tb_1_.PARENT_ID from TREE_NODE tb_1_ where tb_1_.NODE_ID = ? /* 1 */ Query first layer child nodes downstairs select tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE tb_1_ where tb_1_.PARENT_ID = ? /* 10 */ Query second layer child nodes downstairs select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE tb_1_ where tb_1_.PARENT_ID in ( ? /* 11 */, ? /* 15 */ ) Query third layer child nodes downstairs (This step does not query any data and the recursive query downstairs ends) select tb_1_.PARENT_ID, tb_1_.NODE_ID, tb_1_.NAME from TREE_NODE tb_1_ where tb_1_.PARENT_ID in ( ? /* 12 */, ? /* 13 */, ? /* 14 */, ? /* 16 */, ? /* 17 */ ) Finally, the query result is: { \"id\":10, \"name\":\"Woman\", \"parent\":{ // Recursive query upstairs \"id\":9, \"name\":\"Clothing\", \"parent\":{ \"id\":1, \"name\":\"Home\", \"parent\":null } }, \"childNodes\":[ // Recursive query downstairs { \"id\":11, \"name\":\"Casual wear\", \"childNodes\":[ { \"id\":12, \"name\":\"Dress\", \"childNodes\":[] }, { \"id\":13, \"name\":\"Miniskirt\", \"childNodes\":[] }, { \"id\":14, \"name\":\"Jeans\", \"childNodes\":[] } ] }, { \"id\":15, \"name\":\"Formal wear\", \"childNodes\":[ { \"id\":16, \"name\":\"Suit\", \"childNodes\":[] }, { \"id\":17, \"name\":\"Shirt\", \"childNodes\":[] } ] } ] } It is not difficult to see from the correct running of this example that the recursive path of the parent direction and the recursive path of the childNodes direction are completely independent. The recursive query upstairs and downstairs will not be mixed or alternate. Therefore, we can slightly correct the previous discussion on why recursive queries do not require specifying the associated object format: info Associated object format = All properties in the current object format that are not recursively queried (whether associated properties or not) + The currently recursively queried property (excluding other recursively queried properties)","s":"Recursion on Multiple Properties","u":"/jimmer-doc/docs/query/object-fetcher/recursive","h":"#recursion-on-multiple-properties","p":1437},{"i":1450,"t":"In the previous article, we mentioned that Jimmer can not only auto-generate count-query from data-query, but also auto-optimize the count-query. Since count-query only cares about total row count regardless of order and format, some table joins in the original data-query may not need to be copied over to count-query. Jimmer will auto-optimize count-query to copy over as few table joins as possible from the original data-query.","s":"Table Join Optimization","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"","p":1449},{"i":1452,"t":"Table joins used by the where clause cannot be optimized. That is, only table joins used solely by the select or order by clause of the top-level query can be optimized. Table joins based on collection associations (one-to-many, many-to-many) cannot be optimized. Collection associations lead to duplicate data, thus affecting row count. So these table joins must be copied to count-query and cannot be optimized. Table joins based on reference associations (one-to-one, many-to-one) may be optimized, if any of the following conditions is met: Join type is left outer join Although join type is inner join, the association is based on non-null real foreign key. So-called real foreign key means there is a foreign key constraint in the database. See Real vs Fake Foreign Keys. In summary, to determine whether a table join in the original data-query can be automatically removed in the count-query, use the following optimization rules: AND Is based on reference association, i.e. many-to-one or one-to-one Is used solely by select or orderBy clause of top-level query OR Is left outer join Association is non-null and foreign key constraint exists in database","s":"Optimization Rules","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"#optimization-rules","p":1449},{"i":1454,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; ConfigurableRootQuery query = sqlClient .createQuery(book) .where( book.price().between( new BigDecimal(20), new BigDecimal(30) ) ) .orderBy(book.store().name()) .orderBy(book.name()) .select(book); int rowCount = query.fetchUnlimitedCount(); val query = sqlClient.createQuery(Book::class) { where( table.price.between( BigDecimal(20), BigDecimal(30) ) ) orderBy(table.store.name) // α orderBy(table.name) select(table) } val rowCount = query.fetchUnlimitedCount() Note α: Although table.store() is only used by orderBy clause without being used by where clause, table.store() is inner join Book.store association is nullable So the optimization rules do not apply. The count-query still needs to retain table.store() and ultimately generates JOIN clause in SQL: select count(tb_1_.ID) from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ?","s":"Non-Optimizable Scenario","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"#non-optimizable-scenario","p":1449},{"i":1456,"t":"For the unoptimizable case discussed above, any of the following modifications will enable optimization: Change Book.store association to non-null Use left outer join Here we choose the second approach, left outer join: Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; ConfigurableRootQuery query = sqlClient .createQuery(book) .where( book.price().between( new BigDecimal(20), new BigDecimal(30) ) ) .orderBy(book.store(JoinType.LEFT).name()) .orderBy(book.name()) .select(book); int rowCount = query.fetchUnlimitedCount(); val query = sqlClient.createQuery(Book::class) { where( table.price.between( BigDecimal(20), BigDecimal(30) ) ) orderBy(table.`store?`.name) // α orderBy(table.name) select(table) } val rowCount = query.fetchUnlimitedCount() Now optimization can take effect. The final count-query generates SQL: select count(tb_1_.ID) from BOOK as tb_1_ where tb_1_.PRICE between ? and ?","s":"Optimizable Scenario","u":"/jimmer-doc/docs/query/paging/unnecessary-join","h":"#optimizable-scenario","p":1449},{"i":1458,"t":"In last doc we introduced scalar property fetching. In this doc we discuss association fetching. ORM has two types of association properties: Reference association: Associated with a single object (or null), the property return type is an entity object, used to express one-to-one and many-to-one associations. info This article uses the many-to-one association property Book.store as an example. Collection association: Associated with multiple objects, the property return type is a list of entities, used to express one-to-many and many-to-many associations. info This article uses the many-to-many association property Book.authors as an example.","s":"Associations","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"","p":1457},{"i":1460,"t":"When fetching associated objects without any parameters, only the id property of the associated objects is returned.","s":"Fetch associated objects with only id","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#fetch-associated-objects-with-only-id","p":1457},{"i":1462,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store() ) ) .execute(); System.out.println(toJson(list)); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() store() } ) } .execute() Here, store() indicates fetching the associated object. We did not specify any parameters for store(), which means only the id property of the associated object is fetched. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.EDITION = ? Since the many-to-one association Book.store is based on a real foreign key, the foreign key STORE_ID of the current table BOOK is the id of the parent object. Because store() only fetches the id property of the associated object, no additional SQL query is required. The parent object with only the id property can be directly constructed from the foreign key in the current data. The returned value is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } }, ...other objects omitted... ]","s":"ManyToOne: Book.store","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytoone-bookstore","p":1457},{"i":1464,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER. .allScalarFields() .authors() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors() } ) } .execute() Here, authors() indicates fetching the associated objects. We did not specify any parameters for authors(), which means only the id property of the associated objects is fetched. Two SQLs are generated: Query for the Book objects themselves select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? Based on the Book.authors association, query for the Author associated objects with only id for all root objects queried in the previous step select tb_1_.BOOK_ID, /* batch-map key */ tb_1_.AUTHOR_ID /* batch-map value */ from BOOK_AUTHOR_MAPPING as tb_1_ where tb_1_.BOOK_ID in (?, ?, ?, ?) This example demonstrates: The query only needs the id of the associated objects, and no filters are used (filters will be explained later). Jimmer optimizes this case by only querying the BOOK_AUTHOR_MAPPING table instead of the AUTHOR table, because the middle table already contains the id of the associated objects. where tb_1_.BOOK_ID in (?, ?, ?, ?) is a batch query, because the first query returns 4 root objects. Jimmer uses batch queries to solve the N+1 problem, similar to DataLoader in GraphQL. When a batch becomes too large, jimmer-sql will split it into smaller batches. This will be explained in the BatchSize section. Jimmer queries the associated objects via separate SQL instead of using LEFT JOIN in the main query SQL to fetch associated objects. This is designed to avoid duplicate results when joining collection associations, which can be devastating for paged queries on aggregate roots. The printed result is (formatted for readability, original output is compact): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, \"authors\":[ {\"id\":1}, {\"id\":2} ] }, ...other objects omitted... ]","s":"ManyToMany: Book.authors","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytomany-bookauthors","p":1457},{"i":1466,"t":"When fetching associated objects, parameters can be specified to get associated objects with more information.","s":"Fetch complex associated objects","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#fetch-complex-associated-objects","p":1457},{"i":1468,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) ) ) .execute(); System.out.println(toJson(list)); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() store { allScalarFields() } } ) } .execute() Here, store(...) indicates fetching the associated object. We specify parameters for store(...) to fetch information other than id of the associated object. Two SQLs are generated: Query for Book objects select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.EDITION = ? Based on the Book.store association, query for relatively complete BookStore associated objects for all root objects queried in the previous step select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE from BOOK_STORE tb_1_ where tb_1_.ID in (?, ?) where tb_1_.ID in (?, ?) is a batch query. The first query returns 4 root objects, but the foreign key values are deduplicated to only 2 values. The returned value is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null } }, ...other objects omitted... ]","s":"ManyToOne: Book.store","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytoone-bookstore-1","p":1457},{"i":1470,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER. .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors { allScalarFields() } } ) } .execute() Here, authors(...) indicates fetching the associated objects. We specify parameters for authors(...) to fetch information other than id of the associated objects. Two SQLs are generated: Query for the Book objects themselves select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? Based on the Book.authors association, query for relatively complete Author associated objects for all root objects queried in previous step select /* batch-map key */ tb_2_.BOOK_ID, /* batch-map value */ tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) This example shows: Information other than id is required for the associated objects, so both the BOOK_AUTHOR_MAPPING table and the AUTHOR table are queried, besides just the middle table. where tb_2_.BOOK_ID in (?, ?, ?, ?) is a batch query, because the first query returns 4 root objects. Jimmer uses batch queries to solve the N+1 problem, similar to DataLoader in GraphQL. Jimmer queries the associated objects via separate SQL instead of using LEFT JOIN in the main query SQL. This is designed to avoid duplicate results when joining collection associations, which can be devastating for paged queries on aggregate roots. The printed result is (formatted for readability): [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, \"authors\":[ { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" }, { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" } ] }, ...other objects omitted... ]","s":"ManyToMany: Book.authors","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#manytomany-bookauthors-1","p":1457},{"i":1472,"t":"In some cases, all fields defined in the table are needed. allTableFields can be used for this. allTableFields fetches all properties defined in the table, including all scalar properties (same as allScalarFields), one-to-one/many-to-one associations based on foreign keys. It does not include one-to-many, many-to-many associations, one-to-one/many-to-one associations based on middle tables, calculated properties or view properties. info allTableFields includes all one-to-one/many-to-one associations based on foreign keys, in addition to allScalarFields. The fetched associated objects only have the id property. Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allTableFields() ) ) .execute(); System.out.println(toJson(list)); val bookAllTableFields = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allTableFields() } ) } .execute() The result is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"store\": { \"id\": 1 } } ...other objects omitted ] info In some cases, select(table.fetch(Fetchers.XXX_FETCHER.allTableFields())) is equivalent to select(table). The latter can be considered as shorthand for the former. The equivalence holds when associated objects are not affected by filters. The simple equivalent shorthand is: Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select(book) .execute(); System.out.println(toJson(list)); val bookAllScalarFields = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select(table) } .execute()","s":"Fetching all table fields","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#fetching-all-table-fields","p":1457},{"i":1475,"t":"For one-to-many/many-to-many associations, a large number of associated objects may impact application performance. The batchSize configuration is provided for management. The following example does not configure batchSize: Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER.allScalarFields() .authors(Fetchers.AUTHOR_FETCHER.allScalarFields()) ) ) .execute(); System.out.println(toJson(list)); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allTableFields() authors { allScalarFields() } } ) } .execute() The generated SQL is: # 1. Query book table to get all BOOK_ID select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK tb_1_ where tb_1_.EDITION = ? # 2. Use BOOK_ID from previous step to join query author table select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) In this example, no batchSize is configured so the default will be used. All BOOK_ID will be directly used in the in(...) list of the second query. The output is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"authors\": [ { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" }, { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" } ] }, ...omit other objects ] In the example above, we see the query: select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?, ?, ?) Here, the in expression implements batch query to solve N+1 problem. If a batch is too large, it will be split into multiple batches based on batchSize configuration, such as: Java Kotlin BookTable book = Tables.BOOK_TABLE; List list = sqlClient.createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER.allScalarFields() .authors(Fetchers.AUTHOR_FETCHER.allScalarFields(), it -> it.batch(2)) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors({ batch(2) }) {} } ) } .execute() danger Here the batchSize for authors is set to 2. Such a small value would cause poor performance, it is only for demo purposes. Please do not use such small values in real projects. This would cause the in(?, ?, ?, ?) to be split into two in(?, ?), and the SQL to fetch associated objects would be split into two. select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?) select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME, tb_1_.GENDER from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in (?, ?) In real projects, in most cases batchSize would not be configured like this at fetcher level. Instead, use the global configurations in SqlClient: JSqlClient.getDefaultBatchSize(): Default batchSize for one-to-one and many-to-one associations, default 128 JSqlClient.getDefaultListBatchSize(): Default batchSize for one-to-many and many-to-many associations, default 16 When creating SqlClient, the global configs can be changed: Using spring boot Add configuration into application.yml or application.properties jimmer: default-batch-size: 256 default-list-batch-size: 32 Using low-level API Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDefaultBatchSize(256) .setDefaultListBatchSize(32) .... build(); val sqlClient = newKSqlClient { setDefaultBatchSize(256) setDefaultListBatchSize(32) .... } caution No matter association-level batchSize or global batchSize, do not set above 1000 because Oracle database allows max 1000 values in in(...).","s":"BatchSize","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#batchsize","p":1457},{"i":1477,"t":"For collection associations, limit(limit, offset) can be specified during fetching to do pagination at association level. caution Association-level pagination and batch loading cannot coexist. Association-level pagination necessarily causes N+1 problem. Please use this feature cautiously! If association-level pagination is used, batchSize must be set to 1, otherwise exceptions would be thrown. This is designed to make it clear to developers and readers that the code has N+1 performance risk. Java Kotlin BookTable book = Tables.BOOK_TABLE; List books = sqlClient .createQuery(book) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER.allScalarFields(), it -> it.batch(1).limit(/*limit*/ 10, /*offset*/ 90) ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( table.fetchBy { allScalarFields() authors({ batch(1) limit(limit = 90, offset = 10) }) { allScalarFields() } } ) } .execute() Since association pagination cannot solve N+1 problem, multiple SQLs are generated For simplicity let's assume H2Dialect is used so different databases have the same paging SQL Query current Book objects select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? Paginated query on authors collection of the 1st Book object select tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID = ? limit ? offset ? Paginated query on authors collection of the 2nd Book object Same as above, omitted. Paginated query on authors collection of the 3rd Book object Same as above, omitted. Paginated query on authors collection of the 4th Book object Same as above, omitted.","s":"Pagination at Association Level","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#pagination-at-association-level","p":1457},{"i":1479,"t":"When fetching associations, filters can be specified to filter associated objects. Here for comparison, the query selects two columns, both are Book type. The Book.authors of the first column uses filter The Book.authors of the second column does not use filter Java Kotlin BookTable book = Tables.BOOK_TABLE; List> books = sqlClient .createQuery(book) .select( // First column book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER.allScalarFields(), // Use filter it -> it.filter(args -> { args.where(args.getTable().firstName().ilike(\"a\")); }) ) ), // Second column book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .authors( Fetchers.AUTHOR_FETCHER.allScalarFields() // No filter used ) ) ) .execute(); val tuples: List> = sqlClient .createQuery(Book::class) { where(table.edition.eq(3)) select( // First column table.fetchBy { allScalarFields() authors({ // Use filter filter { where(table.firstName ilike \"a\") } }) { allScalarFields() } }, // Second column table.fetchBy { allScalarFields() authors { // No filter used allScalarFields() } } ) } .execute() Three SQLs are generated: Query the two Book objects needed for the tuple select /* For tuple._1 */ tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, /* For tuple._2 */ tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE from BOOK as tb_1_ where tb_1_.EDITION = ? For the authors association of the 4 Book objects in column 1, use filter select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID in (?, ?, ?, ?) and /* Use filter here */ lower(tb_3_.FIRST_NAME) like ? For the authors association of the 4 Book objects in column 2, no filter select tb_1_.BOOK_ID, tb_1_.AUTHOR_ID, tb_3_.FIRST_NAME, tb_3_.LAST_NAME, tb_3_.GENDER from BOOK_AUTHOR_MAPPING as tb_1_ inner join AUTHOR as tb_3_ on tb_1_.AUTHOR_ID = tb_3_.ID where tb_1_.BOOK_ID in (?, ?, ?, ?) /* No filter here */ The printed result is (formatted for readability): Tuple2{ _1={ \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, // Filter used, incomplete collection \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" } ] }, _2={ \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, // No filter, complete collection \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" },{ \"id\":\"fd6bb6cf-336d-416c-8005-1ae11a6694b5\", \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"MALE\" } ] } } note Filters can not only filter associated objects, but also sort them. The principle is similar so not demonstrated here. caution For associations satisfying both below conditions, applying filters would cause exceptions: Many-to-one Not null After field filters are used, association cache for that field will be ignored. To use the association cache, global filters supporting multi-view cache can be used. A common mistake in real development (Java for example) is: filter(it -> args.getTable().firstName().ilike(\"a\")) This creates the condition expression but does not call args.where. Filter code not calling either args.where or args.orderBy is meaningless. The correct code is: filter(it -> args.where(args.getTable().firstName().ilike(\"a\")))","s":"Property-level Filters","u":"/jimmer-doc/docs/query/object-fetcher/association","h":"#property-level-filters","p":1457},{"i":1482,"t":"For data structures, frontends and backends have different preferences. Backends prefer structured data, while frontends prefer flattened data. For IdOnly objects, Jimmer provides the @IdView annotation to easily flatten IdOnly objects into a field.","s":"IdView","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#idview","p":1480},{"i":1484,"t":"In the example entity interface, two @IdView properties are added, which are view properties. The value of these properties will be automatically synchronized with the value of the corresponding associated object. For the IdView of a collection property, the corresponding association property needs to be specified manually. Java Kotlin @Entity public interface Book { ...Other properties omitted... @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); @IdView Long storeId(); @IdView(\"authors\") List authorIds(); } @Entity interface Book { ...Other properties omitted... @ManyToOne val store: BookStore? @ManyToMany val authors: List @IdView val storeId: Long? @IdView(\"authors\") val authorsIds: List }","s":"Modify the Example Entity Interface","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#modify-the-example-entity-interface","p":1480},{"i":1486,"t":"caution View properties need to be fetched manually. allScalarFields and allTableFields will not automatically fetch view properties. Java Kotlin BookTable book = Tables.BOOK_TABLE; List bookWithIdViews = sqlClient .createQuery(book) .where(book.edition().eq(3)) .select( book.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .storeId() .authorIds() ) ) .execute(); System.out.println(bookWithIdViews); var bookWithIdViews = sqlClient .createQuery(Book::class) { where(table.edition eq 3) select( table.fetchBy { allScalarFields storeId authorIds } ) } .execute() println(bookWithIdViews) The output is: [ { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51.00, \"storeId\": 1, \"authorIds\": [1,2] } ...Other objects omitted ]","s":"Fetch @IdView Properties","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#fetch-idview-properties","p":1480},{"i":1488,"t":"In some scenarios, the join table of a many-to-many association contains not only the IDs of both sides, but also some other fields. A join table with additional fields besides the two IDs cannot be directly mapped to a ManyToMany association. We have no choice but to create three entity types: the original two entities and an intermediate entity. Each side entity has a one-to-many association pointing to the intermediate entity, and the intermediate entity has two many-to-one associations pointing to the two side entities. Fortunately, Jimmer provides @ManyToManyView to abstract a many-to-many association between the two side entities on top of this three-entity structure. To better demonstrate, instead of using books and authors, a more realistic example with students, courses, and learning_link tables is used.","s":"ManyToManyView","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#manytomanyview","p":1480},{"i":1490,"t":"For convenience, H2 database is used here. First create the table structure and initialize data with: drop table course if exists; drop table learning_link if exists; drop table student if exists; create table course( id identity(100, 1) not null, name varchar(50) not null, academic_credit integer not null ); create table student( id identity(100, 1) not null, name varchar(50) not null ); create table learning_link( id identity(100, 1) not null, student_id int not null, course_id int not null, score int null ); alter table learning_link add constraint fk_learning_link__student foreign key(student_id) references student(id) on delete cascade; alter table learning_link add constraint fk_learning_link__course foreign key(course_id) references course(id) on delete cascade; insert into student(id, name) values (1, 'John'), (2, 'Jane'), (3, 'Jack'), (4, 'Jill'), (5, 'Joe'); insert into course(id, name, academic_credit) values (1, 'Math', 100), (2, 'English', 100), (3, 'History', 100), (4, 'Science', 100), (5, 'Art', 100); insert into learning_link(student_id, course_id, score) values (1, 1, 100), (1, 2, 90), (1, 3, 80), (1, 4, 70), (1, 5, 60), (2, 1, 90), (2, 2, 80), (2, 3, 70), (2, 4, 60), (2, 5, 100), (3, 1, 80), (3, 2, 70), (3, 3, 60), (3, 4, 100), (3, 5, 90), (4, 1, 70), (4, 2, 60), (4, 3, 100), (4, 4, 90), (4, 5, 80), (5, 1, 60), (5, 2, 100), (5, 3, 90), (5, 4, 80), (5, 5, 70);","s":"Prepare Data","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#prepare-data","p":1480},{"i":1492,"t":"Student Java Kotlin @Entity public interface Student { @Id long id(); String name(); @OneToMany(mappedBy = \"student\") List learningLinks(); // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `course` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"course\") List courses(); } @Entity interface Student { @Id val id: Long val name: String @OneToMany(mappedBy = \"student\") val learningLinks: List // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `course` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"course\") val courses: List } Course Java Kotlin @Entity public interface Course { @Id long id(); String name(); int academicCredit(); @OneToMany(mappedBy = \"course\") List learningLinks(); // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `student` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"student\") List students(); } @Entity interface Course { @Id val id: Long val name: String val academicCredit: Int @OneToMany(mappedBy = \"course\") val learningLinks: List // ManyToMany view property // prop: One-to-many to intermediate entity `learningLinks` // deeperProp: Many-to-one from intermediate to target entity `student` (optional) @ManyToManyView(prop = \"learningLinks\", deeperProp = \"student\") val students: List } Intermediate Entity LearningLink Java Kotlin @Entity public interface LearningLink { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); // Many-to-one, points to Student entity @ManyToOne @OnDissociate(DissociateAction.DELETE) Student student(); // Many-to-one, points to Course entity @ManyToOne @OnDissociate(DissociateAction.DELETE) Course course(); Integer score(); } @Entity interface LearningLink { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long // Many-to-one, points to Student entity @ManyToOne @OnDissociate(DissociateAction.DELETE) val student: Student // Many-to-one, points to Course entity @ManyToOne @OnDissociate(DissociateAction.DELETE) val course: Course val score: Int }","s":"Define Entities","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#define-entities","p":1480},{"i":1494,"t":"With the introduction of the intermediate entity, Student and Course entities are no longer directly associated. Although they can be indirectly associated through a Student->LearningLink->Course path, the path is too long. Besides, the intermediate LearningLink entity should be hidden as much as possible, only used when reading/writing scores. @ManyToManyView properties (e.g. Student.courses in this example) can be used in object fetchers to reduce the path length. For example, the following query gets all course names for the student with id 1: Java Kotlin Student student = sqlClient .findNullable( 1L, Fetchers.STUDENT_FETCHER .name() .courses( Fetchers.COURSE_FETCHER .name() ) ) System.out.println(student); val student = sqlClient .findNullable( 1L, newFetcher(Student::class).by { name() courses { name() } } ) println(student) The generated SQL is: Query Student select tb_1_.ID, tb_1_.NAME from STUDENT tb_1_ where tb_1_.ID = ? /* 1 */ Query LearningLink select tb_1_.STUDENT_ID, tb_1_.ID, tb_1_.COURSE_ID from LEARNING_LINK tb_1_ where tb_1_.STUDENT_ID in (? /* 1 */) Query Course select tb_1_.ID, tb_1_.NAME from COURSE tb_1_ where tb_1_.ID in ( ? /* 1 */, ? /* 2 */, ? /* 3 */, ? /* 4 */, ? /* 5 */ ) The output is: { \"id\": 1, \"name\": \"John\", \"courses\": [ { \"id\": 1, \"name\": \"Math\" }, { \"id\": 2, \"name\": \"English\" }, { \"id\": 3, \"name\": \"History\" }, { \"id\": 4, \"name\": \"Science\" }, { \"id\": 5, \"name\": \"Art\" } ] } With many-to-many view properties, associated objects can be operated as conveniently as if the intermediate entity did not exist at all.","s":"Fetch @ManyToManyView Properties","u":"/jimmer-doc/docs/query/object-fetcher/view","h":"#fetch-manytomanyview-properties","p":1480},{"i":1497,"t":"Unlike native SQL, in the DSL provided by Jimmer, the select statement comes after where, orderBy, groupBy, having, etc. For example: Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) ❶ .where(table.name().eq(\"SQL in Action\")) .orderBy(table.name().asc(), table.edition().desc()) .select(table) ❷ .limit(10, 100) .execute(); ❸ val books = sqlClient .createQuery(Book::class) { ❶ where(table.name eq \"SQL in Action\") orderBy(table.name.asc(), table.edition.desc()) select(table) ❷ } .limit(10, 100) .execute() ❸ tip Putting select after is not invented by Jimmer. This style was first brought to mainstream by LINQ introduced in C# 3.5. This style has innate advantages for building strongly typed DSL frameworks, so Jimmer naturally adopts it.","s":"Select-After Style","u":"/jimmer-doc/docs/query/usage","h":"#select-after-style","p":1495},{"i":1499,"t":"Now let's explain the code: ❶ Create the query, get a mutable query object. Operations targeting this object continue until ❷. A mutable query object means any operations like where, orderBy, groupBy, having directly modify the current query object. ❷ Call select, convert the mutable query object into an immutable one. Operations targeting this object continue until ❸. An immutable query object means any operations like distinct, limit, forUpdate, reselect, withoutSortingAndPaging, union, unionAll, minus, intersect, do not change the current object but create a new one. For example (to be concise, this pseudo-code uses Kotlin): val query = sqlClient.createQuery(Book::class) { where(...) orderBy(...) select(...) } val query1 = query.limit(10, 0); val query2 = query.limit(10, 1); val query3 = query.limit(10, 2); Here query is the original query, query1, query2, query3 are other queries created based on it. limit does not change query itself but creates new immutable query objects. Finally, query1, query2, query3 share the same filters, sorting and structure projection as query, only differing in paging range. They can coexist without interfering with each other. Also, the mutable query before select has no return type, while the immutable query after select has a return type. That is, select assigns the final return type to the query. ❸ Call execute to execute the query and return data. Before this step, no matter how the DSL is operated and tuned, no SQL operations will be executed. Besides execute, there are other methods to execute queries: fetchOne: Assume the query returns exactly one row, get that row. Throw exception if 0 or more rows are returned during actual execution. fetchOneOrNull: Assume the query returns 0 or 1 row, get that row or null. Throw exception if more rows are returned during actual execution. fetchOptional: Similar to fetchOneOrNull but returns java.util.Optional instead of null | T. caution This API only exists in Java API, not in Kotlin API since Kotlin does not need java.util.Optional. map: Execute directly and do an additional collection map operation at JVM level on top of the returned raw collection. forEach: If returning too much data to avoid materializing a large collection, forEach can be called with a callback to traverse all data. This is what people often refer to as cursor queries. count: Based on the original data query written by users, automatically generate the count aggregate query needed for paging, execute and get total rows before paging. info This is a smart and advanced operation, please see Paging. tip All the methods above to execute queries have two overloaded versions: Parameterless version (as shown in the example) utilizes Jimmer's connection management (usually integrating with Spring transaction management) to get JDBC connection and execute. Version with a parameter accepting a JDBC connection. In special cases developers can discard Jimmer's connection management (usually integrating with Spring transaction management) and execute on a specified JDBC connection. Now the process can be summarized as: +----------------------+ | ❶ createQuery | +-----------+----------+ | Mutable Query (Operations like where, orderBy directly modify the query) | | \\|/ +----------------------+ | ❷ select | +-----------+----------+ | Immutable Query (Operations like limit, distinct create new queries without modifying current one) | | \\|/ +----------------------+ | ❸ execute or others | +-----------+----------+ | \\|/ Execution Result (Result type is specified by ❷ select)","s":"Code Structure","u":"/jimmer-doc/docs/query/usage","h":"#code-structure","p":1495},{"i":1501,"t":"This section only enumerates the usage methods of the most important functions in Jimmer to allow readers to build a preliminary impression. Therefore, this section only provides the usage and reference links of relevant functions without in-depth discussion. In this section, we take a quick tour of the three most core features of Jimmer Query arbitrary data structures Save arbitrary data structures Implement arbitrarily complex dynamic queries","s":"Quick View ★","u":"/jimmer-doc/docs/quick-view/","h":"","p":1500},{"i":1503,"t":"Jimmer supports strongly typed SQL DSL. tip Note that unlike most frameworks that use strongly typed DSLs, Jimmer's strongly typed DSL is not only for compile-time safety assurance and IDE intelligent prompt experience of SQL statements, but also for solving the problem of table joins and subqueries in native SQL. They are too cumbersome so jimmer gives them higher abstractions. After giving table joins and subqueries higher abstractions, building arbitrary complex dynamic queries with Jimmer becomes very easy. From the beginning, Jimmer is designed for easy construction of arbitrary complex dynamic queries. In addition, for the powerful non-sql-standard features owned by specific database products, Jimmer's SQL DSL can embed Native SQL fragments without the abstraction of the strongly typed DSL affecting developers' full use of the special features of the data. (This part of the function will not be introduced in the quick preview. Interested supervisors please check Query/Native Expressions)","s":"3. Arbitrary Dynamic Query","u":"/jimmer-doc/docs/quick-view/dsl/","h":"","p":1502},{"i":1507,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().in(sqlClient .createSubQuery(author) .where(author.firstName().eq(\"Alex\")) .select(author.books().id()) ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id valueIn subQuery(Author::class) { where(table.firstName eq \"Alex\") select(table.books.id) } ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME = ? )","s":"IN expression based on single column","u":"/jimmer-doc/docs/query/sub-query","h":"#in-expression-based-on-single-column","p":1504},{"i":1509,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List newestBooks = sqlClient .createQuery(book) .where( Expression.tuple( book.name(), book.edition() ).in(sqlClient .createSubQuery(book) .groupBy(book.name()) .select( book.name(), book.edition().max() ) ) ) .select(book) .execute(); val newestBooks = sqlClient .createQuery(Book::class) { where( tuple( table.name, table.edition ) valueIn subQuery(Book::class) { groupBy(table.name) select( table.name, max(table.edition).asNonNull() ) } ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where (tb_1_.NAME, tb_1_.EDITION) in ( select tb_2_.NAME, max(tb_2_.EDITION) from BOOK as tb_2_ group by tb_2_.NAME )","s":"IN expression based on multiple columns","u":"/jimmer-doc/docs/query/sub-query","h":"#in-expression-based-on-multiple-columns","p":1504},{"i":1511,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; List newestBooks = sqlClient .createQuery(book) .where( book.price().gt(sqlClient .createSubQuery(book) .groupBy(book.name()) .select( book .price() .avg() .coalesce(BigDecimal.ZERO) ) ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.price gt subQuery(Book::class) { select( avg(table.price) .coalesce(BigDecimal.ZERO) ) } ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.PRICE > ( select coalesce(avg(tb_2_.PRICE), ?) from BOOK as tb_2_ )","s":"Treat subquery as simple value","u":"/jimmer-doc/docs/query/sub-query","h":"#treat-subquery-as-simple-value","p":1504},{"i":1513,"t":"Java Kotlin BookStoreTable store = Tables.BOOK_STORE_TABLE; BookTable book = Tables.BOOK_TABLE; MutableRootQuery query = sqlClient.createQuery(store); TypedSubQuery subQuery = sqlClient .createSubQuery(book) .where(book.store().eq(store)) .select( book .price() .avg() .coalesce(BigDecimal.ZERO) ); List> storeAvgPriceTuples = query .orderBy( subQuery.desc() ) .select( store, subQuery ) .execute(); val storeAvgPriceTuples = sqlClient .createQuery(BookStore::class) { val avgPriceSubQuery = subQuery(Book::class) { where(table.store eq parentTable) select(avg(table.price)) } orderBy( avgPriceSubQuery.desc() ) select( table, avgPriceSubQuery ) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.WEBSITE, ( select coalesce(avg(tb_2_.PRICE), ?) from BOOK as tb_2_ ) from BOOK_STORE as tb_1_ order by ( select coalesce(avg(tb_2_.PRICE), ?) from BOOK as tb_2_ ) desc","s":"Use subquery in select and orderBy clauses","u":"/jimmer-doc/docs/query/sub-query","h":"#use-subquery-in-select-and-orderby-clauses","p":1504},{"i":1515,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().eq(sqlClient .createSubQuery(author) .where( author.firstName().in( Arrays.asList(\"Alex\", \"Bill\") ) ) .select(author.books().id()) .any() ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id eq any( subQuery(Author::class) { where( table.firstName valueIn listOf( \"Alex\", \"Bill\" ) ) select(table.id) } ) ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID = any( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME in (?, ?) )","s":"Use ANY operator","u":"/jimmer-doc/docs/query/sub-query","h":"#use-any-operator","p":1504},{"i":1517,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where( book.id().ne(sqlClient .createSubQuery(author) .where( author.firstName().in( Arrays.asList(\"Alex\", \"Bill\") ) ) .select(author.books().id()) .all() ) ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( table.id ne all( subQuery(Author::class) { where( table.firstName valueIn listOf( \"Alex\", \"Bill\" ) ) select(table.id) } ) ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID = all( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_2_.FIRST_NAME in (?, ?) )","s":"Use ALL operator","u":"/jimmer-doc/docs/query/sub-query","h":"#use-all-operator","p":1504},{"i":1519,"t":"Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where(sqlClient .createSubQuery(author) .where( author.books().eq(book), author.firstName().eq(\"Alex\") ) .select(author) .exists() ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( exists( subQuery(Author::class) { where( table.books eq parentTable, table.firstName eq \"Alex\" ) select(table) } ) ) select(table) } .execute() The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where exists ( select 1 from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_1_.ID = tb_3_.BOOK_ID and tb_2_.FIRST_NAME = ? ) info Note that in the final SQL, the selected column in the subquery is the constant 1, not what is specified in the Java/Kotlin code. This is because the exists operator only cares if the subquery can match data, not what columns are selected. Whatever you select in the Java/Kotlin code will be ignored.","s":"Use EXISTS operator","u":"/jimmer-doc/docs/query/sub-query","h":"#use-exists-operator","p":1504},{"i":1521,"t":"The last example in previous section is exists subquery where whatever is selected in Java code gets ignored. In that case, why specify the return type for exists subqueries in Java code? Therefore, jimmer-sql supports untyped subqueries (wild subqueries). Unlike normal subqueries, for wild subqueries the final select() call is no longer needed, i.e. no return type. Java Kotlin BookTable book = Tables.BOOK_TABLE; AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; List books = sqlClient .createQuery(book) .where(sqlClient .createSubQuery(author) .where( author.books().eq(book), author.firstName().eq(\"Alex\") ) // No select here .exists() ) .select(book) .execute(); val books = sqlClient .createQuery(Book::class) { where( exists( wildSubQuery(Author::class) { where( table.books eq parentTable, table.firstName eq \"Alex\" ) // No select here } ) ) select(table) } .execute() The final SQL remains the same: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where exists ( select 1 from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_1_.ID = tb_3_.BOOK_ID and tb_2_.FIRST_NAME = ? ) info The only value of untyped subqueries is when used with exists operator.","s":"Untyped Subqueries","u":"/jimmer-doc/docs/query/sub-query","h":"#untyped-subqueries","p":1504},{"i":1523,"t":"Super QBE is a very powerful feature that uses DTO Language to generate parameter types for complex queries and automatically implement query logic.","s":"Super QBE","u":"/jimmer-doc/docs/query/super_qbe","h":"","p":1522},{"i":1525,"t":"In any project that can access entity types, create the src/main/dto directory, and create the Book.dto file in this directory. For Java projects, if the current project is not the project that defines the entity type, you need to add the @EnableDtoGeneration annotation to any class in the current project. Add the following code to the head of the file: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.dto The above steps, as well as how to compile DTO files, are discussed in detail in DTO Language #2. Create File, and will not be repeated here.","s":"Create File","u":"/jimmer-doc/docs/query/super_qbe","h":"#create-file","p":1522},{"i":1527,"t":"...export statement omitted... specification BookSpecification { }","s":"Define Specification Type","u":"/jimmer-doc/docs/query/super_qbe","h":"#define-specification-type","p":1522},{"i":1529,"t":"After compilation, Java/Kotlin code like this will be generated: Java Kotlin BookSpecification.java package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.ast.query.specification.JSpecification; import org.babyfish.jimmer.sql.ast.query.specification.SpecificationArgs; ...other imports omitted... public class BookSpecification implements JSpecification { @Override public void applyTo(SpecificationArgs args) {} } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( // Now data class has no fields, will cause compile error ) : KSpecification { override fun applyTo(args: KSpecificationArgs) {} } info applyTo is a method specific to the compiled specification code. It dynamically adds where conditions to Jimmer queries according to the information of the current object. This method does not require user invocation (invoked by internal Jimmer behaviors), and users do not need to care about its internal code implementation. Just knowing what this method does is enough here. In subsequent discussions, we will gradually add properties to BookSpecification in the DTO file. Accordingly, for the automatically generated BookSpecification class, on the one hand, properties will be added synchronously, on the other hand, the code in the applyTo method will also grow.","s":"Compiled Code","u":"/jimmer-doc/docs/query/super_qbe","h":"#compiled-code","p":1522},{"i":1531,"t":"Use in queries Java Kotlin public List find( Specification specification ❶ ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(specification) ❷ .select(table) .execute(); } fun find( specification: Specification ❶ ): List = sqlClient.createQuery(Book::class) { where(specification) ❷ select(table) }.execute() ❶ The argument whose type is org.babyfish.jimmer.Specification type, which is used to generate dynamic SQL predicates. ❷ No matter how simple or complex the specification format is, it can be used with just a simple where statement. Use in Spring Data Repository Jimmer integrates Spring Data, so Spring Data Repository can be defined, please refer to Spring Data Style to learn more. Jimmer's Spring Data Repository has two query styles, abstract methods and default methods. The code using specification in default methods is the same as above, so let's look at an example of using specification in abstract query methods: Java Kotlin public interface BookRepository : JRepository { public List find( Specification specification ) } interface BookRepository : KRepository { fun find( specification: Specification ): List }","s":"Usage","u":"/jimmer-doc/docs/query/super_qbe","h":"#usage","p":1522},{"i":1534,"t":"...export statement omitted... specification BookSpecification { name } This maps entity properties to DTOs. The generated code is: Java Kotlin BookSpecification.java public class BookSpecification implements JSpecification { @Nullable private String name; ...getters and setters omitted... @Override public void applyTo(SpecificationArgs args) { ...omitted... } } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( val name: String? = null ) : KSpecification { override fun applyTo(args: KSpecificationArgs) { ...omitted... } }","s":"Map Attributes","u":"/jimmer-doc/docs/query/super_qbe","h":"#map-attributes","p":1522},{"i":1536,"t":"We find that in the generated code, the name field can be null, which is where the specialty of specification lies. tip Specifications are used as query parameters. To support dynamic queries, all properties are nullable by default unless explicitly specified as non-nullable using ! (see DTO Language #7. Nullability).","s":"Nullability","u":"/jimmer-doc/docs/query/super_qbe","h":"#nullability","p":1522},{"i":1538,"t":"Let the name field of BookSpecification be null Java Kotlin BookSpecification specification = new BookSpecification(); List books = bookRepository.find(specification); val specification = BookSpecification() val books = bookRepository.find(specification) Since specification.name is null, the generated SQL does not contain any where conditions. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME = ? info Such queries that do not specify relevant specification properties will inevitably lead to queries without any conditions. This example is only demonstrated once in this article. Make the name field of BookSpecification non-null Java Kotlin BookSpecification specification = new BookSpecification(); specification.setName(\"GraphQL in Action\"); List books = bookRepository.find(specification); val specification = BookSpecification( name = \"GraphQL in Action\" ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME = ? /* GraphQL in Action */","s":"Usage","u":"/jimmer-doc/docs/query/super_qbe","h":"#usage-1","p":1522},{"i":1541,"t":"In the code above, when specification.name is specified, the generated where condition is equality. Equality is not necessarily what we need. QBE functions can be applied to mapped properties to change the operator. Take like as an example: ...export statement omitted... specification BookSpecification { like(name) } The like function does not affect the properties of the generated BookSpecification class, but affects its applyTo method, whose internal implementation is the where condition addition logic that users do not need to care about. Execute: Java Kotlin BookSpecification specification = new BookSpecification(); specification.setName(\"GraphQL\"); List books = bookRepository.find(specification); val specification = BookSpecification( name = \"GraphQL\" ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME like ? /* %GraphQL% */","s":"Introduction to QBE Functions","u":"/jimmer-doc/docs/query/super_qbe","h":"#introduction-to-qbe-functions","p":1522},{"i":1543,"t":"like is a special one among all QBE functions, supporting 3 options: i: Case insensitive ^: Exact match at the beginning (Jimmer does not automatically add % before the parameter value) $: Exact match at the end (Jimmer does not automatically add % after the parameter value) If options are needed, / can be added after like, followed by the required options. Such as: like/i, like/^, like/$, like/i^, like/i$, and like/i^$. caution Although i, ^ and $ are optional, their order is fixed. Let's try case-insensitive like by modifying the DTO code as follows: ...export statement omitted... specification BookSpecification { like/i(name) } Execute the code above again, the following SQL is executed: Databases that do not support ilike: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ Databases that support ilike: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where tb_1_.NAME ilike ? /* %graphql% */","s":"like Function Options","u":"/jimmer-doc/docs/query/super_qbe","h":"#like-function-options","p":1522},{"i":1545,"t":"In fact, in addition to like, speciation supports a large number of QBE functions covering common SQL judgments, as shown in the table below: QBE Function Original Entity Attribute Type (or Requirement) Generated DTO Class Attribute Type Remarks eq Any non-associative property Original type Equal, equivalent to not using any QBE function ne Any non-associative property Original type Not equal gt Any non-associative property Original type Greater than ge Any non-associative property Original type Greater than or equal to lt Any non-associative property Original type Less than le Any non-associative property Original type Less than or equal to like String String Fuzzy match notLike String String Fuzzy mismatch null Any property boolean is null judgment if DTO property is true notNull Any property boolean is not null judgment if DTO property is true valueIn Any non-associative property List in(...) valueNotIn Any non-associative property List not in(...) associatedIdEq Any associative property Type of associated entity's id property Associated id = ?. Note that it is equivalent to id (inherent DTO language function) associatedIdNe Any associative property Type of associated entity's id property Associated id <> ? associatedIdIn Any associative property List Associated id in(...) associatedIdNotIn Any associative property List Associated id not in(...)","s":"All QBE Functions","u":"/jimmer-doc/docs/query/super_qbe","h":"#all-qbe-functions","p":1522},{"i":1547,"t":"Modify the DTO code: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) le(price) } ge(price) will specify the default alias minPrice, le(price) will specify the default alias maxPrice, so the above code can also be written as: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) as minPrice le(price) as maxPrice } As you can see, some QBE functions have built-in default alias functionality. Assuming the original property name is Prop, the default alias behaviors of all QBE functions are as follows: QBE Function Default alias eq (or no QBE function specified) prop ne Not supported, no alias specified will cause compile error gt minPropExclusive ge minProp lt maxPropExclusive le maxProp like prop notLike Not supported, no alias specified will cause compile error valueIn Not supported, no alias specified will cause compile error valueNotIn Not supported, no alias specified will cause compile error associatedIdEq or id If the association is a reference (non-collection), propId; otherwise, compile error associatedIdNe If the association is a reference (non-collection), excludedPropId; otherwise, compile error associatedIdIn If the association is a reference (non-collection), propIds; otherwise, compile error associatedIdNotNull If the association is a reference (non-collection), excludedPropIds; otherwise, compile error The compiled code is: Java Kotlin BookSpecification.java public class BookSpecification implements JSpecification { @Nullable private String name; @Nullable private BigDecimal minPrice; @Nullable private BigDecimal maxPrice; ...getters and setters omitted... @Override public void applyTo(SpecificationArgs args) { ...omitted... } } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( val name: String? = null, val minPrice: BigDecimal? = null, val maxPrice: BigDecimal? = null ) : KSpecification { override fun applyTo(args: KSpecificationArgs) { ...omitted... } } Execute: Java Kotlin BookSpecification specification = new BookSpecification(); specification.setName(\"GraphQL\"); specification.setMinPrice(new BigDecimal(40)); specification.setMaxPrice(new BigDecimal(40)); List books = bookRepository.find(specification); val specification = BookSpecification( name = \"GraphQL\", minPrice = BigDecimal(40), maxPrice = BigDecimal(60) ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ and tb_1_.PRICE >= ? /* 40 */ and tb_1_.PRICE <= ? /* 60 */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Comprehensive Example","u":"/jimmer-doc/docs/query/super_qbe","h":"#comprehensive-example","p":1522},{"i":1549,"t":"In previous examples, all filtering rules are for fields of the current table. Now let's filter on associated objects. Modify the DTO file as follows: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) le(price) flat(store) { ❶ like/i(name) as storeName } flat(authors) { ❷ like/i(firstName) as authorName } } We find that the code above uses the flat function. The flat function is discussed in detail in DTO Language #10.4-flat function, and will not be repeated here. info Since specification serves as a parameter for complex queries, it is very likely to be HTTP GET parameters. Using the flat function to eliminate associations and generate flattened DTO objects is more beneficial for developing HTTP GET APIs based on Spring MVC. ❶ Book.store is a reference association ❷ Book.authors is a collection association The compiled code is: Java Kotlin BookSpecification.java public class BookSpecification implements JSpecification { @Nullable private String name; @Nullable private BigDecimal minPrice; @Nullable private BigDecimal maxPrice; @Nullable private String storeName; @Nullable private String authorName; ...getters and setters omitted... @Override public void applyTo(SpecificationArgs args) { ...omitted... } } BookSpecification.kt package com.yourcompany.yourproject.dto; import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecification import org.babyfish.jimmer.sql.kt.ast.query.specification.KSpecificationArgs ...other imports omitted... data class BookSpecification( val name: String? = null, val minPrice: BigDecimal? = null, val maxPrice: BigDecimal? = null, val storeName: String? = null, val authorName: String? = null ) : KSpecification { override fun applyTo(args: KSpecificationArgs) { ...omitted... } } Execute: Java Kotlin BookSpecification specification = new BookSpecification(); specification.setStoreName(\"MANNING\"); specification.setAuthorName(\"a\"); List books = bookRepository.find(specification); val specification = BookSpecification( storeName = \"MANNING\", authorName = \"a\" ) val books = bookRepository.find(specification) The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ /* ❶ */ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME ilike ? /* %manning% */ and exists( /* ❷ */ select 1 from AUTHOR tb_3_ inner join BOOK_AUTHOR_MAPPING tb_4_ on tb_3_.ID = tb_4_.AUTHOR_ID where tb_1_.ID = tb_4_.BOOK_ID and tb_3_.FIRST_NAME ilike ? /* %a% */ ) ❶ Book.store is a reference association that does not break pagination safety. So only dynamic JOIN is needed to apply the filtering condition represented by the storeName property of the DTO object. ❷ Book.authors is a collection association that breaks pagination safety. So subqueries must be used instead of dynamic JOIN to apply the filtering condition represented by the authorName property of the DTO object.","s":"Associated Objects","u":"/jimmer-doc/docs/query/super_qbe","h":"#associated-objects","p":1522},{"i":1551,"t":"In previous examples, Jimmer generates multiple where conditions according to each property of the DTO object, and the relationship between these conditions is logical AND. But can logical OR be supported? In addition, the entity type Author has the lastName property in addition to the firstName property. Mapping only firstName to authorName in the previous example does not seem reasonable. Is there a better way? The above two issues are the same issue. To solve this problem, Super QBE supports logical OR, also known as multi-property mapping. Modify the DTO code as follows: ...export statement omitted... specification BookSpecification { like/i(name) ge(price) le(price) flat(store) { like/i(name) as storeName } flat(authors) { like/i(firstName, lastName) as authorName } } Here, the DTO property authorName maps two properties, firstName and lastName. This is called multi-property mapping. Multi-property mapping can only be used in specification and cannot be used in other types described in DTO Language. The types of multiple properties mapped by QBE functions must be completely consistent (but nullability is allowed to differ). For example, both firstName and lastName here are of type String. The DTO property of multi-property mapping must be aliased via as, otherwise compilation errors will occur. Not all QBE functions support multi-property mapping. QBE functions that support multi-property mapping are: eq ne null notNull valueIn associatedIdEq associatedIdIn Allowing all QBE functions to support multi-property mapping blindly would lead to ambiguous understanding. So there is this restriction. Repeating the query in the previous example generates the following SQL: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME ilike ? /* %manning% */ and exists( select 1 from AUTHOR tb_3_ inner join BOOK_AUTHOR_MAPPING tb_4_ on tb_3_.ID = tb_4_.AUTHOR_ID where tb_1_.ID = tb_4_.BOOK_ID and ( tb_3_.FIRST_NAME ilike ? /* %a% */ or tb_3_.LAST_NAME ilike ? /* %a% */ ) ) It is not difficult to see that multi-property mapping is logical OR.","s":"Logical OR","u":"/jimmer-doc/docs/query/super_qbe","h":"#logical-or","p":1522},{"i":1554,"t":"Although Jimmer entities are strongly typed, they are also dynamic and can express the ever-changing shape of data structures. Therefore, Jimmer supports ObjectFetcher, which can control the shape of the queried data structure and then uniformly return Jimmer entities. This is an extremely similar concept to GraphQL, but there are huge differences: GraphQL is an application layer protocol based on HTTP that can only expose this capability by building HTTP services, and only HTTP clients can enjoy this capability. For Jimmer, the ability to query arbitrary shapes is an inherent behavior of ORM that can be used programmed anywhere. You can use it to expose GraphQL services. As shown in the content of this section, you can also expose REST services. It can even be used within applications without crossing any remote boundaries.","s":"Basic Concepts","u":"/jimmer-doc/docs/quick-view/fetch/","h":"#basic-concepts","p":1552},{"i":1556,"t":"Java Kotlin Your browser does not support the video tag. Your browser does not support the video tag. info Compare to GraphQL GraphQL is based on HTTP services, which can only be experienced if it crosses the boundaries of HTTP services. In Jimmer, this is the underlying API for ORM, and you can use this capability in any code logic. Until now, the GraphQL protocol does not support recursive queries on self-associated properties with infinite depth; And Jimmer supports","s":"Demo","u":"/jimmer-doc/docs/quick-view/fetch/","h":"#demo","p":1552},{"i":1558,"t":"The comparison is as below: Return Entities Directly Use DTO Language Similarities Both can present DTO type definitions for the return type of each API to client developers Both can generate online OpenApi docs and TypeScript RPC code Both can show information in code comments to clients Differences Directly return entities (Easy) Need to use DTO language to quickly generate DTO types Need @FetchBy annotation in RestController to supplement type info for entity types Directly develop RestController based on the generated DTO types (Easy) More oriented to external API exposure Both external exposure and internal use are applicable tip No matter how users choose, Jimmer can elegantly solve the DTO Explosion Problem with development costs unimaginable in other JVM stacks.","s":"Comparison","u":"/jimmer-doc/docs/quick-view/fetch/export/comparison","h":"","p":1557},{"i":1560,"t":"Through the introduction of the previous article, we quickly previewed Jimmer's powerful ability to query arbitrary data structures at will. Jimmer entities are both strongly typed and dynamic. This dynamicity can easily express any data structure and return it directly. This eliminates DTO explosions However, for client developers, getting a dynamic data structure that is possible at all is a very painful thing. The client wants each query API to precisely define the type of its returned data format. To this end, Jimmer provides two methods, both of which can provide first-class API support for clients. Directly return dynamic entities As a comprehensive solution, Jimmer is not limited to ORM. It generates client code for HTTP clients. In the generated client code, precise DTO types are defined for each specific data structure. tip If the service itself does not use the query results, but directly as an HTTP Response, it is suitable to use this method. Jimmer supports a programming language called DTO that can quickly define DTO types for output data structures at extremely low cost. tip When any of the following is met, this method can be adopted. The query results are not intended to be returned directly as HTTP Response, but the service itself uses them. At this point, the business code that uses the query results does not want to get dynamic entities with slightly weaker compile-time safety (although Jimmer entities are still strongly typed). The front-end team does not accept multiple interrelated objects and requires all non-collection association attributes to be flat operated to form an ultra-large orphan object, which seems very stubborn. (This situation will be introduced in detail in related chapters, not discussed in depth here).","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/fetch/export/","h":"","p":1559},{"i":1563,"t":"Pagination query is a very characteristic function of Jimmer, which can greatly improve development efficiency. Pagination requires executing two SQL queries: Query the total number of rows that meet the criteria, the result of which can calculate how many pages there are in total, and whether the user's page number is out of bounds. info For discussion purposes, Jimmer refers to this SQL as count-query. Query all data within the current page, the number of returned data rows does not exceed the page size, and skip all data from previous pages. info For discussion purposes, Jimmer refers to this SQL as data-query. tip Jimmer's feature: The developer only needs to write the data-query (actual data-query without limit and offset), and the framework automatically generates the count-query. Not only can Jimmer automatically generate count-query, it can also optimize count-query. This optimization will be discussed in next article.","s":"Features of Jimmer Pagination","u":"/jimmer-doc/docs/query/paging/usage","h":"#features-of-jimmer-pagination","p":1561},{"i":1565,"t":"When used with Spring Data, developers derive custom Repository interfaces from JRepository/KRepository, and there are two options for adding query methods to the custom interfaces: Declare abstract methods according to certain conventions, and let Jimmer automatically implement them. caution This usage is too simple, hiding all details, and is not suitable for discussing pagination here. You can check Spring Section/Spring Data Style/Abstract Methods to learn how to implement pagination queries in this way. Directly define default methods in the custom interface and implement the query logic yourself. Java Kotlin BookRepository.java import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; ...other imports omitted... public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page findBooks( Pageable pageable, @Nullable String name, @Nullable String storeName, ) { return sql() .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) ❶ .select(table) .fetchPage( ❷ pageable.getPageNumber(), pageable.getPageSize() SpringPageFactory.getInstance() ); } } BookRepository.kt import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable ...other imports omitted... interface BookRepository : KRepository { fun findBooks( pageable: Pageable, name: String? = null, storeName: String? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } storeName?.takeIf { it.isNotEmpty() }?.let { where(table.store.name eq it) } orderBy(pageable.sort) ❶ select(table) } .fetchSpringPage(pageable) ❷ } ❶ Since Spring Data's Pageable contains dynamic sorting, dynamic sorting needs to be applied. ❷ Pagination query, returns org.springframework.data.domain.Page type of object Jimmer pagination can use any Page object, whether it's Spring Data's Page, Jimmer's own Page, or even Page defined by third parties. Here, the Java code uses SpringPageFactory.getInstance() to request the current pagination operation to return Spring Data's Page. In fact, the Kotlin code can also use SpringPageFactory.getInstance() for the same purpose, but in Kotlin there is a more convenient extension method fetchSpringPage(). If we execute: Page page = bookRepository.findBooks( PageRequest.of( 1, 5, SortUtils.toSort(\"name asc, edition desc\") ), null, null ) caution In Spring Data, the page number of Pageable starts from 0 instead of 1, so this queries the second page. It will generate two SQL statements: count-query select count(tb_1_.ID) from BOOK tb_1_ data-query (assuming the database is H2) select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 5 */, ? /* 5 */ This example allows us to understand Jimmer's pagination functionality, but Jimmer's Spring API hides some details. Therefore, next we bypass Spring Data and explain more clearly from a lower level perspective.","s":"When Used with Spring Data","u":"/jimmer-doc/docs/query/paging/usage","h":"#when-used-with-spring-data","p":1561},{"i":1568,"t":"Since Spring Data is not used, naturally org.springframework.data.domain.Page cannot be used. For this, Jimmer defines org.babyfish.jimmer.Page with the following definition: Page.java package org.babyfish.jimmer; public class Page { private final List rows; private final int totalRowCount; private final int totalPageCount; ...Omit other fields... } It can be seen that Jimmer's own Page is much simpler than Spring Data's Page, the differences are: info org.springframework.data.domain.Page is designed for server-side paging so that the page must still maintain its previous state after being refreshed. A lot of information (such as tedious sort information) needs to be returned verbatim to the client, so it is very complex. org.babyfish.jimmer.Page is designed for rich client pages. Such client pages are stateful applications themselves, the server only needs to provide pure data services, so returning just the bare necessities is enough, hence very simple.","s":"Jimmer's Page object","u":"/jimmer-doc/docs/query/paging/usage","h":"#jimmers-page-object","p":1561},{"i":1570,"t":"Java Kotlin public Page findBooks( int pageIndex, int pageSize, @Nullable String name, @Nullable String storeName ) { return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(table.name().asc(), table.edition().desc()) .select(table) .fetchPage(pageIndex, pageSize); } fun findBooks( pageIndex: Int, pageSize: Int, name: String? = null, storeName: String? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } storeName?.takeIf { it.isNotEmpty() }?.let { where(table.store.name eq it) } orderBy(table.name.asc(), table.edition.desc()) select(table) } .fetchPage(pageIndex, pageSize) The finally generated SQL is the same as the example discussed earlier with Spring Data, so I won't repeat it here.","s":"Implement Business Logic","u":"/jimmer-doc/docs/query/paging/usage","h":"#implement-business-logic","p":1561},{"i":1572,"t":"In the above examples, we discussed language differences between Java and Kotlin, as well as using or not using Spring Data. The underlying logic of these behaviors is the same, taking Java as an example: BookTable table = Tables.BOOK_TABLE; ConfigurableRootQuery query = ❶ sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(table.name().asc(), table.edition().desc()) int totalCount = query.fetchUnlimitedCount(); ❷ int totalPage = (totalCount + pageSize - 1) / pageSize; if (pageIndex >= totalPage) { return new Page(totalCount, totalPage, Collections.emptyList()); } List entities = query .limit(pageSize, pageIndex * pageSize) ❸ .execute(); ❹ return new Page<>( ❺ totalCount, totalPage, entities ) caution To simplify the discussion, this pseudocode does not consider reverse sorting optimization. ❶ Create the query, but do not execute it yet. I can call it the template query. ❷ Based on the original template query without modification, generate the count-query, then execute the count-query to get the total number of rows before pagination. Here the fetchUnlimitedCount method is a shortcut API, and its underlying logic is: public interface ConfigurableRootQuery, R> extends ... { default int fetchUnlimitedCount() { return count(null); } default int fetchUnlimitedCount(Connection con) { return reselect((q, t) -> q.select(t.count())) .withoutSortingAndPaging() .execute(con) .get(0) .intValue(); } } reselect((q, t) -> q.select(t.count())): The count-query does not query data, but queries COUNT withoutSortingAndPaging(): The count-query does not need the sorting clause order by nor the paging clause (such as H2's limit ? offset ?) tip Not only can Jimmer automatically generate count-query, it can also automatically optimize count-query, please refer to Join Optimization. ❸ limit(limit, offset): Based on the original template query without modification, generate the real data-query with pagination limits. ❹ Execute the data-query generated in ❸ to get the data within one page. ❺ Combine the data obtained in ❷ and ❹ into the page object and return it.","s":"Internal Mechanism","u":"/jimmer-doc/docs/query/paging/usage","h":"#internal-mechanism","p":1561},{"i":1574,"t":"This section discusses the SQL implementation of data-query with pagination limits under different databases. Consider the following single page data query: Java Kotlin List books = query .limit(/*limit*/ 10, /*offset*/ 90) .execute(); val books = query .limit(limit = 10, offset = 90) .execute() Here limit(limit, offset) sets the pagination range. Different databases have vastly different support for pagination queries. So when creating SqlClient, the dialect needs to be specified. Spring Data configuration method: Add a configuration in application.properties or application.yml called jimmer.dialect with value as the class name of the dialect class provided by Jimmer: jimmer: dialect: org.babyfish.jimmer.sql.dialect.H2Dialect Non-Spring Data configuration method: Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setDialect(new H2Dialect()) ...other code omitted... .build(); val sqlClient = newKSqlClient { setDialect(H2Dialect()) ...other code omitted... } Different dialects will use different SQL to implement the limit query:","s":"Dialects","u":"/jimmer-doc/docs/query/paging/usage","h":"#dialects","p":1561},{"i":1576,"t":"info Default behavior includes DefaultDialect, H2Dialect and PostgresDialect. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ? order by tb_2_.NAME asc, tb_1_.NAME asc limit ? offset ?","s":"Default Behavior","u":"/jimmer-doc/docs/query/paging/usage","h":"#default-behavior","p":1561},{"i":1578,"t":"select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ? order by tb_2_.NAME asc, tb_1_.NAME asc limit ?, ?","s":"MySqlDialect","u":"/jimmer-doc/docs/query/paging/usage","h":"#mysqldialect","p":1561},{"i":1580,"t":"When offset is not 0: select * from ( select core__.*, rownum rn__ from ( select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_1_.PRICE between ? and ? order by tb_2_.NAME asc, tb_1_.NAME asc ) core__ where rownum <= ? ❶ ) limited__ where rn__ > ? ❷ Where the variable at ❶ is limit + offset, and at ❷ is offset. When offset is 0: select core__.* from ( select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID core__ where rownum <= ? ❶ Where ❶ is the variable limit.","s":"OracleDialect","u":"/jimmer-doc/docs/query/paging/usage","h":"#oracledialect","p":1561},{"i":1582,"t":"The object fetcher defines the shape of the queried object, allowing the queried object to carry more associated objects. This feature can be used together with pagination. info After the paged query is completed, Jimmer launches queries for other association objects, only for objects within a single page. Take the Spring Data mode as an example. Now, let's modify the BookRepository we discussed earlier to support object fetchers: Java Kotlin BookRepository.java import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; ...other imports omitted... public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page findBooks( Pageable pageable, @Nullable Fetch fetcher, @Nullable String name, @Nullable String storeName ) { return sql() .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().eq(name) ) .whereIf( storeName != null && !storeName.isEmpty(), table.store().name().eq(storeName) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) .select( table.fetch(fetcher) ) .fetchPage( pageable.getPageNumber(), pageable.getPageSize(), SpringPageFactory.getInstance() ); } } BookRepository.kt import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable ...other imports omitted... interface BookRepository : KRepository { fun findBooks( pageable: Pageable, fetcher: Fetcher? = null, name: String? = null, storeName: String? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name eq it) } storeName?.takeIf { it.isNotEmpty() }?.let { where(table.store.name eq it) } orderBy(pageable.sort) select( table.fetch(fetcher) ) } .fetchSpringPage(pageable) } If called as follows: Java Kotlin Page.java Page page = bookRepository.findBooks( PageRequest.of( 1, 5, SortUtils.toSort(\"name asc, edition desc\") ), Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ), null, null ); Page.kt val page = bookRepository.findBooks( PageRequest.of( 1, 5, SortUtils.toSort(\"name asc, edition desc\") ), newFetcher(Book::class).by { allScalarFields() store { allScalarFields() } authors { allScalarFields() } } ) It will generate the following 4 SQL statements: count-query select count(tb_1_.ID) from BOOK tb_1_ data-query (assuming the database is H2) select tb_1_.ID, tb_1_.CREATED_TIME, tb_1_.MODIFIED_TIME, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc limit ? /* 5 */, ? /* 5 */ Query the many-to-one association Book.store for the 5 paged objects select tb_1_.ID, tb_1_.NAME from BOOK_STORE tb_1_ where tb_1_.ID in ( ? /* 2 */, ? /* 1 */ ) info Although there are 5 paged objects, their foreign key STORE_ID only has two values. Query the many-to-many association Book.authors for the 5 paged objects select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR tb_1_ inner join BOOK_AUTHOR_MAPPING tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ? /* 10 */, ? /* 3 */, ? /* 2 */, ? /* 1 */, ? /* 9 */ ) Finally, in the obtained pagination, each object conforms to the data structure of the object fetcher. { \"content\":[ // Current page { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\", \"website\":null }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81, \"store\":{ \"id\":2, \"name\":\"MANNING\", \"website\":null }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82, \"store\":{ \"id\":2, \"name\":\"MANNING\", \"website\":null }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] } ], \"totalPages\":3, // Total page count is 3 \"totalElements\":12, // Total row count before pagination is 12 ...Spring Data's Page object has too many properties, omitted... }","s":"Used with Object Fetcher","u":"/jimmer-doc/docs/query/paging/usage","h":"#used-with-object-fetcher","p":1561},{"i":1585,"t":"From the previous article, we know Jimmer SQL DSL is inherently designed for arbitrary complex dynamic queries, completely different from other frameworks' SQL DSLs that only provide strong typing experience. But there are two issues: With more and more parameters introduced in the previous article, the method signatures become less Java-friendly. We urgently need to encapsulate all the query parameters into one object. I'm really lazy. I want to achieve all the capabilities introduced in the previous article, but I don't want to write those code. I just want to write one line of code. Jimmer's built-in DTO language can quickly solve the above two problems.","s":"Can It Be Simpler","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#can-it-be-simpler","p":1583},{"i":1587,"t":"Since in the article Query Arbitrary Shape/Exposing Features/Return Output DTO, we have already had some understanding about the DTO language when introducing Output DTO, this article does not repeat it. Install the DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This step is not required but highly recommended) Create a new directory src/main/dto Create a file Book.dto under src/main/dto and write the code below: Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto specification BookSpecification { like/i(name) ge(price) // Default alias: minPrice le(price) // Default alias: maxPrice flat(store) { as(^ -> store) { like/i(name) like/i(website) } } flat(authors) { like/i(firstName, lastName) as authorName gender as authorGender } } ...Omit other DTO type definitions... info Different from the Output/Input DTO we discussed before, here the query Specification DTO uses the specification modifier. The QBE functions used extensively inside this Specification DTO are self-explanatory. As this article belongs to the quick tour section, we do not explain them in detail.","s":"Define Specification DTO","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#define-specification-dto","p":1583},{"i":1589,"t":"After compiling the project, Jimmer will automatically generate the following code: Java Kotlin BookSpecification.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class BookSpecification implements JSpecification { ❷ @Nullable private String name; @Nullable private BigDecimal minPrice; @Nullable private BigDecimal maxPrice; @Nullable private String storeName; @Nullable private String storeWebsite; @Nullable private String authorName; @Nullable private Gender authorGender; @Override public void applyTo(SpecificationArgs args) { ❸ ...Omit complex dynamic query logic... } ...Omit getters, setters, hashCode, equals, toString... } BookSpecification.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class BookSpecification( val name: String? = null, val minPrice: BigDecimal? = null, val maxPrice: BigDecimal? = null, val storeName: String? = null, val storeWebsite: String? = null, val authorName: String? = null, val authorGender: Gender? = null ) : KSpecification { ❷ override applyTo(args: KSpecificationArgs) { ❸ ...Omit complex dynamic query logic... } } ❶ Reminds developers that this class is auto-generated by Jimmer at compile time ❷ Interface implemented by the Specification DTO ❸ This class knows how to generate SQL predicates","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#generated-code","p":1583},{"i":1591,"t":"Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( BookSpecification specification, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(specification) .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( specification: BookSpecification, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(specification) select(table.fetch(table)) } .execute() } We can see that with only one line of code, complex dynamic queries can be achieved. It has the same capabilities as the last example in the previous article. No need to repeat here.","s":"Usage","u":"/jimmer-doc/docs/quick-view/dsl/super_qbe","h":"#usage","p":1583},{"i":1593,"t":"Through the previous chapters, we already have a basic impression of Jimmer. Now we can start practicing. In this series of articles, we will introduce how to create your own Jimmer project from scratch.","s":"Get Started","u":"/jimmer-doc/docs/quick-view/get-started/","h":"","p":1592},{"i":1596,"t":"The examples in this tutorial require the following four entity types: BookStore, Book, Author: Demonstrate various associations including one-to-many, many-to-one, many-to-many. TreeNode: Demonstrates infinite recursion (self-associated properties), include recursive queries and recursive saving.","s":"UML","u":"/jimmer-doc/docs/quick-view/get-started/create-database","h":"#uml","p":1594},{"i":1598,"t":"This tutorial uses MySQL. Create a new SQL file jimmer-demo.sql with the following code: create database jimmer_demo; use jimmer_demo; create table book_store( id bigint unsigned not null auto_increment primary key, name varchar(50) not null, website varchar(100) ) engine=innodb; ... create table book ( id bigint unsigned not null auto_increment primary key, name varchar(50) not null, edition integer not null, price numeric(10, 2) not null, store_id bigint unsigned ) engine=innodb; ... create table author( id bigint unsigned not null auto_increment primary key, first_name varchar(25) not null, last_name varchar(25) not null, gender char(1) not null, created_time datetime not null, modified_time datetime not null ) engine=innodb; ... /* Many-to-many relationship between entities requires join table in ORM implementation. This table stores many-to-many mapping between books and authors. It is a join table, not an entity table, so no corresponding entity in the UML diagram above. */ create table book_author_mapping( book_id bigint unsigned not null, author_id bigint unsigned not null ) engine=innodb; ... create table tree_node( node_id bigint unsigned not null auto_increment primary key, name varchar(20) not null, parent_id bigint unsigned ) engine=innodb; ... insert into book_store(id, name) values (1, 'O''REILLY'), (2, 'MANNING') ; insert into book(id, name, edition, price, store_id) values (1, 'Learning GraphQL', 1, 50, 1), (2, 'Learning GraphQL', 2, 55, 1), (3, 'Learning GraphQL', 3, 51, 1), (4, 'Effective TypeScript', 1, 73, 1), (5, 'Effective TypeScript', 2, 69, 1), (6, 'Effective TypeScript', 3, 88, 1), (7, 'Programming TypeScript', 1, 47.5, 1), (8, 'Programming TypeScript', 2, 45, 1), (9, 'Programming TypeScript', 3, 48, 1), (10, 'GraphQL in Action', 1, 80, 2), (11, 'GraphQL in Action', 2, 81, 2), (12, 'GraphQL in Action', 3, 80, 2) ; insert into author(id, first_name, last_name, gender, created_time, modified_time) values (1, 'Eve', 'Procello', 'F', now(), now()), (2, 'Alex', 'Banks', 'M', now(), now()), (3, 'Dan', 'Vanderkam', 'M', now(), now()), (4, 'Boris', 'Cherny', 'M', now(), now()), (5, 'Samer', 'Buna', 'M', now(), now()) ; insert into book_author_mapping(book_id, author_id) values (1, 1), (2, 1), (3, 1), (1, 2), (2, 2), (3, 2), (4, 3), (5, 3), (6, 3), (7, 4), (8, 4), (9, 4), (10, 5), (11, 5), (12, 5) ; insert into tree_node( node_id, name, parent_id ) values (1, 'Home', null), (2, 'Food', 1), (3, 'Drinks', 2), (4, 'Coca Cola', 3), (5, 'Fanta', 3), (6, 'Bread', 2), (7, 'Baguette', 6), (8, 'Ciabatta', 6), (9, 'Clothing', 1), (10, 'Woman', 9), (11, 'Casual wear', 10), (12, 'Dress', 11), (13, 'Miniskirt', 11), (14, 'Jeans', 11), (15, 'Formal wear', 10), (16, 'Suit', 15), (17, 'Shirt', 15), (18, 'Man', 9), (19, 'Casual wear', 18), (20, 'Jacket', 19), (21, 'Jeans', 19), (22, 'Formal wear', 18), (23, 'Suit', 22), (24, 'Shirt', 22) ; This SQL file shows: Entity tables - book_store, book, author, tree_node map to entities in UML Join table - book_author_mapping represents many-to-many mapping between Book and Author note This is a basic database structure. More fields will be added in later tutorials. See https://github.com/babyfish-ct/jimmer-examples/blob/main/env-with-cache/maxwell/jimmer-demo.sql for full SQL.","s":"Create SQL File","u":"/jimmer-doc/docs/quick-view/get-started/create-database","h":"#create-sql-file","p":1594},{"i":1599,"t":"Install Docker. Open a command line, navigate to the SQL file directory, and run: docker run \\ --name jimmer-demo-mysql \\ ... mysql \\ --lower_case_table_names=1 docker cp jimmer-demo.sql jimmer-demo-mysql:/var/jimmer-demo.sql docker exec jimmer-demo-mysql /bin/sh -c \\ 'mysql -uroot -p123456 findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) ❶ .where(table.price().betweenIf(minPrice, maxPrice)) ❷ .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) ❶ where(table.price.`between?`(minPrice, maxPrice)) ❷ select(table.fetch(table)) } .execute() } Where the meaning of the fetcher parameter has been introduced in Quick Tour/Fetch Any Shape, this article does not repeat it and readers can ignore it. ❶ Different from the static predicate ilike, ilikeIf/ilike? is a dynamic predicate that decides whether to add the SQL condition based on parameters. If name is neither null nor empty string, the SQL condition name ilike :name will be added. ❷ Different from the static predicate between, betweenIf/between? is a dynamic predicate that decides whether to add the SQL condition based on parameters. There are four cases: If both minPrice and maxPrice are not null, the SQL condition price between :minPrice and :maxPrice will be added. If only minPrice is not null, the SQL condition name >= :minPrice will be added. If only maxPrice is not null, the SQL condition name <= :maxPrice will be added. If both minPrice and maxPrice are null, no SQL condition will be added. Now let's see the effects: When all three parameters are null: Java Kotlin List books = bookRepository.findBooks( null, // name null, // minPrice null, // maxPrice null ); val books = bookRepository.findBooks() No where condition will be generated and the SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ // No SQL predicates When all three parameters are not null: Java Kotlin List books = bookRepository.findBooks( \"GraphQL\", // name new BigDecimal(20), // minPrice new BigDecimal(50), // maxPrice null ); val books = bookRepository.findBooks( name = \"GraphQL\", minPrice = BigDecimal(20), maxPrice = BigDecimal(50) ) All where conditions will be generated and the SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where lower(tb_1_.NAME) like ? /* %graphql% */ and (tb_1_.PRICE between ? /* 20 */ and ? /* 50 */)","s":"Dynamic Predicates","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#dynamic-predicates","p":1600},{"i":1607,"t":"In the previous examples, our dynamic SQL conditions are all applied to the current entity (Book). Next, we use the reference association (one-to-one or many-to-one) to get associated object and add SQL conditions for it. The many-to-one association Book.store is associated with the BookStore entity. Let us add dynamic SQL conditions for BookStore.name and BookStore.website. Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .where(table.price().betweenIf(minPrice, maxPrice)) .where(table.store().name().ilikeIf(storeName)) ❶ .where(table.store().website().ilikeIf(storeWebsite)) ❷ .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) ❶ where(table.store.name `ilike?` storeWebsite) ❷ select(table.fetch(table)) } .execute() } tip The path table.store() in Java code or table.store in Kotlin code is called a dynamic table join path, which is represented by the following SQL logic from BOOK b inner join BOOK_STORE s on b.STORE_ID = s.ID Here is the translation to English: You can also use outer join. The Java code is table.store(JoinType.LEFT), and the Kotlin code is table.storeId?. In fact, if the entity model is richer, you can write a longer path, such as 'table.store().city().province()'. Here, just for the quick preview, there is no need to build richer entity model to demonstrate a longer join path, and the shortest join path 'table.store()' is enough. ❶ When 'storeName' is neither null nor empty string Associate to the BookStore entity via the association Book.store Add the SQL condition to 'BookStore.name' ❷ When 'storeWebsite' is neither null nor empty string Associate to the BookStore entity via the association Book.store Add the SQL condition to 'BookStore.website'","s":"Define dynamic table joins","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#define-dynamic-table-joins","p":1600},{"i":1609,"t":"If both the storeName and storeWebsite parameters are null Java Kotlin List books = bookRepository.findBooks( null, null, null, null, // storeName null, // storeWebsite null ); val books = bookRepository.findBooks() This will cause the 'ilikeIf'/'ilike?' at ❶ and ❷ to be invalid, further causing 'table.store()'/'table.store' to be ignored. That is, although a table join is created, it is not used. tip If a table join is created in the DSL but is not actually used, the table join will be automatically ignored and there will be no corresponding SQL join in the generated SQL statement. Note: Jimmer does not have the concept of join fetch like JPA. The only purpose of a join is to be referenced by other SQL expressions, so any unused join objects will be ignored. The generated SQL statement is as follows select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ // No SQL table joins","s":"Ignore useless table joins","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#ignore-useless-table-joins","p":1600},{"i":1611,"t":"If both storeName and storeWebsite parameters are not null: Java Kotlin List books = bookRepository.findBooks( null, null, null, \"M\", // storeName \".com\", // storeWebsite null ); val books = bookRepository.findBooks( storeName = \"M\", storeWebsite = \".com\" ) This will make both ❶ and ❷ ilikeIf/ilike? effective, which further makes both table joins table.store()/table.store effective. That is, the table join is created and used multiple times. tip If conflicting table joins of the same association are created multiple times in DSL, all the conflicting joins will be automatically merged into one JOIN in the final SQL without duplicate JOINs. The generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ /* Multiple conflicting table joins are merged into one */ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where lower(tb_2_.NAME) like ? /* %m% */ and lower(tb_2_.WEBSITE) like ? /* %.com% */","s":"Merge Conflicting Table Joins","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#merge-conflicting-table-joins","p":1600},{"i":1614,"t":"In the previous examples, the dynamic table joins are created based on references (one-to-one or many-to-one). For collection associations (one-to-many or many-to-many), we can create implicit subqueries. Actually, we can also create dynamic table joins based on collection associations using special DSL syntax. But it is more recommended to create implicit subqueries based on collection associations. Next, we demonstrate related features using the many-to-many association Book.authors. Java Kotlin BookRepository.java @Repository public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } List findBooks( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName, @Nullable Gender authorGender, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .where(table.price().betweenIf(minPrice, maxPrice)) .where(table.store().name().ilikeIf(storeName)) .where(table.store().website().ilikeIf(storeWebsite)) .where( table.authors(author -> ❶ Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .where( table.authors(author -> ❷ author.gender().eqIf(authorGender) ) ) .select(table.fetch(fetcher)) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, authorName: String? = null, authorGender: String? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.name `ilike?` storeWebsite) where += table.authors { ❶ or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } where += table.authors { ❷ gender `eq?` authorGender } select(table.fetch(table)) } .execute() } The two SQL conditions based on lambda expressions at ❶ and ❷ are implicit subqueries. Actually these two implicit subqueries can be merged into one. But two subqueries are created on purpose here to demonstrate subsequent features. ❶ Create the subquery of associated Author objects through the many-to-many association Book.authors and check if Author's firstName or lastName property fuzzy matches the authorName parameter. ❷ Create the subquery of associated Author objects through the many-to-many association Book.authors and check if Author's gender property equals the authorGender parameter. tip If effective, implicit subqueries will eventually generate SQL exists statements. The subqueries in SQL exists usually have a condition for joining parent and child queries. However, from the above code, we can see that all the conditions in subqueries are applied to Author objects without the join condition. Actually, the join condition between parent and child queries is implicitly included by implicit subqueries. It is always generated automatically. So users only need to write conditions related to associated objects. Note: Here we are discussing implicit subqueries instead of normal subqueries (Jimmer also supports normal subqueries which are not included in the quick tour). The rules here do not apply to normal subqueries.","s":"Define implicit subqueries","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#define-implicit-subqueries","p":1600},{"i":1616,"t":"If both authorName and authorGender parameters are null: Java Kotlin List books = bookRepository.findBooks( null, null, null, null, null, null, // authorName null, // authorGender null ); val books = bookRepository.findBooks() The first implicit subquery will be ignored: Java Kotlin where( ⑤ table.authors(author -> ④ Predicate.or( ③ author.firstName().ilikeIf(authorName), ① author.lastName().ilikeIf(authorName) ② ) ) ) where += ⑤ table.authors { ④ or( ③ firstName `ilike?` authorName, ① lastName `ilike?` authorName ② ) } When authorName is null or empty string, At ① and ②, ilikeIf/ilike? will be ignored and return null As expressions at ① and ② are null, the or expression at ③ will become null the or expression at ③ being null will lead to no SQL conditions for the subquery, so the predicate based on implicit subquery at ④ is null. The expression at ④ being null make where at ⑤ become meaningless, so the whole operation will be ignored. That is, the first implicit subquery is ignored. Similarly, the second implicit subquery will also be ignored. The final SQL does not contain any subqueries: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ // No SQL sub queries","s":"Ignore useless subqueries","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#ignore-useless-subqueries","p":1600},{"i":1618,"t":"If both authorName and authorGender parameters are not null: Java Kotlin List books = bookRepository.findBooks( null, null, null, null, null, \"A\", // authorName Gender.MALE, // authorGender null ); val books = bookRepository.findBooks( authorName = \"A\", authorGender = Gender.MALE ) In this case, two implicit subqueries based on the same association (Book.authors) will take effect. tip If conflicting implicit subqueries of the same association are created multiple times in DSL, all the conflicting subqueries will be automatically merged into one subquery in the final SQL. The final generated SQL is: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where /* Multiple conflicting implicit subqueries are merged into one */ exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where /* Parent-child query join condition implied by the implicit subquery */ tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) and tb_2_.GENDER = ? /* M */ ) There is a restriction on conflicting implicit subquery merges, multiple subqueries that are merged must be inside the same context of and, or, or not.","s":"Merge conflicting subqueries","u":"/jimmer-doc/docs/quick-view/dsl/feature","h":"#merge-conflicting-subqueries","p":1600},{"i":1621,"t":"caution At present, this part of the content supports Spring, and more web frameworks will be supported in the future. To export client code, you first need to enable Web API analysis capabilities. Developers have two options Use @org.babyfish.jimmer.client.EnableImplicitApi to decorate any class in the project where the RestController belongs. For Spring Boot applications, the Application class is a good choice. Use @org.babyfish.jimmer.client.Api to decorate all RestController classes that need to be exported and their HTTP Mapping methods. The first method is relatively simple, so applying the @EnableImplicitApi annotation to the Spring Boot Application class is enough. Since the code is too simple, there is no need to demonstrate.","s":"Enable Web API Analysis","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#enable-web-api-analysis","p":1619},{"i":1623,"t":"As an example, there is no complex business logic. We ignore the Service layer and write BookController directly based on the BookRepository in the previous article, as follows: Java Kotlin BookController.java @RestController public class BookController implements Fetchers { private final BookRepository bookRepository; public BookController(BookRepository bookRepository) { this.bookRepository = bookRepository; } @Nullable @GetMapping(\"/book/{id}\") public @FetchBy(\"COMPLEX_BOOK\") Book ❶ findBookById(@PathVariable(\"id\") long id) { return bookRepository.findBookById( id, COMPLEX_BOOK ❷ ); } @GetMapping(\"/books\") public List< @FetchBy(\"SIMPLE_BOOK\") Book ❸ > findBooksByName( @RequestParam(name = \"name\", required = false) String name ) { return bookRepository.findBooksByName( name, SIMPLE_BOOK ❹ ); } /** * Simple Book DTO which can only access `id` and `name` of `Book` itself */ private static final Fetcher SIMPLE_BOOK = ❺ BOOK_FETCHER .name(); /** * Complex Book DTO which can access not only properties of `Book` itself, * but also associated `BookStore` and `Author` objects with names */ private static final Fetcher COMPLEX_BOOK = ❻ BOOK_FETCHER .allScalarFields() .store( BOOK_STORE_FETCHER.name() ) .authors( AUTHOR_FETCHER .firstName() .lastName() ); } BookController.kt @RestController class BookController( private val bookRepository: BookRepository ) { @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long ): @FetchBy(\"COMPLEX_BOOK\") Book = ❶ bookRepository.findBookById( id, COMPLEX_BOOK ❷ ) @GetMapping(\"/books\") fun findBooksByName( @RequestParam(required = false) name: String ): List< @FetchBy(\"SIMPLE_BOOK\") Book ❸ > = bookRepository.findBooksByName( name, SIMPLE_BOOK ❹ ) companion object { /** * Simple Book DTO which can only access `id` and `name` of `Book` itself */ val SIMPLE_BOOK = ❺ newFetcher(Book::class).by { name() } /** * Complex Book DTO which can access not only properties of `Book` itself, * but also associated `BookStore` and `Author` objects with names */ private val COMPLEX_BOOK = ❻ newFetcher(Book::class).by { allScalarFields() store { name() } authors { firstName() lastName() } } } } The focus is on the 6 numbered items: ❶ Declare that the exact shape of the Book object returned by the findBookById method is defined by the static variable COMPLEX_BOOK ❷ The internal implementation of the findBookById method needs to be consistent with the external declaration at ❶, querying the Book object in the shape of COMPLEX_BOOK ❸ Declare that the exact shape of each Book object in the List returned by the findBooksByName method is defined by the static variable SIMPLE_BOOK ❹ The internal implementation of the findBooksByName method needs to be consistent with the external declaration at ❸, querying the Book object in the shape of SIMPLE_BOOK ❺ The definition of the SIMPLE_BOOK shape is used both at ❸ as part of the external API declaration and at ❹ to control the shape of the returned data structure ❻ The definition of the COMPLEX_BOOK shape is used both at ❶ as part of the external API declaration and at ❷ to control the shape of the returned data structure","s":"Write RestController","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#write-restcontroller","p":1619},{"i":1625,"t":"To recognize the Jimmer-specific annotation @FetchBy, Jimmer gives OpenAPI/Swagger a set of highly distinctive implementations. Without using any other frameworks in the JVM ecosystem for automatically generating OpenAPI/Swagger, just modify application.yml (or application.properties) as follows: application.yml jimmer: ...Omit other configurations... client: openapi: path: /openapi.yml ui-path: /openapi.html properties: info: title: My Web Service description: | Restore the DTO explosion that was eliminated by server-side developers version: 1.0 Start the web project and access http://localhost:8080/openapi.html with a browser to see: Expand /books to see that each element in the returned collection is a relatively simple DTO object Expand /books/{id} to see that the return type is a relatively complex DTO type","s":"View API Documentation","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#view-api-documentation","p":1619},{"i":1627,"t":"Modify application.yml (or application.properties) to add support for TypeScript: application.yml jimmer: ...Omit other configurations... client: openapi: ...Omit openapi related configurations... ts: path: /ts.zip Start the web project, download http://localhost:8080/ts.zip, unzip it, and you can see the TypeScript client code defines BookController as follows: services/BookController.ts import type {Executor} from '../'; import type {BookDto} from '../model/dto/'; export class BookController { constructor(private executor: Executor) {} async findBookById(options: BookControllerOptions['findBookById']): Promise< BookDto['BookController/COMPLEX_BOOK'] > { ...Omit specific logic... } async findBooksByName(options: BookControllerOptions['findBooksByName']): Promise< ReadonlyArray< BookDto['BookController/SIMPLE_BOOK'] > > { ...Omit specific logic... } } export type BookControllerOptions = { 'findBookById': { readonly id: number }, 'findBooksByName': { readonly name?: string | undefined } } Where BookDto['BookController/COMPLEX_BOOK'] and BookDto['BookController/SIMPLE_BOOK'] are the restored DTO types in the TypeScript client code generated by Jimmer. You can open the model/dto/BookDto.ts file to view their definitions as follows: model/dto/BookDto.ts export type BookDto = { /** * Complex Book DTO which can access not only properties of `Book` itself, * but also associated `BookStore` and `Author` objects with names */ 'BookController/COMPLEX_BOOK': { readonly id: number; readonly name: string; readonly edition: number; readonly price: number; readonly store?: { readonly id: number; readonly name: string; } | null | undefined; readonly authors: ReadonlyArray<{ readonly id: number; readonly firstName: string; readonly lastName: string; }>; } /** * Simple Book DTO which can only access `id` and `name` of `Book` itself */ 'BookController/SIMPLE_BOOK': { readonly id: number; readonly name: string; } }","s":"Generate TypeScript","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#generate-typescript","p":1619},{"i":1629,"t":"Through the above demonstration, we see that the server side does not need to define any Java/Kotlin types related to DTOs, while the client sees that each specific business API automatically defines precise DTO return types. In this way, both the server side and the client side get the programming models they expect. This article focuses on demonstrating this powerful feature without discussing how to add textual descriptions to various parts of the API (e.g. types, API methods, API parameters, object properties). tip Jimmer provides the simplest solution to these issues. Java/Kotlin developers only need to write the most basic documentation comments, and all documentation comments are automatically copied to the client API. This feature is simple. Readers can experiment on their own without elaboration here.","s":"Document Comments","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#document-comments","p":1619},{"i":1631,"t":"If the associated object has only the id property, the associated id is better than the associated object. For example: Using the associated object will lead to a large number of objects with only the id property, making the results slightly redundant: { \"id\" : 1, \"name\" : \"Learning GraphQL\", \"edition\" : 1, \"price\" : 50.00, \"store\" : { \"id\" : 1 }, \"authors\" : [{ \"id\" : 1 }, { \"id\" : 2 }] } Using the associated id makes the results relatively concise: { \"id\" : 1, \"name\" : \"Learning GraphQL\", \"edition\" : 1, \"price\" : 50.00, \"storeId\" : 1, \"authorIds\" : [1, 2] } If you choose to directly return entities (rather than the DTO returns in the next article), and want to use associated ids, you need to add @IdView properties to the entities first: Java Kotlin @Entity public interface Book { @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); @Nullable @IdView Long storeId(); @IdView(\"authors\") List authorIds(); ...Omit other members... } @Entity interface Book { @ManyToOne val store: BookStore? @ManyToMany val authors: List @IdView val storeId: Long? @IdView(\"authors\") val authorIds: List ...Omit other members... } In the above example: The storeId property is not a brand new property. It is just a view of the store property, getting the id property of the associated object represented by the store property (or null). storeId and store share the same data. The authorIds property is not a brand new property either. It is just a view of the authors property, getting a list of id properties of all associated objects represented by the authors property. authorIds and authors share the same data. Now, write the REST Controller as follows: Java Kotlin BookController.java @RestController public class BookController implements Fetchers { private final BookRepository bookRepository; public BookController(BookRepository bookRepository) { this.bookRepository = bookRepository; } @Nullable @GetMapping(\"/book\") public @FetchBy(\"SHALLOW_BOOK\") Book findBookById( @PathVariable(\"id\") long id ) { return bookRepository.findBookById(id, SHALLOW_BOOK); } /** * Shallow Book DTO which can access * 1. All scalar properties of `Book` itself * 2. All associated ids, not associated objects. */ private static final Fetcher SHALLOW_BOOK = BOOK_FETCHER .allScalarFields() .storeId() .authorIds(); ...Omit other members... } BookController.kt @RestController class BookController( private val bookRepository: BookRepository ) { @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long ): @FetchBy(\"SHALLOW_BOOK\") Book = bookRepository.findBookById(id, SHALLOW_BOOK) ...Omit other members... companion object { /** * Shallow Book DTO which can access * 1. All scalar properties of `Book` itself * 2. All associated ids, not associated objects. */ val SHALLOW_BOOK = newFetcher(Book::class).by { allScalarFields() storeId() authorIds() } ...Omit other shape definitions... } }","s":"Flat Associated IDs","u":"/jimmer-doc/docs/quick-view/fetch/export/entity","h":"#flat-associated-ids","p":1619},{"i":1634,"t":"Use https://start.spring.io/ to create a Spring Boot project. You need to choose your preferred language - Java or Kotlin. The choice of language is important because Jimmer supports two different sets of APIs. Java API - Ensures maximum developer usage Kotlin API - APIs designed specifically for Kotlin to optimize the development experience","s":"Create a Spring Boot Project","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#create-a-spring-boot-project","p":1632},{"i":1636,"t":"Jimmer itself is highly neutral and can be used without Spring Boot. But it also provides great integration with Spring Boot. Users can choose to use it with or without Spring Boot. Different choices require adding different dependencies. groupId: org.babyfish.jimmer artifactId: Integrate with Spring Boot Standalone Usage Java jimmer-spring-boot-starter jimmer-sql Kotlin jimmer-sql-kotlin Compared to standalone usage, integrating with Spring Boot is simpler. So this tutorial will demonstrate the jimmer-spring-boot-starter. Modify build.gradle or pom.xml to add dependencies: Maven Gradle Gradle (Kts) Gradle Plugin Gradle Plugin (kts) pom.xml 0.9.25 org.babyfish.jimmer jimmer-spring-boot-starter ${jimmer.version} ...other dependencies omitted... ext { jimmerVersion = '0.9.25' } dependencies { implementation \"org.babyfish.jimmer:jimmer-spring-boot-starter:${jimmerVersion}\" ...other dependencies omitted... } val jimmerVersion = \"0.9.25\" dependencies { implementation(\"org.babyfish.jimmer:jimmer-spring-boot-starter:${jimmerVersion}\") ...other dependencies omitted... } build.gradle plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ... other plugins omitted ... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"0.9.25\" } build.gradle.kts plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" ... other plugins omitted ... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"0.9.25\" } info If you are using Gradle as your build tool, you can also use third-party Gradle plugin tech.argonariod.gradle-plugin-jimmer provided by the community to automatically identify the project type and add dependencies automatically. The tech.argonariod.gradle-plugin-jimmer gradle plugin is community-provided and maintained to simplify Jimmer project configuration, and it is not officially maintained by Jimmer. Repository URL: https://github.com/ArgonarioD/gradle-plugin-jimmer","s":"Add Dependencies","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#add-dependencies","p":1632},{"i":1638,"t":"If using Kotlin, you must modify the Spring Boot configuration file - this is very important. warning Kotlin projects must configure jimmer.language application.properties application.yml jimmer.language = kotlin jimmer: language: kotlin","s":"Additional Configuration Needed for Kotlin","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#additional-configuration-needed-for-kotlin","p":1632},{"i":1640,"t":"In addition to the required jimmer.language for Kotlin projects, there are other useful configurations. Here are a few basic configurations that work for both Java and Kotlin: Property Type Default Description jimmer.dialect string org.babyfish.jimmer.sql.dialect.DefaultDialect Database dialect class name jimmer.show-sql boolean false Print executed SQL if true jimmer.pretty-sql boolean false Ensure that the printed SQL is well-formatted (compact by default) jimmer.database-validation-mode NONE|WARNING|ERROR NONE Validate consistency between database schema and entity types. WARNING logs inconsistencies, ERROR throws errors. See Spring/Appendix for complete documentation on configurations. application.properties application.yml jimmer.dialect = org.babyfish.jimmer.sql.dialect.MySqlDialect jimmer.show-sql = true jimmer.pretty-sql = true jimmer.database-validation-mode = ERROR ...other configurations omitted... jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect show-sql: true pretty-sql: true database-validation-mode: ERROR ...other configurations omitted...","s":"Other Useful Configurations","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#other-useful-configurations","p":1632},{"i":1642,"t":"In addition to Jimmer, some other dependencies are required like spring-web, JDBC driver, etc. Modify build.gradle or pom.xml to add dependencies: Maven Gradle Gradle (Kts) org.springframework.boot spring-boot-starter-web mysql mysql-connector-java 8.0.30 runtime ...other dependencies omitted... dependencies { implementation 'org.springframework.boot:spring-boot-starter-web' runtimeOnly 'mysql:mysql-connector-java:8.0.30' ...other dependencies omitted... } dependencies { implementation(\"org.springframework.boot:spring-boot-starter-web\") runtimeOnly(\"mysql:mysql-connector-java:8.0.30\") ...other dependencies omitted... }","s":"Add Other Required Dependencies","u":"/jimmer-doc/docs/quick-view/get-started/create-project","h":"#add-other-required-dependencies","p":1632},{"i":1645,"t":"Similar to JPA2.0 Criteria, QueryDsl, Fluent MyBatis, etc., Jimmer uses strongly typed DSLs to catch errors at compile-time rather than runtime. So some additional code needs to be generated at compile-time based on user-defined entities: Java users use Annotation Processor Kotlin users use KSP Java (Maven) Java (Gradle) Kotlin (Gradle.kts) Java (Gradle Plugin) Kotlin (Gradle Plugin) pom.xml ...other code omitted... org.apache.maven.plugins maven-compiler-plugin 3.10.1 org.babyfish.jimmer jimmer-apt ${jimmer.version} ...other code omitted... dependencies { ...other dependencies omitted... annotationProcessor \"org.babyfish.jimmer:jimmer-apt:${jimmerVersion}\" } plugins { // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10-1.0.6\" ...other plugins omitted... } dependencies { // Apply Jimmer's KSP code generator ksp(\"org.babyfish.jimmer:jimmer-ksp:${jimmerVersion}\") ...other dependencies omitted... } // Add generated code to compile path. // Gradle build works without this, but IntelliJ won't find generated code. kotlin { sourceSets.main { kotlin.srcDir(\"build/generated/ksp/main/kotlin\") } } build.gradle plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. id \"tech.argonariod.gradle-plugin-jimmer\" version \"latest.release\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } build.gradle.kts plugins { // Starting from Gradle 7.0, you can use \"latest.release\" instead of a specific version number to represent the use of the latest version. id(\"tech.argonariod.gradle-plugin-jimmer\") version \"latest.release\" // You can also use the '+' character to indicate matching the latest version number starting from the '+' character. // Add KSP plugin id(\"com.google.devtools.ksp\") version \"1.7.10+\" ...other plugins omitted... } jimmer { // Set the Jimmer dependency version, where you can also use version range expressions such as \"latest.release\" or \"0.+\" version = \"${jimmerVersion}\" } info The first three: Standard configurations The last two: Community-provided Gradle plugin for further simplifying configurations note KSP only supports gradle, It has been proven that KSP's third-party Maven plug-in support cannot keep up with the version iteration of 'kotlin/KSP' itself, and often encounters many problems during the upgrade process. Eventually, Jimmer dropped Maven support for Kotlin and asked Kotlin developers to use Gradle. After this configuration, running Maven or Gradle will generate additional source code based on user-defined entities. caution The above only applies to simple projects without separation. For real projects with separate entity definition, generator (annotation processor/ksp) must be configured in the project that defines entity types. Jimmer data types require one of: @Immutable @Entity @MappedSuperclass @Embeddable The first is ORM-agnostic, the others are ORM-related. If entities use the ORM annotations (eg: @Entity), the generated code requires jimmer-sql while entity code itself only needs jimmer-core: Maven Java (Gradle Plugin) Kotlin (Gradle Plugin) Java (Gradle) Kotlin (Gradle.kts) pom.xml ...other code omitted... org.babyfish.jimmer jimmer-core ${jimmer.version} org.babyfish.jimmer jimmer-sql ${jimmer.version} provided ...other dependencies omitted... ...other code omitted... build.gradle jimmer { // Ensure that jimmer-sql is only depended upon during code generation and compilation. ormCompileOnly = true ...other configurations omitted... } ...other code omitted... build.gradle.kts jimmer { // Ensure that jimmer-sql-kotlin is only depended upon during code generation and compilation. ormCompileOnly = true ...other configurations omitted... } ...other code omitted... ...other code omitted... dependencies { ...other dependencies omitted... // User entity code implementation \"org.babyfish.jimmer:jimmer-core:${jimmerVersion}\" // Generated code compileOnly \"org.babyfish.jimmer:jimmer-sql:${jimmerVersion}\" } ...other code omitted... ...other code omitted... dependencies { ...other dependencies omitted... // User entity code implementation(\"org.babyfish.jimmer:jimmer-core:${jimmerVersion}\") // Generated code compileOnly(\"org.babyfish.jimmer:jimmer-sql:${jimmerVersion}\") } ...other code omitted...","s":"Code Generation","u":"/jimmer-doc/docs/quick-view/get-started/generate-code","h":"#code-generation","p":1643},{"i":1647,"t":"If generation succeeded, developers should see: Java Kotlin note Screenshots are from Gradle project. For Maven, top level directory is target instead of build. caution Normally IDE marks generated code directories with icon. But sometimes IntelliJ fails to do so, preventing use of generated code. In this case, right-click on directory, choose Mark Directory As -> Generated Sources Root. Generated code includes: Java Kotlin Description XXXDraft.java XXXDraft.kt Mutable proxy interface for immutable object, object implementation, and methods to create and \"modify\" objects XXXProps.java XXXProps.kt Typed SQL DSL XXXTable.java XXXTableEx.java XXXFetcher.java XXXFetcher.kt Object fetcher DSL defining shape of complex query results","s":"Verify Successful Generation","u":"/jimmer-doc/docs/quick-view/get-started/generate-code","h":"#verify-successful-generation","p":1643},{"i":1649,"t":"To quickly preview Jimmer's main features, we need to provide several entities here as the basic assumption of all discussions in this section.","s":"Precondition","u":"/jimmer-doc/docs/quick-view/precondition","h":"","p":1648},{"i":1651,"t":"tip In Jimmer applications, the only thing that matters is the unified global ORM entity model. The global entity model is finalized with the database design, irrelevant to specific query/modification business logics' requirements for interaction formats, and relatively stable. As for what kind of DTO types each query/modification business needs to interact with, it is completely unimportant. Either no DTO is needed at all, e.g. Quick View/Query Arbitrary Shape/Exposing Features/Return Entities Directly. Or DTO types can be quickly generated through Object/DTO Conversion/DTO Language, making DTO extremely cheap. Only the relatively stable entity model is important. So Jimmer is good at handling changing requirements.","s":"Status of Entities","u":"/jimmer-doc/docs/quick-view/precondition","h":"#status-of-entities","p":1648},{"i":1653,"t":"Here we list three entity types: BookStore, Book, Author and TreeNode, as the basic assumptions for all discussions in the current section.","s":"UML Relationships Between Entities","u":"/jimmer-doc/docs/quick-view/precondition","h":"#uml-relationships-between-entities","p":1648},{"i":1656,"t":"Java Kotlin @Entity public interface BookStore { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); @Nullable String website(); @OneToMany(mappedBy = \"store\") List books(); } @Entity interface BookStore { @Id @@GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String val website: String? @OneToMany(mappedBy = \"store\") val books: List }","s":"BookStore","u":"/jimmer-doc/docs/quick-view/precondition","h":"#bookstore","p":1648},{"i":1658,"t":"Java Kotlin @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); @Key String name(); @Key int edition(); BigDecimal price(); @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); } @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val name: String @Key val edition: Int val price: BigDecimal @ManyToOne val store: BookStore? @ManyToMany val authors: List }","s":"Book","u":"/jimmer-doc/docs/quick-view/precondition","h":"#book","p":1648},{"i":1660,"t":"Java Kotlin @Entity public interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) UUID id(); @Key String firstName(); @Key String lastName(); Gender gender(); @ManyToMany(mappedBy = \"authors\") List books(); } @Entity interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long @Key val firstName String @Key val lastName: String val gender: Gender @ManyToMany(mappedBy = \"authors\") val books: List } Where Gender is a very simple enum type Java Kotlin public enum Gender { MALE, FEMALE } enum class Gender { MALE, FEMALE }","s":"Author","u":"/jimmer-doc/docs/quick-view/precondition","h":"#author","p":1648},{"i":1662,"t":"The save directive is a very powerful capability of Jimmer. With just one function call, data structures of any shape can be saved. Whether the data structure to be saved is simple (such as a single object or even a mutilated object) or complex (an aggregate root object holds many associated objects through associative relationships, with unlimited depth and breadth), it can be saved into the database with one function call. tip Saving operations for single table records has never been the difficulty of application development. Even without using any ORM framework, it is very easy to achieve with direct use of JDBC. However, saving complex data structures is not so easy. Developers will have to query existing data structures from the database and compare them with the data structures to be saved, so as to discover multiple changed parts and convert them into corresponding INSERT, UPDATE and DELETE statements. This process is very cumbersome and error-prone. Therefore, from the very beginning, Jimmer focused on how to save complex data structures, rather than how to save a single entity object.","s":"2. Save Arbitrary Shape","u":"/jimmer-doc/docs/quick-view/save/","h":"","p":1661},{"i":1664,"t":"In Save Any Shape/Feature Introduction, we introduced the powerful data saving capability of Jimmer, but also pointed out that for security reasons, Jimmer dynamic entities cannot be directly used as input parameters to directly expose this capability. To protect system security, DTO Language needs to be used to define Input DTO. Unlike Jimmer dynamic entities, InputDTO is static with fixed shape. Using Input DTO as the type constraint of the input parameters of remote APIs can solve security issues.","s":"Exposing Features","u":"/jimmer-doc/docs/quick-view/save/export/","h":"","p":1663},{"i":1666,"t":"Here is the English translation of the file, with the code indentation preserved:","s":"Feature Introduction","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"","p":1665},{"i":1668,"t":"Jimmer can query data structures of any shape, with control over the queried data structure as fine-grained as GraphQL. Next, we will demonstrate its usage in three scenarios.","s":"Basic Usage","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#basic-usage","p":1665},{"i":1670,"t":"info A partial object refers to querying only part of an object's properties, with less information than an isolated object. Usage1: Query Entity Objects Usage2: Query DTOs Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch( Fetchers.BOOK_FETCHER .name() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"Learning GraphQL\" select( table.fetchBy { name() } ) } .execute() DTO代码 export yourpackage.Book -> package yourpackage.dto; BookView { id name } After compilation, Java/Kotlin type BookView will be automatically generated. Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"Learning GraphQL\" select( table.fetch(BookView::class) ) } .execute() Output Result [ {\"id\":10,\"name\":\"Learning GraphQL\"}, {\"id\":11,\"name\":\"Learning GraphQL\"}, {\"id\":12,\"name\":\"Learning GraphQL\"} ] Output Result [ BookView(id=10, name=Learning GraphQL), BookView(id=11, name=Learning GraphQL), BookView(id=12, name=Learning GraphQL) ]","s":"1. Query Partial Objects","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#1-query-partial-objects","p":1665},{"i":1672,"t":"info Select an entity as the aggregate root, and query not only the aggregate root object but also its associated objects, with no restrictions on depth or breadth. This level of control over the format is as fine-grained as GraphQL. Usage1: Query Entity Objects Usage2: Query DTOs Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch( Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_STORE_FETCHER .allScalarFields() ) .authors( Fetchers.AUTHOR_FETCHER .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"Learning GraphQL\" select( table.fetchBy { allScalarFields() store { allScalarFields() } authors { allScalarFields() } } ) } .execute() DTO Code export yourpackage.Book -> package yourpackage.dto; BookView { #allScalars store { #allScalars } authors { #allScalars } } After compilation, Java/Kotlin type BookView will be automatically generated. Query Code Java Kotlin BookTable table = Tables.BOOK_TABLE; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { table.name eq \"GraphQL\" select( table.fetch(BookView::class) ) } .execute() Output Result [ { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 50, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null }, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] }, { \"id\": 2, \"name\": \"Learning GraphQL\", \"edition\": 2, \"price\": 55, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null }, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] }, { \"id\": 3, \"name\": \"Learning GraphQL\", \"edition\": 3, \"price\": 51, \"store\": { \"id\": 1, \"name\": \"O'REILLY\", \"website\": null }, \"authors\": [ { \"id\": 2, \"firstName\": \"Alex\", \"lastName\": \"Banks\", \"gender\": \"MALE\" }, { \"id\": 1, \"firstName\": \"Eve\", \"lastName\": \"Procello\", \"gender\": \"FEMALE\" } ] } ] Output Result [ BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookView.TargetOf_store( id=1, name=O'REILLY, website=null ), authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, store=BookView.TargetOf_store( id=1, name=O'REILLY, website=null ), authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, store=BookView.TargetOf_store( id=1, name=O'REILLY, website=null ), authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) ]","s":"2. Include Associated Objects","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#2-include-associated-objects","p":1665},{"i":1674,"t":"info If an entity contains Self-correlation properties, you can perform a recursive query. As of now, the GraphQL protocol does not support recursive queries. Usage1: Query Entity Objects Usage2: Query DTOs Query Code Java Kotlin TreeNode rootNode = sqlClient .findById( Fetchers.TREE_NODE_FETCHER .allScalarFields() // Recursion upwards .recursiveParent() ❶ // Recursion downward .recursiveChildNodes() ❷ 10L ); val rootNode = sqlClient .findById( newFetcher(TreeNode::class).by { allScalarFields() // Recursion upwards `parent*`() ❶ // Recursion downward `childNodes*`() ❷ } ) DTO代码 export yourpackage.TreeNode -> package yourpackage.dto; RecursiveTreeNodeView { id // Recursion upwards parent* ❶ // Recursion downward childNodes* ❷ } After compilation, Java/Kotlin type RecursiveTreeNodeView will be automatically generated. Query Code Java Kotlin RecursiveTreeNodeView rootNode = sqlClient .findById( RecursiveTreeNodeView.class, 10L ); val rootNode = sqlClient .findById( RecursiveTreeNodeView::class, 10L ); Output Result { \"id\": 10, \"name\": \"Woman\", \"parent\": { ❶ \"id\": 9, \"name\": \"Clothing\", ❶ \"parent\": { \"id\": 1, \"name\": \"Home\", \"parent\": null ❶ } }, \"childNodes\": [ ❷ { \"id\": 11, \"name\": \"Casual wear\", \"childNodes\": [ ❷ { \"id\": 12, \"name\": \"Dress\", \"childNodes\": [] ❷ }, { \"id\": 13, \"name\": \"Miniskirt\", \"childNodes\": [] ❷ }, { \"id\": 14, \"name\": \"Jeans\", \"childNodes\": [] ❷ } ] }, { \"id\": 15, \"name\": \"Formal wear\", \"childNodes\": [ ❷ { \"id\": 16, \"name\": \"Suit\", \"childNodes\": [] ❷ }, { \"id\": 17, \"name\": \"Shirt\", \"childNodes\": [] ❷ } ] } ] } Output Result RecursiveTreeNodeView( id=10, name=Woman, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=9, name=Clothing, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=1, name=Home, parent=null ❶ ) ), childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=11, name=Casual wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=12, name=Dress, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=13, name=Miniskirt, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=14, name=Jeans, childNodes=[] ❷ ) ] ), RecursiveTreeNodeView.TargetOf_childNodes( id=15, name=Formal wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=16, name=Suit, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=17, name=Shirt, childNodes=[] ❷ ) ] ) ] )","s":"3. Recursive Query","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#3-recursive-query","p":1665},{"i":1676,"t":"The above code is only intended to demonstrate Jimmer's powerful control over the format of the queried data through three scenarios and does not organize the code structure. In actual development, we must organize the code in some way, with data operation-level code placed in the Repository. caution The previous examples showed two usages: querying entity objects and querying DTO objects. To control the complexity of this document, the following sections will only discuss how to organize code for querying entity objects.","s":"Repository Code Style","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#repository-code-style","p":1665},{"i":1678,"t":"Now let's write a BookRepository for querying Book Java Kotlin BookRepository.java @Repository pubic class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Nullable public Book findBookById(long id) { return sqlClient.findById(Book.class, id); } public List findBooksByName(@Nullable String name) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().ilike(name) ) .select(table) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBookById(id: Long): Book? = sqlClient.findById(Book::class, id) fun findBooksByName(name: String?): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike name); } select(table) } .execute() } JSqlClient in Java code and KSqlClient in Kotlin code are the API entry points provided by Jimmer for Java and Kotlin developers. In actual projects, the object is a global object. This chapter document is used for quick preview and does not introduce details. Readers can ignore specific details for the time being and just know that sqlClient is the API entry point. The purpose of this article is to control the format of returned objects, not to introduce complex query conditions (this part of the content is introduced in Quick Preview/Arbitrary Dynamic Queries). So these two methods symbolically use Book.id and Book.name as filters. Jimmer is technically neutral, but using Spring-style code often serves to simplify explanation, so this example uses Spring-style writing. However, for convenience of non-Spring users to read, it deliberately does not use Jimmer support for Spring Data here, but uses the relatively primitive injection of sqlClient, which reduces interference from Spring to a minimum. Tables.BOOK_TABLE in Java code is code that Jimmer automatically generates at compile time. If there is an instance bookRepository of the above class, take findBookById as an example: Java Kotlin System.out.println(bookRepository.findBookById(1L)); println(bookRepository.findBookById(1L)); The output result is as follows: { \"id\" : 1, \"name\" : \"Learning GraphQL\", \"edition\" : 1, \"price\" : 50.00, \"store\" : { \"id\" : 1 } } The output format is fixed and does not match the topic “Query Any Data Structure Shape” we are discussing now, so we need to improve BookRepository.","s":"The Simplest Repository","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#the-simplest-repository","p":1665},{"i":1680,"t":"Let's make some minor improvements to the previous BookRepository class Java Kotlin BookRepository.java @Repository pubic class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Nullable public Book findBookById( long id, Fetcher fetcher ) { return sqlClient.findById( fetcher, id ); } public List findBooksByName( @Nullable String name, @Nullable Fetcher fetcher ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().ilike(name) ) .select( table.fetch(fetcher) ) .execute(); } } BookRepository.kt @Repository class BookRepository( private val sqlClient: KSqlClient ) { fun findBookById( id: Long, fetcher: Fetcher ): Book? = sqlClient.findById( fetcher, id ) fun findBooksByName( name: String? = null, fetcher: Fetcher? = null ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike name); } select( table.fetch(fetcher) ) } .execute() } In this example, we add a parameter of type Fetcher for each query method, through which we can flexibly control the format of the queried object (i.e. the shape of the queried data structure). tip This is the recommended usage. The Repository is only responsible for filtering, sorting, paging and other operations, but does not control the format of the returned data. Instead, it exposes the control of the data format through the Fetcher parameter to Let the upper layer business logic decide.","s":"Improved Repository","u":"/jimmer-doc/docs/quick-view/fetch/feature","h":"#improved-repository","p":1665},{"i":1683,"t":"In the previous article, we introduced that the web service does not need to define DTO types, directly returns entities, and uses @FetchBy annotations to restore all DTO type definitions in automatically generated client code. However, what if a query result is not returned to the Web remote client, but the server itself uses it? Java Kotlin List books = bookRepository.findBooksByName( \"graphql\", Fetchers.BOOK_FETCHER ❶ .name() .edition() ); for (Book book : books) { System.out.println(\"--------\"); System.out.println(\"Id: \" + book.id()); System.out.println(\"Name: \" + book.name()); System.out.println(\"Edition: \" + book.edition()); System.out.println(\"Price:\" + book.price()); ❷ } val books = bookRepository.findBooksByName( \"graphql\", newFetcher(Book::class).by { ❶ name() edition() } ) for (book in books) { println(\"--------\") println(\"Id: ${book.id}\") println(\"Name: ${book.name}\") println(\"Edition: ${book.edition}\") println(\"Price: ${book.price}\") ❷ } Here, there is no web service or remote call, it is just a call within the same JVM ❶ Only queries three properties of the object: id (implicit), name and edition ❷ Access the unqueried price property of the book object. This erroneous access will cause an exception: Exception type: org.babyfish.jimmer.UnloadedException Exception message: The property \"com.yourcompany.yourproject.model.Book.price\" is unloaded It can be seen that it is not enough to only consider automatically defining DTO types in remote client APIs. When the JVM itself directly uses query results, if sufficient compile-time security is required, defining DTO types for Java/Kotlin will be inevitable and necessary to ensure better compile-time safety.","s":"Java/Kotlin Applications Use Query Results","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#javakotlin-applications-use-query-results","p":1681},{"i":1685,"t":"The mutual conversion between entity objects and DTO objects is a boring, labor-intensive and error-prone thing that is common pain point in information management software development. Although many frameworks are trying to mitigate this problem, development efficiency has remained unable to be improved qualitatively. In order to minimize the cost of DTO type creation, Jimmer introduces the DTO language, which supplements the Java/Kotlin type system and can quickly generate Java/Kotlin DTO type definitions at compile time. This article only provides a quick overview without detailed introduction. For complete information, please refer to DTO Language","s":"DTO Language","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#dto-language","p":1681},{"i":1687,"t":"A jimmer user provide Intellij plugins for the DTO language. For details, see https://github.com/ClearPlume/jimmer-dto Installing the DTO language plugin is not required, but you can get a better development experience after installation, so it is recommended to install.","s":"DTO Language Plugin","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#dto-language-plugin","p":1681},{"i":1689,"t":"For any Java/Kotlin project that needs to use the DTO language, create a subdirectory dto under its src/main directory. That is, src/main/dto is where DTO files are stored. Create a Book.dto file under src/main/dto and enter the following code: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto SimpleBookView { id name } ComplexBookView { #allScalars(this) store { id name } authors { id firstName lastName } } Compile the project (either use gradle/maven commands on the command line or click gradle/maven build on the right side of Intellij) to generate related DTO types","s":"Define DTO Files","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#define-dto-files","p":1681},{"i":1691,"t":"After compilation, the following two types SimpleBookView and ComplexView will be generated automatically. The code for each is as follows: SimpleBookView Java Kotlin SimpleBookView.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class SimpleBookView implements View { ❷ private long id; @NotNull private String name; public SimpleBookView(@NotNull Book base) { ❸ ...omitted... } @Override public Book toEntity() { ❹ ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... } SimpleBookView.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class SimpleBookView( val id: Long val name: String ) : View { ❷ constructor(base: Book): ❸ this(...omitted...) override fun toEntity(): Book = ❹ ...omitted... ...Omit other members... } ❶ Reminds users that this is code automatically generated by Jimmer ❷ Output DTO based on Book entity needs to implement View interface ❸ Converts entity to DTO ❹ Converts DTO to entity ComplexBookView Java Kotlin ComplexBookView.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class ComplexBookView implements View { ❷ private long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private TargetOf_store store; @NotNull private List authors; public ComplexBookView(@NotNull Book base) { ❸ ...omitted... } @Override public Book toEntity() { ❹ ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... public static class TargetOf_store implements View { ❺ private long id; @NotNull private String name; public TargetOf_store(@NotNull BookStore base) { ...omitted... } @Override public BookStore toEntity() { ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... } public static class TargetOf_authors implements View { ❻ private long id; @NotNull private String firstName; @NotNull private String lastName; public TargetOf_authors(@NotNull Author base) { ...omitted... } @Override public Author toEntity() { ...omitted... } ...Omit getters and setters... ...Omit hashCode/equals/toString... ...Omit other members... } } ComplexBookView.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class ComplexBookView( val id: Long, val name: String, val edition: Int, val price: BigDecimal, val store: TargetOf_store?, val authors: List ) : View { ❷ constructor(base: Book): ❸ this(...omitted...) override fun toEntity(): Book = ❹ ...omitted... data class TargetOf_store( ❺ val id: Long, val name: String ) : View { constructor(base: BookStore): this(...omitted...) override fun toEntity(): BookStore = ...omitted... } data class TargetOf_authors( ❻ val id: Long, val firstName: String, val lastName: String ) : View { constructor(base: Author): this(...omitted...) override fun toEntity(): Author = ...omitted... } } ❶ Reminds users that this is code automatically generated by Jimmer ❷ Output DTO based on Book entity needs to implement View interface ❸ Converts entity to DTO ❹ Converts DTO to entity ❺ DTO definition of associated object referenced by many-to-one association Book.store ❻ DTO definition of associated object referenced by many-to-many association Book.authors","s":"View Generated DTOs","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#view-generated-dtos","p":1681},{"i":1694,"t":"In the Feature Introduction article, we wrote a BookRepository class Java Kotlin public class BookRepository { @Nullable public Book findBookById( long id, Fetcher fetcher ) { ...omitted... } public List findBooksByName( @Nullable String name, @Nullable Fetcher fetcher ) { ...omitted... } ...Omit other members... } BookRepository.kt class BookRepository( ...Omit other members... ) { fun findBookById( id: Long, fetcher: Fetcher ): Book? = ...omitted... fun findBooksByName( name: String? = null, fetcher: Fetcher? = null ): List = ...omitted... } Each query method adds a parameter of type Fetcher. We can use it to flexibly control the format of queried objects (that is, the shape of queried data structures). This is the recommended usage. The Repository is only responsible for filtering, sorting, paging and other operations, but does not control the format of the returned data. Instead, it exposes the control of the data format through the Fetcher parameter to allow upper layer business logic to decide.","s":"Review Old BookRepository","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#review-old-bookrepository","p":1681},{"i":1696,"t":"Now, this BookRepository no longer meets our requirements. Because we no longer want to query Jimmer entities, but want to query DTO types automatically generated by the DTO language, we need to modify it. However, we want BookRepository to still maintain the excellent quality of exposing shape control externally. The modified code is as follows. Java Kotlin @Component public class BookRepository { private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Nullable public > V findBookById( ❶ long id, Class viewType ❷ ) { return sqlClient.findById( viewType, ❸ id ); } public > List findBooksByName( ❹ @Nullable String name, Class viewType ❺ ) { BookTable table = Tables.BOOK_TABLE; return sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), table.name().ilike(name) ) .select( table.fetch(viewType) ❻ ) .execute(); } } BookRepository.kt @Component class BookRepository( private val sqlClient: KSqlClient ) { fun > findBookById( ❶ id: Long, viewType: KClass ❷ ): V? = sqlClient.findById( viewType, ❸ id ) fun > findBooksByName( ❹ name: String? = null, viewType: KClass ❺ ): List = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } select( table.fetch(viewType) ❻ ) } .execute() } ❶ ❹: > in java or > in kotlin defines a generic parameter V representing any Output DTO type based on Book. For example: SimpleBookView and ComplexBookView generated above implement the View interface. ❷ ❺: Use the type of any DTO based on Book as a parameter. The return type varies with the change of the parameter type to achieve querying any DTO type and hand over the decision of the DTO type to the upper caller. ❸ ❻: Let Jimmer query data of the specified type tip The DTO type internally includes a Fetcher matching the shape. First, entity data structures matching the shape are queried through this Fetcher, and then automatically converted to DTO types.","s":"Write New BookRepository","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#write-new-bookrepository","p":1681},{"i":1698,"t":"Take bookRepository.findById as an example Query relatively simple SimpleBookView Java Kotlin System.out.println( bookRepository.findBookById( 1L, SimpleBookView.class ) ); println( bookRepository.findBookById( 1L, SimpleBookView::class ) ) Print output: SimpleBookView( id=1, name=Learning GraphQL ) Query relatively complex ComplexBookView Java Kotlin System.out.println( bookRepository.findBookById( 1L, ComplexBookView.class ) ); println( bookRepository.findBookById( 1L, ComplexBookView::class ) ) Print output: ComplexBookView( id=1, name=Learning GraphQL, edition=1, price=50.0, store=ComplexBookView.TargetOf_store( id=1, name=O'REILLY ), authors=[ ComplexBookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello ), ComplexBookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks ) ] )","s":"Try New BookRepository","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#try-new-bookrepository","p":1681},{"i":1700,"t":"Although the DTO language is more suitable for Java/Kotlin applications to use query results internally, you can also use them as return information for HTTP APIs without any difference from using ordinary POJOs. Java Kotlin BookController.java @RestController public class BookController implements Fetchers { private final BookRepository bookRepository; public BookController(BookRepository bookRepository) { this.bookRepository = bookRepository; } @Nullable @GetMapping(\"/book/{id}\") public ComplexBookView findBookById(@PathVariable(\"id\") long id) { return bookRepository.findBookById( id, ComplexBookView.class ); } @GetMapping(\"/books\") public List findBooksByName( @RequestParam(name = \"name\", required = false) String name ) { return bookRepository.findBooksByName( name, SimpleBookView.class ); } } BookController.kt @RestController class BookController( private val bookRepository: BookRepository ) { @GetMapping(\"/book/{id}\") fun findBookById( @PathVariable id: Long ): ComplexBookView = bookRepository.findBookById( id, ComplexBookView::class ) @GetMapping(\"/books\") fun findBooksByName( @RequestParam(required = false) name: String ): List = bookRepository.findBooksByName( name, SimpleBookView::class ) }","s":"Write BookController","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#write-bookcontroller","p":1681},{"i":1702,"t":"In the previous article, we mentioned that Jimmer can copy the document comments in Java/Kotlin code to the client Api, whether it is OpenApi online documentation or generated TypeScript code. The method introduced in this article has the same functionality, but it needs to be explained that the types and properties in the DTO language support document comments like Java/Kotlin types, so the DTO language can override Java/Kotlin document comments. For example, the original entity definition is as follows Java Kotlin /** * The book entity */ @Entity public interface Book { /** * The name of book entity */ String name(); ...Omit other members... } /** * The book entity */ @Entity interface Book { /** * The name of book entity */ val price: BigDecimal ...Omit other members... } The document comments here are the original document comments. The DTO Language also supports document comments. For example: Book.Dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto /** * Simple book dto */ SimpleBookView { /** * The name of simple book dto */ name ...Omit other members... } ...Omit other DTO definitions... info The document comment of the DTO Language has higher priority. That is, the document comments in the DTO language can override the document comments of the original entity, finally it is used to generate OpenApi documentation or TypeScript code.","s":"Document Comments","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#document-comments","p":1681},{"i":1704,"t":"If the associated object only has the id property, the associated Id will be better than the associated object. For example: Using associated objects will lead to a large number of objects with only id properties, making the results slightly redundant: { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 50.00, \"store\": { \"id\": 1 }, \"authors\": [{ \"id\": 1 }, { \"id\": 2 }] } Using associated Ids makes the results relatively concise: { \"id\": 1, \"name\": \"Learning GraphQL\", \"edition\": 1, \"price\": 50.00, \"storeId\": 1, \"authorIds\": [1, 2] } If you choose to return DTO (instead of directly returning entities as in the previous article), you can define the following DTO code: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto ShallowBookView { #allScalars(this) id(store) id(authors) as authorIds } ...Omit other DTO definitions... After compilation, the following code is generated: Java Kotlin ShallowBookView.java @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class ShallowBookView implements View { private long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private Long storeId; @NotNull private List authorIds; ...Omit other members... } ShallowBookView.kt @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class ShallowBookView( val id: Long, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, val authorIds: List ): View { ...Omit other members... }","s":"Flat Association ID","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#flat-association-id","p":1681},{"i":1706,"t":"A large part of server development teams will deal with a type of frontend development team who do not accept data structures composed of associated multiple objects, and only want to accept a huge single object. So they require all non-collection associations to be flattened. That is: They do not accept structured return information: { \"prop1\": 1, \"prop2\": 2, \"a\": { \"prop1\": 3, \"prop2\": 4, \"b\": { \"prop1\": 5, \"prop2\": 6, } }, \"c\": { \"prop1\": 7, \"prop2\": 8, \"d\": { \"prop1\": 9, \"prop2\": 10, } } } Insist on asking for such flat data: { \"prop1\": 1, \"prop2\": 2, \"aProp1\": 3, \"aProp2\": 4, \"aBProp1\": 5, \"abProp2\": 6, \"cProp1\": 7, \"cProp2\": 8, \"cdProp1\": 9, \"cdProp2\": 10 } In fact, such flat non-structured data is a disaster for client programs that need state management. But such frontend teams only do UI rendering without state management, so they do not realize this problem and insist on it very much. When you can't argue but need to complete the task quickly, write DTO code as follows: Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto FlatBookView { #allScalars(this) flat(store) { ❶ as(^ -> store) { ❷ #allScalar(this) } } } ...Omit other DTO definitions... ❶ The flat function means to flatten the properties of the associated object pointed to by the Book.store one-to-many association to the current object. ❷ For the properties of the associated object, the property name needs to be changed after being flattened to the current object. Prefix the old property name with store. For example, name -> storeName. After compilation, the following code is generated: Java Kotlin FlatBookView.java @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class FlatBookView implements View { private long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private Long storeId; @Nullable private String storeName; @Nullable private String storeWebsite; ...Omit other members... } FlatBookView.kt @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class FlatBookView( val id: Long, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long?, val storeName: String?, val storeWebsite: String? ): View { ...Omit other members... } Here, the flattened properties are all nullable, because the Book.store association itself allows null.","s":"Flat Associated Objects","u":"/jimmer-doc/docs/quick-view/fetch/export/dto","h":"#flat-associated-objects","p":1681},{"i":1708,"t":"Unlike ORMs like JPA/Hibernate, entities in Jimmer are defined as interfaces instead of classes. The reasons are discussed in Why Interfaces. Before defining entities, two concepts need to be introduced: Jimmer entities are not simple Java beans, but dynamic objects. That is, an unset property is completely different from a property set to null. Jimmer entities are immutable, so interfaces only have getters, no setters.","s":"Define Entities","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"","p":1707},{"i":1710,"t":"Assume the entity package is \"com.example.model\". Ignore associated properties first, entity definitions are: BookStore Java Kotlin BookStore.java package com.example.model; import org.babyfish.jimmer.sql.*; import org.jetbrains.annotations.Nullable; @Entity public interface BookStore { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); @Nullable String website(); } BookStore.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface BookStore { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String val website: String? } Book Java Kotlin Book.java package com.example.model; import org.babyfish.jimmer.sql.*; import java.math.BigDecimal; @Entity public interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); int edition(); BigDecimal price(); } Book.kt package com.example.model import org.babyfish.jimmer.sql.* import java.math.BigDecimal @Entity interface Book { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String val edition: Int val price: BigDecimal } Author Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String firstName(); String lastName(); /* * Gender is an enum defined later */ Gender gender(); } Author.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface Author { @Id @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val firstName: String val lastName: String /* * Gender is an enum defined later */ val gender: Gender } Where Gender is an enum with two options: MALE and FEMALE. ORMs can map enums to strings (default) or numbers. Although this example maps enum to string by default, the database has a check constraint limiting values to 'M' and 'F', not default 'MALE' and 'FEMALE'. So the enum needs to be configured as: Java Kotlin Author.java package com.example.model; import org.babyfish.jimmer.sql.EnumItem; public enum Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE } Author.kt package com.example.model import org.babyfish.jimmer.sql.EnumItem enum class Gender { @EnumItem(name = \"M\") MALE, @EnumItem(name = \"F\") FEMALE } TreeNode Java Kotlin TreeNode.java package com.example.model; import org.babyfish.jimmer.sql.*; @Entity public interface TreeNode { @Id @Column(name = \"NODE_ID\") @GeneratedValue(strategy = GenerationType.IDENTITY) long id(); String name(); } TreeNode.kt package com.example.model import org.babyfish.jimmer.sql.* @Entity interface TreeNode { @Id @Column(name = \"NODE_ID\") @GeneratedValue(strategy = GenerationType.IDENTITY) val id: Long val name: String } For Java, each getter can use the traditional Java bean get/is prefix like getName(), or omit it like name() in this example. note Breaking the Java bean convention of getter prefixes is enabled by Java 14 records, not Jimmer. The new style allows more concise immutable objects. Jimmer entities are very sensitive to nullability: For Kotlin, use language's own nullity. For Java: Primitives like boolean, char, byte, short, int, long, float, double are non-null. Boxed types like Boolean, Character, Byte, Short, Integer, Long, Float, Double are nullable. Other types are non-null by default. Add @Nullable to allow null. Annotations used in example: @Entity - Indicates entity type. @Id - Specifies ID property. @GeneratedValue - Specifies auto-generated ID, using database autoincrement here. Java/Kotlin interface short name is converted to table name using word1Word2...WordN -> WORD1_WORD2_..._WORDN. If mismatch, use @Table on interface. Similarly, property name is converted to column name. If mismatch, use @Column on property. note Note @Column can be used on non-foreign key fields, not just foreign keys discussed later. Entities have non-null ID like long, not nullable ID like Long, otherwise framework will report error. note JPA/Hibernate users note this difference in handling ID nullability.","s":"Define Non-Associated Fields","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#define-non-associated-fields","p":1707},{"i":1712,"t":"Modify Book.java/Book.kt to add store association: Java Kotlin Book.java package com.example.model; ...imports omitted... @Entity public interface Book { ...other properties omitted... @ManyToOne @Nullable BookStore store(); } Book.kt package com.example.model ...imports omitted... @Entity interface Book { ...other properties omitted... @ManyToOne val store: BookStore? } @ManyToOne declares one-to-many association, mapping foreign key to associated entity. Property name is converted to foreign key column like store -> STORE_ID, matching database. If mismatch, use @JoinColumn on property.","s":"One-to-Many Association Book.store","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#one-to-many-association-bookstore","p":1707},{"i":1714,"t":"Modify BookStore.java/BookStore.kt to add books association: Java Kotlin BookStore.java package com.example.model; ...imports omitted... @Entity public interface BookStore { ...other properties omitted... @OneToMany(mappedBy = \"store\") List books(); } BookStore.kt package com.example.model ...imports omitted... @Entity interface BookStore { ...other properties omitted... @OneToMany(mappedBy = \"store\") val books: List } @OneToMany declares one-to-many association. It does not map any database field, just mirrors @ManyToOne to make association bidirectional. Here, mappedBy = \"store\" means BookStore.books is mirror of Book.store. @Entity public interface BookStore { @OneToMany( mappedBy = \"store\" ) List books(); ... } @Entity public interface Book { @ManyToOne @Nullable BookStore store(); ... } The side with mappedBy is called the mirror side. Mirroring is optional, bidirectional association is not required. Unlike JPA/Hibernate, @OneToMany in Jimmer can only mirror @ManyToOne, always implying bidirection.","s":"One-to-Many Association BookStore.books","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#one-to-many-association-bookstorebooks","p":1707},{"i":1716,"t":"Modify Book.java/Book.kt to add authors association: Java Kotlin Book.java package com.example.model; ...imports omitted... @Entity public interface Book { ...other properties omitted... @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) List authors(); } Book.kt package com.example.model ...imports omitted... @Entity interface Book { ...other properties omitted... @ManyToMany @JoinTable( name = \"BOOK_AUTHOR_MAPPING\", joinColumnName = \"BOOK_ID\", inverseJoinColumnName = \"AUTHOR_ID\" ) val authors: List } @ManyToMany declares many-to-many association. There are two sides of many-to-many: owner and mirror. This is the owner side. For owner, @JoinTable can specify join table: name: Join table name (default based on entities) joinColumnName: FK to current entity (Book) inverseJoinColumnName: FK to target entity (Author) note Here @JoinTable uses all default values, so it can be omitted.","s":"Many-to-Many Association Book.authors","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#many-to-many-association-bookauthors","p":1707},{"i":1718,"t":"Modify Author.java/Author.kt to add books association: Java Kotlin Author.java package com.example.model; ...imports omitted... @Entity public interface Author { ...other properties omitted... @ManyToMany(mappedBy = \"authors\") List books(); } Author.kt package com.example.model ...imports omitted... @Entity interface Author { ...other properties omitted... @ManyToMany(mappedBy = \"authors\") val books: List } Here, mappedBy makes this the mirror side of the many-to-many mapping. @ManyToMany(mappedBy = \"authors\") means Author.books mirrors Book.authors. @Entity public interface Author { @ManyToMany( mappedBy = \"authors\" ) List books(); ... } @Entity public interface Book { @ManyToMany @JoinTable(...略...) List authors(); ... } Mirroring many-to-many is optional, bidirection association is optional. But if bidirectional, one side must be owner and the other one must be mirror. tip Unlike JPA/Hibernate, owner vs mirror does not affect save behavior in Jimmer. You can choose freely.","s":"Many-to-Many Association Author.books","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#many-to-many-association-authorbooks","p":1707},{"i":1720,"t":"Now we understand associations. Let's quickly complete TreeNode: Java Kotlin TreeNode.java package com.example.model; ...imports omitted... @Entity public interface TreeNode { ...other properties omitted... @ManyToOne @Nullable TreeNode parent(); @OneToMany(mappedBy = \"parent\") List childNodes(); } TreeNode.kt package com.example.model ...imports omitted... @Entity interface TreeNode { ...other properties omitted... @ManyToOne val parent: TreeNode? @OneToMany(mappedBy = \"parent\") val childNodes: List }","s":"Complete TreeNode Definition","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#complete-treenode-definition","p":1707},{"i":1722,"t":"We've seen entities declared as interfaces, not classes. Why? Dynamicity Jimmer entities are not simple Java beans, but dynamic objects. Unset vs null property are totally different Accessing non-existent property throws UnloadedException Serializing with Jackson omits unset properties See Dynamic for details on dynamicity. Benefits of dynamicity Easily express arbitrary complex data structures. Entities can be partial object, complete object, or aggregate root of complex tree. Since data structure is flexible, ORM can query and save entire object graph in one go instead of individual entities. For querying, dynamic entity graphs can directly return from HTTP services without needing DTOs. Compared to dynamic language ORMs As discussed, Jimmer exploits dynamicity for flexibility unmatched by static language ORMs. But it rejects unsafety and unmaintainability of dynamic languages. Jimmer entities remain ordinary Java/Kotlin objects with all static typing, even null safety in Kotlin. note The only unsafety is UnloadedException when accessing unloaded properties, similar to LazyInitializationException in JPA/Hibernate. This is a necessary cost universally accepted in ORM. tip Jimmer finds the optimal balance between dynamic language flexibility and static language safety. Immutability We've seen entities only have getters, meaning they are immutable. Mutable object allows circular references which the most headache problem of business system, Immutable data avoids this risk. However, enjoying and leveraging the advantages of immutable objects while suppressing their disadvantages is not an easy thing, especially for scenarios like ORM where the object hierarchy is very deep. Luckily, in the JavaScript/TypeScript domain, there is a framework called immer that provides a perfect way to handle deep immutability. Jimmer ports immer to Java/Kotlin and makes it the foundational programming model for the entire ORM. The name \"Jimmer\" is also a tribute to immer. See Immutability/Solution for details on how to create and \"modify\" immutable objects. In summary, because Jimmer entities themselves are dynamic and immutable, they are not simple Java objects. Their types have complex internal implementations. Therefore, Jimmer chooses to have developers write interfaces, and generate implementations at compile-time using AnnotationProcessors (Java) or KSP (Kotlin).","s":"Why Interfaces","u":"/jimmer-doc/docs/quick-view/get-started/define-entity","h":"#why-interfaces","p":1707},{"i":1725,"t":"A short association refers to only changing the association relationship between the current object and other objects, without further modifying the associated object. For the UI interface: Reference association (one-to-one and many-to-one) is rendered as a radio menu Collection association (one-to-many and many-to-many) is rendered as a multiple select menu For example: Book Form Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"What is Short Association","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#what-is-short-association","p":1723},{"i":1727,"t":"Name Name Edition Edition Price Price Store O'REILLY Authors Authors Eve Procello, Alex Banks Authors Submit","s":"Book Form","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"","p":1723},{"i":1729,"t":"Install DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This process is not required but highly recommended) Create a new directory src/main/dto Under src/main/dto, create a file Book.dto and write the following code: Book.dto input BookInputWithShortAssociations { #allScalars(this) id(store) //default alias storeId id(authors) as authorIds }","s":"Define Input DTO","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#define-input-dto","p":1723},{"i":1731,"t":"Java Kotlin BookInputWithShortAssociations.java @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookInputWithShortAssociations implements Input { @Nullable private Long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; @Nullable private Long storeId; @NotNull private List authorIds; ...Omit other methods... } BookInputWithShortAssociations.kt @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookInputWithShortAssociations( val id: Long?, val name: String, val edition: Int, val price: BigDecimal, val storeId: Long? val authorIds: List ) : Input { ...Omit other methods... }","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#generated-code","p":1723},{"i":1733,"t":"Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/book\") public int saveBookInputWithShortAssociations( @RequestBody BookInputWithShortAssociations input ) { return sqlClient .save(input) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @PutMapping(\"/book\") fun saveBookInputWithShortAssociations( @RequestBody input: BookInputWithShortAssociations ): Int = sqlClient .save(input) .totalAffectedRowCount } It can be seen that no matter how the Input DTO changes, Jimmer still only needs one method call to complete data saving.","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/short","h":"#write-http-service","p":1723},{"i":1735,"t":"Jimmer's Two Usages Use Jimmer's Spring Boot Starter Directly use the underlying SqlClient Jimmer has complete sample projects. For how to use Jimmer's Spring Boot Starter, please refer to the examples. This article discusses using the underlying sqlClient directly without Spring.","s":"Final Usage","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"","p":1734},{"i":1737,"t":"SqlClient is the lowest-level API in Jimmer Java org.babyfish.jimmer.sql.JSqlClient Kotlin org.babyfish.jimmer.sql.kt.KSqlClient You need to create a global object of this type, which is the API entry point for all ORM behaviors of Jimmer. Multiple data sources require creating multiple global objects. However, here we discuss the most common case of a single data source, where one global object is sufficient. Since we are using the Jimmer Spring Boot Starter, in this case, please specify the following configuration in application.yml (or application.properties) Java Kotlin spring: datasource: driver-class-name: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/jimmer_demo username: root password: 123456 jimmer: dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect show-sql: true pretty-sql: true database-validation-mode: ERROR spring: datasource: driver-class-name: com.mysql.cj.jdbc.Driver url: jdbc:mysql://localhost:3306/jimmer_demo username: root password: 123456 jimmer: language: kotlin // This is important for kotlin dialect: org.babyfish.jimmer.sql.dialect.MySqlDialect show-sql: true pretty-sql: true database-validation-mode: ERROR The Jimmer Spring Boot Starter will automatically create this global object Note that for Kotlin, in order to create KSqlClient instead of JSqlClient, you need to configure jimmer.language = kotlin in application.yml/application.properties. info Therefore, you can directly inject an object of type JSqlClient/KSqlClient anywhere. The subsequent code in this article will assume there is a sqlClient variable and use it, but it will not provide an explanation, as a detailed explanation has already been given here.","s":"SqlClient","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#sqlclient","p":1734},{"i":1739,"t":"Java Kotlin package com.example.model.repository; import org.babyfish.jimmer.sql.JSqlClient; import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.babyfish.jimmer.Page; import com.example.model.Book; import com.example.model.BookTable; public class BookRepository { private static final BookTable T = BookTable.$; private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } public Page findBooks( int pageIndex, // Starts from 0 int pageSize, @Nullable Fetcher fetcher, // e.g. \"name asc, edition desc\" @Nullable String sortCode, @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName, @Nullable Gender authorGender ) { return sqlClient .createQuery(T) .where(T.name().ilikeIf(name)) .where(T.price().betweenIf(minPrice, maxPrice)) .where(T.store().name().ilikeIf(storeName)) .where(T.store().website().ilikeIf(storeWebsite)) .where( T.authors(author -> Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .where(T.authors(author -> author.gender().eqIf(authorGender))) .orderBy( Order.makeOrders( T, sortCode != null ? sortCode : \"name asc, edition desc\" ) ) .select( T.fetch(fetcher) ) .fetchPage(pageIndex, pageSize); } } package com.example.model.repository import org.babyfish.jimmer.sql.kt.KSqlClient import org.babyfish.jimmer.sql.fetcher.Fetcher import org.babyfish.jimmer.Page import com.example.model.* class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( pageIndex: Int, // Starts from 0 pageSize: Int = 10, fetcher: Fetcher? = null, sortCode: String = \"name asc, edition desc\", name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, authorName: String? = null, authorGender: Gender? = null ): Page = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.website `ilike?` storeWebsite) where += table.authors { or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } where += table.authors { gender `eq?` authorGender } orderBy(table.makeOrders(sortCode)) select( table.fetch(fetcher) ) } .fetchPage(pageIndex, pageSize) } Users can create BookRepository objects and combine the parameters in various ways to test: Dynamic queries (including dynamic joins, implicit subqueries) Dynamic sorting Paged queries Details omitted here.","s":"Query","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#query","p":1734},{"i":1742,"t":"In the src/main/dto directory, create any file with extension dto and edit its code: export com.example.model.Book -> package com.example.model.dto input BookInput { #allScalars(this) id(store) // as storeId id(authors) as authorIds } Compile to generate the Java/Kotlin DTO type com.example.model.dto.BookInput: View Generated Code Then modify the BookRepository: Java Kotlin public class BookRepository { ...other members omitted... public long saveBook(BookInput input) { return sqlClient .save(input) .execute() .getModifiedEntity() // Return auto-generated id if `input.id` is null .getId(); } } class BookRepository { ...other members omitted... fun saveBook(input: BookInput): Long = sqlClient .save(input) .modifiedEntity // Return auto-generated id if `input.id` is null .id }","s":"Save Short Associations","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#save-short-associations","p":1734},{"i":1744,"t":"In the src/main/dto directory, create any file with extension dto and edit its code: export com.example.model.BookStore -> package com.example.model.dto input CompositeBookStoreInput { #allScalars(this) books { #allScalars(this) -id } } Compile to generate the Java/Kotlin DTO type com.example.model.dto.CompositeBookStoreInput: View Generated Code Then create the BookStoreRepository: Java Kotlin public class BookStoreRepository { public long saveBookStore(CompositeBookStoreInput input) { return sqlClient .save(input) .execute() .getModifiedEntity() // Return auto-generated id if `input.id` is null .getId(); } } class BookStoreRepository { fun saveBookStore(input: CompositeBookStoreInput): Long = sqlClient .save(input) .modifiedEntity // Return auto-generated id if `input.id` is null .id }","s":"Save Long Associations","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#save-long-associations","p":1734},{"i":1746,"t":"Modify the BookRepository: Java Kotlin public class BookRepository { ...other members omitted... public void deleteBook(long id) { sqlClient.deleteById(Book.class, id); } } class BookRepository { ...other members omitted... fun deleteBook(id: Long) { sqlClient.deleteById(Book::class, id) } }","s":"Delete","u":"/jimmer-doc/docs/quick-view/get-started/usage","h":"#delete","p":1734},{"i":1748,"t":"Through the previous chapters: We learned about the three core functionalities of Jimmer and got a basic impression of it. We also went through a simple project to understand the basics of using Jimmer, including how to use its Annotation Processor (Java) / KSP (Kotlin). However, for a comprehensive solution, having rich examples is better. Jimmer provides a series standard examples: tip Combining the accompanying examples is the most efficient way to get familiar with Jimmer.","s":"Standard Examples","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"","p":1747},{"i":1750,"t":"Like JOOQ, JPA2.0 Criteria, QueryDSL, MyBatis-Flex, Fluent-MyBatis and other types of strong-typed SQL DSL implementations, Jimmer needs to generate more source code based on user code. For Java, it is annotation processor For Kotlin, it is ksp When a user opens the accompanying examples in an IDE (such as IntelliJ) for the first time, some classes that should have been automatically generated will be missing. info Don't panic, click the run button and all errors will disappear automatically.","s":"Prerequisites","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#prerequisites","p":1747},{"i":1752,"t":"The accompanying examples of Jimmer are very helpful for quickly mastering Jimmer. The root directory of all examples: https://github.com/babyfish-ct/jimmer-examples This project provides 5 examples, each with Java and Kotlin versions, for a total of 10 projects. Java Kotlin Description How to Run Importance java/jimmer-core java/jimmer-core-kt ORM-unrelated example demonstrating immer-style immutable objects Run main method ★★★★ java/jimmer-sql java/jimmer-sql-kt Use Jimmer to quickly build REST services. This example demonstrates most of Jimmer's capabilities and is the most important and fundamental example. Run main method Visit swagger page: http://localhost:8080/ui Download client TypeScript code: http://localhost:8080/ts.zip Notes ★★★★★ java/jimmer-sql-graphql java/jimmer-sql-graphql-kt Use Jimmer to quickly build GraphQL services Run main method Visit GraphiQL page: http://localhost:8080/graphiql Notes ★★ java/jimmer-cloud java/jimmer-cloud-kt Microservice project based on Spring Cloud, demonstrating Jimmer's remote associations Start the registry center by running the main method of the registry-center subproject Start all microservices by running the main method in store-service, book-service and author-service Wait about half a minute to ensure the registry center correctly identifies all microservices to avoid exceptions in subsequent swagger calls where some remote services cannot be recognized. Visit the swagger-ui of any of the following microservices store-service: http://localhost:7001/ui book-service: http://localhost:7002/ui author-service: http://localhost:7003/ui note After starting all projects locally, if there is a communication failure between the microservices and it persists after waiting for some time, please visit http://localhost:7000 to open the eureka registration center, add the hostnames of the various registered services to your local hosts file. ★ java/save-command kotlin/save-command-kt Dedicated example for save commands Run all unit tests ★★★ tip When getting started, the most important examples are jimmer-sql and jimmer-sql-kt. Open either of them according to your language preference: Java jimmer-examples/java/jimmer-sql Kotlin jimmer-examples/kotlin/jimmer-sql-kt","s":"Example Introduction","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#example-introduction","p":1747},{"i":1754,"t":"Non-cache mode is the default running mode for all examples. No external environment needs to be installed for them to run directly. If an example depends on a database, it will use the H2 in-memory database in non-cache mode, and automatically create the database at startup. As you can see, non-cache mode is very simple and ideal for quickly getting familiar with the examples.","s":"Non-Cache Mode","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#non-cache-mode","p":1747},{"i":1756,"t":"As introduced above, there are 10 accompanying examples, 4 of which can demonstrate Jimmer's caching and cache consistency. java/jimmer-sql and kotlin/jimmer-sql-kt java/jimmer-sql-graphql and kotlin/jimmer-sql-graphql-kt By default, caching is not used, and they run on embedded in-memory databases with automatic database initialization. This ensures no external environment installation is required. Just click the run button to demonstrate. You can also start them in cache mode by running the program with the spring-boot profile maxwell or debezium. These two spring profiles utilize the CDC push capabilities of maxwell or debezium to achieve Cache Consistency tip In fact, relying on CDC push services like maxwell or debezium is not the only way to achieve Cache Consistency. Even without the help of any external technology, Jimmer can also achieve this capability. Jimmer's own capability to capture data changes is called Transaction Trigger Pushing database changes to Jimmer via external CDC technology is called BinLog Trigger Please refer to Trigger Classification. BinLog Trigger has better performance and universality (even if the database is changed through other means that bypass Jimmer, such as directly modifying the data using a SQL IDE, it can also be intercepted), so it is the recommended solution. Therefore, although Transaction Trigger can achieve Cache Consistency without relying on any special external environment, the official examples still use BinLog Trigger to synchronize the cache, as this is the more recommended approach. So we need to set up CDC services like maxwell or debezium to push database changes to Jimmer. Enabling cache mode requires building an external environment. First, you need to install docker on your local machine. Install the external environment The accompanying examples support two external environments. Feel free to choose either one to experience Cache Consistency","s":"Cache Mode","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#cache-mode","p":1747},{"i":1758,"t":"Although Maxwell only supports MySQL, it is the simplest of all database change push technologies. So it has demonstrational value. Open the command line, enter the local directory corresponding to jimmer-examples/env-with-cache/maxwell, and execute bash ./install.sh After installation, docker host port usage is enabled as follows Container Name Port Description maxwell-demo-zookeeper 4000 Support Kafka, users do not use directly maxwell-demo-kafka 4100 The exposed address is localhost, that is, assuming the docker host is your local machine. If you want to use a remote server as the docker host, you need to modify the kafka installation command in install.sh and modify the spring-boot configuration file in the examples maxwell-demo-kafdrop 4101 A Kafka GUI tool, visit http://localhost:4101 with a browser maxwell-demo-mysql 4200 Database service in this mode maxwell-demo-maxwell NA Background service that pushes MySQL changes to Kafka maxwell-demo-redis 4400 Caching service in this mode","s":"Maxwell + MySQL","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#maxwell--mysql","p":1747},{"i":1760,"t":"Debezium supports many databases and has good versatility. The example uses it to support change propagation for Postgres. info Postgres is a great open source database. If your project is brand new without any historical baggage, consider trying Postgres. This is why Jimmer's examples use Debezium to support Postgres. Open the command line, enter the local directory corresponding to jimmer-examples/env-with-cache/debezium, and execute bash ./install.sh After installation, docker host port usage is enabled as follows Container Name Port Description debezium-demo-zookeeper 5000 Support Kafka, users do not use directly debezium-demo-kafka 5100 The exposed address is localhost, that is, assuming the docker host is your local machine. If you want to use a remote server as the docker host, you need to modify the kafka installation command in install.sh and modify the spring-boot configuration file in the examples debezium-demo-kafdrop 5101 A Kafka GUI tool, visit http://localhost:5101 with a browser debezium-demo-postgres 5200 Database service in this mode debezium-demo-connect 5300 Responsible for pushing Postgres changes to Kafka using kafka-connector. You can verify whether the pg-connector named debezium-connector is successfully installed by visiting http://localhost:5300/connectors debezium-demo-redis 5400 Caching service in this mode","s":"Debezium + Postgres","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#debezium--postgres","p":1747},{"i":1762,"t":"caution If both the Maxwell + MySQL and Debezium + Postgres external environments are installed, some containers may fail to start due to insufficient memory. For example, on my Mac, the default memory allocated to docker is 2GB. Installing and starting all of the above containers, plus a few other unrelated containers, led to insufficient memory. The problem was resolved after setting to 3GB.","s":"Notes","u":"/jimmer-doc/docs/quick-view/standard-demo","h":"#notes","p":1747},{"i":1765,"t":"Save instructions allow developers to save data structures of any shape, rather than save simple objects. By default, when AssociatedSaveMode is set to REPLACE, Jimmer will completely replace the existing data structure in the database with the structure being saved, as shown in the figure: Top right: Users pass in a data structure of any shape for Jimmer to write to the database. Top left: Query the existing data structure from the database to compare with the new data structure passed in by users. Whatever shape of data structure the user passes in, the same shape will be queried from the database, ensuring the shapes of old and new data structures are identical. Therefore, the querying and comparison costs are determined by the complexity of the user-provided data structure. Below:Compare the new and old data structures, find the DIFF and execute corresponding SQL operations to make them consistent: Orange parts: For entity objects that exist in both new and old data structures, modify data if scalar properties have changed Blue parts: For entity objects that exist in both new and old data structures, modify associations if they have changed Green parts: For entity objects that exist in the old data structure but not in the new one, decouple this object, clear associations and possibly delete data Red parts: For entity objects that exist in the new data structure but not in the old one, insert data and establish associations tip Unlike other ORMs, Jimmer doesn't require describing how data should be saved in the entity model Whether certain scalar properties need to be saved Taking JPA as an example, this is controlled throughColumn.insertable andColumn.updatable. Whether certain association properties need to be saved Taking JPA as an example, this is controlled throughOneToOne.cascade,ManyToOne.cascade,OenToMany.cascade andManyToOne.cascade. Jimmer adopts a completely different strategy - its entity objects are not POJOs and can flexibly control the shape of data structures. That is, entity objects have dynamic properties - not specifying a property for an entity object and setting an entity's property to null are completely different things. For any entity object, Jimmer will only save the specified properties while ignoring unspecified ones. Therefore, Jimmer doesn't need to consider data saving behavior during entity modeling, but rather describes the expected behavior at runtime through the data structure being saved itself, providing absolute flexibility.","s":"Concept","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#concept","p":1763},{"i":1767,"t":"The UI design for modifying data in an application can be divided into two styles: Fully Commit This type of UI often has complex forms and provides a final button. After editing, the user submits all the information in the form at once. Incremental Commit This type of UI does not have a submit button. Each time the user completes a local operation, the page automatically submits the changed part, which is a fragmented commit mode. The greatest value of the Save Command lies in simplifying the development of fully commit mode functionality. For the two different modes, the usage is different. Fully Commit Incremental Commit Jimmer automatically handles the internal details, comparing the new and old data to find all differences and executing the relevant modification operations (Jimmer's unique perspective) Use the Save Command (parameters are often complex data structures) Business code uses a combination of multiple simple operations to implement complex operations, and the user handles the internal details (the same as traditional methods). Comprehensively use multiple methods: Save Command (parameters are often relatively simple objects) Delete Command Update Statement Delete Statement Directly Modify Join Tables Developers need to analyze their business scenarios to determine whether the current modification operation is a fully commit or an incremental commit, and make the right choice accordingly, without abuse.","s":"Scenarios","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#scenarios","p":1763},{"i":1769,"t":"In actual development, the data to be saved is always submitted by the client and can be passively accepted by the server (for example, @RequestBody in Spring). However, to simplify the discussion here, we directly hard code the object to be saved, so the code for the saved parameters is relatively more. Save simple object Java Kotlin sqlClient.save( Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(4); draft.setPrice(new BigDecimal(\"59.9\")); }) ); sqlClient.save( Book { name = \"GraphQL in Action\" edition = 4 price = BigDecimal(\"59.9\") } ) note Here, the id property of the object to be saved is not specified. Jimmer will determine whether related data exists in the database according to the name and edition properties, so as to decide whether to INSERT or UPDATE. This is because in the entity definition, Book.name and Book.edition are annotated with @org.babyfish.jimmer.sql.Key. This article is just a quick preview and does not go deep into it. Interested parties can view Mapping Part/Advanced Mapping/Key and Mutation Part/Save Command. Save data structures formed by multiple objects Java Kotlin sqlClient.save( Immutables.createBook(draft -> { draft.setName(\"GraphQL in Action\"); draft.setEdition(4); draft.setPrice(new BigDecimal(\"59.9\")); draft.applyStore(store -> { store.setName(\"MANNING\"); store.setWebsite(\"https://www.manning.com\"); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Bob\"); author.setLastName(\"Rockefeller\"); author.setGender(Gender.MALE); }); draft.addIntoAuthors(author -> { author.setFirstName(\"Eve\"); author.setLastName(\"Procello\"); author.setGender(Gender.FEMALE); }); }) ); sqlClient.save( Book { name = \"GraphQL in Action\" edition = 4 price = BigDecimal(\"59.9\") store { name = \"MANNING\" website = \"https://www.manning.com\" } authors().addBy { firstName = \"Bob\" lastName = \"Rockefeller\" gender = Gender.MALE } authors().addBy { firstName = \"Eve\" lastName = \"Procello\" gender = Gender.FEMALE } } );","s":"Demo","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#demo","p":1763},{"i":1771,"t":"In the previous text, we demonstrated two examples, one describing how to save a simple object, and the other describing how to save an aggregate root object and cascade save more associated objects. It is obvious that Jimmer's save directive can appear both simple and complex, depending on whether the data structure expressed by the dynamic entity passed by the user is simple or complex. Jimmer does not provide configuration cascade options for association properties like traditional ORM, because it is not necessary at all. The dynamic entity gives Jimmer's save capability unlimited possibilities, so there is no need to limit it to some fixed configuration. This absolute flexibility has many wonderful uses. For example, changing the price of book with id 100 to 60, the traditional ORM and Jimmer approaches are different: Traditional ORM (take JPA as an example) adopts find first and then modify, which is intuitive but wastes performance Book book = entityManager.find(Book.class, 100L); if (book != null) { book.setPrice(new BigDecimal(60)); // entityManager.merge(book); //Omit if the current JPA transaction context exists } Jimmer's approach, make up a mutilated object and directly update Java Kotlin boolean matched = sqlClient.update( Immutables.createBook(draft -> { draft.setId(100L); draft.setPrice(new BigDecimal(60)); // No other properties except `id` and `price` are specified // So no other properties except `price` will be affected }) ).getTotalAffectedRowCount() != 0; val matched = sqlClient.update( Book { id = 100L price = BigDecimal(60) // No other properties except `id` and `price` are specified // So no other properties except `price` will be affected } ).totalAffectedRowCount != 0","s":"Essential Difference from Other ORM","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#essential-difference-from-other-orm","p":1763},{"i":1773,"t":"The ability to save data structures of arbitrary shapes is too powerful so that it cannot be exposed directly, otherwise, it will lead to huge security vulnerabilities. For example: warning Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/book\") pubic int saveBook( @RequestBody Book book ) { return sqlClient .save(book) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @PutMapping(\"/book\") fun saveBook( @RequestBody book: Book ): Int = sqlClient .save(book) .totalAffectedRowCount } This method can work and is very powerful. The client can upload any data structure with Book as the aggregate root for the server to save. But this is also dangerous. You cannot limit the complexity of the data structure uploaded by the client. The client can arbitrarily modify associated data of any depth through this API. Even if you try to verify and limit the shape of the book parameter, it is still very easy to overlook and make mistakes. warning Therefore, the powerful Jimmer data saving capability can only be used as an underlying support internally in the service, and cannot expose this capability directly to remote clients by using dynamic entities as input parameters, because this will result in the security door wide open. To safely expose Jimmer's data saving capabilities, please continue reading the next article: Exposing Features","s":"Note: Cannot Expose Directly","u":"/jimmer-doc/docs/quick-view/save/feature","h":"#note-cannot-expose-directly","p":1763},{"i":1776,"t":"A long association refers to not only changing the association relationship between the current object and other objects, but also further modifying the associated object. For the UI interface, it is usually manifested as nested parent-child forms (or even recursive trees). The forms are diverse, and sub-forms embedded in forms are quite common, as follows: Purchaser Schneewittchen Purchaser Province Province City City Address Address Order Items Commodity Quantity Unit price Item price Delete Timeless Vitamin C Plus E 10 Percent Ferulic Acid Serum Serum Unisex 1 oz 14.69 29.38 Olaplex No. 4 Bond Maintenance Shampoo 30 30 Add Total price:59.379999999999995 Submit info As long as developers are willing, the depth of this nested parent-child form structure can be more than two layers. In theory, the depth can be infinite, which is why it is called a long association.","s":"What is Long Association","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#what-is-long-association","p":1774},{"i":1778,"t":"In the current example in the entity definition, the more suitable example as a long association to save is the BookStore and its associated books collection. Install DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This process is not required but highly recommended) Create a new directory src/main/dto Under src/main/dto, create a file BookStore.dto and write the following code: BookStore.dto export org.doc.j.model.BookStore -> package org.doc.j.model.dto input BookStoreWithLongAssociation { #allScalars(this) books { // LongAssociation #allScalars(this) -id id(authors) as authorIds } }","s":"Write DTO","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#write-dto","p":1774},{"i":1780,"t":"After compilation, Jimmer will generate the following code: Java Kotlin BookStoreWithLongAssociation.java @GeneratedBy( file = \"/src/main/dto/BookStore.dto\" ) public class BookStoreWithLongAssociation implements Input { @Nullable private Long id; @NotNull private String name; @Nullable private String website; @NotNull private List books; ...Omit other methods... public static class TargetOf_books implements Input { @NotNull private String name; private int edition; @NotNull private BigDecimal price; @NotNull private List authorIds; ...Omit other methods... } } BookStoreWithLongAssociation.kt @GeneratedBy( file = \"/src/main/dto/BookStore.dto\" ) data class BookStoreWithLongAssociation( val id: Long? val name: String, val website: String?, val books: List ) : Input { ...Omit other methods... data class TargetOf_authors( val name: String, val edition: Int, val price: BigDecimal, val authorIds: List ) }","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#generated-code","p":1774},{"i":1782,"t":"Java Kotlin BookStoreController.java @RestController public class BookStoreController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/bookStore\") public int saveBookStoreWithLongAssociation( @RequestBody BookStoreWithLongAssociation input ) { return sqlClient .save(input) .getTotalAffectedRowCount(); } } BookStoreController.java class BookStoreController( private val sqlClient: KSqlClient ) { @PutMapping(\"/bookStore\") fun saveBookStoreWithLongAssociation( @RequestBody input: BookStoreWithLongAssociation ): Int = sqlClient .save(input) .totalAffectedRowCount } It can be seen that no matter how the Input DTO changes, Jimmer still only needs one method call to complete data saving.","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/long","h":"#write-http-service","p":1774},{"i":1785,"t":"https://discord.gg/PmgR5mpY3E","s":"Discuss","u":"/jimmer-doc/docs/resource/discuss","h":"","p":1784},{"i":1790,"t":"Jimmer focuses only on the ORM itself and does not provide auxiliary tools, such as generating entity interface definitions based on the database structure. Enthusiastic people have contributed related tools, welcome everyone to actively contribute related tools, and submit PRs for me to include them in the list. As of now, the collected projects are:","s":"Ecosystem","u":"/jimmer-doc/docs/resource/ecosystem","h":"","p":1789},{"i":1792,"t":"IDE Project URL Intellij Plugin https://github.com/ClearPlume/jimmer-dto Supports any IDE that supports LSP https://github.com/Enaium/jimmer-dto-lsp","s":"DTO Language Syntax Highlighting Plugin","u":"/jimmer-doc/docs/resource/ecosystem","h":"#dto-language-syntax-highlighting-plugin","p":1789},{"i":1794,"t":"Project Type Tool Support Language Support Project URL Gradle Plugin Gradle Java & Kotlin https://github.com/ArgonarioD/gradle-plugin-jimmer Gradle Plugin Gradle Java & Kotlin https://github.com/Enaium/jimmer-gradle","s":"Simplify Project Configurations","u":"/jimmer-doc/docs/resource/ecosystem","h":"#simplify-project-configurations","p":1789},{"i":1796,"t":"Project Type Language Support Project URL Intellij Plugin Java & Kotlin https://github.com/ClearPlume/jimmer-generator Intellij Plugin Java & Kotlin https://github.com/huyaro/CodeGenX Maven Plugin Java https://github.com/TokgoRonin/code-generator-jimmer Gradle Plugin Java&Kotlin https://github.com/Enaium/jimmer-gradle Model Designer Java&Kotlin https://pot-mot.github.io/jimmer-code-gen-doc","s":"Generate Entity Definitions by Database","u":"/jimmer-doc/docs/resource/ecosystem","h":"#generate-entity-definitions-by-database","p":1789},{"i":1798,"t":"https://github.com/flynndi/quarkus-jimmer-extension","s":"Quarkus Extension","u":"/jimmer-doc/docs/resource/ecosystem","h":"#quarkus-extension","p":1789},{"i":1800,"t":"https://github.com/zengyufei/xm-jimmer-solon-plugin","s":"Solon Extension","u":"/jimmer-doc/docs/resource/ecosystem","h":"#solon-extension","p":1789},{"i":1802,"t":"There are two concepts in Jimmer Query multiple columns Query one object column and specify multiple properties of the queried objects They are completely different concepts","s":"1. Basic Query","u":"/jimmer-doc/docs/showcase/base","h":"","p":1801},{"i":1804,"t":"Java Kotlin BookTable table = BookTable.$; List> tuples = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.edition().desc()) .select( table.id(), table.name(), table.edition() ) .execute(); val tuples = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.edition.desc()) select( table.id, table.name, table.edition ) } .execute() In Jimmer, all queries except queries that return only one column are multi-column queries. This example queries three columns, so the return type is 'Tuple3'. The following data is obtained [ { \"_1\" : 12, \"_2\" : \"GraphQL in Action\", \"_3\" : 3 }, { \"_1\" : 11, \"_2\" : \"GraphQL in Action\", \"_3\" : 2 }, { \"_1\" : 10, \"_2\" : \"GraphQL in Action\", \"_3\" : 1 } ]","s":"Query multiple columns","u":"/jimmer-doc/docs/showcase/base","h":"#query-multiple-columns","p":1801},{"i":1806,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.edition().desc()) .select( table.fetch( BookTableFetcher.$ // `id()` is implicit and is always queried .name() .edition() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.edition.desc()) select( table.fetchBy { // `id()` is implicit and is always queried name() edition() } ) } .execute() The result is [ { \"id\" : 12, \"name\" : \"GraphQL in Action\", \"edition\" : 3 }, { \"id\" : 11, \"name\" : \"GraphQL in Action\", \"edition\" : 2 }, { \"id\" : 10, \"name\" : \"GraphQL in Action\", \"edition\" : 1 } ] It's easy to see that although this query has only one column, we can precisely control the format of this object. In this example, not all the properties of the Book object are queried ('price' and many-to-one association 'store' are not queried), because the Jimmer entity type 'Book' supports dynamic properties, the number of properties queried for the object does not affect the return type, and it is always of the 'Book' type. tip Jimmer entity objects are dynamic and can be typed uniformly to represent objects of any format (format is also called shape). Therefore, we do not need to use a multi-column query to control the return format under Jimmer, but we should use a single-column query to return a column of objects and flexibly control the object format. This results in Jimmer making less use of tuple-based multi-column queries and being more object-oriented.","s":"Specify properties of the queried object","u":"/jimmer-doc/docs/showcase/base","h":"#specify-properties-of-the-queried-object","p":1801},{"i":1808,"t":"Java Kotlin BookTable table = BookTable.$; List> tuples = sqlClient .createQuery(table) .where(table.name().eq(\"GraphQL in Action\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() ), Expression.numeric().sql( Integer.class, \"row_number() over(partition by %e order by %e desc)\", new Expression[] { table.storeId(), table.price() } ) ) .execute(); val tuples = sqlClient .createQuery(Book::class) { where(table.name eq \"GraphQL in Action\") orderBy(table.edition.desc()) .select( table.fetchBy { allScalarFields() }, sql(Int::class, \"row_number() over(partition by %e order by %e desc)\") { expression(table.storeId) expression(table.price) } ) } .execute() The result is [ { \"_1\":{ \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80 }, \"_2\":3 }, { \"_1\":{ \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81 }, \"_2\":2 }, { \"_1\":{ \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82 }, \"_2\":1 } ] This example queries two columns The first column is the object type, and the object format is 'allScalarFields' (contains all non-associated attributes)* The second column is a native SQL expression that calls the underlying database parse function ('%e' indicates a DSL expression that is used to implant the native SQL code) It's clearly a combination of the two.","s":"Combine both","u":"/jimmer-doc/docs/showcase/base","h":"#combine-both","p":1801},{"i":1813,"t":"Although Jimmer's data saving capability is designed for arbitrary complex data structures, in order to show how to safely expose the data saving capability step by step, this article only discusses saving a single object, and saving complex data structures will be described in subsequent articles. For more practical guidance, this article discusses two situations: Homogeneous change scenario: This is a relatively simple business scenario where the form structure of the INSERT operation and the UPDATE operation is consistent. Heterogeneous change scenario: This is a relatively complex business scenario where the form structures of the INSERT operation and the UPDATE operation are inconsistent. In addition, since the save directive only requires one function call, encapsulating it with Repository does not make much sense. In order to simplify unnecessary complexity, this article no longer defines Repository, but lets Controller use sqlClient directly.","s":"Overview","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#overview","p":1811},{"i":1816,"t":"Since we have some understanding of the DTO language in Query Arbitrary Shape/Exposing Features/Return Output DTO, this article will not repeat the discussion. Install DTO language Intellij plugin: https://github.com/ClearPlume/jimmer-dto (This process is not required but highly recommended) Create a new directory src/main/dto Under src/main/dto, create a file Book.dto and write the following code: Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto input BookInput { #allScalars(this) } ...Omit other DTO definitions... info Unlike the Output DTO in Query Arbitrary Shape/Exposing Features, the input DTO here uses the input modifier","s":"Define Input DTO","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#define-input-dto","p":1811},{"i":1818,"t":"After compilation, Jimmer will automatically generate the following types: Java Kotlin BookInput.java @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) public class BookInput implements Input { ❷ @Nullable ❸ private Long id; @NotNull private String name; private int edition; @NotNull private BigDecimal price; public BookInput(@NotNull Book base) { ❹ ...omitted... } @Override public Book toEntity() { ❺ ...omitted... } ...Omit other members... } BookInput.kt @GeneratedBy( ❶ file = \"/src/main/dto/Book.dto\" ) data class BookInput( id: Long?, ❸ name: String, edition: Int, price: BigDecimal ) : Input { ❷ constructor(base: Book): ❹ this(...) override fun toEntity(): Book = ❺ ... } ❶ Remind developers that this class is automatically generated by Jimmer ❷ Unlike the Output DTO in Query Arbitrary Shape/Exposing Features/Return Output DTO, after using the input modifier in the DTO language, the generated class will implement the Input interface instead of the View interface. ❸ If an auto increment strategy (such as automatic change, sequence, UUID, snowflake ID) is configured for the id attribute of the original entity, using the input modifier in the DTO language will cause the id attribute of the DTO to be null. The final DTO object will be converted to an entity object through ❺ and then saved by Jimmer. If the id attribute of the DTO is null, then after conversion to the entity, the id attribute of the entity will be in an unspecified state. For save operations that do not explicitly specify INSERT mode or UPDATE mode: If the id attribute of the entity object is specified, judge whether it should be INSERT or UPDATE according to id If the id attribute of the entity object is not specified, judge whether it should be INSERT or UPDATE according to key (in this case name and edition) ❹ Convert entity to DTO ❺ Convert DTO to entity","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#generated-code","p":1811},{"i":1820,"t":"Since DTO can be converted to entities, you can program like this: Java Kotlin BookInput input = ...omitted...; sqlClient.save(input.toEntity()); val input: BookInput = ...omitted... sqlClient.save(input.toEntity()) In fact, Jimmer provides a more convenient way, so that even calling the toEntity method to convert the DTO to an entity is not necessary, so the code can be simplified to: Java Kotlin BookInput input = ...omitted...; sqlClient.save(input); val input: BookInput = ...omitted... sqlClient.save(input) Next, you can implement the Controller: Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @PutMapping(\"/book\") public int saveBook( @RequestBody BookInput input ) { return sqlClient .save(input) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @PutMapping(\"/book\") fun saveBook( @RequestBody input: BookInput ): Int = sqlClient .save(input) .totalAffectedRowCount }","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#write-http-service","p":1811},{"i":1823,"t":"Here we assume that there are two types of book management roles: Provide two roles that can save books: Operator: Can only modify the price of existing books Administrator: Can create and edit all information of books For the Administrator role, the Web API for creating new books and the Web API for editing books need to be separated","s":"Requirements","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#requirements","p":1811},{"i":1825,"t":"Book.dto export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto /** * Input for the `Operator` role to modify books, can only modify the `price` attribute */ input BookOperatorUpdateInput { id! // Override default behavior, id cannot be null price } /** * Input for the `Administrator` role to create new books, no id attribute */ input BookAdministratorCreateInput { #allScalars(this) -id // Creating new books does not need id } /** * Input for the `Administrator` role to modify books, id attribute cannot be null */ input BookAdministratorUpdateInput { #allScalars(this) id! // Override default behavior, id cannot be null } ...Omit other DTO definitions...","s":"Write DTO","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#write-dto","p":1811},{"i":1827,"t":"After compilation, the following three types are automatically generated: BookOperatorUpdateInput Java Kotlin BookOperatorUpdateInput /** * Input for the `Operator` role to modify books, can only modify the `price` attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookOperatorUpdateInput implements Input { private long id; @NotNull private BigDecimal price; ...Omit other methods... } BookOperatorUpdateInput /** * Input for the `Operator` role to modify books, can only modify the `price` attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookOperatorUpdateInput( val id: Long, val price: BigDecimal ) : Input { ...Omit other methods... } BookAdministratorCreateInput Java Kotlin BookAdministratorCreateInput /** * Input for the `Administrator` role to create new books, no id attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookAdministratorCreateInput implements Input { @NotNull private String name; private int edition; @NotNull private BigDecimal price; ...Omit other methods... } BookAdministratorCreateInput /** * Input for the `Administrator` role to create new books, no id attribute */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookAdministratorCreateInput( val name: String, val edition: Int, val price: BigDecimal ) : Input { ...Omit other methods... } BookAdministratorUpdateInput Java Kotlin BookAdministratorUpdateInput /** * Input for the `Administrator` role to modify books, id attribute cannot be null */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) public class BookAdministratorUpdateInput implements Input { @NotNull private String name; private int edition; @NotNull private BigDecimal price; private long id; ...Omit other methods... } BookAdministratorUpdateInput /** * Input for the `Administrator` role to modify books, id attribute cannot be null */ @GeneratedBy( file = \"/src/main/dto/Book.dto\" ) data class BookAdministratorUpdateInput( val name: String, val edition: Int, val price: BigDecimal, val id: Long ) : Input { ...Omit other methods... }","s":"Generated Code","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#generated-code-1","p":1811},{"i":1829,"t":"Java Kotlin BookController.java @RestController public class BookController { private final JSqlClient sqlClient; public BookController(JSqlClient sqlClient) { this.sqlClient = sqlClient; } @Secured(\"ADMINISTRATOR\") @PostMapping(\"/book\") public int createBookByAdministrator( @RequestBody BookAdministratorCreateInput input ) { return sqlClient .insert(input) .getTotalAffectedRowCount(); } @Secured(\"OPERATOR\") @PutMapping(\"/book/byOperator\") public int updateBookByOperator( @RequestBody BookOperatorUpdateInput input ) { return sqlClient .update(input) .getTotalAffectedRowCount(); } @Secured(\"ADMINISTRATOR\") @PutMapping(\"/book\") public int updateBookByAdministrator( @RequestBody BookAdministratorUpdateInput input ) { return sqlClient .update(input) .getTotalAffectedRowCount(); } } BookController.java class BookController( private val sqlClient: KSqlClient ) { @Secured(\"ADMINISTRATOR\") @PutMapping(\"/book\") fun createBookByAdministrator( @RequestBody input: BookAdministratorCreateInput ): Int = sqlClient .insert(input) .totalAffectedRowCount @Secured(\"OPERATOR\") @PutMapping(\"/book/byOperator\") fun createBookByAdministrator( @RequestBody input: BookOperatorUpdateInput ): Int = sqlClient .update(input) .totalAffectedRowCount @Secured(\"ADMINISTRATOR\") @PutMapping(\"/book/byOperator\") fun updateBookByAdministrator( @RequestBody input: BookAdministratorUpdateInput ): Int = sqlClient .update(input) .totalAffectedRowCount } It is not difficult to find that no matter how diversified the Input DTO parameters are, Jimmer completes the data saving with one method call.","s":"Write HTTP Service","u":"/jimmer-doc/docs/quick-view/save/export/root","h":"#write-http-service-1","p":1811},{"i":1832,"t":"Java Kotlin BookStoreTable table = BookStoreTable.$; List stores = sqlClient .createQuery(table) .where(table.name().eq(\"MANNING\")) .select( table.fetch( BookStoreFetcher.$ .allScalarFields() .books( ❶ BookFetcher.$ .allScalarFields() .authors( ❷ AuthorFetcher.$ .allScalarFields() ) ) ) ) .execute(); val books = sqlClient .createQuery(BookStore::class) { where(table.name eq \"MANNING\") select( table.fetchBy { allScalarFields() books { ❶ allScalarFields() authors { ❷ allScalarFields() } } } ) } .execute() The result is [ { \"id\":2, \"name\":\"MANNING\", \"website\":null, \"books\":[ ❶ { \"id\":12, \"name\":\"GraphQL in Action\", \"edition\":3, \"price\":80, \"authors\":[ ❷ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":11, \"name\":\"GraphQL in Action\", \"edition\":2, \"price\":81, \"authors\":[ ❷ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] }, { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82, \"authors\":[ ❷ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\", \"gender\":\"MALE\" } ] } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/fetch-association/deeper-association","h":"#query-dynamic-entities","p":1830},{"i":1834,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.BookStore -> package com.yourcompany.yourproject.model.dto BookStoreView { #allScalars(this) books { ❶ #allScalars(this) authors { ❷ #allScalars(this) } } } Compile the project, a java/kotlin class named BookStoreView will be automatically generated. Java Kotlin BookStoreTable table = BookStoreTable.$; List stores = sqlClient .createQuery(table) .where(table.name().eq(\"MANNING\")) .select( table.fetch(BookStoreView.class) ) .execute(); val stores = sqlClient .createQuery(BookStore::class) { where(table.name eq \"Learning GraphQL\") select( table.fetch(BookStoreView::class) ) } .execute() The result is [ BookStoreView( id=2, name=MANNING, website=null, books=[ BookStoreView.TargetOf_books( id=12, name=GraphQL in Action, edition=3, price=80.00, authors=[ BookStoreView.TargetOf_books.TargetOf_authors_2( id=5, firstName=Samer, lastName=Buna, gender=MALE ) ] ), BookStoreView.TargetOf_books( id=11, name=GraphQL in Action, edition=2, price=81.00, authors=[ BookStoreView.TargetOf_books.TargetOf_authors_2( id=5, firstName=Samer, lastName=Buna, gender=MALE ) ] ), BookStoreView.TargetOf_books( id=10, name=GraphQL in Action, edition=1, price=82.00, authors=[ BookStoreView.TargetOf_books.TargetOf_authors_2( id=5, firstName=Samer, lastName=Buna, gender=MALE ) ] ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/deeper-association","h":"#query-static-dto","p":1830},{"i":1837,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .authors( AuthorFetcher.$ .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() authors { allScalarFields() } } ) } .execute() The result is [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/fetch-association/associated-object","h":"#query-dynamic-entities","p":1835},{"i":1839,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars(this) authors { #allScalars(this) } } Compile the project, a java/kotlin class named BookView will be automatically generated. Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetch(BookView::class) ) } .execute() The result is [ BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, authors=[ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/associated-object","h":"#query-static-dto","p":1835},{"i":1841,"t":"Unlike the previous example, here we only need to fetch the associated object id, not the entire associated object.","s":"2.4 Associated Id","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"","p":1840},{"i":1844,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .authors() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() authors() } ) } .execute() The result is [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":2 }, { \"id\":1 } ] } ] This will lead to large numbers of objects that have only the id property (JPA users can understand them as entity proxies), although correct, this may not be the format preferred by developers. In the next section we discuss how to solve this problem.","s":"If there is no IdView property","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"#if-there-is-no-idview-property","p":1840},{"i":1846,"t":"In order to solve the above problem, we can add the @IdView property for entity interface, namely the associated id property. Java Kotlin @Entity public interface Book { @ManyToMany List authors(); @IdView(\"authors\") List authorIds(); ....省略其他属性... } @Entity interface Book { @ManyToMany val authors: List @IdView(\"authors\") val authorIds: List ....省略其他属性... } Here, the authorIds property is a view of the authors property, and they share data. So, it does not change the entity format, it just diversifies the expression. info This is just a case study, no in-depth discussion of the @IdView property. Please refer here for more details Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .authorIds() ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() authorIds() } ) } .execute() The result is [ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authorIds\":[2, 1] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"authorIds\":[2, 1] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"authorIds\":[2, 1] } ]","s":"If there is IdView property","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"#if-there-is-idview-property","p":1840},{"i":1848,"t":"No need to define @IdView attributes in entities, create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars id(authors) as authorIds } Compile the project, a java/kotlin class named BookView will be automatically generated. Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetch(BookView::class) ) } .execute() The result is [ BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, authorIds=[2, 1] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, authorIds=[2, 1] ), BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, authorIds=[2, 1] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/associated-id","h":"#query-static-dto","p":1840},{"i":1851,"t":"So far, we've quickly demonstrated the following features Object Fetcher, i.e. querying arbitrarily shaped data structures, are what are shown in Fetch Association and Recursive Query. Conditions, especially Dynamic table join and Implicit subquery Sorting, including dynamic sorting Paging queries Now, let's combine all of the above features into a relatively powerful query Again, there are two ways to develop Query dynamic entities Query static DTOs","s":"7. Comprehensive Query","u":"/jimmer-doc/docs/showcase/comprehensive-query","h":"","p":1850},{"i":1853,"t":"Java Kotlin public class BookRepository { private static final BookTable T = BookTable.$; private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } public Page findBooks( int pageIndex, int pageSize, @Nullable String sortCode, @Nullable Fetcher fetcher, @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName ) { return sqlClient .createQuery(T) .where(T.name().ilikeIf(name)) .where(T.price().betweenIf(minPrice, maxPrice)) .where(T.store().name().ilikeIf(storeName)) .where(T.store().website().ilikeIf(storeWebsite)) .where( T.authors(author -> Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .orderBy( Order.makeOrders( T, sortCode != null ? sortCode : \"name asc, edition desc\" ) ) .select(T.fetch(fetcher)) .fetchPage(pageIndex, pageSize); } } class BookRepository( private val sqlClient: KSqlClient ) { fun findBooks( pageIndex: Int, pageSize: Int = 10, sortCode: String = \"name asc, edition desc\", fetcher: Fetcher? = null, name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, name: String? = null ): Page = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.website `ilike?` storeWebsite) where += table.authors { or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } orderBy(table.makeOrders(sortCode)) select(table.fetch(fetcher)) } .fetchPage(pageIndex, pageSize) } info Here, the 'findBooks' method has too many parameters. This doesn't matter to Kotlin, but it may not be a good design for Java. If your project is based on the Java language, you can choose to reduce the number of parameters in the Java language by distilling all or some of the parameters into an object. However, this does not provide substantial benefit to the example presentation here, therefore, we do not do so in order to maintain a high degree of consistency between the Java and Kotlin examples. The user can use it like this (considering that Java doesn't have a good way to simplify the invocation to a method with many parameters, just a demonstration the kotlin invocation) val bookRepository = ...Omitted... val page = bookRepository.findBooks( pageIndex = 1, pageSize = 2, name = \"GraphQL\", maxPrice = BigDecimal(60), authorName = \"alex\", fetcher = newFetcher(Book::class).by { allScalarFields() store { name() } authors { firstName() lastName() } } ) The result is Page{ rows=[ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50.00, \"store\":{\"id\":1,\"name\":\"O'REILLY\"}, \"authors\":[ {\"id\":2,\"firstName\":\"Alex\",\"lastName\":\"Banks\"}, {\"id\":1,\"firstName\":\"Eve\",\"lastName\":\"Procello\"} ] } ], totalRowCount=3, totalPageCount=2 }","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/comprehensive-query","h":"#query-dynamic-entities","p":1850},{"i":1855,"t":"Java Kotlin public class BookRepository { private static final BookTable T = BookTable.$; private final JSqlClient sqlClient; public BookRepository(JSqlClient sqlClient) { this.sqlClient = sqlClient; } public > Page findBooks( int pageIndex, int pageSize, @Nullable String sortCode, @Nullable Class viewType, @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice, @Nullable String storeName, @Nullable String storeWebsite, @Nullable String authorName ) { return sqlClient .createQuery(T) .where(T.name().ilikeIf(name)) .where(T.price().betweenIf(minPrice, maxPrice)) .where(T.store().name().ilikeIf(storeName)) .where(T.store().website().ilikeIf(storeWebsite)) .where( T.authors(author -> Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .orderBy( Order.makeOrders( T, sortCode != null ? sortCode : \"name asc, edition desc\" ) ) .select(T.fetch(viewType)) .fetchPage(pageIndex, pageSize); } } class BookRepository( private val sqlClient: KSqlClient ) { fun > findBooks( pageIndex: Int, pageSize: Int = 10, sortCode: String = \"name asc, edition desc\", viewType: KClass, name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null, storeName: String? = null, storeWebsite: String? = null, name: String? = null ): Page = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.price.`between?`(minPrice, maxPrice)) where(table.store.name `ilike?` storeName) where(table.store.website `ilike?` storeWebsite) where += table.authors { or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } orderBy(table.makeOrders(sortCode)) select(table.fetch(viewType)) } .fetchPage(pageIndex, pageSize) } info Here, the 'findBooks' method has too many parameters. This doesn't matter to Kotlin, but it may not be a good design for Java. If your project is based on the Java language, you can choose to reduce the number of parameters in the Java language by distilling all or some of the parameters into an object. However, this does not provide substantial benefit to the example presentation here, therefore, we do not do so in order to maintain a high degree of consistency between the Java and Kotlin examples. To demonstrate the invocation, let's first use the DTO language to automatically generate a DTO type that implements the View interface. Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars store { id name } authors { id firstName lastName } } Compile the project, a java/kotlin class named BookView will be automatically generated. The user can use it like this (considering that Java doesn't have a good way to simplify the invocation to a method with many parameters, just a demonstration the kotlin invocation) val bookRepository = ...Omitted... val page = bookRepository.findBooks( name = \"GraphQL\", maxPrice = BigDecimal(60), authorName = \"alex\", viewType = BookView::class ) 得到如下结果 Page{ rows=[ BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookView.TargetOf_store(id=1, name=O'REILLY), authors=[ BookView.TargetOf_authors(id=2, firstName=Alex, lastName=Banks), BookView.TargetOf_authors(id=1, firstName=Eve, lastName=Procello) ] ) ], totalRowCount=3, totalPageCount=2 }","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/comprehensive-query","h":"#query-static-dto","p":1850},{"i":1857,"t":"Dynamic sorting refers to the sorting method being dynamically specified by the client.","s":"5.2 Dynamic Sorting","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"","p":1856},{"i":1859,"t":"The simplest way for the client to specify sorting is strings. The string formats supported by Jimmer are as follows: store.name asc, name asc, edition desc or store.name asc; name asc; edition desc Where store.name means first inner join the associated object BookStore through the Book.store property, and then sort by the name property of the associated object. The path length is unlimited, but the association type along the way needs to be one-to-one or many-to-one. Java Kotlin String sortCode = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy(Order.makeOrders(table, sortCode)) .select(table) .execute(); val sortCode: String = ...Omitted... val books = sqlClient .createQuery(Book::class) { orderBy(table.makeOrders(sortCode)) select(table) } .execute()","s":"Use Strings Directly","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#use-strings-directly","p":1856},{"i":1861,"t":"Sometimes, when developing in combination with Spring Data, org.springframework.data.domain.Sort may be used to represent dynamic sorting. At this point, developers need to perform two steps:","s":"Transfer via Spring Sort","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#transfer-via-spring-sort","p":1856},{"i":1863,"t":"The easiest uploading way for the client is still the string discussed earlier, like store.name asc, name asc, edition desc or store.name asc; name asc; edition desc. Therefore, first the string needs to be converted to the org.springframework.data.domain.Sort object. After importing the dependency org.babyfish.jimmer:jimmer-spring-boot-starter:$version, the static method org.babyfish.jimmer.spring.model.SortUtils.toSort can then be used, as follows: Java Kotlin String sortCode = ...Omitted...; Sort sort = SortUtils.toSort(sortCode); val sortCode: String = ...Omitted... val sort = SortUtils.toSort(sortCode)","s":"I. Convert string to Sort Object","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#i-convert-string-to-sort-object","p":1856},{"i":1865,"t":"After importing the dependency org.babyfish.jimmer:jimmer-spring-boot-starter:$version: Java: Use the utility method org.babyfish.jimmer.spring.repository.SpringOrders.toOrders to convert the org.springframework.data.domain.Sort object into a collection of ordering objects accepted by Jimmer. Kotlin: Directly use the orderBy extension function that accepts org.springframework.data.domain.Sort object. Java Kotlin org.springframework.data.domain.Sort sort = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy(SpringOrders.toOrders(table, sort)) .select(table) .execute(); val sort: org.springframework.data.domain.Sort = ...Omitted... val books = sqlClient .createQuery(Book::class) { orderBy(sort) select(table) } .execute()","s":"II. Sort using Sort object","u":"/jimmer-doc/docs/showcase/order-by/dynamic","h":"#ii-sort-using-sort-object","p":1856},{"i":1868,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch( BookFetcher.$ .allScalarFields() .store( ❶ BookStoreFetcher.$ .allScalarFields() ) .authors( ❷ AuthorFetcher.$ .allScalarFields() ) ) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetchBy { allScalarFields() store { ❶ allScalarFields() } authors { ❷ allScalarFields() } } ) } .execute() The result is [ { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ ❶ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ ❷ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ ❶ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ ❷ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store\":{ ❶ \"id\":1, \"name\":\"O'REILLY\", \"website\":null }, \"authors\":[ ❷ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/fetch-association/more-association","h":"#query-dynamic-entities","p":1866},{"i":1870,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.Book -> package com.yourcompany.yourproject.model.dto BookView { #allScalars(this) store { ❶ #allScalars(this) } authors { ❷ #allScalars(this) } } Compile the project, a java/kotlin class named BookView will be automatically generated. Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().eq(\"Learning GraphQL\")) .orderBy(table.edition().desc()) .select( table.fetch(BookView.class) ) .execute(); val books = sqlClient .createQuery(Book::class) { where(table.name eq \"Learning GraphQL\") orderBy(table.edition.desc()) select( table.fetch(BookView::class) ) } .execute() The result is [ BookView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookView.TargetOf_store( ❶ id=1, name=O'REILLY, website=null ), authors=[ ❷ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=2, name=Learning GraphQL, edition=2, price=55.00, store=BookView.TargetOf_store( ❶ id=1, name=O'REILLY, website=null ), authors=[ ❷ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ), BookView( id=3, name=Learning GraphQL, edition=3, price=51.00, store=BookView.TargetOf_store( ❶ id=1, name=O'REILLY, website=null ), authors=[ ❷ BookView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/fetch-association/more-association","h":"#query-static-dto","p":1866},{"i":1873,"t":"Jimmer supports built-in Page objects org.babyfish.jimmer.Page org.springframework.data.domain.Page note In fact, Jimmer allows users to customize any Page object. However, this article does not discuss this issue, partly because this article is only a showcase page and does not want to go into depth, and on the other hand, these two built-in Page objects are usually sufficient. As far as these two built-in Page objects are concerned, the differences are as follows: org.springframework.data.domain.Page: Designed for server-side pages, in order for the page to remain in its previous state after refresh, a lot of information (such as cumbersome sorting information) needs to be returned to the client as is, so it is very complex. org.babyfish.jimmer.Page: For the design of rich client pages, this kind of client page itself is a stateful application, and the server side provide pure data services, and only return the most necessary information, so it is very simple.","s":"Two types of Page objects","u":"/jimmer-doc/docs/showcase/page","h":"#two-types-of-page-objects","p":1871},{"i":1875,"t":"Java Kotlin int pageIndex = ...Omitted...; // 从0开始 int pageSize = ...Omitted...; BookTable table = BookTable.$; org.babyfish.jimmer.Page page = sqlClient .createQuery(table) .orderBy(table.name().asc()) .orderBy(table.edition().desc()) .select(table) .fetchPage(pageIndex, pageSize); val pageIndex: Int = ...Omitted...; // Starts from 0 val pageSize: Int = ...Omitted...; val page: org.babyfish.jimmer.Page = sqlClient .createQuery(Book::class) { orderBy(table.name.asc()) orderBy(table.edition().desc()) select(table) } .fetchPage(pageIndex, pageSize) If pageIndex is 1 * (page 2) * and pageSize is 5, the result is Page{ rows=[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82.00, \"store\":{\"id\":2} }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51.00, \"store\":{\"id\":1} }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55.00, \"store\":{\"id\":1} }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50.00, \"store\":{\"id\":1} }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48.00, \"store\":{\"id\":1} } ], totalRowCount=12, totalPageCount=3 }","s":"Using the page of Jimmer","u":"/jimmer-doc/docs/showcase/page","h":"#using-the-page-of-jimmer","p":1871},{"i":1877,"t":"After importing the dependency 'org.babyfish.jimmer:jimmer-spring-boot-starter:$version' Usage supported by both Java and Kotlin: Use SpringPageFactory.getInstance() as the third argument to fetchPage Kotlin-specific usage: Directly call the extension function fetchSpringPage. Java Kotlin int pageIndex = ...Omitted...; // 从0开始 int pageSize = ...Omitted...; BookTable table = BookTable.$; org.springframework.data.domain.Page page = sqlClient .createQuery(table) .orderBy(table.name().asc()) .orderBy(table.edition().desc()) .select(table) .fetchPage( pageIndex, pageSize, SpringPageFactory.getInstance() ); val pageIndex: Int = ...Omitted...; // Starts from 0 val pageSize: Int = ...Omitted...; val page: org.springframework.data.domain.Page = sqlClient .createQuery(Book::class) { orderBy(table.name.asc()) orderBy(table.edition().desc()) select(table) } .fetchSpringPage( pageIndex, pageSize ) If pageIndex is 1 * (page 2) * and pageSize is 5, the result is { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":82, \"store\":{\"id\":2} }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{\"id\":1} }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{\"id\":1} }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"store\":{\"id\":1} }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{\"id\":1} } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"numberOfElements\":5, \"first\":false, \"size\":5, \"number\":1, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"empty\":false }","s":"Using the page of Spring Data","u":"/jimmer-doc/docs/showcase/page","h":"#using-the-page-of-spring-data","p":1871},{"i":1881,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch( TreeNodeFetcher.$ .allScalarFields() .recursiveChildNodes( cfg -> cfg.depth(2) ) ) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { depth(2) } } ) } .execute() The currently queried aggregate roots are defined as the 0th layer. On this basis, query two layers of child objects downwards to obtain the following data: [ { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":2, \"name\":\"Food\", \"childNodes\":[ {\"id\":3,\"name\":\"Drinks\"}, {\"id\":6,\"name\":\"Bread\"} ] }, { \"id\":9, \"name\":\"Clothing\", \"childNodes\":[ {\"id\":10,\"name\":\"Woman\"}, {\"id\":18,\"name\":\"Man\"} ] } ] } ] info The deepest 4 objects do not have the childNodes property as [], but do not have the childNodes property at all. This means whether these 4 objects have subordinate objects is unknown, because the recursion process was prematurely terminated due to manual intervention.","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/depth","h":"#query-dynamic-entities","p":1879},{"i":1883,"t":"Restricting recursion depth for static DTOs will be provided in later versions, please wait for later versions.","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/depth","h":"#query-static-dto","p":1879},{"i":1886,"t":"Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy(table.name().asc()) .orderBy(table.edition().desc()) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { orderBy(table.name.asc()) orderBy(table.edition.desc()) select(table) } .execute()","s":"Multiple orderBy actions","u":"/jimmer-doc/docs/showcase/order-by/usage","h":"#multiple-orderby-actions","p":1884},{"i":1888,"t":"There is another way to write the equivalent of the above code Java Kotlin BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .orderBy( table.name().asc(), table.edition().desc() ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { orderBy( table.name.asc(), table.edition.desc() ) select(table) } .execute() However, the previous way of writing is more conducive to the organization of the code structure, so the previous way of writing is more recommended.","s":"orderBy with multiple arguments","u":"/jimmer-doc/docs/showcase/order-by/usage","h":"#orderby-with-multiple-arguments","p":1884},{"i":1890,"t":"Java Kotlin BookTable table = BookTable.$; AuthorTableEx author = AuthorTableEx.$; List books = sqlClient .createQuery(table) .orderBy( sqlClient .createSubQuery(author) .where(author.books().eq(table)) .select(Expression.rowCount()) .desc() ) .select(table) .execute(); val books = sqlClient .createQuery(Book::class) { orderBy( subQuery(Author::class) { where(table.books() eq parentTable) select(rowCount()) } .desc() ) select(table) } .execute()","s":"Sorting based on subqueries","u":"/jimmer-doc/docs/showcase/order-by/usage","h":"#sorting-based-on-subqueries","p":1884},{"i":1893,"t":"Java Kotlin BookTable book = BookTable.$; List newestBooks = sqlClient .createQuery(book) .where( Expression.tuple( book.name(), book.edition() ).in(sqlClient .createSubQuery(book) .groupBy(book.name()) .select( book.name(), book.edition().max() ) ) ) .select(book) .execute(); val newestBooks = sqlClient .createQuery(Book::class) { where( tuple( table.name, table.edition ) valueIn subQuery(Book::class) { groupBy(table.name) select( table.name, max(table.edition).asNonNull() ) } ) select(table) } .execute()","s":"标准子查询","u":"/jimmer-doc/docs/showcase/other-query","h":"#标准子查询","p":1891},{"i":1895,"t":"为了支持特有数据库产品特有的能力，Jimmer的SQL DSL支持嵌入Native SQL表达式。以正则表达式查询为例。 Java Kotlin AuthorTable table = Tables.AUTHOR_TABLE; List authors = sqlClient .createQuery(table) .where( Predicate.sql( \"regexp_like(%e, %v)\", it -> it .expression(table.firstName()) .value(\"^Ste(v|ph)en$\") ) ) .select(table) .execute(); val authors = sqlClient .createQuery(Author::class) { where( sql(Boolean::class, \"regexp_like(%e, %v)\") { expression(table.firstName) value(\"^Ste(v|ph)en$\") } ) select(table) } .execute() Native SQL片段中的%e表示可以嵌入一个强类型的Jimmer DSL表达式。 Lambda中的expression(...)指定用于替换%e的表达式。 Native SQL片段中的%v表示可以嵌入一个字面量。 Lambda中的value(...)指定用于替换%v的字面量。","s":"Native SQL","u":"/jimmer-doc/docs/showcase/other-query","h":"#native-sql","p":1891},{"i":1898,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch( TreeNodeFetcher.$ .allScalarFields() .recursiveChildNodes(cfg -> { cfg.recursive(it -> { return !it.getEntity().name().equals(\"Clothing\"); }); }) ) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*` { recursive { entity.name != \"Clothing\" } } } ) } .execute() If the name of the current tree node is equal to Clothing, terminate the recursion, otherwise continue recursion. The result is as follows: [ { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":2, \"name\":\"Food\", \"childNodes\":[ { \"id\":3, \"name\":\"Drinks\", \"childNodes\":[ { \"id\":4, \"name\":\"Coca Cola\", \"childNodes\":[] }, { \"id\":5, \"name\":\"Fanta\", \"childNodes\":[] } ] }, { \"id\":6, \"name\":\"Bread\", \"childNodes\":[ { \"id\":7, \"name\":\"Baguette\", \"childNodes\":[] }, { \"id\":8, \"name\":\"Ciabatta\", \"childNodes\":[] } ] } ] }, {\"id\":9,\"name\":\"Clothing\"} ] } ] info The Clothing object does not have the childNodes property as [], but does not have the childNodes property at all. This means whether the Clothing object has subordinate objects is unknown, because the recursion process was prematurely terminated due to manual intervention.","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/node-control","h":"#query-dynamic-entities","p":1896},{"i":1900,"t":"Controlling whether each node recurses using static DTOs will be provided in later versions, please wait for later versions.","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/node-control","h":"#query-static-dto","p":1896},{"i":1902,"t":"In the past few months, save command has been undergoing a major restructuring, so it has not been written. The good news is that this historically significant restructuring of Jimmer has finally been completed and stabilized, so the content here will be completed soon.","s":"X. To be Continued...","u":"/jimmer-doc/docs/showcase/to-be-conitnued","h":"","p":1901},{"i":1907,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; TreeNode treeNode = sqlClient .findById( TreeNodeFetcher.$ .allScalarFields() .recursiveParent() ❶ .recursiveChildNodes() ❷, 10L ); val treeNode = sqlClient .findById( newFetcher(TreeNode::class).by { allScalarFields() `parent*`() ❶ `childNodes*`() ❷ }, 10L ) The result is { \"id\":10, \"name\":\"Woman\", \"parent\":{ ❶ \"id\":9, \"name\":\"Clothing\", \"parent\":{ ❶ \"id\":1, \"name\":\"Home\", \"parent\":null ❶ } }, \"childNodes\":[ ❷ { \"id\":11, \"name\":\"Casual wear\", \"childNodes\":[ ❷ { \"id\":12, \"name\":\"Dress\", \"childNodes\":[] ❷ }, { \"id\":13, \"name\":\"Miniskirt\", \"childNodes\":[] ❷ }, { \"id\":14, \"name\":\"Jeans\", \"childNodes\":[] ❷ } ] }, { \"id\":15, \"name\":\"Formal wear\", \"childNodes\":[ ❷ { \"id\":16, \"name\":\"Suit\", \"childNodes\":[] ❷ }, { \"id\":17, \"name\":\"Shirt\", \"childNodes\":[] ❷ } ] } ] }","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/multiple-props","h":"#query-dynamic-entities","p":1905},{"i":1909,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.TreeNode -> package com.yourcompany.yourproject.model.dto RecursiveTreeNodeView { #allScalars(this) parent* ❶ childNodes* ❷ } Compile the project, a java/kotlin class named RecursiveTreeNodeView will be automatically generated. Java Kotlin TreeNodeTable table = TreeNodeTable.$; RecursiveTreeNodeView treeNode = sqlClient .findById( RecursiveTreeNodeView.class, 10L ); val treeNode = sqlClient .findById( RecursiveTreeNodeView::class, 10L ) The result is RecursiveTreeNodeView( id=10, name=Woman, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=9, name=Clothing, parent=RecursiveTreeNodeView.TargetOf_parent( ❶ id=1, name=Home, parent=null ❶ ) ), childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=11, name=Casual wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=12, name=Dress, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=13, name=Miniskirt, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=14, name=Jeans, childNodes=[] ❷ ) ] ), RecursiveTreeNodeView.TargetOf_childNodes( id=15, name=Formal wear, childNodes=[ ❷ RecursiveTreeNodeView.TargetOf_childNodes( id=16, name=Suit, childNodes=[] ❷ ), RecursiveTreeNodeView.TargetOf_childNodes( id=17, name=Shirt, childNodes=[] ❷ ) ] ) ] )","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/multiple-props","h":"#query-static-dto","p":1905},{"i":1912,"t":"Query all TreeNodes with parentId being null, i.e. root nodes. Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select(table) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select(table) } .execute() tip In the code above, parentId is automatically generated by Jimmer at compile time based on the many-to-one property TreeNode.parent, even if the developer does not define the @IdView property named parentId.","s":"IsNull判断","u":"/jimmer-doc/docs/showcase/where/associated-id","h":"#isnull判断","p":1910},{"i":1914,"t":"In fact, eq supports null parameters. When the parameter of eq is null, is null is rendered: caution Note: The eqIf of java and eq? of kotlin are different, null is considered a dynamic query and does not render any SQL condition. Java Kotlin @Nullable Long parentId = ...Omitted...; TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().eq(parentId)) .select(table) .execute(); val parentId: Long? = ...Omitted...; val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId eq parentId) select(table) } .execute()","s":"Judgment of any value","u":"/jimmer-doc/docs/showcase/where/associated-id","h":"#judgment-of-any-value","p":1910},{"i":1917,"t":"Java Kotlin @Nullable String name = ...Omitted...; @Nullable Integer edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .whereIf( name != null && !name.isEmpty(), () -> table.name().ilike(name) ) .whereIf( edition != null, table.edition().eq(edition) ) .select(table) .execute(); val name: String? = ...Omitted... val edition: Int? = ...Omitted... val books = sqlClient .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } edition?.let { where(table.edition eq it) } select(table) } .execute() caution In the Java code, the first whereIf uses a lambda to pass in the expression. This is because in addition to eq and ne which can accept null values (translated to is null and is not null), other conditions (such as ilike here) do not accept null and treats it as a bug made by developers.","s":"Using whereIf","u":"/jimmer-doc/docs/showcase/where/dynamic-where","h":"#using-whereif","p":1915},{"i":1919,"t":"whereIf is not the only way to write dynamic queries. The above code can be replaced with another syntax. Java Kotlin @Nullable String name = ...Omitted...; @Nullable Integer edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().ilikeIf(name)) .whereIf(table.edition().eqIf(edition)) .select(table) .execute(); val name: String? = ...Omitted... val edition: Int? = ...Omitted... val books = sqlClient .createQuery(Book::class) { where(table.name `ilike?` name) where(table.edition `eq?` edition) select(table) } .execute() tip Most SQL conditions (such as ilike here) do not accept null and treat it as a bug made by developers. (eq and ne are exceptions, as they render null as is null and not null) However, dynamic predicates (ilikeIf in Java and ilike? in Kotlin) are completely different, they accept null values and understand them as dynamic queries. That is, if the parameter is null or \"\", the current SQL condition is ignored.","s":"Using Dynamic Predicate","u":"/jimmer-doc/docs/showcase/where/dynamic-where","h":"#using-dynamic-predicate","p":1915},{"i":1921,"t":"Although whereIf has good readability, dynamic predicates can adapt to more complex scenarios (can be used in complex conditions, including multi-layer nested and, not, or structures). In the following text, we use dynamic predicates throughout.","s":"Comparison","u":"/jimmer-doc/docs/showcase/where/dynamic-where","h":"#comparison","p":1915},{"i":1923,"t":"Jimmer itself is highly neutral and does not couple with any container framework, but can easily integrate with any container framework. Since SpringBoot is extremely common, Jimmer has built-in SpringBoot Starter to simplify development.","s":"Spring","u":"/jimmer-doc/docs/spring/","h":"","p":1922},{"i":1925,"t":"Implicit subqueries can only be used for collection associations. This article discusses implicit subqueries through the many-to-many Book.authors.","s":"4.5 Implicit Subquery","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"","p":1924},{"i":1927,"t":"Java Kotlin @Nullable String authorName = ...Omitted...; @Nullable Gender authorGender = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where( table.authors(author -> ❶ Predicate.or( author.firstName().ilikeIf(authorName), author.lastName().ilikeIf(authorName) ) ) ) .where( table.authors(author -> ❷ author.gender().eqIf(authorGender) ) ) .select(table) .execute(); val authorName: String? = ...Omitted... val authorGender: Gender? = ...Omitted... val books = sqlClient .createQuery(Book::class) { where += table.authors { ❶ or( firstName `ilike?` authorName, lastName `ilike?` authorName ) } where += table.authors { ❷ gender `eq?` authorGender } select(table) } .execute() In fact, the two implicit subqueries in the code above can be merged into one, but in order to better demonstrate in the following text, they are deliberately written as two.","s":"Usage","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#usage","p":1924},{"i":1930,"t":"If both authorName and authorGender are null, it will cause the subqueries created at ❶ and ❷ to be invalid, and no actual SQL subqueries will be rendered. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_","s":"All subqueries are invalid","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#all-subqueries-are-invalid","p":1924},{"i":1932,"t":"If authorName is specified as non-null while authorGender remains null, the subquery at ❶ takes effect, while the subquery at ❷ is ignored. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) )","s":"Some subqueries take effect","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#some-subqueries-take-effect","p":1924},{"i":1934,"t":"If both authorName and authorGender are specified as non-null, the implicit subqueries created at ❶ and ❷ will both take effect. tip Jimmer can automatically merge conflicting implicit subqueries. The two implicit subqueries will be merged into one implicit subquery. Ultimately, only one SQL subquery will be rendered. select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ where exists( select 1 from AUTHOR tb_2_ inner join BOOK_AUTHOR_MAPPING tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where tb_3_.BOOK_ID = tb_1_.ID and ( lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) and tb_2_.GENDER = ? /* M */ )","s":"All subqueries take effect","u":"/jimmer-doc/docs/showcase/where/implicit-subquery","h":"#all-subqueries-take-effect","p":1924},{"i":1936,"t":"The following three ways of writing are equivalent","s":"4.1 Base Usage","u":"/jimmer-doc/docs/showcase/where/usage","h":"","p":1935},{"i":1938,"t":"Java Kotlin String name = ...Omitted...; int edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.name().ilike(name)) .where(table.edition().eq(edition)) .select(table) .execute(); val name: String = ...Omitted... val edition: Int = ...Omitted... val books = sqlClient .createQuery(Book::class) { where(table.name ilike name) where(table.edition eq edition) select(table) } .execute()","s":"Use multiple filters","u":"/jimmer-doc/docs/showcase/where/usage","h":"#use-multiple-filters","p":1935},{"i":1940,"t":"Java Kotlin String name = ...Omitted...; int edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where( table.name().ilike(name), table.edition().eq(edition) ) .select(table) .execute(); val name: String = ...Omitted... val edition: Int = ...Omitted... val books = sqlClient .createQuery(Book::class) { where( table.name ilike name, table.edition eq edition ) select(table) } .execute();","s":"Filter with multiple arguments","u":"/jimmer-doc/docs/showcase/where/usage","h":"#filter-with-multiple-arguments","p":1935},{"i":1942,"t":"Java Kotlin String name = ...Omitted...; int edition = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where( Predicate.and( table.name().ilike(name), table.edition().eq(edition) ) ) .select(table) .execute(); val name: String = ...Omitted... val edition: Int = ...Omitted... val books = sqlClient .createQuery(Book::class) { where( and( table.name ilike name, table.edition eq edition ) ) select(table) } .execute()","s":"Logic And","u":"/jimmer-doc/docs/showcase/where/usage","h":"#logic-and","p":1935},{"i":1944,"t":"The above three ways are completely equivalent. However, there is no doubt that the first one is the easiest, so it is recommended.","s":"Suggestion","u":"/jimmer-doc/docs/showcase/where/usage","h":"#suggestion","p":1935},{"i":1947,"t":"Java Kotlin @Nullable String storeName = ...Omitted...; @Nullable String storeWebsite = ...Omitted...; BookTable table = BookTable.$; List books = sqlClient .createQuery(table) .where(table.store().name().eqIf(storeName)) ❶ .where(table.store().website().eqIf(storeWebsite)) ❷ .select(table) .execute(); val storeName: String? = ...Omitted... val storeWebsite: String? = ...Omitted... val books = sqlClient .createQuery(Book::class) { where(table.store.name `eq?` storeName) ❶ where(table.store.website `eq?` storeWebsite) ❷ select(table) } .execute() info In the above code, Java's table.store() and Kotlin's table.store represent the inner join between the table defined by Book and the table defined by BookStore through the many-to-one association Book.store. That is, the following SQL logic is represented: from BOOK b inner join BOOK_STORE s on b.STORE_ID = s.ID In fact, if the entity model is richer, longer paths can be written, such as table.store().city().province(). Here, just for quick start guide and preview, it is unnecessary to build a richer entity model to demonstrate longer paths. The shortest table chain join path table.store() is enough.","s":"Usage","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#usage","p":1945},{"i":1950,"t":"If both storeName and storeWebsite are null, it will cause the dynamic table joins created at ❶ and ❷ to be unused. Unused table joins will be automatically ignored without rendering any actual SQL joins. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_","s":"All table joins do not take effect","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#all-table-joins-do-not-take-effect","p":1945},{"i":1952,"t":"If storeName is specified as non-null while storeWebsite remains null, the dynamic table join at ❶ takes effect, while the dynamic table join at ❷ is ignored. At this time, the following SQL is generated: select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? /* MANNING */","s":"Some table joins take effect","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#some-table-joins-take-effect","p":1945},{"i":1954,"t":"If both storeName and storeWebsite are specified as non-null, the dynamic table joins created at ❶ and ❷ will both take effect. tip Jimmer can automatically merge conflicting table joins. The two joins will be merged into one. Ultimately, only one SQL join will be rendered select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK tb_1_ inner join BOOK_STORE tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? /* MANNING */ and tb_2_.WEBSITE = ? /* https://www.manning.com */","s":"All table joins take effect","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#all-table-joins-take-effect","p":1945},{"i":1956,"t":"类似Java中table.store()或Kotlintable.store这样的连接路径，会被渲染成SQL的内连接，而非外连接，这是因为 info 内连接比外连接拥有更好的性能！ caution 为此，Jimmer不惜通过异常让默认情况下内连接而得到的表对象不支持isNull。 如果要对关联对象施加isNull，必须明确采用外连接操作，例如 Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parent(JoinType.LEFT).isNull()) .select(table) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.`parent?`.isNull()) select(table) } .execute() Java代码中的.parent(JoinType.LEFT)和Kotlin代码中的.parent?表示左连接。 其实，这种案例更适合上一文中的关联id条件 Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select(table) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select(table) } .execute()","s":"IsNull和外连接","u":"/jimmer-doc/docs/showcase/where/dynamic-join","h":"#isnull和外连接","p":1945},{"i":1958,"t":"Jimmer has many configurations, some of which can be configured in Spring Boot's application.yml or application.properties. Such as: Property Type Default Value Description jimmer.language java | kotlin java Must be configured for Kotlin projects jimmer.dialect string Jimmer's default dialect Jimmer dialect class name jimmer.show-sql boolean false Whether to print SQL logs jimmer.pretty-sql boolean false Whether to format SQL jimmer.inline-sql-variables boolean false Whether to inline SQL parameters(This only affects the logs. The actual SQL executed still uses JDBC parameters) jimmer.executor-context-prefixes List [] Usually multiple package names or full class names, Jimmer judges whether the current stacktrace should be appended to the SQL logs jimmer.database-validation.mode NONE | WARNING | ERROR NONE Database validation mode jimmer.database-validation-mode Same as above Same as above Same as above jimmer.database-validation.catalog string Catalog of validated tables' database, configured when table name conflicts jimmer.database-validation.schema string Schema of validated tables' database, configured when table name conflicts jimmer.trigger-type BINLOG_ONLY | TRANSACTION_ONLY | BOTH BINLOG_ONLY Trigger type jimmer.id-only-target-checking-level NONE | FAKE | ALL NONE Whether to check short associated ids in save commands jimmer.save-command-pessimistic-lock boolean false Whether queries in save commands use pessimistic locks jimmer.default-enum-strategy NAME | ORDINAL NAME Default mapping mode for enums without explicit declaration jimmer.default-batch-size int 128 Default fetch size for non-collection properties jimmer.default-list-batch-size int 16 Default fetch size for collection properties jimmer.offset-optimizing-threshold int Integer.MAX_VALUE Offset threshold to enable deep paging optimization for paged queries jimmer.is-foreign-key-enabled-by-default boolean true Foreign keys without explicit declaration are treated as real foreign keys jimmer.transaction-cache-operator-fixed-delay int 5000 Retry interval for failed or excessive cache invalidation tasks when trigger type is TRANSACTION_ONLY (not relying on external CDC) jimmer.micro-service-name string Service name of current application if using remote associations jimmer.error-translator.disabled boolean false Whether to disable exception mapping in automatic front-end integration jimmer.error-translator.http-status int 500 Unified HTTP status of server exceptions on client side jimmer.error-translator.debug-info-supported boolean false Whether to include exception message etc. to help debugging in client errors, should be disabled in production jimmer.error-translator.debug-info-max-stack-trace-count int 0 Maximum number of stacktrace in exception information in client errors, should be disabled in production jimmer.client.ts.path string Download path of automatically generated TypeScript code, e.g. \"/ts.zip\" jimmer.client.ts.api-name string Api API name of automatically generated TypeScript code jimmer.client.ts.indent int 4 Indentation of automatically generated TypeScript code jimmer.client.ts.anonymous boolean false Whether to use anonymous style to avoid naming DTO types in automatically generated TypeScript code jimmer.client.ts.mutable boolean false By default, the Typescript generated by Jimmer serves the React ecosystem, so there are a lot of readonly modifiers in the TS type declarations. If this behavior is not desirable, please set this configuration to true jimmer.client.java-feign.path string Download path of automatically generated Spring Cloud Feign Java code, e.g. \"/java-feign.zip\" jimmer.client.java-feign.api-name string Api API name of automatically generated Spring Cloud Feign Java code jimmer.client.java-feign.indent int 4 Indentation of automatically generated Spring Cloud Feign Java code jimmer.client.java-feign.base-package string Top level package of automatically generated Spring Cloud Feign Java code","s":"Appendix","u":"/jimmer-doc/docs/spring/appendix","h":"","p":1957},{"i":1960,"t":"Jimmer provides Spring Data Repository style APIs, so you can: Define Repository Declare simple queries through abstract methods Implement complex queries through default methods","s":"Spring Data","u":"/jimmer-doc/docs/spring/repository/","h":"","p":1959},{"i":1963,"t":"Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch( TreeNodeFetcher.$ .allScalarFields() .recursiveChildNodes() ) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetchBy { allScalarFields() `childNodes*`() } ) } .execute() The result is [ { \"id\":1, \"name\":\"Home\", \"childNodes\":[ { \"id\":2, \"name\":\"Food\", \"childNodes\":[ { \"id\":3, \"name\":\"Drinks\", \"childNodes\":[ { \"id\":4, \"name\":\"Coca Cola\", \"childNodes\":[] }, { \"id\":5, \"name\":\"Fanta\", \"childNodes\":[] } ] }, { \"id\":6, \"name\":\"Bread\", \"childNodes\":[ { \"id\":7, \"name\":\"Baguette\", \"childNodes\":[] }, { \"id\":8, \"name\":\"Ciabatta\", \"childNodes\":[] } ] } ] }, { \"id\":9, \"name\":\"Clothing\", \"childNodes\":[ { \"id\":10, \"name\":\"Woman\", \"childNodes\":[ { \"id\":11, \"name\":\"Casual wear\", \"childNodes\":[ { \"id\":12, \"name\":\"Dress\", \"childNodes\":[] }, { \"id\":13, \"name\":\"Miniskirt\", \"childNodes\":[] }, { \"id\":14, \"name\":\"Jeans\", \"childNodes\":[] } ] }, { \"id\":15, \"name\":\"Formal wear\", \"childNodes\":[ { \"id\":16, \"name\":\"Suit\", \"childNodes\":[] }, { \"id\":17, \"name\":\"Shirt\", \"childNodes\":[] } ] } ] }, { \"id\":18, \"name\":\"Man\", \"childNodes\":[ { \"id\":19, \"name\":\"Casual wear\", \"childNodes\":[ { \"id\":20, \"name\":\"Jacket\", \"childNodes\":[] }, { \"id\":21, \"name\":\"Jeans\", \"childNodes\":[] } ] }, { \"id\":22, \"name\":\"Formal wear\", \"childNodes\":[ { \"id\":23, \"name\":\"Suit\", \"childNodes\":[] }, { \"id\":24, \"name\":\"Shirt\", \"childNodes\":[] } ] } ] } ] } ] } ]","s":"Query Dynamic Entities","u":"/jimmer-doc/docs/showcase/recursive-query/usage","h":"#query-dynamic-entities","p":1961},{"i":1965,"t":"Create any file with the dto extension under the src/main/dto folder, and edit the code as follows: export com.yourcompany.yourproject.model.TreeNode -> package com.yourcompany.yourproject.model.dto RecursiveTreeNodeView { #allScalars(this) childNodes* } Compile the project, a java/kotlin class named RecursiveTreeNodeView will be automatically generated. Java Kotlin TreeNodeTable table = TreeNodeTable.$; List rootNodes = sqlClient .createQuery(table) .where(table.parentId().isNull()) .select( table.fetch(RecursiveTreeNodeView.class) ) .execute(); val rootNodes = sqlClient .createQuery(TreeNode::class) { where(table.parentId.isNull()) select( table.fetch(RecursiveTreeNodeView::class) ) } .execute() The result is [ RecursiveTreeNodeView( id=1, name=Home, childNodes=[ RecursiveTreeNodeView( id=2, name=Food, childNodes=[ RecursiveTreeNodeView( id=3, name=Drinks, childNodes=[ RecursiveTreeNodeView( id=4, name=Coca Cola, childNodes=[] ), RecursiveTreeNodeView( id=5, name=Fanta, childNodes=[] ) ] ), RecursiveTreeNodeView( id=6, name=Bread, childNodes=[ RecursiveTreeNodeView( id=7, name=Baguette, childNodes=[] ), RecursiveTreeNodeView( id=8, name=Ciabatta, childNodes=[] ) ] ) ] ), RecursiveTreeNodeView( id=9, name=Clothing, childNodes=[ RecursiveTreeNodeView( id=10, name=Woman, childNodes=[ RecursiveTreeNodeView( id=11, name=Casual wear, childNodes=[ RecursiveTreeNodeView( id=12, name=Dress, childNodes=[] ), RecursiveTreeNodeView( id=13, name=Miniskirt, childNodes=[] ), RecursiveTreeNodeView( id=14, name=Jeans, childNodes=[] ) ] ), RecursiveTreeNodeView( id=15, name=Formal wear, childNodes=[ RecursiveTreeNodeView( id=16, name=Suit, childNodes=[] ), RecursiveTreeNodeView( id=17, name=Shirt, childNodes=[] ) ] ) ] ), RecursiveTreeNodeView( id=18, name=Man, childNodes=[ RecursiveTreeNodeView( id=19, name=Casual wear, childNodes=[ RecursiveTreeNodeView( id=20, name=Jacket, childNodes=[] ), RecursiveTreeNodeView( id=21, name=Jeans, childNodes=[] ) ] ), RecursiveTreeNodeView( id=22, name=Formal wear, childNodes=[ RecursiveTreeNodeView( id=23, name=Suit, childNodes=[] ), RecursiveTreeNodeView( id=24, name=Shirt, childNodes=[] ) ] ) ] ) ] ) ] ) ]","s":"Query Static DTO","u":"/jimmer-doc/docs/showcase/recursive-query/usage","h":"#query-static-dto","p":1961},{"i":1967,"t":"Jimmer integrates spring data and provides a base repository interface for Java and Kotlin users respectively. Java org.babyfish.jimmer.spring.repository.JRepository Kotlin org.babyfish.jimmer.spring.repository.KRepository This interface has two generic parameters E: Entity type ID: Entity ID type By inheriting this interface, developers can quickly implement various Repository BookStoreRepository Java Kotlin BookStoreRepository.java package com.example.repository; import com.example.model.BookStore; import org.babyfish.jimmer.spring.repository.JRepository; public interface BookRepository extends JRepository {} BookStoreRepository.kt package com.example.repository import com.example.model.BookStore import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository BookRepository Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; public interface BookRepository extends JRepository {} BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository AuthorRepository Java Kotlin AuthorRepository.java package com.example.repository; import com.example.model.Author; import org.babyfish.jimmer.spring.repository.JRepository; public interface AuthorRepository extends JRepository {} AuthorRepository.kt package com.example.repository import com.example.model.Author import org.babyfish.jimmer.spring.repository.KRepository interface AuthorRepository : KRepository TreeNodeRepository Java Kotlin TreeNodeRepository.java package com.example.repository; import com.example.model.TreeNode; import org.babyfish.jimmer.spring.repository.JRepository; public interface TreeNodeRepository extends JRepository {} TreeNodeRepository.kt package com.example.repository import com.example.model.TreeNode import org.babyfish.jimmer.spring.repository.KRepository interface TreeNodeRepository : KRepository note The rest is the same as spring-data. Just define the interface and Jimmer will automatically implement these interfaces and register them in Spring. However, there is one caveat: By default, the package of the custom Repository must be the same as the package of the SpringBoot main class or its subpackage. Otherwise, you need to use @org.babyfish.jimmer.spring.repository.EnableJimmerRepositories to annotate the SpringBoot main class or other Spring configuration class to explicitly specify the package where the custom Repository interface is located.","s":"Define Repository","u":"/jimmer-doc/docs/spring/repository/concept","h":"","p":1966},{"i":1969,"t":"Jimmer provides DTO language. tip Essentially, this language is another way to express object fetchers. Using this language, developers can quickly define multiple data structure shapes with an entity type as the aggregate root. The compiler will generate the corresponding Java/Kotlin DTO classes for each shape. Each DTO type contains the mutual conversion logic between itself and the original dynamic type, as well as an object fetcher that matches its own shape. In some cases, after the server queries data of a certain shape, it is not used as the return of an HTTP request, but is used by itself to drive subsequent complex business logic. This is an ideal scenario for using this approach. caution Note that if the data of a certain shape queried by the server is not for its own use, but to be directly returned as the HTTP request return value, it is more recommended to directly return the dynamic entity object and use the scheme in Generate Client Code to automatically generate client code with high development experience.","s":"Query DTO","u":"/jimmer-doc/docs/spring/repository/dto","h":"","p":1968},{"i":1971,"t":"This article focuses on how to query static DTO types, not a systematic introduction to the DTO language. Please refer to Object/DTO Conversion/DTO Language for a complete DTO language. Assume the fully qualified name of the Book class is com.yourcompany.yourproject.model.Book, you can In the project where the entity is defined, create a directory src/main/dto Under src/main/dto, create subdirectories com/yourcompany/yourproject/model according to the package path where the entity is located In the directory created in the previous step, create the file Book.dto. The file name must be the same as the entity class name, and the extension must be dto Edit this file and use the DTO language to define various DTO shapes of the Book entity Book.dto BookDetailView { #allScalars store { #allScalars } authors { #allScalars } } SimpleBookView { ...Omitted... } ...Omit other DTO shape definitions...","s":"Define DTO shape","u":"/jimmer-doc/docs/spring/repository/dto","h":"#define-dto-shape","p":1968},{"i":1973,"t":"Jimmer is responsible for compiling dto files and automatically generating DTO types that conform to these shapes. caution If files other than dto files are modified in addition to dto files, directly clicking the run button in the IDE may cause the dto file to be recompiled. However, if no other Java/Kotlin files are modified except for the dto file, simply clicking the run button in the IDE will not cause the dto file to be recompiled unless explicitly rebuilding! If you are using Gradle as your build tool, you can also use the third-party Gradle plugin provided by the community to solve this problem: jimmer-gradle Take BookDetailView in the above code as an example. After this dto file is successfully compiled by Jimmer, the following DTO type will be automatically generated: Java Kotlin BookDetailView.java package com.yourcompany.yourproject.model.dto; import com.yourcompany.yourproject.model.Book; import org.babyfish.jimmer.View; @GeneratedBy(file = \"/src/main/dto/Book.dto\") public class BookDetailView implements Input { private long id; private String name; private int edition; private BigDecimal price; private TargetOf_store store; private List authors; public static class TargetOf_store implements Input { private long id; private String name; @Nullable private String website; ...Omitted other members... } public static class TargetOf_authors implements Input { private long id; private String firstName; private String lastName; private Gender gender; ...Omitted other members... } ...Omitted other members... } BookDetailView.kt package com.yourcompany.yourproject.model.dto import com.yourcompany.yourproject.model.Book import org.babyfish.jimmer.View @GeneratedBy(file = \"/src/main/dto/Book.dto\") data class BookDetailView( val id: Long = 0, val name: String = \"\", val edition: Int = 0, val price: BigDecimal, val store: TargetOf_store? = null, val authors: List = emptyList(), ) : Input { data class TargetOf_store( val id: Long = 0, val name: String = \"\", val website: String? = null, ) : Input { ...Omitted other members... } data class TargetOf_authors( val id: Long = 0, public val firstName: String = \"\", public val lastName: String = \"\", public val gender: Gender, ) : Input { ...Omitted other members... } ...Omitted other members... } info The generated DTO classes are not in the package where the entity is located, but in its dto subpackage. For Java, it is assumed that lombok has been used.","s":"Automatically generate DTO types","u":"/jimmer-doc/docs/spring/repository/dto","h":"#automatically-generate-dto-types","p":1968},{"i":1975,"t":"There are several ways to query DTO types: Use inherited methods from JRepository/KRepository Define abstract methods in custom Repository Define default methods in custom Repository (Which is actually the method of the underlying API to query DTO types)","s":"Query DTO types","u":"/jimmer-doc/docs/spring/repository/dto","h":"#query-dto-types","p":1968},{"i":1977,"t":"Java Kotlin public static void main(String[] args) { ApplicationContext ctx = SpringApplication.run(MyApp.class, args); BookRepository bookRepository = ctx.getBean(BookRepository.class); Book view = bookRepository .viwer(BookDetailView.class) .findNullable(1L); System.out.println(view); } fun main(args: Array) { val ctx = runApplication(*args) val bookRepository = ctx.getBean(BookRepository.class.java) val view = bookRepository .viwer(BookDetailView.class) .findNullable(1L) println(view) } Where viewer(BookDetailView.class) indicates that the following methods are used to query DTO objects instead of dynamic entity objects. The print result is as follows (Formatted manually for readability): BookDetailView( id=1, name=Learning GraphQL, edition=1, price=50.00, store=BookDetailView.TargetOf_store( id=1, name=O'REILLY, website=null, version=0 ), authors=[ BookDetailView.TargetOf_authors( id=2, firstName=Alex, lastName=Banks, gender=MALE ), BookDetailView.TargetOf_authors( id=1, firstName=Eve, lastName=Procello, gender=FEMALE ) ] ) It is not difficult to find that although the query no longer returns dynamic entity objects, the function is exactly the same as the object fetcher. Why is this? In fact, an object fetcher is automatically generated inside the BookDetailView class. Jimmer uses it to query dynamic entity objects matching the shape from the database and automatically converts them to DTO objects. tip Related details have been discussed in detail in Object Fetcher/DTO Query. This article will not repeat. This is why this article says at the beginning that the DTO language is essentially another way to express object fetchers.","s":"Use inherited methods from Repository","u":"/jimmer-doc/docs/spring/repository/dto","h":"#use-inherited-methods-from-repository","p":1968},{"i":1979,"t":"There are two implementation plans: Intuitive but not recommended Java Kotlin BookRepository.java // Intuitive but not recommended public interface BookRepository extends JRepository { List findByNameLikeIgnoreCase( @Nullable String name ); } BookRepository.kt // Intuitive but not recommended interface BookRepository : KRepository { fun findByNameLikeIgnoreCase( name: String? = null ) : List } This approach is very simple, the abstract method no longer returns dynamic entities representing arbitrary data, just return the DTO type with fixed shape. Very easy to understand. caution However, this approach still has drawbacks and is not recommended. Recommended approach The above code is simple and intuitive, but violates one of the important values ​​that Jimmer has been trying to pursue: tip Do not solidify the shape of the data structure to be queried in the data layer, but let the upper layer business decide. Java Kotlin BookRepository.java public interface BookRepository extends JRepository { > List findByNameLikeIgnoreCase( @Nullable String name, Class viewType ); } BookRepository.kt interface BookRepository : KRepository { fun > findByNameLikeIgnoreCase( name: String? = null viewType: KClass ) : List } You can see: First, define a method-level generic parameter V, which must extend org.babyfish.jimmer.View (this is very important, otherwise Jimmer will remind developers to do so via exceptions). Then, use V to declare the parameter viewType of type Class or KClass, and hand over the decision-making power of the data structure shape to the caller. Finally, return results carrying the V type, such as V, List or Page. In this way, we can use it to query data structures of various shapes. Take Java as an example: bookRepository.findByNameLikeIgnoreCase(null, BookDetailView.class) bookRepository.findByNameLikeIgnoreCase(null, SimpleBookView.class) bookRepository.findByNameLikeIgnoreCase(null, DefaultBookView.class) Let's recall how we used object fetchers directly to achieve the same functionality before introducing the DTO type: Java Kotlin BookRepository.java public interface BookRepository extends JRepository { List findByNameLikeIgnoreCase( @Nullable String name, fetcher fetcher ); } BookRepository.kt interface BookRepository : KRepository { fun findByNameLikeIgnoreCase( name: String? = null viewType: Fetcher ) : List } tip Comparing the code using DTO with the code using object fetcher directly, it is not difficult to find that the two are doing the same thing in different ways. This confirms again what is said at the beginning of this article that the DTO language is essentially another way to express object fetchers.","s":"Define abstract methods in custom Repository","u":"/jimmer-doc/docs/spring/repository/dto","h":"#define-abstract-methods-in-custom-repository","p":1968},{"i":1981,"t":"Java Kotlin BookRepository.java public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default > List find( @Nullable String name, @Nullable String storeName, @Nullable String authorName, Class viewType ) { return sql() .createQuery(table) whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table.fetch(viewType)) .execute(); } } BookRepository.kt interface BookRepository : KRepository { fun > findByNameLikeIgnoreCase( name: String? = null viewType: KClass ) : List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(table.name) orderBy(table.edition.desc()) select(table.fetch(viewType)) } .execute() } Here we see table.fetch(fetcher) is replaced with table.fetch(viewType). In fact, viewType can also replace fetcher in other underlying query APIs. For example, sqlClient.findById(fetcher, 1L) can be replaced with sqlClient.find(viewType, 1L). tip All underlying query APIs can replace fetcher with viewType, which confirms again that the DTO language is essentially another way to express object fetchers, as stated at the beginning of this article.","s":"Define default methods in custom Repository","u":"/jimmer-doc/docs/spring/repository/dto","h":"#define-default-methods-in-custom-repository","p":1968},{"i":1984,"t":"In Jimmer, all database operation APIs have two execution modes: Execute on a specified JDBC connection Execute without specifying a JDBC connection, but a ConnectionManager needs to be configured for Jimmer to teach Jimmer how to borrow and return connections. Please refer to here So Jimmer itself does not provide connection/transaction management capabilities, such management capabilities completely rely on user customization of ConnectionManager. ConnectionManager is the key to integrate Jimmer with the connection/transaction management capabilities of any IOC framework (of course including Spring).","s":"Integrate Spring Transaction","u":"/jimmer-doc/docs/spring/transaction","h":"#integrate-spring-transaction","p":1982},{"i":1986,"t":"If using the Spring Boot Starter provided by Jimmer, no extra work is needed. Jimmer will automatically integrate into Spring's transaction management mechanism.","s":"Using Spring Boot starter","u":"/jimmer-doc/docs/spring/transaction","h":"#using-spring-boot-starter","p":1982},{"i":1988,"t":"If using Spring only, without the Spring Boot Starter provided by Jimmer. You need to code by yourself to integrate Jimmer into Spring's transaction management mechanism. Developers need to create JSqlClient/KSqlClient and set its ConnectionManager. In ConnectionManager, use Spring's org.springframework.jdbc.datasource.DataSourceUtils to open and close connections. Java Kotlin Book.java @Bean public JSqlClient sqlClient(DataSource dataSource) { return JSqlClient.newBuilder() .setConnectionManager( new ConnectionManager() { @Override public R execute( Function block ) { Connection con = DataSourceUtils .getConnection(dataSource); try { return block.apply(con); } finally { DataSourceUtils .releaseConnection(con, dataSource); } } } ) ...Omit other configurations... .build(); } Book.kt @Bean fun sqlClient(dataSource: DataSource): KSqlClient = newKSqlClient { setConnectionManager { val con = DataSourceUtils .getConnection(dataSource) try { proceed(con) } finally { DataSourceUtils .releaseConnection(con, dataSource) } } ...Omit other configurations... } caution Don't use normal methods to borrow (dataSource.getConnection) and return (con.close) connections from the connection pool. You must use Spring's org.springframework.jdbc.datasource.DataSourceUtils, because this can be combined with Spring's transaction management mechanism.","s":"Not Using Spring Boot Starter","u":"/jimmer-doc/docs/spring/transaction","h":"#not-using-spring-boot-starter","p":1982},{"i":1990,"t":"Jimmer adopts minimalist design. The API entry point JSqlClient/KSqlClient exposes stateless APIs. Many database operation frameworks provide lightweight stateful wrappers for JDBC connections, such as JPA's EntityManager Hibernate's Session MyBatis's SqlSession. And they also provide stateful wrappers for database transactions, such as JPA's EntityManager.getTransaction() Hibernate's Session.getTransaction() MyBatis's SqlSession.commit() Jimmer doesn't have similar abstractions. The API entry point JSqlClient/KSqlClient exposes stateless APIs. JDBC connection is the only low-level dependency of Jimmer. tip This enables an important feature: Jimmer's transaction management is exactly the same as JdbcTemplate's transaction management. Jimmer doesn't need to provide any APIs like createNativeQuery For report queries that are not closely related to ORM, users expect to write complete Native SQL, then JdbcTemplate can be used directly, because Jimmer's transaction management is exactly the same as JdbcTemplate's. For Jimmer's ORM-style queries, inject Native SQL expressions in strongly typed SQL DSL.","s":"Work with JdbcTemplate","u":"/jimmer-doc/docs/spring/transaction","h":"#work-with-jdbctemplate","p":1982},{"i":1992,"t":"In the previous sections, we discussed the integration of Spring transactions in the single data source scenario. As for multiple data sources, please refer to this section.","s":"Multiple Data Sources","u":"/jimmer-doc/docs/spring/transaction","h":"#multiple-data-sources","p":1982},{"i":1994,"t":"Remote associations are Jimmer's first thoughts on microservice architecture. Through vertical splitting, entity types can be divided into different microservices, or in other words, divided into different databases. The associations (including one-to-one, many-to-one, one-to-many and many-to-many) between entity types belonging to different microservices are remote associations. tip Jimmer automatically implements automatic query of remote associated data. That is, if the object fetcher contains remote association properties of any depth, it will query different parts of the data across multiple microservices, and finally merge the query results of different parts into the data structure expected by the object fetcher as a whole return. No need for developers to implement remote queries and data splicing themselves.","s":"Remote Associations","u":"/jimmer-doc/docs/spring/spring-cloud","h":"","p":1993},{"i":1996,"t":"In this article, each entity is divided as follows: info BOOK_AUTHOR_MAPPING as the many-to-many association intermediate table, can be divided into either the book-service service or the author-service service. In this example, it is divided into the book-service service, the reason will be explained later. Solid arrows indicate foreign key references within the same database, whose validity can be freely chosen by developers. Dashed arrows indicate foreign key references across database boundaries, which must be pseudo foreign keys. To simplify the discussion, the database initialization scripts for the three services are as follows: Language Example Service (Subproject) Database Initialization SQL Java jimmer-examples/java/jimmer-cloud store-service jimmer-cloud/store-service/src/main/resources/store.sql book-service jimmer-cloud/book-service/src/main/resources/book.sql author-service jimmer-cloud/author-service/src/main/resources/author.sql Kotlin jimmer-examples/kotlin/jimmer-cloud-kt store-service jimmer-cloud-kt/store-service/src/main/resources/store.sql book-service jimmer-cloud-kt/book-service/src/main/resources/book.sql author-service jimmer-cloud-kt/author-service/src/main/resources/author.sql info The accompanying examples jimmer-examples/java/jimmer-cloud or jimmer-examples/kotlin/jimmer-cloud-kt use H2, each service will automatically initialize its own database after startup.","s":"Databases","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#databases","p":1993},{"i":1998,"t":"In a separate subproject (the accompanying examples are jimmer-examples/java/jimmer-cloud/model or jimmer-examples/kotlin/jimmer-cloud-kt/model), define all entity types. These entity types constitute the global model. Entity types belong to different microservices. Entities between different microservices constitute remote associations, which can actually be understood as the interaction contracts between entities belonging to different microservices. Java Kotlin BookStore.java @Entity(microServiceName = \"store-service\") public interface BookStore { @OneToMany(mappedBy = \"store\") List books(); ...other code omitted... } BookStore.kt @Entity(microServiceName = \"store-service\") interface BookStore { @OneToMany(mappedBy = \"store\") val books: List ...other code omitted... } Java Kotlin Book.java @Entity(microServiceName = \"book-service\") public interface Book { @Nullable @ManyToOne BookStore store(); @ManyToMany List authors(); ...other code omitted... } Book.kt @Entity(microServiceName = \"book-service\") interface Book { @ManyToOne val store: BookStore? @ManyToMany val authors: List ...other code omitted... } Java Kotlin Author.java @Entity(microServiceName = \"author-service\") public interface Book { @ManyToMany(mappedBy = \"authors\") List books(); ...other code omitted... } Author.kt @Entity(microServiceName = \"author-service\") interface Author { @ManyToMany(mappedBy = \"authors\") val books: List ...other code omitted... } The microServiceName of the @Entity annotation of the entity class is specified, so that it is clear which microservice each entity belongs to, i.e. which database. In this example, the entity types BookStore, Book and Author belong to the services store-service, book-service and author-service respectively. Here the microservice is the name of each service in the registry center, for spring-cloud it is the global configuration spring.application.name. The associations between entities belonging to different microservices are remote associations. BookStore.books and Book.store: BookStore belongs to store-service, while Book belongs to book-service Book.authors and Author.books: Book belongs to book-service, while Author belongs to author-service The many-to-one association Book.store must be nullable, because the remote association means its foreign key must reference data in another database, that is, it must be a pseudo foreign key. And in Jimmer, the field corresponding to a pseudo foreign key must be nullable. Please refer to Real and Pseudo Foreign Keys. For the bidirectional many-to-many association between books and authors, Book.authors is the owning side, while Author.books is the inverse side (mappedBy of @ManyToMany is configured). info Jimmer stipulates that the intermediate table of remote associations must belong to the microservice where the owning side entity belongs. Here the question left in the previous section is answered, why in this example the intermediate table BOOK_AUTHOR_MAPPING is defined in the book-service database instead of the author-service database.","s":"Entity Definition","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#entity-definition","p":1993},{"i":2000,"t":"Microservice applications need a registry center, which is a basic feature of microservice architecture, no explanation is needed in this article. In the accompanying examples, it is jimmer-examples/java/jimmer-cloud/registry-center or jimmer-examples/kotlin/jimmer-cloud-kt/registry-center","s":"Registry Center","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#registry-center","p":1993},{"i":2002,"t":"Since the implementations of the microservices store-service, book-service and author-service are highly similar, this document only explains how to implement store-service. note Although this document only explains store-service, to experience the effect of remote associations, all three services need to be fully implemented. Complete code can be found in the accompanying examples jimmer-examples/java/jimmer-cloud or jimmer-examples/kotlin/jimmer-cloud-kt.","s":"Implementing Services","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#implementing-services","p":1993},{"i":2004,"t":"Any microservice must enable Jimmer's microservice support. There are two ways: Use Spring Boot Starter Modify spring configuration file application.yml (or application.properties) spring: application: name: store-service jimmer: micro-service-name: ${spring.application.name} ...other configurations omitted... eureka: client: serviceUrl: defaultZone: http://localhost:7000/eureka/ Here, \"store-service\" is used both as the name of the current service in spring-cloud registry center and as the microservice configuration in Jimmer. When using low-level APIs Java Kotlin JSqlClient sqlClient = JSqlClient .newBuilder() .setMicroServiceName(\"...\") ...other configurations omitted... .build(); val sqlClient = newKSqlClient { setMicroServiceName(\"...\") ...other configurations omitted... } Once jimmer.micro-service-name is configured, Jimmer knows which entity types belong to the current service (here is BookStore). Using Jimmer's ORM APIs to operate on the entity types belonging to the current microservice will execute correctly, just like everything explained in previous documents. Using Jimmer's ORM APIs to operate on entity types belonging to other microservices will throw exceptions. tip As long as each service ensures spring.application.name and jimmer.micro-service-name are the same, Jimmer will automatically implement automatic query of remote associated data without requiring developers to write any code.","s":"Enable Microservice Support in Jimmer","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#enable-microservice-support-in-jimmer","p":1993},{"i":2006,"t":"Java Kotlin BookStoreService.java @GetMapping(\"/store/{id}/detail\") public @FetchBy(\"COMPLEX_FETCHER\") BookStore findStoreDetail( @PathVariable(\"id\") long id ) { return storeRepository.findNullable(id, COMPLEX_FETCHER); } public static final Fetcher COMPLEX_FETCHER = Fetchers.BOOK_STORE_FETCHER ❶ .allScalarFields() .books( ❷ Fetchers.BOOK_FETCHER .allScalarFields() .authors( ❸ Fetchers.AUTHOR_FETCHER .allScalarFields() ) ); BookStoreService.kt @GetMapping(\"/store/{id}/detail\") fun findStoreDetail( @PathVariable(\"id\") id: Long ): @FetchBy(\"COMPLEX_FETCHER\") BookStore? = storeRepository.findNullable(id, COMPLEX_FETCHER) companion object { val COMPLEX_FETCHER = newFetcher(BookStore::class).by { ❶ allScalarFields() books { ❷ allScalarFields() authors { ❸ allScalarFields() } } } } ❶ Query root aggregate, queried directly from the database belonging to the current service store-service ❷ Query associated objects through remote association property BookStore.books Access remote microservice book-service indirectly to get data via HTTP protocol ❸ Query associated objects through remote association property Book.authors Access remote microservice author-service indirectly to get data via HTTP protocol tip Users only need to implement queries for root aggregate objects, queries for associated properties (including remote associations) are fully automated by Jimmer. Therefore, even without writing any Java/Kotlin code for the other two microservices book-service and author-service, as long as their configuration files are modified to support microservices, this method can still run correctly.","s":"Implement Business Query Logic","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#implement-business-query-logic","p":1993},{"i":2008,"t":"Assuming store-service is started on localhost with port 7001, accessing http://localhost:7001/store/1/detail will get the result: { \"id\":1, \"name\":\"O'REILLY\", \"website\":null, \"books\":[ { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":50, \"authors\":[ { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\", \"gender\":\"FEMALE\" }, { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\", \"gender\":\"MALE\" } ] }, { \"id\":2, ...omitted... }, { \"id\":3, ...omitted... }, { \"id\":4, \"name\":\"Effective TypeScript\", \"edition\":1, \"price\":73, \"authors\":[ { \"id\":3, \"firstName\":\"Dan\", \"lastName\":\"Vanderkam\", \"gender\":\"MALE\" } ] }, { \"id\":5, ...omitted... }, { \"id\":6, ...omitted... }, { \"id\":7, \"name\":\"Programming TypeScript\", \"edition\":1, \"price\":47.5, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\", \"gender\":\"MALE\" } ] }, { \"id\":8, ...omitted... }, { \"id\":9, ...omitted... } ] }","s":"Run Effects","u":"/jimmer-doc/docs/spring/spring-cloud","h":"#run-effects","p":1993},{"i":2010,"t":"Just like other Spring Data implementations, users can define abstract methods in the Repository interface. As long as the names, parameters and return values of these methods follow conventions, Jimmer implements them automatically. For example: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; public interface BookRepository extends JRepository { List findByNameOrderByEditionDesc( @Nullable String name ); List findByPriceBetweenOrderByName( @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ); long countByName(String name); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository { fun findByNameOrderByEditionDesc( name: String? ): List fun findByPriceBetweenOrderByName( minPrice: BigDecimal?, maxPrice: BigDecimal? ): List fun countByName(String name): Long } note There are various conventions for method names, but basic usage is similar to Spring Data JPA. So please refer to https://docs.spring.io/spring-data/jpa/docs/current/reference/html/#repository-query-keywords, this article will not repeat it.","s":"Simple Queries","u":"/jimmer-doc/docs/spring/repository/abstract","h":"","p":2009},{"i":2012,"t":"You may have noticed that in the above examples, many parameters can be null. In Jimmer, the automatically implemented abstract methods are inherently dynamic queries, that is, any query parameter can be null. Let's look at another more representative example, where the abstract method is defined as: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; public interface BookRepository extends JRepository { List findByNameLikeIgnoreCaseAndPriceBetween( @Nullable String name, @Nullable BigDecimal minPrice, @Nullable BigDecimal maxPrice ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository { fun findByNameLikeIgnoreCaseAndPriceBetween( name: String? = null, minPrice: BigDecimal? = null, maxPrice: BigDecimal? = null ): List } Each parameter of this method can be null, look at the 6 possible invocations: Not specify any parameters Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, null, null ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween() The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ Specify name Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( \"G\", null, null ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween(name = \"G\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where lower(tb_1_.NAME) like ? /* %g% */ Specify minPrice Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, new BigDecimal(40), null ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( minPrice = BigDecimal(40) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.PRICE >= ? /* 40 */ Specify maxPrice Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, null, new BigDecimal(60) ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( maxPrice = BigDecimal(60) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.PRICE <= ? /* 60 */ Specify both minPrice and maxPrice Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, new BigDecimal(40), new BigDecimal(60) ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( null, BigDecimal(40), BigDecimal(60) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where (tb_1_.PRICE between ? /* 40 */ and ? /* 60 */) Specify all parameters Java Kotlin List books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( \"G\", new BigDecimal(40), new BigDecimal(60) ); val books = bookRepository .findByNameLikeIgnoreCaseAndPriceBetween( \"G\", BigDecimal(40), BigDecimal(60) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where lower(tb_1_.NAME) like ? /* %g% */ and (tb_1_.PRICE between ? /* 40 */ and ? /* 60 */)","s":"Dynamic WHERE","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#dynamic-where","p":2009},{"i":2014,"t":"Users can not only apply filters to properties of the currently queried object, but also to properties of associated objects. For example: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; public interface BookRepository extends JRepository { // name -> `Book.name` // storeName -> `Book.store.name` List findByNameStartsWithAndStoreName( @Nullable String name, @Nullable String storeName ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository interface BookRepository : KRepository { // name -> `Book.name` // storeName -> `Book.store.name` fun findByNameStartsWithAndStoreName( name: String? = null, storeName: String? = null ): List } Here, storeName in findByNameStartWithAndStoreName actually refers to store.name. It means a join is performed through Book.store to BookStore first, then a condition is applied on BookStore.name. note JOIN will only be generated in the SQL if the storeName parameter is specified The association that can be used by the convention method must be a non-collection association (one-to-one, many-to-one) Let's see how to use it: Specify name parameter, no JOIN Java Kotlin List books = bookRepository .findByNameStartsWithAndStoreName(\"G\", null); val books = bookRepository .findByNameStartsWithAndStoreName(\"G\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.NAME like ? /* G% */ Specify storeName parameter, JOIN generated Java Kotlin List books = bookRepository .findByNameStartsWithAndStoreName(null, \"MANNING\"); val books = bookRepository .findByNameStartsWithAndStoreName(null, \"MANNING\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where tb_2_.NAME = ? /* MANNING */","s":"Dynamic JOIN","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#dynamic-join","p":2009},{"i":2016,"t":"As long as the abstract method has a parameter of type org.springframework.data.domain.Sort, dynamic ordering can be achieved. For example: Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Sort; public interface BookRepository extends JRepository { List findByNameLikeIgnoreCase( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. @Nullable String name, @Nullable Sort sort ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.springframework.data.domain.Sort interface BookRepository : KRepository { fun findByNameLikeIgnoreCase( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. name: String? = null, sort: Sort? = null ): List } To facilitate the top-level code to accept sorting strings from the frontend, Jimmer provides the utility class org.babyfish.jimmer.spring.model.SortUtils to convert the sorting string passed from the client to org.springframework.data.domain.Sort. It can be used like: Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ); val sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ) or Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); val sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); ORDER BY without JOIN Java Kotlin List books = bookRepository .findByName( null, SortUtils.toSort(\"name, edition desc\") ); val books = bookRepository .findByName( null, SortUtils.toSort(\"name, edition desc\") ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc ORDER BY requiring JOIN Java Kotlin List books = bookRepository .findByName( null, SortUtils.toSort(\"store.name, name, edition desc\") ); val books = bookRepository .findByName( null, SortUtils.toSort(\"store.name, name, edition desc\") ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID order by tb_2_.NAME asc, tb_1_.NAME asc, tb_1_.EDITION desc","s":"Dynamic ORDER BY","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#dynamic-order-by","p":2009},{"i":2018,"t":"To perform paged queries, the method needs: A parameter of type org.springframework.data.domain.Pageable Return org.springframework.data.domain.Page Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Pageable; import org.springframework.data.domain.Page; public interface BookRepository extends JRepository { Page findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. @Nullable String name, Pageable pageable ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.springframework.data.domain.Pageable import org.springframework.data.domain.Page interface BookRepository : KRepository { fun findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. name: String? = null, pageable: Pageable ): Page } It can be used like: Java Kotlin Page page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ); val page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ) The returned Page object is like: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2 } }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1 } }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1 } }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1 } }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1 } } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"numberOfElements\":5, \"first\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"number\":1, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before paging */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query data within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL paging */ limit ?, /* 5 (offset) */ ? /* 5 (limit) */","s":"Paged Queries","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#paged-queries","p":2009},{"i":2020,"t":"Object fetchers are one of Jimmer's signature features, allowing querying of arbitrary complex data structures instead of just simple entity objects. Adding a parameter of type org.babyfish.jimmer.sql.fetcher.Fetcher makes the abstract method capable of this. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Pageable; import org.springframework.data.domain.Page; public interface BookRepository extends JRepository { Page findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. @Nullable String name, Pageable pageable, @Nullable Fetcher fetcher ); } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.fetcher.Fetcher import org.springframework.data.domain.Pageable import org.springframework.data.domain.Page interface BookRepository : KRepository { fun findByName( // This parameter is not used in subsequent examples, always null. // Reason: // If a query does not need any parameters, the method from base // interface is enough, no need to define this method. The value // of this parameter in this example is solely to make the current // custom abstract method look reasonable. name: String? = null, pageable: Pageable, fetcher: Fetcher? = null ): Page } If no Fetcher is passed or a shape of simple objects is passed, the result will be necessarily similar to previous examples, no need to repeat. So let's just demonstrate querying a complex data structure: Java Kotlin Page page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_FETCHER .name() // associated object only queries id (implicit+mandatory) and name ) .authors( Fetchers.AUTHOR_FETCHER // associated object only queries id (implicit+mandatory), firstName and lastName .firstName().lastName() ) ); val page = bookRepository .findByName( null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), newFetcher(Book::class).by { allScalarFields() store { // associated object only queries id // (implicit+mandatory) and name name() } authors { // associated object only queries // id (implicit+mandatory), firstName and lastName firstName() lastName() } } ) The returned Page object is: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\" }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\" } ] } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"numberOfElements\":5, \"number\":1, \"first\":false, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before paging */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query aggregate root objects within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL paging */ limit ?, /* 5 (offset) */ ? /* 5 (limit) */ /* * Step 3: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.store` * * Note: * In current case, the foreign key `STORE_ID` will be queried, so finding parent * objects directly via foreign key. Although there are 5 rows of data, * the foreign keys only have two distinct values, so only two SQL params. */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ where tb_1_.ID in ( ?, ? /* actual param list: 2, 1 */ ) /* * Step 4: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.authors` */ select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ?, ?, ?, ?, ? /* actual param list: 10, 3, 2, 1, 9 */ ) tip Whether it is simple queries discussed in this article, or complex queries to be discussed in next article, as long as the query returns entity objects or their collections instead of simple column tuples, it is highly recommended to add a Fetcher parameter to make all object queries as powerful in data structure shaping as GraphQL. This brings great convenience to higher level business code.","s":"Object Fetchers","u":"/jimmer-doc/docs/spring/repository/abstract","h":"#object-fetchers","p":2009},{"i":2022,"t":"In the previous document, we introduced adding abstract methods to custom Repository interfaces following certain conventions, which are implemented automatically by Jimmer. However, this approach has some issues: Results in very long method names Cannot implement complex query logic If developers add methods violating conventions, it leads to startup failures rather than compile time errors So Jimmer provides another approach that allows developers to write queries themselves and control all details. To maximize the safety of static languages, Jimmer provides a strongly typed SQL DSL, rather than weak, string-based solutions like Spring Data JPA's @Query. In Jimmer, query logic can be directly implemented in default methods of the Repository interface.","s":"Complex Queries","u":"/jimmer-doc/docs/spring/repository/default","h":"","p":2021},{"i":2024,"t":"Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; ❶ default List find(@Nullable String name) { return sql() ❷ .createQuery(table) .whereIf( ❸ StringUtils.hasText(name), table.name().ilike(name) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table) ❹ .execute(); ❺ } } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.kt.ast.expression.* interface BookRepository : KRepository { fun find(name: String? = null): List = sql ❷ .createQuery(Book::class) { ❶ name?.takeIf { it.isNotEmpty() }?.let { ❸ where(table.name ilike it) } orderBy(table.name) orderBy(table.edition.desc()) select(table) ❹ } .execute() ❺ } ❶ Java: The parent query is based on the table object Tables.BOOK, renamed to table for convenience. This rename applies to all default methods of the current interface, so declaring it as a static interface variable is appropriate. Kotlin: createQuery accepts a lambda expression which switches the meaning of this, so code inside the lambda can directly use the table variable. ❷ Java: The sql() method inherited from JRepository returns org.babyfish.jimmer.sql.JSqlClient, which is the total entry point for Java API of the SQL DSL. Kotlin: The sql property inherited from KRepository returns org.babyfish.jimmer.sql.kt.KSqlClient, which is the total entry point for Kotlin API of the SQL DSL. ❸ Only add the where condition when the query parameter is non-null and string length is non-zero. Obviously, this query is dynamic. ❹ The select statement is always at the end. Before select, the query has no return type; only after select can the return type of the query be determined. This is why select appears at the end. note The practice of putting select at the end is not originally invented by Jimmer, it was first introduced in C# linq. ❺ Between select and execute: In Java, the expression type is TypedRootQuery In Kotlin, the expression type is KTypedRootQuery But neither is List. This represents a query that is created but not yet executed. It needs to call execute to actually execute it to get the final result List. note The query is not executed immediately after creation, execute must be called to execute it. This is not a design flaw, but an important capability that the pagination query section will illustrate. execute is not the only execution method, in addition to execute, there are other execution methods: Method Return Type Note execute (as shown in this example) List Returns a list fetchOne T (cannot be null) Returns one record, throws exception if no data or multiple data fetchOneOrNull T (can be null) Returns one record, throws exception if multiple data fetchOptional (Java only) Optional wrapping of T or null Returns one record, throws exception if multiple data forEach No return Use when data volume is large, don't want to build collection, just iterate All these execution methods have two overloaded versions: Version without parameters (current example): Execute based on JDBC connection managed by Spring transaction. Should be called in most cases. Version with java.sql.Connection parameter: Execute based on the JDBC connection specified by the user. Usage: Do not specify parameter Java Kotlin List books = bookRepository .find(null); val books = bookRepository.find() The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc Specify parameter Java Kotlin List books = bookRepository.find(\"G\"); val books = bookRepository.find(\"G\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where lower(tb_1_.NAME) like ? /* %g% */ order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Dynamic WHERE","u":"/jimmer-doc/docs/spring/repository/default","h":"#dynamic-where","p":2021},{"i":2026,"t":"Next, add a storeName parameter to this query method to filter on the name property of BookStore associated via the Book.store property of the current Book. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default List find( @Nullable String name, @Nullable String storeName ) { return sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table) .execute(); } } BookRepository.kt package com.example.repository import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.kt.ast.expression.* interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null ): List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } orderBy(table.name) orderBy(table.edition.desc()) select(table) } .execute() } Where Java's table.store().name() or Kotlin's table.store.name means: Starting from the current queried object Book, join to the BookStore object via the association property Book.store, and finally apply filter condition on the BookStore.name property. Obviously, if the storeName parameter is not specified, the final SQL will not contain JOIN, no need to demonstrate. So let's demonstrate the case where the storeName parameter is specified. Java Kotlin List books = bookRepository.find(null, \"M\"); val books = bookRepository.find(storeName = \"M\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ inner join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID where lower(tb_2_.NAME) like ? order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Dynamic JOIN","u":"/jimmer-doc/docs/spring/repository/default","h":"#dynamic-join","p":2021},{"i":2028,"t":"Next, add an authorName parameter to this query method to filter on the firstName or lastName properties of Author associated via Book.authors property of the current Book. note Unfortunately, if you try to emulate the previous example's table.store.name by writing table.authors.firstName, you'll find there is no table.authors option in the IDE auto-complete of table. This is because Book.authors is a collection association (collective term for one-to-many and many-to-many associations). Blindly joining other objects via collection associations will lead to duplicate data in the query results. More importantly, this duplication is fatal for pagination queries to be shown later. For more details, please refer to Pagination Safety. If you read Pagination Safety, you'll know you can force connecting via collection associations using table.asTableEx().authors. However, this capability is not suitable for use here. In short, Jimmer's API will subtly hint that this should be implemented using subqueries rather than JOIN. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.jetbrains.annotations.Nullable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default List find( @Nullable String name, @Nullable String storeName, @Nullable String authorName ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; ❶ return sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) ❷ .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(table.name()) .orderBy(table.edition().desc()) .select(table) .execute(); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.sql.kt.ast.expression.* interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null ): List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { ❶❷ where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(table.name) orderBy(table.edition.desc()) select(table) } .execute() } ❶ Java: The subquery is based on the global variable TableExes.AUTHOR_TABLE_EX, alias it to author for subsequent convenience. Here, the subquery is based on TableExes.AUTHOR_TABLE_EX rather than Tables.AUTHOR_TABLE so that select(table.books().id()) can compile. Please read query/Pagination Safety for more details. Kotlin: subQuery accepts a lambda expression where this is redefined, so table variable can be used directly inside, but note: Inside subquery lambda: table var represents KNonNullTableEx Outside subquery lambda, inside parent query lambda: table var represents KNonNullTable If need to reference parent query table inside subquery (not shown in this example, usually used for correlated subqueries): please use parentTable ❷ Create subquery Obviously, if the authorName parameter is not specified, the final SQL will not contain sub query, no need to demonstrate. So let's demonstrate the case where authorName is specified. Java Kotlin List books = bookRepository.find(null, null, \"A\"); val books = bookRepository.find(authorName = \"M\") The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ where tb_1_.ID in ( select tb_3_.BOOK_ID from AUTHOR as tb_2_ inner join BOOK_AUTHOR_MAPPING as tb_3_ on tb_2_.ID = tb_3_.AUTHOR_ID where lower(tb_2_.FIRST_NAME) like ? /* %a% */ or lower(tb_2_.LAST_NAME) like ? /* %a% */ ) order by tb_1_.NAME asc, tb_1_.EDITION desc","s":"Subqueries","u":"/jimmer-doc/docs/spring/repository/default","h":"#subqueries","p":2021},{"i":2030,"t":"So far, the sorting in our queries has been static. We expect to accept external parameters to achieve dynamic sorting. Add a parameter of type org.springframework.data.domain.Sort to the query method and use it to sort. Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.spring.repository.SpringOrders; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Sort; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default List find( @Nullable String name, @Nullable String storeName, @Nullable String authorName, @Nullable Sort sort ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; return sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(SpringOrders.toOrders(table, sort)) .select(table) .execute(); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.spring.repository.orderBy import org.babyfish.jimmer.sql.kt.ast.expression.* import org.springframework.data.domain.Sort interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null, sort: Sort? = null ): List = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(sort) select(table) } .execute() } For Java, org.babyfish.jimmer.spring.repository.SpringOrders.toOrders is needed to convert the Spring Data Sort object to the sorting accepted by Jimmer. For Kotlin, org.babyfish.jimmer.spring.repository.orderBy extends the capability of Jimmer's underlying SQL DSL, so the query object can sort based on the Spring Data Sort object. To facilitate the top-level code to accept sorting strings from the client, Jimmer provides the utility class org.babyfish.jimmer.spring.model.SortUtils to convert the string passed from the frontend to org.springframework.data.domain.Sort. It can be used like: Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ); val sort = SortUtils.toSort( \"store.name asc\", \"name asc\", \"edition desc\" ) or Java Kotlin Sort sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); val sort = SortUtils.toSort( \"store.name asc, name asc, edition desc\" ); Now let's demonstrate the usage of dynamic sorting by specifying all other query parameters as null to focus on the sorting logic. Java Kotlin List books = bookRepository.find( null, null, null, SortUtils.toSort( \"store.name\", // This sort implies JOIN \"price desc\" ) ); val books = bookRepository.find( sort = SortUtils.toSort( \"store.name\", // This sort implies JOIN \"price desc\" ) ) The generated SQL is (formatted for readability): select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ /* Dynamic sort causes table join */ left join BOOK_STORE as tb_2_ on tb_1_.STORE_ID = tb_2_.ID /* Dynamic sort */ order by tb_2_.NAME asc, tb_1_.PRICE desc","s":"Dynamic ORDER BY","u":"/jimmer-doc/docs/spring/repository/default","h":"#dynamic-order-by","p":2021},{"i":2032,"t":"Let's continue improving the example by adding pagination capability. To implement pagination, need: Replace the org.springframework.data.domain.Sort type parameter with org.springframework.data.domain.Pageable (Pageable contains Sort) Change return value from java.util.List to org.springframework.data.domain.Page Internally use specific APIs to achieve pagination in one statement Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.spring.repository.SpringOrders; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page find( ❶ @Nullable String name, @Nullable String storeName, @Nullable String authorName, Pageable pageable ❷ ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; return pager(pageable).execute( ❸ sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) ❹ .select(table) ); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.spring.repository.orderBy import org.babyfish.jimmer.sql.kt.ast.expression.* import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null, pageable: Pageable ❷ ): Page = ❶ sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(pageable.sort) ❹ select(table) } .fetchPage( ❸ pageable.pageNumber, pageable.pageSize ) } ❶ Return org.springframework.data.domain.Page rather than java.util.List ❷ Parameter becomes org.springframework.data.domain.Pageable ❸ Execute paged query Java Create a Pager object to paginate the original unexecuted query pager is a method inherited from base interface JRepository/KRepository The pager method has multiple overloaded versions, here the one called accepts a pagable object The pager method creates a Pager object, which has an execute method that accepts the unexecuted original query Kotlin Kotlin API provides the extension method fetchPage for KConfigurableRootQuery<*, E> types to implement paged queries ❹ Get sort object from pageable to perform dynamic sorting Now let's demonstrate the usage of paging query by specifying all other query parameters as null to focus on the pagination logic. Java Kotlin List books = bookRepository.find( null, null, null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ); val books = bookRepository.find( pageable = PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ) ) The returned Page object is: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2 } }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1 } }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1 } }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1 } }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1 } } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"numberOfElements\":5, \"first\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"number\":1, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before pagination */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query data within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL pagination */ limit ?, /* 5(offset) */ ? /* 5(limit) */","s":"Pagination","u":"/jimmer-doc/docs/spring/repository/default","h":"#pagination","p":2021},{"i":2034,"t":"Object fetchers are one of Jimmer's signature features, allowing querying of arbitrary complex data structures instead of just simple entity objects. To use it, need: Add a parameter of type org.babyfish.jimmer.sql.fetcher.Fetcher Change the select call of the top-level query from select(table) to select(table.fetch(fetcher)) Java Kotlin BookRepository.java package com.example.repository; import com.example.model.AuthorTableEx; import com.example.model.Book; import com.example.model.BookTable; import org.babyfish.jimmer.spring.repository.JRepository; import org.babyfish.jimmer.spring.repository.SpringOrders; import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.jetbrains.annotations.Nullable; import org.springframework.data.domain.Page; import org.springframework.data.domain.Pageable; import org.springframework.util.StringUtils; public interface BookRepository extends JRepository { BookTable table = Tables.BOOK_TABLE; default Page find( @Nullable String name, @Nullable String storeName, @Nullable String authorName, Pageable pageable, @Nullable Fetcher fetcher ) { AuthorTableEx author = TableExes.AUTHOR_TABLE_EX; return pager(pageable).execute( sql() .createQuery(table) .whereIf( StringUtils.hasText(name), table.name().ilike(name) ) .whereIf( StringUtils.hasText(storeName), table.store().name().ilike(storeName) ) .whereIf( StringUtils.hasText(authorName), table.id().in( sql() .createSubQuery(author) .where( Predicate.or( author.firstName().ilike(authorName), author.lastName().ilike(authorName) ) ) .select( author.books().id() ) ) ) .orderBy(SpringOrders.toOrders(table, pageable.getSort())) .select( table.fetch(fetcher) ) ); } } BookRepository.kt package com.example.repository import com.example.model.Author import com.example.model.Book import org.babyfish.jimmer.spring.repository.KRepository import org.babyfish.jimmer.spring.repository.orderBy import org.babyfish.jimmer.sql.fetcher.Fetcher; import org.babyfish.jimmer.sql.kt.ast.expression.* import org.springframework.data.domain.Page import org.springframework.data.domain.Pageable interface BookRepository : KRepository { fun find( name: String? = null, storeName: String? = null, authorName: String? = null, pageable: Pageable, fetcher: Fetcher? = null ): Page = sql .createQuery(Book::class) { name?.takeIf { it.isNotEmpty() }?.let { where(table.name ilike it) } storeName?.takeIf { it.isNotEmpty() }?.let { table.store.name ilike it } authorName?.takeIf { it.isNotEmpty() }?.let { where( table.id valueIn subQuery(Author::class) { where( or( table.firstName ilike it, table.lastName ilike it ) ) select(table.books.id) } ) } orderBy(pageable.sort) select( table.fetch(fetcher) ) } .fetchPage( pageable.pageNumber, pageable.pageSize ) } If no fetcher is passed or simple object shape is passed, the result will necessarily be similar to previous examples, no need to repeat. So let's just demonstrate querying a complex data structure directly. To focus on the object fetcher, all other query parameters are specified as null except the fetcher. Java Kotlin Page page = bookRepository .find( null, null, null, PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), Fetchers.BOOK_FETCHER .allScalarFields() .store( Fetchers.BOOK_FETCHER .name() // associated object only queries id (implicit+mandatory) and name ) .authors( Fetchers.AUTHOR_FETCHER // associated object only queries id (implicit+mandatory), firstName and lastName .firstName().lastName() ) ); val page = bookRepository .find( pageable = PageRequest.of( 1, // zero based, 1 means second page 5, SortUtils.toSort(\"name, edition desc\") ), fetcher = newFetcher(Book::class).by { allScalarFields() store { // associated object only queries // id (implicit+mandatory) and name name() } authors { // associated object only queries // id (implicit+mandatory), firstName and lastName firstName() lastName() } } ) The returned Page object is: { \"content\":[ { \"id\":10, \"name\":\"GraphQL in Action\", \"edition\":1, \"price\":80, \"store\":{ \"id\":2, \"name\":\"MANNING\" }, \"authors\":[ { \"id\":5, \"firstName\":\"Samer\", \"lastName\":\"Buna\" } ] }, { \"id\":3, \"name\":\"Learning GraphQL\", \"edition\":3, \"price\":51, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":2, \"name\":\"Learning GraphQL\", \"edition\":2, \"price\":55, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":1, \"name\":\"Learning GraphQL\", \"edition\":1, \"price\":45, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":2, \"firstName\":\"Alex\", \"lastName\":\"Banks\" }, { \"id\":1, \"firstName\":\"Eve\", \"lastName\":\"Procello\" } ] }, { \"id\":9, \"name\":\"Programming TypeScript\", \"edition\":3, \"price\":48, \"store\":{ \"id\":1, \"name\":\"O'REILLY\" }, \"authors\":[ { \"id\":4, \"firstName\":\"Boris\", \"lastName\":\"Cherny\" } ] } ], \"pageable\":{ \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"pageNumber\":1, \"pageSize\":5, \"offset\":5, \"paged\":true, \"unpaged\":false }, \"totalPages\":3, \"totalElements\":12, \"last\":false, \"sort\":{ \"unsorted\":false, \"sorted\":true, \"empty\":false }, \"numberOfElements\":5, \"number\":1, \"first\":false, \"size\":5, \"empty\":false } The generated SQL is (formatted for readability): /* Step 1: Query total rows before pagination */ select count(tb_1_.ID) from BOOK as tb_1_ /* Step 2: Query aggregate root objects within one page */ select tb_1_.ID, tb_1_.NAME, tb_1_.EDITION, tb_1_.PRICE, tb_1_.STORE_ID from BOOK as tb_1_ order by tb_1_.NAME asc, tb_1_.EDITION desc /* MySQL pagination */ limit ?, /* 5(offset) */ ? /* 5(limit) */ /* * Step 3: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.store` * * Note: * Here the foreign key `STORE_ID` of the 5 records will be queried, * so finding parent objects directly via foreign key. * Although there are 5 rows of data, the foreign keys only * have two distinct values, so only two SQL params. */ select tb_1_.ID, tb_1_.NAME from BOOK_STORE as tb_1_ where tb_1_.ID in ( ?/* 2 */, ?/* 1 */ ) /* * Step 4: For the 5 paged data (not 12 rows before paging), * query the associated objects of property `Book.authors` */ select tb_2_.BOOK_ID, tb_1_.ID, tb_1_.FIRST_NAME, tb_1_.LAST_NAME from AUTHOR as tb_1_ inner join BOOK_AUTHOR_MAPPING as tb_2_ on tb_1_.ID = tb_2_.AUTHOR_ID where tb_2_.BOOK_ID in ( ?/* 10 */, ?/* 3 */, ?/* 2 */, ?/* 1 */, ?/* 9 */ ) tip Whether it is complex queries discussed in this article, or simple queries discussed in previous article, as long as the query returns entity objects or their collections rather than simple column tuples, it is highly recommended to add a Fetcher parameter to make all object queries as powerful in data structure shaping as GraphQL. This brings great convenience to higher level business code.","s":"Object 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