Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected.
- cluster: set of Elasticsearch instances that share the data of the same application
- node: one Elasticsearch instance of a cluster, in a cluster a master node is choosen by majority vote
- shard: Elasticsearch provides the ability to subdivide your index into multiple pieces called shards
- primary: original indexes data
- replicat: indexes data replication
- index: collection of documents that have somewhat similar characteristics; similar to a database in SQL
- type: or document type, logical category/partition of your index whose semantics is completely up to you; similar to a SQL database
- document: basic unit of information that can be indexed; similar to a row in a SQL table
- field: one entry of the document, can store
string,integerlist,object, etc.; similar to a table SQL cell
- mapping: the process of defining how a document, and the fields it contains, are stored and indexed
- query: search query with ranking results
- filter: boolean query without ranking
- aggregator: facets
- analzyer: transform a document value in a set of tokens; index entities
- char_filter: are used to preprocess the stream of characters before it is passed to the tokenizer
- tokenizer: receives a stream of characters, breaks it up into individual tokens
- token filter: accept a stream of tokens from a tokenizer and can modify tokens; for example:
Lowercase Token Filteror language stemmers
A complete Elasticsearch glossary is available in 2.
docker run --name es --rm -ti -p 9200:9200 -p 9300:9300 elasticsearchOpen http://localhost:9200 in a browser.