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Grouping Top N queries documentation (#8173)
* Grouping Top N queries documentation Signed-off-by: Siddhant Deshmukh <[email protected]> * Fix dead links Signed-off-by: Siddhant Deshmukh <[email protected]> * Fix dead link Signed-off-by: Siddhant Deshmukh <[email protected]> * Fix dead links Signed-off-by: Siddhant Deshmukh <[email protected]> * Address reviewdog comments Signed-off-by: Siddhant Deshmukh <[email protected]> * reviewdog fix Signed-off-by: Siddhant Deshmukh <[email protected]> * Doc review Signed-off-by: Fanit Kolchina <[email protected]> * Add table Signed-off-by: Siddhant Deshmukh <[email protected]> * Table review and added ability to collapse the response Signed-off-by: Fanit Kolchina <[email protected]> * More explanation to a couple of parameters Signed-off-by: Fanit Kolchina <[email protected]> * Typo fix Signed-off-by: Fanit Kolchina <[email protected]> * Apply suggestions from code review Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> * Editorial comment Signed-off-by: Fanit Kolchina <[email protected]> * Update _observing-your-data/query-insights/grouping-top-n-queries.md Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> --------- Signed-off-by: Siddhant Deshmukh <[email protected]> Signed-off-by: Fanit Kolchina <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> Co-authored-by: Fanit Kolchina <[email protected]> Co-authored-by: kolchfa-aws <[email protected]> Co-authored-by: Nathan Bower <[email protected]>
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_observing-your-data/query-insights/grouping-top-n-queries.md
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| --- | ||
| layout: default | ||
| title: Grouping top N queries | ||
| parent: Query insights | ||
| nav_order: 20 | ||
| --- | ||
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| # Grouping top N queries | ||
| **Introduced 2.17** | ||
| {: .label .label-purple } | ||
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| Monitoring the [top N queries]({{site.url}}{{site.baseurl}}/observing-your-data/query-insights/top-n-queries/) can help you to identify the most resource-intensive queries based on latency, CPU, and memory usage in a specified time window. However, if a single computationally expensive query is executed multiple times, it can occupy all top N query slots, potentially preventing other expensive queries from appearing in the list. To address this issue, you can group similar queries, gaining insight into various high-impact query groups. | ||
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| Starting with OpenSearch version 2.17, the top N queries can be grouped by `similarity`, with additional grouping options planned for future version releases. | ||
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| ## Grouping queries by similarity | ||
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| Grouping queries by `similarity` organizes them based on the query structure, removing everything except the core query operations. | ||
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| For example, the following query: | ||
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| ```json | ||
| { | ||
| "query": { | ||
| "bool": { | ||
| "must": [ | ||
| { "exists": { "field": "field1" } } | ||
| ], | ||
| "query_string": { | ||
| "query": "search query" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| ``` | ||
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| Has the following corresponding query structure: | ||
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| ```c | ||
| bool | ||
| must | ||
| exists | ||
| query_string | ||
| ``` | ||
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| When queries share the same query structure, they are grouped together, ensuring that all similar queries belong to the same group. | ||
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| ## Aggregate metrics per group | ||
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| In addition to retrieving latency, CPU, and memory metrics for individual top N queries, you can obtain aggregate statistics for the | ||
| top N query groups. For each query group, the response includes the following statistics: | ||
| - The total latency, CPU usage, or memory usage (depending on the configured metric type) | ||
| - The total query count | ||
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| Using these statistics, you can calculate the average latency, CPU usage, or memory usage for each query group. | ||
| The response also includes one example query from the query group. | ||
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| ## Configuring query grouping | ||
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| Before you enable query grouping, you must enable top N query monitoring for a metric type of your choice. For more information, see [Configuring top N query monitoring]({{site.url}}{{site.baseurl}}/observing-your-data/query-insights/top-n-queries/#configuring-top-n-query-monitoring). | ||
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| To configure grouping for top N queries, use the following steps. | ||
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| ### Step 1: Enable top N query monitoring | ||
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| Ensure that top N query monitoring is enabled for at least one of the metrics: latency, CPU, or memory. For more information, see [Configuring top N query monitoring]({{site.url}}{{site.baseurl}}/observing-your-data/query-insights/top-n-queries/#configuring-top-n-query-monitoring). | ||
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| For example, to enable top N query monitoring by latency with the default settings, send the following request: | ||
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| ```json | ||
| PUT _cluster/settings | ||
| { | ||
| "persistent" : { | ||
| "search.insights.top_queries.latency.enabled" : true | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| ### Step 2: Configure query grouping | ||
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| Set the desired grouping method by updating the following cluster setting: | ||
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| ```json | ||
| PUT _cluster/settings | ||
| { | ||
| "persistent" : { | ||
| "search.insights.top_queries.group_by" : "similarity" | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The default value for the `group_by` setting is `none`, which disables grouping. As of OpenSearch 2.17, the supported values for `group_by` are `similarity` and `none`. | ||
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| ### Step 3 (Optional): Limit the number of monitored query groups | ||
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| Optionally, you can limit the number of monitored query groups. Queries already included in the top N query list (the most resource-intensive queries) will not be considered in determining the limit. Essentially, the maximum applies only to other query groups, and the top N queries are tracked separately. This helps manage the tracking of query groups based on workload and query window size. | ||
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| To limit tracking to 100 query groups, send the following request: | ||
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| ```json | ||
| PUT _cluster/settings | ||
| { | ||
| "persistent" : { | ||
| "search.insights.top_queries.max_groups_excluding_topn" : 100 | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The default value for `max_groups_excluding_topn` is `100`, and you can set it to any value between `0` and `10,000`, inclusive. | ||
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| ## Monitoring query groups | ||
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| To view the top N query groups, send the following request: | ||
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| ```json | ||
| GET /_insights/top_queries | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The response contains the top N query groups: | ||
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| <details open markdown="block"> | ||
| <summary> | ||
| Response | ||
| </summary> | ||
| {: .text-delta} | ||
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| ```json | ||
| { | ||
| "top_queries": [ | ||
| { | ||
| "timestamp": 1725495127359, | ||
| "source": { | ||
| "query": { | ||
| "match_all": { | ||
| "boost": 1.0 | ||
| } | ||
| } | ||
| }, | ||
| "phase_latency_map": { | ||
| "expand": 0, | ||
| "query": 55, | ||
| "fetch": 3 | ||
| }, | ||
| "total_shards": 1, | ||
| "node_id": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "query_hashcode": "b4c4f69290df756021ca6276be5cbb75", | ||
| "task_resource_usages": [ | ||
| { | ||
| "action": "indices:data/read/search[phase/query]", | ||
| "taskId": 30, | ||
| "parentTaskId": 29, | ||
| "nodeId": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "taskResourceUsage": { | ||
| "cpu_time_in_nanos": 33249000, | ||
| "memory_in_bytes": 2896848 | ||
| } | ||
| }, | ||
| { | ||
| "action": "indices:data/read/search", | ||
| "taskId": 29, | ||
| "parentTaskId": -1, | ||
| "nodeId": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "taskResourceUsage": { | ||
| "cpu_time_in_nanos": 3151000, | ||
| "memory_in_bytes": 133936 | ||
| } | ||
| } | ||
| ], | ||
| "indices": [ | ||
| "my_index" | ||
| ], | ||
| "labels": {}, | ||
| "search_type": "query_then_fetch", | ||
| "measurements": { | ||
| "latency": { | ||
| "number": 160, | ||
| "count": 10, | ||
| "aggregationType": "AVERAGE" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "timestamp": 1725495135160, | ||
| "source": { | ||
| "query": { | ||
| "term": { | ||
| "content": { | ||
| "value": "first", | ||
| "boost": 1.0 | ||
| } | ||
| } | ||
| } | ||
| }, | ||
| "phase_latency_map": { | ||
| "expand": 0, | ||
| "query": 18, | ||
| "fetch": 0 | ||
| }, | ||
| "total_shards": 1, | ||
| "node_id": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "query_hashcode": "c3620cc3d4df30fb3f95aeb2167289a4", | ||
| "task_resource_usages": [ | ||
| { | ||
| "action": "indices:data/read/search[phase/query]", | ||
| "taskId": 50, | ||
| "parentTaskId": 49, | ||
| "nodeId": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "taskResourceUsage": { | ||
| "cpu_time_in_nanos": 10188000, | ||
| "memory_in_bytes": 288136 | ||
| } | ||
| }, | ||
| { | ||
| "action": "indices:data/read/search", | ||
| "taskId": 49, | ||
| "parentTaskId": -1, | ||
| "nodeId": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "taskResourceUsage": { | ||
| "cpu_time_in_nanos": 262000, | ||
| "memory_in_bytes": 3216 | ||
| } | ||
| } | ||
| ], | ||
| "indices": [ | ||
| "my_index" | ||
| ], | ||
| "labels": {}, | ||
| "search_type": "query_then_fetch", | ||
| "measurements": { | ||
| "latency": { | ||
| "number": 109, | ||
| "count": 7, | ||
| "aggregationType": "AVERAGE" | ||
| } | ||
| } | ||
| }, | ||
| { | ||
| "timestamp": 1725495139766, | ||
| "source": { | ||
| "query": { | ||
| "match": { | ||
| "content": { | ||
| "query": "first", | ||
| "operator": "OR", | ||
| "prefix_length": 0, | ||
| "max_expansions": 50, | ||
| "fuzzy_transpositions": true, | ||
| "lenient": false, | ||
| "zero_terms_query": "NONE", | ||
| "auto_generate_synonyms_phrase_query": true, | ||
| "boost": 1.0 | ||
| } | ||
| } | ||
| } | ||
| }, | ||
| "phase_latency_map": { | ||
| "expand": 0, | ||
| "query": 15, | ||
| "fetch": 0 | ||
| }, | ||
| "total_shards": 1, | ||
| "node_id": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "query_hashcode": "484eaabecd13db65216b9e2ff5eee999", | ||
| "task_resource_usages": [ | ||
| { | ||
| "action": "indices:data/read/search[phase/query]", | ||
| "taskId": 64, | ||
| "parentTaskId": 63, | ||
| "nodeId": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "taskResourceUsage": { | ||
| "cpu_time_in_nanos": 12161000, | ||
| "memory_in_bytes": 473456 | ||
| } | ||
| }, | ||
| { | ||
| "action": "indices:data/read/search", | ||
| "taskId": 63, | ||
| "parentTaskId": -1, | ||
| "nodeId": "ZbINz1KFS1OPeFmN-n5rdg", | ||
| "taskResourceUsage": { | ||
| "cpu_time_in_nanos": 293000, | ||
| "memory_in_bytes": 3216 | ||
| } | ||
| } | ||
| ], | ||
| "indices": [ | ||
| "my_index" | ||
| ], | ||
| "labels": {}, | ||
| "search_type": "query_then_fetch", | ||
| "measurements": { | ||
| "latency": { | ||
| "number": 43, | ||
| "count": 3, | ||
| "aggregationType": "AVERAGE" | ||
| } | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
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| </details> | ||
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| ## Response fields | ||
|
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| The response includes the following fields. | ||
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| Field | Data type | Description | ||
| :--- |:---| :--- | ||
| `top_queries` | Array | The list of top query groups. | ||
| `top_queries.timestamp` | Integer | The execution timestamp for the first query in the query group. | ||
| `top_queries.source` | Object | The first query in the query group. | ||
| `top_queries.phase_latency_map` | Object | The phase latency map for the first query in the query group. The map includes the amount of time, in milliseconds, that the query spent in the `expand`, `query`, and `fetch` phases. | ||
| `top_queries.total_shards` | Integer | The number of shards on which the first query was executed. | ||
| `top_queries.node_id` | String | The node ID of the node that coordinated the execution of the first query in the query group. | ||
| `top_queries.query_hashcode` | String | The hash code that uniquely identifies the query group. This is essentially the hash of the [query structure](#grouping-queries-by-similarity). | ||
| `top_queries.task_resource_usages` | Array of objects | The resource usage breakdown for the various tasks belonging to the first query in the query group. | ||
| `top_queries.indices` | Array | The indexes searched by the first query in the query group. | ||
| `top_queries.labels` | Object | Used to label the top query. | ||
| `top_queries.search_type` | String | The search request execution type (`query_then_fetch` or `dfs_query_then_fetch`). For more information, see the `search_type` parameter in the [Search API documentation]({{site.url}}{{site.baseurl}}/api-reference/search/#url-parameters). | ||
| `top_queries.measurements` | Object | The aggregate measurements for the query group. | ||
| `top_queries.measurements.latency` | Object | The aggregate latency measurements for the query group. | ||
| `top_queries.measurements.latency.number` | Integer | The total latency for the query group. | ||
| `top_queries.measurements.latency.count` | Integer | The number of queries in the query group. | ||
| `top_queries.measurements.latency.aggregationType` | String | The aggregation type for the current entry. If grouping by similarity is enabled, then `aggregationType` is `AVERAGE`. If it is not enabled, then `aggregationType` is `NONE`. |
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