387 lines
10 KiB
Markdown
387 lines
10 KiB
Markdown
---
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layout: default
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title: Search pipelines
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nav_order: 100
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has_children: true
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has_toc: false
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---
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# Search pipelines
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This is an experimental feature and is not recommended for use in a production environment. For updates on the progress of the feature or if you want to leave feedback, join the discussion in the [OpenSearch forum](https://forum.opensearch.org/t/rfc-search-pipelines/12099).
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{: .warning}
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You can use _search pipelines_ to build new or reuse existing result rerankers, query rewriters, and other components that operate on queries or results. Search pipelines make it easier for you to process search queries and search results within OpenSearch. Moving some of your application functionality into an OpenSearch search pipeline reduces the overall complexity of your application. As part of a search pipeline, you specify a list of processors that perform modular tasks. You can then easily add or reorder these processors to customize search results for your application.
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## Terminology
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The following is a list of search pipeline terminology:
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* _Search request processor_: A component that takes a search request (the query and the metadata passed in the request), performs an operation with or on the search request, and returns a search request.
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* _Search response processor_: A component that takes a search response and search request (the query, results, and metadata passed in the request), performs an operation with or on the search response, and returns a search response.
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* _Processor_: Either a search request processor or a search response processor.
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* _Search pipeline_: An ordered list of processors that is integrated into OpenSearch. The pipeline intercepts a query, performs processing on the query, sends it to OpenSearch, intercepts the results, performs processing on the results, and returns them to the calling application, as shown in the following diagram.
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Both request and response processing for the pipeline are performed on the coordinator node, so there is no shard-level processing.
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{: .note}
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## Search request processors
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OpenSearch supports the following search request processors:
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- [`script`]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/script-processor/): Adds a script that is run on newly indexed documents.
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- [`filter_query`]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/filter-query-processor/): Adds a filtering query that is used to filter requests.
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## Search response processors
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OpenSearch supports the following search response processors:
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- [`rename_field`]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/rename-field-processor/): Renames an existing field.
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## Viewing available processor types
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You can use the Nodes Search Pipelines API to view the available processor types:
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```json
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GET /_nodes/search_pipelines
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```
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{% include copy-curl.html %}
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The response contains the `search_pipelines` object that lists the available request and response processors:
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<details open markdown="block">
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<summary>
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Response
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</summary>
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{: .text-delta}
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```json
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{
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"_nodes" : {
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"total" : 1,
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"successful" : 1,
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"failed" : 0
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},
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"cluster_name" : "runTask",
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"nodes" : {
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"36FHvCwHT6Srbm2ZniEPhA" : {
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"name" : "runTask-0",
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"transport_address" : "127.0.0.1:9300",
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"host" : "127.0.0.1",
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"ip" : "127.0.0.1",
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"version" : "3.0.0",
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"build_type" : "tar",
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"build_hash" : "unknown",
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"roles" : [
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"cluster_manager",
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"data",
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"ingest",
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"remote_cluster_client"
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],
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"attributes" : {
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"testattr" : "test",
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"shard_indexing_pressure_enabled" : "true"
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},
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"search_pipelines" : {
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"request_processors" : [
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{
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"type" : "filter_query"
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},
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{
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"type" : "script"
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}
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],
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"response_processors" : [
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{
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"type" : "rename_field"
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}
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]
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}
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}
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}
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}
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```
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</details>
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In addition to the processors provided by OpenSearch, additional processors may be provided by plugins.
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{: .note}
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## Creating a search pipeline
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Search pipelines are stored in the cluster state. To create a search pipeline, you must configure an ordered list of processors in your OpenSearch cluster. You can have more than one processor of the same type in the pipeline. Each processor has a `tag` identifier that distinguishes it from the others. Tagging a specific processor can be helpful for debugging error messages, especially if you add multiple processors of the same type.
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#### Example request
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The following request creates a search pipeline with a `filter_query` request processor that uses a term query to return only public messages:
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```json
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PUT /_search/pipeline/my_pipeline
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{
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"request_processors": [
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{
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"filter_query" : {
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"tag" : "tag1",
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"description" : "This processor is going to restrict to publicly visible documents",
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"query" : {
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"term": {
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"visibility": "public"
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}
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}
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}
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}
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]
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}
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```
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{% include copy-curl.html %}
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## Retrieving search pipelines
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To retrieve the details of an existing search pipeline, use the Search Pipeline API.
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To view all search pipelines, use the following request:
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```json
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GET /_search/pipeline
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```
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{% include copy-curl.html %}
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The response contains the pipeline that you set up in the previous section:
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<details open markdown="block">
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<summary>
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Response
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</summary>
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{: .text-delta}
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```json
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{
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"my_pipeline" : {
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"request_processors" : [
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{
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"filter_query" : {
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"tag" : "tag1",
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"description" : "This processor is going to restrict to publicly visible documents",
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"query" : {
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"term" : {
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"visibility" : "public"
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}
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}
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}
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}
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]
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}
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}
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```
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</details>
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To view a particular pipeline, specify the pipeline name as a path parameter:
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```json
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GET /_search/pipeline/my_pipeline
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```
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{% include copy-curl.html %}
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You can also use wildcard patterns to view a subset of pipelines, for example:
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```json
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GET /_search/pipeline/my*
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```
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{% include copy-curl.html %}
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## Using a search pipeline
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To search with a pipeline, specify the pipeline name in the `search_pipeline` query parameter:
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```json
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GET /my_index/_search?search_pipeline=my_pipeline
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```
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{% include copy-curl.html %}
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For a complete example of using a search pipeline with a `filter_query` processor, see [`filter_query` processor example]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/filter-query-processor#example).
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## Default search pipeline
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For convenience, you can set a default search pipeline for an index. Once your index has a default pipeline, you don't need to specify the `search_pipeline` query parameter in every search request.
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### Setting a default search pipeline for an index
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To set a default search pipeline for an index, specify the `index.search.default_pipeline` in the index's settings:
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```json
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PUT /my_index/_settings
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{
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"index.search.default_pipeline" : "my_pipeline"
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}
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```
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{% include copy-curl.html %}
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After setting the default pipeline for `my_index`, you can try the same search for all documents:
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```json
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GET /my_index/_search
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```
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{% include copy-curl.html %}
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The response contains only the public document, indicating that the pipeline was applied by default:
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<details open markdown="block">
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<summary>
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Response
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</summary>
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{: .text-delta}
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```json
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{
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"took" : 19,
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"timed_out" : false,
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"_shards" : {
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"total" : 1,
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"successful" : 1,
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"skipped" : 0,
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"failed" : 0
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},
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"hits" : {
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"total" : {
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"value" : 1,
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"relation" : "eq"
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},
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"max_score" : 0.0,
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"hits" : [
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{
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"_index" : "my_index",
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"_id" : "1",
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"_score" : 0.0,
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"_source" : {
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"message" : "This is a public message",
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"visibility" : "public"
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}
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}
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]
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}
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}
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```
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</details>
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### Disabling the default pipeline for a request
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If you want to run a search request without applying the default pipeline, you can set the `search_pipeline` query parameter to `_none`:
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```json
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GET /my_index/_search?search_pipeline=_none
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```
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{% include copy-curl.html %}
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### Removing the default pipeline
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To remove the default pipeline from an index, set it to `null` or `_none`:
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```json
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PUT /my_index/_settings
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{
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"index.search.default_pipeline" : null
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}
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```
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{% include copy-curl.html %}
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```json
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PUT /my_index/_settings
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{
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"index.search.default_pipeline" : "_none"
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}
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```
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{% include copy-curl.html %}
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## Updating a search pipeline
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To update a search pipeline dynamically, replace the search pipeline using the Search Pipeline API.
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#### Example request
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The following request upserts `my_pipeline` by adding a `filter_query` request processor and a `rename_field` response processor:
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```json
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PUT /_search/pipeline/my_pipeline
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{
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"request_processors": [
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{
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"filter_query": {
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"tag": "tag1",
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"description": "This processor returns only publicly visible documents",
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"query": {
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"term": {
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"visibility": "public"
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}
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}
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}
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}
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],
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"response_processors": [
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{
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"rename_field": {
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"field": "message",
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"target_field": "notification"
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}
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}
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]
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}
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```
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{% include copy-curl.html %}
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## Search pipeline versions
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When creating your pipeline, you can specify a version for it in the `version` parameter:
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```json
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PUT _search/pipeline/my_pipeline
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{
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"version": 1234,
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"request_processors": [
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{
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"script": {
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"source": """
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if (ctx._source['size'] > 100) {
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ctx._source['explain'] = false;
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}
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"""
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}
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}
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]
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}
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```
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{% include copy-curl.html %}
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The version is provided in all subsequent responses to `get pipeline` requests:
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```json
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GET _search/pipeline/my_pipeline
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```
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The response contains the pipeline version:
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<details open markdown="block">
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<summary>
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Response
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</summary>
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{: .text-delta}
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```json
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{
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"my_pipeline": {
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"version": 1234,
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"request_processors": [
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{
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"script": {
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"source": """
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if (ctx._source['size'] > 100) {
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ctx._source['explain'] = false;
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}
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"""
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}
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}
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]
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}
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}
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```
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</details> |