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.
## Terminology
The following is a list of search pipeline terminology:
* [_Search request processor_]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-processors#search-request-processors): A component that intercepts a search request (the query and the metadata passed in the request), performs an operation with or on the search request, and returns the search request.
* [_Search response processor_]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-processors#search-response-processors): A component that intercepts 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 the search response.
* [_Search phase results processor_]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-processors#search-phase-results-processors): A component that runs between search phases at the coordinating node level. A search phase results processor intercepts the results retrieved from one search phase and transforms them before passing them to the next search phase.
* [_Processor_]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-processors/): Either a search request processor or a search response processor.
* _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.
To learn more about available search processors, see [Search processors]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-processors/).
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.
The following request creates a search pipeline with a `filter_query` request processor that uses a term query to return only public messages and a response processor that renames the field `message` to `notification`:
By default, a search pipeline stops if one of its processors fails. If you want the pipeline to continue running when a processor fails, you can set the `ignore_failure` parameter for that processor to `true` when creating the pipeline:
```json
"filter_query" : {
"tag" : "tag1",
"description" : "This processor is going to restrict to publicly visible documents",
"ignore_failure": true,
"query" : {
"term": {
"visibility": "public"
}
}
}
```
If the processor fails, OpenSearch logs the failure and continues to run all remaining processors in the search pipeline. To check whether there were any failures, you can use [search pipeline metrics](#search-pipeline-metrics).
Alternatively, you can use a temporary pipeline with a request or set a default pipeline for an index. To learn more, see [Using a search pipeline]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/using-search-pipeline/).
For information about retrieving search pipeline statistics, see [Search pipeline metrics]({{site.url}}{{site.baseurl}}/search-plugins/search-pipelines/search-pipeline-metrics/).