OpenSearch/docs/reference/query-dsl/percolate-query.asciidoc

[[query-dsl-percolate-query]]
=== Percolate Query

The `percolate` query can be used to match queries
stored in an index. The `percolate` query itself
contains the document that will be used as query
to match with the stored queries.

[float]
=== Sample Usage

Create an index with two mappings:

[source,js]
--------------------------------------------------
PUT /my-index
{
    "mappings": {
        "doctype": {
            "properties": {
                "message": {
                    "type": "string"
                }
            }
        },
            "queries": {
                "properties": {
                    "query": {
                        "type": "percolator"
                    }
                }
            }
    }
}
--------------------------------------------------
// CONSOLE

The `doctype` mapping is the mapping used to preprocess
the document defined in the `percolator` query before it
gets indexed into a temporary index.

The `queries` mapping is the mapping used for indexing
the query documents. The `query` field will hold a json
object that represents an actual Elasticsearch query. The
`query` field has been configured to use the
<<percolator,percolator field type>>. This field type understands
the query dsl and stored the query in such a way that it
can be used later on to match documents defined on the `percolate` query.

Register a query in the percolator:

[source,js]
--------------------------------------------------
PUT /my-index/queries/1
{
    "query" : {
        "match" : {
            "message" : "bonsai tree"
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

Match a document to the registered percolator queries:

[source,js]
--------------------------------------------------
GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field" : "query",
            "document_type" : "doctype",
            "document" : {
                "message" : "A new bonsai tree in the office"
            }
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

The above request will yield the following response:

[source,js]
--------------------------------------------------
{
  "took": 5,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0.5716521,
    "hits": [
      { <1>
        "_index": "my-index",
        "_type": "queries",
        "_id": "1",
        "_score": 0.5716521,
        "_source": {
          "query": {
            "match": {
              "message": "bonsai tree"
            }
          }
        }
      }
    ]
  }
}
--------------------------------------------------

<1> The query with id `1` matches our document.

[float]
==== Parameters

The following parameters are required when percolating a document:

[horizontal]
`field`:: The field of type `percolator` and that holds the indexed queries. This is a required parameter.
`document_type`:: The type / mapping of the document being percolated. This is a required parameter.
`document`:: The source of the document being percolated.

Instead of specifying a the source of the document being percolated, the source can also be retrieved from an already
stored document. The `percolate` query will then internally execute a get request to fetch that document.

In that case the `document` parameter can be substituted with the following parameters:

[horizontal]
`index`:: The index the document resides in. This is a required parameter.
`type`:: The type of the document to fetch. This is a required parameter.
`id`:: The id of the document to fetch. This is a required parameter.
`routing`:: Optionally, routing to be used to fetch document to percolate.
`preference`:: Optionally, preference to be used to fetch document to percolate.
`version`:: Optionally, the expected version of the document to be fetched.

[float]
==== Percolating an Existing Document

In order to percolate a newly indexed document, the `percolate` query can be used. Based on the response
from an index request, the `_id` and other meta information can be used to immediately percolate the newly added
document.

[float]
===== Example

Based on the previous example.

Index the document we want to percolate:

[source,js]
--------------------------------------------------
PUT /my-index/message/1
{
  "message" : "A new bonsai tree in the office"
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
Index response:

[source,js]
--------------------------------------------------
{
  "_index": "my-index",
  "_type": "message",
  "_id": "1",
  "_version": 1,
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "created": true
}
--------------------------------------------------

Percolating an existing document, using the index response as basis to build to new search request:

[source,js]
--------------------------------------------------
GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field": "query",
            "document_type" : "doctype",
            "index" : "my-index",
            "type" : "message",
            "id" : "1",
            "version" : 1 <1>
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

<1> The version is optional, but useful in certain cases. We can then ensure that we are try to percolate
the document we just have indexed. A change may be made after we have indexed, and if that is the
case the then the search request would fail with a version conflict error.

The search response returned is identical as in the previous example.

[float]
==== Percolate query and highlighting

The `percolate` query is handled in a special way when it comes to highlighting. The queries hits are used
to highlight the document that is provided in the `percolate` query. Whereas with regular highlighting the query in
the search request is used to highlight the hits.

[float]
===== Example

This example is based on the mapping of the first example.

Save a query:

[source,js]
--------------------------------------------------
PUT /my-index/queries/1
{
    "query" : {
        "match" : {
            "message" : "brown fox"
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

Save another query:

[source,js]
--------------------------------------------------
PUT /my-index/queries/2
{
    "query" : {
        "match" : {
            "message" : "lazy dog"
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

Execute a search request with the `percolate` query and highlighting enabled:

[source,js]
--------------------------------------------------
GET /my-index/_search
{
    "query" : {
        "percolate" : {
            "field": "query",
            "document_type" : "doctype",
            "document" : {
                "message" : "The quick brown fox jumps over the lazy dog"
            }
        }
    },
    "highlight": {
      "fields": {
        "message": {}
      }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

This will yield the following response.

[source,js]
--------------------------------------------------
{
  "took": 83,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 2,
    "max_score": 0.5446649,
    "hits": [
      {
        "_index": "my-index",
        "_type": "queries",
        "_id": "2",
        "_score": 0.5446649,
        "_source": {
          "query": {
            "match": {
              "message": "lazy dog"
            }
          }
        },
        "highlight": {
          "message": [
            "The quick brown fox jumps over the <em>lazy</em> <em>dog</em>" <1>
          ]
        }
      },
      {
        "_index": "my-index",
        "_type": "queries",
        "_id": "1",
        "_score": 0.5446649,
        "_source": {
          "query": {
            "match": {
              "message": "brown fox"
            }
          }
        },
        "highlight": {
          "message": [
            "The quick <em>brown</em> <em>fox</em> jumps over the lazy dog" <1>
          ]
        }
      }
    ]
  }
}
--------------------------------------------------

Instead of the query in the search request highlighting the percolator hits, the percolator queries are highlighting
the document defined in the `percolate` query.

[float]
==== How it Works Under the Hood

When indexing a document into an index that has the <<percolator,percolator field type>> mapping configured, the query
part of the documents gets parsed into a Lucene query and is kept in memory until that percolator document is removed.
So, all the active percolator queries are kept in memory.

At search time, the document specified in the request gets parsed into a Lucene document and is stored in a in-memory
temporary Lucene index. This in-memory index can just hold this one document and it is optimized for that. Then all the queries
that are registered to the index that the search request is targeted for, are going to be executed on this single document
in-memory index. This happens on each shard the search request needs to execute.

By using `routing` or additional queries the amount of percolator queries that need to be executed can be reduced and thus
the time the search API needs to run can be decreased.