Retrieve selected fields from a search

By default, each hit in the search response includes the document _source, which is the entire JSON object that was provided when indexing the document. To retrieve specific fields in the search response, you can use the fields parameter:

POST my-index-000001/_search
{
  "query": {
    "match": {
      "message": "foo"
    }
  },
  "fields": ["user.id", "@timestamp"],
  "_source": false
}

The fields parameter consults both a document’s _source and the index mappings to load and return values. Because it makes use of the mappings, fields has some advantages over referencing the _source directly: it accepts multi-fields and field aliases, and also formats field values like dates in a consistent way.

A document’s _source is stored as a single field in Lucene. So the whole _source object must be loaded and parsed even if only a small number of fields are requested. To avoid this limitation, you can try another option for loading fields:

You can also use the script_field parameter to transform field values in the response using a script.

You can find more detailed information on each of these methods in the following sections:

The fields parameter allows for retrieving a list of document fields in the search response. It consults both the document _source and the index mappings to return each value in a standardized way that matches its mapping type. By default, date fields are formatted according to the date format parameter in their mappings. You can also use the fields parameter to retrieve runtime field values.

The following search request uses the fields parameter to retrieve values for the user.id field, all fields starting with http.response., and the @timestamp field:

POST my-index-000001/_search
{
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  },
  "fields": [
    "user.id",
    "http.response.*", 
    {
      "field": "@timestamp",
      "format": "epoch_millis" 
    }
  ],
  "_source": false
}

The values are returned as a flat list in the fields section in each hit:

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my-index-000001",
        "_id" : "0",
        "_score" : 1.0,
        "_type" : "_doc",
        "fields" : {
          "user.id" : [
            "kimchy"
          ],
          "@timestamp" : [
            "4098435132000"
          ],
          "http.response.bytes": [
            1070000
          ],
          "http.response.status_code": [
            200
          ]
        }
      }
    ]
  }
}

Only leaf fields are returned — fields does not allow for fetching entire objects.

The fields parameter handles field types like field aliases and constant_keyword whose values aren’t always present in the _source. Other mapping options are also respected, including ignore_above, ignore_malformed and null_value.

By default, the fields parameter returns only values of mapped fields. However, Elasticsearch allows storing fields in _source that are unmapped, for example by setting Dynamic field mapping to false or by using an object field with enabled: false, thereby disabling parsing and indexing of its content.

Fields in such an object can be retrieved from _source using the include_unmapped option in the fields section:

PUT my-index-000001
{
  "mappings": {
    "enabled": false 
  }
}

PUT my-index-000001/_doc/1?refresh=true
{
  "user_id": "kimchy",
  "session_data": {
     "object": {
       "some_field": "some_value"
     }
   }
}

POST my-index-000001/_search
{
  "fields": [
    "user_id",
    {
      "field": "session_data.object.*",
      "include_unmapped" : true 
    }
  ],
  "_source": false
}

The response will contain fields results under the session_data.object.* path even if the fields are unmapped, but will not contain user_id since it is unmapped but the include_unmapped flag hasn’t been set to true for that field pattern.

{
  "took" : 2,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 1,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "my-index-000001",
        "_id" : "1",
        "_score" : 1.0,
        "_type" : "_doc",
        "fields" : {
          "session_data.object.some_field": [
            "some_value"
          ]
        }
      }
    ]
  }
}

You can use the docvalue_fields parameter to return doc values for one or more fields in the search response.

Doc values store the same values as the _source but in an on-disk, column-based structure that’s optimized for sorting and aggregations. Since each field is stored separately, Elasticsearch only reads the field values that were requested and can avoid loading the whole document _source.

Doc values are stored for supported fields by default. However, doc values are not supported for text or text_annotated fields.

The following search request uses the docvalue_fields parameter to retrieve doc values for the user.id field, all fields starting with http.response., and the @timestamp field:

GET my-index-000001/_search
{
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  },
  "docvalue_fields": [
    "user.id",
    "http.response.*", 
    {
      "field": "date",
      "format": "epoch_millis" 
    }
  ]
}

It’s also possible to store an individual field’s values by using the store mapping option. You can use the stored_fields parameter to include these stored values in the search response.

Allows to selectively load specific stored fields for each document represented by a search hit.

GET /_search
{
  "stored_fields" : ["user", "postDate"],
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}

* can be used to load all stored fields from the document.

An empty array will cause only the _id and _type for each hit to be returned, for example:

GET /_search
{
  "stored_fields" : [],
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}

If the requested fields are not stored (store mapping set to false), they will be ignored.

Stored field values fetched from the document itself are always returned as an array. On the contrary, metadata fields like _routing are never returned as an array.

Also only leaf fields can be returned via the stored_fields option. If an object field is specified, it will be ignored.

To disable the stored fields (and metadata fields) entirely use: _none_:

GET /_search
{
  "stored_fields": "_none_",
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}

You can use the _source parameter to select what fields of the source are returned. This is called source filtering.

The following search API request sets the _source request body parameter to false. The document source is not included in the response.

GET /_search
{
  "_source": false,
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  }
}

To return only a subset of source fields, specify a wildcard (*) pattern in the _source parameter. The following search API request returns the source for only the obj field and its properties.

GET /_search
{
  "_source": "obj.*",
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  }
}

You can also specify an array of wildcard patterns in the _source field. The following search API request returns the source for only the obj1 and obj2 fields and their properties.

GET /_search
{
  "_source": [ "obj1.*", "obj2.*" ],
  "query": {
    "match": {
      "user.id": "kimchy"
    }
  }
}

For finer control, you can specify an object containing arrays of includes and excludes patterns in the _source parameter.

If the includes property is specified, only source fields that match one of its patterns are returned. You can exclude fields from this subset using the excludes property.

If the includes property is not specified, the entire document source is returned, excluding any fields that match a pattern in the excludes property.

The following search API request returns the source for only the obj1 and obj2 fields and their properties, excluding any child description fields.

GET /_search
{
  "_source": {
    "includes": [ "obj1.*", "obj2.*" ],
    "excludes": [ "*.description" ]
  },
  "query": {
    "term": {
      "user.id": "kimchy"
    }
  }
}

You can use the script_fields parameter to retrieve a script evaluation (based on different fields) for each hit. For example:

GET /_search
{
  "query": {
    "match_all": {}
  },
  "script_fields": {
    "test1": {
      "script": {
        "lang": "painless",
        "source": "doc['price'].value * 2"
      }
    },
    "test2": {
      "script": {
        "lang": "painless",
        "source": "doc['price'].value * params.factor",
        "params": {
          "factor": 2.0
        }
      }
    }
  }
}

Script fields can work on fields that are not stored (price in the above case), and allow to return custom values to be returned (the evaluated value of the script).

Script fields can also access the actual _source document and extract specific elements to be returned from it by using params['_source']. Here is an example:

GET /_search
    {
        "query" : {
            "match_all": {}
        },
        "script_fields" : {
            "test1" : {
                "script" : "params['_source']['message']"
            }
        }
    }

Note the _source keyword here to navigate the json-like model.

It’s important to understand the difference between doc['my_field'].value and params['_source']['my_field']. The first, using the doc keyword, will cause the terms for that field to be loaded to memory (cached), which will result in faster execution, but more memory consumption. Also, the doc[...] notation only allows for simple valued fields (you can’t return a json object from it) and makes sense only for non-analyzed or single term based fields. However, using doc is still the recommended way to access values from the document, if at all possible, because _source must be loaded and parsed every time it’s used. Using _source is very slow.