elasticsearch/docs/reference/search/explain.asciidoc

[[search-explain]]
== Explain API

The explain api computes a score explanation for a query and a specific
document. This can give useful feedback whether a document matches or
didn't match a specific query.

The `index` and `type` parameters expect a single index and a single
type respectively.

[float]
=== Usage

Full query example:

[source,js]
--------------------------------------------------
GET /twitter/tweet/0/_explain
{
      "query" : {
        "match" : { "message" : "elasticsearch" }
      }
}
--------------------------------------------------
// CONSOLE
// TEST[setup:twitter]

This will yield the following result:

[source,js]
--------------------------------------------------
{
   "_index": "twitter",
   "_type": "tweet",
   "_id": "0",
   "matched": true,
   "explanation": {
      "value": 1.55077,
      "description": "sum of:",
      "details": [
         {
            "value": 1.55077,
            "description": "weight(message:elasticsearch in 0) [PerFieldSimilarity], result of:",
            "details": [
               {
                  "value": 1.55077,
                  "description": "score(doc=0,freq=1.0 = termFreq=1.0\n), product of:",
                  "details": [
                     {
                        "value": 1.3862944,
                        "description": "idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:",
                        "details": [
                           {
                              "value": 1.0,
                              "description": "docFreq",
                              "details": []
                           },
                           {
                              "value": 5.0,
                              "description": "docCount",
                              "details": []
                           }
                        ]
                     },
                     {
                        "value": 1.1186441,
                        "description": "tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:",
                        "details": [
                           {
                              "value": 1.0,
                              "description": "termFreq=1.0",
                              "details": []
                           },
                           {
                              "value": 1.2,
                              "description": "parameter k1",
                              "details": []
                           },
                           {
                              "value": 0.75,
                              "description": "parameter b",
                              "details": []
                           },
                           {
                              "value": 5.4,
                              "description": "avgFieldLength",
                              "details": []
                           },
                           {
                              "value": 4.0,
                              "description": "fieldLength",
                              "details": []
                           }
                        ]
                     }
                  ]
               }
            ]
         },
         {
            "value": 0.0,
            "description": "match on required clause, product of:",
            "details": [
               {
                  "value": 0.0,
                  "description": "# clause",
                  "details": []
               },
               {
                  "value": 1.0,
                  "description": "*:*, product of:",
                  "details": [
                     {
                        "value": 1.0,
                        "description": "boost",
                        "details": []
                     },
                     {
                        "value": 1.0,
                        "description": "queryNorm",
                        "details": []
                     }
                  ]
               }
            ]
         }
      ]
   }
}
--------------------------------------------------
// TESTRESPONSE

There is also a simpler way of specifying the query via the `q`
parameter. The specified `q` parameter value is then parsed as if the
`query_string` query was used. Example usage of the `q` parameter in the
explain api:

[source,js]
--------------------------------------------------
GET /twitter/tweet/0/_explain?q=message:search
--------------------------------------------------
// CONSOLE
// TEST[setup:twitter]

This will yield the same result as the previous request.

[float]
=== All parameters:

[horizontal]
`_source`::

    Set to `true` to retrieve the `_source` of the document explained. You can also
    retrieve part of the document by using `_source_include` & `_source_exclude` (see <<get-source-filtering,Get API>> for more details)

`stored_fields`::
    Allows to control which stored fields to return as part of the
    document explained.

`routing`::
    Controls the routing in the case the routing was used
    during indexing.

`parent`::
    Same effect as setting the routing parameter.

`preference`::
    Controls on which shard the explain is executed.

`source`::
    Allows the data of the request to be put in the query
    string of the url.

`q`::
    The query string (maps to the query_string query).

`df`::
    The default field to use when no field prefix is defined within
    the query. Defaults to _all field.

`analyzer`::
    The analyzer name to be used when analyzing the query
    string. Defaults to the analyzer of the _all field.

`analyze_wildcard`::
    Should wildcard and prefix queries be analyzed or
    not. Defaults to false.

`lenient`::
    If set to true will cause format based failures (like
    providing text to a numeric field) to be ignored. Defaults to false.

`default_operator`::
    The default operator to be used, can be AND or
    OR. Defaults to OR.