[[search-aggregations-metrics-top-hits-aggregation]]
=== Top hits Aggregation

A `top_hits` metric aggregator keeps track of the most relevant document being aggregated. This aggregator is intended
to be used as a sub aggregator, so that the top matching documents can be aggregated per bucket.

The `top_hits` aggregator can effectively be used to group result sets by certain fields via a bucket aggregator.
One or more bucket aggregators determines by which properties a result set get sliced into.

==== Options

* `from` - The offset from the first result you want to fetch.
* `size` - The maximum number of top matching hits to return per bucket. By default the top three matching hits are returned.
* `sort` - How the top matching hits should be sorted. By default the hits are sorted by the score of the main query.

==== Supported per hit features

The top_hits aggregation returns regular search hits, because of this many per hit features can be supported:

* <<search-request-highlighting,Highlighting>>
* <<search-request-explain,Explain>>
* <<search-request-named-queries-and-filters,Named filters and queries>>
* <<search-request-source-filtering,Source filtering>>
* <<search-request-stored-fields,Stored fields>>
* <<search-request-script-fields,Script fields>>
* <<search-request-docvalue-fields,Doc value fields>>
* <<search-request-version,Include versions>>

==== Example

In the following example we group the questions by tag and per tag we show the last active question. For each question
only the title field is being included in the source.

[source,js]
--------------------------------------------------
POST /sales/_search?size=0
{
    "aggs": {
        "top_tags": {
            "terms": {
                "field": "type",
                "size": 3
            },
            "aggs": {
                "top_sales_hits": {
                    "top_hits": {
                        "sort": [
                            {
                                "date": {
                                    "order": "desc"
                                }
                            }
                        ],
                        "_source": {
                            "includes": [ "date", "price" ]
                        },
                        "size" : 1
                    }
                }
            }
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]

Possible response:

[source,js]
--------------------------------------------------
{
  ...
  "aggregations": {
    "top_tags": {
       "doc_count_error_upper_bound": 0,
       "sum_other_doc_count": 0,
       "buckets": [
          {
             "key": "hat",
             "doc_count": 3,
             "top_sales_hits": {
                "hits": {
                   "total": 3,
                   "max_score": null,
                   "hits": [
                      {
                         "_index": "sales",
                         "_type": "sale",
                         "_id": "AVnNBmauCQpcRyxw6ChK",
                         "_source": {
                            "date": "2015/03/01 00:00:00",
                            "price": 200
                         },
                         "sort": [
                            1425168000000
                         ],
                         "_score": null
                      }
                   ]
                }
             }
          },
          {
             "key": "t-shirt",
             "doc_count": 3,
             "top_sales_hits": {
                "hits": {
                   "total": 3,
                   "max_score": null,
                   "hits": [
                      {
                         "_index": "sales",
                         "_type": "sale",
                         "_id": "AVnNBmauCQpcRyxw6ChL",
                         "_source": {
                            "date": "2015/03/01 00:00:00",
                            "price": 175
                         },
                         "sort": [
                            1425168000000
                         ],
                         "_score": null
                      }
                   ]
                }
             }
          },
          {
             "key": "bag",
             "doc_count": 1,
             "top_sales_hits": {
                "hits": {
                   "total": 1,
                   "max_score": null,
                   "hits": [
                      {
                         "_index": "sales",
                         "_type": "sale",
                         "_id": "AVnNBmatCQpcRyxw6ChH",
                         "_source": {
                            "date": "2015/01/01 00:00:00",
                            "price": 150
                         },
                         "sort": [
                            1420070400000
                         ],
                         "_score": null
                      }
                   ]
                }
             }
          }
       ]
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
// TESTRESPONSE[s/AVnNBmauCQpcRyxw6ChK/$body.aggregations.top_tags.buckets.0.top_sales_hits.hits.hits.0._id/]
// TESTRESPONSE[s/AVnNBmauCQpcRyxw6ChL/$body.aggregations.top_tags.buckets.1.top_sales_hits.hits.hits.0._id/]
// TESTRESPONSE[s/AVnNBmatCQpcRyxw6ChH/$body.aggregations.top_tags.buckets.2.top_sales_hits.hits.hits.0._id/]


==== Field collapse example

Field collapsing or result grouping is a feature that logically groups a result set into groups and per group returns
top documents. The ordering of the groups is determined by the relevancy of the first document in a group. In
Elasticsearch this can be implemented via a bucket aggregator that wraps a `top_hits` aggregator as sub-aggregator.

In the example below we search across crawled webpages. For each webpage we store the body and the domain the webpage
belong to. By defining a `terms` aggregator on the `domain` field we group the result set of webpages by domain. The
`top_hits` aggregator is then defined as sub-aggregator, so that the top matching hits are collected per bucket.

Also a `max` aggregator is defined which is used by the `terms` aggregator's order feature the return the buckets by
relevancy order of the most relevant document in a bucket.

[source,js]
--------------------------------------------------
POST /sales/_search
{
  "query": {
    "match": {
      "body": "elections"
    }
  },
  "aggs": {
    "top_sites": {
      "terms": {
        "field": "domain",
        "order": {
          "top_hit": "desc"
        }
      },
      "aggs": {
        "top_tags_hits": {
          "top_hits": {}
        },
        "top_hit" : {
          "max": {
            "script": {
              "source": "_score"
            }
          }
        }
      }
    }
  }
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]

At the moment the `max` (or `min`) aggregator is needed to make sure the buckets from the `terms` aggregator are
ordered according to the score of the most relevant webpage per domain. Unfortunately the `top_hits` aggregator
can't be used in the `order` option of the `terms` aggregator yet.

==== top_hits support in a nested or reverse_nested aggregator

If the `top_hits` aggregator is wrapped in a `nested` or `reverse_nested` aggregator then nested hits are being returned.
Nested hits are in a sense hidden mini documents that are part of regular document where in the mapping a nested field type
has been configured. The `top_hits` aggregator has the ability to un-hide these documents if it is wrapped in a `nested`
or `reverse_nested` aggregator. Read more about nested in the <<nested,nested type mapping>>.

If nested type has been configured a single document is actually indexed as multiple Lucene documents and they share
the same id. In order to determine the identity of a nested hit there is more needed than just the id, so that is why
nested hits also include their nested identity. The nested identity is kept under the `_nested` field in the search hit
and includes the array field and the offset in the array field the nested hit belongs to. The offset is zero based.

Let's see how it works with a real sample. Considering the following mapping:

[source,js]
--------------------------------------------------
PUT /sales
{
    "mappings": {
        "product" : {
            "properties" : {
                "tags" : { "type" : "keyword" },
                "comments" : { <1>
                    "type" : "nested",
                    "properties" : {
                        "username" : { "type" : "keyword" },
                        "comment" : { "type" : "text" }
                    }
                }
            }
        }
    }
}
--------------------------------------------------
// CONSOLE
<1> The `comments` is an array that holds nested documents under the `product` object.

And some documents:

[source,js]
--------------------------------------------------
PUT /sales/product/1?refresh
{
    "tags": ["car", "auto"],
    "comments": [
        {"username": "baddriver007", "comment": "This car could have better brakes"},
        {"username": "dr_who", "comment": "Where's the autopilot? Can't find it"},
        {"username": "ilovemotorbikes", "comment": "This car has two extra wheels"}
    ]
}
--------------------------------------------------
// CONSOLE
// TEST[continued]

It's now possible to execute the following `top_hits` aggregation (wrapped in a `nested` aggregation):

[source,js]
--------------------------------------------------
POST /sales/_search
{
    "query": {
        "term": { "tags": "car" }
    },
    "aggs": {
        "by_sale": {
            "nested" : {
                "path" : "comments"
            },
            "aggs": {
                "by_user": {
                    "terms": {
                        "field": "comments.username",
                        "size": 1
                    },
                    "aggs": {
                        "by_nested": {
                            "top_hits":{}
                        }
                    }
                }
            }
        }
    }
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
// TEST[s/_search/_search\?filter_path=aggregations.by_sale.by_user.buckets/]

Top hits response snippet with a nested hit, which resides in the first slot of array field `comments`:

[source,js]
--------------------------------------------------
{
  ...
  "aggregations": {
    "by_sale": {
      "by_user": {
        "buckets": [
          {
            "key": "baddriver007",
            "doc_count": 1,
            "by_nested": {
              "hits": {
                "total": 1,
                "max_score": 0.2876821,
                "hits": [
                  {
                    "_nested": {
                      "field": "comments",  <1>
                      "offset": 0 <2>
                    },
                    "_score": 0.2876821,
                    "_source": {
                      "comments": {
                        "comment": "This car could have better brakes", <3>
                        "username": "baddriver007"
                      }
                    }
                  }
                ]
              }
            }
          }
          ...
        ]
      }
    }
  }
}
--------------------------------------------------
// TESTRESPONSE[s/\.\.\.//]
<2> Name of the array field containing the nested hit
<3> Position if the nested hit in the containing array
<4> Source of the nested hit

If `_source` is requested then just the part of the source of the nested object is returned, not the entire source of the document.
Also stored fields on the *nested* inner object level are accessible via `top_hits` aggregator residing in a `nested` or `reverse_nested` aggregator.

Only nested hits will have a `_nested` field in the hit, non nested (regular) hits will not have a `_nested` field.

The information in `_nested` can also be used to parse the original source somewhere else if `_source` isn't enabled.

If there are multiple levels of nested object types defined in mappings then the `_nested` information can also be hierarchical
in order to express the identity of nested hits that are two layers deep or more.

In the example below a nested hit resides in the first slot of the field `nested_grand_child_field` which then resides in
the second slow of the `nested_child_field` field:

[source,js]
--------------------------------------------------
...
"hits": {
 "total": 2565,
 "max_score": 1,
 "hits": [
   {
     "_index": "a",
     "_type": "b",
     "_id": "1",
     "_score": 1,
     "_nested" : {
       "field" : "nested_child_field",
       "offset" : 1,
       "_nested" : {
         "field" : "nested_grand_child_field",
         "offset" : 0
       }
     }
     "_source": ...
   },
   ...
 ]
}
...
--------------------------------------------------
// NOTCONSOLE