[[sort-search-results]]
== Sort search results

Allows you to add one or more sorts on specific fields. Each sort can be
reversed as well. The sort is defined on a per field level, with special
field name for `_score` to sort by score, and `_doc` to sort by index order.

Assuming the following index mapping:

[source,console]
--------------------------------------------------
PUT /my-index-000001
{
  "mappings": {
    "properties": {
      "post_date": { "type": "date" },
      "user": {
        "type": "keyword"
      },
      "name": {
        "type": "keyword"
      },
      "age": { "type": "integer" }
    }
  }
}
--------------------------------------------------

[source,console]
--------------------------------------------------
GET /my-index-000001/_search
{
  "sort" : [
    { "post_date" : {"order" : "asc"}},
    "user",
    { "name" : "desc" },
    { "age" : "desc" },
    "_score"
  ],
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}
--------------------------------------------------
// TEST[continued]

NOTE: `_doc` has no real use-case besides being the most efficient sort order.
So if you don't care about the order in which documents are returned, then you
should sort by `_doc`. This especially helps when <<scroll-search-results,scrolling>>.

[discrete]
=== Sort Values

The sort values for each document returned are also returned as part of
the response.

[discrete]
=== Sort Order

The `order` option can have the following values:

[horizontal]
`asc`:: Sort in ascending order
`desc`:: Sort in descending order

The order defaults to `desc` when sorting on the `_score`, and defaults
to `asc` when sorting on anything else.

[discrete]
=== Sort mode option

Elasticsearch supports sorting by array or multi-valued fields. The `mode` option
controls what array value is picked for sorting the document it belongs
to. The `mode` option can have the following values:

[horizontal]
`min`:: Pick the lowest value.
`max`:: Pick the highest value.
`sum`:: Use the sum of all values as sort value. Only applicable for
        number based array fields.
`avg`:: Use the average of all values as sort value. Only applicable
        for number based array fields.
`median`:: Use the median of all values as sort value.  Only applicable
           for number based array fields.

The default sort mode in the ascending sort order is `min` -- the lowest value
is picked. The default sort mode in the descending order is `max` --
the highest value is picked.

[discrete]
==== Sort mode example usage

In the example below the field price has multiple prices per document.
In this case the result hits will be sorted by price ascending based on
the average price per document.

[source,console]
--------------------------------------------------
PUT /my-index-000001/_doc/1?refresh
{
   "product": "chocolate",
   "price": [20, 4]
}

POST /_search
{
   "query" : {
      "term" : { "product" : "chocolate" }
   },
   "sort" : [
      {"price" : {"order" : "asc", "mode" : "avg"}}
   ]
}
--------------------------------------------------

[discrete]
=== Sorting numeric fields

For numeric fields it is also possible to cast the values from one type
to another using the `numeric_type` option.
This option accepts the following values: [`"double", "long", "date", "date_nanos"`]
and can be useful for searches across multiple data streams or indices where the sort field is mapped differently.

Consider for instance these two indices:

[source,console]
--------------------------------------------------
PUT /index_double
{
  "mappings": {
    "properties": {
      "field": { "type": "double" }
    }
  }
}
--------------------------------------------------

[source,console]
--------------------------------------------------
PUT /index_long
{
  "mappings": {
    "properties": {
      "field": { "type": "long" }
    }
  }
}
--------------------------------------------------
// TEST[continued]

Since `field` is mapped as a `double` in the first index and as a `long`
in the second index, it is not possible to use this field to sort requests
that query both indices by default. However you can force the type to one
or the other with the `numeric_type` option in order to force a specific
type for all indices:

[source,console]
--------------------------------------------------
POST /index_long,index_double/_search
{
   "sort" : [
      {
        "field" : {
            "numeric_type" : "double"
        }
      }
   ]
}
--------------------------------------------------
// TEST[continued]

In the example above, values for the `index_long` index are casted to
a double in order to be compatible with the values produced by the
`index_double` index.
It is also possible to transform a floating point field into a `long`
but note that in this case floating points are replaced by the largest
value that is less than or equal (greater than or equal if the value
is negative) to the argument and is equal to a mathematical integer.

This option can also be used to convert a `date` field that uses millisecond
resolution to a `date_nanos` field with nanosecond resolution.
Consider for instance these two indices:

[source,console]
--------------------------------------------------
PUT /index_double
{
  "mappings": {
    "properties": {
      "field": { "type": "date" }
    }
  }
}
--------------------------------------------------

[source,console]
--------------------------------------------------
PUT /index_long
{
  "mappings": {
    "properties": {
      "field": { "type": "date_nanos" }
    }
  }
}
--------------------------------------------------
// TEST[continued]

Values in these indices are stored with different resolutions so sorting on these
fields will always sort the `date` before the `date_nanos` (ascending order).
With the `numeric_type` type option it is possible to set a single resolution for
the sort, setting to `date` will convert the `date_nanos` to the millisecond resolution
while `date_nanos` will convert the values in the `date` field to the nanoseconds resolution:

[source,console]
--------------------------------------------------
POST /index_long,index_double/_search
{
   "sort" : [
      {
        "field" : {
            "numeric_type" : "date_nanos"
        }
      }
   ]
}
--------------------------------------------------
// TEST[continued]

[WARNING]
To avoid overflow, the conversion to `date_nanos` cannot be applied on dates before
1970 and after 2262 as nanoseconds are represented as longs.

[discrete]
[[nested-sorting]]
=== Sorting within nested objects.

Elasticsearch also supports sorting by
fields that are inside one or more nested objects. The sorting by nested
field support has a `nested` sort option with the following properties:

`path`::
    Defines on which nested object to sort. The actual
    sort field must be a direct field inside this nested object.
    When sorting by nested field, this field is mandatory.

`filter`::
    A filter that the inner objects inside the nested path
    should match with in order for its field values to be taken into account
    by sorting. Common case is to repeat the query / filter inside the
    nested filter or query. By default no `nested_filter` is active.
`max_children`::
    The maximum number of children to consider per root document
    when picking the sort value. Defaults to unlimited.
`nested`::
    Same as top-level `nested` but applies to another nested path within the
    current nested object.

[WARNING]
.Nested sort options before Elasticsearch 6.1
============================================

The `nested_path` and `nested_filter` options have been deprecated in
favor of the options documented above.

============================================

[discrete]
==== Nested sorting examples

In the below example `offer` is a field of type `nested`.
The nested `path` needs to be specified; otherwise, Elasticsearch doesn't know on what nested level sort values need to be captured.

[source,console]
--------------------------------------------------
POST /_search
{
   "query" : {
      "term" : { "product" : "chocolate" }
   },
   "sort" : [
       {
          "offer.price" : {
             "mode" :  "avg",
             "order" : "asc",
             "nested": {
                "path": "offer",
                "filter": {
                   "term" : { "offer.color" : "blue" }
                }
             }
          }
       }
    ]
}
--------------------------------------------------

In the below example `parent` and `child` fields are of type `nested`.
The `nested_path` needs to be specified at each level; otherwise, Elasticsearch doesn't know on what nested level sort values need to be captured.

[source,console]
--------------------------------------------------
POST /_search
{
   "query": {
      "nested": {
         "path": "parent",
         "query": {
            "bool": {
                "must": {"range": {"parent.age": {"gte": 21}}},
                "filter": {
                    "nested": {
                        "path": "parent.child",
                        "query": {"match": {"parent.child.name": "matt"}}
                    }
                }
            }
         }
      }
   },
   "sort" : [
      {
         "parent.child.age" : {
            "mode" :  "min",
            "order" : "asc",
            "nested": {
               "path": "parent",
               "filter": {
                  "range": {"parent.age": {"gte": 21}}
               },
               "nested": {
                  "path": "parent.child",
                  "filter": {
                     "match": {"parent.child.name": "matt"}
                  }
               }
            }
         }
      }
   ]
}
--------------------------------------------------

Nested sorting is also supported when sorting by
scripts and sorting by geo distance.

[discrete]
=== Missing Values

The `missing` parameter specifies how docs which are missing
the sort field should be treated: The `missing` value can be
set to `_last`, `_first`, or a custom value (that
will be used for missing docs as the sort value).
The default is `_last`.

For example:

[source,console]
--------------------------------------------------
GET /_search
{
  "sort" : [
    { "price" : {"missing" : "_last"} }
  ],
  "query" : {
    "term" : { "product" : "chocolate" }
  }
}
--------------------------------------------------

NOTE: If a nested inner object doesn't match with
the `nested_filter` then a missing value is used.

[discrete]
=== Ignoring Unmapped Fields

By default, the search request will fail if there is no mapping
associated with a field. The `unmapped_type` option allows you to ignore
fields that have no mapping and not sort by them. The value of this
parameter is used to determine what sort values to emit. Here is an
example of how it can be used:

[source,console]
--------------------------------------------------
GET /_search
{
  "sort" : [
    { "price" : {"unmapped_type" : "long"} }
  ],
  "query" : {
    "term" : { "product" : "chocolate" }
  }
}
--------------------------------------------------

If any of the indices that are queried doesn't have a mapping for `price`
then Elasticsearch will handle it as if there was a mapping of type
`long`, with all documents in this index having no value for this field.

[discrete]
[[geo-sorting]]
=== Geo Distance Sorting

Allow to sort by `_geo_distance`. Here is an example, assuming `pin.location` is a field of type `geo_point`:

[source,console]
--------------------------------------------------
GET /_search
{
  "sort" : [
    {
      "_geo_distance" : {
          "pin.location" : [-70, 40],
          "order" : "asc",
          "unit" : "km",
          "mode" : "min",
          "distance_type" : "arc",
          "ignore_unmapped": true
      }
    }
  ],
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}
--------------------------------------------------



`distance_type`::

    How to compute the distance. Can either be `arc` (default), or `plane` (faster, but inaccurate on long distances and close to the poles).

`mode`::

    What to do in case a field has several geo points. By default, the shortest
    distance is taken into account when sorting in ascending order and the
    longest distance when sorting in descending order. Supported values are
    `min`, `max`, `median` and `avg`.

`unit`::

    The unit to use when computing sort values. The default is `m` (meters).


`ignore_unmapped`::

    Indicates if the unmapped field should be treated as a missing value. Setting it to `true` is equivalent to specifying
    an `unmapped_type` in the field sort. The default is `false` (unmapped field cause the search to fail).

NOTE: geo distance sorting does not support configurable missing values: the
distance will always be considered equal to +Infinity+ when a document does not
have values for the field that is used for distance computation.

The following formats are supported in providing the coordinates:

[discrete]
==== Lat Lon as Properties

[source,console]
--------------------------------------------------
GET /_search
{
  "sort" : [
    {
      "_geo_distance" : {
        "pin.location" : {
          "lat" : 40,
          "lon" : -70
        },
        "order" : "asc",
        "unit" : "km"
      }
    }
  ],
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}
--------------------------------------------------

[discrete]
==== Lat Lon as String

Format in `lat,lon`.

[source,console]
--------------------------------------------------
GET /_search
{
  "sort": [
    {
      "_geo_distance": {
        "pin.location": "40,-70",
        "order": "asc",
        "unit": "km"
      }
    }
  ],
  "query": {
    "term": { "user": "kimchy" }
  }
}
--------------------------------------------------

[discrete]
==== Geohash

[source,console]
--------------------------------------------------
GET /_search
{
  "sort": [
    {
      "_geo_distance": {
        "pin.location": "drm3btev3e86",
        "order": "asc",
        "unit": "km"
      }
    }
  ],
  "query": {
    "term": { "user": "kimchy" }
  }
}
--------------------------------------------------

[discrete]
==== Lat Lon as Array

Format in `[lon, lat]`, note, the order of lon/lat here in order to
conform with http://geojson.org/[GeoJSON].

[source,console]
--------------------------------------------------
GET /_search
{
  "sort": [
    {
      "_geo_distance": {
        "pin.location": [ -70, 40 ],
        "order": "asc",
        "unit": "km"
      }
    }
  ],
  "query": {
    "term": { "user": "kimchy" }
  }
}
--------------------------------------------------

[discrete]
=== Multiple reference points

Multiple geo points can be passed as an array containing any `geo_point` format, for example

[source,console]
--------------------------------------------------
GET /_search
{
  "sort": [
    {
      "_geo_distance": {
        "pin.location": [ [ -70, 40 ], [ -71, 42 ] ],
        "order": "asc",
        "unit": "km"
      }
    }
  ],
  "query": {
    "term": { "user": "kimchy" }
  }
}
--------------------------------------------------

and so forth.

The final distance for a document will then be `min`/`max`/`avg` (defined via `mode`) distance of all points contained in the document to all points given in the sort request.


[discrete]
=== Script Based Sorting

Allow to sort based on custom scripts, here is an example:

[source,console]
--------------------------------------------------
GET /_search
{
  "query": {
    "term": { "user": "kimchy" }
  },
  "sort": {
    "_script": {
      "type": "number",
      "script": {
        "lang": "painless",
        "source": "doc['field_name'].value * params.factor",
        "params": {
          "factor": 1.1
        }
      },
      "order": "asc"
    }
  }
}
--------------------------------------------------

[discrete]
=== Track Scores

When sorting on a field, scores are not computed. By setting
`track_scores` to true, scores will still be computed and tracked.

[source,console]
--------------------------------------------------
GET /_search
{
  "track_scores": true,
  "sort" : [
    { "post_date" : {"order" : "desc"} },
    { "name" : "desc" },
    { "age" : "desc" }
  ],
  "query" : {
    "term" : { "user" : "kimchy" }
  }
}
--------------------------------------------------

[discrete]
=== Memory Considerations

When sorting, the relevant sorted field values are loaded into memory.
This means that per shard, there should be enough memory to contain
them. For string based types, the field sorted on should not be analyzed
/ tokenized. For numeric types, if possible, it is recommended to
explicitly set the type to narrower types (like `short`, `integer` and
`float`).
