Sortedit

Allows to add one or more sort 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.

{
    "sort" : [
        { "post_date" : {"order" : "asc"}},
        "user",
        { "name" : "desc" },
        { "age" : "desc" },
        "_score"
    ],
    "query" : {
        "term" : { "user" : "kimchy" }
    }
}

Sort Valuesedit

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

Sort Orderedit

The order option can have the following values:

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.

Sort mode optionedit

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:

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.

Sort mode example usageedit

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

curl -XPOST 'localhost:9200/_search' -d '{
   "query" : {
    ...
   },
   "sort" : [
      {"price" : {"order" : "asc", "mode" : "avg"}}
   ]
}'

Sorting within nested objects.edit

Elasticsearch also supports sorting by fields that are inside one or more nested objects. The sorting by nested field support has the following parameters on top of the already existing sort options:

nested_path
Defines the on what nested object to sort. The actual sort field must be a direct field inside this nested object. The default is to use the most immediate inherited nested object from the sort field.
nested_filter
A filter 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.

Nested sorting exampleedit

In the below example offer is a field of type nested. Because offer is the closest inherited nested field, it is picked as nested_path. Only the inner objects that have color blue will participate in sorting.

curl -XPOST 'localhost:9200/_search' -d '{
   "query" : {
    ...
   },
   "sort" : [
       {
          "offer.price" : {
             "mode" :  "avg",
             "order" : "asc",
             "nested_filter" : {
                "term" : { "offer.color" : "blue" }
             }
          }
       }
    ]
}'

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

Missing Valuesedit

The missing parameter specifies how docs which are missing the 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). For example:

{
    "sort" : [
        { "price" : {"missing" : "_last"} },
    ],
    "query" : {
        "term" : { "user" : "kimchy" }
    }
}
Note

If a nested inner object doesn’t match with the nested_filter then a missing value is used.

Ignoring Unmapped Fieldsedit

Before 1.4.0 there was the ignore_unmapped boolean parameter, which was not enough information to decide on the sort values to emit, and didn’t work for cross-index search. It is still supported but users are encouraged to migrate to the new unmapped_type instead.

By default, the search request will fail if there is no mapping associated with a field. The unmapped_type option allows 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:

{
    "sort" : [
        { "price" : {"unmapped_type" : "long"} },
    ],
    "query" : {
        "term" : { "user" : "kimchy" }
    }
}

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.

Geo Distance Sortingedit

Allow to sort by _geo_distance. Here is an example:

{
    "sort" : [
        {
            "_geo_distance" : {
                "pin.location" : [-70, 40],
                "order" : "asc",
                "unit" : "km",
                "mode" : "min",
                "distance_type" : "sloppy_arc"
            }
        }
    ],
    "query" : {
        "term" : { "user" : "kimchy" }
    }
}
distance_type
How to compute the distance. Can either be sloppy_arc (default), arc (slightly more precise but significantly slower) or plane (faster, but inaccurate on long distances and close to the poles).

Note: the geo distance sorting supports sort_mode options: min, max and avg.

The following formats are supported in providing the coordinates:

Lat Lon as Propertiesedit

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

Lat Lon as Stringedit

Format in lat,lon.

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

Geohashedit

{
    "sort" : [
        {
            "_geo_distance" : {
                "pin.location" : "drm3btev3e86",
                "order" : "asc",
                "unit" : "km"
            }
        }
    ],
    "query" : {
        "term" : { "user" : "kimchy" }
    }
}

Lat Lon as Arrayedit

Format in [lon, lat], note, the order of lon/lat here in order to conform with GeoJSON.

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

Multiple reference pointsedit

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

"pin.location" : [[-70, 40], [-71, 42]]
"pin.location" : [{"lat": -70, "lon": 40}, {"lat": -71, "lon": 42}]

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.

Script Based Sortingedit

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

{
    "query" : {
        ....
    },
    "sort" : {
        "_script" : {
            "script" : "doc['field_name'].value * factor",
            "type" : "number",
            "params" : {
                "factor" : 1.1
            },
            "order" : "asc"
        }
    }
}

Note, it is recommended, for single custom based script based sorting, to use function_score query instead as sorting based on score is faster.

Track Scoresedit

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

{
    "track_scores": true,
    "sort" : [
        { "post_date" : {"reverse" : true} },
        { "name" : "desc" },
        { "age" : "desc" }
    ],
    "query" : {
        "term" : { "user" : "kimchy" }
    }
}

Memory Considerationsedit

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).