[[search-request-sort]] === Sort 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. [source,js] -------------------------------------------------- { "sort" : [ { "post_date" : {"order" : "asc"}}, "user", { "name" : "desc" }, { "age" : "desc" }, "_score" ], "query" : { "term" : { "user" : "kimchy" } } } -------------------------------------------------- ==== Sort Values The sort values for each document returned are also returned as part of the response. ==== 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. ===== Sort mode example usage 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. [source,js] -------------------------------------------------- curl -XPOST 'localhost:9200/_search' -d '{ "query" : { ... }, "sort" : [ {"price" : {"order" : "asc", "mode" : "avg"}} ] }' -------------------------------------------------- ==== 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 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 example 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. [source,js] -------------------------------------------------- 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 Values 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: [source,js] -------------------------------------------------- { "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 Fields coming[1.4.0] 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: [source,js] -------------------------------------------------- { "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 Sorting Allow to sort by `_geo_distance`. Here is an example: [source,js] -------------------------------------------------- { "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` (slighly 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 Properties [source,js] -------------------------------------------------- { "sort" : [ { "_geo_distance" : { "pin.location" : { "lat" : 40, "lon" : -70 }, "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } } -------------------------------------------------- ===== Lat Lon as String Format in `lat,lon`. [source,js] -------------------------------------------------- { "sort" : [ { "_geo_distance" : { "pin.location" : "-70,40", "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } } -------------------------------------------------- ===== Geohash [source,js] -------------------------------------------------- { "sort" : [ { "_geo_distance" : { "pin.location" : "drm3btev3e86", "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } } -------------------------------------------------- ===== 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,js] -------------------------------------------------- { "sort" : [ { "_geo_distance" : { "pin.location" : [-70, 40], "order" : "asc", "unit" : "km" } } ], "query" : { "term" : { "user" : "kimchy" } } } -------------------------------------------------- ==== Multiple reference points added[1.4.0] Multiple geo points can be passed as an array containing any `geo_point` format, for example [source,js] -------------------------------------------------- "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 Sorting Allow to sort based on custom scripts, here is an example: [source,js] -------------------------------------------------- { "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 Scores When sorting on a field, scores are not computed. By setting `track_scores` to true, scores will still be computed and tracked. [source,js] -------------------------------------------------- { "track_scores": true, "sort" : [ { "post_date" : {"reverse" : true} }, { "name" : "desc" }, { "age" : "desc" } ], "query" : { "term" : { "user" : "kimchy" } } } -------------------------------------------------- ==== 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 six_hun types (like `short`, `integer` and `float`).