361 lines
9.3 KiB
Plaintext
361 lines
9.3 KiB
Plaintext
[[search-request-sort]]
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=== Sort
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Allows to add one or more sort on specific fields. Each sort can be
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reversed as well. The sort is defined on a per field level, with special
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field name for `_score` to sort by score.
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{ "post_date" : {"order" : "asc"}},
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"user",
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{ "name" : "desc" },
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{ "age" : "desc" },
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"_score"
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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==== Sort Values
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The sort values for each document returned are also returned as part of
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the response.
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==== Sort Order
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The `order` option can have the following values:
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[horizontal]
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`asc`:: Sort in ascending order
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`desc`:: Sort in descending order
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The order defaults to `desc` when sorting on the `_score`, and defaults
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to `asc` when sorting on anything else.
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==== Sort mode option
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Elasticsearch supports sorting by array or multi-valued fields. The `mode` option
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controls what array value is picked for sorting the document it belongs
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to. The `mode` option can have the following values:
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[horizontal]
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`min`:: Pick the lowest value.
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`max`:: Pick the highest value.
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`sum`:: Use the sum of all values as sort value. Only applicable for
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number based array fields.
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`avg`:: Use the average of all values as sort value. Only applicable
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for number based array fields.
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===== Sort mode example usage
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In the example below the field price has multiple prices per document.
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In this case the result hits will be sort by price ascending based on
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the average price per document.
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[source,js]
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--------------------------------------------------
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curl -XPOST 'localhost:9200/_search' -d '{
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"query" : {
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...
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},
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"sort" : [
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{"price" : {"order" : "asc", "mode" : "avg"}}
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]
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}'
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--------------------------------------------------
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==== Sorting within nested objects.
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Elasticsearch also supports sorting by
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fields that are inside one or more nested objects. The sorting by nested
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field support has the following parameters on top of the already
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existing sort options:
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`nested_path`::
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Defines the on what nested object to sort. The actual
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sort field must be a direct field inside this nested object. The default
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is to use the most immediate inherited nested object from the sort
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field.
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`nested_filter`::
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A filter the inner objects inside the nested path
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should match with in order for its field values to be taken into account
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by sorting. Common case is to repeat the query / filter inside the
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nested filter or query. By default no `nested_filter` is active.
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===== Nested sorting example
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In the below example `offer` is a field of type `nested`. Because
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`offer` is the closest inherited nested field, it is picked as
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`nested_path`. Only the inner objects that have color blue will
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participate in sorting.
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[source,js]
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--------------------------------------------------
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curl -XPOST 'localhost:9200/_search' -d '{
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"query" : {
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...
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},
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"sort" : [
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{
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"offer.price" : {
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"mode" : "avg",
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"order" : "asc",
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"nested_filter" : {
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"term" : { "offer.color" : "blue" }
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}
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}
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}
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]
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}'
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--------------------------------------------------
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Nested sorting is also supported when sorting by
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scripts and sorting by geo distance.
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==== Missing Values
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The `missing` parameter specifies how docs which are missing
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the field should be treated: The `missing` value can be
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set to `_last`, `_first`, or a custom value (that
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will be used for missing docs as the sort value). For example:
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{ "price" : {"missing" : "_last"} },
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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NOTE: If a nested inner object doesn't match with
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the `nested_filter` then a missing value is used.
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==== Ignoring Unmapped Fields
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By default, the search request will fail if there is no mapping
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associated with a field. The `unmapped_type` option allows to ignore
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fields that have no mapping and not sort by them. The value of this
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parameter is used to determine what sort values to emit. Here is an
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example of how it can be used:
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{ "price" : {"unmapped_type" : "long"} },
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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If any of the indices that are queried doesn't have a mapping for `price`
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then Elasticsearch will handle it as if there was a mapping of type
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`long`, with all documents in this index having no value for this field.
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==== Geo Distance Sorting
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Allow to sort by `_geo_distance`. Here is an example:
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{
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"_geo_distance" : {
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"pin.location" : [-70, 40],
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"order" : "asc",
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"unit" : "km",
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"mode" : "min",
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"distance_type" : "sloppy_arc"
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}
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}
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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`distance_type`::
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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).
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Note: the geo distance sorting supports `sort_mode` options: `min`,
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`max` and `avg`.
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The following formats are supported in providing the coordinates:
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===== Lat Lon as Properties
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{
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"_geo_distance" : {
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"pin.location" : {
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"lat" : 40,
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"lon" : -70
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},
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"order" : "asc",
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"unit" : "km"
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}
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}
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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===== Lat Lon as String
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Format in `lat,lon`.
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{
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"_geo_distance" : {
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"pin.location" : "-70,40",
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"order" : "asc",
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"unit" : "km"
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}
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}
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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===== Geohash
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{
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"_geo_distance" : {
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"pin.location" : "drm3btev3e86",
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"order" : "asc",
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"unit" : "km"
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}
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}
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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===== Lat Lon as Array
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Format in `[lon, lat]`, note, the order of lon/lat here in order to
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conform with http://geojson.org/[GeoJSON].
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[source,js]
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--------------------------------------------------
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{
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"sort" : [
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{
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"_geo_distance" : {
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"pin.location" : [-70, 40],
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"order" : "asc",
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"unit" : "km"
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}
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}
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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==== Multiple reference points
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Multiple geo points can be passed as an array containing any `geo_point` format, for example
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[source,js]
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--------------------------------------------------
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"pin.location" : [[-70, 40], [-71, 42]]
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"pin.location" : [{"lat": -70, "lon": 40}, {"lat": -71, "lon": 42}]
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--------------------------------------------------
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and so forth.
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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.
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==== Script Based Sorting
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Allow to sort based on custom scripts, here is an example:
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[source,js]
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--------------------------------------------------
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{
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"query" : {
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....
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},
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"sort" : {
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"_script" : {
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"script" : "doc['field_name'].value * factor",
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"type" : "number",
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"params" : {
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"factor" : 1.1
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},
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"order" : "asc"
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}
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}
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}
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--------------------------------------------------
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Note, it is recommended, for single custom based script based sorting,
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to use `function_score` query instead as sorting based on score is faster.
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==== Track Scores
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When sorting on a field, scores are not computed. By setting
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`track_scores` to true, scores will still be computed and tracked.
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[source,js]
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--------------------------------------------------
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{
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"track_scores": true,
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"sort" : [
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{ "post_date" : {"reverse" : true} },
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{ "name" : "desc" },
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{ "age" : "desc" }
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],
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"query" : {
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"term" : { "user" : "kimchy" }
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}
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}
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--------------------------------------------------
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==== Memory Considerations
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When sorting, the relevant sorted field values are loaded into memory.
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This means that per shard, there should be enough memory to contain
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them. For string based types, the field sorted on should not be analyzed
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/ tokenized. For numeric types, if possible, it is recommended to
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explicitly set the type to six_hun types (like `short`, `integer` and
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`float`).
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