2013-08-28 19:24:34 -04:00
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[[query-dsl-nested-query]]
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2019-07-18 10:18:11 -04:00
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=== Nested query
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++++
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<titleabbrev>Nested</titleabbrev>
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++++
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2013-08-28 19:24:34 -04:00
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2019-07-10 08:50:54 -04:00
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Wraps another query to search <<nested,nested>> fields.
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The `nested` query searches nested field objects as if they were indexed as
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separate documents. If an object matches the search, the `nested` query returns
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the root parent document.
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[[nested-query-ex-request]]
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==== Example request
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[[nested-query-index-setup]]
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===== Index setup
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To use the `nested` query, your index must include a <<nested,nested>> field
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mapping. For example:
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2013-08-28 19:24:34 -04:00
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2019-09-09 12:35:50 -04:00
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[source,console]
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2019-07-10 08:50:54 -04:00
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----
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2019-01-22 09:13:52 -05:00
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PUT /my_index
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{
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"mappings" : {
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"properties" : {
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"obj1" : {
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"type" : "nested"
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2013-08-28 19:24:34 -04:00
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}
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}
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}
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}
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2016-05-24 12:15:52 -04:00
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2019-07-10 08:50:54 -04:00
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----
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2013-08-28 19:24:34 -04:00
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2019-07-10 08:50:54 -04:00
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[[nested-query-ex-query]]
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===== Example query
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2013-08-28 19:24:34 -04:00
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2019-09-09 12:35:50 -04:00
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[source,console]
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2019-07-10 08:50:54 -04:00
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----
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GET /my_index/_search
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{
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"query": {
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"nested" : {
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"path" : "obj1",
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"query" : {
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"bool" : {
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"must" : [
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{ "match" : {"obj1.name" : "blue"} },
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{ "range" : {"obj1.count" : {"gt" : 5}} }
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]
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}
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},
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"score_mode" : "avg"
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}
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}
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}
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2019-07-10 08:50:54 -04:00
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----
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2019-09-25 02:01:37 -04:00
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// TEST[continued]
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2019-07-10 08:50:54 -04:00
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[[nested-top-level-params]]
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==== Top-level parameters for `nested`
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`path`::
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(Required, string) Path to the nested object you wish to search.
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`query`::
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+
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--
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(Required, query object) Query you wish to run on nested objects in the `path`.
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If an object matches the search, the `nested` query returns the root parent
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document.
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You can search nested fields using dot notation that includes the complete path,
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such as `obj1.name`.
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Multi-level nesting is automatically supported, and detected, resulting in an
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inner nested query to automatically match the relevant nesting level, rather
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than root, if it exists within another nested query.
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See <<multi-level-nested-query-ex>> for an example.
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--
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`score_mode`::
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+
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--
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(Optional, string) Indicates how scores for matching child objects affect the
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root parent document's <<relevance-scores,relevance score>>. Valid values
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are:
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`avg` (Default)::
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Use the mean relevance score of all matching child objects.
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`max`::
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Uses the highest relevance score of all matching child objects.
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`min`::
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Uses the lowest relevance score of all matching child objects.
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`none`::
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Do not use the relevance scores of matching child objects. The query assigns
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parent documents a score of `0`.
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`sum`::
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Add together the relevance scores of all matching child objects.
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--
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`ignore_unmapped`::
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+
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--
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(Optional, boolean) Indicates whether to ignore an unmapped `path` and not
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return any documents instead of an error. Defaults to `false`.
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If `false`, {es} returns an error if the `path` is an unmapped field.
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You can use this parameter to query multiple indices that may not contain the
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field `path`.
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2019-09-25 02:01:37 -04:00
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--
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[[nested-query-notes]]
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==== Notes
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[[multi-level-nested-query-ex]]
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===== Multi-level nested queries
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To see how multi-level nested queries work,
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first you need an index that has nested fields.
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The following request defines mappings for the `drivers` index
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with nested `make` and `model` fields.
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[source,console]
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----
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PUT /drivers
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{
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"mappings" : {
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"properties" : {
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"driver" : {
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"type" : "nested",
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"properties" : {
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"last_name" : {
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"type" : "text"
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},
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"vehicle" : {
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"type" : "nested",
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"properties" : {
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"make" : {
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"type" : "text"
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},
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"model" : {
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"type" : "text"
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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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}
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}
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----
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Next, index some documents to the `drivers` index.
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[source,console]
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----
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PUT /drivers/_doc/1
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{
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"driver" : {
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"last_name" : "McQueen",
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"vehicle" : [
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{
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"make" : "Powell Motors",
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"model" : "Canyonero"
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},
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{
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"make" : "Miller-Meteor",
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"model" : "Ecto-1"
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}
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]
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}
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}
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PUT /drivers/_doc/2?refresh
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{
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"driver" : {
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"last_name" : "Hudson",
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"vehicle" : [
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{
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"make" : "Mifune",
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"model" : "Mach Five"
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},
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{
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"make" : "Miller-Meteor",
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"model" : "Ecto-1"
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}
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]
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}
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}
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----
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// TEST[continued]
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You can now use a multi-level nested query
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to match documents based on the `make` and `model` fields.
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[source,console]
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----
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GET /drivers/_search
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{
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"query" : {
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"nested" : {
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"path" : "driver",
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"query" : {
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"nested" : {
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"path" : "driver.vehicle",
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"query" : {
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"bool" : {
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"must" : [
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{ "match" : { "driver.vehicle.make" : "Powell Motors" } },
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{ "match" : { "driver.vehicle.model" : "Canyonero" } }
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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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}
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}
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----
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// TEST[continued]
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The search request returns the following response:
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[source,console-result]
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----
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{
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"took" : 5,
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"timed_out" : false,
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"_shards" : {
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"total" : 1,
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"successful" : 1,
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"skipped" : 0,
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"failed" : 0
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},
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"hits" : {
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"total" : {
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"value" : 1,
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"relation" : "eq"
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},
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"max_score" : 3.7349272,
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"hits" : [
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{
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"_index" : "drivers",
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"_type" : "_doc",
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"_id" : "1",
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"_score" : 3.7349272,
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"_source" : {
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"driver" : {
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"last_name" : "McQueen",
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"vehicle" : [
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{
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"make" : "Powell Motors",
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"model" : "Canyonero"
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},
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{
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"make" : "Miller-Meteor",
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"model" : "Ecto-1"
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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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}
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}
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----
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// TESTRESPONSE[s/"took" : 5/"took": $body.took/]
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