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[DOCS] Add multi-level nested query example to nested query docs (#46986
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jrodewig authored Sep 25, 2019
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173 changes: 165 additions & 8 deletions docs/reference/query-dsl/nested-query.asciidoc
Original file line number Diff line number Diff line change
Expand Up @@ -19,11 +19,11 @@ the root parent document.
To use the `nested` query, your index must include a <<nested,nested>> field
mapping. For example:

[source,js]
[source,console]
----
PUT /my_index
{
"mappings": {
"mappings" : {
"properties" : {
"obj1" : {
"type" : "nested"
Expand All @@ -33,17 +33,15 @@ PUT /my_index
}
----
// CONSOLE
// TESTSETUP

[[nested-query-ex-query]]
===== Example query

[source,js]
[source,console]
----
GET /my_index/_search
{
"query": {
"query": {
"nested" : {
"path" : "obj1",
"query" : {
Expand All @@ -59,7 +57,7 @@ GET /my_index/_search
}
}
----
// CONSOLE
// TEST[continued]

[[nested-top-level-params]]
==== Top-level parameters for `nested`
Expand All @@ -80,6 +78,8 @@ such as `obj1.name`.
Multi-level nesting is automatically supported, and detected, resulting in an
inner nested query to automatically match the relevant nesting level, rather
than root, if it exists within another nested query.

See <<multi-level-nested-query-ex>> for an example.
--

`score_mode`::
Expand Down Expand Up @@ -116,4 +116,161 @@ If `false`, {es} returns an error if the `path` is an unmapped field.

You can use this parameter to query multiple indices that may not contain the
field `path`.
--
--

[[nested-query-notes]]
==== Notes

[[multi-level-nested-query-ex]]
===== Multi-level nested queries

To see how multi-level nested queries work,
first you need an index that has nested fields.
The following request defines mappings for the `drivers` index
with nested `make` and `model` fields.

[source,console]
----
PUT /drivers
{
"mappings" : {
"properties" : {
"driver" : {
"type" : "nested",
"properties" : {
"last_name" : {
"type" : "text"
},
"vehicle" : {
"type" : "nested",
"properties" : {
"make" : {
"type" : "text"
},
"model" : {
"type" : "text"
}
}
}
}
}
}
}
}
----

Next, index some documents to the `drivers` index.

[source,console]
----
PUT /drivers/_doc/1
{
"driver" : {
"last_name" : "McQueen",
"vehicle" : [
{
"make" : "Powell Motors",
"model" : "Canyonero"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
PUT /drivers/_doc/2?refresh
{
"driver" : {
"last_name" : "Hudson",
"vehicle" : [
{
"make" : "Mifune",
"model" : "Mach Five"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
----
// TEST[continued]

You can now use a multi-level nested query
to match documents based on the `make` and `model` fields.

[source,console]
----
GET /drivers/_search
{
"query" : {
"nested" : {
"path" : "driver",
"query" : {
"nested" : {
"path" : "driver.vehicle",
"query" : {
"bool" : {
"must" : [
{ "match" : { "driver.vehicle.make" : "Powell Motors" } },
{ "match" : { "driver.vehicle.model" : "Canyonero" } }
]
}
}
}
}
}
}
}
----
// TEST[continued]

The search request returns the following response:

[source,console-result]
----
{
"took" : 5,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 3.7349272,
"hits" : [
{
"_index" : "drivers",
"_type" : "_doc",
"_id" : "1",
"_score" : 3.7349272,
"_source" : {
"driver" : {
"last_name" : "McQueen",
"vehicle" : [
{
"make" : "Powell Motors",
"model" : "Canyonero"
},
{
"make" : "Miller-Meteor",
"model" : "Ecto-1"
}
]
}
}
}
]
}
}
----
// TESTRESPONSE[s/"took" : 5/"took": $body.took/]

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