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[DOCS] Add multi-level example to nested query docs #46986

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Sep 25, 2019
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[DOCS] Add multi-level example to nested query docs #46986

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de5db5f
[DOCS] Add multi-level example to nested query docs
jrodewig Sep 23, 2019
9e33d8d
Relocate mapping note
jrodewig Sep 24, 2019
eb51564
Relocate mapping note
jrodewig Sep 24, 2019
e3c6f4c
Reword search request sentence
jrodewig Sep 24, 2019
40e4c5c
Reword search request sentence
jrodewig Sep 24, 2019
5179a36
Reword search request sentence
jrodewig Sep 24, 2019
0eb74e5
Rework example
jrodewig Sep 24, 2019
2dedd58
Adjust wording for example updates
jrodewig Sep 24, 2019
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124 changes: 120 additions & 4 deletions docs/reference/query-dsl/nested-query.asciidoc
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ mapping. For example:
----
PUT /my_index
{
"mappings": {
"mappings" : {
"properties" : {
"obj1" : {
"type" : "nested"
Expand All @@ -33,7 +33,6 @@ PUT /my_index
}

----
// TESTSETUP

[[nested-query-ex-query]]
===== Example query
Expand All @@ -42,7 +41,7 @@ PUT /my_index
----
GET /my_index/_search
{
"query": {
"query": {
"nested" : {
"path" : "obj1",
"query" : {
Expand All @@ -58,6 +57,7 @@ GET /my_index/_search
}
}
----
// TEST[continued]

[[nested-top-level-params]]
==== Top-level parameters for `nested`
Expand All @@ -78,6 +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 @@ -114,4 +116,118 @@ 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

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[[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 the `model` field nested under `driver -> vehicle -> model`:

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

Next, index a document to the `drivers` index.

[source,console]
----
PUT /drivers/_doc/1?refresh
{
"driver" : {
"vehicle" : {
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I think in order to demonstrate why nested field & query are needed here a more complex
example should be shown here. The document should contain multiple drivers and models and
two match queries on two different model fields. Otherwise an mapping with regular object fields
and just match queries would work too.

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Thanks for your feedback @martijnvg.

I added some more detail to the example with 0eb74e5 and 2dedd58.

This should make the example a bit more realistic and add two match queries.

"model" : "Canyonero"
}
}
}
----
// TEST[continued]

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

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

The search request returns the following response:

[source,console-result]
----
{
"took" : 75,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 0.2876821,
"hits" : [
{
"_index" : "drivers",
"_id" : "1",
"_score" : 0.2876821,
"_source" : {
"driver" : {
"vehicle" : {
"model" : "Canyonero"
}
}
},
}
]
}
}
----
// TESTRESPONSE[s/"took" : 75/"took": $body.took/]