OpenSearch/docs/reference/aggregations/bucket/parent-aggregation.asciidoc

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[[search-aggregations-bucket-parent-aggregation]]
=== Parent Aggregation
A special single bucket aggregation that selects parent documents that have the specified type, as defined in a <<parent-join,`join` field>>.
This aggregation has a single option:
* `type` - The child type that should be selected.
For example, let's say we have an index of questions and answers. The answer type has the following `join` field in the mapping:
[source,js]
--------------------------------------------------
PUT parent_example
{
"mappings": {
"_doc": {
"properties": {
"join": {
"type": "join",
"relations": {
"question": "answer"
}
}
}
}
}
}
--------------------------------------------------
// CONSOLE
The `question` document contain a tag field and the `answer` documents contain an owner field. With the `parent`
aggregation the owner buckets can be mapped to the tag buckets in a single request even though the two fields exist in
two different kinds of documents.
An example of a question document:
[source,js]
--------------------------------------------------
PUT parent_example/_doc/1
{
"join": {
"name": "question"
},
"body": "<p>I have Windows 2003 server and i bought a new Windows 2008 server...",
"title": "Whats the best way to file transfer my site from server to a newer one?",
"tags": [
"windows-server-2003",
"windows-server-2008",
"file-transfer"
]
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
Examples of `answer` documents:
[source,js]
--------------------------------------------------
PUT parent_example/_doc/2?routing=1
{
"join": {
"name": "answer",
"parent": "1"
},
"owner": {
"location": "Norfolk, United Kingdom",
"display_name": "Sam",
"id": 48
},
"body": "<p>Unfortunately you're pretty much limited to FTP...",
"creation_date": "2009-05-04T13:45:37.030"
}
PUT parent_example/_doc/3?routing=1&refresh
{
"join": {
"name": "answer",
"parent": "1"
},
"owner": {
"location": "Norfolk, United Kingdom",
"display_name": "Troll",
"id": 49
},
"body": "<p>Use Linux...",
"creation_date": "2009-05-05T13:45:37.030"
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
The following request can be built that connects the two together:
[source,js]
--------------------------------------------------
POST parent_example/_search?size=0
{
"aggs": {
"top-names": {
"terms": {
"field": "owner.display_name.keyword",
"size": 10
},
"aggs": {
"to-questions": {
"parent": {
"type" : "answer" <1>
},
"aggs": {
"top-tags": {
"terms": {
"field": "tags.keyword",
"size": 10
}
}
}
}
}
}
}
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
<1> The `type` points to type / mapping with the name `answer`.
The above example returns the top answer owners and per owner the top question tags.
Possible response:
[source,js]
--------------------------------------------------
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total" : {
"value": 3,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"top-names": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "Sam",
"doc_count": 1, <1>
"to-questions": {
"doc_count": 1, <2>
"top-tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "file-transfer",
"doc_count": 1
},
{
"key": "windows-server-2003",
"doc_count": 1
},
{
"key": "windows-server-2008",
"doc_count": 1
}
]
}
}
},
{
"key": "Troll",
"doc_count": 1,
"to-questions": {
"doc_count": 1,
"top-tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "file-transfer",
"doc_count": 1
},
{
"key": "windows-server-2003",
"doc_count": 1
},
{
"key": "windows-server-2008",
"doc_count": 1
}
]
}
}
}
]
}
}
}
--------------------------------------------------
// TESTRESPONSE[s/"took": 9/"took": $body.took/]
<1> The number of answer documents with the tag `Sam`, `Troll`, etc.
<2> The number of question documents that are related to answer documents with the tag `Sam`, `Troll`, etc.