opensearch-docs-cn/_query-dsl/aggregations/bucket/nested.md

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default	Nested	Bucket aggregations	Aggregations	140

Nested aggregations

The nested aggregation lets you aggregate on fields inside a nested object. The nested type is a specialized version of the object data type that allows arrays of objects to be indexed in a way that they can be queried independently of each other

With the object type, all the data is stored in the same document, so matches for a search can go across sub documents. For example, imagine a logs index with pages mapped as an object datatype:

PUT logs/_doc/0
{
  "response": "200",
  "pages": [
    {
      "page": "landing",
      "load_time": 200
    },
    {
      "page": "blog",
      "load_time": 500
    }
  ]
}

OpenSearch merges all sub-properties of the entity relations that looks something like this:

{
  "logs": {
    "pages": ["landing", "blog"],
    "load_time": ["200", "500"]
  }
}

So, if you wanted to search this index with pages=landing and load_time=500, this document matches the criteria even though the load_time value for landing is 200.

If you want to make sure such cross-object matches don’t happen, map the field as a nested type:

PUT logs
{
  "mappings": {
    "properties": {
      "pages": {
        "type": "nested",
        "properties": {
          "page": { "type": "text" },
          "load_time": { "type": "double" }
        }
      }
    }
  }
}

Nested documents allow you to index the same JSON document but will keep your pages in separate Lucene documents, making only searches like pages=landing and load_time=200 return the expected result. Internally, nested objects index each object in the array as a separate hidden document, meaning that each nested object can be queried independently of the others.

You have to specify a nested path relative to parent that contains the nested documents:

GET logs/_search
{
  "query": {
    "match": { "response": "200" }
  },
  "aggs": {
    "pages": {
      "nested": {
        "path": "pages"
      },
      "aggs": {
        "min_load_time": { "min": { "field": "pages.load_time" } }
      }
    }
  }
}

Example response

...
"aggregations" : {
  "pages" : {
    "doc_count" : 2,
    "min_price" : {
      "value" : 200.0
    }
  }
 }
}