Nested Aggregations

In the same way as we need to use the special nested query to gain access to nested objects at search time, the dedicated nested aggregation allows us to aggregate fields in nested objects:

GET /my_index/blogpost/_search?search_type=count
{
  "aggs": {
    "comments": { 
      "nested": {
        "path": "comments"
      },
      "aggs": {
        "by_month": {
          "date_histogram": { 
            "field":    "comments.date",
            "interval": "month",
            "format":   "yyyy-MM"
          },
          "aggs": {
            "avg_stars": {
              "avg": { 
                "field": "comments.stars"
              }
            }
          }
        }
      }
    }
  }
}

The nested aggregation “steps down” into the nested comments object.

Comments are bucketed into months based on the comments.date field.

The average number of stars is calculated for each bucket.

The results show that aggregation has happened at the nested document level:

...
"aggregations": {
  "comments": {
     "doc_count": 4, 
     "by_month": {
        "buckets": [
           {
              "key_as_string": "2014-09",
              "key": 1409529600000,
              "doc_count": 1, 
              "avg_stars": {
                 "value": 4
              }
           },
           {
              "key_as_string": "2014-10",
              "key": 1412121600000,
              "doc_count": 3, 
              "avg_stars": {
                 "value": 2.6666666666666665
              }
           }
        ]
     }
  }
}
...

There are a total of four comments: one in September and three in October.

reverse_nested Aggregation

A nested aggregation can access only the fields within the nested document. It can’t see fields in the root document or in a different nested document. However, we can step out of the nested scope back into the parent with a reverse_nested aggregation.

For instance, we can find out which tags our commenters are interested in, based on the age of the commenter. The comment.age is a nested field, while the tags are in the root document:

GET /my_index/blogpost/_search?search_type=count
{
  "aggs": {
    "comments": {
      "nested": { 
        "path": "comments"
      },
      "aggs": {
        "age_group": {
          "histogram": { 
            "field":    "comments.age",
            "interval": 10
          },
          "aggs": {
            "blogposts": {
              "reverse_nested": {}, 
              "aggs": {
                "tags": {
                  "terms": { 
                    "field": "tags"
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

The nested agg steps down into the comments object.

The histogram agg groups on the comments.age field, in buckets of 10 years.

The reverse_nested agg steps back up to the root document.

The terms agg counts popular terms per age group of the commenter.

The abbreviated results show us the following:

..
"aggregations": {
  "comments": {
     "doc_count": 4, 
     "age_group": {
        "buckets": [
           {
              "key": 20, 
              "doc_count": 2, 
              "blogposts": {
                 "doc_count": 2, 
                 "tags": {
                    "doc_count_error_upper_bound": 0,
                    "buckets": [ 
                       { "key": "shares",   "doc_count": 2 },
                       { "key": "cash",     "doc_count": 1 },
                       { "key": "equities", "doc_count": 1 }
                    ]
                 }
              }
           },
...

There are four comments.

There are two comments by commenters between the ages of 20 and 30.

Two blog posts are associated with those comments.

The popular tags in those blog posts are shares, cash, and equities.

When to Use Nested Objects

Nested objects are useful when there is one main entity, like our blogpost, with a limited number of closely related but less important entities, such as comments. It is useful to be able to find blog posts based on the content of the comments, and the nested query and filter provide for fast query-time joins.

The disadvantages of the nested model are as follows:

  • To add, change, or delete a nested document, the whole document must be reindexed. This becomes more costly the more nested documents there are.
  • Search requests return the whole document, not just the matching nested documents. Although there are plans afoot to support returning the best -matching nested documents with the root document, this is not yet supported.

Sometimes you need a complete separation between the main document and its associated entities. This separation is provided by the parent-child relationship.