Sum Bucket Aggregationedit

Warning

This functionality is experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.

A sibling pipeline aggregation which calculates the sum across all bucket of a specified metric in a sibling aggregation. The specified metric must be numeric and the sibling aggregation must be a multi-bucket aggregation.

Syntaxedit

A sum_bucket aggregation looks like this in isolation:

{
    "sum_bucket": {
        "buckets_path": "the_sum"
    }
}

Table 5. sum_bucket Parameters

Parameter Name

Description

Required

Default Value

buckets_path

The path to the buckets we wish to find the sum for (see the section called “buckets_path Syntaxedit” for more details)

Required

gap_policy

The policy to apply when gaps are found in the data (see the section called “Dealing with gaps in the dataedit” for more details)

Optional

skip

format

format to apply to the output value of this aggregation

Optional

null


The following snippet calculates the sum of all the total monthly sales buckets:

POST /sales/_search
{
    "size": 0,
    "aggs" : {
        "sales_per_month" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "month"
            },
            "aggs": {
                "sales": {
                    "sum": {
                        "field": "price"
                    }
                }
            }
        },
        "sum_monthly_sales": {
            "sum_bucket": {
                "buckets_path": "sales_per_month>sales" 
            }
        }
    }
}

buckets_path instructs this sum_bucket aggregation that we want the sum of the sales aggregation in the sales_per_month date histogram.

And the following may be the response:

{
   "took": 11,
   "timed_out": false,
   "_shards": ...,
   "hits": ...,
   "aggregations": {
      "sales_per_month": {
         "buckets": [
            {
               "key_as_string": "2015/01/01 00:00:00",
               "key": 1420070400000,
               "doc_count": 3,
               "sales": {
                  "value": 550.0
               }
            },
            {
               "key_as_string": "2015/02/01 00:00:00",
               "key": 1422748800000,
               "doc_count": 2,
               "sales": {
                  "value": 60.0
               }
            },
            {
               "key_as_string": "2015/03/01 00:00:00",
               "key": 1425168000000,
               "doc_count": 2,
               "sales": {
                  "value": 375.0
               }
            }
         ]
      },
      "sum_monthly_sales": {
          "value": 985.0
      }
   }
}