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Sum bucket aggregation

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

Syntax

A sum_bucket aggregation looks like this in isolation:

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

Parameter Name Description Required Default Value
buckets_path The path to the buckets we wish to find the sum for (see buckets_path Syntax for more details) Required
gap_policy The policy to apply when gaps are found in the data (see Dealing with gaps in the data for more details) Optional skip
format DecimalFormat pattern for theoutput value. If specified, the formatted value is returned in the aggregation’svalue_as_string property. 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",
        "calendar_interval": "month"
      },
      "aggs": {
        "sales": {
          "sum": {
            "field": "price"
          }
        }
      }
    },
    "sum_monthly_sales": {
      "sum_bucket": {
        "buckets_path": "sales_per_month>sales" 1
      }
    }
  }
}
  1. 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
      }
   }
}