[[search-aggregations-reducer-sum-bucket-aggregation]]
=== Sum Bucket Aggregation

A sibling reducer 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.

==== Syntax

A `sum_bucket` aggregation looks like this in isolation:

[source,js]
--------------------------------------------------
{
    "sum_bucket": {
        "buckets_path": "the_sum"
    }
}
--------------------------------------------------

.`sum_bucket` Parameters
|===
|Parameter Name |Description |Required |Default Value
|`buckets_path` |The path to the buckets we wish to find the sum for (see <<bucket-path-syntax>> for more
 details) |Required |
 |`gap_policy` |The policy to apply when gaps are found in the data (see <<gap-policy>> for more
 details)|Optional, defaults to `skip` ||
 |`format` |format to apply to the output value of this aggregation |Optional, defaults to `null` |
|===

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

[source,js]
--------------------------------------------------
{
    "aggs" : {
        "sales_per_month" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "month"
            },
            "aggs": {
                "sales": {
                    "sum": {
                        "field": "price"
                    }
                }
            }
        },
        "sum_monthly_sales": {
            "sum_bucket": {
                "buckets_paths": "sales_per_month>sales" <1>
            }
        }
    }
}
--------------------------------------------------
<1> `bucket_paths` 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:

[source,js]
--------------------------------------------------
{
   "aggregations": {
      "sales_per_month": {
         "buckets": [
            {
               "key_as_string": "2015/01/01 00:00:00",
               "key": 1420070400000,
               "doc_count": 3,
               "sales": {
                  "value": 550
               }
            },
            {
               "key_as_string": "2015/02/01 00:00:00",
               "key": 1422748800000,
               "doc_count": 2,
               "sales": {
                  "value": 60
               }
            },
            {
               "key_as_string": "2015/03/01 00:00:00",
               "key": 1425168000000,
               "doc_count": 2,
               "sales": {
                  "value": 375
               }
            }
         ]
      },
      "sum_monthly_sales": {
          "value": 985
      }
   }
}
--------------------------------------------------