[[search-aggregations-pipeline-sum-bucket-aggregation]]
=== 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:

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

[[sum-bucket-params]]
.`sum_bucket` Parameters
[options="header"]
|===
|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 <<gap-policy>> 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:

[source,console]
--------------------------------------------------
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>
      }
    }
  }
}
--------------------------------------------------
// TEST[setup:sales]

<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:

[source,console-result]
--------------------------------------------------
{
   "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
      }
   }
}
--------------------------------------------------
// TESTRESPONSE[s/"took": 11/"took": $body.took/]
// TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
// TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
