[[search-aggregations-pipeline-sum-bucket-aggregation]] === Sum Bucket Aggregation 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. ==== 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 <> for more details) |Required | |`gap_policy` |The policy to apply when gaps are found in the data (see <> 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/]