[[search-aggregations-pipeline-cumulative-sum-aggregation]] === Cumulative Sum Aggregation A parent pipeline aggregation which calculates the cumulative sum of a specified metric in a parent histogram (or date_histogram) aggregation. The specified metric must be numeric and the enclosing histogram must have `min_doc_count` set to `0` (default for `histogram` aggregations). ==== Syntax A `cumulative_sum` aggregation looks like this in isolation: [source,js] -------------------------------------------------- { "cumulative_sum": { "buckets_path": "the_sum" } } -------------------------------------------------- .`cumulative_sum` Parameters |=== |Parameter Name |Description |Required |Default Value |`buckets_path` |The path to the buckets we wish to find the cumulative sum for (see <> for more details) |Required | |`format` |format to apply to the output value of this aggregation |Optional, defaults to `null` | |=== The following snippet calculates the cumulative sum of the total monthly `sales`: [source,js] -------------------------------------------------- { "aggs" : { "sales_per_month" : { "date_histogram" : { "field" : "date", "interval" : "month" }, "aggs": { "sales": { "sum": { "field": "price" } }, "cumulative_sales": { "cumulative_sum": { "buckets_paths": "sales" <1> } } } } } } -------------------------------------------------- <1> `bucket_paths` instructs this cumulative sum aggregation to use the output of the `sales` aggregation for the cumulative sum 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 }, "cumulative_sales": { "value": 550 } }, { "key_as_string": "2015/02/01 00:00:00", "key": 1422748800000, "doc_count": 2, "sales": { "value": 60 }, "cumulative_sales": { "value": 610 } }, { "key_as_string": "2015/03/01 00:00:00", "key": 1425168000000, "doc_count": 2, "sales": { "value": 375 }, "cumulative_sales": { "value": 985 } } ] } } } --------------------------------------------------