OpenSearch/docs/reference/aggregations/pipeline/sum-bucket-aggregation.asci...

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[[search-aggregations-pipeline-sum-bucket-aggregation]]
=== Sum Bucket Aggregation
coming[2.0.0]
experimental[]
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"
}
}
--------------------------------------------------
.`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
}
}
}
--------------------------------------------------