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.
A sum_bucket aggregation looks like this in isolation:
{
"sum_bucket": {
"buckets_path": "the_sum"
}
}
| 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 Dealing with gaps in the data for more details) | Optional | skip |
format |
DecimalFormat pattern for theoutput value. If specified, the formatted value is returned in the aggregation’svalue_as_string property. |
Optional | null |
The following snippet calculates the sum of all the total monthly sales buckets:
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
}
}
}
}
buckets_pathinstructs this sum_bucket aggregation that we want the sum of thesalesaggregation in thesales_per_monthdate histogram.
And the following may be the response:
{
"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
}
}
}