Sum bucket aggregation
editSum bucket aggregation
editA 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
editA sum_bucket
aggregation looks like this in isolation:
{ "sum_bucket": { "buckets_path": "the_sum" } }
Table 80. sum_bucket
Parameters
Parameter Name | Description | Required | Default Value |
---|---|---|---|
|
The path to the buckets we wish to find the sum for (see |
Required |
|
|
The policy to apply when gaps are found in the data (see Dealing with gaps in the data for more details) |
Optional |
|
|
DecimalFormat pattern for the
output value. If specified, the formatted value is returned in the aggregation’s
|
Optional |
|
The following snippet calculates the sum of all the total monthly sales
buckets:
resp = client.search( index="sales", 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" } } }, ) print(resp)
response = client.search( index: 'sales', body: { size: 0, aggregations: { sales_per_month: { date_histogram: { field: 'date', calendar_interval: 'month' }, aggregations: { sales: { sum: { field: 'price' } } } }, sum_monthly_sales: { sum_bucket: { buckets_path: 'sales_per_month>sales' } } } } ) puts response
const response = await client.search({ index: "sales", 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", }, }, }, }); console.log(response);
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" } } } }
|
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 } } }