A sibling pipeline aggregation which calculates a variety of stats 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.
A stats_bucket aggregation looks like this in isolation:
{
"stats_bucket": {
"buckets_path": "the_sum"
}
}Table 12. stats_bucket Parameters
| Parameter Name | Description | Required | Default Value |
|---|---|---|---|
| The path to the buckets we wish to calculate stats 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 |
|
| format to apply to the output value of this aggregation | Optional |
|
The following snippet calculates the stats for monthly sales:
POST /sales/_search
{
"size": 0,
"aggs" : {
"sales_per_month" : {
"date_histogram" : {
"field" : "date",
"interval" : "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
}
}
},
"stats_monthly_sales": {
"stats_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
}
}
]
},
"stats_monthly_sales": {
"count": 3,
"min": 60.0,
"max": 550.0,
"avg": 328.3333333333333,
"sum": 985.0
}
}
}