Stats bucket aggregation
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.
Syntax
A stats_bucket aggregation looks like this in isolation:
{
"stats_bucket": {
"buckets_path": "the_sum"
}
} Table 80. 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 |
|
| DecimalFormat pattern for the output value. If specified, the formatted value is returned in the aggregation’s | Optional |
|
The following snippet calculates the stats for monthly sales:
resp = client.search(
index="sales",
size=0,
aggs={
"sales_per_month": {
"date_histogram": {
"field": "date",
"calendar_interval": "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
}
}
},
"stats_monthly_sales": {
"stats_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'
}
}
}
},
stats_monthly_sales: {
stats_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",
},
},
},
},
stats_monthly_sales: {
stats_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"
}
}
}
},
"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
}
}
}
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https://www.elastic.co/guide/en/elasticsearch/reference/8.17/search-aggregations-pipeline-stats-bucket-aggregation.html