OpenSearch/docs/reference/aggregations/pipeline/extended-stats-bucket-aggre...

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[[search-aggregations-pipeline-extended-stats-bucket-aggregation]]
=== Extended 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.
This aggregation provides a few more statistics (sum of squares, standard deviation, etc) compared to the `stats_bucket` aggregation.
==== Syntax
A `extended_stats_bucket` aggregation looks like this in isolation:
[source,js]
--------------------------------------------------
{
"extended_stats_bucket": {
"buckets_path": "the_sum"
}
}
--------------------------------------------------
// NOTCONSOLE
.`extended_stats_bucket` Parameters
|===
|Parameter Name |Description |Required |Default Value
|`buckets_path` |The path to the buckets we wish to calculate stats for (see <<buckets-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 | `skip`
|`format` |format to apply to the output value of this aggregation |Optional | `null`
|`sigma` |The number of standard deviations above/below the mean to display |Optional | 2
|===
The following snippet calculates the extended stats for monthly `sales` bucket:
[source,js]
--------------------------------------------------
POST /sales/_search
{
"size": 0,
"aggs" : {
"sales_per_month" : {
"date_histogram" : {
"field" : "date",
"interval" : "month"
},
"aggs": {
"sales": {
"sum": {
"field": "price"
}
}
}
},
"stats_monthly_sales": {
"extended_stats_bucket": {
"buckets_path": "sales_per_month>sales" <1>
}
}
}
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]
<1> `bucket_paths` instructs this `extended_stats_bucket` aggregation that we want the calculate stats for the `sales` aggregation in the
`sales_per_month` date histogram.
And the following may be the response:
[source,js]
--------------------------------------------------
{
"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,
"sum_of_squares": 446725.0,
"variance": 41105.55555555556,
"std_deviation": 202.74505063146563,
"std_deviation_bounds": {
"upper": 733.8234345962646,
"lower": -77.15676792959795
}
}
}
}
--------------------------------------------------
// TESTRESPONSE[s/"took": 11/"took": $body.took/]
// TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
// TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]