OpenSearch/docs/reference/aggregations/pipeline/extended-stats-bucket-aggregation.asciidoc

[[search-aggregations-pipeline-extended-stats-bucket-aggregation]]
=== Extended Stats Bucket Aggregation

experimental[]

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/]