Extended Stats Bucket Aggregationedit
This functionality is experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.
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 multibucket aggregation.
This aggregation provides a few more statistics (sum of squares, standard deviation, etc) compared to the stats_bucket
aggregation.
Syntaxedit
A extended_stats_bucket
aggregation looks like this in isolation:
{ "extended_stats_bucket": { "buckets_path": "the_sum" } }
Table 7. extended_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 number of standard deviations above/below the mean to display  Optional  2 
The following snippet calculates the sum of all the total monthly sales
buckets:
{ "aggs" : { "sales_per_month" : { "date_histogram" : { "field" : "date", "interval" : "month" }, "aggs": { "sales": { "sum": { "field": "price" } } } }, "stats_monthly_sales": { "extended_stats_bucket": { "buckets_paths": "sales_per_month>sales" } } } }

And the following may be the response:
{ "aggregations": { "sales_per_month": { "buckets": [ { "key_as_string": "2015/01/01 00:00:00", "key": 1420070400000, "doc_count": 3, "sales": { "value": 550 } }, { "key_as_string": "2015/02/01 00:00:00", "key": 1422748800000, "doc_count": 2, "sales": { "value": 60 } }, { "key_as_string": "2015/03/01 00:00:00", "key": 1425168000000, "doc_count": 2, "sales": { "value": 375 } } ] }, "stats_monthly_sales": { "count": 3, "min": 60, "max": 550, "avg": 328.333333333, "sum": 985, "sum_of_squares": 446725, "variance": 41105.5555556, "std_deviation": 117.054909559, "std_deviation_bounds": { "upper": 562.443152451, "lower": 94.2235142151 } } } }