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Elasticsearch Guide [2.4] » Aggregations » Pipeline Aggregations » Avg Bucket Aggregation
« Pipeline Aggregations Derivative Aggregation »

Avg 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 the (mean) average value of a specified metric in a sibling aggregation. The specified metric must be numeric and the sibling aggregation must be a multi-bucket aggregation.

Syntaxedit

An avg_bucket aggregation looks like this in isolation:

{
    "avg_bucket": {
        "buckets_path": "the_sum"
    }
}

Table 1. avg_bucket Parameters

Parameter Name Description Required Default Value

buckets_path

The path to the buckets we wish to find the average for (see buckets_path Syntax for more details)

Required

gap_policy

The policy to apply when gaps are found in the data (see Dealing with gaps in the data for more details)

Optional, defaults to skip

format

format to apply to the output value of this aggregation

Optional, defaults to null

The following snippet calculates the average of the total monthly sales:

{
    "aggs" : {
        "sales_per_month" : {
            "date_histogram" : {
                "field" : "date",
                "interval" : "month"
            },
            "aggs": {
                "sales": {
                    "sum": {
                        "field": "price"
                    }
                }
            }
        },
        "avg_monthly_sales": {
            "avg_bucket": {
                "buckets_path": "sales_per_month>sales" 
            }
        }
    }
}

buckets_path instructs this avg_bucket aggregation that we want the (mean) average value of the sales aggregation in the sales_per_month date histogram.

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
               }
            }
         ]
      },
      "avg_monthly_sales": {
          "value": 328.33333333333333
      }
   }
}
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