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Bucket script aggregation

A parent pipeline aggregation which executes a script which can perform per bucket computations on specified metrics in the parent multi-bucket aggregation. The specified metric must be numeric and the script must return a numeric value.

A bucket_script aggregation looks like this in isolation:

{
  "bucket_script": {
    "buckets_path": {
      "my_var1": "the_sum",                     1
      "my_var2": "the_value_count"
    },
    "script": "params.my_var1 / params.my_var2"
  }
}
  1. Here, my_var1 is the name of the variable for this buckets path to use in the script, the_sum is the path to the metrics to use for that variable.

Parameter Name Description Required Default Value
script The script to run for this aggregation. The script can be inline, file or indexed. (see Scriptingfor more details) Required
buckets_path A map of script variables and their associated path to the buckets we wish to use for the variable(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 skip
format DecimalFormat pattern for theoutput value. If specified, the formatted value is returned in the aggregation’svalue_as_string property Optional null

The following snippet calculates the ratio percentage of t-shirt sales compared to total sales each month:

 POST /sales/_search {
  "size": 0,
  "aggs": {
    "sales_per_month": {
      "date_histogram": {
        "field": "date",
        "calendar_interval": "month"
      },
      "aggs": {
        "total_sales": {
          "sum": {
            "field": "price"
          }
        },
        "t-shirts": {
          "filter": {
            "term": {
              "type": "t-shirt"
            }
          },
          "aggs": {
            "sales": {
              "sum": {
                "field": "price"
              }
            }
          }
        },
        "t-shirt-percentage": {
          "bucket_script": {
            "buckets_path": {
              "tShirtSales": "t-shirts>sales",
              "totalSales": "total_sales"
            },
            "script": "params.tShirtSales / params.totalSales * 100"
          }
        }
      }
    }
  }
}

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,
               "total_sales": {
                   "value": 550.0
               },
               "t-shirts": {
                   "doc_count": 1,
                   "sales": {
                       "value": 200.0
                   }
               },
               "t-shirt-percentage": {
                   "value": 36.36363636363637
               }
            },
            {
               "key_as_string": "2015/02/01 00:00:00",
               "key": 1422748800000,
               "doc_count": 2,
               "total_sales": {
                   "value": 60.0
               },
               "t-shirts": {
                   "doc_count": 1,
                   "sales": {
                       "value": 10.0
                   }
               },
               "t-shirt-percentage": {
                   "value": 16.666666666666664
               }
            },
            {
               "key_as_string": "2015/03/01 00:00:00",
               "key": 1425168000000,
               "doc_count": 2,
               "total_sales": {
                   "value": 375.0
               },
               "t-shirts": {
                   "doc_count": 1,
                   "sales": {
                       "value": 175.0
                   }
               },
               "t-shirt-percentage": {
                   "value": 46.666666666666664
               }
            }
         ]
      }
   }
}