--- navigation_title: "Bucket script" mapped_pages: - https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-pipeline-bucket-script-aggregation.html --- # Bucket script aggregation [search-aggregations-pipeline-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. ## Syntax [bucket-script-agg-syntax] A `bucket_script` aggregation looks like this in isolation: ```js { "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. $$$bucket-script-params$$$ | Parameter Name | Description | Required | Default Value | | --- | --- | --- | --- | | `script` | The script to run for this aggregation. The script can be inline, file or indexed. (see [Scripting](docs-content://explore-analyze/scripting.md)for 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](/reference/data-analysis/aggregations/pipeline.md#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](/reference/data-analysis/aggregations/pipeline.md#gap-policy) for more details) | Optional | `skip` | | `format` | [DecimalFormat pattern](https://docs.oracle.com/en/java/javase/11/docs/api/java.base/java/text/DecimalFormat.html) for theoutput value. If specified, the formatted value is returned in the aggregation’s`value_as_string` property | Optional | `null` | The following snippet calculates the ratio percentage of t-shirt sales compared to total sales each month: ```console 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: ```console-result { "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 } } ] } } } ```