Bucket script aggregation
editBucket script aggregation
editA 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
editA bucket_script
aggregation looks like this in isolation:
{ "bucket_script": { "buckets_path": { "my_var1": "the_sum", "my_var2": "the_value_count" }, "script": "params.my_var1 / params.my_var2" } }
Here, |
Table 53. bucket_script
Parameters
Parameter Name | Description | Required | Default Value |
---|---|---|---|
|
The script to run for this aggregation. The script can be inline, file or indexed. (see Scripting for more details) |
Required |
|
|
A map of script variables and their associated path to the buckets we wish to use for the variable
(see |
Required |
|
|
The policy to apply when gaps are found in the data (see Dealing with gaps in the data for more details) |
Optional |
|
|
DecimalFormat pattern for the
output value. If specified, the formatted value is returned in the aggregation’s
|
Optional |
|
The following snippet calculates the ratio percentage of t-shirt sales compared to total sales each month:
response = client.search( index: 'sales', body: { size: 0, aggregations: { sales_per_month: { date_histogram: { field: 'date', calendar_interval: 'month' }, aggregations: { total_sales: { sum: { field: 'price' } }, "t-shirts": { filter: { term: { type: 't-shirt' } }, aggregations: { sales: { sum: { field: 'price' } } } }, "t-shirt-percentage": { bucket_script: { buckets_path: { "tShirtSales": 't-shirts>sales', "totalSales": 'total_sales' }, script: 'params.tShirtSales / params.totalSales * 100' } } } } } } ) puts response
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 } } ] } } }