OpenSearch/docs/reference/aggregations/pipeline/bucket-script-aggregation.a...

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[[search-aggregations-pipeline-bucket-script-aggregation]]
=== Bucket Script Aggregation
experimental[]
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
A `bucket_script` aggregation looks like this in isolation:
[source,js]
--------------------------------------------------
{
"bucket_script": {
"buckets_path": {
"my_var1": "the_sum", <1>
"my_var2": "the_value_count"
},
"script": "params.my_var1 / params.my_var2"
}
}
--------------------------------------------------
// NOTCONSOLE
<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` Parameters
|===
|Parameter Name |Description |Required |Default Value
|`script` |The script to run for this aggregation. The script can be inline, file or indexed. (see <<modules-scripting>>
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>> for more details) |Required |
|`gap_policy` |The policy to apply when gaps are found in the data (see <<gap-policy>> for more
details)|Optional |`skip`
|`format` |format to apply to the output value of this aggregation |Optional |`null`
|===
The following snippet calculates the ratio percentage of t-shirt sales compared to total sales each month:
[source,js]
--------------------------------------------------
POST /sales/_search
{
"size": 0,
"aggs" : {
"sales_per_month" : {
"date_histogram" : {
"field" : "date",
"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"
}
}
}
}
}
}
--------------------------------------------------
// CONSOLE
// TEST[setup:sales]
And the following may be the response:
[source,js]
--------------------------------------------------
{
"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
}
}
]
}
}
}
--------------------------------------------------
// TESTRESPONSE[s/"took": 11/"took": $body.took/]
// TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
// TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]