OpenSearch/docs/java-api/aggregations/metrics/scripted-metric-aggregation.asciidoc

[[java-aggs-metrics-scripted-metric]]
==== Scripted Metric Aggregation

Here is how you can use
{ref}/search-aggregations-metrics-scripted-metric-aggregation.html[Scripted Metric Aggregation]
with Java API.

Don't forget to add Groovy in your classpath if you want to run Groovy scripts in an embedded data node
(for unit tests for example).
For example, with Maven, add this dependency to your `pom.xml` file:

[source,xml]
--------------------------------------------------
<dependency>
    <groupId>org.codehaus.groovy</groupId>
    <artifactId>groovy-all</artifactId>
    <version>2.3.2</version>
    <classifier>indy</classifier>
</dependency>
--------------------------------------------------


===== Prepare aggregation request

Here is an example on how to create the aggregation request:

[source,java]
--------------------------------------------------
MetricsAggregationBuilder aggregation =
        AggregationBuilders
                .scriptedMetric("agg")
                .initScript("_agg['heights'] = []")
                .mapScript(new Script("if (doc['gender'].value == \"male\") " +
                        "{ _agg.heights.add(doc['height'].value) } " +
                        "else " +
                        "{ _agg.heights.add(-1 * doc['height'].value) }"));
--------------------------------------------------

You can also specify a `combine` script which will be executed on each shard:

[source,java]
--------------------------------------------------
MetricsAggregationBuilder aggregation =
        AggregationBuilders
                .scriptedMetric("agg")
                .initScript(new Script("_agg['heights'] = []"))
                .mapScript(new Script("if (doc['gender'].value == \"male\") " +
                        "{ _agg.heights.add(doc['height'].value) } " +
                        "else " +
                        "{ _agg.heights.add(-1 * doc['height'].value) }"))
                .combineScript(new Script("heights_sum = 0; for (t in _agg.heights) { heights_sum += t }; return heights_sum"));
--------------------------------------------------

You can also specify a `reduce` script which will be executed on the node which gets the request:

[source,java]
--------------------------------------------------
MetricsAggregationBuilder aggregation =
        AggregationBuilders
                .scriptedMetric("agg")
                .initScript(new Script("_agg['heights'] = []"))
                .mapScript(new Script("if (doc['gender'].value == \"male\") " +
                        "{ _agg.heights.add(doc['height'].value) } " +
                        "else " +
                        "{ _agg.heights.add(-1 * doc['height'].value) }"))
                .combineScript(new Script("heights_sum = 0; for (t in _agg.heights) { heights_sum += t }; return heights_sum"))
                .reduceScript(new Script("heights_sum = 0; for (a in _aggs) { heights_sum += a }; return heights_sum"));
--------------------------------------------------


===== Use aggregation response

Import Aggregation definition classes:

[source,java]
--------------------------------------------------
import org.elasticsearch.search.aggregations.bucket.terms.Terms;
import org.elasticsearch.search.aggregations.metrics.tophits.TopHits;
--------------------------------------------------

[source,java]
--------------------------------------------------
// sr is here your SearchResponse object
ScriptedMetric agg = sr.getAggregations().get("agg");
Object scriptedResult = agg.aggregation();
logger.info("scriptedResult [{}]", scriptedResult);
--------------------------------------------------

Note that the result depends on the script you built.
For the first example, this will basically produce:

[source,text]
--------------------------------------------------
scriptedResult object [ArrayList]
scriptedResult [ {
"heights" : [ 1.122218480146643, -1.8148918111233887, -1.7626731575142909, ... ]
}, {
"heights" : [ -0.8046067304119863, -2.0785486707864553, -1.9183567430207953, ... ]
}, {
"heights" : [ 2.092635728868694, 1.5697545960886536, 1.8826954461968808, ... ]
}, {
"heights" : [ -2.1863201099468403, 1.6328549117346856, -1.7078288405893842, ... ]
}, {
"heights" : [ 1.6043904836424177, -2.0736538674414025, 0.9898266674373053, ... ]
} ]
--------------------------------------------------

The second example will produce:

[source,text]
--------------------------------------------------
scriptedResult object [ArrayList]
scriptedResult [-41.279615707402876,
                -60.88007362339038,
                38.823270659734256,
                14.840192739445632,
                11.300902755741326]
--------------------------------------------------

The last example will produce:

[source,text]
--------------------------------------------------
scriptedResult object [Double]
scriptedResult [2.171917696507009]
--------------------------------------------------