Sampler Aggregation

The Sampler aggregation is a single-bucket aggregation that returns a sample of the documents that fall into the aggregation scope. This aggregation is particularly useful when you want to run sub-aggregations on a representative sample of documents rather than on the entire dataset.

To use the Sampler aggregation, import the following:

import zio.elasticsearch.aggregation.SamplerAggregation
import zio.elasticsearch.ElasticAggregation.samplerAggregation

A Sampler aggregation must always have at least one sub-aggregation. You can create a Sampler aggregation with an initial sub-aggregation using the samplerAggregation method this way:

import zio.elasticsearch.ElasticAggregation.avgAggregation
val aggregation: SamplerAggregation = samplerAggregation(
  name = "samplerAggregation", 
  subAgg = avgAggregation(name = "avgRating", field = Document.intField)
)

If you want to add another sub-aggregation, you can use withSubAgg method:

val aggregationWithMultipleSubAggs: SamplerAggregation = samplerAggregation(
  name = "termsAggregation", 
  field = Document.stringField
).withSubAgg(maxAggregation(name = "maxAggregation", field = Document.intField))

By default, the shard_size parameter for a Sampler aggregation is set to 100. This means that each shard will return a maximum of 100 documents to be sampled. If you want to change the shard_size, you can use the maxDocumentsPerShard method:

val aggregationWithShardSize: SamplerAggregation = samplerAggregation(
  name = "samplerAggregation",
  subAgg = avgAggregation(name = "avgRating", field = Document.intField)
).maxDocumentsPerShard(500)

You can find more detailed information about the Sampler aggregation in the official Elasticsearch documentation here.