org.apache.spark.partial.GroupedCountEvaluator.scala Maven / Gradle / Ivy
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* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
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package org.apache.spark.partial
import scala.collection.Map
import scala.collection.mutable.HashMap
import scala.reflect.ClassTag
import org.apache.spark.util.collection.OpenHashMap
/**
* An ApproximateEvaluator for counts by key. Returns a map of key to confidence interval.
*/
private[spark] class GroupedCountEvaluator[T : ClassTag](totalOutputs: Int, confidence: Double)
extends ApproximateEvaluator[OpenHashMap[T, Long], Map[T, BoundedDouble]] {
private var outputsMerged = 0
private val sums = new OpenHashMap[T, Long]() // Sum of counts for each key
override def merge(outputId: Int, taskResult: OpenHashMap[T, Long]): Unit = {
outputsMerged += 1
taskResult.foreach { case (key, value) =>
sums.changeValue(key, value, _ + value)
}
}
override def currentResult(): Map[T, BoundedDouble] = {
if (outputsMerged == totalOutputs) {
sums.map { case (key, sum) => (key, new BoundedDouble(sum, 1.0, sum, sum)) }.toMap
} else if (outputsMerged == 0) {
new HashMap[T, BoundedDouble]
} else {
val p = outputsMerged.toDouble / totalOutputs
sums.map { case (key, sum) => (key, CountEvaluator.bound(confidence, sum, p)) }.toMap
}
}
}