MaxGekk commented on a change in pull request #26447: [SPARK-29816][MLLIB]
Missing persist in
mllib.evaluation.BinaryClassificationMetrics.recallByThreshold()
URL: https://github.com/apache/spark/pull/26447#discussion_r344456930
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetrics.scala
##########
@@ -165,13 +165,15 @@ class BinaryClassificationMetrics @Since("3.0.0") (
confusions: RDD[(Double, BinaryConfusionMatrix)]) = {
// Create a bin for each distinct score value, count weighted positives and
// negatives within each bin, and then sort by score values in descending
order.
- val counts = scoreLabelsWeight.combineByKey(
+ val binnedWeights = scoreLabelsWeight.combineByKey(
createCombiner = (labelAndWeight: (Double, Double)) =>
new BinaryLabelCounter(0.0, 0.0) += (labelAndWeight._1,
labelAndWeight._2),
mergeValue = (c: BinaryLabelCounter, labelAndWeight: (Double, Double)) =>
c += (labelAndWeight._1, labelAndWeight._2),
mergeCombiners = (c1: BinaryLabelCounter, c2: BinaryLabelCounter) => c1
+= c2
- ).sortByKey(ascending = false)
+ )
+ binnedWeights.persist()
Review comment:
Could you explain why do you persist `binnedWeights` but not `counts`? As I
can see `binnedWeights` is used only once ... or I missed something?
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