srowen commented on a change in pull request #26454: [SPARK-29818][MLLIB]
Missing persist on RDD
URL: https://github.com/apache/spark/pull/26454#discussion_r345886134
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/BinaryClassificationMetrics.scala
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@@ -165,13 +166,17 @@ 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)
+ )
+ if (scoreLabelsWeight.getStorageLevel != StorageLevel.NONE) {
+ binnedWeights.persist()
+ }
+ val counts = binnedWeights.sortByKey(ascending = false)
Review comment:
Wait, hm, I don't understand this. You persist binnedWeights, but it is now
only used once. Why? If anything it's binnedCounts that needs persisting. I'm
still not clear if it makes enough difference to matter.
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