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https://issues.apache.org/jira/browse/SPARK-29816?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean R. Owen resolved SPARK-29816.
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Resolution: Duplicate
> Missing persist in
> mllib.evaluation.BinaryClassificationMetrics.recallByThreshold()
> -----------------------------------------------------------------------------------
>
> Key: SPARK-29816
> URL: https://issues.apache.org/jira/browse/SPARK-29816
> Project: Spark
> Issue Type: Sub-task
> Components: MLlib
> Affects Versions: 2.4.3
> Reporter: Dong Wang
> Priority: Minor
>
> The rdd scoreAndLabels.combineByKey is used by two actions: sortByKey and
> count(), so it needs to be persisted.
> {code:scala}
> val counts = scoreAndLabels.combineByKey(
> createCombiner = (label: Double) => new BinaryLabelCounter(0L, 0L) +=
> label,
> mergeValue = (c: BinaryLabelCounter, label: Double) => c += label,
> mergeCombiners = (c1: BinaryLabelCounter, c2: BinaryLabelCounter) => c1
> += c2
> ).sortByKey(ascending = false) // first use
> val binnedCounts =
> // Only down-sample if bins is > 0
> if (numBins == 0) {
> // Use original directly
> counts
> } else {
> val countsSize = counts.count() //second use
> {scala}
> This issue is reported by our tool CacheCheck, which is used to dynamically
> detecting persist()/unpersist() api misuses.
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