felixcheung commented on a change in pull request #25442: [SPARK-28722][ML]
Change sequential label sorting in StringIndexer fit to parallel
URL: https://github.com/apache/spark/pull/25442#discussion_r313960696
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File path: mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala
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@@ -213,32 +221,36 @@ class StringIndexer @Since("1.4.0") (
val labelsArray = $(stringOrderType) match {
case StringIndexer.frequencyDesc =>
val sortFunc = StringIndexer.getSortFunc(ascending = false)
- countByValue(dataset, inputCols).map { counts =>
+ val orgStrings = countByValue(dataset, inputCols).toSeq
+ ThreadUtils.parmap(orgStrings, "sortingStringLabels", 8) { counts =>
counts.toSeq.sortWith(sortFunc).map(_._1).toArray
- }
+ }.toArray
case StringIndexer.frequencyAsc =>
val sortFunc = StringIndexer.getSortFunc(ascending = true)
- countByValue(dataset, inputCols).map { counts =>
+ val orgStrings = countByValue(dataset, inputCols).toSeq
+ ThreadUtils.parmap(orgStrings, "sortingStringLabels", 8) { counts =>
counts.toSeq.sortWith(sortFunc).map(_._1).toArray
- }
+ }.toArray
case StringIndexer.alphabetDesc =>
- import dataset.sparkSession.implicits._
dataset.persist()
- val labels = inputCols.map { inputCol =>
-
dataset.select(inputCol).na.drop().distinct().sort(dataset(s"$inputCol").desc)
- .as[String].collect()
- }
+ val selectedCols = getSelectedCols(dataset,
inputCols).map(collect_set(_))
+ val allLabels = dataset.select(selectedCols: _*)
+ .collect().toSeq.flatMap(_.toSeq).asInstanceOf[Seq[Seq[String]]]
Review comment:
thanks, I think this is a reasonable trade-off, with caveat then that at
very high cardinality this might OOM the driver.
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