Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/12265#discussion_r59088469
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala ---
@@ -152,16 +152,10 @@ class CountVectorizer(override val uid: String)
(word, count)
}.cache()
val fullVocabSize = wordCounts.count()
- val vocab: Array[String] = {
- val tmpSortedWC: Array[(String, Long)] = if (fullVocabSize <=
vocSize) {
- // Use all terms
- wordCounts.collect().sortBy(-_._2)
- } else {
- // Sort terms to select vocab
- wordCounts.sortBy(_._2, ascending = false).take(vocSize)
- }
- tmpSortedWC.map(_._1)
- }
+
+ val vocab: Array[String] = wordCounts.map(_.swap)
--- End diff --
Rather than swap them, you can provide the ordering directly to top, right?
Nit: math.min instead of Math.min.
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