Github user hhbyyh commented on a diff in the pull request:
https://github.com/apache/spark/pull/18154#discussion_r121836024
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/CountVectorizer.scala ---
@@ -154,13 +155,19 @@ class CountVectorizer @Since("1.5.0")
(@Since("1.5.0") override val uid: String)
override def fit(dataset: Dataset[_]): CountVectorizerModel = {
transformSchema(dataset.schema, logging = true)
val vocSize = $(vocabSize)
+
+ val handlePersistence = $(minDF) < 1.0 &&
+ dataset.storageLevel == StorageLevel.NONE
--- End diff --
I understand your logic, but I don't think it's necessary to make it
complicated. How about we just add the unpersist for both input and wordCounts.
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