Github user WeichenXu123 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19904#discussion_r156550777
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -146,25 +147,18 @@ class CrossValidator @Since("1.2.0") (@Since("1.4.0")
override val uid: String)
val validationDataset = sparkSession.createDataFrame(validation,
schema).cache()
logDebug(s"Train split $splitIndex with multiple sets of
parameters.")
+ val completeFitCount = new AtomicInteger(0)
--- End diff --
@MrBago About what your said:
> You can use futures to do this, you need to use a var for modelFutures,
then map on those futures to Unit, then collect those into a sequence, then map
on that to unpersist, and also set modelFutures to null to release those
references
Can you post some pseudo code so I can check whether it works fine and its
peak memory occupation.
Thanks!
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