Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/18281#discussion_r122007474
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala ---
@@ -325,8 +350,13 @@ final class OneVsRest @Since("1.4.0") (
multiclassLabeled.persist(StorageLevel.MEMORY_AND_DISK)
}
+ val iters = Range(0, numClasses).par
+ iters.tasksupport = new ForkJoinTaskSupport(
+ new ForkJoinPool(Math.min(getParallelism, numClasses))
--- End diff --
I don't think `ForkJoinPool` is the best thing to use here. It's more
geared for a bunch of small tasks that might spawn other tasks. Just a regular
thread-pool is fine. Also, it is a little better for the case of `parallelism`
1 to use `sameThreadExecutor`. This will just run in the current thread and
has no overhead (equivalent to running in serial), where a thread-pool of size
1 will still create another thread and does have some overhead.
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