Github user BryanCutler commented on the issue:
https://github.com/apache/spark/pull/16774
@thunterdb and @MLnick I updated this to use a configurable
`ExecutorService` and `Future`s instead of Scala parallel collections. The
ExecutorService is retrieved by a function to lazily initialize the thread-pool
until it is needed. When running cross-validation there is a trade-off between
waiting for the all calculations to complete at each split before continuing to
the next and excessively caching all of the split datasets at once. I chose to
be safe and just wait for calculations at each split to complete, but let me
know what you guys think - hopefully this makes sense :)
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