Github user BryanCutler commented on the issue:
https://github.com/apache/spark/pull/18281
> w.r.t. putting parallelism in a trait
I think this would be a goot idea and it could be shared with `OneVsRest`,
`CrossValidator` and `TrainValidationSplit` right off the bat. It could have
the `parallelism` Param and return an `ExecutionContext` based on `paralelsim`
to either return a thread-pool or same-thread executor.
> The usage of par collections / Futures in OneVsRest vs tuning looks a bit
different.
It is a little different. For CrossValidator, Futures are nice because I
could add a callback to unpersist training data once all training is complete
and can continue to evaluate each model as soon as it is ready instead of
blocking.
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