Mixing Parallel Collections with Akka

Question

How well to scala parallel collection operations get along with the concurrency/parallelism used by Akka Actors (and Futures) with respect to efficient scheduling on the system?

Actors' and Futures' execution is handled by an ExecutionContext generally provided by the Dispatcher. What I find on parallel collections indicates they use a TaskSupport object. I found a ExecutionContextTaskSupport object that may connect the two but am not sure.

What is the proper way to mix the two concurrency solutions, or is it advised not to?

Answer 1

At present this is not supported / handled well.

Prior to Scala 2.11-M7, attempting to use the dispatcher as the ContextExecutor throws an exception.

That is, the following code in an actor's receive will throw a NotImplementedError:

val par = List(1,2,3).par
par.tasksupport = new ExecutionContextTaskSupport(context.dispatcher)

par foreach println

Incidentally, this has been fixed in 2.11-M7, though it was not done to correct the above issue.
In reading through the notes on the fix it sounds like the implementation provided by ExecutionContextTaskSupport in the above case could have some overhead over directly using one of the other TaskSupport implementations; however, I have done nothing to test that interpretation or evaluate the magnitude of any impact.

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A Note on Parallel Collections:
By default Parallel Collections will use the global ExecutorContext (ExecutionContext.Implicits.global) just as you might use for Futures. While this is well behaved, if you want to be constrained by the dispatcher (using context.dispatcher)—as you are likely to do with Futures in Akka—you need to set a different TaskSupport as shown in the code sample above.