Question

Is there any equivalent in scala parallel collections to LINQ s withDegreeOfParallelism which sets the number of threads which will run a query? I want to run an operation in parallel which needs to have a set number of threads running.

Answer 1

用最先进的中继器,使用JRV 1.6或新手,使用:

collection.parallel.ForkJoinTasks.defaultForkJoinPool.setParallelism(parlevel: Int)

这可能是未来变化的结果。计划在下一期发行时采用更加统一的方法,将所有Schala任务与APIC平行。

然而,请注意,虽然这将确定处理器的数量,但这可能不是处理电离层的实际数量。由于平行收集支持固然是并行的,如果发现有必要,实际的网络安装可分配更多的线索来管理询问。

EDIT:

从Schala 2.10开始,确定平行水平的首选方法是将tasksupport/code>领域设定为新的TaskSupport的物体,例如:



scala> import scala.collection.parallel._
import scala.collection.parallel._

scala> val pc = mutable.ParArray(1, 2, 3)
pc: scala.collection.parallel.mutable.ParArray[Int] = ParArray(1, 2, 3)

scala> pc.tasksupport = new ForkJoinTaskSupport(new scala.concurrent.forkjoin.ForkJoinPool(2))
pc.tasksupport: scala.collection.parallel.TaskSupport = scala.collection.parallel.ForkJoinTaskSupport@4a5d484a

scala> pc map { _ + 1 }
res0: scala.collection.parallel.mutable.ParArray[Int] = ParArray(2, 3, 4)


While instantiating the ForkJoinTaskSupport object with a fork join pool, the parallelism level of the fork join pool must be set to the desired value (2 in the example).

Answer 2

独立的是联合考试委员会版本,即Scala 2.9+(平行收集),你还可以使用<编码>分组(Int)和par的功能,在小丘克从事平行工作,如:

scala> val c = 1 to 5
c: scala.collection.immutable.Range.Inclusive = Range(1, 2, 3, 4, 5)

scala> c.grouped(2).seq.flatMap(_.par.map(_ * 2)).toList
res11: List[Int] = List(2, 4, 6, 8, 10)

然而,与确定工人集合参数相比,这种效率可能略低,我不相信这一点。

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