_parallel

Parallel

Returns Stream.Flow with parallel execution

Each consecutive element will be sent to a new thread for processing

  (1 <> 5).stream
     .parallel
     .map("Value: " + _ + "\t" + Thread.currentThread.getName)
     .foreach(println)

  // Possible Output
  Value: 1    ForkJoinPool.commonPool-worker-9
  Value: 3    ForkJoinPool.commonPool-worker-11
  Value: 2    main
  Value: 4    ForkJoinPool.commonPool-worker-2
  Value: 5    ForkJoinPool.commonPool-worker-4

Conditionally parallel

Returns Stream.Flow with parallel or sequential implementation, depending on given parameter

   (1 <> 50).stream.parallelIf(true).isParallel   // Returns true

   (1 <> 50).stream.parallelIf(false).isParallel  // Returns false

Conditionally parallel

Returns Stream.Flow with parallel or sequential implementation, depending on stream having element count equal or greater than given ''threshold''

  (1 <> 50).stream.parallelIfOver(100).isParallel   // Returns false

  (1 <> 200).stream.parallelIfOver(100).isParallel  // Returns true

Parallel with Priority

This is very expensive operation, because it creates a custom thread pool. It only sutable for long running streams

   (1 <> 100).stream.parallelWithPriority(MIN, 4).foreach(v => ())

   (1 <> 100).stream.parallelWithPriority(MAX).foreach(v => ())

   (1 <> 100).stream.parallelWithPriority(J.Priority(5), 4).foreach(v => ())

Note: parallelism determines how many parallel threads are allowed. Default value is CPU core count minus 1