這個例子來源於scala聖經級教程《Functional Programming in Scala》，由於本人跟著書中的程式碼敲了一遍，然後寫了點測試程式碼驗證了一下正確性，所以就放在這做個備忘吧。貼出來只是為了方便自己，如果看不懂，但是又感興趣的就去看原書吧……

> 注：本文是上一篇文章《使用Scala實現一個併發庫(阻塞版本, 下一篇文章提供NonBlocking版本)》的延續

package parallelism

import java.util.concurrent._
import java.util.concurrent.atomic.AtomicReference

import
 
 parallelism.Nonblocking.Future

import language.implicitConversions

object Nonblocking {

  trait Future[+A] {
    private[parallelism] def apply(k: A => Unit): Unit
  }

  type Par[+A] = ExecutorService => Future[A]

  object Par {

    def run[A](es: ExecutorService)(p: Par[A]): A = {
      // A mutable, threadsafe reference, to use for storing the result
 

      val ref = new java.util.concurrent.atomic.AtomicReference[A]
      // A latch which, when decremented, implies that `ref` has the result
      val latch = new CountDownLatch(1)
      // Asynchronously set the result, and decrement the latch
      p(es) { a => ref.set(a); latch.countDown }
      // Block until the `latch.countDown` is invoked asynchronously
 

      latch.await
      // Once we've passed the latch, we know `ref` has been set, and return its value
      ref.get
    }

    def unit[A](a: A): Par[A] =
      es => new Future[A] {
        def apply(cb: A => Unit): Unit =
          cb(a)
      }

    /** A non-strict version of `unit` */
    def delay[A](a: => A): Par[A] =
      es => new Future[A] {
        def apply(cb: A => Unit): Unit =
          cb(a)
      }

    def fork[A](a: => Par[A]): Par[A] =
      es => new Future[A] {
        def apply(cb: A => Unit): Unit =
          eval(es)(a(es)(cb))
      }

    /**
      * Helper function for constructing `Par` values out of calls to non-blocking continuation-passing-style APIs.
      * This will come in handy in Chapter 13.
      */
    def async[A](f: (A => Unit) => Unit): Par[A] = es => new Future[A] {
      def apply(k: A => Unit) = f(k)
    }

    /**
      * Helper function, for evaluating an action
      * asynchronously, using the given `ExecutorService`.
      */
    def eval(es: ExecutorService)(r: => Unit): Unit =
      es.submit(new Callable[Unit] {
        def call = r
      })

    def map2[A, B, C](p: Par[A], p2: Par[B])(f: (A, B) => C): Par[C] =
      es => new Future[C] {
        def apply(cb: C => Unit): Unit = {
          var ar: Option[A] = None
          var br: Option[B] = None
          // this implementation is a little too liberal in forking of threads -
          // it forks a new logical thread for the actor and for stack-safety,
          // forks evaluation of the callback `cb`
          val combiner = Actor[Either[A, B]](es) {
            case Left(a) =>
              if (br.isDefined) eval(es)(cb(f(a, br.get)))
              else ar = Some(a)
            case Right(b) =>
              if (ar.isDefined) eval(es)(cb(f(ar.get, b)))
              else br = Some(b)
          }
          p(es)(a => combiner ! Left(a))
          p2(es)(b => combiner ! Right(b))
        }
      }

    // specialized version of `map`
    def map[A, B](p: Par[A])(f: A => B): Par[B] =
      es => new Future[B] {
        def apply(cb: B => Unit): Unit =
          p(es)(a => eval(es) {
            cb(f(a))
          })
      }

    def lazyUnit[A](a: => A): Par[A] =
      fork(unit(a))

    def asyncF[A, B](f: A => B): A => Par[B] =
      a => lazyUnit(f(a))

    def sequenceRight[A](as: List[Par[A]]): Par[List[A]] =
      as match {
        case Nil => unit(Nil)
        case h :: t => map2(h, fork(sequence(t)))(_ :: _)
      }

    def sequenceBalanced[A](as: IndexedSeq[Par[A]]): Par[IndexedSeq[A]] = fork {
      if (as.isEmpty) unit(Vector())
      else if (as.length == 1) map(as.head)(a => Vector(a))
      else {
        val (l, r) = as.splitAt(as.length / 2)
        map2(sequenceBalanced(l), sequenceBalanced(r))(_ ++ _)
      }
    }

    def sequence[A](as: List[Par[A]]): Par[List[A]] =
      map(sequenceBalanced(as.toIndexedSeq))(_.toList)

    def parMap[A, B](as: List[A])(f: A => B): Par[List[B]] =
      sequence(as.map(asyncF(f)))

    def parMap[A, B](as: IndexedSeq[A])(f: A => B): Par[IndexedSeq[B]] =
      sequenceBalanced(as.map(asyncF(f)))

    // exercise answers

    /*
     * We can implement `choice` as a new primitive.
     *
     * `p(es)(result => ...)` for some `ExecutorService`, `es`, and
     * some `Par`, `p`, is the idiom for running `p`, and registering
     * a callback to be invoked when its result is available. The
     * result will be bound to `result` in the function passed to
     * `p(es)`.
     *
     * If you find this code difficult to follow, you may want to
     * write down the type of each subexpression and follow the types
     * through the implementation. What is the type of `p(es)`? What
     * about `t(es)`? What about `t(es)(cb)`?
     */
    def choice[A](p: Par[Boolean])(t: Par[A], f: Par[A]): Par[A] =
      es => new Future[A] {
        def apply(cb: A => Unit): Unit =
          p(es) { b =>
            if (b) eval(es) {
              t(es)(cb)
            }
            else eval(es) {
              f(es)(cb)
            }
          }
      }

    /* The code here is very similar. */
    def choiceN[A](p: Par[Int])(ps: List[Par[A]]): Par[A] =
      es => new Future[A] {
        def apply(cb: A => Unit): Unit =
          p(es) { ind =>
            eval(es) {
              ps(ind)(es)(cb)
            }
          }
      }

    def choiceViaChoiceN[A](a: Par[Boolean])(ifTrue: Par[A], ifFalse: Par[A]): Par[A] =
      choiceN(map(a)(b => if (b) 0 else 1))(List(ifTrue, ifFalse))

    def choiceMap[K, V](p: Par[K])(ps: Map[K, Par[V]]): Par[V] =
      es => new Future[V] {
        def apply(cb: V => Unit): Unit =
          p(es)(k => ps(k)(es)(cb))
      }

    /* `chooser` is usually called `flatMap` or `bind`. */
    def chooser[A, B](p: Par[A])(f: A => Par[B]): Par[B] =
      flatMap(p)(f)

    def flatMap[A, B](p: Par[A])(f: A => Par[B]): Par[B] =
      es => new Future[B] {
        def apply(cb: B => Unit): Unit =
          p(es)(a => f(a)(es)(cb))
      }

    def choiceViaFlatMap[A](p: Par[Boolean])(f: Par[A], t: Par[A]): Par[A] =
      flatMap(p)(b => if (b) t else f)

    def choiceNViaFlatMap[A](p: Par[Int])(choices: List[Par[A]]): Par[A] =
      flatMap(p)(i => choices(i))

    def join[A](p: Par[Par[A]]): Par[A] =
      es => new Future[A] {
        def apply(cb: A => Unit): Unit =
          p(es)(p2 => eval(es) {
            p2(es)(cb)
          })
      }

    def joinViaFlatMap[A](a: Par[Par[A]]): Par[A] =
      flatMap(a)(x => x)

    def flatMapViaJoin[A, B](p: Par[A])(f: A => Par[B]): Par[B] =
      join(map(p)(f))

    /* Gives us infix syntax for `Par`. */
    implicit def toParOps[A](p: Par[A]): ParOps[A] = new ParOps(p)

    // infix versions of `map`, `map2` and `flatMap`
    class ParOps[A](p: Par[A]) {
      def map[B](f: A => B): Par[B] = Par.map(p)(f)

      def map2[B, C](b: Par[B])(f: (A, B) => C): Par[C] = Par.map2(p, b)(f)

      def flatMap[B](f: A => Par[B]): Par[B] = Par.flatMap(p)(f)

      def zip[B](b: Par[B]): Par[(A, B)] = p.map2(b)((_, _))
    }

  }


  def main(args: Array[String]): Unit = {

    // _print for dubug purpose
    val _print = (flag: Boolean) => if (flag) println(": " + Thread.currentThread()) else println(Thread.currentThread())

    val es = Executors.newFixedThreadPool(3)

    val intDelayPar = Par.delay[Int]({
      _print(false);
      math.pow(999, 67).toInt
    });

    intDelayPar(es).apply((a: Int) => {
      _print(true);
      println(a)
    })

    intDelayPar(es)((a: Int) => {
      _print(true);
      println(a)
    })

    Par.fork(intDelayPar)(es)((a: Int) => {
      _print(true);
      println(a)
    })


    Thread.sleep(6000L)
    println("**********************************************")

    Par.run(es)(intDelayPar)

    Thread.sleep(6000L)
    println("**********************************************")


    val _intDelayPar = Par.delay[Int]({
      val future = es.submit(new Callable[Int] {
        _print(true);
        override def call = math.pow(999, 67).toInt
      })
      val res = future.get
      println(res)
      res
    });
    Par.run(es)(_intDelayPar)

    println("-------------------------------------------")

    import scala.language.implicitConversions
    import Par.toParOps

    // 通過隱式轉換將 map 方法變為中綴操作方式
    (Par.delay(1) map {(a: Int) => 111 * a})(es)(println(_))
    (Par.delay(2) map {(a: Int) => 111 * a})(es)(println(_))
    (Par.delay(3) map {(a: Int) => 111 * a})(es)(println(_))

    es.shutdown()
  }

}

上述程式碼的執行結果是：

Thread[main,5,main]
: Thread[main,5,main]
2147483647
Thread[main,5,main]
: Thread[main,5,main]
2147483647
Thread[pool-1-thread-1,5,main]
: Thread[pool-1-thread-1,5,main]
2147483647
**********************************************
Thread[main,5,main]
**********************************************
: Thread[main,5,main]
2147483647
-------------------------------------------
111
222
333

上述程式碼用到的Actor原始碼是：

package parallelism

import java.util.concurrent.atomic.{AtomicInteger, AtomicReference}
import java.util.concurrent.{Callable,ExecutorService}
import annotation.tailrec

/*
 * Implementation is taken from `scalaz` library, with only minor changes. See:
 *
 * https://github.com/scalaz/scalaz/blob/scalaz-seven/concurrent/src/main/scala/scalaz/concurrent/Actor.scala
 *
 * This code is copyright Andriy Plokhotnyuk, Runar Bjarnason, and other contributors,
 * and is licensed using 3-clause BSD, see LICENSE file at:
 *
 * https://github.com/scalaz/scalaz/blob/scalaz-seven/etc/LICENCE
 */

/**
 * Processes messages of type `A`, one at a time. Messages are submitted to
 * the actor with the method `!`. Processing is typically performed asynchronously,
 * this is controlled by the provided `strategy`.
 *
 * Memory consistency guarantee: when each message is processed by the `handler`, any memory that it
 * mutates is guaranteed to be visible by the `handler` when it processes the next message, even if
 * the `strategy` runs the invocations of `handler` on separate threads. This is achieved because
 * the `Actor` reads a volatile memory location before entering its event loop, and writes to the same
 * location before suspending.
 *
 * Implementation based on non-intrusive MPSC node-based queue, described by Dmitriy Vyukov:
 * [[http://www.1024cores.net/home/lock-free-algorithms/queues/non-intrusive-mpsc-node-based-queue]]
 *
 * @see scalaz.concurrent.Promise for a use case.
 *
 * @param handler  The message handler
 * @param onError  Exception handler, called if the message handler throws any `Throwable`.
 * @param strategy Execution strategy, for example, a strategy that is backed by an `ExecutorService`
 * @tparam A       The type of messages accepted by this actor.
 */
final class Actor[A](strategy: Strategy)(handler: A => Unit, onError: Throwable => Unit = throw(_)) {
  self =>

  private val tail = new AtomicReference(new Node[A]())
  private val suspended = new AtomicInteger(1)
  private val head = new AtomicReference(tail.get)

  /** Alias for `apply` */
  def !(a: A) {
    val n = new Node(a)
    head.getAndSet(n).lazySet(n)
    trySchedule()
  }

  /** Pass the message `a` to the mailbox of this actor */
  def apply(a: A) {
    this ! a
  }

  def contramap[B](f: B => A): Actor[B] =
    new Actor[B](strategy)((b: B) => (this ! f(b)), onError)

  private def trySchedule() {
    if (suspended.compareAndSet(1, 0)) schedule()
  }

  private def schedule() {
    strategy(act())
  }

  private def act() {
    val t = tail.get
    val n = batchHandle(t, 1024)
    if (n ne t) {
      n.a = null.asInstanceOf[A]
      tail.lazySet(n)
      schedule()
    } else {
      suspended.set(1)
      if (n.get ne null) trySchedule()
    }
  }

  @tailrec
  private def batchHandle(t: Node[A], i: Int): Node[A] = {
    val n = t.get
    if (n ne null) {
      try {
        handler(n.a)
      } catch {
        case ex: Throwable => onError(ex)
      }
      if (i > 0) batchHandle(n, i - 1) else n
    } else t
  }
}

private class Node[A](var a: A = null.asInstanceOf[A]) extends AtomicReference[Node[A]]

object Actor {

  /** Create an `Actor` backed by the given `ExecutorService`. */
  def apply[A](es: ExecutorService)(handler: A => Unit, onError: Throwable => Unit = throw(_)): Actor[A] =
    new Actor(Strategy.fromExecutorService(es))(handler, onError)
}

/**
 * Provides a function for evaluating expressions, possibly asynchronously.
 * The `apply` function should typically begin evaluating its argument
 * immediately. The returned thunk can be used to block until the resulting `A`
 * is available.
 */
trait Strategy {
  def apply[A](a: => A): () => A
}

object Strategy {

  /**
   * We can create a `Strategy` from any `ExecutorService`. It's a little more
   * convenient than submitting `Callable` objects directly.
   */
  def fromExecutorService(es: ExecutorService): Strategy = new Strategy {
    def apply[A](a: => A): () => A = {
      val f = es.submit { new Callable[A] { def call = a} }
      () => f.get
    }
  }

  /**
   * A `Strategy` which begins executing its argument immediately in the calling thread.
   */
  def sequential: Strategy = new Strategy {
    def apply[A](a: => A): () => A = {
      val r = a
      () => r
    }
  }
}

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|   | .'|          .-''         '.  \    \   /    /.-''         '.            
|   |<  |         /     .-''"'-.  `. '   '. /'   //     .-''"'-.  `. .-,.--.  
|   | | |        /     /________\   \|    |'    //     /________\   \|  .-. | 
|   | | | .'''-. |                  ||    ||    ||                  || |  | | 
|   | | |/.'''. \\    .-------------''.   `'   .'\    .-------------'| |  | | 
|   | |  /    | | \    '-.____...---. \        /  \    '-.____...---.| |  '-  
|   | | |     | |  `.             .'   \      /    `.             .' | |      
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      | '.    | '.                                                   |_|      
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