scala并发编程Actor（二十四）

scala 2.10.x版本及之前使用的是内置的Actor。scala 2.11.x版本后将Akka作为并发编程实现。Akka也实现了类似scala Actor的模型，核心概念也是Actor。

概述

scala的Actor类似于Java中的多线程编程，但却有所不同。scala中的Actor尽可能地避免锁和共享状态，避免多线程并发时出现资源争用的情况，进而提升多线程编程的性能。

Java内置线程模型	Scala Actor模型
“共享数据-锁”模型	不共享数据
每个object有一个monitor,监视多线程对可变状态的对象资源的访问	actor之间通过message通信，复制不可变状态的对象资源的一个副本，基于Actor消息发送、接收机制进行并发编程
加锁的代码用synchronized标识
死锁问题
每个线程内部顺序执行	每个actor内部顺序执行

实现步骤

Scala提供了Actor trait来让我们更方便地进行actor多线程编程，就Actor trait就类似于Java中的Thread和Runnable一样，是基础的多线程基类和接口。

首先调用start()方法启动Actor
调用start()方法后act()方法会被执行
actor内部使用receive/react和模式匹配接收消息

actor接收消息

方法	说明
!	异步消息，发送方没有返回值
!?	同步消息，发送方等待返回值
!!	异步消息，发送方返回值是Future[Any]

方法操作

actor启动，调用act()方法

import scala.actors.Actor

object ActorTest {
  def main(args: Array[String]): Unit = {
    println("线程 启动！")
    MyActor1.start()
    MyActor2.start()
  }
}

object MyActor1 extends Actor {
  override def act(): Unit = {
    for (i <- 11 to 19) {
      println("actor01---" + i)
      Thread.sleep(500)
    }
  }
}

object MyActor2 extends Actor {
  override def act(): Unit = {
    for (i <- 21 to 29) {
      println("actor02---" + i)
      Thread.sleep(500)
    }
  }
}

可以不间断地接收消息

object ActorTest {
  def main(args: Array[String]): Unit = {
    println("线程 启动！")
    val actor1 = new MyActor1
    actor1.start()
    // 以下为异步消息，不等待返回
    actor1 ! "start"
    actor1 ! "stop"
    println("消息发送完毕！")
  }
}

class MyActor1 extends Actor {
  override def act(): Unit = {
    while (true) { //以下就是偏函数
      receive {
        case "start" => {
          println("启动中...")
          Thread.sleep(500)
          println("启动完成！")
        }
        case "stop" => {
          println("停止中...")
          Thread.sleep(500)
          println("停止完成！")
        }
      }
    }
  }
}

react方式会复用线程，比receive更高效

import scala.actors.Actor

object ActorTest {
  def main(args: Array[String]): Unit = {
    println("线程 启动！")
    val actor1 = new MyActor1
    actor1.start()
    // 以下为异步消息，不等待返回
    actor1 ! "start"
    actor1 ! "stop"
    println("消息发送完毕！")
  }
}

class MyActor1 extends Actor {
  override def act(): Unit = {
    loop {
      react {
        case "start" => {
          println("starting ...")
          Thread.sleep(1000)
          println("started")
        }
        case "stop" => {
          println("stopping ...")
          Thread.sleep(1000)
          println("stopped ...")
        }
      }
    }
  }
}

结合case class发送消息

import scala.actors.Actor

class AppleActor extends Actor {

  def act(): Unit = {
    while (true) {
      receive {
        case "start" => println("starting ...")
        case SyncMsg(id, msg) => {
          println(id + ",sync " + msg)
          Thread.sleep(5000)
          sender ! ReplyMsg(3,"finished")
        }
        case AsyncMsg(id, msg) => {
          println(id + ",async " + msg)
          Thread.sleep(5000)
        }
      }
    }
  }
}

object AppleActor {
  def main(args: Array[String]) {
    val a = new AppleActor
    a.start()
    //异步消息
    a ! AsyncMsg(1, "hello actor")
    println("异步消息发送完成")
    //同步消息
    //val content = a.!?(1000, SyncMsg(2, "hello actor"))
    //println(content)
    val reply = a !! SyncMsg(2, "hello actor")
    println(reply.isSet)
    //println("123")
    val c = reply.apply()
    println(reply.isSet)
    println(c)
  }
}
case class SyncMsg(id : Int, msg: String)
case class AsyncMsg(id : Int, msg: String)
case class ReplyMsg(id : Int, msg: String)

WordCount案例

import java.io.File

import scala.actors.{Actor, Future}
import scala.collection.mutable
import scala.io.Source


class Task extends Actor {

  override def act(): Unit = {
    loop {
      react {
        case SubmitTask(fileName) => {
          val contents = Source.fromFile(new File(fileName)).mkString
          val arr = contents.split("\r\n")
          val result = arr.flatMap(_.split(" ")).map((_, 1)).groupBy(_._1).mapValues(_.length)
          //val result = arr.flatMap(_.split(" ")).map((_, 1)).groupBy(_._1).mapValues(_.foldLeft(0)(_ + _._2))
          sender ! ResultTask(result)
        }
        case StopTask => {
          exit()
        }
      }
    }
  }
}

object WorkCount {
  def main(args: Array[String]) {
    val files = Array("c://words.txt", "c://words.log")

    val replaySet = new mutable.HashSet[Future[Any]]
    val resultList = new mutable.ListBuffer[ResultTask]

    for(f <- files) {
      val t = new Task
      val replay = t.start() !! SubmitTask(f)
      replaySet += replay
    }

    while(replaySet.size > 0){
      val toCumpute = replaySet.filter(_.isSet)
      for(r <- toCumpute){
        val result = r.apply()
        resultList += result.asInstanceOf[ResultTask]
        replaySet.remove(r)
      }
      Thread.sleep(100)
    }
    val finalResult = resultList.map(_.result).flatten.groupBy(_._1).mapValues(x => x.foldLeft(0)(_ + _._2))
    println(finalResult)
  }
}

case class SubmitTask(fileName: String)
case object StopTask
case class ResultTask(result: Map[String, Int])

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