注:我们现在学的Scala Actor是scala 2.10.x版本及以前版本的Actor。
Scala在2.11.x版本中将Akka加入其中,作为其默认的Actor,老版本的Actor已经废弃
什么是Scala Actor
概念
Scala中的Actor能够实现并行编程的强大功能,它是基于事件模型的并发机制,Scala是运用消息(message)的发送、接收来实现多线程的。使用Scala能够更容易地实现多线程应用的开发。
传统java并发编程与Scala Actor编程的区别

对于Java,我们都知道它的多线程实现需要对共享资源(变量、对象等)使用synchronized 关键字进行代码块同步、对象锁互斥等等。而且,常常一大块的try…catch语句块中加上wait方法、notify方法、notifyAll方法是让人很头疼的。原因就在于Java中多数使用的是可变状态的对象资源,对这些资源进行共享来实现多线程编程的话,控制好资源竞争与防止对象状态被意外修改是非常重要的,而对象状态的不变性也是较难以保证的。 而在Scala中,我们可以通过复制不可变状态的资源(即对象,Scala中一切都是对象,连函数、方法也是)的一个副本,再基于Actor的消息发送、接收机制进行并行编程
Actor方法执行顺序
首先调用start()方法启动Actor
调用start()方法后其act()方法会被执行
向Actor发送消息
发送消息的方式
| ! | 发送异步消息,没有返回值。 |
|---|---|
| !? | 发送同步消息,等待返回值。 |
| !! | 发送异步消息,返回值是 Future[Any]。 |
Actor实战
第一个例子
//注意导包是scala.actors.Actorimport scala.actors.Actorobject MyActor1 extends Actor{//重新act方法def act(){for(i <- 1 to 10){println("actor-1 " + i)Thread.sleep(2000)}}}object MyActor2 extends Actor{//重新act方法def act(){for(i <- 1 to 10){println("actor-2 " + i)Thread.sleep(2000)}}}object ActorTest extends App{//启动ActorMyActor1.start()MyActor2.start()}
说明:上面分别调用了两个单例对象的start()方法,他们的act()方法会被执行,相同与在java中开启了两个线程,线程的run()方法会被执行
注意:这两个Actor是并行执行的,act()方法中的for循环执行完成后actor程序就退出了
第二个例子(可以不断地接收消息)
import scala.actors.Actorclass MyActor extends Actor {override def act(): Unit = {while (true) {receive {case "start" => {println("starting ...")Thread.sleep(5000)println("started")}case "stop" => {println("stopping ...")Thread.sleep(5000)println("stopped ...")}}}}}object MyActor {def main(args: Array[String]) {val actor = new MyActoractor.start()actor ! "start"actor ! "stop"println("消息发送完成!")}}
说明:在act()方法中加入了while (true) 循环,就可以不停的接收消息
注意:发送start消息和stop的消息是异步的,但是Actor接收到消息执行的过程是同步的按顺序执行
第三个例子(react方式会复用线程,比receive更高效)
示例1
import scala.actors.Actor
class YourActor extends Actor {
/*
* loop + react 相当于加入一个ThreadPool(线程池),提高了线程的并发复用
*/
override def act(): Unit = {
//调用loop方法,循环
loop {
//react 偏函数(偏函数两个参数一个为输入,一个为输出),不用写match
//作用:复用线程
react {
case "start" => {
println("starting ...")
Thread.sleep(5000)
println("started")
}
case "stop" => {
println("stopping ...")
Thread.sleep(8000)
println("stopped ...")
}
}
}
}
}
object YourActor {
def main(args: Array[String]) {
val actor = new YourActor
actor.start()
actor ! "start"
actor ! "stop"
println("消息发送完成!")
}
}
示例2
package com.zhiyoulxj.actor.actor
import scala.actors.Actor
/*
* 自己给自己发送消息,实现Actor模型通信
* */
class MyActor extends Actor{
override def act(): Unit = {
while (true) {
//receive是一个偏函数(用于匹配接收到消息),接收actor发送的消息
receive{
case "start" =>{
print("start.....")
Thread.sleep(5000)
}
case "stop" =>{
print("stop.....")
Thread.sleep(5000)
}
}
}
}
}
/*
* loop + react 相当于加入一个ThreadPool(线程池),提高了线程的并发复用
*/
class MyActor1 extends Actor {
override def act(): Unit = {
//调用loop方法,循环
loop{
//react 偏函数(偏函数两个参数一个为输入,一个为输出),不用写match
//作用:复用线程
react{
case "start" => {
println("startint...")
}
case "stop" => {
println("stopping...")
}
}
}
}
}
//伴生对象
object MyActor{
def main(args: Array[String]): Unit = {
/*val actor = new MyActor
actor.start()
actor ! "start"
actor ! "stop"
println("消息发送成功")*/
val actor1 = new MyActor1
actor1.start()
actor1 ! "start"
actor1 ! "stop"
println("输入完成")
}
}
说明: react 如果要反复执行消息处理,react外层要用loop,不能用while
第四个例子(结合case class发送消息)
示例1
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)
示例2
package com.zhiyoulxj.actor.actor
import scala.actors.Actor
case class AsyMSG(id: Int,name: String) //异步
case class SynMSG(id: Int,name: String) //同步
case class FutureMSG(id: Int,name: String) //带返回值的:Future
/*
* Actor三种消息发送模式 !异步无返回值 !?同步等待返回值 !!异有返回值
* */
class CaseClassActor extends Actor{
override def act(): Unit = {
while (true) {
receive {
case "start" => println("starting....")
case AsyMSG(id, name) => {
println(id + " Asy... " + name)
}
case SynMSG(id, name) => {
println(id + " Syn... " + name)
sender ! FutureMSG(3,"wangwu finish")
}
case FutureMSG(id, name) => {
println(id + " Future... " + name)
}
}
}
}
}
object CaseClassActor{
def main(args: Array[String]): Unit = {
val actor = new CaseClassActor
actor.start()
// actor ! AsyMSG(1,"zhangsan 异步")
// println("!:发送异步消息没有返回值")
// val returnVal = actor !? (2000,SynMSG(2,"李四 同步"))
// println(returnVal)
// print("!?:发送同步消息等待返回值")
//!! 发送异步消息,返回值是 Future[Any]。
// 异步发送消息后,不会等待返回值发送过来,随机拿走一个"空箱子",返回值发送过来后就放进去
// 当正常使用用的就是发送过来的返回值
val FutureVal = actor !! SynMSG(4,"zhaoliu 同步有返回值")
println(FutureVal.isSet)
val c = FutureVal.apply()
//FutureVal.apply() ---->toString()
println(c)
}
}
练习
用actor并发编程写一个单机版的WorldCount,将多个文件作为输入,计算完成后将多个任务汇总,得到最终的结果
Actor中的WordCount
示例1
import java.io.File
import scala.actors.{Actor, Future}
import scala.collection.mutable
import scala.io.Source
/**
* Created by ZX on 2016/4/4.
*/
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])
示例2
package com.zhiyoulxj.actor.actor
import scala.actors.{Actor, Future}
import scala.collection.mutable
import scala.collection.mutable.ListBuffer
import scala.io.Source
class ActorWordCount extends Actor{
override def act(): Unit ={
loop{
react{
case MapTask(filename) => {
//Map的业务逻辑 1.读取文件 2.单词切割
// 3.(key,1)加 1 操作 4.combiner
//combiner局部汇总,结果是Map[String,Int]
// Source.fromFile(filename)从本地读文件内容
val result = Source.fromFile(filename).getLines().
flatMap(_.split(" ")).map((_,1)).
toList.groupBy(_._1).mapValues(_.size)
//将Map结果发送给Reduce
sender ! ReduceTask(result)
}
case ExistTask => {
exit()
}
}
}
}
}
object ActorWordCount {
def main(args: Array[String]): Unit = {
val resSet = new mutable.HashSet[Future[Any]]()
val resultList = new ListBuffer[ReduceTask]
val files = Array[String]("D://words.txt", "D://MR.txt")
for (filename <- files) {
val actor = new ActorWordCount
//启动actor并向MapTask发送消息,返回值是一个Future
val res = actor.start() !! MapTask(filename)
resSet += res //把这些Future放到Set集合中
}
while (resSet.size > 0){
//isSet判断resSet中Future返回值是否可用
val toHandle = resSet.filter(_.isSet) //取出有效的结果集,待处理的数据
for(f <- toHandle) {
var result = f.apply()
//获取ReduceTask的实例
val result1 = result.asInstanceOf[ReduceTask] //asInstanceOf 相当于java中的强转A-->B
resultList += result1 //将有效的数据放到另一个容器中
resSet -= f //从future所在集合中删除用过的元素
}
}
// println(resultList)
//resultList:((hello,3),(hello,2),(tom,1)....)
var r = resultList.flatMap(_.result).groupBy(_._1).mapValues(_.foldLeft(0)(_+_._2))
println(r.toBuffer)
}
}
case class MapTask(filename: String)
case class ReduceTask(result:Map[String,Int])
case object ExistTask
RPC通信(AKKA)
Master类与Worker类

业务逻辑:
启动Master,然后启动所有的worker。
Worker向Master发送建立连接。
向Master注册,向Master发送列表信息,通过一个封装好的类。
Master收到Worker的注册信息将Worker信息保存起来,然后向Worker发送反馈注册成功。
Worker要定时的向Master发送心跳,为了告诉Master我还活着。
Master会定时清除超时的Worker。
Master类
package com.zhiyoulxj.actor.akka
import akka.actor.{Actor, ActorSystem, Props}
import com.typesafe.config.ConfigFactory
import scala.concurrent.duration._
import scala.collection.mutable
class Master extends Actor {
//用来封装worker传输过来的信息,value最好用一个实体类,以后方便实用其中的属性
val ids = new mutable.HashMap[String,WorkInfo]()
//保存Map中的WorkInfo的集合,方便以后Master对象其中属性的排序
val workers = new mutable.HashSet[WorkInfo]()
val CHECK_BEAT = 15000
//生命周期之启动Actor ctrl+o 查询未实现的方法
override def preStart(): Unit = {
print("Actor is preStart ....")
//定时器,检查work心跳是否正常
//隐式转换,增强功能
import context.dispatcher
context.system.scheduler.schedule(0.millis,CHECK_BEAT.millis,self,CheckTimeOut)
}
//用于接收信息
override def receive: Receive = {
//接收客户端的注册信息并保存数据
case RegisterWorker(id,mem,cores) =>{
//判断一下worker是否注册过
if (!ids.contains(id)) {
val workInfo = new WorkInfo(id, mem, cores)
//保存数据策略:1.保存在内存 2.持久化到磁盘 3.保存到zookeeper
//map.put操作
ids(id) = workInfo
//Set的追加操作
workers += workInfo
//创建样例类发送注册成功的确认消息
sender ! RegisterFinish("akka.tcp://MasterSystem@$masterHost:$masterPort/user/Master")
}
}
case HeartBeat(id) =>{
if(ids.contains(id)){
val workInfo = ids(id)
val currentTime = System.currentTimeMillis()
//把心跳时间用当前时间置换
workInfo.LastBeat = currentTime
}
}
case CheckTimeOut => {
val currentTime = System.currentTimeMillis()
val toClean = workers.filter(x=>currentTime - x.LastBeat > CHECK_BEAT)
for (w <- toClean){
workers -= w
ids -= w.id
}
println("活着的worker数量: "+workers.size)
}
}
}
object Master{
def main(args: Array[String]): Unit = {
val host = args(0)
val port = args(1).toInt
//准备配置文件
val config =
s"""
|akka.actor.provider = "akka.remote.RemoteActorRefProvider"
|akka.remote.netty.tcp.hostname = "$host"
|akka.remote.netty.tcp.port = "$port"
""".stripMargin
val cfg = ConfigFactory.parseString(config)
//ActorSystem:Actor的领导,监控所有的actor,singletong 单例
val actorSystem = ActorSystem("MasterSystem",cfg)
//创建actor
val master = actorSystem.actorOf(Props[Master],"Master")
master ! "nihao"
actorSystem.awaitTermination() //让进程等待,不结束
}
}
Worker类
package com.zhiyoulxj.actor.akka
import java.util.UUID
import akka.actor.{Actor, ActorSelection, ActorSystem, Props}
import com.typesafe.config.ConfigFactory
import scala.concurrent.duration._
class Worker(val masterHost:String,val masterPort:Int,val mem:Int,var cores:Int) extends Actor {
var master:ActorSelection = _
val workersID = UUID.randomUUID().toString
val HEART_BEAT = 10000
//建立连接
override def preStart(): Unit = {
//参数需要有/user/master
master = context.actorSelection(s"akka.tcp://MasterSystem@$masterHost:$masterPort/user/Master")
//向master发送注册信息,Master的receive方法中的case class 接收
master ! RegisterWorker(workersID,mem,cores)
}
override def receive: Receive = {
//worker收到master返回的确认消息
case RegisterFinish(masterURL) =>{
println(masterURL)
//定时发送心跳 scheduler 调度
//导入隐式转换
import context.dispatcher
//自己给自己发 self (发送者:自己) SendHeartBeat(发送内容)
context.system.scheduler.schedule(0.millis,HEART_BEAT.millis,self,SendHeartBeat)
}
//接收自己发送给自己的心跳,然后再发送给master
case SendHeartBeat =>{
println("确认接收到心跳")
master ! HeartBeat(workersID)
}
}
}
object Worker{
def main(args: Array[String]): Unit = {
val host = args(0)
val port = args(1).toInt
val masterHost = args(2)
val masterPort = args(3).toInt
val mem = args(4).toInt
val cores = args(5).toInt
//准备配置
val config =
s"""
|akka.actor.provider = "akka.remote.RemoteActorRefProvider"
|akka.remote.netty.tcp.hostname = "$host"
|akka.remote.netty.tcp.port = "$port"
""".stripMargin
val cfg = ConfigFactory.parseString(config)
//ActorSystem 单例 actor的管理者
val actorSystem = ActorSystem("WorkerSystem",cfg)
//actorOf 实例化一个actor
actorSystem.actorOf(Props(new Worker(masterHost,masterPort,mem,cores)),"Worker")
actorSystem.awaitTermination()
}
}
所用样例类
package com.zhiyoulxj.actor.akka
/*
* 交互信息:用来封装Master与Worker进行交互的信息
* 1.注册 2.Master的反馈 3.心跳 4.检查信息(时间超时)
* 这里面都是样例类,因为在网络间传输,所以必须实现序列化
*/
trait IntervalMessage extends Serializable
//注册样例类,封装了从Worker到Master的注册消息 worker-->master
case class RegisterWorker(id:String,mem:Int,cores:Int)extends IntervalMessage
//注册成功确认消息 master --->worker
case class RegisterFinish(masterURL:String)extends IntervalMessage
//发送心跳 worker --> worker(不用序列化)
case object SendHeartBeat
//发送心跳 worker ---> master
case class HeartBeat(id:String) extends IntervalMessage
//超时检查 master-->master
case object CheckTimeOut
封装信息的类
package com.zhiyoulxj.actor.akka
/*
* 用来封装master接收到的worker的信息
*/
class WorkInfo(val id:String,val mem:Int,val cores:Int) {
var LastBeat:Long=_
}
