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Java7之forkjoin简介_动力节点Java学院整理

投稿:mrr

Java7引入了Fork Join的概念,来更好的支持并行运算。接下来通过本文给大家分享Java7之forkjoin简介,感兴趣的朋友一起看看吧

Java7引入了Fork Join的概念,来更好的支持并行运算。顾名思义,Fork Join类似与流程语言的分支,合并的概念。也就是说Java7 SE原生支持了在一个主线程中开辟多个分支线程,并且根据分支线程的逻辑来等待(或者不等待)汇集,当然你也可以fork的某一个分支线程中再开辟Fork Join,这也就可以实现Fork Join的嵌套。

有两个核心类ForkJoinPool和ForkJoinTask。

ForkJoinPool实现了ExecutorService接口,起到线程池的作用。所以他的用法和Executor框架的使用时一样的,当然Fork Join本身就是Executor框架的扩展。ForkJoinPool有3个关键的方法,来启动线程,execute(…),invoke(…),submit(…)。具体描述如下:

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ForkJoinTask是分支合并的执行任何,分支合并的业务逻辑使用者可以再继承了这个抽先类之后,在抽象方法exec()中实现。其中exec()的返回结果和ForkJoinPool的执行调用方(execute(…),invoke(…),submit(…)),共同决定着线程是否阻塞,具体请看下面的测试用例。

首先,用户需要创建一个自己的ForkJoinTask。代码如下:

public class MyForkJoinTask extends ForkJoinTask {
 
 /**
  *
  */
 private static final long serialVersionUID = 1L;
 private V value;
 private boolean success = false;
 @Override
 public V getRawResult() {
  return value;
 }
 @Override
 protected void setRawResult(V value) {
  this.value = value;
 }
 @Override
 protected boolean exec() {
  System.out.println("exec");
  return this.success;
 }
 public boolean isSuccess() {
  return success;
 }
 public void setSuccess(boolean isSuccess) {
  this.success = isSuccess;
 }
}

测试ForkJoinPool.invoke(…):

 @Test
 public void testForkJoinInvoke() throws InterruptedException, ExecutionException {
  ForkJoinPool forkJoinPool = new ForkJoinPool();
  MyForkJoinTask task = new MyForkJoinTask();
  task.setSuccess(true);
  task.setRawResult("test");
  String invokeResult = forkJoinPool.invoke(task);
  assertEquals(invokeResult, "test");
 }
 @Test
 public void testForkJoinInvoke2() throws InterruptedException, ExecutionException {
  final ForkJoinPool forkJoinPool = new ForkJoinPool();
  final MyForkJoinTask task = new MyForkJoinTask();
  new Thread(new Runnable() {
   public void run() {
    try {
     Thread.sleep(1000);
    } catch (InterruptedException e) {
    }
    task.complete("test");
   }
  }).start();
  // exec()返回值是false,此处阻塞,直到另一个线程调用了task.complete(...)
  String result = forkJoinPool.invoke(task);
  System.out.println(result);
 }
 @Test
 public void testForkJoinSubmit() throws InterruptedException, ExecutionException {
  final ForkJoinPool forkJoinPool = new ForkJoinPool();
  final MyForkJoinTask task = new MyForkJoinTask();
  task.setSuccess(true); // 是否在此任务运行完毕后结束阻塞
  ForkJoinTask result = forkJoinPool.submit(task);
  result.get(); // 如果exec()返回值是false,在此处会阻塞,直到调用complete
 }

测试ForkJoinPool.submit(…):

@Test
 public void testForkJoinSubmit() throws InterruptedException, ExecutionException {
  final ForkJoinPool forkJoinPool = new ForkJoinPool();
  final MyForkJoinTask task = new MyForkJoinTask();
  task.setSuccess(true); // 是否在此任务运行完毕后结束阻塞
  ForkJoinTask result = forkJoinPool.submit(task);
  result.get(); // 如果exec()返回值是false,在此处会阻塞,直到调用complete
 }
 @Test
 public void testForkJoinSubmit2() throws InterruptedException, ExecutionException {
  final ForkJoinPool forkJoinPool = new ForkJoinPool();
  final MyForkJoinTask task = new MyForkJoinTask();
  forkJoinPool.submit(task);
  Thread.sleep(1000);
 }
 @Test
 public void testForkJoinSubmit3() throws InterruptedException, ExecutionException {
  final ForkJoinPool forkJoinPool = new ForkJoinPool();
  final MyForkJoinTask task = new MyForkJoinTask();
  new Thread(new Runnable() {
   public void run() {
    try {
     Thread.sleep(1000);
    } catch (InterruptedException e) {
    }
    task.complete("test");
   }
  }).start();
  ForkJoinTask result = forkJoinPool.submit(task);
  // exec()返回值是false,此处阻塞,直到另一个线程调用了task.complete(...)
  result.get();
  Thread.sleep(1000);
 }

测试ForkJoinPool.execute(…):

 @Test
 public void testForkJoinExecute() throws InterruptedException, ExecutionException {
  ForkJoinPool forkJoinPool = new ForkJoinPool();
  MyForkJoinTask task = new MyForkJoinTask();
  forkJoinPool.execute(task); // 异步执行,无视task.exec()返回值。
 }

在实际情况中,很多时候我们都需要面对经典的“分治”问题。要解决这类问题,主要任务通常被分解为多个任务块(分解阶段),其后每一小块任务被独立并行计算。一旦计算任务完成,每一快的结果会被合并或者解决(解决阶段)。ForkJoinTask天然就是为了支持“分治”问题的。

分支/合并的完整过程如下: 

下面列举一个分治算法的实例。

import java.util.Random;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveTask;
public class MaximumFinder extends RecursiveTask<Integer> {
 private static final int SEQUENTIAL_THRESHOLD = 5;
 private final int[] data;
 private final int start;
 private final int end;
 public MaximumFinder(int[] data, int start, int end) {
 this.data = data;
 this.start = start;
 this.end = end;
 }
 public MaximumFinder(int[] data) {
 this(data, 0, data.length);
 }
 @Override
 protected Integer compute() {
 final int length = end - start;
 if (length < SEQUENTIAL_THRESHOLD) {
  return computeDirectly();
 }
 final int split = length / 2;
 final MaximumFinder left = new MaximumFinder(data, start, start + split);
 left.fork();
 final MaximumFinder right = new MaximumFinder(data, start + split, end);
 return Math.max(right.compute(), left.join());
 }
 private Integer computeDirectly() {
 System.out.println(Thread.currentThread() + ' computing: ' + start
      + ' to ' + end);
 int max = Integer.MIN_VALUE;
 for (int i = start; i < end; i++) {
  if (data[i] > max) {
  max = data[i];
  }
 }
 return max;
 }
 public static void main(String[] args) {
 // create a random data set
 final int[] data = new int[1000];
 final Random random = new Random();
 for (int i = 0; i < data.length; i++) {
  data[i] = random.nextInt(100);
 }
 // submit the task to the pool
 final ForkJoinPool pool = new ForkJoinPool(4);
 final MaximumFinder finder = new MaximumFinder(data);
 System.out.println(pool.invoke(finder));
 }
}

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