这里有新鲜出炉的Java设计模式,程序狗速度看过来!
java 是一种可以撰写跨平台应用软件的面向对象的程序设计语言,是由Sun Microsystems公司于1995年5月推出的Java程序设计语言和Java平台(即JavaEE(j2ee), JavaME(j2me), JavaSE(j2se))的总称。
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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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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