Java在JDK7之后加入了并行计算的框架Fork/Join，可以解决我们系统中大数据计算的性能问题。Fork/Join采用的是分治法，Fork是将一个大任务拆分成若干个子任务，子任务分别去计算，而Join是获取到子任务的计算结果，然后合并，这个是递归的过程。子任务被分配到不同的核上执行时，效率最高。

package com.thread.forkjoin;import java.util.Arrays;
import java.util.Random;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveTask;/*** Java在JDK7之后加入了并行计算的框架Fork/Join，可以解决我们系统中大数据计算的性能问题。* Fork/Join采用的是分治法，Fork是将一个大任务拆分成若干个子任务，子任务分别去计算，而Join是获取到子任务的计算结果，然后合并，这个是递归的过程。* 子任务被分配到不同的核上执行时，效率最高。*/
public class ForkJoinTest extends RecursiveTask<Long> {private static final int THREADSHOLD = 50000;private long[] array;private int low;private int hight;public ForkJoinTest(long[] array, int low, int hight) {this.array = array;this.low = low;this.hight = hight;}@Overrideprotected Long compute() {long sum = 0;if (hight - low < THREADSHOLD) {for (int i = low; i < hight; i++) {sum += array[i];}} else {int middle = (low + hight) >>> 1;ForkJoinTest left = new ForkJoinTest(array, low, middle);ForkJoinTest right = new ForkJoinTest(array, middle + 1, hight);left.fork();right.fork();sum = left.join() + right.join();}return sum;}public static void main(String[] args) throws ExecutionException, InterruptedException {long[] array = genArray(1000000);System.out.println(Arrays.toString(array));ForkJoinTest forkJoinTest = new ForkJoinTest(array, 0, array.length - 1);long begin = System.currentTimeMillis();ForkJoinPool forkJoinPool = new ForkJoinPool();forkJoinPool.submit(forkJoinTest);Long result = forkJoinTest.get();long end = System.currentTimeMillis();System.out.println(String.format("结果 %s 耗时 %sms", result, end - begin));}private static long[] genArray(int size) {long[] array = new long[size];for (int i = 0; i < size; i++) {array[i] = new Random().nextLong();}return array;}
}