Java并发编程——分支合并(ForkJoin)

ForkJoin并行执行任务！提高效率！大数据量！
任务的分割与合并主流程

ForkJoin特点：工作窃取
这里面维护的都是双端队列

测试代码：

//求和计算的任务
/*
 * 如何使用forkjoin
 * 1.forkjoinPool通过它来执行
 * 2.计算任务 forkjoinPool.execute(ForkJoinTask task)
 * 3.计算类要继承ForkJoinTask
 */

public class ForkJoinDemo extends RecursiveTask<Long> {
    private Long start;//1
    private Long end;//1990900000

    //临界值
    private long temp=10000;

    public ForkJoinDemo(Long start, Long end) {
        this.start = start;
        this.end = end;
    }

    //计算方法
    @Override
    protected Long compute() {
        if ((end-start)<temp){
            Long sum=0L;
            for (Long i = start; i <= end; i++) {
                sum+=i;
            }
            return sum;
        }else{//forkjoin递归
            long middle = (start + end) / 2;//中间值
            ForkJoinDemo task1 = new ForkJoinDemo(start, middle);
            task1.fork();//拆分任务，把任务压入线程队列
            ForkJoinDemo task2 = new ForkJoinDemo(middle+1, end);
            task2.fork();//拆分任务，把任务压入线程队列
            return task1.join() + task2.join();
        }
    }
}

public class Test {
    public static void main(String[] args) throws ExecutionException, InterruptedException {
        //test1();//4478
        //test2();//7173
        //test3();//184
    }

    //普通程序员
    public static void test1() {
        Long sum=0L;
        long start = System.currentTimeMillis();
        for (int i = 1; i <= 10_0000_0000; i++) {
            sum+=i;
        }
        long end = System.currentTimeMillis();
        System.out.println("sum="+ sum + "时间：" + (end - start));
    }
    //会使用forkjoin的
    public static void test2() throws ExecutionException, InterruptedException {
        long start = System.currentTimeMillis();
        ForkJoinPool forkJoinPool=new ForkJoinPool();
        ForkJoinTask<Long> task = new ForkJoinDemo(0L, 10_0000_0000L);
        ForkJoinTask<Long> submit = forkJoinPool.submit(task);//提交任务
        Long sum = submit.get();
        long end = System.currentTimeMillis();
        System.out.println("sum=" + sum + "时间：" + (end - start));
    }

    //stream并行流
    public static void test3() {
        long start = System.currentTimeMillis();
        Long sum=LongStream.rangeClosed(0,10_0000_0000).parallel().reduce(0,Long::sum);
        long end = System.currentTimeMillis();
        System.out.println("sum=" + sum + "时间：" + (end - start));
    }
}