Java 多线程进阶-并发编程(三) ForkJoinPool(JDK7以上)

• ForkJoinPool
  • Java7 提供另一种并行框架: 分解/治理/合并(分治编程)
  • 适用于一种特殊任务, 这类任务的计算量不好确定(最小任务可确定)
  • 关键类
    • ForkJoinPool 任务池
    • RecursiveAction
    • RecursiveTask
  • 代码示例

    package thread0418;
    
    import java.time.LocalDateTime;
    import java.util.concurrent.ExecutionException;
    import java.util.concurrent.ForkJoinPool;
    import java.util.concurrent.ForkJoinTask;
    import java.util.concurrent.RecursiveTask;
    
    /**
     * 分任务求和
     * 使用 java.util.concurrent.ForkJoinPool (分治编程)
     * 使用 RecursiveTask (可以递归的任务接口)
     * 1) 把任务分解 一直分解直到 分解到上下限差值小于等于5
     * 2) 完成任务
     * 3) 把结果合并
     */
    public class ForkJoinPoolDemo1 {
        public static void main(String[] args) throws ExecutionException, InterruptedException {
            // 创建执行线程池
            ForkJoinPool pool = new ForkJoinPool();
    //        ForkJoinPool pool = new ForkJoinPool(4); // parallelism
    
            // 创建任务
            SumTask111 task = new SumTask111(1, 100000000);
    
            // 提交任务
            ForkJoinTask<Long> result = pool.submit(task);
    
            do {
                System.out.printf(LocalDateTime.now() + " => " + "Main: PoolActiveThreadCount:%d" + "\n", pool.getActiveThreadCount());
                System.out.printf(LocalDateTime.now() + " => " + "Main: 并行度(PoolParallelism): %d" + "\n", pool.getParallelism());
                try {
                    Thread.sleep(50);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            } while (!task.isDone());
    
            // 输出结果
            System.out.println(LocalDateTime.now() + " => " + result.get().toString());
        }
    }
    
    class SumTask111 extends RecursiveTask<Long> {
        private int start;
        private int end;
    
        public SumTask111(int start, int end) {
            this.start = start;
            this.end = end;
        }
    
        public static final int threadHold = 5;
    
        @Override
        protected Long compute() {
            long sum = 0L;
            // 如果任务足够小, 直接执行
            boolean canCompute = (end - start) <= threadHold;
            if (canCompute) {
                for (int i = start; i <= end; i++) {
                    sum = sum + i;
                }
            } else {
                // 任务大于阈值, 分裂为 2 个任务
                int middle = (start + end) / 2;
                SumTask111 subTask1 = new SumTask111(start, middle);
                SumTask111 subTask2 = new SumTask111(middle + 1, end);
    
                invokeAll(subTask1, subTask2);
    
                Long sum1 = subTask1.join();
                Long sum2 = subTask2.join();
    
                // 结果合并
                sum = sum1 + sum2;
            }
            return sum;
        }
    }
  
  

• 总结
  • 了解 Fork-Join 和Executor 的区别
  • 控制任务分解粒度
  • 熟悉 Fork-Join 框架, 提高多线程执行效率.