线程在线程池中休眠

Question

假设我们有一个线程池数量有限的线程。

Executor executor = Executors.newFixedThreadPool(3);

现在假设其中一项活动任务必须休眠 3 秒（无论出于何种原因）。

executor.execute(() -> {
    try {
        Thread.sleep(3000L);
    } catch (InterruptedException ignore) {}
});

我们如何实现这样一个线程池，当一个任务休眠（或等待监视器/条件）时，线程¹可以有效地用于运行另一个任务？

¹ 通过螺纹我的意思不是“物理” Java线程，因为当线程处于睡眠状态，这将是不可能的。我的意思是，线程池有一个抽象的实现，它实际上似乎允许一个线程在睡眠期间运行另一个任务。关键是总是有 N 个同时运行（非休眠）的任务。

有点类似于监视器处理对关键区域的访问的方式：

• 如果一个线程等待一个资源，该资源可以被另一个线程使用。
• 如果线程得到通知，它就会被放入等待集中以（重新）获得对该资源的访问权。

Answer 1

我实现了一个最小的工作示例，它基本上可以实现我认为您想要的功能。

一个 Task 接口（很像 runnable 接口，只是带有传递的 Context 来执行等待）

package io.medev.stackoverflow;

import java.util.concurrent.TimeUnit;
import java.util.function.BooleanSupplier;

public interface Task {

    /**
     * Wraps the given runnable into a Task with a not guessable execution time (meaning guessExecutionTime always returns Long.MAX_VALUE)
     * @param runnable The runnable to wrap
     * @return a Task wrapping this runnable
     */
    static Task wrap(Runnable runnable) {
        return wrap(runnable, Long.MAX_VALUE);
    }

    /**
     * Wraps the given runnable using the given guessedExecutionTimeMillis
     * @param runnable The runnable to wrap
     * @param guessedExecutionTimeMillis The guessed execution time in millis for this runnable
     * @return a Task wrapping this runnable
     */
    static Task wrap(Runnable runnable, long guessedExecutionTimeMillis) {
        return new Task() {
            @Override
            public long guessExecutionTimeMillis() {
                return guessedExecutionTimeMillis;
            }

            @Override
            public void run(Context context) {
                runnable.run();
            }
        };
    }

    /**
     * Should more or less guess how long this task will run
     * @return The execution time of this Task in milliseconds
     */
    long guessExecutionTimeMillis();

    void run(Context context);

    interface Context {

        /**
         * Block until the condition is met, giving other Tasks time to execute
         * @param condition the condition to check
         * @throws InterruptedException if the current thread is interrupted
         */
        void idle(BooleanSupplier condition) throws InterruptedException;

        /**
         * Blocks at least for the given duration, giving other Tasks time to execute
         * @param timeout
         * @param timeUnit
         * @throws InterruptedException if the current thread is interrupted
         */
        void idle(long timeout, TimeUnit timeUnit) throws InterruptedException;

        /**
         * Blocks until the condition is met or the timeout expires, giving other Tasks time to execute
         * @param condition the condition to check
         * @param timeout
         * @param timeUnit
         * @throws InterruptedException if the current thread is interrupted
         */
        void idle(BooleanSupplier condition, long timeout, TimeUnit timeUnit) throws InterruptedException;
    }
}

还有一个基本的固定线程池执行器 - 但你必须依赖于这里的具体实现：

package io.medev.stackoverflow;

import java.util.Comparator;
import java.util.concurrent.*;
import java.util.function.BooleanSupplier;

public class TimeEfficientExecutor implements Executor {

    private final BlockingQueue<Task> taskQueue;
    private final CountDownLatch latch;
    private volatile boolean alive;

    public TimeEfficientExecutor(int threads) {
        this.taskQueue = new PriorityBlockingQueue<>(10, Comparator.comparingLong(Task::guessExecutionTimeMillis));
        this.latch = new CountDownLatch(threads);
        this.alive = true;

        for (int i = 0; i < threads; i++) {
            Thread thread = new Thread(new TimeEfficientExecutorRunnable());
            thread.start();
        }
    }

    @Override
    public void execute(Runnable runnable) {
        execute(Task.wrap(runnable));
    }

    public void execute(Runnable runnable, long guessedExecutionTimeMillis) {
        execute(Task.wrap(runnable, guessedExecutionTimeMillis));
    }

    public void execute(Task task) {
        this.taskQueue.offer(task);
    }

    public void shutdown() {
        this.alive = false;
    }

    public void awaitShutdown() throws InterruptedException {
        this.latch.await();
    }

    public void awaitShutdown(long timeout, TimeUnit timeUnit) throws InterruptedException {
        this.latch.await(timeout, timeUnit);
    }

    private class TimeEfficientExecutorRunnable implements Runnable {

        @Override
        public void run() {
            try {
                while (TimeEfficientExecutor.this.alive) {
                    Task task = TimeEfficientExecutor.this.taskQueue.poll();

                    if (task != null) {
                        try {
                            task.run(new IdleTaskContext());
                        } catch (Exception e) {
                            // TODO: logging
                        }
                    }
                }
            } finally {
                TimeEfficientExecutor.this.latch.countDown();
            }
        }
    }

    private class IdleTaskContext implements Task.Context {

        @Override
        public void idle(BooleanSupplier condition) throws InterruptedException {
            idle(condition, Long.MAX_VALUE);
        }

        @Override
        public void idle(long timeout, TimeUnit timeUnit) throws InterruptedException {
            idle(() -> false, timeout, timeUnit);
        }

        @Override
        public void idle(BooleanSupplier condition, long timeout, TimeUnit timeUnit) throws InterruptedException {
            idle(condition, System.currentTimeMillis() + timeUnit.toMillis(timeout));
        }

        private void idle(BooleanSupplier condition, long idleUntilTs) throws InterruptedException {
            long leftMillis = idleUntilTs - System.currentTimeMillis();

            while (TimeEfficientExecutor.this.alive && !condition.getAsBoolean() && leftMillis >= 1L) {
                Task task = TimeEfficientExecutor.this.taskQueue.poll(leftMillis, TimeUnit.MILLISECONDS);
                leftMillis = idleUntilTs - System.currentTimeMillis();

                if (task != null) {
                    if (leftMillis >= 1L && task.guessExecutionTimeMillis() < leftMillis) {
                        task.run(new IdleTaskContext());
                    } else {
                        TimeEfficientExecutor.this.taskQueue.offer(task);
                    }
                }
            }
        }
    }
}

请注意，您不能只向下执行堆栈 - 并且堆栈绑定到正在执行的线程。这意味着如果某些“子”任务开始空闲，则不可能跳回底层空闲任务。您必须“信任”每个任务在guessExecutionTimeMillis-Method 中返回的内容。

由于Executor中使用了PriorityQueue，队列将始终返回执行时间最短的任务。