JAVA并发编程之线程池

JAVA并发编程之线程池ThreadPoolExcutor

Executor接口

public interface Executor {

    void execute(Runnable command);
}

Executor提供了操作Runnable的接口，我们可以直接执行Runnable的方法，也可以创建Thread来执行Runnable，也可以根据实际情况把Runnable放入队列中按顺序执行。

ExecutorService接口

public interface ExecutorService extends Executor {

    void shutdown();
    List<Runnable> shutdownNow();
    boolean isShutdown();
    boolean isTerminated();
    boolean awaitTermination(long timeout, TimeUnit unit)
        throws InterruptedException;

     //提交有返回结果的任务，返回一个Future对象
    <T> Future<T> submit(Callable<T> task);
    //执行成功返回给定的结果
    <T> Future<T> submit(Runnable task, T result);
    
    Future<?> submit(Runnable task);

      //执行系列任务 并返回Future列表
    <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks)
        throws InterruptedException;

    //执行系列任务 设置超时时间
    <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks,
                                  long timeout, TimeUnit unit)
        throws InterruptedException;

    //执行系列任务 返回任意成功执行任务的结果
    <T> T invokeAny(Collection<? extends Callable<T>> tasks)
        throws InterruptedException, ExecutionException;

    <T> T invokeAny(Collection<? extends Callable<T>> tasks,
                    long timeout, TimeUnit unit)
        throws InterruptedException, ExecutionException, TimeoutException;
}

AbstractExecutorService抽象类

AbstractExecutorService实现了ExecutorService的submit(),invokeAny()、invokeAll()方法。

public abstract class AbstractExecutorService implements ExecutorService {

     //创建FutureTask对象
    protected <T> RunnableFuture<T> newTaskFor(Runnable runnable, T value) {
        return new FutureTask<T>(runnable, value);
    }

    protected <T> RunnableFuture<T> newTaskFor(Callable<T> callable) {
        return new FutureTask<T>(callable);
    }

    /**
     * @throws RejectedExecutionException {@inheritDoc}
     * @throws NullPointerException       {@inheritDoc}
     */
    public Future<?> submit(Runnable task) {
        if (task == null) throw new NullPointerException();
        RunnableFuture<Void> ftask = newTaskFor(task, null);
        execute(ftask);
        return ftask;
    }

    /**
     * @throws RejectedExecutionException {@inheritDoc}
     * @throws NullPointerException       {@inheritDoc}
     */
    public <T> Future<T> submit(Runnable task, T result) {
        if (task == null) throw new NullPointerException();
        RunnableFuture<T> ftask = newTaskFor(task, result);
        execute(ftask);
        return ftask;
    }

    /**
     * @throws RejectedExecutionException {@inheritDoc}
     * @throws NullPointerException       {@inheritDoc}
     */
    public <T> Future<T> submit(Callable<T> task) {
        if (task == null) throw new NullPointerException();
        RunnableFuture<T> ftask = newTaskFor(task);
        execute(ftask);
        return ftask;
    }

    /**
     * the main mechanics of invokeAny.
     */
    private <T> T doInvokeAny(Collection<? extends Callable<T>> tasks,
                              boolean timed, long nanos)
        throws InterruptedException, ExecutionException, TimeoutException {
        if (tasks == null)
            throw new NullPointerException();
        int ntasks = tasks.size();
        if (ntasks == 0)
            throw new IllegalArgumentException();
        ArrayList<Future<T>> futures = new ArrayList<Future<T>>(ntasks);
        ExecutorCompletionService<T> ecs =
            new ExecutorCompletionService<T>(this);

        // For efficiency, especially in executors with limited
        // parallelism, check to see if previously submitted tasks are
        // done before submitting more of them. This interleaving
        // plus the exception mechanics account for messiness of main
        // loop.

        try {
            // Record exceptions so that if we fail to obtain any
            // result, we can throw the last exception we got.
            ExecutionException ee = null;
            final long deadline = timed ? System.nanoTime() + nanos : 0L;
            Iterator<? extends Callable<T>> it = tasks.iterator();

            // Start one task for sure; the rest incrementally
            futures.add(ecs.submit(it.next()));
            --ntasks;
            int active = 1;

            for (;;) {
                Future<T> f = ecs.poll();
                if (f == null) {
                    if (ntasks > 0) {
                        --ntasks;
                        futures.add(ecs.submit(it.next()));
                        ++active;
                    }
                    else if (active == 0)
                        break;
                    else if (timed) {
                        f = ecs.poll(nanos, TimeUnit.NANOSECONDS);
                        if (f == null)
                            throw new TimeoutException();
                        nanos = deadline - System.nanoTime();
                    }
                    else
                        f = ecs.take();
                }
                if (f != null) {
                    --active;
                    try {
                        return f.get();
                    } catch (ExecutionException eex) {
                        ee = eex;
                    } catch (RuntimeException rex) {
                        ee = new ExecutionException(rex);
                    }
                }
            }

            if (ee == null)
                ee = new ExecutionException();
            throw ee;

        } finally {
            for (int i = 0, size = futures.size(); i < size; i++)
                futures.get(i).cancel(true);
        }
    }

    public <T> T invokeAny(Collection<? extends Callable<T>> tasks)
        throws InterruptedException, ExecutionException {
        try {
            return doInvokeAny(tasks, false, 0);
        } catch (TimeoutException cannotHappen) {
            assert false;
            return null;
        }
    }

    public <T> T invokeAny(Collection<? extends Callable<T>> tasks,
                           long timeout, TimeUnit unit)
        throws InterruptedException, ExecutionException, TimeoutException {
        return doInvokeAny(tasks, true, unit.toNanos(timeout));
    }

    public <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks)
        throws InterruptedException {
        if (tasks == null)
            throw new NullPointerException();
        ArrayList<Future<T>> futures = new ArrayList<Future<T>>(tasks.size());
        boolean done = false;
        try {
            for (Callable<T> t : tasks) {
                RunnableFuture<T> f = newTaskFor(t);
                futures.add(f);
                execute(f);
            }
            for (int i = 0, size = futures.size(); i < size; i++) {
                Future<T> f = futures.get(i);
                if (!f.isDone()) {
                    try {
                        f.get();
                    } catch (CancellationException ignore) {
                    } catch (ExecutionException ignore) {
                    }
                }
            }
            done = true;
            return futures;
        } finally {
            if (!done)
                for (int i = 0, size = futures.size(); i < size; i++)
                    futures.get(i).cancel(true);
        }
    }

    public <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks,
                                         long timeout, TimeUnit unit)
        throws InterruptedException {
        if (tasks == null)
            throw new NullPointerException();
        long nanos = unit.toNanos(timeout);
        ArrayList<Future<T>> futures = new ArrayList<Future<T>>(tasks.size());
        boolean done = false;
        try {
            for (Callable<T> t : tasks)
                futures.add(newTaskFor(t));

            final long deadline = System.nanoTime() + nanos;
            final int size = futures.size();

            // Interleave time checks and calls to execute in case
            // executor doesn't have any/much parallelism.
            for (int i = 0; i < size; i++) {
                execute((Runnable)futures.get(i));
                nanos = deadline - System.nanoTime();
                if (nanos <= 0L)
                    return futures;
            }

            for (int i = 0; i < size; i++) {
                Future<T> f = futures.get(i);
                if (!f.isDone()) {
                    if (nanos <= 0L)
                        return futures;
                    try {
                        f.get(nanos, TimeUnit.NANOSECONDS);
                    } catch (CancellationException ignore) {
                    } catch (ExecutionException ignore) {
                    } catch (TimeoutException toe) {
                        return futures;
                    }
                    nanos = deadline - System.nanoTime();
                }
            }
            done = true;
            return futures;
        } finally {
            if (!done)
                for (int i = 0, size = futures.size(); i < size; i++)
                    futures.get(i).cancel(true);
        }
    }

}

ThreadPoolExecutor实现类

线程池的状态、数量

//  线程池的状态由ctl是一个由workCount、runState两个字段包装后的AtomicInteger值
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
private static final int COUNT_BITS = Integer.SIZE - 3;//Integer.SIZE=32
////线程池最大线程数=536870911（2^29-1）,运算是左移29 位
private static final int CAPACITY   = (1 << COUNT_BITS) - 1;

// runState is stored in the high-order bits（32位中的高3位表示）
//runState控制生命周期
//RUNNING: 接受任务并执行队列中的任务
//SHUTDOWN:不接受任务但执行队列中的任务
//STOP:不接受任务也不执行队列中的任务并中断执行中的任务
//TIDYING:所有的任务被中止，workerCount是0，线程执行terminated()方法转换状态
//TERMINATED:terminated()执行完成
private static final int RUNNING    = -1 << COUNT_BITS;
private static final int SHUTDOWN   =  0 << COUNT_BITS;
private static final int STOP       =  1 << COUNT_BITS;
private static final int TIDYING    =  2 << COUNT_BITS;
private static final int TERMINATED =  3 << COUNT_BITS;

// Packing and unpacking ctl
private static int runStateOf(int c)     { return c & ~CAPACITY; }
private static int workerCountOf(int c)  { return c & CAPACITY; }
private static int ctlOf(int rs, int wc) { return rs | wc; }

/*
 * Bit field accessors that don't require unpacking ctl.
 * These depend on the bit layout and on workerCount being never negative.
 */

private static boolean runStateLessThan(int c, int s) {
    return c < s;
}

private static boolean runStateAtLeast(int c, int s) {
    return c >= s;
}

private static boolean isRunning(int c) {
    return c < SHUTDOWN;
}

构造函数

   /**
     *线程池所使用的缓冲队列 
     */
    private final BlockingQueue<Runnable> workQueue;
    
    /**
     * 线程工厂
     */
    private volatile ThreadFactory threadFactory;

    /**
     * 任务拒绝策略
     *  CallerRunsPolicy:执行excute的线程直接执行该任务
     *  AbortPolicy:拒绝任务并抛出RejectedExecutionException异常
     *  DiscardPolicy:处理程序拒绝任务,默默地丢弃了任务。
     *  DiscardOldestPolicy:抛弃队列第一个为执行的任务，提交该任务
     */
    private volatile RejectedExecutionHandler handler;

    /**
     * 空闲工作线程的空闲时间,当线程数量大于corePoolSize时回收线程
     * 如果allowCoreThreadTimeout设置为true，则所有线程均会退出直到线程数量为0
     */
    private volatile long keepAliveTime;

    /**
     * 默认false
     */
    private volatile boolean allowCoreThreadTimeOut;

    /**
     * 线程池维护线程的最少数量 
     */
    private volatile int corePoolSize;

    /**
     * 线程池维护线程的最大数量 
     */
    private volatile int maximumPoolSize;

    /**
     * 默认AbortPolicy策略
     */
    private static final RejectedExecutionHandler defaultHandler =
        new AbortPolicy();

    /**
     * 给定线程工厂和拒绝处理器
     */
    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> workQueue) {
        this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
             Executors.defaultThreadFactory(), defaultHandler);
    }

    /**
     *给定默认的拒绝处理器
     */
    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> workQueue,
                              ThreadFactory threadFactory) {
        this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
             threadFactory, defaultHandler);
    }

    /**
     * 给定默认的线程创建工厂
     */
    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> workQueue,
                              RejectedExecutionHandler handler) {
        this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
             Executors.defaultThreadFactory(), handler);
    }


/**
     * 根据给定的初始化参数创建一个ThreadPoolExecutor对象
     *
     * @param corePoolSize  核心线程池线程数量,即使线程池中存在空闲的线程也
     * 会创建新的线程来保持, 除非设置allowCoreThreadTimeOut
     * @param maximumPoolSize 线程池中允许的最大数量
     * @param keepAliveTime 线程池中超过corePoolSize数目的空闲线程最大存活时间
     * @param unit keepAliveTime的时间单位
     * @param workQueue 阻塞任务队列，队列只持有提交的Runnable任务
     * @param threadFactory  executor创建线程的工厂
     * @param handler 当线程和队列达到上线时任务线程的处理器
     */
    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> workQueue,
                              ThreadFactory threadFactory,
                              RejectedExecutionHandler handler) {
        if (corePoolSize < 0 ||
            maximumPoolSize <= 0 ||
            maximumPoolSize < corePoolSize ||
            keepAliveTime < 0)
            throw new IllegalArgumentException();
        if (workQueue == null || threadFactory == null || handler == null)
            throw new NullPointerException();
        this.corePoolSize = corePoolSize;
        this.maximumPoolSize = maximumPoolSize;
        this.workQueue = workQueue;
        this.keepAliveTime = unit.toNanos(keepAliveTime);
        this.threadFactory = threadFactory;
        this.handler = handler;
    }

任务的创建

public Future<?> submit(Runnable task) {
    if (task == null) throw new NullPointerException();
    RunnableFuture<Void> ftask = newTaskFor(task, null);
    execute(ftask);
    return ftask;
}

/**
 * 任务会在新的线程或者已存在的线程执行
 * 
 *如果任务未提交或者未执行，是线程池关闭或容量达到上限
 */
public void execute(Runnable command) {
    if (command == null)
        throw new NullPointerException();
    /*
     * Proceed in 3 steps:
     *
     * 1、如果线程的数量小于corePoolSize的数量，
     *    新建一个新的线程并将该任务当作它的第一个任务
     *    调用addWorker之前检查runState和workerCount
     * 2、任务成功加入队列，仍需要检查避免线程池在添加线程的过程中关闭
     *
     * 3、如果队列已满，我们创建新的线程，如果创建线程失败拒绝任务
     */
    int c = ctl.get();
    if (workerCountOf(c) < corePoolSize) {
        if (addWorker(command, true))
            return;
        c = ctl.get();
    }
    //当前线程数大于核心线程数或者addWroker失败，需要把任务提交到任务队列，等待Worker线程空闲后处理
    if (isRunning(c) && workQueue.offer(command)) {
        int recheck = ctl.get();
        //检查线程池是否关闭，若关闭并且线程没有被执行则删除这个任务
        if (! isRunning(recheck) && remove(command))
            reject(command);
        //如果当前线程池数量为0则创建新线程（刚加入队列的任务也应该执行完成）。
        else if (workerCountOf(recheck) == 0)
            addWorker(null, false);
    }
    //线程数量大于corePoolSize并且队列已满
    else if (!addWorker(command, false))
    //如是提交任务失败则调用reject处理失败任务
        reject(command);
}



/*
 *
 * @param firstTask 
 *
 * @param 
 */
private boolean addWorker(Runnable firstTask, boolean core) {
    retry:
    for (;;) {
        int c = ctl.get();
        int rs = runStateOf(c);

        // Check if queue empty only if necessary.
        if (rs >= SHUTDOWN &&
            ! (rs == SHUTDOWN &&
               firstTask == null &&
               ! workQueue.isEmpty()))
            return false;

        for (;;) {
            int wc = workerCountOf(c);
            //线程数量达到上限
            //core true表示添加任务时线程数量小于corePoolSize，并使用corePoolSize来检查线程池状态；
            //   false则使用maximumPoolSize
            if (wc >= CAPACITY ||
                wc >= (core ? corePoolSize : maximumPoolSize))
                return false;
           //cas修改增加线程池所拥有的线程数（CAS不懂）
            if (compareAndIncrementWorkerCount(c))
                break retry;
            c = ctl.get();  // Re-read ctl
            if (runStateOf(c) != rs)
                continue retry;
            // else CAS failed due to workerCount change; retry inner loop
        }
    }

    boolean workerStarted = false;
    boolean workerAdded = false;
    Worker w = null;
    try {
    //用firstTask创建Worker
        w = new Worker(firstTask);
        final Thread t = w.thread;
        if (t != null) {
            final ReentrantLock mainLock = this.mainLock;
            mainLock.lock();
            try {
                // Recheck while holding lock.
                // Back out on ThreadFactory failure or if
                // shut down before lock acquired.
                int rs = runStateOf(ctl.get());

                if (rs < SHUTDOWN ||
                    (rs == SHUTDOWN && firstTask == null)) {
                    if (t.isAlive()) // precheck that t is startable
                        throw new IllegalThreadStateException();
                    //workers其实是线程存储
                    workers.add(w);
                    int s = workers.size();
                    if (s > largestPoolSize)
                        largestPoolSize = s;
                    workerAdded = true;
                }
            } finally {
                mainLock.unlock();
            }
            if (workerAdded) {
            //启动任务线程
                t.start();
                workerStarted = true;
            }
        }
    } finally {
    //任务没有被启动，从workers中删除，类似回滚操作
        if (! workerStarted)
            addWorkerFailed(w);
    }
    return workerStarted;
}

任务的创建总结：

• 当前线程池中的数量小于corePoolSize，创建并添加的任务。

• 当前线程池中的数量大于等于corePoolSize，缓冲队列workQueue未满，那么任务被放入缓冲队列、等待任务调度执行。

• 当前线程池中的数量大于等corePoolSize，缓冲队列workQueue已满，并且线程池中的数量小于maximumPoolSize，新提交任务会创建新线程执行任务。

  *果当前线程池中的数量大于等corePoolSize，缓冲队列workQueue已满，并且线程池中的数量等于maximumPoolSize，新提交任务由Handler处理。

不管什么条件，添加任务的过程总是不停的检查来确保线程池是正常状态，否则不会添加任务。

任务执行

想要看线程是如何运行的就必须看一下Worker的构造函数

private final class Worker extends AbstractQueuedSynchronizer implements Runnable {

        final Thread thread;
    
        Runnable firstTask;
        /** 记录该线程完成了多少个任务(也就是每一个线程) */
        volatile long completedTasks;

        /**
         * 创建一个Thread时候把this传入，
         * 这样的话如果我调用Worker.thread.start()就相当于该线程会执行Worker里的run方法了
         */
        Worker(Runnable firstTask) {
            setState(-1); // inhibit interrupts until runWorker
            this.firstTask = firstTask;
            this.thread = getThreadFactory().newThread(this);
        }

        /** Delegates main run loop to outer runWorker  */
        public void run() {
            runWorker(this);
        }
}

下面详细分析一下runWorker

final void runWorker(Worker w) {
// 当前线程为什么不是从Worker中取出来？
    Thread wt = Thread.currentThread();
    Runnable task = w.firstTask;
    w.firstTask = null;
    w.unlock(); // allow interrupts
    boolean completedAbruptly = true;
    try {
       //如果存在firstTask则直接执行该任务，否则从任务队列里阻塞获取任务执行
        while (task != null || (task = getTask()) != null) {
            w.lock();
            //线程池状态已被标为停止 或 线程中断 的情况下，如果当前线程没有被中断则中断当前线程
            if ((runStateAtLeast(ctl.get(), STOP) ||
                 (Thread.interrupted() &&
                  runStateAtLeast(ctl.get(), STOP))) &&
                !wt.isInterrupted())
                wt.interrupt();
            try {
            //预留方法，子类继承实现
                beforeExecute(wt, task);
                Throwable thrown = null;
                try {
                //执行任务
                    task.run();
                } catch (RuntimeException x) {
                    thrown = x; throw x;
                } catch (Error x) {
                    thrown = x; throw x;
                } catch (Throwable x) {
                    thrown = x; throw new Error(x);
                } finally {
                // //预留方法，子类继承实现
                    afterExecute(task, thrown);
                }
            } finally {
                task = null;
                w.completedTasks++;
                w.unlock();
            }
        }
        completedAbruptly = false;
    } finally {
        processWorkerExit(w, completedAbruptly);
    }
}

下面看看getTask是如何从堵塞队列取出任务的

private Runnable getTask() {
    boolean timedOut = false; // Did the last poll() time out?

    for (;;) {
        int c = ctl.get();
        int rs = runStateOf(c);

        // 线程池关闭，队列中的任务仍需要执行
        //线程池停止，队列中的任务不再执行
        if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
            decrementWorkerCount();
            return null;
        }

        int wc = workerCountOf(c);

        // Are workers subject to culling?
        boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;

        if ((wc > maximumPoolSize || (timed && timedOut))
            && (wc > 1 || workQueue.isEmpty())) {
            if (compareAndDecrementWorkerCount(c))
                return null;
            continue;
        }

        try {
        //线程池中的线程超过设置的corePoolSize参数,
        //如果等待keepAliveTime时间后仍然没有新的任务分配给它，那么这个线程将会被回收
            Runnable r = timed ?
                workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                workQueue.take();
            if (r != null)
                return r;
            timedOut = true;
        } catch (InterruptedException retry) {
            timedOut = false;
        }
    }
}

Executors 线程池的配置

Executors在这里可以看做是一个工厂，生成不同的线程池，根据参数的不同生成不同的ThreadPoolExecutor：

创建一个线程数目固定的线程池，配置的corePoolSize与maximumPoolSize大小相同，同时使用了一个无界LinkedBlockingQueue存放阻塞任务，因此多余的任务将存在再阻塞队列，不会由RejectedExecutionHandler处理

//指定默认的线程工厂
public static ExecutorService newFixedThreadPool(int nThreads) {
    return new ThreadPoolExecutor(nThreads, nThreads,
                                  0L, TimeUnit.MILLISECONDS,
                                  new LinkedBlockingQueue<Runnable>());
}

public static ExecutorService newFixedThreadPool(int nThreads, ThreadFactory threadFactory) {
return new ThreadPoolExecutor(nThreads, nThreads,
                              0L, TimeUnit.MILLISECONDS,
                              new LinkedBlockingQueue<Runnable>(),
                              threadFactory);
}

创建一个只支持一个线程的线程池，配置corePoolSize=maximumPoolSize=1，无界阻塞队列LinkedBlockingQueue；保证任务由一个线程串行执行

public static ExecutorService newSingleThreadExecutor() {
    return new FinalizableDelegatedExecutorService
        (new ThreadPoolExecutor(1, 1,
                                0L, TimeUnit.MILLISECONDS,
                                new LinkedBlockingQueue<Runnable>()));
}
public static ExecutorService newSingleThreadExecutor(ThreadFactory threadFactory) {
    return new FinalizableDelegatedExecutorService
        (new ThreadPoolExecutor(1, 1,
                                0L, TimeUnit.MILLISECONDS,
                                new LinkedBlockingQueue<Runnable>(),
                                threadFactory));
}

创建一个缓冲功能的线程池，配置corePoolSize=0，maximumPoolSize=Integer.MAX_VALUE，keepAliveTime=60s,以及一个无容量的阻塞队列 SynchronousQueue，因此任务提交之后，将会创建新的线程执行；线程空闲超过60s将会销毁

public static ExecutorService newCachedThreadPool() {
    return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
                                  60L, TimeUnit.SECONDS,
                                  new SynchronousQueue<Runnable>());
}

public static ExecutorService newCachedThreadPool(ThreadFactory threadFactory) {
    return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
                                  60L, TimeUnit.SECONDS,
                                  new SynchronousQueue<Runnable>(),
                                  threadFactory);
}

创建一个有定时功能的线程池，配置corePoolSize，无界延迟阻塞队列DelayedWorkQueue；

public static ScheduledExecutorService newScheduledThreadPool(int corePoolSize) {
    return new ScheduledThreadPoolExecutor(corePoolSize);
}

public static ScheduledExecutorService newScheduledThreadPool(
        int corePoolSize, ThreadFactory threadFactory) {
    return new ScheduledThreadPoolExecutor(corePoolSize, threadFactory);
}

到这里，线程池的使用我们已经简单的了解了，ScheduledThreadPoolExecutor定时线程池与创建不同线程池时使用的QUeue在别的文章中分析。