ThreadPoolExecutor的部分源码分析

本文深入剖析了线程池的执行机制,包括任务提交、线程管理、任务队列处理及异常处理流程等核心内容。重点介绍了execute方法、addWorker方法的工作原理,以及Worker如何运行任务。

从execute开始看起

/**
     * Executes the given task sometime in the future.  The task
     * may execute in a new thread or in an existing pooled thread.
     *
     * If the task cannot be submitted for execution, either because this
     * executor has been shutdown or because its capacity has been reached,
     * the task is handled by the current {@code RejectedExecutionHandler}.
     *
     * @param command the task to execute
     * @throws RejectedExecutionException at discretion of
     *         {@code RejectedExecutionHandler}, if the task
     *         cannot be accepted for execution
     * @throws NullPointerException if {@code command} is null
     */
    public void execute(Runnable command) {
        if (command == null)
            throw new NullPointerException();
        /*
         * Proceed in 3 steps:
         *
         * 1. If fewer than corePoolSize threads are running, try to
         * start a new thread with the given command as its first
         * task.  The call to addWorker atomically checks runState and
         * workerCount, and so prevents false alarms that would add
         * threads when it shouldn't, by returning false.
         *
         * 2. If a task can be successfully queued, then we still need
         * to double-check whether we should have added a thread
         * (because existing ones died since last checking) or that
         * the pool shut down since entry into this method. So we
         * recheck state and if necessary roll back the enqueuing if
         * stopped, or start a new thread if there are none.
         *
         * 3. If we cannot queue task, then we try to add a new
         * thread.  If it fails, we know we are shut down or saturated
         * and so reject the task.
         */
        int c = ctl.get();
        if (workerCountOf(c) < corePoolSize) {//如果线程池里线程的数目小于corePoolSize,则增加新的线程,并在该线程中执行command
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
        if (isRunning(c) && workQueue.offer(command)) {//不满足上面的if判断,加入workQueue,等待在被已有的线程池执行
            int recheck = ctl.get();
            if (! isRunning(recheck) && remove(command))//recheck状态,不是running的话移除刚加入队尾的command
                reject(command);
            else if (workerCountOf(recheck) == 0)//没有线程则加一个线程
                addWorker(null, false);
        }
        else if (!addWorker(command, false))
            reject(command);
    }

接着看addWorker函数,增加WorkerCount的部分使用了CAS无锁编程。

使用lock实现线程同步有很多缺点:

* 产生竞争时,线程被阻塞等待,无法做到线程实时响应。

* dead lock。

* live lock。

* 优先级翻转。

* 使用不当,造成性能下降。

 

如果在不使用 lock 的情况下,实现变量同步,那就会避免很多问题。虽然目前来看,无锁编程并不能替代 lock。

/**
     * Checks if a new worker can be added with respect to current
     * pool state and the given bound (either core or maximum). If so,
     * the worker count is adjusted accordingly, and, if possible, a
     * new worker is created and started, running firstTask as its
     * first task. This method returns false if the pool is stopped or
     * eligible to shut down. It also returns false if the thread
     * factory fails to create a thread when asked.  If the thread
     * creation fails, either due to the thread factory returning
     * null, or due to an exception (typically OutOfMemoryError in
     * Thread.start()), we roll back cleanly.
     *
     * @param firstTask the task the new thread should run first (or
     * null if none). Workers are created with an initial first task
     * (in method execute()) to bypass queuing when there are fewer
     * than corePoolSize threads (in which case we always start one),
     * or when the queue is full (in which case we must bypass queue).
     * Initially idle threads are usually created via
     * prestartCoreThread or to replace other dying workers.
     *
     * @param core if true use corePoolSize as bound, else
     * maximumPoolSize. (A boolean indicator is used here rather than a
     * value to ensure reads of fresh values after checking other pool
     * state).
     * @return true if successful
     */
    private boolean addWorker(Runnable firstTask, boolean core) {
        // 下面是一段CAS无锁编程,在不使用 lock 的情况下,实现变量同步
        // ctl中pack了两个变量:
        // 1、workerCount, indicating the effective number of threads
        // 2、runState,    indicating whether running, shutting down etc
        // 外层循环用来判断runState有没有变化,内层循环用来判断workerCount有没有变化
        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);
                if (wc >= CAPACITY ||
                    wc >= (core ? corePoolSize : maximumPoolSize))
                    return false;
                if (compareAndIncrementWorkerCount(c))
                    break retry;

                // if (compareAndIncrementWorkerCount(c))判断失败,
                // ctrl在上次读出和试图加1期间发生了改变,证明有别的线程修改了ctrl,于是重新读ctl,重试加1
                c = ctl.get();  // Re-read ctl
                if (runStateOf(c) != rs)
                    continue retry;
                // else CAS failed due to workerCount change; retry inner loop (rs没变,只重试内循环)
            }
        }

        boolean workerStarted = false;
        boolean workerAdded = false;
        Worker w = null;
        try {
            w = new Worker(firstTask);//以firstTask作为第一个运行的任务,开启一条新线程
            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();

                        //新线程加入线程池,workers是一个HashSet,保存了线程池的所有线程,并且只能在mainLock的保护下访问
                        workers.add(w);
                        int s = workers.size();
                        if (s > largestPoolSize)
                            largestPoolSize = s;
                        workerAdded = true;
                    }
                } finally {
                    mainLock.unlock();
                }
                if (workerAdded) {
                    t.start();//Worker中的thread start
                    workerStarted = true;
                }
            }
        } finally {
            if (! workerStarted)
                addWorkerFailed(w);
        }
        return workerStarted;
    }


    /**
     * Attempts to CAS-increment the workerCount field of ctl.
     */
    private boolean compareAndIncrementWorkerCount(int expect) {
        return ctl.compareAndSet(expect, expect + 1);
    }

    /**
     * Set containing all worker threads in pool. Accessed only when
     * holding mainLock.
     */
    private final HashSet<Worker> workers = new HashSet<Worker>();


那等待队列中的Runnable什么时候才执行呢?答案在Worker中。Worker也是一个Runnable,并在run方法中调用了外部类的runWorker(this),把自己作为参数传进去

/**
     * Class Worker mainly maintains interrupt control state for
     * threads running tasks, along with other minor bookkeeping.
     * This class opportunistically extends AbstractQueuedSynchronizer
     * to simplify acquiring and releasing a lock surrounding each
     * task execution.  This protects against interrupts that are
     * intended to wake up a worker thread waiting for a task from
     * instead interrupting a task being run.  We implement a simple
     * non-reentrant mutual exclusion lock rather than use
     * ReentrantLock because we do not want worker tasks to be able to
     * reacquire the lock when they invoke pool control methods like
     * setCorePoolSize.  Additionally, to suppress interrupts until
     * the thread actually starts running tasks, we initialize lock
     * state to a negative value, and clear it upon start (in
     * runWorker).
     */
    private final class Worker
        extends AbstractQueuedSynchronizer
        implements Runnable
    {
        /**
         * This class will never be serialized, but we provide a
         * serialVersionUID to suppress a javac warning.
         */
        private static final long serialVersionUID = 6138294804551838833L;

        /** Thread this worker is running in.  Null if factory fails. */
        final Thread thread;
        /** Initial task to run.  Possibly null. */
        Runnable firstTask;
        /** Per-thread task counter */
        volatile long completedTasks;

        /**
         * Creates with given first task and thread from ThreadFactory.
         * @param firstTask the first task (null if none)
         */
        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);
        }

        // Lock methods
        //
        // The value 0 represents the unlocked state.
        // The value 1 represents the locked state.

        protected boolean isHeldExclusively() {
            return getState() != 0;
        }

        protected boolean tryAcquire(int unused) {
            if (compareAndSetState(0, 1)) {
                setExclusiveOwnerThread(Thread.currentThread());
                return true;
            }
            return false;
        }

        protected boolean tryRelease(int unused) {
            setExclusiveOwnerThread(null);
            setState(0);
            return true;
        }

        public void lock()        { acquire(1); }
        public boolean tryLock()  { return tryAcquire(1); }
        public void unlock()      { release(1); }
        public boolean isLocked() { return isHeldExclusively(); }

        void interruptIfStarted() {
            Thread t;
            if (getState() >= 0 && (t = thread) != null && !t.isInterrupted()) {
                try {
                    t.interrupt();
                } catch (SecurityException ignore) {
                }
            }
        }
    }

/**
     * Main worker run loop.  Repeatedly gets tasks from queue and
     * executes them, while coping with a number of issues:
     *
     * 1. We may start out with an initial task, in which case we
     * don't need to get the first one. Otherwise, as long as pool is
     * running, we get tasks from getTask. If it returns null then the
     * worker exits due to changed pool state or configuration
     * parameters.  Other exits result from exception throws in
     * external code, in which case completedAbruptly holds, which
     * usually leads processWorkerExit to replace this thread.
     *
     * 2. Before running any task, the lock is acquired to prevent
     * other pool interrupts while the task is executing, and then we
     * ensure that unless pool is stopping, this thread does not have
     * its interrupt set.
     *
     * 3. Each task run is preceded by a call to beforeExecute, which
     * might throw an exception, in which case we cause thread to die
     * (breaking loop with completedAbruptly true) without processing
     * the task.
     *
     * 4. Assuming beforeExecute completes normally, we run the task,
     * gathering any of its thrown exceptions to send to afterExecute.
     * We separately handle RuntimeException, Error (both of which the
     * specs guarantee that we trap) and arbitrary Throwables.
     * Because we cannot rethrow Throwables within Runnable.run, we
     * wrap them within Errors on the way out (to the thread's
     * UncaughtExceptionHandler).  Any thrown exception also
     * conservatively causes thread to die.
     *
     * 5. After task.run completes, we call afterExecute, which may
     * also throw an exception, which will also cause thread to
     * die. According to JLS Sec 14.20, this exception is the one that
     * will be in effect even if task.run throws.
     *
     * The net effect of the exception mechanics is that afterExecute
     * and the thread's UncaughtExceptionHandler have as accurate
     * information as we can provide about any problems encountered by
     * user code.
     *
     * @param w the worker
     */
    final void runWorker(Worker w) {
        Thread wt = Thread.currentThread();
        Runnable task = w.firstTask;
        w.firstTask = null;
        w.unlock(); // allow interrupts
        boolean completedAbruptly = true;
        try {
            // 下面的循环不断执行task.run()
            // 如果firstTask非空,这是第一个执行的task,第一次不用getTask()
            // 后面就通过getTask()获得新的task运行,直到getTask()为空,或者执行过程中有异常
            while (task != null || (task = getTask()) != null) {
                w.lock();
                // If pool is stopping, ensure thread is interrupted;
                // if not, ensure thread is not interrupted.  This
                // requires a recheck in second case to deal with
                // shutdownNow race while clearing interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    beforeExecute(wt, task);
                    Throwable thrown = null;
                    try {
                        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 {
                        afterExecute(task, thrown);
                    }
                } finally {
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
            completedAbruptly = false;
        } finally {
            processWorkerExit(w, completedAbruptly);
        }
    }
getTask()的核心就是从等待队列中取出Runnable,让线程池中的线程执行
/**
     * Performs blocking or timed wait for a task, depending on
     * current configuration settings, or returns null if this worker
     * must exit because of any of:
     * 1. There are more than maximumPoolSize workers (due to
     *    a call to setMaximumPoolSize).
     * 2. The pool is stopped.
     * 3. The pool is shutdown and the queue is empty.
     * 4. This worker timed out waiting for a task, and timed-out
     *    workers are subject to termination (that is,
     *    {@code allowCoreThreadTimeOut || workerCount > corePoolSize})
     *    both before and after the timed wait, and if the queue is
     *    non-empty, this worker is not the last thread in the pool.
     *
     * @return task, or null if the worker must exit, in which case
     *         workerCount is decremented
     */
    private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?

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

            // Check if queue empty only if necessary.
            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {//英文注释中的2、3场景
                decrementWorkerCount();
                return null;//这种情况下worker必须exit,workerCount也减一
            }

            int wc = workerCountOf(c);

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

            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {//英文注释中的1、4场景
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            try {
                //从队列中取出等待的Runnable
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }


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