Java中 ThreadPoolExecutor 类学习笔记

 

Java中 ThreadPoolExecutor 类学习笔记

1、定义

Java中的线程池。ThreadPoolExecutor类是接口Executor的实现类。如下图所示： 

2、作用

线程池解决两个不同的问题：由于每个任务的调用开销减少，它们通常在执行大量异步任务时提供改进的性能，并且它们提供了一种限制和管理资源（包括执行一个任务。 每个ThreadPoolExecutor还维护一些基本统计信息，例如已完成任务的数量。

3、创建类解释

ThreadPoolExecutor extends AbstractExecutorService。

构造方法：

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;
    }

其中：

1. 　　corePoolSize ： 线程池的核心线程数，即使空闲时仍保留在池中的线程数，除非设置 allowCoreThreadTimeOut.
2. 　　maximumPoolSize : 池中允许的最大线程数
3.        keepAliveTime :  线程的存活时间。当线程池里的线程数大于corePoolSize时，如果等了keepAliveTime时长还没有任务可执行，则线程退出。
4.        unit  : 指定keepAliveTime的单位
5.        workQueue :  一个阻塞队列，提交的任务将会被放到这个队列里
6.    　threadFactory :  执行程序创建新线程时使用的工厂
7.        handler : 执行被阻止时使用的处理程序，因为达到线程限制和队列容量 

4.线程池执行流程

任务被提交到线程池，会先判断当前线程数量是否小于corePoolSize，如果小于则创建线程来执行提交的任务，否则将任务放入workQueue队列，如果workQueue满了，则判断当前线程数量是否小于maximumPoolSize,如果小于则创建线程执行任务，否则就会调用handler，以表示线程池拒绝接收任务。

 5.线程池的几个主要方法分析

5.1 主方法：ThreadPoolExector的execute

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.
         */
　　　　　　
　　　　　//1 当前运行的线程数量小于核心线程数量，直接将任务加入worker启动运行。
        int c = ctl.get();
        if (workerCountOf(c) < corePoolSize) {
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
　

　　/**
　　2 运行线程数量大于核心线程数量时，上面的if分支针对大于corePoolSize，并且缓存队列加入任务操作成功的情况。
　　运行中并且将任务加入缓冲队列成功，正常来说这样已经完成了处理逻辑。
　　但是为了保险起见，增加了状态出现异常的确认判断，如果状态出现异常会继续remove操作，如果执行true，则按照拒绝处理策略驳回任务；
　　*/

        if (isRunning(c) && workQueue.offer(command)) {

int recheck = ctl.get();
            if (! isRunning(recheck) && remove(command))
                reject(command);
            else if (workerCountOf(recheck) == 0)
                addWorker(null, false);
        }

　　/**
　　3 这里针对运行线程数量超过了corePoolSize，并且缓存队列也已经放满的情况。
　　注意第二个参数是false，可以在下面addWorker方法看到，就是针对线程池最大线程数量maximumPoolSize的判断。
　　*/

　　else if (!addWorker(command, false))
            reject(command);
　　}
}

 5.2 关键方法：ThreadPoolExector的addWorker（增加工作线程）

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);
                if (wc >= CAPACITY ||
                    wc >= (core ? corePoolSize : maximumPoolSize)) //创建非核心线程时，即core等于false。判断当前线程数是否大于等于maximumPoolSize，如果大于等于则返回false
                    return false;
                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 {
            w = new Worker(firstTask);
            final Thread t = w.thread;//创建Worker对象，同时也会实例化一个Thread，并启动。
            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.add(w);
                        int s = workers.size();
                        if (s > largestPoolSize)
                            largestPoolSize = s;
                        workerAdded = true;
                    }
                } finally {
                    mainLock.unlock();
                }
                if (workerAdded) {
                    t.start();
                    workerStarted = true;
                }
            }
        } finally {
            if (! workerStarted)
                addWorkerFailed(w);
        }
        return workerStarted;
    }

5.3 Worker中的runWorker方法，也是worker中的run方法主体。

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

/**
     * 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 {
            while (task != null || (task = getTask()) != null) {//线程调用runWoker，会while循环调用getTask方法从workerQueue里读取任务，然后执行任务
                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();//只要getTask方法不返回null,此线程就不会退出。
                    } 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);
        }
 }

5.4 getTask方法实现

     * 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())) {
                decrementWorkerCount();
                return null;
            }

            int wc = workerCountOf(c);

            // Are workers subject to culling?
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;
　　　　　　　
　　　　　　　//如果运行线程数超过了最大线程数，但是缓存队列已经空了，这时递减worker数量。
　　　　　　　//如果有设置允许线程超时或者线程数量超过了核心线程数量，并且线程在规定时间内均未poll到任务且队列为空则递减worker数量

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

            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
  }