Java并发（三）线程池

            public
            class ThreadPoolExecutor extends AbstractExecutorService {
    /**
     * The main pool control state, ctl, is an atomic integer packing
     * two conceptual fields
     *   workerCount, indicating the effective number of threads
     *   runState,    indicating whether running, shutting down etc
     *
     * In order to pack them into one int, we limit workerCount to
     * (2^29)-1 (about 500 million) threads rather than (2^31)-1 (2
     * billion) otherwise representable. If this is ever an issue in
     * the future, the variable can be changed to be an AtomicLong,
     * and the shift/mask constants below adjusted. But until the need
     * arises, this code is a bit faster and simpler using an int.
     *
     * The workerCount is the number of workers that have been
     * permitted to start and not permitted to stop.  The value may be
     * transiently different from the actual number of live threads,
     * for example when a ThreadFactory fails to create a thread when
     * asked, and when exiting threads are still performing
     * bookkeeping before terminating. The user-visible pool size is
     * reported as the current size of the workers set.
     *
     * The runState provides the main lifecycle control, taking on values:
     *
     *   RUNNING:  Accept new tasks and process queued tasks
     *   SHUTDOWN: Don‘t accept new tasks, but process queued tasks
     *   STOP:     Don‘t accept new tasks, don‘t process queued tasks,
     *             and interrupt in-progress tasks
     *   TIDYING:  All tasks have terminated, workerCount is zero,
     *             the thread transitioning to state TIDYING
     *             will run the terminated() hook method
     *   TERMINATED: terminated() has completed
     *
     * The numerical order among these values matters, to allow
     * ordered comparisons. The runState monotonically increases over
     * time, but need not hit each state. The transitions are:
     *
     * RUNNING -> SHUTDOWN
     *    On invocation of shutdown(), perhaps implicitly in finalize()
     * (RUNNING or SHUTDOWN) -> STOP
     *    On invocation of shutdownNow()
     * SHUTDOWN -> TIDYING
     *    When both queue and pool are empty
     * STOP -> TIDYING
     *    When pool is empty
     * TIDYING -> TERMINATED
     *    When the terminated() hook method has completed
     *
     * Threads waiting in awaitTermination() will return when the
     * state reaches TERMINATED.
     *
     * Detecting the transition from SHUTDOWN to TIDYING is less
     * straightforward than you‘d like because the queue may become
     * empty after non-empty and vice versa during SHUTDOWN state, but
     * we can only terminate if, after seeing that it is empty, we see
     * that workerCount is 0 (which sometimes entails a recheck -- see
     * below).
     *//**
     * ctl 为原子类型的变量, 有两个概念
     * workerCount, 表示有效的线程数
     * runState, 表示线程状态, 是否正在运行, 关闭等
     */privatefinal AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
    // 29privatestaticfinalint COUNT_BITS = Integer.SIZE - 3;
    // 容量 22?-1privatestaticfinalint CAPACITY   = (1 << COUNT_BITS) - 1;

    // runState is stored in the high-order bits
    // 线程池的五种状态
    // 即高3位为111, 接受新任务并处理排队任务privatestaticfinalint RUNNING    = -1 << COUNT_BITS;
    // 即高3位为000, 不接受新任务, 但处理排队任务privatestaticfinalint SHUTDOWN   =  0 << COUNT_BITS;
    // 即高3位为001, 不接受新任务, 不处理排队任务, 并中断正在进行的任务privatestaticfinalint STOP       =  1 << COUNT_BITS;
    // 即高3位为010, 所有任务都已终止, 工作线程为0, 线程转换到状态TIDYING, 将运行terminate()钩子方法privatestaticfinalint TIDYING    =  2 << COUNT_BITS;
    // 即高3位为011, 标识terminate（）已经完成privatestaticfinalint TERMINATED =  3 << COUNT_BITS;

    // Packing and unpacking ctl 用来计算线程的方法privatestaticint runStateOf(int c)     { return c & ~CAPACITY; }
    privatestaticint workerCountOf(int c)  { return c & CAPACITY; }
    privatestaticint ctlOf(int rs, int wc) { return rs | wc; }

    ... ...
}

            /**
            
 * 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) {
    
            //
             空则抛出异常
            if (command == null)
        thrownew 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.
     */// 获取当前线程池的状态int c = ctl.get();
    // 计算工作线程数 并判断是否小于核心线程数if (workerCountOf(c) < corePoolSize) {
        // addWorker提交任务, 提交成功则结束if (addWorker(command, true))
            return;
        // 提交失败再次获取当前状态
        c = ctl.get();
    }
    // 判断线程状态, 并插入队列, 失败则移除if (isRunning(c) && workQueue.offer(command)) {
        // 再次获取状态int recheck = ctl.get();
        // 如果状态不是RUNNING, 并移除失败if (! isRunning(recheck) && remove(command))
            // 调用拒绝策略            reject(command);
            // 如果工作线程为0 则调用 addWorkerelseif (workerCountOf(recheck) == 0)
            addWorker(null, false);
    }
    // 提交任务失败 走拒绝策略elseif (!addWorker(command, false))
        reject(command);
}

            /**
            
 * 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
 
            */
            /**
            
 * 检查任务是否可以提交
 
            */
            private
            boolean addWorker(Runnable firstTask, boolean core) {
    retry:
    // 外层循环for (;;) {
        // 获取当前状态int c = ctl.get();
        int rs = runStateOf(c);

        // Check if queue empty only if necessary. 检查线程池是否关闭if (rs >= SHUTDOWN &&
            ! (rs == SHUTDOWN &&
               firstTask == null &&
               ! workQueue.isEmpty()))
            returnfalse;
        // 内层循环for (;;) {
            int wc = workerCountOf(c);
            // 工作线程大于容量 或者大于 核心或最大线程数if (wc >= CAPACITY ||
                wc >= (core ? corePoolSize : maximumPoolSize))
                returnfalse;
            // CAS 线程数增加, 成功则调到外层循环if (compareAndIncrementWorkerCount(c))
                break retry;
            // 失败则再次获取线程状态
            c = ctl.get();  // Re-read ctl
            // 不相等则重新走外层循环if (runStateOf(c) != rs)
                continue retry;
            // else CAS failed due to workerCount change; retry inner loop        }
    }

    /**
     * 创建新worker 开始新线程
     */boolean workerStarted = false;
    boolean workerAdded = false;
    Worker w = null;
    try {
        w = new Worker(firstTask);
        final Thread t = w.thread;
        if (t != null) {
            final ReentrantLock mainLock = this.mainLock;
            // 加锁            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)) {
                    // 判断线程是否存活, 已存活抛出非法异常if (t.isAlive()) // precheck that t is startablethrownew IllegalThreadStateException();
                    //  设置包含池中的所有工作线程。仅在持有mainLock时访问 workers是 HashSet 集合                    workers.add(w);
                    int s = workers.size();
                    // 设置池最大大小, 并将 workerAdded设置为 trueif (s > largestPoolSize)
                        largestPoolSize = s;
                    workerAdded = true;
                }
            } finally {
                // 解锁                mainLock.unlock();
            }
            // 添加成功 开始启动线程 并将 workerStarted 设置为 trueif (workerAdded) {
                t.start();
                workerStarted = true;
            }
        }
    } finally {
        // 启动线程失败if (! workerStarted)
            addWorkerFailed(w);
    }
    return workerStarted;
}

            /**
            
 * 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
{
    ... ...

    
            /**
             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 interruptsboolean completedAbruptly = true;
    try {
        // getTask()方法循环获取工作队列的任务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 interruptif ((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; thrownew Error(x);
                } finally {
                    afterExecute(task, thrown);
                }
            } finally {
                task = null;
                w.completedTasks++;
                w.unlock();
            }
        }
        completedAbruptly = false;
    } finally {
        processWorkerExit(w, completedAbruptly);
    }
}

            /**
            
 * 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();
            returnnull;
        }

        int wc = workerCountOf(c);

        // Are workers subject to culling?
        // 允许核心线程超时 或者当前线程数大于核心线程数boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;

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

        try {
            Runnable r = timed ?
                    // 从工作队列poll任务，不阻塞                workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    // 阻塞等待任务                workQueue.take();
            if (r != null)
                return r;
            timedOut = true;
        } catch (InterruptedException retry) {
            timedOut = false;
        }
    }
}

            new
             ThreadPoolExecutor(corePoolSize, maximumPoolSize, keepAliveTime,
milliseconds,runnableTaskQueue, handler);
        

            new ThreadFactoryBuilder().setNameFormat("XX-task-%d").build();

threadsPool.execute(new Runnable() {
                    @Override
                    publicvoid run() {
                        // TODO Auto-generated method stub                    }
});

Future<Object> future = executor.submit(harReturnValuetask);
        try {
            Object s = future.get();
        } catch (InterruptedException e) {
            // 处理中断异常
        } catch (ExecutionException e) {
            // 处理无法执行任务异常
        } finally {
            // 关闭线程池            executor.shutdown();
        }

            protected
            void beforeExecute(Thread t, Runnable r) { }