线程池技术之：ThreadPoolExecutor 源码解析
java中的所说的线程池，一般都是围绕着 ThreadPoolExecutor 来展开的。其他的实现基本都是基于它，或者模仿它的。所以只要理解 ThreadPoolExecutor, 就相当于完全理解了线程池的精髓。
其实要理解一个东西，一般地，我们最好是要抱着自己的疑问或者理解去的。否则，往往收获甚微。
理解 ThreadPoolExecutor, 我们可以先理解一个线程池的意义: 本质上是提供预先定义好的n个线程，供调用方直接运行任务的一个工具。
线程池解决的问题:
1. 提高任务执行的响应速度，降低资源消耗。任务执行时，直接立即使用线程池提供的线程运行，避免了临时创建线程的CPU/内存开销，达到快速响应的效果。
2. 提高线程的可管理性。线程总数可预知，避免用户主动创建无限多线程导致死机风险，还可以进行线程统一的分配、调优和监控。
3. 避免对资源的过度使用。在超出预期的请求任务情况，响应策略可控。
线程池提供的核心接口:
要想使用线程池，自然是要理解其接口的。一般我们使用 ExecotorService 进行线程池的调用。然而，我们并不针对初学者。
整体的接口如下:
我们就挑几个常用接口探讨下：
submit(Runnable task): 提交一个无需返回结果的任务。
submit(Callable<T> task): 提交一个有返回结果的任务。
invokeAll(Collection<? extends Callable<T>> tasks, long, TimeUnit): 同时执行n个任务并返回结果列表。
shutdown(): 关闭线程程池。
awaitTermination(long timeout, TimeUnit unit): 等待关闭结果，最长不超过timeout时间。
以上是ThreadPoolExector 提供的特性，针对以上特性。
我们应该要有自己的几个实现思路或疑问:
1. 线程池如何接受任务？
2. 线程如何运行任务？
3. 线程池如何关闭？
接下来，就让我们带着疑问去看实现吧。
ThreadPoolExecutor 核心实现原理
1. 线程池的处理流程
我们首先重点要看的是，如何执行提交的任务。我可以通过下图来看看。
总结描述下就是:
1. 判断核心线程池是否已满，如果不是，则创建线程执行任务
2. 如果核心线程池满了，判断队列是否满了，如果队列没满，将任务放在队列中
3. 如果队列满了，则判断线程池是否已满，如果没满，创建线程执行任务
4. 如果线程池也满了，则按照拒绝策略对任务进行处理
另外，我们来看一下 ThreadPoolExecutor 的构造方法，因为这里会体现出每个属性的含义。
/** * Creates a new {@code ThreadPoolExecutor} with the given initial * parameters. * * @param corePoolSize the number of threads to keep in the pool, even * if they are idle, unless {@code allowCoreThreadTimeOut} is set * @param maximumPoolSize the maximum number of threads to allow in the * pool * @param keepAliveTime when the number of threads is greater than * the core, this is the maximum time that excess idle threads * will wait for new tasks before terminating. * @param unit the time unit for the {@code keepAliveTime} argument * @param workQueue the queue to use for holding tasks before they are * executed. This queue will hold only the {@code Runnable} * tasks submitted by the {@code execute} method. * @param threadFactory the factory to use when the executor * creates a new thread * @param handler the handler to use when execution is blocked * because the thread bounds and queue capacities are reached * @throws IllegalArgumentException if one of the following holds:<br> * {@code corePoolSize < 0}<br> * {@code keepAliveTime < 0}<br> * {@code maximumPoolSize <= 0}<br> * {@code maximumPoolSize < corePoolSize} * @throws NullPointerException if {@code workQueue} * or {@code threadFactory} or {@code handler} is null */ 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; }
从构造方法可以看出 ThreadPoolExecutor 的主要参数 7 个，在其注释上也有说明功能，咱们翻译下每个参数的功能:
corePoolSize: 线程池核心线程数（平时保留的线程数）,使用时机: 在初始时刻，每次请求进来都会创建一个线程直到达到该size maximumPoolSize: 线程池最大线程数,使用时机: 当workQueue都放不下时，启动新线程，直到最大线程数，此时到达线程池的极限 keepAliveTime/unit: 超出corePoolSize数量的线程的保留时间,unit为时间单位 workQueue: 阻塞队列，当核心线程数达到或者超出后，会先尝试将任务放入该队列由各线程自行消费; ArrayBlockingQueue: 构造函数一定要传大小 LinkedBlockingQueue: 构造函数不传大小会默认为65536（Integer.MAX_VALUE ），当大量请求任务时，容易造成 内存耗尽。 SynchronousQueue: 同步队列，一个没有存储空间的阻塞队列 ，将任务同步交付给工作线程。 PriorityBlockingQueue: 优先队列 threadFactory：线程工厂,用于线程需要创建时，调用其newThread()生产新线程使用 handler: 饱和策略，当队列已放不下任务，且创建的线程已达到 maximum 后，则不能再处理任务，直接将任务交给饱和策略 AbortPolicy: 直接抛弃（默认） CallerRunsPolicy: 用调用者的线程执行任务 DiscardOldestPolicy: 抛弃队列中最久的任务 DiscardPolicy: 抛弃当前任务
2. submit 流程详解
当调用 submit 方法，就是向线程池中提交一个任务，处理流程如步骤1所示。但是我们需要更深入理解。
submit 方法是定义在 AbstractExecutorService 中，最终调用 ThreadPoolExecutor 的 execute 方法，即是模板方法模式的应用。
// java.util.concurrent.AbstractExecutorService#submit(java.lang.Runnable, T) /** * @throws RejectedExecutionException {@inheritDoc} * @throws NullPointerException {@inheritDoc} */ public <T> Future<T> submit(Runnable task, T result) { if (task == null) throw new NullPointerException(); // 封装任务和返回结果为 RunnableFuture, 统一交由具体的子类执行 RunnableFuture<T> ftask = newTaskFor(task, result); // execute 将会调用 ThreadPoolExecutor 的实现，是我们讨论的重要核心 execute(ftask); return ftask; } // FutureTask 是个重要的线程池组件，它承载了具体的任务执行流 /** * Returns a {@code RunnableFuture} for the given runnable and default * value. * * @param runnable the runnable task being wrapped * @param value the default value for the returned future * @param <T> the type of the given value * @return a {@code RunnableFuture} which, when run, will run the * underlying runnable and which, as a {@code Future}, will yield * the given value as its result and provide for cancellation of * the underlying task * @since 1.6 */ protected <T> RunnableFuture<T> newTaskFor(Runnable runnable, T value) { return new FutureTask<T>(runnable, value); } // ThreadPoolExecutor 的任务提交过程 // java.util.concurrent.ThreadPoolExecutor#execute /** * 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. */ // ctl 是一个重要的控制全局状态的数据结构，定义为一个线程安全的 AtomicInteger // ctl = new AtomicInteger(ctlOf(RUNNING, 0)); int c = ctl.get(); // 当还没有达到核心线程池的数量时，直接添加1个新线程，然后让其执行任务即可 if (workerCountOf(c) < corePoolSize) { // 2.1. 添加新线程，且执行command任务 // 添加成功，即不需要后续操作了，添加失败，则说明外部环境变化了 if (addWorker(command, true)) return; c = ctl.get(); } // 当核心线程达到后，则尝试添加到阻塞队列中，具体添加方法由阻塞队列实现 // isRunning => c < SHUTDOWN; if (isRunning(c) && workQueue.offer(command)) { int recheck = ctl.get(); // 2.2. 添加队列成功后，还要再次检测线程池的运行状态，决定启动线程或者状态过期 // 2.2.1. 当线程池已关闭，则将刚刚添加的任务移除，走reject策略 if (! isRunning(recheck) && remove(command)) reject(command); // 2.2.2. 当一个worker都没有时，则添加worker else if (workerCountOf(recheck) == 0) addWorker(null, false); } // 当队列满后，则直接再创建新的线程运行，如果不能再创建线程了，则 reject else if (!addWorker(command, false)) // 2.3. 拒绝策略处理 reject(command); }
通过上面这一小段代码，我们就已经完整地看到了。通过一个 ctl 变量进行全局状态控制，从而保证了线程安全性。整个框架并没有使用锁，但是却是线程安全的。
整段代码刚好完整描述了线程池的执行流程:
1. 判断核心线程池是否已满，如果不是，则创建线程执行任务;
2. 如果核心线程池满了，判断队列是否满了，如果队列没满，将任务放在队列中;
3. 如果队列满了，则判断线程池是否已满，如果没满，创建线程执行任务;
4. 如果线程池也满了，则按照拒绝策略对任务进行处理;
2.1. 添加新的worker
一个worker，即是一个工作线程。
/** * 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) { // 为确保线程安全，进行CAS反复重试 retry: for (;;) { int c = ctl.get(); // 获取runState , c 的高位存储 // c & ~CAPACITY; int rs = runStateOf(c); // Check if queue empty only if necessary. // 已经shutdown, firstTask 为空的添加并不会成功 if (rs >= SHUTDOWN && ! (rs == SHUTDOWN && firstTask == null && ! workQueue.isEmpty())) return false; for (;;) { int wc = workerCountOf(c); // 如果超出最大允许创建的线程数，则直接失败 if (wc >= CAPACITY || wc >= (core ? corePoolSize : maximumPoolSize)) return false; // CAS 更新worker+1数，成功则说明占位成功退出retry，后续的添加操作将是安全的，失败则说明已有其他线程变更该值 if (compareAndIncrementWorkerCount(c)) break retry; c = ctl.get(); // Re-read ctl // runState 变更，则退出到 retry 重新循环 if (runStateOf(c) != rs) continue retry; // else CAS failed due to workerCount change; retry inner loop } } // 以下为添加 worker 过程 boolean workerStarted = false; boolean workerAdded = false; Worker w = null; try { // 使用 Worker 封闭 firstTask 任务，后续运行将由 Worker 接管 w = new Worker(firstTask); final Thread t = w.thread; if (t != null) { final ReentrantLock mainLock = this.mainLock; // 添加 worker 的过程，需要保证线程安全 mainLock.lock(); try { // Recheck while holding lock. // Back out on ThreadFactory failure or if // shut down before lock acquired. int rs = runStateOf(ctl.get()); // SHUTDOWN 情况下还是会创建 Worker, 但是后续检测将会失败 if (rs < SHUTDOWN || (rs == SHUTDOWN && firstTask == null)) { // 既然是新添加的线程，就不应该是 alive 状态 if (t.isAlive()) // precheck that t is startable throw new IllegalThreadStateException(); // workers 只是一个工作线程的容器，使用 HashSet 承载 // private final HashSet<Worker> workers = new HashSet<Worker>(); workers.add(w); int s = workers.size(); // 维护一个全局达到过的最大线程数计数器 if (s > largestPoolSize) largestPoolSize = s; workerAdded = true; } } finally { mainLock.unlock(); } // worker 添加成功后，进行将worker启起来，里面应该是有一个 死循环，一直在获取任务 // 不然怎么运行添加到队列里的任务呢？ if (workerAdded) { t.start(); workerStarted = true; } } } finally { // 如果任务启动失败，则必须进行清理，返回失败 if (! workerStarted) addWorkerFailed(w); } return workerStarted; } // 大概添加 worker 的框架明白了，重点对象是 Worker, 我们稍后再讲 // 现在先来看看，添加失败的情况，如何进行 /** * Rolls back the worker thread creation. * - removes worker from workers, if present * - decrements worker count * - rechecks for termination, in case the existence of this * worker was holding up termination */ private void addWorkerFailed(Worker w) { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { if (w != null) workers.remove(w); // ctl 中的 workerCount - 1 , CAS 实现 decrementWorkerCount(); // 尝试处理空闲线程 tryTerminate(); } finally { mainLock.unlock(); } } /** * Decrements the workerCount field of ctl. This is called only on * abrupt termination of a thread (see processWorkerExit). Other * decrements are performed within getTask. */ private void decrementWorkerCount() { do {} while (! compareAndDecrementWorkerCount(ctl.get())); } // 停止可能启动的 worker /** * Transitions to TERMINATED state if either (SHUTDOWN and pool * and queue empty) or (STOP and pool empty). If otherwise * eligible to terminate but workerCount is nonzero, interrupts an * idle worker to ensure that shutdown signals propagate. This * method must be called following any action that might make * termination possible -- reducing worker count or removing tasks * from the queue during shutdown. The method is non-private to * allow access from ScheduledThreadPoolExecutor. */ final void tryTerminate() { for (;;) { int c = ctl.get(); // 线程池正在运行、正在清理、已关闭但队列还未处理完，都不会进行 terminate 操作 if (isRunning(c) || // c >= TIDYING runStateAtLeast(c, TIDYING) || (runStateOf(c) == SHUTDOWN && ! workQueue.isEmpty())) return; if (workerCountOf(c) != 0) { // Eligible to terminate // 停止线程的两个方式之一，只中断一个 worker interruptIdleWorkers(ONLY_ONE); return; } // 以下为整个线程池的后置操作 final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { // 设置正在清理标识 if (ctl.compareAndSet(c, ctlOf(TIDYING, 0))) { try { // 线程池已终止的钩子方法，默认实现为空 terminated(); } finally { ctl.set(ctlOf(TERMINATED, 0)); // 此处 termination 为唤醒等待关闭的线程 termination.signalAll(); } return; } } finally { mainLock.unlock(); } // else retry on failed CAS } } /** * Interrupts threads that might be waiting for tasks (as * indicated by not being locked) so they can check for * termination or configuration changes. Ignores * SecurityExceptions (in which case some threads may remain * uninterrupted). * * @param onlyOne If true, interrupt at most one worker. This is * called only from tryTerminate when termination is otherwise * enabled but there are still other workers. In this case, at * most one waiting worker is interrupted to propagate shutdown * signals in case all threads are currently waiting. * Interrupting any arbitrary thread ensures that newly arriving * workers since shutdown began will also eventually exit. * To guarantee eventual termination, it suffices to always * interrupt only one idle worker, but shutdown() interrupts all * idle workers so that redundant workers exit promptly, not * waiting for a straggler task to finish. */ private void interruptIdleWorkers(boolean onlyOne) { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { // 迭代所有 worker for (Worker w : workers) { Thread t = w.thread; // 获取到 worker 的锁之后，再进行 interrupt if (!t.isInterrupted() && w.tryLock()) { try { t.interrupt(); } catch (SecurityException ignore) { } finally { w.unlock(); } } // 只中断一个 worker, 立即返回, 不保证 interrupt 成功 if (onlyOne) break; } } finally { mainLock.unlock(); } }
2.2. 当添加队列成功后，发现线程池状态变更，需要进行移除队列操作
/** * Removes this task from the executor's internal queue if it is * present, thus causing it not to be run if it has not already * started. * * <p>This method may be useful as one part of a cancellation * scheme. It may fail to remove tasks that have been converted * into other forms before being placed on the internal queue. For * example, a task entered using {@code submit} might be * converted into a form that maintains {@code Future} status. * However, in such cases, method {@link #purge} may be used to * remove those Futures that have been cancelled. * * @param task the task to remove * @return {@code true} if the task was removed */ public boolean remove(Runnable task) { // 此移除不一定能成功 boolean removed = workQueue.remove(task); // 上面已经看过，它会尝试停止一个 worker 线程 tryTerminate(); // In case SHUTDOWN and now empty return removed; }
3. 添加失败进行执行拒绝策略
/** * Invokes the rejected execution handler for the given command. * Package-protected for use by ScheduledThreadPoolExecutor. */ final void reject(Runnable command) { // 拒绝策略是在构造方法时传入的，默认为 RejectedExecutionHandler // 即用户只需实现 rejectedExecution 方法，即可以自定义拒绝策略了 handler.rejectedExecution(command, this); }
4. Worker 的工作机制
从上面的实现中，我们可以看到，主要是对 Worker 的添加和 workQueue 的添加，所以具体的工作是由谁完成呢？自然就是 Worker 了。
// Worker 的构造方法，主要是接受一个 task, 可以为 null, 如果非null, 将在不久的将来被执行 // private final class Worker extends AbstractQueuedSynchronizer implements Runnable /** * 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; // 将 Worker 自身当作一个 任务，绑定到 worker.thread 中 // thread 启动时，worker 就启动了 this.thread = getThreadFactory().newThread(this); } // Worker 的主要工作实现，通过一个循环扫描实现 /** Delegates main run loop to outer runWorker */ public void run() { // 调用 ThreadPoolExecutor 外部实现的 runWorker 方法 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 { // 不停地从 workQueue 中获取任务，然后执行，就是这么个逻辑 // getTask() 会阻塞式获取，所以 Worker 往往不会立即退出 while (task != null || (task = getTask()) != null) { // 执行过程中是不允许并发的，即同时只能一个 task 在运行，此时也不允许进行 interrupt 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 // 检测是否已被线程池是否停止 或者当前 worker 被中断 // STOP = 1 << COUNT_BITS; if ((runStateAtLeast(ctl.get(), STOP) || (Thread.interrupted() && runStateAtLeast(ctl.get(), STOP))) && !wt.isInterrupted()) // 中断信息传递 wt.interrupt(); try { // 任务开始前 切点，默认为空执行 beforeExecute(wt, task); Throwable thrown = null; try { // 直接调用任务的run方法， 具体的返回结果，会被 FutureTask 封装到 某个变量中 // 可以参考以前的文章 （FutureTask是怎样获取到异步执行结果的？ https://www.cnblogs.com/yougewe/p/11666284.html） 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 { // 任务开始后 切点，默认为空执行 afterExecute(task, thrown); } } finally { task = null; w.completedTasks++; w.unlock(); } } // 正常退出，有必要的话，可能重新将 Worker 添加进来 completedAbruptly = false; } finally { // 处理退出后下一步操作，可能重新添加 Worker processWorkerExit(w, completedAbruptly); } } /** * Performs cleanup and bookkeeping for a dying worker. Called * only from worker threads. Unless completedAbruptly is set, * assumes that workerCount has already been adjusted to account * for exit. This method removes thread from worker set, and * possibly terminates the pool or replaces the worker if either * it exited due to user task exception or if fewer than * corePoolSize workers are running or queue is non-empty but * there are no workers. * * @param w the worker * @param completedAbruptly if the worker died due to user exception */ private void processWorkerExit(Worker w, boolean completedAbruptly) { if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted decrementWorkerCount(); final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { completedTaskCount += w.completedTasks; workers.remove(w); } finally { mainLock.unlock(); } tryTerminate(); int c = ctl.get(); if (runStateLessThan(c, STOP)) { // 在 Worker 正常退出的情况下，检查是否超时导致，维持最小线程数 if (!completedAbruptly) { int min = allowCoreThreadTimeOut ? 0 : corePoolSize; if (min == 0 && ! workQueue.isEmpty()) min = 1; // 如果满足最小线程要求，则直接返回 if (workerCountOf(c) >= min) return; // replacement not needed } // 否则再添加一个Worker到线程池中备用 // 非正常退出，会直接再添加一个Worker addWorker(null, false); } } /** * 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. // 如果进行了 shutdown, 且队列为空, 则需要将 worker 退出 if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) { // do {} while (! compareAndDecrementWorkerCount(ctl.get())); decrementWorkerCount(); return null; } int wc = workerCountOf(c); // Are workers subject to culling? boolean timed = allowCoreThreadTimeOut || wc > corePoolSize; // 线程数据大于最大允许线程，需要删除多余的 Worker if ((wc > maximumPoolSize || (timed && timedOut)) && (wc > 1 || workQueue.isEmpty())) { if (compareAndDecrementWorkerCount(c)) return null; continue; } try { // 如果开户了超时删除功能，则使用 poll, 否则使用 take() 进行阻塞获取 Runnable r = timed ? workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) : workQueue.take(); // 获取到任务，则可以进行执行了 if (r != null) return r; // 如果有超时设置，则会在下一循环时退出 timedOut = true; } // 忽略中断异常 // 在这种情况下，Worker如何响应外部的中断请求呢？？？ 思考 catch (InterruptedException retry) { timedOut = false; } } }
所以，Worker的作用就体现出来了,一个循环取任务执行任务过程：
1. 有一个主循环一直进行任务的获取;
2. 针对有超时的设置，会使用poll进行获取任务，如果超时，则 Worker 将会退出循环结束线程;
3. 无超时的设置，则会使用 take 进行阻塞式获取，直到有值;
4. 获取任务执行前置+业务+后置任务;
5. 当获取到null的任务之后，当前Worker将会结束；
6. 当前Worker结束后，将会判断是否有必要维护最低Worker数，从而决定是否再添加Worker进来。
还是借用一个网上同学比较通用的一个图来表述下 Worker/ThreadPoolExecutor 的工作流程吧（已经很完美，不需要再造这轮子了）
5. shutdown 操作实现
ThreadPoolExecutor 是通过 ctl 这个变量进行全局状态维护的，shutdown 在线程池中也是表现为一个状态，所以应该是比较简单的。
/** * Initiates an orderly shutdown in which previously submitted * tasks are executed, but no new tasks will be accepted. * Invocation has no additional effect if already shut down. * * <p>This method does not wait for previously submitted tasks to * complete execution. Use {@link #awaitTermination awaitTermination} * to do that. * * @throws SecurityException {@inheritDoc} */ public void shutdown() { // 为保证线程安全，使用 mainLock final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { // SecurityManager 检查 checkShutdownAccess(); // 设置状态为 SHUTDOWN advanceRunState(SHUTDOWN); // 中断空闲的 Worker, 即相当于依次关闭每个空闲线程 interruptIdleWorkers(); // 关闭钩子，默认实现为空操作，为方便子类实现自定义清理功能 onShutdown(); // hook for ScheduledThreadPoolExecutor } finally { mainLock.unlock(); } // 再 tryTerminate(); } /** * Transitions runState to given target, or leaves it alone if * already at least the given target. * * @param targetState the desired state, either SHUTDOWN or STOP * (but not TIDYING or TERMINATED -- use tryTerminate for that) */ private void advanceRunState(int targetState) { for (;;) { int c = ctl.get(); // 自身CAS更新成功或者被其他线程更新成功 if (runStateAtLeast(c, targetState) || ctl.compareAndSet(c, ctlOf(targetState, workerCountOf(c)))) break; } } // 关闭空闲线程（非 running 状态） /** * Common form of interruptIdleWorkers, to avoid having to * remember what the boolean argument means. */ private void interruptIdleWorkers() { // 上文已介绍， 此处 ONLY_ONE 为 false, 即是最大可能地中断所有 Worker interruptIdleWorkers(false); } 与 shutdown 对应的，有一个 shutdownNow, 其语义是 立即停止所有任务。 /** * Attempts to stop all actively executing tasks, halts the * processing of waiting tasks, and returns a list of the tasks * that were awaiting execution. These tasks are drained (removed) * from the task queue upon return from this method. * * <p>This method does not wait for actively executing tasks to * terminate. Use {@link #awaitTermination awaitTermination} to * do that. * * <p>There are no guarantees beyond best-effort attempts to stop * processing actively executing tasks. This implementation * cancels tasks via {@link Thread#interrupt}, so any task that * fails to respond to interrupts may never terminate. * * @throws SecurityException {@inheritDoc} */ public List<Runnable> shutdownNow() { List<Runnable> tasks; final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { checkShutdownAccess(); // 与 shutdown 的差别，设置的状态不一样 advanceRunState(STOP); // 强行中断线程 interruptWorkers(); // 将未完成的任务返回 tasks = drainQueue(); } finally { mainLock.unlock(); } tryTerminate(); return tasks; } /** * Interrupts all threads, even if active. Ignores SecurityExceptions * (in which case some threads may remain uninterrupted). */ private void interruptWorkers() { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { for (Worker w : workers) // 调用 worker 的提供的中断方法 w.interruptIfStarted(); } finally { mainLock.unlock(); } } // ThreadPoolExecutor.Worker#interruptIfStarted void interruptIfStarted() { Thread t; if (getState() >= 0 && (t = thread) != null && !t.isInterrupted()) { try { // 直接调用任务的 interrupt t.interrupt(); } catch (SecurityException ignore) { } } }
6. invokeAll 的实现方式
invokeAll, 望文生义，即是调用所有给定的任务。想来应该是一个个地添加任务到线程池队列吧。
// invokeAll 的方法直接在抽象方便中就实现了，它的语义是同时执行n个任务，并同步等待结果返回 // java.util.concurrent.AbstractExecutorService#invokeAll(java.util.Collection<? extends java.util.concurrent.Callable<T>>) 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); // 依次调用各子类的实现，添加任务 execute(f); } for (int i = 0, size = futures.size(); i < size; i++) { Future<T> f = futures.get(i); if (!f.isDone()) { try { // 依次等待执行结果 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); } }
实现很简单，都是些外围调用。
7. ThreadPoolExecutor 的状态值的设计
通过上面的过程，可以看到，整个ThreadPoolExecutor 非状态的依赖是非常强的。所以一个好的状态值的设计就显得很重要了，runState 代表线程池或者 Worker 的运行状态。如下：
// runState is stored in the high-order bits // 整个状态使值使用 ctl 的高三位值进行控制， COUNT_BITS=29 // 1110 0000 0000 0000 private static final int RUNNING = -1 << COUNT_BITS; // 0000 0000 0000 0000 private static final int SHUTDOWN = 0 << COUNT_BITS; // 0010 0000 0000 0000 private static final int STOP = 1 << COUNT_BITS; // 0100 0000 0000 0000 private static final int TIDYING = 2 << COUNT_BITS; // 0110 0000 0000 0000 private static final int TERMINATED = 3 << COUNT_BITS; // 整个状态值的大小顺序主: RUNNING < SHUTDOWN < STOP < TIDYING < TERMINATED // 而低 29位，则用来保存 worker 的数量，当worker增加时，只要将整个 ctl 增加即可。 // 0001 1111 1111 1111, 即是最大的 worker 数量 private static final int CAPACITY = (1 << COUNT_BITS) - 1; // 整个 ctl 描述为一个 AtomicInteger, 功能如下: /** * 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). */ private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
8. awaitTermination 等待关闭完成
从上面的 shutdown, 可以看到，只是写了 SHUTDOWN 标识后，尝试尽可能地中断停止Worker线程，但并不保证中断成功。要想保证停止完成，需要有另外的机制来保证。从 awaitTermination 的语义来说，它是能保证任务停止完成的，那么它是如何保证的呢？
// ThreadPoolExecutor.awaitTermination() public boolean awaitTermination(long timeout, TimeUnit unit) throws InterruptedException { long nanos = unit.toNanos(timeout); final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { for (;;) { // 只是循环 ctl 状态, 只要 状态为 TERMINATED 状态，则说明已经关闭成功 // 此处 termination 的状态触发是在 tryTerminate 中触发的 if (runStateAtLeast(ctl.get(), TERMINATED)) return true; if (nanos <= 0) return false; nanos = termination.awaitNanos(nanos); } } finally { mainLock.unlock(); } }
看起来, awaitTermination 并没有什么特殊操作，而是一直在等待。所以 TERMINATED 是 Worker 自行发生的动作。
那是在哪里做的操作呢？其实是在获取任务的时候，会检测当前状态是否是 SHUTDOWN, 如果是SHUTDOWN且 队列为空，则会触发获取任务的返回null.从而结束当前 Worker.
Worker 在结束前会调用 processWorkerExit() 方法，里面会再次调用 tryTerminate(), 当所有 Worker 都运行到这个点后， awaitTermination() 就会收到通知了。（注意: processWorkerExit() 会在每次运行后进行 addWorker() 尝试，但是在 SHUTDOWN 状态的添加操作总是失败的，所以不用考虑）
到此，你是否可以解答前面的几个问题了呢？
不要害怕今日的苦，你要相信明天，更苦！
