java线程池源码的理解

线程池

新建线程和切换线程的开销太大了，使用线程池可以节省系统资源。

线程池的关键类：ThreadPoolExecutor。

该类中包含了大量的多线程与并发处理工具，包括ReentrantLock、AtomicInteger、AQS、CAS、BlockingQueue等

主要流程

execute() –> addWorker() –>runWorker() -> getTask()

重要参数及变量

• 控制状态的变量 ctl：
  
  ctl是一个AtomicInteger原子操作类，能够保证线程安全。

ctl变量定义如下：

private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));

private static int ctlOf(int rs, int wc) { return rs | wc; }

详细讲解如下：

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

大概意思是：通过对ctl的运算，能够得到两个重要的变量，workerCount(worker线程数量)和runState(线程池运行状态)。

• 线程池运行状态 runState：

runState由几个整型常量RUNNING 、SHUTDOWN 、STOP、TIDYING、TERMINATED表示。

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

内部类Worker：

Worker类，继承AQS，并实现了Runnable。

这个类主要维护线程运行任务的拦截控制状态，用于简化每个Task(任务)执行时获取和释放锁的过程。

Worker类内部有一个thread线程变量，在Worker类实例化时，thread对象也会随之创建。

Worker类和Task(任务)有什么区别？

Task只实现了Runnable接口，而Worker类还继承了AQS，Worker还会协助获取和释放锁。

worker是线程池中的线程，而Task虽然是runnable，但是并没有真正执行，只是被Worker调用了run方法，只有Worker(工人)真正开启并执行。

    /**
     * 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. */
        //非常重要的线程变量
        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;
            //在Worker类实例化时，thread对象也会随之创建。
            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) {
                }
            }
        }
    }

execute()：

execute()用于执行任务，参数command为将要执行的任务。

根据线程池的运行状态，以及线程池中的线程数量，决定执行addWorker()，还是拒绝策略reject()。

如果线程数小于核心线程数，则创建worker线程任务并执行。

如果线程数大于核心线程数，只有线程池处于running状态，才会将任务加入到工作队列中。

如果线程数大于最大线程数，或者线程池处于非running状态，就会执行拒绝策略。

核心线程数、最大线程数、拒绝策略等相关参数的解析，详情见：https://www.cnblogs.com/expiator/p/9053754.html

    /**
     * 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) {
    //execute()的参数command为即要执行的任务
        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();
        //如果工作线程数小于核心线程数，则创建worker线程任务并执行
        if (workerCountOf(c) < corePoolSize) {
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
        //在阻塞队列 BlockingQueue 中 add() 和 offer()都是用来向队列添加一个元素。
        //在容量已满的情况下，add() 方法会抛出IllegalStateException异常，offer() 方法只会返回 false 。
        //如果工作线程数大于核心线程数，只有线程池处于running状态，才会将任务加入到工作队列中。
        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);
        }
        else if (!addWorker(command, false))
            reject(command);
    }

addWorker()：

addWorker()方法的布尔参数core，取决了workerCount(也就是worker数量)的边界范围。

该方法实例化Worker对象worker，worker内部的线程变量thread获取可重入锁ReentrantLock。

通过ReentrantLock加锁，保证线程安全。

接着会将新建的worker对象添加到HashSet集合workers里面，操作完毕就释放锁。

最后开启线程，会自动执行worker对象内部的run()方法，run()方法内部会执行runWorker()。

    /**
     * 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) {
        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);
                //方法的布尔参数core，取决了workerCount(也就是worker数量)的边界范围
                if (wc >= CAPACITY ||
                    wc >= (core ? corePoolSize : maximumPoolSize))
                    return false;
                //通过CAS机制，进行加1操作。具体内容见下文。
                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 {
            //实例化Worker对象，Worker对象内部的线程变量thread获取可重入锁ReentrantLock，操作完毕就释放锁，保证线程安全。
            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();
                        //将worker对象添加到HashSet<Worker>对象workers里面。这个HashSet集合workers的size()，其实就是线程池的大小。
                        workers.add(w);
                        int s = workers.size();
                        if (s > largestPoolSize)
                            largestPoolSize = s;
                        workerAdded = true;
                    }
                } finally {
                    mainLock.unlock();
                }
                if (workerAdded) {
                    //开启线程，会自动执行Worker对象内部的run()方法，run()方法内部会执行runWorker()。
                    t.start();
                    workerStarted = true;
                }
            }
        } finally {
            if (! workerStarted)
                addWorkerFailed(w);
        }
        return workerStarted;
    }

• AtomicInteger和CAS：

在多线程中操作基本类型变量，为了保证线程安全，使用AtomicInteger是一个非常好的选择。

ctl是一个AtomicInteger对象。AtomiInteger对象，可以通过CAS机制，对变量进行操作，如自增等。

CAS就是CompareAndSwap，比较和替换。当变量的值为期望值时，将其修改为对应的更新值。

关于AtomicInteger和CAS，详情参考：https://www.cnblogs.com/expiator/p/9449298.html

上面的addWorker()中调用的compareAndIncrementWorkerCount()方法如下：

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

/**
* Atomically sets the value to the given updated value
* if the current value {@code ==} the expected value.
*
* @param expect the expected value
* @param update the new value
* @return {@code true} if successful. False return indicates that
* the actual value was not equal to the expected value.
*/
public final boolean compareAndSet(int expect, int update) {
    return unsafe.compareAndSwapInt(this, valueOffset, expect, update);
}

runWorker()

通过task.run();执行任务。

   /**
     * 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 {
            //获取任务
            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 interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    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 {
                        afterExecute(task, thrown);
                    }
                } finally {
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
            completedAbruptly = false;
        } finally {
            processWorkerExit(w, completedAbruptly);
        }
    }

getTask()

从工作队列workQueue中取出任务task。

workQueue是一个BlockingQueue(阻塞队列)，使用take()和poll()函数都可以从队列中取数。

区别是：如果队列中没有数据时，使用take()则线程await()等待。而poll()则不会等待，直接返回null。

    /**
     * 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?
            //是否需要计时处理，如果设置了allowCoreThreadTimeOut或当前工作线程数量大于corePoolSize 则需要计时处理
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;
            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            try {
                //workQueue是一个BlockingQueue(阻塞队列)，使用take()和poll()函数都可以从队列中取数。
                //区别是：如果队列中没有数据时，使用take()则线程await()等待。而poll()则不会等待，直接返回null。
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }

线程池size

前文提到，在addWorker()中，会将新建的worker对象添加到HashSet集合workers里面。

而线程池中的线程数量，就是指workers这个Set集合的size。

    /**
     * Returns the current number of threads in the pool.
     *
     * @return the number of threads
     */
    public int getPoolSize() {
        final ReentrantLock mainLock = this.mainLock;
        mainLock.lock();
        try {
            // Remove rare and surprising possibility of
            // isTerminated() && getPoolSize() > 0
            return runStateAtLeast(ctl.get(), TIDYING) ? 0
                : workers.size();
        } finally {
            mainLock.unlock();
        }
    }

参考资料

《码出高效》

https://www.cnblogs.com/sxkgeek/p/9343519.html

https://blog.csdn.net/programmer_at/article/details/79799267