ThreadPoolExecutor源码解析

LZ目前正在做一个批量生成报表的系统，需要定时批量生成多张报表，便考虑使用线程池来完成。JDK自带的Executors工具类只提供创建固定线程和可伸展但无上限的两个静态方法，并不能满足LZ想自定制线程池大小的要求。于是就直接深入了解下ThreadPoolExecutor类，以方便在工作中灵活使用以及为以后的扩展打下基础。

java doc中对ThreadPoolExecutor的说明是：

An ExecutorService that executes each submitted task using one of possibly several pooled threads, normally configured using Executors factory methods.

一个使用线程池来执行提交的任务的ExecutorService子类，正常通过Executors工具类中的工厂方法进行配置。

那我们就先看一下比较熟悉的Executors中的几个方法的实现代码：

Executors.newCachedThreadPool

public static ExecutorService newCachedThreadPool(ThreadFactory threadFactory) {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
  60L, TimeUnit.SECONDS,
  new SynchronousQueue<Runnable>(),
  threadFactory);
}

Executors.newFixedThreadPool

public static ExecutorService newFixedThreadPool(int nThreads, ThreadFactory threadFactory) {
    return new ThreadPoolExecutor(nThreads, nThreads,
                                  0L, TimeUnit.MILLISECONDS,
                                  new LinkedBlockingQueue<Runnable>(),
                                  threadFactory);
}

Executors.newSingleThreadExecutor

public static ExecutorService newSingleThreadExecutor(ThreadFactory threadFactory) {
    return new FinalizableDelegatedExecutorService
        (new ThreadPoolExecutor(1, 1,
                                0L, TimeUnit.MILLISECONDS,
                                new LinkedBlockingQueue<Runnable>(),
                                threadFactory));
}

可以看到其实这些方法都是通过构造方法创建了ThreadPoolExecutor对象，我们来看下具体的构造方法实现

public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue,
                          ThreadFactory threadFactory) {
    this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
         threadFactory, defaultHandler);
}

这里我们可以看到ThreadPoolExecutor中比较重要的一些参数，这些参数都是可以通过外部传入，对ThreadPoolExecutor内部进行控制。而ThreadPoolExecutor内部的工作机制究竟是怎样进行的呢？下面我们就揭开它的外衣，深入其中仔细探究。

1.ThreadPoolExecutor继承了AbstractExecutorService类

public class ThreadPoolExecutor extends AbstractExecutorService

2. ThreadPoolExecutor的重要变量参数

• ctl: 用来标识线程池状态的重要参数，很多操作执行前都需要对线程池状态进行前置判断，以确定线程池状态是否正常

• workQueue: 任务队列，用来在全部当前线程正在处理任务时存储提交来的任务

• works: 存储所有工作线程

• corePoolSize: 核心线程数

• maximumPoolSize: 最大线程数

• keepAliveTime: 空闲线程等待任务时间

• threadFactory: 线程创建工厂

• handler: 因线程池饱和或关闭触发的拒绝异常处理器

    //标识线程池控制状态
    private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
  
    //线程池状态类型
    //接受新的任务并处理队列中的任务
    private static final int RUNNING= -1 << COUNT_BITS;
    //不接受新任务但处理队列中的任务
    private static final int SHUTDOWN   =  0 << COUNT_BITS;
    //不接受新任务也不处理队列中的任务，且中断正在进行的任务
    private static final int STOP   =  1 << COUNT_BITS;
    //所有任务已经完结，工作线程数为0，并调用terminated方法
    private static final int TIDYING=  2 << COUNT_BITS;
    //terminated方法执行完成
    private static final int TERMINATED =  3 << COUNT_BITS;
    //任务队列，储存任务以提供给工作线程
    private final BlockingQueue<Runnable> workQueue;
    //主要锁，设置workers和相关数据记录调用
    private final ReentrantLock mainLock = new ReentrantLock();
    //存储所有工作线程，设置时需要加mainLock锁
    private final HashSet<Worker> workers = new HashSet<Worker>();
    //线程池已达到的最大数，设置时需要加mainLock锁
    private int largestPoolSize;
    //已完成任务数，设置时需要加mainLock锁
    private long completedTaskCount;
    //线程创建工厂
    private volatile ThreadFactory threadFactory;
    //因饱和或线程池关闭触发的拒绝异常处理器
    private volatile RejectedExecutionHandler handler;
    //空闲线程等待任务时间(单位：纳秒)，到时则会被销毁
    private volatile long keepAliveTime;
    //默认为false，核心线程在空闲时一直存活
    //如果为true，核心线程使用keepAliveTime参数来等待任务
    private volatile boolean allowCoreThreadTimeOut;
    //核心线程数
    private volatile int corePoolSize;
    //最大线程数
    private volatile int maximumPoolSize;
    //默认拒绝异常处理器
    private static final RejectedExecutionHandler defaultHandler =
    new AbortPolicy();
  

3.execute方法，用户通过该方法提交任务给线程池。

处理任务分四种种情况：

1. 如果当前工作线程数小于核心线程数，则创建新的线程来处理任务

2. 如果当前工作线程等于核心线程数，新提交的任务存储到工作队列中
   
   重新检测线程池状态是否正常，如果不是运行状态，则移除任务，并处理拒绝异常
   
   如果线程池正常，工作线程数等于0，则增加工作线程

3. 当工作队列达到最大容量，工作线程数没有达到最大线程数，增加新的工作线程，并处理任务

4. 当工作线程数达到最大线程数，则使用拒绝异常处理器对任务进行处理

    public void execute(Runnable command) {
        if (command == null)
            throw new NullPointerException();
   
        int c = ctl.get();
        if (workerCountOf(c) < corePoolSize) {
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
        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);
    }
   

4.线程池是怎么增加一个新的线程的呢？

接下来我们来看addWorker方法

1. 双重for循环检查线程池是否适合增加新的线程

2. 创建Worker对象并获得mainLock锁

3. 再次检查状态，防止线程工厂失败或线程池关闭

4. works增加worker对象，并更新largestPoolSize，释放锁

5. 启用worker对象中的线程

6. 由于并发原因，可能会出现线程尚未执行，但线程池正在关闭，因此可能会出现线程池关闭时，错过中断当前线程，因此再进行一次判断，如果线程池状态为关闭且当前线程未被中断，则手动中断它

    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))
                    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
            }
        }
        Worker w = new Worker(firstTask);
        Thread t = w.thread;
        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 c = ctl.get();
            int rs = runStateOf(c);
            if (t == null ||
                (rs >= SHUTDOWN &&
                 ! (rs == SHUTDOWN &&
                    firstTask == null))) {
                decrementWorkerCount();
                tryTerminate();
                return false;
            }
            workers.add(w);
            int s = workers.size();
            if (s > largestPoolSize)
                largestPoolSize = s;
        } finally {
            mainLock.unlock();
        }
        t.start();
        // It is possible (but unlikely) for a thread to have been
        // added to workers, but not yet started, during transition to
        // STOP, which could result in a rare missed interrupt,
        // because Thread.interrupt is not guaranteed to have any effect
        // on a non-yet-started Thread (see Thread#interrupt).
        if (runStateOf(ctl.get()) == STOP && ! t.isInterrupted())
            t.interrupt();
        return true;
    }
   

5.Worker类的实现

在addWorker方法中，我们并没有看到任务具体执行的操作，但是可以很明显地猜测到应该是在调用t.start()方法时进行调用。而线程t是来自于Worker对象，我们来看下内部类Worker(删除了部分代码)。

1. Worker类继承自AbstractQueuedSynchronizer，实现了Runnable接口

2. new Worker()时，通过ThreadFactory的newThread方法创建了一个新的线程

3. 当调用addWorker中的t.start()时，其实触发的是run方法中的runWorker(this)

    private final class Worker
        extends AbstractQueuedSynchronizer
        implements Runnable
    {
   
        /** 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);
        }
    }
   

6.runWorker方法是怎么触发任务执行的

1. while循环保证了线程可以重复执行任务，如果firstTask执行完成后，通过getTask方法从任务队列中获取新的任务继续执行

2. 执行前和执行后分别调用beforExecute和afterExecute两个钩子方法，可以用来在子类中自己实现，比如用于线程池监控

3. 如果处理过程中出现意外情况，在finally中调用processWorkerExit进行处理，主要是对线程记录相关变量进行恢复，且处理当核心线程全部超时而任务队列中有新的任务时，重新增加新线程来处理任务

    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) {
                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);
        }
    }
   

7.getTask方法中是怎么获取任务队列中的任务的

1. 判断线程池状态是否正常，根据timed = allowCoreThreadTimeout || wc > corePoolSize来决定队列获取任务的方式是指定keepAliveTime时间进行等待还是阻塞式等待

2. 如果keepAliveTime超时，允许核心线程超时销毁或者当前线程池总量大于核心线程数，则getTask()返回null，回溯到runWorker方法中，则while循环结束，即线程执行完成，此线程将被销毁。

    private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?
        retry:
        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;
            }
            boolean timed;      // Are workers subject to culling?
            for (;;) {
                int wc = workerCountOf(c);
                timed = allowCoreThreadTimeOut || wc > corePoolSize;
                if (wc <= maximumPoolSize && ! (timedOut && timed))
                    break;
                if (compareAndDecrementWorkerCount(c))
                    return null;
                c = ctl.get();  // Re-read ctl
                if (runStateOf(c) != rs)
                    continue retry;
                // else CAS failed due to workerCount change; retry inner loop
            }
            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }