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ThreadPoolExecutor源码解析

1、常用变量的解释

// 1. `ctl`,可以看做一个int类型的数字,高3位表示线程池状态,低29位表示worker数量
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
// 2. `COUNT_BITS`,`Integer.SIZE`为32位,所以`COUNT_BITS`为29位
private static final int COUNT_BITS = Integer.SIZE - 3;
// 3. `CAPACITY`,线程池允许的最大线程数。1左移29位,然后减1,即为 2^29 - 1
private static final int CAPACITY   = (1 << COUNT_BITS) - 1;

// runState is stored in the high-order bits
// 4. 线程池有5种状态,按大小排序如下:RUNNING < SHUTDOWN < STOP < TIDYING < TERMINATED
private static final int RUNNING    = -1 << COUNT_BITS;
private static final int SHUTDOWN   =  0 << COUNT_BITS;
private static final int STOP       =  1 << COUNT_BITS;
private static final int TIDYING    =  2 << COUNT_BITS;
private static final int TERMINATED =  3 << COUNT_BITS;

// Packing and unpacking ctl
// 5. `runStateOf()`,获取线程池状态,通过按位与操作,低29位将全部变成0
private static int runStateOf(int c)     { return c & ~CAPACITY; }
// 6. `workerCountOf()`,获取线程池worker数量,通过按位与操作,高3位将全部变成0
private static int workerCountOf(int c)  { return c & CAPACITY; }
// 7. `ctlOf()`,根据线程池状态和线程池worker数量,生成ctl值
private static int ctlOf(int rs, int wc) { return rs | wc; }

/*
 * Bit field accessors that don't require unpacking ctl.
 * These depend on the bit layout and on workerCount being never negative.
 */
// 8. `runStateLessThan()`,线程池状态小于xx
private static boolean runStateLessThan(int c, int s) {
    return c < s;
}
// 9. `runStateAtLeast()`,线程池状态大于等于xx
private static boolean runStateAtLeast(int c, int s) {
    return c >= s;
}

2、构造方法

public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue,
                          ThreadFactory threadFactory,
                          RejectedExecutionHandler handler) {
    // 基本类型参数校验
    if (corePoolSize < 0 ||
        maximumPoolSize <= 0 ||
        maximumPoolSize < corePoolSize ||
        keepAliveTime < 0)
        throw new IllegalArgumentException();
    // 空指针校验
    if (workQueue == null || threadFactory == null || handler == null)
        throw new NullPointerException();
    this.corePoolSize = corePoolSize;
    this.maximumPoolSize = maximumPoolSize;
    this.workQueue = workQueue;
    // 根据传入参数`unit`和`keepAliveTime`,将存活时间转换为纳秒存到变量`keepAliveTime `中
    this.keepAliveTime = unit.toNanos(keepAliveTime);
    this.threadFactory = threadFactory;
    this.handler = handler;
}

3、提交执行task的过程

  1. 刚开始的时候,线程池里的线程数为0
  2. 来一个任务,起一个核心线程,来一个任务,起一个核心线程
  3. 核心线程数满了之后,都占着呢,怎么办呢?放到队列里
  4. 最后队列也满了,核心线程数也满了,怎么办呢?起非核心线程
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.
     */
    int c = ctl.get();
    // worker数量比核心线程数小,直接创建worker执行任务
    if (workerCountOf(c) < corePoolSize) {
    	// addWorker 第二个参数,表示是否是核心线程。当核心线程数不够的时候,先添加核心线程
        if (addWorker(command, true))
            return;
        // 再次检查这个值c,为什么要再次检查?
        // 因为多线程的情形,在你执行任意两句话的中间,都有可能被其他线程改变了这个状态值
        // 所以一定要重新再那一遍
        c = ctl.get();
    }
    // worker数量超过核心线程数,任务直接进入队列
    if (isRunning(c) && workQueue.offer(command)) {
        int recheck = ctl.get();
        // 线程池状态不是RUNNING状态,说明执行过shutdown命令,需要对新加入的任务执行reject()操作。
        // 这儿为什么需要recheck,是因为任务入队列前后,线程池的状态可能会发生变化。思想类似于DCL的double check
        if (!isRunning(recheck) && remove(command))
        	// 如果不是 running 状态,说明执行过 shutdown 命令。只有 shutdown 命令才会把 running 状态转换成别的状态
        	// 既然已经 shutdown,而我上面把它加到了Queue里头,所以还得把它 remove 出来
        	// remove 完以后,调用 reject 拒绝这个任务
            reject(command);
        // 这儿为什么需要判断0值,主要是在线程池构造方法中,核心线程数允许为0
        else if (workerCountOf(recheck) == 0)
        	// 于是添加非核心线程
            addWorker(null, false);
    }
    // 如果线程池不是运行状态,或者任务进入队列失败,则尝试创建worker执行任务。
    // 这儿有3点需要注意:
    // 1. 线程池不是运行状态时,addWorker内部会判断线程池状态
    // 2. addWorker第2个参数表示是否创建核心线程
    // 3. addWorker返回false,则说明任务执行失败,需要执行reject操作
    else if (!addWorker(command, false))
        reject(command);
}

4、addworker源码解析

添加线程首先你要理解添加到哪儿,肯定是添加到容器里。往里头添加线程的时候,务必要知道可能有好多好多个线程都在往里头扔,所以要做同步,这是第一点。然后呢它要追求效率,所以它不会用sync,它或者用Lock或者用自旋,所以也就增加了代码的一个复杂的程度。

外层自旋,只干了一件事,就是把 Worker 的数量+1。你添加的这个数量在哪儿?就在ctl的那29位里面。ctl的前3位是状态,后29位是数量。要把这个数量+1,而且是在多线程的状态下+1。内层自选,说明经过判断,可以往里加了。

然后下面才是真真正正的

private boolean addWorker(Runnable firstTask, boolean core) {
    retry:
    // 外层自旋,只干了一件事,就是把 Worker 的数量+1。你要add worker 的嘛,数量肯定是要同步的呀。
    // 你添加的这个数量在哪儿?就在ctl的那29位里面。ctl的前3位是状态,后29位是数量。要把这个数量+1,而且是在多线程的状态下+1
    for (;;) {
        int c = ctl.get();
        int rs = runStateOf(c);

        // 这个条件写得比较难懂,我对其进行了调整,和下面的条件等价
        // (rs > SHUTDOWN) || 
        // (rs == SHUTDOWN && firstTask != null) || 
        // (rs == SHUTDOWN && workQueue.isEmpty())
        // 1. 线程池状态大于SHUTDOWN时,说明已经shutdown了,还往里面加个头啊,就别加了嘛,直接返回false
        // 2. 线程池状态等于SHUTDOWN,且firstTask不为null,已经正在shutdown了,里面还有任务呢,你就别往里加了,直接返回false
        // 3. 线程池状态等于SHUTDOWN,且队列为空,直接返回false
        // Check if queue empty only if necessary.
        if (rs >= SHUTDOWN &&
            ! (rs == SHUTDOWN &&
               firstTask == null &&
               ! workQueue.isEmpty()))
            return false;

        // 内层自旋
        for (;;) {
            int wc = workerCountOf(c);
            // worker数量超过容量,直接返回false
            if (wc >= CAPACITY ||
                wc >= (core ? corePoolSize : maximumPoolSize))
                return false;
            // 使用CAS的方式增加worker数量。
            // 若增加成功,则直接跳出外层循环进入到第二部分
            if (compareAndIncrementWorkerCount(c))
                break retry;
            c = ctl.get();  // Re-read ctl
            // 如果线程池状态发生变化,对外层循环进行自旋
            // 如果线程池状态没有发生变化,继续内存循环进行自旋即可
            if (runStateOf(c) != rs)
                continue retry;
            // 其他情况,直接内层循环进行自旋即可
            // else CAS failed due to workerCount change; retry inner loop
        } 
    }
	
	// 这下面开始才是真真正正地起一个 worker
    boolean workerStarted = false;
    boolean workerAdded = false;
    Worker w = null;
    try {
    	// new了一个Worker,此时ThreadFactory会创建一个Thread传给Worker的thread变量。
        w = new Worker(firstTask);
        final Thread t = w.thread;
        if (t != null) {
            final ReentrantLock mainLock = this.mainLock;
            // worker的添加必须是串行的,因此需要加锁
            mainLock.lock();
            try {
                // Recheck while holding lock.
                // Back out on ThreadFactory failure or if
                // shut down before lock acquired.
                // 这儿需要重新检查线程池状态
                int rs = runStateOf(ctl.get());

                if (rs < SHUTDOWN ||
                    (rs == SHUTDOWN && firstTask == null)) {
                    // worker已经调用过了start()方法,则不再创建worker
                    if (t.isAlive()) // precheck that t is startable
                        throw new IllegalThreadStateException();
                    // worker创建并添加到workers成功
                    workers.add(w);
                    // 更新`largestPoolSize`变量
                    int s = workers.size();
                    if (s > largestPoolSize)
                        largestPoolSize = s;
                    workerAdded = true;
                }
            } finally {
                mainLock.unlock();
            }
            // 启动worker线程
            if (workerAdded) {
                t.start();
                workerStarted = true;
            }
        }
    } finally {
        // worker线程启动失败,说明线程池状态发生了变化(关闭操作被执行),需要进行shutdown相关操作
        if (! workerStarted)
            addWorkerFailed(w);
    }
    return workerStarted;
}

5、线程池worker任务单元

worker 继承自 AQS,说明它本身是一把锁,为什么是一把锁呀?Worker 可以看作一个工人,好多任务可以同时往里扔的,也就会有多线程去访问这个对象的,所以它干脆把自己做成了一把锁,就不要去再定义一个Lock了

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. */
    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;
        // 这儿是Worker的关键所在,使用了线程工厂创建了一个线程。传入的参数为当前worker
        this.thread = getThreadFactory().newThread(this);
    }

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

    // 省略代码...
}

6、核心线程执行逻辑-runworker

老师给出的理解:Worker 不是线程,Worker 是 Runnable

final void runWorker(Worker w) {
    Thread wt = Thread.currentThread();
    Runnable task = w.firstTask;
    w.firstTask = null;
    // 调用unlock()是为了让外部可以中断
    w.unlock(); // allow interrupts
    // 这个变量用于判断是否进入过自旋(while循环)
    boolean completedAbruptly = true;
    try {
        // 这儿是自旋
        // 1. 如果firstTask不为null,则执行firstTask;
        // 2. 如果firstTask为null,则调用getTask()从队列获取任务。
        // 3. 阻塞队列的特性就是:当队列为空时,当前线程会被阻塞等待
        while (task != null || (task = getTask()) != null) {
            // 这儿对worker进行加锁,是为了达到下面的目的
            // 1. 降低锁范围,提升性能
            // 2. 保证每个worker执行的任务是串行的
            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
            // 如果线程池正在停止,则对当前线程进行中断操作
            if ((runStateAtLeast(ctl.get(), STOP) ||
                 (Thread.interrupted() &&
                  runStateAtLeast(ctl.get(), STOP))) &&
                !wt.isInterrupted())
                wt.interrupt();
            // 执行任务,且在执行前后通过`beforeExecute()`和`afterExecute()`来扩展其功能。
            // 这两个方法在当前类里面为空实现。
            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 {
                // 帮助gc
                task = null;
                // 已完成任务数加一 
                w.completedTasks++;
                w.unlock();
            }
        }
        completedAbruptly = false;
    } finally {
        // 自旋操作被退出,说明线程池正在结束
        processWorkerExit(w, completedAbruptly);
    }
}
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