• 纯干货,源码6步曲,带你解析完整的ThreadPoolExecutor


    ThreadPoolExecutor源码解析

    今天为了给一个朋友做一份文档,从源码层级解析一下ThreadPoolExecutor。然后就直接在源码上写备注的形式解析,看这篇文章的朋友,就和看源码一样,一步步的跟着向下执行的看就好

    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,所以`COUNT_BITS`为29
    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

    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) {
            if (addWorker(command, true))
                return;
            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。
            if (! isRunning(recheck) && remove(command))
                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)
                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

    private boolean addWorker(Runnable firstTask, boolean core) {
        retry:
        // 外层自旋
        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,直接返回false
            // 2. 线程池状态等于SHUTDOWN,且firstTask不为null,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
                // 线程池状态发生变化,对外层循环进行自旋
                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
            } 
        }
        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;
                // 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

    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

    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);
        }
    }

    怎么样,不知道大家看明白了没有,可能对于有一些朋友来说有那么一点点的困难,但是没关系啊
    既然已经说道thread了,咱也别落下什么,相应的视频合文档已经整理完成

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    部分资料已经上传到我的git仓库中:有需要的可以下载

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  • 原文地址:https://www.cnblogs.com/bwscode/p/13488377.html
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