多线程相关-ThreadPoolExecutor

应用层面:

  ThreadPoolExecutor:

  

  创建多线程池执行器:new ThreadPoolExecutor(),创建方法最终都是走的以下这个构造方法:

    /**
     * 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,//核心线程数
                              int maximumPoolSize,//核心线程最大数量
                              long keepAliveTime,//超出核心线程数的其他空闲线程保留时间
                              TimeUnit unit,//空闲时间单位
                              BlockingQueue<Runnable> workQueue,//对列,当线程数量大于等于核心线程数时,将任务works保存进对列
                              ThreadFactory threadFactory,//创建线程的工厂
                              RejectedExecutionHandler handler) {//超出最大核心线程数的拒绝策略
        if (corePoolSize < 0 ||
            maximumPoolSize <= 0 ||
            maximumPoolSize < corePoolSize ||
            keepAliveTime < 0)
            throw new IllegalArgumentException();
        if (workQueue == null || threadFactory == null || handler == null)
            throw new NullPointerException();
        this.acc = System.getSecurityManager() == null ?
                null :
                AccessController.getContext();
        this.corePoolSize = corePoolSize;
        this.maximumPoolSize = maximumPoolSize;
        this.workQueue = workQueue;
        this.keepAliveTime = unit.toNanos(keepAliveTime);
        this.threadFactory = threadFactory;
        this.handler = handler;
    }

创建线程池的其他方式:(返回的实际对象仍然是ThreadPoolExecutor,只不过是对构造函数的参数进行的特殊规定)

  1、Executors.newFixedThreadPool(int nThreads)

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

  Executors.newFixedThreadPool(int nThreads, ThreadFactory threadFactory)//自动以创建线程的工厂

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

  2、Executors.newSingleThreadExecutor() 

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

  3、Executor.newCachedThreadPool()

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

源码:

ThreadPoolExecutor

构造方法:

ThreadPoolExecutor(int corePoolSize,//核心线程数
                              int maximumPoolSize,//核心线程最大数量
                              long keepAliveTime,//超出核心线程数的其他空闲线程保留时间
                              TimeUnit unit,//空闲时间单位
                              BlockingQueue<Runnable> workQueue,//对列,当线程数量大于等于核心线程数时,将任务works保存进对列
                              ThreadFactory threadFactory,//创建线程的工厂
                              RejectedExecutionHandler handler) {//超出最大核心线程数的拒绝策略

    corePoolSize:线程池的核心线程数,当线程池中的工作线程数小于核心线程数的时候,只要向线程池指派任务,线程池就会创建工作线程。

    maximumPoolSize:线程池最大工作线程数,当线程池中的工作线程达到最大数的时候,即使再向线程池指派任务,线程池不会创建工作线程,回执行对应的拒绝策略。
    keepAliveTime:当线程池的工作线程数大于核心线程数的时候,多余的核心线程数的部分线程(空闲的)可以保持keepAliveTime的空闲时间,当keepAliveTime时间内还没有获取到任务,这些线程后就会被回收。
    unit:保持空闲时间的时间单位。
    workQueue:任务队列,当线程池里面核心线程都在工作的时候,再向线程池指派任务,线程池会将任务放入任务队列里,工作线程在执行完任务后会再向任务队列里取出任务来执行。
    threadFactory:创建执行任务的工作线程的线程工厂。
    handler:拒绝任务加入线程池的策越,当线程池里的线程已经达到最大数后,再向线程池里加派任务时,线程池会决绝执行这些任务,handler就是具体执行拒绝的对象。


线程池的大体工作思路  

1.当线程池小于corePoolSize时,新提交任务将创建一个新线程执行任务,即使此时线程池中存在空闲线程。 
2.当线程池达到corePoolSize时,新提交任务将被放入workQueue中,等待线程池中任务调度执行 
3.当workQueue已满,且maximumPoolSize>corePoolSize时,新提交任务会创建新线程执行任务 
4.当提交任务数超过maximumPoolSize时,新提交任务由RejectedExecutionHandler处理 
5.当线程池中超过corePoolSize数的线程,空闲时间达到keepAliveTime时,关闭空闲线程 

6.当设置allowCoreThreadTimeOut(true)时,线程池中核心线程空闲时间达到keepAliveTime也将关闭

 /**
     * 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
            running状态是可以接受和处理任务 * SHUTDOWN: Don't accept new tasks, but process queued tasks
            shutdown状态时不能接受新的任务,但是仍可以处理对列中的任务 * STOP: Don't accept new tasks, don't process queued tasks,
            stop状态,不接受新任务,也不执行对列中的任务,同事中断正在执行的任务 * 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
            tidying状态,所有的工作线程全部停止,并工作线程数量为0,将调用terminated方法,进入到terninated状态 * TERMINATED: terminated() has completed
            终止状态 * * 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: *各种状态的转换----- * 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)); private static final int COUNT_BITS = Integer.SIZE - 3; private static final int CAPACITY = (1 << COUNT_BITS) - 1;//默认的容量2^29 -1 // runState is stored in the high-order bits 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 private static int runStateOf(int c) { return c & ~CAPACITY; } private static int workerCountOf(int c) { return c & CAPACITY; } private static int ctlOf(int rs, int wc) { return rs | wc; }//rs:状态 ws:数量
转:
为什么线程池的状态简单的定义为 -1,0,1,2,3不就得了,为什么还要用移位操作呢?
原来这样的,ThreadPool
ctl的这个变量的设计哲学是用int的高3位 + 29个0代表状态,,用高位000+低29位来表示线程池中工作线程的数量,太佩服了。
首先CAPACITY的值为workCount的最大容量,该值为 000 11111 11111111 11111111 11111111,29个1(默认的出事容量536870911)
我们来看一下
private static int runStateOf(int c)     { return c & ~CAPACITY; }
用ctl里面的值与容量取反的方式获取状态值。由于CAPACITY的值为000 11111 11111111 11111111 11111111,
那取反后为111 00000 00000000 00000000 00000000, 用 c 与 该值进行与运算,这样就直接保留了c的高三位,
然后将c的低29位设置为0,这不就是线程池状态的存放规则吗,绝。 根据此方法,不难得出计算workCount的方法。
private static int ctlOf(int rs, int wc) { return rs | wc; } 该方法,主要是用来更新运行状态的。确保工作线程数量不丢失。

--------->

理解:

ctl初始化:1110 0000 0000 0000 0000 0000 0000 0000   (该值也就是running状态值)-536870912

capacity: 0001 1111 1111  1111  1111  1111  1111  1111     536870911

当addworker()添加任务是,ctl中的value(也就是通过ctl.get()取到的值)就会加1,

即:       1110 0000 0000 0000 0000 0000 0000 0001

该值  &  初始容量capacity,即workerCountOf(c)方法:结果就是0000 0000 0000 0000 0000 0000 0000 0001(1),也就是线程数量为1个,同理

getTask()的时候回进行-1操作
线程池设计原理:
1)线程池的工作线程为ThreadPoolExecutors的Worker线程,无论是submit还是executor方法中传入的Callable task,Runable参数,只是实现了Runnable接口,在线程池的调用过程,不会调用其start方法,只会调用Worker线程的start方法,然后在Worker线程的run方法中会调用入参的run方法。
2)线程的生命周期在run方法运行结束后(包括异常退出)就结束。要想重复利用线程,就要确保工作线程Worker的run方法运行在一个 无限循环中,然后从任务队列中一个一个获取对象,如果任务队列为空,则阻塞,当然需要提供一些控制,结束无限循环,来销毁线程。在源码 runWorker方法与getTask来实现。 
大概的实现思路是 如果getTask返回null,则该worker线程将被销毁。
那getTask在什么情况下会返回false呢?
1、如果线程池的状态为SHUTDOWN并且队列不为空
2、如果线程池的状态大于STOP
3、如果当前运行的线程数大于核心线程数,会返回null,已销毁该worker线程
对keepAliveTime的理解,如果allowCoreThreadTimeOut为真,那么keepAliveTime其实就是从任务队列获取任务等待的超时时间,也就是workerQueue.poll(keepALiveTime, TimeUnit.NANOSECONDS)
    /**
     * 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.
         */
        int c = ctl.get();//从ctl中取值,该值包含状态和数量
        if (workerCountOf(c) < corePoolSize) {//调用workCountOf方法得到当前的线程数量,和核心线程数比较
            if (addWorker(command, true))//符合,则调用addworker直接创建线程来执行(这里就是表示,当小于核心线程数时,不管有无空闲线程,都会创建新的线程)
                return;//创建成功直接return
            c = ctl.get();
        }
      //没有创建成功则会进行拒绝策略方面的方法判断
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); }

addWorder():

    /**
     * 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://重复执行的标记,下边代码有break retry(结束)和continue retry(返回周之前标记为重新执行)
        for (;;) {
            int c = ctl.get();//取码
            int rs = runStateOf(c);//状态码

            // 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))//进行ctl.value加1操作,成功则结束retry
                    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 {
            w = new Worker(firstTask);//new worker的时候,内部类中会调用工厂来新建一个线程
            final Thread t = w.thread;
            if (t != null) {
                final ReentrantLock mainLock = this.mainLock;//重复锁
                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();
                        workers.add(w);//workers,set集合,保存着所有的worker
                        int s = workers.size();
                        if (s > largestPoolSize)
                            largestPoolSize = s;
                        workerAdded = true;
                    }
                } finally {
                    mainLock.unlock();
                }
                if (workerAdded) {
                    t.start();//
                    workerStarted = true;
                }
            }
        } finally {
            if (! workerStarted)
                addWorkerFailed(w);
        }
        return workerStarted;
    }

getTask():

    /**
     * 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();//处于stop、tidying、terminate状态时,循环减线程数量,回去返回对象
                return null;
            }

            int wc = workerCountOf(c);

            // Are workers subject to culling?
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;//

            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            try {
          //下边这一块代码控制着线程超时时间 Runnable r
= timed ? workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) : workQueue.take(); if (r != null) return r; timedOut = true; } catch (InterruptedException retry) { timedOut = false; } } }

ThreadPoolExecutor的执行:

  当第一次submit或者execute添加任务的时候,如果添加成功会调Thread.start()方法,想线程得到CPU的使用位置的时候,就会走Worker的

run()方法,该run方法会走ThreadPoolExecutor中的runWorker()方法,在这个方法中会走Runnable的run()方法。

关于多线程的blog

http://ifeve.com/volatile/

https://blog.csdn.net/hounanjsj/article/details/73822998

https://blog.csdn.net/wangbiao007/article/details/78196413

https://blog.csdn.net/prestigeding/article/details/53929713

https://blog.csdn.net/wangbiao007/article/details/78196413

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转载自www.cnblogs.com/nxzblogs/p/9231098.html