java中的多线程

线程操作系统能够执行调度的最小单位。我们在面对一些高并发场景或耗时任务的时候,通常都会采用异步线程的方式,在java中,使用线程的方式本身就很多,除了原生的Thread可以包装Runnable,还有Executor线程池可以包装RunnableCallableFutrue接口,也可以用FutrueTask做适配。不同的线程创建方式对应不同的应用场景,而对于一般的后台系统或者应用程序而言,使用合理的线程池来对系统中的不同任务(io、cpu)进行调度是一种比较好的方式。这边先介绍一下基本接口和类的概念。

Runnable

Runnable是一个普通的接口,里面仅包含一个run()方法,并且没有返回值,一般用Thread包装Runnable并执行时,Runnablerun()方法会在单独的线程执行,异步过程中无法阻塞到任务结束再返回结果,并且也不会抛出异常到启动它的线程中。

@FunctionalInterface
public interface Runnable {
    /**
     * When an object implementing interface Runnable is used
     * to create a thread, starting the thread causes the object's
     * run method to be called in that separately executing
     * thread.
     * 

* The general contract of the method run is that it may * take any action whatsoever. * * @see java.lang.Thread#run() */ public abstract void run(); }

Callable

Callable是一个带泛型的接口,并且它的call()方法返回的也就是这个V类型的数据,这也就意味着这里是可以阻塞到结束返回结果的,相应的这里有抛出的异常需要调用方进行处理。可以看到注释解释道:要么返回一个结果,要么抛出一个异常,这样外部只要加上异常处理机制,对于需要根据返回结果来进行操作的任务来说非常友好。

@FunctionalInterface
public interface Callable {
    /**
     * Computes a result, or throws an exception if unable to do so.
     *
     * @return computed result
     * @throws Exception if unable to compute a result
     */
    V call() throws Exception;
}

Thread

Thread是java对于线程这一概念的抽象,我们通常使用Thread创建和启动一个新的线程通常有两种方式

覆写run方法

Thread thread = new Thread() {
            @Override
            void run() {
                //...execute task
            }
        }
thread.start();

通过覆写run()方法的方式,在run()方法中耗时任务或操作,调用Threadstart()方法来开启线程。

包装Runnable

Thread thread = new Thread(new Runnable() {
            @Override
            void run() {
                //...execute task
            }
        });
thread.start();

通过包装Runnable接口,在Runnable接口的run()方法中执行耗时任务好操作,调用Threadstart()方法来开启线程。

Thread内如何启动

我们很好奇为什么这边调用了Threadstart()方法就执行了Thread或者Runnablerun()方法,既然如此那为什么不直接调用thread.run()来开启线程呢?还是在start()方法中间接的调用了run()方法?当然如果是这样肯定是没有意义的。正所谓reading the fucking source code,进入Thread的源码中去查看

    public void run() {
        if (target != null) {
            target.run();
        }
    }

可以看到这里的run()方法执行是判断一个Runnable类型的target是否存在,存在则调用target.run()来执行任务,也就是上述包装了Runnable接口的方式,而如果没有包装Runnable接口采用继承Thread的方式,就会直接覆写了run()方法而不用考虑是否包装了Runnable。我们再看start()方法:

    /**
     * Causes this thread to begin execution; the Java Virtual Machine
     * calls the run method of this thread.
     * 

* The result is that two threads are running concurrently: the * current thread (which returns from the call to the * start method) and the other thread (which executes its * run method). *

* It is never legal to start a thread more than once. * In particular, a thread may not be restarted once it has completed * execution. * * @exception IllegalThreadStateException if the thread was already * started. * @see #run() * @see #stop() */ public synchronized void start() { if (threadStatus != 0) throw new IllegalThreadStateException(); group.add(this); boolean started = false; try { start0(); started = true; } finally { try { if (!started) { group.threadStartFailed(this); } } catch (Throwable ignore) { /* do nothing. If start0 threw a Throwable then it will be passed up the call stack */ } } }

可以看到,这里关键的是调用了start0(),而这是个native方法,这里没法reading the fucking source code,所以看到为什么copy了这么一大堆注释,当然是为了reading the fucking annotation了,可以看到,注释的意思也是在调用的线程调用start()在另一个线程执行了run()方法,也可以猜想到start0()中间应该是分配了线程的一些资源内存等内容,并确实在操作系统创建了一个对应的线程的映射,然后在新创建的线程中调用了run()方法执行新线程的任务。这里也印证了我的想法:从 Java 到 C++, 以 JVM 的角度看 Java 线程的创建与运行

Executor、ExecutorService和ThreadPool

Executor

Execuot是一个接口,声明如下:

public interface Executor {

    /**
     * Executes the given command at some time in the future.  The command
     * may execute in a new thread, in a pooled thread, or in the calling
     * thread, at the discretion of the {@code Executor} implementation.
     *
     * @param command the runnable task
     * @throws RejectedExecutionException if this task cannot be
     * accepted for execution
     * @throws NullPointerException if command is null
     */
    void execute(Runnable command);
}

可以看到这个接口主要就是约定了一个规范,传入一个Runnable然后执行,事实上我们也可以简单的实现这个接口然后通过Thread.start()传入这个Runnable执行。

ExecutorService

ExecutorService扩展了Executor的方法,在原有的基础上增加了一系列的功能:

public interface ExecutorService extends Executor {

    void shutdown();

    List shutdownNow();

    boolean isShutdown();

    boolean isTerminated();

    boolean awaitTermination(long timeout, TimeUnit unit)
        throws InterruptedException;

     Future submit(Callable task);

     Future submit(Runnable task, T result);

    Future submit(Runnable task);

     List> invokeAll(Collection> tasks)
        throws InterruptedException;

     List> invokeAll(Collection> tasks,
                                  long timeout, TimeUnit unit)
        throws InterruptedException;

     T invokeAny(Collection> tasks)
        throws InterruptedException, ExecutionException;

     T invokeAny(Collection> tasks,
                    long timeout, TimeUnit unit)
        throws InterruptedException, ExecutionException, TimeoutException;
}

可以看到ExecutorService相比于Executor而言扩展了很多方法,不仅可以提交Runnable,还可以传入Callable接口,返回Futrue等,功能上强大了很多。

AbstractExecutorService

AbstractExecutorService又实现了ExecutorService接口,实现了submit方法,我们看是如何实现的

    public Future submit(Runnable task) {
        if (task == null) throw new NullPointerException();
        RunnableFuture ftask = newTaskFor(task, null);
        execute(ftask);
        return ftask;
    }

    public  Future submit(Runnable task, T result) {
        if (task == null) throw new NullPointerException();
        RunnableFuture ftask = newTaskFor(task, result);
        execute(ftask);
        return ftask;
    }

    public  Future submit(Callable task) {
        if (task == null) throw new NullPointerException();
        RunnableFuture ftask = newTaskFor(task);
        execute(ftask);
        return ftask;
    }

可以看到,无论submit的是Runnable还是Callable,都是通过一个newTaskFor()方法来获取到RunnableFuture实例的,然后再将实例丢进execute中去执行

    protected  RunnableFuture newTaskFor(Callable callable) {
        return new FutureTask(callable);
    }

    protected  RunnableFuture newTaskFor(Runnable runnable, T value) {
        return new FutureTask(runnable, value);
    }

可以看到,newTaskFor()无论是包装Callable还是Runnable,最终都是返回的一个FutureTask实例,也就是最后是这个实例丢在execute中去执行的。execute的实现在ThreadPoolExecutor中。

ThreadPoolExecutor

ThreadPoolExecutor继承了AbstractExecutorService,实现了ExecutorServiceexecute()方法,我们先看看它的构造函数

    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue workQueue,
                              ThreadFactory threadFactory,
                              RejectedExecutionHandler handler) {
        ...
        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;
    }

ThreadPoolExecutor有4个构造函数,其它3个最终都会调用到这个构造函数,我们主要关心它的参数。

  • corePoolSize:线程池的保持的核心线程数,
  • maximumPoolSize:线程池允许创建的最大线程数,当workQueue是无界队列时此参数失效
  • keepAliveTime:当线程池线程总数大于corePoolSize时,剩余非核心线程存活的时间
  • unitkeepAliveTime的单位,可选SECONDSMINUTESHOURS
  • workQueue:任务队列,如果当前线程数达到corePoolSize,且所有线程都处于活跃状态,就将新加入的任务放入此队列。
  • threadFactory:线程创建的工厂,用户可以传入自定义的ThreadFactory来控制线程创建过程。
  • handler:拒绝策略,默认为AbortPolicy,作用是直接抛出RejectedExecutionException,当线程池和workQueue都满了的情况下会调用该handler的拒绝策略,用户可以通过传入handler来控制拒绝策略的执行。

同时ExecutorServiceexecute()实现实在ThreadPoolExecutor中的:

    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();
        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);
    }

注释很明确,整体分为3步:

  1. 如果正在运行的线程少于coreSize核心线程数,就开启一个新的Thread并将这个Runnable传入其中作为该Thread的第一个任务,调用addWorker的时候会通过原子性的检查runStateworkCount,来确保那些不应该被添加的任务不被添加进来。
  2. 如果任务可以被成功的加入队列,继续上面的原子性检验,再确定是回滚该操作还是开启一个新的线程来执行这个任务。
  3. 如果没办法向队列中添加任务,则调用reject(command)来调用任务拒绝策略。

我们看到源码里ct1.get(),其实这就是一个AtomicInteger

    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;

    // 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; }

我们看到还有其它一系列变量,这里的变量主要是围绕着CAPACITY来做位元算,其实这里是用了一个AtomicInteger来存储线程状态和工作线程数量的,其中,前3位存储状态,后面29位存储工作线程数量,我们看到的CAPACITY最大容量值就是2^29-1,基本上线程池也不可能有这么多的线程。同时基于AtomicInteger来存储状态和工作线程数量保证了这两项数据的原子性,因此每次拿到的值在多线程环境下都是可靠的。

    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
            }
        }


    }

要想知道addWorker做了什么工作,还是跟进源码里比较清楚,首先是一个死循环,里面在不断地获取runState,如果进入到rs >= SHUTDOWN &&! (rs == SHUTDOWN && firstTask == null && ! workQueue.isEmpty())return false结束这个方法表示向线程池添加这个Runnable失败。那么对这个条件拆解一下也就是rs> SHUTDOWN && firstTask!=null && workQueue.isEmpty()firstTask!=null只有传入null时才成立,firstTask不为null时,也就是rs > SHUTDOWN && workQueue.isEmpty()时才会进入这个判断,结合前面的各种状态和注释,也就是说当runStateSTOPTIDYINGTERMINATED时,即使workQueue这个工作队列为空,也拒绝继续向线程池添加该Runnable任务。

接下来又是一个死循环,不断地获取workCount,我们之前说过CAPACITY代表的是当前线程池允许的最大容量2^29-1,而corePoolSizemaximumPoolSize分别代表核心线程数和最大允许线程数,根据传入的参数core决定选择其中一个,这里判断的目的很明显,即工作线程数不能超过线程池允许的最大容量(这里的最大容量可以是corePoolSize/maxmiumSize/CAPACITY),否则也是return false宣告Runnable添加失败。后面执行compareAndIncrementWorkerCount()来尝试将ctl做增1操作,如果成功则跳出retry循环,执行下面的代码。

        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;
                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);
                        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;

这边会创建一个Worker的实例,将传入的Runnable实例包装进去,然后获取到w.thread对象,这里的Thread是由Executors.defaultThreadFactory()来创建的,在构造函数的时候创建,如果用户传入了自己的ThreadFactory则这个Thread实例就是用户创建的Thread实例了。接下来使用了ReentrantLock来对后续的操作加锁,重新获取了当前的runState,根据判断条件很容易看懂,当当前状态为Running时,或者状态为SHUTDOWN且传入的fristTask为空时,会将当前的Work实例加入到workers这个正在工作的队列中,在finally块中对lock解锁后调用t.start()开启线程,从而真正的执行Runnable中的任务。这样一个Runnable或者说一个包装好的FutureTask任务就在线程池中被执行了。

再回到之前的execute()

        int c = ctl.get();
        //直接创建新线程start()执行task
        if (workerCountOf(c) < corePoolSize) {
            if (addWorker(command, true))
                return;
            c = ctl.get();
        }
        // state < SHUTDOWN && works.size()>coreSize && workQueue.offer(command)
        if (isRunning(c) && workQueue.offer(command)) {
            int recheck = ctl.get();
            // 二次校验
            if (! isRunning(recheck) && remove(command))
                reject(command);
            else if (workerCountOf(recheck) == 0)
                addWorker(null, false);
        }
        //直接addWorker,看看是否达到maxmiumPoolSize,add失败进入拒绝策略
        else if (!addWorker(command, false))
            reject(command);

结合前面的分析,主要分为3种状态,

  1. workCount<corePoolSize时,调用addWorker(command,true)进入addWorker()中,因为此时coreSize还没满,因此直接跳出内部的循环,创建Worker实例对象并且调用该Worker内部的t.start()开启线程直接执行该任务。
  2. isRunning(c)&& workQueue.offer(command)时,二次校验如果!isRunning(c),从workQueue中移除刚刚添加的runnable,这种情况的发生可能是调用了ThreadPoolExecutorshutdown终止线程池,而这个task刚刚进入这个方法,这时候会调用拒绝策略。或者可能发生当前的workCount为0,那么这时候添加一个空的任务进去直接返回false了。
  3. 如果不为Running状态或者WorkQueue已满无法添加task时,直接调用addWorker尝试将其添加到一个Worker中并开启新线程执行它,如果失败了就调用拒绝策略。

综上,就是线程池ThreadPoolExecutor执行一个新的任务的全过程。

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