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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：

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
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
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

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

双重for循环检查线程池是否适合增加新的线程
创建Worker对象并获得mainLock锁
再次检查状态，防止线程工厂失败或线程池关闭
works增加worker对象，并更新largestPoolSize，释放锁
启用worker对象中的线程

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)。

Worker类继承自AbstractQueuedSynchronizer，实现了Runnable接口
new Worker()时，通过ThreadFactory的newThread方法创建了一个新的线程

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

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
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

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

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

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;
         }
     }
 }

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原文地址：https://www.cnblogs.com/lntea/p/4678069.html

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