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
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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
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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
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works: 存储所有工作线程
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corePoolSize: 核心线程数
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maximumPoolSize: 最大线程数
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keepAliveTime: 空闲线程等待任务时间
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threadFactory: 线程创建工厂
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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：
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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
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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
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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
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双重for循环检查线程池是否适合增加新的线程
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创建Worker对象并获得mainLock锁
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再次检查状态，防止线程工厂失败或线程池关闭
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works增加worker对象，并更新largestPoolSize，释放锁
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启用worker对象中的线程
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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)。
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Worker类继承自AbstractQueuedSynchronizer，实现了Runnable接口
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new Worker()时，通过ThreadFactory的newThread方法创建了一个新的线程
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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
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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
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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
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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
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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
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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; } } }
