摘要：Java是如何实现和管理线程池的?
本文分享自华为云社区《JUC线程池: ThreadPoolExecutor详解》，作者：龙哥手记 。
提示
请带着这些问题继续后文，会很大程度上帮助你更好的理解相关知识点。@pdai
线程池能够对线程进行统一分配，调优和监控:
Java是如何实现和管理线程池的?
从JDK 5开始，把工作单元与执行机制分离开来，工作单元包括Runnable和Callable，而执行机制由Executor框架提供。
public class WorkerThread implements Runnable { private String command; public WorkerThread(String s){ this.command=s; } @Override public void run() { System.out.println(Thread.currentThread().getName()+" Start. Command = "+command); processCommand(); System.out.println(Thread.currentThread().getName()+" End."); } private void processCommand() { try { Thread.sleep(5000); } catch (InterruptedException e) { e.printStackTrace(); } } @Override public String toString(){ return this.command; } }
import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; public class SimpleThreadPool { public static void main(String[] args) { ExecutorService executor = Executors.newFixedThreadPool(5); for (int i = 0; i < 10; i++) { Runnable worker = new WorkerThread("" + i); executor.execute(worker); } executor.shutdown(); // This will make the executor accept no new threads and finish all existing threads in the queue while (!executor.isTerminated()) { // Wait until all threads are finish,and also you can use "executor.awaitTermination();" to wait } System.out.println("Finished all threads"); } }
程序中我们创建了固定大小为五个工作线程的线程池。然后分配给线程池十个工作，因为线程池大小为五，它将启动五个工作线程先处理五个工作，其他的工作则处于等待状态，一旦有工作完成，空闲下来工作线程就会捡取等待队列里的其他工作进行执行。
这里是以上程序的输出。
pool-1-thread-2 Start. Command = 1 pool-1-thread-4 Start. Command = 3 pool-1-thread-1 Start. Command = 0 pool-1-thread-3 Start. Command = 2 pool-1-thread-5 Start. Command = 4 pool-1-thread-4 End. pool-1-thread-5 End. pool-1-thread-1 End. pool-1-thread-3 End. pool-1-thread-3 Start. Command = 8 pool-1-thread-2 End. pool-1-thread-2 Start. Command = 9 pool-1-thread-1 Start. Command = 7 pool-1-thread-5 Start. Command = 6 pool-1-thread-4 Start. Command = 5 pool-1-thread-2 End. pool-1-thread-4 End. pool-1-thread-3 End. pool-1-thread-5 End. pool-1-thread-1 End. Finished all threads
输出表明线程池中至始至终只有五个名为 "pool-1-thread-1" 到 "pool-1-thread-5" 的五个线程，这五个线程不随着工作的完成而消亡，会一直存在，并负责执行分配给线程池的任务，直到线程池消亡。
Executors 类提供了使用了 ThreadPoolExecutor 的简单的 ExecutorService 实现，但是 ThreadPoolExecutor 提供的功能远不止于此。我们可以在创建 ThreadPoolExecutor 实例时指定活动线程的数量，我们也可以限制线程池的大小并且创建我们自己的 RejectedExecutionHandler 实现来处理不能适应工作队列的工作。
这里是我们自定义的 RejectedExecutionHandler 接口的实现。
import java.util.concurrent.RejectedExecutionHandler; import java.util.concurrent.ThreadPoolExecutor; public class RejectedExecutionHandlerImpl implements RejectedExecutionHandler { @Override public void rejectedExecution(Runnable r, ThreadPoolExecutor executor) { System.out.println(r.toString() + " is rejected"); } }
ThreadPoolExecutor 提供了一些方法，我们可以使用这些方法来查询 executor 的当前状态，线程池大小，活动线程数量以及任务数量。因此我是用来一个监控线程在特定的时间间隔内打印 executor 信息。
import java.util.concurrent.ThreadPoolExecutor; public class MyMonitorThread implements Runnable { private ThreadPoolExecutor executor; private int seconds; private boolean run=true; public MyMonitorThread(ThreadPoolExecutor executor, int delay) { this.executor = executor; this.seconds=delay; } public void shutdown(){ this.run=false; } @Override public void run() { while(run){ System.out.println( String.format("[monitor] [%d/%d] Active: %d, Completed: %d, Task: %d, isShutdown: %s, isTerminated: %s", this.executor.getPoolSize(), this.executor.getCorePoolSize(), this.executor.getActiveCount(), this.executor.getCompletedTaskCount(), this.executor.getTaskCount(), this.executor.isShutdown(), this.executor.isTerminated())); try { Thread.sleep(seconds*1000); } catch (InterruptedException e) { e.printStackTrace(); } } } }
这里是使用 ThreadPoolExecutor 的线程池实现例子。
import java.util.concurrent.ArrayBlockingQueue; import java.util.concurrent.Executors; import java.util.concurrent.ThreadFactory; import java.util.concurrent.ThreadPoolExecutor; import java.util.concurrent.TimeUnit; public class WorkerPool { public static void main(String args[]) throws InterruptedException{ //RejectedExecutionHandler implementation RejectedExecutionHandlerImpl rejectionHandler = new RejectedExecutionHandlerImpl(); //Get the ThreadFactory implementation to use ThreadFactory threadFactory = Executors.defaultThreadFactory(); //creating the ThreadPoolExecutor ThreadPoolExecutor executorPool = new ThreadPoolExecutor(2, 4, 10, TimeUnit.SECONDS, new ArrayBlockingQueue<Runnable>(2), threadFactory, rejectionHandler); //start the monitoring thread MyMonitorThread monitor = new MyMonitorThread(executorPool, 3); Thread monitorThread = new Thread(monitor); monitorThread.start(); //submit work to the thread pool for(int i=0; i<10; i++){ executorPool.execute(new WorkerThread("cmd"+i)); } Thread.sleep(30000); //shut down the pool executorPool.shutdown(); //shut down the monitor thread Thread.sleep(5000); monitor.shutdown(); } }
注意在初始化 ThreadPoolExecutor 时，我们保持初始池大小为 2，最大池大小为 4 而工作队列大小为 2。因此如果已经有四个正在执行的任务而此时分配来更多任务的话，工作队列将仅仅保留他们(新任务)中的两个，其他的将会被 RejectedExecutionHandlerImpl 处理。
上面程序的输出可以证实以上观点。
pool-1-thread-1 Start. Command = cmd0 pool-1-thread-4 Start. Command = cmd5 cmd6 is rejected pool-1-thread-3 Start. Command = cmd4 pool-1-thread-2 Start. Command = cmd1 cmd7 is rejected cmd8 is rejected cmd9 is rejected [monitor] [0/2] Active: 4, Completed: 0, Task: 6, isShutdown: false, isTerminated: false [monitor] [4/2] Active: 4, Completed: 0, Task: 6, isShutdown: false, isTerminated: false pool-1-thread-4 End. pool-1-thread-1 End. pool-1-thread-2 End. pool-1-thread-3 End. pool-1-thread-1 Start. Command = cmd3 pool-1-thread-4 Start. Command = cmd2 [monitor] [4/2] Active: 2, Completed: 4, Task: 6, isShutdown: false, isTerminated: false [monitor] [4/2] Active: 2, Completed: 4, Task: 6, isShutdown: false, isTerminated: false pool-1-thread-1 End. pool-1-thread-4 End. [monitor] [4/2] Active: 0, Completed: 6, Task: 6, isShutdown: false, isTerminated: false [monitor] [2/2] Active: 0, Completed: 6, Task: 6, isShutdown: false, isTerminated: false [monitor] [2/2] Active: 0, Completed: 6, Task: 6, isShutdown: false, isTerminated: false [monitor] [2/2] Active: 0, Completed: 6, Task: 6, isShutdown: false, isTerminated: false [monitor] [2/2] Active: 0, Completed: 6, Task: 6, isShutdown: false, isTerminated: false [monitor] [2/2] Active: 0, Completed: 6, Task: 6, isShutdown: false, isTerminated: false [monitor] [0/2] Active: 0, Completed: 6, Task: 6, isShutdown: true, isTerminated: true [monitor] [0/2] Active: 0, Completed: 6, Task: 6, isShutdown: true, isTerminated: true
注意 executor 的活动任务、完成任务以及所有完成任务，这些数量上的变化。我们可以调用 shutdown() 方法来结束所有提交的任务并终止线程池。
其实java线程池的实现原理很简单，说白了就是一个线程集合workerSet和一个阻塞队列workQueue。当用户向线程池提交一个任务(也就是线程)时，线程池会先将任务放入workQueue中。workerSet中的线程会不断的从workQueue中获取线程然后执行。当workQueue中没有任务的时候，worker就会阻塞，直到队列中有任务了就取出来继续执行。
当一个任务提交至线程池之后:
当ThreadPoolExecutor创建新线程时，通过CAS来更新线程池的状态ctl.
public ThreadPoolExecutor(int corePoolSize, int maximumPoolSize, long keepAliveTime, TimeUnit unit, BlockingQueue<Runnable> workQueue, RejectedExecutionHandler handler)
LinkedBlockingQueue比ArrayBlockingQueue在插入删除节点性能方面更优，但是二者在put(), take()任务的时均需要加锁，SynchronousQueue使用无锁算法，根据节点的状态判断执行，而不需要用到锁，其核心是Transfer.transfer().
当然也可以根据应用场景实现RejectedExecutionHandler接口，自定义饱和策略，如记录日志或持久化存储不能处理的任务。
public static ExecutorService newFixedThreadPool(int nThreads) { return new ThreadPoolExecutor(nThreads, nThreads, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>()); }
线程池的线程数量达corePoolSize后，即使线程池没有可执行任务时，也不会释放线程。
FixedThreadPool的工作队列为无界队列LinkedBlockingQueue(队列容量为Integer.MAX_VALUE), 这会导致以下问题:
public static ExecutorService newSingleThreadExecutor() { return new FinalizableDelegatedExecutorService (new ThreadPoolExecutor(1, 1, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>())); }
初始化的线程池中只有一个线程，如果该线程异常结束，会重新创建一个新的线程继续执行任务，唯一的线程可以保证所提交任务的顺序执行.
由于使用了无界队列, 所以SingleThreadPool永远不会拒绝, 即饱和策略失效
public static ExecutorService newCachedThreadPool() { return new ThreadPoolExecutor(0, Integer.MAX_VALUE, 60L, TimeUnit.SECONDS, new SynchronousQueue<Runnable>()); }
线程池的线程数可达到Integer.MAX_VALUE，即2147483647，内部使用SynchronousQueue作为阻塞队列； 和newFixedThreadPool创建的线程池不同，newCachedThreadPool在没有任务执行时，当线程的空闲时间超过keepAliveTime，会自动释放线程资源，当提交新任务时，如果没有空闲线程，则创建新线程执行任务，会导致一定的系统开销； 执行过程与前两种稍微不同:
遍历线程池中的所有线程，然后逐个调用线程的interrupt方法来中断线程.
将线程池里的线程状态设置成SHUTDOWN状态, 然后中断所有没有正在执行任务的线程.
将线程池里的线程状态设置成STOP状态, 然后停止所有正在执行或暂停任务的线程. 只要调用这两个关闭方法中的任意一个, isShutDown() 返回true. 当所有任务都成功关闭了, isTerminated()返回true.
//这个属性是用来存放 当前运行的worker数量以及线程池状态的 //int是32位的，这里把int的高3位拿来充当线程池状态的标志位,后29位拿来充当当前运行worker的数量 private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0)); //存放任务的阻塞队列 private final BlockingQueue<Runnable> workQueue; //worker的集合,用set来存放 private final HashSet<Worker> workers = new HashSet<Worker>(); //历史达到的worker数最大值 private int largestPoolSize; //当队列满了并且worker的数量达到maxSize的时候,执行具体的拒绝策略 private volatile RejectedExecutionHandler handler; //超出coreSize的worker的生存时间 private volatile long keepAliveTime; //常驻worker的数量 private volatile int corePoolSize; //最大worker的数量,一般当workQueue满了才会用到这个参数 private volatile int maximumPoolSize;
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; }
其中AtomicInteger变量ctl的功能非常强大: 利用低29位表示线程池中线程数，通过高3位表示线程池的运行状态:
execute –> addWorker –>runworker (getTask)
线程池的工作线程通过Woker类实现，在ReentrantLock锁的保证下，把Woker实例插入到HashSet后，并启动Woker中的线程。 从Woker类的构造方法实现可以发现: 线程工厂在创建线程thread时，将Woker实例本身this作为参数传入，当执行start方法启动线程thread时，本质是执行了Worker的runWorker方法。 firstTask执行完成之后，通过getTask方法从阻塞队列中获取等待的任务，如果队列中没有任务，getTask方法会被阻塞并挂起，不会占用cpu资源；
ThreadPoolExecutor.execute(task)实现了Executor.execute(task)
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) { //workerCountOf获取线程池的当前线程数；小于corePoolSize，执行addWorker创建新线程执行command任务 if (addWorker(command, true)) return; c = ctl.get(); } // double check: c, recheck // 线程池处于RUNNING状态，把提交的任务成功放入阻塞队列中 if (isRunning(c) && workQueue.offer(command)) { int recheck = ctl.get(); // recheck and if necessary 回滚到入队操作前，即倘若线程池shutdown状态，就remove(command) //如果线程池没有RUNNING，成功从阻塞队列中删除任务，执行reject方法处理任务 if (! isRunning(recheck) && remove(command)) reject(command); //线程池处于running状态，但是没有线程，则创建线程 else if (workerCountOf(recheck) == 0) addWorker(null, false); } // 往线程池中创建新的线程失败，则reject任务 else if (!addWorker(command, false)) reject(command); }
在多线程环境下，线程池的状态时刻在变化，而ctl.get()是非原子操作，很有可能刚获取了线程池状态后线程池状态就改变了。判断是否将command加入workque是线程池之前的状态。倘若没有double check，万一线程池处于非running状态(在多线程环境下很有可能发生)，那么command永远不会执行。
从方法execute的实现可以看出: addWorker主要负责创建新的线程并执行任务 线程池创建新线程执行任务时，需要 获取全局锁:
private final ReentrantLock mainLock = new ReentrantLock();
private boolean addWorker(Runnable firstTask, boolean core) { // CAS更新线程池数量 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 } } boolean workerStarted = false; boolean workerAdded = false; Worker w = null; try { w = new Worker(firstTask); final Thread t = w.thread; if (t != null) { // 线程池重入锁 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(); // 线程启动，执行任务(Worker.thread(firstTask).start()); workerStarted = true; } } } finally { if (! workerStarted) addWorkerFailed(w); } return workerStarted; }
private final class Worker extends AbstractQueuedSynchronizer implements Runnable{ Worker(Runnable firstTask) { setState(-1); // inhibit interrupts until runWorker this.firstTask = firstTask; this.thread = getThreadFactory().newThread(this); // 创建线程 } /** Delegates main run loop to outer runWorker */ public void run() { runWorker(this); } // ... }
一些属性还有构造方法:
//运行的线程,前面addWorker方法中就是直接通过启动这个线程来启动这个worker final Thread thread; //当一个worker刚创建的时候,就先尝试执行这个任务 Runnable firstTask; //记录完成任务的数量 volatile long completedTasks; Worker(Runnable firstTask) { setState(-1); // inhibit interrupts until runWorker this.firstTask = firstTask; //创建一个Thread,将自己设置给他,后面这个thread启动的时候,也就是执行worker的run方法 this.thread = getThreadFactory().newThread(this); }
runWorker方法是线程池的核心:
通过getTask方法从阻塞队列中获取等待的任务，如果队列中没有任务，getTask方法会被阻塞并挂起，不会占用cpu资源；
final void runWorker(Worker w) { Thread wt = Thread.currentThread(); Runnable task = w.firstTask; w.firstTask = null; w.unlock(); // allow interrupts boolean completedAbruptly = true; try { // 先执行firstTask，再从workerQueue中取task(getTask()) 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); } }
下面来看一下getTask()方法，这里面涉及到keepAliveTime的使用，从这个方法我们可以看出线程池是怎么让超过corePoolSize的那部分worker销毁的。
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(); 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 { Runnable r = timed ? workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) : workQueue.take(); if (r != null) return r; timedOut = true; } catch (InterruptedException retry) { timedOut = false; } } }
注意这里一段代码是keepAliveTime起作用的关键:
boolean timed = allowCoreThreadTimeOut || wc > corePoolSize; Runnable r = timed ? workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) : workQueue.take();
allowCoreThreadTimeOut为false，线程即使空闲也不会被销毁；倘若为ture，在keepAliveTime内仍空闲则会被销毁。
如果线程允许空闲等待而不被销毁timed == false，workQueue.take任务: 如果阻塞队列为空，当前线程会被挂起等待；当队列中有任务加入时，线程被唤醒，take方法返回任务，并执行；
如果线程不允许无休止空闲timed == true, workQueue.poll任务: 如果在keepAliveTime时间内，阻塞队列还是没有任务，则返回null；
public class Test{ public static void main(String[] args) { ExecutorService es = Executors.newCachedThreadPool(); Future<String> future = es.submit(new Callable<String>() { @Override public String call() throws Exception { try { TimeUnit.SECONDS.sleep(2); } catch (InterruptedException e) { e.printStackTrace(); } return "future result"; } }); try { String result = future.get(); System.out.println(result); } catch (Exception e) { e.printStackTrace(); } } }
在实际业务场景中，Future和Callable基本是成对出现的，Callable负责产生结果，Future负责获取结果。
AbstractExecutorService.submit()实现了ExecutorService.submit() 可以获取执行完的返回值, 而ThreadPoolExecutor 是AbstractExecutorService.submit()的子类，所以submit方法也是ThreadPoolExecutor`的方法。
// submit()在ExecutorService中的定义 <T> Future<T> submit(Callable<T> task); <T> Future<T> submit(Runnable task, T result); Future<?> submit(Runnable task); // submit方法在AbstractExecutorService中的实现 public Future<?> submit(Runnable task) { if (task == null) throw new NullPointerException(); // 通过submit方法提交的Callable任务会被封装成了一个FutureTask对象。 RunnableFuture<Void> ftask = newTaskFor(task, null); execute(ftask); return ftask; }
通过submit方法提交的Callable任务会被封装成了一个FutureTask对象。通过Executor.execute方法提交FutureTask到线程池中等待被执行，最终执行的是FutureTask的run方法；
public class FutureTask<V> implements RunnableFuture<V> 可以将FutureTask提交至线程池中等待被执行(通过FutureTask的run方法来执行)
/* The run state of this task, initially NEW. * ... * Possible state transitions: * NEW -> COMPLETING -> NORMAL * NEW -> COMPLETING -> EXCEPTIONAL * NEW -> CANCELLED * NEW -> INTERRUPTING -> INTERRUPTED */ private volatile int state; private static final int NEW = 0; private static final int COMPLETING = 1; private static final int NORMAL = 2; private static final int EXCEPTIONAL = 3; private static final int CANCELLED = 4; private static final int INTERRUPTING = 5; private static final int INTERRUPTED = 6;
内部状态的修改通过sun.misc.Unsafe修改
public V get() throws InterruptedException, ExecutionException { int s = state; if (s <= COMPLETING) s = awaitDone(false, 0L); return report(s); }
内部通过awaitDone方法对主线程进行阻塞，具体实现如下:
private int awaitDone(boolean timed, long nanos) throws InterruptedException { final long deadline = timed ? System.nanoTime() + nanos : 0L; WaitNode q = null; boolean queued = false; for (;;) { if (Thread.interrupted()) { removeWaiter(q); throw new InterruptedException(); } int s = state; if (s > COMPLETING) { if (q != null) q.thread = null; return s; } else if (s == COMPLETING) // cannot time out yet Thread.yield(); else if (q == null) q = new WaitNode(); else if (!queued) queued = UNSAFE.compareAndSwapObject(this, waitersOffset,q.next = waiters, q); else if (timed) { nanos = deadline - System.nanoTime(); if (nanos <= 0L) { removeWaiter(q); return state; } LockSupport.parkNanos(this, nanos); } else LockSupport.park(this); } }
如果主线程被中断，则抛出中断异常；
public void run() { if (state != NEW || !UNSAFE.compareAndSwapObject(this, runnerOffset, null, Thread.currentThread())) return; try { Callable<V> c = callable; if (c != null && state == NEW) { V result; boolean ran; try { result = c.call(); ran = true; } catch (Throwable ex) { result = null; ran = false; setException(ex); } if (ran) set(result); } } finally { // runner must be non-null until state is settled to // prevent concurrent calls to run() runner = null; // state must be re-read after nulling runner to prevent // leaked interrupts int s = state; if (s >= INTERRUPTING) handlePossibleCancellationInterrupt(s); } }
FutureTask.run方法是在线程池中被执行的，而非主线程
shutdown方法会将线程池的状态设置为SHUTDOWN,线程池进入这个状态后,就拒绝再接受任务,然后会将剩余的任务全部执行完
public void shutdown() { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { //检查是否可以关闭线程 checkShutdownAccess(); //设置线程池状态 advanceRunState(SHUTDOWN); //尝试中断worker interruptIdleWorkers(); //预留方法,留给子类实现 onShutdown(); // hook for ScheduledThreadPoolExecutor } finally { mainLock.unlock(); } tryTerminate(); } private void interruptIdleWorkers() { interruptIdleWorkers(false); } private void interruptIdleWorkers(boolean onlyOne) { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { //遍历所有的worker for (Worker w : workers) { Thread t = w.thread; //先尝试调用w.tryLock(),如果获取到锁,就说明worker是空闲的,就可以直接中断它 //注意的是,worker自己本身实现了AQS同步框架,然后实现的类似锁的功能 //它实现的锁是不可重入的,所以如果worker在执行任务的时候,会先进行加锁,这里tryLock()就会返回false if (!t.isInterrupted() && w.tryLock()) { try { t.interrupt(); } catch (SecurityException ignore) { } finally { w.unlock(); } } if (onlyOne) break; } } finally { mainLock.unlock(); } }
shutdownNow做的比较绝，它先将线程池状态设置为STOP，然后拒绝所有提交的任务。最后中断左右正在运行中的worker,然后清空任务队列。
public List<Runnable> shutdownNow() { List<Runnable> tasks; final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { checkShutdownAccess(); //检测权限 advanceRunState(STOP); //中断所有的worker interruptWorkers(); //清空任务队列 tasks = drainQueue(); } finally { mainLock.unlock(); } tryTerminate(); return tasks; } private void interruptWorkers() { final ReentrantLock mainLock = this.mainLock; mainLock.lock(); try { //遍历所有worker，然后调用中断方法 for (Worker w : workers) w.interruptIfStarted(); } finally { mainLock.unlock(); } }
线程池不允许使用Executors去创建，而是通过ThreadPoolExecutor的方式，这样的处理方式让写的同学更加明确线程池的运行规则，规避资源耗尽的风险。 说明：Executors各个方法的弊端：
首先引入：commons-lang3包
ScheduledExecutorService executorService = new ScheduledThreadPoolExecutor(1, new BasicThreadFactory.Builder().namingPattern("example-schedule-pool-%d").daemon(true).build());
首先引入：com.google.guava包
ThreadFactory namedThreadFactory = new ThreadFactoryBuilder().setNameFormat("demo-pool-%d").build(); //Common Thread Pool ExecutorService pool = new ThreadPoolExecutor(5, 200, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>(1024), namedThreadFactory, new ThreadPoolExecutor.AbortPolicy()); // excute pool.execute(()-> System.out.println(Thread.currentThread().getName())); //gracefully shutdown pool.shutdown();
spring配置线程池方式：自定义线程工厂bean需要实现ThreadFactory，可参考该接口的其它默认实现类，使用方式直接注入bean调用execute(Runnable task)方法即可
<bean id="userThreadPool" class="org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor"> <property name="corePoolSize" value="10" /> <property name="maxPoolSize" value="100" /> <property name="queueCapacity" value="2000" /> <property name="threadFactory" value= threadFactory /> <property name="rejectedExecutionHandler"> <ref local="rejectedExecutionHandler" /> </property> </bean> //in code userThreadPool.execute(thread);
从任务的优先级，任务的执行时间长短，任务的性质(CPU密集/ IO密集)，任务的依赖关系这四个角度来分析。并且近可能地使用有界的工作队列。
性质不同的任务可用使用不同规模的线程池分开处理:
可以使用ThreadPoolExecutor以下方法: