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：
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;
}
}
}