上文中描述了Java中线程池相关的架构，了解了这些内容其实我们就可以使用java的线程池为我们工作了，使用其提供的线程池我们可以很方便的写出高质量的多线程代码，本节将分析ThreadPoolExecutor的实现，来探索线程池的运行原理。下面的图片展示了ThreadPoolExecutor的类图：
ThreadPoolExecutor的类图
下面是几个比较关键的类成员：
// 任务队列，我们的任务会添加到该队列里面，线程将从该队列获取任务来执行
private final BlockingQueue workQueue;
//任务的执行值集合，来消费workQueue里面的任务
private final HashSet workers = new HashSet();
//线程工厂
private volatile ThreadFactory threadFactory;
//拒绝策略，默认会抛出异异常，还要其他几种拒绝策略如下：
private volatile RejectedExecutionHandler handler;
1、CallerRunsPolicy：在调用者线程里面运行该任务
2、DiscardPolicy：丢弃任务
3、DiscardOldestPolicy：丢弃workQueue的头部任务
//最下保活work数量
private volatile int corePoolSize;
//work上限
private volatile int maximumPoolSize;
我们尝试执行submit方法，下面是执行的关键路径，总结起来就是：如果Worker数量还没达到上限则继续创建，否则提交任务到workQueue，然后让worker来调度运行任务。
step 1:
Future<?> submit(Runnable task);
step 2:<AbstractExecutorService>
public Future<?> submit(Runnable task) {
if (task == null) throw new NullPointerException();
RunnableFuture<Void> ftask = newTaskFor(task, null);
execute(ftask);
return ftask;
}
step 3:<Executor>
void execute(Runnable command);
step 4:<ThreadPoolExecutor>
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)) { //提交我们的额任务到workQueue
int recheck = ctl.get();
if (! isRunning(recheck) && remove(command))
reject(command);
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
else if (!addWorker(command, false)) //使用maximumPoolSize作为边界
reject(command); //还不行？拒绝提交的任务
}
step 5:<ThreadPoolExecutor>
private boolean addWorker(Runnable firstTask, boolean core)
step 6:<ThreadPoolExecutor>
w = new Worker(firstTask); //包装任务
final Thread t = w.thread; //获取线程（包含任务）
workers.add(w); // 任务被放到works中
t.start(); //执行任务
上面的流程是高度概括的，实际情况远比这复杂得多，但是我们关心的是怎么打通整个流程，所以这样分析问题是没有太大的问题的。观察上面的流程，我们发现其实关键的地方在于Worker，如果弄明白它是如何工作的，那么我们也就大概明白了线程池是怎么工作的了。下面分析一下Worker类。
worker类图
上面的图片展示了Worker的类关系图，关键在于他实现了Runnable接口，所以问题的关键就在于run方法上。在这之前，我们来看一下Worker类里面的关键成员：
final Thread thread;
Runnable firstTask; //我们提交的任务，可能被立刻执行，也可能被放到队列里面
thread是Worker的工作线程，上面的分析我们也发现了在addWorker中会获取worker里面的thread然后start，也就是这个线程的执行，而Worker实现了Runnable接口，所以在构造thread的时候Worker将自己传递给了构造函数，thread.start执行的其实就是Worker的run方法。下面是run方法的内容：
public void run() {
runWorker(this);
}
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);
}
}
