有关线程池的参数和使用方法在上一篇文章中已经介绍过了就不再赘述
这一篇文章主要分析线程池的实现原理，以及线程的复用。 首先我们来看一下线程池，各种状态的表示。线程池中对于状态，和线程数量使用的是位运算来记录
// Android-added: @ReachabilitySensitive
@ReachabilitySensitive
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; }
/*
* Bit field accessors that don't require unpacking ctl.
* These depend on the bit layout and on workerCount being never negative.
*/
private static boolean runStateLessThan(int c, int s) {
return c < s;
}
private static boolean runStateAtLeast(int c, int s) {
return c >= s;
}
private static boolean isRunning(int c) {
return c < SHUTDOWN;
}
根据注释我们知道线程池控制状态ctl是一个原子整数，包装了两个字段workerCount，表示有效线程数runState，表示是否正在运行、正在关闭等 workerCount 是允许启动和不允许停止的工作程序的数量。该值可能与实际的活动线程数暂时不同，例如，当 ThreadFactory 在被询问时未能创建线程时，以及退出线程在终止前仍在执行簿记时。用户可见的池大小报告为工作集的当前大小。
接下来当我们提交任务时，会进入到execute方法。
添加任务分为三步
-
如果运行的线程少于 corePoolSize，尝试调用addWorker来创建一个新的线程来处理任务。在 addWorker中会检查线程池的状态 runState 和 workerCount，如果返回 false 来防止在不应该添加线程时添加线程的错误警报。
-
如果核心线程池满了，并且线程池还在运行，就会把这个任务放入等待队列中，在加入等待队列后，线程池会再次检查线程池的状态，和核心线程池的数量，防止在添加任务的时候线程池被关闭，或者有的核心线程死亡或者任务执行完成。如果核心线程中出现空闲，那么这个任务就会被立即放入核心线程中执行
3.如果等待队列满了，就会尝试添加一个新的非核心线程。如果失败了，表示线程池被关闭或者已经饱和了，因此拒绝任务。
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);
}
在上面的代码中，最重要的方法就是addWork，这个是线程池添加任务的核心代码。addWork接受两个参数，第一个参数表示的是我们提交的任务，第二个参数表示的是否创建的是核心线程，true为核心线程，false为非核心线程。 进入addWork方法首先是两个嵌套for循环，第一个for循环检查线程池是否被关闭，传入的参数是否为NULL。 第二个for循环检查任务线程是否已经达到最大，或者非核心线程已经满了。经过两个for循环检查，最后调用compareAndIncrementWorkerCount方法将线程池的原子整型+1，跳出循环
进入到下面的封装任务代码Work类是实现自Runnable内部实现了一个简单的互斥锁，将任务通过构造器传递给Work类，并校验Wokr中的线程不为空，使用ReentrantLock防止在添加任务的时候出错，最后在校验过线程池的状态后，将Work加入到workes的HashSet中。启动work类中的线程，执行了Work类中的runWork方法。
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
}
}
boolean workerStarted = false;
boolean workerAdded = false;
Worker w = null;
try {
w = new Worker(firstTask);
final Thread t = w.thread;
if (t != null) {
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();
workerStarted = true;
}
}
} finally {
if (! workerStarted)
addWorkerFailed(w);
}
return workerStarted;
}
在runWorker中通过getTask方法从线程池中取出任务队列在getTask（）方法中会区分当前线程是否是核心线程，如果是核心线程则任务队列会一直阻塞，直到有任务进来，如果不是核心线程则在等待一段时间返回false并结束while循环结束线程，如果在给定时间内非核心线程获取到任务，则继续执行，完成线程的复用。
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 {
//如果是核心线程则调用take()方法一直阻塞，如果是非核心线程则调用poll，在存活时间后如果没有任务，就跳出runWorker的线程
Runnable r = timed ?
workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
workQueue.take();
if (r != null)
return r;
timedOut = true;
} catch (InterruptedException retry) {
timedOut = false;
}
}
}
final void runWorker(Worker w) {
Thread wt = Thread.currentThread();
Runnable task = w.firstTask;
w.firstTask = null;
w.unlock(); // allow interrupts
boolean completedAbruptly = true;
try {
//循环取出任务，如果getTask()返回null则跳出循环，结束线程，如果取到任务
则继续继续使用该线程执行任务，完成线程的复用
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 {
//任务开始前的回调，用户可以自己选择
beforeExecute(wt, task);
Throwable thrown = null;
try {
//开始任务
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 {
//任务结束后的回调
afterExecute(task, thrown);
}
} finally {
task = null;
w.completedTasks++;
w.unlock();
}
}
completedAbruptly = false;
} finally {
processWorkerExit(w, completedAbruptly);
}
}
