总结：线程池ThreadPoolExecutor是通过控制Worker对象的数量来维护工作的工人集合，并且通过任务队列workerQueue来存储提交到线程池的任务。通过配置相关的容量，以及拒绝策略来更方便使用以及处理容量饱满的情况。Worker使用了同步器来解决任务执行前执行时执行后的同步问题。
值得注意的是submit()和execute()的区别主要是submit()方法会将任务用FutureTask进行包装，包装之后在用execute()执行
java线程池内容较多，简单的架构如下。
线程池结构
顶层接口定义了execute方法
public interface Executor {
/**
* Executes the given command at some time in the future. The command
* may execute in a new thread, in a pooled thread, or in the calling
* thread, at the discretion of the {@code Executor} implementation.
*
* @param command the runnable task
* @throws RejectedExecutionException if this task cannot be
* accepted for execution
* @throws NullPointerException if command is null
*/
void execute(Runnable command);
}
ExecutorService定义了对像城池的一些操作，submit()和shutdown()在这里定义了
public interface ExecutorService extends Executor {
void shutdown();
List shutdownNow();
boolean isShutdown();
boolean isTerminated();
boolean awaitTermination(long var1, TimeUnit var3) throws InterruptedException;
Future submit(Callable var1);
Future submit(Runnable var1, T var2);
Future submit(Runnable var1);
List> invokeAll(Collection> var1) throws InterruptedException;
List> invokeAll(Collection> var1, long var2, TimeUnit var4) throws InterruptedException;
T invokeAny(Collection> var1) throws InterruptedException, ExecutionException;
T invokeAny(Collection> var1, long var2, TimeUnit var4) throws InterruptedException, ExecutionException, TimeoutException;
}
除了这两个接口意外还定义了ScheduledExecutorService接口，并额外定义了定时执行的功能
public interface ScheduledExecutorService extends ExecutorService {
ScheduledFuture schedule(Runnable var1, long var2, TimeUnit var4);
ScheduledFuture schedule(Callable var1, long var2, TimeUnit var4);
ScheduledFuture scheduleAtFixedRate(Runnable var1, long var2, long var4, TimeUnit var6);
ScheduledFuture scheduleWithFixedDelay(Runnable var1, long var2, long var4, TimeUnit var6);
}
再往下就是具体的实现了ThreadPoolExecutor作为一个具体的实现。来看他的构造方法的参数。
-
corePoolSize：核心数 -
maximumPoolSize：最大核心数 -
keepAliveTime：当线程空闲时间达到keepAliveTime，该线程会退出，直到线程数量等于corePoolSize。（超出核心数的线程最大存活时间） -
unit：时间单位 -
workQueue：任务队列 -
threadFactory：线程工厂，可以设置线程的名字 -
handler：拒绝策略，图示**Policy的就是handler对应的策略ThreadPoolExecutor内部实现了这些策略，可选配。
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue workQueue,
ThreadFactory threadFactory,
RejectedExecutionHandler handler)
- 再来看看线程池的源码入口
execute()或者submit()
- 值得注意的是
submit()调用了execute()方法，具有返回值，并且对task进行了包装。 -
execute()方法就是线程池执行的核心了。结合配置的线程和核心数，拒绝策略，有三种场景
public Future submit(Callable task) {
if (task == null) throw new NullPointerException();
RunnableFuture ftask = newTaskFor(task);
execute(ftask);
return ftask;
}
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.
*/
//获取线程池状态，从而判断场景
//场景一：worker小于核心线程数
int c = ctl.get();
if (workerCountOf(c) < corePoolSize) {
if (addWorker(command, true))
return;
c = ctl.get();
}
//场景二：线程在运行，且任务队列大于核心线程数
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);
}
//场景三：非核心工作线程逻辑
else if (!addWorker(command, false))
//执行拒绝策略
reject(command);
}
通过对源码的分析发现无论如何workQueue和addWorker（cammand,boolean）是关键`。
-
workQueue是一个阻塞队列，用于存放所有被提交到线程池的任务（线程）。 -
addWorker()：线程池里面都是工人的概念，增加一个工人来执行线程任务。工人可复用。
/**
* The queue used for holding tasks and handing off to worker
* threads. We do not require that workQueue.poll() returning
* null necessarily means that workQueue.isEmpty(), so rely
* solely on isEmpty to see if the queue is empty (which we must
* do for example when deciding whether to transition from
* SHUTDOWN to TIDYING). This accommodates special-purpose
* queues such as DelayQueues for which poll() is allowed to
* return null even if it may later return non-null when delays
* expire.
*/
private final BlockingQueue workQueue;
addWorker()的工作主要还是初始化工人并且让工人开始工作，执行任务。并且维护一个HashSet来维护工人workers集合
private final HashSet workers = new HashSet();
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 {
//初始化了一个工人，Worker持有一个thread
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();
//增加一个工人
workers.add(w);
int s = workers.size();
if (s > largestPoolSize)
largestPoolSize = s;
workerAdded = true;
}
} finally {
mainLock.unlock();
}
if (workerAdded) {
//执行任务
t.start();
workerStarted = true;
}
}
} finally {
if (! workerStarted)
addWorkerFailed(w);
}
return workerStarted;
}
Worker工人是ThreadPoolExecutor的一个内部类，实现了Runnable说明他本身是一个任务，继承了AbstractQueuedSynchronizer说明有使用AQS保证一些执行动作是同步
private final class Worker extends AbstractQueuedSynchronizer implements Runnable {
private static final long serialVersionUID = 6138294804551838833L;
//持有线程，该线程有配置的线程工厂产生
final Thread thread;
//持有需要执行的任务本身
Runnable firstTask;
volatile long completedTasks;
Worker(Runnable var2) {
this.setState(-1);
this.firstTask = var2;
this.thread = ThreadPoolExecutor.this.getThreadFactory().newThread(this);
}
//实现了run方法
public void run() {
ThreadPoolExecutor.this.runWorker(this);
}
protected boolean isHeldExclusively() {
return this.getState() != 0;
}
protected boolean tryAcquire(int var1) {
if (this.compareAndSetState(0, 1)) {
this.setExclusiveOwnerThread(Thread.currentThread());
return true;
} else {
return false;
}
}
protected boolean tryRelease(int var1) {
this.setExclusiveOwnerThread((Thread)null);
this.setState(0);
return true;
}
public void lock() {
this.acquire(1);
}
public boolean tryLock() {
return this.tryAcquire(1);
}
public void unlock() {
this.release(1);
}
public boolean isLocked() {
return this.isHeldExclusively();
}
void interruptIfStarted() {
Thread var1;
if (this.getState() >= 0 && (var1 = this.thread) != null && !var1.isInterrupted()) {
try {
var1.interrupt();
} catch (SecurityException var3) {
}
}
}
}
通过源码分析我们知道Worker的run方法调用了runWorker()方法，其中的同步操作就是task.run(),执行具体任务的run方法，而task的来源除了worker持有的firtTask，就是getTask()方法从workQueue中获取得到了。
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 {
//回收工人
processWorkerExit(w, completedAbruptly);
}
}
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;
}
}
}
最后还会通过processWorkerExit然当前工人执行回收策略，回收工人。循环使用了workers
private void processWorkerExit(Worker w, boolean completedAbruptly) {
if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
decrementWorkerCount();
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
completedTaskCount += w.completedTasks;
workers.remove(w);
} finally {
mainLock.unlock();
}
tryTerminate();
int c = ctl.get();
if (runStateLessThan(c, STOP)) {
if (!completedAbruptly) {
int min = allowCoreThreadTimeOut ? 0 : corePoolSize;
if (min == 0 && ! workQueue.isEmpty())
min = 1;
if (workerCountOf(c) >= min)
return; // replacement not needed
}
addWorker(null, false);
}
}