上一个分享中，对线程进行了刨析，因为线程申请和释放，会调用本地native方法，调用liunx的方法进行上下文切换并申请和释放资源。所以采用线程池可以减少这种资源的申请和释放，提高系统的性能。
本章对线程池的池化技术进行刨析。
一、温酒
从图中可以看出，ThreadPoolExecutor继承了AbstractExecutorService这个抽象类，该类实现了ExecutorService，ExecutorService继承了Executor接口。
Exexcutor接口只有一个execute接口，线程池主要依赖于该接口提交线程。
public interface Executor {
void execute(Runnable command);
}
ExecutorService接口主要提供了submit接口：
void shutdown();
List<Runnable> shutdownNow();
boolean isShutdown();
boolean isTerminated();
boolean awaitTermination(long timeout, TimeUnit unit)
<T> Future<T> submit(Runnable task, T result);
Future<?> submit(Runnable task);
<T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks)
throws InterruptedException;
<T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks,
long timeout, TimeUnit unit)
<T> T invokeAny(Collection<? extends Callable<T>> tasks)
throws InterruptedException, ExecutionException;
<T> T invokeAny(Collection<? extends Callable<T>> tasks,
long timeout, TimeUnit unit)
AbstractExecutorService这个抽象类主要实现了submit方法和invokeAny方法。
protected <T> RunnableFuture<T> newTaskFor(Runnable runnable, T value) {
return new FutureTask<T>(runnable, value);
}
protected <T> RunnableFuture<T> newTaskFor(Callable<T> callable) {
return new FutureTask<T>(callable);
}
public Future<?> submit(Runnable task) {
if (task == null) throw new NullPointerException();
RunnableFuture<Void> ftask = newTaskFor(task, null);
execute(ftask);
return ftask;
}
public <T> Future<T> submit(Runnable task, T result) {
if (task == null) throw new NullPointerException();
RunnableFuture<T> ftask = newTaskFor(task, result);
execute(ftask);
return ftask;
}
public <T> Future<T> submit(Callable<T> task) {
if (task == null) throw new NullPointerException();
RunnableFuture<T> ftask = newTaskFor(task);
execute(ftask);
return ftask;
}
private <T> T doInvokeAny(Collection<? extends Callable<T>> tasks,
boolean timed, long nanos)
throws InterruptedException, ExecutionException, TimeoutException {
if (tasks == null)
throw new NullPointerException();
int ntasks = tasks.size();
if (ntasks == 0)
throw new IllegalArgumentException();
ArrayList<Future<T>> futures = new ArrayList<Future<T>>(ntasks);
ExecutorCompletionService<T> ecs =
new ExecutorCompletionService<T>(this);
try {
ExecutionException ee = null;
final long deadline = timed ? System.nanoTime() + nanos : 0L;
Iterator<? extends Callable<T>> it = tasks.iterator();
// Start one task for sure; the rest incrementally
futures.add(ecs.submit(it.next()));
--ntasks;
int active = 1;
for (;;) {
Future<T> f = ecs.poll();
if (f == null) {
if (ntasks > 0) {
--ntasks;
futures.add(ecs.submit(it.next()));
++active;
}
else if (active == 0)
break;
else if (timed) {
f = ecs.poll(nanos, TimeUnit.NANOSECONDS);
if (f == null)
throw new TimeoutException();
nanos = deadline - System.nanoTime();
}
else
f = ecs.take();
}
if (f != null) {
--active;
try {
return f.get();
} catch (ExecutionException eex) {
ee = eex;
} catch (RuntimeException rex) {
ee = new ExecutionException(rex);
}
}
}
if (ee == null)
ee = new ExecutionException();
throw ee;
} finally {
for (int i = 0, size = futures.size(); i < size; I++)
futures.get(i).cancel(true);
}
}
public <T> T invokeAny(Collection<? extends Callable<T>> tasks)
throws InterruptedException, ExecutionException {
try {
return doInvokeAny(tasks, false, 0);
} catch (TimeoutException cannotHappen) {
assert false;
return null;
}
}
public <T> T invokeAny(Collection<? extends Callable<T>> tasks,
long timeout, TimeUnit unit)
throws InterruptedException, ExecutionException, TimeoutException {
return doInvokeAny(tasks, true, unit.toNanos(timeout));
}
public <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks)
throws InterruptedException {
if (tasks == null)
throw new NullPointerException();
ArrayList<Future<T>> futures = new ArrayList<Future<T>>(tasks.size());
boolean done = false;
try {
for (Callable<T> t : tasks) {
RunnableFuture<T> f = newTaskFor(t);
futures.add(f);
execute(f);
}
for (int i = 0, size = futures.size(); i < size; i++) {
Future<T> f = futures.get(i);
if (!f.isDone()) {
try {
f.get();
} catch (CancellationException ignore) {
} catch (ExecutionException ignore) {
}
}
}
done = true;
return futures;
} finally {
if (!done)
for (int i = 0, size = futures.size(); i < size; I++)
futures.get(i).cancel(true);
}
}
public <T> List<Future<T>> invokeAll(Collection<? extends Callable<T>> tasks,
long timeout, TimeUnit unit)
throws InterruptedException {
if (tasks == null)
throw new NullPointerException();
long nanos = unit.toNanos(timeout);
ArrayList<Future<T>> futures = new ArrayList<Future<T>>(tasks.size());
boolean done = false;
try {
for (Callable<T> t : tasks)
futures.add(newTaskFor(t));
final long deadline = System.nanoTime() + nanos;
final int size = futures.size();
// Interleave time checks and calls to execute in case
// executor doesn't have any/much parallelism.
for (int i = 0; i < size; i++) {
execute((Runnable)futures.get(i));
nanos = deadline - System.nanoTime();
if (nanos <= 0L)
return futures;
}
for (int i = 0; i < size; i++) {
Future<T> f = futures.get(i);
if (!f.isDone()) {
if (nanos <= 0L)
return futures;
try {
f.get(nanos, TimeUnit.NANOSECONDS);
} catch (CancellationException ignore) {
} catch (ExecutionException ignore) {
} catch (TimeoutException toe) {
return futures;
}
nanos = deadline - System.nanoTime();
}
}
done = true;
return futures;
} finally {
if (!done)
for (int i = 0, size = futures.size(); i < size; I++)
futures.get(i).cancel(true);
}
}
ThreadPoolExecutor继承了AbstractExecutorService这个抽象类，AbstractExecutorService、Excutor提供了Pool基本的执行能力。
二、跨马
1、线程状态参数
private static final int COUNT_BITS = Integer.SIZE - 3;
private static final int CAPACITY = (1 << COUNT_BITS) - 1;
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;
通过打印：
线程池中线程的工作状态用int的高三位表示，从上面的二进制中可以知道，当线程为RUNNING态时，其值<0，其他状态均>0。
2、构造函数
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory,
RejectedExecutionHandler handler) {
if (corePoolSize < 0 ||
maximumPoolSize <= 0 ||
maximumPoolSize < corePoolSize ||
keepAliveTime < 0)
throw new IllegalArgumentException();
if (workQueue == null || threadFactory == null || handler == null)
throw new NullPointerException();
this.acc = System.getSecurityManager() == null ?
null :
AccessController.getContext();
this.corePoolSize = corePoolSize;//核心线程数
this.maximumPoolSize = maximumPoolSize;//最大线程数
this.workQueue = workQueue;//工作队列
this.keepAliveTime = unit.toNanos(keepAliveTime);//保活时间，unit时间单位
this.threadFactory = threadFactory;//线程工厂
this.handler = handler;//拒绝策略
}
1）默认参数
线程工厂：默认线程工厂如下。
DefaultThreadFactory() {
SecurityManager s = System.getSecurityManager();
group = (s != null) ? s.getThreadGroup() :
Thread.currentThread().getThreadGroup();
namePrefix = "pool-" +
poolNumber.getAndIncrement() +
"-thread-";
}
拒绝策略：拒绝策略一共有四种，默认策略为AbortPolicy()
private static final RejectedExecutionHandler defaultHandler =
new AbortPolicy();
其他几种策略源码如下（）：
//CallerRunsPolicy策略调用deamon线程执行请求任务run方法
public static class CallerRunsPolicy implements RejectedExecutionHandler {
public CallerRunsPolicy() { }
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
if (!e.isShutdown()) {
r.run();
}
}
}
//AbortPolicy策略直接拒绝请求抛出异常
public static class AbortPolicy implements RejectedExecutionHandler {
public AbortPolicy() { }
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
throw new RejectedExecutionException("Task " + r.toString() +
" rejected from " +
e.toString());
}
}
//DiscardPolicy策略拒绝请求，不抛出异常
public static class DiscardPolicy implements RejectedExecutionHandler {
public DiscardPolicy() { }
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
}
}
//DiscardOldestPolicy策略将队列头的任务释放，将任务放入队列中
public static class DiscardOldestPolicy implements RejectedExecutionHandler {
public DiscardOldestPolicy() { }
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
if (!e.isShutdown()) {
e.getQueue().poll();
e.execute(r);
}
}
}
}
3）默认线程池Excutors
//LinkedBlockingQueue阻塞队列是无限扩容的队列
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>());
}
public static ExecutorService newSingleThreadExecutor() {
return new FinalizableDelegatedExecutorService
(new ThreadPoolExecutor(1, 1,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>()));
}
//SynchronousQueue队列是互斥队列，newCachedThreadPool线程池每次请求新建线程，如果该线程<60s未处于空闲状态，则新来请求可以复用未销毁线程来执行任务
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue<Runnable>());
}
//newSingleThreadScheduledExecutor 线程池可以作为定时器使用
public static ScheduledExecutorService newSingleThreadScheduledExecutor() {
return new DelegatedScheduledExecutorService
(new ScheduledThreadPoolExecutor(1));
}
三、回首望京阙
ThreadPoolExecutor组合了ReentrantLock（重入锁）、Condition（状态量）、works（继承了AQS，实现了Runnable接口的线程集合，works继承关系入下图）:
private final ReentrantLock mainLock = new ReentrantLock();
private final HashSet<Worker> workers = new HashSet<Worker>();
private final Condition termination = mainLock.newCondition();
上面大量的篇幅对ThreadPoolExecutor的基础进行了铺垫，下面就ThreadPoolExecutor的具体实现进行刨析。
前面分析过ThreadPoolExecutor类实现了Executor接口，该接口中只有一个方法execute，这是ThreadPoolExecutor的入口。
public void execute(Runnable command) {
if (command == null)
throw new NullPointerException();
//获取线程池统计变量
---------------------------------------
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
private static int ctlOf(int rs, int wc) { return rs | wc; }
采用了32位的后29位作为统计works数
---------------------------------------
int c = ctl.get();
//如果works小于核心线程数
if (workerCountOf(c) < corePoolSize) {
//addWorker是实现将线程添加到works集合的入口，具体实现见下文
if (addWorker(command, true))
return;
c = ctl.get();
}
//上面works大于核心线程数或者添加works失败，该线程是Running态，则将该请求放入任务队列中
if (isRunning(c) && workQueue.offer(command)) {
int recheck = ctl.get();
//重新判断当前线程池状态，如果是非运行态，此时线程池退出，则移除请求并拒绝请求
if (! isRunning(recheck) && remove(command))
reject(command);
//当前工作线程数为0
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
//上述条件都不满足，则拒绝
else if (!addWorker(command, false))
reject(command);
}
addWorker的实现如下：
private boolean addWorker(Runnable firstTask, boolean core) {
retry:
for (;;) {
int c = ctl.get();
int rs = runStateOf(c);
// 如果线程池状态为非Running态，且它不满足（Shutdown态，提交任务为null，任务队列非空）就返回false；看execute的实现中，这种状态下会拒绝任务。
----------------------------------------------------
//上述条件都不满足，则拒绝
else if (!addWorker(command, false))//重试提交任务，失败则拒绝
reject(command);
----------------------------------------------------
if (rs >= SHUTDOWN &&
! (rs == SHUTDOWN &&
firstTask == null &&
! workQueue.isEmpty()))
return false;
//通过for自旋来提交任务
for (;;) {
int wc = workerCountOf(c);
if (wc >= CAPACITY ||
wc >= (core ? corePoolSize : maximumPoolSize))
return false;
//cas自增原子数，成功则进行addWorker下半部分，否则自旋
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
}
}
//addWorker下半部分
boolean workerStarted = false;
boolean workerAdded = false;
Worker w = null;
try {
//新建线程对象
w = new Worker(firstTask);//此处通过构造函数生成Worker对象w
--------------------------------------------
final Thread thread;
Runnable firstTask;
volatile long completedTasks;
Worker(Runnable firstTask) {
setState(-1); // inhibit interrupts until runWorker
this.firstTask = firstTask;
this.thread = getThreadFactory().newThread(this);
}
//Wroker实现了Runnable方法，该处run方法是Worker对象start后的执行方法入口
public void run() {
runWorker(this);
}
——————--——————————————————————
//该方法就是把Worker中的firstTask任务执行其run方法
final void runWorker(Worker w) {
Thread wt = Thread.currentThread();
Runnable task = w.firstTask;
w.firstTask = null;//前面《ThreadLocals因何而得藕》中，讲过线程池中线程复用，该处Worker线程执行完任务后没有销毁，而是将接收的firstTask=null，从而从任务队列中获取任务，见下面
w.unlock(); // allow interrupts
boolean completedAbruptly = true;
try {
//getTask方法中获取可执行的任务
————————————————————————————
private Runnable getTask() {
boolean timedOut = false;
for (;;) {
int c = ctl.get();
int rs = runStateOf(c);
//获取阻塞线程任务时，如果线程池状态变更，减少works数量，同ad dWorker中的原子增正相反
if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
decrementWorkerCount();
return null;
}
int wc = workerCountOf(c);
// Are workers subject to culling?
boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;
//超时且队列为null则尝试原子减
if ((wc > maximumPoolSize || (timed && timedOut))
&& (wc > 1 || workQueue.isEmpty())) {
if (compareAndDecrementWorkerCount(c))
return null;
continue;
}
try {
Runnable r = timed ?
//超时获取任务或非超时获取任务
workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
workQueue.take();
if (r != null)
return r;
timedOut = true;
} catch (InterruptedException retry) {
timedOut = false;
}
}
}
————————————————————————————
//先执行Thread的firstTask任务，如果firstTask任务为null，则从任务队列中获取任务执行，getTask见上面。此处跟上面的firstTask=null呼应，通过此处理解ThreadLocal的使用的注意事项尤其重要。
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 {
//这是其具体调用，参考上面的构造函数，task是请求的任务的Runnable实现
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);
}
}
————————————————————————————
--------------------------------------------
final Thread t = w.thread;//这里线程t是Worker的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());
//判断线程池状态，向works添加线程
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();
}
//添加成功，并启动任务线程
if (workerAdded) {
t.start();//下面看这个方法
workerStarted = true;
}
}
} finally {
if (! workerStarted)
addWorkerFailed(w);
}
return workerStarted;
}
start方法是执行线程的启动方法：
public synchronized void start() {
if (threadStatus != 0)
throw new IllegalThreadStateException();
boolean started = false;
try {
//通过本地start0方法将新建的Worker启动
start0();
started = true;
} finally {
try {
if (!started) {
group.threadStartFailed(this);
}
} catch (Throwable ignore) {
/* do nothing. If start0 threw a Throwable then
it will be passed up the call stack */
}
}
}
通过上面分析，可以知道，线程池启动的是其Worker线程资源，并执行Worker的run方法调用构造函数中传入的请求任务的Runnable接口的run方法来执行任务。
execute方法是无返回值的方法，ThreadPoolExecutor还有一种有返回值的提交任务的方法，叫submit方法，如下：
public <T> Future<T> submit(Callable<T> task) {
if (task == null) throw new NullPointerException();
//RunnableFuture 通过构造函数封装了Callable的任务，具体实现见下面
RunnableFuture<T> ftask = newTaskFor(task);
execute(ftask);
return ftask;
}
---------------------------------------------------
public interface Callable<V> {
V call() throws Exception;
}
————————————————————————
protected <T> RunnableFuture<T> newTaskFor(Callable<T> callable) {
return new FutureTask<T>(callable);
}
public FutureTask(Callable<V> callable) {
if (callable == null)
throw new NullPointerException();
this.callable = callable;
this.state = NEW; // ensure visibility of callable
}
public FutureTask(Runnable runnable, V result) {
this.callable = Executors.callable(runnable, result);
this.state = NEW; // ensure visibility of callable
}
——————————————————-——————
//该run方法是RunnableFuture的run方法，通过该run方法执行Callable任务的call方法，并将返回值通过该RunnableFuture返回
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);
}
}
---------------------------------------------------
四、后记：
百战将军尤在马，回首望，遍地狼烟秋风起，恍恍惚惚好河山。
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