前言:
线程池的使用在java开发中屡见不鲜,我们一般会这样使用
// 1.创建一个固定线程数的线程池
ExecutorService threadPool = Executors.newFixedThreadPool(5);
// 2.提交任务
threadPool.submit(new Runnable() {
@Override
public void run() {
// TODO
}
});
简简单单的两句就完成了线程池的使用和任务提交,简直太简单了有木有...
这只是一方面,看过阿里巴巴Java开发手册的同学应该都知道,手册中对线程池的使用有一个限制(以下摘录自此手册):
【强制】线程池不允许使用 Executors 去创建,而是通过 ThreadPoolExecutor 的方式,的处理方式让写的同学更加明确线程池的运行规则,规避资源耗尽的风险。说明:Executors 返回的线程池对象的弊端如下:1)FixedThreadPool 和 SingleThreadPool:允许的请求队列长度为 Integer.MAX_VALUE,可能会堆积大量的请求,从而导致 OOM。2)CachedThreadPool 和 ScheduledThreadPool:允许的创建线程数量为 Integer.MAX_VALUE,可能会创建大量的线程,从而导致 OOM
这又是为什么呢?
带着这个疑问,我们来看一下Executors的相关代码
1.Executors.newFixedThreadPool()
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>());
}
可以看到,其直接返回了ThreadPoolExecutor的实现
2.ThreadPoolExecutor结构分析
1)线程池状态分析
/** 成员变量 */
// 线程池的运行状态ctl
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;// 最大容量为2^29 - 1
/** 以下几种是线程池的几种状态,用int值来表示 */
// 接收新任务,执行队列中任务
private static final int RUNNING = -1 << COUNT_BITS;
// 停止接收新任务,继续执行队列中任务
private static final int SHUTDOWN = 0 << COUNT_BITS;
// 停止接收新任务,不再执行队列中任务,并且中断正在执行的任务
private static final int STOP = 1 << COUNT_BITS;
// 所有任务中止,workCount=0,调用函数terminated()
private static final int TIDYING = 2 << COUNT_BITS;
// terminated()函数已经执行
private static final int TERMINATED = 3 << COUNT_BITS;
// Packing and unpacking ctl
// 使用c的高3位来表示状态,c & ~CAPACITY运算之后可以与上述RUNNING等线程池状态比较
private static int runStateOf(int c) { return c & ~CAPACITY; }
// 使用c的低29位来表示worker的数量
private static int workerCountOf(int c) { return c & CAPACITY; }
private static int ctlOf(int rs, int wc) { return rs | wc; }
笔者不是太懂这个位运算的偏移过程,干脆就把这些值都打印出来,看一下结果如何,从结果反推(以下是状态值的二进制形式)
private static final int RUNNING = -1 << COUNT_BITS;//11100000000000000000000000000000
private static final int SHUTDOWN = 0 << COUNT_BITS;//00000000000000000000000000000000
private static final int STOP = 1 << COUNT_BITS;//00100000000000000000000000000000
private static final int TIDYING = 2 << COUNT_BITS;//01000000000000000000000000000000
private static final int TERMINATED = 3 << COUNT_BITS;//01100000000000000000000000000000
从二进制数可以看出来,线程池的状态确实是用int的高三位来表示其值
// 常规获取线程池状态的方法如下所示:
int c = ctl.get();
int stateOf = runStateOf(c);
private static int runStateOf(int c) { return c & ~CAPACITY; }
System.out.println(Integer.toBinaryString(c)); //11100000000000000000000000000000
System.out.println(Integer.toBinaryString(~CAPACITY));//11100000000000000000000000000000
// 两者求与操作,低29位全部为0,由此可以获取到高3位的值,正是我们的状态
System.out.println(Integer.toBinaryString(stateOf)); //11100000000000000000000000000000
// 获取活跃的线程数
int c = ctl.get();
private static int workerCountOf(int c) { return c & CAPACITY; }
System.out.println(Integer.toBinaryString(c)); //11100000000000000000000000000000
System.out.println(Integer.toBinaryString(CAPACITY)); //00011111111111111111111111111111
// 两者求&操作,则高3位全部为0,只留下低29位
总结:通过上面的操作分析,可以验证我们之前的结论
线程池状态值是用int值的高3位表示的;活跃线程数workCount是用int值的低29位表示的
2)其他参数分析
private final BlockingQueue<Runnable> workQueue;
// 锁对象
private final ReentrantLock mainLock = new ReentrantLock();
// Worker集合,worker本身也是一个线程,这个集合代表着线程数量
private final HashSet<Worker> workers = new HashSet<Worker>();
// 条件对象
private final Condition termination = mainLock.newCondition();
// 线程工厂类
private volatile ThreadFactory threadFactory;
// 拒绝策略
private volatile RejectedExecutionHandler handler;
// 当线程数超过最大限制后,在规定的时间keepAliveTime,如果没有被使用,则
// 线程会被回收
private volatile long keepAliveTime;
// 核心线程数
private volatile int corePoolSize;
// 最大线程数
private volatile int maximumPoolSize;
// 默认拒绝策略
private static final RejectedExecutionHandler defaultHandler =
new AbortPolicy();
3)ThreadPoolExecutor.Worker分析
线程池中创建的线程对象就是Worker,下面简单看一下Worker的结构
private final class Worker
extends AbstractQueuedSynchronizer
implements Runnable
{
/** worker所对应的线程 */
final Thread thread;
/** 需要执行的任务 */
Runnable firstTask;
/** 已完成任务数量 */
volatile long completedTasks;
Worker(Runnable firstTask) {
setState(-1); // inhibit interrupts until runWorker
this.firstTask = firstTask;
this.thread = getThreadFactory().newThread(this);
}
public void run() {
runWorker(this);
}
protected boolean isHeldExclusively() {
return getState() != 0;
}
protected boolean tryAcquire(int unused) {
if (compareAndSetState(0, 1)) {
setExclusiveOwnerThread(Thread.currentThread());
return true;
}
return false;
}
protected boolean tryRelease(int unused) {
setExclusiveOwnerThread(null);
setState(0);
return true;
}
public void lock() { acquire(1); }
public boolean tryLock() { return tryAcquire(1); }
public void unlock() { release(1); }
public boolean isLocked() { return isHeldExclusively(); }
void interruptIfStarted() {
Thread t;
if (getState() >= 0 && (t = thread) != null && !t.isInterrupted()) {
try {
t.interrupt();
} catch (SecurityException ignore) {
}
}
}
}
Worker继承了AbstractQueuedSynchronizer类,所以相关的lock、unlock等方法直接使用了AQS的相关实现
3.ThreadPoolExecutor构造方法
// 1.使用默认拒绝策略
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
Executors.defaultThreadFactory(), defaultHandler);
}
// 2.使用指定拒绝策略
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
threadFactory, defaultHandler);
}
// 3.使用默认线程池工厂类
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
RejectedExecutionHandler handler) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
Executors.defaultThreadFactory(), handler);
}
// 基础构造函数
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.corePoolSize = corePoolSize;
this.maximumPoolSize = maximumPoolSize;
this.workQueue = workQueue;
this.keepAliveTime = unit.toNanos(keepAliveTime);
this.threadFactory = threadFactory;
this.handler = handler;
}
总结:我们一般会使用默认的线程工厂类Executors.defaultThreadFactory()和默认的拒绝策略AbortPolicy
4.ThreadPoolExecutor任务执行分析
在这里,我们先总结其任务执行的过程,先给出一个结论,然后按照结论来看源码,看是否是这么个结论
主要分为以下四种情况:
1)当线程池小于corePoolSize时,新提交任务将创建一个新线程执行任务,即使此时线程池中存在空闲线程。
2)当线程池达到corePoolSize时,新提交任务将被放入workQueue中,等待线程池中任务调度执行
3)当workQueue已满,且maximumPoolSize>corePoolSize时,新提交任务会创建新线程执行任务
4)当提交任务数超过maximumPoolSize时,新提交任务由RejectedExecutionHandler处理
以下两种情况是线程的关闭情况:
* 当线程池中超过corePoolSize线程,空闲时间达到keepAliveTime时,关闭空闲线程
* 当设置allowCoreThreadTimeOut(true)时,线程池中corePoolSize线程空闲时间达到keepAliveTime也将关闭
5.ThreadPoolExecutor.submit(Runnable task)方法结构分析
// AbstractExecutorService.submit()
public Future<?> submit(Runnable task) {
if (task == null) throw new NullPointerException();
// 1.创建任务
RunnableFuture<Void> ftask = newTaskFor(task, null);
execute(ftask);
return ftask;
}
// newTaskFor()
protected <T> RunnableFuture<T> newTaskFor(Runnable runnable, T value) {
return new FutureTask<T>(runnable, value);
}
// ThreadPoolExecutor.execute()
public void execute(Runnable command) {
// 任务不允许为空
if (command == null)
throw new NullPointerException();
int c = ctl.get();
// 1.当前线程数<核心线程数
if (workerCountOf(c) < corePoolSize) {
if (addWorker(command, true))
return;
c = ctl.get();
}
// 2.当前线程数>核心线程数 && workQueue不满的情况
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);
}
// 3.当前线程数>核心线程数 && workQueue已满的情况
// 判断是否超过最大线程数,没有超过则执行addWorker成功
else if (!addWorker(command, false))
// 4.以上条件均不满足,直接执行拒绝策略
reject(command);
}
按照上述四种情况,我们逐个来分析
1)当前线程数<核心线程数
// workerCountOf(c)计算当前线程数
if (workerCountOf(c) < corePoolSize) {
// 直接执行addWorker()
if (addWorker(command, true))
return;
c = ctl.get();
}
// ThreadPoolExecutor.addWorker()
private boolean addWorker(Runnable firstTask, boolean core) {
retry:
for (;;) {
// 1.获取线程池状态
int c = ctl.get();
int rs = runStateOf(c);
// 2.大于SHUTDOWN的情况就是STOP、TIDYING、TERMINATED,这些情况说明线程池不可用,直接返回
// 非的这个情况没太整明白TODO
if (rs >= SHUTDOWN &&
! (rs == SHUTDOWN &&
firstTask == null &&
! workQueue.isEmpty()))
return false;
// 内部循环
for (;;) {
// 3.获取已存在线程数
int wc = workerCountOf(c);
// 4.当前情况下core=true,所以比较的是核心线程数,
// 如果大于核心线程数,直接返回false
if (wc >= CAPACITY ||
wc >= (core ? corePoolSize : maximumPoolSize))
return false;
// 5.使用CAS增加worker数值,ctl自增1,
// 如果成功,则跳出外层循环,失败则继续内部循环
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 {
// 6.创建worker,firstTask作为参数
/**Worker(Runnable firstTask) {
setState(-1);
this.firstTask = firstTask;
this.thread = getThreadFactory().newThread(this);
}*/
// 可以看出,需要执行的任务就是firstTask,Thread就是线程工厂新创建出来的
// 以当前Worker为Runnable创建Thread
w = new Worker(firstTask);
final Thread t = w.thread;
if (t != null) {
// 7.加锁
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());
// 8.小于SHUTDOWN的状态只有RUNNING,
// 状态为SHUTDOWN,并且firstTask为空,则还可以添加任务
if (rs < SHUTDOWN ||
(rs == SHUTDOWN && firstTask == null)) {
// t是新线程,我们还没有调用启动方法,如果这个时候就alive了,说明线程状态异常,直接抛错
if (t.isAlive()) // precheck that t is startable
throw new IllegalThreadStateException();
// 9.所有状态都符合条件,则直接添加到works集合
workers.add(w);
int s = workers.size();
if (s > largestPoolSize)
largestPoolSize = s;
workerAdded = true;
}
} finally {
mainLock.unlock();
}
// 10.添加到works集合后,workerAdded=true,则直接启动线程,执行任务即可
if (workerAdded) {
// t.start()执行的是Worker.run()方法,后续单独分析
t.start();
workerStarted = true;
}
}
} finally {
if (! workerStarted)
// 11.添加失败则从workers集合中删除该Worker
// 刚才使用CAS修改的ctl值减一
addWorkerFailed(w);
}
return workerStarted;
}
// ThreadPoolExecutor.addWorkerFailed()
private void addWorkerFailed(Worker w) {
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
if (w != null)
workers.remove(w);
decrementWorkerCount();
tryTerminate();
} finally {
mainLock.unlock();
}
}
整个addWorker()方法总结起来就是:
创建Worker对象,启动其run()方法,ctl数量增1
2)当前线程数>核心线程数 && workQueue不满的情况
// ThreadPoolExecutor.execute()代码段
// workQueue.offer(command)如果返回true说明workQueue不满,
// 如果返回false说明workQueue已满,则执行3)
if (isRunning(c) && workQueue.offer(command)) {
int recheck = ctl.get();
// 如果线程池不是RUNNING状态,则删除command,并执行拒绝策略
if (! isRunning(recheck) && remove(command))
reject(command);
// 如果线程池线程数为0,则重新创建Worker
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
主要工作就是将command任务添加到workQueue,在workQueue非满的情况下,会添加成功;否则执行第三步骤
3)当前线程数>核心线程数 && workQueue已满的情况
// 3.当前线程数>核心线程数 && workQueue已满的情况
// 判断是否超过最大线程数,没有超过则执行addWorker成功
else if (!addWorker(command, false))
还是执行addWorker()方法,刚才在1)中我们已经分析过该方法,下面看一下当前情况与1)情况的最大不同。
最大不同就是addWorker()方法的第二个参数,在第一种情况下当前线程数<核心线程数的时候,传入的是true,当前情况下传入的是false,true和false有什么区别呢?
// ThreadPoolExecutor.addWorker()
private boolean addWorker(Runnable firstTask, boolean core) {
retry:
for (;;) {
...
for (;;) {
int wc = workerCountOf(c);
if (wc >= CAPACITY ||
// 就在这里,
// core=true时,比较的是核心线程数
// core=false时,比较的是最大线程数
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
}
}
所以,如果超过了核心线程数,还没有超过最大线程数的时候,还是可以继续执行下面的方法new Worker()...
4)当提交任务数超过maximumPoolSize时,新提交任务由RejectedExecutionHandler处理
// reject(command);
final void reject(Runnable command) {
handler.rejectedExecution(command, this);
}
拒绝策略ThreadPoolExecutor提供了四种,分别是:
// 1.中止策略
public static class AbortPolicy implements RejectedExecutionHandler {
public AbortPolicy() { }
// 直接抛出RejectedExecutionException异常
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
throw new RejectedExecutionException("Task " + r.toString() +
" rejected from " +
e.toString());
}
}
// 2.丢弃策略
public static class DiscardPolicy implements RejectedExecutionHandler {
public DiscardPolicy() { }
// 什么都不做,忽略该任务
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
}
}
// 3.丢弃最早的任务
public static class DiscardOldestPolicy implements RejectedExecutionHandler {
public DiscardOldestPolicy() { }
// 从队列中抛出一个任务,也就是最先进入该队列的任务,
// 然后执行当前新任务
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
if (!e.isShutdown()) {
e.getQueue().poll();
e.execute(r);
}
}
}
// 4.调用者执行
public static class CallerRunsPolicy implements RejectedExecutionHandler {
public CallerRunsPolicy() { }
// 如果线程池未停止,则直接执行该任务
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
if (!e.isShutdown()) {
r.run();
}
}
}
总结:步骤还是蛮长的,希望读者可以安安心心看完
按照这四个分类来执行任务,面试妥妥过。。哈哈
6.ThreadPoolExecutor.Worker.run()真正执行任务
上面只是从四个分类步骤说明了向线程池提交了新的Runnable任务,线程池的执行过程,但是任务什么时候执行的?是如何执行的?从当前说明
1)任务何时执行的?
在刚才分析5节 1)中,当前线程数<核心线程数时,addWorker()方法的分析时
w = new Worker(firstTask);
final Thread t = w.thread;
...
if (workerAdded) {
// Worker添加成功后,执行调用了start()方法,在这里被执行的
t.start();
workerStarted = true;
}
2)任务如何执行?
这个需要好好理一理
// w = new Worker(firstTask);
Worker(Runnable firstTask) {
setState(-1);
// 传过来的Runnable任务
this.firstTask = firstTask;
// 以当前Worker为Runnable,创建线程
this.thread = getThreadFactory().newThread(this);
}
// final Thread t = w.thread;
// t.start();
// 这个t就是以当前Worker为模板创建出来的Thread
所以,真正执行的是Worker.run()方法
// Worker.run()
public void run() {
runWorker(this);
}
// ThreadPoolExecutor.runWorker()
final void runWorker(Worker w) {
Thread wt = Thread.currentThread();
Runnable task = w.firstTask;
w.firstTask = null;
w.unlock(); // allow interrupts
boolean completedAbruptly = true;
try {
// 1.注意:这个是个while循环
// 如果Worker对应的firstTask不为空,或者getTask()方法不为空,则就一直执行
// getTask()下面单独分析
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
// 2.如果线程池已经停止,则需要保证线程是中断状态;否则,线程就不能设置为中断状态
if ((runStateAtLeast(ctl.get(), STOP) ||
(Thread.interrupted() &&
runStateAtLeast(ctl.get(), STOP))) &&
!wt.isInterrupted())
wt.interrupt();
try {
// 3.空实现,等待子类实现
beforeExecute(wt, task);
Throwable thrown = null;
try {
// 4.直接调用run()方法执行任务
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 {
// 5.空实现,等待子类实现
afterExecute(task, thrown);
}
} finally {
task = null;
w.completedTasks++;
w.unlock();
}
}
completedAbruptly = false;
} finally {
// Worker没有任务,线程退出
processWorkerExit(w, completedAbruptly);
}
}
Q:
Worker可以快速执行其成员变量firstTask中对应的任务,那么它又是如何执行workQueue中的任务的呢?
A:
刚才分析的Worker.run()方法中,任务执行是一个while循环,while条件是(task!=null || getTask() != null)
猜测执行workQueue中的任务应该就在这个getTask()方法中
3)getTask()获取workQueue任务
// ThreadPoolExecutor.getTask()
private Runnable getTask() {
boolean timedOut = false; // Did the last poll() time out?
for (;;) {
int c = ctl.get();
int rs = runStateOf(c);
// 1.如果线程池状态非RUNNING,或者线程池中workQueue已空,直接返回null
if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
decrementWorkerCount();
return null;
}
// 2.活跃线程数
int wc = workerCountOf(c);
// Are workers subject to culling?
boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;
// 3.活跃线程数>最大线程数 && workerCount大于1或者worker阻塞队列为空
if ((wc > maximumPoolSize || (timed && timedOut))
&& (wc > 1 || workQueue.isEmpty())) {
// 减少Worker数量,执行continue
if (compareAndDecrementWorkerCount(c))
return null;
continue;
}
try {
// 4.从workQueue中弹出一个任务执行
Runnable r = timed ?
workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
workQueue.take();
if (r != null)
return r;
timedOut = true;
} catch (InterruptedException retry) {
timedOut = false;
}
}
}
总结:所以Worker.run()方法不仅从当前对象中获取firstTask来执行,如果firstTask为空,还从workQueue中获取任务来执行
4)ThreadPoolExecutor.processWorkerExit(w, completedAbruptly);
当一直获取不到任务时,则执行Worker线程退出
// ThreadPoolExecutor.processWorkerExit(w, completedAbruptly)
private void processWorkerExit(Worker w, boolean completedAbruptly) {
// completedAbruptly=false
if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
decrementWorkerCount();
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
// 1.完成任务数+1
// 从workers删除当前Worker
completedTaskCount += w.completedTasks;
workers.remove(w);
} finally {
mainLock.unlock();
}
// 2.尝试中止
tryTerminate();
// 3.查看允许的最小线程数,如果当前线程数<最小线程数,则添加,否则,do nothing
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);
}
}
7.ThreadPoolExecutor.shutdown()停止线程池
public void shutdown() {
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
// 1.查看是否有操作线程许可
checkShutdownAccess();
// 2.设置线程池状态为
advanceRunState(SHUTDOWN);
// 3.执行空闲线程中断操作
interruptIdleWorkers();
onShutdown(); // hook for ScheduledThreadPoolExecutor
} finally {
mainLock.unlock();
}
// 尝试中止线程池
tryTerminate();
}
// ThreadPoolExecutor.tryTerminate()
final void tryTerminate() {
for (;;) {
int c = ctl.get();
// 1.如果线程池正在运行,则不能中止
// 还有另外两个条件都无法中止
if (isRunning(c) ||
runStateAtLeast(c, TIDYING) ||
(runStateOf(c) == SHUTDOWN && ! workQueue.isEmpty()))
return;
// 2.当线程数不为0时,中断一个空闲线程
if (workerCountOf(c) != 0) {
interruptIdleWorkers(ONLY_ONE);
return;
}
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
// 3.设置线程池状态为 TIDYING
if (ctl.compareAndSet(c, ctlOf(TIDYING, 0))) {
try {
terminated();
} finally {
ctl.set(ctlOf(TERMINATED, 0));
// 4.释放在termination条件上等待的所有线程
termination.signalAll();
}
return;
}
} finally {
mainLock.unlock();
}
// else retry on failed CAS
}
}
// ThreadPoolExecutor.interruptIdleWorkers()
private void interruptIdleWorkers(boolean onlyOne) {
final ReentrantLock mainLock = this.mainLock;
mainLock.lock();
try {
for (Worker w : workers) {
Thread t = w.thread;
if (!t.isInterrupted() && w.tryLock()) {
try {
t.interrupt();
} catch (SecurityException ignore) {
} finally {
w.unlock();
}
}
if (onlyOne)
break;
}
} finally {
mainLock.unlock();
}
}
8.写在最后
在开头的时候我们提出一个疑问,就是阿里巴巴java开发手册中对线程池使用的限制。
【强制】线程池不允许使用 Executors 去创建,而是通过 ThreadPoolExecutor 的方式,的处理方式让写的同学更加明确线程池的运行规则,规避资源耗尽的风险。说明:Executors 返回的线程池对象的弊端如下:1)FixedThreadPool 和 SingleThreadPool:允许的请求队列长度为 Integer.MAX_VALUE,可能会堆积大量的请求,从而导致 OOM。2)CachedThreadPool 和 ScheduledThreadPool:允许的创建线程数量为 Integer.MAX_VALUE,可能会创建大量的线程,从而导致 OOM
在分析完源码之后,看这句话应该感觉到,确实是这么回事。
尽量不要使用Executors创建的线程池,而是应该自定义阻塞队列,自定义核心线程数和最大线程数,防止资源耗尽