写在前面:当使用线程的时候就创建一个线程,这样实现起来非常简单,但是当并发的线程数量很多时,每个线程只执行一个时间很短的任务就结束了,而频繁的创建和销毁线程需要时间,会大大降低系统的效率。同时,线程的管理变得极为困难。因此在JAVA1.5中引入了Executor框架,将任务的提交和执行进行解耦。当需要线程时,只需要定义好任务,然后提交给线程池,而不用关心该任务是如何执行、被哪个线程执行以及什么时间执行。线程池对线程统一分配、调优和监控,能够降低资源消耗、提高响应速度,提高线程的可管理性。
1.Executor的类关系
Java中线程池的顶级接口是Executor,严格意义上讲,Executor只是一个执行线程的工具,真正的线程池接口是ExecutorService。线程池的类关系如下图所示:
由图中可以看到
(1)Executor的execute方法只是调用一个Runnable的任务,任务在线程中执行,相当于调用Runnable的run方法。
(2)ExecutorService在Executor基础上增加了一些方法,图中为两个核心的方法。两个方法的区别在于Runnable在执行完毕后没有返回结果,而Callable执行完毕后有一个结果。相同点在于都返回一个Future对象。Future对象可以阻塞线程直到运行完毕,也可以取消任务执行。
(3)ScheduledExecutorService主要解决需要任务重复执行的问题。包括延迟时间一次性执行、延迟的时间周期性执行以及固定延迟时间周期性执行等。
(4)ThreadPoolExecutor是ExecutorService的默认实现。
(5)ScheduleThreadPoolExecutor是继承ThreadPoolExecutor的ScheduleExecutorService接口实现,周期性任务调度的类实现。
(6)CompiletionService接口用于描述顺序获取执行结果的一个线程池包装器。它依赖一个具体的线程池调度,但是能够根据任务的执行先后顺序得到执行结果,在某些情况下可能提高并发效率。
2.线程池参数
ThreadPoolExecutor是线程池中最核心的一个类,它主要提供四个构造方法:
public class ThreadPoolExecutor extends AbstractExecutorService {
.....
public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
BlockingQueue<Runnable> workQueue);
public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
BlockingQueue<Runnable> workQueue,ThreadFactory threadFactory);
public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
BlockingQueue<Runnable> workQueue,RejectedExecutionHandler handler);
public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,
BlockingQueue<Runnable> workQueue,ThreadFactory threadFactory,RejectedExecutionHandler handler);
...
}
前三个构造器实际调用的是第四个构造器进行的初始化工作,第四个构造器中有7个参数:
(1)corePoolSize:线程池中的核心线程数,当提交一个任务时,线程池创建一个新线程执行任务,直到当前线程数等于corePoolSize。如果当前线程数为corePoolSzie,继续提交的任务被保存到阻塞队列中,等待被执行;如果执行了线程池的prestartAllCoreThreads()方法,线程池会提前创建并启动所有核心线程。
(2)maximumPoolSize:线程池中允许的最大线程数,如果当前阻塞队列满了,且继续提交任务,则创建新的线程执行任务,前提是当前线程数小于maximumPoolSize。
(3)keepAliveTime:线程空闲时的存活时间,即当线程没有任务执行时,继续存活的时间;默认情况下,该参数只在线程数大于corePoolSize时才有用。
(4)unit:keepAliveTime的单位,有7种取值,分别为天、小时、分钟、秒、毫秒、微秒、纳秒。
(5)workQueue:用来保存等待被执行的任务的阻塞队列,且任务必须实现Runable接口,在JDK中提供了如下阻塞队列:
ArrayBlockingQueue:基于数组结构的有界阻塞队列,按FIFO排序任务;
LinkedBlockingQuene:基于链表结构的阻塞队列,按FIFO排序任务,吞吐量通常要高于ArrayBlockingQuene;
SynchronousQuene:一个不存储元素的阻塞队列,每个插入操作必须等到另一个线程调用移除操作,否则插入操作一直处于阻塞状态,吞吐量通常要高于LinkedBlockingQuene;
PriorityBlockingQuene:具有优先级的无界阻塞队列。
一般使用LinkedBlockingQueue和SynchronousQueue。
(6)threadFactory:创建线程的工厂,通过自定义的线程工厂可以给每个新建的线程设置一个具有识别度的线程名。
(7)handler:线程池的饱和策略,当阻塞队列满了,且没有空闲的工作线程,如果继续提交任务,必须采取一种策略处理该任务,线程池提供了4种策略:
AbortPolicy:直接抛出异常,默认策略;
CallerRunsPolicy:用调用者所在的线程来执行任务;
DiscardOldestPolicy:丢弃阻塞队列中靠最前的任务,并执行当前任务;
DiscardPolicy:直接丢弃任务;
当然也可以根据应用场景实现RejectedExecutionHandler接口,自定义饱和策略,如记录日志或持久化存储不能处理的任务。
3.线程池的初始化
Executors类里提供了一些静态工厂,生成一些常用的线程池:
3.1 new FixedThreadPool
创建固定大小的线程池。每次提交一个任务就创建一个线程,直到线程达到线程池的最大大小。线程池的大小一旦达到最大值就会保持不变,如果某个线程因为执行异常而结束,那么线程池会补充一个新线程。
示例:
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>());
}
初始化一个指定线程数的线程池,其中corePoolSize == maximumPoolSize,使用LinkedBlockingQuene作为阻塞队列,不过当线程池没有可执行任务时,也不会释放线程。
3.2 new CachedThreadPool
创建一个可缓存的线程池。如果线程池的大小超过了处理任务所需要的线程,那么就会回收部分空闲(60秒不执行任务)的线程,当任务数增加时,此线程池又可以智能的添加新线程来处理任务。此线程池不会对线程池大小做限制,线程池大小完全依赖于操作系统(或者说JVM)能够创建的最大线程大小。
示例:
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue<Runnable>());
}
初始化一个可以缓存线程的线程池,默认缓存60s,线程池的线程数可达到Integer.MAX_VALUE,即2147483647,内部使用SynchronousQueue作为阻塞队列。和newFixedThreadPool创建的线程池不同,newCachedThreadPool在没有任务执行时,当线程的空闲时间超过keepAliveTime,会自动释放线程资源,当提交新任务时,如果没有空闲线程,则创建新线程执行任务,会导致一定的系统开销。
3.3 new SingleThreadExecutor
创建一个单线程的线程池。这个线程池只有一个线程在工作,也就是相当于单线程串行执行所有任务。如果这个唯一的线程因为异常结束,那么会有一个新的线程来替代它。此线程池保证所有任务的执行顺序按照任务的提交顺序执行。
示例:
public static ExecutorService newSingleThreadExecutor(ThreadFactory threadFactory) {
return new FinalizableDelegatedExecutorService
(new ThreadPoolExecutor(1, 1,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>(),
threadFactory));
}
初始化的线程池中只有一个线程,如果该线程异常结束,会重新创建一个新的线程继续执行任务,唯一的线程可以保证所提交任务的顺序执行,内部使用LinkedBlockingQueue作为阻塞队列。
3.4 new ScheduledThreadPool
创建一个大小无限的线程池。此线程池支持定时以及周期性执行任务的需求。
示例:
public static ScheduledExecutorService newScheduledThreadPool(int corePoolSize) {
return new ScheduledThreadPoolExecutor(corePoolSize);
}
初始化的线程池可以在指定的时间内周期性的执行所提交的任务,在实际的业务场景中可以使用该线程池定期的同步数据。
4.内部原理
4.1线程池的状态
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; }
其中AtomicInteger变量ctl的低29位表示线程池中线程数,高3位表示线程池的运行状态。
RUNNING:-1 << COUNT_BITS,即高三位为111,该状态的线程池会接收新任务,并处理阻塞队列中的任务;
SHUTDOWN:0 << COUNT_BITS,即高三位为000,该状态的线程池不会接收新任务,但会处理阻塞队列中的任务;
STOP:1 << COUNT_BITS,即高3位为001,该状态的线程不会接收新任务,也不会处理阻塞队列中的任务,而且会中断正在运行的任务;
TINYING:2 << COUNT_BITS,即高3为010,表示所有任务已经终止,workerCount是0,线程过度到tinying状态需要执行terminated()方法;
TERMINATED:3 << COUNT_BITS,即高3位为011,表示terminated()方法完成后的状态。
4.2任务提交
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 <tt>Executor</tt> 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);
}
通过Executor.execute()方法提交的任务,必须实现Runnable接口,该方式提交的任务不能获取返回值,因此无法判断任务是否执行成功。
/**
* Submits a value-returning task for execution and returns a
* Future representing the pending results of the task. The
* Future's <tt>get</tt> method will return the task's result upon
* successful completion.
*
* <p>
* If you would like to immediately block waiting
* for a task, you can use constructions of the form
* <tt>result = exec.submit(aCallable).get();</tt>
*
* <p> Note: The {@link Executors} class includes a set of methods
* that can convert some other common closure-like objects,
* for example, {@link java.security.PrivilegedAction} to
* {@link Callable} form so they can be submitted.
*
* @param task the task to submit
* @return a Future representing pending completion of the task
* @throws RejectedExecutionException if the task cannot be
* scheduled for execution
* @throws NullPointerException if the task is null
*/
<T> Future<T> submit(Callable<T> task);
通过ExecutorService.submit()方法提交的任务,可以获取任务执行完的返回值。
4.3任务执行
execute实现:
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)) {
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);
}
具体的执行流程如下:
(1)workerCountOf方法根据ctl的低29位,得到线程池的当前线程数,如果线程数小于corePoolSize,则执行addWorker方法创建新的线程执行任务;否则执行步骤(2);
(2)如果线程池处于RUNNING状态,且把提交的任务成功放入阻塞队列中,则执行步骤(3),否则执行步骤(4);
(3)再次检查线程池的状态,如果线程池没有RUNNING,且成功从阻塞队列中删除任务,则执行reject方法处理任务;
(4)执行addWorker方法创建新的线程执行任务,如果addWoker执行失败,则执行reject方法处理任务;
addWorker实现:
/**
* Checks if a new worker can be added with respect to current
* pool state and the given bound (either core or maximum). If so,
* the worker count is adjusted accordingly, and, if possible, a
* new worker is created and started, running firstTask as its
* first task. This method returns false if the pool is stopped or
* eligible to shut down. It also returns false if the thread
* factory fails to create a thread when asked. If the thread
* creation fails, either due to the thread factory returning
* null, or due to an exception (typically OutOfMemoryError in
* Thread#start), we roll back cleanly.
*
* @param firstTask the task the new thread should run first (or
* null if none). Workers are created with an initial first task
* (in method execute()) to bypass queuing when there are fewer
* than corePoolSize threads (in which case we always start one),
* or when the queue is full (in which case we must bypass queue).
* Initially idle threads are usually created via
* prestartCoreThread or to replace other dying workers.
*
* @param core if true use corePoolSize as bound, else
* maximumPoolSize. (A boolean indicator is used here rather than a
* value to ensure reads of fresh values after checking other pool
* state).
* @return true if successful
*/
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 {
final ReentrantLock mainLock = this.mainLock;
w = new Worker(firstTask);
final Thread t = w.thread;
if (t != null) {
mainLock.lock();
try {
// Recheck while holding lock.
// Back out on ThreadFactory failure or if
// shut down before lock acquired.
int c = ctl.get();
int rs = runStateOf(c);
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;
}
addWoker方法实现的前半部分:
(1)判断线程池的状态,如果线程池的状态值大于或等SHUTDOWN,则不处理提交的任务,直接返回;
(2)通过参数core判断当前需要创建的线程是否为核心线程,如果core为true,且当前线程数小于corePoolSize,则跳出循环,开始创建新的线程
后半部分为具体实现,线程池的工作线程通过Woker类实现,在ReentrantLock锁的保证下,把Woker实例插入到HashSet后,并启动Woker中的线程,其中Worker类设计如下:
(1)继承了AQS类,可以方便的实现工作线程的中止操作;
(2)实现了Runnable接口,可以将自身作为一个任务在工作线程中执行;
(3)当前提交的任务firstTask作为参数传入Worker的构造方法;
Worker构造方法:
/**
* Creates with given first task and thread from ThreadFactory.
* @param firstTask the first task (null if none)
*/
Worker(Runnable firstTask) {
setState(-1); // inhibit interrupts until runWorker
this.firstTask = firstTask;
this.thread = getThreadFactory().newThread(this);
}
/** Delegates main run loop to outer runWorker */
public void run() {
runWorker(this);
}
从Woker类的构造方法实现可以发现:线程工厂在创建线程thread时,将Woker实例本身this作为参数传入,当执行start方法启动线程thread时,本质是执行了Worker的runWorker方法。
runWorker实现:
/**
* Main worker run loop. Repeatedly gets tasks from queue and
* executes them, while coping with a number of issues:
*
* 1. We may start out with an initial task, in which case we
* don't need to get the first one. Otherwise, as long as pool is
* running, we get tasks from getTask. If it returns null then the
* worker exits due to changed pool state or configuration
* parameters. Other exits result from exception throws in
* external code, in which case completedAbruptly holds, which
* usually leads processWorkerExit to replace this thread.
*
* 2. Before running any task, the lock is acquired to prevent
* other pool interrupts while the task is executing, and
* clearInterruptsForTaskRun called to ensure that unless pool is
* stopping, this thread does not have its interrupt set.
*
* 3. Each task run is preceded by a call to beforeExecute, which
* might throw an exception, in which case we cause thread to die
* (breaking loop with completedAbruptly true) without processing
* the task.
*
* 4. Assuming beforeExecute completes normally, we run the task,
* gathering any of its thrown exceptions to send to
* afterExecute. We separately handle RuntimeException, Error
* (both of which the specs guarantee that we trap) and arbitrary
* Throwables. Because we cannot rethrow Throwables within
* Runnable.run, we wrap them within Errors on the way out (to the
* thread's UncaughtExceptionHandler). Any thrown exception also
* conservatively causes thread to die.
*
* 5. After task.run completes, we call afterExecute, which may
* also throw an exception, which will also cause thread to
* die. According to JLS Sec 14.20, this exception is the one that
* will be in effect even if task.run throws.
*
* The net effect of the exception mechanics is that afterExecute
* and the thread's UncaughtExceptionHandler have as accurate
* information as we can provide about any problems encountered by
* user code.
*
* @param w the worker
*/
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);
}
}
runWorker方法是线程池的核心:
(1)线程启动之后,通过unlock方法释放锁,设置AQS的state为0,表示运行中断;
(2)获取第一个任务firstTask,执行任务的run方法,不过在执行任务之前,会进行加锁操作,任务执行完会释放锁;
(3)在执行任务的前后,可以根据业务场景自定义beforeExecute和afterExecute方法;
(4)firstTask执行完成之后,通过getTask方法从阻塞队列中获取等待的任务,如果队列中没有任务,getTask方法会被阻塞并挂起,不会占用cpu资源;
getTask()实现:
/**
* Performs blocking or timed wait for a task, depending on
* current configuration settings, or returns null if this worker
* must exit because of any of:
* 1. There are more than maximumPoolSize workers (due to
* a call to setMaximumPoolSize).
* 2. The pool is stopped.
* 3. The pool is shutdown and the queue is empty.
* 4. This worker timed out waiting for a task, and timed-out
* workers are subject to termination (that is,
* {@code allowCoreThreadTimeOut || workerCount > corePoolSize})
* both before and after the timed wait.
*
* @return task, or null if the worker must exit, in which case
* workerCount is decremented
*/
private Runnable getTask() {
boolean timedOut = false; // Did the last poll() time out?
retry:
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;
}
boolean timed; // Are workers subject to culling?
for (;;) {
int wc = workerCountOf(c);
timed = allowCoreThreadTimeOut || wc > corePoolSize;
if (wc <= maximumPoolSize && ! (timedOut && timed))
break;
if (compareAndDecrementWorkerCount(c))
return null;
c = ctl.get(); // Re-read ctl
if (runStateOf(c) != rs)
continue retry;
// else CAS failed due to workerCount change; retry inner loop
}
try {
Runnable r = timed ?
workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
workQueue.take();
if (r != null)
return r;
timedOut = true;
} catch (InterruptedException retry) {
timedOut = false;
}
}
}
整个getTask操作在自旋下完成:
(1)workQueue.take:如果阻塞队列为空,当前线程会被挂起等待;当队列中有任务加入时,线程被唤醒,take方法返回任务,并执行;
(2)workQueue.poll:如果在keepAliveTime时间内,阻塞队列还是没有任务,则返回null;
所以,线程池中实现的线程可以一直执行由用户提交的任务。