多线程开发越来越常见，开发者常常使用多线程完成一些耗时操作，通过并发来提高系统的响应速度。尤其是在Android移动端开发，为了提升用户体验，常常将一些操作放在异步线程中完成。但是，如果一味滥用多线程，会造成系统资源浪费，而且常常会出现并发问题。因此线程的管理就是一个非常重要的事，线程池也就应运而生。
线程池使用意义：
1）降低系统资源的消耗，线程池中实现线程的复用技术减少无限量的线程创建，减少线程创建和销毁带来的资源浪费；
2）提高响应速度，当有异步任务需要执行时，若线程中有空闲线程存在那么可以快速响应，无需新创建线程；
3）提高线程的可管理性，线程本身是一种稀缺资源，无节制的创建线程除了会造成资源浪费，而且会降低系统稳定性，带来许多并发问题。线程池对线程进行统一的管理、分配。
线程池的好处已经显而易见，若是系统中频繁创建线程来执行任务可以采用线程池技术；反之，若频率相对较低也不需要强行使用线程池。总体而言，根据系统的设计来定方案。
线程池的使用：
1、创建线程池,解析其构造函数：
/**
* Creates a new {@code ThreadPoolExecutor} with the given initial
* parameters.
*
* @param corePoolSize the number of threads to keep in the pool, even
* if they are idle, unless {@code allowCoreThreadTimeOut} is set
* @param maximumPoolSize the maximum number of threads to allow in the
* pool
* @param keepAliveTime when the number of threads is greater than
* the core, this is the maximum time that excess idle threads
* will wait for new tasks before terminating.
* @param unit the time unit for the {@code keepAliveTime} argument
* @param workQueue the queue to use for holding tasks before they are
* executed. This queue will hold only the {@code Runnable}
* tasks submitted by the {@code execute} method.
* @param threadFactory the factory to use when the executor
* creates a new thread
* @param handler the handler to use when execution is blocked
* because the thread bounds and queue capacities are reached
* @throws IllegalArgumentException if one of the following holds:
* {@code corePoolSize < 0}
* {@code keepAliveTime < 0}
* {@code maximumPoolSize <= 0}
* {@code maximumPoolSize < corePoolSize}
* @throws NullPointerException if {@code workQueue}
* or {@code threadFactory} or {@code handler} is null
*/
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue 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;
}
1）corePoolSize（核心线程数）：可以理解为线程池的基本线程数量，正常情况下，如果线程池的线程数量小于核心线程数，当有任务提交到线程池执行时，会直接创建一个线程执行。当线程数量大于等于corePoolSize时便不再直接创建线程。
2）maximumPoolSize（最大线程数）：线程池可以容纳的最大线程数量，当线程池中的线程数量大于等于maximumPoolSize时便交给饱和策略，不可以再创建新的线程。
3）keepAliveTime（线程保留时间）：线程池的工作线程执行完任务后，可以保留空闲状态的时间，用于控制空闲线程的保存时间。当线程数量小于等于corePoolSize时，该时间设置之后无用。
4）unit（保留时间单位）：线程存活时间的单位。天、小时、分、秒等。
5）workQueue（任务队列）：用于保存等待执行任务的阻塞队列。可以选择以下集中队列：
ArrayBlockingQueue:基于数组实现的有界阻塞队列，遵循FIFO原则；
LinkedBlockingQueue:基于链表实现的有界阻塞队列，遵循FIFO原则。吞吐量高于ArrayBlockingQueue。Executors.newFixedThreadPool()使用该队列。
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue());
}
SynchronousQueue:不存储元素的阻塞队列，每当任务想要插入时，就会进入阻塞状态，只有等到另外一个线程调用移除操作才会被唤醒。吞吐量高于LinkedBlockingQueue，Executors.newCachedThreadPool()使用该队列。
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue());
}
PriorityBlockingQueue:具有优先级的无限阻塞队列。
6）threadFactory（线程工厂）：用于创建线程工厂类，通常情况下可以不指定，因为有另外一个构造方法指定类默认的线程工厂，Executors.defaultThreadFactory()。
static class DefaultThreadFactory implements ThreadFactory {
private static final AtomicInteger poolNumber = new AtomicInteger(1);
private final ThreadGroup group;
private final AtomicInteger threadNumber = new AtomicInteger(1);
private final String namePrefix;
DefaultThreadFactory() {
SecurityManager s = System.getSecurityManager();
group = (s != null) ? s.getThreadGroup() :
Thread.currentThread().getThreadGroup();
namePrefix = "pool-" +
poolNumber.getAndIncrement() +
"-thread-";
}
public Thread newThread(Runnable r) {
Thread t = new Thread(group, r,
namePrefix + threadNumber.getAndIncrement(),
0);
if (t.isDaemon())
t.setDaemon(false);
if (t.getPriority() != Thread.NORM_PRIORITY)
t.setPriority(Thread.NORM_PRIORITY);
return t;
}
}
7）handler（饱和处理策略）：当线程池的工作队列已满，而且线程数大于等于maximumPoolSize时，若再提交新的任务，则会将其交给饱和策略处理。java中提供了几种处理策略，默认策略为AbortPolicy。
AbortPolicy:直接抛出异常。
CallerRunsPolicy:只用调用者所在线程来运行任务。
DiscardOldestPolicy:丢弃队列中最近的一个任务，并执行当前任务。
DiscardPolicy:不处理，不丢弃。
2、向线程池提交任务：
execute()方法：
threadPoolExecutor.execute(new Runnable() {
@Override
public void run() {
System.out.println("run task by execute");
}
});
submit()方法：
Future future = threadPoolExecutor.submit(new Runnable() {
@Override
public void run() {
System.out.println("run task by submit");
}
});
上述2个方法均可以向线程池提交任务，其最大区别在于是否需要返回值。execute方法没有返回值，submit方法会返回一个Future对象，该对象可以获取任务执行的结果。
3、线程池关闭：
线程池关闭是通过遍历线程中所有的工作线程，然后逐个调用线程的interrupt方法中断线程，因此并不能保证所有线程都能停止，不响应中断的任务则无法终止。
1）shutdown():将线程池的状态设置成SHUTDOWN状态，然后中断所有没有执行任务的线程（中断空闲线程）
2）shutdownNow():将线程池的状态设置成STOP状态，尝试停止所有正在执行或者暂停任务的线程（所有线程），并返回等待执行任务的列表。
线程池原理分析：
流程图
源码解析：
/**
* Executes the given task sometime in the future. The task
* may execute in a new thread or in an existing pooled thread.
*
* If the task cannot be submitted for execution, either because this
* executor has been shutdown or because its capacity has been reached,
* the task is handled by the current {@code RejectedExecutionHandler}.
*
* @param command the task to execute
* @throws RejectedExecutionException at discretion of
* {@code RejectedExecutionHandler}, if the task
* cannot be accepted for execution
* @throws NullPointerException if {@code command} is null
*/
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();
//判断当前线程数量是否小于核心线程数量
if (workerCountOf(c) < corePoolSize) {
//若小于核心线程数量，创建线程执行
if (addWorker(command, true))
return;
c = ctl.get();
}
//将线程加入队列
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)){
//加入到队列失败，则将其交给饱和策略处理
reject(command);
}
}
/**
* 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 {
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;
}
Work类中最终执行任务的方法
/**
* 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 then we
* 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);
}
}
结束语
相信大家阅读此文之后，对于线程池技术有了一定的了解。与其他技术一样，大家只有在实践中才能真正体会到其妙处，当你感受到之后再回过头去理解它的设计原理便会更加清晰。如果有兴趣可以读一下《java并发编程的艺术》这本书，书中的讲解比文章会更加详细。