【Android】线程池

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在Android中,主线程不能执行耗时的操作,否则可能会导致ANR。那么,耗时操作应该在其它线程中执行。线程的创建和销毁都会有性能开销,创建过多的线程也会由于互相抢占系统资源而导致阻塞的现象。这个时候,就需要使用线程池。

线程池的优点可以概括为以下几点:

  • 1、重用线程池中的线程,避免线程创建、销毁带来的性能开销;

  • 2、能有效地控制线程池的最大并发数,避免大量的线程之间因互相抢占系统资源导致的阻塞现象;

  • 3、能够对线程进行简单的管理。

以上线程池的优点引用自《Android开发艺术探索》

线程池的具体实现类为ThreadPoolExecutor,ThreadPoolExecutor继承自AbstractExecutorService,AbstractExecutorService又实现了ExecutorService接口,ExecutorService继承自Executor。

ThreadPoolExecutor有四个重载的构造方法:

public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue) {
    this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
         Executors.defaultThreadFactory(), defaultHandler);
}

public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue,
                          ThreadFactory threadFactory) {
    this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
         threadFactory, defaultHandler);
}

public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue,
                          RejectedExecutionHandler handler) {
    this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
         Executors.defaultThreadFactory(), handler);
}

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;
}

最终都调用到了:

/**
 * 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:<br>
 *         {@code corePoolSize < 0}<br>
 *         {@code keepAliveTime < 0}<br>
 *         {@code maximumPoolSize <= 0}<br>
 *         {@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<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;
}

对应这个方法中的参数:

  • corePoolSize:核心线程数。如果没有设置allowCoreThreadTimeOut为true,则核心线程空闲时也不会销毁。如果设置allowCoreThreadTimeOut为true,则受keepAliveTime控制,空闲时间超过keepAliveTime,会被回收。

  • maximumPoolSize:最大线程数。

  • keepAliveTime:非核心线程的空闲超时时长。超过这个时间,非核心线程会被回收。核心线程如果allowCoreThreadTimeOut为true,则在空闲超过这个时间也会被回收。

  • unit:超时的单位。

  • workQueue:线程池中的任务队列。通过线程池的execute()方法提交的Runnable任务会被放入任务队列中。

  • threadFactory:线程工厂。

  • handler:饱和策略。当任务队列和线程池都满后,对新提交的任务的处理策略。

ThreadPoolExecutor执行任务的规则:

  • 1、如果线程池中的线程数量未达到核心线程数量,则开启一个新的核心线程来执行任务

  • 2、如果线程池中的线程数量已经大于等于核心线程数量,则会把新的任务放入任务队列中

  • 3、如果任务队列已满,并且线程池中的线程未满,则开启非核心线程来处理新的任务

  • 4、如果任务队列和线程池都已满,则会交给handler饱和策略来处理

图片发自简书App

下面通过一个简单的案例来验证以上规则:

static class WorkThread implements Runnable {

	private String name;

	public WorkThread(String name) {
		this.name = name;
	}

	public void run() {
		try {
			Thread.sleep(5000);
			System.out.println("Thread: " + name + " work finish");
		} catch (Exception e) {
			e.printStackTrace();
		}

	}
};

Executor executor = new ThreadPoolExecutor(5, 100, 60, TimeUnit.SECONDS, new LinkedBlockingQueue<>(5));
	for (int i = 0; i < 20; i++) {
		WorkThread thread = new WorkThread("" + i);
		executor.execute(thread);
	}

定义了一个线程池,核心线程池数量为5,线程数量为100,超时时间为60秒,任务队列为5。在子线程中,sleep 5秒来模拟耗时的操作。然后开启了20个线程,并放入线程池中执行。执行的结果如下:

Thread: 0 work finish
Thread: 1 work finish
Thread: 13 work finish
Thread: 10 work finish
Thread: 3 work finish
Thread: 11 work finish
Thread: 4 work finish
Thread: 2 work finish
Thread: 19 work finish
Thread: 18 work finish
Thread: 17 work finish
Thread: 15 work finish
Thread: 16 work finish
Thread: 14 work finish
Thread: 12 work finish
Thread: 5 work finish
Thread: 9 work finish
Thread: 8 work finish
Thread: 7 work finish
Thread: 6 work finish

前五个线程在核心线程中执行,第6-10个线程由于核心线程已满,因此在任务队列中等待执行,第11-20个线程,由于核心线程和队列都已满,而线程池中还可以开启线程,因此在非核心线程中执行。从结果来看,线程0-4,10-19会先执行完,然后任务队列中的线程5-9才执行,验证了以上的线程池任务执行规则。

为便于使用线程池,线程池还有几种简便的定义方法:

public static ExecutorService newFixedThreadPool(int nThreads) {
    return new ThreadPoolExecutor(nThreads, nThreads,
                                  0L, TimeUnit.MILLISECONDS,
                                  new LinkedBlockingQueue<Runnable>());
}

public static ExecutorService newCachedThreadPool() {
    return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
                                  60L, TimeUnit.SECONDS,
                                  new SynchronousQueue<Runnable>());
}

public static ExecutorService newSingleThreadExecutor() {
    return new FinalizableDelegatedExecutorService
        (new ThreadPoolExecutor(1, 1,
                                0L, TimeUnit.MILLISECONDS,
                                new LinkedBlockingQueue<Runnable>()));
}

public static ScheduledExecutorService newScheduledThreadPool(
        int corePoolSize, ThreadFactory threadFactory) {
    return new ScheduledThreadPoolExecutor(corePoolSize, threadFactory);
}

public ScheduledThreadPoolExecutor(int corePoolSize) {
    super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS,
          new DelayedWorkQueue());
}

通过Executors的static方法来创建。其中:

  • FixedThreadPool:线程数量固定的线程池。从方法的定义来看,这种线程池里的线程全都是核心线程,并且没有超时时间,任务队列也是没有限制的。

  • CachedThreadPool:这种线程池没有核心线程,全是非核心线程,并且超时时间为60秒,任务队列没有限制。这种线程适合执行大量的耗时较短的任务。

  • SingleThreadExecutor:只有一个核心线程,没有超时时间,任务队列没有限制。可以确保任务按顺序执行。

  • ScheduledThreadPool:核心线程数量固定。非核心线程没有限制。非核心线程闲置时会被立即回收。这类线程池适合执行定时任务和具有固定周期的重复任务。

posted @ 2019-04-19 13:38  milovetingting  阅读(177)  评论(0编辑  收藏  举报