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## 线程池核心组件图解
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看源码之前,先了解一下该组件 最主要的几个 接口、抽象类和实现类的结构关系。
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![avatar](../../../images/JDK1.8/线程池组件类图.png)
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该组件中,Executor 和 ExecutorService 接口 定义了线程池最核心的几个方法,提交任务 submit
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()、关闭线程池 shutdown()。抽象类 AbstractExecutorService 主要对公共行为 submit()系列方法进行了实现,这些 submit()方法 的实现使用了 模板方法模式,其中调用的 execute()方法 是未实现的 来自 Executor 接口 的方法。实现类 ThreadPoolExecutor 则对线程池进行了具体而复杂的实现。
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另外还有一个常见的工具类 Executors,里面为开发者封装了一些可以直接拿来用的线程池。
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## 源码赏析
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话不多说,直接上源码。(这里只看最主要的代码部分)
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### Executor 和 ExecutorService 接口
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```java
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public interface Executor {
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/**
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* 在将来的某个时间执行给定的 Runnable。该 Runnable 可以在新线程、池线程或调用线程中执行。
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*/
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void execute(Runnable command);
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}
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public interface ExecutorService extends Executor {
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/**
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* 优雅关闭,该关闭会继续执行完以前提交的任务,但不再接受新任务。
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*/
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void shutdown();
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/**
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* 提交一个有返回值的任务,并返回该任务的 未来执行完成后的结果。
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* Future的 get()方法 将在成功完成后返回任务的结果。
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*/
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<T> Future<T> submit(Callable<T> task);
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<T> Future<T> submit(Runnable task, T result);
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Future<?> submit(Runnable task);
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}
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```
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### AbstractExecutorService 抽象类
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```java
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/**
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* 该抽象类最主要的内容就是,实现了 ExecutorService 中的 submit()系列方法
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*/
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public abstract class AbstractExecutorService implements ExecutorService {
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/**
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* 提交任务 进行执行,返回获取未来结果的 Future对象。
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* 这里使用了 “模板方法模式”,execute()方法来自 Executor接口,该抽象类中并未进行实现,
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* 而是交由子类具体实现。
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*/
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public Future<?> submit(Runnable task) {
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if (task == null) throw new NullPointerException();
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RunnableFuture<Void> ftask = newTaskFor(task, null);
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execute(ftask);
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return ftask;
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}
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public <T> Future<T> submit(Runnable task, T result) {
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if (task == null) throw new NullPointerException();
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RunnableFuture<T> ftask = newTaskFor(task, result);
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execute(ftask);
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return ftask;
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}
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public <T> Future<T> submit(Callable<T> task) {
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if (task == null) throw new NullPointerException();
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RunnableFuture<T> ftask = newTaskFor(task);
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execute(ftask);
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return ftask;
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}
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}
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```
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### ThreadPoolExecutor
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```java
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public class ThreadPoolExecutor extends AbstractExecutorService {
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/**
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* **************
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* ** 主要属性 **
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* **************
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*/
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/** 阻塞队列 */
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private final BlockingQueue<Runnable> workQueue;
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/** 用于创建线程的 线程工厂 */
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private volatile ThreadFactory threadFactory;
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/** 核心线程数 */
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private volatile int corePoolSize;
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/** 最大线程数 */
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private volatile int maximumPoolSize;
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/**
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* **************
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* ** 构造方法 **
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* **************
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*/
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/** 最后都使用了最后一个构造方法的实现 */
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public ThreadPoolExecutor(int corePoolSize,
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int maximumPoolSize,
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long keepAliveTime,
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TimeUnit unit,
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BlockingQueue<Runnable> workQueue) {
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this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
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Executors.defaultThreadFactory(), defaultHandler);
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}
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public ThreadPoolExecutor(int corePoolSize,
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int maximumPoolSize,
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long keepAliveTime,
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TimeUnit unit,
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BlockingQueue<Runnable> workQueue,
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ThreadFactory threadFactory) {
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this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
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threadFactory, defaultHandler);
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}
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public ThreadPoolExecutor(int corePoolSize,
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int maximumPoolSize,
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long keepAliveTime,
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TimeUnit unit,
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BlockingQueue<Runnable> workQueue,
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RejectedExecutionHandler handler) {
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this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
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Executors.defaultThreadFactory(), handler);
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}
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public ThreadPoolExecutor(int corePoolSize,
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int maximumPoolSize,
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long keepAliveTime,
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TimeUnit unit,
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BlockingQueue<Runnable> workQueue,
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ThreadFactory threadFactory,
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RejectedExecutionHandler handler) {
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if (corePoolSize < 0 ||
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maximumPoolSize <= 0 ||
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maximumPoolSize < corePoolSize ||
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keepAliveTime < 0)
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throw new IllegalArgumentException();
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if (workQueue == null || threadFactory == null || handler == null)
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throw new NullPointerException();
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this.corePoolSize = corePoolSize;
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this.maximumPoolSize = maximumPoolSize;
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this.workQueue = workQueue;
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this.keepAliveTime = unit.toNanos(keepAliveTime);
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this.threadFactory = threadFactory;
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this.handler = handler;
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}
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/**
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* **************
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* ** 主要实现 **
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* **************
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*/
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/** 执行 Runnable任务 */
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public void execute(Runnable command) {
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if (command == null)
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throw new NullPointerException();
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/*
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* 分三步进行:
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*
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* 1、如果运行的线程少于 corePoolSize,尝试开启一个新的线程;否则尝试进入工作队列
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*
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* 2. 如果工作队列没满,则进入工作队列;否则 判断是否超出最大线程数
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*
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* 3. 如果未超出最大线程数,则尝试开启一个新的线程;否则 按饱和策略处理无法执行的任务
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*/
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int c = ctl.get();
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if (workerCountOf(c) < corePoolSize) {
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if (addWorker(command, true))
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return;
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c = ctl.get();
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}
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if (isRunning(c) && workQueue.offer(command)) {
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int recheck = ctl.get();
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if (! isRunning(recheck) && remove(command))
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reject(command);
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else if (workerCountOf(recheck) == 0)
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addWorker(null, false);
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}
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else if (!addWorker(command, false))
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reject(command);
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}
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/**
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* 优雅关闭,在其中执行以前提交的任务,但不接受新任务。如果已关闭,则调用没有其他效果。
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*/
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public void shutdown() {
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final ReentrantLock mainLock = this.mainLock;
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mainLock.lock();
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try {
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checkShutdownAccess();
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advanceRunState(SHUTDOWN);
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interruptIdleWorkers();
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onShutdown(); // hook for ScheduledThreadPoolExecutor
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} finally {
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mainLock.unlock();
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}
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tryTerminate();
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}
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}
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```
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ThreadPoolExecutor 中的 execute()方法 执行 Runnable 任务 的流程逻辑可以用下图表示。
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![avatar](../../../images/ConcurrentProgramming/线程池流程.png)
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### 工具类 Executors
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看类名也知道,它最主要的作用就是提供 static 的工具方法,为开发者提供各种封装好的 具有各自特性的线程池。
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```java
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public class Executors {
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/**
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* 创建一个固定线程数量的线程池
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*/
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public static ExecutorService newFixedThreadPool(int nThreads) {
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return new ThreadPoolExecutor(nThreads, nThreads,
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0L, TimeUnit.MILLISECONDS,
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new LinkedBlockingQueue<Runnable>());
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}
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/**
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* 创建一个单线程的线程池
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*/
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public static ExecutorService newSingleThreadExecutor() {
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return new FinalizableDelegatedExecutorService
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(new ThreadPoolExecutor(1, 1,
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0L, TimeUnit.MILLISECONDS,
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new LinkedBlockingQueue<Runnable>()));
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}
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/**
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* 创建一个缓存的,可动态伸缩的线程池。
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* 可以看出来:核心线程数为0,最大线程数为Integer.MAX_VALUE,如果任务数在某一瞬间暴涨,
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* 这个线程池很可能会把 服务器撑爆。
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* 另外需要注意的是,它们底层都是使用了 ThreadPoolExecutor,只不过帮我们配好了参数
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*/
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public static ExecutorService newCachedThreadPool() {
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return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
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60L, TimeUnit.SECONDS,
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new SynchronousQueue<Runnable>());
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}
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}
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```
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