ThreadPoolExecutor提供了四个构造方法：

我们以最后一个构造方法（参数最多的那个），对其参数进行解释：

 public ThreadPoolExecutor(int corePoolSize, // 1

                              int maximumPoolSize,  // 2

                              long keepAliveTime,  // 3

                              TimeUnit unit,  // 4

                              BlockingQueue<Runnable> workQueue, // 5

                              ThreadFactory threadFactory,  // 6

                              RejectedExecutionHandler handler ) { //7

        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;

    }

序号	名称	类型	含义
1	corePoolSize	int	核心线程池大小
2	maximumPoolSize	int	最大线程池大小
3	keepAliveTime	long	线程最大空闲时间
4	unit	TimeUnit	时间单位
5	workQueue	BlockingQueue	线程等待队列
6	threadFactory	ThreadFactory	线程创建工厂
7	handler	RejectedExecutionHandler	拒绝策略

如果对这些参数作用有疑惑的请看 ThreadPoolExecutor概述。

知道了各个参数的作用后，我们开始构造符合我们期待的线程池。首先看JDK给我们预定义的几种线程池：

预定义线程池

FixedThreadPool

    public static ExecutorService newFixedThreadPool(int nThreads) {

        return new ThreadPoolExecutor(nThreads, nThreads,

                                      0L, TimeUnit.MILLISECONDS,

                                      new LinkedBlockingQueue<Runnable>());

    }

corePoolSize与maximumPoolSize相等，即其线程全为核心线程，是一个固定大小的线程池，是其优势；

keepAliveTime = 0 该参数默认对核心线程无效，而FixedThreadPool全部为核心线程；

workQueue 为LinkedBlockingQueue（无界阻塞队列），队列最大值为Integer.MAX_VALUE。如果任务提交速度持续大余任务处理速度，会造成队列大量阻塞。因为队列很大，很有可能在拒绝策略前，内存溢出。是其劣势；

FixedThreadPool的任务执行是无序的；

适用场景：可用于Web服务瞬时削峰，但需注意长时间持续高峰情况造成的队列阻塞。

CachedThreadPool

     public static ExecutorService newCachedThreadPool() {

        return new ThreadPoolExecutor(0, Integer.MAX_VALUE,

                                      60L, TimeUnit.SECONDS,

                                      new SynchronousQueue<Runnable>());

    }

corePoolSize = 0，maximumPoolSize = Integer.MAX_VALUE，即线程数量几乎无限制；

keepAliveTime = 60s，线程空闲60s后自动结束。

workQueue 为 SynchronousQueue 同步队列，这个队列类似于一个接力棒，入队出队必须同时传递，因为CachedThreadPool线程创建无限制，不会有队列等待，所以使用SynchronousQueue；

适用场景：快速处理大量耗时较短的任务，如Netty的NIO接受请求时，可使用CachedThreadPool。

SingleThreadExecutor

    public static ExecutorService newSingleThreadExecutor() {

        return new FinalizableDelegatedExecutorService

            (new ThreadPoolExecutor(1, 1,

                                    0L, TimeUnit.MILLISECONDS,

                                    new LinkedBlockingQueue<Runnable>()));

    }

咋一瞅，不就是newFixedThreadPool(1)吗？定眼一看，这里多了一层FinalizableDelegatedExecutorService包装，这一层有什么用呢，写个dome来解释一下：

    public static void main(String[] args) {

        ExecutorService fixedExecutorService = Executors.newFixedThreadPool(1);

        ThreadPoolExecutor threadPoolExecutor = (ThreadPoolExecutor) fixedExecutorService;

        System.out.println(threadPoolExecutor.getMaximumPoolSize());

        threadPoolExecutor.setCorePoolSize(8);

        ExecutorService singleExecutorService = Executors.newSingleThreadExecutor();

//      运行时异常 java.lang.ClassCastException

//      ThreadPoolExecutor threadPoolExecutor2 = (ThreadPoolExecutor) singleExecutorService;

    }

对比可以看出，FixedThreadPool可以向下转型为ThreadPoolExecutor，并对其线程池进行配置，而SingleThreadExecutor被包装后，无法成功向下转型。因此，SingleThreadExecutor被定以后，无法修改，做到了真正的Single。

ScheduledThreadPool

    public static ScheduledExecutorService newScheduledThreadPool(int corePoolSize) {

        return new ScheduledThreadPoolExecutor(corePoolSize);

    }

newScheduledThreadPool调用的是ScheduledThreadPoolExecutor的构造方法,而ScheduledThreadPoolExecutor继承了ThreadPoolExecutor，构造是还是调用了其父类的构造方法。

    public ScheduledThreadPoolExecutor(int corePoolSize) {

        super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS,

              new DelayedWorkQueue());

    }

对于ScheduledThreadPool本文不做描述，其特性请关注后续篇章。

自定义线程池

以下是自定义线程池，使用了有界队列，自定义ThreadFactory和拒绝策略的demo：

public class ThreadTest {

    public static void main(String[] args) throws InterruptedException, IOException {

        int corePoolSize = 2;

        int maximumPoolSize = 4;

        long keepAliveTime = 10;

        TimeUnit unit = TimeUnit.SECONDS;

        BlockingQueue<Runnable> workQueue = new ArrayBlockingQueue<>(2);

        ThreadFactory threadFactory = new NameTreadFactory();

        RejectedExecutionHandler handler = new MyIgnorePolicy();

        ThreadPoolExecutor executor = new ThreadPoolExecutor(

          corePoolSize,

          maximumPoolSize,

          keepAliveTime,

          unit,

          workQueue,

          threadFactory,

          handler);

        executor.prestartAllCoreThreads(); // 预启动所有核心线程

        for (int i = 1; i <= 10; i++) {

            MyTask task = new MyTask(String.valueOf(i));

            executor.execute(task);

        }

        System.in.read(); //阻塞主线程

    }

    static class NameTreadFactory implements ThreadFactory {

        private final AtomicInteger mThreadNum = new AtomicInteger(1);

        @Override

        public Thread newThread(Runnable r) {

            Thread t = new Thread(r, "my-thread-" + mThreadNum.getAndIncrement());

            System.out.println(t.getName() + " has been created");

            return t;

        }

    }

    public static class MyIgnorePolicy implements RejectedExecutionHandler {

        public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {

            doLog(r, e);

        }

        private void doLog(Runnable r, ThreadPoolExecutor e) {

            // 可做日志记录等

            System.err.println( r.toString() + " rejected");

//          System.out.println("completedTaskCount: " + e.getCompletedTaskCount());

        }

    }

    static class MyTask implements Runnable {

        private String name;

        public MyTask(String name) {

            this.name = name;

        }

        @Override

        public void run() {

            try {

                System.out.println(this.toString() + " is running!");

                Thread.sleep(3000); //让任务执行慢点

            } catch (InterruptedException e) {

                e.printStackTrace();

            }

        }

        public String getName() {

            return name;

        }

        @Override

        public String toString() {

            return "MyTask [name=" + name + "]";

        }

    }

}

输出结果如下：

其中线程线程1-4先占满了核心线程和最大线程数量，然后4、5线程进入等待队列，7-10线程被直接忽略拒绝执行，等1-4线程中有线程执行完后通知4、5线程继续执行。

巴特西

【Java多线程】线程池-ThreadPoolExecutor