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;
}
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：
一、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（*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
二、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。
总结，通过自定义线程池，我们可以更好的让线程池为我们所用，更加适应我的实际场景。
https://www.jianshu.com/p/f030aa5d7a28