ThreadPoolExecutor提供了四个构造方法:

1
2
3
4
5
6
7
8
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
Executors.defaultThreadFactory(), defaultHandler);
}
1
2
3
4
5
6
7
8
9
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
ThreadFactory threadFactory) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
threadFactory, defaultHandler);
}
1
2
3
4
5
6
7
8
9
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue,
RejectedExecutionHandler handler) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
Executors.defaultThreadFactory(), handler);
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
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;
}

参数说明:

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

线程池的构建

一、预定义线程池
  1. FixedThreadPool
1
2
3
4
5
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。

  1. CachedThreadPool
1
2
3
4
5
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。

  1. SingleThreadExecutor
1
2
3
4
5
6
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:

**

1
2
3
4
5
6
7
8
9
10
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。

  1. ScheduledThreadPool
1
2
3
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。

1
2
3
4
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。

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:

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
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 + "]";
}
}
}

结果:

image.png

  1. 由于线程预启动,首先创建了1,2号线程,然后task1,task2被执行;
  2. 但任务提交没有结束,此时任务task3,task6到达发现核心线程已经满了,进入等待队列;
  3. 等待队列满后创建任务线程3,4执行任务task3,task6,同时task4,task5进入队列;
  4. 此时创建线程数(4)等于最大线程数,且队列已满,所以7,8,9,10任务被拒绝;
  5. 任务执行完毕后回头来执行task4,task5,队列清空。

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。