Python 官方文档:入门教程 => 点击学习
目录线程池的好处创建线程池的五种方式缓存线程池CachedThreadPool固定容量线程池FixedThreadPool单个线程池SingleThreadExecutor定时任务线
1:缓存线程池(不推荐)
2:固定容量线程池(不推荐)
3:单个线程池(不推荐)
4:定时任务线程池(不推荐)
5:通过ThreadPoolExecutor构造方法创建线程池(阿里巴巴开发手册十分推荐)
前面4种创建线程池的方式都是通过Executors的静态方法来创建。
ExecutorService executorService = Executors.newCachedThreadPool();
for (int i = 0; i < 10; i++) {
final int finalI = i;
executorService.execute(new Runnable() {
public void run() {
System.out.println(Thread.currentThread().getName()+"<thread->run>"+ finalI);
}
});
}
为什么不推荐使用缓存线程池?
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, 2147483647, 60L, TimeUnit.SECONDS, new SynchronousQueue());
}
public ThreadPoolExecutor(int corePoolSize, int maximumPoolSize, long keepAliveTime, TimeUnit unit, BlockingQueue<Runnable> workQueue) {
this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue, Executors.defaultThreadFactory(), defaultHandler);
}
通过上面两个代码片段,我们可以看出CachedThreadPool的maximumPoolSize为Integer的最大值2147483647,相当于可以无限的创建线程,而创建线程是需要内存的,这样就会造成内存溢出,而且一般的机器也没用那么大的内存给它创建这么大量的线程。
newFixedThreadPool(int num),num就是我们要指定的固定线程数量
ExecutorService executorService = Executors.newFixedThreadPool(5);
for (int i = 0; i < 10; i++) {
final int finalI = i;
executorService.execute(new Runnable() {
public void run() {
System.out.println(Thread.currentThread().getName()+"<thread->run>"+ finalI);
}
});
}
输出:
pool-1-thread-5<thread->run>4
pool-1-thread-4<thread->run>3
pool-1-thread-5<thread->run>5
pool-1-thread-3<thread->run>2
pool-1-thread-3<thread->run>8
pool-1-thread-3<thread->run>9
pool-1-thread-2<thread->run>1
pool-1-thread-1<thread->run>0
pool-1-thread-5<thread->run>7
pool-1-thread-4<thread->run>6
可以看出起到了线程的复用。
为什么FixedThreadPool是固定线程池?
源码分析
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue());
}
通过这个源码可以看出,核心线程数(corePoolSize)和最大线程数(maximumPoolSize)都为nThreads,因为只有这样,线程池才不会进行扩容,线程数才固定。
ExecutorService executorService = Executors.newSingleThreadExecutor();
for (int i = 0; i < 10; i++) {
final int finalI = i;
executorService.execute(new Runnable() {
public void run() {
System.out.println(Thread.currentThread().getName()+"<thread->run>"+ finalI);
}
});
}
为什么SingleThreadExecutor只含有一个线程?
源码分析
public static ExecutorService newSingleThreadExecutor() {
return new Executors.FinalizableDelegatedExecutorService(new ThreadPoolExecutor(1, 1, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue()));
}
通过这个源码可以看出,核心线程数(corePoolSize)和最大线程数(maximumPoolSize)都为1,所以它只含有一个线程。
int initDelay=10; //初始化延时
int period=1;//初始化延迟过了之后,每秒的延时
ScheduledExecutorService scheduledExecutorService = Executors.newScheduledThreadPool(10);
scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
@Override
public void run() {
System.out.println(Thread.currentThread().getName()+"<thread->run>");
}
},initDelay,period, TimeUnit.SECONDS);
这段代码的效果是:程序运行之后等10秒,然后输出第一次结果,之后每隔1秒输出一次结果。
为什么不推荐使用ScheduledThreadPool?
源码分析
public ScheduledThreadPoolExecutor(int corePoolSize) {
super(corePoolSize, 2147483647, 10L, TimeUnit.MILLISECONDS, new ScheduledThreadPoolExecutor.DelayedWorkQueue());
}
可以看出ScheduledThreadPool的最大线程数(maximumPoolSize)为Integer的最大值2147483647,相当于可以无限的创建线程,而创建线程是需要内存的,这样就会造成内存溢出,而且一般的机器也没用那么大的内存给它创建这么大量的线程。
ThreadPoolExecutor threadPoolExecutor = new ThreadPoolExecutor(10, 20,
2L, TimeUnit.SECONDS, new ArrayBlockingQueue<>(5),
Executors.defaultThreadFactory(), new ThreadPoolExecutor.AbortPolicy());
for (int i = 0; i < 12; i++) {
final int finalI = i;
threadPoolExecutor.execute(new Runnable() {
public void run() {
System.out.println(Thread.currentThread().getName()+"<thread->run>"+ finalI);
}
});
}
public ThreadPoolExecutor(int corePoolSize, int maximumPoolSize, long keepAliveTime, TimeUnit unit, BlockingQueue<Runnable> workQueue, ThreadFactory threadFactory, RejectedExecutionHandler handler) {
}
ArrayBlockingQueue:有界阻塞队列。队列有大小限制,当容量超过时则会触发扩容或者拒绝策略。
public ArrayBlockingQueue(int capacity) {
this(capacity, false);
}
LinkedBlockingQueue:无界阻塞队列,队列无大小限制,可能会造成内存溢出。
public LinkedBlockingQueue() {
this(2147483647);
}
AbortPolicy:直接抛异常
public static class AbortPolicy implements RejectedExecutionHandler {
public AbortPolicy() {
}
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
throw new RejectedExecutionException("Task " + r.toString() + " rejected from " + e.toString());
}
}
DiscardPolicy:不作任何操作。默默丢弃任务
public static class DiscardPolicy implements RejectedExecutionHandler {
public DiscardPolicy() {
}
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
}
}
DiscardOldestPolicy:丢掉存在时间最长的任务
public static class DiscardOldestPolicy implements RejectedExecutionHandler {
public DiscardOldestPolicy() {
}
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
if (!e.isshutdown()) {
e.getQueue().poll();
e.execute(r);
}
}
}
CallerRunsPolicy:让提交任务的线程去处理任务
public static class CallerRunsPolicy implements RejectedExecutionHandler {
public CallerRunsPolicy() {
}
public void rejectedExecution(Runnable r, ThreadPoolExecutor e) {
if (!e.isShutdown()) {
r.run();
}
}
}
threadFactory
ThreadFactory threadFactory = Executors.defaultThreadFactory();
threadFactory.newThread(new Runnable() {
@Override
public void run() {
System.out.println("threadFactory");
}
}).start();
ThreadPoolExecutor threadPoolExecutor = new ThreadPoolExecutor(10, 20,
2L, TimeUnit.SECONDS, new ArrayBlockingQueue<>(5),
Executors.defaultThreadFactory(), new ThreadPoolExecutor.AbortPolicy());
for (int i = 0; i < 26; i++) { //并发数26
final int finalI = i;
threadPoolExecutor.execute(new Runnable() {
public void run() {
System.out.println(Thread.currentThread().getName()+"<thread->run>"+ finalI);
}
});
}
对于这段代码,如果来了26个并发,10个并发会被核心线程处理,5个会在等待区,剩下11个会因为等待区满了而触发扩容,但是又因为因为这里最多能够扩容10个,这里却是11个,所以会触发拒绝策略。
触发扩容:并发数>核心线程数(corePoolSize)+阻塞队列(workQueue)的大小
下期文章链接https://www.jb51.net/article/241589.htm
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