线程池:3大方法、7大参数、4种拒绝策略
Java中的池大概有:线程池,连接池,内存池,对象池等。
创建、销毁这种动作十分浪费资源,因此可以事先准备好一部分资源,谁要用就来直接取,取完了还回来,这就是池化技术。
线程池的优点:
降低资源的消耗
提高响应的速度
方便管理。
//单个线程
ExecutorService service = Executors.newSingleThreadExecutor();
//固定大小线程池
ExecutorService service = Executors.newFixedThreadPool(5);
//可伸缩
ExecutorService service = Executors.newCachedThreadPool();
先来看看三大方法的源码
public static ExecutorService newSingleThreadExecutor() {
return new FinalizableDelegatedExecutorService
(new ThreadPoolExecutor(1, 1,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>()));
}
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(nThreads, nThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>());
}
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue<Runnable>());
}
可以看到他们最终都是采用ThreadPoolExecutor
创建的线程池
public ThreadPoolExecutor(int corePoolSize, // 核心线程池大小
int maximumPoolSize, // 最大核心线程池大小
long keepAliveTime, // 超时了没有人调用就会释放
TimeUnit unit, // 超时单位
BlockingQueue<Runnable> workQueue, // 阻塞队列
ThreadFactory threadFactory, // 线程工厂:创建线程的,一般 不用动
RejectedExecutionHandler handle // 拒绝策略
) {
if (corePoolSize < 0 ||
maximumPoolSize <= 0 ||
maximumPoolSize < corePoolSize ||
keepAliveTime < 0)
throw new IllegalArgumentException();
if (workQueue == null || threadFactory == null || handler == null)
throw new NullPointerException();
this.acc = System.getSecurityManager() == null ?
null :
AccessController.getContext();
this.corePoolSize = corePoolSize;
this.maximumPoolSize = maximumPoolSize;
this.workQueue = workQueue;
this.keepAliveTime = unit.toNanos(keepAliveTime);
this.threadFactory = threadFactory;
this.handler = handler;
}
在阿里Java开发手册中这样写道
new ThreadPoolExecutor.AbortPolicy() // 银行满了,还有人进来,不处理这个人的,抛出异 常
new ThreadPoolExecutor.CallerRunsPolicy() // 哪来的去哪里!
new ThreadPoolExecutor.DiscardPolicy() //队列满了,丢掉任务,不会抛出异常!
new ThreadPoolExecutor.DiscardOldestPolicy() //队列满了,尝试去和最早的竞争,也不会 抛出异常!
package com.shimeath.demo11;
import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.Executors;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;
/**
* @author Shimeath
*/
public class TestThreadPoolExecutors {
public static void main(String[] args) {
ThreadPoolExecutor poolExecutor = new ThreadPoolExecutor(
2,
5,
0,
TimeUnit.SECONDS,
new ArrayBlockingQueue<>(3),
Executors.defaultThreadFactory(),
new ThreadPoolExecutor.CallerRunsPolicy()
);
try {
for (int i = 0; i < 9; i++) {
poolExecutor.execute(()->{
System.out.println(Thread.currentThread().getName() + " ok");
});
}
} catch (Exception e) {
e.printStackTrace();
} finally {
poolExecutor.shutdown();
}
}
}
池的最大的大小如何去设置!
了解:IO密集型,CPU密集型:(调优)
// 最大线程(maximumPoolSize)到底该如何定义
// 1、CPU 密集型,几核,就是几,可以保持CPu的效率最高!
// 2、IO 密集型 > 判断你程序中十分耗IO的线程,
// 程序 15个大型任务 io十分占用资源! 可以采用30个
// 获取CPU的核数
System.out.println(Runtime.getRuntime().availableProcessors());
原文:https://www.cnblogs.com/shimeath/p/13357915.html