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Java ExecutorService四种线程池及自定义ThreadPoolExecutor机制

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一、Java 线程池

Java通过Executors提供四种线程池,分别为:
1、newCachedThreadPool:创建一个可缓存线程池,如果线程池长度超过处理需要,可灵活回收空闲线程,若无可回收,则新建线程。(线程最大并发数不可控制);线程池为无限大,当执行第二个任务时若第一个任务已经完成,会复用执行第一个任务的线程,而不用每次新建线程。
2、newFixedThreadPool:创建一个定长线程池,可控制线程最大并发数,超出的线程会在队列中等待。
3、newScheduledThreadPool:创建一个定长线程池,支持定时及周期性任务执行、延迟执行。
4、newSingleThreadExecutor:创建一个单线程化的线程池,它只会用唯一的工作线程来执行任务,保证所有任务按照指定顺序(FIFO, LIFO, 优先级)执行。

线程池比较单线程的优势在于:

a. 重用存在的线程,减少对象创建、消亡的开销,性能佳。
b. 可有效控制最大并发线程数,提高系统资源的使用率,同时避免过多资源竞争,避免堵塞。
c. 提供定时执行、定期执行、单线程、并发数控制等功能。

二、ThreadPoolExecutor机制

1、newCachedThreadPool

 

public static ExecutorService newCachedThreadPool() {
        return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
                                      60L, TimeUnit.SECONDS,
                                      new SynchronousQueue<Runnable>());
    }

2、newFixedThreadPool

public static ExecutorService newFixedThreadPool(int nThreads) {
        return new ThreadPoolExecutor(nThreads, nThreads,
                                      0L, TimeUnit.MILLISECONDS,
                                      new LinkedBlockingQueue<Runnable>());
    }

3、newScheduledThreadPool

public static ScheduledExecutorService newScheduledThreadPool(int corePoolSize) {
        return new ScheduledThreadPoolExecutor(corePoolSize);
    }

public ScheduledThreadPoolExecutor(int corePoolSize) {
        super(corePoolSize, Integer.MAX_VALUE, 0, NANOSECONDS,
              new DelayedWorkQueue());
    }

public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> workQueue) {
        this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
             Executors.defaultThreadFactory(), defaultHandler);
    }

 

4、newSingleThreadExecutor

public static ExecutorService newSingleThreadExecutor() {
        return new FinalizableDelegatedExecutorService
            (new ThreadPoolExecutor(1, 1,
                                    0L, TimeUnit.MILLISECONDS,
                                    new LinkedBlockingQueue<Runnable>()));
    }

这几种线程池最终都是返回了ThreadPoolExecutor对象。

ThreadPoolExecutor的构造方法:

public ThreadPoolExecutor(int corePoolSize,//核心线程池大小
                              int maximumPoolSize,//最大线程池大小
                              long keepAliveTime,//线程池中超过corePoolSize数目的空闲线程最大存活时间;可以allowCoreThreadTimeOut(true)成为核心线程的有效时间
                              TimeUnit unit,//keepAliveTime的时间单位
                              BlockingQueue<Runnable> workQueue,//阻塞任务队列
                              ThreadFactory threadFactory,//线程工厂
                              RejectedExecutionHandler handler) {//当提交任务数超过maxmumPoolSize+workQueue之和时,任务会交给RejectedExecutionHandler来处理
        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;
    }

重点讲解: 
其中比较容易让人误解的是:corePoolSize,maximumPoolSize,workQueue之间关系:
1.当线程池小于corePoolSize时,新提交任务将创建一个新线程执行任务,即使此时线程池中存在空闲线程。 
2.当线程池达到corePoolSize时,新提交任务将被放入workQueue中,等待线程池中任务调度执行 
3.当workQueue已满,且maximumPoolSize>corePoolSize时,新提交任务会创建新线程执行任务 
4.当提交任务数超过maximumPoolSize时,新提交任务由RejectedExecutionHandler处理 
5.当线程池中超过corePoolSize线程,空闲时间达到keepAliveTime时,关闭空闲线程 
6.当设置allowCoreThreadTimeOut(true)时,线程池中corePoolSize线程空闲时间达到keepAliveTime也将关闭 

学会使用ThreadPoolExecutor的参数后,我们就可以不用局限于最上面那四种线程池,可以按照需要来构建自己的线程池;还有一点,通过ThreadFactory可以实现对线程的命名;

自定义线程工厂管理线程池:使用spring初始化实例类,使用同步锁将线程池封装到线程集合中;

/**
* @program: airplane-common
* @Date: 2019/1/7 15:54
* @Author: zhenliang.song
* @Description: 使用ThreadPoolExecutor自定义线程池
*/
public class ExecutorPoolFactoryWrap {

/**
* 线程池集合:key-自定义的枚举类型,value-线程池的接口类型,初始化集合长度为枚举类的values长度
*/
private ConcurrentHashMap<ThreadPoolEnum, ExecutorService> PoolFactoryMap = new ConcurrentHashMap<ThreadPoolEnum, ExecutorService>(ThreadPoolEnum.values().length);

/**
* 从集合中获取线程池对象:根据枚举类型映射map集合中的自定义线程对象
* @param poolEnum 枚举类
* @return
*/
public ExecutorService get(ThreadPoolEnum poolEnum) {
ExecutorService executorService = PoolFactoryMap.get(poolEnum);

if (executorService != null) {
return executorService;
}

synchronized (ExecutorPoolFactoryWrap.class) {
if (PoolFactoryMap.get(poolEnum) == null) {
int poolSize = poolEnum.getPoolSize() > 0 ? poolEnum.getPoolSize() : 1;
int capacity = poolEnum.getCapacity() > 0 ? poolEnum.getCapacity() : 256;
RejectedExecutionHandler rejectedHandler = poolEnum.getRejectedHandler() != null ? poolEnum.getRejectedHandler() : getRejectedExecutionHandler();
ThreadFactory threadFactory = new ThreadFactoryBuilder().setNameFormat(poolEnum.getPoolName() + "-%d").build();
PoolFactoryMap.put(poolEnum, new ThreadPoolExecutor(poolSize, poolSize,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>(capacity),
threadFactory,
rejectedHandler
));

}
}

return PoolFactoryMap.get(poolEnum);
}

/**
* 当提交任务数超过maxmumPoolSize+workQueue之和时,任务会交给RejectedExecutionHandler来处理,
* 当没有更多的线程或队列插槽时,自定义如何处理超出能力范围之外的任务
* @return
*/
private RejectedExecutionHandler getRejectedExecutionHandler() {
return new RejectedExecutionHandler() {
public void rejectedExecution(Runnable r, ThreadPoolExecutor executor) {
if (!executor.isShutdown()) {
r.run();
}
}
};
}
/**
* 销毁线程池:销毁集合中的线程池
*/
public void destroy() {
if (MapUtils.isEmpty(PoolFactoryMap)) {
return;
}

for (Map.Entry<ThreadPoolEnum, ExecutorService> entry : PoolFactoryMap.entrySet()) {
ExecutorService executorService = entry.getValue();
try {
if (executorService != null && !executorService.isShutdown()) {
executorService.shutdown();
}
} catch (Exception e) {
e.printStackTrace();
}
}
}
}
 

 

Java ExecutorService四种线程池及自定义ThreadPoolExecutor机制

标签:cto   lan   ted   Fix   blocking   ane   name   讲解   value   

原文地址:https://www.cnblogs.com/aoshicangqiong/p/10233977.html

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