• java中线程池创建的几种方式


    java中创建线程池的方式一般有两种:

    Executors工厂方法创建

    package com.javaBase.LineDistancePond;
    
    import java.util.concurrent.ExecutorService;
    import java.util.concurrent.Executors;
    import java.util.concurrent.ScheduledExecutorService;
    import java.util.concurrent.TimeUnit;
    
    /**
     * 〈一句话功能简述〉;
     * 〈功能详细描述〉
     *
     * @author jxx
     * @see [相关类/方法](可选)
     * @since [产品/模块版本] (可选)
     */
    public class TestThreadPoolExecutor {
    
        public static void main(String[] args) {
            //创建使用单个线程的线程池
            ExecutorService es1 = Executors.newSingleThreadExecutor();
            for (int i = 0; i < 10; i++) {
                es1.submit(new Runnable() {
                    @Override
                    public void run() {
                        System.out.println(Thread.currentThread().getName() + "正在执行任务");
                    }
                });
            }
            //创建使用固定线程数的线程池
            ExecutorService es2 = Executors.newFixedThreadPool(3);
            for (int i = 0; i < 10; i++) {
                es2.submit(new Runnable() {
                    @Override
                    public void run() {
                        System.out.println(Thread.currentThread().getName() + "正在执行任务");
                    }
                });
            }
            //创建一个会根据需要创建新线程的线程池
            ExecutorService es3 = Executors.newCachedThreadPool();
            for (int i = 0; i < 20; i++) {
                es3.submit(new Runnable() {
                    @Override
                    public void run() {
                        System.out.println(Thread.currentThread().getName() + "正在执行任务");
                    }
                });
            }
            //创建拥有固定线程数量的定时线程任务的线程池
            ScheduledExecutorService es4 = Executors.newScheduledThreadPool(2);
            System.out.println("时间:" + System.currentTimeMillis());
            for (int i = 0; i < 5; i++) {
                es4.schedule(new Runnable() {
                    @Override
                    public void run() {
                        System.out.println("时间:"+System.currentTimeMillis()+"--"+Thread.currentThread().getName() + "正在执行任务");
                    }
                },3, TimeUnit.SECONDS);
            }
            //创建只有一个线程的定时线程任务的线程池
            ScheduledExecutorService es5 = Executors.newSingleThreadScheduledExecutor();
            System.out.println("时间:" + System.currentTimeMillis());
            for (int i = 0; i < 5; i++) {
                es5.schedule(new Runnable() {
                    @Override
                    public void run() {
                        System.out.println("时间:"+System.currentTimeMillis()+"--"+Thread.currentThread().getName() + "正在执行任务");
                    }
                },3, TimeUnit.SECONDS);
            }
        }
    }

    new ThreadPoolExecutor()自定义创建

    public ThreadPoolExecutor(int corePoolSize, int maximumPoolSize,long keepAliveTime,TimeUnit unit,BlockingQueue workQueue,ThreadFactory threadFactory,RejectedExecutionHandler handler) ;

    corePoolSize:核心池的大小,这个参数跟后面讲述的线程池的实现原理有非常大的关系。在创建了线程池后,默认情况下,线程池中并没有任何线程,而是等待有任务到来才创建线程去执行任务,除非调用了prestartAllCoreThreads()或者prestartCoreThread()方法,从这2个方法的名字就可以看出,是预创建线程的意思,即在没有任务到来之前就创建corePoolSize个线程或者一个线程。默认情况下,在创建了线程池后,线程池中的线程数为0,当有任务来之后,就会创建一个线程去执行任务,当线程池中的线程数目达到corePoolSize后,就会把到达的任务放到缓存队列当中;
    maximumPoolSize:线程池最大线程数,这个参数也是一个非常重要的参数,它表示在线程池中最多能创建多少个线程;
    keepAliveTime:表示线程没有任务执行时最多保持多久时间会终止。默认情况下,只有当线程池中的线程数大于corePoolSize时,keepAliveTime才会起作用,直到线程池中的线程数不大于corePoolSize,即当线程池中的线程数大于corePoolSize时,如果一个线程空闲的时间达到keepAliveTime,则会终止,直到线程池中的线程数不超过corePoolSize。但是如果调用了allowCoreThreadTimeOut(boolean)方法,在线程池中的线程数不大于corePoolSize时,keepAliveTime参数也会起作用,直到线程池中的线程数为0;
    unit:参数keepAliveTime的时间单位,有7种取值,在TimeUnit类中有7种静态属性:
    TimeUnit.DAYS;               //
    TimeUnit.HOURS;             //小时
    TimeUnit.MINUTES;           //分钟
    TimeUnit.SECONDS;           //
    TimeUnit.MILLISECONDS;      //毫秒
    TimeUnit.MICROSECONDS;      //微妙
    TimeUnit.NANOSECONDS;       //纳秒

    workQueue:一个阻塞队列,用来存储等待执行的任务,这个参数的选择也很重要,会对线程池的运行过程产生重大影响,一般来说,这里的阻塞队列有以下几种选择:

    ArrayBlockingQueue
    LinkedBlockingQueue
    SynchronousQueue
    PriorityBlockingQueue
    ArrayBlockingQueue和PriorityBlockingQueue使用较少,一般使用LinkedBlockingQueue和SynchronousQueue。线程池的排队策略与BlockingQueue有关。

    threadFactory:用于设置创建线程的工厂,可以通过线程工厂给每个创建出来的线程做些更有意义的事情,比如设置daemon和优先级等等
    handler:表示当拒绝处理任务时的策略,有以下四种取值:

    1、AbortPolicy:直接抛出异常。
    2、CallerRunsPolicy:只用调用者所在线程来运行任务。
    3、DiscardOldestPolicy:丢弃队列里最近的一个任务,并执行当前任务。
    4、DiscardPolicy:不处理,丢弃掉。
    5、也可以根据应用场景需要来实现RejectedExecutionHandler接口自定义策略。如记录日志或持久化不能处理的任务。

    ThreadPoolExecutor 源码理解

     public static void test(int size) {
            ThreadPoolExecutor poolExecutor = new ThreadPoolExecutor(5, 20, 2, TimeUnit.SECONDS, new LinkedBlockingQueue<>(5));
    
            for (int i = 0; i < size; i++) {
                poolExecutor.execute(new DemoTask(i));
    
    
                Console.log("poolSize:" + poolExecutor.getPoolSize());
                Console.log("corePoolSize:" + poolExecutor.getCorePoolSize());
                Console.log("maximumPoolSize:" + poolExecutor.getMaximumPoolSize());
                Console.log("queue:" + poolExecutor.getQueue().size());
                Console.log("completedTaskCount:" + poolExecutor.getCompletedTaskCount());
                Console.log("largestPoolSize:" + poolExecutor.getLargestPoolSize());
                Console.log("keepAliveTime:" + poolExecutor.getKeepAliveTime(TimeUnit.SECONDS));
    
            }
    
            poolExecutor.shutdown();
        }
    
    class DemoTask implements Runnable {
    
        private int taskNum;
    
        public DemoTask(int taskNum) {
            this.taskNum = taskNum;
        }
    
        @Override
        public void run() {
            Console.log(StringUtils.center("正在执行" + taskNum, 20, "="));
    
            try {
                Thread.sleep(2000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            Console.log(StringUtils.center("执行完毕" + taskNum, 20, "="));
        }
    }

    执行结果:

    =======正在执行0========
    poolSize:1
    corePoolSize:5
    maximumPoolSize:20
    queue:0
    completedTaskCount:0
    largestPoolSize:1
    keepAliveTime:2
    poolSize:2
    corePoolSize:5
    maximumPoolSize:20
    queue:0
    completedTaskCount:0
    =======正在执行1========
    largestPoolSize:2
    keepAliveTime:2
    poolSize:3
    corePoolSize:5
    maximumPoolSize:20
    =======正在执行2========
    queue:0
    completedTaskCount:0
    largestPoolSize:3
    keepAliveTime:2
    poolSize:4
    corePoolSize:5
    maximumPoolSize:20
    queue:0
    =======正在执行3========
    completedTaskCount:0
    largestPoolSize:4
    keepAliveTime:2
    poolSize:5
    corePoolSize:5
    =======正在执行4========
    maximumPoolSize:20
    queue:0
    completedTaskCount:0
    largestPoolSize:5
    keepAliveTime:2
    poolSize:5
    corePoolSize:5
    maximumPoolSize:20
    queue:1
    completedTaskCount:0
    largestPoolSize:5
    keepAliveTime:2
    poolSize:5
    corePoolSize:5
    maximumPoolSize:20
    queue:2
    completedTaskCount:0
    largestPoolSize:5
    keepAliveTime:2
    poolSize:5
    corePoolSize:5
    maximumPoolSize:20
    queue:3
    completedTaskCount:0
    largestPoolSize:5
    keepAliveTime:2
    poolSize:5
    corePoolSize:5
    maximumPoolSize:20
    queue:4
    completedTaskCount:0
    largestPoolSize:5
    keepAliveTime:2
    poolSize:5
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    completedTaskCount:0
    largestPoolSize:5
    keepAliveTime:2
    poolSize:6
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    completedTaskCount:0
    largestPoolSize:6
    keepAliveTime:2
    poolSize:7
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    completedTaskCount:0
    largestPoolSize:7
    keepAliveTime:2
    =======正在执行11=======
    poolSize:8
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    completedTaskCount:0
    =======正在执行12=======
    =======正在执行10=======
    largestPoolSize:8
    keepAliveTime:2
    poolSize:9
    corePoolSize:5
    =======正在执行13=======
    maximumPoolSize:20
    queue:5
    completedTaskCount:0
    largestPoolSize:9
    keepAliveTime:2
    poolSize:10
    corePoolSize:5
    maximumPoolSize:20
    =======正在执行14=======
    queue:5
    completedTaskCount:0
    largestPoolSize:10
    keepAliveTime:2
    poolSize:11
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    =======正在执行15=======
    completedTaskCount:0
    largestPoolSize:11
    keepAliveTime:2
    poolSize:12
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    completedTaskCount:0
    =======正在执行16=======
    largestPoolSize:12
    keepAliveTime:2
    poolSize:13
    corePoolSize:5
    maximumPoolSize:20
    =======正在执行17=======
    queue:5
    completedTaskCount:0
    largestPoolSize:13
    keepAliveTime:2
    poolSize:14
    corePoolSize:5
    maximumPoolSize:20
    queue:5
    =======正在执行18=======
    completedTaskCount:0
    largestPoolSize:14
    keepAliveTime:2
    poolSize:15
    corePoolSize:5
    maximumPoolSize:20
    =======正在执行19=======
    queue:5
    completedTaskCount:0
    largestPoolSize:15
    keepAliveTime:2
    =======执行完毕0========
    =======正在执行5========
    =======执行完毕1========
    =======执行完毕2========
    =======正在执行6========
    =======正在执行7========
    =======执行完毕4========
    =======正在执行8========
    =======执行完毕3========
    =======正在执行9========
    =======执行完毕13=======
    =======执行完毕12=======
    =======执行完毕10=======
    =======执行完毕11=======
    =======执行完毕15=======
    =======执行完毕16=======
    =======执行完毕14=======
    =======执行完毕19=======
    =======执行完毕18=======
    =======执行完毕17=======
    =======执行完毕5========
    =======执行完毕7========
    =======执行完毕6========
    =======执行完毕8========
    =======执行完毕9========

    参考链接:Java线程池(一)

           Java线程池(二)

  • 相关阅读:
    php5使用docker工具安装mcrypt
    golang 三目运算的实现
    图片壁纸
    使用golang实现栈(stack)
    Qt 异常处理 QT_TRY和QT_CATCH
    OpenCV 实现图片HDR功能
    OpenCV HDR合成
    OpenCV .直方图均衡 CLAHE算法学习
    OpenCV 直方图均衡化原理
    OpenCV 直方图绘制以及直方图均衡化
  • 原文地址:https://www.cnblogs.com/jxxblogs/p/11655670.html
Copyright © 2020-2023  润新知