FixedThreadPool Executors

 

public class T05_ThreadPool {

    public static void main(String[] args) throws InterruptedException {

        ExecutorService service = Executors.newFixedThreadPool(5); // 固定长度的线程池
        for (int i = 0; i < 6; i++) { // 执行六个任务,  在只有五个固定容量的线程池中
            service.execute(() -> {
                try {
                    TimeUnit.MILLISECONDS.sleep(500);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            });
        }
        System.out.println(service); // [Running, pool size = 5, active threads = 5, queued tasks = 1, completed tasks = 0]
        // 内部一般是BlockingQueue
        // pool size =  5  线程池的容量
        // active thread = 5 激活的线程队列长度
        // queued tasks = 1 等待处理任务长度
        // completed task = 0 完成执行的任务数量
        
        // 关闭线程池
        service.shutdown(); // 未执行完毕,不会停止,只会进入停止中状态
        System.out.println(service.isTerminated()); // false 是否结束
        System.out.println(service.isShutdown()); // true 状态是否关闭
        System.out.println(service);  //java.util.concurrent.ThreadPoolExecutor@3b9a45b3[Shutting down, pool size = 5, active threads = 5, queued tasks = 1, completed tasks = 0]
        

        TimeUnit.SECONDS.sleep(5); // 5s 后肯定执行完成了

        System.out.println(service.isTerminated()); // true 
        System.out.println(service.isShutdown()); // true
        System.out.println(service); // java.util.concurrent.ThreadPoolExecutor@3b9a45b3[Terminated, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 6]

        
        // 线程池中维护了两个任务队列
        // 1. 未执行的任务队列
        // 2. 已执行的任务队列
    }  
}

 

线程池的作用：并行计算

/**
 * 线程池的作用:并行计算
 * 计算 1-200000 之间的质数
 */
public class T07_ParallelComputing {

    public static void main(String[] args) throws ExecutionException, InterruptedException {
        long start = System.currentTimeMillis();
        List<Integer> result = getPrime(1, 200000);
        long end = System.currentTimeMillis();
        System.out.println("主线程"+(end - start)); // 使用单线程计算的时间

        ExecutorService service = Executors.newFixedThreadPool(3);
        ComputeTask t1 = new ComputeTask(1, 100000);
        ComputeTask t2 = new ComputeTask(16000, 190000);
        ComputeTask t3 = new ComputeTask(190001, 200000);
        ComputeTask t4 = new ComputeTask(100001, 160000);  // 这里为什么不均分? 因为数字越大, 质数的数量就越多
        // 提交任务给ExecutorService执行
        Future<List<Integer>> f1 = service.submit(t1);
        Future<List<Integer>> f2 = service.submit(t2);
        Future<List<Integer>> f3 = service.submit(t3);
        Future<List<Integer>> f4 = service.submit(t4);
        // 执行开始
        start = System.currentTimeMillis();
        f1.get();
        f2.get();
        f3.get();
        f4.get();
        end = System.currentTimeMillis();
        System.out.println(end - start);
        service.shutdown();
    }

    static class ComputeTask implements Callable<List<Integer>> {

        private int start, end;
        
        ComputeTask (int start, int end) {
            this.start = start;
            this.end = end;
        }

        @Override
        public List<Integer> call() throws Exception {
            return getPrime(start, end);
        }
    }
    

    static boolean isPrime(int num) {
        for (int i = 2; i < num / 2; i++) {
            if (num % i == 0) return false;
        }
        return true;
    }

    /**
     * 返回指定范围的质数列表
     */
    static List<Integer> getPrime(int start, int end) {
        List<Integer> list = new ArrayList<>();
        for (int i = 0; i < end; i++) {
            if (isPrime(i)) list.add(i);
        }
        return list;
    }
}