Java 线程池

系统启动一个线程的成本是比较高的，因为它涉及到与操作系统的交互，使用线程池的好处是提高性能，当系统中包含大量并发的线程时，会导致系统性能剧烈下降，甚至导致JVM崩溃，而线程池的最大线程数参数可以控制系统中并发线程数不超过次数。

一、Executors 工厂类用来产生线程池，该工厂类包含以下几个静态工厂方法来创建对应的线程池。创建的线程池是一个ExecutorService对象，使用该对象的submit方法或者是execute方法执行相应的Runnable或者是Callable任务。线程池本身在不再需要的时候调用shutdown()方法停止线程池，调用该方法后，该线程池将不再允许任务添加进来，但是会直到已添加的所有任务执行完成后才死亡。

1、newCachedThreadPool()，创建一个具有缓存功能的线程池，提交到该线程池的任务（Runnable或Callable对象）创建的线程，如果执行完成，会被缓存到CachedThreadPool中，供后面需要执行的任务使用。

import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class CacheThreadPool {
    static class Task implements Runnable {
        @Override
        public void run() {
            System.out.println(this + " " + Thread.currentThread().getName() + " AllStackTraces map size: "
                    + Thread.currentThread().getAllStackTraces().size());
        }
    }

    public static void main(String[] args) {
        ExecutorService cacheThreadPool = Executors.newCachedThreadPool();

        //先添加三个任务到线程池
        for(int i = 0 ; i < 3; i++) {
            cacheThreadPool.execute(new Task());
        }

        //等三个线程执行完成后，再次添加三个任务到线程池
        try {
            Thread.sleep(3000);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        for(int i = 0 ; i < 3; i++) {
            cacheThreadPool.execute(new Task());
        }
    }

}

执行结果如下：

CacheThreadPool$Task@2d312eb9 pool-1-thread-1 AllStackTraces map size: 7
CacheThreadPool$Task@59522b86 pool-1-thread-3 AllStackTraces map size: 7
CacheThreadPool$Task@73dbb89f pool-1-thread-2 AllStackTraces map size: 7
CacheThreadPool$Task@5795cedc pool-1-thread-3 AllStackTraces map size: 7
CacheThreadPool$Task@256d5600 pool-1-thread-1 AllStackTraces map size: 7
CacheThreadPool$Task@7d1c5894 pool-1-thread-2 AllStackTraces map size: 7

线程池中的线程对象进行了缓存，当有新任务执行时进行了复用。但是如果有特别多的并发时，缓存线程池还是会创建很多个线程对象。

2、newFixedThreadPool(int nThreads) 创建一个指定线程个数，线程可复用的线程池。

import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class FixedThreadPool {
    static class Task implements Runnable {
        @Override
        public void run() {
            System.out.println(this + " " + Thread.currentThread().getName() + " AllStackTraces map size: "
                    + Thread.currentThread().getAllStackTraces().size());
        }
    }

    public static void main(String[] args) {
        ExecutorService fixedThreadPool = Executors.newFixedThreadPool(3);

        // 先添加三个任务到线程池
        for (int i = 0; i < 5; i++) {
            fixedThreadPool.execute(new Task());
        }

        // 等三个线程执行完成后，再次添加三个任务到线程池
        try {
            Thread.sleep(3);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        for (int i = 0; i < 3; i++) {
            fixedThreadPool.execute(new Task());
        }
    }

}

执行结果：

FixedThreadPool$Task@7045c12d pool-1-thread-2 AllStackTraces map size: 7
FixedThreadPool$Task@50fa0bef pool-1-thread-2 AllStackTraces map size: 7
FixedThreadPool$Task@ccb1870 pool-1-thread-2 AllStackTraces map size: 7
FixedThreadPool$Task@7392b4e3 pool-1-thread-1 AllStackTraces map size: 7
FixedThreadPool$Task@5bdeff18 pool-1-thread-2 AllStackTraces map size: 7
FixedThreadPool$Task@7d5554e1 pool-1-thread-1 AllStackTraces map size: 7
FixedThreadPool$Task@24468092 pool-1-thread-3 AllStackTraces map size: 7
FixedThreadPool$Task@fa7b978 pool-1-thread-2 AllStackTraces map size: 7

3、newSingleThreadExecutor(),创建一个只有单线程的线程池，相当于调用newFixedThreadPool(1)

4、newSheduledThreadPool(int corePoolSize),创建指定线程数的线程池，它可以在指定延迟后执行线程。也可以以某一周期重复执行某一线程，知道调用shutdown()关闭线程池。

示例如下：

import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;

public class ScheduledThreadPool {
    static class Task implements Runnable {
        @Override
        public void run() {
            System.out.println("time " + System.currentTimeMillis()  + " " + Thread.currentThread().getName() + " AllStackTraces map size: "
                    + Thread.currentThread().getAllStackTraces().size());
        }
    }

    public static void main(String[] args) {
        ScheduledExecutorService scheduledExecutorService = Executors.newScheduledThreadPool(3);

        scheduledExecutorService.schedule(new Task(), 3, TimeUnit.SECONDS);

        scheduledExecutorService.scheduleAtFixedRate(new Task(), 3, 5, TimeUnit.SECONDS);

        try {
            Thread.sleep(30 * 1000);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        scheduledExecutorService.shutdown();
    }

}

运行结果如下：

time 1458921795240 pool-1-thread-1 AllStackTraces map size: 6
time 1458921795241 pool-1-thread-2 AllStackTraces map size: 6
time 1458921800240 pool-1-thread-1 AllStackTraces map size: 7
time 1458921805240 pool-1-thread-1 AllStackTraces map size: 7
time 1458921810240 pool-1-thread-1 AllStackTraces map size: 7
time 1458921815240 pool-1-thread-1 AllStackTraces map size: 7
time 1458921820240 pool-1-thread-1 AllStackTraces map size: 7

由运行时间可看出，任务是按照5秒的周期执行的。

5、newSingleThreadScheduledExecutor() 创建一个只有一个线程的线程池，同调用newScheduledThreadPool(1)。

二、ForkJoinPool和ForkJoinTask

ForkJoinPool是ExecutorService的实现类，支持将一个任务划分为多个小任务并行计算，在把多个小任务的计算结果合并成总的计算结果。它有两个构造函数

ForkJoinPool(int parallelism)创建一个包含parallelism个并行线程的ForkJoinPool。

ForkJoinPool(),以Runtime.availableProcessors()方法返回值作为parallelism参数来创建ForkJoinPool。

ForkJoinTask 代表一个可以并行，合并的任务。它是实现了Future<T>接口的抽象类，它有两个抽象子类，代表无返回值任务的RecuriveAction和有返回值的RecursiveTask。可根据具体需求继承这两个抽象类实现自己的对象，然后调用ForkJoinPool的submit 方法执行。

RecuriveAction 示例如下，实现并行输出0-300的数字。

import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveAction;
import java.util.concurrent.TimeUnit;

public class ActionForkJoinTask {
    static class PrintTask extends RecursiveAction {
        private static final int THRESHOLD = 50;
        private int start;
        private int end;

        public PrintTask(int start, int end) {
            this.start = start;
            this.end = end;
        }

        @Override
        protected void compute() {
            if (end - start < THRESHOLD) {
                for(int i = start; i < end; i++) {
                    System.out.println(Thread.currentThread().getName() + " " + i);
                }
            } else {
                int middle = (start + end) / 2;
                PrintTask left = new PrintTask(start, middle);
                PrintTask right = new PrintTask(middle, end);
                left.fork();
                right.fork();
            }
        }

    }

    public static void main(String[] args) {
        ForkJoinPool pool = new ForkJoinPool();

        pool.submit(new PrintTask(0,  300));
        try {
            pool.awaitTermination(2, TimeUnit.SECONDS);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        pool.shutdown();
    }

}

在拆分小任务后，调用任务的fork（）方法，加入到ForkJoinPool中并行执行。

RecursiveTask示例，实现并行计算100个整数求和。拆分为每20个数求和后获取结果，在最后合并为最后的结果。

import java.util.Random;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.Future;
import java.util.concurrent.RecursiveTask;

public class TaskForkJoinTask {
    static class CalTask extends RecursiveTask<Integer> {
        private static final int THRESHOLD = 20;

        private int arr[];
        private int start;
        private int end;

        public CalTask(int[] arr, int start, int end) {
            this.arr = arr;
            this.start = start;
            this.end = end;
        }

        @Override
        protected Integer compute() {
            int sum = 0;

            if (end - start < THRESHOLD) {
                for (int i = start; i < end; i++) {
                    sum += arr[i];
                }
                System.out.println(Thread.currentThread().getName() + "  sum:" + sum);
                return sum;
            } else {
                int middle = (start + end) / 2;
                CalTask left = new CalTask(arr, start, middle);
                CalTask right = new CalTask(arr, middle, end);

                left.fork();
                right.fork();

                return left.join() + right.join();
            }
        }

    }

    public static void main(String[] args) {
        int arr[] = new int[100];
        Random random = new Random();
        int total = 0;

        for (int i = 0; i < arr.length; i++) {
            int tmp = random.nextInt(20);
            total += (arr[i] = tmp);
        }
        System.out.println("total " + total);

        ForkJoinPool pool = new ForkJoinPool(4);

        Future<Integer> future = pool.submit(new CalTask(arr, 0, arr.length));
        try {
            System.out.println("cal result: " + future.get());
        } catch (InterruptedException e) {
            e.printStackTrace();
        } catch (ExecutionException e) {
            e.printStackTrace();
        }
        pool.shutdown();
    }

}

执行结果如下：

total 912
ForkJoinPool-1-worker-2  sum:82
ForkJoinPool-1-worker-2  sum:123
ForkJoinPool-1-worker-2  sum:144
ForkJoinPool-1-worker-3  sum:119
ForkJoinPool-1-worker-2  sum:106
ForkJoinPool-1-worker-2  sum:128
ForkJoinPool-1-worker-2  sum:121
ForkJoinPool-1-worker-3  sum:89
cal result: 912

子任务执行完后，调用任务的join（）方法获取子任务执行结果，再相加获得最后的结果。