（四）juc线程高级特性——线程池 / 线程调度 / ForkJoinPool

13. 线程池

/*
* 一、线程池：提供了一个线程队列，队列中保存着所有等待状态的线程。避免了创建与销毁额外开销，提高了响应的速度。
*
* 二、线程池的体系结构：
*     java.util.concurrent.Executor : 负责线程的使用与调度的根接口
*         |--**ExecutorService 子接口: 线程池的主要接口
*             |--ThreadPoolExecutor 线程池的实现类
*             |--ScheduledExecutorService 子接口：负责线程的调度
*                 |--ScheduledThreadPoolExecutor ：继承 ThreadPoolExecutor， 实现 ScheduledExecutorService
*
* 三、工具类 : Executors
* ExecutorService newFixedThreadPool() : 创建固定大小的线程池
* ExecutorService newCachedThreadPool() : 缓存线程池，线程池的数量不固定，可以根据需求自动的更改数量。
* ExecutorService newSingleThreadExecutor() : 创建单个线程池。线程池中只有一个线程
*
* ScheduledExecutorService newScheduledThreadPool() : 创建固定大小的线程，可以延迟或定时的执行任务。
*/
public class TestThreadPool {

public static void main(String[] args) throws Exception {
//1. 创建线程池
ExecutorService pool = Executors.newFixedThreadPool(5);

ThreadPoolDemo tpd = new ThreadPoolDemo();

//2. 为线程池中的线程分配任务，>5，可将线程池里的五个线程都给调用
for (int i = 0; i < 10; i++) {
pool.submit(tpd);
}

//3. 关闭线程池
pool.shutdown();
}
//    new Thread(tpd).start();
//    new Thread(tpd).start();
}

class ThreadPoolDemo implements Runnable{

private int i = 0;

@Override
public void run() {
while(i <= 100){
System.out.println(Thread.currentThread().getName() + " : " + i++);
}
}
}

public static void main(String[] args) throws Exception {
//1. 创建线程池
ExecutorService pool = Executors.newFixedThreadPool(5);

List<Future<Integer>> list = new ArrayList<>();

for (int i = 0; i < 10; i++) {
//Future对象用于接收Callable线程的返回值
Future<Integer> future = pool.submit(new Callable<Integer>(){
//线程调用方法，查询1-100之和
@Override
public Integer call() throws Exception {
int sum = 0;
for (int i = 0; i <= 100; i++) {
sum += i;
}
return sum;
}
});
list.add(future);
}
//关闭线程池
pool.shutdown();
//遍历结果集，会输出10次5050
for (Future<Integer> future : list) {
System.out.println(future.get());
}
}

14. 线程调度

public <V> ScheduledFuture<V> schedule(Callable<V> callable,
long delay,
TimeUnit unit) {
if (callable == null || unit == null)
throw new NullPointerException();
RunnableScheduledFuture<V> t = decorateTask(callable,
new ScheduledFutureTask<V>(callable,
triggerTime(delay, unit)));
delayedExecute(t);
return t;
}

public class TestScheduledThreadPool {
public static void main(String[] args) throws Exception {
　　　　//创建ScheduledExecutorService类型的线程池对象
ScheduledExecutorService pool = Executors.newScheduledThreadPool(5);

for (int i = 0; i < 5; i++) {
Future<Integer> result = pool.schedule(new Callable<Integer>(){
@Override
public Integer call() throws Exception {
int num = new Random().nextInt(100);//生成随机数
System.out.println(Thread.currentThread().getName() + " : " + num);
return num;
}
}, 1, TimeUnit.SECONDS);

System.out.println(result.get());
}
//线程池关闭
pool.shutdown();
}
}

15. ForkJoinPool 分支合并框架-工作窃取

/* @since 1.7
*  @author Doug Lea
*/
public abstract class ForkJoinTask<V> implements Future<V>, Serializable {
...
}

//有返回值
public abstract class RecursiveTask<V> extends ForkJoinTask<V> {}
//无返回值
public abstract class RecursiveAction extends ForkJoinTask<Void> {}

class ForkJoinSumCalculate extends RecursiveTask<Long>{

private static final long serialVersionUID = -1812835340478767238L;

private long start;
private long end;

private static final long THURSHOLD = 10000L;  //临界值

public ForkJoinSumCalculate(long start, long end) {
this.start = start;
this.end = end;
}

@Override
protected Long compute() {
long length = end - start;
//小于临界值，则不进行拆分，直接计算初始值到结束值之间所有数之和
if(length <= THURSHOLD){
long sum = 0L;

for (long i = start; i <= end; i++) {
sum += i;
}

return sum;
}else{  //大于临界值，取中间值进行拆分，递归调用
long middle = (start + end) / 2;

ForkJoinSumCalculate left = new ForkJoinSumCalculate(start, middle);
left.fork(); //进行拆分，同时压入线程队列

ForkJoinSumCalculate right = new ForkJoinSumCalculate(middle+1, end);
right.fork(); //

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

public static void main(String[] args) {
Instant start = Instant.now();
ForkJoinPool pool = new ForkJoinPool();
ForkJoinTask<Long> task = new ForkJoinSumCalculate(0L, 50000000000L);
Long sum = pool.invoke(task);
System.out.println(sum);
Instant end = Instant.now();
System.out.println("耗费时间为：" + Duration.between(start, end).toMillis());
}

@Test
public void test1(){
Instant start = Instant.now();
long sum = 0L;
for (long i = 0L; i <= 50000000000L; i++) {
sum += i;
}
System.out.println(sum);
Instant end = Instant.now();
System.out.println("耗费时间为：" + Duration.between(start, end).toMillis());//35-3142-15704
}

//java8 新特性
@Test
public void test2(){
Instant start = Instant.now();
Long sum = LongStream.rangeClosed(0L, 50000000000L)
.parallel()
.reduce(0L, Long::sum);
System.out.println(sum);
Instant end = Instant.now();
System.out.println("耗费时间为：" + Duration.between(start, end).toMillis());//1536-8118
}

50000000000L