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());
- }
- }
- }
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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
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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());
- }
- }
- }
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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
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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();
- }
- }
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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
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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();
- }
- }
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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();
- }
- }
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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
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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。 |