1. 线程池
线程池：三大方法、7大参数、4种拒绝策略
1.1 线程池的好处
1、降低资源的消耗
2、提高响应的速度
3、方便管理。
4、线程复用、可以控制最大并发数、管理线程
1.2 线程池：三大方法
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public class Demo01 {
public static void main(String[] args) {
ExecutorService threadPool = Executors.newSingleThreadExecutor();
程
个固定的线程池的大小
的，遇强则强，遇弱则弱
try {
for (int i = 0; i < 100; i++) {
threadPool.execute(()->{
System.out.println(Thread.currentThread().getName()+" ok");
});
}
} catch (Exception e) {
e.printStackTrace();
} finally {
threadPool.shutdown();
}
}
}
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1.3 七大参数
源码分析
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| public static ExecutorService newSingleThreadExecutor() {
return new FinalizableDelegatedExecutorService
(new ThreadPoolExecutor(1, 1,0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>()));
}
public static ExecutorService newFixedThreadPool(int nThreads) {
return new ThreadPoolExecutor(5, 5,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>());
}
public static ExecutorService newCachedThreadPool() {
return new ThreadPoolExecutor(0, Integer.MAX_VALUE,
60L, TimeUnit.SECONDS,
new SynchronousQueue<Runnable>());
}
public ThreadPoolExecutor(int corePoolSize, // 核心线程池大小
int maximumPoolSize, // 最大核心线程池大小
long keepAliveTime, // 超时了没有人调用就会释放
TimeUnit unit, // 超时单位
BlockingQueue<Runnable> workQueue, // 阻塞队列
ThreadFactory threadFactory, // 线程工厂：创建线程的，一般
不用动
RejectedExecutionHandler handle // 拒绝策略) {
if (corePoolSize < 0 ||
maximumPoolSize <= 0 ||
maximumPoolSize < corePoolSize ||
keepAliveTime < 0)
throw new IllegalArgumentException();
if (workQueue == null || threadFactory == null || handler == null)
throw new NullPointerException();
this.acc = System.getSecurityManager() == null ?
null :
AccessController.getContext();
this.corePoolSize = corePoolSize;
this.maximumPoolSize = maximumPoolSize;
this.workQueue = workQueue;
this.keepAliveTime = unit.toNanos(keepAliveTime);
this.threadFactory = threadFactory;
this.handler = handler;
}
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手动创建一个线程池
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public class Demo01 {
public static void main(String[] args) {
ExecutorService threadPool = new ThreadPoolExecutor(
2,
5,
3,
TimeUnit.SECONDS,
new LinkedBlockingDeque<>(3),
Executors.defaultThreadFactory(),
new ThreadPoolExecutor.DiscardOldestPolicy());
最早的竞争，也不会抛出异常！
try {
for (int i = 1; i <= 9; i++) {
threadPool.execute(()->{
System.out.println(Thread.currentThread().getName()+" ok");
});
}
} catch (Exception e) {
e.printStackTrace();
} finally {
threadPool.shutdown();
}
}
}
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1.4 四种拒绝策略
1.5 小结和拓展
池的最大的大小如何去设置？
了解：IO密集型，CPU密集型：（调优）
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| public class Demo01 {
public static void main(String[] args) {
System.out.println(Runtime.getRuntime().availableProcessors());
ExecutorService threadPool = new ThreadPoolExecutor(
2,
Runtime.getRuntime().availableProcessors(),
3,
TimeUnit.SECONDS,
new LinkedBlockingDeque<>(3),
Executors.defaultThreadFactory(),
new ThreadPoolExecutor.DiscardOldestPolicy());
最早的竞争，也不会抛出异常！
try {
for (int i = 1; i <= 9; i++) {
threadPool.execute(()->{
System.out.println(Thread.currentThread().getName()+" ok");
});
}
} catch (Exception e) {
e.printStackTrace();
} finally {
threadPool.shutdown();
}
}
}
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2. ForkJoin(分解大任务)
ForkJoin 在 JDK 1.7 ， 并行执行任务！提高效率。处理大数据量！
大数据：Map Reduce （把大任务拆分为小任务）
ForkJoin 特点：工作窃取
这个里面维护的都是双端队列，如果当前队列已无任务，则会去其他队列的另一头窃取任务执行。
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public class ForkJoinDemo extends RecursiveTask<Long> {
private Long start;
private Long end;
private Long temp = 10000L;
public ForkJoinDemo(Long start, Long end) {
this.start = start;
this.end = end;
}
@Override
protected Long compute() {
if ((end-start)<temp){
Long sum = 0L;
for (Long i = start; i <= end; i++) {
sum += i;
}
return sum;
}else {
long middle = (start + end) / 2;
ForkJoinDemo task1 = new ForkJoinDemo(start, middle);
task1.fork();
ForkJoinDemo task2 = new ForkJoinDemo(middle+1, end);
task2.fork();
return task1.join() + task2.join();
}
}
}
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测试
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public class Test {
public static void main(String[] args) throws ExecutionException,
InterruptedException {
}
public static void test1(){
Long sum = 0L;
long start = System.currentTimeMillis();
for (Long i = 1L; i <= 10_0000_0000; i++) {
sum += i;
}
long end = System.currentTimeMillis();
System.out.println("sum="+sum+" 时间："+(end-start));
}
public static void test2() throws ExecutionException, InterruptedException {
long start = System.currentTimeMillis();
ForkJoinPool forkJoinPool = new ForkJoinPool();
ForkJoinTask<Long> task = new ForkJoinDemo(0L, 10_0000_0000L);
ForkJoinTask<Long> submit = forkJoinPool.submit(task);
Long sum = submit.get();
long end = System.currentTimeMillis();
System.out.println("sum="+sum+" 时间："+(end-start));
}
public static void test3(){
long start = System.currentTimeMillis();
long sum = LongStream.rangeClosed(0L,
10_0000_0000L).parallel().reduce(0, Long::sum);
long end = System.currentTimeMillis();
System.out.println("sum="+"时间："+(end-start));
}
}
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3.Future 异步回调
Future 设计的初衷： 对将来的某个事件的结果进行建模
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public class Demo01 {
public static void main(String[] args) throws ExecutionException,
InterruptedException {
CompletableFuture<Integer> completableFuture = CompletableFuture.supplyAsync(()->{
System.out.println(Thread.currentThread().getName()+"supplyAsync=>Integer");
int i = 10/0;
return 1024;
});
System.out.println(completableFuture.whenComplete((t, u) -> {
System.out.println("t=>" + t);
System.out.println("u=>" + u);
}).exceptionally((e) -> {
System.out.println(e.getMessage());
return 233;
}).get());
}
}
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