java并发编程8-自定义线程池

自定义线程池

把main看作任务的生产者,把线程看作任务的消费者,这时候模型就建立出来了 于是我们需要一个缓冲区,采取消费正生产者模式,然后让消费者不断消费,并在适当的时候创建新的消费者,如果所有任务都做完了,就取消消费者

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package com.wsx;


import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.ArrayDeque;
import java.util.Deque;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.ReentrantLock;

public class TestThreadPool {
public static void main(String[] args) {
Logger logger = LoggerFactory.getLogger(ThreadPool.class);
ThreadPool threadPool = new ThreadPool(3, 10, 10);
for (int i = 0; i < 50; i++) {
int finalI = i;
threadPool.execute(() -> {
logger.debug("{}", finalI);
try {
Thread.sleep(1);
} catch (InterruptedException e) {
e.printStackTrace();
}
});
}
}
}

class ThreadPool {
// 线程安全阻塞队列
private final BlockingQueue<Runnable> blockingQueue;
// 线程安全
private final AtomicInteger runingSize = new AtomicInteger(0);
// 线程安全final
private final int maxSize;
// 线程安全final
private final long timeout;

public ThreadPool(int maxSize, long timeout, int queueCapcity) {
this.maxSize = maxSize;
this.timeout = timeout;
this.blockingQueue = new BlockingQueue<>(queueCapcity);
}

public void execute(Runnable task) {
for (int old = runingSize.get(); old != maxSize; old = runingSize.get()) {
if (runingSize.compareAndSet(old, old + 1)) {
new Thread(() -> threadRun(task)).start();
return;
}
}
blockingQueue.put(task);
}

public void threadRun(Runnable task) {
for (; task != null; task = blockingQueue.takeNanos(timeout)) {
try {
task.run();
} catch (Exception e) {
e.printStackTrace();
}
}
// 线程退出,当前线程数量降低1
runingSize.decrementAndGet();
}
}


class BlockingQueue<T> {
private final Deque<T> queue = new ArrayDeque<>();
private final ReentrantLock lock = new ReentrantLock();
private final Condition full = lock.newCondition();
private final Condition empty = lock.newCondition();
private final int capcity;

public BlockingQueue(int capcity) {
this.capcity = capcity;
}

// 带超时的等待
public T takeNanos(long timeout) {
lock.lock();
try {
while (queue.isEmpty()) {
try {
if (timeout <= 0) return null;
// 返回剩余时间
timeout = empty.awaitNanos(timeout);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
T t = queue.removeFirst();
full.signal();
return t;
} finally {
lock.unlock();
}
}

// 超时等待
public T take() {
lock.lock();
try {
while (queue.isEmpty()) {
try {
empty.await(); // 等待空
} catch (InterruptedException e) {
e.printStackTrace();
}
}
T t = queue.removeFirst();
full.signal();
return t;
} finally {
lock.unlock();
}
}

public void put(T element) {
lock.lock();
try {
while (queue.size() == capcity) {
try {
full.await(); // 等待空
} catch (InterruptedException e) {
e.printStackTrace();
}
}
queue.addLast(element);
empty.signal();
} finally {
lock.unlock();
}
}
}

策略模式 当队列满了的时候, 死等,超时等待,让调用者放弃执行,让调用者抛出异常,让调用者自己执行 可以用函数式编程实现