Java 实现的限流算法

Java实现的三种限流算法：

• 滑动日志
• 令牌桶
• 漏桶

获取连接许可的接口

public interface Limiter {//获取许可boolean tryAcquire();
}

1.滑动日志

用一个有序集合来存储所有请求的时间戳，以空间换时间的方式来简化计算

public class CountLimiter implements Limiter{//维护一个优先队列记录请求的时间戳//将PriorityQueue替换为Redis的ZSet的话可以实现分布式的限流private final PriorityQueue queue = new PriorityQueue<>();//限流大小private final int limitCount;//限流时间范围private final Long limitTime;public CountLimiter(int limitCount, Long limitTime) {this.limitCount = limitCount;this.limitTime = limitTime;}@Overridepublic synchronized boolean tryAcquire() {long nowTime = System.currentTimeMillis();if(queue.size() < limitCount){queue.add(nowTime);return true;}else{long preTime = nowTime - limitTime;//淘汰已经超过时间限制的请求while(!queue.isEmpty() && preTime > queue.peek()){queue.poll();}if(queue.size() < limitCount){queue.add(nowTime);return true;}else{return false;}}}
}

2.令牌桶

利用延迟计算来维护令牌数量

public class TokenBucketLimiter implements Limiter{//最大容量private final long capacity;//令牌的生成速率 每rate毫秒生成一个令牌private final long rate;//下一个令牌的发放时间long nextTokenTime = System.currentTimeMillis();//当前持有的令牌总数private long currentTokens;public TokenBucketLimiter(long rate, int capacity,int currentTokens) {this.rate = rate;this.capacity = capacity;//根据需求设置令牌桶中令牌的初始数量this.currentTokens = currentTokens;}@Overridepublic boolean tryAcquire() {long nowTime = System.currentTimeMillis();if(nowTime - nextTokenTime > rate){//计算新产生的令牌数long newTokens = (nowTime - nextTokenTime) / rate;//更新当前持有的令牌数量currentTokens = Math.min(currentTokens + newTokens,capacity);//更新可以获取令牌的时间nextTokenTime = nowTime;}if(currentTokens > 0){currentTokens--;return true;}return false;}
}

3.漏桶

漏桶算法原理类似于线程池，请求到来先放入等待队列，然后消费端从请求队列中拉取请求，当请求队列超过最大容量后，执行拒绝策略

public class LeakyBucketLimiter implements Limiter{private final long capacity;//漏桶流出的速率 每rate毫秒放出一个请求private final long rate;//当前水量private AtomicInteger currentWater = new AtomicInteger(0);//存放请求的请求队列private final BlockingDeque queue;//定时任务线程池private final ScheduledExecutorService executorService = new ScheduledThreadPoolExecutor(1);public LeakyBucketLimiter(long rate, int capacity,BlockingDeque queue) {this.rate = rate;this.capacity = capacity;this.queue = new LinkedBlockingDeque<>();executorService.schedule(new Runnable() {@Overridepublic void run() {//队列中没有请求的时候阻塞等待，防止空转消费资源try {//如果是比较耗时间的任务可以定义额外的线程池来处理，将分发任务和执行任务分隔开System.out.println("处理请求：" + queue.take());} catch (InterruptedException e) {throw new RuntimeException(e);}currentWater.addAndGet(-1);executorService.schedule(this,rate, TimeUnit.MILLISECONDS);}},rate,TimeUnit.MILLISECONDS);}@Overridepublic synchronized boolean tryAcquire() {//成功增加水池水量，失败则回滚if(currentWater.addAndGet(1) <= capacity){return true;}else{currentWater.addAndGet(-1);return false;}}
}

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