详解5种Java中常见限流算法

public class CounterRateLimiter extends MyRateLimiter {
    
    private final long permitsPerSecond;
    
    public long timestamp = System.currentTimeMillis();
    
    private int counter;

    public CounterRateLimiter(long permitsPerSecond) {
        this.permitsPerSecond = permitsPerSecond;
    }

    @Override
    public synchronized boolean tryAcquire() {
        long now = System.currentTimeMillis();
        // 窗口内请求数量小于阈值，更新计数放行，否则拒绝请求
        if (now - timestamp < 1000) {
            if (counter < permitsPerSecond) {
                counter++;
                return true;
            } else {
                return false;
            }
        }
        // 时间窗口过期，重置计数器和时间戳
        counter = 0;
        timestamp = now;
        return true;
    }
}

public class SlidingWindowRateLimiter extends MyRateLimiter {
    
    private final long permitsPerMinute;
    
    private final TreeMap<Long, Integer> counters;

    public SlidingWindowRateLimiter(long permitsPerMinute) {
        this.permitsPerMinute = permitsPerMinute;
        this.counters = new TreeMap<>();
    }

    @Override
    public synchronized boolean tryAcquire() {
        // 获取当前时间的所在的子窗口值； 10s一个窗口
        long currentWindowTime = LocalDateTime.now().toEpochSecond(ZoneOffset.UTC) / 10 * 10;
        // 获取当前窗口的请求总量
        int currentWindowCount = getCurrentWindowCount(currentWindowTime);
        if (currentWindowCount >= permitsPerMinute) {
            return false;
        }
        // 计数器 + 1
        counters.merge(currentWindowTime, 1, Integer::sum);
        return true;
    }
    
    private int getCurrentWindowCount(long currentWindowTime) {
        // 计算出窗口的开始位置时间
        long startTime = currentWindowTime - 50;
        int result = 0;

        // 遍历当前存储的计数器，删除无效的子窗口计数器，并累加当前窗口中的所有计数器之和
        Iterator<Map.Entry<Long, Integer>> iterator = counters.entrySet().iterator();
        while (iterator.hasNext()) {
            Map.Entry<Long, Integer> entry = iterator.next();
            if (entry.geTKEy() < startTime) {
                iterator.remove();
            } else {
                result += entry.getValue();
            }
        }
        return result;
    }
}

public class LeakyBucketRateLimiter extends MyRateLimiter {
    // 桶的容量
    private final int capacity;
    // 漏出速率
    private final int permitsPerSecond;
    // 剩余水量
    private long leftWater;
    // 上次注入时间
    private long timeStamp = System.currentTimeMillis();

    public LeakyBucketRateLimiter(int permitsPerSecond, int capacity) {
        this.capacity = capacity;
        this.permitsPerSecond = permitsPerSecond;
    }

    @Override
    public synchronized boolean tryAcquire() {
        //1. 计算剩余水量
        long now = System.currentTimeMillis();
        long timeGap = (now - timeStamp) / 1000;
        leftWater = Math.max(0, leftWater - timeGap * permitsPerSecond);
        timeStamp = now;
        
        // 如果未满，则放行；否则限流
        if (leftWater < capacity) {
            leftWater += 1;
            return true;
        }
        return false;
    }
}

@Test
public void testLeakyBucketRateLimiter() throws InterruptedException {
    ScheduledExecutorService scheduledExecutorService = Executors.newSingleThreadScheduledExecutor();
    ExecutorService singleThread = Executors.newSingleThreadExecutor();

    LeakyBucketRateLimiter rateLimiter = new LeakyBucketRateLimiter(20, 20);
    // 存储流量的队列
    Queue<Integer> queue = new LinkedList<>();
    // 模拟请求  不确定速率注水
    singleThread.execute(() -> {
        int count = 0;
        while (true) {
            count++;
            boolean flag = rateLimiter.tryAcquire();
            if (flag) {
                queue.offer(count);
                System.out.println(count + "--------流量被放行--------");
            } else {
                System.out.println(count + "流量被限制");
            }
            try {
                Thread.sleep((long) (Math.random() * 1000));
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    });
  
    // 模拟处理请求 固定速率漏水
    scheduledExecutorService.scheduleAtFixedRate(() -> {
        if (!queue.isEmpty()) {
            System.out.println(queue.poll() + "被处理");
        }
    }, 0, 100, TimeUnit.MILLISECONDS);

    // 保证主线程不会退出
    while (true) {
        Thread.sleep(10000);
    }
}

public class TokenBucketRateLimiter extends MyRateLimiter {
    
    private final long capacity;
    
    private final long generatedPerSeconds;
    
    long lastTokenTime = System.currentTimeMillis();
    
    private long currentTokens;

    public TokenBucketRateLimiter(long generatedPerSeconds, int capacity) {
        this.generatedPerSeconds = generatedPerSeconds;
        this.capacity = capacity;
    }

    
    @Override
    public synchronized boolean tryAcquire() {
          
        long now = System.currentTimeMillis();
        if (now - lastTokenTime >= 1000) {
            long newPermits = (now - lastTokenTime) / 1000 * generatedPerSeconds;
            currentTokens = Math.min(currentTokens + newPermits, capacity);
            lastTokenTime = now;
        }
        if (currentTokens > 0) {
            currentTokens--;
            return true;
        }
        return false;
    }
}

public class SlidingLogRateLimiter extends MyRateLimiter {
    
    private static final long PERMITS_PER_MINUTE = 60;
    
    private final TreeMap<Long, Integer> requestLoGCountMap = new TreeMap<>();

    @Override
    public synchronized boolean tryAcquire() {
        // 最小时间粒度为s
        long currentTimestamp = LocalDateTime.now().toEpochSecond(ZoneOffset.UTC);
        // 获取当前窗口的请求总数
        int currentWindowCount = getCurrentWindowCount(currentTimestamp);
        if (currentWindowCount >= PERMITS_PER_MINUTE) {
            return false;
        }
        // 请求成功，将当前请求日志加入到日志中
        requestLogCountMap.merge(currentTimestamp, 1, Integer::sum);
        return true;
    }

    
    private int getCurrentWindowCount(long currentTime) {
        // 计算出窗口的开始位置时间
        long startTime = currentTime - 59;
        // 遍历当前存储的计数器，删除无效的子窗口计数器，并累加当前窗口中的所有计数器之和
        return requestLogCountMap.entrySet()
                .stream()
                .filter(entry -> entry.getKey() >= startTime)
                .mapToInt(Map.Entry::getValue)
                .sum();
    }
}