redis+lua+固定窗口实现分布式限流

用key的过期时间替代固定窗口的时间戳

lua 复制代码

-- KEYS[1]: 限流的key
-- ARGV[1]: 限流窗口大小（秒）
-- ARGV[2]: 限流阈值

local key = KEYS[1]
local window = tonumber(ARGV[1])
local limit = tonumber(ARGV[2])

-- 尝试获取当前计数
local current = redis.call("GET", key)

if current == false then
    -- key不存在，初始化计数器并设置过期时间
    redis.call("SET", key, 1, "EX", window)
    return 1
else
    -- key存在，检查是否超过限制
    if tonumber(current) < limit then
        redis.call("INCR", key)
        return 1
    else
        return 0
    end
end

java客户端

java 复制代码

public class FixedWindowRateLimiterWithTTL {
    private Jedis jedis;
    private String key;
    private int window; // 窗口大小（秒）
    private int limit;  // 限流阈值
    
    private static final String LUA_SCRIPT =
        "local key = KEYS[1]\n" +
        "local window = tonumber(ARGV[1])\n" +
        "local limit = tonumber(ARGV[2])\n" +
        "local current = redis.call(\"GET\", key)\n" +
        "if current == false then\n" +
        "    redis.call(\"SET\", key, 1, \"EX\", window)\n" +
        "    return 1\n" +
        "else\n" +
        "    if tonumber(current) < limit then\n" +
        "        redis.call(\"INCR\", key)\n" +
        "        return 1\n" +
        "    else\n" +
        "        return 0\n" +
        "    end\n" +
        "end";
    
    public FixedWindowRateLimiterWithTTL(Jedis jedis, String key, int window, int limit) {
        this.jedis = jedis;
        this.key = key;
        this.window = window;
        this.limit = limit;
    }
    
    public boolean allowRequest() {
        Object result = jedis.eval(LUA_SCRIPT, 
            Collections.singletonList(key),
            Arrays.asList(
                String.valueOf(window),
                String.valueOf(limit)
            ));
        return "1".equals(result.toString());
    }
}

使用

java 复制代码

public static void main(String[] args) {
    Jedis jedis = new Jedis("localhost");
    // 创建一个每分钟最多100次请求的限流器
    FixedWindowRateLimiterWithTTL limiter = 
        new FixedWindowRateLimiterWithTTL(jedis, "api:limit:user1", 60, 100);
    
    for (int i = 0; i < 120; i++) {
        if (limiter.allowRequest()) {
            System.out.println("处理请求 " + i);
        } else {
            System.out.println("限流请求 " + i);
        }
    }
    
    jedis.close();
}

优点：实现简单

缺点：

固定窗口算法无法解决临界问题

Redis的过期机制是惰性删除+定期删除，可能导致key实际过期时间与预期有微小差异

重启导致的窗口重置
在超高并发下会成为单点瓶颈