redis怎样实现散布式限流

Redis可使用令牌桶算法来实现散布式限流。令牌桶算法是一种经常使用的限流算法，它通过保护一个固定容量的令牌桶，每秒钟往桶里放入一定数量的令牌。当要求到达时，如果令牌桶中有足够的令牌，那末允许要求通过并消耗一个令牌；如果令牌桶中没有足够的令牌，则谢绝要求。
以下是使用Redis实现散布式限流的步骤：
1. 使用Redis的Lua脚本编写一个令牌桶算法的限流器。Lua脚本可以在Redis服务器端履行，可以保证原子性。以下是一个简单的令牌桶算法的Lua脚本示例：
```lua
local key = KEYS[1]
local capacity = tonumber(ARGV[1])
local rate = tonumber(ARGV[2])
local now = tonumber(ARGV[3])
local tokens_key = key .. ":tokens"
local timestamp_key = key .. ":timestamp"
local tokens = tonumber(redis.call("get", tokens_key))
if not tokens then
tokens = capacity
end
local last_refreshed = tonumber(redis.call("get", timestamp_key))
if not last_refreshed then
last_refreshed = now
end
local delta = math.max(0, now - last_refreshed)
local filled_tokens = math.min(capacity, tokens + delta * rate)
local allowed = filled_tokens >= 1
local new_tokens = filled_tokens
local new_timestamp = last_refreshed
if allowed then
new_tokens = filled_tokens - 1
new_timestamp = now
end
redis.call("set", tokens_key, new_tokens)
redis.call("set", timestamp_key, new_timestamp)
return allowed
```
2. 在代码中调用该Lua脚本，传入限流器的唯一标识符、限流器的容量、限流器的速率和当前时间戳作为参数，获得限流结果。
```java
import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
public class RedisRateLimiter {
private JedisPool jedisPool;
public RedisRateLimiter(JedisPool jedisPool) {
this.jedisPool = jedisPool;
}
public boolean allowRequest(String key, int capacity, int rate) {
try (Jedis jedis = jedisPool.getResource()) {
long now = System.currentTimeMillis();
Object result = jedis.eval(
"local key = KEYS[1] " +
"local capacity = tonumber(ARGV[1]) " +
"local rate = tonumber(ARGV[2]) " +
"local now = tonumber(ARGV[3]) " +
" " +
"local tokens_key = key .. ":tokens" " +
"local timestamp_key = key .. ":timestamp" " +
" " +
"local tokens = tonumber(redis.call("get", tokens_key)) " +
"if not tokens then " +
" tokens = capacity " +
"end " +
" " +
"local last_refreshed = tonumber(redis.call("get", timestamp_key)) " +
"if not last_refreshed then " +
" last_refreshed = now " +
"end " +
" " +
"local delta = math.max(0, now - last_refreshed) " +
"local filled_tokens = math.min(capacity, tokens + delta * rate) " +
"local allowed = filled_tokens >= 1 " +
" " +
"local new_tokens = filled_tokens " +
"local new_timestamp = last_refreshed " +
"if allowed then " +
" new_tokens = filled_tokens - 1 " +
" new_timestamp = now " +
"end " +
" " +
"redis.call("set", tokens_key, new_tokens) " +
"redis.call("set", timestamp_key, new_timestamp) " +
" " +
"return allowed",
1,
key,
Integer.toString(capacity),
Integer.toString(rate),
Long.toString(now)
);
return (Boolean) result;
}
}
}
```
3. 在需要进行限流的地方调用RedisRateLimiter的allowRequest方法进行