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redis如何實現分布式限流

小億
116
2023-09-09 11:34:52
欄目: 云計算

Redis可以使用令牌桶算法來實現分布式限流。令牌桶算法是一種常用的限流算法，它通過維護一個固定容量的令牌桶，每秒鐘往桶里放入一定數量的令牌。當請求到達時，如果令牌桶中有足夠的令牌，那么允許請求通過并消耗一個令牌；如果令牌桶中沒有足夠的令牌，則拒絕請求。

以下是使用Redis實現分布式限流的步驟：

  1. 使用Redis的Lua腳本編寫一個令牌桶算法的限流器。Lua腳本可以在Redis服務器端執(zhí)行，可以保證原子性。以下是一個簡單的令牌桶算法的Lua腳本示例：
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. 在代碼中調用該Lua腳本，傳入限流器的唯一標識符、限流器的容量、限流器的速率以及當前時間戳作為參數，獲取限流結果。
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]\n" +
"local capacity = tonumber(ARGV[1])\n" +
"local rate = tonumber(ARGV[2])\n" +
"local now = tonumber(ARGV[3])\n" +
"\n" +
"local tokens_key = key .. \":tokens\"\n" +
"local timestamp_key = key .. \":timestamp\"\n" +
"\n" +
"local tokens = tonumber(redis.call(\"get\", tokens_key))\n" +
"if not tokens then\n" +
"    tokens = capacity\n" +
"end\n" +
"\n" +
"local last_refreshed = tonumber(redis.call(\"get\", timestamp_key))\n" +
"if not last_refreshed then\n" +
"    last_refreshed = now\n" +
"end\n" +
"\n" +
"local delta = math.max(0, now - last_refreshed)\n" +
"local filled_tokens = math.min(capacity, tokens + delta * rate)\n" +
"local allowed = filled_tokens >= 1\n" +
"\n" +
"local new_tokens = filled_tokens\n" +
"local new_timestamp = last_refreshed\n" +
"if allowed then\n" +
"    new_tokens = filled_tokens - 1\n" +
"    new_timestamp = now\n" +
"end\n" +
"\n" +
"redis.call(\"set\", tokens_key, new_tokens)\n" +
"redis.call(\"set\", timestamp_key, new_timestamp)\n" +
"\n" +
"return allowed",
1,
key,
Integer.toString(capacity),
Integer.toString(rate),
Long.toString(now)
);
return (Boolean) result;
}
}
}
  1. 在需要進行限流的地方調用RedisRateLimiter的allowRequest方法進行

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