引入redis的reactive依赖
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis-reactive</artifactId> <version>2.6.2</version> </dependency>定义一下限流的具体维度
@Configurationpublic class DemoConfiguration { @Bean public KeyResolver pathKeyResolver() { return exchange -> Mono.just(exchange.getRequest().getPath().toString()); }}两种形式，一种是application.yml中配置
spring: redis: host: 127.0.0.1 port: 6379 cloud: gateway: routes: - id: routeB uri: http://www.b.com predicates: - Path=/pathB filters: - name: RequestRateLimiter args: # 每秒解决多少个均匀申请数 redis-rate-limiter.replenishRate: 2 # 令容许在一秒钟内实现的最大申请数 redis-rate-limiter.burstCapacity: 2 # 获取 Bean 对象，@Bean的标识，默认bean名称与办法名一样。 key-resolver: "#{@apiKeyResolver}"另一种在RouteDefinitionRepository的实现中，即动静路由的实现中
FilterDefinition filter3 = new FilterDefinition(); filter3.setName("RequestRateLimiter"); Map<String, String> map3 = new HashMap<>(); map3.put("redis-rate-limiter.replenishRate", "3"); map3.put("redis-rate-limiter.burstCapacity", "2"); map3.put("key-resolver", "#{@pathKeyResolver}"); filter3.setArgs(map3);能够在本地redis中应用monitor命令观察所执行的内容
127.0.0.1:6379> monitorOK那么来看一下同一秒中间断执行两次申请的状况：
1643107233.014412 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"1643107233.014451 [0 lua] "TIME"1643107233.014462 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"1643107233.014469 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"1643107233.014484 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "1"1643107233.014495 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107233"1643107233.326166 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"1643107233.326219 [0 lua] "TIME"1643107233.326228 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"1643107233.326235 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"1643107233.326251 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "0"1643107233.326262 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107233"再看一下同一秒内间断三次的状况：
1643107474.188667 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"1643107474.188704 [0 lua] "TIME"1643107474.188712 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"1643107474.188718 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"1643107474.188733 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "1"1643107474.188745 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107474"1643107474.347245 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"1643107474.347283 [0 lua] "TIME"1643107474.347291 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"1643107474.347298 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"1643107474.347313 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "0"1643107474.347324 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107474"1643107474.494758 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"1643107474.494793 [0 lua] "TIME"1643107474.494801 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"1643107474.494808 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"1643107474.494823 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "0"1643107474.494834 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107474"第三次的申请， 曾经被限流了， 返回了http code 429
执行的lua脚本具体内容从源码中能够看到：
redis.replicate_commands()local tokens_key = KEYS[1]local timestamp_key = KEYS[2]--redis.log(redis.LOG_WARNING, "tokens_key " .. tokens_key)local rate = tonumber(ARGV[1])local capacity = tonumber(ARGV[2])local now = redis.call('TIME')[1]local requested = tonumber(ARGV[4])local fill_time = capacity/ratelocal ttl = math.floor(fill_time*2)--redis.log(redis.LOG_WARNING, "rate " .. ARGV[1])--redis.log(redis.LOG_WARNING, "capacity " .. ARGV[2])--redis.log(redis.LOG_WARNING, "now " .. now)--redis.log(redis.LOG_WARNING, "requested " .. ARGV[4])--redis.log(redis.LOG_WARNING, "filltime " .. fill_time)--redis.log(redis.LOG_WARNING, "ttl " .. ttl)local last_tokens = tonumber(redis.call("get", tokens_key))if last_tokens == nil then last_tokens = capacityend--redis.log(redis.LOG_WARNING, "last_tokens " .. last_tokens)local last_refreshed = tonumber(redis.call("get", timestamp_key))if last_refreshed == nil then last_refreshed = 0end--redis.log(redis.LOG_WARNING, "last_refreshed " .. last_refreshed)local delta = math.max(0, now-last_refreshed)local filled_tokens = math.min(capacity, last_tokens+(delta*rate))local allowed = filled_tokens >= requestedlocal new_tokens = filled_tokenslocal allowed_num = 0if allowed then new_tokens = filled_tokens - requested allowed_num = 1end--redis.log(redis.LOG_WARNING, "delta " .. delta)--redis.log(redis.LOG_WARNING, "filled_tokens " .. filled_tokens)--redis.log(redis.LOG_WARNING, "allowed_num " .. allowed_num)--redis.log(redis.LOG_WARNING, "new_tokens " .. new_tokens)if ttl > 0 then redis.call("setex", tokens_key, ttl, new_tokens) redis.call("setex", timestamp_key, ttl, now)end-- return { allowed_num, new_tokens, capacity, filled_tokens, requested, new_tokens }return { allowed_num, new_tokens }