扫二维码与项目经理沟通
我们在微信上24小时期待你的声音
解答本文疑问/技术咨询/运营咨询/技术建议/互联网交流
这篇文章主要讲解了“如何理解spring-cloud-gateway自带redis限流脚本”,文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习“如何理解spring-cloud-gateway自带redis限流脚本”吧!
创新互联公司10多年成都企业网站定制服务;为您提供网站建设,网站制作,网页设计及高端网站定制服务,成都企业网站定制及推广,对成都水泥搅拌车等多个行业拥有多年的网站制作经验的网站建设公司。
filter入口: org.springframework.cloud.gateway.filter.factory.RequestRateLimiterGatewayFilterFactory#apply
限流判断入口: org.springframework.cloud.gateway.filter.ratelimit.RedisRateLimiter#isAllowed
@Override @SuppressWarnings("unchecked") public MonoisAllowed(String routeId, String id) { if (!this.initialized.get()) { throw new IllegalStateException("RedisRateLimiter is not initialized"); } Config routeConfig = loadConfiguration(routeId); // How many requests per second do you want a user to be allowed to do? int replenishRate = routeConfig.getReplenishRate(); // How much bursting do you want to allow? int burstCapacity = routeConfig.getBurstCapacity(); try { List keys = getKeys(id); // The arguments to the LUA script. time() returns unixtime in seconds. List scriptArgs = Arrays.asList(replenishRate + "", burstCapacity + "", Instant.now().getEpochSecond() + "", "1"); // allowed, tokens_left = redis.eval(SCRIPT, keys, args) Flux > flux = this.redisTemplate.execute(this.script, keys, scriptArgs); // .log("redisratelimiter", Level.FINER); return flux.onErrorResume(throwable -> Flux.just(Arrays.asList(1L, -1L))) .reduce(new ArrayList
(), (longs, l) -> { longs.addAll(l); return longs; }).map(results -> { boolean allowed = results.get(0) == 1L; Long tokensLeft = results.get(1); Response response = new Response(allowed, getHeaders(routeConfig, tokensLeft)); if (log.isDebugEnabled()) { log.debug("response: " + response); } return response; }); } catch (Exception e) { /* * We don't want a hard dependency on Redis to allow traffic. Make sure to set * an alert so you know if this is happening too much. Stripe's observed * failure rate is 0.01%. */ log.error("Error determining if user allowed from redis", e); } return Mono.just(new Response(true, getHeaders(routeConfig, -1L))); }
lua脚本加载入口: org.springframework.cloud.gateway.config.GatewayRedisAutoConfiguration#redisRequestRateLimiterScript
@Bean @SuppressWarnings("unchecked") public RedisScript redisRequestRateLimiterScript() { DefaultRedisScript redisScript = new DefaultRedisScript<>(); redisScript.setScriptSource(new ResourceScriptSource( new ClassPathResource("META-INF/scripts/request_rate_limiter.lua"))); redisScript.setResultType(List.class); return redisScript; }
request_rate_limiter.lua脚本
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 = tonumber(ARGV[3]) local requested = tonumber(ARGV[4]) local fill_time = capacity/rate local 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 " .. ARGV[3]) --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 = capacity end --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 = 0 end --redis.log(redis.LOG_WARNING, "last_refreshed " .. last_refreshed) local delta = math.max(0, now-last_refreshed) --重点是这里,rate是相对于capacity而言,如果大于等于capacity,那么每秒的并发量就是capacity, --如果小于capacity,那么才会每秒固定添加rate个令牌到桶中。 --正常限流建议设置小于capacity,否则当capacity瞬间用完,这个时候说明已经达到了系统最大并发阀值, --下一秒瞬间又恢复最大令牌桶阀值,速率过大反而起不到限流作用。 local filled_tokens = math.min(capacity, last_tokens+(delta*rate)) local allowed = filled_tokens >= requested local new_tokens = filled_tokens local allowed_num = 0 if allowed then new_tokens = filled_tokens - requested allowed_num = 1 end --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) redis.call("setex", tokens_key, ttl, new_tokens) redis.call("setex", timestamp_key, ttl, now) return { allowed_num, new_tokens }
感谢各位的阅读,以上就是“如何理解spring-cloud-gateway自带redis限流脚本”的内容了,经过本文的学习后,相信大家对如何理解spring-cloud-gateway自带redis限流脚本这一问题有了更深刻的体会,具体使用情况还需要大家实践验证。这里是创新互联,小编将为大家推送更多相关知识点的文章,欢迎关注!
我们在微信上24小时期待你的声音
解答本文疑问/技术咨询/运营咨询/技术建议/互联网交流