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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！
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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 Mono isAllowed(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！