Spring Cloud Gateway 限流操做

開發高併發系統時有三把利器用來保護系統:緩存、降級和限流。react

API網關做爲全部請求的入口,請求量大,咱們能夠經過對併發訪問的請求進行限速來保護系統的可用性。redis

經常使用的限流算法好比有令牌桶算法,漏桶算法,計數器算法等。算法

在Zuul中咱們能夠本身去實現限流的功能(Zuul中如何限流在個人書《Spring Cloud微服務-全棧技術與案例解析》中有詳細講解),Spring Cloud Gateway的出現自己就是用來替代Zuul的。spring

要想替代那確定得有強大的功能,除了性能上的優點以外,Spring Cloud Gateway還提供了不少新功能,好比今天咱們要講的限流操做,使用起來很是簡單,今天咱們就來學習在如何在Spring Cloud Gateway中進行限流操做。api

目前限流提供了基於Redis的實現,咱們須要增長對應的依賴:緩存

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-redis-reactive</artifactId>
</dependency>

能夠經過KeyResolver來指定限流的Key,好比咱們須要根據用戶來作限流,IP來作限流等等。微信

IP限流併發

@Bean
public KeyResolver ipKeyResolver() {
    return exchange -> Mono.just(exchange.getRequest().getRemoteAddress().getHostName());
}

經過exchange對象能夠獲取到請求信息,這邊用了HostName,若是你想根據用戶來作限流的話這邊能夠獲取當前請求的用戶ID或者用戶名就能夠了,好比:ide

用戶限流
使用這種方式限流,請求路徑中必須攜帶userId參數。spring-boot

@Bean
KeyResolver userKeyResolver() {
    return exchange -> Mono.just(exchange.getRequest().getQueryParams().getFirst("userId"));
}

接口限流
獲取請求地址的uri做爲限流key。

@Bean
KeyResolver apiKeyResolver() {
    return exchange -> Mono.just(exchange.getRequest().getPath().value());
}

而後配置限流的過濾器信息:

server:
  port: 8084
spring:
  redis:
    host: 127.0.0.1
    port: 6379
  cloud:
    gateway:
      routes:
      - id: fsh-house
        uri: lb://fsh-house
        predicates:
        - Path=/house/**
        filters:
        - name: RequestRateLimiter
          args:
            redis-rate-limiter.replenishRate: 10
            redis-rate-limiter.burstCapacity: 20
            key-resolver: "#{@ipKeyResolver}"
  • filter名稱必須是RequestRateLimiter
  • redis-rate-limiter.replenishRate:容許用戶每秒處理多少個請求
  • redis-rate-limiter.burstCapacity:令牌桶的容量,容許在一秒鐘內完成的最大請求數
  • key-resolver:使用SpEL按名稱引用bean
    能夠訪問接口進行測試,這時候Redis中會有對應的數據:
127.0.0.1:6379> keys *
1) "request_rate_limiter.{localhost}.timestamp"
2) "request_rate_limiter.{localhost}.tokens"

大括號中就是咱們的限流Key,這邊是IP,本地的就是localhost

  • timestamp:存儲的是當前時間的秒數,也就是System.currentTimeMillis() / 1000或者Instant.now().getEpochSecond()
  • tokens:存儲的是當前這秒鐘的對應的可用的令牌數量

Spring Cloud Gateway目前提供的限流仍是相對比較簡單的,在實際中咱們的限流策略會有不少種狀況,好比:

  • 每一個接口的限流數量不一樣,能夠經過配置中心動態調整
  • 超過的流量被拒絕後能夠返回固定的格式給調用方
  • 對某個服務進行總體限流(這個你們能夠思考下用Spring Cloud Gateway如何實現,其實很簡單)
  • ……
    固然咱們也能夠經過從新RedisRateLimiter來實現本身的限流策略,這個咱們後面再進行介紹。

限流源碼

// routeId也就是咱們的fsh-house,id就是限流的key,也就是localhost。
public Mono<Response> isAllowed(String routeId, String id) {
    // 會判斷RedisRateLimiter是否初始化了
    if (!this.initialized.get()) {
        throw new IllegalStateException("RedisRateLimiter is not initialized");
    }
    // 獲取routeId對應的限流配置
    Config routeConfig = getConfig().getOrDefault(routeId, defaultConfig);

    if (routeConfig == null) {
        throw new IllegalArgumentException("No Configuration found for route " + routeId);
    }

    // 容許用戶每秒作多少次請求
    int replenishRate = routeConfig.getReplenishRate();

    // 令牌桶的容量,容許在一秒鐘內完成的最大請求數
    int burstCapacity = routeConfig.getBurstCapacity();

    try {
        // 限流key的名稱(request_rate_limiter.{localhost}.timestamp,request_rate_limiter.{localhost}.tokens)
        List<String> keys = getKeys(id);

        // The arguments to the LUA script. time() returns unixtime in seconds.
        List<String> scriptArgs = Arrays.asList(replenishRate + "", burstCapacity + "",
                Instant.now().getEpochSecond() + "", "1");
        // allowed, tokens_left = redis.eval(SCRIPT, keys, args)
        // 執行LUA腳本
        Flux<List<Long>> 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<Long>(), (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) {
        log.error("Error determining if user allowed from redis", e);
    }
    return Mono.just(new Response(true, getHeaders(routeConfig, -1L)));
}

LUA腳本在:
Spring Cloud Gateway 限流操做
WX20180715-150447@2x.png

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)
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 }

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Spring Cloud Gateway 限流操做

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