SpringCloud Gateway 通过redis实现限流【SpringCloud系列8】

末蓝、 2023-10-08 21:22 16阅读 0赞

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本文章是系列文章中的一篇

*  [1、SpringCloud 项目基础工程搭建 【SpringCloud系列1】][1_SpringCloud _ _SpringCloud_1]
 *  [2、SpringCloud 集成Nacos注册中心 【SpringCloud系列2】][2_SpringCloud _Nacos_ _SpringCloud_2]
 *  [3、SpringCloud Feign远程调用 【SpringCloud系列3】][3_SpringCloud Feign_ _SpringCloud_3]
 *  [4、SpringCloud Feign远程调用公共类抽取 【SpringCloud系列4】][4_SpringCloud Feign_ _SpringCloud_4]
 *  [5、SpringCloud 整合Gateway服务网关 【SpringCloud系列5】][5_SpringCloud _Gateway_ _SpringCloud_5]
 *  [6、SpringCloud 整合 Spring Security 认证鉴权【SpringCloud系列6】][6_SpringCloud _ Spring Security _SpringCloud_6]
 *  [SpringCloud网关Gateway认证鉴权【SpringCloud系列7】][SpringCloud_Gateway_SpringCloud_7]

在高并发的系统中，往往需要在系统中做限流，常见的限流方式：

*  Hystrix适用线程池隔离，超过线程池的负载，走熔断的逻辑
 *  tomcat容器 通过限制它的线程数
 *  通过时间窗口的平均速度来控制流量

常见的限流算法

*  计数器算法,一般会限制一秒钟的能够通过的请求数
 *  漏桶算法, 算法内部有一个容器，类似生活用到的漏斗，当请求进来时，相当于水倒入漏斗，然后从下端小口慢慢匀速的流出。不管上面流量多大，下面流出的速度始终保持不变
 *  令牌桶算法,令牌桶算法是对漏桶算法的一种改进，桶算法能够限制请求调用的速率，而令牌桶算法能够在限制调用的平均速率的同时还允许一定程度的突发调用  
    ![在这里插入图片描述][8639baa8478d45eab85ff40b2fd464dc.png]  
    本文章实现的是 redis 的限流，无熔断功能

##### 1 在网关项目配置 #####

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

实现KeyResolver接口，UriKeyResolver是对URI进行限流。

import org.springframework.cloud.gateway.filter.ratelimit.KeyResolver;
    import org.springframework.stereotype.Component;
    import org.springframework.web.server.ServerWebExchange;
    import reactor.core.publisher.Mono;
    
    @Component
    public class UriKeyResolver implements KeyResolver {
        
    
        @Override
        public Mono<String> resolve(ServerWebExchange exchange) {
        
            final String path = exchange.getRequest().getURI().getPath();
            System.out.println(path);
            return Mono.just(path);
        }
    }

##### 2 配置指定接口的限制 #####

比如我这里配置 order-service 的接口访问限流

server:
      port: 10001
    spring:
      application:
        name: '@project.name@'
      redis:
        database: 0  # Redis数据库索引（默认为0）
        host: localhost # Redis服务器地址
        port: 6379  # Redis服务器连接端口
        password: 12345678  # Redis服务器连接密码（默认为空）
      cloud:
        nacos:
          server-addr: localhost:8848 # nacos地址
        gateway:
          routes: # 网关路由配置
            - id: order-service # 路由id，自定义，只要唯一即可
              # uri: http://127.0.0.1:8081 # 路由的目标地址 http就是固定地址
              uri: lb://order-service
              predicates:
                - Path=/order/**
              filters:
                - name: RequestRateLimiter
                  args:
                    # 每秒处理多少个平均请求数
                    redis-rate-limiter.replenishRate: 1
                    # 令允许在一秒钟内完成的最大请求数
                    redis-rate-limiter.burstCapacity: 1
                    # 获取 Bean 对象，@Bean的标识，默认bean名称与方法名一样。
                    key-resolver: "#{@uriKeyResolver}"

*  key-resolver 字段中 “\#\{@uriKeyResolver\}” 对应上述配置的UriKeyResolver。  
    然后我这里配置的限流规则是 1秒处理1个平均请求数，然后我使用postman 访问order 接口来查询订单详情
 *  name 字段必须为RequestRateLimiter

连续调用两次，第一次可以正常访问，第二次就会出现 429 错误  
![在这里插入图片描述][93987775136b42c08db9773054537671.png]

##### 3 自定义 429 返回错误 #####

限流过滤器编写在RequestRateLimiterGatewayFilterFactory中，Gateway中配置的RequestRateLimiter正是此过滤器去掉后缀后的结果，所以只需重写此过滤器即可。

import lombok.extern.slf4j.Slf4j;
    import org.springframework.cloud.gateway.filter.GatewayFilter;
    import org.springframework.cloud.gateway.filter.factory.RequestRateLimiterGatewayFilterFactory;
    import org.springframework.cloud.gateway.filter.ratelimit.KeyResolver;
    import org.springframework.cloud.gateway.filter.ratelimit.RateLimiter;
    import org.springframework.cloud.gateway.route.Route;
    import org.springframework.cloud.gateway.support.ServerWebExchangeUtils;
    import org.springframework.core.io.buffer.DataBuffer;
    import org.springframework.http.HttpStatus;
    import org.springframework.http.server.reactive.ServerHttpResponse;
    import org.springframework.stereotype.Component;
    import reactor.core.publisher.Mono;
    
    import java.nio.charset.StandardCharsets;
    import java.util.Map;
    
    @Slf4j
    @Component
    public class GatewayRequestRateLimiterGatewayFilterFactory extends RequestRateLimiterGatewayFilterFactory {
        
    
        private final RateLimiter defaultRateLimiter;
    
        private final KeyResolver defaultKeyResolver;
    
        public GatewayRequestRateLimiterGatewayFilterFactory(RateLimiter defaultRateLimiter, KeyResolver defaultKeyResolver) {
        
            super(defaultRateLimiter, defaultKeyResolver);
            this.defaultRateLimiter = defaultRateLimiter;
            this.defaultKeyResolver = defaultKeyResolver;
        }
    
        @Override
        public GatewayFilter apply(Config config) {
        
            KeyResolver resolver = getOrDefault(config.getKeyResolver(), defaultKeyResolver);
            RateLimiter<Object> limiter = getOrDefault(config.getRateLimiter(), defaultRateLimiter);
            return (exchange, chain) -> resolver.resolve(exchange).flatMap(key -> {
        
                String routeId = config.getRouteId();
                if (routeId == null) {
        
                    Route route = exchange.getAttribute(ServerWebExchangeUtils.GATEWAY_ROUTE_ATTR);
                    routeId = route.getId();
                }
                String finalRouteId = routeId;
                return limiter.isAllowed(routeId, key).flatMap(response -> {
        
                    for (Map.Entry<String, String> header : response.getHeaders().entrySet()) {
        
                        exchange.getResponse().getHeaders().add(header.getKey(), header.getValue());
                    }
                    if (response.isAllowed()) {
        
                        return chain.filter(exchange);
                    }
                    log.warn("已限流: {}", finalRouteId);
                    ServerHttpResponse httpResponse = exchange.getResponse();
                    //修改code为500
                    httpResponse.setStatusCode(HttpStatus.INTERNAL_SERVER_ERROR);
                    if (!httpResponse.getHeaders().containsKey("Content-Type")) {
        
                        httpResponse.getHeaders().add("Content-Type", "application/json");
                    }
                    //此处无法触发全局异常处理，手动返回
                    DataBuffer buffer = httpResponse.bufferFactory().wrap(("{\n"
                            + "  \"code\": \"1414\","
                            + "  \"message\": \"服务器限流\","
                            + "  \"data\": \"Server throttling\","
                            + "  \"success\": false"
                            + "}").getBytes(StandardCharsets.UTF_8));
                    return httpResponse.writeWith(Mono.just(buffer));
                });
            });
        }
    
        private <T> T getOrDefault(T configValue, T defaultValue) {
        
            return (configValue != null) ? configValue : defaultValue;
        }
    }

然后修改限流配置，修改 name: GatewayRequestRateLimiter

server:
      port: 10001
    spring:
      application:
        name: '@project.name@'
      redis:
        database: 0  # Redis数据库索引（默认为0）
        host: localhost # Redis服务器地址
        port: 6379  # Redis服务器连接端口
        password: 12345678  # Redis服务器连接密码（默认为空）
      cloud:
        nacos:
          server-addr: localhost:8848 # nacos地址
        gateway:
          routes: # 网关路由配置
            - id: order-service # 路由id，自定义，只要唯一即可
              # uri: http://127.0.0.1:8081 # 路由的目标地址 http就是固定地址
              uri: lb://order-service
              predicates:
                - Path=/order/**
              filters:
                - name: GatewayRequestRateLimiter 
                  args:
                    # 每秒处理多少个平均请求数
                    redis-rate-limiter.replenishRate: 1
                    # 令允许在一秒钟内完成的最大请求数
                    redis-rate-limiter.burstCapacity: 1
                    # 获取 Bean 对象，@Bean的标识，默认bean名称与方法名一样。
                    key-resolver: "#{@uriKeyResolver}"

然后再次测试限流

![在这里插入图片描述][c17241b25bd44b5aa5954c88aa132f66.png]

本项目源码 [https://gitee.com/android.long/spring-cloud-biglead/tree/master/biglead-api-08-redis-reactive][https_gitee.com_android.long_spring-cloud-biglead_tree_master_biglead-api-08-redis-reactive]  
如果有兴趣可以关注一下公众号 biglead ,每周都会有 java、Flutter、小程序、js 、英语相关的内容分享

[1_SpringCloud _ _SpringCloud_1]: https://biglead.blog.csdn.net/article/details/129668121
[2_SpringCloud _Nacos_ _SpringCloud_2]: https://biglead.blog.csdn.net/article/details/129672545
[3_SpringCloud Feign_ _SpringCloud_3]: https://biglead.blog.csdn.net/article/details/129674404
[4_SpringCloud Feign_ _SpringCloud_4]: https://blog.csdn.net/zl18603543572/article/details/129675612
[5_SpringCloud _Gateway_ _SpringCloud_5]: https://biglead.blog.csdn.net/article/details/129678919
[6_SpringCloud _ Spring Security _SpringCloud_6]: https://biglead.blog.csdn.net/article/details/129687071
[SpringCloud_Gateway_SpringCloud_7]: https://blog.csdn.net/zl18603543572/article/details/129699896
[8639baa8478d45eab85ff40b2fd464dc.png]: https://img-blog.csdnimg.cn/8639baa8478d45eab85ff40b2fd464dc.png
[93987775136b42c08db9773054537671.png]: https://img-blog.csdnimg.cn/93987775136b42c08db9773054537671.png
[c17241b25bd44b5aa5954c88aa132f66.png]: https://img-blog.csdnimg.cn/c17241b25bd44b5aa5954c88aa132f66.png
[https_gitee.com_android.long_spring-cloud-biglead_tree_master_biglead-api-08-redis-reactive]: https://gitee.com/android.long/spring-cloud-biglead/tree/master/biglead-api-08-redis-reactive