springcloudgateway限流 redis,springcloud gateway限流

在搭建前，我们需要了解一下springcloud-getway限流的策略：
有计算器算法、漏桶算法、令牌桶算法；
Spring Cloud Gateway限流
我搭建了两台服务器，一台是getway 一台是demo，我的想法是通过getway去调用demo服务器

getway 服务器搭建：
引入getway jar

<parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>2.1.8.RELEASE</version> <relativePath/> <!-- lookup parent from repository --> </parent> <groupId>com.study</groupId> <artifactId>spring-cloud-getway</artifactId> <version>0.0.1-SNAPSHOT</version> <name>spring-cloud-getway</name> <description>Demo project for Spring Boot</description> <properties> <java.version>1.8</java.version> <spring-cloud.version>Greenwich.SR3</spring-cloud.version> </properties> <dependencies> <!--getway网关--> <dependency> <groupId>org.springframework.cloud</groupId> <artifactId>spring-cloud-starter-gateway</artifactId> </dependency> <!--限流 redis--> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-data-redis-reactive</artifactId> <version>2.0.5.RELEASE</version> </dependency> <dependency> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> <optional>true</optional> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-test</artifactId> <scope>test</scope> </dependency> </dependencies> <dependencyManagement> <dependencies> <dependency> <groupId>org.springframework.cloud</groupId> <artifactId>spring-cloud-dependencies</artifactId> <version>${spring-cloud.version}</version> <type>pom</type> <scope>import</scope> </dependency> </dependencies> </dependencyManagement> <build> <plugins> <plugin> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-maven-plugin</artifactId> <configuration> <excludes> <exclude> <groupId>org.projectlombok</groupId> <artifactId>lombok</artifactId> </exclude> </excludes> </configuration> </plugin> </plugins> </build> <repositories> <repository> <id>spring-milestones</id> <name>Spring Milestones</name> <url>https://repo.spring.io/libs-milestone</url> <snapshots> <enabled>false</enabled> </snapshots> </repository> </repositories>

这里我们需要注意的地方是：
springboot的版本号和spring-boot-starter-data-redis-reactive的版本号；
我这里使用的是springboot 2.1.8 的，如果版本号是2.2以上的spring-boot-starter-data-redis-reactive的版本号也要做好调整不然启动会报错；

配置文件application.yml：

server: port: 9000spring: main: allow-bean-definition-overriding: true cloud: gateway: routes: - id: first_route #自定义id uri: http://192.168.0.74:8080 #ָip转发服务器ip predicates: - Path=/demo/** #请求路径 filters: - name: RequestRateLimiter args: # 令牌桶每秒填充平均速率, 允许用户每秒处理多少个请求。 redis-rate-limiter.replenishRate: 1 # 令牌桶的容量，允许在1s内完成的最大请求数。 redis-rate-limiter.burstCapacity: 2 # 使用SpEL表达式从Spring容器中获取Bean对象, 查看RateLimiteConfig实现类中的方法名 key-resolver: "#{@pathKeyResolver}" #key-resolver: "#{@ipKeyResolver}" #key-resolver: "#{@userKeyResolver}" application: name: gateway-limiter redis: host: 192.168.0.75 port: 6379 password: 123456 database: 0 timeout: 1800000

配置RateLimiteConfig文件

package com.study.config;import org.springframework.cloud.gateway.filter.ratelimit.KeyResolver;import org.springframework.context.annotation.Bean;import org.springframework.context.annotation.Configuration;import org.springframework.context.annotation.Primary;import reactor.core.publisher.Mono;/** * 限流配置KeyResolver——有三种写法(接口限流/ip限流/用户限流) */@Configurationpublic class RateLimiteConfig { /** * 接口限流：根据请求路径限流 * @return */ /* 如果不使用@Primary注解，会报如下错误，需要注意 Description: Parameter 1 of method requestRateLimiterGatewayFilterFactory in org.springframework.cloud.gateway.config.GatewayAutoConfiguration required a single bean, but 3 were found: - pathKeyResolver: defined by method 'pathKeyResolver' in class path resource [com/mkevin/gateway/config/RateLimiteConfig.class] - ipKeyResolver: defined by method 'ipKeyResolver' in class path resource [com/mkevin/gateway/config/RateLimiteConfig.class] - userKeyResolver: defined by method 'userKeyResolver' in class path resource [com/mkevin/gateway/config/RateLimiteConfig.class] Action: Consider marking one of the beans as @Primary, updating the consumer to accept multiple beans, or using @Qualifier to identify the bean that should be consumed */ @Bean @Primary public KeyResolver pathKeyResolver() { //写法1 return exchange -> Mono.just( exchange.getRequest() .getPath() .toString() ); /* //写法2 return new KeyResolver() { @Override public Mono<String> resolve(ServerWebExchange exchange) { return Mono.just(exchange.getRequest() .getPath() .toString()); } }; */ } /** * 根据请求IP限流 * @return */ @Bean public KeyResolver ipKeyResolver() { return exchange -> Mono.just( exchange.getRequest() .getRemoteAddress() .getHostName() ); } /** * 根据请求参数中的userId进行限流 * * 请求地址写法：http://localhost:8801/rate/123?userId=lisi * * @return */ @Bean public KeyResolver userKeyResolver() { return exchange -> Mono.just( exchange.getRequest() .getQueryParams() .getFirst("userId") ); }}

从RateLimiteConfig 配置文件中可以清晰的看出，getaway的限流策略：对路径的限流，对ip限流，对参数限流。这些方式都可以在后面我们实现秒杀的时候其他一定的帮助；
为什么会引入redis呢？
在我们做压力测试的时候，并发量超过我们设置的阈值的时候，会把 错误信息存储到redis中

RequestRateLimiter是使用Redis来进行限流的，并在redis中存储了2个key

另一台服务demo搭建：
主要是接口路径：

我们可以清楚的看到getway服务器在application.yml中配置了
demo的服务器ip已经请求路径

限流配置：

这里采用的是令牌桶算法，配置方式都写了备注；