以上文章演示了Gateway的部分功能的自定义开发，API网关还承担了流量入口的角色，为了保护后端微服务不被高峰流量冲垮，API网关可以进行限流、熔断、降级处理。熔断、降级有Hystrix等组件支持，限流策略也有RequestRateLimiter，我们这篇文章主要演示如何自定义限流策略，学会了自定义限流后，就可以开发更多满足自己业务需求的功能了。
| 开发依赖 | 版本 |
|---|---|
| Spring Boot | 2.7.0 |
| Spring Cloud | 2021.0.1 |
| Spring Cloud Alibaba | 2021.0.1.0 |
本文继续接着上一篇文章往下讲，代码和配置都是接着上一篇，如有看不懂的地方可以把前面关于Gateway的内容过目一下。
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import org.springframework.cloud.gateway.filter.GatewayFilter;
import org.springframework.cloud.gateway.filter.factory.AbstractGatewayFilterFactory;
import org.springframework.http.HttpStatus;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Mono;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;
@Component
@Slf4j
public class DemoRateLimitPerSecondGatewayFilterFactory extends AbstractGatewayFilterFactory<DemoRateLimitPerSecondGatewayFilterFactory.Config> {
private final Map<Long, Map<String, AtomicInteger>> rateLimitMap = new ConcurrentHashMap<>();
public DemoRateLimitPerSecondGatewayFilterFactory() {
super(Config.class);
}
@Override
public List<String> shortcutFieldOrder() {
// yml配置文件中参数的赋值顺序
return Arrays.asList("limit");
}
@Override
public GatewayFilter apply(Config config) {
return (exchange, chain) -> {
String path = exchange.getRequest().getPath().toString();
long nowSecond = System.currentTimeMillis() / 1000;
Map<String, AtomicInteger> apiCount = rateLimitMap.computeIfAbsent(nowSecond, k->new HashMap<String, AtomicInteger>(){{
put(path, new AtomicInteger(1));
}});
AtomicInteger count = apiCount.computeIfAbsent(path, k->new AtomicInteger(1));
int countValue = count.get();
log.debug("count: {}", countValue);
if(countValue > config.getLimit()) {
exchange.getResponse().setStatusCode(HttpStatus.TOO_MANY_REQUESTS);
return exchange.getResponse().setComplete();
}
count.addAndGet(1);
return chain.filter(exchange).then(Mono.fromRunnable(()->{
rateLimitMap.keySet().stream().filter(time->time<nowSecond).forEach(rateLimitMap::remove);
}));
};
}
@Data
public static class Config {
private Integer limit;
}
}
这个过滤器可以根据每秒请求次数进行限制，超过指定的次数，则返回429状态码
server:
port: 8081
spring:
application:
name: demo-gateway
cloud:
gateway:
#路由配置
routes:
- id: baidu
uri: https://www.baidu.com
predicates:
- Path=/baidu
filters:
- DemoRateLimitPerSecond=1
- StripPrefix=1
- Demo=true,hello,world
- name: Demo
args:
enabled: true
arg1: hello2
arg2: world2
上面配置了DemoRateLimitPerSecond限流策略，每秒1个请求
在浏览器输入http://localhost:8081/baidu, 按F5刷新几次
出现以上图片内容，表示限流策略已经生效了。
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import org.springframework.cloud.gateway.filter.GatewayFilter;
import org.springframework.cloud.gateway.filter.factory.AbstractGatewayFilterFactory;
import org.springframework.http.HttpStatus;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Mono;
import java.time.LocalDate;
import java.time.ZoneId;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;
@Component
@Slf4j
public class DemoRateLimitPerDayGatewayFilterFactory extends AbstractGatewayFilterFactory<DemoRateLimitPerDayGatewayFilterFactory.Config> {
private final Map<Long, Map<String, AtomicInteger>> rateLimitMap = new ConcurrentHashMap<>();
public DemoRateLimitPerDayGatewayFilterFactory() {
super(Config.class);
}
@Override
public List<String> shortcutFieldOrder() {
// yml配置文件中参数的赋值顺序
return Arrays.asList("limit");
}
@Override
public GatewayFilter apply(Config config) {
return (exchange, chain) -> {
String path = exchange.getRequest().getPath().toString();
long nowSecond = LocalDate.now().atStartOfDay().atZone(ZoneId.systemDefault()).toInstant().getEpochSecond();
Map<String, AtomicInteger> apiCount = rateLimitMap.computeIfAbsent(nowSecond, k->new HashMap<String, AtomicInteger>(){{
put(path, new AtomicInteger(1));
}});
AtomicInteger count = apiCount.computeIfAbsent(path, k->new AtomicInteger(1));
int countValue = count.get();
log.debug("count: {}", countValue);
if(countValue > config.getLimit()) {
exchange.getResponse().setStatusCode(HttpStatus.TOO_MANY_REQUESTS);
return exchange.getResponse().setComplete();
}
count.addAndGet(1);
return chain.filter(exchange).then(Mono.fromRunnable(()->{
rateLimitMap.keySet().stream().filter(time->time<nowSecond).forEach(rateLimitMap::remove);
}));
};
}
@Data
public static class Config {
private Integer limit;
}
}
这个过滤器可以根据每天请求次数进行限制，超过指定的次数，则返回429状态码
server:
port: 8081
spring:
application:
name: demo-gateway
cloud:
gateway:
#路由配置
routes:
- id: baidu
uri: https://www.baidu.com
predicates:
- Path=/baidu
filters:
- DemoRateLimitPerSecond=10
- DemoRateLimitPerDay=2
- StripPrefix=1
- Demo=true,hello,world
- name: Demo
args:
enabled: true
arg1: hello2
arg2: world2
上面配置了
在浏览器输入http://localhost:8081/baidu, 按F5刷新后
出现以上图片内容，表示限流策略已经生效了。
想验证细节的小伙伴可以在对应的过滤器进行断点，查看具体的次数值，控制台也会输出请求的次数
以上演示了如何在Gateway中实现自定义限流策略，并且简单实现了每秒、每天的限流算法，掌握之后，大家就可以结合自己实际的业务场景进行愉快的开发了。Gateway本身也提供了一些强大的限流策略，比如令牌桶算法的限流策略，是一个基于Redis实现的漏桶算法，下一篇会专门开一篇讲Gateway的令牌桶算法策略。