限流一般有两个实现方式，令牌桶和漏桶。
金牌桶是初始化令牌（容器）的个数，通过拿走里边的令牌就能通过， 没有令牌不能报错，可以设置向容器中增加令牌的速度和最大个数
漏桶是向里边放入请求，当请求数量达到最大值后，丢弃，漏桶中的数据以一定速度流出，没有则不流出
金牌桶实现方式如下：
pom
<dependency>
<groupId>com.github.vladimir-bukhtoyarov</groupId>
<artifactId>bucket4j-core</artifactId>
<version>4.0.0</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis-reactive</artifactId>
</dependency>创建下边类并且继承下边类
public class LimitFilter implements GatewayFilter, Ordered {
private final Logger logger = LoggerFactory.getLogger(LimitFilter.class);
int capacity;
int refillTokens;
Duration refillDuration;
public LimitFilter(int capacity, int refillTokens, Duration refillDuration) {
this.capacity = capacity;
this.refillTokens = refillTokens;
this.refillDuration = refillDuration;
}
private static final Map<String,Bucket> CACHE = new ConcurrentHashMap<>();
private Bucket createNewBucket() {
Refill refill = Refill.of(refillTokens,refillDuration);
Bandwidth limit = Bandwidth.classic(capacity,refill);
return Bucket4j.builder().addLimit(limit).build();
}
@Override
public Mono<Void> filter(ServerWebExchange exchange, GatewayFilterChain chain) {
String ip = exchange.getRequest().getRemoteAddress().getAddress().getHostAddress();
Bucket bucket = CACHE.computeIfAbsent(ip,k -> createNewBucket());
logger.info("IP: " + ip + "，TokenBucket Available Tokens: " + bucket.getAvailableTokens());
if (bucket.tryConsume(1)) {
return chain.filter(exchange);
} else {
exchange.getResponse().setStatusCode(HttpStatus.TOO_MANY_REQUESTS);
return exchange.getResponse().setComplete();
}
}
@Override
public int getOrder() {
return 0;
}
}配置路由
@Bean
public RouteLocator customerRouteLocator(RouteLocatorBuilder builder) {
// @formatter:off
return builder.routes()
.route(r -> r.path("/consulserver/**")
.filters(f -> f.stripPrefix(1)
.filter(new LimitFilter(10,1,Duration.ofSeconds(1))))
.uri("lb://consulserver")
.order(0)
.id("throttle_customer_service")
).build();
// @formatter:on
} 
