Spring Cloud Gateway自定义过滤器进行限流

<dependencies>
    <!-- Spring Cloud Gateway的依赖-->
    <dependency>
        <groupId>org.springframework.cloud</groupId>
        <artifactId>spring-cloud-starter-gateway</artifactId>
    </dependency>
    <!-- Bucket4j限流依赖-->
    <dependency>
        <groupId>com.github.vladimir-bukhtoyarov</groupId>
        <artifactId>bucket4j-core</artifactId>
        <version>4.0.0</version>
    </dependency>
</dependencies>

@SpringBootApplication
public class GatewayApplication {

    @Bean
    public RouteLocator customRouteLocator(RouteLocatorBuilder builder) {
        return builder.routes()
                .route(r -> r.path("/test/rateLimit")
                        .filters(f -> f.rewritePath("test", "hello")
                                .filter(new GatewayRateLimitByIpFilter(10, 1, Duration.ofSeconds(1))))
                        .uri("http://127.0.0.1:9001")
                )
                .build();
    }

    public static void main(String[] args) {
        SpringApplication.run(GatewayApplication.class, args);
    }
}

import io.github.bucket4j.Bandwidth;
import io.github.bucket4j.Bucket;
import io.github.bucket4j.Bucket4j;
import io.github.bucket4j.Refill;
import lombok.Getter;
import lombok.Setter;
import lombok.extern.slf4j.Slf4j;
import org.springframework.cloud.gateway.filter.GatewayFilter;
import org.springframework.cloud.gateway.filter.GatewayFilterChain;
import org.springframework.core.Ordered;
import org.springframework.http.HttpStatus;
import org.springframework.web.server.ServerWebExchange;
import reactor.core.publisher.Mono;

import java.time.Duration;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;

/**
 * @author yezhou
 */
@Slf4j
public class GatewayRateLimitByIpFilter implements GatewayFilter, Ordered {

    /**
     * 单机网关限流用一个ConcurrentHashMap来存储 bucket
     * 如果是分布式集群限流的话，可以采用 Redis等分布式解决方案
     */
    private static final Map<String, Bucket> LOCAL_CACHE = new ConcurrentHashMap<>();

    /**
     * 桶的最大容量，即能装载 Token 的最大数量
     */
    @Getter
    @Setter
    int capacity;
    /**
     * 每次 Token 补充量
     */
    @Getter
    @Setter
    int refillTokens;
    /**
     *补充 Token 的时间间隔
     */
    @Getter
    @Setter
    Duration refillDuration;

    public GatewayRateLimitByIpFilter() {
    }

    public GatewayRateLimitByIpFilter(int capacity, int refillTokens, Duration refillDuration) {
        this.capacity = capacity;
        this.refillTokens = refillTokens;
        this.refillDuration = refillDuration;
    }

    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 = LOCAL_CACHE.computeIfAbsent(ip, k -> createNewBucket());
        log.info("IP:{}, 令牌通可用的Token数量:{}", ip, bucket.getAvailableTokens());
        if (bucket.tryConsume(1)) {
            return chain.filter(exchange);
        } else {
            //当可用的令牌书为0是，进行限流返回429状态码
            exchange.getResponse().setStatusCode(HttpStatus.TOO_MANY_REQUESTS);
            return exchange.getResponse().setComplete();
        }
    }

    @Override
    public int getOrder() {
        return -100;
    }

    public static Map<String, Bucket> getLocalCache() {
        return LOCAL_CACHE;
    }
}