java多租户_（九十二）java版spring cloud 多租户社交电子商务-gateway（实现限流）...
电子商务平台源码请加企鹅求求：三伍三六贰四柒二伍九。限流一般有两个实现方式，令牌桶和漏桶
令牌桶是初始化令牌(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
令牌桶实现方式如下：
pom
com.github.vladimir-bukhtoyarov
bucket4j-core
4.0.0
创建下边类并且继承下边类package com.gla.datacenter.filter;
import io.github.bucket4j.Bandwidth;
import io.github.bucket4j.Bucket;
import io.github.bucket4j.Bucket4j;
import io.github.bucket4j.Refill;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
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;
/**
* @Description: 自定义过滤器进行限流
* @Author: zzh
* @Modified By:
* @Date: 2018/12/3 18:07
*/
public class GatewayRateLimitFilterByIP implements GatewayFilter, Ordered {
private final Logger log = LoggerFactory.getLogger(GatewayRateLimitFilterByIP.class);
/**
* 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 LOCAL_CACHE = new ConcurrentHashMap<>();
/**
* 桶的最大容量，即能装载 Token 的最大数量
*/
int capacity;
/**
* 每次 Token 补充量
*/
int refillTokens;
/**
*补充 Token 的时间间隔
*/
Duration refillDuration;
public GatewayRateLimitFilterByIP() {
}
/**
*
* @param capacity 即能装载 Token 的最大数量.
* @param refillTokens
* @param refillDuration
*/
public GatewayRateLimitFilterByIP(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 filter(ServerWebExchange exchange, GatewayFilterChain chain) {
String ip = exchange.getRequest().getRemoteAddress().getAddress().getHostAddress();
//若ip不存在则创建一个Bucket(令牌桶)
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
log.error("IP:{} ,限制访问:{} " ,ip,bucket.getAvailableTokens());
exchange.getResponse().setStatusCode(HttpStatus.TOO_MANY_REQUESTS);
return exchange.getResponse().setComplete();
}
}
@Override
public int getOrder() {
return -1000;
}
public static Map getLocalCache() {
return LOCAL_CACHE;
}
public int getCapacity() {
return capacity;
}
public void setCapacity(int capacity) {
this.capacity = capacity;
}
public int getRefillTokens() {
return refillTokens;
}
public void setRefillTokens(int refillTokens) {
this.refillTokens = refillTokens;
}
public Duration getRefillDuration() {
return refillDuration;
}
public void setRefillDuration(Duration refillDuration) {
this.refillDuration = refillDuration;
}
}
配置路由@Bean
public RouteLocator customRouteLocator(RouteLocatorBuilder builder) {
//生成比当前时间早一个小时的UTC时间
ZonedDateTime minusTime = LocalDateTime.now().minusHours(1).atZone(ZoneId.systemDefault());
return builder.routes()
.route(r ->r.path("/demo/**")
//过滤器
.filters(f -> f.filter(new APIGatewayFilter())
.filter(new GatewayRateLimitFilterByIP(10,1, Duration.ofSeconds(1))))
.uri("http://192.168.26.113:8001/demo").order(0).id("demo_route"))
.route(r ->r.path("/test")
.uri("http://192.168.26.113/system/nav/login").id("jd_route")
)
build();
}