RateLimiter是guava提供的基于令牌桶算法的实现类,可以非常简单的完成限流特技,并且根据系统的实际情况来调整生成token的速率。
通常可应用于抢购限流防止冲垮系统;限制某接口、服务单位时间内的访问量,譬如一些第三方服务会对用户访问量进行限制;限制网速,单位时间内只允许上传下载多少字节等。
guava的maven依赖
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>25.1-jre</version>
</dependency>
令牌桶的原理,有一个独立线程一直以一个固定的速率往桶中存放令牌 客户端去桶中获取令牌,获取到令牌,就可以访问,获取不到,说明请求过多,需要服务降级。
package com.aiyuesheng.controller;
import java.util.concurrent.TimeUnit;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import com.aiyuesheng.hystrix.OrderHystrixCommand;
import com.aiyuesheng.service.OrderService;
import com.aiyuesheng.utils.LimitService;
import com.alibaba.fastjson.JSONObject;
import com.google.common.util.concurrent.RateLimiter;
@RestController
public class Index {// 令牌桶:1.0 表示 每秒中生成1个令牌存放在桶中
RateLimiter rateLimiter = RateLimiter.create(1.0);
@Autowired
private OrderService orderService;
//令牌桶限流
@RequestMapping("/searchCustomerInfoByRateLimiter")
public Object searchCustomerInfoByRateLimiter() {
// 1.限流判断
// 如果在0.5秒内 没有获取不到令牌的话,则会一直等待
System.out.println("生成令牌等待时间:" + rateLimiter.acquire());
boolean acquire = rateLimiter.tryAcquire(500, TimeUnit.MILLISECONDS); // 每次发送请求,愿意等待0.5秒,如果设为1秒,每次都能查询成功,因为没秒中都会放入一个令牌到桶中
if (!acquire) {
System.out.println("稍后再试!");
return "稍后再试!";
}
// 2.如果没有达到限流的要求,直接调用接口查询
System.out.println(orderService.searchCustomerInfo());
return orderService.searchCustomerInfo();
}
}
基于 AOP 实现:
package com.tree.ztree_demo.currentlimiting;
import java.lang.annotation.*;
/**
* @version V1.0
* @Title: RateLimit.java
* @Package mlq.pic.picback.currentlimiting
* @Description: 限流注解
* @author: MLQ
* @date: 2019/11/14 14:52
*/
@Inherited
@Documented
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
public @interface RateLimit {
/**
* 默认每秒支持2个
*
* @return
*/
int limintNum() default 2;
}
-----
package com.tree.ztree_demo.currentlimiting;
import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.google.common.util.concurrent.RateLimiter;
import groovy.util.logging.Slf4j;
import org.aspectj.lang.ProceedingJoinPoint;
import org.aspectj.lang.Signature;
import org.aspectj.lang.annotation.Around;
import org.aspectj.lang.annotation.Aspect;
import org.aspectj.lang.annotation.Pointcut;
import org.aspectj.lang.reflect.MethodSignature;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Scope;
import org.springframework.stereotype.Component;
import org.springframework.util.ObjectUtils;
import javax.servlet.ServletOutputStream;
import javax.servlet.http.HttpServletResponse;
import java.io.IOException;
import java.lang.reflect.Method;
import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.TimeUnit;
/**
* @version V1.0
* @Title: RateLimitAspect.java
* @Package mlq.pic.picback.currentlimiting
* @Description: 增强限流拦截
* @author: MLQ
* @date: 2019/11/14 14:54
*/
@Component
@Scope
@Aspect
@Slf4j
public class RateLimitAspect {
private static final Logger LOGGER = LoggerFactory.getLogger(RateLimitAspect.class);
/**
* 用来存放不同接口的RateLimiter(key为接口名称,value为RateLimiter)
*/
private ConcurrentHashMap<String, RateLimiter> map = new ConcurrentHashMap<>();
private static final String POINT = "execution (* com.tree.ztree_demo..*.abc*(..))";
private static ObjectMapper objectMapper = new ObjectMapper();
private RateLimiter rateLimiter;
@Autowired
private HttpServletResponse response;
@Pointcut(POINT)
public void serviceLimit() {
}
@Around("serviceLimit()")
public Object around(ProceedingJoinPoint joinPoint) throws NoSuchMethodException {
Object obj = null;
//获取拦截的方法名
Signature sig = joinPoint.getSignature();
//获取拦截的方法名
MethodSignature msig = (MethodSignature) sig;
//返回被织入增加处理目标对象
Object target = joinPoint.getTarget();
//为了获取注解信息
Method currentMethod = target.getClass().getMethod(msig.getName(), msig.getParameterTypes());
//获取注解信息
RateLimit annotation = currentMethod.getAnnotation(RateLimit.class);
if (!ObjectUtils.isEmpty(annotation)) {
//获取注解每秒加入桶中的token
int limitNum = annotation.limintNum();
// 注解所在方法名区分不同的限流策略
String functionName = msig.getName();
//获取rateLimiter
if (map.containsKey(functionName)) {
rateLimiter = map.get(functionName);
} else {
map.put(functionName, RateLimiter.create(limitNum));
rateLimiter = map.get(functionName);
}
// 如果在0.5秒内 没有获取不到令牌的话,则会一直等待
System.out.println("生成令牌等待时间:" + rateLimiter.acquire());
try {
// 每次发送请求,愿意等待0.5秒,如果设为1秒,每次都能查询成功,因为没秒中都会放入一个令牌到桶中
if (rateLimiter.tryAcquire(500, TimeUnit.MILLISECONDS)) {
//执行方法
obj = joinPoint.proceed();
} else {
Map<String, Object> map = new HashMap<>();
map.put("code", 100001);
map.put("message", "系统繁忙,请稍后再试!");
//拒绝了请求(服务降级)
String result = objectMapper.writeValueAsString(map);
LOGGER.info("拒绝了请求:" + result);
outErrorResult(result);
}
} catch (Throwable throwable) {
throwable.printStackTrace();
}
} else {
Map<String, Object> map = new HashMap<>();
map.put("code", 403);
map.put("message", "签名问题");
//拒绝了请求(服务降级)
String result = null;
try {
result = objectMapper.writeValueAsString(map);
} catch (JsonProcessingException e) {
e.printStackTrace();
}
LOGGER.info("拒绝了请求:" + result);
outErrorResult(result);
}
return obj;
}
//将结果返回
public void outErrorResult(String result) {
response.setContentType("application/json;charset=UTF-8");
try (ServletOutputStream outputStream = response.getOutputStream()) {
outputStream.write(result.getBytes("utf-8"));
} catch (IOException e) {
e.printStackTrace();
}
}
static {
objectMapper.setSerializationInclusion(JsonInclude.Include.NON_NULL);
}
}
使用方式:在controller 访问地址加上注解即可
@RateLimit(limintNum = 100)
@RequestMapping("abc")
public Object abc() {
Map<String, Object> map = new HashMap<>();
map.put("code", "200");
map.put("message", "OK");
return JSON.toJSONString(map);
}