系统会维护一个令牌（token）桶，以一个恒定的速度往桶里放入令牌（token），这时如果有请求进来想要被处理，则需要先从桶里获取一个令牌（token），当桶里没有令牌（token）可取时，则该请求将被拒绝服务。令牌桶算法通过控制桶的容量、发放令牌的速率，来达到对请求的限制。
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Google开源工具包Guava提供了限流工具类RateLimiter，该类基于令牌桶算法实现流量限制，使用十分方便，而且十分高效
<properties>
<spring-boot-start-version>2.6.9</spring-boot-start-version>
<guava-version>31.1-jre</guava-version>
</properties>
<!--单机限流-->
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-aop</artifactId>
</dependency>
import java.lang.annotation.Documented;
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
import java.util.concurrent.TimeUnit;
/**
* @description: Guava限流单机
* @author: GuoTong
* @createTime: 2023-05-27 14:30
* @since JDK 1.8 OR 11
**/
@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.METHOD})
@Documented
public @interface GuavaAopLimit {
/**
* 资源的key,唯一：不同的接口，不同的流量控制
*/
String key() default "";
/**
* 最多的访问限制次数
*/
double permitsPerSecond();
/**
* 获取令牌最大等待时间
*/
long timeout();
/**
* 获取令牌最大等待时间,单位(例:分钟/秒/毫秒) 默认:毫秒
*/
TimeUnit timeunit() default TimeUnit.MILLISECONDS;
/**
* 得不到令牌的提示语
*/
String msg() default "Guava单机限流令牌桶没了";
}
import com.google.common.collect.Maps;
import com.google.common.util.concurrent.RateLimiter;
import com.gton.annotation.GuavaAopLimit;
import com.gton.handler.RedisLimitException;
import lombok.extern.slf4j.Slf4j;
import org.aspectj.lang.ProceedingJoinPoint;
import org.aspectj.lang.annotation.Around;
import org.aspectj.lang.annotation.Aspect;
import org.aspectj.lang.reflect.MethodSignature;
import org.springframework.stereotype.Component;
import java.lang.reflect.Method;
import java.util.Map;
/**
* @description: ：使用AOP切面拦截限流注解
* @author: GuoTong
* @createTime: 2023-05-27 14:32
* @since JDK 1.8 OR 11
**/
@Slf4j
@Aspect
@Component
public class GuavaLimitAspect {
/**
* 不同的接口，不同的流量控制
* map的key为 Limiter.key
*/
private final Map<String, RateLimiter> limitMap = Maps.newConcurrentMap();
@Around("@annotation(com.gton.annotation.GuavaAopLimit)")
public Object around(ProceedingJoinPoint joinPoint) throws Throwable {
MethodSignature signature = (MethodSignature) joinPoint.getSignature();
Method method = signature.getMethod();
//拿limit的注解
GuavaAopLimit limit = method.getAnnotation(GuavaAopLimit.class);
if (limit != null) {
//key作用：不同的接口，不同的流量控制
String key = limit.key();
RateLimiter rateLimiter = null;
//验证缓存是否有命中key
if (!limitMap.containsKey(key)) {
// 创建令牌桶
rateLimiter = RateLimiter.create(limit.permitsPerSecond());
limitMap.put(key, rateLimiter);
log.info("新建了令牌桶={}，容量={}", key, limit.permitsPerSecond());
}
rateLimiter = limitMap.get(key);
// 拿令牌
boolean acquire = rateLimiter.tryAcquire(limit.timeout(), limit.timeunit());
// 拿不到命令，直接返回异常提示
if (!acquire) {
log.debug("令牌桶={}，获取令牌失败", key);
throw new RedisLimitException(limit.msg());
}
}
return joinPoint.proceed();
}
}
/**
* @description: 通用返回对象
* 贫血型模型
* @author: GuoTong
* @createTime: 2022-09-24 13:16
* @since JDK 1.8 OR 11
**/
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@Accessors(chain = true)
public class Resp<T> implements Serializable {
//状态码
protected String code;
//提示信息
protected String msg;
//返回的数据
protected T data;
/**
* Description:常用返回数据抽离
*/
public static <T> Resp<T> LoginOk() {
return new Resp<T>().
setCode(ContextCommonMsg.LOGIN_SUCCESS_CODE).
setMsg(ContextCommonMsg.LOGIN_SUCCESS_MSG);
}
public static <T> Resp<T> LoginFail() {
return new Resp<T>().
setCode(ContextCommonMsg.LOGIN_FAIL_CODE).
setMsg(ContextCommonMsg.LOGIN_FAIL_MSG);
}
public static <T> Resp<T> error(String errorMsg) {
return new Resp<T>().
setCode(ContextCommonMsg.FAIL_CODE).
setMsg(errorMsg);
}
public static <T> Resp<T> error() {
return new Resp<T>().
setCode(ContextCommonMsg.FAIL_CODE).
setMsg(ContextCommonMsg.FAIL_MSG);
}
public static <T> Resp<T> error(String errorMsg, String failCode) {
return new Resp<T>().
setCode(failCode).
setMsg(errorMsg);
}
public static <T> Resp<T> error(String errorMsg, String failCode, T data) {
return new Resp<T>().
setCode(failCode).
setData(data).
setMsg(errorMsg);
}
public static <T> Resp<T> Ok(T data) {
return new Resp<T>().
setCode(ContextCommonMsg.SUCCESS_CODE).
setMsg(ContextCommonMsg.SUCCESS_MSG).
setData(data);
}
public static <T> Resp<T> Ok() {
return new Resp<T>().
setCode(ContextCommonMsg.SUCCESS_CODE).
setMsg(ContextCommonMsg.SUCCESS_MSG);
}
public static <T> Resp<T> Ok(T data, String msg) {
return new Resp<T>().
setCode(ContextCommonMsg.SUCCESS_CODE).
setMsg(msg).
setData(data);
}
public static <T> Resp<T> Ok(T data, String msg, String successCode) {
return new Resp<T>().
setCode(successCode).
setMsg(msg).
setData(data);
}
}
/**
* @description: 限流异常
* @author: GuoTong
* @createTime: 2023-05-27 13:46
* @since JDK 1.8 OR 11
**/
public class RedisLimitException extends RuntimeException {
public RedisLimitException(String msg) {
super(msg);
}
}
/**
* @description: 全局异常处理：
* @author: GuoTong
* @createTime: 2022-11-27 11:17
* @since JDK 1.8 OR 11
**/
@RestControllerAdvice
@Slf4j
public class GlobalExceptionHandler {
// 全局异常拦截
@ExceptionHandler
public Resp handlerException(Exception e) {
e.printStackTrace();
log.error("服务执行异常---->{}", e.getMessage());
return Resp.error(e.getMessage());
}
@ExceptionHandler(value = RedisLimitException.class)
public Resp handlerException(RedisLimitException e) {
log.error("限流触发---->{}", e.getMessage());
return Resp.error(e.getMessage());
}
/**
* @description:
* @author: GuoTong
* @createTime: 2022-11-25 00:02
* @since JDK 1.8 OR 11
**/
@RestController
public class AA {
@GetMapping("/guava")
@GuavaAopLimit(key = "limit_guava", permitsPerSecond = 1, timeout = 500, timeunit = TimeUnit.MILLISECONDS, msg = "基于Guava+AOP实现的单机限流！")
public Resp okGuava() {
return Resp.Ok();
}
}
理解并合理运用Spring Boot配置加载的优先级，对于保障应用的安全性、可维护性以及降低部署复杂度至关重要。特别是在大规模微服务架构中，合理的配置管理和迁移对于整体系统的稳定性有着不可忽视的作用。