对前端限流操作（无Redis版本）

如何限制前端的请求次数

最近学习缓存击穿的时候，解决方法是限流，前端限制请求次数。故通过后端来对前端的请求做限流次数。

这里首先不用redis方法，这里采用通过Aop切面的方式来限制请求次数

创建限流注解

/**
 * 限流接口
 */
@Retention(RetentionPolicy.RUNTIME)
@Target({ElementType.TYPE, ElementType.METHOD})
@Documented
@Order(Ordered.HIGHEST_PRECEDENCE)
public @interface RequestLimit {

    // time是调用接口的间隔时间，默认是 5000 毫秒
    long time() default 5000;

}

获取单例的map对象存放数据

SubmitBufferSingleton 用来获取唯一的 HashMap，其中的Value是从 1970-01-01T00:00:00Z（协调世界时，UTC）到当前时间点之间的毫秒数

/**
 * 获取单例map对象
 */
public class SubmitBufferSingleton {

    private static final HashMap<String, Long> map = new HashMap<>();

    private SubmitBufferSingleton() {
    }

    public static HashMap<String, Long> getInstance() {
        return map;
    }

}

创建切面的任务

@Aspect
@Component
@Slf4j
public class NoRepeatSubmitAop {

    // 定义切面
    @Pointcut("@annotation(com.zhuang.aspect.annotation.RequestLimit)")
    private void noRepeatSubmitAop() {

    }


    @Synchronized // 作用是创建一个互斥锁，保证只有一个线程对 SubmitBufferSingleton.getInstance() 这个变量进行修改。
    @Around("noRepeatSubmitAop()&&@annotation(nrs)")
    public Object around(ProceedingJoinPoint pjp, RequestLimit nrs) throws Throwable {

        ServletRequestAttributes attributes = (ServletRequestAttributes) RequestContextHolder.getRequestAttributes();
        assert attributes != null;
        HttpServletRequest request = attributes.getRequest();
        String key = getIp(request) + " ：" + request.getServletPath();
        long time = nrs.time();
        Object o = pjp.proceed();
        HashMap<String, Long> hashMap = SubmitBufferSingleton.getInstance();
        long nowTime = Instant.now().toEpochMilli();
        if (!hashMap.containsKey(key)) {
            hashMap.put(key, nowTime + time);
            return o;
        } else {
            if (nowTime > hashMap.get(key)) {
                hashMap.put(key, nowTime + time);
                return o;
            } else {
                log.error("操作过于频繁 {}", key);
                return "操作过于频繁";
            }
        }

    }


    // 获取调用者ip
    private static String getIp(HttpServletRequest request) {
        String ip = request.getHeader("x-forwarded-for");
        if (ip == null || ip.length() == 0 || "unknown".equalsIgnoreCase(ip)) {
            ip = request.getHeader("Proxy-Client-IP");
        }
        if (ip == null || ip.length() == 0 || "unknown".equalsIgnoreCase(ip)) {
            ip = request.getHeader("WL-Proxy-Client-IP");
        }
        if (ip == null || ip.length() == 0 || "unknown".equalsIgnoreCase(ip)) {
            ip = request.getHeader("HTTP_CLIENT_IP");
        }
        if (ip == null || ip.length() == 0 || "unknown".equalsIgnoreCase(ip)) {
            ip = request.getHeader("HTTP_X_FORWARDED_FOR");
        }
        if (ip == null || ip.length() == 0 || "unknown".equalsIgnoreCase(ip)) {
            ip = request.getRemoteAddr();
        }
        return ip;
    }

}

创建定时任务

这里设置一个定时器在每秒清理一下HashMap数据，防止 HashMap 越来越大。将 HashMap 从 NoRepeatSubmitAop 中抽出来的优点在这里也体现出来了

@Component
@Slf4j
public class NoRepeatSubmitTask {

    @Scheduled(cron = "* * * * * ?")
    public void start() {
        HashMap<String, Long> hashMap = SubmitBufferSingleton.getInstance();
        log.warn(hashMap.toString());
        for (Map.Entry<String, Long> next : hashMap.entrySet()) {
            String key = next.getKey();
            Long value = next.getValue();
            if (value > Instant.now().toEpochMilli()) {
                hashMap.remove(key);
            }
        }
        // 如果对时间没有特别严格的要求就直接clear
//        hashMap.clear();
    }
}

主启动类开启注解

@EnableScheduling //开启定时任务

测试接口，内部方法不用纠结

    @PostMapping("get")
    @RequestLimit(time = 1000)
    public ResultVO getUser(@RequestBody(required = false) UserDto userDto) {
        try {
            if (!ObjectUtils.isEmpty(userDto)) {
                userService.list(userDto);
            }
        } catch (Exception e) {
            log.error(e.getMessage());
            return ResultVOUtil.error(ResultEnum.ERROR);
        }
        return ResultVOUtil.success(ResultEnum.SUCCESS);
    }

第一次请求成功

多次请求后就会限流

查看日志，请求过于频繁了！