Redis实现幂等、防抖、限流等功能

本文章主要讲述如何使用Redis实现幂等、防抖、限流等功能。

幂等组件

import lombok.RequiredArgsConstructor;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.stereotype.Component;

import java.util.Objects;
import java.util.concurrent.TimeUnit;

/**
 * 消息队列幂等处理器
 */
@Component
@RequiredArgsConstructor
public class MessageQueueIdempotentHandler {

    private final StringRedisTemplate stringRedisTemplate;

    private static final String IDEMPOTENT_KEY_PREFIX = "xxx:idempotent:";

    /**
     * 判断当前消息是否消费过
     *
     * @param messageId 消息唯一标识
     * @return 消息是否消费过
     */
    public boolean isMessageBeingConsumed(String messageId) {
        String key = IDEMPOTENT_KEY_PREFIX + messageId;
        return Boolean.FALSE.equals(stringRedisTemplate.opsForValue().setIfAbsent(key, "0", 2, TimeUnit.MINUTES));
    }

    /**
     * 判断消息消费流程是否执行完成
     *
     * @param messageId 消息唯一标识
     * @return 消息是否执行完成
     */
    public boolean isAccomplish(String messageId) {
        String key = IDEMPOTENT_KEY_PREFIX + messageId;
        return Objects.equals(stringRedisTemplate.opsForValue().get(key), "1");
    }

    /**
     * 设置消息流程执行完成
     *
     * @param messageId 消息唯一标识
     */
    public void setAccomplish(String messageId) {
        String key = IDEMPOTENT_KEY_PREFIX + messageId;
        stringRedisTemplate.opsForValue().set(key, "1", 2, TimeUnit.MINUTES);
    }

    /**
     * 如果消息处理遇到异常情况，删除幂等标识
     *
     * @param messageId 消息唯一标识
     */
    public void delMessageProcessed(String messageId) {
        String key = IDEMPOTENT_KEY_PREFIX + messageId;
        stringRedisTemplate.delete(key);
    }
}

@Component
@RocketMQMessageListener(consumerGroup = "saaslink_consumer_group", topic = RedisKeyConstant.SHORT_LINK_STATS_STREAM_TOPIC_KEY)
@Slf4j
public class ShortLinkStatsSaveConsumer implements RocketMQListener<MessageExt> {
    @Override
    public void onMessage(MessageExt msgExt) {
        String msgId = msgExt.getMsgId();
        // 使用redis实现幂等
        if (messageQueueIdempotentHandler.isMessageBeingConsumed(msgId.toString())) {
            // 判断当前的这个消息流程是否执行完成
            if (messageQueueIdempotentHandler.isAccomplish(msgId.toString())) {
                return;
            }
            throw new ServiceException("消息未完成流程，需要消息队列重试");
        }
        try {
            byte[] msgExtBody = msgExt.getBody();
            // 转为map
            Map<String, String> producerMap = JSON.parseObject(msgExtBody, Map.class);
            ShortLinkStatsRecordDTO statsRecord = JSON.parseObject(producerMap.get("statsRecord"), ShortLinkStatsRecordDTO.class);
            // 实际新增的逻辑
            } catch (Throwable ex) {
            // 某某某情况宕机了
            messageQueueIdempotentHandler.delMessageProcessed(msgId.toString());
            log.error("记录短链接监控消费异常", ex);
            throw ex;
        }
        messageQueueIdempotentHandler.setAccomplish(msgId.toString());
    }
}

防抖组件

幂等注解，防止用户重复提交表单信息，主要是通过分布式锁实现。

import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;

/**
 * 幂等注解，防止用户重复提交表单信息
 */
@Target(ElementType.METHOD)
@Retention(RetentionPolicy.RUNTIME)
public @interface NoDuplicateSubmit {

    /**
     * 触发幂等失败逻辑时，返回的错误提示信息
     */
    String message() default "您操作太快，请稍后再试";
}

import cn.hutool.crypto.digest.DigestUtil;
import com.alibaba.fastjson2.JSON;
import com.nageoffer.onecoupon.framework.exception.ClientException;
import lombok.RequiredArgsConstructor;
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.redisson.api.RLock;
import org.redisson.api.RedissonClient;
import org.springframework.web.context.request.RequestContextHolder;
import org.springframework.web.context.request.ServletRequestAttributes;

import java.lang.reflect.Method;

/**
 * 防止用户重复提交表单信息切面控制器
 */
@Aspect
@RequiredArgsConstructor
public final class NoDuplicateSubmitAspect {

    private final RedissonClient redissonClient;

    /**
     * 增强方法标记 {@link NoDuplicateSubmit} 注解逻辑
     */
    @Around("@annotation(com.nageoffer.onecoupon.framework.idempotent.NoDuplicateSubmit)")
    public Object noDuplicateSubmit(ProceedingJoinPoint joinPoint) throws Throwable {
        NoDuplicateSubmit noDuplicateSubmit = getNoDuplicateSubmitAnnotation(joinPoint);
        // 获取分布式锁标识
        String lockKey = String.format("no-duplicate-submit:path:%s:currentUserId:%s:md5:%s", getServletPath(), getCurrentUserId(), calcArgsMD5(joinPoint));
        RLock lock = redissonClient.getLock(lockKey);
        // 尝试获取锁，获取锁失败就意味着已经重复提交，直接抛出异常
        if (!lock.tryLock()) {
            throw new ClientException(noDuplicateSubmit.message());
        }
        Object result;
        try {
            // 执行标记了防重复提交注解的方法原逻辑
            result = joinPoint.proceed();
        } finally {
            lock.unlock();
        }
        return result;
    }

    /**
     * @return 返回自定义防重复提交注解
     */
    public static NoDuplicateSubmit getNoDuplicateSubmitAnnotation(ProceedingJoinPoint joinPoint) throws NoSuchMethodException {
        MethodSignature methodSignature = (MethodSignature) joinPoint.getSignature();
        Method targetMethod = joinPoint.getTarget().getClass().getDeclaredMethod(methodSignature.getName(), methodSignature.getMethod().getParameterTypes());
        return targetMethod.getAnnotation(NoDuplicateSubmit.class);
    }

    /**
     * @return 获取当前线程上下文 ServletPath
     */
    private String getServletPath() {
        ServletRequestAttributes sra = (ServletRequestAttributes) RequestContextHolder.getRequestAttributes();
        return sra.getRequest().getServletPath();
    }

    /**
     * @return 当前操作用户 ID
     */
    private String getCurrentUserId() {
        // 从UserConText中获取
        return "xxx";
    }

    /**
     * @return joinPoint md5
     */
    private String calcArgsMD5(ProceedingJoinPoint joinPoint) {
        return DigestUtil.md5Hex(JSON.toJSONBytes(joinPoint.getArgs()));
    }

限流组件

Sentinel进行限流

/**
 * 初始化限流配置
 */
@Component
public class SentinelRuleConfig implements InitializingBean {

    @Override
    public void afterPropertiesSet() throws Exception {
        List<FlowRule> rules = new ArrayList<>();
        FlowRule createOrderRule = new FlowRule();
        createOrderRule.setResource("xxx");
        createOrderRule.setGrade(RuleConstant.FLOW_GRADE_QPS);
        createOrderRule.setCount(1);
        rules.add(createOrderRule);
        FlowRuleManager.loadRules(rules);
    }
}

/**
 * 自定义流控策略
 */
public class CustomBlockHandler {

    public static Result<ShortLinkCreateRespDTO> createShortLinkBlockHandlerMethod(ShortLinkCreateReqDTO requestParam, BlockException exception) {
        return new Result<ShortLinkCreateRespDTO>().setCode("B100000").setMessage("当前访问网站人数过多，请稍后再试...");
    }
}

    @PostMapping("/api/xxx/v1/create")
    @SentinelResource(
            value = "xxx",
            blockHandler = "createShortLinkBlockHandlerMethod",
            blockHandlerClass = CustomBlockHandler.class
    )
    public Result<ShortLinkCreateRespDTO> create(@RequestBody CreateReqDTO requestParam) {
        return Results.success(Service.create(requestParam));
    }

Redis限流组件

通过lua脚本，判断1s以内的并发请求数是否超过我们的预期，如果超过我们的预计就进行限制。

-- 设置用户访问频率限制的参数
local username = KEYS[1]
local timeWindow = tonumber(ARGV[1]) -- 时间窗口，单位：秒

-- 构造 Redis 中存储用户访问次数的键名
local accessKey = "short-link:user-flow-risk-control:" .. username

-- 原子递增访问次数，并获取递增后的值
local currentAccessCount = redis.call("INCR", accessKey)

-- 设置键的过期时间
if currentAccessCount == 1 then
    redis.call("EXPIRE", accessKey, timeWindow)
end

-- 返回当前访问次数
return currentAccessCount

/**
 * 用户操作流量风控配置文件
 */
@Data
@Component
@ConfigurationProperties(prefix = "xxx.flow-limit")
public class UserFlowRiskControlConfiguration {

    /**
     * 是否开启用户流量风控验证
     */
    private Boolean enable;

    /**
     * 流量风控时间窗口，单位：秒
     */
    private String timeWindow;

    /**
     * 流量风控时间窗口内可访问次数
     */
    private Long maxAccessCount;
}

xxx:
  group:
    max-num: 20
  flow-limit:
    enable: true
    time-window: 1
    max-access-count: 20

import com.alibaba.fastjson2.JSON;
import com.cmk.saaslink.admin.config.common.UserFlowRiskControlConfiguration;
import com.cmk.saaslink.common.convention.biz.user.UserContext;
import com.cmk.saaslink.common.convention.exception.ClientException;
import com.cmk.saaslink.common.convention.result.Results;
import com.google.common.collect.Lists;
import jakarta.servlet.*;
import jakarta.servlet.http.HttpServletResponse;
import lombok.RequiredArgsConstructor;
import lombok.SneakyThrows;
import lombok.extern.slf4j.Slf4j;
import org.springframework.core.io.ClassPathResource;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.scripting.support.ResourceScriptSource;

import java.io.IOException;
import java.io.PrintWriter;
import java.util.Optional;

import static com.cmk.saaslink.common.convention.errorcode.BaseErrorCode.FLOW_LIMIT_ERROR;


/**
 * 用户操作流量风控过滤器
 */
@Slf4j
@RequiredArgsConstructor
public class UserFlowRiskControlFilter implements Filter {

    private final StringRedisTemplate stringRedisTemplate;
    private final UserFlowRiskControlConfiguration userFlowRiskControlConfiguration;

    private static final String USER_FLOW_RISK_CONTROL_LUA_SCRIPT_PATH = "lua/user_flow_risk_control.lua";

    @SneakyThrows
    @Override
    public void doFilter(ServletRequest request, ServletResponse response, FilterChain filterChain) throws IOException, ServletException {
        DefaultRedisScript<Long> redisScript = new DefaultRedisScript<>();
        redisScript.setScriptSource(new ResourceScriptSource(new ClassPathResource(USER_FLOW_RISK_CONTROL_LUA_SCRIPT_PATH)));
        redisScript.setResultType(Long.class);
        String username = Optional.ofNullable(UserContext.getUsername()).orElse("other");
        Long result;
        try {
            result = stringRedisTemplate.execute(redisScript, Lists.newArrayList(username), userFlowRiskControlConfiguration.getTimeWindow());
        } catch (Throwable ex) {
            log.error("执行用户请求流量限制LUA脚本出错", ex);
            returnJson((HttpServletResponse) response, JSON.toJSONString(Results.failure(new ClientException(FLOW_LIMIT_ERROR))));
            return;
        }
        if (result == null || result > userFlowRiskControlConfiguration.getMaxAccessCount()) {
            returnJson((HttpServletResponse) response, JSON.toJSONString(Results.failure(new ClientException(FLOW_LIMIT_ERROR))));
            return;
        }
        filterChain.doFilter(request, response);
    }

    private void returnJson(HttpServletResponse response, String json) throws Exception {
        response.setCharacterEncoding("UTF-8");
        response.setContentType("text/html; charset=utf-8");
        try (PrintWriter writer = response.getWriter()) {
            writer.print(json);
        }
    }
}