设计思路-结合redis完成访问量统计 redis-缓存设计-统计1秒 5秒 1分钟 访问数量

需求

文章,最开始文章详情需要显示点赞数量、访问数量,以前做法是在调用查询接口 数据库+1 点赞时候访问量+1

update question q set q.view_count=q.view_count+1 where id=1 类似这样做法,其实在高并发场景不合理的,但是还好 

 

需求改变

需要支持时间搜索 搜索某一段时间的访问量

 

我的方案

参考《redis-缓存设计-统计1秒 5秒 1分钟 访问数量》

比如我设计1分钟延迟，同一分钟时间片都是redis incr 指定字段时间片,然后时间片过了在刷到数据库，因为不支持时分秒搜索 那么一个文章就算一天点赞10万次上亿次一天就生成一条数据 后续都是update 不存在埋点数据过大问题

数据库表

--文章统计指标
CREATE TABLE `question_metric_item`
(
    `id`            BIGINT(20) NOT NULL AUTO_INCREMENT COMMENT 'ID',
    `question_id`   BIGINT(20) NOT NULL  COMMENT '文章id',
    `answer_count`  int(11) default 0 COMMENT '评论量',
    `subscription_count`  int(11)  default 0 COMMENT '关注量',
    `help_count`  int(11)  default 0 COMMENT '有帮助',
    `comment_count`  int(11) default 0 COMMENT '评论回答数',
    `no_help_count`  int(11)  default 0 COMMENT '无帮助',
    `share_count`  int(11)  default 0 COMMENT '分享数',
    `view_count`  int(11)  default 0 COMMENT '查看数',
    `created_at`    DATETIME   NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
    `provider_id`  BIGINT(20) COMMENT '服务商id',
    PRIMARY KEY (`id`),
) ENGINE = InnoDB
  AUTO_INCREMENT = 1
  DEFAULT CHARSET = utf8
  ROW_FORMAT = DYNAMIC COMMENT ='文章统计指标';

 

埋点实现

在对应地方调用对应方法埋点

   /**
     * 新增阅读量
     *
     * @param questionId
     * @return
     */
    public Boolean addViewCount(Long providerId, Long questionId, Date date, Long count) {
        if (questionId == null) {
            return false;
        }
        addCount(providerId, QuestionMetricItemRo_.viewCount, questionId, count, date);
        return true;
    }

    /**
     * 新增评论量
     *
     * @param questionId
     * @param count
     * @return
     */
    public Boolean addAnswerCount(Long providerId, Long questionId, Date date, Long count) {
        addCount(providerId, QuestionMetricItemRo_.answerCount, questionId, count, date);
        return true;
    }

    /**
     * 关注与取消关注
     *
     * @param questionId
     * @param date
     * @param count
     * @return
     */
    public Boolean addSubscriptionCount(Long providerId, Long questionId, Date date, Long count) {
        addCount(providerId, QuestionMetricItemRo_.subscriptionCount, questionId, count, date);
        return true;
    }

    /**
     * 新增回答量
     *
     * @param questionId
     * @param date
     * @param count
     * @return
     */
    public Boolean addCommentCount(Long providerId, Long questionId, Date date, Long count) {
        addCount(providerId, QuestionMetricItemRo_.commentCount, questionId, count, date);
        return true;
    }

    /**
     * 有帮助
     *
     * @param questionId
     * @param date
     * @param count
     * @return
     */
    public Boolean addHelpCount(Long providerId, Long questionId, Date date, Long count) {
        addCount(providerId, QuestionMetricItemRo_.helpCount, questionId, count, date);
        return true;
    }

    /**
     * 无帮助
     *
     * @param questionId
     * @param date
     * @param count
     * @return
     */
    public Boolean addNoHelpCount(Long providerId, Long questionId, Date date, Long count) {
        addCount(providerId, QuestionMetricItemRo_.noHelpCount, questionId, count, date);
        return true;
    }

    /**
     * 更新分享数
     *
     * @param questionId
     * @param date
     * @param count
     * @return
     */
    public Boolean addShareCount(Long providerId, Long questionId, Date date, Long count) {
        addCount(providerId, QuestionMetricItemRo_.shareCount, questionId, count, date);
        return true;
    }

   


    public void addCount(Long providerId, String field, Long questionId, Long count, Date currentDate) {
        if (log.isDebugEnabled()) {
            log.debug("field={},questionId={},count={}", field, questionId, count);
        }
        String id = formatId(currentDate, questionId);
        String redisIdKey = this.getRoPrimaryId(id);
        //添加到当日list集合
        String listKey = getRoPrefix("list");
        Date formatDate = formatDate(currentDate);
        //时间片过了则统计
        Date scoreDate = Time.when(formatDate).setMinute(Time.when(formatDate).getMinute() + PREISION_MINUTE).setSecond(5).getDate();
        if (!exists(redisIdKey)) {
            Map<String, String> values = MapUtil.newMap(QuestionMetricItemRo_.createdAt, Time.when(currentDate).toString(Time.DEFAULT_TIME_FORMATS[0]),
                    QuestionMetricItemRo_.id, id, QuestionMetricItemRo_.questionId, String.valueOf(questionId), QuestionMetricItemRo_.providerId, String.valueOf(providerId));
            this.hset(redisIdKey, values);
            //定时刷入缓存
            this.zadd(listKey, NumberUtil.toDouble(scoreDate.getTime()), id);
            //设置过期时间
            expire(Sets.newHashSet(redisIdKey, listKey), getRo().expireSeconds());
        }
        //针对文章数量累加1
        this.hincrBy(redisIdKey, field, count);
    }
    public Date formatDate(Date date) {
        int preision = 60000 * PREISION_MINUTE;
        //算出x分钟内的时间片
        long startDateTime = (long) (date.getTime() / preision) * preision;
        return new Date(startDateTime);

    }

定时任务同步

当然同步的时候除了同步每日的,还需要往主表的Ro进行数量增加

  /**
     * 同步redis的统计数量到数据库
     */
    @Override
    public void syncByRedis() throws ParseException {

        int offset = 0;
        int size = 50;
        //队列待消费数量越多 则每次最多偏移200
        Date currentDate = new Date();
        Long waitCount = questionMetricItemRedisDao.listCount(currentDate);
        while (true) {
            Set<String> ids = questionMetricItemRedisDao.listKey(currentDate, offset, size);
            if (CollectionUtils.isEmpty(ids)) {
                log.debug("[QuestionMetricItemSync]没有数据忽略,offset:{},count:{}", offset, waitCount);
                break;
            }
            EweiTLogHandler eweiTLogHandler = new EweiTLogHandler();
            try {

                eweiTLogHandler.before(UUID.randomUUID().toString().replace("-", ""));
                //score到当前时间的数据信息 实现延迟效果
                List<QuestionMetricItemRo> questionMetricItemRos = questionMetricItemRedisDao.listById(ids);
                log.info("[QuestionMetricItemSync]执行同步,offset:{},count:{},Ids:{}", offset, waitCount, JSON.toJSONString(ids));
                log.info("执行同步questionMetricItems={}", JSON.toJSONString(questionMetricItemRos));
                List<QuestionMetricItem> questionMetricItems = QuestionMetricItemConvert.INSTANCE.toQuestionMetricItem(questionMetricItemRos);
                SpringUtil.getBean(IQuestionMetricItemService.class).batchSaveAndSyncQuestion(questionMetricItems);
            } catch (Exception e) {
                //埋点失败也不影响后续执行
                log.error("[QuestionMetricItemSync]执行同步异常", e);
            } finally {
                questionMetricItemRedisDao.deleteByIdAndDelRouting(ids);
                eweiTLogHandler.clear();
            }
        }
    }

针对实时性

我们知道统计是根据我们的时间片有一定延迟的，针对报表有一定延迟是可以接收的,但是针对详情需要实时性

不可能sum我们分日期的统计,直接用主表又会有延迟,很简单 通过主表的数量+当前时间片未同步的数量就好了

 

如以下代码

  /**
     * 合并当前时间片还未同步到redis的count
     *
     * @param
     * @return
     */
    public void combineCount(Question question) {
        if (question == null) {
            return;
        }
        String formatId = formatId(new Date(), NumberUtil.toLong(question.getId()));
        QuestionMetricItemRo itemRo = findById(formatId);
        if (itemRo == null) {
            return;
        }
        Integer answerCount = NumberUtil.toInteger(question.getAnswerCount(), 0) + (NumberUtil.toInteger(question.getAnswerCount(), 0));
        question.setAnswerCount(answerCount);

        Integer subscriptionCount = NumberUtil.toInteger(question.getSubscriptionCount(), 0) + (NumberUtil.toInteger(itemRo.getSubscriptionCount(), 0));
        question.setSubscriptionCount(subscriptionCount);

        Integer commentCount = NumberUtil.toInteger(question.getCommentCount(), 0) + (NumberUtil.toInteger(itemRo.getCommentCount(), 0));
        question.setCommentCount(commentCount);

        Integer helpCount = NumberUtil.toInteger(question.getVoteCount(), 0) + (NumberUtil.toInteger(itemRo.getHelpCount(), 0));
        question.setVoteCount(helpCount);

        Integer noHelpCount = NumberUtil.toInteger(question.getNoHelpCount(), 0) + (NumberUtil.toInteger(itemRo.getNoHelpCount(), 0));
        question.setNoHelpCount(noHelpCount);

        Integer shareCount = NumberUtil.toInteger(question.getShareCount(), 0) + (NumberUtil.toInteger(itemRo.getShareCount(), 0));
        question.setShareCount(shareCount);

        Integer viewCount = NumberUtil.toInteger(question.getViewCount(), 0) + (NumberUtil.toInteger(itemRo.getViewCount(), 0));
        question.setViewCount(viewCount);
    }