設計思路-結合redis完成訪問量統計 redis-緩存設計-統計1秒 5秒 1分鐘 訪問數量

需求

文章,最開始文章詳情需要顯示點贊數量、訪問數量,以前做法是在調用查詢接口 數據庫+1 點贊時候訪問量+1

update question q set q.view_count=q.view_count+1 where id=1 類似這樣做法,其實在高併發場景不合理的,但是還好 

 

需求改變

需要支持時間搜索 搜索某一段時間的訪問量

 

我的方案

參考《redis-緩存設計-統計1秒 5秒 1分鐘 訪問數量》

比如我設計1分鐘延遲，同一分鐘時間片都是redis incr 指定字段時間片,然後時間片過了在刷到數據庫，因爲不支持時分秒搜索 那麼一個文章就算一天點贊10萬次上億次一天就生成一條數據 後續都是update 不存在埋點數據過大問題

數據庫表

--文章統計指標
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 '評論量',
    `subscription_count`  int(11)  default 0 COMMENT '關注量',
    `help_count`  int(11)  default 0 COMMENT '有幫助',
    `comment_count`  int(11) default 0 COMMENT '評論回答數',
    `no_help_count`  int(11)  default 0 COMMENT '無幫助',
    `share_count`  int(11)  default 0 COMMENT '分享數',
    `view_count`  int(11)  default 0 COMMENT '查看數',
    `created_at`    DATETIME   NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '創建時間',
    `provider_id`  BIGINT(20) COMMENT '服務商id',
    PRIMARY KEY (`id`),
) ENGINE = InnoDB
  AUTO_INCREMENT = 1
  DEFAULT CHARSET = utf8
  ROW_FORMAT = DYNAMIC COMMENT ='文章統計指標';

 

埋點實現

在對應地方調用對應方法埋點

   /**
     * 新增閱讀量
     *
     * @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;
    }

    /**
     * 新增評論量
     *
     * @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;
    }

    /**
     * 關注與取消關注
     *
     * @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;
    }

    /**
     * 有幫助
     *
     * @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;
    }

    /**
     * 無幫助
     *
     * @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;
    }

    /**
     * 更新分享數
     *
     * @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);
        //添加到當日list集合
        String listKey = getRoPrefix("list");
        Date formatDate = formatDate(currentDate);
        //時間片過了則統計
        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);
            //定時刷入緩存
            this.zadd(listKey, NumberUtil.toDouble(scoreDate.getTime()), id);
            //設置過期時間
            expire(Sets.newHashSet(redisIdKey, listKey), getRo().expireSeconds());
        }
        //針對文章數量累加1
        this.hincrBy(redisIdKey, field, count);
    }
    public Date formatDate(Date date) {
        int preision = 60000 * PREISION_MINUTE;
        //算出x分鐘內的時間片
        long startDateTime = (long) (date.getTime() / preision) * preision;
        return new Date(startDateTime);

    }

定時任務同步

當然同步的時候除了同步每日的,還需要往主表的Ro進行數量增加

  /**
     * 同步redis的統計數量到數據庫
     */
    @Override
    public void syncByRedis() throws ParseException {

        int offset = 0;
        int size = 50;
        //隊列待消費數量越多 則每次最多偏移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]沒有數據忽略,offset:{},count:{}", offset, waitCount);
                break;
            }
            EweiTLogHandler eweiTLogHandler = new EweiTLogHandler();
            try {

                eweiTLogHandler.before(UUID.randomUUID().toString().replace("-", ""));
                //score到當前時間的數據信息 實現延遲效果
                List<QuestionMetricItemRo> questionMetricItemRos = questionMetricItemRedisDao.listById(ids);
                log.info("[QuestionMetricItemSync]執行同步,offset:{},count:{},Ids:{}", offset, waitCount, JSON.toJSONString(ids));
                log.info("執行同步questionMetricItems={}", JSON.toJSONString(questionMetricItemRos));
                List<QuestionMetricItem> questionMetricItems = QuestionMetricItemConvert.INSTANCE.toQuestionMetricItem(questionMetricItemRos);
                SpringUtil.getBean(IQuestionMetricItemService.class).batchSaveAndSyncQuestion(questionMetricItems);
            } catch (Exception e) {
                //埋點失敗也不影響後續執行
                log.error("[QuestionMetricItemSync]執行同步異常", e);
            } finally {
                questionMetricItemRedisDao.deleteByIdAndDelRouting(ids);
                eweiTLogHandler.clear();
            }
        }
    }

針對實時性

我們知道統計是根據我們的時間片有一定延遲的，針對報表有一定延遲是可以接收的,但是針對詳情需要實時性

不可能sum我們分日期的統計,直接用主表又會有延遲,很簡單 通過主表的數量+當前時間片未同步的數量就好了

 

如以下代碼

  /**
     * 合併當前時間片還未同步到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);
    }