国庆期间每类视频点赞量和转发量

描述

用户-视频互动表tb_user_video_log

id	uid	video_id	start_time	end_time	if_follow	if_like	if_retweet	comment_id
1	101	2001	2021-09-24 10:00:00	2021-09-24 10:00:20	1	1	0	NULL
2	105	2002	2021-09-25 11:00:00	2021-09-25 11:00:30	0	0	1	NULL
3	102	2002	2021-09-25 11:00:00	2021-09-25 11:00:30	1	1	1	NULL
4	101	2002	2021-09-26 11:00:00	2021-09-26 11:00:30	1	0	1	NULL
5	101	2002	2021-09-27 11:00:00	2021-09-27 11:00:30	1	1	0	NULL
6	102	2002	2021-09-28 11:00:00	2021-09-28 11:00:30	1	0	1	NULL
7	103	2002	2021-09-29 11:00:00	2021-10-02 11:00:30	1	0	1	NULL
8	102	2002	2021-09-30 11:00:00	2021-09-30 11:00:30	1	1	1	NULL
9	101	2001	2021-10-01 10:00:00	2021-10-01 10:00:20	1	1	0	NULL
10	102	2001	2021-10-01 10:00:00	2021-10-01 10:00:15	0	0	1	NULL
11	103	2001	2021-10-01 11:00:50	2021-10-01 11:01:15	1	1	0	1732526
12	106	2002	2021-10-02 10:59:05	2021-10-02 11:00:05	2	0	1	NULL
13	107	2002	2021-10-02 10:59:05	2021-10-02 11:00:05	1	0	1	NULL
14	108	2002	2021-10-02 10:59:05	2021-10-02 11:00:05	1	1	1	NULL
15	109	2002	2021-10-03 10:59:05	2021-10-03 11:00:05	0	1	0	NULL

（uid-用户ID, video_id-视频ID, start_time-开始观看时间, end_time-结束观看时间, if_follow-是否关注, if_like-是否点赞, if_retweet-是否转发, comment_id-评论ID）

短视频信息表tb_video_info

id	video_id	author	tag	duration	release_time
1	2001	901	旅游	30	2020-01-01 07:00:00
2	2002	901	旅游	60	2021-01-01 07:00:00
3	2003	902	影视	90	2020-01-01 07:00:00
4	2004	902	美女	90	2020-01-01 08:00:00

（video_id-视频ID, author-创作者ID, tag-类别标签, duration-视频时长, release_time-发布时间）

问题：统计2021年国庆头3天每类视频每天的近一周总点赞量和一周内最大单天转发量，结果按视频类别降序、日期升序排序。假设数据库中数据足够多，至少每个类别下国庆头3天及之前一周的每天都有播放记录。

输出示例：

示例数据的输出结果如下

tag	dt	sum_like_cnt_7d	max_retweet_cnt_7d
旅游	2021-10-01	5	2
旅游	2021-10-02	5	3
旅游	2021-10-03	6	3

解释：

由表tb_user_video_log里的数据可得只有旅游类视频的播放，2021年9月25到10月3日每天的点赞量和转发量如下：

tag	dt	like_cnt	retweet_cnt
旅游	2021-09-25	1	2
旅游	2021-09-26	0	1
旅游	2021-09-27	1	0
旅游	2021-09-28	0	1
旅游	2021-09-29	0	1
旅游	2021-09-30	1	1
旅游	2021-10-01	2	1
旅游	2021-10-02	1	3
旅游	2021-10-03	1	0

因此国庆头3天（10.01~10.03）里10.01的近7天（9.25~10.01）总点赞量为5次，单天最大转发量为2次（9月25那天最大）；同理可得10.02和10.03的两个指标。

示例1

输入：

DROP TABLE IF EXISTS tb_user_video_log, tb_video_info;
CREATE TABLE tb_user_video_log (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    uid INT NOT NULL COMMENT '用户ID',
    video_id INT NOT NULL COMMENT '视频ID',
    start_time datetime COMMENT '开始观看时间',
    end_time datetime COMMENT '结束观看时间',
    if_follow TINYINT COMMENT '是否关注',
    if_like TINYINT COMMENT '是否点赞',
    if_retweet TINYINT COMMENT '是否转发',
    comment_id INT COMMENT '评论ID'
) CHARACTER SET utf8 COLLATE utf8_bin;

CREATE TABLE tb_video_info (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    video_id INT UNIQUE NOT NULL COMMENT '视频ID',
    author INT NOT NULL COMMENT '创作者ID',
    tag VARCHAR(16) NOT NULL COMMENT '类别标签',
    duration INT NOT NULL COMMENT '视频时长(秒数)',
    release_time datetime NOT NULL COMMENT '发布时间'
)CHARACTER SET utf8 COLLATE utf8_bin;

INSERT INTO tb_user_video_log(uid, video_id, start_time, end_time, if_follow, if_like, if_retweet, comment_id) VALUES
   (101, 2001, '2021-09-24 10:00:00', '2021-09-24 10:00:20', 1, 1, 0, null)
  ,(105, 2002, '2021-09-25 11:00:00', '2021-09-25 11:00:30', 0, 0, 1, null)
  ,(102, 2002, '2021-09-25 11:00:00', '2021-09-25 11:00:30', 1, 1, 1, null)
  ,(101, 2002, '2021-09-26 11:00:00', '2021-09-26 11:00:30', 1, 0, 1, null)
  ,(101, 2002, '2021-09-27 11:00:00', '2021-09-27 11:00:30', 1, 1, 0, null)
  ,(102, 2002, '2021-09-28 11:00:00', '2021-09-28 11:00:30', 1, 0, 1, null)
  ,(103, 2002, '2021-09-29 11:00:00', '2021-09-29 11:00:30', 1, 0, 1, null)
  ,(102, 2002, '2021-09-30 11:00:00', '2021-09-30 11:00:30', 1, 1, 1, null)
  ,(101, 2001, '2021-10-01 10:00:00', '2021-10-01 10:00:20', 1, 1, 0, null)
  ,(102, 2001, '2021-10-01 10:00:00', '2021-10-01 10:00:15', 0, 0, 1, null)
  ,(103, 2001, '2021-10-01 11:00:50', '2021-10-01 11:01:15', 1, 1, 0, 1732526)
  ,(106, 2002, '2021-10-02 10:59:05', '2021-10-02 11:00:05', 2, 0, 1, null)
  ,(107, 2002, '2021-10-02 10:59:05', '2021-10-02 11:00:05', 1, 0, 1, null)
  ,(108, 2002, '2021-10-02 10:59:05', '2021-10-02 11:00:05', 1, 1, 1, null)
  ,(109, 2002, '2021-10-03 10:59:05', '2021-10-03 11:00:05', 0, 1, 0, null);

INSERT INTO tb_video_info(video_id, author, tag, duration, release_time) VALUES
   (2001, 901, '旅游', 30, '2020-01-01 7:00:00')
  ,(2002, 901, '旅游', 60, '2021-01-01 7:00:00')
  ,(2003, 902, '影视', 90, '2020-01-01 7:00:00')
  ,(2004, 902, '美女', 90, '2020-01-01 8:00:00');

输出：

旅游|2021-10-01|5|2
旅游|2021-10-02|5|3
旅游|2021-10-03|6|3

分析:

第一步先显示tag、dt、like_cnt、retweet_cnt，所以要进行链表，和左连接

    select
      tb2.tag,
      DATE(start_time) dt,
      sum(if_like) like_cnt,
      sum(if_retweet) retweet_cnt
    from
      tb_user_video_log tb1
      left join tb_video_info tb2 on tb1.video_id = tb2.video_id
    where
      DATE(start_time) BETWEEN '2021-09-25' AND '2021-10-03'
    group by
      dt,
      tag

第二步使用开窗函数进行，partition by找到tag符合的数据，时间进行逆序，并且找6行

select
  tag,
  dt,
  sum(like_cnt) over(
    partition by tag
    order by
      dt rows 6 preceding
  ),
  max(retweet_cnt) over(
    partition by tag
    order by
      dt rows 6 preceding
  ) max_retweet_cnt_7d
from
  (
    select
      tb2.tag,
      DATE(start_time) dt,
      sum(if_like) like_cnt,
      sum(if_retweet) retweet_cnt
    from
      tb_user_video_log tb1
      left join tb_video_info tb2 on tb1.video_id = tb2.video_id
    where
      DATE(start_time) BETWEEN '2021-09-25' AND '2021-10-03'
    group by
      dt,
      tag
  ) a

第三步根据题目要求进行数据过滤和排序就行了

select
  *
from
  (
    select
      tag,
      dt,
      sum(like_cnt) over(
        partition by tag
        order by
          dt rows 6 preceding
      ),
      max(retweet_cnt) over(
        partition by tag
        order by
          dt rows 6 preceding
      ) max_retweet_cnt_7d
    from
      (
        select
          tb2.tag,
          DATE(start_time) dt,
          sum(if_like) like_cnt,
          sum(if_retweet) retweet_cnt
        from
          tb_user_video_log tb1
          left join tb_video_info tb2 on tb1.video_id = tb2.video_id
        where
          DATE(start_time) BETWEEN '2021-09-25' AND '2021-10-03'
        group by
          dt,
          tag
      ) a
  ) b
where
  dt between '2021-10-01' and '2021-10-03'
order by
  tag desc,
  dt

posted @ 2022-12-13 17:06 网抑云黑胶SVIP用户阅读(62) 评论(0) 收藏举报

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国庆期间每类视频点赞量和转发量

描述

示例1

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