SQL统计连续登陆3天的用户(连续活跃超3天用户)

2024-06-04 9231阅读

SQL统计连续登陆3天的用户(连续活跃超3天用户)

目录

    • SQL统计连续登陆3天的用户(连续活跃超3天用户)
      • 1. 数据准备
      • 2. 方法一: 差值计算
      • 3. 方法二: lead或lag函数
        • end

          1. 数据准备

          -- 数据准备
          WITH user_active_info AS (
          SELECT * FROM (
              VALUES ('10001' , '2023-02-01'),('10001' , '2023-02-03')
                    ,('10001' , '2023-02-04'),('10001' , '2023-02-05')
                    ,('10002' , '2023-02-02'),('10002' , '2023-02-03')
                    ,('10002' , '2023-02-04'),('10002' , '2023-02-05')
                    ,('10002' , '2023-02-07'),('10003' , '2023-02-02')
                    ,('10003' , '2023-02-03'),('10003' , '2023-02-04')
                    ,('10003' , '2023-02-05'),('10003' , '2023-02-06')
                    ,('10003' , '2023-02-07'),('10003' , '2023-02-08')
                    ,('10004' , '2023-02-03'),('10004' , '2023-02-04')
                    ,('10004' , '2023-02-06'),('10004' , '2023-02-07')
                    ,('10004' , '2023-02-08'),('10004' , '2023-02-08') 
              	  ,('10005' , '2023-02-02'),('10005' , '2023-02-05') 
          ) AS user_active_info(user_id, active_date) 
          )
          

          2. 方法一: 差值计算

          -- 1. 对用户数据进行分组,按照活跃日期进行排序(去重:防止有一天有多次活跃记录)
          SELECT 
                user_id
              , active_date
              , ROW_NUMBER() OVER(PARTITION BY user_id ORDER BY active_date) AS rn 
          FROM user_active_info
          GROUP BY user_id , active_date
          ; 
          
          user_idactive_datern
          100012023-02-011
          100012023-02-032
          100012023-02-043
          100012023-02-054
          100022023-02-021
          100022023-02-032
          100022023-02-043
          100022023-02-054
          100022023-02-075
          -- 2. 使用活跃日期和排序rn进行差值计算,得到的日期如果是相等的,就说明活跃日期是连续的
          SELECT 
                user_id
              , active_date
              , rn 
              , DATE_SUB(active_date,rn) AS sub_date
          FROM (
              SELECT 
                    user_id
                  , active_date
                  , ROW_NUMBER() OVER(PARTITION BY user_id ORDER BY active_date) AS rn 
              FROM user_active_info 
              GROUP BY user_id , active_date
              ) a
          ; 
          
          user_idactive_daternsub_date
          100012023-02-0112023-01-31
          100012023-02-0322023-02-01
          100012023-02-0432023-02-01
          100012023-02-0542023-02-01
          100022023-02-0212023-02-01
          100022023-02-0322023-02-01
          100022023-02-0432023-02-01
          100022023-02-0542023-02-01
          100022023-02-0752023-02-02
          -- 3. 按照user_id和sub_date 进行分组求和,筛选出连续登陆天数大于3天的用户
          SELECT 
                user_id
              , MIN(active_date) AS begin_date
              , MAX(active_date) AS end_date
              , COUNT (1) AS login_duration
          FROM (
              SELECT 
                    user_id
                  , active_date
                  , rn 
                  , DATE_SUB(active_date,rn) AS sub_date
              FROM (
                  SELECT 
                        user_id
                      , active_date
                      , ROW_NUMBER() OVER(PARTITION BY user_id ORDER BY active_date) AS rn 
                  FROM user_active_info 
                  GROUP BY user_id , active_date
              ) a
          ) b
          GROUP BY user_id , sub_date
          HAVING login_duration >= 3
          ; 
          
          user_idbegin_dateend_datelogin_duration
          100012023-02-032023-02-053
          100022023-02-022023-02-054
          100032023-02-022023-02-087
          100042023-02-062023-02-083

          3. 方法二: lead或lag函数

          -- 1. 将active_date 上抬2行,不存在默认为'0'(计算连续活跃3天以上的, 上抬2行,n天上抬n-1行)(去重:防止有一天有多次活跃记录)
          SELECT 
                user_id
              , active_date
              , lead(active_date , 2 , 0) OVER(PARTITION BY user_id ORDER BY active_date) AS lead_active_date 
          FROM user_active_info
          GROUP BY user_id , active_date
          
          user_idactive_datelead_active_date
          100012023-02-012023-02-04
          100012023-02-032023-02-05
          100012023-02-040
          100012023-02-050
          100022023-02-022023-02-04
          100022023-02-032023-02-05
          100022023-02-042023-02-07
          100022023-02-050
          100022023-02-070
          -- 2. 过滤筛选出, lead_active_date 与 active_date 差值为2的, 差值2 -> 连续活跃了3天
          SELECT 
                user_id , active_date , lead_active_date
          FROM (
              SELECT 
                    user_id
                  , active_date
                  , lead(active_date , 2 , 0) OVER(PARTITION BY user_id ORDER BY active_date) AS lead_active_date
              FROM user_active_info
              GROUP BY user_id , active_date
          ) a 
          WHERE  lead_active_date != '0'
              AND DATEDIFF(lead_active_date , active_date) = 2
          
          user_idactive_datelead_active_date
          100012023-02-032023-02-05
          100022023-02-022023-02-04
          100022023-02-032023-02-05
          -- 3. user_id 去重, 得到连续活跃天数>=3天的用户
          SELECT 
                user_id
          FROM (
              SELECT 
                    user_id , active_date , lead_active_date
              FROM (
                  SELECT 
                        user_id
                      , active_date
                      , lead(active_date , 2 , 0) OVER(PARTITION BY user_id ORDER BY active_date) AS lead_active_date 
                  FROM user_active_info
                  GROUP BY user_id , active_date
              ) a 
              WHERE  lead_active_date != '0'
                  AND DATEDIFF(lead_active_date , active_date) = 2
          ) b
          GROUP BY user_id
          
          user_id
          10001
          10002
          10003
          10004
          end

    免责声明:我们致力于保护作者版权,注重分享,被刊用文章因无法核实真实出处,未能及时与作者取得联系,或有版权异议的,请联系管理员,我们会立即处理! 部分文章是来自自研大数据AI进行生成,内容摘自(百度百科,百度知道,头条百科,中国民法典,刑法,牛津词典,新华词典,汉语词典,国家院校,科普平台)等数据,内容仅供学习参考,不准确地方联系删除处理! 图片声明:本站部分配图来自人工智能系统AI生成,觅知网授权图片,PxHere摄影无版权图库和百度,360,搜狗等多加搜索引擎自动关键词搜索配图,如有侵权的图片,请第一时间联系我们,邮箱:ciyunidc@ciyunshuju.com。本站只作为美观性配图使用,无任何非法侵犯第三方意图,一切解释权归图片著作权方,本站不承担任何责任。如有恶意碰瓷者,必当奉陪到底严惩不贷!

    目录[+]