留存率的时间区间怎么设置？

取N天 第次、7、30留存
如何设置n的变量，取1月整月 次 7 30留存

select
  site `端口`,count(distinct aa.user_id) as`用户数`,
  count(distinct bb.user_id) / count(distinct aa.user_id) as`次日留存率`,
  count(distinct cc.user_id) / count(distinct aa.user_id) as`7日留存率`,
  count(distinct dd.user_id) / count(distinct aa.user_id) as`30日留存率`,aa.dt `日期`
from
      ( select
          distinct dt,
          user_id
        from 表明
        where
          dt='N'
      ) aa
     
left join (
        select
          distinct dt,
          user_id,
        from
          表名
        where
          dt='N+1'
      ) bb on aa.user_id = bb.user_id
      and aa.site = bb.site

left join (
        select
          distinct dt,
          user_id,
        from
          表名
        where
          dt='N+7'
      ) cc on aa.user_id = bb.user_id
      and aa.site = cc.site

left join (
        select
          distinct dt,
          user_id,
        from
          表名
        where
          dt='N+30'
      ) dd on aa.user_id = dd.user_id
      and aa.site = bb.site
      
group by
  aa.dt,
  aa.site

用开窗函数的滑动窗口，可以实现取当前行的下N行，
先提前统计一个数据， dt、site、人数count，3个字段作为子查询，
然后按site分组，按日期排序，取当前行往下数的第7行，比如下面这个，就能在同一行取到第7天的数据了

first_value(人数count) over(partition by site order by dt rows between 7 following and 7 following)

看上去没我之前想的那么简单，还需要排除新用户的影响，那么这个时候就需要先得到一个数据，即每个用户每天在次日、7日、30日时的登录状态，这个可以使用开窗函数中的range between来处理，排序用日期差，这样1天就是一个range


--测试表
create table test_20220318b (dt string,user_id string, site string);
insert into test_20220318b values('20220201','a','app01');
insert into test_20220318b values('20220202','a','app01');
insert into test_20220318b values('20220203','a','app01');
insert into test_20220318b values('20220208','a','app01');
insert into test_20220318b values('20220228','a','app01');
insert into test_20220318b values('20220301','a','app01');
insert into test_20220318b values('20220302','a','app01');
insert into test_20220318b values('20220303','a','app01');
insert into test_20220318b values('20220308','a','app01');
insert into test_20220318b values('20220201','b','app01');
insert into test_20220318b values('20220202','b','app01');
insert into test_20220318b values('20220228','b','app01');
insert into test_20220318b values('20220301','b','app01');
insert into test_20220318b values('20220308','b','app01');


--查询sql
select dt,site,
sum(d1)/count( user_id) `次日留存率`,
sum(d7)/count( user_id) `7日留存率`,
sum(d30)/count( user_id) `30日留存率` 
from (
select aa.dt ,
       aa.site ,
       user_id,
       count(distinct user_id) over(partition by user_id order by df
       range between  current row and 1 following )-1 d1,
       count(distinct user_id) over(partition by user_id order by df
       range between  6 following and 7 following ) d7,
       count(distinct user_id) over(partition by user_id order by df 
       range between  29 following and 30 following ) d30
  from (select distinct dt,
                user_id ,
                site ,
                datediff(from_unixtime(unix_timestamp(dt,'yyyyMMdd'),'yyyy-MM-dd'), 
                         from_unixtime(unix_timestamp('20220201','yyyyMMdd'),'yyyy-MM-dd')) df
          from test_20220318b
         where dt >= '20220201'
        ) aa ) bb
        group by dt,site

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