SQL 保留率

Question

我正在尝试构建一个滚动保留度量，但在弄清楚如何在 redshift 中执行它时遇到了麻烦。

我将留存定义为两组用户之间的交集。第一个是一组不同的用户 ID，从今天起 90 天内至少在该日期起 30 天内（从今天起 90 到 120 天）活跃过一次。第二个是从今天起过去 30 天内活跃的用户数。

留存率 = 90 天前原始队列中的今天 30 天活跃用户 / 90 天前 30 天活跃用户

我的会话表如下所示：

id	created_date
1	2021-03-04
1	2021-01-01
1	2020-12-15
2	2021-02-17

我似乎可以这样做的唯一方法如下：

1. 创建一个寺庙表并插入今天的日期。

with t1 as (
    select distinct customer_id id
    from sessions
    and created_date >= dateadd('day', -29, current_date)
    )
, t2 as (
    select distinct customer_id id
    from sessions
    and created_date <= dateadd('day', -89, current_date) 
    and created_date >= dateadd('day', -119, current_date)
    )
select current_date, 
    count(t1.id) as original, 
    count(t2.id) as current,
    round(cast(count(t2.id) as float) / cast(count(t1.id) as float), 2) as ratio
into temp table temp1
from t1
left join t2
on t1.id = t2.id

1. 在临时表中多次运行插入语句，每次查询从当前日期减去一天

insert into temp1
with t1 as (
    select distinct customer_id id
    from sessions 
    and created_date >= dateadd('day', -29, current_date-1)
    )
, t2 as (
    select distinct customer_id id
    from sessions
    and created_date <= dateadd('day', -89, current_date-1) 
    and created_date >= dateadd('day', -119, current_date-1)
    )
select current_date-1,  
    count(t1.id) as original, 
    count(t2.id) as current,
    round(cast(count(t2.id) as float) / cast(count(t1.id) as float), 2) as ratio
from t1
left join t2
on t1.id = t2.id

1. 获取此表，其中包含 2021 年迄今为止所有日期的每日保留率

原始列是自参考日期起 90 天前 30 天活跃用户的用户群组。 当前列是原始列中同类群组中在参考日期为 30 天活跃用户的用户数。

第 1 步仅返回第一行 2021-03-05，第 2 步返回另一行。

date	original	current	ratio
2021-03-05	100	70	0.7
2021-03-04	100	60	0.6

这个过程显然效率很低，我想知道是否有更快、更简单的方法来做到这一点？问题是我需要比较 3 个月前的不同用户群组，然后看看今天有多少来自群组的用户仍然活跃。

我们将不胜感激！

Answer 1

如果要获取每个日期今天30天和90天前的用户数，查询为：

with t1 as (
  select
    s2.created_date,
    count(distinct customer_id id) as cnt30
  from sessions s1 inner join
    (select distinct created_date from sessions) s2
    on dateadd('day', -29, s2.created_date)<=s1.created_date
       and s1.created_date<=s2.created_date
  group by s2.created_date
)
select a1.current_date, 
  a1.cnt30 as original, 
  a2.cnt32 as current,
  round(cast(a2.cnt30) as float) / cast(count(a1.cnt30) as float), 2) as ratio
from t1 as a1 inner join t1 as a2
  on dateadd('day', -89, a1.created_date)=a2.created_date
order by 1

使用选择列表中的子查询，查询是：

with t1 as (
  select
    s2.created_date,
    (select count(distinct s1.customer_id) from sessions s1
     where dateadd('day', -29, s2.created_date)<=s1.created_date
       and s1.created_date<=s2.created_date) as cnt30
  from
    (select distinct created_date from sessions) s2
)
select a1.current_date, 
  a1.cnt30 as original, 
  a2.cnt32 as current,
  round(cast(a2.cnt30) as float) / cast(count(a1.cnt30) as float), 2) as ratio
from t1 as a1 inner join t1 as a2
  on dateadd('day', -89, a1.created_date)=a2.created_date
order by 1

首先，使用联接和子查询计算每个日期过去 30 天的唯一 ID 数。 接下来，加入相同的表并输出当天和 90 天前的唯一 ID 数。

请注意，我从未使用过 redshift，所以我将根据您的查询和常见的 SQL 语法编写此内容。希望我的回答对你有所帮助。