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sql - 通过滚动窗口分区计算不同的客户

转载 作者:行者123 更新时间:2023-12-05 09:37:20 27 4
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我的问题类似于redshift: count distinct customers over window partition但我有一个滚动窗口分区。

我的查询看起来像这样,但在 Redshift 中的 COUNT 个中是不同的不支持

select p_date, seconds_read, 
count(distinct customer_id) over (order by p_date rows between unbounded preceding and current row) as total_cumulative_customer
from table_x

我的目标是计算每个日期的唯一身份客户总数(因此滚动窗口)。

我尝试使用 dense_rank() approach但它会失败,因为我不能像这样使用窗口函数

select p_date, max(total_cumulative_customer) over ()
(select p_date, seconds_read,
dense_rank() over (order by customer_id rows between unbounded preceding and current row) as total_cumulative_customer -- WILL FAIL HERE
from table_x

任何解决方法或不同的方法都会有所帮助!

编辑:

输入数据样本

+------+----------+--------------+
| Cust | p_date | seconds_read |
+------+----------+--------------+
| 1 | 1-Jan-20 | 10 |
| 2 | 1-Jan-20 | 20 |
| 4 | 1-Jan-20 | 30 |
| 5 | 1-Jan-20 | 40 |
| 6 | 5-Jan-20 | 50 |
| 3 | 5-Jan-20 | 60 |
| 2 | 5-Jan-20 | 70 |
| 1 | 5-Jan-20 | 80 |
| 1 | 5-Jan-20 | 90 |
| 1 | 7-Jan-20 | 100 |
| 3 | 7-Jan-20 | 110 |
| 4 | 7-Jan-20 | 120 |
| 7 | 7-Jan-20 | 130 |
+------+----------+--------------+

预期输出

+----------+--------------------------+------------------+--------------------------------------------+
| p_date | total_distinct_cum_cust | sum_seconds_read | Comment |
+----------+--------------------------+------------------+--------------------------------------------+
| 1-Jan-20 | 4 | 100 | total distinct cust = 4 i.e. 1,2,4,5 |
| 5-Jan-20 | 6 | 450 | total distinct cust = 6 i.e. 1,2,3,4,5,6 |
| 7-Jan-20 | 7 | 910 | total distinct cust = 6 i.e. 1,2,3,4,5,6,7 |
+----------+--------------------------+------------------+--------------------------------------------+

最佳答案

对于这个操作:

select p_date, seconds_read, 
count(distinct customer_id) over (order by p_date rows between unbounded preceding and current row) as total_cumulative_customer
from table_x;

您可以通过两个级别的聚合来做您想做的事情:

select min_p_date,
sum(count(*)) over (order by min_p_date rows between unbounded preceding and current row) as running_distinct_customers
from (select customer_id, min(p_date) as min_p_date
from table_x
group by customer_id
) c
group by min_p_date;

对读取的秒数求和有点棘手,但您可以使用相同的想法:

select p_date,
sum(sum(seconds_read)) over (order by p_date rows between unbounded preceding and current row) as seconds_read,
sum(sum(case when seqnum = 1 then 1 else 0 end)) over (order by p_date rows between unbounded preceding and current row) as running_distinct_customers
from (select customer_id, p_date, seconds_read,
row_number() over (partition by customer_id order by p_date) as seqnum
from table_x
) c
group by min_p_date;

关于sql - 通过滚动窗口分区计算不同的客户,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/64326651/

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