Sql 在滚动窗口分区上统计不同的客户

我的问题类似于，但我有一个滚动窗口分区

我的查询看起来像这样，但不支持在COUNT in中使用distinct

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

我的目标是计算截至每个日期的唯一客户总数

我尝试使用，但它将完全失败，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

任何变通方法或不同的方法都会有帮助

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 |
+------+----------+--------------+

预期产量

+----------+--------------------------+------------------+--------------------------------------------+
|  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 |
+----------+--------------------------+------------------+--------------------------------------------+

---

一种解决方法使用子查询：

select p_date, seconds_read, 
    (
        select count(distinct t1.customer_id) 
        from table_x t1
        where t1.p_date <= t.p_date
    ) as total_cumulative_customer
from table_x t

---

一种解决方法使用子查询：

select p_date, seconds_read, 
    (
        select count(distinct t1.customer_id) 
        from table_x t1
        where t1.p_date <= t.p_date
    ) as total_cumulative_customer
from table_x t

对于此操作：

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;

通过两个级别的聚合，您几乎可以随心所欲：

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;

对读取的秒数求和也有点棘手，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;

对于此操作：

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;

通过两个级别的聚合，您几乎可以随心所欲：

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;

对读取的秒数求和也有点棘手，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;

---

我当前的表有100B行。你认为这个方法和其他方法一样好吗？我不是在质疑你的技能，我真的不知道哪一个会表演better@PirateX您在这里没有太多选择，因为count distinct不能用作窗口函数。我当前的表有100B行。你认为这个方法和其他方法一样好吗？我不是在质疑你的技能，我真的不知道哪一个会表演better@PirateX您在这里没有太多选择，因为count distinct不能用作窗口函数。样本数据和预期结果将有所帮助。“我不明白秒读的目的。@GordonLinoff添加了样本数据。读取的秒数将是累积总和。样本数据和预期结果将有所帮助。“我不明白秒读的目的。@GordonLinoff添加了样本数据。在一个滚动窗口中，相同的用户出现在多个窗口中时，秒读数将是累积的SUMIN，这会因为MINPYDATE？用户只在最短的日期被考虑。在滚动窗口中，同一个用户出现在多个窗口中，这会因为MINPYDATE？仅在最短日期考虑用户。