我试图根据列和另一列的日期范围获取唯一的行列表。以下是示例数据:
billing.Text = "$" + ds.Tables[0].Rows[0]["Billing"].ToString();
我需要按CustomerNum分组,然后按ServiceDate进行分组,但仅限于ServiceDate在7天内。我希望通过分组获得最大(最新)行。所以结果应该是:
id CustomerNum ServiceDate
------------------------------------------------
4406290 000000000066 2017-02-17 13:03:00.000
4406294 000000000066 2017-02-17 13:07:00.000
4406295 000000000066 2017-02-17 13:09:00.000
4406295 000000000066 2017-02-09 13:09:00.000
4406352 000000000066 2017-01-17 13:12:00.000
4406369 000000000066 2017-03-17 13:16:00.000
4582381 000000ABC102 2016-03-22 14:48:00.017
4589037 000000ABC102 2016-07-23 14:54:11.223
4625101 000009983148 2017-03-30 15:21:11.283
4625162 000005555398 2017-01-30 11:22:20.907
4625165 000005555398 2017-03-30 12:22:20.907
4625168 000005555398 2017-03-30 15:22:20.907
我尝试过以下方法:
id CustomerNum ServiceDate
------------------------------------------------
4406295 000000000066 2017-02-17 13:09:00.000
4406295 000000000066 2017-02-09 13:09:00.000
4406352 000000000066 2017-01-17 13:12:00.000
4406369 000000000066 2017-03-17 13:16:00.000
4582381 000000ABC102 2016-03-22 14:48:00.017
4589037 000000ABC102 2016-07-23 14:54:11.223
4625101 000009983148 2017-03-30 15:21:11.283
4625162 000005555398 2017-01-30 11:22:20.907
4625168 000005555398 2017-03-30 15:22:20.907
但这会在所有CustomerNum上给出行号,而不是在满足日期范围后在1处开始行号。
我知道我错过了什么。有什么想法吗?谢谢。
答案 0 :(得分:2)
对于此问题,您希望使用lag()
和累计总和。使用滞后来确定每个组的起始位置,然后使用累计和来分配组:
select sum(case when prev_ServiceDate > dateadd(day, -7, ServiceDate) then 0 else 1 end) over
(partition by CustomerNum order by ServiceDate) as grp
from (select ct.*,
lag(ServiceDate) over (partition by CustomerNum order by ServiceDate) as prev_ServiceDate
from CustomerTransactions ct
) ct;
然后,您可以使用聚合汇总组:
select CustomerNum, min(ServiceDate), max(ServiceDate)
from (select sum(case when prev_ServiceDate > dateadd(day, -7, ServiceDate) then 0 else 1 end) over
(partition by CustomerNum order by ServiceDate) as grp
from (select ct.*,
lag(ServiceDate) over (partition by CustomerNum order by ServiceDate) as prev_ServiceDate
from CustomerTransactions ct
) ct
) ct
group by CustomerNum, grp