我有Table1,我需要让它看起来像Table2:
VisitingCount | Date ----------------------- 1 | 15:09 3 | 15:10 7 | 15:15 1 | 15:39 2 | 15:40 3 | 15:47
VisitingCount | Date ----------------------------- 11 | 15:00-15:30 6 | 15:30-16:00
我编写了这样的sql用户定义函数:
create FUNCTION [dbo].[fn_GetActivityLogsArranger] (@time AS nvarchar(max)) RETURNS nvarchar(max) AS BEGIN declare @Return varchar(30) select @Return = case when @time between '15:00' and '15:30' then '15:00-15:30' when @time between '15:30' and '16:00' then '15:30-16:00' when @time between '16:00' and '16:30' then '16:00-16:30' when @time between '16:00' and '16:30' then '16:00-16:30' when @time between '16:30' and '17:00' then '16:30-17:00' when @time between '17:00' and '17:30' then '17:00-17:30' when @time between '17:30' and '18:00' then '17:30-18:00' else 'Unknown' end return @Return end
在我的sql查询中调用UDF时,我获得了正确的结果:
select Count(Page) as VisitingCount, dbo.fn_GetActivityLogsArranger(CONVERT(VARCHAR(5),Date, 108)) as [Time] from scr_SecuristLog where Date between '2009-04-30' and '2009-05-02' AND [user] in ( select USERNAME from scr_CustomerAuthorities where customerID = Convert(varchar,4) and ID = Convert(varchar,43) ) group by dbo.fn_GetActivityLogsArranger(CONVERT(VARCHAR(5),Date, 108)) order by dbo.fn_GetActivityLogsArranger(CONVERT(VARCHAR(5),Date, 108)) asc
但是我不喜欢这种方法。我梦dream以求的代码如下所示:
select Count(Page) as VisitingCount, dbo.fn_GetActivityLogsArranger(CONVERT(VARCHAR(5),Date, 108)) as **[TIME]** from scr_SecuristLog where Date between '2009-04-30' and '2009-05-02' and user] in ( select USERNAME from scr_CustomerAuthorities where customerID = Convert(varchar,4) and ID = Convert(varchar,43) ) group by **[TIME]** order by **[TIME]** asc
您可以像视图一样加入表并在其中调用函数。这样,您可以在视图的列上调用分组依据和排序依据。
select Count(Page) as VisitingCount, [Time] from ( SELECT Page, Date, [user], dbo.fn_GetActivityLogsArranger(CONVERT(VARCHAR(5),Date, 108)) as [Time] FROM scr_SecuristLog ) scr_SecuristLog2 where Date between '2009-04-30' and '2009-05-02' and [user] in ( select USERNAME from scr_CustomerAuthorities where customerID=Convert(varchar,4) and ID=Convert(varchar,43) ) group by [Time] order by [Time] asc