|
Thanks. That is what I thought as well but even within the first
grouping of "date2" I get weird results when I add the partition by:
dense_rank() over(partition by lsdte order by lsdte,lrdte)) as daycount
LRDTE LSDTE DayCount
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/18/11 04/02/11 2
04/18/11 04/02/11 1
04/18/11 04/02/11 2
04/18/11 04/02/11 2
04/18/11 04/02/11 1
04/21/11 04/02/11 3
04/21/11 04/02/11 2
04/21/11 04/02/11 3
04/21/11 04/02/11 3
There are other columns in this data set and the CTE itself is pretty
ugly. Could other columns in the data set cause the "partition to" to
break prematurely? I tried sorting the entire CTE with an 'Order by'
with the date2, and date1 but I can't explain the "reset" of the ranking.
If I drop the 'partition by' I get the following:
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/17/11 04/02/11 1
04/18/11 04/02/11 2
04/18/11 04/02/11 2
04/18/11 04/02/11 2
04/18/11 04/02/11 2
04/18/11 04/02/11 2
04/21/11 04/02/11 3
04/21/11 04/02/11 3
04/21/11 04/02/11 3
04/21/11 04/02/11 3
04/21/11 04/02/11 3
04/22/11 04/02/11 4
04/22/11 04/02/11 4
04/22/11 04/02/11 4
04/22/11 04/02/11 4
04/22/11 04/02/11 4
05/02/11 05/16/11 5 <== Should be '1'
05/02/11 05/16/11 5
05/02/11 05/16/11 5
05/02/11 05/16/11 5
I could show you the whole SQL with the CTE but it IS a monster...
Pete Helgren
Value Added Software, Inc
www.asaap.com
www.opensource4i.com
On 3/8/2011 2:16 PM, Schutte, Michael D wrote:
You will need to add partition by to the over(). Partition by date2 will cause the counter to start over when it changes.--
So....
Dense_rank() over(partition by date2 order by date1)
-----Original Message-----
From: midrange-l-bounces@xxxxxxxxxxxx [mailto:midrange-l-bounces@xxxxxxxxxxxx] On Behalf Of Pete Helgren
Sent: Tuesday, March 08, 2011 3:43 PM
To: Midrange Systems Technical Discussion
Subject: Dense_Rank Revisited
It looked like dense_rank did the trick with my sample data but when I
had a larger data set I ran into a snag that may not have been apparent
in the example I presented. Here is a slightly different variation that
describes the remaining issue.
BB8179 04/17/11 04/02/11
BE7214 04/17/11 04/02/11
BE7488 04/18/11 04/02/11
BE2178 04/18/11 04/02/11
BE1618 04/18/11 04/02/11
BD9608 04/21/11 04/02/11
BE2180 04/21/11 04/02/11
BE1696 04/21/11 04/02/11
BD9607 05/7/11 05/28/11
BB6382 05/7/11 05/28/11
BB7942 05/10/11 05/28/11
BE7487 05/10/11 05/28/11
BE7489 05/11/11 05/28/11
BE2179 05/11/11 05/28/11
BE8955 05/11/11 05/28/11
What I would like to do is count the unique occurrences of the first
date column within the *same* occurrence of the second date column.
Something like:
BB8179 04/17/11 1 04/02/11
BE7214 04/17/11 1 04/02/11
BE7488 04/18/11 2 04/02/11
BE2178 04/18/11 2 04/02/11
BE1618 04/18/11 2 04/02/11
BD9608 04/21/11 3 04/02/11
BE2180 04/21/11 3 04/02/11
BE1696 04/21/11 3 04/02/11
BD9607 05/7/11 1 05/28/11
BB6382 05/7/11 1 05/28/11
BB7942 05/10/11 2 05/28/11
BE7487 05/10/11 2 05/28/11
BE7489 05/11/11 3 05/28/11
BE2179 05/11/11 3 05/28/11
BE8955 05/11/11 3 05/28/11
I tried adding the second column to the order by clause but that seemed
to make no difference. I also tried 'partition' by using the second
column but that also didn't deliver the desired result. Ideas?
--
Pete Helgren
Value Added Software, Inc
www.asaap.com
www.opensource4i.com
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