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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?
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