Several group

Hello

Could someone tell me how I might have several group from the different count function?
Here's what I'm trying to do.

select x.prev_categ, x.next_categ,
       count(distinct user_id) as countprev2next,
       count(distinct user_id) as countprev2any,
       count(distinct user_id) as countany2next,
       count(distinct user_id) as countany2any
(
     select user_id, prev_categ,  next_categ,
               dense_rank() over (order by prev_categ, next_categ) as rankprev2next,
               dense_rank() over (order by prev_categ) as rankprev2any,
               dense_rank() over (order by next_categ) as rankany2next,
               dense_rank() over() as rankany2any
        from next_categ_data
        where x.prev_categ IS NOT NULL and x.next_categ IS NOT NULL
)x
group by x.prev_categ, x.next_categ
;

In the group by clause, I would like to have group by in the following terms:
(1) prev_categ and next_categ as shown in the query
(2) only prev_categ
(3) only next_categ
(4) user_id

By this motion, I am trying to accomplish the following:
For example, I have a transaction in which category A is passed to category B.
I want to count distinct users who moved from category:
(1) A to B (A2B)
(2) A to any category (A2X)
(3) any to B (X2B)
(4) all for the whole (X2X)

This must be done for all possible transactions.

Sample Data
create table final as

(
select 1 user_id,2 product_id,A categ_id, to_Date('1/1/2009','MM/DD/YYYY') dt from dual union all
select 1 user_id,3 product_id,B categ_id, to_Date('1/1/2009','MM/DD/YYYY') dt from dual union all
select 1 user_id,4 product_id,C categ_id, to_Date('1/3/2009','MM/DD/YYYY') dt from dual union all
select 1 user_id,5 product_id,D categ_id, to_Date('1/3/2009','MM/DD/YYYY') dt from dual union all
select 1 user_id,6 product_id,E categ_id, to_Date('1/3/2009','MM/DD/YYYY') dt from dual union all
select 1 user_id,7 product_id,F categ_id, to_Date('1/10/2009','MM/DD/YYYY') dt from dual union all
select 1 user_id,8 product_id,G categ_id, to_Date('1/11/2009','MM/DD/YYYY') dt from dual union all

select 2 user_id,2 product_id,A categ_id, to_Date('1/1/2009','MM/DD/YYYY') dt from dual union all
select 2 user_id,3 product_id,B categ_id, to_Date('1/2/2009','MM/DD/YYYY') dt from dual union all
select 2 user_id,4 product_id,C categ_id, to_Date('1/4/2009','MM/DD/YYYY') dt from dual union all
select 2 user_id,5 product_id,F categ_id, to_Date('1/5/2009','MM/DD/YYYY') dt from dual union all
select 2 user_id,6 product_id,H categ_id, to_Date('1/6/2009','MM/DD/YYYY') dt from dual union all
select 2 user_id,7 product_id,F categ_id, to_Date('1/12/2009','MM/DD/YYYY') dt from dual union all
select 2 user_id,8 product_id,G categ_id, to_Date('1/15/2009','MM/DD/YYYY') dt from dual union all

select 3 user_id,2 product_id,A categ_id, to_Date('1/11/2009','MM/DD/YYYY') dt from dual union all
select 3 user_id,3 product_id,C categ_id, to_Date('1/12/2009','MM/DD/YYYY') dt from dual union all
select 3 user_id,4 product_id,B categ_id, to_Date('1/13/2009','MM/DD/YYYY') dt from dual union all

) ;

Sample output
Prev_categ | Next_categ | countprev2next | countprev2any | countany2next | countany2any
---------------------------------------------------------------------------------------
  A            B              2                 3              3               3
  A            C              1                 -              3               3
  B            C              2                 2              -               3
  C            B              1                 3              -               3
  C            D              1                 -              1               3
  C            F              1                 -              2               3
  D            E              1                 1              1               3
  E            F              1                 1              -               3
  F            G              2                 2              2               3
  F            H              1                 -              1               3
  H            F              1                 1              -               3

Could you also tell me how I could make the County be repeated? For example, I want to count 3 to print for the two A to B and a-C
under column of prev2any.

I appreciate all help.

Thanks again,

Hello

You can do it with the analytical COUNT function:

SELECT DISTINCT
,       prev_categ
,       next_categ
,       COUNT (DISTINCT user_id) OVER (PARTITION BY prev_id
                          ,           next_id
                         )               AS countprev2next
,       COUNT (DISTINCT user_id) OVER (PARTITION BY prev_id)     AS countprev2any
,       COUNT (DISTINCT user_id) OVER (PARTITION BY next_id)     AS countany2next
,       COUNT (DISTINCT user_id) OVER ()               AS countany2any
FROM       next_categ_data
WHERE       next_categ     IS NOT NULL
ORDER BY  prev_categ
,       next_categ
;

Sorry, I'm not a database now, so I can't test it for 12 hours.

Looking at the code you posted, it seems as if you were on the right track with the partitions, only you were trying the wrong analytical function.

You really have a table like next_categ_data? Most people would use a view, if this isn't a subquery for this, unless the query speed was very important.

Tags: Database

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