subqueries, nested, using elements of the other party of the request

Hi all
I have a delicate problem, and I'll try to explain my best:

DB version is 11.2.0.3.0

create table product_list (product_id number,
                project_name varchar2(30))

create table products (product_id number,
                project_desc varchar2(30))

create table total_counts (product_id number,
                total_count number,
                project_name varchar2(30))

create table fixed_counts (product_id number,
                fixed_count number,
                project_name varchar2(30).
                    fixed_date date)
                    
create table product_rating (product_id number,
                rating number,
                quarter_last_updated number)
                    
create table quarters (quarter_id number,
                quarter_end_date date)


insert into product_list values (1, 'Prod 1');
insert into product_list values (2, 'Prod 2');
insert into product_list values (3, 'Prod 3');

insert into products values (1, 'Prod 1');
insert into products values (2, 'Prod 2');
insert into products values (3, 'Prod 3');

insert into total_counts values (1, 2000, 'Prod 1');
insert into total_counts values (2, 1000, 'Prod 2');
insert into total_counts values (3, 500, 'Prod 3');

insert into fixed_counts values (1, 1, 'Prod 1', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (1, 3, 'Prod 1', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (2, 50, 'Prod 2', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (2, 2, 'Prod 2', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (2, 3, 'Prod 2', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (2, 3, 'Prod 2', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (3, 8, 'Prod 3', to_date('01/01/2013','DD/MM/YYYY'));
insert into fixed_counts values (3, 3, 'Prod 3', to_date('01/03/2013','DD/MM/YYYY'));

insert into product_rating values (1, 1, 1);
insert into product_rating values (3, 2, 2);

insert into quarters values (1, to_date('01/10/2012','DD/MM/YYYY'));
insert into quarters values (2, to_date('01/02/2013','DD/MM/YYYY'));

My current query joins actually 2 tables 'TOTAL_COUNTS' and 'FIXED_COUNTS '. The FIXED_COUNTS table is updated every day when a product has a patch against it and the query returns a list of all products and their "fixed" rate percentage (used in an interactive report of the APEX).

select A.PRODUCT, A.TOTAL, B.FIXED, a.PROD_ID, round((FIXED/TOTAL) * 100,  2) percent
from (
select sum(a.total_count) TOTAL, a.product_id PROD_ID, d.Product_desc PRODUCT
from total_counts a, product_list c, products d
where a.product_id = c.product_id
and lower(a.project_name) = lower(c.project_name) 
and c.product_id = d.product_id
group by a.product_id, d.product_desc
) A
JOIN 
(
select sum(b.fixed_count) FIXED, b.product_id PROD_ID, d.Product_desc PRODUCT
from fixed_counts b, product_list c, products d
where b.product_id = c.product_id
and lower(b.project_name) = lower(c.project_name) 
and c.product_id = d.product_id
group by b.product_id, d.product_desc
) B
on A.PROD_ID = B.PROD_ID and A.PRODUCT = B.PRODUCT

It gives me a result like:

PRODUCT     TOTAL     FIXED     PROD_ID     percent
Prod 1     2000     4     1     0.2
Prod 2     1000     58     2     5.8
Prod 2      500     11     3     2.2

The application works very well and does exactly the job I need. However, I now a requirement that when a product gets a percentage rate 'fixed' more than 1% of the product gets a point added against her in a table 'product_rating' and I have to recalculate the percentage of the date, the item has been added (so no points added we take all 'fixed').

To do this, I added 2 new tables: "product_rating" and "quarters". The "product_rating" table contains the Product_id and points, he has accumulated so far. It is updated once a quarter. 'Quarters' table simply contains the dates for us to use for calculations again.

Actually, I need to replace this:

sum(b.fixed_count) FIXED

with something like this:

if a product has a point against it in the "product_rating" table then we just show fixes from the date the point was added i.e. 
select sum(b.fixed_count) from fixed_counts b, product_rating c, quarters d
where b.product_id = c.product_id and c.quarter_last_updated = d.quarter_id
and b.product_id = PROD_ID
and b.fixed_date > (select quarter_end_date from quarters where quarter_id = the_last_quarter_updated)

Based on the values in the tables above the percentages for "3 Prod' should now be 0.6.» It is because he received a product_rating the quarter 2, then the new calculation is based on all the "corrections" after this date (only the last March 1 13').

I tried many ways to integrate this into the current query, but I can't make it work. Sorry for not adding the info from the entire table, but the tables total_counts and fixed_counts have many more columns that I removed the query so it would be easier to observe. Thanks in advance for your help. If I can add more info ask please.
Tom

Published by: on May 14, 2013 TomH 08:54

Published by: on May 14, 2013 TomH 08:58

TomH wrote:
of course, to the right, thank you.
I added some info table and data that will hopefully a little easier to understand.

OK, thank you... to the future but please try and run the commands yourself for you sure they work. What you provided is close, but it has not executed immediately without modifications.

I will start by expressing my concerns for your data model, it seems... well, for lack of a better word. Although you said you deleted a bunch of stuff to make the example. You have someone, you you work who can look at the model for you?

With respect to the query, it's not pretty (I'm in a bit of a rush here) so you can probably clean it considerably. I just tried to show the basics of what you're going to have to do.

ME_XE? with base_data as
  2  (
  3     select
  4        b.fixed_date,
  5        b.fixed_count,
  6        b.product_id ,
  7        d.project_desc
  8     from fixed_counts b, product_list c, products d
  9     where b.product_id = c.product_id
 10     and lower(b.project_name) = lower(c.project_name)
 11     and c.product_id = d.product_id
 12  ),
 13     final_base_data as
 14  (
 15     select
 16        b.product_id      PROD_ID,
 17        b.project_desc    PRODUCT,
 18        sum
 19        (
 20           case
 21              when b.fixed_date >= stuff.quarter_end_date or stuff.quarter_end_date is null
 22              then
 23                 b.fixed_count
 24              else
 25                 0
 26           end
 27        )  as FIXED
 28     from base_data b
 29     left outer join
 30     (
 31        select
 32           pr.product_id,
 33           qr.quarter_end_date
 34        from product_rating pr , quarters qr
 35        where pr.quarter_last_updated = qr.quarter_id
 36     )  stuff
 37     on (stuff.product_id = b.product_id)
 38     group by b.product_id, b.project_desc
 39  )
 40  select A.PRODUCT, A.TOTAL, B.FIXED, a.PROD_ID, round((b.FIXED/a.TOTAL) * 100,  2) percent
 41  from
 42  (
 43     select sum(a.total_count) TOTAL, a.product_id PROD_ID, d.project_desc PRODUCT
 44     from total_counts a, product_list c, products d
 45     where a.product_id = c.product_id
 46     and lower(a.project_name) = lower(c.project_name)
 47     and c.product_id = d.product_id
 48     group by a.product_id, d.project_desc
 49  ) A
 50  JOIN final_base_data B
 51  on A.PROD_ID = B.PROD_ID and A.PRODUCT = B.PRODUCT
 52  ;

PRODUCT                                     TOTAL              FIXED            PROD_ID            PERCENT
------------------------------ ------------------ ------------------ ------------------ ------------------
Prod 1                                       2000                  4                  1                 .2
Prod 2                                       1000                 58                  2                5.8
Prod 3                                        500                  3                  3                 .6

3 rows selected.

See you soon,.

Tags: Database

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