Rollup/Cube help

Question

Hi,
Can anyone help me to get the following output with site-sub-total and grand-total within the one possible query: (I know it's possible either with Analytic function or new Group By Rollup/Cube functionality but do not know how to use them).
QUERY:
SELECT /*+ index(con con_start_end_i) */
con.id Contract,
con.property_id Property,
con.site_code,
con.ctyp_code,
con.crea_code,
con.purchase_price Puarchase_Amt,
con.commission_amount Comm_Amt,
con.start_date,
con.target_exchange_date,
con.target_completion_date,
con.empl_id,
con.sold_by
FROM
t_contracts con
WHERE
EXISTS ( SELECT 1 FROM t_employee_sites es WHERE es.emp_login_name = USER and es.site_code = con.site_code ) AND
con.empl_id LIKE '%' AND
NVL(con.sold_by,-1) = NVL(NULL, nvl(con.sold_by,-1)) AND
con.ctyp_code = 'SALE' AND
INSTR('WITHDRAW,PULL_OUT,', NVL(con.crea_code,'*')) = 0 AND
con.deleted IS NULL AND
(con.completed_date IS NULL OR con.completed_date > TO_DATE('13/06/2005', 'dd/mm/rrrr')) AND
con.start_date BETWEEN TO_DATE('13/06/2005', 'dd/mm/rrrr') and TRUNC(SYSDATE)
ORDER BY
con.site_code;
Sample Output:
Please find the following sample output:
Contract, Property, Crea_Code, Purchase_Amt, Comm_Amt, Start_Date, Sold_By
Site: <Site_Code1>
xxxx xxxx xxxx 9,999,999.99 9,999,999.99 dd/mm/yyyy xx
xxxx xxxx xxxx 9,999,999.99 9,999,999.99 dd/mm/yyyy xx
Total for Site: <Site_Code1> <Site1_Pur> <Site1_Comm>
No of Property: <Site1_Count>
Site: <Site_Code2>
xxxx xxxx xxxx 9,999,999.99 9,999,999.99 dd/mm/yyyy xx
xxxx xxxx xxxx 9,999,999.99 9,999,999.99 dd/mm/yyyy xx
Total for Site: <Site_Code2> <Site2_Pur> <Site2_Comm>
No of Property: <Site2_Count>
Total: <Tot_Pur> <Tot_Comm>
Total Property: <Tot_Count>
Your help would appreciate to sort this out asap....
Kind Regards,
B Tanna
London
UK

Answer 1

Hi Riedelme,
Thanks for your reply. Further to your reply I go through Group By functionality. I tried the different ways and found the solution. I have to use
GROUP BY GROUPING SETS(con.site_code, (con.site_code, con.id, con.property_id, con.ctyp_code, con.crea_code, con.start_date, con.target_exchange_date, con.target_completion_date, con.empl_id, con.sold_by), ())But now my worry is what happens if number of column grows, say, 35. There should be some way of writing good query. Would it be possible using Analytic Function.
Experts please respond..