Question

I have oracle 10g installed on windows server 2003.
I have 22,000,000 records in single table and this is a transactional table,
increasing of records in same table approx. 50,000 per month.

My question is that whenever I run query on it always my query too slow.
Is there any method by which I can improve the performance of the query, like partitioning the table or else?

the query is

select a.prd_code
       , a.br_code||'-'||br_title
       , a.size_code||'-'||size_title
       ,size_in_gms
       , a.var_code||'-'||var_title
      , a.form_code||'-'||form_title
      , a.pack_code||'-'||pack_title
      , a.pack_type_code||'-'||pack_type_title
      , start_date
      , end_date
      , a.price
from   prices a
       , brand br
       ,  (select distinct prd_code
                 , br_code
                 ,  size_code
                 , var_code
                 , form_code
                 ,packing_code
                 ,  pack_type_code 
            from cphistory 
            where prd_code = '01' 
            and flag = 'Y'  
            and project_yy = '2009' and '01' and '10') cp
       , (select prd_code
                , br_code
                , size_code
                , size_in_gms
          from sizes 
          where prd_code = '01' 
          and end_date = '31-dec-2050' 
          and flag = 'Y') sz
        ,  (select prd_code
                   , br_code
                   , var_code
                   , var_title 
              from varient) vt
          , (select prd_code
                    , br_code
                    , form_code
                    , form_title 
             from form) fm
          ,  (select prd_code
                     , pack_title 
               from package) pc
          ,    (select prd_code
                       , pack_type_title
                 from pakck_type) pt
where a.prd_code = br.prd_code 
and   a.br_code  = br_br_code
and   a.prd_code = sz.prd_code
and   a.br_code  = sz.br_code
and   a.size_code = sz.size_code
and   a.prd_code  = vt.prd_code
and   a.br_code   = vt.br_code
and   a.var_code  = vt.var_code
and   a.prd_code  = fm.prd_code
and   a.br_code   = fm.br_code
and   a.form_code = fm.form_code
and   a.prd_code  = pc.prd_code
and   a.br_code   = pc.br_code
and   a.pack_code = pc.pack_code
and   a.prd_code  = pt.prd_code
and   a.pack_type_code = pt.pack_type_code
and   end_date = '2009'
and   prd_code = '01'
order by a.prd_code
         , a.br_code
         , a.size_code
         , a.var_code
         , a.pack_code
         , a.form_code

tables used in this query are:

prices    : has more than 2.1M rows
cphistory : has more than 2.2M rows
sizes     : has more than 5000 rows
brand     : has more than 1200 rows
varient   : has more than 1800 rows
package   : has more than 200 rows
pack_type : has more than 150 rows

Answer 1

1. Check indexes. Make sure you have a primary key. Alternate candidate keys should have unique constraints and indexes.
2. Run EXPLAIN PLAN on queries and see how the optimizer is running them. If you see TABLE SCAN, add indexes.
3. Make sure the optimizer is using statistics to make its job easier.
4. Move historical data into warehouses if you must.

22M records isn’t that enormous.