Question about De-Factoring a query

Question

Good afternoon,
I have the following query that produces the results I want (it does a DENSE_RANK):
with agelist as
   select age
     from student
    group by age
select age,
        select count(*)
          from agelist x
         where x.age <= agelist.age
       )                                as rankedage
  from agelist
order by rankedage
;As an exercise (I'm learning SQL), I wanted to write the equivalent query without using the WITH clause (and without using DENSE_RANK either - in other words, keeping it plain vanilla SQL). Everything I've tried either gives wrong results or a syntax error <chuckle>.
the question is: What does the working query ;) look like without the WITH (effectively defactoring the "agelist" query ?
Thank you for your help,
John.
DDL to run the query I posted:
  /* table of students */
     create table student
     ( sno integer,
       sname varchar(10),
       age integer
        insert into student values (1,'AARON',20);
        insert into student values (2,'CHUCK',21);
        insert into student values (3,'DOUG',20);
        insert into student values (4,'MAGGIE',19);
        insert into student values (5,'STEVE',22);
        insert into student values (6,'JING',18);
        insert into student values (7,'BRIAN',21);
        insert into student values (8,'KAY',20);
        insert into student values (9,'GILLIAN',20);
        insert into student values (10,'CHAD',21);Edited by: 440bx - 11gR2 on Jul 30, 2010 3:13 PM corrected misspelling in defactoring

Answer 1

Sorry, but I'm not quite sure what you're trying to do.
Your WITH clause returns a distinct list of ages. So any ranking can only be a dense_rank since you'll never have a tie. The rownum solution posted by Clearance will accomplish the same thing.
The whole point of RANK vs DENSE_RANK is how to number the results in the event of equal numbers in the list. Using a distinct or group by kind of defeats the purpose.
If you comment out the GROUP BY in WITH clause, you get this:
SQL> with agelist as
  2    (
  3     select age
  4       from student
  5      --group by age
  6    )
  7  select age,
  8         (
  9          select count(*)
10            from agelist x
11           where x.age <= agelist.age
12         )                                as rankedage
13    from agelist
14   order by rankedage
15  ;
                 AGE            RANKEDAGE
                  18                    1
                  19                    2
                  20                    6
                  20                    6
                  20                    6
                  20                    6
                  21                    9
                  21                    9
                  21                    9
                  22                   10That's not a dense rank or even a regular rank. Ages that have duplicates are assigned the lowest ranking in their group.
Using the RANK analytic function, you get this:
SQL> select age
  2        ,rank() over (order by age) r
  3  from   student;
                 AGE                    R
                  18                    1
                  19                    2
                  20                    3
                  20                    3
                  20                    3
                  20                    3
                  21                    7
                  21                    7
                  21                    7
                  22                   10And using DENSE_RANK you get this:
SQL> select age
  2        ,dense_rank() over (order by age) r
  3  from   student;
                 AGE                    R
                  18                    1
                  19                    2
                  20                    3
                  20                    3
                  20                    3
                  20                    3
                  21                    4
                  21                    4
                  21                    4
                  22                    5