CUBE function and Pivot Table in SQL

I am currently working on a new OA component, pivot table. To mimic the pivot table in Microsoft Excel, I decided to design the functionality in Java rather than using Oracle's powerful CUBE functionality. I can definitely blog about the reasons behind this decision later, but I am overwhelmed by the power of using CUBE and decided to ramble something about it.

1. Its syntax is very simple
2. Its pretty fast

Illustration:

select e.dept_no, e.job_type, e.salary
from emp_table e

DEPT_NO   JOB_TYPE               SALARY
---------------------------------------
10                Manager         10,000
10                Clerk            3,000
10                Clerk            4,000
20                Manager         12,000
20                Clerk            3,000
 20                Clerk            5,000
20                Foreman          1,000

Say we want to see a tabular information of sum of salary for department wise and again group on it based on job type

select e.dept_no, e.job_type, sum(e.salary)
 from emp_table e
group by cube(e.dept_no, e.job_type)

DEPT_NO   JOB_TYPE   SALARY
 ---------------------------------------
          Manager         22,000
          Clerk           15,000
          Foreman          1,000
10        Manager         10,000
10        Clerk            7,000
 10        Foreman              0
10                        17,000
20        Manager         12,000
 20        Clerk            8,000
  20        Foreman          1,000
 20                        21,000
                          38,000

Now we can use the famous pivoting technique in SQL to get the same information like Excel.

select nvl(job_type, 'Grand Total') JOB_TYPEX
       decode(dept_no,10,max(s),0) DEPT_10,
       decode(dept_no,20,max(s),0) DEPT_20,
       decode(nvl(dept_no,-999),-999,max(s),0) ALL_DEPT
from (select e.dept_no, e.job_type, sum(e.salary) s
from emp_table e
group by cube(e.dept_no, e.job_type))
group by job_type
order by job_type

JOB_TYPEX    DEPT_10   DEPT_20  ALL_DEPT
-----------------------------------------
Clerk         7,000    8,000     15,000
Foreman           0    1,000      1,000
Manager      10,000   12,000     22,000  
Grand Total  17,000   21,000     38,000

But the problem is that, we must know all departments to pivot it.