Rank, Percent_Rank, and Cume_Dist, NTILE
SQL>
SQL> -- create demo table
SQL> create table Employee(
2 empno Number(3) NOT NULL, -- Employee ID
3 ename VARCHAR2(10 BYTE), -- Employee Name
4 hireDate DATE, -- Date Employee Hired
5 orig_salary Number(8,2), -- Orignal Salary
6 curr_salary Number(8,2), -- Current Salary
7 region VARCHAR2(1 BYTE) -- Region where employeed
8 )
9 /
Table created.
SQL>
SQL>
SQL> -- prepare data for employee table
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(122,'Alison',to_date('19960321','YYYYMMDD'), 45000, NULL, 'E')
3 /
1 row created.
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(123, 'James',to_date('19781212','YYYYMMDD'), 23000, 32000, 'W')
3 /
1 row created.
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(104,'Celia',to_date('19821024','YYYYMMDD'), NULL, 58000, 'E')
3 /
1 row created.
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(105,'Robert',to_date('19840115','YYYYMMDD'), 31000, NULL, 'W')
3 /
1 row created.
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(116,'Linda', to_date('19870730','YYYYMMDD'), NULL, 53000, 'E')
3 /
1 row created.
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(117,'David', to_date('19901231','YYYYMMDD'), 78000, NULL, 'W')
3 /
1 row created.
SQL> insert into Employee(empno, ename, hireDate, orig_salary, curr_salary, region)
2 values(108,'Jode', to_date('19960917','YYYYMMDD'), 21000, 29000, 'E')
3 /
1 row created.
SQL>
SQL> -- display data in the table
SQL> select * from Employee
2 /
EMPNO ENAME HIREDATE ORIG_SALARY CURR_SALARY R
---------- ---------- --------- ----------- ----------- -
122 Alison 21-MAR-96 45000 E
123 James 12-DEC-78 23000 32000 W
104 Celia 24-OCT-82 58000 E
105 Robert 15-JAN-84 31000 W
116 Linda 30-JUL-87 53000 E
117 David 31-DEC-90 78000 W
108 Jode 17-SEP-96 21000 29000 E
7 rows selected.
SQL>
SQL>
SQL>
SQL> --The use of NTILE with a small amount of data like we have done here is poor statistics, but a reasonable database demonstration. To truly deal with NTILE in a statistical sense, we'd have to use a lot more data.
SQL>
SQL> --What about nulls with the NTILE function? Here is an example using the same query on our Employee table with nulls (Empwnulls):
SQL>
SQL> SELECT ename, curr_salary sal,
2 ntile(2) OVER(ORDER BY curr_salary desc) n2,
3 ntile(3) OVER(ORDER BY curr_salary desc) n3,
4 ntile(4) OVER(ORDER BY curr_salary desc) n4,
5 ntile(5) OVER(ORDER BY curr_salary desc) n5,
6 ntile(6) OVER(ORDER BY curr_salary desc) n6,
7 ntile(8) OVER(ORDER BY curr_salary desc) n8
8 FROM employee;
ENAME SAL N2 N3 N4 N5 N6 N8
---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------
Alison 1 1 1 1 1 1
Robert 1 1 1 1 1 2
David 1 1 2 2 2 3
Celia 58000 1 2 2 2 3 4
Linda 53000 2 2 3 3 4 5
James 32000 2 3 3 4 5 6
Jode 29000 2 3 4 5 6 7
7 rows selected.
SQL>
SQL>
SQL>
SQL> -- clean the table
SQL> drop table Employee;
Table dropped.
SQL>
SQL>
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