Partitioning with PARTITION_BY : PARTITION « Analytical Functions « Oracle PL / SQL

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Oracle PL / SQL » Analytical Functions » PARTITION 
Partitioning with PARTITION_BY
 


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(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  /

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  /

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  /

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  /

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  /

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  /

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  /

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

rows selected.

SQL>
SQL>
SQL>
SQL> --Partitioning with PARTITION_BY
SQL>
SQL>
SQL> SELECT empno, ename, region, curr_salary,
  2    RANK() OVER(PARTITION BY region ORDER BY curr_salary desc)
  3      rank
  4  FROM employee
  5  ORDER BY region;

     EMPNO ENAME      R CURR_SALARY       RANK
---------- ---------- - ----------- ----------
       122 Alison     E                      1
       104 Celia      E       58000          2
       116 Linda      E       53000          3
       108 Jode       E       29000          4
       105 Robert     W                      1
       117 David      W                      1
       123 James      W       32000          3

rows selected.

SQL>
SQL>
SQL>
SQL>
SQL>
SQL>
SQL> -- clean the table
SQL> drop table Employee;

Table dropped.

SQL>
SQL>
           
         
  
Related examples in the same category
1. partition clause
2. Use partitioning in the OVER clause of the aggregate-analytical function like this
3. PARTITION BY: divide the groups into subgroups
4. Count(*) over partition
5. Dense_rank over partition by
6. rank and dense_rank over partition
7. count(*) over partition by, order by and range unbounded preceding
8. dense_rank() over partition by, order by
9. Top with partition
10. Partition Window
11. PARTITION BY (JOB title) and right outer join
12. SPREADSHEET PARTITION BY
13. sum salary over PARTITION BY
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