Oracle PL/SQL Tutorial/Analytical Functions/PERCENTILE CONT
PERCENTILE_CONT(x) examines the percent rank values in each group until it finds one that is greater than or equal to x
PERCENTILE_CONT(x) operate in the reverse sense of PERCENT_RANK().
<source lang="sql">
SQL> SQL> SQL> -- create demo table SQL> create table Employee(
2 ID VARCHAR2(4 BYTE) NOT NULL, 3 First_Name VARCHAR2(10 BYTE), 4 Last_Name VARCHAR2(10 BYTE), 5 Start_Date DATE, 6 End_Date DATE, 7 Salary Number(8,2), 8 City VARCHAR2(10 BYTE), 9 Description VARCHAR2(15 BYTE) 10 ) 11 /
Table created. SQL> SQL> -- prepare data SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values ("01","Jason", "Martin", to_date("19960725","YYYYMMDD"), to_date("20060725","YYYYMMDD"), 1234.56, "Toronto", "Programmer")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("02","Alison", "Mathews", to_date("19760321","YYYYMMDD"), to_date("19860221","YYYYMMDD"), 6661.78, "Vancouver","Tester")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("03","James", "Smith", to_date("19781212","YYYYMMDD"), to_date("19900315","YYYYMMDD"), 6544.78, "Vancouver","Tester")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("04","Celia", "Rice", to_date("19821024","YYYYMMDD"), to_date("19990421","YYYYMMDD"), 2344.78, "Vancouver","Manager")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("05","Robert", "Black", to_date("19840115","YYYYMMDD"), to_date("19980808","YYYYMMDD"), 2334.78, "Vancouver","Tester")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("06","Linda", "Green", to_date("19870730","YYYYMMDD"), to_date("19960104","YYYYMMDD"), 4322.78,"New York", "Tester")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("07","David", "Larry", to_date("19901231","YYYYMMDD"), to_date("19980212","YYYYMMDD"), 7897.78,"New York", "Manager")
3 /
1 row created. SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("08","James", "Cat", to_date("19960917","YYYYMMDD"), to_date("20020415","YYYYMMDD"), 1232.78,"Vancouver", "Tester")
3 /
1 row created. SQL> SQL> SQL> SQL> -- display data in the table SQL> select * from Employee
2 /
ID FIRST_NAME LAST_NAME START_DAT END_DATE SALARY CITY DESCRIPTION
---------- ---------- --------- --------- ---------- ---------- ---------------
01 Jason Martin 25-JUL-96 25-JUL-06 1234.56 Toronto Programmer 02 Alison Mathews 21-MAR-76 21-FEB-86 6661.78 Vancouver Tester 03 James Smith 12-DEC-78 15-MAR-90 6544.78 Vancouver Tester 04 Celia Rice 24-OCT-82 21-APR-99 2344.78 Vancouver Manager 05 Robert Black 15-JAN-84 08-AUG-98 2334.78 Vancouver Tester 06 Linda Green 30-JUL-87 04-JAN-96 4322.78 New York Tester 07 David Larry 31-DEC-90 12-FEB-98 7897.78 New York Manager 08 James Cat 17-SEP-96 15-APR-02 1232.78 Vancouver Tester 8 rows selected. SQL> SQL> SQL> SQL> SELECT
2 PERCENTILE_CONT(0.6) WITHIN GROUP (ORDER BY SUM(salary) DESC) 3 AS percentile_cont, 4 PERCENTILE_DISC(0.6) WITHIN GROUP (ORDER BY SUM(salary) DESC) 5 AS percentile_disc 6 FROM employee 7 GROUP BY city;
PERCENTILE_CONT PERCENTILE_DISC
---------------
10023.36 12220.56
SQL> SQL> SQL> SQL> -- clean the table SQL> drop table Employee
2 /
Table dropped. SQL></source>
select percentile_cont(0.5) within group (order by salary desc )
<source lang="sql">
SQL> CREATE TABLE EMP(
2 EMPNO NUMBER(4) NOT NULL, 3 ENAME VARCHAR2(10), 4 JOB VARCHAR2(9), 5 MGR NUMBER(4), 6 HIREDATE DATE, 7 SAL NUMBER(7, 2), 8 COMM NUMBER(7, 2), 9 DEPTNO NUMBER(2) 10 );
Table created.
SQL> INSERT INTO EMP VALUES(2, "Jack", "Tester", 6,TO_DATE("20-FEB-1981", "DD-MON-YYYY"), 1600, 300, 30); 1 row created. SQL> INSERT INTO EMP VALUES(3, "Wil", "Tester", 6,TO_DATE("22-FEB-1981", "DD-MON-YYYY"), 1250, 500, 30); 1 row created. SQL> INSERT INTO EMP VALUES(4, "Jane", "Designer", 9,TO_DATE("2-APR-1981", "DD-MON-YYYY"), 2975, NULL, 20); 1 row created. SQL> INSERT INTO EMP VALUES(5, "Mary", "Tester", 6,TO_DATE("28-SEP-1981", "DD-MON-YYYY"), 1250, 1400, 30); 1 row created. SQL> INSERT INTO EMP VALUES(7, "Chris", "Designer", 9,TO_DATE("9-JUN-1981", "DD-MON-YYYY"), 2450, NULL, 10); 1 row created. SQL> INSERT INTO EMP VALUES(8, "Smart", "Helper", 4,TO_DATE("09-DEC-1982", "DD-MON-YYYY"), 3000, NULL, 20); 1 row created. SQL> INSERT INTO EMP VALUES(9, "Peter", "Manager", NULL,TO_DATE("17-NOV-1981", "DD-MON-YYYY"), 5000, NULL, 10); 1 row created. SQL> INSERT INTO EMP VALUES(10, "Take", "Tester", 6,TO_DATE("8-SEP-1981", "DD-MON-YYYY"), 1500, 0, 30); 1 row created.
SQL> INSERT INTO EMP VALUES(13, "Fake", "Helper", 4,TO_DATE("3-DEC-1981", "DD-MON-YYYY"), 3000, NULL, 20); 1 row created.
SQL> SQL> select percentile_cont(0.5)
2 within group (order by sal desc ) median_sal 3 from emp;
Enter...
2450
1 row selected. SQL> SQL> drop table emp; Table dropped. SQL></source>
Take a probability value (between 0 and 1) and returns a percentile value (for a continuous distribution)
The general format for this function is:
PERCENTILE_CONT (expr) WITHIN GROUP (ORDER BY expr [DESC |ASC]) OVER (query_partition_clause)]
<source lang="sql">
SQL> SQL> -- create demo table SQL> create table myTable(
2 id NUMBER(2), 3 value NUMBER(6,2) 4 ) 5 /
Table created. SQL> SQL> -- prepare data SQL> insert into myTable(ID, value)values (1,9); 1 row created. SQL> insert into myTable(ID, value)values (2,2.11); 1 row created. SQL> insert into myTable(ID, value)values (3,3.44); 1 row created. SQL> insert into myTable(ID, value)values (4,-4.21); 1 row created. SQL> insert into myTable(ID, value)values (5,10); 1 row created. SQL> insert into myTable(ID, value)values (6,3); 1 row created. SQL> insert into myTable(ID, value)values (7,-5.88); 1 row created. SQL> insert into myTable(ID, value)values (8,123.45); 1 row created. SQL> insert into myTable(ID, value)values (9,98.23); 1 row created. SQL> insert into myTable(ID, value)values (10,938.23); 1 row created. SQL> insert into myTable(ID, value)values (11,984.23); 1 row created. SQL> insert into myTable(ID, value)values (12,198.23); 1 row created. SQL> insert into myTable(ID, value)values (13,928.87); 1 row created. SQL> insert into myTable(ID, value)values (14,25.37); 1 row created. SQL> insert into myTable(ID, value)values (15,918.3); 1 row created. SQL> insert into myTable(ID, value)values (16,9.23); 1 row created. SQL> insert into myTable(ID, value)values (17,8.23); 1 row created. SQL> SQL> select * from myTable
2 /
ID VALUE
----------
1 9
2 2.11
3 3.44
4 -4.21
5 10
6 3
7 -5.88
8 123.45
9 98.23
10 938.23
11 984.23
ID VALUE
----------
12 198.23
13 928.87
14 25.37
15 918.3
16 9.23
17 8.23
17 rows selected. SQL> SQL> SQL> SQL> SELECT PERCENTILE_CONT (0.2) WITHIN GROUP (ORDER BY id )
2 from myTable;
PERCENTILE_CONT(0.2)WITHINGROUP(ORDERBYID)
4.2
SQL> SQL> SQL> SQL> -- clean the table SQL> drop table myTable
2 /
Table dropped. SQL> SQL></source>
