Basic Sql Handouts

Computer Science Department
College of Computer Studies
Ateneo de Naga University
Database Management Systems
Second Semester SY 2008-09

Handout #1 – Oracle SQL Basics
Reference: Oracle Academic Initiative - Introduction to Oracle 9i SQL

I. Basic SQL

SELECT [DISTINCT] * {column | expression [alias], …}
FROM table;

Selecting All Column Rows

SELECT *
FROM departments;

Selecting Specific Columns

SELECT department_id, location_id
FROM departments;

Using Arithmetic Operators

SELECT last_name, salary, salary+300
FROM employees;

SELECT last_name, salary, 12*salary+100
FROM employees;

SELECT last_name, salary, 12*(salary+100)
FROM employees;

Using Column Aliases

SELECT last_name AS name, commission_pct comm.
FROM employees;

SELECT last_name “Name” , salary*12 “Annual Salary”
FROM employees;

Using the Concatenation Operator

SELECT last_name || job_id AS “Employees”
FROM employees;

SELECT last_name || ‘ is a ‘ || job_id AS “Employee Details”
FROM employees;

Eliminating Duplicate Rows

SELECT DISTINCT department_id
FROM employees;

Using the WHERE Clause

SELECT employee_id, last_name, job_id, department_id
FROM employees
WHERE department_id = 90;

Using Comparison Conditions

SELECT last_name, salary
FROM employees
WHERE salary <= 3000;

Using the BETWEEN Condition

SELECT last_name, salary
FROM employees
WHERE salary BETWEEN 2500 AND 3500;

Using the IN Condition

SELECT employee_id, last_name, salary, manager_id
FROM employees
WHERE manager_id IN (100, 101, 201);

Using the LIKE Condition

SELECT first_name
FROM employees
WHERE first_name LIKE ‘S%’;

SELECT last_name
FROM employees
WHERE last_name LIKE ‘ o%’;

Using the NULL condition

SELECT last_name, manager_id
FROM employees
WHERE manager_id IS NULL;

Using the AND Operator

SELECT employee_id, last_name, job_id, salary
FROM employees
WHERE salary >= 10000
AND job_id LIKE ‘%MAN%’;

Using the OR Operator

FROM employees
WHERE salary >= 10000
OR job_id LIKE ‘%MAN%’;

Using the NOT Operator

SELECT last_name, job_id
FROM employees
WHERE job_id NOT IN (‘IT_PROG’, ‘ST_CLERK’, ‘SA_REP’);

Rules of Precedence

SELECT last_name, job_id, salary
FROM employees
WHERE job_id = ‘SA_REP’
OR job_id = ‘AD_PRES’
AND salary > 15000;

Use parentheses to force priority

FROM employees
WHERE (job_id = ‘SA_REP’
OR job_id = ‘AD_PRES’)
AND salary > 15000;

ORDER BY Clause

SELECT last_name, job_id, department_id, hire_date
FROM employees
ORDER BY hire_date;

Sorting in Descending Order

SELECT last_name, job_id, department_id, hire_date
FROM employees
ORDER BY hire_date DESC;

Sorting by Multiple Columns

SELECT last_name, department_id, salary
FROM employees
ORDER BY department_id, salary DESC;

II. FUNCTIONS

Character Manipulation Functions

SELECT employee_id, last_name, department_id
FROM employees
WHERE LOWER(last_name) = ‘higgins’;
SELECT employee_id, CONCAT(first_name, last_name) NAME,
LENGTH last_name, INSTR(last_name, ‘a’),
FROM employees;

Number Functions

SELECT ROUND(45.923, 2), ROUND(45.923, 0),
ROUND(45.923, -1)
FROM dual;
SELECT TRUNC(45.923, 2), TRUNC(45.923),
TRUNC(45.923, -2)
FROM dual;

Using the MOD Function

SELECT last_name, salary, MOD(salary, 5000)
FROM employees
WHERE job_id = ‘SA_REP’;

Case Manipulation Functions

LOWER – converts mixed case or uppercase character strings to lowercase.
UPPER - converts mixed case or lowercase character strings to uppercase.
INITCAP – converts the first letter of each word to uppercase and remaining letters to lowercase.

Example:

LOWER(‘SQL Course’) . sql course
UPPER(‘SQL Course’) . SQL COURSE
INITCAP(‘SQL Course’) . Sql Course
SELECT ‘The job_id for ‘ || UPPER(last_name) || ‘ is ‘
|| LOWER(job_id) AS “EMPLOYEE DETAILS”
FROM employees;

Character Manipulation Functions

CONCAT – joins values together (you are limited to using two parameters with CONCAT).
SUBSTR – extracts a string of determined length.
LENGTH – shows the length of a string as a numeric value.
INSTR – finds numeric position of a named character.
LPAD – pads the character value right-justified.
RPAD – pads the character value left justified.
TRIM – trims heading or trailing characters.

Example:

CONCAT(‘Hello’, ‘World’) . HelloWorld
SUBSTR(‘HelloWorld,1,5) . Hello
LENGTH(‘HelloWorld’) . 10
INSTR(HelloWorld’, ‘W’) . 6
LPAD(salary,10,’*’) . *****24000
RPAD(salary,10,’*’) . 24000*****
TRIM(‘H’ FROM ‘HelloWorld’) . elloWorld
SELECT employee_id, CONCAT(first_name, last_name) NAME,
job_id, LENGTH(last_name), INSTR(last_name, ‘a’) “Lastname contains ‘a’?”
FROM employees
WHERE SUBSTR(job_id, 4) = ‘REP’;

Working with Dates

SELECT last_name, hire_date
FROM employees
WHERE last_name LIKE ‘W%’;

Using Arithmetic Operators with Dates

SELECT last_name, (SYSDATE – hiredate) / 7 AS WEEKS
FROM employees

Date Functions

SELECT employee_id, hire_date,
MONTHS_BETWEEN(SYSDATE, hire_date) TENURE,
ADD_MONTHS(hire_date, 6) REVIEW,
NEXT_DAY(hire_date, ‘FRIDAY’), LAST_DAY(hire_date)
FROM employees;
SELECT employee_id, hire_date,
ROUND(hire_date, ‘MONTH’), TRUNC(hire_date, ‘MONTH’)
FROM employees
WHERE hire_date LIKE ‘%97’;

CONVERSION FUNCTIONS
Elements of the Date Format Model

YYYY – full year in numbers
YEAR – year spelled out
MM – two-digit value for month
MONTH – full name of the month
MON – three-letter abbreviation of the month
DY – three-day abbreviation of the day of the week
DAY – full name of the day of the week
DD – numeric day of the month
AM or PM – meridian indicator
A.M. or P.M. – meridian indicator with periods
HH or HH12 or HH24 – hour of day, or hour(1-12), or hour(0-23)
MI – minute (0-59)
SS – second(0-59)
SSSSS – seconds past midnight(0-86399)
/ . , – punctuation is reproduced in the result
“of the” – quoted string is reproduced in the result
TH – ordinal number (for example, DDTH for 4TH)
SP – spelled out number (for example, DDSP for FOUR)
SPTH or THSP – spelled out ordinal numbers (for example, DDSPTH for FOURTH)

Using the TO_CHAR Function with Dates

SELECT last_name,
TO_CHAR(hire_date, ‘fmDD Month YYYY’) AS HIREDATE
FROM employees;
SELECT last_name,
TO_CHAR(hire_date, ‘fmDdspth “of” Month YYYY fmHH:MI:SS AM’) HIREDATE
FROM employees

Number Format Elements

9 – represents a number
0 – forces a zero to be displayed
$ – places a floating dollar sign
L – uses the floating local currency symbol
. – prints a decimal point
, – prints a thousand indicator

Using the TO_CHAR Function with Numbers

SELECT TO_CHAR(salary, ‘$99,999.00’) SALARY
FROM employees;

GENERAL FUNCTIONS

These functions work with any data type and pertain to using nulls
NVL (expr1, expr2) – converts a null value to an actual value.
NVL2(expr1, expr2, expr3) – if expr1 is not null, nvl2 returns expr2. if expr1 is null, nvl2 returns expr3.
NULLIF(expr1, expr2) – compares two expressions and returns null if they are equal, or the first expression if
they are not equal.
COALESCE(expr1, expr2, …, exprn) – returns the first non-null expression in the expression list.

Using the NVL Function

SELECT last_name,
NVL(TO_CHAR(manager_id), ‘No Manager’)
FROM employees
WHERE manager_id IS NULL;

Using the NVL2 Function

SELECT last_name, salary, commission_pct,
NVL2(commission_pct, ‘Salary+Commission’, ‘Salary’) INCOME
FROM employees;

Using the NULLIF Function

SELECT first_name, LENGTH(first_name) “expr1”,
last_name, LENGTH(last_name) “expr2”,
NULLIF(length(first_name), LENGTH(last_name)) result
FROM employees;

Using the COALESCE Function

SELECT last_name,
COALESCE(commission_pct, salary, 10) comm.
FROM employees
ORDER BY commission_pct;

CONDITIONAL EXPRESSIONS

Facilitates the conditional inquiries by doing the work of an IF-THEN-ELSE statement.

Using the CASE Expression

SELECT last_name, job_id, salary,
CASE job_id WHEN ‘IT_PROG’ THEN 1.10 * salary
WHEN ‘ST_CLERK’ THEN 1.15 * salary
WHEN ‘SA_REP’ THEN 1.20 * salary
ELSE salary
END “Revised Salary”
FROM employees;

Using the DECODE Function

SELECT last_name, job_id, salary,
DECODE(job_id, ‘IT_PROG’, 1.10 * salary,
‘ST_CLERK’, 1.15 * salary,
‘SA_REP’, 1.20 * salary,
salary) “Revised Salary”
FROM employees;

III. DISPLAYING DATA FROM MULTIPLE TABLES

Retrieving Records with Equijoins

SELECT employees.employee_id, employees.last_name,
employees.department_id, departments.department_id,
departments.location_id
FROM employees, departments
WHERE employees.department_id = departments.department_id;

Using Table Aliases

SELECT e.employee_id, e.last_name, e.department_id,
d.department_id, d.location_id
FROM employees e, departments d
WHERE e.department_id = d.department_id;

Joining More than Two Tables

SELECT e.last_name, d.department_name, l.city
FROM employees e, departments d, locations l
WHERE e.department_id = d.department_id
AND d.location_id = l.location_id;

Non-Equijoins

SELECT e.last_name, e.salary, j.grade_level
FROM employees e, job_grades j
WHERE e.salary BETWEEN j.lowest_sal AND j.highest_sal;

Outer Joins

SELECT e.last_name, e.department_id, d.department_name
WHERE e.department_id = d.department_id;
WHERE e.department_id (+) = d.department_id;

Joining a Table to Itself

SELECT w.last_name || ' works for ' || m.last_name
FROM employees w, employees m
WHERE w.manager_id = m.employee_id;

Creating Cross Joins

SELECT last_name, department_name
FROM employees
CROSS JOIN departments;

Natural Joins

It selects rows from tables that have equal values in all matched columns. It can also be written using an
equijoin.

SELECT department_id, department_name, location_id, city
FROM departments

NATURAL JOIN locations;

The USING Clause

If several columns have the same names but the data types do not match, the NATURAL JOIN clause can be
modified with the USING clause to specify the columns that should be used for an equijoin.

SELECT e.employee_id, e.last_name, d.location_id
FROM employees e JOIN departments d
USING (department_id);

The ON Clause

The join condition for the natural join is basically an equijoin of all columns with the same name. To specify
arbitrary conditions or specify columns to join, the ON clause is used.

SELECT e.employee_id, e.last_name, e.department_id,
d.department_id, d.location_id
FROM employees e JOIN departments d
ON (e.department_id = d.department_id);

Three-Way Joins with the ON Clause

SELECT employee_id, city, department_name
FROM employees e
JOIN departments d
ON d.department_id = e.department_id
JOIN locations l
ON d.location_id = l.location_id;

Left Outer Join

FROM employees e
LEFT OUTER JOIN departments d
This query retrieves all rows in the EMPLOYEES table, which is the left table even if there is no match in the
departments table.

Right Outer Join

FROM employees e
RIGHT OUTER JOIN departments d
This query retrieves all rows in the DEPARTMENTS table, which is the right table even if there is no match in the
EMPLOYEES table.

Full Outer Join
FROM employees e
FULL OUTER JOIN departments d
This query retrieves all rows in the EMPLOYEES table, even if there is no match in the
DEPARTMENTS table. It also retrieves all rows in the DEPARTMENTS table, even if there is no
match in the EMPLOYEES table.

IV. GROUP FUNCTIONS

GROUP FUNCTIONS

SELECT AVG(salary), MAX(salary),
MIN(salary), SUM(salary)
FROM employees
WHERE job_id LIKE ‘%REP%’;

SELECT MIN(hire_date), MAX(hire_date)
FROM employees;
SELECT COUNT(*)
FROM employees

SELECT COUNT(commission_pct)
FROM employees

SELECT COUNT(department_id)
FROM employees;

SELECT COUNT(DISTINCT department_id)
FROM employees;

All group functions ignore null values in the column. In the example, the average is calculated based only on the
rows in the table where a valid value is stored in the COMMISSION_PCT column.

SELECT AVG(commission_pct)
FROM employees;

The NVL function forces group functions to include null values. In the example, the average is calculated based
on all rows in the table, regardless of whether null values are stored in the COMMISSION_PCT column.

SELECT AVG(NVL(commission_pct, 0))
FROM employees;

Using the GROUP BY Clause

SELECT department_id, job_id, SUM(salary)
FROM employees
GROUP BY department_id, job_id;

SELECT department_id, COUNT(last_name)
FROM employees
GROUP BY department_id;

Using the HAVING Clause

SELECT department_id, MAX(salary)
FROM employees
GROUP BY department_id
HAVING MAX(salary) > 10000;

SELECT job_id, SUM(salary) “Payroll”
FROM employees
WHERE job_id NOT LIKE ‘%rep%’
GROUP BY job_id

HAVING SUM(salary) > 13000
ORDER BY SUM(salary);

Nesting Group Functions

SELECT MAX(AVG(salary))
FROM employees
GROUP BY department_id;

V. SUBQUERIES

Types of Subqueries:

Single-row subquery
returns
ST_CLERK

Multiple-row subquery
returns
ST_CLERK
SA_MAN

Single-Row Subqueries

SELECT last_name, job_id
FROM employees
WHERE job_id =
(SELECT job_id
FROM employees
WHERE employee_id = 141);
FROM employees
WHERE job_id =
(SELECT job_id
FROM employees
WHERE employee_id = 141)
AND salary >
(SELECT salary
FROM employees
WHERE employee_id = 143);

Using Group Functions in a Subquery

FROM employees
WHERE salary =
(SELECT MIN(salary)
FROM employees);

The HAVING Clause with Subqueries

SELECT department_id, MIN(salary)
FROM employees
GROUP BY department_id
HAVING MIN(salary) >
(SELECT MIN(salary)
FROM employees
WHERE department_id = 50);

Main query
Subquery

Multiple-Row Subqueries
Find the employees who earn the same salary as the minimum salary for each department.

SELECT last_name, salary, department_id
FROM employees
WHERE salary IN
(SELECT MIN(salary)
FROM employees
GROUP BY department_id);

Display the employees who are not IT programmers and whose salary is less than that of
any IT programmer.

FROM employees
WHERE salary < ANY
(SELECT salary
FROM employees
WHERE job_id = ‘IT_PROG’)
AND job_id <> ‘IT_PROG’;

Display the employees whose salary is less than the salary of all employees with a job ID
of IT_PROG and whose job is not IT_PROG.

FROM employees
WHERE salary < ALL
(SELECT salary
FROM employees
WHERE job_id = ‘IT_PROG’)
AND job_id <> ‘IT_PROG’;

VI. DATA MANIPULATION LANGUAGE

Insert a new row containing values for each column

INSERT INTO departments (department_id, department_name, manager_id, location_id)
VALUES (70, ‘Public Relations’, 100, 1700);

Inserting rows with NULL values
Implicit method: Omit the column from the column list.

INSERT INTO departments (department_id, department_name)
VALUES (30, ‘Purchasing’);

Explicit method: specify the NULL keyword in the VALUES clause.

INSERT INTO departments
VALUES (100, ‘Finance’, NULL, NULL);

Inserting special values

INSERT INTO employees (employee_id, first_name, last_name, email, phone_number,
hire_date, job_id, salary, commission_pct, manager_id,

department_id)
VALUES (113, ‘Louis’, ‘Popp’, ‘lpopp@yahoo.com’, ‘515-124-4567’, SYSDATE,
‘AC_ACCOUNT’, 6900, NULL, 205, 100)

Inserting Specific Date Values

INSERT INTO employees
VALUES (114, ‘Den’, ‘Raphaealy’, ‘draphael@yahoo.com’, ‘515-127-4561’,
TO_DATE(‘FEB 3, 1999’, ‘MON DD, YYYY’), ‘AC_ACCOUNT’, 11000,
NULL, 100, 30);

Creating a script
Use substitution in a SQL statement to prompt for values. & is a placeholder for the
variable value.

INSERT INTO departments (department_id, department_name, location_id)
VALUES (&department_id, ‘&department_name’, &location_id)

Modify existing rows
Specific row or rows are modified if you are specify the WHERE clause

UPDATE employees
SET department_id = 70
WHERE employee_id = 113;

Updating Two Columns with a subquery

UPDATE employees
SET job_id = (SELECT job_id
FROM employees
HERE employee_id = 205),
Salary = (SELECT salary
FROM employees
WHERE employee_id = 205)

Deleting Rows from a Table

DELETE FROM employees
DELETE FROM departments
WHERE department_id IN (30, 40)
DELETE FROM employees
WHERE department_id =
(SELECT department_id
FROM departments
WHERE department_name LIKE ‘%Public%’);

VI. CREATING AND MANAGING TABLES
Naming Rules

Table names and column names:
• Must begin with a letter
• Must be 1-30 characters long
• Must contain only A-Z, a-z, 0-9, _, $, and #
• Must not duplicate the name of another object owned by the same user
• Must not be an Oracle server reserved word

Creating Tables

CREATE TABLE dept
(deptno NUMBER(2),
dname VARCHAR2(14),
loc VARCHAR2(13));

Confirm table creation

DESCRIBE dept;

Data Types:

Data Type Description

VARCHAR2(size) Variable-length character data
CHAR(size) Fixed-length character data
NUMBER(p,s) Variable-length numeric data
DATE Date and time values
LONG Variable-length character data up to 2 gigabytes
CLOB Character data up to 4 gigabytes
RAW and LONG RAW Raw binary data
BLOB Binary data up to 4 gigabytes
BFILE Binary data stored in an external file; up to 4 gigabytes
ROWID A 64 base number system representing the unique address of row in its table

Creating a Table by Using a Subquery

CREATE TABLE dept80
AS SELECT employee_id, last_name, salary * 12 ANNUAL_SALARY, hire_date
FROM employees

Adding a Column

ALTER TABLE dept80
ADD (job_id VARCHAR2(9));

Modifying a Column

ALTER TABLE dept80
MODIFY (last_name VARCHAR2(30));

Dropping a Column

ALTER TABLE dept80
DROP COLUMN job_id;

Dropping a Table

DROP TABLE dept80;

Changing the name of a table

RENAME dept TO detail_dept;

VII. CONSTRAINTS

What are constraints?
• Constraints enforce rules at the table level.
• Constraints prevent the deletion of a table if there are dependencies.

Data Integrity Constraints

Constraint Description

NOT NULL Specifies that the column cannot contain a null value
UNIQUE Specifies a column or combination of columns whose values must be unique for all rows in the table
PRIMARY KEY Uniquely identifies each row of the table
FOREIGN KEY Establishes and enforces a foreign key relationship between the column and a column of the
referenced table
CHECK Specifies a condition that must be true

Constraint Guidelines
• Name a constraint or the Oracle server generates a name by using the SYS_Cn format.
• Create a constraint either:
o At the same time as the table is created, or
o After the table has been created
• Define the constraint at the column or table level.
• View a constraint in the data dictionary

Defining Constraints
Constraint Level Description

Column References a single column and is defined within a specification for the owning column; can define any
type of integrity constraint

Table References one or more columns and is defined separately from the definitions of the columns in the
table; can define any type of constraint except NOT NULL

Column constraint level

Column [CONSTRAINT constraint_name] constraint_type,
Table constraint level
column, …
[CONSTRAINT constraint_name] constraint_type
(column, …),

The NOT NULL Constraint

CREATE TABLE employees2 (
employee_id NUMBER(6),

last_name VARCHAR2(25) NOT NULL, System named

email VARCHAR2(25),
salary NUMBER(8,2),
commission_pct NUMBER(2,2),

hire_date DATE
CONSTRAINT emp_hire_date_nn User named
NOT NULL,
…

The UNIQUE Constraint

last_name VARCHAR2(25) NOT NULL,
email VARCHAR2(25),
salary NUMBER(8,2),
hire_date DATE
CONSTRAINT emp_hire_date_nn
NOT NULL,
…
CONSTRAINT emp_email_uk UNIQUE(email));
The PRIMARY KEY Constraint

CREATE TABLE departments2 (
department_id NUMBER(4),
department_name VARCHAR2(30)
CONSTRAINT dept_name NOT NULL,
manager_id NUMBER(6),
location_id NUMBER(4),

CONTRSAINT dept_id_pk PRIMARY KEY(department_id));
The FOREIGN KEY Constraint

email VARCHAR2(25),
salary NUMBER(8,2),
hire_date DATE
NOT NULL,
…

CONSTRAINT emp_dept_fk FOREIGN KEY (department_id)
REFERENCES departments2(department_id),


The CHECK Constraint

email VARCHAR2(25),

salary NUMBER(8,2)
CONSTRAINT emp_salary_min CHECK (salary > 0),

hire_date DATE
NOT NULL,
…
CONSTRAINT emp_dept_fk FOREIGN KEY (department_id)

` REFERENCES departments2(department_id),

Adding a Constraint

ALTER TABLE employees
ADD CONSTRAINT emp_manager_fk
FOREIGN KEY(manager_id)
REFERENCES employees(employee_id);

Dropping a Constraint

DROP CONSTRAINT emp_manager_fk;
ALTER TABLE departments2
DROP PRIMARY KEY CASCADE;
The CASCADE option of the DROP clause causes any dependent constraints also to be
dropped.

Disabling Constraints

DISABLE CONSTRAINT emp_emp_id_pk CASCADE;

Enabling Constraints

DISABLE CONSTRAINT emp_emp_id_pk;

Basic Sql Handouts

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