This document provides an introduction to SQL (Structured Query Language). SQL is a language used to define, query, modify, and control relational databases. The document outlines the main SQL commands for data definition (CREATE, ALTER, DROP), data manipulation (INSERT, UPDATE, DELETE), and data control (GRANT, REVOKE). It also discusses SQL data types, integrity constraints, and how to use SELECT statements to query databases using projections, selections, comparisons, logical conditions, and ordering. The FROM clause is introduced as specifying the relations involved in a query.

1. Data Base Management Systems
(DBMS) – (1)
Code : INF311
Lecture 4

2. In this Lecture
Introduction to SQL

3. SQL
 SQL is acronym for
"Structured Query Language".
 SQL is a high-level language for defining,
querying, modifying, and controlling the
data in a relational database.
 SQL is not case sensitive (the verb
SELECT is the same as verb SelEcT).

4. SQL Commands
Category SQL Description
commands
CREATE Creation of tables
Data Description (DDL) ALTER Modification of tables
DROP Removal of tables
INSERT Insertion of rows in a table
Data Manipulation (DML) UPDATE Update of rows in a table
DELETE Removal of rows in a table
GRANT Grant of access rights
REVOKE Removal of access rights
Data Control (DCL)
COMMIT Treatment of updates
ROLLBACK Removal of updates
Interrogation SELECT Queries

5. Data Definition Language
The SQL data-definition language (DDL)
allows the specification of information about
relations, including:
 The schema for each relation.
 The domain of values associated with each attribute.
 Integrity constraints
 And as we will see later, also other information such as
– The set of indices to be maintained for each relations.
– Security and authorization information for each relation.
– The physical storage structure of each relation on disk.

6. Domain Types in SQL
 char(n): Fixed length character string, with user-specified
length n.
 varchar(n): Variable length character strings, with user-
specified maximum length n.
 Int: Integer (a finite subset of the integers that is machine-
dependent).
 Smallint: Small integer (a machine-dependent subset of the
integer domain type).
 numeric(p,d): Fixed point number, with user-specified
precision of p digits, with n digits to the right of decimal point.
 real, double precision: Floating point and double-
precision floating point numbers, with machine-dependent
precision.
 float(n): Floating point number, with user-specified precision
of at least n digits.
 More are covered later.

7. Create Table Construct
 An SQL relation is defined using the create table
command:
create table r (A1 D1, A2 D2, ..., An Dn ,
(integrity-constraint1),
...,
(integrity-constraintk) );
– r is the name of the relation
– each Ai is an attribute name in the schema of
relation r
– Di is the data type of values in the domain of
attribute Ai

8. Integrity Constraints in Create Table
 not null
 primary key (A1, ..., An )
 foreign key (Am, ..., An ) references r
 Unique Key
 Check

9. Create Example 1
create table instructor (
ID char (5),
name varchar (20) not null ,
dept_name varchar (20),
salary numeric (8,2) );

10. Create Example 2
 Declare dept_name as the primary key for
department.
create table instructor (
ID char (5),
name varchar (20) not null,
dept_name varchar (20),
salary numeric (8,2),
primary key (ID),
foreign key (dept_name) references department );
 primary key declaration on an attribute automatically
ensures not null

11. Create Example 3
Create table employee (
Fname varchar (20) NOT NULL ,
Lname varchar (20) NOT NULL ,
SSN char (9),
Bdate Date ,
Address varchar (30),
Sex Char NoT NULL ,
Salary decimal (10,2),
SuperSSN char (9),
Dno int NOT NULL ,
Primary key (SSN) );

12. And more still
 create table course (
course_id varchar (8) primary key ,
title varchar( 50),
dept_name varchar (20),
credits numeric (2,0),
foreign key (dept_name) references
department) );
 Primary key declaration can be combined with
attribute declaration as shown above

13. Alter Table Constructs
 alter table r add A D ;
– where A is the name of the attribute to be added
to relation r and D is the domain of A.
– All tuples in the relation are assigned null as the
value for the new attribute.
 alter table r drop A ;
– where A is the name of an attribute of relation r
– Dropping of attributes not supported by many
databases

14. Drop Table Constructs
 drop table table_name ;
– Deletes the table and its contents
 delete from table_name ;
– Deletes all contents of table, but retains table

15. Data Manipulation Language
 The DML provide Modification of the Database .

16. INSERT operation
 Add a new tuple to a table
INSERT
INTO table [ (field [,field] … )]
VALUES (literal[,literal ] …) ;

17. Insert examples
 insert into course (course_id, title, dept_name, credits)
values (’CS-437’, ’Database Systems’, ’Comp. Sci.’,
4);
 insert into course
values (’CS-437’, ’Database Systems’, ’Comp. Sci.’, 4);
 insert into student
values (’3003’, ’Green’, ’Finance’, null);
 insert into course (course_id, title)
values (’CS-437’, ’Database Systems’);

18. UPDATE operation
 General format
UPDATE table
SET field = scalar-expression
[, field = scalar-expression ] …..
[ WHERE condition ] ;

19. UPDATE examples
 Increase salaries of instructors whose salary is over
$100,000 by 3%
update instructor
set salary = salary * 1.03
where salary > 100000;
 UPDATE Store_Information
SET Sales = 500
WHERE store_name = "Los Angeles"
AND Date = "Jan-08-1999“;

20. DELETE operation
 Delete all records in a “table” that satisfy a
“condition”
 General format
DELETE FROM table [ WHERE condition ] ;

21. DELETE examples
 Delete all instructors
delete from instructor ;
 Delete all instructors from the Finance department
delete from instructor
where dept_name= ’Finance’;

22. Interrogation operation
 Queries are done by using SELECT command
 The result of an SQL query is a relation.
 Syntax of the SELECT command
SELECT [DISTINCT ] {* | expr [AS alias], ... }
FROM table [alias], ...
[WHERE { conditions | under conditions} ]
[GROUP BY expr, ...] [HAVING conditions]
[ORDER BY {expr | num}{ASC | DESC }, ...];

23. SELECT command
 Syntactical agreements
CAPITAL LETTERS : (SELECT) Enter values exactly as presented.
Italic : column, table. Parameter having to be replaced
by the suitable value.
Alias : Synonym of a name of table or column.
Conditions : Expression having the true or false value.
Under conditions : Expression containing a subquery.
Expr : Column, or calculated attribute (+,-, *, /)
Num : Column number
{} : Ex {ON|OFF}. One of the values separated by "|"
must obligatory be typed in.
[ ] : optional Value.
( ) : the brackets and commas must be type in as
presented.
... : The preceding values can be repeated several
times
_ Underlined : indicate the default value.

24. The select Clause
 An asterisk in the select clause denotes “all
attributes”
 To force the elimination of duplicates, insert the
keyword distinct after select.

25. SQL: Projection
 The operation of projection consists in selecting the
name of the columns of table(s) which one wishes
to see appearing in the answer.
 If one wants to display all the columns "*" should be
used.
 The columns are given after the SELECT clause.

26. Projection examples
Display the contents of the table STUDENT
SELECT *
FROM STUDENT;
Display the Name and the ID of the students
SELECT st_name, st_id
FROM STUDENT;

27. SQL: Selection
 The operation of selection consists in selecting
rows (tuples) of one (or several) table(s) which
satisfy certain conditions.
 The conditions are expressed after the WHERE
clause.

28. Selection examples
Display the list of the students of male sex.
SELECT *
FROM STUDENT
WHERE Cdsexe=‘M';
 Display department ID and name that are located in
Cairo
Select dept_id, dept_name
from departments
where location = ‘Cairo’;

29. Projection and Selection
 The operations of projection and selection can
obviously be used in the same SQL request.
 Display the number and the name of the students
born in 1980
SELECT st_id, st_name
FROM STUDENT
WHERE Dtnaiss >= '1980-01-01' AND Dtnaiss <=
'1980-12-31';

30. Comparison Conditions
 = Equal
 > greater than
 >= greater than or equal
 < less than
 <= less than or equal
 <> not equal
 Between …… AND ….. (between two values)
 IN (set) (Match any of a list of values)
 All ( set) (Match all values in the list)

31. Examples
 Select last_name, salary
from employees
where salary >1000 ;
 SELECT *
FROM suppliers
WHERE supplier_id between 5000 AND 5010;
 Select emp_id, last_name, salary, manager_id
From employees
where manager_id IN (100, 101, 200);

32. Logical Conditions
 AND
 OR
 NOT
Select emp_id, last_name, salary, manager_id
From employees
where manager_id NOT IN (100, 101, 200);

33. Arithmetic Expressions
 +-*/
Select last_name, salary, salary + 300
from employees;
 Order of precedence: * , / , +, -
You can enforce priority by adding parentheses
Select last_name, salary, 10 * (salary + 300)
from employees;

34. Order by Clause
 Retrieval with ordering (ASC, DESC)
 ASC is the default
Select fname, dept_id, hire_date
from employees
Order by hire_date DESC;
Select fname, dept_id, salary
from employees
Order by dept_id, Salary ASC;

35. The FROM clause
 The from clause lists the relations involved in the
query
– Corresponds to the Cartesian product operation
of the relational algebra.
 Find the Cartesian product instructor X teaches
select ∗
from instructor, teaches
– generates every possible instructor – teaches
pair, with all attributes from both relations
 Cartesian product not very useful directly, but useful
combined with where-clause condition

36. Cartesian Product: instructor X teaches
instructor teaches

37. Next Lecture
 SQL more and more