Lecture Database management systems Chapter 4 Relational model

Chapter 4

Relational Model


Relational Model Concept
Relational database: a set of relations
 Each relation resembles a table of values
 Relation: made up of 2 parts


◦ Instance: a table, with rows and columns.
◦ Schema: specifies name of relation, plus name
and type of each column.


TheUser
terms commonly
Model usedProgrammer
Row
Column
Table

Tuple
Attribute
Relation

Record
Field
File

Relational Data Model
The relational model uses a collection of
tables to represent both data and the
relationships among those data.
 Each relation resembles a table of values
 Tables are logical structures maintained
by the database manager.
 Ex:


STUDENT (NO., NAME, DATE_OF_BIRTH, GENDER)

Relation

Set of attributes


Relational Database


Ex:

◦ A row is called tuple.
◦ A column is called attribute.
◦ The table is called relation.


Relational Database


For each column of a table, there is a set
of possible values called its domain.



Domain is the set of valid values for an
attribute.


Relation Schema


Relation Schema R, denoted by R(A1, A2,…, An), is
made up of relation name R and a list of attributes A1,
A2, …,An



Each attribute Ai is the name of a role played by some
domain D in the relation schema R.



D is called the domain of Ai and is denoted by dom(Ai)



R is called the name of the relation



The degree of a relation is the number of attributes n of
its relation schema


Relational Algebra


Symbol
◦
◦
◦
◦

A1, A2, A3, … , An: attribute
D1, D2, D3, … , Dn : domain
R (A1:D1, A2:D2, …, An:Dn): relational model
r(R): relation
 r = {t1, t2, t3, …, tn}
 ti : tuple


Relational Data Model


The relational model is a combination of
three components:
◦ Structural Part: the database as a collection
of relations.

◦ Integrity Part: maintained in the relational
model using primary and foreign keys
◦ Manipulative Part: The relational algebra
and relational calculus are the tools used to
manipulate data in the database.


Concept of Key
An attribute or group of attributes, which
is used to identify a row in a relation.
 Can be classified into 3 types:


◦ Super key
◦ Candidate key
◦ Primary key


Concept of Key


Super key:
◦ a subset of attributes of an entity-set that
uniquely identifies the entities.
◦ Represent a constraint that prevents two
entities from ever having the same value for
those attributes.


Concept of Key



Candidate key:
◦ a minimal super key.
◦ a minimal set of attributes whose values
uniquely identify tuples in the corresponding
relation.



Primary key:
◦ a designated candidate key.
◦ not be null



Foreign key:
◦ Set of fields or attributes in one relation that is
used to “refer” to a tuple in another relation.


Concept of Key


Ex: Employee characterized by these attributes:
◦
◦
◦
◦
◦

employee ID
employee name
employee age
employee experience
employee salary, etc.

 Super keys can be: employee ID, employee
name, employee age, employee experience, etc.
 Candidate keys can be: employee ID, employee
name, employee age.
 Primary key: employee ID.


Concept of Key


Relational Query Languages
A major strength of the relational model:
supports simple, powerful querying of
data.
 Queries can be written intuitively, and the
DBMS is responsible for efficient
evaluation.
 The SQL Query Language is developed
by IBM in the 1970s



Relational Integrity



Four types of data integrity constraints:
◦
◦
◦
◦

Entity
NULL
Domain Integrity Constraint
Referential integrity.


Entity Integrity:
Imply that a primary key cannot accept
null value
 Ex:


◦ The attributes of the entity PLAYER are
Name, Age, Nation, and Rank.
◦ If PLAYER’s name’s used as the primary key
 cannot insert any data in the relation
PLAYER without entering the name of the
player.


Null Integrity


Imply that the data on attributes can be
NULL value are or are not permitted



Ex:
◦ The relation PERSON must have a valid, nonNULL value for the Name attribute, then
Name of PERSON is constrained to be NOT
NUL


Relational Integrity


Domain Integrity Constraint
◦ are based upon the semantics of the real world
enterprise that is being described in the
database relations.
◦ are used in the relational model to define the
characteristics of the columns of a table.



Ex:
◦ The age of the person cannot have any letter
from the alphabet. The age should be a
numerical value.

Relational Integrity


Referential Integrity
◦ a database must not contain any unmatched
foreign key values.
◦ not imply a foreign key cannot be null.
◦ Either each foreign key value must match a
primary key value in another relation or the
foreign key value must be null.


ER design to Relational


Entity sets to tables
Name
Age

Emp_ID

EMPLOYEE



CREATE TABLE Employees
(Emp_ID CHAR(11),
Name CHAR(20),
Age INTEGER,
PRIMARY KEY (Emp_ID))

EMPLOYEE (Emp_ID, Name, Age)


Relational Algebra
Query languages: Allow manipulation and
retrieval of data from a database.
 Relational model supports simple, powerful
QLs:


◦ Strong formal foundation based on logic.
◦ Allows for much optimization.



Query
Languages
languages!

!=

programming

◦ QLs not intended to be used for complex
calculations.
◦ QLs support easy, efficient access to large data
sets.

Relational Algebra
Relational
algebra
Set Operations

Combined set
* Union ()
* Cartesian (x)
* Intersection () * Join (
)
* Difference (-)
* Rename (ρ)

Database
Operations
* Selection
* Projection


Selection
Work on a single relation R
 Define a relation that contains only those
tuples of R that satisfy the specified
condition
 Syntax:
σ <selection condition>(R)


◦ In selection condition:
 Comparison operator : >, >=, <, <=, =, ≠

 Relational operator: , , ¬


Selection


Ex:



Selection operation is associative.


Selection _ example
Student Roll. No
001

Name

GPA

Aravind

7.2

002
003
004

Anand

Balu
Chitra

7.5
8.2
8

005
006
007

Deepa
Govind
Hari

8.5
7.2
6.5



List all students who get GPA mark > 8