CPSC 603 Database Systems

Lecturer: Laurie Webster II, M.S.S.E., M.S.E.E., M.S.BME, Ph.D., P.E.

Lecture 3

Introduction to a First Course in Database Systems

CPSC 603 Database Systems

Design Principles

We have yet to learn many of the details of the E/R model.

We have enough to begin study of the crucial issues of what constitutes a good design and what should be avoided

Design Principle - Faithfulness

First and Foremost - Design Should Be Faithful to the Specifications of the Application

==> Entity Sets and their attributes should

reflect REALITY

Example: We can’t attach an attribute number-

of-cylinders to Entity Stars although

it makes sense for an Entity

Automobile

Design Faithfulness

EXAMPLE 2.12 of Text:

Stars-InMovies

Starsmm

many - many ==> Real World tells us that Stars can appear in more than one movie, and Movies can have more than one star

Design Faithfulness• Sometimes it is less obvious what the

REAL WORLD requires us to do in an E/R model

• Consider Entity Sets Courses and Instructors with a relationship Teaches between them

Courses Teaches Instructors

Is Teaches many-one from Courses to Instructors?

Design Faithfulness

• Sometimes it is less obvious what the REAL WORLD requires us to do in an E/R model

• Consider Entity Sets Courses and Instructors with a relationship Teaches between them

TeachesCourses Instructors

Is Teaches many-one from Courses to Instructors?

The Answer lies in the policy and intentions of the organization creating the database.

Design Faithfulness

School Policy: Can be only one instructor for each

course.

- Even if several instructors may “team-teach” a

course, the school may require that exactly one

of them be listed in the database as the

instructor responsible for the course

In these cases we would make Teaches a many-one relationship form Courses to Instructors

Design Faithfulness

• Alternative Policy– School may use a team of instructors regularly and wish

its database to allow several instructors to be associated with a course

– Or, the intent of the Teaches relationship may not be to reflect the current teacher of a course, but rather those who have ever taught the course, or those who are capable of teaching the course

• We cannot tell simply from the name of the relationship so make Teaches be many-many

Avoiding Redundancy

Say Everything ONCE ONLY

Avoiding REDUNDANCY => avoid saying the same thing more than once

Wastes Space and Encourages Inconsistency

REAL PROBLEM for DATABASES !!!

Avoiding Redundancy• EXAMPLE

ManfByBeers Manfs

name name

addr

Good Design

Avoiding Redundancy

Beers

namemanf

manf addr

Bad: Repeats manufacturer’s address for each beer they manufacture

Simplicity Counts• Avoid introducing more elements into your design

than is absolutely necessary

movies Represents Holdings owns

studios

A Poor Design with an Unnecessary Entity Set

Representsthe REAL WORLD

Modeling of Constraints

a) So far we have seen how to model a slice of the

real world using entity sets and relationships

b) HOWEVER, there are some other important

aspects of the REAL WORLD that we cannot

model with the tools seen so far

c) This additional information often takes the form

of constraints on the data that go beyond the

structural and type constraints imposed by

E.S., attributes, and relationships

Classification of Constraints• Keys are attributes or sets of attributes that

uniquely identify an entity within its entity set = key constraint

• Single-value constraints are requirements that the value in a certain context be unique

• Referential Integrity constraints are requirements that a value referred to by some object actually exists in the database

• Domain constraints require that the value of an attribute must be drawn from a specific set of values or lie within a specific range

Classification of Constraints

An important Constraint on the entities of an entity type is the key or uniqueness constraint on attributes

An entity type usually has an attribute whose vaues are distinct for each individual entity in the collection

=> such an attribute is called a key attribute

Use Schema to Enforce Constraints

The Design Schema should enforce as many constraints as possible

==> Don’t rely on users to follow assumptions

EXAMPLE

If the registrar wants to associate only one instructor with a course, don’t allow sets of instructors and count on departments to enter only one instructor per course

Use Schema to Enforce Constraints• Domain

– A domain is a set of atomic values, i.e. every value in the domain is indivisible as far as the relational model is concerned

– A common method of specifying a domain is to specify a data type from which the data values forming the domain are drawn

• Useful also to specify a name for the domain– EXAMPLE

• USA_phone_numbers: The set of 10 digit phone numbers valid in the US

• Local_phone_numbers: The set of 7 digit phone numbers valid within a particular area code in the United States

• Names: The set of names of persons

Relation Schema

• A relation schema R , denoted by– R(A1, A2, ……, An)

• Relation name R

• List of attributes A1, A2, ……, An

Relation Schema

• 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 dom (Ai )

• A relation schema R is used to describe a relation where R is the name of the relation

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

Relation Schema

Example of Relation Schema of degree 7

R(A1, A2, ……, An) ==>

Student ( Name, SSN, HomePhone, Address,

OfficePhone, Age, GPA)

degree = 7 because there are seven attributes

describes a relation schema for a university student

Relation Schema

• A relation (or relation state) r of the relation schema R(A1, A2, ……, An) , also denoted r(R), is a set of n-tuples r = (t1, t2, ….., tm)

• Each n-tuple t is an ordered list of n values – t = <v1, v2, …., vn>, where each value vi, 1 i n, is an

element of dom(Ai ) or is a special null value.

– The ith value in tuple t , which corresponds to the attribute Ai , is referred to as t[Ai ].

Relation Schema

a) A relation state r(R) is a mathematical relation of degree n on the domains dom (A1 ) , dom (A2 ) ,…,dom (An ), which is a subset of the Cartesian product of the domains that define R:

r(R) (dom (A1 ) × dom (A2 ) ×… × dom (An ) )

b) The Cartesian product specifies all possible combinations of values from the underlying domains.

Relation Schema

c) If we denote the number of values or cardinality of a domain D by D , and assume that all domains are finite, the total number of tuples in the Cartesian product is:

dom (A1 ) * dom (A2 ) *……* dom (An )

Out of all of these possible combinations, a relation state r(R) at a given time - the current relation state - reflects only the valid tuples that represent a particular state of the REAL WORLD

Next Lecture

• Modeling of Constraints

• Weak Entity Sets

• Summary of Chapter 2

• Relational Data Model-Conversion from ER Introduction