Chapter Three( Relational Data Model)

Objectives Introduction to Relational Data Models. Advantages of Relational Data Models. Restriction of Relational Data Model. Keys. What are a good BD Design?

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Relational Data Model: Developed by Codd in 1970. Conceptually simple. Based on mathematical set theory.

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Relational Data Model: Most important advantage of the

RDBMS is its ability to hide the complexities of the relational model from the user.

Relational Database Models:

Data are represented as a set of tables.

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Structure A set of tables ( Relations). Each relation has a unique name. Each relation has a set of

attributes. Each relation has a set of tuples.

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Restriction on Relational DBMS

No two tuples are the same. No two attributes are the same. Order of tuples are immaterial. Order of attributes are immaterial. Value of attributes must be atomic.

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Relational Database Example:

StudentsCoursesFaculty

Attributes of a Relation:

Students (Name, ID, Major, Minor,….)

Courses (C_num, Dept, Cr, Description)

Faculty (Name, ID, SSN, …..)

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Tuples:

Students (Name, ID, Major, Minor,….)

_________________________________John Smith 1111, ITEC, VARTMary Smith 2222, COSC, ITECLorry Joys 4444, ACCT, COSC

Courses (C_num, Dept, Cr, Description)

_______________________________________345 ITEC 3 Databases I445 ITEC 3 Databases II

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Keys: (Constraints)

A set of attributes whose values uniquely identify each entity.

Examples:Students (Name, ID, Major, Minor,….)Courses (C_num, Dept, Cr, Description)Faculty (Name, ID, SSN, …..)

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Keys: (Constraints)

Primary key:

1- Uniqueness:At any given time, no two tuples can have the same value for a given primary key.

2-Minimally:None of the attributes in primary key can be discarded without distorting the uniqueness property

3-Selection:A key selected by the Database Administrator.

Primary key:

Key’s role is based on determination

If you know the value of attribute A, you can look up (determine) the value of attribute B.

ID GPA

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Keys Composite key

Composed of more than one attribute. Key attribute

Any attribute that is part of a key. Superkey

Any combination of attributes that uniquely identifies each row.

Candidate key

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Keys: (Constraints)

Foreign key:An attribute(s) in an entity set

(relation) which is the primary key of other entity set (relation)

Example: Department(Name, Dept_Id, ….) Faculty(Name, Id, Dept_Id,…)

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Normal Forms (Guidelines for RD design)

How do we know this is a good design?

If it is not a good design, What should we do?

Modify our design ??.

Normalization: Process for evaluating and correcting

table structures to minimize data redundancies

Reduces data anomalies Works through a series of stages

called normal forms: First normal form (1NF) Second normal form (2NF) Third normal form (3NF)

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Why Normalize Tables: Structure of data does not handle

data very well The table structure appears to

work; Report generated with ease Unfortunately, report may yield

different results depending on what data anomaly has occurred

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Each table represents a single subject

No data item will be unnecessarily stored in more than one table

All attributes in a table are dependent on the primary key

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Normal Forms (Guidelines for RD design)

A relation is in 1NF if the values of domain is atomic for each attribute.

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First Normal Form: 1NF

Example: Person (Name Age Children )

Smith 42 John, Lori, Mark

Person (Name Age Children )Smith 42 JohnSmith 42 LoriSmith 42 Mark

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First Normal Form: 1NF

Example: Student ( Name Birthday )

S1 Feb 2,91S2 March 8,88

Student (Name, D_Birth, M_Birth, Y_Birth)

Note: 2NF and 3NF Deal with the relationship between non-key and key

First Normal Form: Repeating group

Derives its name from the fact that a group of multiple entries of same type can exist for any single key attribute occurrence

Relational table must not contain repeating groups

Normalizing table structure will reduce data redundancies

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Second Normal Form: 2NF

A relation is in 2NF if it is in 1NF and every attribute is Fully dependent on the entire key in this relation.

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Second Normal Form: 2NF

Example: R(A,B,C,D)

D partially depends on A,B C fully depends on A,B A&B are prime (part of key)

If A is primary key. Is this in 2NF? If A&B is primary key. Is this in 2NF?

A, B ---> C, DA ---> D

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Second Normal Form: 2NF What should we do with a relation which

is not in 2NF?

Example: R(A,B,C,D) A, B ---> C, D A ---> D

R1 (A,B,C) R2(A,D)

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Second Normal Form: 2NF Example: R(Part Warehouse Address Quantity

P1 W1 Frostburg 25

P2 W1 Frostburg 30

P3 W2 Cumberland

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P4 W4 Frostburg 25

P4 W1What is the primary key?

Part, Warehouse ---> QuantityWarehouse ---> Address

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Second Normal Form: 2NF

Problems:1. Repetition of information:

Changing the address W!

2. Unable to present information:Warehouse with no part

So …R1 (Warehouse, Address)R2 (Part, Warehouse, Quantity)

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Second Normal Form: 2NF

Example:

R( Professor,

Student,

Course,

Degree )

P1 S1 C1 Ph.D.

P2 S2 C2 M.S.

P3 S2 C4 M.S.

P4 S3 C4 Ph.D.Professor ---> CourseStudent ---> DegreeProfessor ---> Student

Key? Not in 2NF

R1(Student, Degree)R2(Professor, Course, Student)

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A relation is 3NF if it is in 2NF and every non-key attribute non transitively depends on the Primary Key.

Example: R(A,B,C,D) A, B --->D D ---> C

Fact: 3NF is violated when a non-key is a fact about another non-key

Third Normal Form (3NF):

R1(A,B,D)R2(D,C)

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Third Normal Form (3NF): Example: R(Employee, Dept, Location) Employee ---> Dept

Dept ---> Location

Employee Dept LocationE1 D1 Frostburg

E2 D2 Frostburg

E3 D3 Frostburg

Problems? R1(Employee, Dept)R2(Dept, Location)

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Third Normal Form (3NF): Example: R(A,B,C,D)

A,B ---> C A,C ---> D

So A,B is the Primary Key Not in 3NF

R1(A,B,C) R2(A,C,D)

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Null Values:

No data entry Not permitted in primary key It is represent as:

An unknown attribute value A known, but missing, attribute value A “not applicable” condition

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Controlled redundancy: Makes the relational database work Tables within the database share

common attributes that enable the tables to be linked together

Multiple occurrences of values in a table are not redundant when they are required to make the relationship work

Redundancy exists only when there is unnecessary duplication of attribute values