Fundamental DB Concepts

8/3/2019 Fundamental DB Concepts

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Advanced Database ConceptsISE-830 (3+0)

Fundamental Concepts

Instructor

Dr Sharifullah KhanSeptember 2011


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Advanced Database Concepts 2

Database System

Data recorded facts with implicit meaning

Database an integrated collection of data

preserved over a long period

organized for access and modification Data Base Management Systems (DBMS):

GENERALISED software package designed

to store and manage database

Defining, constructing and manipulating databases

Database System: database together with

DBMS


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Why Use Models?

Models can be useful when we want to

examine or manage part of the real world

The costs of using a model are often

considerably lower than the costs of using

or experimenting with the real world itself

Examples:

airplane simulator

nuclear power plant simulator



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Data Model

Data abstraction hiding details of data

storage

A data model is a collection of concepts that

can be used to describe the structure of a

database:

Data structure, relationships and constraints

A data model provides the necessary meansto achieve this abstraction



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Data Modeling

The model represents a perception of structures of

reality

The data modeling process is to fix a perception of

structures of reality and represent this perception

In the data modeling process we select aspects and

we abstract


REALITY

structures

processes

DATABASE SYSTEM

MODEL

data modeling


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Process Modeling

REALITY

structures

processes

DATABASE SYSTEM

MODEL

process modeling

The use of the model reflects processes of reality

Processes may be represented by programs with embedded

database queries and updates

Processes may be represented by ad-hoc database queries

and updates at run-timeDML DML

PROG


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Database Design

The purpose of database design is to create

a database which

is a model of structures of reality

supports queries and updates modeling

processes of reality

runs efficiently



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Data Model

A data model consists of notations for

expressing:

data structures

integrity constraints

operations



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Categories of Data Models

Conceptual data model High Level.

Entity-Relationship model.

Object data models.

Entity, attributes and relationship.

Representational data model.

Relational data model.

Record structure.

Physical data model Low Level. Record formats, record ordering and access path.



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ER-Model

Data Structures

Integrity Constraints

Operations

The ER-Model is extremely successful as a database design

model

Translation algorithms to many data models

Commercial database design tools, e.g., ERwin

No generally accepted query language


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ER-Model - Data Structures

entity type

Relations

hip type

attribute

multivalued

attribute

derived

attribute

composite

attribute

subsetrelationshi

p type


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ER-Model - Integrity Constraints

A

E

E1 E3E2

RE1 E21 n

RE1 E2

RE1E2

(min,max)

RE1 E2R

cardinality: 1:n for E1:E2 in R

(min,max) participation of E2 in R

total participation of E2 in R

weak entity type E2; identifying

relationship type R

key attribute

d

op

disjoint

overlap

partition


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ER Model - Example

deptairport

date

internationalflight

domesticflight

p

flightinstance

flightschedule

instanceof

arrivairport

airport

1

n

n

1

street

depttime

airportcode

arrivtime

city zip

airportaddr

airportname

reserva-tion

nn

1

n

customer

flight#

customername

customer#

seat#

weekdays

visarequired


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ER-Model - Operations

Several navigational query languages have

been proposed

A closed query language as powerful asrelational languages has not been developed

None of the proposed query languages has

been generally accepted


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Relational Model

Data Structures

Integrity Constraints

Operations

Commercial systems include: ORACLE,DB2, SYBASE, INFORMIX, INGRES, SQL

Server

Dominates the database market on allplatforms



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Relational Model - Data Structures

domains

attributes

relations

flight-scheduleflight#:

integer

airline:

char(20)

weekday:

char(2)

price:

dec(6,2)

relation name

attribute

names

domain names


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Relational Model - Integrity Constraints

Keys

Primary Keys

Entity Integrity

Referential Integrity

reservation

flight# date customer#

flight-schedule

flight#

p

customer

customer# customer name

p


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Relational Model - Operations

Powerful set-oriented query languages

Relational Algebra: procedural; describes

how to compute a query; operators likeJOIN, SELECT, PROJECT

Relational Calculus: declarative; describes

the desired result, e.g. SQL, QBE

insert, delete, and update capabilities



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Advanced Database's Concepts 19

Normalization

FLIGHT# AIRLINE PRICE

FLIGHT-SCHEDULE

101 delta 156

545 american 110

912 scandinavia

n

450

FLIGHT# AIRLINE WEEKDAY PRICE

FLIGHT-SCHEDULE

101 delta mo

545 american mo 110

912 scandinavian fr 450

156

101 delta fr 156545 american we 110545 american fr 110

FLIGHT# AIRLINE WEEKDAYS PRICEFLIGHT-SCHEDULE

101 delta mo,fr 156

545 american mo,we,fr 110

912 scandinavian fr 450

FLIGHT# WEEKDAY

FLIGHT-WEEKDAY

101 mo

545 mo

912 fr

101 fr

545 we

545 fr


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Schemas, Instances and Data State

Schema description of a database.

Frequently changes are unexpected.

Schema construct STUDENT, COURSE.

Instances entities (records) of individualschema construct.

Frequently changed

Data state data at a particular moment intime

Current set of instances.


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Instances and Data State

Student

Name Student Number Class Major

Karim 17 1 CS

Naeem 8 2 CS

Course

CourseName CourseNo CreditHours Departmen

t

Intro to Comp Science CS1310 4 CS

Data Structure CS3320 4 CSDiscrete Mathematics MATH2410 3 MATH

Database CS3380 3 CS


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Three-Schema Architecture

Internal Schema

Conceptual Schema

External View External View

End users

Stored Databases

Conceptual/internal mapping

External/conceptual

mapping


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Data Independence

Logical data independence:

Logical data independence is a measure of how

much the conceptual schema can change without

affecting the application programs Physical data independence:

Physical data independence is a measure of how

much the internal schema can change without

affecting the application programs


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DBMS Languages

Data Definition Language (DDL).

Data Manipulation Language (DML).

Non procedural DML high level.

Set-at-a-time.

Procedural DML low level.

Record-at-a-time.

Query Language High level DML, e.g.

SQL.


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Classification of DBMSs -I

Data model:

Relational DBMSs.

Object DBMSs. Object-relational DBMSs.

Number of users:

Single-user systems.

Multi-user systems.


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Classification of DBMSs - II

Number of Sites:

Centralized DBMSs.

Distributed DBMSs (DDBMSs). Homegeneous DDBMSs.

Hetrogeneous DDBMSs.


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Fundamental DB Concepts

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