File Systems and Databases

11 File Systems and DatabasesChapter 1

Database Systems: Design, Implementation, and

Management, 4th Edition

Peter Rob & Carlos Coronel

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Introducing the DatabaseIntroducing the Database

Major Database Concepts Data and information

Data - Raw facts

Information - Processed data

Data management

Database

Metadata

Database management system (DBMS)

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Figure 1.1

Sales per Employee for Each of ROBCOR’S Two Divisions

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Introducing the DatabaseIntroducing the Database Importance of DBMS

It helps make data management more efficient and effective.

Its query language allows quick answers to ad hoc queries.

It provides end users better access to more and better-managed data.

It promotes an integrated view of organization’s operations -- “big picture.”

It reduces the probability of inconsistent data.

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Figure 1.2

The DBMS Manages the Interaction

Between the End User and the Database

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Introducing the DatabaseIntroducing the Database

Why Database Design Is Important?

A well-designed database facilitates data management and becomes a valuable information generator.

A poorly designed database is a breeding ground for uncontrolled data redundancies.

A poorly designed database generates errors that lead to bad decisions.

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Historical RootsHistorical Roots Why Study File Systems?

It provides historical perspective.

It teaches lessons to avoid pitfalls of data management.

Its simple characteristics facilitate understanding of the design complexity of a database.

It provides useful knowledge for converting a file system to a database system.

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Figure 1.3

Contents of the CUSTOMER File

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Table 1.1 Basic File TerminologyData “Raw” facts that have little meaning unless they have been

organized in some logical manner. The smallest piece of datathat can be “recognized” by the computer is a singlecharacter, such as the letter A, the number 5, or somesymbol such as; ‘ ? > * +. A single character requires onebyte of computer storage.

Field A character or group of characters (alphabetic or numeric)that has a specific meaning. A field might define a telephonenumbers, a birth date, a customer name, a year-to-date(YTD) sales value, and so on.

Record A logically connected set of one or more fields that describesa person, place, or thing. For example, the fields thatcomprise a record for a customer named J. D. Rudd mightconsist of J. D. Rudd’s name, address, phone number, dateof birth, credit limit, unpaid balance, and so on.

File A collection of related records. For example, a file mightcontain data about ROBCOR Company’s vendors; or, a filemight contain the records for the students currently enrolledat Gigantic University.

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Figure 1.4

Contents of the AGENT File

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A Simple File System

Figure 1.5

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File System CritiqueFile System Critique

File System Data Management

File systems require extensive programming in a third-generation language (3GL).

As the number of files expands, system administration becomes difficult.

Making changes in existing file structures is important and difficult.

Security features to safeguard data are difficult to program and usually omitted.

Difficulty to pool data creates islands of information.

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File System CritiqueFile System Critique Structural and Data Dependence

Structural DependenceA change in any file’s structure requires the modification of all programs using that file.

Data DependenceA change in any file’s data characteristics requires changes in all data access programs.

Significance of data dependence is the difference between the data logical format and the data physical format.

Data dependence makes file systems extremely cumbersome from a programming and data management point of view.

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File System CritiqueFile System Critique Field Definitions and Naming Conventions

A good (flexible) record definition anticipates reporting requirements by breaking up fields into their components.

Example:

– Customer Name Last Name, First Name, Initial

– Customer Address Street Address, City, State

FIELD CONTENTS

CUS_LNAME Customer last name

CUS_FNAME Customer first name

CUS_INITIAL Customer initial

CUS_AREACODE Customer area code

CUS_PHONE Customer phone

CUS_ADDRESS Customer street address or box number

CUS_CITY Customer city

CUS_STATE Customer state

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File System CritiqueFile System Critique

Field Definitions and Naming Conventions

Selecting proper field names is very important.

Names must be as descriptive as possible within restrictions.

Naming must reflect designer’s documentation needs and user’s reporting and processing requirements.

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File System CritiqueFile System Critique Data Redundancy:

Uncontrolled data redundancy sets the stage for

Data Inconsistency (lack of data integrity)

Data anomalies

Modification anomalies

Insertion anomalies

Deletion anomalies

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Figure 1.6

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Figure 1.7

The Database System Environment

Figure 1.7

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Database SystemsDatabase Systems

The Database System Components Hardware

Computer Peripherals

Software Operating systems software DBMS software Applications programs and utilities software

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Database SystemsDatabase Systems The Database System Components

People Systems administrators Database administrators (DBAs) Database designers Systems analysts and programmers End users

Procedures Instructions and rules that govern the design and use of

the database system

Data Collection of facts stored in the database

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Database SystemsDatabase Systems The Database System Components

The complexity of database systems depends on various organizational factors:

Organization’s size

Organization’s function

Organization’s corporate culture

Organizational activities and environment

Database solutions must be cost effective AND strategically effective.

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Database SystemsDatabase Systems Types of Database Systems

Number of Users Single-user

– Desktop database Multiuser

– Workgroup database– Enterprise database

Scope Desktop Workgroup Enterprise

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Database SystemsDatabase Systems

Types of Database Systems Location

Centralized Distributed

Use Transactional (Production) Decision support Data warehouse

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Database SystemsDatabase Systems DBMS Functions

1. Data Dictionary Management

2. Data Storage Management

3. Data Transformation and Presentation

4. Security Management

5. Multi-User Access Control

6. Backup and Recovery Management

7. Data Integrity Management

8. Database Access Languages (DDL and DML) and Application Programming Interfaces

9. Database Communication Interfaces

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Database ModelsDatabase Models A database model is a collection of logical

constructs used to represent the data structure and the data relationships found within the database.

Two Categories of Database Models Conceptual models focus on the logical nature of

the data representation. They are concerned with what is represented rather than how it is represented.

Implementation models place the emphasis on how the data are represented in the database or on how the data structures are implemented.

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Database Models Database Models Three Types of Relationships

One-to-many relationships (1:M) A painter paints many different paintings, but each one

of them is painted by only that painter.– PAINTER (1) paints PAINTING (M)

Many-to-many relationships (M:N) An employee might learn many job skills, and each job

skill might be learned by many employees.– EMPLOYEE (M) learns SKILL (N)

One-to-one relationships (1:1) Each store is managed by a single employee and each

store manager (employee) only manages a single store.– EMPLOYEE (1) manages STORE (1)

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Database ModelsDatabase Models

Three Types of Implementation Database Models

Hierarchical database model

Network database model

Relational database model

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A Hierarchical Structure

Figure 1.8

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Database Models Database Models Hierarchical Database Model

Basic Structure

Collection of records logically organized to conform to the upside-down tree (hierarchical) structure.

The top layer is perceived as the parent of the segment directly beneath it.

The segments below other segments are the children of the segment above them.

A tree structure is represented as a hierarchical path on the computer’s storage media.

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Database Models Database Models Hierarchical Database Model

Advantages Conceptual simplicity Database security Data independence Database integrity Efficiency dealing with a large database

Disadvantages Complex implementation Difficult to manage Lacks structural independence Applications programming and use complexity Implementation limitations Lack of standards

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Child with Multiple Parents

Figure 1.9

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Database Models Database Models Network Database Model

Basic Structure

Set -- A relationship is called a set. Each set is composed of at least two record types: an owner (parent) record and a member (child) record.

A set is represents a 1:M relationship between the owner and the member.

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A Network Database Model

Figure 1.10

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Database Models Database Models Network Database Model

Advantages Conceptual simplicity

Handles more relationship types

Data access flexibility

Promotes database integrity

Data independence

Conformance to standards

Disadvantages System complexity

Lack of structural independence

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Database Models Database Models Relational Database Model

Basic Structure RDBMS allows operations in a human logical

environment. The relational database is perceived as a collection of

tables. Each table consists of a series of row/column

intersections. Tables (or relations) are related to each other by

sharing a common entity characteristic. The relationship type is often shown in a relational

schema. A table yields complete data and structural

independence.

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Linking Relational Tables

Figure 1.11

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Database Models Database Models Relational Database Model

Advantages Structural independence Improved conceptual simplicity Easier database design, implementation, management,

and use Ad hoc query capability (SQL) Powerful database management system

Disadvantages Substantial hardware and system software overhead Possibility of poor design and implementation Potential “islands of information” problems

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A Relational Schema

Figure 1.12

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Database ModelsDatabase Models

Entity-Relationship Data Model It is one of the most widely accepted graphical data

modeling tools.

It graphically represents data as entities and their relationships in a database structure.

It complements the relational data model concepts.

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Database ModelsDatabase Models Entity Relationship Data Model

Basic Structure E-R models are normally represented in an entity

relationship diagram (ERD). An entity is represented by a rectangle. Each entity is described by a set of attributes. An

attribute describes a particular characteristics of the entity.

A relationship is represented by a diamond connected to the related entities.

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Figure 1.13 Relationship Depiction: The ERD

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Figure 1.14 Relationship Depiction: The Crow’s Foot

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Database ModelsDatabase Models Entity-Relationship Data Model

Advantages Exceptional conceptual simplicity

Visual representation

Effective communication tool

Integrated with the relational database model

Disadvantages Limited constraint representation

Limited relationship representation

No data manipulation language

Loss of information content

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Database ModelsDatabase Models Object-Oriented Database Model

Characteristics

An object is described by its factual content.

An object includes information about relationships between the facts within the object, as well as with other objects.

An object is a self-contained building block for autonomous structures.

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Database ModelsDatabase Models Object-Oriented Database Model

Basic Structure

Objects are abstractions of real-world entities or events.

Attributes describe the properties of an object.

Objects that share similar characteristics are grouped in classes.

A class is a collection of similar objects with shared structure (attributes) and behavior (methods).

Classes are organized in a class hierarchy.

An object can inherit the attributes and methods of the classes above it.

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A Comparison: The OO Data Model and the ER Model

Figure 1.15

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Database ModelsDatabase Models Object-Oriented Database Model

Advantages Add semantic content

Visual presentation includes semantic content

Database integrity

Both structural and data independence

Disadvantages Lack of OODM standards

Complex navigational data access

Steep learning curve

High system overhead slows transactions

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The Development of Data Models

Figure 1.16

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Wrap-Up: The Evolution of Data Models

Wrap-Up: The Evolution of Data Models

Common characteristics required for data models: A data model must show some degree of conceptual

simplicity without compromising the semantic completeness.

A data model must represent the real world as closely as possible.

The representation of the real-world transformations (behavior) must be in compliance with the consistency and integrity characteristics of any data model.

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Wrap-Up: The Evolution of Data Models

Wrap-Up: The Evolution of Data Models

Database Models and the InternetThe use of the Internet as a prime business tool is shifting focus to database products that interface efficiently and easily with the Internet.

Successful “Internet age” databases are characterized by:

Flexible, efficient, and secure Internet access. Support for complex data types and relationships. Seamless interfacing with multiple data sources and

structures. Simplicity of the conceptual database model. An abundance of available database tools. A powerful DBMS to help make the DBA’s job easier.