chapter one overview of database objectives: -introduction -dbms architecture -definitions -data...

Chapter OneOverview of Database

Objectives:-Introduction

-DBMS architecture-Definitions-Data models-DB lifecycle

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Definitions Database Management System

(DBMS): is a record keeping system (software) that allows one or more people to use or modify the data.

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Why DBMS: Centralized Control

Redundancy(Eliminated or Reduced)(Propagating update)

Inconsistency (Avoided) Shared Data Standardization Security Integrity Transaction Support

Complex Design Required Specialist (DBA) Training Cost Program Failures (potential) Cost

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Good DBMS must have: Support for at least one Data Model Support for certain high level languages for

Retrieve, Insert, Deletes, etc. into Database (Navigate)

Transaction Management:Capable of access to DB by many users at

once Access control:

Limit access to DB by unauthorized user Recovery capability form system failure Security System

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Architecture of DBMS

View Level: Def: Example (SQL)

CREATE VIEW GradStudentSELECT Name, ID, GPAFROM Students;

Data Manipulation Language (DML) (Query Language)

View Conceptual DB Physical DB

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Architecture of DBMS Conceptual Level:

Describe what data are stored & relationship among data (DB)

Example:

Students=RecordName:char[15];ID:Integer;

End;

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Architecture of DBMS

Example: Create table Students

(Name VARCHAR2(30), ID NUMBER(14), GPA NUMBER(3,2));

Data Definition Language (DDL)

Application Program

SystemCalls

QueryDB

Scheme

DMLCompiler

QueryProcessor

DDLCompiler

Application Program

Object CodeDB Manager

File Manager

Data DictionaryData File

Conceptual Level

InternalLevel

ExternalLevel

EndUser

DB AdministratorApplication Program

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Definitions File DB DBMS

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Definitions (Continued)

Instances & Schemes

Instance: The collection of Information stored in a DB at a particular instant of time

Scheme: The overall design of the DB

Example:Students (ID, Name, Address, GPA)

111, John, 34 1st, 2.6, 123, Mary, 18 Main, 2.8

(Plan for view is called sub-scheme)

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Definitions (Continued)

Data Independence:a. Physical data Independence

The ability to modify physical scheme without changing the application program

b. Logical data Independence:The ability to modify conceptual scheme without changing the application program

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Definitions (Continued)

Data Definition Language (DDL)a. A set of instructions which define

the DB schemeb. Result of compilation of DDL in a set

of tables which are stored in a special file called “data dictionary”.

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Definitions (Continued)

Data Manipulation Language (DML) A set of instructions to manipulate data. (Insert, Retrieve, Delete, …)

a. Types of DMLi. Procedural:ii. Non Procedural (Declarative)

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Definitions (Continued)

Database Manager:A program which provides the

interface between data stored in DB and application programs

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Definitions (Continued)

Database manager is responsible for:

a. Interaction with the file manager (retrieving & updating data in DB)

b. Integrity enforcement:c. Data value must satisfy certain

types of consistency constraintsd. Security enforcemente. Backup & recovery

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Definitions (Continued)

Database Administrator (DBA):Person(s) who involves in central control

Function of DBA: 1. Scheme definitions2. Storage structure & access method (Physical

organization)3. Modification of scheme & physical

organization4. Granting of authorization for data access

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Definitions (Continued)

Database Usersa. Application Programmerb. End User (Query Language)

Host Language:High level programming language

supported by DBMS that can be used to manipulate DB

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Overall System Structure Database Administration

File Manager Data File Data Dictionary Database Manager

Query Processes DML Compiler DDL Compiler

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Data Models Introduction:

Physical Model Mathematical Model Abstract Model Data Model

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Data Model Describes Data, Data Relationships,

Data Semantics and Data Constraints

<Object Name, Object Property, Property Values, Time>

Example: Car PersonEmployer Manager

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Representing Models

• -Networking• -Categories

• Strictly Typed• Loosely Typed

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Types of Models

1. Object Based logical Model2. Record Based Model3. Physical Data Model4. Object Record Model

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Object Based Logical Models Describing data at the conceptual and

view levels Flexible structure Specify data constraints explicitly

Example:1. Entity-Relationship2. Semantic Data Modeling3. Binary Data Model4. Infological Model

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Entity-Relationship Model (ER Model):

Consists of a collection of basic objects called (Entities) and (Relationships)

An entity is an object which exists and is distinguished from other objects

Each entity has a set of attributes which describes the object

A relationship is an association among several entities

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Binary Data Model Base on graph data model; nodes and

arcs Node represents a classification of data

instances into a type called category (Generalization)

Arc represents a binary relationship between categories and is called binary relation

This graph is called Type Graph

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Record-Based Logical Models

Describing data at the conceptual and view levels

They do not provide facilities for specifying data constraints explicitly

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Record-Based Logical Models (Continued)

1. Relational data and relationships are represented by a collection of Tables(Relations)

2. Network data are represented by collections of records and relationships among data are represented by links

3. Hierarchical similar to network, but records are organized as a collection of trees rather than arbitrary graph

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Physical Data Models Describes data at the lowest level

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Object Relational Present information in object form Object of object type (hierarchical) Inheritance Encapsulation Interface Polymorphism

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Database LifecycleStage One:

a. Analysis: Study and Analyze business requirements Interview manager, and users for the

information requirements Incorporate the future system specifications

b. Develop a user system specifications

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Database Lifecycle

Stage Two:Design

Entity relational model Unify modeling language

Check the design

Stage Three:Build the Databases/Document/Test

Create tables, views and programs Produce manuals (User documentation)

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Database Lifecycle

Stage Four:Product delivery

Load the software Monitor the performance