Part 2 Dbms Models

©Silberschatz, Korth and Sudarshan1.1Database System Concepts

PART-2 PART-2 DATABASES MODELSDATABASES MODELS

{ Relational,Heirarchical,Network,E-R Model}{ Relational,Heirarchical,Network,E-R Model}&&

RELATIONAL ALGEBRA OPERATIONSRELATIONAL ALGEBRA OPERATIONS

DBMS by Er. K.S.Dhindsa © 2006

Lecture Series By :Lecture Series By :Er. Kanwalvir Singh DhindsaEr. Kanwalvir Singh DhindsaDeptt. of CSE & ITDeptt. of CSE & IT

For downloading slides of DBMS, Visit :For downloading slides of DBMS, Visit :

WEBSITE : WEBSITE : www.dhindsa.infowww.dhindsa.info Homepage: Homepage: http://groups.google.com/group/DBMS-2006http://groups.google.com/group/DBMS-2006


Types of Databases Types of Databases

• Relational DBMS

• Hierarchical DBMS

• Network DBMS

• Object-Oriented Databases

{ Advantages,Disadvantages & Comparisons }


Relational Database ModelRelational Database Model

• Represents data as two-dimensional tables called relations• Relates data across tables based on common data element

Examples: DB2, Oracle, MS SQL Server


• Select: Creates subset of rows that meet specific criteria

• Join: Combines relational tables to provide users with information

• Project: Enables users to create new tables containing only relevant information

Three Basic Operations in a Three Basic Operations in a Relational DatabaseRelational Database


Three Basic Operations in a Relational Three Basic Operations in a Relational DatabaseDatabase

SELECT

PROJECT

JOIN


Hierarchical Database ModelHierarchical Database Model

• It is a pointer based model

• Organizes data in a tree-like structure

• Stores data in tables and views relationships as links

• Supports one-to-many parent-child relationships

• Prevalent in large legacy systems


Network DBMSNetwork DBMS Depicts data logically as many-to-many relationships

Organizes data in tables and views relationships as links

It is also a pointer based model

Organizes data in arbitrary graphs


Hierarchical and Network DBMSHierarchical and Network DBMS

Some of the Disadvantages

Outdated

Complex pointer based organization

Less flexible compared to RDBMS

Lack support for ad-hoc and English language-like queries


Object-Oriented DatabasesObject-Oriented Databases

Object-oriented DBMS: Stores data and procedures as objects

that can be retrieved and shared automatically

Object-relational DBMS: Provides capabilities of both object-

oriented and relational DBMS


Types of Databases Types of Databases : : SummarySummary

• In a relational database the data is perceived as tables (and

nothing but tables) by the user

• The relational operators available are used to manipulate the

data in the tables


Introduction to Data ModelingIntroduction to Data Modeling

What is Data Modeling?

A technique for analyzing requirements and for identifying the

information needs of an organization

• Why Data Modeling is important?

Cannot build a good system without knowing what data needs to be

captured and how it needs to be organized


• An Overview :

• Conceptual representation of the data structures required by a

database

• Data structures include the data objects, the associations between data

objects, and the rules which govern operations on the objects

• Focuses on what data is required and how it should be organized

• Independent of hardware or software constraints

• Data Model And Database Design:

• Data Model is to a Database what a Building plan or a blueprint is to a

Building

• A Database Design translates a data model into a database

• A Data Model is the conceptual design of a database

Introduction to Data ModelingIntroduction to Data Modeling


E-R ModelingE-R Modeling

Originally proposed by Peter Chen (1976)

Views the real world as entities and relationships

Key component is the E-R Diagram

Most common model used for designing relational databases

• Entity- An identifiable object or concept of significance

• Attribute- Property of an entity or relationship

• Relationship- An association between entities

• Identifier- one or more attributes identifying an instance

(occurrence) of an entity


Entity relationship diagramEntity relationship diagram


has works for• Dept No.

• Name

• Name• Emp Id.

Entity

Relationship Attributes

EMPLOYEEDEPARTMENT

Identifier



• Entity

• Any object or thing of significance about which data needs to be collected

and maintained

• Could be

• Concrete or tangible like a person or a building

• Abstract like a concept or activity

• Analogous to a table in a relational database

Examples: EMPLOYEES, PROJECTS, INVOICES



• Entity Rules

• Any thing or object may only be represented by one entity.

• Each entity must be uniquely identifiable. Each instance (occurrence)

of an entity must be separate and distinctly identifiable from all other

instances of that type of entity.

• Entity Classification and Types

• Classified as dependent and independent

• An independent entity is one that does not rely on another for

identification

• A dependent entity is one that relies on another for identification

• In some, methodologies, the terms used are strong and weak,

respectively

E-R Modeling


• Entity Classification and Types • Fundamental entity - An entity that exists and is of interest in its own right.

Generally, most entities in the data model are fundamental entities.

Example :Department and Employee are both fundamental entities

• Special Entity Types

• Associative Entity - Used to associate two entities in order to reconcile

a many-many relationship

• Sub-type/super-type- Used in generalization hierarchies to represent a subset

of instances of their of parent entity

E-R Modeling


ORDER ITEMORDER LINEappears onfor ahas

belongs to


Example of Associative entity :


• Generalization Hierarchies

• Generalization occurs when two or more entities

represent categories of the same real-world object.

Example: CAR and TRUCK represent categories of the

same entity, VEHICLE is the super-type; CAR and

TRUCK would be the subtypes

E-R Modeling



• Form of abstraction that specifies that two or more entities that

share common attributes can be generalized into a higher level

entity type called a super-type or generic entity.

• The lower-level of entities become the sub-type, or categories,

to the super-type. Sub-types are dependent entities.

E-R Modeling



• Example: Entity PERSON represents people at a university. It has three subtypes,

FACULTY, STAFF, and STUDENT. A STAFF member could also be registered as a

STUDENT

E-R Modeling

PERSON

FACULTYSTUDENT STAFF


• Generalization Hierarchies - NestedGeneralization Hierarchies - Nested

E-R Modeling

PERSON

FACULTYSTUDENT

UNDERGRAD GRADUATE


E-R Modeling

• Attribute

• Attributes describe a property or a characteristic of an entity

• A particular instance of an attribute is a value.

For example “John Doe” is one value of the attribute Name.

• Simple attribute

Contains only atomic values

• Composite attribute

Has component attributes

Student Name

FName

LName

MI

DOB

Simple Composite


E-R Modeling

• Attribute Classification• Single-valued attribute

• Has exactly one value per instance of an entity

• Multi-valued attribute• Contains repeating values per instance of an entity

Module

Student

Math

PhysicsId

Multi-valued

Single-valued


E-R Modeling

• Identifiers and Descriptors

• Attributes can be classified as identifiers or descriptors

• Identifiers, more commonly called keys, uniquely identify an

instance of an entity.

• A descriptor describes a non-unique characteristic of an entity

instance.

An Example :

Entity: Employee

Unique Identifier: Employee No.

Descriptor: Name, DOJ, DOB


E-R Modeling

• Relationship • Represents an association between two or more entities

Examples

- Employees work for Departments

- Departments manage one or more projects

- Employees are assigned to projects

- Projects have sub-tasks

- Orders have line items

• Defined in terms of:

- Degree

- Connectivity

- Cardinality

- Direction

- Type

- Existence


• Degree

• Number of entities associated with the relationship

• Binary relationships, the association between two entities is the

most common type in the real world.

Connectivity

• Mapping of associated entity instances in the relationship.

• The values of connectivity are "one" or "many”.

• Cardinality

Actual number of related occurrences for each of the two entities.

The basic types of connectivity for relations are: one-to-one, one-to-many,

and many-to-many.

E-R Modeling


E-R Modeling

• Connectivity and Cardinality

• A one-to-one (1:1) relationship is when at most one instance of a entity A Is

associated with one instance of entity B.

FOR EXAMPLE:

Employees in the company are each assigned their own office. For each

Employee there exists a unique office and for each office there exists a

unique employee.

• A one-to-many (1:N) relationships is when for one instance of entity A,

there are zero, one, or many instances of entity B, but for one instance of

entity B, there is only one instance of entity A.

An example :

A department has many employees, each employee is assigned to one department


E-R Modeling

• Connectivity and Cardinality

• A many-to-many relationship, is when for one instance of entity A, there

are zero, one, or many instances of entity B and for one instance of entity B

there are zero, one, or many instances of entity A.

An example is:

Employees can be assigned to no more than two projects at the

same time; Project must have assigned at least three employees


E-R Modeling

• Entities• Represented by labeled rectangles• The label is the name of the entity• Entity names should be singular nouns.

• Relationships• Represented by a solid line connecting two

entities. • Name written above the line• Relationship names should be verbs

Employee

Department

Works for


E-R Modeling

• Attributes• Listed inside the entity rectangle • Underlined • Names should be singular nouns

• Cardinality • Many is represented by a line ending in a

crow's foot. If omitted, cardinality is one

• Existence • Represented by placing a circle or a

perpendicular bar on the line

Employee•EmpID

•EmpName


E-R Modeling : Assignment

How to create an E-R Model from Requirements ?

Step 1: Identify Entities• Entities are things people talk about, record information about and do work

on – by definition

• Any keyword (noun) is a candidate

• Identify generic object from reference to instances or occurrences

• Combine synonyms to represent a single entity

An Example : Purchase Order - System Requirements

A buyer creates a purchase order (PO) as and when the need arises. A PO is for a

Specific vendor. A PO has one or more line items. A buyer cannot create a PO of

Total value more than his approval limit. A PO can be sent to the vendor by mail,

fax, EDI. A PO can be canceled before it is submitted. A PO can be linked to a

sales order…


Step 1: Identify Entities• Entities

Purchase Order (PO)Buyer?VendorLine ItemsSales OrderApproval Limit?

• Buyer characterizes a PO• Approval Limit characterizes a Buyer

What does it tell us?

• Approval Limit is not an entity• Buyer is an entity• Approval Limit is an attribute of the entity Buyer

E-R Modeling


Step 2: Identify Relationships

Look for phrases describing a link between two things or objects

Verbs relating two nouns often suggest relationships

e.g. A buyer creates a purchase order, A purchase order has one

or more

Lines

Requirements may or may not contain information regarding

degree,

existence, cardinality of a relationship up front

Further questioning may need to be done to determine the above

E-R Modeling


Step 2: Identify Relationships

Grid Technique

PO

PO replaced by Buyer

Buyer creates a is approver of

Vendor

Vendor supplies against a

- - Line

Line belongs to a - created for item supplied by

-

E-R Modeling


Step 2 : Identify Relationships

• Analyzing Existing Systems (Files, Databases)

• Look for -

Pointers

Foreign Keys

Repeating Groups

Structured Codes

• All of the above imply relationships

E-R Modeling


• Step 3 : Identify Attributes

• An attribute is any detail that server to identify, classify, quantify or

express the the state of an entity

• Ask the following question for each entity “What information do you need

to know or hold about …?”

• Potential attributes are easily found by examining paper forms

E-R Modeling


• Step 3: Identify Attributes

E-R Modeling

Purchase Order No __________

Buyer _________ Vendor ___________

Date Created ______

No Item Quantity Value___ ___________ ______ _____________ ___________ ______ _____________ ___________ ______ __________

Shipping AddressStreet _________City __________Zip _______ Total Value

______

Example Purchase Order Form• Purchase Order No

• Vendor

• Buyer

• Date Created

• Item?

• Address

• City

• State

• Zip

• Total Value?


E-R Model of the Purchase Order Example

PURCHASE ORDER

VENDOR

BUYERcreates

created by

supplies against

created for a

LINE

has

belongs to

ITEM

created for

exists on

E-R Modeling


Major Modeling Techniques

Peter Chen’s original entity/relationship diagrams

Information Engineering

Richard Barker’s notation, used by Oracle corporation

IDEF1X

Object Role Modeling

Unified Modeling Language (UML)

Extensible Markup Language (XML)

E-R Modeling


E-R Modeling

• Major Modeling Techniques

• Data Modeling has sets of two audiences:

• User community - Uses the models to verify that the analysts understand

their environment and their requirements.

• Systems designers - Use the business rules implied by the models as the

basis for their design of computer systems.

• Different techniques are better for one audience or the other.

• All techniques are fundamentally the same

• Differences are mainly in syntactic or notational


Relational ModelRelational Model

Formally introduced by Dr. E. F. Codd in 1970

Represents data in the form of two-dimensional tables

A relational database is a collection of two-dimensional tables

Basic understanding of the model needed to design and use

relational databases


Tables, Columns and Rows

Relationships and Keys

Data Integrity

Normalization

What is a table?

• Represents some real-world person, place, thing, or event

• Two-dimensional

• Columns

• Rows


Course No. Course_Title C_Hrs. Dept. C

CIS 120 Intro to CIS 4 Cis

MKT 333 Intro to Mkting 3 MKT

ECO 473 Labor Econ. 3 ECO

BA201 Intro to Stat. 5 ECOCIS 345 Intro to Dbase 4 CIS


Table

• Columns represent a property of the person, place, thing or event that the table represents

• Rows represent an occurrence or instance of what the table represents

• A data value is stored in the intersection of a row and column

• Each named column has a domain, which is the set of values that may appear in that column


Empid Name Level DOJ Manager

101412 John M3 4/10/98 101667

102235 Nancy M4 1/23/01 101412

101398 Mike S1 8/15/95 101667

101667 Jeff M2 6/2/96 100351

103893 Cindy M3 7/17/95 101284

101116 Rahul S2 2/20/00 101412

102739 Scott C1 4/13/01 101667

Employee



In this document Formal Terms Many Database Manuals

Table Relation Table

Column Attribute Field

Row Tuple Record

Table - Terminology



• Salient features of a relational table

• Values are atomic (1NF)

• Column values are of the same kind (Domain)

• Each Row is unique (Primary Key)

• Sequence of columns is insignificant

• Sequence of rows is insignificant

• Each column must have a unique name

• Relationships and Keys• Keys - Fundamental to the concept of relational databases

• Relationship - An association between two or more tables defined by

means of keys



• Primary Key

• Column or a set of columns that uniquely identify a row in a table

• Must be unique and must have a value

• Foreign Key

• Column or set of columns which references the primary key or a

unique key of another table

• Rows in two tables are linked by matching the values of the foreign

key in one table with the values of the primary key in another

•EMP_ID in table EMPLOYEE is the primary key

• DEPT_NO in table DEPARTMENT is the primary key

• DEPT_NO in table EMPLOYEE is a foreign key

Examples



• Data Integrity

• Ensures correct and consistent navigation and manipulation of

relational tables

• Two types of integrity rules

• Entity integrity

• Referential integrity

• The entity integrity rule states that the value of the primary key can

never be a null value

• The referential integrity rule states that if a relational table has a foreign

key, then every value of the foreign key must either be null or match the

values in the relational table in which that foreign key is a primary key


Relational Model OperatorsRelational Model Operators

• Data Manipulation

• Relational tables are equivalent to sets

• Operations that can be performed on sets can be performed

on relational tables

• Relational Operations such as :• Selection• Projection• Join• Union• Intersection• Difference• Product• Division

UNION

INTERSECTION

DIFFERENCE



• Selection• The select operator, sometimes called restrict to prevent confusion with the SQL SELECT command, retrieves subsets of rows from a relational table based on a value(s) in a column or columns

A B C D E

1 A 212 Y 2

2 C 45 N 84

3 B 8656 N 4

4 D 324 N 56

5 C 5656 Y 34

6 A 445 N 4

7 B 546 Y 55


• Projection• The project operator retrieves subsets of columns from a relational table removing duplicate rows from the result

A B C D E

1 A 212 Y 2

2 C 45 N 84

3 B 8656 N 4

4 D 324 N 56

5 C 5656 Y 34

6 A 445 N 4

7 B 546 Y 55


k x y

1 A 2

2 B 4

3 C 6

k x y

1 A 2

4 D 8

5 E 10

Table A

Table B

A TIMES B

ak ax ay bk bx by

1 A 2 1 A 2

1 A 2 4 D 8

1 A 2 5 E 10

2 B 4 1 A 2

2 B 4 4 D 8

2 B 4 5 E 10

3 C 6 1 A 2

3 C 6 4 D 8

3 C 6 5 E 10

• Product• The product of two relational tables, also called the Cartesian Product, is the concatenation of every row in one table with every row in the second. • The product of table A (having m rows) and table B (having n rows) is the table C (having m x n rows). The product is denoted as A X B or A TIMES B


• Join• Combines the product, selection and projection operations• Combines (concatenates) data from one row of a table with rows from

another or same table• Criteria involve a relationship among the columns in the join relational table

If the join criterion is based on equality of column value, the result is called an equi join A natural join is an equi join with redundant columns removed Joins can also be done on criteria other than equality. Such joins are called non-equi joins

k a b

1 A 2

2 B 4

3 C 6k c

1 aa

3 bb

5 cc

k a b k c

1 A 2 1 aa

3 C 6 3 bb

k a b c

1 A 2 aa

3 C 6 bb

Table A

Equi-JoinTable B

Natural Join



• Union• The UNION operation of two tables is formed by appending rows from one

table to those of a second to produce a third. Duplicate rows are eliminated• Tables in an UNION operation must have the same number of columns and

corresponding columns must come from the same domain

Table A

Table B

k x y

1 A 2

2 B 4

3 C 6

k x y

1 A 2

4 D 8

5 E 10

k x y

1 A 2

2 B 4

3 C 6

4 D 8

5 E 10

A Union B



• Intersection • The intersection of two relational tables is a third table that contains common rows. Both tables must be union compatible. The notation for the intersection of A and B is A [intersection] B = C or A INTERSECT B

k x y

1 A 2

2 B 4

3 C 6

k x y

1 A 2

4 D 8

5 E 10

k x y

1 A 2

Table A

Table B

A Intersect B



• Difference

• The difference of two relational tables is a third that contains those

rows that occur in the first table but not in the second. The Difference

operation requires that the tables be union compatible.

The notation for difference is A MINUS B or A-B. As with arithmetic, the order of

subtraction matters. That is, A - B is not the same as B - A.

k x y

1 A 2

2 B 4

3 C 6

Table A

Table B

A MINUS B

k x y

1 A 2

4 D 8

5 E 10

B MINUS A

k x y

2 B 4

3 C 6

k x y

4 D 8

5 E 10



Table A Table B

A DIV B

• Division• The division operator results in columns values in one table for which there are other matching column values corresponding to every row in another table.

k x y

1 A 2

1 B 4

2 A 2

3 B 4

4 B 4

3 A 2

x y

A 2

B 4

k

1

3


PART-2 PART-2 DATABASES MODELSDATABASES MODELS

{ Relational,Heirarchical,Network,E-R Model}{ Relational,Heirarchical,Network,E-R Model}&&

RELATIONAL ALGEBRA OPERATIONSRELATIONAL ALGEBRA OPERATIONS

DBMS by Er. K.S.Dhindsa © 2006

Lecture Series By :Lecture Series By :Er. Kanwalvir Singh DhindsaEr. Kanwalvir Singh DhindsaDeptt. of CSE & ITDeptt. of CSE & IT

For downloading slides of DBMS, Visit :For downloading slides of DBMS, Visit :

WEBSITE : WEBSITE : www.dhindsa.infowww.dhindsa.info Homepage: Homepage: http://groups.google.com/group/DBMS-2006http://groups.google.com/group/DBMS-2006

Part 2 Dbms Models

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