section 08 - review

Section 08 - REVIEW

E-R Diagrams

• The Entity-Relationship Approach

– Represents reality using well-defined graphics and rules

• Basic building blocks are “things” (entities) and relationships

Member

Animal

1 Adopts

E-R Diagrams

• Advantages– Theoretical foundation (Set Theory)– Good for communication– Build E-R Model, then translate to any

type of RDBMS• Disadvantages

– Different (yet another new thing to learn)– Must translate to the relational model

E-R Diagrams

• Entity-Relationship Model: Basic Concepts

– Entity

• Thing, Object, Concept of interest to the enterprise

• Each occurrence can be uniquely identified

E-R Diagrams

– Attribute

• Property of an entity

• Column

E-R Diagrams

– Relationship

• Association between two (or more) entities

E-R Diagrams

– Entity Identifier

• Attribute(s) whose value uniquely identifies an entity

• Primary Key

E-R Diagrams

• What is an Entity?

– Physical entity types

• Person

• Building

• Machine

• Book

• Usually Singular

E-R Diagrams

– Conceptual entity types

• Contract

• Account

• Order

• Course

E-R Diagrams

– Event entity types

• Transaction

• Shipment

• Reservation

• Phone Call

• Seminar Offering

E-R Diagrams

• Entity-Relationship Model: Diagrams– Example:

– Soft Rectangle represents entities• Noun• Singular

– Connecting Line represents relationships• Verb

Member

Animal

Adopts

E-R Diagrams

• Relationships have Characteristics

– A relationship has Cardinality (Degree)

One-to-One One-to-Many Many-to-Many

E-R Diagrams

• Each entity’s participation is Mandatory or Optional

• Cardinality & Optionality

are based on business rules

Mandatory

Optional

E-R Diagrams

• Mandatory

– Every instance of the entity MUST participate in the relationship

– Example:

• Every animal is cared for by at least one employee

E-R Diagrams

• Optional

– An instance of the entity CAN participate in the relationship

– Example:

• Some employees do not take care of animals

E-R Diagrams

• Determining Optionality & Cardinality

– Optionality & Cardinality

• Specify lower and upper bounds of each entity’s participation in the relationship

• Use one of the following templates

E-R Diagrams

• Template 1

One ________(can/must) ________ (one and only one/one or more) __________

• Template 2 One ________ ________a minimum of (0/1) and a maximum of (1/many) __________

E-R Diagrams

• Use either template

– Read each relationship twice

• Left to Right

• Right to Left

E-R Diagrams

• Guidelines to Develop an E-R Diagram

– Identify the Major Entities

– Identify the Attributes for each entity

– Determine the Unique Identifier(s)

– Identify the Relationships

– Assign Cardinality

– Determine Optionality

– Resolve M:N Relationships

E-R Diagrams

• Mapping the E-R Diagram to the Relational Database

– Each entity becomes a Table

– Each attribute becomes a Column

– Unique Identifier becomes the PK

– Each 1:M becomes a FK on the Many Side

E-R Diagrams

• Practice 01

– A company has ten departments

– A company has five divisions

– A company has one hundred employees

– Each employee must work for one department

– Each division has two departments

E-R Diagrams

• Practice 02

– A company has twenty employees

– Each employee works for a department

– There are two departments in the company

E-R Diagrams

• Practice 03

– A company has three divisions

– A company has one manager per division

– Each manager is in charge of one committee

E-R Diagrams

• Practice 04

– A company has a sales department with fifteen salespersons

– Each salesperson works for the sales department

– Each salesperson is supervised by one manager

– The managers may not have an employee to supervise

E-R Diagrams

• Practice 05

– A piece of equipment is built with ten parts

– The parts come from suppliers

– All parts are held in inventory until needed to build a piece of equipment

E-R Diagrams

• Practice 06

– There are two hundred students

– Each student must attend an orientation

– An orientation is held at the beginning of each semester

– Students attend the orientation in their first or second semester

E-R Diagrams

• Practice 07

– There are forty rooms in a dorm

– Each room in the dorm holds two students

– There are five dorms on campus

– Each dorm has four floors

E-R Diagrams

• Practice 08

– Each faculty member advises fifty students

– Each student has an advisor

– There are faculty that do not advise students

E-R Diagrams

• Practice 09

– Students enroll in courses

– Courses are taught each semester

– Students receive a final grade for each course

– Each course has a maximum number of students enrolled

– Each course has a minimum number of students enrolled

E-R Diagrams

• Practice 10– Basketball players sign contracts– Contracts are good for one to three years– Some players play in a game– Not all players may play in a game– Some players may be injured– Some injuries require a hospital visit– Hospitals take care of patients– Some hospital patients are basketball

players

End 10-21-05

Normalization

• Normalization using Codd’s Rules– Codd and contemporaries developed rules for

“Normal Forms”• 1NF• 2NF• 3NF

– Normal levels to do in database design• Boyce/Codd NF – 3.5NF• 4NF• 5NF

Normalization

Class Enrolment

Class CodeClass

DescriptionStudent Number Name

Mgt Info Systems

000010000300005

Masters, RickSmith, SteveJones, Terry

Quant Methods

000020000300004

Wallace, FredSmith, SteveNurk, Sterling

Normalization

Class Enrolment

Class Code Class Description Student Number Name

503 Mgt Info Systems 00001 Masters, Rick

503 Mgt Info Systems 00003 Smith, Steve

503 Mgt Info Systems 00005 Jones, Terry

540 Quant Methods 00002 Wallace, Rusty

540 Quant Methods 00003 Smith, Steve

540 Quant Methods 00004 Nurk, Sterling

Normalization2NF

Class Enrolment

Normalization

Class Code Class Description

503 Mgt Info Systems

540 Quant Methods

2NF & 3NF

Student Number

00001 Masters, Rick

00006 Smith, Steve

00005 Jones, Terry

00002Wallace, Rusty

00003 Smith, Steve

00004 Nurk, Sterling

STUDENT

Normalization

• Rules for 1NF, 2NF, & 3NF– 1NF

• Break out repeating groups into a separate entity– 2NF

• Break out attributes that are dependent on part of the primary key into a separate entity

• Called Partial Dependency– 3NF

• Break out attributes that are wholly dependent on another key (not PK) into a separate entity

• Called Transitive Dependency

Normalization

• Normalization Cont’d– A relation is in 3NF if all the attributes are

functionally dependent• On the Key• On the Whole Key, and• On Nothing but the Key

–(So Help Me Codd)

Functional Dependency & Normalization

• How to Normalize Data using Functional Dependencies– Definition of Functional Dependency

• Given a relation R, attribute Y of R is functionally dependent on attribute X of R, if and only if each X value in R has associated with it precisely one Y-value in R (at any one time)

Functional Dependency

• Y of R is Dependent on X of R• X functionally determines Y

WARD NAME

WARD TYPE NO. OF BEDS

SENIOR NURSE

PATINET NO

PATIENT NAME

DATE OF BIRTH

Liston Orthopedic 6 J Bryan 45812 D Carter 21/02/65

Liston Orthopedic 6 J Bryan 71384 R Willis 08/10/46

Liston Orthopedic 6 J Bryan 69355 G Barnes 17/06/41

Godlee General 10 V Fox 52217 M Brown 21/02/35

Godlee General 10 V Fox 10823 R Willis 12/03/54

• Example 01

Subscriber

Number

Magazine

Magazine Start Date

End Date

101 Jones TIM Time 3/1993 2/1999

110 Allen NEW Newsweek

2/1996 1/1999

SCI Science 6/1994 5/2000

202 Smith

NEW Newsweek

2/1994 1/1999

TIM Time 5/1994 4/2001

• Example 01• Normalization begins with the arrangement of

information into tables with rows and columns such that repeating groups of information have been eliminated, that is, the "cells" have data with atomic values. In addition, normalized tables should have some data field(s) which is unique for all rows.

• In this case, because SMITH has two identical subscriptions, we need to invent a new field, namely SUBSCRIPTION NUMBER, in order to insure uniqueness, i.e. no duplicate rows

• Example 01• 1NF – Resulting Table

Subscriber

Number

Subscription

Number

Magazine

Magazine Start Date

End Date

101 Jones 001 TIM Time 3/1993 2/1999

110 Allen 002 NEW Newsweek

2/1996 1/1999

110 Allen 003 SCI Science 6/1994 5/2000

202 Smith

004 NEW Newsweek

2/1994 1/1999

202 Smith

005 TIM Time 5/1994 4/2001

202 Smith

006 TIM Time 5/1994 4/2001

• Example 01• Functional Dependency A central concept of

the normalization process is the functional dependency. Simply put, a functional dependency exists between two data fields when for each distinct value of one field, there is only one possible value for the other field.

• Example 01• For example, if we assume that SUBSCRIBER

NUMBER is a uniquely assigned number for each subscriber, then there is a functional dependency between SUBSCRIBER NUMBER and NAME. We could say that SUBSCRIBER NUMBER functionally determines NAME or, conversely,that NAME is functionally dependent upon SUBSCRIBER NUMBER.

• Example 01• This functional dependency and others are shown

below, using a convenient notation, i.e. " A-->B.“

• SUBSCRIBER NUMBER-->NAME• MAGAZINE CODE-->MAGAZINE• SUBSCRIPTION NUMBER-->SUBSCRIBER

NUMBER, NAME, MAGAZINE CODE,MAGAZINE, START DATE, END DATE

• Example 01• It is critical to this process to fully understand

the underlying assumptions about the information that is being normalized. Successful normalization is, for all practical purposes, impossible without understanding the meaning and usage of information.

• Example 01• In our example, our assumptions are: • (1) SUBSCRIBER NUMBER is uniquely

assigned to each subscriber.• (2) MAGAZINE CODE is a convenient unique

code for each magazine name.• (3) SUBSCRIPTION NUMBER is uniquely

assigned to each subscription and therefore functionally determines all fields.

• Example 01• 2NF• Information which is in Second Normal Form has the

quality that some field (or fields) functionally determines all of the others. This field(s) is called a primary key. Building Second Normal Form tables is simply the mechanical process of making tables out of the functional dependencies and noting which field(s) is the primary key. The following notation shows our new tables in Second Normal Form.

• Example 01• 2NF

Subscriber

NumberKEY

Subscriber

Magazine

CodeKEY

Magazine

Subscription

NumberKEY

Subscriber

Number

Magazine

EndDate

Subscriber Table

Magazine Table

Subscription Table

• Example 01• At this point in the normalization process, the

task is to determine if the Second Normal Form tables are also in Third Normal Form. Third Normal Form tables are defined as tables where there is no functional dependency between non-key fields.

• Example 01• The SUBSCRIBER and MAGAZINE tables are

therefore in Third Normal Form since each has only one non-key field. The SUBSCRIPTION table, however, has several functional dependencies between non-key fields. They are:

• SUBSCRIBER NUMBER --> NAME• MAGAZINE CODE --> MAGAZINE. • This table can be made into Third Normal Form by

very simply eliminating the dependent field(s).

• Example 01• 3NF

Subscriber

NumberKEY

Subscriber

Magazine

CodeKEY

Magazine

Subscription

NumberKEY

EndDate

Subscriber Table

Magazine Table

Subscription Table

• Example 01• Having reached Third Normal Form, it

should be possible to identify foreign keys. Foreign keys are some field(s) in one table which is(are) the primary key in another.

• Example 01• In this case, SUBSCRIBER NUMBER in the

SUBSCRIPTION table is a foreign key referencing the primary key of the SUBSCRIBER table. And MAGAZINE CODE in the SUBSCRIPTION table is a foreign key referencing the primary key of the MAGAZINE table.

SubscriptionNumber

Primary Key

SubscriberNumber

Foreign Key

MagazineCode

Foreign Key

EndDate

Normalization

• Practice 01

Student# Advisor Adv-Room Class1 Class2 Class3

1022 Jones 412 101-07 143-01 159-02

4123 Smith 216 201-01 211-02 214-01

Normalization

• Practice 01• 1NF

Student# Advisor Adv-Room Class#

1022 Jones 412 101-07

1022 Jones 412 143-01

1022 Jones 412 159-02

4123 Smith 216 201-01

4123 Smith 216 211-02

4123 Smith 216 214-01

Normalization

Student:

Student# Advisor Adv-Room

1022 Jones 412

4123 Smith 216

Registration:

Student# Class#

1022 101-07

1022 143-01

1022 159-02

4123 201-01

4123 211-02

4123 214-01

Normalization

Students:

Student# Advisor

1022 Jones

4123 Smith

Faculty

Advisor Room

Jones 412

Smith 216

Normalization

• Practice 01• Final Tables

Student:

Student# Advisor

1022 Jones

4123 Smith

Faculty

Advisor Room

Jones 412

Smith 216

Registration:

Student# Class#

1022 101-07

1022 143-01

1022 159-02

4123 201-01

4123 211-02

4123 214-01

Normalization

• Practice 02

Class Enrollment

Class CodeClass

DescriptionStudent Number

00003 Smith, Steve

00005 Jones, Terry

540 Quant Methods 00002 Wallace, Fred

00003 Smith, Steve

Normalization

Class Enrollment

Normalization

• Practice 02• 2NF• 3NF

Student Number

00001 Masters, Rick

00002 Wallace, Rusty

00003 Smith, Steve

00005 Jones, Terry

Class CodeClass

Description

503 Mgt Info Systems

540 Quant Methods

STUDENT

Normalization

• Practice 03

Projectnumber

Project name

Employee number

Employeename

RateCategory

Hourlyrate

1023Madagascartravel site

11VincentRadebe

12 Pauline James B $50

16Charles

RamorazC $40

1056OnlineEstateagency

11VincentRadebe

17MoniqueWilliams

Normalization

Project number

Project name

Employee number

Employee name

Rate category

Hourly rate

1023Madagascar

travel site11

Vincent Radebe

1023Madagascar

travel site12

Pauline James

1023Madagascar

travel site16

Charles Ramoraz

1056Online estate

agency11

Vincent Radebe

1056Online estate

agency17

Monique Williams

Normalization• Practice 03• 2NF Cont’d

Project number

Project name

1023 Madagascar travel site

1056 Online estate agency

PROJECT

Normalization• Practice 03• 2NF

Employee number

Employee name

Rate category

Hourly rate

11Vincent Radebe

12Pauline James

16Charles

RamorazC $40

17Monique Williams

EMPLOYEE

Normalization

Employeenumber

Employee name

11 Vincent Radebe

12 Pauline James

16 Charles Ramoraz

17 Monique Williams

EMPLOYEE

Rate category Hourly rate

• De-normalization– De-normalization means combining two

(or more) tables• Usually done when tables are

frequently joined– De-normalization (joining two tables)

depends on usage• Depends on how applications and

users access the data

De-Normalization

• De-normalization is done to improve performance

– Tailors data structures for one specific application’s use

– Improves performance of one type of access at expense of others

De-Normalization

• De-normalization Trade-Offs

Normalization De-normalization

Eliminates update anomalies Improves performance for specific application(s)

Minimizes data redundancy

Supports simpler logic

Provides application-independent database design

Encourages sharing of data

• When to De-Normalize– This is EVIL, Do Not Do…– When does de-normalization have

minimal impact?• Data is accessed primarily on a

read-only basis• Data is accessed primarily by one

application

De-Normalization

• When to de-normalize

– After database design is done and tables are normalized to 3NF

– After clustering related tables in the same logical container

– After considering trade-offs and usage of data

De-Normalization

• Alternatives to de-normalization– Physical placement of data

• Use of container• Can improve performance without

impacting logical design– Selective hardware upgrades

• More main memory, expanded storage, cache storage devices

De-Normalization

• Fragmentation – Better alternative to de-normalization– Means breaking one table into two (or

more) tables• Usually done when one table is very

large• Or groups of user almost exclusively

access a subset of data in a table

Fragmentation

• Fragmentation can be based on selection or projection– Must be able to reconstruct the

original table – by union or join– Primary key column(s) must be

included in all vertical fragments• Disadvantage is that the user must be

aware of all the fragmented tables

Fragmentation

Physical Design

• Physical Database Design– Goals

• Improve performance–By minimizing disk I/O

• Improving management of the data

–By grouping tables that can be managed as a group

• Steps in Physical Design Process– Determine which tables can be managed

as a group• Many RDBMSs support the concept of

a Container (Oracle Tablespace, db space, Access uses the .mdb)

–A collection of tables, and indexes

Physical Design

– Develop a plan for allocating tables to disk devices• Consider parallel disk controllers• Group tables together that are

frequently joined• Distribute heavily accessed table to

different disk devices–To avoid excessive head movement

on one disk

Physical Design

– Build indexes on table columns, based on frequency of use

– Restructure tables if necessary

• Fragment large tables into multiple smaller ones

• De-normalize tables if appropriate

Physical Design

• Indexes

– Index is a separate structure (table)

• Points into the data table

• Built on one or more columns in the data table

Physical Design

• Comments on Indexing– An index can be built on any column or

combination of columns– An index can be unique or non-unique– An index on the primary key is called the

primary index– Most RDBMSs use an internal row id as

the pointer to the row– Use of the index is transparent to the user

Physical Design

• Use of an index

– Provides access to a row based on data value(s)

– Avoids duplicates – only way

– Supports sequential processing on the indexed field

– Improves performance

Physical Design

• Use of an index improves performance on Retrieval– Processing an index is more efficient than

processing a table – for reads• Index is usually small, relative to the

table–Can be held entirely in memory

• The smaller the index value, the more entries per block the more likely the index will be in memory

Physical Design

• Use of index degrades performance on Updates

– Inserting a row is the source of much disk I/O (overhead)

• Every index on the table must be searched and updated also

Physical Design

• Data Types– Depends on the conventions used by a

particular database– ORACLE uses:

• NUMBER• CHAR - Characters

• VARCHAR2 - Characters• DATE/TIME• LOB

Physical Design

• NUMBER– Numerical data– Guaranteed to 38 digits accuracy– NUMBER(10) – 10 digits allowed

• CHAR– Character data– Fixed-Length up to 2,000 bytes– Good for 2 or 3 characters– Y/N, T/F, USA/CAN– CHAR(2) – 2 characters allowed

Physical Design

• VARCHAR2– Character data– Variable-Length up to 4,000 bytes– VARCHAR2(15) – up to 15 characters

• DATE/TIME– Date & Time data– DATE – DD-MON-YY (Default)– TIME – HH:MN:SE (Default)

Physical Design

• LOB– Large OBject data type

• CLOB–Long variable length characters

• BLOB–Binary objects – Video, Sound, Graphics

• BFILE–Reference to an OS file

– Up to 4GB of data per file

Physical Design

• Structured Query Language

– DDL – Data Definition Language

• CREATE

• DROP

• ALTER

– DML – Data Manipulation Language

• SELECT

• INSERT

• DELETE

• UPDATE

– DCL – Data Control Language

• GRANT

• REVOKE

• Primary Key SQL

– PRIMARY KEY (student_ID)

• Foreign Key SQL

– CONSTRAINT student_ID FOREIGN KEY (student_id) REFERENCES Student(student_ID)

SQL• Practice 01• Create these Tables with SQL

Student:

Student# Advisor

1022 Jones

4123 Smith

Faculty

Advisor Room Dept

Jones 412 42

Smith 216 42

Registration:

Student# Class#

1022 101-07

1022 143-01

1022 159-02

4123 201-01

4123 211-02

4123 214-01

• Practice 01

• Registration Table

– CREATE TABLE registration

• (Student# NUMBER(5),

• Class# NUMBER(5));

• Practice 01

• Student Table

– CREATE TABLE student

• (Student# NUMBER(5),

• Advisor VARCHAR2(12));

• Practice 01

• Faculty Table

– CREATE TABLE faculty

• (Advisor VARCHAR2(12),

• Room NUMBER(4),

• Dept NUMBER(2));

• Practice 02• Create using SQL

SUPPLIER_ID NAME LOCATION ZIPCODE

10024 Best Buy OH 45502

13467 Circuit City WV 36709

45001 Staples KY 20065

SUPPLIER

SQL• Practice 02• Supplier Table

– CREATE TABLE supplier• (Supplier_ID Number(5),• Name

VARCHAR2(20),• Location CHAR(2),• Zipcode Number(5));

• Practice 03

• Create using SQL

Part# Part_Name Part_Loc Part_Price

Z143028G Widget 114 100

G45610B Thingy 232 500

WAREHOUSE

WHSE# WHSE_Size WHSE_City WHSE_StateWHSE_Statu

114 24000 Rio Grande OH Full

232 3200 Charleston WV Empty

• Practice 03

• Parts Table

– CREATE TABLE Parts

• (Part# VARCHAR2(12),

• Part_Name VARCHAR2(20),

• Part_Loc NUMBER(3),

• Part_Price NUMBER(4));

SQL• Practice 03• Warehouse Table

– CREATE TABLE warehouse • (WHSE# NUMBER(3),• WHSE_Size NUMBER(6),• WHSE_City VARCHAR2(15),• WHSE_State CHAR(2),• WHSE_Status VARCHAR2(10));

• Practice 04

• Use SQL to find the following:

– How many people make $10,000 per month

EMPLOYEE

Employee#Employee_Nam

eSalary

1001 Smith 10000

1002 Jones 12000

1003 Thomas 8000

1004 Harrison 9500

• Practice 04

– SQL• SELECT employee#, employee_name,

salary• FROM employee• WHERE salary = 10000;

eSalary

1001 Smith 10000

• Practice 05

– Who makes more than $8000 but less then $10000

EMPLOYEE

eSalary

1001 Smith 10000

1002 Jones 12000

1003 Thomas 8000

1004 Harrison 9500

• Practice 05

– SQL• SELECT employee#, employee_name,

salary• FROM employee• WHERE salary > 8000 AND salary < 10000;

eSalary

1004 Harrison 9500

• Practice 06

– Give me a list of employees and their salaries in alphabetical order?

EMPLOYEE

eSalary

1001 Smith 10000

1002 Jones 12000

1003 Thomas 8000

1004 Harrison 9500

• Practice 06

– SQL• SELECT employee_name Name, salary• FROM employee• ORDER BY employee_name;

Name Salary

Harrison 9500

Jones 12000

Smith 10000

Thomas 8000

END REVIEW

section 08 - review

er diagramidentify

er diagramsuse

companyer diagramspractice

committeeer diagramspractice

sideer diagramspractice

lefter diagramsguidelines

communicationbuild er

relationship twiceleft

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