Keys-ERDs

Database Fundamentals - A Review

Victor Raj, PhDMurray State University

Objectives

• In this module, we will review the following:

• Primary key & its characteristics

• Composite Keys

• Foreign keys

• Anomalies & Relationships

• Dependencies and Normalization

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Tables

• Table: two-dimensional structure composed of rows and columns

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What is a database ‘table’?

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Primary Key

• Each row in a table must be uniquely identifiable

• A Primary Key is one or more attributes that determine other attributes

• PK’s role is based on determination• If you know the value of attribute/column A, you

can determine the value of attribute B

• If you know a person’s M# (at Murray), you can determine their name

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Keys (continued)

• Composite key• A key that is composed of more than one attribute

• Key attribute• Any attribute that is part of a key

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The importance of ‘null’

• Nulls:

• No data entered. Or the absence of a value

• Not permitted in primary key

• Should be avoided in other attributes

• Can represent • An unknown attribute value; a known, but missing,

attribute value; a “not applicable” condition

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Nulls (continued)

• Issues with Nulls:

• Can create problems when functions such as COUNT, AVERAGE, and SUM are used

• Can create logical problems when relational tables are linked – it may not retrieve some rows (costly lapse!)

• Databases need special functions to deal with themCIS609 (Review) 8

Back to Keys…

• Foreign key (FK)

• An attribute whose values match primary key values in a related table

• Referential integrity

• FK MUST contain a value that refers to an existing valid row in another table

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Integrity rules

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Integrity Rules (cont’d)

• Many RDBMs enforce integrity rules automatically

• However, it is safer to manage entity and referential integrity rules in the application - allows easier database migration.

• Developers use flags to avoid nulls – represents ‘unknown’

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Redundancy

• Simply means “duplication”

• Controlled redundancy:

• Makes the relational database work

• Facilitates linking of tables together

• Multiple occurrences of values not redundant when required to make the relationship work

• Redundancy exists only when there is unnecessary duplication of attribute values

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Excessive redundancy Anomalies

• Insert - You cannot add a row without being forced to add information that may not yet be available

• Delete - Deleting a row will result in the loss of other important information that you had no desire of losing

• Update - You are forced to make changes repeatedly

• See Video linked on canvas http://youtu.be/G9SA0Yv-o28

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Update anomaly

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What’s the problem here?

Deletion anomaly

M-number

Last name

First name

Course Time Room

M001 Smith Job ACC200 11:30 MW

BB302

M002 Smith Jhansi ACC200 12:30 TR

BB302

M001 Smith Job BUS215 12:30 MW

BB206

M003 Kline Smith BUS215 12:30 MW

BB206

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What challenges do you face when you delete a student? Or a

course?

Insertion anomaly

M-number

Last name

First name

Course Time Room

ACC200 11:30 MW

BB302

ACC200 12:30 TR

BB302

BUS215 12:30 MW

BB206

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Can you list all available courses?(Recall definition of PK… No NULLS allowed)

A good database designer can spot and fix such anomalies intuitively

How do you “fix” these anomalies?

…understand database relationships

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Relationships within the Relational Database

• 1:M relationship

• Very common

• 1:1 relationship

• Should be rare in any relational database design

• M:N relationships

• Also very common, but missed by novices

• Converted to two (or more) 1:M relationshipsCIS609 (Review) 18

The 1:M Relationship

• Relational database norm

• Found in any database environment

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Implementing 1:M

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The 1:1 Relationship

• One entity related to only one other entity, and vice versa

• Sometimes means that entity components were not defined properly

• Could indicate that two entities actually belong in the same table

• Certain conditions absolutely require their use

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The M:N Relationship

• Implemented by breaking it up to produce a set of 1:M relationships

• If two entities – STUDENTS, COURSES – have a M:N relationship, create a THIRD table to tie these two together (example follows)

• You must include (at the least) the primary keys of the tables to be linked in this THIRD table to ensure referential integrity (remember that?)

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Ensures referential integrity...

Cannot enroll students in classes that

don’t exist. Or enroll students that don’t exist in STUDENT

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This separation ensures that the

course information (title, credits etc.) are

not repeated unnecessarily.

Degree

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Now you know…

• The importance of keys

• Controlled redundancy

• The types of anomalies and the dangers they present

• The degree and types of relationships and how to spot them

• … now for Normalization

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Normal forms

• First – no repeating groups, but very likely to have partial dependencies

• Second – no repeating groups, no partial dependencies, but very likely to have transitive dependencies

• Third - no repeating groups, no partial dependencies, and no transitive dependencies.

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Repeating groups

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Partial dependency

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Transitive and partial dependency

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Removing all but the functional dependency will result in a 3NF design. “Removal” is accomplished by splitting the table into a set of related tables.

Summary - 1

• Tables are basic building blocks of a relational database

• Keys are central to the use of relational tables

• Keys define functional dependencies• Primary key

• Foreign key

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Summary - 2

• Each table row must have a primary key that uniquely identifies the other attributes

• Tables linked by common attributes• Good design begins by identifying entities,

attributes, and relationships• 1:1, 1:M, M:N (connectivity)

• Unary, binary, ternary (degree)

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Summary - 3

• Normalization

• First – no repeating groups, will have partial dependency

• Second – no partial dependency or repeating groups, will have transitive dependency

• Third – no transitive or partial dependency or even repeating groups.

• Normalization is good for maintaining data consistency and storage efficiency.

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