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CXB 3104

Advanced Database Systems

Lecture 3

Muthu

muthma@sunway.edu.my

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Relational tables are sets.

Rows of the tables can be considered as

elements of the set

Operations that can be performed on sets

can be done on relational tables.

Relational Data Manipulation

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Union Operator

The union operation of two relational tables

is formed by appending rows from one table

to those of a second table to produce athird.

Duplicate rows are eliminated.

Tables that are union compatible must have

the same number of columns and

corresponding columns must come from

the same domain.

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Union Operator

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Difference Operator

The difference of two relational tables is a

third that contains those rows that occur in

the first table but not in the second

Requires that the tables be union

compatible.

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Difference Operator

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Intersection Operator

The intersection of two relational tables is a

third table that contains common rows.

Requires that the tables be union compatible.

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Intersection Operator

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Product Operator

The product of two relational tables iscalled the Cartesian product.

It is the concatenation of every row in onetable with every row in the second.

The product of table A (having m rows) andtable B (having n rows) is the table C (having

m x n rows).

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Product Operator

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Projection & Selection Operators

Projection The project operator retrieves a subset of columns from

a table, removing duplicate rows from the result.

Yields vertical subset of a table

Selection The select operator retrieves subsets of rows from a

relational table based on a value(s) in a column or

columns.

Yields a horizontal subset of a table

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combines the product, selection, and projection

combines data from one row of a table with rows fromanother or the same table when certain criteria are met.

criteria involves a relationship among the columns in thejoin relational table.

If the join criterion is based on equality of column value,the result is called an equijoin.

A natural join removes redundant columns.

Join Operator

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Join Operator

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Results in columns values in one table for

which there are other matching column

values corresponding to every row in another

table.

Division Operator

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Data Dictionary

It provides details of all tables found within thedatabase.

It contains all the attribute name and characteristicsfor each table in the system.

The data dictionary contains metadata - data aboutdata

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Data Dictionary

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Normalization

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Database Tables and Normalization

Normalization

Process for evaluating and correcting table

structures to minimize data redundancies

helps eliminate data anomalies

Works through a series of stages called normal

forms:

Normal form (1NF)

Second normal form (2NF)

Third normal form (3NF)

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Database Tables and Normalization

2NF is better than 1NF; 3NF is better than

2NF

For most business database design purposes,

3NF is highest we need to go in the

normalization process

Highest level of normalization is not always

most desirable

What is Normalisation?

In a RDB normalisation is crucial for:

retaining data consistency on updates

Minimizing data redundancy and

therefore reducing file space required

in the database

Minimize data storage

Key Concepts in normalization are

Functional Dependency and keys

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Update Anomalies

Tables that have redundant data may have

problems called update anomalies.

Consider the following table of data on products

and required manufacturing equipment:

Derby

Derby

Rugby

Derby

Westwood

Westwood

Davison

Westwood

Smith

Smith

Jones

Jones

cooler

heater

pump

heater

Ethylene

Ethylene

Styrene

Styrene

Supplier

address

Equipment

supplier

Product

manager

Equipment

name

Product

name

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Deletion Anomalies

If a row is deleted that represents the

last product with a particular piece of

equipment, the equipment details are

also lost - this is a deletion anomaly.

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Deletion Anomalies example

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Derby

Derby

Rugby

Derby

Westwood

Westwood

Davison

Westwood

Smith

Smith

Jones

Jones

cooler

heater

pump

heater

Ethylene

Ethylene

Styrene

Styrene

Supplieraddress

Equipmentsupplier

Productmanager

Equipmentname

Productname

Loss of equipment Supplier Details

Insert Anomalies

Insert anomalies -

New rows that are entered must always

have consistent sets of product and/orequipment - human error may lead to

inconsistencies

Product and equipment data cannot be

entered separately without using null values

- this might violate primary keys

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Insert Anomalies example

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Potential for inconsistent data sets

Modification Anomalies

An update on the values of product or

equipment in one row must also be

performed on all the other rows that

have the same product or equipment, or

inconsistencies will occur in the data -

modification anomaly

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Modification Anomalies example

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Normal Forms

Normal Forms are rules developed to

avoid logical inconsistencies from table

update operations.

Each normal form prohibits a form of

redundancy in table organisation that

could yield meaningless results if one

table were updated independently of

other tables or other rows in the table.

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Normal Forms

There are multiple levels of normal forms.

Each higher level adds in an additionalconstraint to the level preceding it.

As the database design satisfies higher levelnormal forms the tables become morefragmented. This means that:

As data consistency is improved database navigationand hence queries become slower

The tables become less like the real-world systemthey represent.

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Normal Forms

The six normal form levels are: 1st Normal Form (1NF)

2nd Normal Form (2NF)

3rd Normal Form (3NF)

Boyce-Codd Normal Form (BCNF)

4th Normal Form (4NF)

5th Normal Form (5NF)

Usually ensuring that the database satisfies thethird normal form is sufficient for dataconsistency.

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First Normal Form- 1

A table is in first normal form when a

primary key can be defined for each

combination of data.

In the example below, a row has two entries in

column Equipment name.

Product

name

Equipment

name

Product

manager

Equipment

supplier

Supplier

address

Ethylene

Styrene

Styrene

cooler, heater

pump

heater

Smith

Jones

Jones

Westworld

Davison

Westworld

Derby

Rugby

Derby

Table violates INF

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First Normal Form2

This can be remedied by using two rows for the

dual entry:

Product

name

Equipment

name

Product

manager

Equipment

supplier

Supplier

address

Ethylene

Ethylene

Styrene

Styrene

cooler

heater

pump

heater

Smith

Smith

Jones

Jones

Westwood

Westwood

Davison

Westwood

Derby

Derby

Rugby

Derby

Table satisfies INF Table violates 2NF

Primary key: (Product name, Equipment name)

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Third Normal Form - 1

A table is in third normal form when it

satisfies second normal form and each non-

primary key column directly depends on the

primary key.

In the example, 3NF is violated because there

is transitive dependency. Supplier address

depends on Equipment supplier which in turn

depends on the primary key.

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Third Normal Form2

This can be remedied by splitting off this

indirect dependence into a further table:

Tables satisfy 3NF

Primary key:(Product name, Equipment name)

Product

name

Product

manager

Ethylene

Styrene

Smith

Jones

Primary key:

(Product name)

Equipment

supplier

Supplier

address

Westwood

Davison

Derby

Rugby

Product

name

Equipment

name

Equipment

supplier

Ethylene

Ethylene

Styrene

Styrene

cooler

heater

pump

heater

Westwood

Westwood

Davison

WestwoodPrimary key:

(Equipment supplier)

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Other Normal Forms

The data in a RDB is free of redundancy when

it is in the fifth normal form.

In this state an update on a column in anytable should not lead to data inconsistencies

occurring.

In practice it is adequate to normalise data

into the 3NF.

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