Transcript The Relational Database Model

Chapter 2
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The Relational Database Model
Database Systems: Design, Implementation, and Management
4th Edition
Peter Rob & Carlos Coronel
A Logical View of Data
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 Relational database model’s structural and
data independence enables us to view data
logically rather than physically.
 The logical view allows a simpler file
concept of data storage.
 The use of logically independent tables is
easier to understand.
 Logical simplicity yields simpler and more
effective database design methodologies.
A Logical View of Data
 Entities and Attributes

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An entity is a person, place, event, or thing for
which we intend to collect data.
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
University -- Students, Faculty Members, Courses
Airlines -- Pilots, Aircraft, Routes, Suppliers
Each entity has certain characteristics known as
attributes.

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Student -- Student Number, Name, GPA, Date of
Enrollment, Data of Birth, Home Address, Phone
Number, Major
Aircraft -- Aircraft Number, Date of Last Maintenance,
Total Hours Flown, Hours Flown since Last
Maintenance
A Logical View of Data
 Entities and Attributes

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A grouping of related entities becomes an entity
set.

The STUDENT entity set contains all student entities.

The FACULTY entity set contains all faculty entities.
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The AIRCRAFT entity set contains all aircraft entities.
A Logical View of Data
 Tables and Their Characteristics
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
A table contains a group of related entities -- i.e.
an entity set.

The terms entity set and table are often used
interchangeably.
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A table is also called a relation.
Summary of the Characteristics of a Relational Table
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Table 2.1
A Listing of the STUDENT Table Attribute Values
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Figure 2.1
Keys
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 Controlled redundancy (shared common
attributes) makes the relational database
work.
 The primary key of one table appears again
as the link (foreign key) in another table.
 If the foreign key contains either matching
values or nulls, the table(s) that make use of
such a foreign key are said to exhibit
referential integrity.
Figure 2.2
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An Example of a Simple Relational Database
The Relational Schema for the CH2_SALE_CO Database
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Figure 2.3
Keys
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
A key helps define entity relationships.

The key’s role is based on a concept known as
determination, which is used in the definition of
functional dependence.
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The attribute B is functionally dependent on A if A
determines B.
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An attribute that is part of a key is known as a key
attribute.

A multi-attribute key is known as a composite key.
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If the attribute (B) is functionally dependent on a
composite key (A) but not on any subset of that
composite key, the attribute (B) is fully functionally
dependent on (A).
Student Classification
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Table 2.2
Relational Database Keys
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Table 2.3
Integrity Rules Revisited
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Table 2.4
Figure 2.4
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An Illustration of Integrity Rules
Relational Database Operators
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 The degree of relational completeness can
be defined by the extent to which relational
algebra is supported.
 Relational algebra defines the theoretical
way of manipulating table contents using
the eight relational functions: SELECT,
PROJECT, JOIN, INTERSECT, UNION,
DIFFERENCE, PRODUCT, and DIVIDE.
Relational Database Operators
 UNION combines all rows from two tables.
The two tables must be union compatible.
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Figure 2.5 UNION
Relational Database Operators
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 INTERSECT produces a listing that contains
only the rows that appear in both tables. The
two tables must be union compatible.
Figure 2.6 INTERSECT
Relational Database Operators
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 DIFFERENCE yields all rows in one table
that are not found in the other table; i.e., it
subtracts one table from the other. The
tables must be union compatible.
Figure 2.7 DIFFERENCE
Relational Database Operators
 PRODUCT produces a list of all possible
pairs of rows from two tables.
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Figure 2.8 PRODUCT
Relational Database Operators
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 SELECT yields values for all attributes
found in a table. It yields a horizontal subset
of a table.
Relational Database Operators
 PROJECT produces a list of all values for selected
attributes. It yields a vertical subset of a table.
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Relational Database Operators
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 JOIN allows us to combine information from
two or more tables. JOIN is the real power
behind the relational database, allowing the
use of independent tables linked by
common attributes.
Relational Database Operators
 Natural
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JOIN links tables by selecting
only the rows with common values in
their common attribute(s). It is the result
of a three-stage process:
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A PRODUCT of the tables is created. (Figure
2.12)
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A SELECT is performed on the output of the
first step to yield only the rows for which the
common attribute values match. (Figure 2.13)
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A PROJECT is performed to yield a single
copy of each attribute, thereby eliminating the
duplicate column. (Figure 2.14)
Natural Join, Step 1: PRODUCT
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Figure 2.12
Figure 2.13 Natural Join, Step 2: SELECT
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Figure 2.14 Natural Join, Step 3: PROJECT
Relational Database Operators

EquiJOIN links tables based on an equality
condition that compares specified columns of
each table. The outcome of the EquiJOIN does not
eliminate duplicate columns and the condition or
criteria to join the tables must be explicitly
defined.

Theta JOIN is an equiJOIN that compares
specified columns of each table using a
comparison operator other than the equality
comparison operator.
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In an Outer JOIN, the unmatched pairs would be
retained and the values for the unmatched other
tables would be left blank or null.
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Outer JOIN
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Figure 2.15
Relational Database Operators
 DIVIDE requires the use of one singlecolumn table and one two-column table.
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Figure 2.16 DIVIDE
The Data Dictionary and the
System Catalog
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 Data dictionary contains metadata to provide detailed
accounting of all tables within the database.
 System catalog is a very detailed system data
dictionary that describes all objects within the
database.
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System catalog is a system-created database whose
tables store the database characteristics and contents.
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System catalog tables can be queried just like any other
tables.
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System catalog automatically produces database
documentation.
A Sample Data Dictionary
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Table 2.6
Relationships within the
Relational Database
 E-R Diagram (ERD)
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
Rectangles are used to represent entities.
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Entity names are nouns and capitalized.
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Diamonds are used to represent the
relationship(s) between the entities.
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The number 1 is used to represent the “1” side of
the relationship.
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The letter M is used to represent the “many” sides
of the relationship.
The Relationship Between Painter and Painting
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Figure 2.17
An Alternate Way to Present the Relationship
Between Painter and Painting
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Figure 2.18
A 1:M Relationship: The CH2_MUSEUM Database
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Figure 2.19
The 1:M Relationship Between Course and Class
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Figure 2.20
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The M:N Relationship Between Student and Class
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Figure 2.22
Sample Student Enrollment Data
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Table 2.7
A Many-to-Many Relationship Between Student and Class
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Figure 2.23
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Changing the M:N Relationship to Two 1:M Relationships
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Figure 2.25
The Expanded Entity Relationship Model
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Figure 2.26
The Relational Schema for the Entity Relationship Diagram
in Figure 2.26
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Figure 2.27
Data Redundancy Revisited
 Proper use of foreign keys is crucial to
exercising data redundancy control.
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 Database designers must reconcile three
often contradictory requirements: design
elegance, processing speed, and
information requirements. (Chapter 4)
 Proper data warehousing design even
requires carefully defined and controlled
data redundancies, to function properly.
(Chapter 13)
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Figure 2.28
A Small Invoicing System
Figure 2.29
The Relational Schema for the Invoicing System in Figure 2.28
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The redundancy is crucial to the system’s success.
Copying the product price from the PRODUCT table
to the LINE table means that it is possible to maintain
the historical accuracy of the transactions.
Indexes
 An index is composed of an index key and a
set of pointers.
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Figure 2.30 Components of an Index