1. Chapter 4: Logical Database Design and the Relational Model (Part I)
Modern Database Management
11th Edition
Jeffrey A. Hoffer, V. Ramesh,
Heikki Topi
We learned
Database Analysis;
We are moving into
Database Design

2. Objectives Part 1: Define terms List five properties of relations
Disambiguation:
“Data model” means E-R diagram;
“Relational model” means what we are learning in the current chapter
1) short text statement, and
2) graphical representation
Part 1:
Define terms
List five properties of relations
State two properties of candidate keys
Define first, second, and third normal form
Describe problems from merging relations
Transform E-R and EER diagrams to relations
Create tables with entity and relational integrity constraints
Part 2:
Use normalization to convert anomalous tables to well-structured relations

3. Database Schema (Ch 1, Slide #40)
External Schema
User Views
Subsets of Conceptual Schema
Can be determined from business-function/data entity matrices [Fig 1-6]
DBA determines schema for different users
Conceptual Schema
E-R models – covered in Chapters 2 and 3
Internal Schema
Logical structures–covered in Chapter 4 (Relational model)
Physical structures–covered in Chapter 5

4. Introduction
Logical DB design: process of transforming the conceptual data model (i.e., ERD) into a logical data model (i.e., models in this chap)
Conceptual data modeling: getting the right requirements >>model the biz logic correctly
Logical DB design: getting the requirements right >>correctly transform the biz logic for implementation
An E-R data model is not a relational data model need normalization [2nd half of Ch 4]
ERD is developed for the purpose of understanding biz rules, not structuring data for sound DB processing
The last part is the goal of logical DB design

5. NOTE: all relations are in 1st Normal form
A relation is a named, two-dimensional table of data.
A table consists of rows (records) and columns (attributes or fields).
Requirements for a table to qualify as a relation:
It must have a unique name.
Every attribute value must be atomic
(not multivalued, not composite).
Every row must be unique (can’t have two rows with exactly the same values for all their fields).
Attributes (columns) in tables must have unique names.
The order of the columns must be irrelevant.
The order of the rows must be irrelevant.
NOTE: all relations are in 1st Normal form

6. Correspondence with E-R Model
Relations (tables) correspond with entity types and with many-to-many relationship types.
Columns correspond with attributes.
Rows correspond with entity instances and with many-to-many relationship instances.
We can express the structure of a relation by a shorthand notation (“text description”):
RELATION (attribute1, attribute2, attribute3, …)
Example: PRODUCT( … )  exercise
NOTE: The word relation (in relational database) is NOT to be confused with the word relationship (in E-R model): …

7. Correspondence of terms
Entity (type)
Entity instance
Attribute
Relation/Table
Row
Column
Examples:
STUDENT
John Smith
3.5 (for GPA field)
COMPANY
STUD_CLUB
EXAM

8. Key Fields Keys are special fields that serve two main purposes:
Primary keys are unique identifiers of the relation in question. - how we can guarantee that all rows are unique.
Foreign keys are identifiers that enable a dependent relation (on the many side of a relationship) to refer to its parent relation (on the one side of the relationship).
an attribute in a relation (table) of a database that serves as the primary key of another relation in the same database
Keys can be simple (a single field) or composite (more than one field).
Keys usually are used as indexes to speed up the response to user queries (Ch 5).

9. Removing multivalued attributes Fig 4-2a
Identify the multivalued attributes for several records (entity instances)

10. Removing multivalued attributes Fig 4-2b
Simple ways of treating multivalued and composite attributes …

11. Schemas The structure of the DB is described through schemas
Two common methods for expressing schema:
Short text statements (example: Slide 12)
RELATION (attribute1, attribute2, attribute3, …)
EMPLOYEE (Emp_ID, LastName, FirstName, …)
Graphical representation (example: Slide 13)
Each relation represented by a rectangle containing attributes
RELATION
Attr1
Attr2
Attr3
Attr4
Attr5

12. Short Text Statement of PVFC
Primary key Foreign key
Short Text Statement of PVFC
Graphical representation:
Lines/curves with arrowhead are used to indicate the referencing relationship (referential integrity – Slides #13 and 17) between foreign key and primary key.

13. Foreign Key (implements 1:N relationship between customer and order)
Fig 4-3 Schema for four relations (graphical representation)
Primary Key
Will be req’d the most
for HW
Foreign Key (implements 1:N relationship between customer and order)
Combined, these are a composite primary key (uniquely identifies the order line)…
Individually, they are foreign keys (implement M:N relationship between order and product)
The curvy arrows here indicate relationships (PK – FK pairs)

14. Integrity Constraints
Domain Constraints
Allowable values for an attribute. See Table 4-1, P160
Other examples:
Entity Integrity
No primary key attribute may be null. All primary key fields MUST have data
Referential integrity
Primary key – Foreign key relationship
(   Slide #16)

15. Domain definitions enforce domain integrity constraints

16. Integrity Constraints – Referential Integrity
Rule states that any foreign key value (in the relation of the many side) MUST match a primary key value (in the relation of the one side). (Or the foreign key can be null)
For example: Delete Rules
Restrict–don’t allow delete of “parent” side if related rows exist in “child” / “dependent” side
Cascade–automatically delete “dependent” side rows that correspond with the “parent” side row to be deleted
Set-to-Null–set the foreign key in the dependent side to null if deleting from the parent side  not allowed for weak entities
Example using IS 312 DB

17. Note: From … To … Compared w next slide:
Figure 4-5
Referential integrity constraints (Pine Valley Furniture)
Note: From … To …
Referential integrity constraints are drawn via arrows from dependent to parent table …
From “M” to”1”
Compared w next slide:

18. (1) Primary key appears… (2) Foreign key departs from… ends at…
Figure 1-3(b), P.11
(1) Primary key appears…
(2) Foreign key departs from… ends at…

19. Summary of previous section
In ERD
In Rel Schema
Note
Entity
Table
No space in table name
Attribute
Column
attribute domains
Primary key
can be composite
1:M relationship
Prim. key on 1-side
Foreign on M-side
Don’t flip the two
! ! !
M:N relationship
New relation/table for the M:N relationship
M:N   associative entity  
table on its own
Relationship arrow always points from ___-side to __-side;
From _______ key to _______ key

20. Referential integrity constraints are implemented with
Figure 4-6 SQL table definitions
Referential integrity constraints are implemented with
foreign key to
primary key references

21. Anomalies Three anomalies in this relation/table: Insertion anomaly
Deletion anomaly
Modification anomaly (PP. 162~163)

22. Transforming EER Diagrams into Relations (PP. 165-6)
Three types of entities:

23. Transforming EER Diagrams into Relations
Mapping Regular Entities to Relations – handling attributes:
Simple attributes: E-R attributes map directly onto the relation (Fig 4-8, next slide)
Composite attributes: Use only their simple, component attributes (Figure 4-9)
Multivalued attribute: Becomes a separate relation with a foreign key taken from the superior entity (Figure 4-10)

24. Figure 4-8 Mapping a regular entity
(a) CUSTOMER entity type with simple attributes
(b) CUSTOMER relation

25. Figure 4-9 Mapping a composite attribute
(a) CUSTOMER entity type with composite attribute
(b) CUSTOMER relation with address detail

26. Figure 4-10 Mapping an entity with a multivalued attribute
Multivalued attribute becomes a separate relation with foreign key
Ref Slide #23
(b)
Imagine tables?
Q: from the left, who’s 1 and who’s M?
One–to–many relationship between original entity and new relation

27. Multi-valued attributes
The first relation EMPLOYEE has the primary key Employee_ID
The second relation EMPLOYEE_SKILL has two attributes Employee_ID and Skill, which form the primary key

28. Transforming EER Diagrams into Relations (cont.)
Mapping Weak Entities
Becomes a separate relation with a foreign key taken from the superior entity
Primary key composed of:
Partial identifier of weak entity
Primary key of identifying relation (strong entity)

29. What is its function/role?
Figure 4-11 Example of mapping a weak entity
a) Weak entity DEPENDENT
What is this?
What is its function/role?

30. “a foreign key taken from…” S#28
Figure 4-11 Example of mapping a weak entity (cont.)
b) Relations resulting from weak entity
NOTE: the domain constraint for the foreign key should NOT allow null value if DEPENDENT is a weak entity
Foreign key
Composite primary key
(= ? + ?)
“a foreign key taken from…” S#28

31. Transforming EER Diagrams into Relations (cont.)
Mapping Binary Relationships
One-to-Many–Primary key on the one-side becomes a foreign key on the many-side
Many-to-Many–Create a new relation with the primary keys of the two entities as its primary key
One-to-One–Primary key on the mandatory side becomes a foreign key on the optional side
(curvy) Arrows indicating referential integrity constraints
Points from M-side to 1-side
From foreign key to primary key

32. Figure 4-12 Example of mapping a 1:M relationship
a) Relationship between customers and orders
Note the mandatory one
b) Mapping the relationship
Again, no null value in the foreign key…this is because of the mandatory minimum cardinality
Foreign key

33. Map binary many-to-many (M:N) relationships
If M:N relationship exists between entity types A and B, we create a new relation C,
include as foreign keys in C the primary keys for A and B,
these attributes, together, become the primary key of C

34. Figure 4-13 Example of mapping an M:N relationship
a) Completes relationship (M:N)
Will be treated as an associative entity
The Completes relationship will need to become a separate relation

35. Figure 4-13 Example of mapping an M:N relationship (cont.)
b) Three resulting relations
The old “Completes” relationship
Composite primary key
New intersection relation
Foreign key
Foreign key
What can we say about arrow direction?
Associative entity/intersection relation is always on the M-side

36. Figure 4-14 Example of mapping a binary 1:1 relationship
a) In charge relationship (1:1)
Often in 1:1 relationships, one direction is optional

37. Map binary 1:1 relationships
In a 1:1 relationship, the association in one direction is often optional one, while the association in the other direction is mandatory one
think about STUDENT and PARKING_PERMIT
The primary key of one of the relations is included as a foreign key in the other relation
The primary key of the Mandatory side 
The foreign key of the optional side

38. Figure 4-14 Example of mapping a binary 1:1 relationship (cont.)
b) Resulting relations
Arrow points from _______ side to ____ side,
from ______ key to ____ key
Foreign key goes in the relation on the optional side,
matching the primary key on the mandatory side
Practice the same for the STUDENT and PARKING_PERMIT relationship

39. Transforming EER Diagrams into Relations (cont.)
Mapping Associative Entities
Three relations will be created: one for each of the original entities, and a third for the associative entity. Two situations:
Identifier Not Assigned
Default primary key for the association relation is composed of the primary keys of the two entities (as in M:N relationship)
Identifier Assigned (, when- )
It is natural and familiar to end-users
Default identifier may not be unique

40. Figure 4-15 Example of mapping an associative entity
An associative entity (will be transformed to an
“Intersection Relation”)
Regular entity
Associative entity
Regular relation
Intersection relation

41. Figure 4-15 Example of mapping an associative entity (cont.)
b) Three resulting relations
Associative entity/intersection relation is on _____-side; arrow points from ~~ to ~~
Composite primary key - two primary key attributes from the other two relations
two foreign keys, referencing the other two entities

42. Figure 4-16 Example of mapping an associative entity with
an identifier
a) SHIPMENT associative entity
In this situation, the associative entity type has a natural identifier that is familiar to end users – Shipment ID

43. Figure 4-16 Example of mapping an associative entity with
an identifier (cont.)
b) Three resulting relations
Primary key differs from foreign keys - identifier assigned

44. Transforming EER Diagrams into Relations (cont.)
Mapping Unary Relationships
One-to-Many: Recursive foreign key in the same relation
Many-to-Many: Two relations:
One for the entity type
One for an associative relation in which the primary key has two attributes, both taken from the primary key of the entity

45. Note the direction of the arrow!
Figure 4-17 Mapping a unary 1:N relationship
(a) EMPLOYEE entity with unary relationship
(b) EMPLOYEE relation with recursive foreign key
Note the direction of the arrow!
Examine the tables: …

46. An associative entity Figure 4-18 Mapping a unary M:N relationship
(a) Bill-of-materials relationships (M:N)
Is_contained_in
How do I know??
(b) ITEM and COMPONENT relations
An associative entity

47. Transforming EER Diagrams into Relations (cont.)
Mapping Ternary (and n-ary) Relationships
One relation for each entity, and one for the associative entity
Associative entity has foreign keys to each of the regular entities in the relationship

48. Figure 4-19 Mapping a ternary relationship
a) PATIENT TREATMENT Ternary relationship with associative entity

49. Figure 4-19 Mapping a ternary relationship (cont.)
b) Mapping the ternary relationship PATIENT TREATMENT
Remember that the primary key MUST be unique
This is why treatment date and time are included in the composite primary key
But this makes a cumbersome key…
It would be better to create a surrogate key like Treatment#
An associative entity

50. Transforming EER Diagrams into Relations (cont.)
Mapping Supertype/Subtype Relationships
One relation for supertype and for each subtype
Supertype attributes (including identifier and subtype discriminator) go into supertype relation
Subtype attributes go into each subtype; primary key of supertype relation also becomes primary key of subtype relation
1:1 relationship established between supertype and each subtype, with supertype as primary table
The last three slides – 50~52 – wait till we learn Chap 3

51. Figure 4-20 Supertype/subtype relationships

52. These are implemented as one-to-one relationships
Figure 4-21
Mapping supertype/subtype relationships to relations
These are implemented as one-to-one relationships