Introduction of Physical Database Design Process Designing Fields Choosing Data Types Controlling Data Integrity Denormalizing and Partitioning Data Designing Physical Database Files File Organizations Clustering Files Indexes Optimizing Queries

1. Institute of Southern Punjab,
Multan
Mr. Muhammad Nouman Farooq
BSC-H (Computer Science)
MS (Telecomm. and Networks)
Honors:
Magna Cumm Laude Honors Degree
Gold Medalist!
Blog Url: noumanfarooqatisp.wordpress.com
E-Mail: noman.iefr@hotmail.com

2. Advance Database Systems
Lecture# 7
Physical Database Design & Performance

3. Lecture 7: Physical Database Design & Performance
 Introduction of Physical Database Design Process
 Designing Fields
 Choosing Data Types
 Controlling Data Integrity
 Denormalizing and Partitioning Data
 Designing Physical Database Files
 File Organizations
 Clustering Files
 Indexes
 Optimizing Queries
3

4. Introduction of Physical Database Design &
Performance
4
 In previous lectures; We have learned how to describe and model
organizational data during the conceptual data modeling and logical
database design phases of the database development process. We
learned how to use EER notation, the relational data model, and
normalization to develop constructs of organizational data that
capture the meaning of data; however, these notations do not
explain how data will be processed or stored.
 The purpose of physical database design is to translate the logical
description of data into the technical specifications for storing and
retrieving data. The goal is to create a design for storing data that
will provide high performance and ensure database integrity,
security, and recoverability. Physical database design does not
include implementing files and databases (i.e., creating them and
loading data)

5.  Introduction of Physical Database Design
Process
5

6. 6
 The primary goal of physical database design is data processing
efficiency. It is very important for database developer to design the
physical database to minimize the time required by users to interact with
the information system.
 Designing physical files and databases requires certain information that
should have been collected and produced during prior database
development phases. The information needed for physical file and
database design includes these requirements:
• Normalizing Relations to eliminate anomalies
• Definitions of each attribute, along with physical specifications such as
maximum possible length
• Descriptions of where and when data are used: entered, retrieved,
deleted, and updated
• Requirements for response time and data security, backup, recovery
and integrity
• Descriptions of the simulator (database management systems) used for
implementing the database
Introduction of Physical Database Design Process

7. 7
 Physical database design requires several critical decisions that
will affect the integrity and performance of the application system.
These key decisions include the following:
• Choosing the storage format (called data type) for each attribute
from the logical data model. The format and associated
parameters are chosen to minimize storage space and to
maximize data integrity.
• Selecting structures (called indexes and database architectures)
for storing and connecting files to make retrieving related data
more efficient.
• Preparing strategies for handling queries against the database
that will optimize performance and take advantage of the file
organizations and indexes that you have specified.
Continued..

8.  Designing Fields
8

9. 9
Designing Fields
The basic decisions you must make in specifying each field concern
the type of data (or storage type) used to represent values of this
field, data integrity controls built into the database.

10.  Choosing Data Types
10

11. 11
Choosing Data Types
 A data type is a detailed coding scheme recognized by system
software, such as a DBMS, for representing organizational data.
 Selecting a data type involves four objectives that will have
different levels of importance for different applications:
1. Minimizing Storage Space
2. Represent all possible Values
3. Improve Data Integrity (only Legal Values allowed as per Field)
4. Support all Data Manipulations

12. 12

13. 13

14. 14
 Some attributes have set of values so large that, given data
volumes, considerable storage space will be consumed. A field with
a limited number of possible values can be translated into a CODE
that requires less space.
 Consider the example of the ProductFinish field illustrated in
Figure 5-2 on next slide. Products at Pine Valley Furniture come in
only a limited number of woods: Birch, Maple, and Oak. By creating
a code or translation table, each ProductFinish field value can be
replaced by a code, a cross-reference to the lookup table, similar to
a foreign key. This will decrease the amount of space for the
ProductFinish field and hence for the PRODUCT file. There will be
additional space for the PRODUCT FINISH lookup table, and when
the ProductFinish field value is needed, an EXTRA ACCESS (called a
JOIN) to this lookup table will be required.
CODING TECHNIQUES

15. 15

16.  Controlling Data Integrity
16

17. 17
 For many DBMS, data integrity controls (controls on the possible value a
field can assume) can be built into the physical structure of the fields and
controls enforced by the DBMS on those fields.
 The data type enforces one form of data integrity control because it
may limit the type of data (numeric or character) and the length of a field
value.
 Some other typical integrity controls that a DBMS may support are the
following:
1. Default Value:
A default value is the value a field will assume unless a user
enters an explicit value for an instance of that field. Assigning a default
value to a field can reduce data entry time because entry of a value can
be skipped and it can also help to reduce data entry errors for the most
common value. It can be achieved by implementing an Auto-Increment
check on field having data type Integer.
Controlling Data Integrity

18. 18
2. Range Control:
A range control limits the set of allowable
values a field may assume. Range controls must be used with
caution because the limits of the range may change over time. A
combination of range controls and coding led to the Year 2000
problem faced by many Organizations, in which a field for year is
represented by only the numbers 00 to 99.
Continued..

19. 19
3. Null Value Control:
A null value was also defined in previous
lectures as an empty value. Each Primary Key must have an Integrity
control that prohibits a null value. Any other required field may also
have a Null Value control placed on it if that is the policy of the
organization. For example, a university may prohibit adding a
course to its database unless that course has a Title as well as a
value of the Primary Key field CourseID.
Continued..

20. 20
4. Referential Integrity:
The term “Referential Integrity" was also
defined in previous lectures. Referential Integrity on a field is a
form of range control in which the value of that field must exist as
the value in some field in another Row of the same or (most
commonly) different table.
Continued..

21.  Denormalizing and Partitioning Data
21

22. 22

23. 23

24. 24

25. 25

26. 26

27. 27

28. 28

29. 29

30. 30

31. 31

32. 32

33. 33

34. 34

35. 35

36. 36

37. 37

38. 38

39. 39

40.  Designing Physical Database Files
40

41. 41

42.  File Organizations
42

43. 43

44. 44

45. 45

46. 46

47. 47

48. 48

49. 49

50. 50

51. 51

52. 52

53. 53

54. 54

55.  Clustering Files
55

56. 56

57. 57

58. 58

59. 59

60.  Indexes
60

61. 61

62. 62

63. 63

64. 64

65. 65

66.  Optimizing Queries
66

67. 67

68. 68

69. 69

70. 70

71. 71

72. 72

73. 73

74. 74

75. 75

76. Recommended Readings
Chapter 6 from: -
 Modern Database Management by Jeffrey A. Hoffer, Marry B.
Presscott & Fred R. McFadden; 8th Edition (Page No. 273-319)
Chapter 5 from: -
 Modern Database Management by Jeffrey A. Hoffer, V. Ramesh
& H. Toppi; 10th Edition (Page No. 247-280)
76

77. Summary of Lecture
77
Lecture 7➦
 Introduction of Physical Database Design Process
 Designing Filed
 Choosing Data Types
 Controlling Data Integrity
 Denormalizing and Partitioning Data
 Designing Physical Database Files
 File Organizations
 Clustering Files
 Indexes
 Optimizing Queries

78.  END OF LECTURE 7
78