1. Physical Database Design
MGIS 641
Koç University

2. Learning objectives
Define the terms: Physical database design, and its major objectives.
Describe major components of physical DB design.
Describe the purpose of data volume and usage analysis.
Describe basic purposes of indexes.
Query Optimization
Storage Technology RAID
Describe basic data distribution strategies.

3. Introduction
Physical database design is the last stage of DB design process.
Major objective is to implement the the DB as a set of stored records, files, indexes etc that will provide adequate performance and ensure DB integrity, security and recoverability.

4. DB development process
Planning
Enterprise data model
Analysis
Conceptual data model
Logical DB design
Logical data model
Physical DB design
Technology model
Implementation
DB & repositories

5. Physical Design Process
Normalized relations
Volume estimates
Attribute definitions
Response time expectations
Data security needs
Backup/recovery needs
Integrity expectations
DBMS technology used
Inputs
Attribute data types
Physical record descriptions
File organizations
Indexes
Query optimization
Leads to
Decisions

6. Figure 6.1 - Composite usage map
(Pine Valley Furniture Company)

7. Figure 6.1 - Composite usage map
(Pine Valley Furniture Company)
Data volumes

8. Figure 6.1 - Composite usage map
(Pine Valley Furniture Company)
Access Frequencies (per hour)

9. Figure 6.1 - Composite usage map (Pine Valley Furniture Company)
Usage analysis:
200 purchased parts accessed per hour 
80 quotations accessed from these purchased part accesses 
70 suppliers accessed from these 80 quotation accesses

10. Figure 6.1 - Composite usage map (Pine Valley Furniture Company)
Usage analysis:
75 suppliers accessed per hour 
40 quotations accessed from these 75 supplier accesses 
40 purchased parts accessed from these 40 quotation accesses

11. Volume Analysis TREATMENT PHYSICIAN PATIENT 4000 50 1000 (20) (4) (10)
CHARGE
PATIENT
PHYSICIAN
ITEM
TREATMENT
1000 50
500
4000
10,000
(4)
(20)
(10)
Estimated No. of Entity instances
After an Avg. period of 30 days patient records are archived.
There are 100 beds
on Avg.
A patient stays for 3 days.
4 treatments during stay.
10 charges.
No. of charges outstanding for an item is 20.
A physician treats 20 patients in 30 days.

12. Data Usage Analysis Identify major transactions required
Analyse transactions to determine access paths and usage frequency
TRANSACTION ANALYSIS FORM
Transaction No : xxx-555 Date :3/5/2005
Transaction Name : Create Patient Bill Transaction Volume : Avg : 2/Hr Max : 10/Hr
PATIENT 1
Transaction Map :
Diagram showing the
sequence of logical DB
accesses.
1000 2 3
ITEM
CHARGE
500
10,000
No Name Type of No of References
Access Per Trans. Per Period
1 Entry-PATIENT R 1 10
2 PATIENT-CHARGE R
3 CHARGE-ITEM R

13. Composite Usage Map (75) (25) (100) (30) (60) (25) TREATMENT PATIENT
PHYSICIAN
4000
1000 50
(25)
(50)
(125)
(50)
(250)
ITEM
CHARGE
Composite Usage Map :
Concise reference to the
estimated volume and
usage of data in the DB
500
10,000
Composite Usage Map including other types of transactions

14. Designing Fields Field: smallest unit of data in database Field design
Choosing data type
Coding, compression, encryption
Controlling data integrity

15. Choosing Data Types CHAR – fixed-length character
VARCHAR2 – variable-length character (memo)
LONG – large number
NUMBER – positive/negative number
DATE – actual date
BLOB – binary large object (good for graphics, sound clips, etc.)

16. Example code-look-up table (Pine Valley Furniture Company)
Figure 6.2
Example code-look-up table (Pine Valley Furniture Company)
Code saves space, but costs an additional lookup to obtain actual value.

17. Field Data Integrity
Default value - assumed value if no explicit value
Range control – allowable value limitations (constraints or validation rules)
Null value control – allowing or prohibiting empty fields
Referential integrity –for foreign-key to primary-key match-ups

18. Handling Missing Data
Substitute an estimate of the missing value (e.g. using a formula)
Construct a report listing missing values
In programs, ignore missing data unless the value is significant
Triggers can be used to perform these operations

19. File Organisation
File organisation : A technique for physically arranging the records of a file on secondary storage
Important factors to consider:
Fast data retrieval
High throuhput for processing data input and maintenance transactions
Efficient usage of storage space
Protection from failures or data loss
Minimizing the need for reorganization
Accomodating growth
Security from unauthorized access

20. Indexes
Index : A table or other data structure that is used to determine the locations of rows in a table
that satisfy a condition.
PRODUCT
PRODUCT NO RECORD NO
50 3
Index tables are small and can be kept in
the main memory.

21. When to use Indexes Larger tables Primary key, foreign key
Specify index for nonkey attributes that are referred to in qualification, sorting, and grouping commands (e.g. WHERE, ORDER BY, GROUP BY)
Check DBMS for the limit

22. Query Optimization Wise use of indexes Compatible data types
Simple queries
Avoid query nesting
Temporary tables for query groups
Select only needed columns
No sort without index

23. File Access-Storage Technology RAID
RAID An array of physical disk drives to the database user as if they form one logical storage unit.

24. RAID-0

25. RAID-1

26. RAID-5

27. Definitions
Distributed Database: A single logical database that is spread physically across computers in multiple locations that are connected by a data communications link
Decentralized Database: A collection of independent databases on non-networked computers
They are NOT the same thing!

28. Reasons for Distributed Database
Business unit autonomy and distribution
Data sharing
Data communication costs
Data communication reliability and costs
Multiple application vendors
Database recovery
Transaction and analytic processing

29. Data Distribution Strategy
Basic data distribution strategies :
Centralised : All data are centralised at a single site.
Access problems for for remote users, data comms. cost, DB fails when central system fails.
Replicated : A full copy of DB is assigned to more than one site.
Maximise local access, update problems.
Partitioned : DB is partitioned into is divided into non-overlapping partitions and assigned to a particular site.
Data closer to local users
Hybrid: DB is fragmented into critical and non-critical fragments, non-critical fragments stored at only one site others at multiple sites etc.

30. Partitioning
Horizontal Partitioning: Distributing the rows of a table into several separate files
Useful for situations where different users need access to different rows
Vertical Partitioning: Distributing the columns of a table into several separate files
Useful for situations where different users need access to different columns
The primary key must be repeated in each file
Combinations of Horizontal and Vertical
Partitions often correspond with User Schemas (user views)

31. Partitioning Advantages of Partitioning:
Records used together are grouped together
Each partition can be optimized for performance
Security, recovery
Partitions stored on different disks: contention
Take advantage of parallel processing capability
Disadvantages of Partitioning:
Slow retrievals across partitions
Complexity

32. Data Replication
Purposely storing the same data in multiple locations of the database
Improves performance by allowing multiple users to access the same data at the same time with minimum contention
Sacrifices data integrity due to data duplication