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Database Management Systems

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Database Management System (CS403)
VU
Lecture No. 22
Overview of Lecture
Data Volume and Usage Analysis
o
Designing Fields
o
Choosing Data Type
o
Coding Techniques
o
Coding Example
o
Controlling Data Integrity
o
The Physical Database Design Considerations and Implementation
The physical design of the database is one of the most important phases in the
computerization of any organization. There are a number of important steps involved
in the physical design of the database. Steps are carried out in sequence and need to
be performed precisely so that the result of the first step is properly used as input to
the next step.
Before moving onto the Physical database design the design of the database should
have undergone the following steps,
Normalization of relations
Volume estimate
Definition of each attribute
Description of where and when data is used (with frequencies)
Expectation or requirements of response time and data security.
Description of the technologies.
For the physical database design we need to check the usage of the data in term of its
size and the frequency. This critical decision is to be made to ensure that proper
structures are used and the database is optimized for maximum performance and
efficiency.
The following steps are necessary once we have the prerequisite complete:
Select the appropriate attribute and a corresponding data type for the attribute.
The process of selecting the attribute to be placed in a specific relation in the physical
design. Need considerable care as it is one of the most important and basic aspects for
the creation of the database.
Grouping of attributes in the logical order so that the relation is created in such a way
that no information is missing from the relation and also no redundant or unnecessary
information is placed in the relation.
Looking at the logical design at the time of transformation into physical design there
may be stages when the information combined logically in the logical design looks
odd when transforming the design into a physical one.
Arrangement of Similar records into the secondary memory (hard disk)
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Database Management System (CS403)
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The scheme of storage on hard disk is important as it leads to the efficiency and
management of the data on disk. Different types of data access mechanism are
available and are useful for rapid access, storage, and modification of data.
Different types of database structures can be used for placement of data on disks,
management of data in the forms of indexes and different database architecture is vital
and leads to better retrieval and recovery of records.
Preparing queries and handling strategies for the proper usage of the database, so that
any type of input or output operation performed on the database is executed in an
optimized and efficient way.
DESIGNING FIELDS
Field is the smallest unit of application data recognized by system software, such as a
programming language or any database management system.
Designing fields in the databases' physical design as discussed earlier is a major issue
and needs to be dealt with great care and accuracy. Data types are the structure
defined for placing data in the attributes. Each data type is appropriate for use with
certain type of data.
4 major objectives for using data types when specifying attributes in a database are
given as under:
Minimized usage of storage space
Represent all possible values
Improve data integrity
Support all data manipulation
The correct data type selection and decision for proper domain of the attribute is very
necessary as it provides a number of benefits.
Most common data types used in the available DBMS of the day have the following
set of common attributes.
Max
Size:
Data type
Description
PL/SQL
Variable length character string having maximum
32767
bytes
VARCHAR2(size)
length
bytes.
size
minimum is 1
You must specify size
Now deprecated - VARCHAR is a synonym for
VARCHAR
VARCHAR2 but this usage may change in future
versions.
32767
bytes
Fixed length character data of length size bytes.
Default
and
CHAR(size)
This should be used for fixed length data. Such as
minimum size is 1
codes A100, B102...
byte.
Magnitude
1E-130
..
10E125
maximum precision of 126 binary digits, which is roughly equivalent to
38
decimal
digits
NUMBER(p,s)
The
scale
s
can
range
from
-84
to
127.
For
floating
point
don't
specify
p,s
REAL has a maximum precision of 63 binary digits, which is roughly
equivalent to 18 decimal digits
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Database Management System (CS403)
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32760
bytes
Note this is smaller
Character data of variable length (A bigger
LONG
than  the  maximum
version the VARCHAR2 data type)
width  of  a  LONG
column
from January 1, 4712
BC to December 31,
DATE
Valid date range
AD.
9999
(in Oracle7 = 4712
AD)
Raw  binary  data  of  length  size  bytes.
RAW(size)
32767 bytes
You must specify size for a RAW value.
32760
bytes
Note this is smaller
Raw binary data of variable length. (not
LONG RAW
than  the  maximum
interpreted by PL/SQL)
width  of  a  LONG
RAW column
BLOB
Binary Large Object
4Gigabytes
CODING AND COMPRESSION TECHNIQUES:
There a re some attributes which have some sparse set of values, these values when
they are represented in any data type are hard to express, for this purpose some codes
are used. As the codes defined by the database administrator or the programmer
consume less space so they are better for use in situations where we have large
number of records and wastage of small amount of space in each record can lead to
loss of huge amount of data storage space. Thus causing lowered database efficiency.
STID
STNAME
HOBBY
S1020
Sohail Dar
Reading
S1038
Shoaib Ali
Gardening
S1015
Tahira Ejaz
Reading
S1015
Tahira Ejaz
Movie
S1018
Arif Zia
Reading
Coding techniques are also useful for compression of data values appearing the data,
by replacing those data values with the smaller sized codes we can further reduce the
space needed by the data for storage in the database.
Following tables give the use of codes and their utilization in the database
environment
Coding Example:
Student
STID
STNAME
HOBBY
S1020
Sohail Dar
R
S1038
Shoaib Ali
G
S1015
Tahira Ejaz
R
S1015
Tahira Ejaz
M
S1018
Arif Zia
R
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Database Management System (CS403)
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Hobby Table
CODE
HOBBY
R
Reading
G
Gardening
M
Movies
In the above example we have seen the implementation of the codes as replacement to
the data in the actual table, here we actually allocated codes to different hobbies and
then replace the codes instead of writing the codes in the table.
We get a number of benefits by the use of data types and the benefit can be in a
number of dimensions.
Default value
Default values are the values which are associated with a specific attribute and
can help us to reduce the chances of inserting incorrect values in the attribute
space. And also it can help us preventing the attribute value be left empty.
Range Control
Range control implemented over the data can be very easily achieved by using
any data type. As the data type enforces the entry of data in the field according
to the limitations of the data type.
Null Value Control
As we already know that a null value is an empty value and is distinct from
zero and spaces, Databases can implement the null value control by using the
different data types or their build in mechanisms.
Referential Integrity
Referential Integrity means to keep the input values for a specific attribute in
specific limits in comparison to any other attribute of the same or any other
relation.
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Table of Contents:
  1. Introduction to Databases and Traditional File Processing Systems
  2. Advantages, Cost, Importance, Levels, Users of Database Systems
  3. Database Architecture: Level, Schema, Model, Conceptual or Logical View:
  4. Internal or Physical View of Schema, Data Independence, Funct ions of DBMS
  5. Database Development Process, Tools, Data Flow Diagrams, Types of DFD
  6. Data Flow Diagram, Data Dictionary, Database Design, Data Model
  7. Entity-Relationship Data Model, Classification of entity types, Attributes
  8. Attributes, The Keys
  9. Relationships:Types of Relationships in databases
  10. Dependencies, Enhancements in E-R Data Model. Super-type and Subtypes
  11. Inheritance Is, Super types and Subtypes, Constraints, Completeness Constraint, Disjointness Constraint, Subtype Discriminator
  12. Steps in the Study of system
  13. Conceptual, Logical Database Design, Relationships and Cardinalities in between Entities
  14. Relational Data Model, Mathematical Relations, Database Relations
  15. Database and Math Relations, Degree of a Relation
  16. Mapping Relationships, Binary, Unary Relationship, Data Manipulation Languages, Relational Algebra
  17. The Project Operator
  18. Types of Joins: Theta Join, Equi–Join, Natural Join, Outer Join, Semi Join
  19. Functional Dependency, Inference Rules, Normal Forms
  20. Second, Third Normal Form, Boyce - Codd Normal Form, Higher Normal Forms
  21. Normalization Summary, Example, Physical Database Design
  22. Physical Database Design: DESIGNING FIELDS, CODING AND COMPRESSION TECHNIQUES
  23. Physical Record and De-normalization, Partitioning
  24. Vertical Partitioning, Replication, MS SQL Server
  25. Rules of SQL Format, Data Types in SQL Server
  26. Categories of SQL Commands,
  27. Alter Table Statement
  28. Select Statement, Attribute Allias
  29. Data Manipulation Language
  30. ORDER BY Clause, Functions in SQL, GROUP BY Clause, HAVING Clause, Cartesian Product
  31. Inner Join, Outer Join, Semi Join, Self Join, Subquery,
  32. Application Programs, User Interface, Forms, Tips for User Friendly Interface
  33. Designing Input Form, Arranging Form, Adding Command Buttons
  34. Data Storage Concepts, Physical Storage Media, Memory Hierarchy
  35. File Organizations: Hashing Algorithm, Collision Handling
  36. Hashing, Hash Functions, Hashed Access Characteristics, Mapping functions, Open addressing
  37. Index Classification
  38. Ordered, Dense, Sparse, Multi-Level Indices, Clustered, Non-clustered Indexes
  39. Views, Data Independence, Security, Vertical and Horizontal Subset of a Table
  40. Materialized View, Simple Views, Complex View, Dynamic Views
  41. Updating Multiple Tables, Transaction Management
  42. Transactions and Schedules, Concurrent Execution, Serializability, Lock-Based Concurrency Control, Deadlocks
  43. Incremental Log with Deferred, Immediate Updates, Concurrency Control
  44. Serial Execution, Serializability, Locking, Inconsistent Analysis
  45. Locking Idea, DeadLock Handling, Deadlock Resolution, Timestamping rules