Dbms Useful PPT

Data:
Data is a raw fact or unorganized form (such as
alphabets, numbers, or symbols) that refers to or
represent, condition, ideas or objects data is
limitless and present everywhere in the universe.

Information :
Data that
has been verified to be accurate and timely.
 Is specific and organized for a purpose.
Is represented within a context that gives it
meaning and relevance.
That can lead to an increase in
understanding and decrease in uncertainty
is called information.

Database :
A database is a collection of information that is
organized so that it can easily be accessed
managed and update. There are two type of
database:
 Conventional Database: Collection of data without
use of computer. E.g. Telephone diary, register.
 Computerized database: The collection of data
with the help of computer in the form of data file is
known as computerized database. The types of
computer systems that can run database
management system are Centralized PC and
Client/Server and distributed.

Elements of Database:
1. Field: Smallest unit of Database.
2. Record: A Collection of multiple related
fields.
3. Table: A collection of records or group of
records with the row and column order.
4. Tuple: A record row in the database.
5. Index: It is a process of organizing data in
specific order.
6. Cell: A cell is a inter section of rows and
columns.

Data base system :
The data base data collection with DBMS is called data
base system. A database system is a way of organizing
information on a computer, implemented by a set of
computer programs. This kind of organization should
offer:
o simplicity - an easy way to collect, access-connect, and
display information;
o stability - to prevent unnecessary loss of data;
o security - to protect against unauthorized access to private
data;
o speed - for fast results in a short time, and for easy
maintenance in case of changes in the organization that
stores the information.

DBMS (Database management system):
DBMS is a software that defines a database,
stores the data, support a query language,
produced reports and create data entry
screen.
Some useful Database Management System
softwares are Ms-Access, SQL/SQL PLUS,
dbase, FoxPro, Sybase, Oracle, IMS, IDS, IDMS,
AdaBASE, CDS/ISIS, OMNIS, RBASE, FOXBASE.

In this figure illustrate that the DBMS stands
between the database and the users.

Data wared house:
A data structure that is optimized for
distribution. It collects and stores integrated sets
of historical data from multiple operational
systems and feeds them to one or more data
marts. It may also provide end-user access to
support enterprise views of data.
Data Mart: A data structure that is optimized for
access. It is designed to facilitate end-user
analysis of data. It typically supports a single,
analytic application used by a distinct set of
workers.

Data mining :
Data mining or knowledge discovery is the
computer assisted process of digging through and
analyzing enormous sets of data and then extracting
the meaning of the data. Data mining tools predict
behaviors and future, allowing business to make
proactive knowledge driven decisions .

DBMS Evolution/history of DBMS :
i) 1960’s(Traditional File System) :
In 1960’s the traditional file system in invented. The
traditional file based system is basically file based
system in which we manually or through computer
handle the database.
ii) Early 1970’s(Tree Structure Model) :
The emergence of the first types of DBMS, the
hierarchical DBMS. IBM had the first model
developed on IBM 360, and their DBMS was called
IMS, originally it was written for the Apollo program.
This types of DBMS was based in binary trees, where
the shape was like a tree and relations were only
limited between parent and child record.

Advantage :
- Less redundant data
- Data independence
- Security & integrity
- Efficient searching
Disadvantages :
- Complex implementation
- Harder to handle many relationship

iii)Late 1970’s (Network Data Model):
The emergence of the network DBMS, charles
Bachman developed first DBMS at Honeywell
database named Integrated data store (IDS).
Then a group called COD ASYL who is responsible
for the creation of COBOL and that system
standardized network DBMS where we developed
for business use. In this model, each record can
have multiple parents .
 Disadvantage :-
- Complex to understand
- Difficult to design & maintenance

iv) 1980’s(Relational Data Model):
The emergence of relational DBMS on the hands
of Edgar codd . He worked at IBM, and he was
invented relation data model this was a new
system for entering data and working with big
database where the idea was use a table of
records.
v) 1990’s & onwards(Object Oriented Model) :
In 1990 the DBMS took on a new objects oriented
approach, joint with relational DBMS In This
approach, text multimedia internet and web use
in conjunction with DBMS were available and
possible.

Advantages of DBMS :
 Controlling data redundancy
 Elimination of inconsistency
 Betters service to the user
 Flexibility of the system is improved
 Integrity can be improved
 Standards can be enforced .
 Security can be improved
 Provides backup and recovery

Disadvantages :
 Database system are complex, difficult,
and time consuming to design.
 Qualified personnel.
 Extensive conversion costs in moving from
a file system to a database system.
Initial training required for all programmers
and users.

APPLICATION DEVELOPMENT WITHOUT DATABASE:
Application development would be complicated
and would cause the serious problems during the
data access, without a good database system.
Programs need to store data and retrieve those
stored data later in future when required. Using
the traditional file processing system to store the
data can cause various problems, some of
problems described below:

• Data redundancy
• Program/data dependency
• Lack of flexibility
• Poor programmer productivity
• Excessive program maintenance

• Data independence :
Data independence is usually consisting
from the two points of view.
(i) Physical Data independence
(ii) Logical data independence
Physical data independence allows changes
in the physical storage devices or
organization of the file to be mode without
requiring changes in the concept view or
any of the external view and hence in the
application program using database.

Logical data independence
The ability to change the logical (conceptual)
schema without changing the External schema
(User View) is called logical data
independence. For example, the addition or
removal of new entities, attributes, or
relationships to the conceptual schema should
be possible without having to change existing
external schemas or having to rewrite existing
application programs.

• Data Abstraction in DBMS :
The purpose of database users with an abstracts
view of the data that is system hides certain
details of how the data are stored and
maintained. It gives and architecture is to
separate the user application and physical
database.
• Centralized Database:
Centralized database has all its data on one place.
As it is totally different from distributed database
which has data on different place. In centralized
database all the data reside on one place. so
problem of bottleneck can occur and data
availability is not efficient as in distributed data
base.

• Distributed Database :
Distributed database is define as the
collection of logically distributed database. Which
are connect with each other through network. A
distributed DBMS is used for managing distributed
database. Each side has its own database and
operating system.
• Database administrator (DBA)
DBA is a person responsible for the installation,
configuration, upgrade , monitoring and
maintenances of physical database. The role
includes the developing and design of database
strategies, monitoring database performances
capacity and planning for future expansible
requirement. They may also plan, coordinate
and implement security measure to safeguard of
the database.

Unit2: Database Design(for bcis)
Definition:
Database design is the process of producing a detailed
data model of a database. This logical data model
contains all the needed logical and physical design
choices and physical storage parameters needed to
generate a design in a Data Definition Language, which
can then be used to create a database. A fully
attributed data model contains detailed attributes for
each entity.
The term database design can be used to describe
many different parts of the design of an overall
database system.

Basic step of Database designing

Feasibility Study
A feasibility study is an evaluation and analysis of
the potential of the proposed project which is
based on extensive investigation and research to
support the process of decision making.
The goal of a feasibility study is to determine
whether a proposed project is worth pursuing.
– Operational Feasibility: Operational feasibility is a
measure of how well a proposed system solves the
problems, and takes advantage of the opportunities
identified during scope definition and how it satisfies
the requirements identified in the requirements
analysis phase of system development.

– Economic Feasibility: The purpose of the economic
feasibility assessment is to determine the positive
economic benefits to the organization that the
proposed system will provide.
– Technical Feasibility: The technical feasibility
assessment is focused on gaining an understanding of
the present technical resources of the organization
and their applicability to the expected needs of the
proposed system.

Associations and relationships

Unit-2
Data Dictionary:
Data dictionary or metadata repository is a
centralized repository of information about
data such as meaning relationship to other
data origin, usage and format.
Most database management system keeps the
data dictionary hidden from users to prevent
them from accidentally destroying its
contents.

Data model :
Data model is a collection of conceptual tools
used for describing data, data relationships and
data constraints. The model should enable the
designer to incorporate a major portion of
semantics of the database in the system.

Types of data model :
i) Object based data model :
Object based data model are used in
describing data and data relationship in
accordance with concept. In general, the
object based data models are gaining wide
acceptance for their flexible structuring
capabilities. The Entity relationship model
which is an object based model is widely used
in practices as an appropriate database design
tool.

ii) Record based data model :
these data models are used to specify the overall
logical structure of database. The three widely
accepted record based data models are relational
model ,network model and hierarchical model.
iii) Physical data model :
These models are used to have high level
description of the storage structure of the
database and their access mechanism with the
physical models. It is possible to implement to
database of the system level.

vi. A conceptual data model identifies the
highest-level relationships between the
different entities. Features of conceptual data
model include:
– Includes the important entities and the
relationships among them.
– No attribute is specified.
– No primary key is specified.

A logical data model describes the data in as
much detail as possible, without regard to how
they will be physical implemented in the
database. Features of a logical data model
include:
– Includes all entities and relationships among them.
– All attributes for each entity are specified.
– The primary key for each entity is specified.
– Foreign keys (keys identifying the relationship
between different entities) are specified.
– Normalization occurs at this level.

Physical data model represents how the model will
be built in the database. A physical database model
shows all table structures, including column name,
column data type, column constraints, primary key,
foreign key, and relationships between tables.
Features of a physical data model include:
– Specification all tables and columns.
– Foreign keys are used to identify relationships between
tables.
– Denormalization may occur based on user requirements.
– Physical considerations may cause the physical data
model to be quite different from the logical data model.
– Physical data model will be different for different RDBMS.
For example, data type for a column may be different
between MySQL and SQL Server.

Entity relationship model :
The Entity Relationship model is based on the
perception of the real world as a collection of
basic objects called entities and relationships
among these objects entity.
An entity is an object that exist and is
distinguished from other objects. The distinction is
accomplished by associating with each entity. A
set of attribute which describes the object. For
example the attributes p_no and p_name describe
projects undertaken.

• Relationship :
A relationship is an associating among several
entities. For example working in relationship
associate a project with each employee that
she/he is working in .
• E-R Diagram :
The overall logical structure of a database can be
expressed graphically by E-R diagram which
consist of following components :
- Rectangles, which represent entity sets.
- Ellipses, which represent attributes.
- Diamonds which represent relationships among
entity sets.

- Lines, which links attributes to entity sets and
entity set to relationship
Example :
E- No E- Name P-No P- Name
Employees works in project
Address
Figure : E-R diagram for a part of the database of a
project management system entity set:
• An entity set is represented by a set of attributes.
Possible attributes of the employee entity set are
emp- No emp- Name and address.

• Relationship sets.
A relationship set is a set of relationship of
the same type finally it is a mathematical
relation on n  2 entity sets.
# Mapping constraints :-
One important constraint is mapping
cardinalities which express the no. of
entities of an entity set to which entities of
another entity set can be associated with a
relationship. There are four types of
mapping cardinality.

i) One to One :
An entity in A is associated with at must one
entity in B and an entity B is also associated with
at most one entity in A.
a1 b1
a2 b2
a3 b3
a4
A B
Fig: One to one relationship
ii) One to many :
An entity in A is associated with any number
entities in B. An entity in B, however can be
associated with at most one entity.

a1 b1
a2 b2
a3 b3
b4
b5
A B
Fig: One to many relationships
iii) Many to one :-
An entity in A is associated with at most
one entity in B. An entity in B, however can
be associated with any no. of entities in A.

a1 b1
a2 b2
a3 b3
a4
a5
A B
Fig : many to one relationship
iv) Many to many :
An entity in A is associated with any number of
entities in B and an entity in B is also associated
with any number of entities in A.

Other Associations:Aggregation
Some special types of associations arise often
enough that UML has defined special
techniques for handling them. One category is
known as an aggregation or a collection. For
example, a Sale consists of a collection of
Items being purchased. As shown in Figure ,
aggregation is indicated by a small diamond
on the association line next to the class that is
the aggregate.

Composition
composition is a stronger aggregate association
that does arise more often. In a composition, the
individual items become the new object.
Consider a bicycle, which is built from a set of
components (wheels, crank, stem, and so on).
UML provides two methods to display
composition. In Figure 2.12 the individual classes
are separated and marked with a filled diamond.

Generalization
Another common association that arises in
business settings is generalization. This
situation generates a class hierarchy. The most
general description is given at the top, and
more specific classes are derived from it.
Figure 2.14 presents a sample from Sally’s Pet
Store.

Reflexive Association
A reflexive relationship is another situation
that arises in business that requires special
handling. A reflexive association is a
relationship from one class back to itself. The
most common business situation is shown in
Figure 2.17. most employees (worker) have a
manager.

# Keys :-
The key is define as the column or attributes of
the database table. For example if a table has
id, name & address as the column names then
each one is known as the key for that table.
i) Super key :-
Super key for an entity set is a set of one or
more attribute whose combined value
uniquely identifies the entities in the entity set.
For example, for an entity set employees the
set of attributes (emp_code, emp_name,
address) can be considered to be a super key.

ii) Candidate key :
A candidate key is minimal super key that super key
which doesn’t have any proper subset which is also
super key for example (emp_no) and (emp_name,
address) are two candidate keys for the entity set
employee.
iii) Primary key :-
Primary key is usually the key selected to identify a row
when database is physically implemented, for example
(emp_no) can be considered to be the primary key for the
entity set employees.

iv) Foreign key :
Foreign key is an attribute that appears as
a non key attribute in one relation and as
primary key attributes in another relation.

Schema Diagram
• A schema diagram is described in a formal
language supported by the database
management system (DBMS). In a relational
database, the schema defines the tables, the
fields in each table, and the relationships
between fields and tables.
• Schemas are generally stored in a data dictionary.
Although a schema is defined in text database
language, the term is often used to refer to a
graphical depiction of the database structure

Levels of schema Diagram
 Conceptual schema, a map of concepts and
their relationships
 Logical schema, a map of entities and their
attributes and relations
 Physical schema, a particular implementation
of a logical schema

Unit3
Relational Database :-
A relational database consists of a collection of
tables i.e, in this model entity sets and
relationships all are represented by tables. A row
in a table represents a relationship among a set of
values. Each row of a relation (table) is called a
tuple. Fig shows the Structure of relational
Database .
Table Name : student
S.N. Name Address
224 Ram joshi Butwal-13
220 Hari psd Sukhanager-10
200 Gita kharel Milanchowk-10
Values
attributes

# Important of relational database :-
 Relational database are based on relational set
theory. It supports relational algebra like :- (union,
intersection, difference and cartessian product )
and also support select project, join, division,
operations etc.
 Relational database supports concept of
dynamic views.
 Relational database use SQL (structured query
language)
 Relational database have an excellent security.
 Rational database support to new hardware
technologies.

# Relational Algebra:-
The basic set of operation for the relational model
is the relational algebra. These operations enable
a user to specify basic retrieval request sets of
operations include:-
 Select
 Project
 Union
 Set difference
 Cartesian product
 Rename
 Intersection
 Join
 Division

i) Selection operation :-
To identify a set of tuples which is a part of a
relation and to extract only these tuples out. The
select operation selects tuples that satisfy a given
predicate or condition.
 It is a unary operation defined on a single
relation.
 It is denoted as sigma ().
 It supports arithmetic comparison operator and
logical operator.
Note: Arithmetic comparison operator :
 (<,>,<=,>=,==,!=)
Logical operator : (NOT, OR, AND)

Example :
Table :Book
Acc.No YR_PUB TITLE
734216 1982 Algorithm Design
23767 1995 Database Design
89476 1992 Compiler Design
54678 1991 Programming Design
376112 1992 Machine Design
Select from relation “Book” all books whose year
of publication is 1992.
Solution: Relational Algebra:
YR_PUB=1992 (Book)
SQL : Select* from Book where YR_PUB=1992

ii) Projection operation:
Returns its argument relation with certain
attributes left out.
q It is an unary operation defined on a
single relation.
q It is a denoted as  (Pie)
Example;
List all the Title and Acc-No of the “book”
relation.
Relation algebra=  Acc_No, Title (Book)
SQL=Select Acc_No, TITLE from Book

Relational Expression :
Example :
Find the title whose publication year in 1992 from
book.
• Relational Algebra:
 TITLE (YR_PUB=1992 (Book))
Table : Employee :
E_ID E_Name E_Address Phone
2467 Ram psd. Butwal 98472…
2576 Hari Bdr. Bhairahawa 98472…
2666 Meena singh Pokhara 98472…
2789 Rita Raj Kathmandu 98472…
2899 Ram psd Butwal 98472…

Create Table :
create table Employee (Eid int, E_name
varchar(50),E_address varchar (100), Phone
varchar(12));
q Find the all employee name whose address is
butwal
SQL= Select E_name from employee
Where E_address =”Butwal”
qFind out all in formation from relation employee
SQL=Select *from employee
q Find out name, & phone number whose
employee ID is 2467 and 2899 from relational
employee
SQL=Select E_Name , Phone from Employee
Where Eid= 2467 And Eid=2899

Set Operations:
Union :
Union is used when we need attributes that appear in
either or both of two relations. It is denoted as U.
Ex. R S
a b c b c a
d c a c d f
b f e b f e
Output:-
R U S= a b c
d c a
b f e
b c a
c d f

For example :
Borrower(customer_name,loan_no)
Depositor (customer_name ,Account_number)
List all the customers who have either an account
or loan number or both
relational Algebra= customer_name (borrower)
union customer_name (depositor)
SQL= Select customer_name from Borrower union
Select customer name from depositor

Different Operation (MINUS)/ Except:
Finds tuples in one relation but not in other. It is
denoted as “–”. Example : (output)
R-S= a b c
d c a
Example :
Find the names of all customers who have an
account but not a loan numbers
Relational Algebra:
 customer_name (Depositor )-  customer_ name
(Borrower)
SQL= Select customer_name from Depositor MINUS
select customer_name from borrower

Cartesian product (cross join operation): -
It allows combining information from two
relations.
- It is denoted as R×S where R and S Are
relations.

Example;
R×S= a b c b c a
a b c c d f
a b c b f e
d c a b c a
d c a c d f
d c a b f e
b f e b c a
b f e c d f
b f e b f e

• Example : List all information of relation employer and
department.
Employee (Ename, Department_ID)
Department (Department_ID, Department_ name)
Relational Algebra = (employee)×(department)
SQL=Select* From employee, department
Or
Select* From employee CROSS JOIN Department

Intersection operation :
Find tuples in both the relation. It is denoted as  .
Output
R S= b f e
Example :
Borrow (customername, loan_number)
Depositor (customername, accountnumber)
qList all the customer’s who have both a loan & an account.
Relational Algebra=
 customername(Borrower)  customername (depositor)
SQL=
select customername from Borrower intersect
select customername from Depositor

RENAME operation :
RENAME operation is used rename attributes. It is
denoted as ρ(row)
Example : Employee (name, eid)
Change attributes name to employee name
Relational Algebra= ρ employee_name/name (employee)
SQL=ALTER TABLE employee RENAME column name to
employee_name;
Also, we can rename table name
SQL= RENAME Employee To student;

Join Operation :
The Join operation is defined by the symbol and
is used to compound similar tuples from two
relation into single longer tuples. Every row of the
first table is joined to every row of second table.
The result is tuples taken from both tables.
Syntax:
A <Join condition>B
Types of join
q inner join (equi-join)
An inner join creates a new results table by
combining column value of two tables A and B
based upon the join predicate.

The query compares each row of A with each
row of B to find all pairs of rows which satisfy
the join predicate.
Relational Algebra= R <R. primary-key=s.foreign-key>
s
For Example :
Students Courses
Student# Name Course Course# Name
100 Ram PH PH Pharmacy
200 Shyam CM CM Computing
300 Hari CM

Relation algebra for inner point join or equi-join
students course =course# courses
SQL=
Select* from students INNER JOIN
courses on students.course= courses.course;

qNatural join :-
A natural join offers a further specialization of equi-joins.
The join predicates arise implicitly by comparing
all columns in both tables that have the same column-name
in the join tables. The resulting tables one
column for each pair of equally named columns.
Relation algebra=
Students <course=course#>courses
SQL=Select*from students natural join courses

Theta Join :
A Cartesian product with a condition applied R<condition>S is
called theta join.
SQL= Select* from student, courses where student#=200;

Outer Join
An outer join doesn’t require each
record in the two joined tables to have
a matching record. The joined tables
retains each-record-even if no other
matching records exists.
There are three types of outer join:
Left outer join
Right outer join
Full outer join

i) Left Outer join :-
The result of the left outer join (left join) for table A and B
always contains all records of the “left” table A, even if
the join condition doesn’t find any matching record in
the “right” table B. It is denoted by .
Syntax;
R <r-primary key =s. foreign-key>s
Example
Student <student. Course= courses. course#> courses
SQL=select*from students left outer join courses on
student .course= courses. course#;

ii) Right outer join :
A right outer join (right join) closely
resembles a left outer join except with
treatment of the tables reversed. Every row
from the “right” table B will appear in the
joined table at list one. Matching row from the
left table A exist . Null will appear in columns
from A for those records that have no match in
A. It is denoted by .

Syntax:
R <R.primary-key=S.foreign-key>S
Relational Algebra=student course <student.
course = courses.course#> Courses
SQL=Select* from student full other join courses
on students.course=courses.course#

Division (Quotient) operation:
The division is a binary operation that is
written as R ÷ S. The result consists of the
restrictions of tuples in R to the attribute
names unique to R, i.e., in the header of R but
not in the header of S, for which it holds that
all their combinations with tuples in S are
present in R. For an example see the tables
Completed, DBProject and their division:

Example
A B C D C D
b c e f e f
a b i j g h
b c g h S
b c a d
d i g h
d i j k
d i e f
R
Here, Relational Algebra
RS=  A,B (R)-  A,B ( A,B(R)×S-R

Relation calculus :
Relation calculus consist of two calculi:
- Tuple relational calculus
- Domain relational calculus
That are apart of the relational model to
databases and provide a declarative way to
specify database queries. The relational
calculus would formulate a descriptive
declarative way.

For example :
To retrieve the phone numbers and name of book
stores that supply some sample Book.
Relational calculus= Get store name, and store
phone for supplies such that these exists a title
book with the some bookstore ID value and with a
Book title value of some simple book.
Note :
The relational algebra and relational calculus are
essentially logically equivalent.
-

• Tuple relational calculus :
Is a calculus that was introduced by Edgar F-codd
as part of relational model, in order to
provide a declarative database query
language- for this data model it formed the
inspiration for the database- query language
QUEL & SQL.

- Domain relational calculus :
• Is a calculus that was introduced by Michel
Lacroix & Alain Pirotte as a declarative database
query language for relational data model. The
operator used in DRC: (and), (or), (not),
(existential quantifier), (universal quantifier) etc.

schema :
schema of a database system is it’s structure
described in a formal language supported by
DBMS and refers to the organization of data to
create blue print of how database will be
constructed .

External
level
External view External view
Conceptual schema
Internal schema
External conceptual
mapping
Conceptual level
Conceptual internal
mapping
Internal level
Store database

-Internal level :
Internal level has an internal schema which describe
the physical storage structure of the database. The
internal schema uses a physical data model and
describes the complete details of data storage and
access path for the database.
- Conceptual level :
Conceptual level has a conceptual schema, which
describe the structure of the whole database for a
community of users. The conceptual schema hides the
details of physical storage structure and concentrates
on describing entities, data types, relationship users
operation & constraints.
- External level :-
External level includes a number of external schema
or user view. Each external schema describes a part of
the database that a particular user group is interested
in and hides that rest of the database from that user
group.

# Instance:-
Actual data in the database may change quite
frequently. For example, the database change
every time we add a student or enter the new
grade .The data in the database at a particular
moment in time is called a database State or snap
shot . It is also called the current set of
occurrences or instances in the database.
# View:- View is a single table that is described
from other tables. These other tables can be base
tables or previously defined views. A view doesn’t
necessarlly exist in physical form, it is considered a
virtual table.

Advantages of views:-
 View can represent a subset of the
data contained in a table.
 Views can join multiple
table into a single virtual table.
 View can hide the complexity of data.
 View take very little space to store.

SQL(Structure Query Language)
Definition:
SQL (Structured Query Language is a special-purpose
programming language designed for
managing data held in a relational database
management system (RDBMS).
Originally based upon relational algebra and
tuple relational calculus, SQL consists of a data
definition language and a data manipulation
language. The scope of SQL includes data insert,
query, update and delete, schema creation and
modification, and data access control.

History:
SQL was initially developed at IBM by Donald D.
Chamberlin and Raymond F. Boyce in the early 1970s.
This version, initially called SEQUEL (Structured English
Query Language), was designed to manipulate and
retrieve data stored in IBM's original quasi-relational
database management system, System R, which a
group at IBM San Jose Research Laboratory had
developed during the 1970s.The acronym SEQUEL was
later changed to SQL.
In the late 1970s, Relational Software, Inc. (now Oracle
Corporation) saw the potential of the concepts
described by Codd, Chamberlin, and Boyce and
developed their own SQL-based RDBMS with
aspirations of selling it to the U.S. Navy, Central
Intelligence Agency, and other U.S. government
agencies.

In June 1979, Relational Software, Inc.
introduced the first commercially available
implementation of SQL, Oracle V2 (Version2)
for VAX computers.
After testing SQL at customer test sites to
determine the usefulness and practicality of
the system, IBM began developing commercial
products based on their System R prototype
including System/38, SQL/DS, and DB2, which
were commercially available in 1979, 1981,
and 1983, respectively.

Query:
• In computers, what a user of a search engine
or database enters is sometimes called the
query. To query (verb) means to submit a
query (noun).
• A database query can be either a select query
or an action query. A select query is simply a
data retrieval query. An action query can ask
for additional operations on the data, such as
insertion, updating, or deletion.

Sub queries :
A sub query is a form of an SQL statement that
appears in inside another SQL statement it is
also termed nested query. Subqueries can be
used with the SELECT, INSERT, UPDATE, and
DELETE statements along with the operators
like =, <, >, >=, <=, IN, BETWEEN etc.
It can be used by the following commands.
- To insert records in a targets in the table created.
- To update records in a target table .
- To crate view

# Data types(Domain) in SQL :
Is an attribute that specifies the types of data that the
object can hold integer data, character data, date and
time data and so on.
Some of data types are given below.
Char (size)
This data types is used to store character string
values of fixed length. The size in brackets determine
the number of characters the cell can hold.
Varchar(size)/ Varchar2(size) :
This data types is used in store variable length
alphanumeric data.
Number :
The number database is used to store number
(fixed or floating point).

Date :
This data types is used to represent data
& time. The standard format is DD-MM-YY as
21-jun-2012.
Long :
This data type is used to store variable
length character string containing upto 2
GB.
Boolean :-
This data type has values of True and
False.

o Date/Time Use for dates and times
o Text: Use for text or combinations of text and
numbers. 255 characters maximum.
o Memo: Memo is used for larger amounts of text.
Stores up to 65,536 characters.
o Yes/No A logical field can be displayed as Yes/No,
True/False, or On/Off.
o AutoNumber: AutoNumber fields automatically
give each record its own number, usually starting
at 1.
o Currency: Use for currency. Holds up to 15 digits
of whole dollars, plus 4 decimal places.

DDL : (Data definition language )
DDL is a syntax similar to a computer programming
language for defining data structures, specially
database schemas.
Many data description, language SQL uses a
collection of imperative verb whose effect is to
modify the schema of database by adding changing
and deleting definitions of table or other objects .

Create statements :
To make a new database table, index or view etc.
Syntax.
CREATE TABLE[table name]
(columnname1 data types (size), column name2 data types
(size)………));
Example :-
Create employee table having same attributes.
create table employee (id integer primary key, fname
varchar(50) , Lname varchar (50) , date_of_Birth date);

Drop statement :
To destroy an existing database, table, index
or view.
syntax:
Drop object_type object_name;
Example:
Destroy employee table
Drop TABLE employee;

Alter statement : To modify an existing data base object.
Syntax:
A LTER object type object of name parameters;
Example :
The command to add (then remove)
Add a column named bubbles for an existing table
named sink .
ALTER TABLE Sink Add bubbles integer;
Drop a column named bubbles for an existing table
named sink .
ALTER TABLE sink Drop column bubbles;

DML (Data Manipulation Language): statements
are used for managing data within schema
objects.
DML is a family of syntax element similar to a
computer programming language used for
inserting deleting and updating data in database.
DML statements are.
Select…………..from…………where
Insert………….into …………..values…….
Update………..set…………….where……..
Delete ………….from………….where……

The SQL SELECT Statement
• The SELECT statement is used to select data
from a database.
SQL SELECT Syntax
SELECT column_name,column_name
FROM table_name;
Example:
SELECT * FROM employee;

The SQL INSERT INTO Statement
• The INSERT INTO statement is used to insert new
records in a table.
SQL INSERT INTO Syntax
INSERT INTO table_name
VALUES (value1,value2,value3,...);
Or
INSERT INTO table_name
(column1,column2,column3,...)
VALUES (value1,value2,value3,...);
Example:
INSERT INTO Customers (CustomerName, City,
Country)
VALUES ('Cardinal', 'Stavanger', 'Norway');

The SQL UPDATE Statement
• The UPDATE statement is used to update existing
records in a table.
SQL UPDATE Syntax
UPDATE table_name
SET column1=value1,column2=value2,...
WHERE some_column=some_value;
Example
UPDATE Customers
SET ContactName='Alfred Schmidt',
City='Hamburg'
WHERE CustomerName='Alfreds Futterkiste';

The SQL DELETE Statement
• The DELETE statement is used to delete rows
in a table.
SQL DELETE Syntax
• DELETE FROM table_name
WHERE some_column=some_value;
Example
DELETE FROM Customers
WHERE CustomerName='Alfreds Futterkiste'
AND ContactName='Maria Anders';

Data Control Language (DCL)
The Data Control Language (DCL) is a subset of
the Structured Query Lanaguge (SQL) that
allows database administrators to configure
security access to relational databases. Some
examples:
– GRANT - gives user's access privileges to database
– REVOKE - withdraw access privileges given with
the GRANT command

Operator in SQL:
oRelational operator :=,>=, <,>,<=,!=
oArithmetic operator : +, -,/,*
oLogical operator : AND, OR, NOT

And operator:
Process all rows in a table & display the result only when
all of the conditions specified using AND operator is
satisfied.
Example :
Retrieve the contents of the columns product_no,
description, profit_percent, sell-price from the table
product master where the values contained in the field
profit_ percent is between 10 & 20 both inclusive.
select product_no, description, profit_percent,
sell_price from product_master
where profit_percent>=10 AND
Profit_percent<=20;

OR operator :
Process all rows in a table & display the result only when
any of the conditions, specified using OR operator is
satisfied .
Example
Retrieve client information like client _no, name, address,
city, pin_code for all the clients where the pin code has
the value 400054 or 400057;
select * from client_master where pin_code =400054 OR
pin_code=400057;

Not operator :-
Process all the rows in a table and display the result only
when non of the conditions specified using the Not
operator are satisfied.
Example :
Retrieve specified client information for the clients who
are Not in “Butwal” OR “Pokhara”
select client_no, name, address, city pin_code
from client_master
where Not (city=‘Butwal’ or city=‘ pokhara’);

Range Searching:
BETWEEN Operator:
Allows the selection of rows that contains values
within a specified lower and upper limit.
Example :
 Retrieve all information from the table product-master
where the values contain within the field
profit-percent is betn 10 & 20 both inclusive.
Select* from product-master
where profit_percent between 10 AND 20;

Pattern matching :
LIKE predicate :
allows for a comparison of one string value with another
string value which is not identical.
for character data types :
q The percent sign(%) matches any string.
q The underscore ( _) matches any single character.
Example :
- Retrieve all information about supplier whose name begin
with letters ‘ja’ from supplier_master.
Select *from supplier_master where supplier_name =‘ja%’;
select* from supplier_master
Where supplier_name like ’l_r%’ or
Supplier_name Like ‘_h%’;

Function In SQL :-
SQL has many built-in functions for performing
calculations on data. Function are also capable of
accepting user-supplied variables or constants and
operating on them.
 Aggregate functions:
SQL aggregate functions return a single value,
calculate from the values in column.
i) Avg : returns the average value.
eg.
select avg(sell-price)“Average” from
product_master;

ii) MIN :
Returns the smallest value.
Eg.
select MIN(bal-due) “minimum balance”
from client_master;
iii) Count (expr):
Returns the number of rows where “expr” is not
null.
Eg.
select count (product_No) “No of product”
from product_master;

iv) Count (*):
Returns the number of rows in tables including duplicates
and those with nulls.
Eg.
select count(*) “total” from client_master;
v) Max():
Returns the largest value.
Exmaple :
select max (bal_due) “maximum” from client-master;

vi) Sum :
Returns the sum.
Example:
select sum (bal_due) “total balance due”
from client_master;
vii) SQRT :-
Returns square root of ‘n’ .
example :
select SQRT (25) “Square Root” from dual;

Group By clause :
Group by clause is another section of the select
statement. To group rows based on distinct
values that exits for specified column i.e. it
creates a data set, containing several set of
records grouped together based on a condition.

Table : sales
Detail ord no. Product No. Qty ordered Qty Display
019001 P0001 10 10
019001 P0004 3 3
019001 P0006 1 7
019002 P0002 4 4
019002 P0005 10 10
019003 P0003 2 2
019004 P0001 6 6
019005 P0006 4 4
019005 P0004 1 1
019006 P0006 8 8

Example :
Retrieve the product and the total quantity
ordered for each product from the sales tables.
select product_No, Sum (Qty_ordered) “Total
Qty” from sales group by product_No;

Having clause:
The HAVING Clause can be used in conjunction
with group by clause. HAVING imposes a
condition on the group by clause, which further
filter the group created by the group by clause.
Eg,
- Retrieve the product No. & total quantity ordered
for products ‘Pooo1’ or ‘Pooo4’ From sale table .
Select product_No, Sum (Qty ordered) “Total Qty”
from sales
group by product_No
having product_No=“P0001’ OR
product_No= ‘P0004’ ;

ORDER BY clause :
allows data from a table to be viewed in a sorted order.
The rows retrieved from the table will be sorted in
either ascending or descending order depending on the
condition specified in the select sentence.
Eg,
- Retrieve all rows from the table client_masters & display
this data sorted on the value contained in the field client
no in ascending order.
select* from client_master
ORDER By client- no;
Note : if we want to descending order then,
Select* from client_master
ORDER by client-No Desc;

Stored Procedure
• A stored procedure is a subroutine available to applications
that access a relational database system. A stored procedure
(sometimes called a proc, sproc, StoPro, StoredProc, sp or SP)
is actually stored in the database data dictionary.
• Typical use for stored procedures include data validation
(integrated into the database) or access control mechanisms.
Furthermore, stored procedures can consolidate and
centralize logic that was originally implemented in
applications. Extensive or complex processing that requires
execution of several SQL statements is moved into stored
procedures, and all applications call the procedures. One can
use nested stored procedures by executing one stored
procedure from within another.
• Stored procedures are similar to user-defined functions
(UDFs).

QBE(Query By Example )& GQBE :
is database query language for relational database. It
was devised by Moshe M. Zloof at IBM research during
the mid 1970’s, in parallel to the development of SQL. It
is the first graphical query language, using Visual tables
where the user would enter commands, example,
elements, & condition. Many graphical front- ends for
databases use the ideas from QBE today. Originally
limited only for the purpose of retrieving data, QBE was
later extended to allow other operations, such as inserts,
deletes & updates as well as creation temporary tables.

Unit-5
Relational Database Design
Data Normalization :-
The essence of data normalization is to split your
data into several tables that will be connected to
each other based on the data within them. The
goal of data normalization is to identify the
business rules so that you can design good
database table. By designing database tables
carefully, we
 Save space
Minimize duplication
Project the data to ensure it’s consistency
Provide faster transactions by sending less data.

Fundamental rules of Database Normalization.
 Each call in a table contain atomic (single-valued)
data.
Each non-key column depends on all of the
primary key columns.
Each non-key column depends on nothing
outside of the key columns.
- Types of Normalization :-
i) 1 normal form (1NF)
ii) 2 normal form (2NF)
iii) 3 normal form (3NF)
iv) Boyce codd Normal form (BCNF)

i) 1 normal form (1NF) :-
An entity is in the first normal form if it contains no
repeating groups or each cells contain atomic data
Example :
Entity :Customer(cid,full_name,tele_ph)
is not in 1NF & Now converting 1NF we have to split the
table.
CID F-name Surname Tele.ph.
123 Rohan Pandey 071-
456 Hari Sharma 072-
789 Mohan K.C 076-
Customer info(CID,first name, surname)
Customer tel(CID, Telephone_ number)

2) Second normal form (2NF):-
A relation R is in second normal form (2NF) if & only if it
is in 1NF & every non-key attributes is fully functionally
dependent on the primary key.
Note: full functional dependency
- A&B are attributes of a relation.
- B is fully dependent on A if B is functionally dependent on
A (E.g. AB)

Example
Sale line (sale ID, Item ID, Description, list
price, Quantity, Quantity on Hand )
it is not in 2NF, Now converting into 2NF
Item(ItemID, Desription, listprice, Quantity on
hand)
Sale_Items (sales ID, ItemID, Quantity)

3) Third normal form (3NF):-
A relation that is in 1NF, 2NF in which no
non_primary key attribute is transitively
dependent on the primary key.
Note: Transitive Dependency
A,B, & c are attributes of relation such that if
AB and B C, then C A is transitively
dependent on A through B.

Example
Sale_form (sale ID, sales date, customers Id,
first name, last name, city, state, zip code)
above table is not in 3NF because there is
transitive dependency, now, convert into 3NF.
Sale (sales Id, sale Date, customer ID)
customer (customer Id, first name, last name
city, state, zip code)

4) BCNF( Boyce codd Normal form) :-
Definition
A relation is in Boyce-Codd normal form if and only if it is
in third normal form and every determinant is a
candidate key. That is, if there is an FD X → Y, then X
must be the primary key (or equivalent to the primary
key). In simpler terms: there cannot be a hidden
dependency, where hidden means it is not part of the
primary key.

example
Employee.specialty (EID, specialty, manager)
Above table is not in BCNF because there is
hidden dependency. Now converting into
BCNF.
Employee_info (EID, manager)
manager_specialty (manager, specialty)

Fourth normal form
Fourth normal form (4NF) is a normal form used in
database normalization. Introduced by Ronald Fagin
in 1977, 4NF is the next level of normalization after
Boyce–Codd normal form (BCNF). Whereas the
second, third, and Boyce–Codd normal forms are
concerned with functional dependencies, 4NF is
concerned with a more general type of dependency
known as a multivalued dependency. A Table is in
4NF if and only if, for every one of its non-trivial
multivalued dependencies X Y, X is a superkey—that
is, X is either a candidate key or a superset thereof.

Multivalued dependencies
Multivalued dependencies are also referred to as tuple generating
dependencies. After the Boyce -Codd normal form the results may be
devoid of any functional dependencies but it may encounter
multivalued dependencies as the multivalued dependencies also cause
redundancy of data.
For eg:
If there are 3 attributes involved in a relation,A,B, and C..
Then for every value of A we will have respective values for B and C..
But it is a necessary in the 4th normal form that both B and C values are
independent of each other.
This is represented by .,,
A->>B
A->>C..
MVD or Multivalued Dependency is a dependency where one attribute
value is potentially a "multivalued fact" about another and the
attributes must be independent of each other.

Data constraints/Data rules and integrity :-
Rules which are enforced on data being
entered and prevents the user from
entering invalid data into tables are called
constraints. Thus constraints control data
being entered in tables for permanent
storage.
Data constraints to be attached to table
column via SQL syntax that will check data
for integrity.

Types of data constraints :
i)I/O Constraints :
This data constraint determine the speed at
which data can be inserted or extracted
from a table. I/O constraints divided into
two parts.
a. Primary key constraints
• that the data entered in the table column
is unique.
• That none of the cells belonging to the
table column left empty.

b. Foreign key constraints :
This constraints establishes a relationship
between records. This relationship ensures :
• Records can not be inserted into a detail table if
corresponding records in the master table do not
exist.
ii) Business Rule constraints :
DBMS allows the application of business rules to
table columns. Business manager determine,
business rules. These rules are applied to data
prior the data being inserted into table columns
eg,
The rule that no employee in the company shall
get salary less than Rs.1000/- is a business rule.

 Trigger :
A database trigger is procedural code that is
automatically executed in response to certain
events on a particular table or view in a database.
In addition to trigger that fire when data is
modified & when user logon or logoff events occur.
There are four type of trigger:
 Row level Trigger :This gets executed before or
after any column value of a row changes
Column level Trigger :This gets executed before or
after the specified column changes.
 For each row types : This trigger gets executed
once for each row of the result set cause by
insert/update/delete.
For each statement : This trigger executed only
once for the entire result set, but fires each time
the statement is executed.

Unit- 6
Security :
- The security of a database can be thought
of as a barrier which prevents unauthorized
access of data.
- Database security concerns the use of a
broad range of information security
controls to protect database (potentially
including the data, the database application
or stored functions, the data base systems,
the database severs and the associated
networks links) against compromises of
their confidentily, integrity and availability.

- It involves various types or categories of control,
such as technical, procedural administrative and
physical.
Need of security :
- Unauthorized or unintended activity or misuse by
authorized database users, database
administrator or network system managers, or by
unauthorized user or hackers.
- Mal ware infections causing incidents such as
unauthorized access, leakage or disclosure of
personal or proprietary data, deletion or damage
to the data or program.
- Overloads, performance constraints and capacity
issues resulting in the inability of authorized
users to use databases as intended.

- Physical damage to database serves caused
by computer room fires or floods,
overheating, lightning, accidental liquid
spills, static discharge, electronic
breakdown/ equipment failures.
# Access Control :
- Access control mechanisms enforce rules
about who can perform what operation or
who can access which data.
- Thus any access control mechanism must
concern itself which three basic
components, namely.

i) Identification and authentication of Accessor :
- The process of identification may involves several
parameters such as personal identification of
accessor, location of accessor, time and day of
access, frequency of access etc.
- Personal identification may be performs with the
help of passwords, voice prints, finger prints
signatures etc.
- The process of authentication requires supplying
information known only to the person the
accessor has claimed to be.
- This may be done by quoting a password or by
answering some question from system.

- The location of the accessor or time and day of
access are also useful in detecting unauthorized
access.
ii) Object to be locked :-
a) Data object :
The data objects to be locked may be files or
some records of a file. Sometimes if may be
necessary to lock and privacy keys are used to
control access to a particular record type.
b) View :
The another levels of security provided by
DBMS is defining views or the external model of
the schema. The owner of a database may grant
views which may consist of the entire data base
or a certain portion of the database.

c) Type of Access :-
Once an object is created, the own may grant
other genuine accessors any of the following
access right the object. Read, Run, modify, delete
insert, create , Destroy.
iii) Crypto System:
A cryptosystem is the combination of three
elements an encryption engine keying
information, and operational procedures for their
secure use.
In other to cryptographically secure high-value
data on a hard disk (or on back-up media), it is
necessary to employ a high-grade cryptosystem:
one which even an attacker processing both a
copy of your encryption engine and knowledge of
your operating procedures cannot break without
your keying information.

Encryption and Decryption :
- Encryption is a method of modifying the
original information according to some
code so that it can be read only if the user
known the decryption key.
- - Encryption should be used when
transmitting information from one
computer to another particularly when
using the internet.
- Sensitive information store within a
database also can be encrypted.
- Decryption is the reserve operation of
encryption.

- The process of decoding data that has been
encrypted into a secret format decryption
requires a secret key or password.
(Advanced encryption Standard)
Fig : single-key encryption
Key : 9837362
Key : 9837362
Plain text message
AES
Encrypted text
AES
Plain text message

Unit-7
Query Processing :
- All database systems must be able to
respond to request for information from the
user- I.e process queries.
- Obtaining the desired information from a
database system in a predictable and
reliable fashion is the scientific art of query
processing.

Basic steps in processing on SQL Query
SQL Query Parser &
Translator
Relational algebra
expression
Query Result
Evaluation
engine
Optimizer
Statistics
System catalogs
Execution plan
Data files

Parsing and translating :
- Translate the query into its internal form (parse
free)
- This is then translated into an expression of the
relational algebra.
- Parser checks syntax, validates relations,
attributes and access permissions.
Query interpretation (Query translation)
Given a query there are a number of ways to
process the query; in SQL or relational algebra we
can have equivalent expressions. Each method of
expressing a query suggests a strategy for
processing the query system must transform user
query to an equivalent more efficient query-optimization
similar to compiler code
optimization.

In relational models, commercial database
system provide a query optimizer there by
reducing the burden on the users.
i) Translating SQL Queries into Relational
Algebra (Equivalence to expression)
-SQL query is first translated into an
equivalent extended relational algebra
expression.
- SQL queries are decomposed into query
blocks, which form the basic units that
translated into the algebraic operators &
optimized.

- Query block contains a single SELECT
FROM-WHERE expression, as well as Group
by and Having clauses.
- Nested queries within a query are identified
as separate query block.
Query optimization :
- The query optimization or more accurately
improving query processing strategy helps
in reducing query execution time and
overhead.
- Find the “cheapest” execution plan for a
query.

- Query optimization is a function of many
relational database management systems in
which multiple query plans for satisfying a query
are examined and a good query plan is identified.
- - The set of query plans examined is formed (e.g.
primary index access, secondary index access, full
file scan) and various relational table join
techniques (e.g, merge join,hash join, product
join).
There are two types of optimization:
- These consist of logical optimization which
generates a sequences of relational algebra to
solve the query.

- In addition, there is physical optimization which is
used to determine the means of carrying out each
operation to join.
Join strategies :
- The join operation can be implemented in a variety of
ways.
- In terms of disk accesses, the join operations can be very
expansive, so implementing.
- Utilizing efficient join algorithms is critical in minimizing a
query is execution time.
The following are 4 well-known types of join
algorithms.
i) Nested-loop join (Brute force)
- For each record t in R (outer loop) retrieve every record D
for S (inner loop) and test whether the two record satisfy
the join condition t[A]=s[e].

ii) Single-loop join (using an access structure
to retrieve the matching records)
- If an index (or hash key) exists for one of
the two join attributes (e.g B of S) retrieve
each record t in R, one at a time (single
loop), and then use the access structure to
retrieve directly all matching records S from
S that satisfy S[B]=t[A].
iii) Sort-merge join:-
- If the records of R and S are physically
sorted (ordered) by value of the join
attributes A and B, respectively, we can
implemented join in the most efficient way.

- Both files are scanned concurrently in order
of the join attributes, matching the records
that have the same values for A and B.
- If the files are not sorted they may be
sorted first by using external sorting.
- Pairs of file blocks are copied into memory
buffers in order and records of each file are
scanned only once each for matching with
the other file if A and B are key attributes.
- The method is slightly modified in case
where A and B are not key attributes.

iv) Query Decomposition :
- The basic idea behind query decomposition is to
break a complex query into simpler sub queries
which can more easily be evaluated.
- QUEL query decomposition method can be
conveniently described if the query expression is
represented with the help of a hyper graph.
- Hyper graph : is a pair (N, ) where N is the set of
nodes and  is the set of edges called hyper
edges. A hyper edges in any arbitrary, non-empty
subset of N.

Unit-8
Filing and file structure :-
File :-
The file consist of records and the record may
consist of several fields the typical operations that
may be performed on the information stored in
the file are as follows.
-Retrieve :
To find the record having a particular value of the
particular field or where the field values satisfy
certain conditions.
-Insert :
Insert a record at some specific locations.

- Delete :
Deletes a particular record.
- Update :
Modifies the field values of a record.
# Factors affecting physical organization of
Data:
- Efficient use of storage.
- Minimization of Data Redundancy.
- Expandability
- Recovery from data loss.
# Buffer Management :-
- The buffer is that part of the main memory
available for the storage of the contents of some
of the blocks.

- The subsystems responsible for the allocation of
buffer space is called the buffer manager .
- The buffer manager services all request made by
the file management system for blocks on the file
currently being operated upon by the DBMS.
- If a requested block is already in the buffer, a
address of the block in the main memory is passed
on to the file manager & subsequently to the
DBMS.
- The most commonly used technique for buffer
management is the buffer cache.

# File Organization :-
Define :
A file organization essentially measure
organization of records in the file. Some basic file
organization techniques are given below.
- Heap (or pile)
- Sequential
- Indexed sequential
- Direct (or hashed)
• Heap (or pile or unordered) :
Basically theses files are unordered files. It is the
simplest & most basic type. These files consist of
randomly ordered records. The records will have
no particular order. The operations we can
perform on the record are insert, retrieve and

Delete. The features of the heap file or the pile
file organization are
- New records can be inserted in any empty space
that can accommodate them.
- When old records are deleted, the occupied space
becomes empty & available for any new insertion.
- If updated records grow; they may need to be
relocated (moved) to new empty space. This
needs to keep a list of empty space.
Advantages of heap files
- this is a simple file organization method.
- Insertion is some how efficient.
- Good for bulk-loading data into a table best if the
file scans are common or insertions are frequent.

Disadvantages of heap files.
-Retrieval requires a linear search and is inefficient.
- Deletion can result in unused space need for
reorganization.
Sequential file organization :
- The most basic way to organize the collection of
records in a file is to use sequential organization.
- Records of the file are stored in sequence by the
primary key field values. They are accessible only
in the order stored, I.e, in the primary key order.
- This kind of file organization works well for tasks
which need to access nearly every record in a file,
e.g. payroll

- Sequential files are inefficient for random
access, however, are suitable for sequential
access.
- A sequential file can be stored on device
like magnetic tape that allow sequential
access.
Advantages of sequential file organization.
- It is the fast and efficient which dealing
with large volumes of data that need to be
processed periodically (batch system).

Disadvantages of sequential file organization:
-Requires that all new transactions be sorted into
the proper sequence for sequential access
processing.
-Locating, sorting, modifying, deleting or adding
records in the file require rearranging the file.
The method is too slow to handle applications
requiring immediate updating or responses.
Indexed (indexed sequential) file organization.
-It organizes the file like a large dictionary I.e;
records are stored in order of the key but an index is
kept which also permits a type of direct access.
- The records are stored sequentially by primary key
values and there is an index built over the primary
key field.

- An index is set of index value, address pairs.
Indexing associated a set of objects to a set of
orderable quantities that are usually smaller in
number or their properties .
- Thus an index is a mechanism for faster search.
Hashed file organization :
- Hashing is the most common form of purely
random access to a file or data base.
- It is also used to access columns that do not have
an index as an optimization technique.
- Hash functions calculate the address of the page
in which the records is to be stored based on one
or more filed in the record.
- The record in a hash file appear randomly
distributed across the available space.

-It requires some hashing algorithm and the
technique.
- Hashing algorithms converts a primary key value
into record address .
Advantage of hashed file organization :
- Insertion or search on hash key is fast.
- Best if equality search is needed on hash key.
Disadvantages of hashed file organization :
- It is a complex file organization method.
- Range search is slow.
- It suffers from disk space overhead.
- Unbalanced buckets degrade performance.

B+Trees
a B+ tree or B plus tree is a type of tree which represents sorted
data in a way that allows for efficient insertion, retrieval and
removal of records, each of which is identified by a key.
In practice, each node or element on the tree would contain an
index element much like those in given figure A.
That is, each element would contain the key value, a pointer to
the rest of the data, and two link pointers.
For the particular tree in Figure A , each element has at most
two links. One link (the line to the left) points to elements that
have lower values.
The other link (line to the right) points to elements that have a
value greater than or equal to the value in the node. The root is
the highest node on the tree.
The bottom nodes are called leaves because they are at the end
of the tree branches.

Drawbacks
• One criticism has been that the coding is
relatively complex.

Unit- 9
Crash Recovery:
- Recovery restoring the database to a state that is
known be correct after some failure has rendered the
current state.
- Correct– does not violate any integrity rule.
A database is correct if it satisfies the logic AND of all
known rules.
- Failure- can be local or global.

Importance of DBMS Recovery
• Recovery—that is, the return to a fully
operational environment after a hardware or
software failure—is an important process.
• Moreover, the effects of a system failure on
the organization must be curtailed to minimize
any substantial financial loss.
• Actions must be taken to prevent DBMS
failures or resolve them quickly if they occur.
• A review of DBMS recovery ensures adherence
to appropriate practices and procedures and
minimizes business losses.

Categories of failures
There are many causes of DBMS failure. When a
DBMS fails, it falls into an incorrect state and will
likely contain erroneous data. Typical causes of
DBMS failures include errors in the application
program, an error by the terminal user, an
operator error, loss of data validity and
consistency, a hardware error, media failures, an
error introduced by the environment, and errors
caused by mischief or catastrophe. Type of
failures are given below:

• Transaction Failure.
Transaction failures occur when the
transaction is not processed and the
processing steps are rolled back to a specific
point in the processing cycle. In a distributed
data base environment, a single logical data
base may be spread across several physical
data bases. Transaction failure can occur when
some, but not all, physical data bases are
updated at the same time.

• System Failure.
System failure can be caused by bugs in the
data base, operating system, or hardware. In
each case, the Transaction processing is
terminated without control of the application.
Data in the memory is lost; however, disk
storage remains stable. The system must
recover in the amount of time it takes to
complete all interrupted transactions. At one
transaction per second, the system should
recover in a few seconds. System failures may
occur as often as several times a week.

• Media Failure.
Disk crashes or controller failures can occur
because of disk-write bugs in the operating
system release, hardware errors in the
channel or controller, head crashes, or media
degradation. These failures are rare but costly.

Recovery facilities :
DBMS should provide following facilities to assist
with recovery.
- Backup mechanism, which makes periodic
backup copies of database.
- Logging facilities, which keep track of current
state of transactions and database changes.
- Check point facility, which enables updates to
database in progress to be made permanent.
- Recovery manager, which allows DBMS to store
the database to a consistent state following
failures.

Log based recovery
• Every action starting from the database start up
and also each and every transaction is recorded
in a log file step by step
• In case, if within an ongoing transaction, the
system crashes or may be for some reason u
cannot complete the transaction, then the
database will remain in an inconsistent state
• So using the log files we can return back to our
previous state as if nothing has happened to the
database.
• and also to recover some data log files are used..
• There are various types of log files like redo log
files, event viewer log files etc.

Data Backup
• A data backup is the result of copying or
archiving files and folders for the purpose of
being able to restore them in case of data loss.
• Data loss can be caused by many things ranging
from computer viruses to hardware failures to file
corruption to fire, flood, or theft (etc). If you are
responsible for business data, a loss may involve
critical financial, customer, and company data. If
the data is on a personal computer, you could
lose financial data and other key files, pictures,
music, etc that would be hard to replace.

As part of a data backup plan, you should
consider the following:
– What data (files and folders) to backup
– What compression method to use
– How often to run your backups
– What type of backups to run*
– What kind of media on which to store the backups
– Where to store the backup data for safekeeping

Remote Backup
• In storage terminology, a remote backup refers to
an online managed backup service for backing up
data to a remote, cloud-based server ("cloud
backup").
• To update or restore a cloud backup, customers
need to use the service provider's specific client
application or Web browser interface. Files and
data can be automatically saved to the cloud
backup service on a regular, scheduled basis, or
the information can be automatically backed up
anytime changes are made.

Unit 10.Transaction Processing and
Concurrency Control
What is database transaction?
In database, a database transaction is a logical
unit of database operations which are executed
as a whole to process user requests for retrieving
data or updating the database. Transactions in a
database environment have two main purposes:
– To provide reliable units of work that allow correct
recovery from failures and keep a database consistent
even in cases of system failure, when execution stops
(completely or partially) and many operations upon a
database remain uncompleted, with unclear status.
– To provide isolation between programs accessing a
database concurrently.

Properties of database transactions are often
referred to by the acronym ACID.
– Atomicity: A transaction is an indivisible unit. It is
included in all operations or have done or not done.
– Consistency: Transaction must keep the database from
one consistent state to another consistent state variable.
– Isolation: A transaction is implemented and can not be
interfered with by other transactions. That is, an internal
operation of a transaction and the use of the data is
isolated with other transaction, the concurrent
implementation of all transactions can not interfere
between with each other.
– Durability: It's also called permanence. It refers to a
transaction which is submitted, and the data in the
database it changes should be permanent. The next
operation or other faults should not have any impact on
them.

Concurrency control
Definition
Concurrency control is a database
management systems (DBMS) concept that is
used to address conflicts with the simultaneous
accessing or altering of data that can occur
with a multi-user system. Concurrency control,
when applied to a DBMS, is meant to
coordinate simultaneous transactions while
preserving data integrity. The Concurrency is
about to control the multi-user access of
Database.

Schedules
In the fields of databases and transaction processing
(transaction management), a schedule (or history) of a
system is an abstract model to describe execution of
transactions running in the system. Often it is a list of
operations (actions) ordered by time, performed by a
set of transactions that are executed together in the
system. If order in time between certain operations is
not determined by the system, then a partial order is
used. Examples of such operations are requesting a read
operation, reading, writing, aborting, committing,
requesting lock, locking, etc. Not all transaction
operation types should be included in a schedule, and
typically only selected operation types (e.g., data access
operations) are included, as needed to reason about
and describe certain phenomena.

Serializability :
• Serializability is a property of a transaction
schedule (history). It relates to the isolation
property of a database transaction.
• Serializability of a schedule means equivalence
(in the outcomes, the database state, data
values) to a serial schedule (i.e; sequential with
no transaction overlap in time) with the same
transactions. It, is the major criterion for the
correctness of concurrent transactions schedule,
and thus supported in all general purpose
database system.

Locking :-
- A lock is a system object associated with the shared
resource such as data item of an elementary type, a row
in a database or a page or memory.
- In a database, a lock an a database object (a data
access lock) may need to be acquired by a transactions
before accessing the object.
- Correct use of locks prevents undesired, incorrect or
inconsistent operation on shared resources by other
concurrent transactions.
- When a database object with an existing lock acquired
by one transactions needs to be accessed by another
transactions the existing lock for the objects and the
type the intended access are checked by the system .

Two phase locking (locking):
- in database and transactions processing, two
phase locking (2pl) is a concurrency control
method that guarantees seralizability. It is also
the name of the resulting set of the data base
transaction schedules (histories).
- The protocol utilizes locks, applied by a
transaction to data, which may block (interpreted
as signals to stop) other transaction form
accessing the same data during the transactions
life. By the 2PL protocol locks are applied and
removed in two phases
– Expanding phase:
Locks are acquired and no locks are released.
– Shrinking phase :
Locks are released and no lock are acquired .

Two major types of locks are utilized:
- Write lock (exclusive lock) is associated with a database
object by a transaction (terminology “ the transaction
locks the object, “or” acquires lock for it”) before writing
(inserting/modifying/deleting) this object.
- Read lock (shared lock) is associated with a database
object by a transaction before reading (retrieving the
state of) this object.

Timestamp based concurrency control:
Definition :
In computer science, a timestamp-based concurrency
control algorithm is a non-lock concurrency control
method. It is used in some databases to safely handle
transactions, using timestamps.
– Every timestamp value is unique and accurately represents an
instant in time.
– No two timestamps can be the same.
– A higher-valued timestamp occurs later in time than a lower-valued
timestamp.

Unit 11
Advanced Database Concepts

OBJECT-ORIENTEDDATABASE MODEL : In the
object oriented data model the (OODM). Both
data and their relationship are contained in a
single structure known us an object. An object
includes information about relationship
between the facts within the object, as well as
information about its relationship with other
objects. An object is the abstraction of the
real- word entity. An object represents only
one occurrence of entity. Attributes describe
the property of an object. Objects that are
similar in characteristics are grouped in class.

Class: is a collection of similar objects with
shared structure ( attributes) and behavior
(method).
Method: represents areal word action such as
finding a selected person’s name, changing
person’s name or printing a persons address.
Inheritance is the ability of an object within
the class hierarchy to inherit the attributes
and methods of the class above it.

Object-relational database/Model
• An object-relational database (ORD), or
object-relational database management
system (ORDBMS), is a database management
system (DBMS) similar to a relational
database, but with an object-oriented
database model: objects, classes and
inheritance are directly supported in database
schemas and in the query language. In
addition, just as with pure relational systems,
it supports extension of the data model with
custom data-types and methods.

An object-relational database can be said to
provide a middle ground between relational
databases and object-oriented databases
(OODBMS). In object-relational databases, the
approach is essentially that of relational
databases: the data resides in the database and is
manipulated collectively with queries in a query
language; at the other extreme are OODBMSes in
which the database is essentially a persistent
object store for software written in an object-oriented
programming language, with a
programming API for storing and retrieving
objects, and little or no specific support for
querying.

Distributed Databases
A distributed database is a database in which portions
of the database are stored on multiple computers
within a network. Users have access to the portion of
the database at their location so that they can access
the data relevant to their tasks without interfering with
the work of others. A centralized distributed database
management system (DDBMS) manages the database
as if it were all stored on the same computer. The
DDBMS synchronizes all the data periodically and, in
cases where multiple users must access the same data,
ensures that updates and deletes performed on the
data at one location will be automatically reflected in
the data stored elsewhere.

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