UNIT machine learning unit 1,algorithm pdf

18CSC303J - DATABASE
MANAGEMENT SYSTEMS
UNIT -1 INTRODUCTION

INTRODUCTION
• Data
• Data is information (or) set of values that has been
gathered and translated for some purpose, usually
analysis.
• It can be any character, including text, numbers,
pictures, sound and video suitable for use with a
computer.
• Database
• A database is a collection of information that is
organized so that it can be easily accessed, managed
and updated.

File Processing
System
• A File Processing System is a collection of data, files
and records.
• In initial days, these records were stored in the form
of files. (Papers and notepad etc..)
• Each fields of information separated by space, tab,
comma, semicolon or any other symbol.
• Before DBMS were introduced, organizations usually
stored information in such systems.

Disadvantages of
FPS
• Data redundancy
• It is possible that the same information may be
duplicated in different files. This leads to data
redundancy. It results in memory wastage.
• Data inconsistency
• data may not be in consistent state.
• Difficulty in accessing data
• Accessing data is not convenient and efficient in
conventional file processing system.

Disadvantages of
FPS
• Data Isolation
• Data are separated in various files.
• Different files may have different formats.
• These files may be stored in different folders or
different computers.
• So, due to this data isolation, it is difficult to share
data among different applications.
• Integrity problems
• It refers to the accuracy and consistency of data
stored in a database.
• Data values stored in the database must satisfy
certain types of constraints.

Disadvantages of
FPS
• Atomicity problems
• File system does not guarantee the atomicity.
• If there is any failure to insert, update or delete in
the file system, there is no mechanism to switch
back to the previous state.
• Concurrent-access anomalies
• Multiple users are allowed to access data
simultaneously for better performance and faster
response.
• In the file system, concurrent access leads to
incorrect data.

Disadvantages of
FPS
• Security problems
• Not every user of the database system should be
able to access all the data.

Comparison
File Processing System
• File-based system
caused data
redundancy. The data
may be duplicated in
different files
• File –based system
caused data
inconsistency. The data
in different files may be
different that cause
data inconsistency.
DBMS
• Database system
control data
redundancy. The data
appeared only once in
the system.
• In database system
data always consistent.
Because data appeared
only once.

Comparison
• The data cannot be
shared because data is
distributed in different
files.
• File based system does
not provide
consistency constrains
DBMS
• In database data is
easily shared because
data is stored at one
place.
• Database system
provides a different
consistency constrains
to maintain data
integrity in the system

Comparison
• The cost of file
processing system is
less then database
system.
not provide
concurrency facility.
not provide data
atomicity functionality.
DBMS
• The cost of database
system is much more
than a file processing
system.
• Database system
provides concurrency
facility.
• Database system
provides data
atomicity functionality

PURPOSE OF
DATABASE SYSTEMS
• In the early days, database applications were built on top
of file systems
• Drawbacks of using file systems to store data:
• Data redundancy and inconsistency
• Multiple file formats, duplication of information in
different files
• Difficulty in accessing data
• Need to write a new program to carry out each new
task
• Data isolation — multiple files and formats
• Integrity problems
• Integrity constraints (e.g. account balance > 0)
become part of program code
• Hard to add new constraints or change existing ones

PURPOSE OF
DATABASE SYSTEMS
• Drawbacks of using file systems (cont.)
• Atomicity of updates
• Failures may leave database in an inconsistent state
with partial updates carried out
• E.g. transfer of funds from one account to another
should either complete or not happen at all
• Concurrent access by multiple users
• Concurrent accessed needed for performance
• Uncontrolled concurrent accesses can lead to
inconsistencies
• E.g. two people reading a balance and updating it
at the same time
• Security problems
• Database systems offer solutions to all the above problems

Database
Applications
• Banking: transactions
• Airlines: reservations, schedules
• Universities: registration, grades
• Sales: customers, products, purchases
• Online retailers: order tracking, customized
recommendations
• Manufacturing: production, inventory, orders, supply
chain
• Human resources: employee records, salaries, tax
deductions

Elements of Database
• Tables
• Data Types - what types of
data will be stored inside
each and every table
column when creating a
SQL table.
• Constraints - maintain
the data integrity during
an update/delete/insert
into a table.
• Indexes - an use to speed
up data retrieval.
• Procedures and Views

UNIT machine learning unit 1,algorithm pdf

• Databases can be classified according to types of
content and organizational approach
• Bibliographic - contains list of books with authors
and publishers

• full-text - contains complete text of books, thesis,
journals, magazines, newspapers and other kind of
textual documents(BLOB) E.g. Libraries
• Numeric
• Multimedia - images, graphic objects, drawings,
sketches, audio and video(BLOB).

Types of Databases
• Centralized database - A centralized database is
a database that is located, stored, and maintained in a
single location.
• E.g. desktop or server CPU, or a mainframe computer.

Types of Databases
• Distributed database - set of databases stored on
multiple computers. The data on several computers
can be simultaneously accessed and modified using a
network. Each database server in the distributed
database is controlled by its local DBMS

Types of Databases
• Object-oriented programming database
• Operational database
• End-user database
• Commercial database
• Personal database

DATABASE
MANAGEMENT
SYSTEM
• DBMS is a computer software that managing all
databases that are currently installed on a system
hard drive or network.
• MySQL Database
• Oracle Database
• Red Brick
• Microsoft SQL Server
• File Maker

Data Model
• Basic structure of a database is called data model.
• A data model is a set of tables, linked by relationships.
• Data models define how data is connected to each
other and how they are processed and stored inside
the system.
• The data models can be classified into four different
categories
• Relational Model
• Entity-Relationship Model
• Object-Based Data Model
• Semistructured Data Model

Relational Model
• Relational database
• All data must be stored in tables called relations
with rows and columns.
• Relations can be normalized(No Duplication).
• Relationship is maintained by storing a common
field.

E-R Model
• An entity relationship model, also called an entity-
relationship(ER) diagram, is a graphical
representation of entities and their relationships to
each other.

Object-Based Data
Model.
• Another method of representing real world objects.
• It considers each entity in the world as objects and
isolates it from each other.
• Object-oriented programming (especially in Java, C++,
or C#) has become the dominant software-
development methodology. Describe the state and
behavior of the object.

Semistructured
Data Model
• The XML Language is
widely used to
represent semi
structured data.
• Semistructured model
is a database
model where there is
no separation between
the data and the schema

Data Catalog
• The database catalog of a database instance consists
of metadata containing database object definitions
like base tables, synonyms, views and indexes.

Data Abstraction
• For the system to be usable, it must retrieve data
efficiently.
• Database systems are made-up of complex data
structures.
• To ease the user interaction with database, the
developers hide internal irrelevant details from users.
• This process of hiding irrelevant details from user is
called data abstraction. several levels of abstraction..
• View level
• Logical level
• Physical level

Data Abstraction –
VIEW OF DATA

Data Abstraction
• View level
• Highest level of data abstraction. This level
describes the user interaction with database
system.
• Example
• At view level, user just interact with system with
the help of GUI and enter the details at the screen,
they are not aware of how the data is stored and
what data is stored.

Data Abstraction
• Logical level
• This is the middle level of 3-level data abstraction
architecture. It describes what data is stored in
database.
• Example
• At the logical level these records can be described
as fields and attributes along with their data types.
The programmers generally work at this level
because they are aware of such things about
database systems.

Data Abstraction
• Physical level
• This is the lowest level of data abstraction. It
describes how data is actually stored in database.
You can get the complex data structure details at
this level.
• Example
• Let’s consider storing customer information in a
customer table. At physical level these records can
be described as blocks of storage (bytes, gigabytes,
terabytes etc.) in memory. These details are often
hidden from the programmers.

DBMS Architecture
• 2-tier DBMS Architecture
• 2-tier DBMS architecture includes an Application
layer between the user and the DBMS, which is
responsible to communicate the user's request to
the DBMS and then send the response to the user
from the DBMS.
• An application interface known as ODBC(Open
Database Connectivity) provides an API that allow
client side program to call the DBMS.
• Client application – on which remote database users
work.
• Server application – on which the database system
runs.

DBMS Architecture
• 3-tier DBMS Architecture
• The objective of the three level architecture is to
separate each user's view of the database from the
Way the database is physically represented.
• In a 3-tier architecture, the client machine acts as a
front end application and does not contain any direct
database calls.
• Instead, the client end communicates with an
application server, usually through a forms
interface.

DBMS System
Structure
• A primary goal of a database system is to retrieve
information from database and store information into
the database.
• People who work with a database can be categorized
as database users or database administrators.
• Different types of user interfaces have been designed
for the different types of users.
• There are four different types of database-system
users can be classified.

DBMS System
Structure
• Naive users Any user who does not have any
knowledge about database. There task is to just use
the developed application and get the desired results.
• Application programmers are computer professionals
who write application programs. They can choose
many tools to develop user interfaces.
• Sophisticated users interact with the system without
writing programs. Instead, they form their requests
either using a database query language or by using
tools.

DBMS System
Structure
• DBA (Database Administrator)
• DBA can be a single person or it can be a group of
person.
• Database Administrator is responsible for
everything that is related to database.
• He makes the policies, strategies and provides
technical supports.

DBMS System
Structure
• Query Processor Components
• DML Compiler
• It translates DML statements into low level
instructions(Binary language) that query
evaluation engine understands.
• Embedded DML Pre-compiler
• It converts DML statements to normal procedure
calls. The Pre-compiler must interact with the DML
compiler to generate the appropriate code(host
language).

DBMS System
Structure
• DDL Interpreter
• It interprets the DDL statements and records them
in a set of tables containing meta data or data
dictionary.
• Query Evaluation Engine
• It executes low-level instructions generated by the
DML compiler.
• Storage Manager Components
• They provide the interface between the disk
storage and query processor.
• Authorization and Integrity Manager
• It tests for the satisfaction of integrity constraints
checks the authority of users to access data.

DBMS System
Structure
• Transaction Manager
• It ensures that the database remains in a consistent
state despite the system failures and that
concurrent transaction execution proceeds without
conflicting.
• File Manager
• It manages the allocation of space on disk storage.
• Buffer Manager
• It is responsible for fetching data from disk storage
into main memory and deciding what data to cache
in memory.

DBMS System
Structure
• Disk Storage
• Data Files
• It stores the database files(Binary format)
• Data Dictionary
• It stores meta data (data about data) about the
structure of the database.
• Indices
• Provide fast access to data items that hold particular
values.
• Statistical Data
• It stores statistical information about the data in the
database. This information is used by query processor
to select efficient ways to execute query.

DATABASE
LANGUAGES
TWO TYPES:
• Data Definition Language (DDL)
• Data Manipulation Language (DML)

DDL:
DDL or Data Definition Language actually consists of
the SQL commands that can be used to define the
database schema.
It simply deals with descriptions of the database
schema and is used to create and modify the
structure of database objects in the database.

Data Definition
Language (DDL)
• Specification notation for defining the database schema
• E.g.
create table account (
account-number char(10),
balance integer)
• DDL compiler generates a set of tables stored in a data
dictionary
• Data dictionary contains metadata (i.e., data about data)
• database schema
• Data storage and definition language
• language in which the storage structure and access
methods used by the database system are specified
• Usually an extension of the data definition language

Data Manipulation
Language (DML)
• Language for accessing and manipulating the data
organized by the appropriate data model
• DML also known as query language
• Two classes of languages
• Procedural – user specifies what data is required
and how to get those data
• Nonprocedural – user specifies what data is
required without specifying how to get those data
• SQL is the most widely used query language

SQL
• SQL: widely used non-procedural language
• E.g. find the name of the customer with customer-id
192-83-7465
select customer.customer-name
from customer
where customer.customer-id = ‘192-83-7465’
• E.g. find the balances of all accounts held by the customer
with customer-id 192-83-7465
select account.balance
from depositor, account
where depositor.customer-id = ‘192-83-7465’ and
depositor.account-number = account.account-
number
• Application programs generally access databases through one of
• Language extensions to allow embedded SQL
• Application program interface (e.g. ODBC/JDBC) which allow
SQL queries to be sent to a database

SQL- STRUCTURED
QUERY LANGUAGE
• Structured Query Language(SQL) as we all know is
the database language by the use of which we can
perform certain operations on the existing database
and also we can use this language to create a
database. SQL uses certain commands like Create,
Drop, Insert etc. to carry out the required tasks.
• These SQL commands are mainly categorized into
four categories as:
1. DDL – Data Definition Language
2. DQl – Data Query Language
3. DML – Data Manipulation Language
4. DCL – Data Control Language

DDL(Data Definition Language) : DDL or Data Definition
Language actually consists of the SQL commands that can be
used to define the database schema. It simply deals with
descriptions of the database schema and is used to create and
modify the structure of database table in the database.
Examples of DDL commands:
• CREATE – is used to create the database or its objects (like
table, index, function, views, store procedure and triggers).
• DROP – is used to delete table from the database.
• ALTER-is used to alter the structure of the database.
• TRUNCATE–is used to remove all records from a table,
including all spaces allocated for the records are removed.
• COMMENT –is used to add comments to the data dictionary.
• RENAME –is used to rename an table existing in the
database.

CREATE
CREATE TABLE TABLE_NAME (COLUMN_NAME D
ATATYPES[,....]);
DROP
DROP TABLE TABLE NAME;
ALTER (ADD NEW COLUMN)
ALTER TABLE table_name ADD column_name CO
LUMN-de nition;

ALTER (MODIFY)
ALTER TABLE MODIFY(COLUMN DEFINITION....);
TRUNCATE:
TRUNCATE TABLE TABLE NAME;
RENAME:
RENAME OLD TABLE NAME TO NEW TABLE
NAME;

DQL (Data Query Language) :
• DML statements are used for performing queries on
the data within schema objects. The purpose of
DQL Command is to get some schema relation
based on the query passed to it.
• Example of DQL:
• SELECT – is used to retrieve data from the a
database.
SELECT * FROM TABLE NAME;

DML(Data Manipulation Language) : The SQL
commands that deals with the manipulation of data
present in the database belong to DML or Data
Manipulation Language and this includes most of the
SQL statements.Examples of DML:
• INSERT – is used to insert data into a table.
• UPDATE – is used to update existing data within a
table.
• DELETE – is used to delete records from a
database table.

INSERT:
INSERT INTO TABLE_NAME
(col1, col2, col3,.... col N)
VALUES (value1, value2, value3, .... valueN);
INSERT:
INSERT INTO TABLE_NAME
VALUES (value1, value2, value3, .... valueN);
• For example:

UPDATE:
UPDATE table_name SET [column_name1= value1,
...column_nameN = valueN] [WHERE CONDITION]
DELETE:
DELETE FROM table_name [WHERE condition];

DCL(Data Control Language) : DCL includes
commands such as GRANT and REVOKE which
mainly deals with the rights, permissions and other
controls of the database system.Examples of DCL
commands:
• GRANT-gives user’s access privileges to database.
• REVOKE-withdraw user’s access privileges given
by using the GRANT command.

GRANT:
GRANT SELECT,
UPDATE ON MY_TABLE TO SOME_USER,
ANOTHER_USER;
REVOKE:
REVOKE SELECT,
UPDATE ON MY_TABLE FROM USER1, USER2;

TCL(transaction Control Language) : TCL
commands deals with the transaction within the
database.Examples of TCL commands:
• COMMIT– commits (SAVE) a Transaction.
• ROLLBACK– rollbacks a transaction in case of any
error occurs.
• SAVEPOINT–sets a savepoint within a transaction.
ie) It is used to roll the transaction back to a ce ain point without
rolling back the entire transaction.
• SET TRANSACTION–specify characteristics for the
transaction.

COMMIT:
COMMIT;
ROLLBACK:
ROLLBACK;
SAVEPOINT:
SAVEPOINT SAVEPOINT_NAME;

Database Users
• Users are differentiated by the way they expect to
interact with the system
• Application programmers – interact with system
through DML calls
• Sophisticated users – form requests in a database
query language
• Specialized users – write specialized database
applications that do not fit into the traditional data
processing framework
• Naïve users – invoke one of the permanent
application programs that have been written
previously
– E.g. people accessing database over the web, bank
tellers, clerical staff

Database
Administrator
• Coordinates all the activities of the database system;
the database administrator has a good understanding
of the enterprise’s information resources and needs.
• Database administrator's duties include:
– Schema definition
– Storage structure and access method definition
– Schema and physical organization modification
– Granting user authority to access the database
– Specifying integrity constraints
– Acting as liaison with users
– Monitoring performance and responding to
changes in requirements

Data Independence
• Data independence can be explained using the
three-schema architecture.
• Data independence refers characteristic of being
able to modify the schema at one level of the
database system without altering the schema at
the next higher level.
ere are two types of data independence:
1.Logical Data Independence
2. Physical Data Independence

Logical Data Independence
• Logical data independence refers characteristic
of being able to change the conceptual schema
without having to change the external schema.
• Logical data independence is used to separate
the external level from the conceptual view.
• If we do any changes in the conceptual view of
the data, then the user view of the data would
not be a ected.
• Logical data independence occurs at the user
inte ace level.

Physical Data Independence
• Physical data independence can be de ned as the
capacity to change the internal schema without
having to change the conceptual schema.
• If we do any changes in the storage size of the
database system se er, then the Conceptual
structure of the database will not be a ected.
• Physical data independence is used to separate
conceptual levels from the internal levels.
• Physical data independence occurs at the logical
inte ace level.

UNIT machine learning unit 1,algorithm pdf

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