DATA BASE MANAGEMENT SYSTEM KCS 501

Er. Navnish Goel Assistant Professor Department of Information Technology

S. D. COLLEGE OF ENGINEERING TECHNOLOGY Page 1

DATA BASE MANAGEMENT SYSTEM – KCS 501

Programme: CSE / IT Degree: B. Tech. Year: III

Course: Database Management Systems Design Semester: V Credits: 3

Course Code: KCS501 Course Type: Core

Course Area/Domain: System Software Concepts Contact Hours: 3 Hours / Week

Corresponding Lab Course Code (If Any): KCS551 Lab Course Name: Database Management Systems Lab

Syllabus

KCS-501: Database Management Systems 4-0-0

Unit Topic Proposed

Lecture

I Introduction: Overview, Database System vs File System, Database System Concept

and Architecture, Data Model Schema and Instances, Data Independence and

Database Language and Interfaces, Data Definitions Language, DML, Overall

Database Structure. Data Modelling Using the Entity Relationship Model: ER Model

Concepts, Notation for ER Diagram, Mapping Constraints, Keys, Concepts of Super

Key, Candidate Key, Primary Key, Generalization, Aggregation, Reduction of an ER

Diagrams to Tables, Extended ER Model, Relationship of Higher Degree.

08

II Relational data Model and Language: Relational Data Model Concepts, Integrity

Constraints, Entity Integrity, Referential Integrity, Keys Constraints, Domain

Constraints, Relational Algebra, Relational Calculus, Tuple and Domain Calculus.

Introduction on SQL: Characteristics of SQL, Advantage of SQL. Sql Data Type and

Literals. Types of SQL Commands. SQL Operators and Their Procedure. Tables,

Views and Indexes. Queries and Sub Queries. Aggregate Functions. Insert, Update

and Delete Operations, Joins, Unions, Intersection, Minus, Cursors, Triggers,

Procedures in SQL/PL SQL

08

III Data Base Design & Normalization: Functional dependencies, normal forms, first,

second, 8 third normal forms, BCNF, inclusion dependence, loss less join

decompositions, normalization using FD, MVD, and JDs, alternative approaches to

database design

08

IV Transaction Processing Concept: Transaction System, Testing of Serialability,

Serialability of Schedules, Conflict & View Serializable Schedule, Recoverability,

Recovery from Transaction Failures, Log Based Recovery, Checkpoints, Deadlock

Handling. Distributed Database: Distributed Data Storage, Concurrency Control and

Directory System.

08

V Concurrency Control Techniques: Concurrency Control, Locking Techniques for

Concurrency Control, Time Stamping Protocols for Concurrency Control,

Validation Based Protocol, Multiple Granularity, Multi Version Schemes, Recovery

with Concurrent Transaction, Case Study of Oracle.

08

Total Hours 40

Text / Reference Books:

1. Korth, Silbertz, Sudarshan,” Database Concepts”, McGraw Hill

2. Date C J, “An Introduction to Database Systems”, Addision Wesley

3. Elmasri, Navathe, “Fundamentals of Database Systems”, Addision Wesley

4. RAMAKRISHNAN"Database Management Systems",McGraw Hill

5. Bipin C. Desai, “An Introduction to Database Systems”, Gagotia Publications




Course Objective:

1. To impart the basic understanding of the theory and applications of database management systems.

2. To give basic level understanding of internals of database systems.

3. To expose to some of the recent trends in databases.

By the end of the course, students will be able to:

Course Outcome:

KCS501.1 understand the concepts of DBMS and would have acquired skills to analyse the real- world problem

domains in the context of DBMS and demonstrate the same through ER diagram.

KCS501.2 apply and demonstrate with understanding of relational query languages such as SQL, Relational

Algebra & Relational Calculus. The students will be able to construct an Entity-Relationship (E-R)

model from specifications and to perform the transformation of the conceptual model into

corresponding logical data structures.

KCS501.3 design a relational database following the design principles. To relate the concepts of inference rules,

data constraints and normalization. Students would also have acquired skills to identify application

of the same.

KCS501.4 understand basic issues of transaction processing, concurrency control and serializability.

KCS501.5 define, explain and illustrate fundamental principles of data organization, query optimization. To

classify various concurrency control techniques and recovery procedures.

WEB SOURCE REFERENCES:

1. https://nptel.ac.in/courses/106/105/106105175/

2. www.tutorialspoint.com/plsql

3. https://swayam.gov.in/nd1_noc20_cs09/preview

https://nptel.ac.in/courses/106/105/106105175/

http://www.tutorialspoint.com/plsql

https://swayam.gov.in/nd1_noc20_cs09/preview




UNIT-I (CHAPTER 1)

IMPORTANT QUESTION AND ANSWERS

1. What is Data?

Data is a collection of raw, unorganised facts and details like text, observations, figures,

symbols and description of any things etc. In other words, data does not carry any specific

purpose and has no significance itself. Moreover, data is measured in terms of bits and bytes -

which are basic units of information in the context of computer storage and processing. Name

of a student, age, class and name of subjects can be counted as data for recording purposes.

Collection of related data is known as Database. The collection of data, usually referred to

as the database, contains information relevant to an enterprise. For example: Set of student info.

2. What is Information?

Information is the processed, organised and structured data. It provides context for data and

enables decision making. For example, if we have data about marks obtained by all students,

we can then find out toppers of the class and average marks etc.

3. Explain Data Vs Information in tabular form?

Basis for

Comparison Data Information

Meaning Data means raw facts gathered

about someone or something,

which is bare and random.

Facts, concerning a particular event or

subject, which are refined by

processing is called information.

What is it? It is just text and numbers. It is refined data or meaningful data

Based on Records and Observations Analysis

Form Unorganized Organized

Useful May or may not be. Always

Dependency Does not depend on

information.

Without data, information cannot be

processed.

4. What do you mean by database management system?



A database-management system (DBMS) is a collection of interrelated data and a set of

programs to access these data. A database management system stores data, in such a way which

is easier to retrieve, manipulate and helps to produce information. The primary goal of a DBMS

is to provide a way to store and retrieve database information that is both convenient and

efficient. Database systems are designed to manage large bodies of information. Management

of data involves both defining structures for storage of information and providing mechanisms

for the manipulation of information. In addition, the database system must ensure the safety of

the information storage, system crashes or unauthorized access.

Interface Between User and Files

Disk

Figure 1: Flow of DBMS

5. Define DBMS and File management system (FMS)?

Database management system (DBMS) is a collection of interrelated data and a set of

programs to access those data. Some well-known DBMS software are Microsoft Access,

Microsoft SQL Server, Oracle, SAP, dBASE, FoxPro, IBM dB2, SQLite etc.

Figure 2: FMS Vs DBMS

A file management system is an abstraction to store, retrieve, management and update a set

of files. In simple terms, a File Management System (FMS) is a kind of Database Management

System that allows access to single files or tables at a time. FMS’s accommodate flat files that

USER

DBMS SOFTWARE

DB FILES



have no relation to other files. The FMS was the predecessor for the Database Management

System (DBMS), which allows access to multiple files or tables at a time.

6. Explain the difference between file systems, DBMS in detail.

File Management System Database Management System

File System is a general, easy-to-use system to

store general files which require less security

and constraints.

Database management system is used

when security constraints are high.

Data Redundancy is more in file management

system.

Data Redundancy is less in database

management system.

Data Inconsistency is more in file system. Data Inconsistency is less in database

management system.

Centralization is hard to get when it comes to

File Management System.

Centralization is achieved in Database

Management System.

User locates the physical address of the files to

access data in File Management System.

In Database Management System, user is

unaware of physical address where data is

stored.

Security is low in File Management System. Security is high in Database Management

System.

7. What are the disadvantages of file management system over DBMS?

The disadvantages of file management systems over DBMS are:

a) Data redundancy and inconsistency.

b) Difficulty in accessing data.

c) Data isolation.

d) Integrity problems.

e) Atomicity problems.

f) Concurrent access anomalies.

8. What are the advantages of DBMS over file management system?

The advantages of DBMS over file management system are:

a) Control redundancy

b) Restrict unauthorized access



c) Provide multiple user interfaces

d) Enforce integrity constraints.

e) Provide backup and recover.

9. Explain Database Users with their types?

DBMS users are those persons who work with a database for different purposes. The users

of DBMS are categized into two groups.

A) END USER

➢ End users are those who actually reap the benefit of having a DBMS.

➢ End users are the people whose jobs require access to the database for a

querying, updating and generating reports.

➢ Other subtypes of end uses are Casual End User, Naïve, Sophisticated, Stand

Alone End User.

END USER ADMINISTRATOR DESIGNERS (OPTIONAL)

Figure 3: DATABASE USERS

B) DBA (Data Base Administrator)

Data Base Administrator maintain the DBMS and are responsible for administrating the

database. They are responsible to look after its usage and by whom it should be used.

10. Is there any difference between DBMS and file management system in terms of ACID

properties?

DBMS ensures data integrity by managing transactions through ACID property.

A = Atomicity.

C = Consistency.

I = Isolation

D = Durability.

While such integrity is absent in file management system.

DBMS



UNIT-I (CHAPTER 2)


11. Explain view of data at different levels of abstraction or data abstraction?

Abstraction is one of the main features of database systems. Hiding irrelevant details from user

and providing abstract view of data to users, helps in easy and efficient user-database

interaction. In other words, Abstraction is the process to hide the irrelevant things from the

users and represent the relevant things to the user. Database systems contain of complex data

structures. Thus, to retrieval the data and reduce the complexity of the users, we use the data

abstraction method. There are mainly three levels of data abstraction:

a) Internal Level: Actual physical storage structure and access paths.

b) Conceptual or Logical Level: Structure and constraints for the entire database

c) External or View level: Describes various user views.

Figure 4: View of Data / Data Abstraction

External View – This is the highest level of abstraction as seen by a user. It describes only the

part of entire database, which is relevant to a particular user.

Conceptual View – This is the next higher level of abstraction which is the sum total of

Database Management System user's views. It describes what data are actually stored in the

database. It contains information about entire database in terms of a small number of relatively

simple structure.

Internal View – This is the lowest level of abstraction. It describes how the data are physically

stored and describes the data structures and access methods to be used by the database.



12. Explain Instance and Schema?

The description of a database is called the database schemas, which is specified during database

design and is not expected to change frequently for example student schema

Name Roll_no Class Marks

Course Course_no Department

Figure 5: Schemas and Instance

Every time we insert or delete a record or change the values of a data items in a record, we

change one stage of database into another stage.

13. Explain Data Models?

Underlying the structure of a database is the data model: a collection of conceptual tools for

describing data, data relationships, data semantics, and consistency constraints. To illustrate

the concept of a data model, first we will try to understand few other terms related to data base.

Schema - description of data at some level (e.g., tables, attributes, constraints, domains)

Model - tools and languages for describing:

• Languages – Conceptual / logical and external schema described by the data definition

language (DDL).

• Integrity constraints, domains described by DDL

• Operations on data described by the data manipulation language (DML)

Types of data models:

a) Entity-Relationship model - Proposed by P.P. Chen in 1970s. E-R modelling is a

conceptual level model.

• Entities are real-world objects about which we collect data, represented by rectangles.

• Attributes describe the entities, it is represented by ellipses.

• Relationships are associations among entities, it is represented by diamonds.

• Entity set - set of entities of the same type.

• Relationship set - set of relationships of same type.

• Relationships sets may have descriptive attributes.

b) Relational Model

The most popular data model in DBMS is the Relational Model. It is more scientific a model than

others. It uses collection of tables to represent both data and the relationships among those data.

Each table has multiple columns, and each column has a unique name.





The main highlights of this model are −

• Data is stored in tables called relations.

• Relations can be normalized.

• In normalized relations, values saved are atomic values.

• Each row in a relation contains a unique value.

• Each column in a relation contains values from a same domain.

14. Explain various symbols used to draw an E-R diagram and illustrate example using

given information about a bank, customers and their account. Customer has a name,

address which consists of house number, area and city, and one or more phone

numbers. Account has number, type and balance. We need to record customers who

own an account. Account can be held individually or jointly. An account cannot exist

without a customer. Arrive at an E-R diagram. Clearly indicate attributes, keys, the

cardinality ratios and participation constraints.?

Figure 5: Notations of E-R diagram



Figure 6: Banking management information about a bank, customers, their account details.

15. What do you mean by Data Independence? Explain the types of Data Independence

(D/I)?



16. Explain Database Languages in details?



There are two types of DML

[1] Procedural DMLs. A query in procedural DML requires the user to specify not only ―what

data is required to be extracted from the database‖ but also to specify ―how to extract those

data‖.

[2] Non-Procedural DMLs. A Query in Non-Procedural DML requires the user to specify only

―what data is needed‖, without specifying how to get those data. Non-procedural DMLs are

easier to learn and to use than the procedural DMLs. However, since non-Procedural DMLs do

not specify ―how to get the data‖.

This limitation of Non-Procedural DMLs is overcome by performing query optimization at

the System Level.

17. What do you mean by Referential Integrity?

Referential integrity requires that a foreign key must have a matching primary key or it must

be null. This constraint is specified between two tables (parent and child); it maintains the

correspondence between rows in these tables. It means the reference from a row in one table to

another table must be valid. Examples of referential integrity constraint in the Customer/Order

database of the Company:

Customer (CustID, CustName) Order (OrderID, CustID, OrderDate)

To ensure that there are no orphan records, we need to enforce referential integrity. An orphan

record is one whose foreign key FK value is not found in the corresponding entity – the entity

where the PK is located. Recall that a typical join is between a PK and FK.

The referential integrity constraint states that the customer ID (CustID) in the Order table

must match a valid CustID in the Customer table. Most relational databases have declarative

referential integrity. In other words, when the tables are created the referential integrity

constraints are set up.

Here is another example from a Course/Class database:

Course (CrsCode, DeptCode, Description) Class (CrsCode, Section, ClassTime)

The referential integrity constraint states that CrsCode in the Class table must match a valid

CrsCode in the Course table. In this situation, it’s not enough that the CrsCode and Section in

the Class table make up the PK, we must also enforce referential integrity.



18. Construct E-R Diagram for College management system?



19. Construct E-R diagram for Hospital Management System?



20. Reduced given E-R diagram into table?

The database can be represented using the notations, and these notations can be reduced to a

collection of tables. In the database, every entity set or relationship set can be represented in

tabular form. The ER diagram is given below:

There are some points for converting the ER diagram to the table:

o Entity type becomes a table.

In the given ER diagram, LECTURE, STUDENT, SUBJECT and COURSE forms individual

tables.

o All single-valued attribute becomes a column for the table.

In the STUDENT entity, STUDENT_NAME and STUDENT_ID form the column of

STUDENT table. Similarly, COURSE_NAME and COURSE_ID form the column of

COURSE table and so on.

o A key attribute of the entity type represented by the primary key.

In the given ER diagram, COURSE_ID, STUDENT_ID, SUBJECT_ID, and LECTURE_ID

are the key attribute of the entity.

o The multivalued attribute is represented by a separate table.

In the student table, a hobby is a multivalued attribute. So it is not possible to represent multiple

values in a single column of STUDENT table. Hence we create a table STUD_HOBBY with

column name STUDENT_ID and HOBBY. Using both the column, we create a composite key.

o Composite attribute represented by components.

In the given ER diagram, student address is a composite attribute. It contains CITY, PIN,

DOOR#, STREET, and STATE. In the STUDENT table, these attributes can merge as an

individual column.

o Derived attributes are not considered in the table.

In the STUDENT table, Age is the derived attribute. It can be calculated at any point of time

by calculating the difference between current date and Date of Birth.



Using these rules, you can convert the ER diagram to tables and columns and assign the

mapping between the tables. Table structure for the given ER diagram is as below

Figure: Table structure



UNIT-II (CHAPTER 1)


21. Define Integrity Constraints?

Integrity Constraints

• Integrity constraints are a set of rules. It is used to maintain the quality of information.

• Integrity constraints ensure that the data insertion, updating, and other processes have

to be performed in such a way that data integrity is not affected.

• Thus, integrity constraint is used to guard against accidental damage to the database.

Types of Integrity Constraint

A. DOMAIN CONSTRAINTS

• Domain constraints can be defined as the definition of a valid set of values for an

attribute.

• The data type of domain includes string, character, integer, time, date, currency, etc.

The value of the attribute must be available in the corresponding domain.

CREATE TABLE customer_details

(

customer_id character varying(255) NOT NULL,

customer_name character varying(255) NOT NULL,

quantity integer NOT NULL,

date_purchased date

);

CREATE TABLE Student

(

s_id int NOT NULL,

name varchar(60),

age int

);

If you wish to alter the table after it has been created, then we can use the ALTER command

for it: ALTER TABLE Student MODIFY s_id int NOT NULL;

CREATE TABLE employee

(

id number(5) PRIMARY KEY,

name char(20),

dept char(10),

age number(2),

gender char(1) CHECK (gender in ('M','F')),

salary number(10),

location char(10)

);



CHECK CONSTRAINT AT TABLE LEVEL:


(

id number(5) PRIMARY KEY,

name char(20),

dept char(10),

age number(2),

gender char(1),

salary number(10),

location char(10),

CONSTRAINT gender_ck CHECK (gender in ('M','F'))

);

USING CHECK CONSTRAINT AT TABLE LEVEL

CREATE table Student

(

s_id int NOT NULL CHECK(s_id > 0),

Name varchar (60) NOT NULL,

Age int

);

ALTER table Student ADD CHECK(s_id > 0)



B. ENTITY CONSTRAINTS

• The entity integrity constraint states that primary key value can't be null.

• This is because the primary key value is used to identify individual rows in relation and

if the primary key has a null value, then we can't identify those rows.

• A table can contain a null value other than the primary key field.

CREATE TABLE Students

(

Student_ID int NOT NULL,

Student_Name varchar(255) NOT NULL,

Class_Name varchar(255) UNIQUE,

Age int,

PRIMARY KEY (Student_ID)

);

ALTER table Student ADD PRIMARY KEY (s_id);

PRIMARY KEY AT COLUMN LEVEL:


(

id number(5),

name char(20),

dept char(10),

age number(2),

salary number(10),

location char(10),

CONSTRAINT emp_id_pk PRIMARY KEY (id)

);

PRIMARY KEY AT TABLE LEVEL:


(

id number(5), NOT NULL,

name char(20),

dept char(10),

age number(2),

salary number(10),

location char(10), ALTER TABLE employee ADD CONSTRAINT PK_EMPLOYEE_ID PRIMARY KEY (id)

);



C. REFERENTIAL INTEGRITY CONSTRAINTS

• A referential integrity constraint is specified between two tables.

• In the Referential integrity constraints, if a foreign key in Table 1 refers to the Primary

Key of Table 2, then every value of the Foreign Key in Table 1 must be null or be

available in Table 2.

CREATE TABLE Department

(

Department_ID int NOT NULL,

Department_Name varchar(255) NOT NULL,

PRIMARY KEY(Department_ID)

);

CREATE TABLE Employees

(

Employee_ID int NOT NULL,

Employee_Name varchar(255) NOT NULL,

Department int NOT NULL,

Age int,

FOREIGN KEY (Department) REFERENCES Department(Department_ID)

);

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DATA BASE MANAGEMENT SYSTEM KCS 501