PPT Lecture 1.1 and 1.2(Database concepts and database system architecture) (1).pptx

2
Course Outcome Will be covered in
this lecture
Department of Computer Science and Engineering (CSE)
CO1: To make student learn all
core subjects of respective
engineering background

Contents of the Syllabus
3
Unit-1 Data Base Management Systems Contact Hours:4
CHAPTER
1.1
Introduction and applications of DBMS, Purpose of data base, Data, Independence,
Database System architecture- levels.
CHAPTER
1.2
Structure of relational databases, Domains, Relations, Relational algebra – fundamental
operators and syntax, relational algebra queries, tuple relational calculus.
CHAPTER
1.3
Basic concepts, Design process, constraints, Keys, Design issues, E-R diagrams, weak
entity sets, extended E-R features – generalization, specialization, aggregation, reduction
to E-R database schema
CHAPTER
1.4
Functional Dependency – definition, trivial and non-trivial FD, closure of FD set, closure of
attributes, irreducible set of FD, Normalization – 1Nf, 2NF, 3NF, Decomposition using FD-
dependency preservation, BCNF, Multi- valued dependency, 4NF, Join dependency and
5NF
Contact
Hours:4

4
Unit-2 Structured Query Language Contact Hours:4
CHAPTER 2.1 Basics of SQL, DDL, DML, DCL, structure – creation, alteration, defining constraints –
Primary key, foreign key, unique, not null, check, IN operator,
Functions - aggregate functions, Built-in functions –numeric, date, string functions, set
operations, sub-queries, correlated sub-queries, use of group by, having, order by, join
and its types, Exist, Any, All, view and its types. transaction control commands – Commit,
Rollback, Save point
CHAPTER 2.2 Cursors, Stored Procedures, Stored Function, Database Triggers
Unit-3 Views , Packages and procedures , triggers, Transection
management and concurrency control.
Contact Hours:4
CHAPTER 3.1 Package, Procedures and Triggers: Parts of procedures, Parameter modes, Advantages of
procedures, Syntax for creating triggers, Types of triggers, package specification and package
body, developing a package, Bodiless package, Advantages of packages.

CHAPTER 3.2
Transaction Management and Concurrency Control: Introduction to Transaction
Processing, Properties of Transactions, Serializability and Recoverability, Need for
Concurrency Control, Locking Techniques, Time Stamping Methods, Optimistic
Techniques, Granularity of Data items, Database Recovery of database: Introduction,
Need for Recovery, Types of errors, Recovery Techniques.

University Institute of Engineering (UIE)
OBJECTIVES
At the completion of this Chapter , students should be able
to do the following:
• Understand the role of a database
management system in an organization.
• Understand basic database concepts, including the
structure and operation of the relational data model.

Department of Computer Science and Engineering
(CSE)
University Institute of Engineering
File system vs. Database
system
File System-
• Data storage traditionally used individual, unrelated files, sometimes
called flat files.
• In the past, each application program in an organization used its own file.
• In a university, for example, each department might have its own set of
files: the record office kept a file about the student information and their
grades, the scheduling office kept the name of the professors and the
courses they were teaching, the payroll department kept its own file about
the whole staff and so on.
• Today, however, all of these flat files can be combined in a single
entity; the database for the whole university

(CSE)
Data
vs.
Informtion

(CSE)
Database Management System
(DBMS)
• The related information when placed is an organized form makes a database.
• The organization of data/information is necessary because unorganized information
has no meaning.
• Collection of interrelated data
• Set of programs to access the data
• DBMS contains information about a particular enterprise
• DBMS provides an environment that is both convenient and efficient to use.
• Database Applications:
– Banking: all transactions
– Airlines: reservations, schedules
– Universities: registration, grades
– Sales: customers, products, purchases
– Manufacturing: production, inventory, orders, supply chain
– Human resources: employee records, salaries, tax deductions
• Databases touch all aspects of our lives

(CSE)
Purpose of Database
System
• 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 provide a way of ensuring that changes
made to the database by authorized users do not result in a
loss of data consistency.
• Hard to add new constraints or change existing ones

(CSE)
Purpose of Database
System
• 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

(CSE)
Disadvantages of Traditional File
system
• Data Redundancy
Since each application has its own data file, the
same data may have to be recorded and stored in
many files
For example-
Personal file and payroll file, both contain data on
employee name, designation etc. The result is
unnecessary duplicate or redundant data items. This
redundancy requires additional or higher storage
space, costs extra time and money, and requires
additional efforts to keep all files upto-date.

(CSE)
• Data Inconsistency
Data redundancy leads to data inconsistency especially when
data is to be updated. Data inconsistency occurs due to the
same data items that appear in more than one file do not get
updated simultaneously in each and every file.
• Lack of Data Integration
• Data Dependence
• Limited Data Sharing
• Poor Data Control
• Problem of Security
• Data Manipulation Capability is Inadequate
Disadvantages of Traditional File
system

(CSE)
Operations on
Databases

(CSE)
Advantages of
Databases
• Less redundancy
– In a flat-file system there is a lot of redundancy. For example, in the flat file
system for a university, the names of professors and students are stored in
more than one file.
• Inconsistency avoidance
When the same data is duplicated and changes are made at one site, which
is not propagated to the other site, it gives rise to inconsistency and the two
entries regarding the same data will not agree.
– If the same piece of information is stored in more than one place, then any
changes in the data need to occur in all places that data is stored.

(CSE)
• Efficiency
– A database is usually more efficient that a flat file system,
because a piece of information is stored in fewer locations.
• Data integrity
• Integrity of data means that data in database is always accurate, such that
incorrect information cannot be stored in database.
– In a database system it is easier to maintain data integrity, because a
piece of data is stored in fewer locations.
• Confidentiality
– It is easier to maintain the confidentiality of the information if the storage of
data is centralized in one location.
Advantages of
Databases

(CSE)
• Data can be shared
• Providing Backup and Recovery
• Standards can be enforced
• Restricting unauthorized access
• Solving enterprise requirement than individual requirement
Advantages of
Databases

(CSE)
Disadvantages of
DBMS
• Complexity
• Size
• Performance
• Higher impact of a
failure
• Cost of DBMS
• Additional Hardware
costs
• Cost of Conversion

(CSE)
Use a DBMS when this is
important
• persistent storage of data
• centralized control of data
• control of redundancy
• control of consistency and
integrity
• multiple user support
• sharing of data
• data documentation
• data independence
• control of access and security
• backup and recovery
Do not use a DBMS when
• the initial investment in hardware,
software, and training is too high
• the generality a DBMS provides is not
needed
• the overhead for security, concurrency
control, and recovery is too high
• data and applications are simple and
stable
• real-time requirements cannot be met by
it
• multiple user access is not needed

(CSE)
File
Management
e.g. COBOL or C++
Program
• Small systems
• Relatively Cheap
• Few Files
• Files are Files
• Simple Structure
• Redundant Data
• Chances of Inconsistency
• Isolated Data
• Little Preliminary Design
• Integrity Left to application
Programmer
• NO Security
• Simple, Primitive
backup/Recovery
• Often Single User
• Large systems
• Relatively Expensive
• Many Files
• Files are Tables
• Complex Structure
• Reduced Redundancy
• Consistent
• Data can be Shared
• Vast Preliminary Design
• Rigorous inbuilt Integrity
checking
• Rigorous Security
• Complex & Sophisticated
backup/Recovery
• Multiple Users
Database
Management
e.g. Oracle

BASIC DEFINITIONS
⮚Database: A collection of related data.
⮚Data: Known facts that can be recorded and have an implicit
meaning.
⮚Database Management System (DBMS): A software package/
system to facilitate the creation and maintenance of a computerized
database.
⮚Database System: The DBMS software together with the data
itself. Sometimes, the applications are also included.
(CSE)

(CSE)
Outcomes
• Differentiate database systems from file systems by
enumerating the features provided by database
systems and describe each in both function and
benefit.
• Define the terminology, features, classifications, and
characteristics embodied in database systems.
• Master the basic concepts and appreciate the
applications of database systems.

(CSE)
References
• Database System Concepts by Abraham
Silberschatz
• Database System Concepts by
Sudarshan, Korth Education)
(McGraw-Hill
• Fundamentals of Database System By
Elmasari &Navathe- Pearson Education
• http://ecomputernotes.com/database-system/rdbms
• https://www.tutorialspoint.com/sql/sql-rdbms-concepts.htm
• https://www.studytonight.com/dbms/rdbms-concept

(CSE)
(UIE)

OBJECTIVES
At the completion of this Chapter , students should be
able to do the following:
• Understand DBMS Architecture
• Appreciate the evolution of ANSI SPARC (3 level
architecture)

Introduction
ANSI
American National Standards Institute
SPARC
Standards Planning And Requirements Committee
• It is an abstract design standard for a Database Management
System (DBMS), first proposed in 1975.

Three-level architecture
• External level
• Conceptual level
• Internal level
• The Three Level Architecture has the aim of enabling users to
access the same data but with a personalized view of it. The
distancing of the internal level from the external level means that
users do not need to know how the data is physically stored in
the database. This level separation also allows the Database
Administrator (DBA) to change the database storage structures
without affecting the users' views.

Three-level architecture
• External Level (User Views): A user's view of the database describes
a part of the database that is relevant to a particular user. It excludes
irrelevant data as well as data which the user is not authorized to
access.
• Conceptual Level: The conceptual level is a way of describing
what data is stored within the whole database and how the data is
inter-related. The conceptual level does not specify how the data is
physically stored.
• Internal Level: The internal level involves how the database is
physically represented on the computer system. It describes how
the data is actually stored in the database and on the computer
hardware.

Objective of the three-level
architecture
• It allows independent customized user views: Each user should be
able to access the same data, but have a different customized view
of the data. These should be independent: changes to one view
should not affect others.
• It hides the physical storage details from users: Users should
not have to deal with physical database storage details.
• The database administrator should be able to change the
database storage structures without affecting the users’ views.
• The internal structure of the database should be unaffected by
changes to the physical aspects of the storage: For example, a
changeover to a new disk.

Database schemas
There are three different types of schema corresponding to the three
levels in the ANSI-SPARC architecture.
Schema is the structure of the database that defines the objects in the
database
• The external schemas describe the different external views
of the data and there may be many external schemas for a
given database.
• The conceptual schema describes all the data items and
relationships between them, together with integrity constraints
(later). There is only one conceptual schema per database.
• The internal schema at the lowest level contains definitions
of the stored records, the methods of representation, the
data fields, and indexes. There is only one internal schema
per database.

(CSE)
The
way
users
perceiv
e the
data.
The way the
DBMS and OS
perceive the
data.

Mapping between views
• Three view-levels are described by means of three schemas.
• These schemas are stored in the data dictionary.
• In DBMS, each user refers only to its own external schema.
• Hence, the DBMS must transform a request on. a specified external schema into a
request against conceptual schema, and then into a request against internal schema
to store and retrieve data to and from the database.
• The process to convert a request (from external level) and the result between view
levels is called mapping.
• The mapping defines the correspondence between three view levels.
• The mapping description is also stored in data dictionary.
• The DBMS is responsible for mapping between these three types of schemas.

Mapping between views
There are two types of mapping.
(i) External-Conceptual mapping
• An external-conceptual mapping defines the correspondence between a particular
external view and the conceptual view.
• The external-conceptual mapping tells the DBMS which objects on the conceptual
level correspond to the objects requested on a particular user's external view.
• If changes are made to either an external view or conceptual view, then mapping
must be changed accordingly.
(ii) Conceptual-Internal mapping
• The conceptual-internal mapping defines the correspondence between the
conceptual view and the internal view, i.e. database stored on the physical storage
device.
• It describes how conceptual records are stored and retrieved to and from the
storage device.

Example

Data Independence
• The ability to modify a scheme definition in one level without
affecting a scheme definition in a higher level is called data
independence.
There are two kinds:
• Logical data independence
• Physical data independence

Data Independence
Logical data independence
• The ability to modify the conceptual scheme without causing
application programs to be rewritten.
• Immunity of external schemas to changes in the conceptual schema.
• The change would be absorbed by mapping
between external and conceptual levels.
Physical data independence
• The ability to modify the internal scheme or physical storage
structures and devices without affecting conceptual or external
schemas .
• Modifications at this level are usually to improve performance.
Logical data independence is difficult to achieve than
physical data independence.

Database Administrator (DBA)
• A database administrator (DBA) is an IT professional responsible for
the installation, configuration, upgrading, administration, monitoring,
maintenance, and security of databases in an organization.

Responsibilities of DBA
Makes decisions concerning the content of the database.
✔ Identify the entities of interest to the enterpriseand
to identify
information to be recorded about those entities
Plans storage structures and access strategies.
✔ How the data is to be represented in the database.
✔ Specify the representation by writing the storage structure definition
(using the internal data definition language).
✔ The associated mapping between the storage structure definition and the conceptual schema
must also be specified.
Provides support to users.
✔ Ensure that the data users require is available,and
to write the necessary external schemas.
✔ The mapping between any given eA1ernal schema and the conceptual' schema must also be
specified.

Responsibilities of DBA
Defines security and integrity checks.
✔ Providing the authorization and authentication checks such
that no
malicious users can access database and it must remain protected.
✔ DBA must also ensure the integrity of the database.
Interprets backup and recovery strategies.
✔ Define and implement an appropriate recovery
strategy to recover he
database from all types of failures.
Monitoring performance and responding to changes in requirements.
✔ DBA is responsible for so organizing the system as to get the performance that is
"best for the enterprise," and for making the appropriate adjustments as
requirements change.

Outcomes
• Analyze an information storage problem and derive an
information model expressed in the form of an entity
relation diagram and other optional analysis forms,
such as a data dictionary.
• Demonstrate an understanding of the relational data
model.
• Appreciate the roles & responsibilities of DBA.

References
• Database System Concepts by Abraham
Silberschatz
• Database System Concepts by
Sudarshan, Korth Education)
(McGraw-
Hill
• Fundamentals of Database SystemBy Elmasari
&Navathe- Pearson Education

46
Database
Management
System
CO
Number
Title Level
CO1 To perceive the significance and
implementation of a commercial
relational database system (Oracle)
by writing SQL using the system.
Remember
CO2 To understand the relational database
theory, and be able to write
relational algebra expressions for
queries
Understand
CO3 To identify the basic issues of
transaction processing and
concurrency control and find out its
solutions.
Analysis and
application
this lecture

47
UNIT-I [10h]
Overview of Databases: Database concepts, DBMS, Data Base System Architecture (Three
Level ANSI-SPARC Architecture), Advantages and Disadvantages of DBMS, Data Independence, DBA
and Responsibilities of DBA, Relational Data Structure, Keys, Relations, Attributes, Schema and
Instances, Referential integrity, Entity integrity.
Data Models: Relational Model, Network Model, Hierarchical Model, ER Model: Design,
issues, Mapping constraints, ER diagram, Comparison of Models.
Relational Algebra & Relational Calculus: Introduction, Syntax, Semantics, Additional
operators, Grouping and Ungrouping, Relational comparisons, Tuple Calculus, Domain Calculus,
Calculus Vs Algebra, Computational capabilities.
UNIT-II [10h]
Functional dependencies and Normalization: Functional dependencies, Decomposition, Full
Functional Dependency (FFD), Transitive Dependency (TD), Join Dependency (JD), Multi-valued
Dependency (MVD), Normal Forms (1NF, 2NF, 3NF, BCNF), De-normalization.
Database Security: Introduction, Threats, Counter Measures.
Control Structures: Introduction to conditional control, Iterative control and sequential control
statements, Cursors, Views.

48
UNIT-III [10h]
Package, Procedures and Triggers: Parts of procedures, Parameter modes, Advantages of
procedures, Syntax for creating triggers, Types of triggers, package specification and package body,
developing a package, Bodiless package, Advantages of packages.
Transaction Management and Concurrency Control: Introduction to Transaction Processing,
Properties of Transactions, Serializability and Recoverability, Need for Concurrency Control, Locking
Techniques, Time Stamping Methods, Optimistic Techniques and Granularity of Data items.
Database Recovery of database: Introduction, Need for Recovery, Types of errors, Recovery
Techniques.

49
Chapter 1.2
(Data Models)
Data Models: Relational Model, Network Model, Hierarchical Model, ER Model:
Design, issues, Mapping constraints, ER diagram, Comparison of Models.

Learning Objective
• Method to organize data required in an application as
relations.
• Importance for an integrated database in organizations.
• Goals of Data Base Management systems (DBMS).
• Entity-Relationship(ER) modeling to develop a
conceptual model of data.
• Structure and organization of DBMS

Learning Outcome
• Define program-data independence, data models for
database systems, database schema and database
instances.
• Identify the methodology of conceptual modeling
through Entity Relationship model.
• Identify the methodology of logical model.
• Identify the methodology of physical model.

Entity-Relationship Model..contd
Relationships: Link between different entities of the database is called
relationship.
Mapping Cardinalities
Cardinality defines the number of entities in one entity set, which can be
associated with the number of entities of other set via relationship set.
•Express the number of entities to which another entity can be associated via
a relationship set.
•Most useful in describing binary relationship sets.

Types of Relationships
One - One Relationship:- (1 – 1)
Each value in the first table could relate with only one record in the
second table.
One – Many Relationship:- (1 - ∞)
Each value in the first table could relate with many records in the second
table.
Many – Many Relationship (∞ - ∞)
table and each value of the second table could relate with many records in
the first table.
Many – One Relationship(∞-1)
•More than one entities from entity set A can be associated with at most one
entity of entity set B, however an entity from entity set B can be associated
with more than one entity from entity set A.

Relationships….contd
One - One Relationship:- (1 – 1)
Each value in the first table could relate with only one record in the
second table.

One – Many Relationship:- (1 - ∞)
table.

• Many-to-many − One entity from A can be associated with more than
one entity from B and vice versa

• Many-to-one − More than one entities from entity set A can
be associated with at most one entity of entity set B, however
an entity from entity set B can be associated with more than
one entity from entity set A.

E-R Diagrams
• ER Diagram stands for Entity Relationship Diagram, also known
as ERD is a diagram that displays the relationship of entity sets
stored in a database. In other words, ER diagrams help to
explain the logical structure of databases. ER diagrams are
created based on three basic concepts: entities, attributes and
relationships.
• ER Diagrams contain different symbols that use rectangles to
represent entities, ovals to define attributes and diamond
shapes to represent relationships.
• At first look, an ER diagram looks very similar to the flowchart.
However, ER Diagram includes many specialized symbols, and
its meanings make this model unique. The purpose of ER
Diagram is to represent the entity framework infrastructure.

E-R Diagrams Symbols
• Entity Relationship Diagram Symbols & Notations mainly contains
three basic symbols which are rectangle, oval and diamond to
represent relationships between elements, entities and attributes.
There are some sub-elements which are based on main elements in
ERD Diagram. ER Diagram is a visual representation of data that
describes how data is related to each other using different ERD
Symbols and Notations.
• Following are the main components and its symbols in ER
Diagrams:
• Rectangles: This Entity Relationship Diagram symbol represents
entity types
• Ellipses : Symbol represent attributes
• Diamonds: This symbol represents relationship types
• Lines: It links attributes to entity types and entity types with other
relationship types
• Primary key: attributes are underlined
• Double Ellipses: Represent multi-valued attributes

E-R Diagrams Symbols

E-R Diagrams
● Rectangles represent entity sets.
● Diamonds represent relationship sets.
● Lines link attributes to entity sets and entity sets to relationship sets.
● Ellipses represent attributes
● Double ellipses represent multivalued attributes.
● Dashed ellipses denote derived attributes.
● Underline indicates primary key attributes (will study later)

E-R Diagram With Composite,
Multivalued, and Derived Attributes

Usage of E-R Diagrams
• Helps you to define terms related to entity relationship modeling
• Provide a preview of how all your tables should connect, what fields
are going to be on each table
• Helps to describe entities, attributes, relationships
• ER diagrams are translatable into relational tables which allows you to
build databases quickly
• ER diagrams can be used by database designers as a blueprint for
implementing data in specific software applications
• The database designer gains a better understanding of the
information to be contained in the database with the help of ERP
diagram
• ERD Diagram allows you to communicate with the logical structure of
the database to users

Design Issues
• Use of entity sets vs. attributes
Choice mainly depends on the structure of the enterprise being modeled,
and on the semantics associated with the attribute in question.
• Use of entity sets vs. relationship sets
Possible guideline is to designate a relationship set to describe an action
that occurs between entities
• Binary versus n-ary relationship sets
Although it is possible to replace any nonbinary (n-ary, for n > 2)
relationship set by a number of distinct binary relationship sets, a n-ary
relationship set shows more clearly that several entities participate in a
single relationship.
• Placement of relationship attributes

65
Data Models: A Summary
• Each new data model capitalized on the shortcomings of previous models
• Common characteristics:
– Conceptual simplicity without compromising the semantic
completeness of the database
– Represent the real world as closely as possible
– Representation of real-world transformations (behavior) must comply
with consistency and integrity characteristics of any data model

Data Dictionary
It contains information about the data attributes, elements relationship, user
details, security restrictions and integrity constraints.

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

FAQ
1.Define DBMS? List Database system Applications.
2. Discuss Database Administrator’s responsibilities.
3. What do you understand by dimension and attribute?
4. What is a fact & a fact table?
5. List out few common mistakes encountered during Data
Modelling?
6. What do you understand by Data Modelling?
7. Explain your understanding of different data models?

References
OTHER REFRENCES
• ER Diagram: Entity Relationship Diagram Model | DBMS
Example (guru99.com)
• ER Diagram Representation - Tutorialspoint
• Entity Relationship Diagram - ER Diagram in DBMS
(beginnersbook.com)
• SUGGESTED BOOK REFERENCES
• Ramez Elmasri and Shamkant B. Navathe,“Fundamentals
of Database System”, The Benjamin / Cummings Publishing
Co.
• Korth and Silberschatz Abraham, “Database
SystemConcepts”, McGraw Hall.
• Pratt,”DBMS”, Cengage Learning.

73
Database
Management
System
CO
Number
Title Level
Remember
queries
Understand
solutions.
Analysis and
application
this lecture
Department of Computer Scienceand Engineering (CSE)

74
UNIT-I [10h]
UNIT-II [10h]

75
UNIT-III [10h]
Techniques.

76
Chapter 1.2
(Data Models)
Data Models: Relational Model, Network Model, Hierarchical Model, ER Model:
Design, issues, Mapping constraints, ER diagram, Comparison of Models.

Relationship Types
• Specialization
• Generalization
• Aggregation

Specialization
In specialization, an entity is divided
into sub-entities based on their
characteristics. It is a top-down
approach where higher level entity is
specialized into two or more lower level
entities.
For Example, EMPLOYEE entity in an
Employee management system can be
specialized into DEVELOPER, TESTER
etc. as shown in Figure 2. In this case,
common attributes like E_NAME, E_SAL
etc. become part of higher entity
(EMPLOYEE) and specialized attributes
like TES_TYPE become part of
specialized entity (TESTER).

Aggregation
An ER diagram is not capable of
representing relationship between an
entity and a relationship which may be
required in some scenarios. In those
cases, a relationship with its
corresponding entities is aggregated
into a higher level entity.
For Example, Employee working for a
project may require some machinery.
So, REQUIRE relationship is needed
between relationship WORKS_FOR
and entity MACHINERY. Using
aggregation, WORKS_FOR
relationship with its entities
EMPLOYEE and PROJECT is
aggregated into single entity and
relationship REQUIRE is created
between aggregated entity and
MACHINERY.

Generalization
Generalization is the process of
extracting common properties from a
set of entities and create a
generalized entity from it. It is a
bottom-up approach in which two or
more entities can be generalized to a
higher level entity if they have some
attributes in common.
For Example,
STUDENT and FACULTY can be
generalized to a higher level entity
called PERSON as shown in Figure
1. In this case, common attributes like
P_NAME, P_ADD become part of
higher entity (PERSON) and
specialized attributes like S_FEE
become part of specialized entity
(STUDENT).

Comparison of Record based
model
Hierarchical Network Relational
Relationship between
records is of parent child
type.
records is expressed in the
form of pointers or links
records is represented by a
relation that contains a key
for each record involved in
the relatonship.
Many to Many relationship
cannot be expressed in this
model
can be easily implemented.
can also be implemented.
It is simple, straightforward
and natural method of
implementing record
relationships
Record relationship
implementation is very
complex due to the use of
pointers
Relationship
implementation is very easy
through the use of a key or
composite key field

Comparison of Record based
model
Hierarchical Network Relational
This type of model is useful
only when there is some
hierarchical character in the
database
Network model is useful for
representing such records
which have many to many
relationships
Relational model is useful
for representing most of the
real world objects and
relationships among them
In order to represent links
among records, pointers are
used. Thus relations among
records are physical
In network model also the
record relations are physical
Relational model does not
maintain physical
connection among record.
Data is organized logically in
the form of rows and
columns, and stored in
table.
Searching for record is very
difficult since one can
retrieve a child only after
going through its parent
record
Searching a record is easy
since there are multiple
access paths to a data
elements.
A unique indexed key field Is
used to search for a data
element.

85
• Each new data model capitalized on the shortcomings of previous models
• Common characteristics:
– Conceptual simplicity without compromising the semantic
completeness of the database
– Represent the real world as closely as possible
– Representation of real-world transformations (behavior) must comply
with consistency and integrity characteristics of any data model

SQL COMPONENTS
SQL consists of three components:
1. Data Definition Language (DDL)
2. Data Manipulation Language (DML)
3. Data Control Language (DCL)

DATA DEFINITION LANGUAGE (DDL)
This component of the SQL language is used to create and modify tables and
other objects in the database. For tables there are three main commands:
CREATE TABLE tablename  to create a table in the database
DROP TABLE tablename  to remove a table from the database
ALTER TABLE tablename  to add or remove columns from a table in the
database
RENAME <new table name> to <old table name>;  To change the name
of a table as per the user’s wish or requirement.
TRUNCATE TABLE<table name>;  Truncate Tables empties the table
completely. Once the data deleted cannot be retrieved.
DESC tablename  To view just the blank table

CREATE TABLE COMMAND
Purpose:- Tables are the basic unit of data storage in an Oracle
Database. Data is stored in rows and columns.
Syntax:- Create table <TableName> (<ColumnName1> <Data Type>(<Size>),
<ColumnName2> <Data Type>(<Size>), ………..<ColumnName n> <Data
Type>(<Size>));
Example:-
Create table STUDENT (Roll_no number(5), Name varchar2(20), Branch
varchar2(10));

ALTER TABLE COMMAND
Purpose:- The structure of a table can be modified by using a alter table
command. Alter Table allows changing the structure of an existing table. With
Alter Table it is possible to add or delete columns, create or destroy indexes,
change the data type of existing columns, or rename columns or the table itself
Syntax:-
Adding New Columns
Alter table <table name> add(<new col name> <data type> (<Size>), <new col
name> <data type> (<Size>),…..);
Modifying Existing Column
Alter table <table name> modify(<col name> <new data type> (< new Size>),
<col name> <new data type> (<new Size>),…..);
Dropping A Column
Alter table <table name> drop column <col name>;

Example:-
Alter table STUDENT add( Telephone number(10));
Alter table STUDENT modify( Telephone number(20));
Alter table STUDENT drop column Telephone;

RENAME TABLE COMMAND
Purpose:- To change the name of a table as per the user’s wish or
requirement.
Syntax:- Rename <new table name> to <old table name>;
Example:- Rename STUDENT to group_a101;

DROP TABLE COMMAND
Purpose:- Sometimes table in the database becomes obsolete and need to be
discarded, so we use drop table command.
Syntax:- Drop table <table name>;
Example:-
Drop table CSEA_Data101;

DATA MANIPULATION LANGUAGE (DML)
DML component of the SQL language is used to manipulate data within a
table. There are four main commands:
SELECT  to select rows of data from a table
INSERT  to insert rows of data into a table
UPDATE  to change rows of data in a table
DELETE  to remove rows of data from a table

INSERT COMMAND
Command:- Insert data into a table
Purpose:- The Insert Into Table command is used to load the created table
with data to be manipulated later.
Syntax:- Insert into <table name>(<col1>,<col2>,……..,<col n>) values
(<expression1>, <expression2> ,……,<expression3>);
Example:-
Insert into STUDENT values(101, ‘Aanchal’, ’CSE’);
Insert into STUDENT values(126, ‘Jotnain’, ’CSE’);
Insert into STUDENT values(149, ‘Sapanpreet’, ’ECE’);
Insert into STUDENT values(151, ‘Savita’, ’CSE’);

INSERT DATA INTO A TABLE FROM A TABLE
(Copying contents of a table to another table)
Command:- Insert into….Select
Purpose:- To filter the data that is not required
Syntax:- Insert into <table name>Select <col name1>, <col name2>….
from <table name>;
Example:-
Insert into CSEA_Data101 Select roll_no,name from STUDENT where
roll_no=149;

SELECT COMMAND
Command:- (a) Selecting all rows and all columns
Purpose:- This command is used to view all the rows and columns of the
table created in the database.
Syntax:- Select * from <table name>;
Example:-
Select * from STUDENT;

SELECT COMMAND
(b) Selected rows and all columns using where clause
Purpose:- If the information of a particular student is to be retrieved from a
table, its retrieval must be based on a specific condition
Syntax:- Select * from <table name> where <condition>;
Example:-
Select * from STUDENT where roll_no=151;

ALIAS
Purpose:- SQL aliases are used to give a table, or a column in a table, a
temporary name.
ALIAS COLUMN SYNTAX
Syntax:- SELECT column_name AS alias_name
FROM table_name;
Example:-
SELECT CustomerID AS ID, CustomerName AS Customer
FROM Customers;

ALIAS TABLE SYNTAX
Syntax:- SELECT column_name(s) FROM table_name AS alias_name;
Example:-
SELECT o.OrderID, o.OrderDate, c.CustomerName
FROM Customers AS c, Orders AS o
WHERE c.CustomerName='Around the
Horn' AND c.CustomerID=o.CustomerID;

DELETE COMMAND
Purpose:- To delete the rows from the table that satisfies the condition
provided by its where clause and returns the number of records deleted.
Syntax:- Removal of all rows
Delete from <table name>;
Removal of Specific Row(s)
Delete from <table name> where <condition>;
Example:-
Delete from CSEA_Data101 where rollno=149;
Delete from CSEA_Data101;

DELETE & TRUNCATE
TRUNCATE
 TRUNCATE is a DDL command
 TRUNCATE is executed using a table lock and the whole table is locked to remove all
records.
 We cannot use the WHERE clause with TRUNCATE.
 TRUNCATE removes all rows from a table.
 Minimal logging in the transaction log, so it is faster performance-wise.
DELETE
 DELETE is a DML command.
 DELETE is executed using a row lock, each row in the table is locked for deletion.
 We can use where clause with DELETE to filter & delete specific records.
 The DELETE command is used to remove rows from a table based on WHERE
condition.
 It maintains the log, so it slower than TRUNCATE.

DROP COMMAND
1. The DROP command removes a table from the
database.
2. All the tables' rows, indexes, and privileges will also
be removed.
3. No DML triggers will be fired.
4. The operation cannot be rolled back.
5. DROP and TRUNCATE are DDL commands, whereas
DELETE is a DML command.
6. DELETE operations can be rolled back (undone),
while DROP and TRUNCATE operations cannot be
rolled back

Difference between DELETE, DROP and TRUNCATE
DELETE DROP TRUNCATE
1. It is a DML command. 1. It is a DDL command. 1. It is a DDL command.
2. It is used to delete rows or records
based on conditions specified in the
WHERE clause.
2. It is used to delete the entire table
along with its schema and structure
respectively.
2. It is used to delete the entire
records of a table without affecting
the schema of the table.
3. If the WHERE clause is not specified
with conditions it deletes all the
records of the table.
3. There is no WHERE clause. 3. There is no WHERE clause.
4. It is a DML command. As a result,
the operation can be rolled back.
4. It is a DDL command. As a result,
the changes cannot be rolled back or
undone.
4. It is a DDL command. As a result,
the changes cannot be rolled back or
undone.
5. It scans every row before deleting
making it slower and time-consuming.
5. It is faster and time-saving.
5. It is faster than DELETE in execution
because it does not scan every row
before deleting which makes it the
least time-consuming.
6. Syntax: DELETE FROM TABLE
Table_Name WHERE [CONDITIONS];
6. Syntax: DROP TABLE Table_Name;
6. Syntax: TRUNCATE
TABLE Table_Name;

UPDATE COMMAND
Purpose:- The Update statement updates columns in the existing table’s
rows with new values. The Set clause indicates which column data should be
modified and the new valued they should hold.
Syntax:-
Updating Specific Records
Update <table name> set <col name1>=<expression1>, <col
name2>=<expression2> where <condition>;
Updating All The Records
Update <table name> set <col name1>=<expression1>, <col
name2>=<expression2>;
Example:-
Update STUDENT set Branch=’ECE’ where roll_no=101;
Update STUDENT set Branch=’CSE’;

DATA CONTROL LANGUAGE (DCL)
This component of the SQL language is used to create privileges to allow
users access to, and manipulation of, the database. There are two main
commands:
GRANT  to grant a privilege to a user
REVOKE  to revoke (remove) a privilege from a user.

References
• OTHER REFRENCES
• ER Diagram: Entity Relationship Diagram Model | DBMS Example (guru99.com)
• ER Diagram Representation - Tutorialspoint
• Entity Relationship Diagram - ER Diagram in DBMS (beginnersbook.com)
• http://nptel.ac.in/courses/Webcourse-contents/IISc-
BANG/notused/IISc/New%20Rajaram%20pdfs/module8.pdf
• http://ecomputernotes.com/fundamental/what-is-a-database/type-of-data-models
• https://beginnersbook.com/2015/04/data-models-in-dbms/
• http://www.odbms.org/wp-
content/uploads/2013/11/Data_Modeling_ConcepttoDBMS.pdf
SUGGESTED BOOK REFERENCES
• Ramez Elmasri and Shamkant B. Navathe,“Fundamentals of Database System”, The Benjamin / Cummings Publishing Co.
• Korth and Silberschatz Abraham, “Database SystemConcepts”, McGraw Hall.

113
Database
Management
System
CO
Number
Title Level
Remember
queries
Understand
solutions.
Analysis and
application
this lecture

114
UNIT-I [10h]
UNIT-II [10h]

115
UNIT-III [10h]
Techniques.

116
Chapter 1.3
(Relational Algebra & Relational Calculus)
operators, Grouping and Ungrouping, Relational comparisons, Tuple Calculus, Domain
Calculus, Calculus vs Algebra, Computational capabilities.

Learning Objective
• To study relational algebra concepts, selection ,projection
,relational calculus which helps in understanding queries
• Fundamentals operations on Relational Algebra
• Tuple and Domain Relational Calculus

Learning Outcome
• Apply relational database theory, and be able to write
relational algebra expressions for queries
• Utilize the knowledge of basics of SQL and construct
queries using SQL
• Understanding relational algebra operators including
extended operators

Introduction
• Relational algebra
– Basic set of operations for the relational model
– More operational (procedural), very useful for representing
execution plans.
• Relational calculus
– Higher-level declarative language for specifying relational queries
– Lets users describe what they want, rather than how to compute
it: Non-operational, declarative.

Relational Algebra
• Relational algebra operations work on one or more relations to define
another relation without changing the original relations.
• Both operands and results are relations, so output from one operation
can become input to another operation.
• Allows expressions to be nested, just as in arithmetic. This property is
called closure.
• Five basic operations in relational algebra: Selection, Projection,
Cartesian product, Union and Set Difference.
• These perform most of the data retrieval operations needed.
• Also have Join, Intersection, and Division operations, which can be
expressed in terms of 5 basic operations.

Relational Algebra
• Basic operations:
– Selection ( ) Selects a subset of rows from relation.
– Projection ( ) Deletes unwanted columns from relation.
– Cross-product ( ) Allows us to combine two relations.
– Set-difference ( ) Tuples in reln. 1, but not in reln. 2.
– Union ( ) Tuples in reln. 1 and in reln. 2.
• Additional operations:
– Intersection, join, division, renaming: Not essential, but (very!) useful.

Relational Algebra Operations

124
Selection (or Restriction)
• σpredicate (R)
– Works on a single relation R and defines a relation that contains only
those tuples (rows) of R that satisfy the specified condition (predicate).
– Selects rows that satisfy selection condition.
– No duplicates in result!
– Schema of result identical to schema of input relation.
– Selection is distributive over binary operators
– Selection is commutative

Example - Selection Restriction)
• List all staff with a salary greater than £10,000.
σsalary > 10000 (Staff)

Projection
• Πcol1, . . . , coln(R)
– Works on a single relation R and defines a relation that contains a
vertical subset of R, extracting the values of specified attributes and
eliminating duplicates.
– Deletes attributes that are not in projection list.
– Schema of result contains exactly the fields in the projection list,
with the same names that they had in the input relation.
– Projection operator has to eliminate duplicates!
Note: real systems typically don’t do duplicate elimination unless the
user explicitly asks for it (by DISTINCT). Why not?

Example - Projection
• Produce a list of salaries for all staff, showing only staffNo, fName,
lName, and salary details.
ΠstaffNo, fName, lName, salary(Staff)

Union
• R ∪ S
– Union of two relations R and S defines a relation that contains all the
tuples of R, or S, or both R and S,
duplicate tuples being eliminated.
– R and S must be union-compatible.
• If R and S have I and J tuples, respectively, union is obtained by
concatenating them into one relation with a maximum of (I + J) tuples.

Example - UNION
• List all cities where there is either a branch office or a property for rent.
Πcity(Branch) ∪ Πcity(PropertyForRent)

Set Difference
• R – S
– Defines a relation consisting of the tuples that are in relation R,
but not in S.

Example - Set Difference
• List all cities where there is a branch office but no properties for rent.
Πcity(Branch) – Πcity(PropertyForRent)

Intersection
• R ∩ S
– Defines a relation consisting of the set of all tuples that are in both R
and S.
• Expressed using basic operations:
R ∩ S = R – (R – S)

Example - Intersection
• List all cities where there is both a branch office and at least one property
for rent.
Πcity(Branch) ∩ Πcity(PropertyForRent)

Cartesian product
• R X S
– Defines a relation that is the concatenation of every tuple of
relation “R with every tuple of relation S”

135
Example - Cartesian product
• List the names and comments of all clients who have viewed a property for
rent.
(ΠclientNo, fName, lName(Client)) X (ΠclientNo, propertyNo, comment (Viewing))
Pearson Education © 2009

136
Example - Cartesian product and
Selection
• Use selection operation to extract those tuples where Client.clientNo =
Viewing.clientNo.
sClient.clientNo = Viewing.clientNo((ÕclientNo, fName, lName(Client)) Χ (ÕclientNo,
propertyNo, comment(Viewing)))
● Cartesian product and Selection can be reduced to a single operation called a Join.

137
Join Operations
• JOINs can be used to combine tables
• Join is a derivative of Cartesian product.
• Equivalent to performing a Selection, using join predicate as selection
formula, over Cartesian product of the two operand relations.
• One of the most difficult operations to implement efficiently in an
RDBMS and one reason why RDBMSs have intrinsic performance
problems.

138
Join Operations
• Various forms of join operation
– JOIN (Inner Join) : Return rows when there is at least one match
in both tables
– LEFT JOIN(Left Outer Join): Return all rows from the left
table, even if there are no matches in the right table
– RIGHT JOIN(Right Outer Join): Return all rows from the right
table, even if there are no matches in the left table
– FULL JOIN: Return rows when there is a match in one of the
tables

SQL INNER JOIN Syntax
SELECT column_name(s) FROM table_name1 INNER JOIN table_name2
ON
table_name1.column_name=table_name2.column_name
INNER JOIN is the same as JOIN
The word "INNER" is optional

*
Example - Inner Join

Left Join

Example - Left Join

Right Join

Example – Right Join

Full Join

Example – Full Join

FAQ
1. How does Tuple-oriented relational calculus differ from domain-
oriented relational calculus?
2. Define Relational Algebra and Relational Calculus
3. What is degree of a Relation?
4. What is a Relation Schema and a Relation?
5. List various Operators used in Relational Algebra and Calculus
6. Solve the given by relational algebra. The Relations are :
• Emp(empno,ename,sal,job,comm,deptno)
• Dept (deptno,dname,dloc)
• Create a query to list unique jobs that are in deptno 30 and include the
location of department 30 in output

References
OTHER REFRENCES
• https://cs.uwaterloo.ca/~tozsu/courses/CS348/notes/4b-calculus-handout-notes.pdf
• http://www.ccs.neu.edu/home/kathleen/classes/cs3200/4-RAAndRC.pdf
• https://www2.cs.sfu.ca/CourseCentral/354/louie/Chap3_practice.pdf
• http://www.nyu.edu/classes/jcf/CSCI-GA.2433-
001_fa11/slides/session5/RelationalAlgebra-RelationalCalculus-SQL.pdf
• https://blog.inf.ed.ac.uk/da15/files/2015/01/inf1-da-15-t3.pdf
• DatabaseSystemConceptsbySudarshan,Korth(McGraw-HillEducation)
• FundamentalsofDatabaseSystemByElmasari&Navathe-PearsonEducation
• Ramez Elmasri and Shamkant B. Navathe,“Fundamentals of Database System”, The
Benjamin / Cummings Publishing Co.

150
Database
Management
System
CO
Number
Title Level
Remember
queries
Understand
solutions.
Analysis and
application
this lecture

151
UNIT-I [10h]
UNIT-II [10h]

152
UNIT-III [10h]
Techniques.

153
Chapter 3
(Relational Algebra & Relational Calculus)
operators, Grouping and Ungrouping, Relational comparisons, Tuple Calculus, Domain
Calculus, Calculus vs Algebra, Computational capabilities.

Relational Calculus
• There are two versions of the relational calculus:
– Tuple relational calculus (TRC)
– Domain relational calculus (DRC)
• The calculus is non-procedural (‘declarative’) compared to the relational algebra
• Calculus has variables, constants, comparison ops, logical connectives and
quantifiers.
– TRC: Variables range over (i.e., get bound to) tuples.
– DRC: Variables range over domain elements (= field values).
– Both TRC and DRC are simple subsets of first-order logic.
• Expressions in the calculus are called formulas. An answer tuple is essentially an
assignment of constants to variables that make the formula evaluate to true.

• Relational Calculus
• Relational Algebra is a PROCEDURAL LANGUAGE
⮚ we must explicitly provide a sequence of operations to
• generate a desired output result
• Relational Calculus is a DECLARATIVE LANGUAGE
⮚ we specify what to retrieve, not how to retrieve it

What is Relational Calculus?
• It is a formal language based upon predicate calculus
• It allows you to express the set of tuples you want from a
database using a formula
• Expressions in the calculus are called formula
• An answer tuple is essentially an assignment of constants to vari
ables that make the formula evaluate to true.

Declarative ~ Non-Procedural
Two variants of relational calculus are
• TUPLE Relational Calculus
• Domain Relational Calculus
• Calculus has variables, constants, comparison ops, logical
connectives and quantifiers.
• TRC: Variables range over (i.e., get bound to) tuples.
• DRC: Variables range over domain elements
(= field values)

RELATIONAL CALCULUS
• If a retrieval can be specified in the relational calculus, it
can be specified in the relational algebra, and vise versa
→expressive power of the languages is identical
• A query language L is Relationally complete if
L can express any query that can be expressed in the
relational calculus

Relational Calculus
• TRC and DRC are semantically similar
• In TRC, tuples share an equal status as variables, and field referencing
can be used to select tuple parts
• In DRC, formal variables are explicit

Tuple Relational Calculus
• Query: {T | P(T)}
– T is tuple variable
– P(T) is a formula that describes T
• Result, the set of all tuples t for which P(t) evaluates True.
– Find all sailors with a rating above 7.
–
• Atomic formula
–
– R.a op S.b , op is one of
– R.a op constant

Tuple Relational Calculus
• A logical language with variables ranging over tuples:
{ T | Cond }
– Return all tuples T that satisfy the condition Cond.
• { T | R(T) }: returns all tuples T such that T is a tuple in relation
R.
• { T.name | F ACULT Y (T) AND T.DeptId = ‘CS’ }.
returns the values of name field of all faculty tuples with the
value ’CS’ in their department id field.
– The variable T is said to be free since it is not bound by a
quantifier (for all, exists).
– The result of this statement is a relation (or a set of tuples) that
correspond to all possible ways to satisfy this statement.
– Find all possible instances of T that make this statement true.

TUPLE RELATIONAL CALCULUS
• Query: {T|P(T)}
• T is tuple variable
• P(T) is a formula that describes T
Result: the set of all tuples t for which P(t) evaluates Tr
ue.
⮚ Find all sailors with a rating above 7.

OPERATIONS in Tuple Relational Calculus
• ∧ - AND
• ∨ - OR
• ¬ - NOT
• ∃x – there exists x
• ∀x – for all x
Note: General power of 1st order predicate calculus – allow
more flexible expression formats

TUPLE RELATIONAL CALCULUS

JOINS IN THE TUPLE RELATIONAL CALCULUS

Examples
Consider relations for queries:
• Relation 1:

Relation 2:
Relation
3:

1. Find the loan number, branch, amount of loans of greater than or equal
to 10000 amount
{t| t ∈ loan ∧ t[amount]>=10000}
2. Find the loan number for each loan of an amount greater or equal to
10000.
{t| ∃ s ∈ loan(t[loan number] = s[loan number] ∧ s[amount]>=10000)}
3. Find the names of all customers who have a loan and an account at the
bank.
{t | ∃ s ∈ borrower( t[customer-name] = s[customer-name]) ∧ ∃ u ∈ depositor(
t[customer-name] = u[customer-name])}

4. Find the names of all customers having a loan at the
“ABC” branch.
{t | ∃ s ∈ borrower(t[customer-name] = s[customer-name]
∧ ∃ u ∈ loan(u[branch-name] = “ABC” ∧ u[loan-number] =
s[loan-number]))}

Domain Relational Calculus
• Query has the form:
❖ Answer includes all tuples that
make the formula be true.
Formula is recursively defined, starting with simple atomic formulas
(getting tuples from relations or making comparisons of values), and
building bigger and better formulas using the logical connectives.

• Query has the form:
{ <x1,x2….xn>| p(<x1,x2….xn>)}
• Domain Variable – ranges over the values in the domain of
some attribute or is a constant
• Example: If the domain variable x1 maps to attribute -
Name char(20) then x1 ranges over all strings that are 20
characters long
Not just the strings values in the relation’s attribute
• Answer includes all tuples that make the formula p() true.

DOMAIN RELATIONAL CALCULUS

DRC Formulas
• Atomic Formulas
1. <x1,x2,…xn>∈ Relation where Relation is a relation with n attributes
2. X operation Y
3. X operation constant
Where operation is an operator in the set { , = , ≤, ≥, ≠ }
• Recursive definition of a Formula:
1. An atomic formula
2. ¬p, p∧q, p∨q, where p and q are formulas
3. ∃X(p(X)), where variable X is free in p(X)
4. ∀X(p(X)), where variable X is free in p(X)
The use of quantifiers ∃X and ∀X is said to bind X
A variable that is not bound is free.

Quantifiers: ∀x and ∃x
• Variable x is said to be subordinate to the quantifier
You are restricting (or binding) the value of the variable x
to set S
• The set S is known as the range of the quantifier
• ∀x predicate true for all elements in set S
• ∃x predicate true for at least 1 element in set S

Examples
1. Find the loan number, branch, amount of loans of greater
than or equal to 100 amount.
{≺l, b, a≻ | ≺l, b, a≻ ∈ loan ∧ (a ≥ 100)}
2. Find the loan number for each loan of an amount greater
or equal to 150.
{≺l≻ | ∃ b, a (≺l, b, a≻ ∈ loan ∧ (a ≥ 150)}
3. Find the names of all customers having a loan at the
“Main” branch and find the loan amount .
{≺c, a≻ | ∃ l (≺c, l≻ ∈ borrower ∧ ∃ b (≺l, b, a≻ ∈ loan
∧ (b = “Main”)))}

Relational Calculus: Summary
• Relational calculus is non-operational
⮚ Users define queries in terms of what they want, not in
terms of how to compute it. (Declarativeness.)
• Algebra and safe calculus have the same expressive
power, leading to the notion of relational completeness.
• Relational calculus had big influence on the design of SQL
and Query-by-Example

Summary
• Relational algebra is more operational; useful as internal representation
for query evaluation plans.
• Relational calculus is non-operational, and users define queries in terms
of what they want, not in terms of how to compute it. (Declarativeness.)
• Algebra and safe calculus have same expressive power, leading to the
notion of relational completeness.

FAQ
1. How does Tuple-oriented relational calculus differ from
domain-oriented relational calculus?
2. Define Relational Algebra and Relational Calculus
3. What is degree of a Relation?
4. What is a Relation Schema and a Relation?
5. List various Operators used in Relational Algebra and
Calculus

References
OTHER REFRENCES
• https://cs.uwaterloo.ca/~tozsu/courses/CS348/notes/4b-calculus-handout-notes.pdf
• http://www.ccs.neu.edu/home/kathleen/classes/cs3200/4-RAAndRC.pdf
• https://www2.cs.sfu.ca/CourseCentral/354/louie/Chap3_practice.pdf
• http://www.nyu.edu/classes/jcf/CSCI-GA.2433-001_fa11/slides/session5/RelationalAlgebra-
RelationalCalculus-SQL.pdf
• https://blog.inf.ed.ac.uk/da15/files/2015/01/inf1-da-15-t3.pdf
• DatabaseSystemConceptsbySudarshan,Korth(McGraw-HillEducation)
• FundamentalsofDatabaseSystemByElmasari&Navathe-PearsonEducation
• Ramez Elmasri and Shamkant B. Navathe,“Fundamentals of Database System”, The
Benjamin / Cummings Publishing Co.

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