SlideShare a Scribd company logo
1 of 67
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Relational Database: Definitions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L1-1
Example Instance of Students Relation Slide No:L1-2 ,[object Object],[object Object],[object Object]
Relational Query Languages ,[object Object],[object Object],[object Object],[object Object],Slide No:L1-3
The SQL Query Language Slide No:L1-4 SELECT  * FROM   Students S WHERE   S.age=18 ,[object Object],SELECT   S.name, S.login
Querying Multiple Relations ,[object Object],Slide No:L1-5 SELECT  S.name, E.cid FROM   Students S, Enrolled E WHERE   S.sid=E.sid  AND  E.grade=“A” Given the following instances of Enrolled and Students: we get:
Creating Relations in SQL ,[object Object],[object Object],Slide No:L1-6 CREATE TABLE Students (sid:  CHAR(20) ,    name:  CHAR(20) ,    login:  CHAR(10),   age:  INTEGER ,   gpa:  REAL )  CREATE TABLE Enrolled (sid:  CHAR(20) ,    cid:  CHAR(20) ,    grade:  CHAR (2))
Destroying and Altering Relations ,[object Object],Slide No:L1-7 DROP   TABLE   Students  ,[object Object],ALTER   TABLE   Students  ADD   COLUMN   firstYear: integer
Adding and Deleting Tuples ,[object Object],Slide No:L1-8 INSERT INTO  Students (sid, name, login, age, gpa) VALUES   (53688, ‘Smith’, ‘smith@ee’, 18, 3.2) ,[object Object],DELETE   FROM  Students S WHERE  S.name = ‘Smith’
Integrity Constraints (ICs) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L1-9
Primary Key Constraints ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L1-10
Primary and Candidate Keys in SQL ,[object Object],Slide No:L1-11 CREATE TABLE Enrolled (sid CHAR(20) cid  CHAR(20), grade CHAR(2), PRIMARY KEY   (sid,cid)  ) ,[object Object],[object Object],CREATE TABLE Enrolled (sid CHAR(20) cid  CHAR(20), grade CHAR(2), PRIMARY KEY   (sid), UNIQUE  (cid, grade) )
Foreign Keys, Referential Integrity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L1-12
Foreign Keys in SQL ,[object Object],Slide No:L1-13 CREATE TABLE Enrolled (sid CHAR(20),  cid CHAR(20),  grade CHAR(2), PRIMARY KEY   (sid,cid), FOREIGN KEY   (sid)  REFERENCES   Students ) Enrolled Students
Enforcing Referential Integrity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L2-1
Referential Integrity in SQL ,[object Object],[object Object],[object Object],[object Object],Slide No:L2-2 CREATE TABLE  Enrolled (sid  CHAR (20), cid  CHAR(20) , grade  CHAR (2), PRIMARY KEY   (sid,cid), FOREIGN KEY   (sid) REFERENCES   Students ON DELETE CASCADE ON UPDATE SET  DEFAULT  )
Where do ICs Come From? ,[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L2-3
Logical DB Design: ER to Relational ,[object Object],Slide No:L3-1 CREATE TABLE  Employees  (ssn  CHAR (11), name  CHAR (20), lot  INTEGER , PRIMARY KEY   (ssn)) Employees ssn name lot
Relationship Sets to Tables ,[object Object],[object Object],[object Object],[object Object],Slide No:L3-2 CREATE TABLE  Works_In( ssn  CHAR (11), did  INTEGER , since  DATE , PRIMARY KEY  (ssn, did), FOREIGN KEY  (ssn)  REFERENCES  Employees, FOREIGN KEY  (did)  REFERENCES  Departments)
Review: Key Constraints ,[object Object],Slide No:L3-3 Translation to  relational model? Many-to-Many 1-to-1 1-to Many Many-to-1 budget did Departments dname since lot name ssn Manages Employees
Translating ER Diagrams with Key Constraints ,[object Object],[object Object],[object Object],[object Object],Slide No:L3-4 CREATE TABLE  Manages( ssn  CHAR(11) , did  INTEGER , since  DATE , PRIMARY KEY  (did), FOREIGN KEY  (ssn)  REFERENCES  Employees, FOREIGN KEY  (did)  REFERENCES  Departments) CREATE TABLE  Dept_Mgr( did  INTEGER, dname  CHAR(20), budget  REAL, ssn  CHAR(11) , since  DATE , PRIMARY KEY  (did), FOREIGN KEY  (ssn)  REFERENCES  Employees)
Review: Participation Constraints ,[object Object],[object Object],[object Object],Slide No:L3-5 lot name dname budget did since name dname budget did since Manages since Departments Employees ssn Works_In
Participation Constraints in SQL ,[object Object],Slide No:L3-6 CREATE TABLE  Dept_Mgr( did  INTEGER, dname  CHAR(20) , budget  REAL , ssn  CHAR(11)  NOT NULL , since  DATE , PRIMARY KEY  (did), FOREIGN KEY  (ssn)  REFERENCES  Employees, ON DELETE NO ACTION )
Review: Weak Entities ,[object Object],[object Object],[object Object],Slide No:L4-1 lot name age pname Dependents Employees ssn Policy cost
Translating Weak Entity Sets ,[object Object],[object Object],Slide No:L4-2 CREATE TABLE  Dep_Policy ( pname  CHAR(20) , age  INTEGER , cost  REAL , ssn  CHAR(11) NOT NULL , PRIMARY KEY  (pname, ssn), FOREIGN KEY  (ssn)  REFERENCES  Employees, ON DELETE CASCADE )
Review: ISA Hierarchies ,[object Object],[object Object],Slide No:L4-3 Contract_Emps name ssn Employees lot hourly_wages ISA Hourly_Emps contractid hours_worked ,[object Object],[object Object]
Translating ISA Hierarchies to Relations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L4-4
Review: Binary vs. Ternary Relationships ,[object Object],Slide No:L4-5 age pname Dependents Covers age pname Dependents Purchaser Bad design Better design name Employees ssn lot Policies policyid cost Beneficiary policyid cost Policies name Employees ssn lot
Binary vs. Ternary Relationships (Contd.) ,[object Object],[object Object],[object Object],Slide No:L4-6 CREATE TABLE  Policies ( policyid  INTEGER , cost  REAL , ssn  CHAR(11)  NOT NULL , PRIMARY KEY  (policyid). FOREIGN KEY  (ssn)  REFERENCES  Employees, ON DELETE CASCADE ) CREATE TABLE  Dependents   ( pname  CHAR(20) , age  INTEGER , policyid  INTEGER , PRIMARY KEY  (pname, policyid). FOREIGN KEY  (policyid)  REFERENCES  Policies, ON DELETE CASCADE )
Views ,[object Object],Slide No:L5-1 CREATE  VIEW   YoungActiveStudents (name, grade) AS   SELECT  S.name, E.grade FROM   Students S, Enrolled E WHERE   S.sid = E.sid and S.age<21 ,[object Object],[object Object],[object Object]
Views and Security ,[object Object],[object Object],Slide No:L5-2
View Definition ,[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L5-3
Example Queries ,[object Object],Slide No:L5-4 ,[object Object],create view  all_customer  as   ( select  branch_name, customer_name     from  depositor, account   where  depositor.account_number = account.account_number  ) union   ( select  branch_name, customer_name   from  borrower, loan   where  borrower.loan_number = loan.loan_number  ) select  customer_name from  all_customer where  branch_name =  'Perryridge'
Uses of Views ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L5-5
Processing of Views ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L5-6
View Expansion ,[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L5-7
With Clause ,[object Object],[object Object],Slide No:L5-8
Complex Queries using With Clause ,[object Object],Slide No:L5-9 with   branch_total  ( branch _ name ,  value )  as   select   branch _ name ,  sum  ( balance )   from   account   group   by   branch _ name   with   branch _ total _ avg  ( value )  as   select   avg  ( value )   from   branch _ total   select  branch _ name   from   branch _ total ,  branch _ total_avg    where   branch_total.value >= branch_total_avg.value ,[object Object],[object Object]
Update of a View ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L5-10
Formal Relational Query Languages ,[object Object],[object Object],[object Object],Slide No:L6-1
Preliminaries ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L6-2
Example Instances ,[object Object],[object Object],Slide No:L6-3 R1 S1 S2
Relational Algebra ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L6-4
Projection ,[object Object],[object Object],[object Object],[object Object],Slide No:L6-5
Selection ,[object Object],[object Object],[object Object],[object Object],Slide No:L6-6
Union, Intersection, Set-Difference ,[object Object],[object Object],[object Object],[object Object],Slide No:L6-7
Cross-Product ,[object Object],[object Object],[object Object],Slide No:L6-8 ,[object Object]
Joins ,[object Object],[object Object],[object Object],[object Object],Slide No:L6-9
Joins ,[object Object],[object Object],[object Object],Slide No:L6-10
Division ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L6-11
Examples of Division A/B Slide No:L6-12 A B1 B2 B3 A/B1 A/B2 A/B3
Expressing A/B Using Basic Operators ,[object Object],[object Object],[object Object],[object Object],Slide No:L6-13 ,[object Object],A/B: all disqualified tuples
Find names of sailors who’ve reserved boat #103 ,[object Object],Slide No:L6-14 ,[object Object],[object Object]
Find names of sailors who’ve reserved a red boat ,[object Object],Slide No:L6-15 A query optimizer can find this, given the first solution! ,[object Object]
Find sailors who’ve reserved a red or a green boat ,[object Object],Slide No:L6-16 ,[object Object],[object Object]
Find sailors who’ve reserved a red  and  a green boat ,[object Object],Slide No:L6-17
Relational Calculus ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L7-1
Domain Relational Calculus ,[object Object],Slide No:L7-2 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
DRC Formulas ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L7-3
Free and Bound Variables ,[object Object],[object Object],[object Object],Slide No:L8-1 ,[object Object]
Find all sailors with a rating above 7 ,[object Object],[object Object],[object Object],[object Object],[object Object],Slide No:L8-2
Find sailors rated > 7 who have reserved boat #103 ,[object Object],[object Object],Slide No:L8-3
Find sailors rated > 7 who’ve reserved a red boat ,[object Object],[object Object],Slide No:L8-4
Find sailors who’ve reserved all boats ,[object Object],Slide No:L8-5
Find sailors who’ve reserved all boats (again!) ,[object Object],[object Object],Slide No:L8-6 .....
Unsafe Queries,  Expressive Power ,[object Object],[object Object],[object Object],[object Object],Slide No:L8-7

More Related Content

What's hot

Chapter 6 relational data model and relational
Chapter  6  relational data model and relationalChapter  6  relational data model and relational
Chapter 6 relational data model and relationalJafar Nesargi
 
Relational database intro for marketers
Relational database intro for marketersRelational database intro for marketers
Relational database intro for marketersSteve Finlay
 
Chapter 2 Relational Data Model-part 2
Chapter 2 Relational Data Model-part 2Chapter 2 Relational Data Model-part 2
Chapter 2 Relational Data Model-part 2Eddyzulham Mahluzydde
 
The relational data model part[1]
The relational data model part[1]The relational data model part[1]
The relational data model part[1]Bashir Rezaie
 
Chapter-6 Relational Algebra
Chapter-6 Relational AlgebraChapter-6 Relational Algebra
Chapter-6 Relational AlgebraKunal Anand
 
Fundamentals of database system - Relational data model and relational datab...
Fundamentals of database system  - Relational data model and relational datab...Fundamentals of database system  - Relational data model and relational datab...
Fundamentals of database system - Relational data model and relational datab...Mustafa Kamel Mohammadi
 
Chapter-5 The Relational Data Model
Chapter-5 The Relational Data ModelChapter-5 The Relational Data Model
Chapter-5 The Relational Data ModelKunal Anand
 
Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013Prosanta Ghosh
 
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...Raj vardhan
 
Relational Data Model Introduction
Relational Data Model IntroductionRelational Data Model Introduction
Relational Data Model IntroductionNishant Munjal
 
Chapter-9 Normalization
Chapter-9 NormalizationChapter-9 Normalization
Chapter-9 NormalizationKunal Anand
 
Functional dependencies and normalization for relational databases
Functional dependencies and normalization for relational databasesFunctional dependencies and normalization for relational databases
Functional dependencies and normalization for relational databasesJafar Nesargi
 
Database : Relational Data Model
Database : Relational Data ModelDatabase : Relational Data Model
Database : Relational Data ModelSmriti Jain
 
Chapter-8 Relational Database Design
Chapter-8 Relational Database DesignChapter-8 Relational Database Design
Chapter-8 Relational Database DesignKunal Anand
 
Relational Database Fundamentals
Relational Database FundamentalsRelational Database Fundamentals
Relational Database FundamentalsKHALID C
 

What's hot (20)

Chapter 6 relational data model and relational
Chapter  6  relational data model and relationalChapter  6  relational data model and relational
Chapter 6 relational data model and relational
 
Relational database intro for marketers
Relational database intro for marketersRelational database intro for marketers
Relational database intro for marketers
 
Chapter 2 Relational Data Model-part 2
Chapter 2 Relational Data Model-part 2Chapter 2 Relational Data Model-part 2
Chapter 2 Relational Data Model-part 2
 
The relational data model part[1]
The relational data model part[1]The relational data model part[1]
The relational data model part[1]
 
Dbms relational data model and sql queries
Dbms relational data model and sql queries Dbms relational data model and sql queries
Dbms relational data model and sql queries
 
Chapter-6 Relational Algebra
Chapter-6 Relational AlgebraChapter-6 Relational Algebra
Chapter-6 Relational Algebra
 
Fundamentals of database system - Relational data model and relational datab...
Fundamentals of database system  - Relational data model and relational datab...Fundamentals of database system  - Relational data model and relational datab...
Fundamentals of database system - Relational data model and relational datab...
 
Chapter3
Chapter3Chapter3
Chapter3
 
Chapter-5 The Relational Data Model
Chapter-5 The Relational Data ModelChapter-5 The Relational Data Model
Chapter-5 The Relational Data Model
 
Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013Dbms ii mca-ch4-relational model-2013
Dbms ii mca-ch4-relational model-2013
 
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...
 
Relational Data Model Introduction
Relational Data Model IntroductionRelational Data Model Introduction
Relational Data Model Introduction
 
Chapter-9 Normalization
Chapter-9 NormalizationChapter-9 Normalization
Chapter-9 Normalization
 
Functional dependencies and normalization for relational databases
Functional dependencies and normalization for relational databasesFunctional dependencies and normalization for relational databases
Functional dependencies and normalization for relational databases
 
Database : Relational Data Model
Database : Relational Data ModelDatabase : Relational Data Model
Database : Relational Data Model
 
Lesson03 the relational model
Lesson03 the relational modelLesson03 the relational model
Lesson03 the relational model
 
Relational model
Relational modelRelational model
Relational model
 
Chapter-8 Relational Database Design
Chapter-8 Relational Database DesignChapter-8 Relational Database Design
Chapter-8 Relational Database Design
 
Relational model
Relational modelRelational model
Relational model
 
Relational Database Fundamentals
Relational Database FundamentalsRelational Database Fundamentals
Relational Database Fundamentals
 

Viewers also liked (6)

Normalization
NormalizationNormalization
Normalization
 
Database anomalies
Database anomaliesDatabase anomalies
Database anomalies
 
Database Concept - Normalization (1NF, 2NF, 3NF)
Database Concept - Normalization (1NF, 2NF, 3NF)Database Concept - Normalization (1NF, 2NF, 3NF)
Database Concept - Normalization (1NF, 2NF, 3NF)
 
Anomalies in database
Anomalies in databaseAnomalies in database
Anomalies in database
 
Database design & Normalization (1NF, 2NF, 3NF)
Database design & Normalization (1NF, 2NF, 3NF)Database design & Normalization (1NF, 2NF, 3NF)
Database design & Normalization (1NF, 2NF, 3NF)
 
DBMS - Normalization
DBMS - NormalizationDBMS - Normalization
DBMS - Normalization
 

Similar to Unit03 dbms

Eer >r.model
Eer >r.modelEer >r.model
Eer >r.modellavya3
 
Ch3_Rel_Model-95.ppt
Ch3_Rel_Model-95.pptCh3_Rel_Model-95.ppt
Ch3_Rel_Model-95.pptAtharvaBagul2
 
4_RelationalDataModelAndRelationalMapping.pdf
4_RelationalDataModelAndRelationalMapping.pdf4_RelationalDataModelAndRelationalMapping.pdf
4_RelationalDataModelAndRelationalMapping.pdfLPhct2
 
Preparing for BIT – IT2301 Database Management Systems 2001d
Preparing for BIT – IT2301 Database Management Systems 2001dPreparing for BIT – IT2301 Database Management Systems 2001d
Preparing for BIT – IT2301 Database Management Systems 2001dGihan Wikramanayake
 
Mca ii-dbms- u-iii-sql concepts
Mca ii-dbms- u-iii-sql conceptsMca ii-dbms- u-iii-sql concepts
Mca ii-dbms- u-iii-sql conceptsRai University
 
L1 Intro to Relational DBMS LP.pdfIntro to Relational .docx
L1 Intro to Relational DBMS LP.pdfIntro to Relational .docxL1 Intro to Relational DBMS LP.pdfIntro to Relational .docx
L1 Intro to Relational DBMS LP.pdfIntro to Relational .docxDIPESH30
 
Introduction to SQL
Introduction to SQLIntroduction to SQL
Introduction to SQLDHAAROUN
 

Similar to Unit03 dbms (20)

Eer >r.model
Eer >r.modelEer >r.model
Eer >r.model
 
Unit 03 dbms
Unit 03 dbmsUnit 03 dbms
Unit 03 dbms
 
Ch3_Rel_Model-95.ppt
Ch3_Rel_Model-95.pptCh3_Rel_Model-95.ppt
Ch3_Rel_Model-95.ppt
 
uniT 4 (1).pptx
uniT 4 (1).pptxuniT 4 (1).pptx
uniT 4 (1).pptx
 
DBMS-Unit-2.pptx
DBMS-Unit-2.pptxDBMS-Unit-2.pptx
DBMS-Unit-2.pptx
 
Keys.ppt
Keys.pptKeys.ppt
Keys.ppt
 
4_RelationalDataModelAndRelationalMapping.pdf
4_RelationalDataModelAndRelationalMapping.pdf4_RelationalDataModelAndRelationalMapping.pdf
4_RelationalDataModelAndRelationalMapping.pdf
 
2 rel-algebra
2 rel-algebra2 rel-algebra
2 rel-algebra
 
Preparing for BIT – IT2301 Database Management Systems 2001d
Preparing for BIT – IT2301 Database Management Systems 2001dPreparing for BIT – IT2301 Database Management Systems 2001d
Preparing for BIT – IT2301 Database Management Systems 2001d
 
RDBMS
RDBMSRDBMS
RDBMS
 
ch3.ppt
ch3.pptch3.ppt
ch3.ppt
 
NMEC RD_UNIT 1.ppt
NMEC RD_UNIT 1.pptNMEC RD_UNIT 1.ppt
NMEC RD_UNIT 1.ppt
 
Mca ii-dbms- u-iii-sql concepts
Mca ii-dbms- u-iii-sql conceptsMca ii-dbms- u-iii-sql concepts
Mca ii-dbms- u-iii-sql concepts
 
L1 Intro to Relational DBMS LP.pdfIntro to Relational .docx
L1 Intro to Relational DBMS LP.pdfIntro to Relational .docxL1 Intro to Relational DBMS LP.pdfIntro to Relational .docx
L1 Intro to Relational DBMS LP.pdfIntro to Relational .docx
 
PPT
PPTPPT
PPT
 
Unit 04 dbms
Unit 04 dbmsUnit 04 dbms
Unit 04 dbms
 
Sql (DBMS)
Sql (DBMS)Sql (DBMS)
Sql (DBMS)
 
ch3.ppt
ch3.pptch3.ppt
ch3.ppt
 
Introduction to SQL
Introduction to SQLIntroduction to SQL
Introduction to SQL
 
ch3.ppt
ch3.pptch3.ppt
ch3.ppt
 

Recently uploaded

Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Farhan Tariq
 
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...Alkin Tezuysal
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotesMuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotesManik S Magar
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPathCommunity
 
Emixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native developmentEmixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native developmentPim van der Noll
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationKnoldus Inc.
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfNeo4j
 
QCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architecturesQCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architecturesBernd Ruecker
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxLoriGlavin3
 
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Nikki Chapple
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesThousandEyes
 
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better StrongerModern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better Strongerpanagenda
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Hiroshi SHIBATA
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
Generative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptxGenerative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptxfnnc6jmgwh
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxLoriGlavin3
 
Potential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsPotential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsRavi Sanghani
 

Recently uploaded (20)

Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...
 
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
Unleashing Real-time Insights with ClickHouse_ Navigating the Landscape in 20...
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotesMuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
MuleSoft Online Meetup Group - B2B Crash Course: Release SparkNotes
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to Hero
 
Emixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native developmentEmixa Mendix Meetup 11 April 2024 about Mendix Native development
Emixa Mendix Meetup 11 April 2024 about Mendix Native development
 
Data governance with Unity Catalog Presentation
Data governance with Unity Catalog PresentationData governance with Unity Catalog Presentation
Data governance with Unity Catalog Presentation
 
Connecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdfConnecting the Dots for Information Discovery.pdf
Connecting the Dots for Information Discovery.pdf
 
QCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architecturesQCon London: Mastering long-running processes in modern architectures
QCon London: Mastering long-running processes in modern architectures
 
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptxThe Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
The Role of FIDO in a Cyber Secure Netherlands: FIDO Paris Seminar.pptx
 
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
Microsoft 365 Copilot: How to boost your productivity with AI – Part one: Ado...
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
 
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better StrongerModern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
Modern Roaming for Notes and Nomad – Cheaper Faster Better Stronger
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
Generative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptxGenerative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptx
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
 
Potential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsPotential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and Insights
 

Unit03 dbms

  • 1.
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44.
  • 45.
  • 46.
  • 47.
  • 48.
  • 49.
  • 50.
  • 51.
  • 52. Examples of Division A/B Slide No:L6-12 A B1 B2 B3 A/B1 A/B2 A/B3
  • 53.
  • 54.
  • 55.
  • 56.
  • 57.
  • 58.
  • 59.
  • 60.
  • 61.
  • 62.
  • 63.
  • 64.
  • 65.
  • 66.
  • 67.

Editor's Notes

  1. 3
  2. 4
  3. 9
  4. 15
  5. 16
  6. 10
  7. 5
  8. 6
  9. 6
  10. 7
  11. 7
  12. 13
  13. 14
  14. 3 The slides for this text are organized into several modules. Each lecture contains about enough material for a 1.25 hour class period. (The time estimate is very approximate--it will vary with the instructor, and lectures also differ in length; so use this as a rough guideline.) This covers Lectures 1 and 2 (of 6) in Module (5). Module (1): Introduction (DBMS, Relational Model) Module (2): Storage and File Organizations (Disks, Buffering, Indexes) Module (3): Database Concepts (Relational Queries, DDL/ICs, Views and Security) Module (4): Relational Implementation (Query Evaluation, Optimization) Module (5): Database Design (ER Model, Normalization, Physical Design, Tuning) Module (6): Transaction Processing (Concurrency Control, Recovery) Module (7): Advanced Topics
  15. 5
  16. 6
  17. 7
  18. 8
  19. 9
  20. 10
  21. 11
  22. 12
  23. 13
  24. 7
  25. 8
  26. 18
  27. 22
  28. 4
  29. 5
  30. 6
  31. 7
  32. 8
  33. 9
  34. 10
  35. 11
  36. 12
  37. 13
  38. 14
  39. 15
  40. 16
  41. 17
  42. 18
  43. 19