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DataBase Technology
by
Dr.S.Sridhar, Ph.D.(JNUD),
RACI(Paris, NICE), RMR(USA), RZFM(Germany)
DIRECTOR
ARUNAI ENGINEERING
COLLEGE
TIRUVANNAMALAI
Lecture by
Prof.Dr.S.Sridhar
1
DBMS CONCEPTS
Data
Base
Management
Systems
•
•
•
•
•
•
•
•
•
•
•
Examples of Databases
Files & DB – Systems
Advantages of DBMS
Attributes / Entities
Normalization in RDBMS
RDBMS & Examples
SQL in DB & Examples
Entity-relationship model
3NF
Students/s DB – Case Study
Data Base Security / Backups
Lecture by
Prof.Dr.S.Sridhar
2
• What’s Database System ?
- It is nothing but a computerized
record keeping system.
- The DB itself can be regarded as
electronic filing cabinet.
- It is a collection of files.
The user of the system will have the
following facilities :
• Adding New, empty files to the DB.
• Inserting new data into existing
files.
• Retrieving data from existing files.
• Deleting data from existing files.
• Removing existing files, empty or
otherwise, from the DB
Data base is a collection of files.
Data base is a collection of records.
Data base is a collection of fields.
Lecture by
Prof.Dr.S.Sridhar
3
BI
N
WINE
PRODUCER
YEAR
BOTTLE
S
REA
DY
2
Chardonnary
Buena Vista
1992
1
1994
3
Chardonnary
Geyser Peak
1992
5
1994
6
Chardonnary
Stonestreet
1991
4
1993
12
Jo.Riesling
Jekel
1993
1
1994
21
Fune ‘ Blanc
Ch.St.Jean
1992
4
1994
22
Fune ‘ Blanc
Geyser Peak
1991
2
1993
30
Cab.Saurigno
n
Jekel
1986
12
1995
43
Cab.Saurigno
n
Jekel
1990
2
1993
45
Pinot Noir
Buena Vista
1989
9
1998
50
Pinrot Noir
Buena Vista
1990
2
1998
• The above file is referred as ‘Table’ in RDBMS –
Sense.
• Call this table as “CELLAR”
• This contains many records.
• Each record has fields.
• Here
BI WIN PRODUC YEA
• is a record
N E
ER
R
• The values inside the table
Lecture by
are called “ Field values”Prof.Dr.S.Sridhar
BOTTLE
S
READ
Y
4
Fields
Retrieve Data (Query Language)
SELECT WINE, BIN, PRODUCER
FROM CELLAR
WHERE READY = 1995 ;
RESULT
WINE
Cab.Saurig
non
BIN
30
PRODUCER
JEKEL
is the command used to Retrive
from which table ( file )
Condition
INSERT:
INSERT
INTO CELLAR ( BIN, WINE, PRODUCER )
VALUES ( 53, ‘Pinot Noir’, ‘Saintsbury’);
UPDATE:
UPDATE CELLAR
SET BOTTLES = 4
WHERE BIN = 3; Lecture by
5
Prof.Dr.S.Sridhar
DELETE
DELETE
FROM CELLAR
WHERE BIN = 2;
Thus, the commands like, SELECT, INSERT,
UPDATE and DELETE are actually the
examples of Database Query Language.
SQL – Structured Query Language
Remarks :
- One should be very careful.
Whenever DELETE or
UPDATE
operations are done
in the DB.
Here,
- Retrieving any amount of fields for a
particular record is done .
- Inserting into file for a particular
field(s) with values is done.
- Updating is for a particular field in a
record is done.
- Deleting is done for a record under a
matching condition.
Lecture by
Prof.Dr.S.Sridhar
6
(DBMS)
Data Base Management System
Data Base
Application
Programs
END
USERS
Major Components:
* Data
* Hardware
Simplified View
* Software
of Data base System
* Users
An Overview of Database Management
Lecture by
Prof.Dr.S.Sridhar
7
Examples of Data Bases:
 Financial Database
 Personnel Database ( Employee)
 Payroll Database
 Accounting Database
 Inventory Database
 Management Information Database
 Library Database
and so on.
Examples of DBMS (Data Base Management
System)
 ORACLE
 INFORMIX
 INGRESS
 SYBASE
and so on.
What ‘s Data ?
It is the meaning full information stored in
computer system.
Two Kinds
 Integrated
 Shared
Integrated, means that the Database can be thought
of as a unification of several otherwise distinct
data files, with any redundancy among those files
wholly or partially.
Lecture by
Prof.Dr.S.Sridhar
8
Example
A Database containing both the files.
EMPLOYEE
IDNO
Name
Address
Department
Salaries
Phone No.
Permanent Address
and a training file.
TRAINING
IDNO
Course a Headed
Course Details
Course Fees
Location of Course
Feedback
Grade Offered
Shared Database means that individual pieces of data in
the database can be shared by several different users.
For example from the file ‘EMPLOYEE’,
The general details can be utilised by Personnel
department.
The salary details may be utilized by Financial
department. All done in shared manner.
and so on.
Lecture by
Prof.Dr.S.Sridhar
9
Hardware Consisting of
 Secondary storage volumes that are used to
hold the stored data with associated I/O
devices(Disk drives etc), Devices Controllers,
I/O channels,etc.
 The Processors and associated main memory
that are used to support the execution of the
Database system software.
Software Consisting of
 Database Manager (DB Manager) or more
commonly used term as ‘DBMS’, Data Base
Management System.
 Additional utilities like Application
development tools, design aids, report writers
and so on.
Example: Oracle, Informix, Sybase,etc.
Users
 Application Programmers, who are
responsible for writing programs to access the
Database for Insert, Update, Delete, Query,
Reports etc.
 End users who are really accessing the
database for queries / data entry / report
generation etc.
Lecture by
Prof.Dr.S.Sridhar
10
What is Database ?
 It is a collection of ‘Persistent data’ that is used by
the application systems of some given enterprise.
 Input data : refers the information entered into the
systems for the very first time ( typically from a
terminal or workstation). It may be part of
persistent data but it is not initially part of the
databases
 Output Data : refers for messages and results
coming out from the system ( typically printed or
displayed on a screen). Again such information is
derived from persistent data but it is not itself
considered to the part of the database.
Enterprise (Egs)
************
 A Manufacturing
Company
 A Bank
 A Hospital
 A University
 A govt. Dept.
Persistent Data (Egs)
****************
* Product Data
* Account Data
* Patient Data
Lecture by
Prof.Dr.S.Sridhar
11
Advantages of Databases
 Compactness ( No read for Voluminous papers)
 Speed ( for retrieval of Queries / Reports etc)
 Currency (Accurate, up-to-date information is
available on demand anytime )
 Centralized control of data.
The foregoing benefits apply even more force in
multi – user environment, of course, where the
database is likely to be much larger and much
more complex then in the single-user-case.







Redundancy of data can be avoided.
In consistency can be avoided to some extent.
The data can be shared by many users.
Standards can be enforced.
Security restrictions can be applied.
Integrity can be maintained.
Conflicting requirement can be balanced.
Lecture by
Prof.Dr.S.Sridhar
12
RDBMS (Relational Data Base Mgmt. System)
Relational Systems are such that
1. The data perceived by users as tables.
2. The operators are at users’ disposal.(eg) Data
retrieval – are operators that qurerate new tables
from old and those operators include atleast
‘SELECT’, PROJECT and JOIN.
EXAMPLE :
DEPT
DEPT#
DNAME
BUDGET
D1
D2
D3
Marketing
Development
Research
10M
12M
5M
EMP
EMP ENAME
#
DEPT
Salary
E1
E2
E3
E4
D1
D1
D2
D2
40k
25k
42k
35k
John
Marsal
Lemark
Cheng
Lecture by
Prof.Dr.S.Sridhar
13
SELECT – Operation extracts specified rows from a
table.
PROJECT - Operation extracts specified columns
from a table
JOIN
- Operation joins together two tables on
the basis of common values in a
common column.
Apply the above operations on DEPT & EMP Tables
SELECT DEPTs WHERE BUDGET > 8M
Result
DEPT# DNAME
BUDGET
(Specified Rows)
D1
D2
Marketing
Development
10M
12M
PROJECT DEPTs OVER DEPT#, BUDGET
DEPT# BUDGET
Result
(Specified Columns)
D1
10M
D2
D3
JOIN DEPTs and EMPs OVER DEPT#
Result
DEP DNAME
BUD
Common
T#
GET
Rows
D1
Marketing
10M
Common
Marketing
10M
Columns D1
D2
D2
Development 12M
Development
Lecture by12M
Prof.Dr.S.Sridhar
12M
5M
EM ENAM
P# E
E1
E2
E3
E4
SAL
John
40K
Marsal 25K
Lemark 42K
Cherq 14 35K
Concept
ENTITY
Entity – Attributes –Relationship models
Information
Examples
Definition
A Distinguishable
object
PROPERTY
A piece of information
to describe an entity
RELATIONSHIP An entity that serves to
interconnect 2 or more
entities
- Supplier
- Part
- Person
- Purchase Order
and so on
- Supplier number
- Shipment Qty
- Person height
- P.O.data
etc.
- Shipment
(Supplier-part)
- Assignment
(Emp-Dept.)
Here Note
1) Shipment is RELATIONSHIP between supplier and part.
R
Supplier
R
Part
Similarly for Assignment.
Lecture by
Prof.Dr.S.Sridhar
15
Department
Dept-Emp
Emp
Employee
Ename
Emp-Dep
First
MN
Salary
Last
Dependent
Entity / Relationship diagram (Example)
-----*---------*----------*--------*---------*
Entities
: Department, Employee, Dependent
Relations
: Dept-Emp, Emp-dep
Attributes
: ( to employee)
Emp#, Ename,Salary
First
MN
Last
Lecture by
(GroupProf.Dr.S.Sridhar
item)
16
Properties:
Entities have properties : (Known as
attributes). Take the case of Employee whose
properties are Emp#, Ename and Salary. (all
these are attributes).
Simple a Composite:
Emp# is simple
But Ename contains First, MN and Last,
three simple items groped together to address
Ename. Such type of attributes are ‘Composite’.
Key :
It is one of the uniquely defined attributes.
For eg. Emp# is unique and that is called ‘key’ to
access the other properties of the entity employee,
like Ename and Salary.
Emp#
Ename Salary
Key
Lecture by
Prof.Dr.S.Sridhar
17
Types of Relations
1–1
(One to One)
1–M
(One to Many)
M–1
(Many to One)
M – M ) (Many to Many)
Examples ( 1-1)
For every employee there is only one seat
R
Emp
Seat
(1-1)
In an organization.
(1-M)
R
Customer1
;
.
;
Supplier
Customer-m
(M-1)
R
Student1
:
:
;
Teacher
Student-m
(M – M)
Suplier
1…….m
Lecture by
Prof.Dr.S.Sridhar
Customer1
1………m
18
Many Examples of Attributes / Entities & Relations
Example 1:
Book –Student
BOOK-STD
R>
R
Student
Book
R<
STD -BOOK
Entities : Book, Student
Relation : BOOK-STD and STD-BOOK
Attributes of Book
 Author
 Title
 Publisher
 Year
 ISBN Number
 Number of pages
 Price
 Printer
 Location of printing
 Edition-Nature
 Remarks
Attributes of Student
 RollNo
 ExamNo
 Name
 Class
 Address
 Phone No
 Remarks
Lecture by
Prof.Dr.S.Sridhar
19
Example 2
(R)
Part-Sup
(R)
Part
Entities
Relations
Supplier
Sub-part
(R)
: Part, Supplier
: Part-Sup and Sub-part
Attributes of part
Supplier








PartNo
Description
Qty
Unit price
Opening balance
Parts-new
Net balance
Remarks
Attributes of
 Supplier code
 Supplier address
 Supplier phone
 Supplier location
 Delivery time
 Address demand
 Warranty Period
 Remarks
Lecture by
Prof.Dr.S.Sridhar
20
Example 3:
Student
Entities
Relations
Stud-fac
R
R
R
Fac-stud
Faculty
: Student and Faculty
: Stud-fac and Fac-stud
Attributes of Student
 RollNo
 ExamNo
 Name
Handling
 Class
 Address
 PhoneNo
 Faculty Division
 Remarks
Attributes of Faculty
 Facuty ID
 Name
 Classes
 Qualification
 Designation
 Address
 Phone No
 Students Related for
Advising
Lecture by
Prof.Dr.S.Sridhar
21
NORMALIZATION in RDBMS
The logical design considered are:
S ( S#, SNAME, STATUS, CITY)
PRIMARY KEY ( S#)
P (P#, PNAME,COLOR, WEIGHT, CITY)
PRIMARY KEY (P#)
SP (S#, p#,QTY)
PRIMARY KEY (S#, P#)
FOREIGN KEY ( S#) REFERENCE S
FOREIGN KEY (P#) REFERENCE P
SCP (Relation) Table
S#
CITY
P#
QTY
S1
S1
S1
S1
S1
S1
S2
S2
S3
S4
S4
S4
London
London
London
London
London
London
Paris
Paris
Paris
London
London
London
P1
P2
P3
P4
P5
P6
P1
P2
P2
P2
P4
Lecture by
Prof.Dr.S.Sridhar
P5
300
200
400
200
100
100
300
400
200
200
300
400
22
From the table we find ‘Redundancy’ of data. So a
good design principle is “ One fact in one place”
((ie) avoid redundancy). How to do this ? That
process is known as “ Normalization”. There are
3NF (Normal forms – NF).
Namely
First NF (1NF)
Second NF (2NF)
Third NF (3NF)
1NF:
Every Normalized relation is in 1NF if and only
if, if satisfied the condition that it contains scalar
values ONLY.
Example
FIRST (S#, STATUS, CITY, P#, QTY)
PRIMARY KEY (S#, P#)
Functional Dependencies in relation FIRST
S#
CITY
QTY
P#
STATUS
Lecture by
Prof.Dr.S.Sridhar
23
Sample Tabulation of FIRST
S#
STATUS
S1
S1
S1
S1
S1
S1
S2
S2
S3
S4
S4
S4
20
20
20
20
20
20
10
10
10
20
20
20
CITY
London
London
London
London
London
London
Paris
Paris
Paris
London
London
London
P#
P1
P2
P3
P4
P5
P6
P1
P2
P2
P2
P4
P5
QTY
300
200
400
200
100
100
300
400
200
200
300
400
Now problems, We face with
 INSERT
 DELETE
 UPDATE
Lecture by
Prof.Dr.S.Sridhar
24
Problems with
INSERT
- For examples, while inserting S5 after S! or S2
or S3 or S4, Confusion arises, Where to insert ?!
- Insert a status after 20 – problem !
- Insert a city after LONDON – problem !
- Insert P# after P2 – Problem !
DELETE
While deleting some record,
One should be more careful.
Now delete a record corresponding to S# = 1.
This will delete all records corresponding to S# =
1, whereas user may NOT mean this !
Similarly,
UPDATE :
Update city for S# = 2
This will update all city values, corresponding to
S# = 2, whereas user does not mean this !
Lecture by
Prof.Dr.S.Sridhar
25
Second Normal Form :
A relation is in 2NF if and only if is in !NF and
every non-key attribute is irreducibly dependent
on the primary key.
Example
SECOND (S#, STATUS, CITY)
and SP(S#, P#, OTY)
CITY
S#
QTY
S#
STATUS
P#
Functional Dependencies in relation
SECOND AND SP
S#
P#
QTY
S1
S1
S1
S1
20
London
S1
S2
10
Paris
S1
S1
S3
10
Paris
S2
S4
20
London
S2
S5
30
Athens
S3
S4
SAMPLE TABULATION
OF
Lecture by S4
SECOND AND SP Prof.Dr.S.SridharS4
P1
P2
P3
P4
P5
P6
P1
P2
P2
P2
P4
P5
300
200
400
200
100
100
300
400
200
200
300
400
SECOND
S# Status
City
26
INSERT :
Eventhough S5 is not supplying any
parts, we can insert the information that S5 is
located in Athens, in SECOND.
DELETE :
While deleting the shipment
connecting S3 and P2 in SP, we do NOT loose
information that S3 is located in PARIS.
UPDATE :
In the revised structure, the city for
given supplier appears once not many times.
Thus S# CITY redundancy is eliminated. For
example we can change for S1, the city as
Amsterdam from London. This way updation is
also possible in 2NF.
Third Normal Form (3NF):
A relation is in 3NF if it is in 2NF
and every non-key attribute is non-transitively
dependent on the primary key.
This increases the data
independance,.
Lecture by
Prof.Dr.S.Sridhar
27
Example:
Key
S#
CITY
S1
S2
S3
S4
S5
London
Paris
Paris
London
Athens
Key
CITY
STATUS
Anthen
London
Paris
Rome
30
20
10
50
Sample Tabulation of SC and CS
The above relation SC and CS are in 3NF.
Whereas, SECOND is not in 3NF.
SECOND
S#
STATUS
CITY
S1
S2
S3
S4
S5
20
10
10
20
30
London
Paris
Paris
London
Athens
Thus SECOND (S#, STATUS, CITY) is tabulated in 3NF
as
Lecture by
28
SC(S#, CITY)Prof.Dr.S.Sridhar
and CS (CITY, STATUS)
Database Security & Back-ups
Security problems :
 Legal, Social and ethical aspects
Eg : does a person making the request
say for customer’s credit
- have a legal right to the requested information.
 Physical Controls
Eg : Computer or Terminal room locked !
Or otherwise guarded ? !
 Policy Questions
Who should have access ? !
To what level ? !
 Operational Problems
- Password is used. Then
- How are the passwords Rept secrete ?
- How often they are changed ?
Lecture by
Prof.Dr.S.Sridhar
29
Hardware Control
- Whether the processing unit has any
security measures,such as storage protection keys
or privileged operation mode ?
Operating System Security
- Whether the O /S erase the contents of
storage ? !
and Data files ? !
Issues Concerned with DBMS
- Whether the DBMS has the concept of
ownership ?
Examples of Discretionary Access control
Create Security Rule SR3
GRANT RETRIEVE (S#, SNAME, CITY),
DELETE ON S WHERE
S.CITY = ‘LONDON’
TO JIM, FRED, MARY
ON ATTEMPTED VIOLATION REJECT;
Lecture by
Prof.Dr.S.Sridhar
30
 CREATE SECURITY RULE EX1:
GRANT RETRIVE (S#, SNAME, CITY)
ON S
TO JAC, ANNE, CHARLEY;
 CREATE SECURITY RULE EX4:
GRANT RETRIVE (S#, SNAME)
ON S WHERE S. STATUS > 50
TO JAC, PAVL;
 CREATE VIEW SSS AS
(S.S#, S.NAME) WHERE
S.STATUS > 50;
Request Modification :
 DEFINE PERMIT RETRIEVE ON P TO U
WHERE P.CITY = “London”
 RETRIEVE (P.P#, P.WEIGHT)
WHERE P.COLOR = “Red”
 RETRIEVE (P.P#, P.WEIGHT)
WHERE P.CITY = “London”
Lecture by
Prof.Dr.S.Sridhar
31
Back – ups:
Daily Back-up
After the day work of all
transactions, copying the entire
system files / data files on a floppy,
disk (CD), or a tape depending on the
size of total volume.
Weekly back-up
Monthly back-up
Yearly back-up
In DBMS – Mirroring concept as
back –up.
Stand-by server as back-up
CD- Server as back –up
Software, specially in Oracle like
RDBMS, auto back-up and retrieval
systems.
Lecture by
Prof.Dr.S.Sridhar
32
SQL – Language
CREATE TABLE
( S# S# NOT NULL, P# P# NOT NULL,
QTY QTY NOT NULL,
PRIMARY KEY (S#) REFERENCE S
ON DELETE CASECADE
ON UPDATE CASCADE,
CHECK(QTY > 0 AND QTY < 5001));
This is to create a table with attributes S#, P#,
QTY, all NOT NULL values and the primary key
is S# also, check the condition while creating the
table itself whether QTY is > 0 and QTY < 5001.
Here CASCADE is used as an Option.
ALTER TABLE S ADD COLUMN DISCOUNT
INTEGER
DEFAULT – 1;
Here we can alter the table S by adding a new
column namely DISCOUNT which is an integer
quantity with default value = -1.
Lecture by
Prof.Dr.S.Sridhar
33
DROP TABLE S;
This will drop the created table S
from the database.
Data Manipulation (Retrieval operations)
(called DML)
SELECT P.COLOR, P.CITY
FROM P
WHERE P.CITY < >’PARIS’
AND P.WEIGHT > 10;
------------------------------------------------------------------SELECT DISTINCT P.COLOR, P.CITY
FROM P
WHERE P.CITY < > ‘PARIS’
AND P.WEIGHT > 10;
-----------------------------------------------------------------SELECT P.COLOR, P.CITY
FROM P
WHERE P.CITY < >’PARIS’
AND P.WEIGHT > 10;
ORDER BY CITY DESC;
Lecture by
Prof.Dr.S.Sridhar
34
SELECT P.P#, P.WEIGHT * 454 AS GMNT
From P;
------------------------------------------------------------------SELECT * FROM S;
------------------------------------------------------------------SELECT S.S#, S.NAME, S.STATUS, S.CITY,
P.P#, P.NAME, P.COLOR, P. WEIGHT,
FROM S, P
WHERE S.CITY = P.CITY;
----------------------------------------------------------------S JOIN P USING CITY
-----------------------------------------------------------------SELECT DISTINCT S.CITY AS SCITY,
P. CITY AS PCITY
FROM S JOIN SP USING S# JOIN P USING P#;
------------------------------------------------------------------SELECT COUNT(*) AS NFROM S;
------------------------------------------------------------------SELECT MAX (SP.QTY)AS MAXQ,
MIN (SP.QTY)AS MINQ
FROM SP
WHERE SP.P# = ‘P2’;
Lecture by
Prof.Dr.S.Sridhar
35
Update Operations
INSERT
INTO P (P#, PNAME, COLOR, CITY)
VALUES (‘P8’, ‘Sprocket’,’pink’, ‘Nice’);
------------------------------------------------------------------INSERT
INTO TEMP(S#, CITY)
SELECT S.S#, S.CITY
FROM S
WHERE S.STATUS > 15;
------------------------------------------------------------------DELETE
FROM SP
WHERE ‘London’ =
(SELECT S.CITY
FROM S
WHERE S.S# = SP. S#);
------------------------------------------------------------------All or Any conditions
SELECT DISTINCT PX.NAME
FROM P AS PX
WHERE PX.WEIGHT > ALL
( SELECT PY.WEIGHT
FROM P AS PY
WHERE PY.COLOR = ‘Blue’);
Lecture by
Prof.Dr.S.Sridhar
36
1)
Exercises ON SQL
CREATE TABLE ( S# S# NOT NULL,
P# P# NOT NULL, QTY QTY NOT NULL)
Ans
S#
P#
QTY
4532
4533
4534
4535
123
234
345
567
10
20
40
5
2) CREATE TABLE ( S# S# NOT NULL,
P# P# NOT NULL, QTY QTY NOT NULL)
PRIMARY KEY (S#) REFERENCE S
CHECK (QTY >0 NAD QTY <= 20));
Ans
S#
P#
QTY
4532
4533
4535
123
234
567
10
20
5
Lecture by
Prof.Dr.S.Sridhar
37
3) ALTER TABLE S ADD COLUMN DISCOUNT
INTEGER DEFAULT –1;
Ans
S#
P#
Qty
Discount
4532
4533
4535
123
234
567
10
20
5
-1
10
5
4) DROP TABLE S;
( Then the table S will NOT be in DB)
DATA MANIPULATION
1) SELECT S.P#, S.QTY FROM S
WHERE S.QTY < > 20
AND S.P# > 500 ;
Ans
S#
P#
QTY
4535
567
5
2) SELECT DISTINCT S.S#, S.P#, S.QTY
FROM S
WHERE S.QTY < > 20
AND S,P# > 500;
Ans
S#
P#
QTY
4535
567
Lecture by
Prof.Dr.S.Sridhar
5
38
3) SELECT DISTINCT S.S#, S.P#, S.QTY
S. Discount FROM S
WHERE S.QTY < 5
AND S,P# > 125
ORDER BY S# DESC;
Ans
S#
P#
QTY Discount
4533 234
20
10
4) SELECT S.S#, S.P#, S.QTY * 10 AS
QTY2 FROM S
WHERE DISCOUNT > 0;
Ans
S#
P#
QTY
QTY2
4533 234
4535 567
20
5
5) SELECT * FROM S;
Ans
S#
P#
4532
4533
4535
200
50
Qty
123
10
234
20
Lecture by
567
5
Prof.Dr.S.Sridhar
Discount
-1
10
5
39
6) SELECT S.S#, S.P#, S.QTY,
P. P#, P.NAME
FROM S, P
WHERE S.P# = P.P# ;
S
Ans ( input)



S#
P#
Qty
Discount
4532
4533
4534
4535
123
234
345
567
10
20
40
5
-1
10
-1
5



P#
PNAME
4532
4555
4535
4534
NUT
BOLT
SCREEN
ROD
Answer
S.S# S.P# S.QTY
4532
4534
4535
7)
123
345
567
10
40
5
P#
PNAME
4532
4534
4535
NUT
ROD
SCREEN
S JOIN P USING P#
Answer is the same as 6.
.X. in this case only
Lecture by
Prof.Dr.S.Sridhar
40
8) SELECT COUNT ( * ) AS N FORM S;
Ans Count = N = 4
9) SELECT MAX ( S.QTY) AS MAXQ,
MIN (S.QTY) AS MINQ
FROM S
WHERE S. DISCOUNT = -1;
Answer MAXQ = 40
MINQ = 10
10) UPDATE Operations:
INSERT INTO P ( P#, PNMAE)
VALUES (4536, ‘STRING’);
P#
PNAME
4532
4555
4535
4534
4536
NUT
BOLT
SCREEN
ROD
STRING
?
Ans 
DELETE FROM P WHERE P.PNAME = ‘ROD’;
P#
PNAME
4532
NUT
4555
BOLT
4535 Lecture
SCREEN
by
4536 Prof.Dr.S.Sridhar
STRING
41