Integrity constraints in dbms

Creating a table,
populating data, adding
integrity constraints
Prepared by,
Mr. K.Vignesh Saravanan
Assistant Professor
Department of Computer Science and Engineering
Ramco Institute of Technology
Rajapalayam

Recap
Language SQL Commands
Data Definition
Language
(DDL)
1. CREATE
2. ALTER
3. DROP
4. TRUNCATE
5. RENAME

Recap
Data Manipulation
Language
(DML)
1. INSERT
2. UPDATE
3. DELETE

Recap
Data Control Language
(DCL)
1. GRANT
2. REVOKE
Data Query Language
(DQL)
1. SELECT

Recap
Transaction Control
Language
(TCL)
1. COMMIT
2. ROLLBACK
3. SAVEPOINT

• DCL – to give privilege / to revoke privilege to the
users to perform DDL, DML operations
• User are given the rights (or restricted) to execute the
select, insert, update, alter, create… etc
Syntax:
GRANT(REVOKE) [privilege] on [tablename] from [users];
• > GRANT select, update on employee to 17ee001;
• > REVOKE alter, delete on employee from 17ee001;

To give permission to perform all commands:
• > GRANT all on employee to 17ee001;
• > REVOKE all on employee from 17ee001;
Names
17ee001
17ee002
17ee003
17ee004
.
.
.
.
17ee060
To give permission to many users:
• > GRANT all on employee to Users;
• > REVOKE all on employee from Users;
• > REVOKE update, delete on employee
from Users;
Users

Transaction Control Language
• To control/save the changes done by the DML
commands.
• commit – It saves the state of the Database and no
previous commands can be undone.
• savepoint – creates a temporary state where we can
return to undo any changes made. To reverse any
commands we can use this savepoints.
• rollback – command use to restore to a particular
savepoint.

NAME REGNO MARKS
AAA 1001 89
BBB 1002 90
CCC 1003 92
• > savepoint s1;
• > delete from student where marks=90;
• > savepoint s2;
• > rollback s1;
NAME REGNO MARKS
AAA 1001 89
CCC 1003 92

NAME REGNO MARKS
AAA 1001 89
BBB 1002 90
CCC 1003 92
• > delete from student where marks=92;
• > savepoint s3;
• > commit;
• > rollback s3; # Error
NAME REGNO MARKS
AAA 1001 89
BBB 1002 90

Integrity Constraints
• Integrity – Data Quality
• Constraints – Conditions
• To ensure the quality of data in the database some
integrity constraints are used.
• KEYS
• NOT NULL
• UNIQUE
• CHECK
• DEFAULT

Consider a student database (regno, name, marks, attd)
• Integrity constraints required are:
– Student name should not be null;
– No student regno must be same (unique regno
needed);
– Student mark will be 0 by default;
– Student attendance should be > 75;

• NOT NULL – if the particular field should not be left
empty (i.e null values are not allowed)
• CREATE table student
(
regno int,
name varchar(20) not null,
marks int,
attd int
);

• UNIQUE – the regno for two students should not be
same (i.e unique regno are only allowed)
(
regno int unique,
marks int,
attd int
);

• KEY – the primary key can be set to the table to
uniquely identify a tuple. (so primary key will be always
not null and unique)
(
regno int primary key,
marks int,
attd int
);

• KEY – the primary key can be set to the table to
uniquely identify a tuple. (so primary key will be always
not null and unique) (ANOTHER WAY OF DEFINING KEY)
(
regno int,
marks int,
attd int,
primary key(regno)
);

• DEFAULT– to provide a default values to the attributes
• To give the marks value to be zero.
(
marks int default 0,
attd int
);

• CHECK – to ensure if the attribute values has satisfied
the specific condition
• To check if the attendance should be >75.
(
marks int default 0,
attd int check(attd>75)
);

SELECT - Restrictions
• Restricting the values:
– ALL / DISTINCT keyword;
• Select city from location;
NAME CITY
AAA SVKS
BBB SRI
CCC SRI
DDD RJPM
EEE SVKS
FFF RJPM
GGG VNR
LOCATION
CITY
SVKS
SRI
SRI
RJPM
SVKS
RJPM
VNR
select all city from location;
Same result

SELECT - Restrictions
• Restricting the values:
– ALL / DISTINCT keyword;
• To know what are the places
from which the persons are
coming:
• Select distinct city from
location;
NAME CITY
AAA SVKS
BBB SRI
CCC SRI
DDD RJPM
EEE SVKS
FFF RJPM
GGG VNR
LOCATION
CITY
SVKS
SRI
RJPM
VNR

SELECT – Pattern Matching
• Pattern matching for string:
– LIKE keyword;
• To retrieve a string data based
on a pattern (or) based on
some character
To select city names starting with
the letter ‘T’
• Select * from location
where city like ‘T%’;
NAME CITY
AAA Sivakasi
BBB Sriviliputtur
CCC Rajapalayam
DDD Sattur
EEE Tenkasi
FFF Erode
GGG Chennai
LOCATION
NAME CITY
EEE Tenkasi

SELECT – Pattern Matching
To select city names ending with
the letter ‘i’
• Select city from location
where city like ‘%i’;
To select the string from
the middle:
• Select * from location
where city like ‘_ _o_ _’;
NAME CITY
AAA Sivakasi
BBB Sriviliputtur
CCC Rajapalayam
DDD Sattur
EEE Tenkasi
FFF Erode
GGG Chennai
LOCATION
CITY
Sivakasi
Tenkasi
Chennai
NAME CITY
FFF Erode

SELECT – between
Retrieve all employees in
department 5 whose salary is
between $30,000 and $40,000.
• Select * from Employee
where salary > 30000 and
salary < 40000;
• Select * from Employee where
salary between 30000 and 40000;
NAME SALARY
AAA 10000
BBB 35000
CCC 25000
DDD 32000
EEE 41000
Employee
NAME SALARY
BBB 35000
DDD 32000

SELECT – ordering the data
Arrange the data in the table in some
particular order
(by default ascending order)
• Select * from Employee
order by salary;
NAME SALARY
AAA 10000
BBB 35000
CCC 25000
DDD 32000
EEE 41000
Employee
NAME SALARY
AAA 10000
CCC 25000
DDD 32000
BBB 35000
EEE 41000
NAME SALARY
EEE 41000
BBB 35000
DDD 32000
CCC 25000
AAA 10000
Select * from Employee
order by salary desc;

Assertions
• An assertion (statement) is a predicate
expressing a condition that
– is always expected to satisfy (or)
– The database should always satisfy
• Types:
– Domain constraints
– Referential Integrity constraints
• Ex: Customers maintain minimum balance
Rs.1000/- in their bank account

• Syntax:
create assertion assertion_name check predicate;
• Example:
create assertion min_balance check
(select * from customers where balance<500)
• Complex assertions leads to DB overhead.
• Assertions are not most widely used recently.
• Equivalent functionality can be implemented
using triggers

Authorization
• Authorization - a privilege
• Providing different levels of grants / privilege
to the database users.
– Authorization to read data
– Authorization to insert new data
– Authorization to update data
– Authorization to delete data
• SQL – DCL – includes grant and revoke
commands

• Syntax: (grant)
grant <privilege list>
on <relation name or view name>
to <user/role list>;
• Privileges can be select, insert, update, delete,
alter, etc.,
• grant select on department to Amit, Satoshi;
• grant update (budget) on department to Amit, Satoshi;
Note: user/role should be declared as public – if access to
all common users

• Syntax: (revoke)
revoke <privilege list>
on <relation name or view name>
from <user/role list>;
• revoke select on department from Amit, Satoshi;
• revoke update (budget) on department from Amit,
Satoshi;
Note: user/role should be declared as public – if access to
all common users

Integrity constraints in dbms

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