1. STRUCTURED
QUERY LANGUAGE
Chandra S. Amaravadi

2. IN THIS PRESENTATION Codd’s rules for relational systems Types of SQL
DDL and DML
Examples

3. CODD’S RULES
AND
TYPES OF SQL

4. CODD’S RULES FOR RDBMSs
Codd has written a paper in which he outlined the rules for
relational systems. These are as follows:
Information representation
Guaranteed access
Dynamic on-line catalog
Comprehensive data sub-language
View updating
Note: Codd was a research fellow at IBM in the ’70s

5. CODD’S RULES FOR RDBMSs..
High-level insert, update and delete
Physical data independence
Logical data independence
Integrity independence
Distribution independence
Non-subversion

6. CODD’S RULES FOR RDBMSs
Information representation -- all information should be represented as atomic values
in tables.
Guaranteed access given a row, column and table name we should be able to
access values in the table.
Online catalog the system catalog (data dictionary) should be online
and accessible by the system.
Comp. data lang there should be a language for data definition and data
manipulation.
View updating the system must be able to automatically update views
based on a base table.

7. CODD’S RULES FOR RDBMSs
High level insertion, update insertion, deletion and update should operate on a
table.
Physical data independence should be able to change internal storage structures
without affecting application programs.
Logical data independence should be able to change logical scheama
Integrity independence integrity controls must be independent of appln. prog.
Distribution independence the users/appln. programs should not be affected
by where the data is physically stored.
Non subversion should not be able to bypass integrity rules by
using the data sub language.

8. STRUCTURED QUERY LANGUAGE
SQL: command language used to define/retrieve data from a database
Originated from SEQEL (system R)
based on relational calculus
(uses select, project, join etc.)
standardized in ’82,’95, ‘05
Embedded SQL a standard in ‘89
Two major types and three other types
DDL, DML
SQL/T, SQL/I, DCL
Embedded SQL

9. STRUCTURED QUERY LANGUAGE
There are five types of SQL as follows:
DDL - Creating / modifying schema objects
DML - Retrieving / inserting / updating information
SQL/T - Transaction boundaries
SQL/I - Integrity constraints
DCL. - To authorize access to the database objects

10. DATA DEFINITION
LANGUAGE

11. DATA DEFINITION LANGUAGE
DDL is the language used to define/modify the database
Schema.
Create/Open Database (not discussed) Create Schema Employee;
Create/Alter/Drop Table
Create/Drop View
Create/Drop Index

12. DATA DEFINITION LANGUAGE..
TYPICAL FORMAT
Action DatabaseComponent ComponentName…
Create
Drop
Table
View
Index
Cust…..
Emp…..
…………
Alter
Table
Emp…..

13. DATA DEFINITION LANGUAGE..
Command used to create tables
CREATE TABLE Table name (attribute attr. type,
attribute attr.type..)
[CONSTRAINT Constr name TYPE attr];
Command used to change attributes in tables
ALTER TABLE Table name ADD attr. attr. type,
attr. attr. type;
Command used to delete table definitions
DROP TABLE Table name ;

14. CREATE TABLE Creates a table (schema) Dept.
d_no d_name d_mgr_ssn d_phone
CREATE TABLE DEPT. ( d_no Integer,
d_name VarChar(15),
d_mgr_SSN Char(9),
d_phone Char(12));

15. ALTER, DROP TABLE
Alter table adds/drops attributes; Drop table drops the entire table.
Dept.
d_no d_name d_mgr_ssn d_phone no_of_emp
ALTER TABLE DEPT. ADD no_of_emp Integer;
ALTER TABLE DEPT. DROP no_of_emp;
DROP TABLE Dept.;

16. CREATE VIEW CREATE VIEW Viewname AS SELECT...
Command used to create VIEWS
CREATE VIEW Viewname AS SELECT...
A view is the way a user looks at the data.
Views are subsets of the data in the database.
A view could include data from more than one table.
All application programs access data via views.
Views provide logical data independence.
Reports can be created from views (as well as from tables)

17. CREATE VIEW.. Creates a query; AS is an “alias” or name Emp.
e_ssn e_name e_title
Create a view of employees who are analysts
CREATE VIEW Analysts AS
SELECT e_name, e_title
FROM Emp.
WHERE e_title = “analyst”;
DROP VIEW ANALYSTS;

18. CREATE/DROP INDEX CREATE INDEX TI_INDEX ON EMP(e_title);
An index is an example of file organization used to facilitate retrieval
CREATE INDEX TI_INDEX
ON EMP(e_title);
DROP INDEX TI_INDEX;

19. DATA MANIPULATION
LANGUAGE

20. DATA MANIPULATION LANGUAGE
DML is the language used to create/modify and delete
data in the database.
INSERT
insert a record
UPDATE
change values
DELETE
delete records
SELECT
choose record

21. THE INSERT COMMAND..
Inserts a record into a table with name TABLENAME.
FORMAT
INSERT INTO TABLENAME
VALUES (attr1 value, attr2 value….);

22. THE INSERT COMMAND.. Insert employee record EMP. e_ssn e_name e_title
INSERT INTO EMP
VALUES (‘ ’, ‘Sullivan’, ‘developer’);
e_ssn
e_name
e_title
Sullivan
developer

23. THE UPDATE COMMAND Update employee title to ‘analyst’ EMP.
e_ssn e_name e_title
UPDATE EMP
SET e_title = ‘analyst’
WHERE e_name = ‘Sullivan’;
/* table name */
/* new values */
/* condition */
EMP.
e_ssn
e_name
e_title
Sullivan
analyst

24. THE DELETE COMMAND Delete Employee record EMP. DELETE FROM EMP.
e_ssn
e_name
e_title
Sullivan
analyst
DELETE FROM EMP.
WHERE e_name = ‘Sullivan’;
EMP.
e_ssn
e_name
e_title
What if you were to issue,
DELETE FROM EMP?

25. THE SELECT STATEMENT

26. THE SELECT STATEMENT SELECT <Attribute list>
FROM <table list>
[WHERE <Conditions> AND/OR <Conditions>]
[GROUP BY <Attribute list>]
[HAVING <Conditions>]
[ORDER BY <Attribute list>
DESC/ASC];
Group by is used to organize data into groups and provide summary
information. Having is used for the group condition.

27. ADDITIONAL NOTES ON SELECT
Notes on the select statement
The Select part can include literals (“The number of..”)
Some functions can be included in SELECT part or WHERE part
More than one table and one condition can be specified
Conditions are connected by logical operators -- and/or etc.
When GROUP BY is used, the WHERE clause is not used.
Instead the group condition is specified by HAVING.
ORDER BY is optional and used if sorting is required.

28. DISCUSSION The output of a SELECT statement is: a) an attribute ?
b) a single record ?
c) table ?

29. FUNCTIONS IN SQL
Operators to carry out different types of calculations
Logical
Arithmetic
String
Date
IN WHICH PART OF THE QUERY ARE FUNCTIONS USED?

30. LOGICAL OPERATORS
Logical operators are generally used to carry out comparison
“=“, “>“, “<“
“>=“, “<=“
“<>“ OR “!=“
(NOT) BETWEEN X1 AND X2 (inclusive)
LIKE
“_” or “%” IN
(NOT) NULL
Dept.
d_name
d_phone
Finance
Sales
Marketing
Fin. records
(Select….Where D_Name like “%fin%”)
Finance
Financial Records

31. LOGICAL OPERATORS.. To select employees between certain income range
Select emp#, emp name
From emp
Where income between and 90000;
To select customers in Macomb, Chicago or Bloomington
Cust.
Select cust.cust#
From cust
Where cust.zip in (61455, 60601….)
cust#
zip
1156
61455
1157
61706
1158
54555
1160
60601

32. BUILT-IN ARITHMETIC FUNCTIONS
Arithmetic functions are used to carry out math operations
ABS
ROUND
TRUNC
COUNT
SUM
AVG
MAX
MIN
Select count(emp_name)…
Select max(emp_salary)…..

33. STRING FUNCTIONS
String functions are used to carry out string manipulation
LENGTH(string)
SUBSTR(string, start, no of ch.)
LOWER
UPPER
Select substr(prob_descr, 0, 10)
………
Prob_descr = “I am unable to log in…”

34. DATE FUNCTIONS Date functions are used to carry out date arithmetic
ADD_MONTHS(1/1/17, 5) = 6/1/17
MONTHS_BETWEEN (sysdate, hiredate)
NEXT_DAY(hiredate, ‘Friday’)
TO_DATE(string, picture)
TO_DATE(“12/12/17”, ‘DY th MM, YYYY’) = 12 th DEC, 2017
Next_day(12/12/17, ‘Friday’) = 12/16/17

35. SIMPLE RETRIEVALS Select employees who are analysts EMP.
e_ssn e_name e_title
SELECT e_name
FROM EMP
WHERE e_title = ‘analyst’;

36. SIMPLE RETRIEVALS.. EMPLOYEE e_ssn e_name e_title e_salary 456-34-8895
Smith
developer
$35,000
Johnson
analyst
$27,000
Weintraub
$60,000
Dickson
manager
$64,000
Ferrel
$47,000
Rao
$71,000
McDonald
$85,000

37. SIMPLE RETRIEVALS.. Select employees whose name ends with ‘son’ EMP.
e_ssn e_name e_title
SELECT e_name
FROM EMP
WHERE e_name like ‘%son’

38. SIMPLE RETRIEVALS..
Select employees whose name does not begin with ‘a’
EMP.
e_ssn e_name e_title
SELECT e_name
FROM EMP
WHERE e_name not like ‘a%’

39. RETRIEVALS WITH AGGREGATES..
Count the number of developers
EMP.
e_ssn e_name e_title
SELECT COUNT(e_name)
FROM EMP
WHERE e_title = ‘developer’

40. RETRIEVALS WITH AGGREGATES..
EMP.
e_ssn e_name e_title e_salary
SELECT “Average Salary=“, Avg(e_salary)
From EMP
Where e_title = ‘developer’ or
e_title = ‘analyst’ ;
What does this query do?

41. RETRIEVALS WITH EXPRESSIONS..
List employees and their witholdings (calculated as
8% of salary).
EMP.
e_ssn e_name e_title e_salary
SELECT e_name, e_salary * 0.08 AS withholdings
FROM EMP

42. RETRIEVALS WITH GROUP BY..
List all job titles and the number of emps in each
EMP.
e_ssn e_name e_title
SELECT e_title, COUNT(e_name)
FROM EMP
GROUP BY e_title

43. GROUP BY.. EMPLOYEE e_ssn e_name e_title e_salary 456-34-8895 Smith
developer
$35,000
Johnson
analyst
$27,000
Weintraub
$60,000
Dickson
manager
$64,000
Ferrel
$47,000
Rao
$71,000
McDonald
$85,000

44. RETRIEVALS WITH HAVING..
List the number of employees in each job category with
salary > $50,000
EMP.
e_ssn e_name e_title e_salary
SELECT “Number of: “, e_title, “=“, COUNT(e_name)
FROM EMP
GROUP BY e_title
HAVING e_salary > 50000

45. RETRIEVALS WITH HAVING..
EMP.
e_ssn
e_name
e_title
e_salary
Smith
developer
$35,000
Johnson
analyst
$27,000
Weintraub
$60,000
Dickson
manager
$64,000
Ferrel
$47,000
Rao
$71,000
McDonald
$85,000

46. RETRIEVAL FROM MULTIPLE TABLES
Sharing of information a key concept
Normalization process leads to multiple tables
When data is retrieved from > 1 table, need to
link tables together
This is done by equating FK values with PK values
for each set of tables that need to be linked
Emp.
emp#, emp name, dept#
Dept.
dept#, dept name, mgr

47. RETRIEVAL FROM MULTIPLE TABLES
EMP.
e_ssn e_name e_title
Dept.
d_name d_no d_mgr_ssn d_phone
SELECT Emp.e_name, Dept.d_name
FROM EMP, dept.
WHERE EMP.e_ssn = dept.d_mgr_ssn

48. RETRIEVAL FROM MULTIPLE TABLES..
EMPLOYEE
e_ssn
e_name
e_title
e_salary
Smith
developer
$35,000
Johnson
analyst
$27,000
Weintraub
$60,000
Dickson
manager
$64,000
Ferrel
$47,000
Rao
$71,000
McDonald
$85,000
DEPARTMENT
d_name
d_no
d_mgr_ssn
d_phone
Manugistics
142
IMS
230
Pilot
345
InfoSec
467

49. DISCUSSION Write SQL queries for the following:
1. Create Emp table with E_SSN, E_Name, E_title as attr. -- assume
data types.
2. Add E_salary to the Employee table.
3. Create an index, “Ti_ndx” on E_title.
4. Insert Bob White with SS# as an analyst
5. List employees and job titles in order of title.
6. List employees other than developers.
7. Create a view “hi_flier” listing developers with salary > $100K.
8. Count the #. of employees who are managers.