The document provides an overview of SQL, focusing on Data Definition Language (DDL) and Data Manipulation Language (DML) concepts, including commands for creating, altering, and managing tables, as well as querying data. It covers various SQL operations such as selecting data, using aggregate functions, applying where clauses, grouping and sorting results, and performing table joins. Key concepts include the distinction between DDL and DML, the use of projections, and the specifics of SQL syntax for different operations.

1. SQL
Sharafat Ibn Mollah Mosharraf
Software Engineer,
Therap (BD) Ltd.

2. Outline
• DDL (Data Definition Language)
– CREATE TABLE Statement
– DROP TABLE Statement
– ALTER TABLE Statement
• DML (Data Manipulation Language)
– SELECT Statement
• Projection • Table Joins
• Aggregate Functions - Cross Join / Inner Join
• Renaming Projected Columns - Natural Join
• WHERE clause - Outer Join
• Grouping Rows • Set Operations
• Sorting rows - UNION and INTERSECT
• Limiting rows returned - MINUS
– INSERT Statement
– UPDATE Statement
– DELETE Statement
4/3/2012 2SQL

3. DDL & DML
DDL (Data Definition Language)
– Manages table and index structure
– CREATE, ALTER, DROP, TRUNCATE statements
DML (Data Manipulation Language)
– Adds, retrieves, updates and deletes data
– INSERT, SELECT, UPDATE, DELETE statements
4/3/2012 3SQL

4. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
– Projecting All Columns: *
– Projecting Specific Columns
– Generalized Projection
– DISTINCT keyword for selecting unique values
• Aggregate Functions
4/3/2012 4SQL

5. DML
SELECT Statement - Projection
Projecting All Columns
SELECT * FROM result
Projecting Specific Columns
SELECT student, marks FROM result
Generalized Projection
SELECT marks + 5 FROM result
Selecting Unique Values of a Column
SELECT DISTINCT marks FROM result
4/3/2012 5SQL
result
student marks
A 25
B 56
C 82
D 25
E 39

6. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
– count()
– min()
– max()
– avg()
– sum()
• Renaming Projected Columns
4/3/2012 6SQL

7. DML
SELECT Statement – Aggregate Functions
count()
SELECT count(marks) FROM result
min()
SELECT min(marks) FROM result
max()
SELECT max(marks) FROM result
avg()
SELECT avg(marks) FROM result
sum()
SELECT sum(marks) FROM result
4/3/2012 7SQL
result
student marks
A 25
B 56
C 82
D 25
E 39

8. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
• Renaming Projected Columns
• WHERE clause
4/3/2012 8SQL

9. DML
SELECT Statement – Renaming Columns
SELECT count(marks) AS marks_count
FROM result
4/3/2012 9SQL
result
student marks
A 25
B 56
C 82
D 25
E 39
optional

10. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
• Renaming Projected Columns
• WHERE clause
– Comparison Operators: =, <>, >, >=, <, <=
– Logical Connectives: AND, OR, NOT
– BETWEEN and NOT BETWEEN Predicates
– IN Predicate
– IS NULL and IS NOT NULL Predicates
– LIKE Predicate
• Grouping Rows
4/3/2012 10SQL

11. DML
SELECT Statement – WHERE Clause
• Comparison Operators: =, <>, >, >=, <, <=
• Logical Connectives: AND, OR, NOT
• BETWEEN and NOT BETWEEN Predicates
Find students having marks between 75 and 79.
SELECT *
FROM result
WHERE marks BETWEEN 75 AND 79
OR
SELECT *
FROM result
WHERE marks >= 75 AND marks <= 79
4/3/2012 11SQL
result
student marks
A 25
B 56
C 82
D 25
E 39

12. DML
SELECT Statement – WHERE Clause
• IN Predicate
Find the marks of the students of class 10.
SELECT *
FROM result
WHERE student IN (
SELECT student
FROM student_class
WHERE class = 10
)
4/3/2012 12SQL
result
student marks
A 25
B 56
C 82
D 25
E 39
student_class
class student
9 A
9 B
10 C
8 D
10 E

13. DML
SELECT Statement – WHERE Clause
• LIKE Predicate
Single Character Matching Wildcard: _
Find students who have the first account number (i.e.
x01, e.g. 101, 201 etc.) in subgroups of account group A.
SELECT * FROM account WHERE acc_no LIKE ′A-_01′
Substring Matching Wildcard: %
Find students who have accounts in account group A.
SELECT * FROM account WHERE acc_no LIKE ′A-%′
4/3/2012 13SQL
account
student acc_no
A A-101
B A-102
C A-156
D B-101
E B-450

14. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
• Renaming Projected Columns
• WHERE clause
• Grouping Rows
– GROUP BY Clause
– HAVING Clause
– Difference Between GROUP BY and HAVING Clauses
• Sorting Rows
4/3/2012 14SQL

15. DML
SELECT Statement – Grouping Rows
4/3/2012 15SQL
salary_statistics
emp org salary
A X 500
B X 1000
C Y 1000
D Y 2500
E Z 3000
• GROUP BY Clause
Find the payroll* of each organization.
SELECT org, sum(salary) payroll
FROM salary_statistics
GROUP BY org
Result:
* Payroll: the total amount of money paid by a company as salary for all the employees.
org payroll
X 1500
Y 3500
Z 3000

16. DML
SELECT Statement – Grouping Rows
4/3/2012 16SQL
salary_statistics
emp org salary
A X 500
B X 1000
C Y 1000
D Y 2500
E Z 3000
• HAVING Clause
Find the organizations with payroll less than $3200.
SELECT org, sum(salary) payroll
FROM salary_statistics
GROUP BY org
HAVING payroll < 3200
Result:
org payroll
X 1500
Z 3000

17. DML
SELECT Statement – Grouping Rows…
4/3/2012 17SQL
• The Difference Between WHERE and HAVING Clauses
 WHERE gets processed before any GROUP BY, and so it doesn't have access to
aggregated values (that is, the results of min(), max(), etc. functions).
 HAVING gets processed after GROUP BY and so can be used to constrain the result
set to only those with aggregated values that match a certain predicate.
Find the organizations with payroll less than $3200.
SELECT org, sum(salary) payroll
FROM salary_statistics
WHERE payroll < 3200
GROUP BY org
SELECT org, sum(salary) payroll
FROM salary_statistics
GROUP BY org
HAVING payroll < 3200
}
}
✗
Incorrect
✓ Correct

18. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
• Renaming Projected Columns
• WHERE clause
• Grouping Rows
• Sorting Rows
– ORDER BY Clause
• Limiting Rows
4/3/2012 18SQL

19. DML
SELECT Statement – ORDER BY Clause
Find students ordered by merit position.
SELECT *
FROM result
ORDER BY marks DESC
Find students ordered by merit position; and if the merit
position is the same, then order by the natural order of
their names.
SELECT *
FROM result
ORDER BY marks DESC, student ASC
4/3/2012 19SQL
result
student marks
A 25
B 56
C 82
D 25
E 39
optional
(default)

20. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
• Renaming Projected Columns
• WHERE clause
• Grouping Rows
• Sorting Rows
• Limiting Rows
– LIMIT Clause
• Table Joins
4/3/2012 20SQL

21. DML
SELECT Statement – LIMIT Clause
Find the top 3 students in the class.*
SELECT *
FROM result
ORDER BY marks DESC
LIMIT 3
Who is the 2nd boy/girl in the class?*
SELECT *
FROM result
ORDER BY marks DESC
LIMIT 1, 1
4/3/2012 21SQL
result
student marks
A 25
B 56
C 82
D 30
E 39
* Assuming each merit position belongs to a single student.

22. Where We Are
• DML (Data Manipulation Language)
– SELECT Statement
• Projection
• Aggregate Functions
• Renaming Projected Columns
• WHERE clause
• Grouping Rows
• Sorting Rows
• Limiting Rows
• Table Joins
– Cross Join
– Inner Join
– Natural Join
– Outer Join
» Left Outer Join
» Right Outer Join
» Full Outer Join
• Set Operations
4/3/2012 22SQL

23. DML
SELECT Statement – WHERE Clause
• IN Predicate
Find the marks of the students of class 10.
SELECT *
FROM result
WHERE student IN (
SELECT student
FROM student_class
WHERE class = 10
)
4/3/2012 23SQL
result
student marks
A 25
B 56
C 82
D 25
E 39
student_class
class student
9 A
9 B
10 C
8 D
10 E

24. DML
Table Joins – Cross Join
Find the marks of the students of class 10.
SELECT result.student, result.marks
FROM result, student_class
WHERE result.student = student_class.student
AND student_class.class = 10
4/3/2012 24SQL
result
student marks
A 25
B 56
C 82
D 25
E 39
student_class
class student
9 A
9 B
10 C
8 D
10 E

25. DML
Table Joins – Cross Join: Execution Steps
SELECT result.student, result.marks
FROM result, student_class
WHERE result.student = student_class.student
AND student_class.class = 10
Step 1 - Cross Join. Result:
4/3/2012 25SQL
result
student marks
A 25
B 56
student_class
class student
9 A
10 B
result student_class
student marks class student
A 25 9 A
A 25 10 B
B 56 9 A
B 56 10 B Step 2 – Filter Records
Step 3 – Project. Output:
student marks
B 56

26. DML
Table Joins – Inner Join
Find the marks of the students of class 10.
SELECT result.student, result.marks
FROM result INNER JOIN student_class
ON result.student = student_class.student
WHERE student_class.class = 10
• The ON clause must be used along with
the INNER JOIN clause.
• INNER JOIN makes the query look cleaner
and easier to understand than cross join
with record filtering in the WHERE clause.
4/3/2012 26SQL
result
student marks
A 25
B 56
student_class
class student
9 A
10 B

27. DML
Table Joins – Natural Join
Find the marks of the students of class 10.
SELECT student, marks
FROM result NATURAL JOIN student_class
WHERE class = 10
4/3/2012 27SQL
result
student marks
A 25
B 56
student_class
class student
9 A
10 B

28. DML
Table Joins – Natural Join: Execution Steps
Find the marks of the students of class 10.
SELECT student, marks
FROM result NATURAL JOIN student_class
WHERE class = 10
4/3/2012 28SQL
student marks class
A 25 9
B 56 10
Step 1 – Natural Join. Output:
result
student marks
A 25
B 56
student_class
class student
9 A
10 B
Step 2 – Filter Records
Step 3 – Project. Output:
student marks
B 56