1. CSC 453 Database Systems Lecture
Tanu Malik
College of CDM
DePaul University

2. Last time SQL Basic SQL on two tables Subqueries Nested subqueries
Correlated subqueries

3. Today Grading SQL Functional Dependencies Review
Update, Delete statements
Creating Views
Temporary Tables
Functional Dependencies

4. SQL

5. SQL Queries General form of a query:
SELECT list of attributes to report FROM list of tables [CROSS JOIN| [LEFT|REIGHT] OUTER JOIN] [WHERE tuple condition] [GROUP BY list of grouping attributes] [HAVING group condition] [ORDER BY list of ordering attributes] ;
[UNION|INTERSECT|EXCEPT]
Result is an ordered set of ordered tuples

6. Subqueries
The result of one query may be needed by another to compute its result.
There are two kinds of subqueries

7. Nested Subquery Vs Correlation
SELECT LastName, FirstName, SID,
(SELECT count(*)
FROM enrolled
WHERE SID = StudentID) AS EnrCrs
FROM student;
SELECT Student.*
FROM Student
WHERE started = (SELECT min(started)
FROM student
WHERE city = ‘Chicago’)

8. Subquery check Different ways of checking: Within the inner query set
Not within the inner query set
Against all members of the inner query set
Against any one member of the inner query set
Does the set exists

9. Subquery Practice

10. Update/Delete Statements
UPDATE table_name SET column1 = value1, column2 = value2, ... WHERE condition;
DELETE FROM table_name WHERE condition;
INSERT INTO table2 SELECT * FROM table1 WHERE condition;

11. SQL Views

12. Create View base tables (CREATE TABLE) stored in database
CREATE OR REPLACE VIEW CSstudents AS
SELECT *
FROM student
WHERE Program = 'COMP-SCI';
FROM CSstudents;
base tables (CREATE TABLE) stored in database
views (CREATE VIEW)
dependent on base tables or other views, may or may not be stored (virtual vs materialized)
temporary tables (subquery, etc.)
limited lifetime

13. Reasons for Creating Views
CREATE VIEW studentview AS
SELECT LastName, FirstName, SID, Career, Program
FROM student;
Hide information (grant access to relevant info)
SELECT name
FROM studentgroup
WHERE name NOT IN (SELECT groupname
FROM CSstudents, memberof
WHERE StudentID = SID);
Simplify queries (improve readability)
not necessarily a good reason to create a view in general, if temporary table is sufficient

14. Improving Readability
CREATE VIEW enrollment(SID, LName, CID, CNR, Dpt) AS
SELECT SID, LastName, CID, CourseNr, Department
FROM student, enrolled, course
WHERE SID = studentID AND CourseID = CID;
SELECT count(*)
FROM enrollment
WHERE CNR = 440 AND Dpt = 'CSC';

15. Temporary Tables or “on commit preserve rows”
create global temporary table gradstudent(
LASTNAME VARCHAR2(40),
SID NUMBER(5,0),
PROGRAM VARCHAR2(10),
primary key(sid) )
on commit delete rows;
insert into gradstudent
select lastname, sid, program
from student
where career = ‘GRD';
or “on commit preserve rows”
lifetime of temporary data is limited to session
table exists beyond session
on the database corresponding to different information organizations, avoiding the need for data duplication or information consistency problems Physical DB
Database Files
Conceptual database
Employee, Department, Salary, Birth Date
Views
Employee, Salary, Age

16. Common Table Expression (CTE)
WITH GradStudents AS
(SELECT SID, LastName, SSN
FROM student
WHERE Career = ‘GRD')
SELECT *
FROM enrolled
WHERE StudentID NOT IN (SELECT SID FROM GradStudents);
Temporary table, exists only for lifetime of query,
cannot be used in other queries
can create multiple such tables

17. CTE Example WITH StudentEnrollment(SID, Quarter, Year, crs_nbr) AS
(SELECT StudentID, Quarter, Year, count(CourseID)
FROM enrolled GROUP BY StudentID, Quarter, Year),
StudentMax(SID, maxcrs)
(SELECT SID, max(crs_nbr)
FROM StudentEnrollment
GROUP BY SID)
SELECT *
FROM student S, StudentMax SM
WHERE S.SID = SM.SID;
temporary table can refer to previous temporary table
mutual recursion not allowed (in Oracle)

18. Modifying Views
DROP VIEW Csstudents;
What about other objects that depend on it (e.g other views)?
How is/are the underlying base table(s) affected?
INSERT INTO CSstudents(LastName, FirstName, SID)
VALUES ('Crackenden', 'Gloria', 123);
What do INSERT, DELETE, UPDATE mean for a view?

19. Updateable Views
“An updatable view is one you can use to insert, update, or delete base table rows.”
Roughly:
FROM contains only a single relation
no DISTINCT, aggregation, set, calculated value
WHERE clause may not contain a sub-query involving the relation the view is based on
Statement can still fail (e.g. if primary key is missing in INSERT or non-null attributes are not included)

20. Functional Dependencies

21. ssn
name
projectID
rating
hourly_wages
hours_worked
Alice 48 8 10 40
Bob 22 30
Charlie 35 5 7
Don 32
Ellie
hourly_wages attribute is determined by the rating attribute.
Integrity Constraint: for a given rating value,
there is only one permissible hourly_wages value.

22. Create Table statement
CREATE TABLE EmployeeRec ( ssn number(10) primary key, name varchar2(100), projectid number(2), rating number(1), hourly_wages number(3), hours_worked float, unique (rating,hourly_wages) );

23. UPDATE EmployeeRec SET hourly_wages = 11 WHERE name = ‘Alice’

24. Anomalies
Update Anomaly: The hourly_wages in the first tuple could be updated without making a similar change in the second tuple.
Insertion Anomaly: Cannot insert a tuple for the hourly_wages unless have an employee with that wage.
Deletion Anomaly: If we delete all tuples with a given rating value (e.g., we delete the tuples for Charlie and Don) we lose the association between that rating value and its hourly_wage value.

25. Better way? Decomposition ssn name ProjectID rating hours_worked
Alice 48 8 40
Bob 22 30
Charlie 35 5
Don 32
Ellie
rating
hourly_wages 8 10 5 7

26. Functional Dependencies
Set of attributes Y is functionally dependent on set of attributes X if and only if the values of X uniquely determine the values of Y
Also “X determines Y”, “X  Y”
X is called the determinant
A functional dependency must hold for all possible relation states to be valid

27. Search notion of a f.d Accessing ‘x’ requires a column name and rowidB C 1 a x 2 b y 3 4 c
A BC
BC A

28. Inference Rules Reflexivity: If X includes Y, then X  Y
Augmentation: If X  Y, then XZ  YZ
Transitivity: If X  Y and Y  Z, then X  Z
[Decomposition: If X  YZ, then X  Y and X  Z ]
[Union: If X  Y and X  Z, then X  YZ]
[Pseudo-transitivity: If X  Y and WY  Z,
then WX  Z]

29. Closures
For a set of functional dependencies F, the closure of F (F+) is the set of all functional dependencies that can be derived from F
F+ can be constructed from the closures under F of all possible sets of attributes X
For F and a set of attributes X, the closure of X under F (X+) is the set of all attributes that can be determined from X

30. Finding a Closure of X under F
To find the closure of X under F:
set X+ = X
repeat
set oldX+ = X+
for each Y  Z in F do
if X+ includes Y, then set X+ = X+ U Z
until oldX+ = X+

31. Attribute Closures: Example 1
Given:
R = {A, B, C, D, E, H}
F = {A → BC,
B → CE,
A → E,
AC → H,
D → B}
What is the closure of CD (i.e., (CD)+)?

32. Attribute Closures: Example 1
Given:
R = {A, B, C, D, E, H}
F = {A → BC,
CD → E,
CD → H,
B → E,
D → B}
What is the closure of AD (i.e., (AD)+)?

33. SuperKey=Key For each set X, find the closure of X under F
If X+ contains all attributes, then X is a superkey

34. Candidate Key
If X is a superkey, but no subset Y of X is a superkey, then X is a candidate key
Why candidate key? Because they are minimal.

35. SuperKey Vs Candidate Key
Example
F = {A → BCD, AB → CD, ABC → D,BD → AB,C → AD}
F.Ds
SuperKey
Candidate Key
A → BCD
AB → CD
ABC → D
BD → AB
C → AD

36. SuperKey Vs Candidate Key
Example
F = {A → BCD, AB → CD, ABC → D,BD → AB,C → AD}
F.Ds
SuperKey
Candidate Key
Primary Key
A → BCD
AB → CD
ABC → D
BD → AB
C → AD

37. Primary Key
Choose a candidate key to be the primary key

38. More closure examples R(ABCDEHI) R(ABCDEG)
F = {A → B,BC → DE,AEI → I}.
Find (AC)+
R(ABCDEG)
F = {AB → C,BC → AD,D → E,CG → B}.
Find (AB)+

39. Example 1: Keys Given: R = {A, B, C, D, E, H} F = {A → BC, CD → E,
CD → H,
B → E,
D → B}

40. Determining Keys What is (ACD)+? (ACD)+ → R
How can you determine if ACD is a super key?
It is if (ACD)+ → R
How can you determine if ACD is a candidate key?
It is if: (ACD)+ → R, but NOT
(AC)+ → R, (AD)+ → R, (CD)+ → R

41. Find Candidate Keys R(ABCDEFGH) F = {AB →C, A → DE, B → F, F → GH}
F = {AB →C, BD → EF, AD → G, A → H}
R(ABCDE)
F = {BC → ACE, D →B}
F = {AB → CD, D →A, BC →DE}

42. More examples
R(WXYZ)
Z → W Y → XZ WX → Y

43. Equivalent Set of F.Ds
Given a relation R and two set of functional dependencies F and G on R, the equivalence question is if
F ⊆ G,
G ⊆ F,
F = G, or
F ̸= G.

44. Example
F={A→B,AB→C,D→AC,D→E}
G={A→BC,D→AE}

45. Algorithm Must bring F and G on the same starting point. How?
Compute the closure set of left hand attributes in F, but by using the f.ds in G.
Compute the closure set of left hand attributes in G but using the f.ds in F.
Compare F’s search power as stated by its f.d set is equivalent to the search power of G.

46. Minimal Cover
F is a minimal cover if F no dependency can be removed from F
In other words, F is an irreducible funcitonal dependency set

47. Finding Minimal Cover
Find a minimal cover by eliminating the redundant/extraneous set of attributes in the set F .
Given a f.d α → β, 3 kinds of redundancies:
the redundancy is on the r.h.s,
the redundancy is on l.h.s, or
the entire f.d is redundant.

48. Eliminate redundancy on R.H.S
Use decomposition rule to decompose all f.d’s in F.
α → βγ to α → β, and α → γ
We have only one attribute on r.h.s, either the entire f.d will be redundant or the f.d will not be redundant.

49. Eliminate entire f.d
Eliminate a f.d if you see it exactly repeated again or can be inferred transitively.
Given a α → β in F,
Find α+ first using F,
compute α+ but this time using F − {α → β}.
If α+ does not change then surely the f.d is redundant.

50. Eliminate redundancy on l.h.s
Given a f.d such αγ → β, determine if α → γ holds in F′ = F −{αγ → β}.
If γ can be searched by just α in F’ without the given f.d, then clearly γ is redundant in the given f.d to search for β.