1. Database Management Systems (CS 564)
Fall 2017
Lecture 5

2. “It’s so easy marketers can learn it!”
SQL: Part 2
“It’s so easy marketers can learn it!”
CS 564 (Fall'17)

3. Recap DDL: DML CREATE TABLE INSERT DELETE UPDATE
PRIMARY KEY, FOREIGN KEY, NOT NULL, ON DELETE (NO ACTION, CASCADE, SET DEFAULT/NULL)
DML
INSERT
DELETE
UPDATE
CS 564 (Fall'17)

4. Recap: Basic SELECT SELECT * Arithmetic expressions LIKE ORDER BY
SELECT [DISTINCT] target-list
FROM relation-list
[WHERE condition];
SELECT *
Arithmetic expressions
LIKE
ORDER BY
LIMIT
CS 564 (Fall'17)

5. Recap: Multi-relation Queries
General form
Natural language semantics
Start with the Cartesian product R1×R2×…×Rn
Apply the selection conditions from the WHERE clause
Project the results onto a1,a2,…,ak
SELECT a1, a2, …, ak
FROM R1 AS x1, R2 AS x2, …, Rn AS xn
WHERE <conditions>;
CS 564 (Fall'17)

6. Review Example User(UID: string, Name: string, Age: int)
Event(EID: string, Name: string, Location: string,
StartDT: DateTime, EndDT: DateTime, Description: string,
CreatorUID: string, CreateDT: DateTime)
ParticipateIn(EID: string, UID: string, RSVPDT: DateTime)
What are the Names of all Users who have participated in some Super Bowl Event?
SELECT U.Name
FROM User U, Event E, ParticipateIn P
WHERE U.UID = P.UID AND E.EID = P.EID AND
(E.Name LIKE ‘%SuperBowl%’ OR
E.Name LIKE ‘%Super Bowl%’);
CS 564 (Fall'17)

7. Set (and Bag) Operations
Student
UNION
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
PHYS 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Class = 21;
Union-compatible
UNION
SELECT Name
FROM Student
WHERE Major = ‘CS’;
Name
Brown
Moreno
Bakhtiari
Set semantics
CS 564 (Fall'17)

8. Set (and Bag) Operations (Cont.)
Student
UNION ALL
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
PHYS 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Class = 21;
UNION ALL
SELECT Name
FROM Student
WHERE Major = ‘CS’;
Name
Moreno
Bakhtiari
Brown
Bag semantics
CS 564 (Fall'17)

9. Set (and Bag) Operations (Cont.)
Student
INTERSECT
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
PHYS 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Class = 21;
INTERSECT
SELECT Name
FROM Student
WHERE Major = ‘CS’;
Name
Bakhtiari
CS 564 (Fall'17)

10. Set (and Bag) Operations (Cont.)
Student
EXCEPT (set minus)
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
PHYS 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Class = 21;
EXCEPT
SELECT Name
FROM Student
WHERE Major = ‘CS’;
Name
Moreno
CS 564 (Fall'17)

11. Nested Queries
Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What are the Names of all Courses which are in the same Department as “Database Management Systems”?
SELECT Name
FROM Course
WHERE Department =
(SELECT Department
WHERE Name = ‘Database Management Systems’);
CS 564 (Fall'17)

12. Nested Queries (Cont.)
A parenthesized SELECT-FROM- WHERE statement (subquery) used in
SELECT clauses
FROM clauses
WHERE clauses
Easier to write certain types of queries using nested queries
SELECT CID, Name
FROM (SELECT *
FROM Course
WHERE Department = ‘CS’)
WHERE Name LIKE ‘%Management%’;
CS 564 (Fall'17)

13. Unnesting
Rewriting a nested query without subqueries such that the rewritten version is equivalent to the original query; i.e. they return the same data for any database instance
Query optimizers can use unnesting to speed-up the execution of certain queries
CS 564 (Fall'17)

14. Unnesting (Cont.) SELECT CID, Name FROM (SELECT * FROM Course
WHERE Department = ‘CS’)
WHERE Name LIKE ‘%Management%’;
Can you unnest this query?
SELECT CID, Name
FROM Department
WHERE Department = ‘CS’ AND
Name LIKE ‘%Management%’;
CS 564 (Fall'17)

15. Unnesting (Cont.) SELECT D.Name FROM Department AS D WHERE D.DID = (
SELECT Major
FROM Student
WHERE SID = 17);
Can you unnest this query?
SELECT D.Name
FROM Department AS D, Student AS S
WHERE D.DID = S.Major AND
S.SID = 17;
CS 564 (Fall'17)

16. Set Comparison Operators in Nested Queries: IN
User(UID, Name, Age)
Event(EID, Name, Location, StartDT, EndDT, Description,
CreatorUID, CreateDT)
What are the Names of all Events whose creators are under 18?
SELECT E.Name
FROM Event AS E
WHERE E.CreatorID IN (
SELECT UID
FROM User
WHERE Age < 18);
CS 564 (Fall'17)

17. Set Comparison Operators in Nested Queries: NOT IN
User(UID, Name, Age)
Event(EID, Name, Location, StartDT, EndDT, Description,
CreatorUID, CreateDT)
What are the Names of all Events whose creators are NOT under 18?
SELECT E.Name
FROM Event AS E
WHERE E.CreatorID NOT IN (
SELECT UID
FROM User
WHERE Age < 18);
Q: Not the same as using IN and Age >= 18. Why?
A: NULLs!
CS 564 (Fall'17)

18. Set Comparison Operators in Nested Queries: EXISTS
Course(CID, Name, Credits, Department)
Section(SecID, CID, Semester, Year, Instructor)
What are the Names of all Courses which have at least one Section offered in 2010?
SELECT C.Name
FROM Course AS C
WHERE EXISTS (
SELECT *
FROM Section AS S
WHERE S.Year = ‘2010’ AND
C.CID = S.CID);
Correlated subqueries
CS 564 (Fall'17)

19. Set Comparison Operators in Nested Queries: NOT EXISTS
Course(CID, Name, Credits, Department)
Section(SecID, CID, Semester, Year, Instructor)
What are the Names of all Courses which have no Sections offered in 2010?
SELECT C.Name
FROM Course AS C
WHERE NOT EXISTS (
SELECT *
FROM Section AS S
WHERE S.Year = ‘2010’ AND
C.CID = S.CID);
CS 564 (Fall'17)

20. Set Comparison Operators in Nested Queries: UNIQUE
Course(CID, Name, Credits, Department)
Section(SecID, CID, Semester, Year, Instructor)
What are the Names of all Courses which have at most one Section offered each year?
Returns TRUE if there are no duplicates in the results of the subquery (empty results set yields true)
SELECT C.Name
FROM Course AS C
WHERE UNIQUE (
SELECT Year
FROM Section AS S
WHERE C.CID = S.CID);
CS 564 (Fall'17)

21. Set Comparison Operators in Nested Queries: NOT UNIQUE
Course(CID, Name, Credits, Department)
Section(SecID, CID, Semester, Year, Instructor)
What are the Names of all Courses which have more than one Section offered in at least one year?
SELECT C.Name
FROM Course AS C
WHERE NOT UNIQUE (
SELECT Year
FROM Section AS S
WHERE C.CID = S.CID);
CS 564 (Fall'17)

22. Set Comparison Operators in Nested Queries: ANY
Course(CID, Name, Credits, Department)
Section(SecID, CID, Semester, Year, Instructor)
What are the Names of all Courses some Section of which has been offered after some Course offered by the late Jim Gray?
SELECT C.Name
FROM Course AS C, Section AS S1
WHERE C.CID = S1.CID AND
S1.Year > ANY (
SELECT S2.Year
FROM Section AS S2
WHERE S2.Instructor = ‘Jim Gray’);
CS 564 (Fall'17)

23. Set Comparison Operators in Nested Queries: ALL
Course(CID, Name, Credits, Department)
Section(SecID, CID, Semester, Year, Instructor)
What are the Names of all Courses some Section of which has been offered before any Courses offered by the late Jim Gray?
SELECT C.Name
FROM Course AS C, Section AS S1
WHERE C.CID = S1.CID AND
S1.Year < ALL (
SELECT S2.Year
FROM Section AS S2
WHERE S2.Instructor = ‘Jim Gray’);
CS 564 (Fall'17)

24. Recap Multi-relation queries Aliases Set and bag operations
Basis SELECT
SELECT *, arithmetic expressions, LIKE, ORDER BY, LIMIT
Multi-relation queries
Aliases
Set and bag operations
Nested queries and unnesting
Set comparison operators
(NOT) IN, (NOT) EXISTS, (NOT) UNIQUE, op ANY, op ALL
op ∈ {=, <>, >, >=, <, <=}
CS 564 (Fall'17)

25. Rewriting INTERSET Using IN
SELECT Name
FROM Student
WHERE Class = 21
INTERSECT
WHERE Major = ‘CS’;
SELECT Name
FROM Student
WHERE Class = 21
AND SID IN (
SELECT SID
WHERE Major = ‘CS’);
CS 564 (Fall'17)

26. Rewriting EXCEPT Using NOT IN
SELECT Name
FROM Student
WHERE Class = 21
EXCEPT
WHERE Major = ‘CS’;
SELECT Name
FROM Student
WHERE Class = 21
AND SID NOT IN (
SELECT SID
WHERE Major = ‘CS’);
CS 564 (Fall'17)

27. Aggregates Getting into the realm of data analytics
Applied to a column to generate aggregated values
SUM, AVG, COUNT, MIN, MAX
CS 564 (Fall'17)

28. COUNT SELECT COUNT(*) FROM Course WHERE Department = ‘CS’; Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
How many Courses does CS department offer?
SELECT COUNT(*)
FROM Course
WHERE Department = ‘CS’;
COUNT(*) 3
CS 564 (Fall'17)

29. COUNT DISTINCT SELECT COUNT(DISTINCT Credits) FROM Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
How many different Credits CS department Courses have?
SELECT COUNT(DISTINCT Credits)
FROM Course
WHERE Department = ‘CS’;
COUNT(DISTINCT Credits) 2
CS 564 (Fall'17)

30. SUM SELECT SUM(Credits) FROM Course WHERE Department = ‘CS’; Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What is the total number of Credits for CS department Courses?
SELECT SUM(Credits)
FROM Course
WHERE Department = ‘CS’;
SUM(Credits) 10
CS 564 (Fall'17)

31. AVG SELECT AVG(Credits) FROM Course WHERE Department = ‘CS’; Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What is the average number of Credits for CS department Courses?
SELECT AVG(Credits)
FROM Course
WHERE Department = ‘CS’;
AVG(Credits)
3.33
CS 564 (Fall'17)

32. MAX and MIN Column renaming SELECT MAX(Credits) AS MaxCreds,
Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What are the max and min number of Credits for CS department Courses?
SELECT MAX(Credits) AS MaxCreds,
MIN(Credits) AS MinCreds
FROM Course
WHERE Department = ‘CS’;
MaxCreds
MinCreds 4 3
Column renaming
CS 564 (Fall'17)

33. Aggregates (Cont.) SELECT CID, MAX(Credits) AS MaxCreds FROM Course
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
SELECT CID,
MAX(Credits) AS MaxCreds
FROM Course
WHERE Department = ‘CS’;
Q: Is this a valid query?
A: No. Can’t use attributes in the target-list as such.
CS 564 (Fall'17)

34. Aggregates (Cont.) SELECT C1.Name FROM Course AS C1
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What are the Names of all Courses whose number of Credits is greater than the overall average number of Credits across all Departments?
SELECT C1.Name
FROM Course AS C1
WHERE C1.Credits > (
SELECT AVG(C2.Credits)
FROM Course AS C2 );
Name
Discrete Mathematics
Intro to Data Structures
CS 564 (Fall'17)

35. Aggregates on Groups
How about computing average number of Credits for Courses in each Department separately?
Write an aggregation query for each Department, or …
Use GROUP BY clause
CS 564 (Fall'17)

36. GROUP BY
Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What are the average number of Credits for Courses in each Department ?
SELECT Department,
AVG(Credits) AS AvgCreds
FROM Course
GROUP BY Department;
Department
AvgCreds
MATH 4 CS
3.33
CS 564 (Fall'17)

37. GROUP BY (Cont.)
If any aggregation is used, then each element of the SELECT list must be either
aggregated, or
an attribute on the GROUP BY list
What if we are only interested in retrieving groups satisfying a specific condition; e.g. all the Departments with average number of Credits above 3.5?
Use HAVING clause
CS 564 (Fall'17)

38. GROUP BY … HAVING SELECT Department, AVG(Credits) AS AvgCreds
Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What are all the Departments with average number of Credits above 3.5??
SELECT Department,
AVG(Credits) AS AvgCreds
FROM Course
GROUP BY Department
HAVING AvgCreds > 3.5;
Department
AvgCreds
MATH 4
CS 564 (Fall'17)

39. GROUP BY … HAVING (Cont.)
Course
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
What are the average number of Credits for Courses in each Department offering more than one Course?
SELECT Department,
AVG(Credits) AS AvgCreds
FROM Course
GROUP BY Department
HAVING COUNT(*) > 1;
Department
AvgCreds CS
3.33
CS 564 (Fall'17)

40. Recap: Aggregates
SELECT [DISTINCT] target-list
FROM relation-list
[WHERE condition]
GROUP BY grouping-list
HAVING group-condition;
target-list may contain from grouping- list and/or any aggregates, but no other attributes
condition may contain conditions on any attributes in relation-list
group-condition may contain conditions on aggregate expressions
CS 564 (Fall'17)

41. Recap: Aggregates (Cont.)
SELECT [DISTINCT] target-list
FROM relation-list
[WHERE condition]
GROUP BY grouping-list
HAVING group-condition;
Conceptual evaluation steps
Compute the FROM relation-list [WHERE condition] part, obtain a table with all attributes in relation-list
Group by the attributes in grouping-list
Compute the aggregates in group-condition and keep only groups satisfying the conditions
Compute aggregates in target-list and return the result
CS 564 (Fall'17)

42. NULL: The Hairy Beast (Revisited)
A special value which signifies one of the following:
Nonexistent value
e.g. a Student has not declared a Major
Missing value
e.g. a Student has not entered their Height
Not applicable
e.g. a single-family Home does not have an AptNo
NULL does not mean 0, “” or NaN.
NULL ≠ NULL
824
Fernando 19
NULL
CS 564 (Fall'17)

43. NULL and Simple Predicates
Student
What are the Names of all Students who have declared a CS Major?
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
NULL 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Major = ‘CS’;
NULL values “fail” to satisfy the condition due to ambiguity.
Name
Brown
Bakhtiari
CS 564 (Fall'17)

44. NULL and Complicated Predicates
Student
What are the Names of all Students who have declared a CS Major or are in Class 21?
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
NULL 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Major = ‘CS’ OR
Class = 21;
Q: What would the result set look like?
CS 564 (Fall'17)

45. Binary Logic Familiar, two-valued logic OR TRUE FALSE AND TRUE FALSE
NOT
TRUE
FALSE
CS 564 (Fall'17)

46. Ternary Logic
Predicates including NULLs would be evaluated to UNKNOWN. OR
TRUE
FALSE
UNKNOWN
AND
TRUE
FALSE
UNKNOWN
NOT
TRUE
FALSE
UNKNOWN
CS 564 (Fall'17)

47. NULL and Complicated Predicates
Student
What are the Names of all Students who have declared a CS Major or are in Class 21?
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
NULL 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Major = ‘CS’ OR
Class = 21;
Name
Brown
Moreno
Bakhtiari
CS 564 (Fall'17)

48. NULL and Complicated Predicates
Student
SID
Name
Class
Major 17
Smith 22
MATH 8
Brown 24 CS 5
Moreno 21
NULL 23
Boll
BIOL 7
Bakhtiari
SELECT Name
FROM Student
WHERE Major = ‘CS’ OR
Major <> ‘CS’;
Name
Smith
Brown
Boll
Bakhtiari
CS 564 (Fall'17)

49. Recap Multi-relation queries Aliases Set and bag operations
Basis SELECT
SELECT *, arithmetic expressions, LIKE, ORDER BY, LIMIT
Multi-relation queries
Aliases
Set and bag operations
Nested queries and unnesting
Set comparison operators
(NOT) IN, (NOT) EXISTS, (NOT) UNIQUE, op ANY, op ALL (op ∈ {=, <>, >, >=, <, <=})
Aggregates
SUM, AVG, COUNT, MIN, MAX
GROUP BY … HAVING
NULL and ternary logic
CS 564 (Fall'17)

50. More DDL Delete a table Modify a table Add a new column
Delete a column
DROP TABLE User;
ALTER TABLE User
ADD COLUMN Weight INT CHECK (Weight < 1000);
ALTER TABLE User
DROP COLUMN Weight;
CS 564 (Fall'17)

51. More DDL: Constraints Declare (alternate) key constraints
CREATE TABLE User (
UID CHAR(20),
Name CHAR(50),
Age INTEGER,
SSN INTEGER,
PRIMARY KEY (UID),
UNIQUE (SSN));
CS 564 (Fall'17)

52. More DDL: Constraints (Cont.)
Integrity constraints
CREATE TABLE User (
UID CHAR(20),
Name CHAR(50),
Age INTEGER,
SSN INTEGER
CHECK (SSN < ),
PRIMARY KEY (UID),
UNIQUE (SSN);
A CHECK is checked (!) when a value for the attribute is inserted or updated.
CS 564 (Fall'17)

53. More DDL: Constraints (Cont.)
Integrity constraints (cont.)
CREATE TABLE User (
UID CHAR(20),
Name CHAR(50),
Age INTEGER,
SSN INTEGER,
PRIMARY KEY (UID),
UNIQUE (SSN),
CHECK (Age >= 0 AND Age <= 150);
CS 564 (Fall'17)

54. More DDL: Constraints (Cont.)
Named integrity constraints
CREATE TABLE Event (
EID CHAR(20), Name CHAR(50), Location CHAR(50),
StartDT DATE, EndDT DATE, Description CHAR(100),
CreatorUID CHAR(20) NOT NULL,
CreateDT DATE,
PRIMARY KEY (EID),
FOREIGN KEY (CreatorUID) REFERENCES User(UID)
CONSTRAINT CreatorAgeConstr
CHECK (18 <= (SELECT U.Age
FROM User AS U
WHERE U.UID = Event.CreatorUID));
CS 564 (Fall'17)

55. Assertions
Another mechanism to declare constraints which span multiple relations
In principle, checked every time any relation in database is modified
CREATE ASSERTION MoreStudsThanProfs
CHECK (
(SELECT COUNT(*) FROM Professor) <=
(SELECT COUNT(*) FROM Student) );
CS 564 (Fall'17)

56. Assertions (Cont.)
In reality, DBMSs are more clever and check only if the assertion can be violated
e.g. the above assertions does not need to be checked if we only change the age of a Student
However, it is not trivial to find out only the assertions that could possibly have been violated upon every update to the database
CS 564 (Fall'17)

57. Triggers
A more general and comprehensive tool to enforce integrity constraints and more!
Follows a Event-Condition-Action model
Event: what activates the trigger
Condition: when the trigger should be executed
Action: how the trigger operates
CS 564 (Fall'17)

58. Example Trigger CREATE TRIGGER AddAgeTrig BEFORE INSERT ON Student
FOR EACH ROW
BEGIN SELECT RAISE(ABORT , ’Age lt average')
WHERE NEW.Age < (
SELECT AVG(Age) FROM Student );
END
Don’t insert a Student whose Age is less than the average Age of current Students.
CS 564 (Fall'17)

59. Trigger General Syntax
CREATE [OR REPLACE] TRIGGER <Trigger name>
{BEFORE | AFTER | INSTEAD OF}
{INSERT | DELETE | UPDATE [OF <Columns>]}
ON <Table name>
[REFERENCING {OLD | NEW} {ROW | TABLE}
AS <Reference name>]
[FOR EACH {ROW | STATEMENT}]
[WHEN (search condition)]
<SQL statement> |
BEGIN [ATOMIC] <SQL statements> END
CS 564 (Fall'17)

60. Triggers (Cont.) “When” of the event “What” of the event
BEFORE, AFTER, INSTEAD OF
“What” of the event
INSERT, DELETE, UPDATE, UPDATE OF <attribute>
Action granularity
FOR EACH ROW, FOR EACH STATEMENT
Referring to modified values
NEW.<attribute>: the new value before the event (INSERT and UPDATE)
OLD.<attribute>: the old value before the event (DELETE and UPDATE)
NEW and OLD can be temporary tables containing all modified tuples
CS 564 (Fall'17)

61. Another Example Trigger
CREATE TRIGGER CreateCourseForSectionTrig
AFTER INSERT ON Section
REFERENCING NEW ROW AS n
FOR EACH ROW
WHEN (NOT EXISTS (
SELECT *
FROM COURSE AS C
WHERE C.CID = n.CID))
BEGIN INSERT INTO Course
VALUES (n.CID, ‘TBD’, 3, ‘CS’);
END
CS 564 (Fall'17)

62. Triggers vs. Constraints
Both provide to enforce integrity and consistency of the database
Constraints are declarative, whereas triggers are “operational”
Having many interrelated triggers can cause unexpected or unwanted behaviors, whereas constraints are easier to understand/reason about
Triggers are more powerful and expressive
Complex integrity constraints (e.g., enforce credit limits)
Form auto-completing
Generating logs for specific auditing/security reasons …
CS 564 (Fall'17)

63. View
A ”virtual table” that is defined based on the contents of other tables (base tables) and views
Useful to avoid rewriting, sometimes complex, queries
Provides logical data independence
Another layer of isolation between end user and database internals
CS 564 (Fall'17)

64. CREATE VIEW CREATE VIEW CourseInfo AS SELECT C.CID, C.Name, C.Credits,
MAX(S.Year) AS YearLastOffered
FROM Course AS C, Section AS S
WHERE C.CID = S.SID
GROUP BY C.CID, C.Name, C.Credits;
CS 564 (Fall'17)

65. Example View CourseInfo Section Course CID Name Credits
Semester
Year
Instructor
30098
MATH240
Fall
2017
Euclid
40026
CS367
2016
Dijkstra
1005
Spring
2004
Gauss
30451
CS764
Patel
20006
CS564
2001
Codd
CID
Name
Credits
Department
CS564
Database Management Systems 3 CS
MATH240
Discrete Mathematics 4
MATH
CS367
Intro to Data Structures
CS764
Adv. Database Management
CourseInfo
CID
Name
Credits
YearLastOffered
CS564
Database Management Systems 3
2001
MATH240
Discrete Mathematics 4
2017
CS367
Intro to Data Structures
2016
CS764
Adv. Database Management
CS 564 (Fall'17)

66. Example View (Cont.) Logical Data Independence CourseInfo Section
SecID
CID
Semester
Year
Instructor
30098
MATH240
Fall
2017
Euclid
40026
CS367
2016
Dijkstra
1005
Spring
2004
Gauss
30451
CS764
Patel
20006
CS564
2001
Codd
CID
Name
Credits
Department
Textbook
CS564
Database Management Systems 3 CS
Cow book
MATH240
Discrete Mathematics 4
MATH
Casino book
CS367
Intro to Data Structures
Tree book
CS764
Adv. Database Management
Complete book
Logical Data Independence
CourseInfo
CID
Name
Credits
YearLastOffered
CS564
Database Management Systems 3
2001
MATH240
Discrete Mathematics 4
2017
CS367
Intro to Data Structures
2016
CS764
Adv. Database Management
CS 564 (Fall'17)

67. Query A View SELECT * FROM CourseInfo; DBMS Query Rewriting SELECT *
FROM (SELECT C.CID, C.Name, C.Credits,
MAX(S.Year) AS YearLastOffered
FROM Course AS C, Section AS S
WHERE C.CID = S.SID
GROUP BY C.CID, C.Name, C.Credits);
CS 564 (Fall'17)

68. Update A View A bit trickier since a view does not really exist
Possible solution: using triggers!
Still tricky since multiple underlying base tables might need to change
CS 564 (Fall'17)

69. Update A View (Cont.) CREATE TRIGGER ClassInfoInsert
CREATE VIEW ClassInfo AS
SELECT C.CID, C.Name, C.Credits, S.Semester, S.Year
FROM Course AS C, Section AS S
WHERE C.CID = S.SID;
CREATE TRIGGER ClassInfoInsert
INSTEAD OF INSERT ON ClassInfo
FOR EACH ROW
BEGIN
INSERT INTO Course
VALUES (NEW.CID, NEW.Name,
NEW.Credits, ‘CS’);
INSERT INTO Section
VALUES (
(SELECT MAX(S.SID) FROM Section AS S) + 1,
NEW.CID, NEW.Semester, NEW.Year, ‘TBA’ );
END;
CS 564 (Fall'17)

70. Recap Set and bag operations Nested queries and unnesting
Basis SELECT, multi-relation queries and aliases
Set and bag operations
Nested queries and unnesting
Set comparison operators
Aggregates
NULL and ternary logic
Integrity Constraints
CHECK, CONSTRAINT, ASSERTION, TRIGGER
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CS 564 (Fall'17)

71. Schema Refinement: Escaping Data Traps
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Schema Refinement: Escaping Data Traps
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CS 564 (Fall'17)