CS 405G: Introduction to
Database Systems
Lecture 7: SQL II
Instructor: Chen Qian



Homework 2 due on 2/26
Next Monday (2/29) Dr. Qian will be on business travel.
The TA Fatemah Alghamedy will give a lecture of
practicing questions.
Propose to change Midterm exam to 3/9 (1-2pm)
7/1/2016
Chen Qian @ University of Kentucky
2
Today’s Topic



NULL value
Outer join
Nested queries
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Chen Qian @ University of Kentucky
3
Incomplete information


Example: Student (SID, name, age, GPA)
Value unknown


Value not applicable


We do not know Nelson’s age
Nelson has not taken any classes yet; what is his GPA?
How to express these values in SQL language?
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Chen Qian @ University of Kentucky
4
Solution 1

A dedicated special value for each domain (type)


GPA cannot be –1, so use –1 as a special value to indicate
a missing or invalid GPA
Leads to incorrect answers if not careful


Complicates applications


SELECT AVG(GPA) FROM Student;
SELECT AVG(GPA) FROM Student
WHERE GPA <> -1;
Remember the Y2K bug?

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“00” was used as a missing or invalid year value
Chen Qian @ University of Kentucky
5
Solution 2

A valid-bit for every column


Student (SID, name, name_is_valid,
age, age_is_valid,
GPA, GPA_is_valid)
Complicates schema and queries

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SELECT AVG(GPA) FROM Student
WHERE GPA_is_valid;
Chen Qian @ University of Kentucky
6
Solution 3?

Decompose the table; missing row = missing value




StudentName (SID, name)
StudentAge (SID, age)
StudentGPA (SID, GPA)
StudentID (SID)
Conceptually the cleanest solution
Still complicates schema and queries


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How to get all information about a student in a table?
Would natural join work?
Chen Qian @ University of Kentucky
7
SQL’s solution

A special value NULL



For every domain
Special rules for dealing with NULL’s
Example: Student (SID, name, age, GPA)

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< 789, “Nelson”, NULL, NULL >
Chen Qian @ University of Kentucky
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Three-valued logic





TRUE = 1, FALSE = 0, UNKNOWN = 0.5
x AND y = min(x, y)
x OR y = max(x, y)
NOT x = 1 – x
AND
True
True
True
False
False
NULL
UNK
False
NULL
False False
UNK False
AND
False
UNK
OR
True
True
True
False
False
NULL
TRUE
False False False
NULL TRUE UNK
OR
UNK
UNK
WHERE and HAVING clauses only select rows for output if the
condition evaluates to TRUE

UNKNOWN is not enough
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Chen Qian @ University of Kentucky
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Computing with NULL’s



(Arithmetic operation) when we operate on a NULL and
another value (including another NULL) using +, –, etc.,
the result is NULL
Aggregate functions ignore NULL, except COUNT(*)
(since it counts rows)
When we compare a NULL with another value
(including another NULL) using =, >, etc., the result is
UNKNOWN
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Chen Qian @ University of Kentucky
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Unfortunate consequences

SELECT AVG(GPA) FROM Student


SELECT SUM(GPA)/COUNT(*) FROM Student;



3.4
2.72
SELECT * FROM Student;
SELECT * FROM Student WHERE GPA = GPA

Not equivalent
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sid
name
age
gpa
1234
John Smith
21
3.5
1123
Mary Carter
19
3.8
1011
Bob Lee
22
NULL
1204
Susan Wong
22
3.4
1306
Kevin Kim
18
2.9
Chen Qian @ University of Kentucky
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Another problem

Example: Who has NULL GPA values?

SELECT * FROM Student WHERE GPA =
NULL;


(SELECT * FROM Student)
EXCEPT ALL
(SELECT * FROM Student WHERE GPA =
GPA)


Does not work; never returns anything
Works, but ugly
Introduced built-in predicates IS NULL and IS NOT
NULL

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SELECT * FROM Student WHERE GPA IS NULL;
Chen Qian @ University of Kentucky
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Outerjoin motivation

Example: a master class list
SELECT c.CID, s.SID
FROM Enroll e, Student s, Course c

WHERE e.SID = s.SID and c.CID = e.CID;

What if a student take no classes


What if a course with no student enrolled yet?


For these students, CID column should be NULL
For these courses, SID should be NULL
Therefore the above query does not return the complete
list!
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Chen Qian @ University of Kentucky
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Outerjoin

SELECT * FROM R FULL OUTER JOIN S ON p;

A full outer join between R and S (denoted R
includes all rows in the result of R pS, plus


S)
“Dangling” R rows (those that do not join with any S
rows) padded with NULL’s for S’s columns
“Dangling” S rows (those that do not join with any R
rows) padded with NULL’s for R’s columns
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Chen Qian @ University of Kentucky
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Outerjoin (II)

SELECT * FROM R LEFT

SELECT * FROM R RIGHT OUTER JOIN S ON p;

A left outer join includes rows in R S plus dangling R rows
padded with NULL’s
A right outer join includes rows in R S plus dangling S rows
padded with NULL’s

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OUTER JOIN S ON p;;
Chen Qian @ University of Kentucky
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Outerjoin examples
SELECT * FROM Employee LEFT OUTER
JOIN Department ON Eid = Mid
Employee
Eid
Name
Eid
Name
Did
Mid
Dname
1123
John Smith
1123
John Smith
4
1123
Research
1234
Mary Carter
1234
Mary Carter
5
1234
Finance
1311
Bob Lee
1311
Bob Lee
NULL
NULL
NULL
SELECT * FROM Employee FULL
RIGHTOUTER
OUTER
JOIN Department ON Eid = Mid
Department
Did
Mid
Dname
Eid
Name
Did
Mid
Dname
4
1123
Research
1123
John Smith
4
1123
Research
5
1234
Finance
1234
Mary Carter
5
1234
Finance
6
1312
HR
NULL
1311
Bob
NULL
Lee
NULL
6
NULL
1312
NULL
HR
NULL
NULL
6
1312
HR
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Chen Qian @ University of Kentucky
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Summary

Query







SELECT-FROM-WHERE statements
Ordering
Set and bag operations
Aggregation and grouping
Table expressions, subqueries
NULL
Outerjoins
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Chen Qian @ University of Kentucky
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Exercise


Goal: Get the Name of one’s supervisor
EMPLOYEE (Eid, Mid, Name)
SQL Statement:
SELECT EID, Name FROM EMPLOYEE WHERE MId
=Eid;
SELECT E1.EID, E2.Name FROM EMPLOYEE E1,
EMPLOYEE E2 WHERE E1.MId = E2.EId;
Eid
Mid
Name
Eid
Name
1123
1234
John Smith
1123
Mary Carter
1234
1311
Mary Carter
1234
Bob Lee
1311
1611
Bob Lee
1311
Jack Snow
1455
1611
Lisa Wang
1455
Jack Snow
1611
1611
Jack Snow
1611
Jack Snow
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Chen Qian @ University of Kentucky
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
SELECT DISTINCT E2.Name FROM EMPLOYEE
E1, EMPLOYEE E2 WHERE E1.MId = E2.EId;
Name
Mary Carter
Bob Lee
Jack Snow
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Chen Qian @ University of Kentucky
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More on Nested Queries: Scoping

To find out which table a column belongs to



Start with the immediately surrounding query
If not found, look in the one surrounding that; repeat if
necessary
Use table_name.column_name notation and AS
(renaming) to avoid confusion
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Chen Qian @ University of Kentucky
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An Example
SELECT * FROM Student s
WHERE EXISTS
(SELECT * FROM Enroll e
WHERE SID = s.SID
AND EXISTS
(SELECT * FROM Enroll
WHERE SID = s.SID
AND CID <> e.CID));
Students who are taking at least two courses
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Chen Qian @ University of Kentucky
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Quantified subqueries


A quantified subquery can be used as a value in a WHERE
condition
Universal quantification (for all):
… WHERE x op ALL (subquery) …


True iff for all t in the result of subquery, x op t
Existential quantification (exists):
… WHERE x op ANY (subquery) …


True iff there exists some t in the result of subquery such that x op t
Beware


7/1/2016
In common parlance, “any” and “all” seem to be synonyms
In SQL, ANY really means “some”
Chen Qian @ University of Kentucky
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Examples of quantified subqueries

Which employees have the highest salary?
Employee (Sid, Name, Salary)
 SELECT *
FROM Employee
WHERE Salary >= ALL
(SELECT Salary FROM Employee);

How about the lowest salary?

SELECT *
FROM Employee
WHERE Salary <= ALL
(SELECT salary FROM Employee);
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Chen Qian @ University of Kentucky
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More ways of getting the highest Salary

Who has the highest Salary?


SELECT * FROM Employee e
WHERE NOT EXISTS
(SELECT * FROM Employee
WHERE Salary > e.Salary);
SELECT * FROM Employee
WHERE Eid NOT IN
(SELECT e1.SID
FROM Employee e1, Employee e2
WHERE e1.Salary < e2.Salary);
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Chen Qian @ University of Kentucky
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Nested Queries

Nested queries do not add expression power to SQL



For convenient
Write intuitive SQL queries
Can always use SQL queries without nesting to complete
the same task (though sometime it is hard)
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Chen Qian @ University of Kentucky
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More Exercise
Sailors (sid: INTEGER, sname: string, rating: INTEGER, age:
REAL)
Boats (bid: INTEGER, bname: string, color: string)
Reserves (sid: INTEGER, bid: INTEGER)
Sailors
Boats
sid
1
sname
Fred
2
3
Jim
2
Nancy 8
Reserves
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rating
7
sid
bid
1
2
102
102
age
22
bid
101
bname
Nina
color
red
39
27
102
103
Pinta
Santa
Maria
blue
red
Chen Qian @ University of Kentucky
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Exercise I



Find sid’s of sailors who’ve reserved a red AND a green boat
SELECT R1.sid
FROM Boats B1, Reserves R1, Boats B2, Reserves R2
WHERE B1.color=‘red’ AND B2.color=‘green’
AND R1.bid=B1.bid AND R2.bid=B2.bid
AND R1.sid=R2.sid
SELECT sid
FROM Boats, Reserves
Where B.color = ‘red’
INTERSECT
(SELECT sid
FROM Boats, Reserves
Where B.color = ‘green’)
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Chen Qian @ University of Kentucky
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Exercise II

Find sid’s of sailors who have not reserved a boat
SELECT sid
Non-monotonic operation!
FROM Sailors
EXCEPT
(SELECT S.sid
FROM Sailors S, Reserves R
WHERE S.sid=R.sid)
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Chen Qian @ University of Kentucky
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Exercise III (a tough one)

Find sailors who’ve reserved all boats
Non-monotonic operation!
SELECT Sid
FROM Sailor
#All sailors
EXCEPT
#Those who do not reserve all
SELECT Sid
boats
FROM
#All possible combinations
(SELECT bid, sid
between sid and bid
FROM Boat, Sailor
EXCEPT
#Existing reservations
Reserves)
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Chen Qian @ University of Kentucky
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Summary of SQL features
covered so far

SELECT-FROM-WHERE statements


Set and bag operations
Ordering
Aggregation and grouping
Table expressions, subqueries
NULL’s and outerjoins

Next: data modification statements, constraints



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Chen Qian @ University of Kentucky
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Review: Create Table in SQL

An SQL relation is defined using the create table
command:
CREATE TABLE r (A1 D1, A2 D2, ..., An Dn,
(integrity-constraint1),
...,
(integrity-constraintk))



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r is the name of the relation
each Ai is an attribute name in the schema of relation r
Di is the data type of values in the domain of attribute Ai
Chen Qian @ Univ. of Kentucky
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Constrains in SQL

Attribute constraint



Key constraint



NOT NULL
DEFAULT <value>
PRIMARY KEY
UNIQUE
Referential Integrity

FOREIGN KEY
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Constraints in Table Declaration

Restrictions on allowable data in a database




In addition to the simple structure and type restrictions
imposed by the table definitions
Declared as part of the schema
Enforced by the DBMS
Why use constraints?


Protect data integrity (catch errors)
Tell the DBMS about the data (so it can optimize better)
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Types of SQL constraints



Key constraint
NOT NULL
Referential integrity (foreign key)
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Key declaration

At most one PRIMARY KEY per table



Typically implies a primary index
Rows are stored inside the index, typically sorted by the
primary key value ( best speedup for queries)
Any number of UNIQUE keys per table


Typically implies a secondary index
To speedup queries
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NOT NULL

Indicates that the value of an attribute can not be NULL
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Examples



CREATE TABLE Student
(SID INTEGER NOT NULL PRIMARY KEY,
name VARCHAR(30) NOT NULL,
Used for query
email VARCHAR(30) UNIQUE,
age INTEGER,
processing
GPA FLOAT);
CREATE TABLE Course
(CID CHAR(10) NOT NULL PRIMARY KEY,
title VARCHAR(100) NOT NULL);
CREATE TABLE Enroll
(SID INTEGER NOT NULL,
CID CHAR(10) NOT NULL,
PRIMARY KEY(SID, CID));
This form is required for multi-attribute keys
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Referential integrity example



Enroll.SID references Student.SID
 If an SID appears in Enroll, it must appear in Student
Enroll.CID references Course.CID
 If a CID appears in Enroll, it must appear in Course
That is, no “dangling pointers”
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Chen Qian @ Univ. of Kentucky
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Referential integrity in SQL

Referenced column(s) must be PRIMARY KEY
Referencing column(s) form a FOREIGN KEY

Example


CREATE TABLE Enroll
(SID INTEGER NOT NULL,
CID CHAR(10) NOT NULL,
PRIMARY KEY(SID, CID),
FOREIGN KEY CID REFERENCES
Course(CID)
FOREIGN KEY SID REFERENCES
Student(SID));
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Chen Qian @ Univ. of Kentucky
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Enforcing referential integrity
Example: Enroll.SID references Student.SID
 Insert or update an Enroll row so it refers to a nonexistent SID


Reject
Delete or update a Student row whose SID is referenced
by some Enroll row





Reject
Cascade: ripple changes to all referring rows
Set NULL: set all references to NULL
Set DEFAULT: use the default value of the attribute
All four options can be specified in SQL
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Database Modification Operations



INSERT
DELETE
UPDATE
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INSERT

Insert one row

INSERT INTO Enroll VALUES (456,
’EECS647’);


Student 456 takes EECS647
Insert the result of a query

INSERT INTO Enroll
(SELECT SID, ’CS647’ FROM Student
WHERE SID NOT IN (SELECT SID FROM
Enroll
WHERE CID = ’CS647’));

7/1/2016
Qian @
Univ. of Kentucky
Force everybody toChen
take
EECS647!
42
DELETE

Delete everything


DELETE FROM Enroll;
Delete according to a WHERE condition
Example: Student 456 drops CS116

DELETE FROM Enroll
WHERE SID = 456 AND CID = ’CS116’;
Example: Drop students from all CS classes with GPA lower than
1.0

7/1/2016
DELETE FROM Enroll
WHERE SID IN (SELECT SID FROM Student
WHERE GPA < 1.0)
AND CID LIKE ’CS%’;
Chen Qian @ Univ. of Kentucky
43
UPDATE

Example: Student 142 changes name to “Barney”

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UPDATE Student
SET name = ’Barney’
WHERE SID = 142;
Chen Qian @ Univ. of Kentucky
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Summary of SQL features
covered so far

Query








Constraints
Modification


SELECT-FROM-WHERE statements
Set and bag operations
Table expressions, subqueries
Aggregation and grouping
Ordering
Outerjoins
INSERT/DELETE/UPDATE
Next: triggers, views, indexes
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Chen Qian @ Univ. of Kentucky
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Tuple- and attribute-based CHECK’s



Associated with a single table
Only checked when a tuple or an attribute is inserted or
updated
Example:

CREATE TABLE Enroll
(SID INTEGER NOT NULL
CHECK (SID IN (SELECT SID FROM
Student)),
CID ...);

Is it a referential integrity constraint?
Not quite; not checked when Student is modified

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Build-in Domain Types in SQL

Numeric:





int. Integer.
smallint. Small integer (a machine-dependent subset of the integer
domain type).
decimal(p,d). Fixed point number, with user-specified precision of a
total of p digits, with d digits to the right of decimal point.
real, double precision. Floating point and double-precision floating
point numbers.
String


char(n). Fixed length character string, with user-specified length n.
varchar(n). Variable length character strings, with user-specified
maximum length n.
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User-Created Domains

CREATE DOMAIN <domain name> AS <domain type>

Example


CREATE DOMAIN SSN_TYPE as CHAR(9)
CREATE DOMAIN SALARY as Int
CHECK SALARY > 0
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Drop and Alter Table Constructs


The drop table command deletes all information
about the dropped relation from the database.
The alter table command is used to add attributes
to an existing relation:
ALTER TABLE r ADD[DROP] COLUMN A D
where A is the name of the attribute to be added
(dropped) to relation r and D is the domain of A.

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All tuples in the relation are assigned null as the
value for the new attribute.
Chen Qian @ Univ. of Kentucky
49
Advanced Techniques

No-chicken-no-egg problem



CREATE TABLE Dept
(name CHAR(20) NOT NULL PRIMARY KEY,
chair CHAR(30) NOT NULL REFERENCES
Prof(name));
CREATE TABLE Prof
(name CHAR(30) NOT NULL PRIMARY KEY,
dept CHAR(20) NOT NULL REFERENCES
Dept(name));
The first INSERT will always violate a constraint!
Deferred constraint checking is necessary


Check only at the end of a transaction
Allowed in SQL as an option
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“Active” data

Constraint enforcement: When an operation violates a
constraint, abort the operation or try to “fix” data



Example: enforcing referential integrity constraints
Generalize to arbitrary constraints?
Data monitoring: When something happens to the data,
automatically execute some action


Example: When price rises above $20 per share, sell
Example: When enrollment is at the limit and more
students try to register, email the instructor
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51
Triggers

A trigger is an event-condition-action (ECA) rule


When event occurs, test condition; if condition is
satisfied, execute action
Example:



Event: whenever there comes a new student…
Condition: with GPA higher than 3.0…
Action: then make him/her take CS 405G!
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Chen Qian @ Univ. of Kentucky
52
Trigger example
CREATE TRIGGER CS405AutoRecruit
AFTER INSERT ON Student Event
REFERENCING NEW ROW AS newStudent
FOR EACH ROW
WHEN (newStudent.GPA > 3.0)Condition
INSERT INTO Enroll
VALUES(newStudent.SID, ’CS405’);
Action
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Trigger options

Possible events include:




Granularity—trigger can be activated:



INSERT ON table
DELETE ON table
UPDATE [OF column] ON table
FOR EACH ROW modified
FOR EACH STATEMENT that performs modification
Timing—action can be executed:

AFTER or BEFORE the triggering event
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Transition variables





OLD ROW: the modified row before the triggering event
NEW ROW: the modified row after the triggering event
OLD TABLE: a hypothetical read-only table containing all
modified rows before the triggering event
NEW TABLE: a hypothetical table containing all modified rows
after the triggering event
Not all of them make sense all the time, e.g.

AFTER INSERT statement-level triggers


BEFORE DELETE row-level triggers


Can use only NEW TABLE
Can use only OLD ROW
etc.
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Chen Qian @ Univ. of Kentucky
55
Statement-level trigger example
CREATE TRIGGER AutoRecruit
AFTER INSERT ON Student
REFERENCING NEW TABLE AS newStudents
FOR EACH STATEMENT
INSERT INTO Enroll
(SELECT SID, ’CS405’
FROM newStudents
WHERE GPA > 3.0);
Efficiency???
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Chen Qian @ Univ. of Kentucky
56
BEFORE trigger example



Never give faculty more than 50% raise in one update
CREATE TRIGGER NotTooGreedy
BEFORE UPDATE OF salary ON Faculty
REFERENCING OLD ROW AS o, NEW ROW AS n
FOR EACH ROW
WHEN (n.salary > 1.5 * o.salary)
SET n.salary = 1.5 * o.salary;
BEFORE triggers are often used to “condition” data
Another option is to raise an error in the trigger body to abort the
transaction that caused the trigger to fire
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Chen Qian @ Univ. of Kentucky
57
Statement- vs. row-level triggers
Why are both needed?
 Certain triggers are only possible at statement level


If the average GPA of students inserted by this statement
exceeds 3.0, do …
Simple row-level triggers are easier to implement and
may be more efficient


Statement-level triggers require significant amount of
state to be maintained in OLD TABLE and NEW TABLE
However, a row-level trigger does get fired for each row,
so complex row-level triggers may be inefficient for
statements that generate lots of modifications
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Chen Qian @ Univ. of Kentucky
58
Another statement-level trigger

Give faculty a raise if GPA’s in one update statement are all
increasing
CREATE TRIGGER AutoRaise
AFTER UPDATE OF GPA ON Student
REFERENCING OLD TABLE AS o, NEW TABLE AS n
FOR EACH STATEMENT
WHEN (NOT EXISTS(SELECT * FROM o, n
WHERE o.SID = n.SID
AND o.GPA >= n.GPA))
UPDATE Faculty SET salary = salary + 1000;

A row-level trigger would be difficult to write in this case
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Chen Qian @ Univ. of Kentucky
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System issues

Recursive firing of triggers


Action of one trigger causes another trigger to fire
Can get into an infinite loop



Some DBMS restrict trigger actions
Most DBMS set a maximum level of recursion (16 in DB2)
Interaction with constraints (very tricky to get right!)

When do we check if a triggering event violates constraints?


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After a BEFORE trigger (so the trigger can fix a potential violation)
Before an AFTER trigger
AFTER triggers also see the effects of, say, cascaded deletes caused
by referential integrity constraint violations
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Views

A view is like a “virtual” table



Defined by a query, which describes how to compute the
view contents on the fly
DBMS stores the view definition query instead of view
contents
Can be used in queries just like a regular table
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Creating and dropping views

Example: CS647roster


CREATE VIEW CS647Roster AS
SELECT SID, name, age, GPACalled “base tables”
FROM Student
WHERE SID IN (SELECT SID FROM Enroll
WHERE CID = ’CS647’);
To drop a view

DROP VIEW view_name;
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Using views in queries

Example: find the average GPA of CS647 students

SELECT AVG(GPA) FROM CS647Roster;

To process the query, replace the reference to the view by
its definition
SELECT AVG(GPA)
FROM (SELECT SID, name, age, GPA
FROM Student
WHERE SID IN (SELECT SID
FROM Enroll
WHERE CID =
’CS647’));

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Why use views?
To hide data from users
To hide complexity from users
Logical data independence







If applications deal with views, we can change the
underlying schema without affecting applications
Recall physical data independence: change the physical
organization of data without affecting applications
To provide a uniform interface for different
implementations or sources
Real database applications use tons of views
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Modifying views




Does not seem to make sense since views are virtual
But does make sense if that is how users see the
database
Goal: modify the base tables such that the modification
would appear to have been accomplished on the view
Be careful!



There may be one way to modify
There may be many ways to modify
There may be no way to modify
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A simple case
CREATE VIEW StudentGPA AS
SELECT SID, GPA FROM Student;
DELETE FROM StudentGPA WHERE SID = 123;
translates to:
DELETE FROM Student WHERE SID = 123;
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An impossible case
CREATE VIEW HighGPAStudent AS
SELECT SID, GPA FROM Student
WHERE GPA > 3.7;
INSERT INTO HighGPAStudent
VALUES(987, 2.5);

No matter what you do on Student, the inserted row will
not be in HighGPAStudent
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A case with too many possibilities
CREATE VIEW AverageGPA(GPA) AS
SELECT AVG(GPA) FROM Student;

Note that you can rename columns in view definition
UPDATE AverageGPA SET GPA = 2.5;



Set everybody’s GPA to 2.5?
Adjust everybody’s GPA by the same amount?
Just lower Lisa’s GPA?
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Summary of SQL features covered so
far





Query
Modification
Constraints
Triggers
Views
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