1. Lecture 5 Relational Algebra and Calculus SQL Syntax
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Lecture 5
Relational Algebra and Calculus
SQL Syntax
Cartesian product examples
SQL examples
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2. Relational Algebra and Calculus
Relational Algebra is a procedural whereas Relational Calculus is declarative.
SQL is based on Relational Calculus. You tell server WHAT you want, not how you want to get it.

3. Two tables for today’s examples
LastName
DepartmentID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

4. Cross Join
Cross joins are the Cartesian product of two tables. There are two ways to express cross joins.
SELECT * FROM Employee E, Department D
SELECT * FROM Employee E CROSS JOIN Department D
REFERENCE
E.LastName
E.DeptID
D.ID
D.Name
Smith 1 HR 2
Sales 3
Engineering 4
Marketing
Johnson
Miller
Lee
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

5. Inner Join
Inner joins are the most common type of Join performed in SQL.
There are actually two ways to express an Inner. An inner join is done by taking the Cartesian product of the two tables, then only returning the rows that match the conditional.
SELECT * FROM Employee E, Department D
WHERE D.ID=E.DeptID
SELECT * FROM Employee E
JOIN Department D ON D.ID=E.DeptID
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE
E.LastName
E.DeptID
D.ID
D.Name
Smith 1 HR
Johnson
Miller 2
Sales
Lee 3
Engineering
Sub-Types of Inner Joins: Natural Join, Equal-Jon ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

6. Outer Join
Outer joins are used to return all rows from one table regardless of a match in the other table. If no match is found in the other table, a NULL is returned. Three types: LEFT, RIGHT, FULL
Show all the departments and the employees in them, if any:
SELECT * FROM Department D
LEFT JOIN Employee E ON D.ID=E.DeptID
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE
D.ID
D.Name
E.LastName
E.DeptID 1 HR
Smith
Johnson 2
Sales
Miller 3
Engineering
Lee 4
Marketing
NULL
FULL OUTER JOIN not even supported in MySQL, Oracle 8i and early, etc. ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

7. Self Join
 A self-join is a query in which a table is joined (compared) to itself.  Self-joins are used to compare values in a column with other values in the same column in the same table. 
One practical use for self-joins:  obtaining running counts and running totals in an SQL query. To write the query, select from the same table listed twice with different aliases,
set up the comparison, and eliminate cases where a particular value would be equal to itself. 
Example           Which customers are located in the same state (column name is Region)? 
SELECT DISTINCT c1.ContactName, c1.Address, c1.City, c1.Region           
FROM Customers AS c1, Customers AS c2           
WHERE c1.Region = c2.Region  AND c1.ContactName <> c2.ContactName           
ORDER BY c1.Region, c1.ContactName;

Another example: Exercise Which customers are located in the same city?  (32 rows) 

8. Aggregate Functions
While returning rows is nice, often times you want to return data based upon a computed value from a set.
Count
Sum
Min
Max
Avg

9. An example of Aggregates
Name
Grade
Steve
2.5
John
3.5
Wendy
3.8
Niki
4.0
Kevin
1.4
SELECT
count(*), max(grade), min(grade), avg(grade), sum(grade)
FROM student_grades
Count(*)
Max(grade)
Min(grade)
Avg(grade)
Sum(grade) 5 4
1.4
3.04
15.2

10. SELECT Statement - Grouping
Now that you have aggregate functions, they become useful in grouping results.
Back to the example Join tables, maybe you want a count of the number of employees in each department.
The GROUP BY clause is added to the end of the SELECT statement.

11. SELECT Statement - Grouping
All column names in SELECT list must appear in GROUP BY clause unless name is used only in an aggregate function.
If WHERE is used with GROUP BY, WHERE is applied first, then groups are formed from remaining rows satisfying predicate.
ISO considers two nulls to be equal for purposes of GROUP BY.
It is important to note the group by is applied last.

12. Group By Example How many employees are in each department? REFERENCE
SELECT D.Name, COUNT(E.DeptID) FROM Department D
LEFT JOIN Employee E ON D.ID=E.DeptID
GROUP BY D.Name
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE
D.Name
COUNT(E.DeptID) HR 2
Sales 1
Engineering
Marketing ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

13. HAVING clause
But what if we want to return results based upon a GROUP BY? Enter the HAVING clause.
Let’s only see the departments with people in them:
SELECT D.Name, COUNT(E.DeptID)
FROM Department D
LEFT JOIN Employee E ON D.ID=E.DeptID
GROUP BY D.Name
HAVING COUNT(E.DeptID) > 0
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE
The having clause is applied last. ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE
D.Name
COUNT(E.DeptID) HR 2
Sales 1
Engineering

14. ORDER BY clause
Finally, what if we want some order imposed on our results?
Order by can contain any field or value specified in the selection criteria.
SELECT D.Name, COUNT(E.DeptID)
FROM Department D
LEFT JOIN Employee E ON D.ID=E.DeptID
GROUP BY D.Name
HAVING COUNT(E.DeptID) > 0
ORDER BY D.Name
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE
Discuss DESC, ASC.. Multiple ORDER BYs, etc. ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE
D.Name
COUNT(E.DeptID)
Engineering 1 HR 2
Sales

15. Set A Set B Set Theory Review The Intersection Intersection of 2 Sets
R = {1,2,3,4} S = {4,5,6,7}  R  S = { 4 }
R = { Joe, Suzie } S = { Jane, Bob, Sam }  R  S = { Ø }
R = { ‘big stereo’, ‘blue’, ‘safe’ } S = { ‘blue’, ‘fire trap’ , ‘AM radio’ }
 R  S = { ‘blue’ }
Set A
Set B
The Intersection

16. Set A Set B Set Theory Review Union of 2 Sets
R = {1,2,3,4} S = {4,5,6,7}  R  S = {1,2,3,4,5,6,7}
R = { Joe, Suzie } S = { Jane, Bob, Sam }
 R  S = {Joe, Suzie, Jane, Bob, Sam }
R = { ‘big stereo’, ‘blue’, ‘safe’ } S = { ‘AM radio’, ‘blue’, ‘fire trap’ }
 R  S = {‘big stereo’, ‘blue’, ‘safe’, ‘AM radio’, ‘fire trap’ }
Set A
Set B

17. Set A Set B Set Theory Review The Difference Difference of 2 Sets
R = {1,2,3,4} S = {4,5,6,7}  R \ S = {1,2,3}
R = { Joe, Suzie } S = { Jane, Bob, Sam }  R  S = {Joe, Suzie }
R = { ‘big stereo’, ‘blue’, ‘safe’ } S = { ‘AM radio’, ‘blue’, ‘fire trap’ }
 R  S = {‘big stereo’, ‘safe’ }
Set A
Set B
The Difference

18. Union, Intersect, and Difference (Except)
Use between select clauses
Keyword for union is union
Keyword for intersection is intersect
Keyword for difference is except
Column names must match in each query.
Example: (select Name from Staff) union (select Name from Faculty)

19. INSERT INSERT INTO TableName [ (columnList) ] VALUES (dataValueList)
columnList is optional; if omitted, SQL assumes a list of all columns in their original CREATE TABLE order.
Any columns omitted must have been declared as NULL when table was created, unless DEFAULT was specified when creating column.
© Pearson Education Limited 1995, 2005

20. INSERT dataValueList must match columnList as follows:
number of items in each list must be same;
must be direct correspondence in position of items in two lists;
data type of each item in dataValueList must be compatible with data type of corresponding column.
© Pearson Education Limited 1995, 2005

21. INSERT … VALUES
Insert a new row into Employee table supplying data for all columns.
Let’s finally put someone in the marketing department!
Full table, so can omit the column names: INSERT INTO Employee VALUES (‘Brown’, 4);
Or we can explicitly list the column names: INSERT INTO Employee (LastName, DeptID) VALUES (‘Brown’, 4);
Perhaps we the DeptID field allows NULLs or has a default: INSERT INTO Employee (LastName) VALUES (‘Brown’);

22. UPDATE UPDATE TableName SET columnName1 = dataValue1
[WHERE searchCondition]
TableName can be name of a base table or an updatable view.
SET clause specifies names of one or more columns that are to be updated.
WHERE clause is optional, if omitted all rows are updated.
© Pearson Education Limited 1995, 2005

23. UPDATE example
Ms. Johnson gets married and wants to change her name to Anderson. UPDATE EMPLOYEE SET LastName=‘Anderson’ WHERE LastName=‘Johnson’
Better way to find Ms. Johnson UPDATE EMPLOYEE SET LastName=‘Anderson’ WHERE LastName=‘Johnson’ AND DeptID=1
The Marketing department is being merged with Sales and as such all the employees in that department are being moved into Sales. UPDATE EMPLOYEE SET DeptID=2 WHERE DeptID=4
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE
Discuss how the first query is poor because it will probably update everyone..
Note that while ANSI SQL doesn’t allow JOINs in the update, many Database software packages do. ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

24. DELETE DELETE FROM TableName [WHERE searchCondition]
TableName can be name of a base table or an updatable view.
searchCondition is optional; if omitted, all rows are deleted from table. This does not delete table. If search_condition is specified, only those rows that satisfy condition are deleted.
© Pearson Education Limited 1995, 2005

25. DELETE example
Mr. Smith decides to take another job and quits: DELETE FROM EMPLOYEE WHERE LastName=‘Smith’ AND DeptId=1
Remember the Marketing department? Well, rather than merge with Sales we are going to eliminate it and all the employees in that department. DELETE FROM EMPLOYEE WHERE DeptID=4
REFERENCE
LastName
DeptID
Smith 1
Johnson
Miller 2
Lee 3
EMPLOYEE TABLE ID
Name 1 HR 2
Sales 3
Engineering 4
Marketing
DEPARTMENT TABLE

26. Variants & Like
There is a rich set of functions that can be used in SQL. Of course, most of them are highly language-variant dependent.
LIKE. Allows searching a text field for a value. SELECT * FROM students WHERE name LIKE ‘R%’
% is a wildcard, whereas _ matches just one character
Discuss examples like MySQL can do SHA1, string manipulation, SELECT 5*10+10 works, etc.

27. CASE statements
SELECT CASE Sex WHEN ‘M’ THEN ‘Male’ WHEN ‘F’ THEN ‘Female’ END CASE FROM Students

28. Mini-Project Due Feb 4, 2009 Choose between the following:
Build on your iSchool MySQL account
Choose between the following:
UW OnTech Archive
UW Privacy Policy Set

29. Mini-Project
UW OnTech Archive --
UW Privacy Policy –

30. UW OnTech
contents by issue
archive contents

31. UW OnTech
issue contents
article example

32. UW OnTech Sample questions:
How many contents by issue pages list topics that are not the same as the topics on the corresponding issue contents pages ? Or are missing entirely ?
How many pages list an ‘exposed address’ on its readable page?
How many pages have an address that is visible in the page source?

33. UW OnTech More sample questions:
What is the average number of clickable links per article in the archive ?
What is the min & max number of clickable links in the archive
Which articles were they
More to come

34. UW Privacy & Security Policies
Sample questions:
Which policies have the greatest distance between Effective Date & Review Date ?
Which ones are they?
How many policies have the same Effective Date & Review Date?
Which policies have more than 5 attachments?

35. UW Privacy & Security Policies
More sample questions:
Which policies have greater than 5 references?
Which policies are they ?
What is most often cited reference in the reference section ?
Do any of the policies in these two sets reference each other ?

36. Customers