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Relational Algebra and My SQL

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Title: Relational Algebra and My SQL


1
Relational Algebra and My SQL
Lecture 5 CS157B
  • Prof. Sin Min Lee
  • Deparment of Computer Science
  • San Jose State University

2
Functional Dependency
A, B ? R(.) , we say FD A?B if
  • For all t1, t2 element of R if t1A t2A gt
    t1B t2B

Definition A? R(.) is a key if FD A
?R
Definition A? R(.) is a candidate key if FD
A?R and not proper subset of A is a key.
3
4. Find all the candidate keys for the following
table ( Mid1 Study Guide)
  • R(A B C D)
  • 1 2 3 4
  • 2 2 3 5
  • 3 2 5 1
  • 1 2 5 6
  • S (A B C D)
  • 1 2 3 4
  • 2 2 3 5
  • 3 2 5 1
  • 1 2 5 6

4
Queries
  • Q1
  • A?R ()
  • A is not a key
  • Q2
  • B?R ()
  • B is not a key
  • Q3
  • C?R ()
  • C is not a key
  • Q4
  • D?R ()
  • Yes-D is a key
  • Q5
  • AB?R ()
  • AB together cannot form the key
  • Q6
  • AC?R ()
  • Yes- AC together cannot form the key
  • Q7

5
Relational Algebra
  • Basic operations
  • Selection ( ) Selects a subset of rows
    from relation.
  • Projection ( ) Deletes unwanted columns
    from relation.
  • Cross-product ( ) Allows us to combine two
    relations.
  • Set-difference ( ) Tuples in reln. 1, but
    not in reln. 2.
  • Union ( ) Tuples in reln. 1 and in reln. 2.
  • Additional operations
  • Intersection, join, division, renaming Not
    essential, but (very!) useful.
  • Since each operation returns a relation,
    operations can be composed! (Algebra is closed.)

6
Projection
  • Deletes attributes that are not in projection
    list.
  • Schema of result contains exactly the fields in
    the projection list, with the same names that
    they had in the (only) input relation.
  • Projection operator has to eliminate duplicates!
    (Why??, what are the consequences?)
  • Note real systems typically dont do duplicate
    elimination unless the user explicitly asks for
    it.

7
Selection
  • Selects rows that satisfy selection condition.
  • Schema of result identical to schema of (only)
    input relation.
  • Result relation can be the input for another
    relational algebra operation! (Operator
    composition.)

8
Union, Intersection, Set-Difference
  • All of these operations take two input relations,
    which must be union-compatible
  • Same number of fields.
  • Corresponding fields have the same type.
  • What is the schema of result?

9
Cross-Product
  • Each row of S1 is paired with each row of R1.
  • Result schema has one field per field of S1 and
    R1, with field names inherited if possible.
  • Conflict Both S1 and R1 have a field called sid.
  • Renaming operator

10
Joins
  • Condition Join
  • Result schema same as that of cross-product.
  • Fewer tuples than cross-product. Filters tuples
    not satisfying the join condition.
  • Sometimes called a theta-join.

11
Joins
  • Equi-Join A special case of condition join
    where the condition c contains only equalities.
  • Result schema similar to cross-product, but only
    one copy of fields for which equality is
    specified.
  • Natural Join Equijoin on all common fields.

12
Division
  • Not supported as a primitive operator, but useful
    for expressing queries like

    Find sailors who
    have reserved all boats.
  • Precondition in A/B, the attributes in B must be
    included in the schema for A. Also, the result
    has attributes A-B.
  • SALES(supId, prodId)
  • PRODUCTS(prodId)
  • Relations SALES and PRODUCTS must be built using
    projections.
  • SALES/PRODUCTS the ids of the suppliers
    supplying ALL products.

13
Examples of Division A/B
B1
B2
B3
A/B1
A/B2
A/B3
A
14
Expressing A/B Using Basic Operators
  • Division is not essential op just a useful
    shorthand.
  • (Also true of joins, but joins are so common that
    systems implement joins specially. Division is
    NOT implemented in SQL).
  • Idea For SALES/PRODUCTS, compute all products
    such that there exists at least one supplier not
    supplying it.
  • x value is disqualified if by attaching y value
    from B, we obtain an xy tuple that is not in A.

The answer is ?sid(Sales) - A
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17
EQUALITY JOIN, NATURAL JOIN, JOIN, SEMI-JOIN
  • Equality join connects tuples from two relations
    that match on certain attributes. The specified
    joining columns are kept in the resulting
    relation.
  • ?name(?dnametoy(Emp Dept)))
  • Natural join connects tuples from two relations
    that match on the specified common attributes
  • ?name(?dnametoy(Emp Dept)))
  • How is an equality join between Emp and Dept
    using dno different than a natural join between
    Emp and Dept using dno?
  • Equality join SS, name, age, salary, Emp.dno,
    Dept.dno,
  • Natural join SS, name, age, salary, dno,
    dname,
  • Join is similar to equality join using different
    comparison operators
  • A S op , ?, , , lt, gt
  • att op att

(dno)
(dno)
18
EXAMPLE JOIN
SS Name Age Salary dno
1 Joe 24 20000 2
2 Mary 20 25000 1
3 Bob 22 27000 1
4 Kathy 30 30000 2
5 Shideh 4 4000 1
dno dname floor mgrss
1 Toy 1 5
2 Shoe 2 1
  • Equality Join, (Emp Dept)))

Dept
EMP
SS Name Age Salary EMP.dno Dept.dno dname floor mgrss
1 Joe 24 20000 2 2 Shoe 2 1
2 Mary 20 25000 1 1 Toy 1 5
3 Bob 22 27000 1 1 Toy 1 5
4 Kathy 30 30000 2 2 Shoe 2 1
5 Shideh 4 4000 1 1 Toy 1 5
(dno)
19
EXAMPLE JOIN
SS Name Age Salary dno
1 Joe 24 20000 2
2 Mary 20 25000 1
3 Bob 22 27000 1
4 Kathy 30 30000 2
5 Shideh 4 4000 1
dno dname floor mgrss
1 Toy 1 5
2 Shoe 2 1
  • Natural Join, (Emp Dept)))

Dept
EMP
SS Name Age Salary dno dname floor mgrss
1 Joe 24 20000 2 Shoe 2 1
2 Mary 20 25000 1 Toy 1 5
3 Bob 22 27000 1 Toy 1 5
4 Kathy 30 30000 2 Shoe 2 1
5 Shideh 4 4000 1 Toy 1 5
(dno)
20
EXAMPLE JOIN
SS Name Age Salary dno
1 Joe 24 20000 2
2 Mary 20 25000 1
3 Bob 22 27000 1
4 Kathy 30 30000 2
5 Shideh 4 4000 1
dno dname floor mgrss
1 Toy 1 5
2 Shoe 2 1
  • Join, (Emp ?x(Emp))))

Dept
EMP
SS Name Age Salary dno x.SS x.Name x.Age x.Salary x.dno
2 Mary 20 25000 1 2 Shideh 4 4000 1
3 Bob 22 27000 1 3 Shideh 4 4000 1
4 Kathy 30 30000 2 4 Shideh 4 4000 1
Salary gt 5 salary
21
EQUALITY JOIN, NATURAL JOIN, JOIN, SEMI-JOIN
(Cont)
  • Example retrieve the name of employees who earn
    more than Joe
  • ?name(Emp (salgtx.sal)?nameJoe(? x(Emp)))
  • Semi-Join selects the columns of one relation
    that joins with another. It is equivalent to a
    join followed by a projection
  • Emp (dno)Dept ?SS, name, age, salary,
    dno(Emp Dept)

22
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24
JOIN OPERATORS
  • Condition Joins
  • - Defined as a cross-product followed by a
    selection
  • R ?c S sc(R ? S)
    (? is called the bow-tie)
  • where c is the condition.
  • - Example
  • Given the sample relational instances S1 and R1

The condition join S ?S1.sidltR1.sid R1 yields
25
JOIN OPERATORS
  • Condition Joins
  • - Defined as a cross-product followed by a
    selection
  • R ?c S sc(R ? S)
    (? is called the bow-tie)
  • where c is the condition.
  • - Example
  • Given the sample relational instances S1 and R1

The condition join S ?S1.sidltR1.sid R1 yields
26
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29
  • Equijoin
  • Special case of the condition join where the join
    condition consists solely of equalities between
    two fields in R and S connected by the logical
    AND operator (?).
  • Example Given the two sample relational
    instances S1 and R1

The operator S1 R.sidSsid R1 yields
30
SQL
  • SQL (Structured Query Language) is the standard
    language for commercial DBMSs
  • SEQUEL (Structured English QUEry Language)was
    originally defined by IBM for System R
  • standardization of SQL began in the 80s
  • current standard is SQL-99
  • SQL is more than a query language it includes a
    DDL, DML and administration commands
  • SQL is an example of a transform-oriented
    language.
  • A language designed to use relations to transform
    inputs into required outputs.

31
Basic structure of an SQL query
2
32
2
The SituationStudent Particulars
field type width contents id numeric
4 student id number name character
10 name dob date 8 date of
birth sex character 1 sex M /
F class character 2 class hcode character
1 house code R, Y, B, G dcode character
3 district code remission logical 1 fee
remission mtest numeric 2 Math test score
33
General Structure
I
SELECT ...... FROM ...... WHERE ......
SELECT ALL / DISTINCT expr1 AS col1, expr2
AS col2 FROM tablename WHERE condition
34
General Structure
I
SELECT ALL / DISTINCT expr1 AS col1, expr2
AS col2 FROM tablename WHERE condition
  • The query will select rows from the source
    tablename and output the result in table form.
  • Expressions expr1, expr2 can be
  • (1) a column, or
  • (2) an expression of functions and fields.
  • And col1, col2 are their corresponding column
    names in the output table.

35
  • 3.2 SQL
  • SELECT a1, ..., an
  • FROM R1, R2, , Rm
  • WHERE Con1, ,Conk
  • This means
  • p a1, ..., an( s Con1( (s Conk ( R1 R2
    Rm))))

36
  • Example
  • Find the SSN and tax for each person.
  • SELECT SSN, Tax
  • FROM Taxrecord, Taxtable
  • WHERE wages interest capital_gain
    income

37
  • AS keyword used to rename relations
  • Two SQL expressions can be combined by
  • INTERSECT
  • UNION
  • MINUS set difference

38
  • Example
  • Find the names of the streets that intersect.
  • SELECT S.NAME, T.NAME
  • FROM Streets AS S, Streets AS T
  • WHERE S.X T.X and
  • S.Y T.Y

39
  • Example Assume we have the relations
  • Broadcast ( Radio, X , Y )
  • Town ( Name, X, Y )
  • Find the parts of Lincoln, NE that can
  • be reached by at least one Radio station.
  • (SELECT X, Y
  • FROM Town
  • WHERE Name Lincoln)
  • INTERSECT
  • (SELECT X, Y
  • FROM Broadcast)

40
  • Example
  • Find the SSN and tax for each person.
  • pSSN,Tax swagesinterestcapital_gain
    income Taxrecord Taxtable
  • Example
  • Find the area of Lincoln reached by a radio
    station.
  • ( pX,Y ( sNameLincoln Town ) ) ? (
    pX,Y Broadcast )

41
  • Another way of connecting SQL expressions
  • is using the IN keyword.
  • SELECT ..
  • FROM ..
  • WHERE a IN ( SELECT b
  • FROM ..
  • WHERE .. )

42
  • SQL with aggregation
  • SELECT aggregate_function
  • FROM .
  • WHERE
  • aggregate_function
  • Max (c1a1 .. cnan)
    where ai are attributes
  • Min (c1a1 .. cnan)
    and ci are constants
  • Sum(a) where a is an
    attribute that is
  • Avg(a) constant in
    each constraint tuple
  • Count(a)

43
  • Example
  • Package(Serial_No, From, Destination, Weight)
  • Postage (Weight , Fee)
  • Find the total postage of all packages sent
  • from Omaha.
  • SELECT Sum(Fee)
  • FROM Package, Postage
  • WHERE Package.Weight Postage.Weight AND
  • Package.From Omaha

44
  • GROUP BY
  • SELECT a1, , an, aggregate_function
  • FROM ..
  • WHERE
  • GROUP BY a1, ..., ak
  • Evaluates basic SQL query
  • Groups the tuples according to different values
    of a1,..,ak
  • Applies the aggregate function to each group
    separately
  • a1, , ak ? a1, , an

45
  • Example
  • Find the total postage sent out from each
    city.
  • SELECT Package.From, Sum(Postage.Fee)
  • FROM Package, Postage
  • WHERE Package.Weight Postage.Weight
  • GROUP BY Package.From

46
General Structure
I
SELECT ALL / DISTINCT expr1 AS col1, expr2
AS col2 FROM tablename WHERE condition
  • DISTINCT will eliminate duplication in the output
    while ALL will keep all duplicated rows.
  • condition can be
  • (1) an inequality, or
  • (2) a string comparison
  • using logical operators AND, OR, NOT.

47
General Structure
I
  • Before using SQL, open the student file
  • USE student

eg. 1 List all the student records.
SELECT FROM student
48
General Structure
I
eg. 2 List the names and house code of 1A
students.
SELECT name, hcode, class FROM student
WHERE class"1A"
49
General Structure
I
eg. 2 List the names and house code of 1A
students.
50
General Structure
I
eg. 3 List the residential district of the Red
House members.
SELECT DISTINCT dcode FROM student WHERE
hcode"R"
51
Data Manipulation
  • Select query data in the database
  • Insert insert data into a table
  • Update updates data in a table
  • Delete delete data from a table

Source Database Systems Connolly/Begg
52
Retrieve all columns and all rows
  • SELECT firstColumn,,lastColumn
  • FROM tableName
  • SELECT
  • FROM tableName

53
Use of Distinct
  • SELECT DISTINCT columnName
  • FROM tableName

columnName
A A B B C D
columnName
A B C D
54
Calculated fields
  • SELECT columnName/2
  • FROM tableName

price
5.00 3.00 6.00
price
10.00 6.00 12.00
55
Comparison Search Condition
  • equals
  • lt gt is not equal to (ISO standard)
  • ! (allowed in some dialects)
  • lt is less than
  • gt is greater than
  • lt is less than or equal to
  • gt is greater than or equal to

Source Database Systems Connolly/Begg
56
Comparison Search Condition
  • An expression is evaluated left to right.
  • Subexpressions in brackets are evaluated first.
  • NOTs are evaluated before ANDs and ORs.
  • ANDs are evaluated before ORs.

Source Database Systems Connolly/Begg
57
Range Search Condition
  • SELECT columnName
  • FROM tableName
  • WHERE columnName BETWEEN 20 AND 30
  • SELECT columnName
  • FROM tableName
  • WHERE columnName gt 20
  • AND columnName lt 30

58
Set membership search condition
  • SELECT columnName
  • FROM tableName
  • WHERE columnName
  • IN (name1, name2)
  • SELECT columnName
  • FROM tableName
  • WHERE columnName name1
  • OR columnName name2

59
Pattern matching symbols
  • represents any sequence of zero
  • or more characters (wildcard).
  • _ represents any single character

Source Database Systems Connolly/Begg
60
Pattern match search condition
  • h begins with the character h .
  • h_ _ _ four character string beginning with
    the
  • character h.
  • e any sequence of characters, of length
    at
  • least 1, ending with the character e.
  • CS157B any sequence of characters of any
  • length containing CS157B

Source Database Systems Connolly/Begg
61
Pattern match search condition
  • LIKE h
  • begins with the character h .
  • NOT LIKE h
  • does not begin with the character h.

Source Database Systems Connolly/Begg
62
Pattern match search condition
  • To search a string that includes a
  • pattern-matching character
  • 15
  • Use an escape character to represent
  • the pattern-matching character.
  • LIKE 15 ESCAPE

Source Database Systems Connolly/Begg
63
NULL search condition
  • DOES NOT WORK
  • comment
  • comment !
  • DOES WORK
  • comment IS NULL
  • comment IS NOT NULL

64
Sorting
  • The ORDER BY clause
  • consists of list of column identifiers that the
    result is to be sorted on, separated by commas.
  • Allows the retrieved rows to be ordered by
    ascending (ASC) or descending (DESC) order

Source Database Systems Connolly/Begg
65
Sorting
  • Column identifier may be
  • A column name
  • A column number (deprecated)

Source Database Systems Connolly/Begg
66
Sorting
  • SELECT type, rent
  • FROM tableName
  • ORDER BY type, rent ASC

type rent
Apt Apt Flat Flat 450 500 600 650
type rent
Flat Apt Flat Apt 650 450 600 500
Source Database Systems Connolly/Begg
67
Aggregate Functions
  • COUNT returns the number
  • SUM returns the sum
  • AVG returns the average
  • MIN returns the smallest
  • MAX returns the largest
  • value in a specified column.

Source Database Systems Connolly/Begg
68
Use of COUNT( )
  • How many students in CS157B?
  • SELECT COUNT( ) AS my count
  • FROM CS157B

my count
40
69
GROUP BY clause
  • When GROUP BY is used, each item in the SELECT
    list must be single-valued per group.
  • The SELECT clause may contain only
  • Column names
  • Aggregate functions
  • Constants
  • An expression involving combinations of the above

Source Database Systems Connolly/Begg
70
Grouping
  • SELECT dept, COUNT(staffNo) AS my count
    SUM(salary)
  • FROM tableName
  • GROUP BY dept
  • ORDER BY dept

dept staffNo Salary
A B C A B 1 1 1 2 2 200.00 200.00 200.00 100.00 100.00
dept my count Salary
A B C 2 2 1 300.00300.00 200.00
71
Restricting Grouping
  • HAVING clause
  • is with the GROUP BY clause.
  • filters groups into resulting table.
  • includes at least one aggregate function.
  • WHERE clause
  • filters individual rows into resulting table.
  • Aggregate functions cannot be used.

Source Database Systems Connolly/Begg
72
  • SELECT dept, COUNT(staffNo) AS my count,
    SUM(salary) AS my sum
  • FROM Staff
  • GROUP BY dept
  • HAVING COUNT(staffNo) gt 1
  • ORDER BY dept

dept staffNo Salary
A B C A B 1 1 1 2 2 200.00 200.00 200.00 100.00 100.00
dept my count my sum
A B 2 2 300.00 300.00
Source Database Systems Connolly/Begg
73
Subqueries
  • SELECT columnNameA
  • FROM tableName1
  • WHERE columnNameB (SELECT columnNameB
  • FROM tableName2
  • WHERE condition)

result from inner SELECT applied as a condition
for the outer SELECT
Source Database Systems Connolly/Begg
74
Subquery with Aggregate Function
List all staff whose salary is greater than the
average salary, show by how much their salary is
greater than the average.
  • SELECT fName, salary
  • ( SELECT AVG(salary)
  • FROM Staff ) AS salDiff
  • FROM Staff
  • WHERE salary gt ( SELECT AVG(salary)
  • FROM Staff )

Source Database Systems Connolly/Begg
75
Nested Subqueries Use of IN
  • SELECT property
  • FROM PropertyForRent
  • WHERE staff IN(
  • SELECT staff
  • FROM Staff
  • WHERE branch (
  • SELECT branch
  • FROM Branch
  • WHERE street
  • 112 A St))

Selects branch at 112 A St
Source Database Systems Connolly/Begg
76
Nested Subqueries Use of IN
  • SELECT property
  • FROM PropertyForRent
  • WHERE staff IN(
  • SELECT staff
  • FROM Staff
  • WHERE branch ( branch ) )

Select staff members who works at branch.
Source Database Systems Connolly/Begg
77
Nested Subqueries Use of IN
  • SELECT property
  • FROM PropertyForRent
  • WHERE staff IN( staffs who works
  • at branch on 112 A St)

Since there are more than one row selected,
cannot be used.
Source Database Systems Connolly/Begg
78
Use of ANY/SOME
  • SELECT name, salary
  • FROM Staff
  • WHERE salary gt SOME( SELECT salary
  • FROM Staff
  • WHERE branch A )

Result list of staff with salary greater than
2000.
Result2000,3000,4000
Source Database Systems Connolly/Begg
79
Use of ALL
  • SELECT name, salary
  • FROM Staff
  • WHERE salary gt ALL( SELECT salary
  • FROM Staff
  • WHERE branch A )

Result list of staff with salary greater than
4000.
Result2000,3000,4000
Source Database Systems Connolly/Begg
80
Use of Any/Some and All
  • If the subquery is empty
  • ALL returns true
  • ANY returns false
  • ISO standard allows SOME to be
  • used interchangeably with ANY.

Source Database Systems Connolly/Begg
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