Transcript Document

Introduction to Database
CHAPTER 2
RELATIONAL MODEL






2.1 Structure of Relational Databases
2.2 Fundamental Relational-Algebra Operations
2.3 Additional Relational-Algebra Operations
2.4 Extended Relational-Algebra Operations
2.5 Null Values
2.6 Modification of the Database
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-1
PART 1: Relational Databases


Relational Database: a shared repository of data that perceived by the
容器
users as a collection of tables.
To make database available to users:
 Requests for data by
•
•
•
SQL (Chapter 3, 4)
QBE (Chapter 5)
Datalog (Chapter 5)

Data Integrity: protect data from damage by unintentional (Chapter 8)

Data Security: protect data from damage by intentional (Chapter 8)

Database Design (Chapter 7)
•
•
•
Design of database schema, tables
Normalization: Normal forms
Tradeoff: Possibility of inconsistency vs. efficiency
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-2
2.1 Structure of Relational Databases


Relational Database: a collection of tables
 Table has a unique name

A row (tuple) in a table: a relationship of a set of values
account

Table: mathematical concept of relation
Relational Model: proposed by Codd, 1970, ref. p.1108: Bibliography
[Codd 1970] E. F. Codd, "A Relational Model for Large Shared Data banks,"
CACM Vol. 13, No.6, (1970), pp. 377-387
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Source: Database System Concepts, Silberschatz etc. 2006
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2.1.1 Basic Structure

Relation:
 Formally, given sets D1, D2, …. Dn

D1 x D2 x … x Dn = {(a1, a2, …, an) | where each ai  Di}

a Relation r is a subset of D1 x D2 x … x Dn


Thus a relation is a set of n-tuples (a1, a2, …, an) where
each ai  Di
Example: if
customer-name = {Jones, Smith, Curry, Lindsay}
customer-street = {Main, North, Park}
customer-city = {Harrison, Rye, Pittsfield}
Then r = {(Jones, Main, Harrison), (Smith, North, Rye),
(Curry, North, Rye), (Lindsay, Park, Pittsfield)}
is a relation over customer-name x customer-street x customer-city
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
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Example: The account Relation, Fig. 2.1
account

D1 = {
}

D2 = {
}

D3 = {
}

D1 x D2 x D3 =

account =
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-5
Attribute Types





account
Each attribute of a relation has a name
The set of allowed values for each attribute is
called the domain of the attribute
Attribute values are (normally) required to be atomic,
that is, indivisible
 E.g. multivalued attribute values are not atomic,
(A-201, A-217)
 E.g. composite attribute values are not atomic,
BirthDate: (5, 17, 1950)
The special value null is a member of every domain
The null value causes complications in the definition
of many operations
 we shall ignore the effect of null values in our
main presentation and consider their effect later
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
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2.1.2 Database Schema
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
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Attributes: Suppose A1, A2, …, An are attributes
Relation schema: R = (A1, A2, …, An) is a relation schema
e.g. Customer-schema =
(customer-name, customer-street, customer-city)
Relation: r(R) is a relation on the relation schema R
e.g. customer(Customer-schema)
attributes
(or columns)
customer
customer-name
customer-street
customer-city
Jones
Smith
Curry
Lindsay
Main
North
North
Park
Harrison
Rye
Rye
Pittsfield
tuples
(or rows)
customer
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
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Relation Instance


Relation Instance: The current values (relation instance) of a
relation are specified by a table
Tuple: An element t of r is a tuple, represented by a row in a table
attributes
(or columns)
customer
customer-name customer-street
Jones
Smith
Curry
Lindsay
Edited: Wei-Pang Yang, IM.NDHU, 2009
Main
North
North
Park
customer-city
Harrison
Rye
Rye
Pittsfield
Source: Database System Concepts, Silberschatz etc. 2006
tuples
(or rows)
2-8
Relations are Unordered


Order of tuples is irrelevant (tuples may be stored in an arbitrary order)
e.g. The account relation with unordered tuples
(unordered tuples)
account
(ordered by account-number)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-9
Database
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

Database: A database consists of multiple relations (ref. p. 1-??)
Information about an enterprise is broken up into parts, with each
relation storing one part of the information
E.g.: account: stores information about accounts
depositor: stores information about which customer
owns which account
customer: stores information about customers
Storing all information as a single relation such as
bank(account-number, balance, customer-name, ..)
results in
bank
…
repetition of information (e.g. two customers own an account)
 the need for null values (e.g. represent a customer without an
account)
Normalization theory (Chapter 7) deals with how to design relational
schemas


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Source: Database System Concepts, Silberschatz etc. 2006
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Example: Banking Database

Banking Database: consists 6 relations:
1. branch (branch-name, branch-city, assets)
2. customer (customer-name, customer-street, customer-only)
3. account (account-number, branch-name, balance)
4. loan (loan-number, branch-name, amount)
5. depositor (customer-name, account-number)
6. borrower (customer-name, loan-number)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
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Example: Banking Database
1. branch 分公司
4. borrower
貸款戶
Edited: Wei-Pang Yang, IM.NDHU, 2009
2. customer 客戶(存款戶,貸款戶) 3. depositor
5. account
存款帳
6. loan
Source: Database System Concepts, Silberschatz etc. 2006
存款戶
貸款帳
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2.1.3 Keys



Let K  R = (A1, A2, …, An), set of attributes of relation r(R)
Superkey: K is a superkey of R if values for K are sufficient to identify
a unique tuple of each possible relation r(R)
 Example: {customer-name, customer-street} and {customer-name}
are both superkeys of Customer, if no two customers can possibly
have the same name.
Candidate key: K is a candidate key if K is minimal
e.g: {customer-name} is a candidate key for Customer,
customer
since it is a superkey and
no subset of it is a superkey.


Primary Key
Foreign key
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
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Schema Diagram, Fig. 2.8

Primary Key and foreign key can be depicted by schema diagram
 Schema Diagram for the Banking Enterprise, Fig. 2.8
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-14
2.1.4 Query Languages

Query Language: user requests information from the database.

Categories of languages
 procedural

non-procedural
• SQL (ch. 3, ch. 4)
• QBE (Section 5.3)


“Pure” languages:
 Relational Algebra (Section 2.2, 2.3, 2.4)

Tuple Relational Calculus (Section 5.1)

Domain Relational Calculus (Section 5.2)
Pure languages form underlying basis of query languages that
people use (e.g. SQL).
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-15
Introduction to Database
CHAPTER 3
RELATIONAL MODEL






2.1 Structure of Relational Databases
2.2 Fundamental Relational-Algebra Operations
2.3 Additional Relational-Algebra Operations
2.4 Extended Relational-Algebra Operations
2.5 Null Values
2.6 Modification of the Database
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-16
Relational-Algebra Operations


Procedural language
The operators take one or more relations as inputs and
give a new relation as a result.

Fundamental Relational-Algebra Operations
 Select
 Project
 Union
 Set difference
 Cartesian product
 Rename

Additional Relational-Algebra Operations
 Intersection
 Natural Join
 Division
 Assignment
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-17
2.2 Fundamental Relational-Algebra Operations






Select
Project
Union
Set difference
Cartesian product
Rename
Select ()
Project ()
Difference ()
Union (
Product (x)
a
b
c
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
x
y
a
a
b
b
c
c
x
y
x
y
x
y
2-18
2.2.1 Select Operation: Example
 Relation r
 A=B ^ D > 5 (r)
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B
C
D


1
7


5
7


12
3


23 10
A
B
C
D


1
7


23 10
Source: Database System Concepts, Silberschatz etc. 2006
2-19
Select Operation



Notation:  p(r)
p is called the selection predicate
Defined as:
p(r) = {t | t  r and p(t)}

Where p is a formula in propositional calculus consisting of
terms connected by :  (and),  (or),  (not)
Each term is one of:
<attribute> op <attribute> or <constant>
where op is one of: =, , >, . <. 
Example of selection:
 branch-name=“Perryridge”(account)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-20
Example Queries 1: Select

Find all loans of over $1200
amount > 1200 (loan)
5. loan
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-21
2.2.2 Project Operation: Example

Relation r:
A,C (r)
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B
C

10
1

20
1

30
1

40
2
A
C
A
C

1

1

1

1

1

2

2
=
Source: Database System Concepts, Silberschatz etc. 2006
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Project Operation

Notation:
A1, A2, …, Ak (r)
where A1, A2 are attribute names and r is a relation name.

The result is defined as the relation of k columns obtained by erasing the
columns that are not listed

Duplicate rows removed from result, since relations are sets

e.g. To eliminate the branch-name attribute of account
account-number, balance (account)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-23
Example Queries 2: Project

List all all loan numbers and the amount of the loans
loan-number, amount (loan)
Fig. 2.10
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-24
Example Queries 3: Project
Can use =, =, < > <=, >=, and, or, not …
Find all loans of over $1200 made by the Perryridge branch


梨崗山
amount > 1200 ^ branch-name=“Perryridge” (loan)

loan
Fig. 2.9
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-25
2.2.3 Composition of Operations
We can build expressions by using multiple operations
Example:
A
B
C
D
E
expression: A=C(r x s)


r
s
A
B

1

2
C
D
E
10
10
20
10
a
a
b
b




op1: r x s
op2: A=C(r x s)
Edited: Wei-Pang Yang, IM.NDHU, 2009








1
1
1
1
2
2
2
2








10
10
20
10
10
10
20
10
a
a
b
b
a
a
b
b
A
B
C
D
E



1
2
2



10
20
20
a
a
b
Source: Database System Concepts, Silberschatz etc. 2006
2-26
Example Queries 4: Select/Project

Find the loan number for each loan of an amount greater than $1200
loan-number (amount > 1200 (loan))
5. loan
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Source: Database System Concepts, Silberschatz etc. 2006
2-27
Example Queries 5: Composition

Find those customers who live in Harrison
customer-name (customer-city=“Harrison” (customer))
2. customer
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Source: Database System Concepts, Silberschatz etc. 2006
2-28
2.2.4 Union Operation: Example

Relations r, s:
A
B
A
B

1

2

2

3

1
s
r
r  s:
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B

1

2

1

3
Source: Database System Concepts, Silberschatz etc. 2006
2-29
Union Operation




Notation: r  s
Defined as:
r  s = {t | t  r or t  s}
For r  s to be valid.
1. r, s must have the same arity (same number of attributes, same heading)
2. The attribute domains must be compatible (e.g., 2nd column
of r deals with the same type of values as does the 2nd
column of s)
E.g. to find all customers with either an account or a loan
customer-name (depositor)  customer-name (borrower)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-30
Example Queries 6: Union/Intersection

Find the names of all customers who have a loan,
an account, or both, from the bank
customer-name (borrower)  customer-name (depositor)

Find the names of all customers who have a loan
and an account at bank.
Fig. 2.11
customer-name (borrower)  customer-name (depositor)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-31
2.2.5 Set-Difference Operation: Example

Relations r, s:
A
B
A
B

1

2

2

3

1
s
r
r – s:
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B

1

1
Source: Database System Concepts, Silberschatz etc. 2006
2-32
Set Difference Operation



Notation r – s
Defined as:
r – s = {t | t  r and t  s}
Set differences must be taken between compatible relations.
 r and s must have the same arity

attribute domains of r and s must be compatible
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-33
Example Queries 7: Set Difference

Find the names of all customers who have an account, but not a loan
customer-name (depositor) - customer-name (borrower)
4. depositor
6. borrower
Fig. 2.12
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-34
2.2.6 Cartesian-Product Operation: Example
Relations r, s:
r
A
B
s C
D
E

1

2




10
10
20
10
a
a
b
b
Product (x)
a
b
c
x
y
a
a
b
b
c
c
r x s:
x
y
x
y
x
y
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B
C
D
E








1
1
1
1
2
2
2
2








10
10
20
10
10
10
20
10
a
a
b
b
a
a
b
b
Source: Database System Concepts, Silberschatz etc. 2006
2-35
Cartesian-Product Operation




Notation r x s
Defined as:
r x s = {t q | t  r and q  s}
Assume that attributes of r(R) and s(S) are disjoint. (That is,
R  S = ).
If attributes of r(R) and s(S) are not disjoint, then renaming must be used.
Product (x)
a
b
c
Edited: Wei-Pang Yang, IM.NDHU, 2009
x
y
a
a
b
b
c
c
x
y
x
y
x
y
Source: Database System Concepts, Silberschatz etc. 2006
2-36
Example Queries 8: Cartesian-Product

borrower x loan
6. borrower
Edited: Wei-Pang Yang, IM.NDHU, 2009
5. loan
Source: Database System Concepts, Silberschatz etc. 2006
2-37
Queries 8:
borrower 
loan (Fig. 2.13)
8 x 7 = 56 tuples
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-38
Queries 8.1:
Find the names of all
customers who have a loan
at the Perryridge branch.
 branch-name = “Perryridge”
(borrower  loan)
8 x 2 = 16 tuples
(Fig. 2.14)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-39
 branch-name = “Perryridge” (borrower 
loan),
(Fig. 2.14)
8 x 2 = 16 tuples
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Source: Database System Concepts, Silberschatz etc. 2006
2-40
Queries 8.2:
(borrower.loan-number =
loan.loan-number
(borrower x loan))
8 x 1 = 8 tuples
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Source: Database System Concepts, Silberschatz etc. 2006
2-41
Queries 8.3:
(branch-name=“Perryridge”
(borrower.loan-number =
loan.loan-number (borrower
x loan)))
2 tuples
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Source: Database System Concepts, Silberschatz etc. 2006
2-42
Example Queries 8.4: Cartesian-Product

Query: Find the names of all customers who have a loan at the Perryridge branch.
customer-name (branch-name=“Perryridge”
(borrower.loan-number = loan.loan-number (borrower x loan)))
(Fig. 2.15)
6. borrower
Edited: Wei-Pang Yang, IM.NDHU, 2009
5. loan
Source: Database System Concepts, Silberschatz etc. 2006
2-43
Example Queries 9

Query: Find the names of all customers who have a loan at the Perryridge
branch but do not have an account at any branch of the bank.
customer-name (branch-name = “Perryridge”
(borrower.loan-number = loan.loan-number(borrower x loan))) –
customer-name (depositor)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-44
Example Queries 10: Comparison

Query: “Find the names of all customers who have a loan at the Perryridge
branch.
 Query 1
customer-name (branch-name = “Perryridge” (
borrower.loan-number = loan.loan-number (borrower x loan)))
8 x 7 = 56 tuples
 Query 2
customer-name (loan.loan-number = borrower.loan-number (
(branch-name = “Perryridge” (loan)) x borrower))
2 x 8 = 16 tuples
Which one is better?
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-45
2.2.7 Rename Operation

Rename Operation: Allows us to name, and therefore to refer to, the
results of relational-algebra expressions.
 E.g.1:
 x (E)
returns the expression E under the name X
 E.g. 2. If a relational-algebra expression E has arity n, then
x (A1, A2, …, An) (E)
returns the result of expression E under the name X, and with the
attributes renamed to A1, A2, …., An.

E.g. 3.
 x (r) ?
• SQL: Rename r As x
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Source: Database System Concepts, Silberschatz etc. 2006
2-46
Example Queries 11: Rename, p.53
Query: Find the largest account balance

Rename account relation as d

The query is:
balance(account) - account.balance
(account.balance < d.balance (account x rd (account)))
3. account
Edited: Wei-Pang Yang, IM.NDHU, 2009
3. Account = d
Source: Database System Concepts, Silberschatz etc. 2006
2-47
Example Queries 11: Rename
(cont.)
account.balance (account.balance < d.balance (account x rd (account)))
3. account
(Fig. 2.16)
Edited: Wei-Pang Yang, IM.NDHU, 2009
3. Account = d
(Fig. 2.17)
Source: Database System Concepts, Silberschatz etc. 2006
2-48
Example Queries 12: Rename


Query: “Find the names of all customers who live on the same street and
in the same city as Smith”
Algebra: p. 54
2. customer
Fig. 2.18
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-49
2.2.8 Formal Definition

A basic expression in the relational algebra consists of either one of the
following:
 A relation in the database


A constant relation
Let E1 and E2 be relational-algebra expressions; the following are all
relational-algebra expressions:
 E1  E2
 E1 - E2
 E1 x E2
 p (E1), P is a predicate on attributes in E1
 s(E1), S is a list consisting of some of the attributes in E1
  x (E1), x is the new name for the result of E1
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-50
Introduction to Database
CHAPTER 3
RELATIONAL MODEL






2.1 Structure of Relational Databases
2.2 Fundamental Relational-Algebra Operations
2.3 Additional Relational-Algebra Operations
2.4 Extended Relational-Algebra Operations
2.5 Null Values
2.6 Modification of the Database
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-51
2.3 Additional Relational-Algebra Operations


Four Additional Operations:
 Set intersection

Natural join

Division

Assignment
Additional Operations:
 do not add any power to the relational algebra,

Why?
but that simplify common queries.
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-52
2.3.1 Set-Intersection Operation




Notation: r  s
Defined as:
r  s ={ t | t  r and t  s }
Assume:
 r, s have the same arity


attributes of r and s are compatible
Note: r  s = r - (r - s)
Intersection ()
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-53
Set-Intersection Operation: Example

Relation r, s:
A
B



1
2
1
r

A
B


2
3
s
rs
A
B

2
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-54
2.3.2 Natural-Join Operation: r s

Let r and s be relations on schemas R and S respectively.
Then, r s is a relation on schema R  S obtained as follows:
 Consider each pair of tuples tr from r and ts from s.

If tr and ts have the same value on each of the attributes in R  S, add a
tuple t to the result, where
• t has the same value as tr on r
• t has the same value as ts on s

Example:
R = (A, B, C, D)
S = (E, B, D)

Result schema = (A, B, C, D, E)

r
s is defined as:
r.A, r.B, r.C, r.D, s.E (r.B = s.B  r.D = s.D (r x s))
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-55
Natural-Join Operation: r s
(Natural)Join
R1 x
y
R2 z
a1 b1
a2 b1
a3 b2
w
b1 c1
b2 c2
b3 c3
a1 b1 c1
a2 b1 c1
a3 b2 c2
R 1 x R2
x y
a1 b1
a1 b1
a1 b1
a2 b1
.
.
.
R1
.
.
.
z
b1
b2
b3
b1
.
.
.
w
c1
c2
c3
c1
.
.
.
R2
y=z
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-56
Natural Join Operation: Example

Relations r, s:
A
B
C
D
B
D
E





1
2
4
1
2





a
a
b
a
b
1
3
1
2
3
a
a
a
b
b





r
r
s
r.B = s.B  r.D = s.D
Edited: Wei-Pang Yang, IM.NDHU, 2009
s
A
B
C
D
E





1
1
1
1
2





a
a
a
a
b





Source: Database System Concepts, Silberschatz etc. 2006
2-57
customer-name, loan-number, amount (borrower
6. borrower
loan)
5. loan
Fig. 2.20
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-58
Query: Find the names of all branches with customers who have an
account and live in Harrison
branch-name(customer-city = “Harrison”(customer account depositor))
2. customer
3. account
4. depositor
Fig. 2.21
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-59
2.3.3 Division Operation: r  s


Suited to queries that include the phrase “for all”.
Let r and s be relations on schemas R and S respectively where
 R = (A1, …, Am, B1, …, Bn)

S = (B1, …, Bn)
The result of r  s is a relation on schema
R – S = (A1, …, Am)
r  s = { t | t   R-S(r)   u  s ( tu  r ) }
Divide ()
a
a
a
b
c
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
x
y
z
x
y
x
z
a
2-60
Division Operation: Example 1
 Relations r, s:
Edited: Wei-Pang Yang, IM.NDHU, 2009
s
r
r  s:
A
B
B
A











1
2
3
1
1
1
3
4
6
1
2
1

2

Source: Database System Concepts, Silberschatz etc. 2006
2-61
Division Operation: Example 2
 Relations r, s:
A
B
C
D
E
D
E








a
a
a
a
a
a
a
a








a
a
b
a
b
a
b
b
1
1
1
1
3
1
1
1
a
b
1
1
s
r
r  s:
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B
C


a
a


Source: Database System Concepts, Silberschatz etc. 2006
2-62
Division Operation (Cont.)


Property
 Let q = r  s
 Then q is the largest relation satisfying q x s  r
Definition in terms of the basic algebra operation
Let r(R) and s(S) be relations, and let S  R
r  s = R-S (r) –R-S ( (R-S (r) x s) – R-S,S(r))
To see why
 R-S,S(r) simply reorders attributes of r

R-S(R-S (r) x s) – R-S,S(r)) gives those tuples t in
R-S (r) such that for some tuple u  s, tu  r.
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-63
Division Operation: Example 3

Find all customers who have an account at all the branches
located in Brooklyn
customer-name, branch-name(depositor
account)

branch-name(branch-city = “Brooklyn”(branch))
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-64
customer-name, branch-name(depositor
4. depositor
Edited: Wei-Pang Yang, IM.NDHU, 2009
account), Fig. 2.23
3. account
Source: Database System Concepts, Silberschatz etc. 2006
2-65
branch-name(branch-city = “Brooklyn”(branch)), Fig. 2.22
1. branch
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-66
2.3.4 Assignment Operation


The assignment operation () provides a convenient way to
express complex queries.

Write query as a sequential program consisting of
• a series of assignments
• followed by an expression whose value is displayed as a
result of the query.
 Assignment must always be made to a temporary relation
variable.
Example: Write r  s as
temp1  R-S (r)
temp2  R-S ((temp1 x s) – R-S,S (r))
result = temp1 – temp2
 The result to the right of the  is assigned to the relation
variable on the left of the .
 May use variable in subsequent expressions.
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-67
Introduction to Database
CHAPTER 3
RELATIONAL MODEL






2.1 Structure of Relational Databases
2.2 Fundamental Relational-Algebra Operations
2.3 Additional Relational-Algebra Operations
2.4 Extended Relational-Algebra Operations
2.5 Null Values
2.6 Modification of the Database
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-68
2.4 Extended Relational-Algebra Operations



Generalized Projection
Aggregate Functions
Outer Join
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-69
2.4.1 Generalized Projection




Extends the projection operation by allowing arithmetic functions to be
used in the projection list.
 F1, F2, …, Fn(E)
E is any relational-algebra expression
Each of F1, F2, …, Fn are are arithmetic expressions involving constants
and attributes in the schema of E.
Given relation credit-info(customer-name, limit, credit-balance), find
how much more each person can spend:
customer-name, limit – credit-balance (credit-info)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-70
Generalized Projection: Example

Query: Find how much more each person can spend
customer-name, (limit – credit-balance) as credit-available(credit-info).
credit-info
P. 61
Fig. 2.24
Edited: Wei-Pang Yang, IM.NDHU, 2009
Fig. 2.25
Source: Database System Concepts, Silberschatz etc. 2006
2-71
2.4.2 Aggregate Functions

Aggregation function takes a collection of values and returns a single
value as a result.
1. avg: average value
2. min: minimum value
3. max: maximum value
4. sum: sum of values
4. count: number of values

Aggregate operation in relational algebra
G1, G2, …, Gn g F1( A1), F2( A2),…, Fn( An) (E)




E is any relational-algebra expression
G1, G2, …, Gn is a list of attributes on which to group (can be empty)
Each Fi is an aggregate function
Each Ai is an attribute name
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-72
Aggregate Functions: Example 1

Relation r:
g sum(c) (r)
Edited: Wei-Pang Yang, IM.NDHU, 2009
A
B
C








7
7
3
10
sum-C
27
Source: Database System Concepts, Silberschatz etc. 2006
2-73
Aggregate Functions: Example 2

Relation account grouped by branch-name:
branch-name
Perryridge
Perryridge
Brighton
Brighton
Redwood
branch-name
g
account-number
balance
A-102
A-201
A-217
A-215
A-222
400
900
750
750
700
sum(balance) (account)
branch-name
balance
Perryridge
Brighton
Redwood
Edited: Wei-Pang Yang, IM.NDHU, 2009
1300
1500
700
Source: Database System Concepts, Silberschatz etc. 2006
2-74
Aggregate Functions: Rename

Result of aggregation does not have a name
 Can use rename operation to give it a name

For convenience, we permit renaming as part of aggregate operation
branch-name
g
sum(balance) as sum-balance (account)
branch-name
Perryridge
Brighton
Redwood
Edited: Wei-Pang Yang, IM.NDHU, 2009
sum-balance
1300
1500
700
Source: Database System Concepts, Silberschatz etc. 2006
2-75
Aggregate Functions: Example 3
pt-works Fig. 2.26
pt-works
Fig. 2.27
The pt-works relation after Grouping

Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-76
Aggregate Functions: Example 3 (cont.)
pt-works

branch-name
 sum(salary) (pt-works)
Fig. 2.28
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-77
Aggregate Functions: Example 3 (cont.)
pt-works
branch-name 
sum salary, max(salary) as max-salary
Edited: Wei-Pang Yang, IM.NDHU, 2009
(pt-works), Fig. 2.29
Source: Database System Concepts, Silberschatz etc. 2006
2-78
2.4.3 Outer Join



An extension of the join operation that avoids loss of information.
Computes the join and then adds tuples form one relation that do not
match tuples in the other relation to the result of the join.
Uses null values:
 null signifies that the value is unknown or does not exist

All comparisons involving null are (roughly speaking) false by
definition.
•
Will study precise meaning of comparisons with nulls later
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-79
Example 1: Outer Join
 The employee and ft-works Relations, Fig. 2.30
employee
ft-works
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-80
Example 1: Natural Join
employee
ft-works
Fig. 2.31: The Result of employee
Edited: Wei-Pang Yang, IM.NDHU, 2009
ft-works
Source: Database System Concepts, Silberschatz etc. 2006
2-81
Example 1: Left Outer Join
employee
ft-works
Fig. 2.32: The Result of employee
Edited: Wei-Pang Yang, IM.NDHU, 2009
ft-works
Source: Database System Concepts, Silberschatz etc. 2006
2-82
Example 1: Right Outer Join
employee
ft-works
Fig. 2.33: Result of employee
Edited: Wei-Pang Yang, IM.NDHU, 2009
ft-works
Source: Database System Concepts, Silberschatz etc. 2006
2-83
Example 1: Full Outer Join
employee
ft-works
Fig. 2.34: Result of employee
Edited: Wei-Pang Yang, IM.NDHU, 2009
ft-works
Source: Database System Concepts, Silberschatz etc. 2006
2-84
Outer Join: Example 2

Relation loan
loan-number
L-170
L-230
L-260

branch-name
amount
Downtown
Redwood
Perryridge
3000
4000
1700
Relation borrower
customer-name
Jones
Smith
Hayes
Edited: Wei-Pang Yang, IM.NDHU, 2009
loan-number
L-170
L-230
L-155
Source: Database System Concepts, Silberschatz etc. 2006
2-85
Outer Join: Example 2 (cont.)

Inner Join
loan
Borrower
loan-number
L-170
L-230
branch-name
Downtown
Redwood
amount
3000
4000
customer-name
Jones
Smith
 Left Outer Join
loan
Borrower
loan-number
L-170
L-230
L-260
Edited: Wei-Pang Yang, IM.NDHU, 2009
branch-name
Downtown
Redwood
Perryridge
amount
3000
4000
1700
customer-name
Jones
Smith
null
Source: Database System Concepts, Silberschatz etc. 2006
2-86
Outer Join: Example 2 (cont.)
Right Outer Join
loan
borrower

loan-number branch-name
L-170
Downtown
L-230
Redwood
L-155
null

Full Outer Join
loan
borrower
loan-number
L-170
L-230
L-260
L-155
Edited: Wei-Pang Yang, IM.NDHU, 2009
branch-name
Downtown
Redwood
Perryridge
null
amount customer-name
3000
Jones
4000
Smith
null
Hayes
amount customer-name
3000
Jones
4000
Smith
1700
null
null
Hayes
Source: Database System Concepts, Silberschatz etc. 2006
2-87
Introduction to Database
CHAPTER 3
RELATIONAL MODEL






2.1 Structure of Relational Databases
2.2 Fundamental Relational-Algebra Operations
2.3 Additional Relational-Algebra Operations
2.4 Extended Relational-Algebra Operations
2.5 Null Values
2.6 Modification of the Database
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-88
2.5 Null Values




It is possible for tuples to have a null value, denoted by null, for
some of their attributes
null signifies an unknown value or that a value does not exist.
The result of any arithmetic expression involving null is null.
Aggregate functions simply ignore null values
 Is an arbitrary decision. Could have returned null as result
instead.


We follow the semantics of SQL in its handling of null values
For duplicate elimination and grouping, null is treated like any other
value, and two nulls are assumed to be the same
 Alternative: assume each null is different from each other

Both are arbitrary decisions, so we simply follow SQL
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-89
Null Values

Comparisons with null values return the special truth value unknown
 If false was used instead of unknown, then
not (A < 5)
would not be equivalent to
A >= 5

Three-valued logic using the truth value unknown:
 OR: (unknown or true)
= true,
(unknown or false)
= unknown
(unknown or unknown) = unknown

AND: (true and unknown)
= unknown,
(false and unknown)
= false,
(unknown and unknown) = unknown

NOT: (not unknown) = unknown


In SQL “P is unknown” evaluates to true if predicate P evaluates to
unknown
Result of select predicate is treated as false if it evaluates to unknown
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-90
2.6 Modification of the Database


The content of the database may be modified using the
following operations:
 Deletion

Insertion

Updating
All these operations are expressed using the assignment
operator.
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-91
2.6.1 Deletion



A delete request is expressed similarly to a query, except instead
of displaying tuples to the user, the selected tuples are removed
from the database.
Can delete only whole tuples; cannot delete values on only
particular attributes
A deletion is expressed in relational algebra by:
rr–E
where r is a relation and E is a relational algebra query.
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-92
Deletion: Examples


Delete all account records in the Perryridge branch.
account  account – branch-name = “Perryridge” (account)
Delete all loan records with amount in the range of 0 to 50
loan  loan – amount 0 and amount  50 (loan)

Delete all accounts at branches located in Needham.
r1   branch-city = “Needham” (account
branch)
r2  branch-name, account-number, balance (r1)
r3   customer-name, account-number (r2
depositor)
account  account – r2
depositor  depositor – r3
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-93
2.6.2 Insertion

To insert data into a relation, we either:
 specify a tuple to be inserted



write a query whose result is a set of tuples to be inserted
in relational algebra, an insertion is expressed by:
r r  E
where r is a relation and E is a relational algebra expression.
The insertion of a single tuple is expressed by letting E be a constant
relation containing one tuple.
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-94
Insertion: Examples

Insert information in the database specifying that Smith has $1200 in
account A-973 at the Perryridge branch.
account  account  {(“Perryridge”, A-973, 1200)}
depositor  depositor  {(“Smith”, A-973)}

Provide as a gift for all loan customers in the Perryridge branch, a
$200 savings account. Let the loan number serve as the account
number for the new savings account.
r1  (branch-name = “Perryridge” (borrower
loan))
account  account  branch-name, account-number,200 (r1)
depositor  depositor  customer-name, loan-number(r1)
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-95
2.6.3 Updating



A mechanism to change a value in a tuple without charging all values in
the tuple
Use the generalized projection operator to do this task
r   F1, F2, …, FI, (r)
Each Fi is either
 the ith attribute of r, if the ith attribute is not updated, or,

if the attribute is to be updated Fi is an expression, involving only
constants and the attributes of r, which gives the new value for the
attribute
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-96
Update: Examples

Make interest payments by increasing all balances by 5 percent.
account   AN, BN, BAL * 1.05 (account)
where AN, BN and BAL stand for account-number, branch-name and
balance, respectively.

Pay all accounts with balances over $10,000 6 percent interest and
pay all others 5 percent
account 
Edited: Wei-Pang Yang, IM.NDHU, 2009
 AN, BN, BAL * 1.06 ( BAL  10000 (account))
 AN, BN, BAL * 1.05 (BAL  10000 (account))
Source: Database System Concepts, Silberschatz etc. 2006
2-97
2.7 Summary

P.70
Edited: Wei-Pang Yang, IM.NDHU, 2009
Source: Database System Concepts, Silberschatz etc. 2006
2-98