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CS 3630
Database Design and Implementation
Design Methodology
Three main phases
1.
Conceptual database design
Understanding client data
E-R (EER) Model
Contract between clients and designers
E-R Model could be used for any database system
2.
Logical database design
Step1: Mapping E-R Model to (relational) database schema
Step2: Normalization
3.
Physical database design
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Normalization
Relational Database
A set of normalized relations.
Normalization
To get desired performance
Data consistency
1NF, 2NF, 3NF, BCNF, 4NF
and higher normal forms
We stop at BCNF
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Example: DreamHome
Table schemas (after mapping):
Staff (Sno, Name, Address, Phone, Bno, BAddress, BPhone)
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Problems
Staff (Sno, Name, Address, Phone, Bno, BAddress, BPhone)
Redundancy and Inconsistency
Waste space
: for each staff, store BAddress and BPhone
Extra work on insertion: insert staff requires insertion of branch
Extra work on updating: change BPhone, all staff in the branch
Inconsistent data
: when inserting and updating
Sno
Name
Address
Phone
Bno
Baddress
BPhone
S001
. . . .
. . . .
. . . .
B20
20 main st, Platteville, WI 53818
348-8815
S012
. . . .
. . . .
. . . .
B20
20 main st, Platteville, WI 53818
348-8815
S032
. . . .
. . . .
. . . .
B20
20 main st, Platteville, WI 53818
348-8815
S034
. . . .
. . . .
. . . .
B20
20 main st, Platteville, WI 53818
348-8825
S033
. . . .
. . . .
. . . .
B20
25 main st, Platteville, WI 53818
348-8815
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Example: DreamHome
Table schemas
Staff_and_Branch (Sno, Name, Address, Phone, Bno, BAddress, BPhone)
Major Issue
Data Redundancy
Data Inconsistency
Should be
Staff (Sno, Name, Address, Phone, Bno)
Branch (Bno, Address, Phone)
Normalization!
Functional Dependency!
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Functions
A function is a mapping
y = f(x)
y1 = f(x1)
y2 = f(x2)
If x1 = x2 Then
y1 = y2
If x1 != x2 Then
y1 != y2
YES!
NO!
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Examples
Example 1
y = f(x)
= x2
f(2) = f(-2)
Is it possible that
f(v1) != f(v2), but v1 = v2?
NO!
Example 2
y = g(x)
= x2 - 5x + 6
y1 = g(2) = 0
y2 = g(3) = 0
Is it possible that
g(u1) != g(u2), but u1 = u2?
NO!
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Functions
y = f(x)
y1 = f(x1)
y2 = f(x2)
x1 = x2  y1 = y2
True
Same x value, then same y value.
False
x1 != x2  y1 != y2
True
False
Different x values, then same or different y values.
Is it possible that val1 = val2 but f(val1) != f(val2)
NO! Not a function!
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Functional Dependency
Table schema (DBDL) from E-R Model
R (A, B, C, D, E, F)
PK: A
AK: B, C
FK: C references R1
Functional Dependency:
BD
For any two records of R
Same B value
Same D value
Different B values
Same or different D values
(We don’t care!)
D = f(B)
No such a function to calculate the value of D from that of B!
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Example
Staff (Sno, Name, Address, Bno, BAddress)
PK: Sno
AK: None
FK: None
FD: ???
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Example
Staff (Sno, Name, Address, Bno, BAddress)
FD: Sno  Name
Address  Name
Name  Address
Bno  BAddress
BAddress  Bno
Sno
Name
Address
Bno
BAddress
S001
J. Clifton
102 main
B01
1 westhill
S002
M. Smith
102 main
B02
3 easttown
S013
M. Smith
20 main
B01
1 westhill
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Functional Dependency
R (A, B, C, D, E, F)
PK: A
AK: B, C
FK: C references R1
Functional Dependencies:
BD
For any two records of R
Same B value
Same D value
Different B values
Same or different D values
(We don’t care!)
B  D not true
Find two records of R
Same B value
Different D values
(val1 = val2 but f(val1) != f(val2))
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Example
Property (Pno, Address, Type, Ono, Oname)
PK: Pno
AK: Address
FK: Ono references Owner
FD: ???
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Example
Property (Pno, Address, Type, Ono, Oname)
Pno  All
Address  All
Ono  All
Ono  OName
OName  Ono
Pno
Address
Type
YES
YES
NO
YES
NO
Ono
OName
P001
1 Moonnite
House
O01
J. Clifton
P002
3 Sunny
House
O02
M. Smith
P013
9 S. Drive, U22
Aparts
O03
J. Clifton
P014
9 S. Drive, U15
Aparts
O02
M. Smith
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Example
A
10
20
10
30
10
30
B
X
X
Y
Y
Y
X
C
200
300
200
200
200
100
D
CS
CS
SE
SE
CS
CS
AC?
Yes
B  D?
NO
Same value implies same value
Different values?
We do not care!
A  C?
B  D?
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Example
A
10
20
10
30
10
10
30
20
B
X
X
Y
Y
Y
V
Z
W
C
200
300
200
200
200
250
?
?
D
CS
SE
CS
CS
CS
XX
EE
CJ
AC?
Possible
B  D?
NO
Business rules! Must be true for all table instances!
Must be part of table schema and apply to all table instances!
Not just from some table instances!
Checking data entry if A  C is true!
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Functional Dependency
Definition
Assume A and B are attributes of a table R.
A  B (B is functionally dependent on A)
If each value of A in R is associated with exactly one value of B in R.
A is called Determinant.
Any two records of R
If they agree on A (have the same value on A),
Then they will agree on B (have the same value on B).
If they have different values on A,
Then they may have different values or the same value on B.
B = f(A)
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Assignment 5-1
Due Friday, February 24, by 5 PM
Friday will cover all materials for A5-1
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Assignment 4
Due February 22
By Noon.
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