Download Workshop 3

CSS/416
Data Design
and Retrieval
Workshop 3
Database Management
Systems
Terminology
Traditional
MIS
File
RDBMS
Table
Relational
Algebra
Relation
Record
Row
Tuple
Field
Column
Attribute
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Database management
Systems
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Relational model
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Based on 1970 paper by E.F. Codd
User sees all data in tables
Tables can be combined using “set”
operations (linked via columns)
Metadata also stored in tables as above
Logical design separate from physical
implementations
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Database Management
Systems
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Functional Dependencies
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A -> B; A determines B (A is Determinant)
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Partial (PK = AB, B -> C)
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CustID -> Customer Name
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Database Management
Systems
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Keys
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Derived from entity identifier
One or more attributes (more = composite
key)
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Uniquely determine a row
Functionally determine an entire row’s
attributes
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Database management
systems
Modification Anomalies (multiple themes)
SID
100
Activity
Skiing
Fee
200
150
175
200
Swimming
Squash
Swimming
50
50
50
- Can’t insert fact that scuba diving cost $175
- Cant update swimming fee
- Delete SID 100=>lose skiing data
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Database Normalization
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Entities should have common theme
Stages
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First Normal form
Second
Third
Others (BCNF, 4th, 5th, DK)
Impact on referential integrity
Denormalize for performance (city, state, zip is
classic example)
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Database Normalization
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1st normal form – eliminate multivalued attributes(repeating groups)
2nd normal – no partial key functional
dependencies
3rd normal – eliminate transitive
dependencies
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Database Normal Forms
Violates first normal – why?
Plant
Name
Eqpt
Name
Plant
Mgr
Eqpt
Mfgr
ethylene
Final cooler,
feed heater
Jim Smith ABC
Exchanger
1247 Locust
styrene
Feed pump
Bill Gunn
XYZ Pumps
432
Broadway
styrene
Feed pump
Bill Gunn
ABC
Exchanger
1247 Locust
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Mfgr
Addr
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Database Normalization
1st Normal satisfied
Still violates 2nd normal– why?
Plant
Name
Eqpt Name
Plant
Mgr
Eqpt Mfgr
ethylene
Final cooler
Jim Smith ABC
Exchanger
1247 Locust
ethylene
Feed heater
Jim Smith ABC
Exchanger
1247 Locust
styrene
Feed pump
Bill Gunn
XYZ Pumps
432
Broadway
styrene
Feed heater
Bill Gunn
ABC
Exchanger
1247 Locust
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Mfgr Addr
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Database Normalization
PlantN
ame
Plant Mgr
PlantN
ame
Eqpt
name
Eqpt Mfgr
Mfgr Addr
ethylene
Jim Smith
ethylene
Final
cooler
ABC Exchanger
1247 Locust
styrene
Bill Gunn
ethylene
Feed
heater
ABC Exchanger
1247 Locust
styrene
Feed pump XYZ Pumps
432 Broadway
styrene
Feed
heater
1247 Locust
2nd OK but 3rd?
ABC Exchanger
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Database Normalization
PlantN
ame
Plant Mgr
Ethylene
Jim Smith
styrene
Bill Gunn
Eqpt Mfgr
Mfgr Addr
ABC
Exchanger
1247 Locust
XYZ Pumps
432 Broadway
PlantN
ame
Eqpt
name
Eqpt Mfgr
ethylene
Final
cooler
ABC Exchanger
ethylene
Feed
heater
ABC Exchanger
styrene
Feed pump XYZ Pumps
styrene
Feed
heater
ABC Exchanger
Satisfies 3rd normal form
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Database Normalization
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BCNF – Every determinant is a
candidate key
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Fourth – Multi-valued dependencies
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Fifth – Can recombine relations
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Database Normalization
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Domain Key (DK/NF)
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Provably free from anomalies
But no one way to generate this form
All constraints follow from domain
definitions and keys
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Database Normalization
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Domain Key (DK/NF)
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“The key, the whole key, and nothing but
the key”
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Database Design
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Translating a model to the Database
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Entities -> tables
Establish primary & foreign keys
Many-to-many relations ->Junction table
Business rules -> triggers, constraints, etc.
Surrogate keys
Security
Typically done with a “CASE” tool
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Database Design
One-to-one
Auto #
Employee
1
Has
1
Auto
Emp #
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Database Design
One-to-many
Mfgr
1
Makes
N
Equipment
Mfgr #
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Database Design
One-to-many (w/ ID Dependency
PK = inv#, item#
Invoice
1
Has
N
Line Item
Inv #
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Database Design
Many-to-many
Mfg #
Eqpt ID
Mfgr_Eqpt
Equipment
Mfgr
M
N
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Database Design
Recursive
Member
1
1
Referred by
Member #
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Database Design
IS-A relationship (Subscriptions)
Member
Member#
Print
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Database Design
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Learning teams to implement sample
relations for above E-R relationships:
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1 to 1
1 to many
Many to many
1 to many w/ ID Dependency
Recursive
IS-A
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SQL
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Two main language components
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Data definition language (DDL)
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Data manipulation language (DML)
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SQL
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Data definition language (DDL)
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Create, alter, drop, etc.
Frequently implemented via various CASE
tools: Visio, Embarcadero, ERWin, etc.
But – also very useful for database
administration
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SQL
Create Statement
Create table patient
(name
varchar2(35) not null,
age
smallint,
gender
varchar2(1),
account_number integer not null,
primary key
account_number)
<..additional constraints such as foreign keys, etc. ..>
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SQL
Select (Projection)
Select plantname
from equipment
Select (Restriction)
Select *
from equipment
where eqpt_name = ‘feed heater’
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SQL
Select (Selection + projection)
Select eqpt_name
from equipment
where plantname = “styrene”
Sorting (Ordering)
Select *
from manufacturers
order by eqpt_mfgr
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SQL
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There are many built in functions
Some are called aggregate
functions
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Count
Max
Avg
Etc.
Example
Select max(age) from dependents
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SQL
Joins (old syntax)
Select m.mfgr_addr
from manufacturers m, equipment e
where m.eqpt_mfgr = e.eqpt_mfgr
and e.plantname = ‘styrene’
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SQL
Joins (new syntax)
Select m.mfgr_addr
from manufacturers m
inner join equipment e
On e.name = m.name
where e.plantname = ‘styrene’
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SQL
Subqueries
Select m.mfg_addr
from manufacturers m
where eqpt_mfgr in
(select e.eqpt_name from equipment e)
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SQL
Insert
Insert into equipment
values(‘propylene’, ‘feed heater’,
‘ABC Exchanger’)
Update
Update manufacturers
Set address = ‘18 Front Road’
Where mfgr_name = ‘ABC Exchanger’
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SQL
Delete
Delete from equipment
Where plant_name = ‘styrene’
And eqpt_name = ‘feed cooler’
How many rows could this delete?
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SQL Exercise
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Create the tables in the design exercise
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Create a few sample SQL selects, etc.
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Functions of a Database
Application
Page 238
Figure 10-1
© 2000 Prentice Hall
CRUD
“the first function of a database
application is to CRUD views”
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Create
Read
Update
Delete
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Format or Materialize views
“the second function of a database
application; the appearance of the
content”
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Other database functions
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Enforce constraints
Provide for security and control
Execute business logic
Page 238
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E-R Diagram
Page 240
Figure 10-3b
© 2000 Prentice Hall
Relational Design
Page 240
Figure 10-3c
© 2000 Prentice Hall
Relational Design
(w/ Surrogate Keys)
Page 240
Figure 10-3d
© 2000 Prentice Hall
Relational Diagram
Page 241
Figure 10-3e
© 2000 Prentice Hall
View
“A structured list of data items
(attributes) from the entities or
semantic objects defined in the data
model”
A view can be materialized or formatted
as a form or report
Page 242
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Recordset
“the result of an SQL statement”
Page 243
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CRUD actions on a view
Read
SELECT CUSTOMER.CustomerID,
CUSTOMER.Name
FROM CUSTOMER, WORK
WHERE CUSTOMER.CustomerID =
WORK.CustomerID
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CRUD actions on a view
Create
INSERT INTO CUSTOMER
(CUSTOMER.Name, CUSTOMER.City)
VALUES (NewCust.CUSTOMER.Name,
NewCust.CUSTOMER.City)
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CRUD actions on a view
Update
INSERT INTO CUSTOMER
(CUSTOMER.Name, CUSTOMER.City)
VALUES (NewCust.CUSTOMER.Name,
NewCust.CUSTOMER.City)
Page 246
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CRUD actions on a view
Delete
Cascading deletions depends on relationship
cardinality
Page 247
Figure 10-6
© 2000 Prentice Hall
Form
“a screen display used for data entry and
edit”
Forms should...
 reflect the view structure
 make data associations graphically clear
 encourage appropriate action
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Forms in a GUI Environment
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Drop-down list
Option buttons in groups
Check boxes
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GUI controls
Page 252
Figure 10-10
© 2000 Prentice Hall
Report Design
Reports should...
 reflect the structure of the underlying
view
 handle implied objects
Page 253
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Enforcing Constraints
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Domain
Uniqueness
Relationship
Cardinality
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1.1 and 1.N
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fragments
orphans
Business Rule
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triggers
Page 256
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Security
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Horizontal
Vertical
Page 264
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Control
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System of menus
Transaction boundaries(Atomic unit of
work)
Page 265
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