IS 257 – Fall 2009 2009-09-15 SLIDE 1

Physical Database Design

University of California, Berkeley

School of Information

I 257: Database Management

IS 257 – Fall 2009 2009-09-15 SLIDE 2

Lecture Outline

• Review– Normalization

• Physical Database Design

• Access Methods

IS 257 – Fall 2009 2009-09-15 SLIDE 3

Lecture Outline

• Review– Normalization

• Physical Database Design

• Access Methods

IS 257 – Fall 2009 2009-09-15 SLIDE 4

Database Design Process

ConceptualModel

LogicalModel

External Model

Conceptual requirements

Conceptual requirements

Conceptual requirements

Conceptual requirements

Application 1

Application 1

Application 2 Application 3 Application 4

Application 2

Application 3

Application 4

External Model

External Model

External Model

Internal Model

IS 257 – Fall 2009 2009-09-15 SLIDE 5

Normalization

• Normalization theory is based on the observation that relations with certain properties are more effective in inserting, updating and deleting data than other sets of relations containing the same data

• Normalization is a multi-step process beginning with an “unnormalized” relation– Hospital example from Atre, S. Data Base:

Structured Techniques for Design, Performance, and Management.

IS 257 – Fall 2009 2009-09-15 SLIDE 6

Normal Forms

• First Normal Form (1NF)

• Second Normal Form (2NF)

• Third Normal Form (3NF)

• Boyce-Codd Normal Form (BCNF)

• Fourth Normal Form (4NF)

• Fifth Normal Form (5NF)

IS 257 – Fall 2009 2009-09-15 SLIDE 7

Normalization

Boyce-Codd and

Higher

Functional dependencyof nonkey attributes on the primary key - Atomic values only

Full Functional dependencyof nonkey attributes on the primary key

No transitive dependency between nonkey attributes

All determinants are candidate keys - Single multivalued dependency

IS 257 – Fall 2009 2009-09-15 SLIDE 8

Unnormalized Relations

• First step in normalization is to convert the data into a two-dimensional table

• In unnormalized relations data can repeat within a column

IS 257 – Fall 2009 2009-09-15 SLIDE 9

Unnormalized RelationPatient # Surgeon # Surg. date Patient Name Patient Addr Surgeon Surgery Postop drugDrug side effects

1111145 311

Jan 1, 1995; June 12, 1995 John White

15 New St. New York, NY

Beth Little Michael Diamond

Gallstones removal; Kidney stones removal

Penicillin, none-

rash none

1234243 467

Apr 5, 1994 May 10, 1995 Mary Jones

10 Main St. Rye, NY

Charles Field Patricia Gold

Eye Cataract removal Thrombosis removal

Tetracycline none

Fever none

2345 189Jan 8, 1996 Charles Brown

Dogwood Lane Harrison, NY

David Rosen

Open Heart Surgery

Cephalosporin none

4876 145Nov 5, 1995 Hal Kane

55 Boston Post Road, Chester, CN Beth Little

Cholecystectomy Demicillin none

5123 145May 10, 1995 Paul Kosher

Blind Brook Mamaroneck, NY Beth Little

Gallstones Removal none none

6845 243

Apr 5, 1994 Dec 15, 1984 Ann Hood

Hilton Road Larchmont, NY

Charles Field

Eye Cornea Replacement Eye cataract removal

Tetracycline Fever

IS 257 – Fall 2009 2009-09-15 SLIDE 10

First Normal Form

• To move to First Normal Form a relation must contain only atomic values at each row and column.– No repeating groups– A column or set of columns is called a

Candidate Key when its values can uniquely identify the row in the relation.

IS 257 – Fall 2009 2009-09-15 SLIDE 11

First Normal Form

Patient # Surgeon #Surgery DatePatient NamePatient AddrSurgeon Name Surgery Drug adminSide Effects

1111 145 01-Jan-95 John White

15 New St. New York, NY Beth Little

Gallstones removal Penicillin rash

1111 311 12-Jun-95 John White

15 New St. New York, NY

Michael Diamond

Kidney stones removal none none

1234 243 05-Apr-94 Mary Jones10 Main St. Rye, NY Charles Field

Eye Cataract removal

Tetracycline Fever

1234 467 10-May-95 Mary Jones10 Main St. Rye, NY Patricia Gold

Thrombosis removal none none

2345 189 08-Jan-96Charles Brown

Dogwood Lane Harrison, NY David Rosen

Open Heart Surgery

Cephalosporin none

4876 145 05-Nov-95 Hal Kane

55 Boston Post Road, Chester, CN Beth Little

Cholecystectomy Demicillin none

5123 145 10-May-95 Paul Kosher

Blind Brook Mamaroneck, NY Beth Little

Gallstones Removal none none

6845 243 05-Apr-94 Ann Hood

Hilton Road Larchmont, NY Charles Field

Eye Cornea Replacement

Tetracycline Fever

6845 243 15-Dec-84 Ann Hood

Hilton Road Larchmont, NY Charles Field

Eye cataract removal none none

IS 257 – Fall 2009 2009-09-15 SLIDE 12

Second Normal Form

• A relation is said to be in Second Normal Form when every nonkey attribute is fully functionally dependent on the primary key.– That is, every nonkey attribute needs the full

primary key for unique identification

IS 257 – Fall 2009 2009-09-15 SLIDE 13

Second Normal Form

Patient # Patient Name Patient Address

1111 John White15 New St. New York, NY

1234 Mary Jones10 Main St. Rye, NY

2345Charles Brown

Dogwood Lane Harrison, NY

4876 Hal Kane55 Boston Post Road, Chester,

5123 Paul KosherBlind Brook Mamaroneck, NY

6845 Ann HoodHilton Road Larchmont, NY

IS 257 – Fall 2009 2009-09-15 SLIDE 14

Second Normal Form

Surgeon # Surgeon Name

145 Beth Little

189 David Rosen

243 Charles Field

311 Michael Diamond

467 Patricia Gold

IS 257 – Fall 2009 2009-09-15 SLIDE 15

Second Normal Form

Patient # Surgeon # Surgery Date Surgery Drug Admin Side Effects

1111 145 01-Jan-95Gallstones removal Penicillin rash

1111 311 12-Jun-95

Kidney stones removal none none

1234 243 05-Apr-94Eye Cataract removal Tetracycline Fever

1234 467 10-May-95Thrombosis removal none none

2345 189 08-Jan-96Open Heart Surgery

Cephalosporin none

4876 145 05-Nov-95Cholecystectomy Demicillin none

5123 145 10-May-95Gallstones Removal none none

6845 243 15-Dec-84Eye cataract removal none none

6845 243 05-Apr-94Eye Cornea Replacement Tetracycline Fever

IS 257 – Fall 2009 2009-09-15 SLIDE 16

Third Normal Form

• A relation is said to be in Third Normal Form if there is no transitive functional dependency between nonkey attributes– When one nonkey attribute can be determined with

one or more nonkey attributes there is said to be a transitive functional dependency.

• The side effect column in the Surgery table is determined by the drug administered – Side effect is transitively functionally dependent on

drug so Surgery is not 3NF

IS 257 – Fall 2009 2009-09-15 SLIDE 17

Third Normal Form

Patient # Surgeon # Surgery Date Surgery Drug Admin

1111 145 01-Jan-95 Gallstones removal Penicillin

1111 311 12-Jun-95Kidney stones removal none

1234 243 05-Apr-94 Eye Cataract removal Tetracycline

1234 467 10-May-95 Thrombosis removal none

2345 189 08-Jan-96 Open Heart Surgery Cephalosporin

4876 145 05-Nov-95 Cholecystectomy Demicillin

5123 145 10-May-95 Gallstones Removal none

6845 243 15-Dec-84 Eye cataract removal none

6845 243 05-Apr-94Eye Cornea Replacement Tetracycline

IS 257 – Fall 2009 2009-09-15 SLIDE 18

Third Normal Form

Drug Admin Side Effects

Cephalosporin none

Demicillin none

none none

Penicillin rash

Tetracycline Fever

IS 257 – Fall 2009 2009-09-15 SLIDE 19

Boyce-Codd Normal Form

• Most 3NF relations are also BCNF relations.

• A 3NF relation is NOT in BCNF if:– Candidate keys in the relation are composite

keys (they are not single attributes)– There is more than one candidate key in the

relation, and– The keys are not disjoint, that is, some

attributes in the keys are common

IS 257 – Fall 2009 2009-09-15 SLIDE 20

BCNF Relations

Patient # Patient Name

1111 John White

1234 Mary Jones

2345Charles Brown

4876 Hal Kane

5123 Paul Kosher

6845 Ann Hood

Patient # Patient Address

111115 New St. New York, NY

123410 Main St. Rye, NY

2345Dogwood Lane Harrison, NY

487655 Boston Post Road, Chester,

5123Blind Brook Mamaroneck, NY

6845Hilton Road Larchmont, NY

IS 257 – Fall 2009 2009-09-15 SLIDE 21

Fourth Normal Form

• Any relation is in Fourth Normal Form if it is BCNF and any multivalued dependencies are trivial

• Eliminate non-trivial multivalued dependencies by projecting into simpler tables

IS 257 – Fall 2009 2009-09-15 SLIDE 22

Fifth Normal Form

• A relation is in 5NF if every join dependency in the relation is implied by the keys of the relation

• Implies that relations that have been decomposed in previous NF can be recombined via natural joins to recreate the original relation.

IS 257 – Fall 2009 2009-09-15 SLIDE 23

Normalization

• Normalization is performed to reduce or eliminate Insertion, Deletion or Update anomalies.

• However, a completely normalized database may not be the most efficient or effective implementation.

• “Denormalization” is sometimes used to improve efficiency.

IS 257 – Fall 2009 2009-09-15 SLIDE 24

Denormalization

• Usually driven by the need to improve query speed

• Query speed is improved at the expense of more complex or problematic DML (Data manipulation language) for updates, deletions and insertions.

IS 257 – Fall 2009 2009-09-15 SLIDE 25

Downward Denormalization

Customer

ID

Address

Name

Telephone

Order

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Before:Customer

ID

Address

Name

Telephone

Order

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Cust Name

After:

IS 257 – Fall 2009 2009-09-15 SLIDE 26

Upward DenormalizationOrder

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Cust Name

Order Price

Order Item

Order No

Item No

Item Price

Num Ordered

Order

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Cust Name

Order Item

Order No

Item No

Item Price

Num Ordered

IS 257 – Fall 2009 2009-09-15 SLIDE 27

Using RDBMS to help normalize

• Example database: Cookie

• Database of books, libraries, publisher and holding information for a shared (union) catalog

IS 257 – Fall 2009 2009-09-15 SLIDE 28

Cookie relationships

IS 257 – Fall 2009 2009-09-15 SLIDE 29

Cookie BIBFILE relation

ACCNO AUTHOR TITLE LOC PUBID DATE PRICE PAGINATIONILL HEIGHTA003 AMERICAN LIBRARY ASSOCIATIONALA BULLETIN CHICAGO 04 $3.00 63 V. ILL. 26T082 ANDERSON, THEODORETHE TEACHING OF MODERN LANGUAGESPARIS 53 1955 $10.95 294 P. 22C024 AXT, RICHARD G. COLLEGE SELF STUDY : LECTURES ON INSTITUBOULDER, CO. 51 1960 $7.00 X, 300 P. GRAPHS 28B006 BALDERSTON, FREDERICK E.MANAGING TODAYS UNIVERSITYSAN FRANCISCO 27 1975 $6.00 XVI, 307 P. 24B007 BARZUN, JACQUES TEACHER IN AMERICAGARDEN CITY 18 1954 $7.00 280 P. 18B005 BARZUN, JACQUES THE AMERICAN UNIVERSITY : HOW IT RUNS, WNEW YORK 24 1970 $5.00 XII, 319 P. 20B008 BARZUN, JACQUES THE HOUSE OF INTELLECTNEW YORK 24 1961 $8.00 VIII, 271 P. 21B010 BELL, DANIEL THE COMING OF POST-INDUSTRIAL SOCIETY :NEW YORK 09 1976 $10.00 XXVII, 507 P. 21B009 BENSON, CHARLES S. IMPLEMENTING THE LEARNING SOCIETYSAN FRANCISCO 27 1974 $9.00 XVII, 147 P. 24B012 BERG, IVAR EDUCATION AND JOBS : THE GREAT TRAININGBOSTON 10 1971 $12.00 XX, 200 P. 21B011 BERSI, ROBERT M. RESTRUCTURING THE BACCALAUREATEWASHINGTON, D.C.03 1973 $11.00 IV, 160P. 23B014 BEVERIDGE, WILLIAM I.THE ART OF SCIENTIFIC INVESTIGATIONNEW YORK 58 1957 $14.00 XIV, 239 P. 18B013 BIRD, CAROLINE THE CASE AGAINST COLLEGENEW YORK 08 1975 $13.00 XII, 308 P. 18B016 BISSELL, CLAUDE T. THE STRENGTH OF THE UNIVERSITYTORONTO 57 1968 $14.00 VII, 251 P. 21B017 BLAIR, GLENN MYERS EDUCATIONAL PSYCHOLOGYNEW YORK 30 1962 $11.00 678 P. 24F047 BLAKE, ELIAS, JR. THE FUTURE OF THE BLACK COLLEGESCAMBRIDGE, MA.02 1971 $14.25 VIII, PP. 539 23B116 BOLAND, R.J. CRITICAL ISSUES IN INFORMATION SYSTEMS RCHICHESTER, ENG.63 1987 $30.95 XV, 394 P. ILL. 24S102 BROWN, SANBORN C., ED.SCIENTIFIC MANPOWERCAMBRIDGE, MASS.29 1971 $4.00 X, 180 P. 26B118 BUCKLAND, MICHAEL K.LIBRARY SERVICES IN THEORY AND CONTEXTELMSFORD, NY 70 1983 $12.00 XII, 201 P. ILL. 23B018 BUDIG, GENE A. ACADEMIC QUICKSAND : SOME TRENDS AND ISSLINCOLN, NEBRASKA37 1973 $13.00 74 P. 23C031 CALIFORNIA. DEPT. OF JUSTICELAW IN THE SCHOOLMONTCLAIR, N.J. 35 1974 $0.50 IV, 87 P. 21C032 CAMPBELL, MARGARET A.WHY WOULD A GIRL GO INTO MEDICINE?OLD WESTBURY, N.Y.48 1973 $1.50 V, 114 P. 24C034 CARNEGIE COMMISSION ON HIGHERA DIGEST OF REPORTS OF THE CARNEGIE COMMNEW YORK 30 1974 $3.50 399 P. 24

IS 257 – Fall 2009 2009-09-15 SLIDE 30

How to Normalize?

• Currently no way to have multiple authors for a given book, and there is duplicate data spread over the BIBFILE table

• Can we use the DBMS to help us normalize?

• Access example…

IS 257 – Fall 2009 2009-09-15 SLIDE 31

DBMS Assisted Normalization

• SELECT DISTINCT items to be factored out into a new table

• Add new ID (autonumber) to table create primary key

• SELECT DISTINCT ID from new table and original table ID to new linking table

• Remove column(s) factored out from original table

IS 257 – Fall 2009 2009-09-15 SLIDE 32

Lecture Outline

• Review– Normalization

– Using Relational DBs in normalization

• Physical Database Design

• Access Methods

IS 257 – Fall 2009 2009-09-15 SLIDE 33

Database Design Process

ConceptualModel

LogicalModel

External Model

Conceptual requirements

Conceptual requirements

Conceptual requirements

Conceptual requirements

Application 1

Application 1

Application 2 Application 3 Application 4

Application 2

Application 3

Application 4

External Model

External Model

External Model

Internal Model

PhysicalDesign

IS 257 – Fall 2009 2009-09-15 SLIDE 34

Physical Database Design

• Many physical database design decisions are implicit in the technology adopted– Also, organizations may have standards or an

“information architecture” that specifies operating systems, DBMS, and data access languages -- thus constraining the range of possible physical implementations.

• We will be concerned with some of the possible physical implementation issues

IS 257 – Fall 2009 2009-09-15 SLIDE 35

Physical Database Design

• The primary goal of physical database design is data processing efficiency

• We will concentrate on choices often available to optimize performance of database services

• Physical Database Design requires information gathered during earlier stages of the design process

IS 257 – Fall 2009 2009-09-15 SLIDE 36

Physical Design Information

• Information needed for physical file and database design includes:– Normalized relations plus size estimates for them– Definitions of each attribute– Descriptions of where and when data are used

• entered, retrieved, deleted, updated, and how often

– Expectations and requirements for response time, and data security, backup, recovery, retention and integrity

– Descriptions of the technologies used to implement the database

IS 257 – Fall 2009 2009-09-15 SLIDE 37

Physical Design Decisions

• There are several critical decisions that will affect the integrity and performance of the system– Storage Format– Physical record composition– Data arrangement– Indexes– Query optimization and performance tuning

IS 257 – Fall 2009 2009-09-15 SLIDE 38

Storage Format

• Choosing the storage format of each field (attribute). The DBMS provides some set of data types that can be used for the physical storage of fields in the database

• Data Type (format) is chosen to minimize storage space and maximize data integrity

IS 257 – Fall 2009 2009-09-15 SLIDE 39

Objectives of data type selection

• Minimize storage space• Represent all possible values• Improve data integrity• Support all data manipulations• The correct data type should, in minimal

space, represent every possible value (but eliminate illegal values) for the associated attribute and can support the required data manipulations (e.g. numerical or string operations)

IS 257 – Fall 2009 2009-09-15 SLIDE 40

Access Data Types

• Numeric (1, 2, 4, 8 bytes, fixed or float)• Text (255 max)• Memo (64000 max)• Date/Time (8 bytes)• Currency (8 bytes, 15 digits + 4 digits decimal)• Autonumber (4 bytes)• Yes/No (1 bit)• OLE (limited only by disk space)• Hyperlinks (up to 64000 chars)

IS 257 – Fall 2009 2009-09-15 SLIDE 41

Access Numeric types

• Byte – Stores numbers from 0 to 255 (no fractions). 1 byte

• Integer– Stores numbers from –32,768 to 32,767 (no fractions) 2 bytes

• Long Integer (Default) – Stores numbers from –2,147,483,648 to 2,147,483,647 (no fractions). 4

bytes

• Single– Stores numbers from -3.402823E38 to –1.401298E–45 for negative

values and from 1.401298E–45 to 3.402823E38 for positive values.4 bytes

• Double– Stores numbers from –1.79769313486231E308 to –

4.94065645841247E–324 for negative values and from 1.79769313486231E308 to 4.94065645841247E–324 for positive values. 15 8 bytes

• Replication ID– Globally unique identifier (GUID) N/A 16 bytes

IS 257 – Fall 2009 2009-09-15 SLIDE 42

Controlling Data Integrity

• Default values

• Range control

• Null value control

• Referential integrity (next time)

• Handling missing data

IS 257 – Fall 2009 2009-09-15 SLIDE 43

Designing Physical Records

• A physical record is a group of fields stored in adjacent memory locations and retrieved together as a unit

• Fixed Length and variable fields

IS 257 – Fall 2009 2009-09-15 SLIDE 44

Designing Physical/Internal Model

• Overview

• terminology

• Access methods

IS 257 – Fall 2009 2009-09-15 SLIDE 45

Physical Design

• Internal Model/Physical Model

OperatingSystem

Access Methods

DataBase

User request

DBMSInternal ModelAccess Methods

External Model

Interface 1

Interface 3

Interface 2

IS 257 – Fall 2009 2009-09-15 SLIDE 46

Physical Design

• Interface 1: User request to the DBMS. The user presents a query, the DBMS determines which physical DBs are needed to resolve the query

• Interface 2: The DBMS uses an internal model access method to access the data stored in a logical database.

• Interface 3: The internal model access methods and OS access methods access the physical records of the database.

IS 257 – Fall 2009 2009-09-15 SLIDE 47

Physical File Design

• A Physical file is a portion of secondary storage (disk space) allocated for the purpose of storing physical records

• Pointers - a field of data that can be used to locate a related field or record of data

• Access Methods - An operating system algorithm for storing and locating data in secondary storage

• Pages - The amount of data read or written in one disk input or output operation

IS 257 – Fall 2009 2009-09-15 SLIDE 48

Internal Model Access Methods

• Many types of access methods:– Physical Sequential– Indexed Sequential– Indexed Random– Inverted– Direct– Hashed

• Differences in – Access Efficiency– Storage Efficiency

IS 257 – Fall 2009 2009-09-15 SLIDE 49

Physical Sequential

• Key values of the physical records are in logical sequence

• Main use is for “dump” and “restore”

• Access method may be used for storage as well as retrieval

• Storage Efficiency is near 100%

• Access Efficiency is poor (unless fixed size physical records)

IS 257 – Fall 2009 2009-09-15 SLIDE 50

Indexed Sequential

• Key values of the physical records are in logical sequence

• Access method may be used for storage and retrieval

• Index of key values is maintained with entries for the highest key values per block(s)

• Access Efficiency depends on the levels of index, storage allocated for index, number of database records, and amount of overflow

• Storage Efficiency depends on size of index and volatility of database

IS 257 – Fall 2009 2009-09-15 SLIDE 51

Index Sequential

Data File

Block 1

Block 2

Block 3

AddressBlockNumber

1

2

3

…

ActualValue

Dumpling

Harty

Texaci

...

AdamsBecker

Dumpling

GettaHarty

MobileSunociTexaci

IS 257 – Fall 2009 2009-09-15 SLIDE 52

Indexed Sequential: Two Levels

Address

7

8

9

…

Key Value

385

678

805

001003

.

.150

705710

.

.785

251..

385

455480

.

.536

605610

.

.678

791..

805

Address

1

2

Key Value

150

385

Address

3

4

Key Value

536

678

Address

5

6

Key Value

785

805

IS 257 – Fall 2009 2009-09-15 SLIDE 53

Indexed Random

• Key values of the physical records are not necessarily in logical sequence

• Index may be stored and accessed with Indexed Sequential Access Method

• Index has an entry for every data base record. These are in ascending order. The index keys are in logical sequence. Database records are not necessarily in ascending sequence.

• Access method may be used for storage and retrieval

IS 257 – Fall 2009 2009-09-15 SLIDE 54

Indexed Random

AddressBlockNumber

2

1

3

2

1

ActualValue

Adams

Becker

Dumpling

Getta

Harty

BeckerHarty

AdamsGetta

Dumpling

IS 257 – Fall 2009 2009-09-15 SLIDE 55

Btree

F | | P | | Z |

R | | S | | Z |H | | L | | P |B | | D | | F |

Devils

AcesBoilersCars

MinorsPanthers

Seminoles

Flyers

HawkeyesHoosiers

IS 257 – Fall 2009 2009-09-15 SLIDE 56

Inverted

• Key values of the physical records are not necessarily in logical sequence

• Access Method is better used for retrieval

• An index for every field to be inverted may be built

• Access efficiency depends on number of database records, levels of index, and storage allocated for index

IS 257 – Fall 2009 2009-09-15 SLIDE 57

Inverted

AddressBlockNumber

1

2

3

…

ActualValue

CH 145

CS 201

CS 623

PH 345

CH 145101, 103,104

CS 201102

CS 623

105, 106

Adams

Becker

Dumpling

Getta

Harty

Mobile

Studentname

CourseNumber

CH145

cs201

ch145

ch145

cs623

cs623

IS 257 – Fall 2009 2009-09-15 SLIDE 58

Direct

• Key values of the physical records are not necessarily in logical sequence

• There is a one-to-one correspondence between a record key and the physical address of the record

• May be used for storage and retrieval• Access efficiency always 1• Storage efficiency depends on density of

keys• No duplicate keys permitted

IS 257 – Fall 2009 2009-09-15 SLIDE 59

Hashing

• Key values of the physical records are not necessarily in logical sequence

• Many key values may share the same physical address (block)

• May be used for storage and retrieval• Access efficiency depends on distribution of

keys, algorithm for key transformation and space allocated

• Storage efficiency depends on distibution of keys and algorithm used for key transformation

IS 257 – Fall 2009 2009-09-15 SLIDE 60

Comparative Access Methods

IndexedNo wasted space for databut extra space for index

Moderately Fast

Moderately FastVery fast with multiple indexesOK if dynamic OK if dynamic

Easy but requiresMaintenance ofindexes

FactorStorage spaceSequential retrieval on primary keyRandom Retr.Multiple Key Retr.Deleting records

Adding records

Updating records

SequentialNo wasted space

Very fast

ImpracticalPossible but needsa full scancan create wasted spacerequires rewriting fileusually requires rewriting file

Hashedmore space needed foraddition and deletion ofrecords after initial load

Impractical

Very fast

Not possiblevery easy

very easy

very easy

IS 257 – Fall 2009 2009-09-15 SLIDE 61

Database Creation in Access

• Simplest to use a design view– wizards are available, but less flexible

• Need to watch the default values

• Helps to know what the primary key is, or if one is to be created automatically– Automatic creation is more complex in other

RDBMS and ORDBMS

• Need to make decision about the physical storage of the data

IS 257 – Fall 2009 2009-09-15 SLIDE 62

Database Creation in Access

• Some Simple Examples

IS 257 – Fall 2009 2009-09-15 SLIDE 63

Next Time

• Indexes and when to index

• Integrity Constraints

• Referential Integrity