9/25/2001sims 257: database management physical database design university of california, berkeley...

9/25/2001 SIMS 257: Database Management

Physical Database Design

University of California, Berkeley

School of Information Management and Systems

SIMS 257: Database Management


Review

• Database Design Process

• Normalization


Database Design Process

ConceptualModel

LogicalModel

External Model

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


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.


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)


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


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


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


First Normal FormPatient # 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


Second Normal FormPatient # Patient Name Patient Address

1111 John White15 New St. New York, NY

1234 Mary Jones10 Main St. Rye, NY

2345Charles Brown


4876 Hal Kane55 Boston Post Road, Chester,

5123 Paul KosherBlind Brook Mamaroneck, NY

6845 Ann HoodHilton Road Larchmont, NY


Second Normal FormSurgeon # Surgeon Name

145 Beth Little

189 David Rosen

243 Charles Field

311 Michael Diamond

467 Patricia Gold


Second Normal FormPatient # 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


Third Normal FormPatient # 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


Third Normal Form

Drug Admin Side Effects

Cephalosporin none

Demicillin none

none none

Penicillin rash

Tetracycline Fever


Most 3NF Relations are also BCNF

Patient # Patient Name Patient Address

1111 John White15 New St. New York, NY

1234 Mary Jones10 Main St. Rye, NY

2345Charles Brown


4876 Hal Kane55 Boston Post Road, Chester,

5123 Paul KosherBlind Brook Mamaroneck, NY

6845 Ann HoodHilton Road Larchmont, NY


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


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.


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.


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.


Downward DenormalizationCustomer

ID

Address

Name

Telephone

Customer

ID

Address

Name

Telephone

Order

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Order

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Cust Name

Before: After:


Upward DenormalizationOrder

Order No

Date Taken

Date Dispatched

Date Invoiced

Cust ID

Cust Name

Order

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 Item

Order No

Item No

Item Price

Num Ordered


Today

• Physical Database Design

• Access Methods

• Indexes

Based on McFadden Modern Database Management and Atre Database:Structured Techniques for Design,Performance and Management


Database Design Process

ConceptualModel

LogicalModel

External Model





Application 1

Application 1

Application 2 Application 3 Application 4

Application 2

Application 3

Application 4

External Model

External Model

External Model

Internal Model

Physical 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



• 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


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


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


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


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 eliminated illegal values) for the associated attribute and can support the required data manipulations (e.g. numerical or string operations)


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)


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


Controlling Data Integrity

• Default values

• Range control

• Null value control

• Referential integrity

• Handling missing data


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


Designing Physical Files/Internal Model

• Overview

• terminology

• Access methods


Physical Design• Internal Model/Physical Model

OperatingSystem

Access Methods

DataBase

User request

DBMSInternal ModelAccess Methods

External Model

Interface 1

Interface 3

Interface 2


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.


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


Internal Model Access Methods• Many types of access methods:

– Physical Sequential

– Indexed Sequential

– Indexed Random

– Inverted

– Direct

– Hashed

• Differences in – Access Efficiency

– Storage Efficiency


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)


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


Index SequentialData File

Block 1

Block 2

Block 3

AddressBlockNumber

1

2

3

…

ActualValue

Dumpling

Harty

Texaci

...

AdamsBecker

Dumpling

GettaHarty

MobileSunociTexaci


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


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


Indexed Random

AddressBlockNumber

2

1

3

2

1

ActualValue

Adams

Becker

Dumpling

Getta

Harty

BeckerHarty

AdamsGetta

Dumpling


Btree

F | | P | | Z |

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

Devils

AcesBoilers

Cars

MinorsPanthers

SeminolesFlyers

HawkeyesHoosiers


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


Inverted

CH145

cs201

ch145

ch145

cs623

cs623

AddressBlockNumber

1

2

3

…

ActualValue

CH 145

CS 201

CS 623

PH 345

CH 145101, 103,104

CS 201102

CS 623105, 106

Adams

Becker

Dumpling

Getta

Harty

Mobile

Studentname

CourseNumber


Direct


• 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


Hashing


• 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


Comparative Access MethodsFactorStorage 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

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

Hashedmore space needed foraddition and deletion ofrecords after initial load

Impractical

Very fast

Not possiblevery easy

very easy

very easy

9/25/2001sims 257: database management physical database design university of california, berkeley...

Documents