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9/26/2000 SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257: Database Management

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Page 1: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

9/26/2000 SIMS 257: Database Management

Physical Database Design

University of California, Berkeley

School of Information Management and Systems

SIMS 257: Database Management

Page 2: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Review

• Normalization

• Denormalization

Page 3: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 4: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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.

Page 5: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Today

• Physical Database Design

• Access Methods

• Indexes

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

Page 6: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Physical Design

Page 7: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 8: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 9: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

9/26/2000 SIMS 257: Database Management

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

Page 10: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 11: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 12: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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)

Page 13: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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)

Page 14: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

9/26/2000 SIMS 257: Database Management

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

Page 15: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Controlling Data Integrity

• Default values

• Range control

• Null value control

• Referential integrity

• Handling missing data

Page 16: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 17: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Designing Physical Files/Internal Model

• Overview

• terminology

• Access methods

Page 18: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Physical Design• Internal Model/Physical Model

OperatingSystem

Access Methods

DataBase

User request

DBMSInternal ModelAccess Methods

External Model

Interface 1

Interface 3

Interface 2

Page 19: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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.

Page 20: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 21: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Internal Model Access Methods• Many types of access methods:

– Physical Sequential

– Indexed Sequential

– Indexed Random

– Inverted

– Direct

– Hashed

• Differences in – Access Efficiency

– Storage Efficiency

Page 22: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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)

Page 23: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 24: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Index SequentialData File

Block 1

Block 2

Block 3

AddressBlockNumber

1

2

3

ActualValue

Dumpling

Harty

Texaci

...

AdamsBecker

Dumpling

GettaHarty

MobileSunociTexaci

Page 25: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 26: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 27: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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Indexed Random

AddressBlockNumber

2

1

3

2

1

ActualValue

Adams

Becker

Dumpling

Getta

Harty

BeckerHarty

AdamsGetta

Dumpling

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Btree

F | | P | | Z |

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

Devils

AcesBoilers

Cars

MinorsPanthers

SeminolesFlyers

HawkeyesHoosiers

Page 29: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 30: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 31: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 32: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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

Page 33: 9/26/2000SIMS 257: Database Management Physical Database Design University of California, Berkeley School of Information Management and Systems SIMS 257:

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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