Database Administration: The Complete Guide to

Database Administration: The Complete Guide to
Accolades for Database Administration
“I’ve forgotten how many times I’ve recommended this book to people. It’s
well written, to the point, and covers the topics that you need to know to
become an effective DBA.”
—Scott Ambler, Thought Leader, Agile Data Method
“This is a well-written, well-organized guide to the practice of database
administration. Unlike other books on general database theory or relational
database theory, this book focuses more directly on the theory and reality
of database administration as practiced by database professionals today, and
does so without catering too much to any specific product implementation.
As such, Database Administration is very well suited to anyone interested
in surveying the job of a DBA or those in similar but more specific roles
such as data modeler or database performance analyst.”
—Sal Ricciardi, Program Manager, Microsoft
“One of Craig’s hallmarks is his ability to write in a clear, easy-to-read fashion. The main purpose of any technical book is to transfer information from
writer to reader, and Craig has done an excellent job. He wants the reader
to learn—and it shows.”
—Chris Foot, Manager, Remote DBA Experts and Oracle ACE
“A complete and comprehensive listing of tasks and responsibilities for
DBAs, ranging from creating the database environment to data warehouse
administration, and everything in between.”
—Mike Tarrani, Computer Consultant
“I think every business manager and every IT manager should have a copy
of this book.”
—Dan Hotka, Independent Consultant and Oracle ACE
“This book by Craig Mullins is wonderfully insightful and truly important.
Mullins describes the role and duties of data administrators and database
administrators in modern organizations with remarkable insight and clarity.”
—Michael Tozer, Author and former U.S. Navy officer
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Database
Administration
Second Edition
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Database
Administration
The Complete Guide to DBA Practices
and Procedures
Second Edition
Craig S. Mullins
Upper Saddle River, NJ • Boston • Indianapolis • San Francisco
New York • Toronto • Montreal • London • Munich • Paris • Madrid
Capetown • Sydney • Tokyo • Singapore • Mexico City
Many of the designations used by manufacturers and sellers to distinguish their
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The author and publisher have taken care in the preparation of this book, but
make no expressed or implied warranty of any kind and assume no responsibility for errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of the use of the information or
programs contained herein.
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Editor-in-Chief
Mark Taub
Acquisitions Editor
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Development Editor
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Managing Editor
John Fuller
Production Editor
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Copy Editor
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Indexer
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Visit us on the Web: informit.com/aw
Technical Reviewers
Library of Congress Cataloging-in-Publication Data
William Arledge
Kevin Kline
Database administration : the complete guide to DBA practices and procedures /
Craig S. Mullins.—2 [edition].
pages cm
Includes bibliographical references and index.
ISBN 978-0-321-82294-9 (alk. paper)—ISBN 0-321-82294-3 (alk. paper)
1. Database management. I. Title.
QA76.9.D3M838 2013
005.74—dc23
2012029466
Copyright © 2013 Craig S. Mullins
All rights reserved. Printed in the United States of America. This publication is
protected by copyright, and permission must be obtained from the publisher
prior to any prohibited reproduction, storage in a retrieval system, or transmission in any form or by any means, electronic, mechanical, photocopying,
recording, or likewise. To obtain permission to use material from this work,
please submit a written request to Pearson Education, Inc., Permissions Department, One Lake Street, Upper Saddle River, New Jersey 07458, or you may fax
your request to (201) 236-3290.
ISBN-13: 978-0-321-82294-9
ISBN-10:
0-321-82294-3
Text printed in the United States on recycled paper at Edwards Brothers Malloy
in Ann Arbor, Michigan.
First printing October, 2012
Editorial Assistant
Michelle Housley
Cover Designer
Chuti Prasertsith
Compositor
Rob Mauhar
The CIP Group
To my wife, Beth, for her unending love,
constant support, and beautiful smile.
This page intentionally left blank
Contents
Preface
xxxi
How to Use This Book
xxxiii
Acknowledgments
xxxv
About the Author
xxxvii
Chapter 1 What Is a DBA?
1
Why Learn Database Administration?
3
A Unique Vantage Point
4
DBA Salaries
4
Database Technology
6
The Management Discipline of Database Administration
A Day in the Life of a DBA
12
Evaluating a DBA Job Offer
14
9
ix
x
Contents
Database, Data, and System Administration
15
Data Administration
15
Database Administration
19
System Administration
20
DBA Tasks
20
Database Design
21
Performance Monitoring and Tuning
22
Ensuring Availability
24
Database Security and Authorization
24
Governance and Regulatory Compliance
26
Backup and Recovery
26
Ensuring Data Integrity
27
DBMS Release Migration
29
Jack-of-All-Trades
29
The Types of DBAs
31
System DBA
31
Database Architect
32
Database Analyst
33
Data Modeler
33
Application DBA
34
Task-Oriented DBA
36
Performance Analyst
36
Data Warehouse Administrator
36
Staffing Considerations
37
How Many DBAs?
37
DBA Reporting Structures
40
Multiplatform DBA Issues
42
Production versus Test
44
The Impact of Newer Technology on DBA
46
Procedural DBAs: Managing Database Logic
46
xi
Contents
The Internet: From DBA to eDBA
50
The Personal DBA and the Cloud
53
NoSQL, Big Data, and the DBA
55
New Technology Impacts on DBA
56
DBA Certification
56
The Rest of the Book
58
Review
58
Bonus Question
59
Chapter 2 Creating the Database Environment
61
Defining the Organization’s DBMS Strategy
61
Choosing a DBMS
63
DBMS Architectures
68
DBMS Clustering
71
DBMS Proliferation
73
Hardware Issues
73
Cloud Database Systems
74
Installing the DBMS
75
DBMS Installation Basics
75
Hardware Requirements
76
Storage Requirements
76
Memory Requirements
78
Configuring the DBMS
80
Connecting the DBMS to Supporting Infrastructure Software
Installation Verification
81
DBMS Environments
82
Upgrading DBMS Versions and Releases
82
Features and Complexity
87
Complexity of the DBMS Environment
87
Reputation of the DBMS Vendor
89
Support Policies of the DBMS
89
81
xii
Contents
Organization Style
89
DBA Staff Skill Set
90
Platform Support
90
Supporting Software
91
Fallback Planning
92
Migration Verification
92
The DBMS Upgrade Strategy
92
Database Standards and Procedures
92
Database Naming Conventions
93
Other Database Standards and Procedures
DBMS Education
103
Summary
104
Review
104
Bonus Question
105
Suggested Reading
105
96
Chapter 3 Data Modeling and Normalization
107
Data Modeling Concepts
108
Entity-Relationship Diagramming
110
The Components of a Data Model
113
Entities
113
Attributes
115
Keys
120
Relationships
122
Discovering Entities, Attributes, and Relationships
124
Conceptual, Logical, and Physical Data Models
125
What Is Normalization?
128
The Normal Forms
128
First Normal Form
129
Second Normal Form
129
Third Normal Form
132
Contents
A Normalized Data Model
133
Further Normal Forms
134
Normalization in Practice
135
Additional Data Modeling Issues
135
Summary
136
Review
137
Bonus Question
138
Suggested Reading
138
Chapter 4 Database Design
141
From Logical Model to Physical Database
141
Transform Entities to Tables
142
Transform Attributes to Columns
142
Build Referential Constraints for All Relationships
Build Physical Data Structures
147
Database Performance Design
150
Designing Indexes
150
Hashing
158
Clustering
159
Interleaving Data
160
Denormalization
160
When to Denormalize
161
Prejoined Tables
164
Report Tables
164
Mirror Tables
165
Split Tables
165
Combined Tables
168
Redundant Data
168
Repeating Groups
169
Derivable Data
170
Hierarchies
171
146
xiii
xiv
Contents
Special Physical Implementation Needs
Denormalization Summary
173
Views
175
Data Definition Language
177
Temporal Data Support
177
A Temporal Example
178
Business Time and System Time
179
Summary
180
Review
181
Bonus Question
181
Suggested Reading
182
173
Chapter 5 Application Design
185
Database Application Development and SQL
186
SQL
186
Set-at-a-Time Processing and Relational Closure
Embedding SQL in a Program
191
SQL Middleware and APIs
192
Application Infrastructure
193
Object Orientation and SQL
199
Types of SQL
200
SQL Coding for Performance
202
Querying XML Data
203
Defining Transactions
205
Transaction Guidelines
207
Unit of Work
207
Transaction Processing Systems
207
Application Servers
209
Locking
210
Types of Locks
212
Lock Time-outs
213
189
xv
Contents
Deadlocks
214
Lock Duration
215
Lock Escalation
219
Programming Techniques to Minimize Locking Problems
Locking Summary
220
Batch Processing
221
Summary
222
Review
222
Bonus Question
223
Suggested Reading
223
Chapter 6 Design Reviews
227
What Is a Design Review?
227
Rules of Engagement
228
Design Review Participants
229
Knowledge and Skills Required
232
Types of Design Reviews
232
Conceptual Design Review
233
Logical Design Review
235
Physical Design Review
236
Organizational Design Review
237
SQL and Application Code Design Review
238
Pre-Implementation Design Review
239
Post-Implementation Design Review
239
Design Review Output
239
Additional Considerations
240
Dealing with Remote Staff
240
Mentorship and Knowledge Transfer
240
Summary
241
Review
241
Suggested Reading
242
220
xvi
Contents
Chapter 7 Database Change Management
243
Change Management Requirements
244
The Change Management Perspective of the DBA
246
Types of Changes
247
DBMS Software
248
Hardware Configuration
248
Logical and Physical Design
248
Applications
249
Physical Database Structures
250
Impact of Change on Database Structures
250
The Limitations of ALTER
252
Database Change Scenarios
254
Comparing Database Structures
257
Requesting Database Changes
258
Standardized Change Requests
259
Communication
260
Coordinating Database and Application Changes
260
Compliance
261
DBA Scripts and Change Management
262
Summary
262
Review
263
Suggested Reading
263
Chapter 8 Data Availability
265
Defining Availability
267
Increased Availability Requirements
Cost of Downtime
271
How Much Availability Is Enough?
Availability Problems
274
Loss of the Data Center
274
Network Problems
275
268
273
Contents
Loss of the Server Hardware
276
Disk-Related Outages
278
Operating System Failure
279
DBMS Software Failure
279
Application Problems
279
Security and Authorization Problems
280
Corruption of Data
280
Loss of Database Objects
281
Loss of Data
282
Data Replication and Propagation Failures
283
Severe Performance Problems
283
Recovery Issues
284
DBA Mistakes
284
Outages: Planned and Unplanned
286
Ensuring Availability
287
Perform Routine Maintenance While Systems Remain
Operational
288
Automate DBA Functions
290
Exploit High-Availability Features
291
Exploit Clustering Technology
292
Database Architecture and NoSQL
296
Summary
296
Review
297
Suggested Reading
298
Chapter 9 Performance Management
299
Defining Performance
299
A Basic Database Performance Road Map
302
Monitoring versus Management
304
Reactive versus Proactive
306
xvii
xviii
Contents
Preproduction Performance Estimation
Historical Trending
308
Service-Level Management
308
Types of Performance Tuning
311
System Tuning
311
Database Tuning
312
Application Tuning
312
Performance Tuning Tools
313
DBMS Performance Basics
315
Summary
316
Review
316
Bonus Question
317
Suggested Reading
317
307
Chapter 10 System Performance
319
The Larger Environment
320
Interaction with the Operating System
320
Allied Agents
321
Hardware Configuration
322
Components of the DBMS
324
DBMS Installation and Configuration Issues
327
Types of Configuration
327
Memory Usage
328
Data Cache Details
332
“Open” Database Objects
336
Database Logs
336
Locking and Contention
341
The System Catalog
342
Other Configuration Options
343
General Advice
344
System Monitoring
345
Contents
Summary
346
Review
346
Bonus Question
Suggested Reading
347
347
Chapter 11 Database Performance
349
Techniques for Optimizing Databases
349
Partitioning
350
Raw Partition versus File System
351
Indexing
352
Denormalization
355
Clustering
356
Interleaving Data
360
Free Space
360
Compression
361
File Placement and Allocation
362
Page Size (Block Size)
364
Database Reorganization
365
Determining When to Reorganize
369
Automation
371
Summary
371
Review
371
Suggested Reading
372
Chapter 12 Application Performance
Designing Applications for Relational Access
Relational Optimization
374
CPU and I/O Costs
376
Database Statistics
376
Query Analysis
378
Joins
379
Access Path Choices
381
373
373
xix
xx
Contents
Additional Optimization Considerations
391
View Access
391
Query Rewrite
392
Rule-Based Optimization
393
Reviewing Access Paths
394
Forcing Access Paths
398
SQL Coding and Tuning for Efficiency
399
A Dozen SQL Rules of Thumb
400
Additional SQL Tuning Tips
406
Identifying Poorly Performing SQL
406
Summary
407
Review
407
Suggested Reading
408
Chapter 13 Data Integrity
409
Types of Integrity
409
Database Structure Integrity
410
Types of Structural Problems
410
Managing Structural Problems
411
Semantic Data Integrity
414
Entity Integrity
416
Unique Constraints
417
Data Types
417
Default Values
419
Check Constraints
419
Triggers
426
Referential Integrity
433
Temporal Database Systems
444
Summary
446
Review
447
Suggested Reading
448
Contents
Chapter 14 Database Security
449
Data Breaches
449
Database Security Basics
451
Database Users
455
Granting and Revoking Authority
456
Types of Privileges
457
Granting to PUBLIC
460
Revoking Privileges
461
Label-Based Access Control
463
Security Reporting
465
Authorization Roles and Groups
466
Roles
466
Groups
467
Other Database Security Mechanisms
468
Using Views for Security
468
Using Stored Procedures for Security
470
Encryption
470
Data at Rest Encryption
472
Data in Transit Encryption
472
Encryption Techniques
472
SQL Injection
473
SQL Injection Prevention
475
Auditing
477
External Security
478
Job Scheduling and Security
479
Non-DBMS DBA Security
480
DBMS Fixpacks and Maintenance
480
Summary
481
Review
481
Suggested Reading
482
xxi
xxii
Contents
Chapter 15
Regulatory Compliance and Database
Administration
483
A Collaborative Approach to Compliance
486
Why Should DBAs Care about Compliance?
487
Metadata Management, Data Quality, and Data Governance
Metadata
488
Data Quality
489
Data Governance
489
Database Auditing and Data Access Tracking
490
Database Auditing Techniques
493
Privileged User Auditing
495
Data Masking and Obfuscation
496
Data Masking Techniques
497
Database Archiving for Long-Term Data Retention
498
The Life Cycle of Data
499
Database Archiving
500
Components of a Database Archiving Solution
505
The Impact of e-Discovery on DBA
506
Closer Tracking of Traditional DBA Tasks
507
Database Change Management
508
Database Backup and Recovery
508
Summary
511
Review
511
Suggested Reading
512
Chapter 16 Database Backup and Recovery
The Importance of Backup and Recovery
515
Preparing for Problems
516
Backup
517
Full versus Incremental Backups
521
Database Objects and Backups
523
515
488
Contents
DBMS Control
524
Concurrent Access Issues
525
Backup Consistency
527
Log Archiving and Backup
529
Determining Your Backup Schedule
531
DBMS Instance Backup
533
Designing the DBMS Environment for Recovery
533
Alternate Approaches to Database Backup
534
Document Your Backup Strategy
536
Database Object Definition Backups
536
Recovery
537
Determining Recovery Options
538
General Steps for Database Object Recovery
540
Types of Recovery
541
Index Recovery
550
Testing Your Recovery Plan
551
Recovering a Dropped Database Object
552
Recovering Broken Blocks and Pages
553
Populating Test Databases
553
Alternatives to Backup and Recovery
554
Standby Databases
554
Replication
555
Disk Mirroring
556
Summary
557
Review
557
Suggested Reading
558
Chapter 17 Disaster Planning
The Need for Planning
559
Risk and Recovery
561
559
xxiii
xxiv
Contents
General Disaster Recovery Guidelines
563
The Remote Site
564
The Written Plan
564
Personnel
569
Backing Up the Database for Disaster Recovery
569
Tape Backups
570
Storage Management Backups
572
Other Approaches
573
Some Guidelines
573
Disaster Prevention
575
Disaster and Contingency Planning Web Sites
576
Summary
576
Review
576
Suggested Reading
577
Chapter 18 Data and Storage Management
Storage Management Basics
579
Files and Data Sets
583
File Placement on Disk
584
Raw Partitions versus File Systems
586
Temporary Database Files
587
Space Management
587
Data Page Layouts
588
Index Page Layouts
592
Transaction Logs
594
Fragmentation and Storage
595
Storage Options
596
RAID
597
JBOD
604
Storage Area Networks
604
579
Contents
Network-Attached Storage
Tiered Storage
606
Planning for the Future
608
Capacity Planning
608
Summary
609
Review
609
Suggested Reading
610
605
Chapter 19 Data Movement and Distribution
Loading and Unloading Data
614
The LOAD Utility
614
The UNLOAD Utility
618
Maintaining Application Test Beds
621
EXPORT and IMPORT
622
Bulk Data Movement
623
ETL Software
623
Replication and Propagation
623
Messaging Software
624
Other Methods
625
Distributed Databases
626
Setting Up a Distributed Environment
627
Data Distribution Standards
629
Accessing Distributed Data
630
Two-Phase COMMIT
631
Distributed Performance Problems
632
Summary
633
Review
634
Bonus Question
634
Suggested Reading
635
613
xxv
xxvi
Contents
Chapter 20 Data Warehouse Administration
637
What Is a Data Warehouse?
637
Analytical versus Transaction Processing
638
Administering the Data Warehouse
640
Too Much Focus on Technology?
641
Data Warehouse Design
641
Data Movement
644
Data Cleansing
645
Data Warehouse Scalability
649
Data Warehouse Performance
650
Data Freshness
654
Data Content
654
Data Usage
655
Financial Chargeback
655
Backup and Recovery
656
Don’t Operate in a Vacuum!
657
Summary
658
Review
658
Suggested Reading
659
Chapter 21 Database Connectivity
Multitier, Distributed Computing
661
A Historical Look
661
Business Issues
663
What Is Client/Server Computing?
Types of Client/Server Applications
Network Traffic
670
Database Gateways
671
Database Drivers
672
Connection Pooling
674
661
663
667
Contents
xxvii
Databases, the Internet, and the Web
675
Internet-Connected Databases
676
Web Development and Web Services
680
Summary
681
Review
682
Suggested Reading
682
Chapter 22 Metadata Management
685
What Is Metadata?
685
From Data to Knowledge and Beyond
686
Metadata Strategy
687
Data Warehousing and Metadata
688
Types of Metadata
689
Repositories and Data Dictionaries
691
Repository Benefits
693
Repository Challenges
693
Data Dictionaries
695
Summary
696
Review
696
Suggested Reading
697
Chapter 23 DBA Tools
699
Types and Benefits of DBA Tools
699
Data Modeling and Design
700
Database Change Management
701
Table Editors
707
Performance Management
708
Backup and Recovery
714
Database Utilities
715
Data Protection, Governance, Risk, and Compliance Tools
716
Data Warehousing, Analytics, and Business Intelligence
721
xxviii
Contents
Programming and Development Tools
Miscellaneous Tools
726
Examine Native DBA Tools
728
Evaluating DBA Tool Vendors
729
Homegrown DBA Tools
732
Summary
733
Review
733
724
Chapter 24 DBA Rules of Thumb
735
Write Down Everything
735
Keep Everything
736
Automate!
737
Share Your Knowledge
739
Analyze, Simplify, and Focus
741
Don’t Panic!
742
Measure Twice, Cut Once
743
Understand the Business, Not Just the Technology
Don’t Become a Hermit
745
Use All of the Resources at Your Disposal
745
Keep Up-to-Date
746
Invest in Yourself
747
Summary
748
Final Exam
748
Appendix A Database Fundamentals
What Is a Database?
753
Why Use a DBMS?
754
Advantages of Using a DBMS
755
Summary
759
753
743
Contents
Appendix B The DBMS Vendors
761
The Big Three
762
The Second Tier
763
Other Significant Players
763
Open-Source DBMS Offerings
764
Nonrelational DBMS Vendors
765
NoSQL DBMS Vendors
765
Object-Oriented DBMS Vendors
766
PC-Based DBMS Vendors
766
Appendix C DBA Tool Vendors
769
The Major Vendors
769
Other DBA Tool Vendors
770
Data Modeling Tool Vendors
771
Repository Vendors
772
Data Movement and Business Intelligence Vendors
Appendix D DBA Web Resources
Usenet Newsgroups
775
Mailing Lists
776
Web Sites, Blogs, and Portals
778
Vendor Web Sites
778
Magazine Web Sites
778
Consultant Web Sites
779
Blogs
780
Database Portals
781
Other Web Sites
782
775
Appendix E Sample DBA Job Posting
Job Posting
785
Database Administrator (DBA)
785
785
773
xxix
xxx
Contents
Bibliography
793
Database Management and Database Systems
793
Data Administration, Data Modeling, and Database Design
Database Security, Protection, and Compliance
802
Data Warehousing
804
SQL
805
Object Orientation and Database Management
807
Operating Systems
807
Related Topics
808
DB2
812
IMS
813
MySQL
813
Oracle
814
SQL Server
815
Sybase
816
Other Database Systems
817
Glossary
Index
819
853
799
Preface
The need for database administration is as strong as, or stronger than, it was
when I originally wrote the first edition of this book in 2002. Relational
database management systems are still at the core of most serious production systems, and they still need to be managed. And this is still the job of
database administrators. Whether you use Oracle, Microsoft SQL Server,
DB2, Informix, Sybase, MySQL, Teradata, PostgreSQL, Ingres, or any combination of these popular DBMS products, you will benefit from the information in this book.
But a decade is forever in the world of information technology. And
even though some basic things stay the same (e.g., databases require
administration), many things change. The second edition of this book
incorporates the many changes that impact database administration that
have occurred in the industry over the past decade. What made the book
unique remains. It is still the industry’s only non-product-based description
of database administration techniques and practices. The book defines the
job of database administrator and outlines what is required of a database
xxxi
xxxii
Preface
administrator, or DBA, in clear, easy-to-understand language. The book can
be used
• As a text for learning the discipline of database administration
• As the basis for setting up a DBA group
• To augment a DBMS-specific manual or textbook
• To help explain to upper-level management what a DBA is, and why
the position is required
But what is new? One of the significant improvements added to this
edition is coverage of regulatory compliance. The number of governmental
and industry regulations has exploded over the course of the past decade,
and many of these regulations dictate changes in the way that data is
managed, handled, and processed. Although the most visible governmental regulation is undoubtedly the Sarbanes-Oxley Act (aka the U.S. Public
Company Accounting Reform and Investor Protection Act of 2002), there
are many others, including HIPAA (the Health Insurance Portability and
Accountability Act) and GLB (the Gramm-Leach-Bliley Act) to name a couple. The most visible industry regulation is PCI DSS (Payment Card Industry
Data Security Standard). All of these regulations, and many others, impose
an additional administrative burden on data. This edition of the book provides an entire chapter devoted to this topic, including the impact of regulatory compliance on data management tasks such as metadata management,
data quality, database auditing, data masking, database archiving, and more
traditional DBA tasks such as database change management and database
recovery.
Database security is another rapidly evolving area that required a significant upgrade from the first edition. Fresh coverage is offered on new security functionality and requirements, including label-based access control,
encryption, and preventing SQL injection attacks.
The book adds coverage of technology that was not widely adopted
ten years ago, such as XML, and where appropriate it discusses nascent
technology that DBAs should be aware of, including NoSQL and cloud computing. It also covers newer DBMS functionality, such as temporal database
support and INSTEAD-OF triggers.
How to Use This Book
xxxiii
Finally, the entire book was reviewed and revised to ensure that each
topic addressed up-to-date technology and requirements. Care was taken to
ensure that the example DBMS features used to highlight specific technologies are accurate and up-to-date. For example, consider the descriptions
of DB2 HADR, SQL Server 2012 AlwaysOn, and Oracle Transparent Data
Encryption.
With the second edition of this book you now have a timely, accurate,
and updated guide to implementing and maintaining heterogeneous database administration. You can use it to learn what is required to be a successful database administrator. And you can use it on the job in conjunction
with the vendors’ manuals or product-specific books for your particular
DBMS products.
How to Use This Book
This book can be used as both a tutorial and a reference. The book is organized to proceed chronologically through DBA tasks that are likely to be
encountered. Therefore, if you read the book sequentially from Chapter 1
through Chapter 24, you will get a comprehensive sequential overview
of the DBA job. Alternatively, you can read any chapter independently
because each chapter deals with a single topic. References to other chapters are clearly made if other material in the book would aid the reader’s
understanding.
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Acknowledgments
Writing is a rewarding task, but it also requires a lot of time—researching,
writing, reviewing, editing, and rewriting over and over again until you get
it just right. But no one can write a technical book in a vacuum. I had many
knowledgeable and helpful people to assist me along the way.
First of all, I’d like to thank the many industry experts who reviewed
the original book proposal. The following folks provided many useful suggestions and thoughts on my original outline that helped me to create a
much better book: Michael Blaha, Keith W. Hare, Michael J. Hernandez,
Robert S. Seiner, and David L. Wells. Additionally, I’d like to thank everyone
who took the time to listen to my ideas for this book before I began writing.
This list of folks is too numerous to include, and I’m sure I’d miss someone—but you know who you are.
I would like to thank the many folks who have reviewed and commented on the text of this book. For the second edition of the book, Bill
Arledge and Kevin Kline provided their expertise to the review process
and offered many helpful corrections and suggestions that improved the
quality of the book. And let’s not forget the reviewers of the first edition:
Dan Hotka, Chris Foot, Chuck Kosin, David L. Wells, and Anne Marie Smith
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Acknowledgments
pored over each chapter of various incarnations of the manuscript, and this
book is much better thanks to their expert contributions. Special thanks go
to data modeling and administration gurus William J. Lewis and Robert S.
Seiner, who took extra time to review and make suggestions on Chapter 3.
I’d also like to thank my brother, Scott Mullins, who offered his guidance
on application design and development by reviewing Chapter 5.
My appreciation goes to Mary Barnard, who did a wonderful job editing
the first edition of this book; and Greg Doench, who did a similarly fantastic job with the second edition. Kudos to both Mary and Greg for making
my book much more readable.
Additionally, thanks to the many understanding and patient folks at
Addison-Wesley who worked with me to make each edition of the book
come to fruition. This list includes Michelle Housley, Patrick Peterson,
Stacie Parillo, Barbara Wood, and Mary O’Brien who were particularly helpful throughout the process of coordinating the production of the book.
Thank you, too, to my wonderful wife, Beth, whose understanding and
support made it possible for me to write this book. Indeed, thanks go out
to all my family and friends for being supportive and helpful along the way.
And finally, a thank-you to all of the people with whom I have worked
professionally at SoftwareOnZ, NEON Enterprise Software, Embarcadero
Technologies, BMC Software, Gartner Group, PLATINUM Technology, Inc.,
Duquesne Light Company, Mellon Bank, USX Corporation, and ASSET, Inc.
This book is a better one due to the many outstanding individuals with
whom I have had the honor to work.
About the Author
Craig S. Mullins is President and Principal Consultant for Mullins Consulting, Inc., a consulting practice specializing in data management and database
management systems. Craig has extensive experience in the field of database management, having worked as an application developer, a DBA, and
an instructor with multiple database management systems, including DB2,
Oracle, and SQL Server. Craig has worked in multiple industries, including
manufacturing, banking, commercial software development, education,
research, utilities, and consulting. Additionally, Craig worked as a Research
Director with Gartner Group, covering the field of database administration.
He is the author of DB2 Developer’s Guide, the industry-leading book on
DB2 for z/OS, currently in its sixth edition.
Craig is a frequent contributor to computer industry publications, having authored hundreds of articles in the past several years. His articles have
appeared in popular industry magazines and Web sites, including Database
Programming & Design, Data Management Review, DBMS, DB2 Update,
Oracle Update, SQL Server Update, and many others. Craig writes several
regular columns, including a monthly column called “The DBA Corner” for
Database Trends and Applications magazine, a quarterly column called
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About the Author
“The Database Report” for The Data Administration Newsletter (www.
tdan.com), and a regular column on DB2 and mainframe data management
called “z/Data Perspectives” for zJournal Magazine. Craig is also a regular
blogger, managing and authoring two popular data-related blogs: The DB2
Portal (http://db2portal.blogspot.com) focusing on DB2 for z/OS and mainframe “stuff,” and Data and Technology Today (http://datatechnologytoday.
wordpress.com), which focuses on data and database management issues,
DBA news and thoughts, metadata management, and data architecture, as
well as data-related topics in the realm of IT and software. Craig is also the
publisher and editor of The Database Site (www.thedatabasesite.com).
Craig regularly presents technical topics at database industry conferences and events. He has spoken to thousands of technicians about database
management and administration issues at such conferences as Database
and Client/Server World, SHARE, GUIDE, DAMA Symposium, Enterprise
Data World, IBM Information On Demand Conference, the DB2 Technical
Conference, the International DB2 Users Group (IDUG), and Oracle Open
World. He has also spoken at regional database user groups across North
America, Europe, Asia, and Australia.
Craig graduated cum laude from the University of Pittsburgh with a
double major in computer science and economics and a minor in mathematics. Craig has been appointed as an Information Management Champion
by IBM for his work in the field of DB2 database administration, development, and management.
Readers can obtain information about this book, including corrections,
future editions, and additional writings on database administration by the
author, at the author’s Web site at www.craigsmullins.com. The author can
be contacted at craig@craigsmullins.com or in care of the publisher.
2
Creating the Database Environment
One of the primary tasks associated with the job of DBA is the process of
choosing and installing a DBMS. Unfortunately, many business executives
and IT professionals without database management background assume
that once the DBMS is installed, the bulk of the work is done. The truth
is, choosing and installing the DBMS is hardly the most difficult part of a
DBA’s job. Establishing a usable database environment requires a great deal
of skill, knowledge, and consideration. This chapter will outline the principles involved in establishing a usable database environment.
Defining the Organization’s DBMS Strategy
Choosing a
suitable DBMS for
enterprise database
management is not
as difficult as it used
to be.
The process of choosing a suitable DBMS for enterprise database management is not as difficult as it used to be. The number of major DBMS vendors
has dwindled due to industry consolidation and domination of the sector
by a few very large players.
Yet, large and medium-size organizations typically run multiple DBMS
products, from as few as two to as many as ten. For example, it is not uncommon for a large company to use IMS or IDMS and DB2 on the mainframe,
61
62
The DBA group
should be empowered to make the
DBMS decisions for
the organization.
Chapter 2
Creating the Database Environment
Oracle and MySQL on several different UNIX servers, Microsoft SQL Server
on Windows servers, as well as pockets of other DBMS products such as
Sybase, Ingres, Adabas, and PostgreSQL on various platforms, not to mention single-user PC DBMS products such as Microsoft Access, Paradox, and
FileMaker. Who chose to install all these DBMSs and why?
Unfortunately, often the answer is that not much thought and planning went into the decision-making process. Sometimes the decision to
purchase and install a new DBMS is driven by a business need or a new
application. This is reasonable if your organization has no DBMS and must
purchase one for the first time. This is rarely the case, though. Regardless
of whether a DBMS exists on-site, a new DBMS is often viewed as a requirement for a new application. Sometimes a new DBMS product is purchased
and installed without first examining if the application could be successfully implemented using an existing DBMS. Or, more likely, the DBAs know
the application can be implemented using an existing DBMS but lack the
organizational power or support to reject a new DBMS proposal.
There are other reasons for the existence of multiple DBMS platforms
in a single organization. Perhaps the company purchased a commercial offthe-shelf application package that does not run on any of the current DBMS
platforms. Sometimes the decision to buy a new DBMS is driven by the
desire to support the latest and greatest technology. For example, many
mainframe shops moving from a hierarchic (IMS) or CODASYL (IDMS)
database model to the relational model deployed DB2, resulting in an additional DBMS to learn and support. Then, when client/server computing
became popular, additional DBMSs were implemented on UNIX, Linux, and
Windows servers.
Once a DBMS is installed, removal can be difficult because of incompatibilities among the different DBMSs and the necessity of converting application code. Furthermore, when a new DBMS is installed, old applications
and databases are usually not migrated to it. The old DBMS remains and
must continue to be supported. This complicates the DBA’s job.
So what should be done? Well, the DBA group should be empowered
to make the DBMS decisions for the organization. No business unit should
be allowed to purchase a DBMS without the permission of the DBA group.
This is a difficult provision to implement and even more difficult to enforce.
Business politics often work against the DBA group because it frequently
possesses less organizational power than other business executives.
Defining the Organization’s DBMS Strategy
63
Choosing a DBMS
When choosing
a DBMS, select a
product from a
tier-1 vendor.
The DBA group should set a policy regarding the DBMS products to be
supported within the organization. Whenever possible, the policy should
minimize the number of different DBMS products. For a shop with multiple
operating systems and multiple types of hardware, choose a default DBMS
for the platform. Discourage deviation from the default unless a compelling
business case exists—a business case that passes the technical inspection
of the DBA group.
Most of the major DBMS products have similar features, and if the feature or functionality does not exist today, it probably will within 18 to 24
months. So, exercise caution before deciding to choose a DBMS based solely
on its ability to support a specific feature.
When choosing a DBMS, it is wise to select a product from a tier-1 vendor as listed in Table 2.1. Tier 1 represents the largest vendors having the
most heavily implemented and supported products on the market. You cannot go wrong with DB2 or Oracle. Both are popular and support just about
any type of database. Another major player is Microsoft SQL Server, but only
for Windows platforms. DB2 and Oracle run on multiple platforms ranging
from mainframe to UNIX, as well as Windows and even handheld devices.
Choosing a DBMS other than these three should be done only under specific circumstances.
After the big three come MySQL, Sybase, Teradata, and Informix. Table 2.2
lists these tier-2 DBMS vendors. All of these offerings are quality DBMS
Table 2.1 Tier-1 DBMS Vendors
DBMS Vendor
DBMS Product
IBM Corporation
New Orchard Road
Armonk, NY 10504
Phone: (914) 499-1900
DB2
Oracle Corporation
500 Oracle Parkway
Redwood Shores, CA 94065
Phone: (650) 506-7000
Oracle
Microsoft Corporation
One Microsoft Way
Redmond, WA 98052
Phone: (425) 882-8080
SQL Server
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Table 2.2 Tier-2 DBMS Vendors
Choosing any of the
lower-tier candidates
involves incurring
additional risk.
DBMS Vendor
DBMS Product
IBM Corporation
New Orchard Road
Armonk, NY 10504
Phone: (914) 499-1900
Informix Dynamic Server
Sybase Inc. (an SAP Company)
6475 Christie Avenue
Emeryville, CA 94608
Phone: (510) 922-3500
Adaptive Server Enterprise
Teradata Corporation
10000 Innovation Drive
Dayton, OH 45342
Phone: (937) 242-4030
Teradata
MySQL (a subsidiary of Oracle Corporation)
Phone: (208) 338-8100
MySQL
products, but their installed base is smaller, their products are engineered
and marketed for niche purposes, or the companies are smaller with fewer
resources than the Big Three (IBM, Oracle, and Microsoft), so there is some
risk in choosing a DBMS from tier 2 instead of tier 1. However, there may be
solid reasons for deploying a tier-2 solution, such as the high performance
offered by Informix or the data warehousing and analytics capabilities of
Teradata.
Of course, there are other DBMS products on the market, many of
which are fine products and worthy of consideration for specialty processing, certain predefined needs, and niche roles. If your company is heavily
into the open-source software movement, PostgreSQL, EnterpriseDB, or
MySQL might be viable options. If an object DBMS is important for a specific project, you might consider ObjectDesign or Versant. And there are a
variety of NoSQL DBMS offerings available, too, such as Hadoop, Cassandra,
and MongoDB.1
However, for the bulk of your data management needs, a DBMS from a
tier-1, or perhaps tier-2, DBMS vendor will deliver sufficient functionality
with minimal risk. A myriad of DBMS products are available, each with
1. If you prefer commercial software over open source, there are commercial offerings
of some of the NoSQL products. For example, DataStax is based on Cassandra.
Defining the Organization’s DBMS Strategy
65
certain features that make them worthy of consideration on a case-by-case
basis. Choosing any of the lower-tier candidates—even such major names
as Software AG’s Adabas and Actian’s Ingres—involves incurring additional
risk. Refer to Appendix B for a list of DBMS vendors.
I do not want it to sound as if the selection of a DBMS is a no-brainer.
You will need a strategy and a plan for selecting the appropriate DBMS for
your specific situation. When choosing a DBMS, be sure to consider each
of these factors:
• Operating system support. Does the DBMS support the operating
systems in use at your organization, including the versions that you
are currently using and plan on using?
• Type of organization. Take into consideration the corporate philosophy when you choose a DBMS. Some organizations are very
conservative and like to keep a tight rein on their environments;
these organizations tend to gravitate toward traditional mainframe
environments. Government operations, financial institutions, and
insurance and health companies usually tend to be conservative.
More-liberal organizations are often willing to consider alternative
architectures. It is not uncommon for manufacturing companies,
dot-coms, and universities to be less conservative. Finally, some
companies just do not trust Windows as a mission-critical environment and prefer to use UNIX; this rules out some database vendors
(Microsoft SQL Server, in particular).
Benchmarks are
constantly updated
to show new
and improved
performance
measurements.
• Benchmarks. What performance benchmarks are available from the
DBMS vendor and other users of the DBMS? The Transaction Processing Performance Council (TPC) publishes official database performance benchmarks that can be used as a guideline for the basic
overall performance of many different types of database processing.
(Refer to the sidebar “The Transaction Processing Performance
Council” for more details.) In general, performance benchmarks can
be useful as a broad indicator of database performance but should
not be the only determinant when selecting a DBMS. Many of the
TPC benchmarks are run against database implementations that are
not representative of most production database systems and therefore are not indicative of the actual performance of a particular
DBMS. In addition, benchmarks are constantly updated to show new
66
Chapter 2
Creating the Database Environment
and improved performance measurements for each of the major
DBMS products, rendering the benchmark “winners” obsolete very
quickly.
• Scalability. Does the DBMS support the number of users and database sizes you intend to implement? How are large databases built,
supported, and maintained—easily or with a lot of pain? Are there
independent users who can confirm the DBMS vendor’s scalability
claims?
• Availability of supporting software tools. Are the supporting tools
you require available for the DBMS? These items may include query
and analysis tools, data warehousing support tools, database administration tools, backup and recovery tools, performance-monitoring
The Transaction Processing Performance
Council (TPC)
The Transaction Processing Performance Council is an independent, not-for-profit organization that manages and administers performance benchmark tests. Its mission is to define
transaction processing and database benchmarks to provide the industry with objective,
verifiable performance data. TPC benchmarks measure and evaluate computer functions
and operations.
The definition of transaction espoused by the TPC is a business one. A typical TPC transaction includes the database updates for things such as inventory control (goods), airline
reservations (services), and banking (money).
The benchmarks produced by the TPC measure performance in terms of how many
transactions a given system and database can perform per unit of time, for example, number of transactions per second. The TPC defines three benchmarks:
• TPC-C, for planned production workload in a transaction environment
• TPC-H, a decision support benchmark consisting of a suite of business-oriented ad
hoc queries and concurrent data modifications
• TPC-E, an updated OLTP workload (based on financial transaction processing)
Additional information and in-depth definitions of these benchmarks can be found at
the TPC Web site at www.tpc.org (see Figure 2.1).
Defining the Organization’s DBMS Strategy
67
tools, capacity-planning tools, database utilities, and support for
various programming languages.
• Technicians. Is there a sufficient supply of skilled database professionals for the DBMS? Consider your needs in terms of DBAs, technical support personnel (system programmers and administrators,
operations analysts, etc.), and application programmers.
• Cost of ownership. What is the total cost of ownership of the
DBMS? DBMS vendors charge wildly varying prices for their technology. Total cost of ownership should be calculated as a combination
of the license cost of the DBMS; the license cost of any required
supporting software; the cost of database professionals to program,
support, and administer the DBMS; and the cost of the computing
resources required to operate the DBMS.
Figure 2.1 The TPC Web site
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Chapter 2
Creating the Database Environment
• Release schedule. How often does the DBMS vendor release a new
version? Some vendors have rapid release cycles, with new releases
coming out every 12 to 18 months. This can be good or bad,
depending on your approach. If you want cutting-edge features, a
rapid release cycle is good. However, if your shop is more conservative, a DBMS that changes frequently can be difficult to support.
A rapid release cycle will cause conservative organizations either
to upgrade more frequently than they would like or to live with
outdated DBMS software that is unlikely to have the same level of
support as the latest releases.
• Reference customers. Will the DBMS vendor supply current user references? Can you find other users on your own who might provide
more impartial answers? Speak with current users to elicit issues
and concerns you may have overlooked. How is support? Does the
vendor respond well to problems? Do things generally work as
advertised? Are there a lot of bug fixes that must be applied continuously? What is the quality of new releases? These questions can be
answered only by the folks in the trenches.
When choosing a DBMS, be sure to take into account the complexity of
the products. DBMS software is very complex and is getting more complex
with each new release. Functionality that used to be supported only with
add-on software or independent programs is increasingly being added as
features of the DBMS, as shown in Figure 2.2. You will need to plan for and
support all the features of the DBMS. Even if there is no current requirement for certain features, once you implement the DBMS the programmers
and developers will find a reason to use just about anything the vendor
threw into it. It is better to plan and be prepared than to allow features to
be used without a plan for supporting them.
DBMS Architectures
The supporting
architecture for the
DBMS environment
is very critical to the
success of the database applications.
The supporting architecture for the DBMS environment is very critical
to the success of the database applications. One wrong choice or poorly
implemented component of the overall architecture can cause poor performance, downtime, or unstable applications.
When mainframes dominated enterprise computing, DBMS architecture was a simpler concern. Everything ran on the mainframe, and that
69
Defining the Organization’s DBMS Strategy
Unstructured
Data
OLTP and
Parallel
Query
Database
Management
System
OLAP and
Analytics
Data Extract,
Transform,
and Load
Figure 2.2
Four levels of DBMS
architecture are
available: enterprise,
departmental, personal, and mobile.
Convergence of features and functionality in DBMS software
was that. However, today the IT infrastructure is distributed and heterogeneous. The overall architecture—even for a mainframe DBMS—will probably consist of multiple platforms and interoperating system software. A
team consisting of business and IT experts, rather than a single person or
group, should make the final architecture decision. Business experts should
include representatives from various departments, as well as from accounting and legal for software contract issues. Database administration representatives (DA, DBA, and SA), as well as members of the networking group,
operating system experts, operations control personnel, programming
experts, and any other interested parties, should be included in this team.
Furthermore, be sure that the DBMS you select is appropriate for the
nature and type of processing you plan to implement. Four levels of DBMS
architecture are available: enterprise, departmental, personal, and mobile.
An enterprise DBMS is designed for scalability and high performance.
An enterprise DBMS must be capable of supporting very large databases, a
large number of concurrent users, and multiple types of applications. The
enterprise DBMS runs on a large-scale machine, typically a mainframe or a
high-end server running UNIX, Linux, or Windows Server. Furthermore, an
enterprise DBMS offers all the “bells and whistles” available from the DBMS
vendor. Multiprocessor support, support for parallel queries, and other
advanced DBMS features are core components of an enterprise DBMS.
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Chapter 2
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A departmental DBMS, sometimes referred to as a workgroup DBMS,
serves the middle ground. The departmental DBMS supports small to medium-size workgroups within an organization; typically, it runs on a UNIX,
Linux, or Windows server. The dividing line between a departmental database server and an enterprise database server is quite gray. Hardware and
software upgrades can allow a departmental DBMS to tackle tasks that
previously could be performed only by an enterprise DBMS. The steadily
falling cost of departmental hardware and software components further
contributes to lowering the total cost of operation and enabling a workgroup environment to scale up to serve the enterprise.
A personal DBMS is designed for a single user, typically on a low- to
medium-powered PC platform. Microsoft Access, SQLite, and FileMaker2
are examples of personal database software. Of course, the major DBMS
vendors also market personal versions of their higher-powered solutions,
such as Oracle Database Personal Edition and DB2 Personal Edition. Sometimes the low cost of a personal DBMS results in a misguided attempt to
choose a personal DBMS for a departmental or enterprise solution. However, do not be lured by the low cost. A personal DBMS product is suitable
only for very small-scale projects and should never be deployed for multiuser applications.
Finally, the mobile DBMS is a specialized version of a departmental
or enterprise DBMS. It is designed for remote users who are not usually
connected to the network. The mobile DBMS enables local database access
and modification on a laptop or handheld device. Furthermore, the mobile
DBMS provides a mechanism for synchronizing remote database changes to
a centralized enterprise or departmental database server.
A DBMS designed for one type of processing may be ill suited for other
uses. For example, a personal DBMS is not designed for multiple users, and
an enterprise DBMS is generally too complex for single users. Be sure to
understand the differences among enterprise, departmental, personal, and
mobile DBMS software, and choose the appropriate DBMS for your specific
data-processing needs. You may need to choose multiple DBMS types—that
is, a DBMS for each level—with usage determined by the needs of each
development project.
If your organization requires DBMS solutions at different levels, favor
the selection of a group of DBMS solutions from the same vendor whenever
2. FileMaker is offered in a professional, multiuser version, too.
71
Defining the Organization’s DBMS Strategy
possible. Doing so will minimize differences in access, development, and
administration. For example, favor Oracle Database Personal Edition for
your single-user DBMS needs if your organization uses Oracle as the enterprise DBMS of choice.
DBMS Clustering
A modern DBMS
offers clustering
support to enhance
availability and
scalability.
The main advantage of sharednothing clustering
is scalability.
Clustering is the use of multiple “independent” computing systems working together as a single, highly available system. A modern DBMS offers
clustering support to enhance availability and scalability. The two predominant architectures for clustering are shared-disk and shared-nothing.
These names do a good job of describing the nature of the architecture—at
least at a high level.
Shared-nothing clustering is depicted in Figure 2.3. In a shared-nothing
architecture, each system has its own private resources (memory, disks,
etc.). The clustered processors communicate by passing messages through
a network that interconnects the computers. In addition, requests from clients are automatically routed to the system that owns the resource. Only
one of the clustered systems can “own” and access a particular resource at a
time. In the event a failure occurs, resource ownership can be dynamically
transferred to another system in the cluster. The main advantage of sharednothing clustering is scalability. In theory, a shared-nothing multiprocessor
Interconnection
Network
1
CPU 1
CPU 2
CPU n
Memory 1
Memory 2
Memory n
2
n
Disks 1
Figure 2.3
n
1
2
Disks 2
Shared-nothing architecture
1
n
2
Disks n
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Chapter 2
Creating the Database Environment
can scale up to thousands of processors because they do not interfere with
one another—nothing is shared.
In a shared-disk environment, all the connected systems share the
same disk devices, as shown in Figure 2.4. Each processor still has its
own private memory, but all the processors can directly address all the
disks. Typically, shared-disk clustering does not scale as well for smaller
machines as shared-nothing clustering. Shared-disk clustering is better
suited to large-enterprise processing in a mainframe environment. Mainframes—very large processors—are capable of processing enormous volumes of work. Great benefits can be obtained with only a few clustered
mainframes, while many PC and midrange processors would need to be
clustered to achieve similar benefits.
Shared-disk clustering is usually preferable for applications and services
requiring only modest shared access to data and for applications or workloads that are very difficult to partition. Applications with heavy data update
requirements are probably better implemented as shared-nothing. Table 2.3
compares the capabilities of shared-disk and shared-nothing architectures.
Shared-disk clustering is better suited
to large- enterprise
processing in
a mainframe
environment.
CPU 1
CPU 2
CPU n
Memory 1
Memory 2
Memory n
Interconnection
Network
Disk 1
Figure 2.4
Table 2.3
Disk 2
Disk n
Shared-disk architecture
Comparison of Shared-Disk and Shared-Nothing Architectures
Shared-Disk
Shared-Nothing
Quick adaptability to changing workloads
Can exploit simpler, cheaper hardware
High availability
Almost unlimited scalability
Performs best in a heavy read environment
Works well in a high-volume, read-write environment
Data need not be partitioned
Data is partitioned across the cluster
Defining the Organization’s DBMS Strategy
73
The major DBMS vendors provide support for different types of clustering with different capabilities and requirements. For example, DB2 for z/OS
provides shared-disk clustering with its Data Sharing and Parallel Sysplex
capabilities; DB2 on non-mainframe platforms uses shared-nothing clustering. Oracle’s Real Application Clusters provide shared-disk clustering.
For most users, the primary benefit of clustering is the enhanced availability that accrues by combining processors. In some cases, clustering can
help an enterprise to achieve five-nines (99.999 percent) availability. Additionally, clustering can be used for load balancing and failover.
DBMS Proliferation
A proliferation of
different DBMS
products can be
difficult to support.
As a rule of thumb, create a policy (or at least some simple guidelines) that
must be followed before a new DBMS can be brought into the organization.
Failure to do so can cause a proliferation of different DBMS products that
will be difficult to support. It can also cause confusion regarding which
DBMS to use for which development effort.
As mentioned earlier, there is a plethora of DBMS vendors, each touting
its benefits. As a DBA, you will be bombarded with marketing and sales
efforts that attempt to convince you that you need another DBMS. Try to
resist unless a very compelling reason is given and a short-term return on
investment (ROI) can be demonstrated. Even when confronted with valid
reasons and good ROI, be sure to double-check the arguments and ROI
calculations. Sometimes the reasons specified are outdated and the ROI figures do not take everything into account—such as the additional cost of
administration.
Remember, every DBMS requires database administration support.
Moreover, each DBMS uses different methods to perform similar tasks. The
fewer DBMS products installed, the less complicated database administration becomes, and the better your chances become of providing effective
data management resources for your organization.
Hardware Issues
Factor hardware
platform and
operating system
constraints into the
DBMS selection
criteria.
When establishing a database environment for application development,
selecting the DBMS is only part of the equation. The hardware and operating system on which the DBMS will run will greatly impact the reliability,
availability, and scalability (RAS) of the database environment. For example,
a mainframe platform such as an IBM zEC12 running z/OS will probably
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Chapter 2
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provide higher RAS than a midrange IBM xSeries machine running AIX,
which in turn will probably exceed a Dell server running Windows. That
is not to say everything should run on a mainframe; other issues such as
cost, experience, manageability, and the needs of the applications to be
developed must be considered. The bottom line is that you must be sure to
factor hardware platform and operating system constraints into the DBMS
selection criteria.
Cloud Database Systems
Cloud computing (see the sidebar) is increasing in usage, especially at
small to medium-size businesses. A cloud implementation can be more
cost- effective than building an entire local computing infrastructure that
requires management and support.
A cloud database system delivers DBMS services over the Internet. The
trade-off essentially comes down to trusting a cloud provider to store and
manage your data in return for minimizing database administration and
maintenance cost and effort. Using cloud database systems can enable
organizations, especially smaller ones without the resources to invest in an
enterprise computing infrastructure, to focus on their business instead of
their computing environment.
By consolidating data sources in the cloud, it is possible to improve
collaboration among partners, branch offices, remote workers, and mobile
devices, because the data becomes accessible as a service. There is no need
to install, set up, patch, or manage the DBMS software because the cloud
Cloud Computing Overview
At a high level, cloud computing is the delivery of computing as a service. Cloud computing applications rely on a network (typically the Internet) to provide users with shared
resources, software, and data. With cloud computing, computer systems and applications
are supposed to function like a utility provider (such as the electricity grid).
The term cloud is used as a metaphor for the Internet. It is based on the tendency to
draw network access as an abstract “cloud” in infrastructure diagrams. An example of this
can be seen in Figure 1.11 in Chapter 1 of this book.
From a DBMS perspective, cloud computing moves the data and its management away
from your local computing environment and delivers it as a service over the Internet.
Installing the DBMS
75
provider manages and cares for these administrative tasks. Of course, the
downside is that your data is now stored and controlled by an external
agent—the cloud provider. Another inherent risk of cloud computing is the
possibility of nefarious agents posing as legitimate customers.
An example of a cloud database platform is Microsoft SQL Azure. It is
built on SQL Server technologies and is a component of the Windows Azure
platform.
Installing the DBMS
Once the DBMS has been chosen, you will need to install it. Installing a
DBMS is not as simple as popping a CD into a drive and letting the software
install itself (or, for you mainframe folks, just using IEBGENER to copy it
from a tape). A DBMS is a complex piece of software that requires up-front
planning for installation to be successful. You will need to understand the
DBMS requirements and prepare the environment for the new DBMS.
DBMS Installation Basics
Read the installation
guide from cover to
cover.
The very first thing to do when you install a DBMS for the first time is to
understand the prerequisites. Every DBMS comes with an installation manual or guide containing a list of the operating requirements that must be
met for the DBMS to function properly. Examples of prerequisites include
ensuring that an appropriate version of the operating system is being used,
verifying that there is sufficient memory to support the DBMS, and ensuring that any related software to be used with the DBMS is the proper version and maintenance level.
Once the basics are covered, read the installation guide from cover to
cover. Make sure that you understand the process before you even begin
to install the DBMS. Quite a few preparations need to be made before
installing a DBMS, and reading about them before you start will ensure a
successful installation. Review how the installation program or routine for
the DBMS operates, and follow the explicit instructions in the installation
guide provided with the DBMS software. You additionally might want to
work closely with the DBMS vendor during an initial installation to ensure
that your plans are sound. In some cases, working with a local, experienced vendor or consultant can be beneficial to avoid installation and configuration errors.
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The remainder of this section will discuss some of the common preparations that are required before a DBMS can be installed. If the DBMS is
already operational and you are planning to migrate to a new DBMS release,
refer to the section “Upgrading DBMS Versions and Releases.”
Hardware Requirements
Choose the correct
DBMS for your
needs and match
your hardware to
the requirements of
the DBMS.
Every DBMS has a basic CPU requirement, meaning a CPU version and
minimum processor speed required for the DBMS to operate. Additionally,
some DBMSs specify hardware models that are required or unsupported.
Usually the CPU criterion will suffice for an Intel environment, but in a
mainframe or enterprise server environment the machine model can make
a difference with regard to the DBMS features supported. For example, certain machines have built-in firmware that can be exploited by the DBMS if
the firmware is available.
Furthermore, each DBMS offers different “flavors” of its software for specific needs. (I use “flavor” as opposed to “version” or “release,” which specify different iterations of the same DBMS.) Different flavors of the DBMS (at
the same release level) are available for specific environments such as parallel processing, pervasive computing (such as handheld devices), data warehousing, and/or mobile computing. Be sure to choose the correct DBMS for
your needs and to match your hardware to the requirements of the DBMS.
Storage Requirements
A DBMS requires disk storage to run. And not just for the obvious reason—
to create databases that store data. A DBMS will use disk storage for the
indexes to be defined on the databases as well as for the following items:
• The system catalog or data dictionary used by the DBMS to manage
and track databases and related information. The more database
objects you plan to create, the larger the amount of storage required
by the system catalog.
• Any other system databases required by the DBMS, for example, to
support distributed connections or management tools.
• Log files that record all changes made to every database. These
include active logs, archive logs, rollback segments, and any other
type of change log required by the DBMS.
Installing the DBMS
77
• Start-up or control files that must be accessed by the DBMS when it
is started or initialized.
• Work files used by the DBMS to sort data or for other processing
needs.
• Default databases used by the DBMS for system structures or as a
default catchall for new database objects as they are created.
• Temporary database structures used by the DBMS (or by applications accessing databases) for transient data that is not required to
be persistent but needs reserved storage during operations (such as
rebuilding clustered indexes on Microsoft SQL Server).
• System dump and error-processing files.
• DBA databases used for administration, monitoring, and tuning—for
example, DBA databases used for testing new releases, migration
scripts, and so on.
Factor in every
storage requirement
of the DBMS and
reserve the appropriate storage.
Be sure to factor in every storage requirement of the DBMS and reserve
the appropriate storage. Also, be aware that the DBMS will use many of
these databases and file structures concurrently. Therefore, it is a good idea
to plan on using multiple storage devices even if you will not fill them to
capacity. Proper database and file placement will enable the DBMS to operate more efficiently because concurrent activities will not be constrained
by the physical disk as data is accessed.
Disk storage is not the only requirement of a DBMS. Tape or optical
discs (such as DVDs and CDs) are also required for tasks such as database
backups and log off-loading. When the active log file fills up, the log records
must be off-loaded to an archive log either on disk or on tape, as shown in
Figure 2.5. Depending on the DBMS being used and the features that have
been activated, this process may be automatic or manual. The archive log
files must be retained for recovery purposes, and even if originally stored
on disk, they must eventually be migrated to an external storage mechanism for safekeeping.
Plan on maintaining multiple tape or CD/DVD drives to enable the
DBMS to run concurrent multiple processes that require external storage,
such as concurrent database backups. Database outages can occur if you
single-thread your database backup jobs using a single drive.
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DBMS
Disk
Active
Log
Tape or
DVD/CD
Archive Logs
Figure 2.5
Log off-loading
Memory Requirements
Relational DBMSs, as well as their databases and applications, love memory.
A DBMS requires memory for basic functionality and will use it for most
internal processes such as maintaining the system global area and performing many DBMS tasks.
A DBMS requires a significant amount of memory to cache data in memory structures in order to avoid I/O. Reading data from a disk storage device
is always more expensive and slower than moving the data around in memory. Figure 2.6 shows how the DBMS uses a memory structure called a buffer pool or data cache to reduce physical I/O requests. By caching data that
is read into a buffer pool, the DBMS can avoid I/O for subsequent requests
for the same data, as long as it remains in the buffer pool. In general, the
larger the buffer pool, the longer the data can remain in memory and the
better overall database processing will perform.
Besides data, the DBMS will cache other structures in memory. Most
DBMSs set aside memory to store program structures required by the DBMS
Installing the DBMS
DBMS
(1) Program requests
a row of data.
(4) and to the
program.
(2) CBMS finds the
requested data
(6) DBMS finds
the data in the
buffer pool
Buffer
Pool
(3) and moves it to
the buffer pool
Database
Figure 2.6
Ensure that the
DBMS has a
more-than-adequate supply of
memory at its
disposal.
79
Program
1
(5) A subsequent request
is made for the same
row of data.
Program
2
(7) and moves it to
the program without
reading it from disk.
Buffer pool (or data cache)
to process database requests.3 The program cache stores things like “compiled” SQL statements, database authorizations, and database structure
blocks that are used by programs as they are executed. When these structures are cached, database processing can be optimized because additional
I/O requests to access them from a physical storage device are avoided.
Memory is typically required by the DBMS to support other features
such as handling lock requests, facilitating distributed data requests, sorting data, optimizing processes, and processing SQL.
Ensure that the DBMS has a more-than-adequate supply of memory at
its disposal. This will help to optimize database processing and minimize
potential problems.
3. In DB2, the area used for caching program structures in memory is referred to as the
EDM pool. In SQL Server it is called the SQL cache, and in Oracle two structures are
used, the PGA and the shared pool in the SGA.
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Configuring the DBMS
Each DBMS also
provides a method
to change the
system parameters
once the DBMS is
operational.
Configuring the system parameters of the DBMS controls the manner in
which the DBMS functions and the resources made available to it.4 Each
DBMS allows its system parameters to be modified in different ways, but
the installation process usually sets the DBMS system parameters by means
of radio buttons, menus, or panel selections. During the installation process, the input provided to the installation script will be used to establish
the initial settings of the system parameters.
Each DBMS also provides a method to change the system parameters
once the DBMS is operational. Sometimes you can use DBMS commands to
set the system’s parameters; sometimes you must edit a file that contains
the current system parameter settings. If you must edit a file, be very careful: An erroneous system parameter setting can be fatal to the operational
status of the DBMS.
What do the system parameters control? Well, for example, system
parameters control DBA authorization to the DBMS and the number of
active database logs; system parameters set the amount of memory used for
data and program caching and turn DBMS features on or off. Although every
DBMS has system parameters that control its functionality, each DBMS has
a different method of setting and changing the values. And, indeed, each
DBMS has different specifications that can be set using system parameters.
Beware of simply using default system parameters when installing the
database system software. Although using defaults can save time and make
for an easier installation, it can also result in subsequent problems. Most
DBMSs are poorly served, in the long run, by default settings and, in some
cases, can experience worsening performance over time because resources
were not preallocated during installation or setup.
Be sure to understand fully the parameters used by your DBMS. Failure to do so can result in an incorrectly configured database environment,
which can cause performance problems, data integrity problems, or even
DBMS failure.
4. In DB2, system parameters are set by assembling the DSNZPARM member. SQL
Server uses the SP_CONFIGURE system procedure to set system parameters, and Oracle
parameters are controlled using INIT.ORA.
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81
Connecting the DBMS to Supporting Infrastructure Software
Each piece of
supporting infrastructure software
will have different
requirements for
interfacing with the
DBMS.
Part of the DBMS installation process is the connection of the DBMS to
other system software components that must interact with the DBMS. Typical infrastructure software that may need to be configured to work with
the DBMS includes networks, transaction processing monitors, message
queues, other types of middleware, programming languages, systems management software, operations and job control software, Web servers, and
application servers.
Each piece of supporting infrastructure software will have different
requirements for interfacing with the DBMS. Typical configuration procedures can include installing DLL files, creating new parameter files to establish connections, and possibly revisiting the installation procedures for the
supporting software to install components required to interact with the
DBMS.
Installation Verification
After installing the DBMS, you should run a battery of tests to verify that
the DBMS has been properly installed and configured. Most DBMS vendors
supply sample programs and installation verification procedures for this
purpose. Additionally, you can ensure proper installation by testing the
standard interfaces to the DBMS. One standard interface supported by most
DBMSs is an interactive SQL interface where you can submit SQL statements
directly to the DBMS.5
Create a set of SQL code that comprises SELECT, INSERT, UPDATE, and
DELETE statements issued against sample databases. Running such a script
after installation helps you to verify that the DBMS is installed correctly and
operating as expected.
Furthermore, be sure to verify that all required connections to supporting software are operational and functioning properly. If the DBMS vendor
does not supply sample programs, you may need to create and run simple
test programs for each environment to ensure that the supporting software
connections are functioning correctly with the DBMS.
5. In DB2, the SQL interface is referred to as SPUFI. IBM also provides Data Studio for
GUI-based SQL creation and submission. SQL Server calls the interface ISQL, and when
using Oracle you can choose to submit SQL using SQL*Plus or the SQL Worksheet in
Oracle Enterprise Manager.
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DBMS Environments
Generally, installing a DBMS involves more than simply installing one
instance or subsystem. To support database development, the DBA needs
to create multiple DBMS environments to support, for example, testing,
quality assurance, integration, and production work. Of course, it is possible to support multiple environments in a single DBMS instance, but it is
not prudent. Multiple DBMS installations are preferable to support multiple
development environments for a single database. This minimizes migration
issues and won’t require complex database naming conventions to support.
Furthermore, segregating database instances makes testing, tuning, and
monitoring easier.
Upgrading DBMS Versions and Releases
Change is a fact
of life.
Change is a fact of life, and each of the major DBMS products changes quite
rapidly. A typical release cycle for DBMS software is 18 to 24 months for
major releases, with constant bug fixes and maintenance updates delivered
between major releases. Indeed, keeping DBMS software up-to-date can be
a full-time job.
The DBA must develop an approach to upgrading DBMS software that
conforms to the organization’s needs and minimizes business disruptions
due to outages and database unavailability.
You may have noticed that I use the terms version and release somewhat interchangeably. That is fine for a broad discussion of DBMS upgrades,
but a more precise definition is warranted. For a better discussion of the
differences between a version and a release, please refer to the sidebar.
A DBMS version upgrade can be thought of as a special case of a new
installation. All the procedures required of a new installation apply to an
upgrade: You must plan for appropriate resources, reconsider all system
parameters, and ensure that all supporting software is appropriately connected. However, another serious issue must be planned for: existing users
and applications. An upgrade needs to be planned to cause as little disruption to the existing users as possible. Furthermore, any additional software
that works with the DBMS (such as purchased applications, DBA tools, utilities, and so on) must be verified to be compatible with the new DBMS version. Therefore, upgrading can be a tricky and difficult task.
Upgrading DBMS Versions and Releases
83
Version or Release?
Vendors typically make a distinction between a version and a release of a software product. A new version of software is a major concern, with many changes and new features. A
release is typically minor, with fewer changes and not as many new features.
For example, moving from Version 10g of Oracle Database to Version 11g would be a
major change—a version change. However, an in-between point such as Oracle Database
11g Release 2 would be considered a release—consisting of a smaller number of changes.
Usually DBMS vendors increase prices for versions, but not necessarily for releases (but that
is not a hard-and-fast rule).
Usually significant functionality is added for version upgrades, less so for point releases.
Nevertheless, upgrading from one point release to another can have just as many potential
pitfalls as a version upgrade. It depends on the nature of the new features provided in each
specific release.
The issues and concerns discussed in this chapter pertain to both types of DBMS
upgrades: to a new release and to a new version.
In a complex, heterogeneous, distributed database environment, a
coherent upgrade strategy is essential. Truthfully, even organizations with
only a single DBMS should approach DBMS upgrades cautiously and plan
accordingly. Failure to plan a DBMS upgrade can result in improper and
inefficient adoption of new features, performance degradation of new and
existing applications, and downtime.
Upgrading to a new DBMS release offers both rewards and risks. The
following are some of the benefits of moving to a new release:
• Developers can avail themselves of new features and functionality
delivered only in the new release. If development requires a new
feature, or can simply benefit from a new feature, program development time can be reduced or made more cost-effective.
• For purchased applications, the application vendor may require a
specific DBMS version or release for specific versions of its application to enable specific functionality within the application.
• New DBMS releases usually deliver enhanced performance and
availability features that can optimize existing applications.
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Sometimes a new DBMS release is required to scale applications to
support additional users or larger amounts of data.
• DBMS vendors often provide better support and respond to problems faster for a new release of their software. DBMS vendors are
loath to allow bad publicity about bugs in a new and heavily promoted version of their products.
• Cost savings may accrue by upgrading to a new DBMS release. Some
vendors charge additionally when a company uses multiple versions
of a DBMS, such as the new version in a test environment and the
old in production. When both are migrated to the same version, the
price tag for the DBMS sometimes can be reduced.
• Production migration to a new DBMS release will align the test and
production database environments, thereby providing a consistent
environment for development and implementation. If a new release
is running in the test environment for too long, database administration and application development tasks become more difficult
because the test databases will operate differently from the production databases.
An effective DBMS
upgrade strategy
must balance the
benefits against the
risks of upgrading.
However, an effective DBMS upgrade strategy must balance the benefits against the risks of upgrading to arrive at the best timeline for migrating
to a new DBMS version or release. The risks of upgrading to a new DBMS
release include the following:
• An upgrade to the DBMS usually involves some level of disruption to
business operations. At a minimum, databases will not be available
while the DBMS is being upgraded. This can result in downtime and
lost business opportunities if the DBMS upgrade occurs during normal business hours (or if there is no planned downtime). Clustered
database implementations may permit some database availability
while individual database clusters are migrated to the new DBMS
version.
• Other disruptions can occur, such as having to convert database
structures or discovering that previously supported features
were removed from the new release (thereby causing application
errors). Delays to application implementation timelines are another
possibility.
Upgrading DBMS Versions and Releases
85
• The cost of an upgrade can be a significant barrier to DBMS release
migration. First, the cost of the new version or release must be budgeted for (price increases for a new DBMS version can amount to
as much as 10 to 25 percent). The upgrade cost must also factor in
the costs of planning, installing, testing, and deploying not just the
DBMS but also any applications that use databases. Finally, be sure
to include the cost of any new resources (such as memory, storage,
additional CPUs) required to use the new features delivered by the
new DBMS version. 6
• DBMS vendors usually tout the performance gains that can be
achieved with a new release. However, when SQL optimization
techniques change, it is possible that a new DBMS release will generate SQL access paths that perform worse than before. DBAs must
implement a rigorous testing process to ensure that new access
paths are helping, not harming, application performance. When
performance suffers, application code may need to be changed—a
very costly and time-consuming endeavor. A rigorous test process
should be able to catch most of the access path changes in the test
environment.
• New DBMS releases may cause features and syntax that are being
used in existing applications to be deprecated.7 When this occurs,
the applications must be modified before migration to the new
release can proceed.
• To take advantage of improvements implemented in a new DBMS
release, the DBA may have to apply some invasive changes. For
example, if the new version increases the maximum size for a database object, the DBA may have to drop and recreate that object to
take advantage of the new maximum. This will be the case when
the DBMS adds internal control structures to facilitate such changes.
• Supporting software products may lack immediate support for a
new DBMS release. Supporting software includes the operating
6. Be careful, too, to examine the specifications for any new DBMS version or release.
Sometimes features and functionality are removed from the DBMS, which might result
in having to spend additional money to replace the lost functionality. For example, IBM
removed its formerly free database utilities from DB2 between Versions 6 and 7 and
bundled them for sale.
7. When a feature is deprecated it is no longer supported in the software.
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system, transaction processors, message queues, purchased applications, DBA tools, development tools, and query and reporting
software.
After weighing the benefits of upgrading against the risks of a new
DBMS release, the DBA group must create an upgrade plan that works for
the organization. Sometimes the decision will be to upgrade immediately
upon availability, but often there is a lag between the general availability of
a new release and its widespread adoption.
When the risks of a new release outweigh the benefits, some organizations may decide to skip an interim release if doing so does not impact a
future upgrade. For example, a good number of Oracle customers migrated
directly from Oracle7 to Oracle8i, skipping Oracle8. If the DBMS vendor
does not allow users to bypass a version or release, it is still possible to
“skip” a release by waiting to implement that release until the next release
is available. For example, consider the following scenario:
1. ABC Corporation is using DB Version 8 from DBCorp.
2. DBCorp announces Version 9 of DB.
3. ABC Corporation analyzes the features and risks and determines not
to upgrade immediately.
4. DBCorp later announces DB Version 10 and that no direct migration
path will be provided from Version 8 to Version 10.
5. ABC Corporation decides that DB Version 10 provides many useful
features and wants to upgrade its current Version 8 implementation
of DB. However, it has no compelling reason to first implement and
use Version 9.
6. To fulfill its requirements, ABC Corporation first upgrades Version 8
to Version 9 and then immediately upgrades Version 9 to Version 10.
A multiple-release
upgrade allows
customers to effectively control when
and how they will
migrate to new
releases of a DBMS.
Although a multiple-release upgrade takes more time, it allows customers to effectively control when and how they will migrate to new releases of
a DBMS instead of being held hostage by the DBMS vendor. When attempting a multiple-release upgrade of this type, be sure to fully understand
the features and functionality added by the DBMS vendor for each interim
release. In the case of the hypothetical ABC Corporation, the DBAs would
Upgrading DBMS Versions and Releases
87
need to research and prepare for the new features of not just Version 10 but
also Version 9.
An appropriate DBMS upgrade strategy depends on many things. The
following sections outline the issues that must be factored into an effective
DBMS release upgrade strategy.
Features and Complexity
Perhaps the biggest factor in determining when and how to upgrade to
a new DBMS release is the functionality supported by the new release.
Tightly coupled to functionality is the inherent complexity involved in supporting and administering new features.
It is more difficult to delay an upgrade if application developers are
clamoring for new DBMS features. If DBMS functionality can minimize the
cost and effort of application development, the DBA group will feel pressure to migrate swiftly to the new release. An additional factor that will
coerce rapid adoption of a new release is when DBMS problems are fixed in
the new release (instead of through regular maintenance fixes).
Regardless of a new release’s “bells and whistles,” certain administration and implementation details must be addressed before upgrading. The
DBA group must ensure that standards are modified to include the new
features, educate developers and users as to how new features work and
should be used, and prepare the infrastructure to support the new DBMS
functionality.
The types of changes required to support the new functionality must
be factored into the upgrade strategy. When the DBMS vendor makes
changes to internal structures, data page layouts, or address spaces, the
risks of upgrading are greater. Additional testing is warranted in these situations to ensure that database utilities, DBA tools, and data extraction and
movement tools still work with the revised internal structures.
Complexity of the DBMS Environment
The more complex your database environment is, the more difficult it will
be to upgrade to a new DBMS release. The first complexity issue is the size
of the environment. The greater the number of database servers, instances,
applications, and users, the greater the complexity. Additional concerns
include the types of applications being supported. A DBMS upgrade is easier
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to implement if only simple, batch-oriented applications are involved. As
the complexity and availability requirements of the applications increase,
the difficulty of upgrading also increases.
Location of the database servers also affects the release upgrade strategy. Effectively planning and deploying a DBMS upgrade across multiple
database servers at various locations supporting different lines of business
is difficult. It is likely that an upgrade strategy will involve periods of supporting multiple versions of the DBMS at different locations and for different applications. Supporting different versions in production should be
avoided, but that is not always possible.
Finally, the complexity of the applications that access your databases
must be considered. The more complex your applications are, the more
difficult it will be to ensure their continuing uninterrupted functionality
when the DBMS is modified. Complexity issues include the following:
• Usage of stored procedures and user-defined functions.
• Complexity of the SQL—the more tables involved in the SQL and
the more complex the SQL features, the more difficult it becomes to
ensure that access path changes do not impact performance.
• Client/server processing—network usage and usage of multiple tiers
complicates testing the new DBMS release.
• Applications that are designed, coded, and generated by a framework or an IDE (for example, Hibernate) may have additional components that need to be tested with a new DBMS release.
• Integration with other infrastructure software such as message
queues and transaction processors can complicate migration
because new versions of these products may be required to support
the new DBMS release.
• The language used by the programs might also impact DBMS release
migration due to different support for compiler versions, changes to
APIs (application programming interfaces), or new ways of embedding SQL into application programs.
Upgrading DBMS Versions and Releases
89
Reputation of the DBMS Vendor
The better the
reputation of the
vendor, the greater
the likelihood of
organizations rapidly
adopting a new
release.
DBMS vendors have different reputations for technical support, fixing bugs,
and responding to problems, which is why customer references are so
important when choosing a database.
The better the reputation of the vendor, the greater the likelihood of
organizations rapidly adopting a new release. If the DBMS vendor is good
at responding to problems and supporting its customers as they migrate
to new releases, those customers will more actively engage in migration
activities.
Support Policies of the DBMS
As new releases are introduced, DBMS vendors will retire older releases
and no longer support them. The length of time that the DBMS vendor will
support an old release must be factored into the DBMS release migration
strategy. You should never run a DBMS release in production that is no longer supported by the vendor. If problems occur, the DBMS vendor will not
be able to resolve them for you.
Sometimes a DBMS vendor will provide support for a retired release on
a special basis and at an increased maintenance charge. If you absolutely
must continue using a retired DBMS release (for business or application
issues), be sure to investigate the DBMS vendor’s policies regarding support
for retired releases of its software.
Organization Style
Every organization displays characteristics that reveal its style when it
comes to adopting new products and technologies. Industry analysts at
Gartner, Inc., have ranked organizations into three distinct groups labeled
types A, B, and C. A type-A enterprise is technology driven and, as such,
is more likely to risk using new and unproven technologies to try to gain
a competitive advantage. A type-B organization is less willing to take risks
but will adopt new technologies once others have shaken out the bugs.
Finally, a type-C enterprise, very conscious of cost and averse to risk, will
lag behind the majority when it comes to migrating to new technology.
Only type-A organizations should plan on moving aggressively to new
DBMS releases immediately upon availability and only if the new features
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of the release will deliver advantages to the company. Type-C enterprises
should adopt a very conservative strategy to ensure that the DBMS release
is stable and well tested by type-A and type-B companies first. Type-B organizations will fall somewhere between types A and C: Almost never upgrading immediately, the type-B company will adopt the new release after the
earliest users have shaken out the biggest problems, but well before type-C
enterprises.
DBA Staff Skill Set
The risk of an
upgrade increases
as the skills of the
DBA staff decrease.
Upgrading the DBMS is easier if your DBA staff is highly skilled and/or
experienced. The risk of an upgrade increases as the skills of the DBA staff
decrease. If your DBAs are not highly skilled, or have never migrated a
DBMS to a new release, consider augmenting your DBA staff with consultants for the upgrade. Deploying an integrated team of internal DBAs and
consultants will ensure that your upgrade goes as smoothly as possible.
Furthermore, the DBA staff will be better prepared to handle the future
upgrades alone.
If consultants will be required, be sure to include their contracting cost
in the DBMS release upgrade budget. The budget should allow you to retain
the consultants until all production database environments are stable.
Platform Support
When a DBMS vendor unleashes a new release of its product, not all platforms and operating systems are immediately supported. The DBMS vendor
usually first supports the platforms and operating systems for which it has
the most licensed customers. The order in which platforms are supported
for a new release is likely to differ for each DBMS vendor. For example,
Linux for System z is more strategic to IBM than to Oracle, so a new DB2
release will most likely support Linux for System z very quickly, whereas
this may not be true of Oracle. The issue is even thornier for UNIX platforms because of the sheer number of UNIX variants in the marketplace.
The most popular variants are Oracle’s Solaris, IBM’s AIX, Hewlett-Packard’s HP-UX, and Linux, the open-source version of UNIX (the Red Hat and
Suse distributions are supported more frequently and rapidly than others).
Most DBMS vendors will support these UNIX platforms quickly upon general availability. Other less popular varieties of UNIX will take longer for
the DBMS vendors to support.
Upgrading DBMS Versions and Releases
91
When planning your DBMS upgrade, be sure to consider the DBMS platforms you use and try to gauge the priority of your platform to your vendor. Be sure to build some lag time into your release migration strategy to
accommodate the vendor’s delivery schedule for your specific platforms.
Supporting Software
Carefully consider
the impact of a
DBMS upgrade
on any supporting
software.
Carefully consider the impact of a DBMS upgrade on any supporting software. Supporting software includes purchased applications, DBA tools,
reporting and analysis tools, and query tools. Each software vendor will
have a different time frame for supporting and exploiting a new DBMS
release. Review the sidebar to understand the difference between support
and exploitation of a new DBMS release.
Some third-party tool vendors follow guidelines for supporting and
exploiting new DBMS releases. Whenever possible, ask your vendors to
state their policies for DBMS upgrade support. Your vendors will probably
not commit to any firm date or date range to support new versions and
releases—some DBMS versions are larger and more complicated and therefore take longer to fully exploit.
Support versus Exploit
Some vendors differentiate specifically between supporting and exploiting a new DBMS
version or release. Software that supports a new release will continue to function the same
as before the DBMS was upgraded, but with no new capabilities. Therefore, if a DBA tool,
for example, supports a new version of Oracle, it can provide all the services it did for the
last release, as long as none of the new features of the new version of Oracle are used. In
contrast, a DBA tool that exploits a new version or release provides the requisite functionality to operate on the new features of the new DBMS release.
So, to use a concrete example, IBM added support for hashing in Version 10 of DB2. A
DBA tool can support DB2 Version 10 without operating on hashes, but it must operate on
hashes to exploit DB2 Version 10.
Prior to migrating to a new DBMS version or release, make sure you understand the
difference between supporting and exploiting a new version, and get a schedule for both
from your third-party vendors for the DBA tools you use.
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Fallback Planning
Each new DBMS version or release should come with a manual that outlines
the new features of the release and describes the fallback procedures to
return to a prior release of the DBMS. Be sure to review the fallback procedures provided by the DBMS vendor in its release guide. You may need
to return to a previous DBMS release if the upgrade contains a bug, performance problems ensue, or other problems arise during or immediately
after migration. Keep in mind that fallback is not always an option for every
new DBMS release.
If fallback is possible, follow the DBMS vendor’s recommended procedures to enable it. You may need to delay the implementation of certain
new features for fallback to remain an option. Understand fully the limitations imposed by the DBMS vendor on fallback, and exploit new features
only when fallback is no longer an option for your organization.
Migration Verification
The DBA should
implement
procedures to
verify that the DBMS
release upgrade is
satisfactory.
The DBA should implement procedures—similar to those for a new installation—to verify that the DBMS release upgrade is satisfactory. Perform the
same steps as with a brand-new DBMS install, but also test a representative
sampling of your in-house applications to verify that the DBMS upgrade is
working correctly and performing satisfactorily.
The DBMS Upgrade Strategy
In general, design your DBMS release upgrade policy according to the guidelines discussed in the preceding sections. Each specific DBMS upgrade will
be unique, but the strategies we’ve discussed will help you to achieve success more readily. A well-thought-out DBMS upgrade strategy will prepare
you to support new DBMS releases with minimum impact on your organization and in a style best suited to your company.
Database Standards and Procedures
Standards and
procedures must
be developed for
database usage.
Before a newly installed DBMS can be used effectively, standards and procedures must be developed for database usage. Studies have shown that
companies with high levels of standardization reduce the cost of supporting end users by as much as 35 percent or more as compared to companies
with low levels of standardization.
Database Standards and Procedures
93
Standards are common practices that ensure the consistency and
effectiveness of the database environment, such as database naming conventions. Procedures are defined, step-by-step instructions that direct the
processes required for handling specific events, such as a disaster recovery
plan. Failure to implement database standards and procedures will result in
a database environment that is confusing and difficult to manage.
The DBA should develop database standards and procedures as a component of corporate-wide IT standards and procedures. They should be
stored together in a central location as a printed document, in an online format, or as both. Several vendors offer “canned” standards and procedures
that can be purchased for specific DBMS products.
Database Naming Conventions
One of the first standards to be implemented should be a set of guidelines
for the naming of database objects. Without standard database object naming conventions, it will be difficult to identify database objects correctly
and to perform the proper administration tasks.
Database object naming standards should be developed in conjunction
with all other IT naming standards in your organization. In all cases, database
naming standards should be developed in cooperation with the data administration department (if one exists) and, wherever possible, should peacefully
coexist with other IT standards, but not at the expense of impairing the database environment. For example, many organizations have shop conventions
for naming files, but coordinating the database object to the operating system file may require a specific format for database filenames that does not
conform to the shop standards (see Figure 2.7). Therefore, it may be necessary to make exceptions to existing shop standards for naming database files.
Filename
Figure 2.7
Data Sets
or Files
System
Catalog
OS File System
DBMS
Database objects map to filenames
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Chapter 2
Be sure to establish
naming conventions
for all database
objects.
Be sure to create and publish naming standards for all database objects
that can be created within each DBMS used by your organization. A basic
list of database objects supported by most DBMSs includes databases, tables,
columns, views, indexes, constraints, programs, user-defined data types,
user-defined functions, triggers, and stored procedures. However, this list is
incomplete because each DBMS uses other database objects specific to its
operation. For example, DB2 uses plans and storage groups; Oracle uses database links and clusters; SQL Server uses filegroups and rules (see the sidebar).
The database naming standard should be designed to minimize name
changes across environments. For example, embedding a T into the name
for “test” and a P for “production” is a bad idea. It is especially important
to avoid this approach for user-visible database objects such as columns,
Minimize name
changes across
environments.
Creating the Database Environment
Example Nonstandard Database Objects
Unless you use all three of DB2, Oracle, and SQL Server, some of the database objects that
are specific to only one of these database systems probably will be unfamiliar to you. Given
that, this sidebar offers short definitions of the database objects mentioned in this section.
For DB2:
• A plan is associated with a DB2 application program and refers to packages that
contain bound access path details for the SQL in that program.
• A storage group is a database object used to associate disk storage with DB2
tablespaces.
For Oracle:
• A database link is a schema object in one database that enables you to access
objects in another database.
• A cluster is made up of a group of tables that share the same data blocks. The
tables are grouped together because they share common columns and are often
used together.
For SQL Server:
• Database objects and files can be grouped together in filegroups for allocation
and administration purposes.
• A rule is a freestanding database constraint that can be attached to columns. Microsoft has indicated that rules will be removed from a future version of SQL Server.
Database Standards and Procedures
Avoid encoding
table names to
make them shorter.
95
tables, and views. Minimizing name changes simplifies the migration of
databases from one environment to another. It is possible to make all the
database object names the same by assigning each environment to a different instance or subsystem. The instance or subsystem name, rather than
the database object names, will differentiate the environments.
In most cases, for objects not accessed by typical end users, provide a
way to differentiate types of database objects. For example, start indexes
with I or X and databases with D. For tables and similar objects, though, as
discussed earlier, this approach is inappropriate.
In general, do not impose unnecessary restrictions on the names of
objects accessed by end users. Relational databases are supposed to be user
friendly. A strict database naming convention, if not developed logically,
can be antithetical to a useful and effective database environment. Some
organizations impose arbitrary length limitations on database tables, such
as an 8-byte limit even though the DBMS can support up to 128-byte table
names. There is no practical reason to impose a limitation on the length of
database table names.
Table names should be as descriptive as possible, within reason. Furthermore, the same naming conventions should be used for all “tablelike”
objects, including views, synonyms, and aliases, if supported by the DBMS.
Each of these objects is basically a collection of data accessible as rows and
columns. Developing separate naming conventions for each is of no real
value. With this approach, database objects that operate like tables will be
defined similarly with a very descriptive name. The type of object can always
be determined by querying the DBMS system catalog or data dictionary.
Encoding table names to make them shorter is another arbitrary naming standard that should be avoided. Table names should include a 2- or
3-byte application identification prefix, followed by an underscore and
then a clear, user-friendly name. For example, a good name for the table
containing employee information in a human resources system would be
HR_EMPLOYEE. You may want to drop the application identification prefix
from the table name for tables used by multiple applications.
Keep in mind, too, that some database object names will, in some cases,
be externalized. For instance, most DBMSs externalize constraint names
when the constraint is violated. There are many types of constraints—triggers, unique constraints, referential constraints, check constraints—each of
which can be named. Keeping the names consistent across environments
allows the error messages to be consistent. If the DBMS delivers the same
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error message in the development, test, integration, and production environments, debugging and error correction will be easier.
Standard Abbreviations
Create a list
of standard
abbreviations.
Although you should keep the database object names as English-like as possible, you will inevitably encounter situations that require abbreviations.
Use abbreviations only when the full text is too long to be supported as an
object name or when it renders the object name unwieldy or difficult to
remember. Create a list of standard abbreviations and forbid the use of nonstandard abbreviations. For example, if “ORG” is the standard abbreviation
for “organization,” do not allow variants such as “ORGZ” to be used. Using
standard abbreviations will minimize mistyping and make it easier for users
to remember database object names. Adhering to this practice will make it
easier to understand the database objects within your environment.
Other Database Standards and Procedures
Although database naming standards are important, you will need to
develop and maintain other types of database standards. Be sure to develop
a comprehensive set of standards and procedures for each DBMS used by
your organization. Although you can write your database standards from
scratch, there are other potentially easier ways to build your standards
library. Basic standards that can be modified to your requirements can be
bought from a publisher or software vendor. Or you can gather suggested
standards from the community via user groups and conferences.
Regardless of whether they are purchased, written in house, or adopted
from a user group or committee, each of the following areas should be
covered.
Roles and Responsibilities
The successful operation of a DBMS requires the coordinated management efforts of many skilled technicians and business experts. A matrix of
database management and administration functions should be developed
that documents each support task and who within the organization provides the support. The matrix can be created at a departmental level, a job
description level, or even by individual name. A sample matrix is shown in
Table 2.4. An X in the matrix indicates involvement in the process, whereas
a P indicates primary responsibility.
Table 2.4
Database Support Roles and Responsibilities
Task
DBA
DA
SA
Management
P
DBMS budget
X
X
DBMS installation
P
X
DBMS upgrade
P
X
X
X
Applications
End
Users
X
X
X
X
X
X
X
X
X
X
Operations
Database usage policy
P
Capacity planning
X
X
Data modeling and analysis
X
Metadata policy
X
P
Governance and compliance
X
X
Database design
P
X
Database creation
P
System performance
X
P
Database performance
P
X
X
Application performance
X
X
P
Backup and recovery
P
X
X
Disaster recovery
P
X
X
Database security
P
X
X
Stored procedures
X
P
Triggers
P
X
User-defined functions
X
P
Application design
X
P
Application turnover
X
Application design reviews
X
P
X
P
X
X
X
X
X
X
P
X
X
X
X
X
P
X
X
P
X
97
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Of course, you can create whatever tasks you deem necessary in your
roles and responsibilities matrix. You may need additional tasks, or fewer
than in this sample. For example, you may wish to differentiate between
stored-procedure development, testing, and management by creating a different task category for each and breaking down the support requirements
differently.
Whatever the final format of your roles and responsibilities matrix, be
sure to keep it accurate and up-to-date with new DBMS features and tasks.
An up-to-date matrix makes it easier to define roles within the organization
and to effectively apportion database-related workload.
Communication Standards
You might also choose to develop specific standards for communication
between groups and specific personnel. For example, you might want to
document how and when the DBA group must communicate with the systems programming group when a new DBMS release is being installed.
Developing robust communication standards can simplify a DBA’s job
during the inevitable downtime that occurs due to system, application, or
even hardware errors. For example, consider adopting a standard whereby
the DBA communicates only with the manager during troubleshooting and
emergency remediation. This keeps the manager informed and enables the
DBA to dodge the dozens of phone calls that come in from angry users, the
help desk, and so on. The manager can communicate the status outward
while the DBA focuses exclusively on troubleshooting and getting the systems back up and running again.
Data Administration Standards
Include DA
standards in the
DBA standards as
appropriate.
If a DA group exists within your organization, they should develop a basic
data administration standards guide to outline the scope of their job role.
If a DA group does not exist, be sure to include DA standards in the DBA
standards as appropriate.
The data administration standards should include the following items:
• A clear statement of the organization’s overall policy with regard to
data, including its importance to the company
• Guidelines for establishing data ownership and stewardship
• Rules for data creation, data ownership, and data stewardship
Database Standards and Procedures
99
• Metadata management policy
• Conceptual and logical data modeling guidelines
• The organization’s goals with regard to creating an enterprise data
model
• Responsibility for creating and maintaining logical data models
• Guidelines for tool usage and instructions on how data models are
to be created, stored, and maintained
• Organizational data-sharing policies
• Instructions on how to document when physical databases deviate
from the logical data model
• Guidelines on communication between data administration and
database administration to ensure effective database creation and
usage
Database Administration Standards
The DBA standards
serve as a guide to
specific approaches
to supporting
the database
environment.
A basic set of database administration standards should be established to
ensure the ongoing success of the DBA function. The standards serve as a
guide to the DBA services offered and to specific approaches to supporting
the database environment. For example, standards can be developed that
outline how requests are made to create a new database or make changes
to existing databases, and that specify which types of database objects
and DBMS features are favored and under which circumstances they are
to be avoided. Standards can establish backup and recovery procedures
(including disaster recovery plans) and communicate the methods used to
transform a logical data model into a physical database implementation. An
additional set of DBA standards that cover database performance monitoring and tuning may be useful to document procedures for overcoming performance problems.
Although the DBA standards will be most useful for the DBA staff, the
application development staff will need them to learn how best to work
with the DBA staff. Furthermore, any performance tuning tricks that are
documented in the DBA standards should be shared with programmers.
The more the application programmers understand the nuances of the
DBMS and the role of the DBA, the better the working relationship between
DBA and development will be—resulting in a more efficient database
environment.
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System Administration Standards
Once again, standards for system administration or systems programming
are required only if your organization separates the SA function from the
DBA function. System administration standards are needed for many of the
same reasons that DBA standards are required. Standards for SA may include
• DBMS installation and testing procedures
• Upgrade policies and procedures
• Bug fix and maintenance practices
• A checklist of departments to notify for impending changes
• Interface considerations
• DBMS storage, usage, and monitoring procedures
Database Application Development Standards
The development of database applications differs from typical program
development. You should document the special development considerations required when writing programs that access databases. The database
application development standards should function as an adjunct to any
standard application development procedures within your organization.
This set of standards should include
• A description of how database access differs from flat file access
• SQL coding standards
• SQL performance tips and techniques
• Program preparation procedures and guidance on how to embed
SQL in an application program
• Interpretations of SQLSTATEs and error codes
• References to other useful programming materials for teleprocessing monitors, programming languages, and general application
development standards
Database Security Standards
The DBA group often applies and administers DBMS security. However,
at some shops the corporate data security unit handles DBMS security. A
Database Standards and Procedures
101
resource outlining the necessary standards and procedures for administering database security should contain the following information:
• Details on what authority to grant for specific types of situations;
for example, if a program is being migrated to production status,
what DBMS authorization must be granted before the program will
operate successfully in production
• Specific documentation of any special procedures or documentation
required for governance- and compliance-related requests
• A definitive list of who can approve what types of database authorization requests
• Information on any interfaces being used to connect DBMS security
with operating system security products
• Policies on the use of the WITH GRANT OPTION clause of the SQL
GRANT statement and how cascading REVOKEs are to be handled
Outline necessary
standards and
procedures for
administering database security.
• Procedures for notifying the requester that database security has
been granted
• Procedures for removing security from retiring, relocating, and
terminated employees
Application Migration and Turnover Procedures
As discussed earlier, the minimum number of environments for supporting database applications is two: test and production. Some organizations,
however, create multiple environments to support, for example, different
phases of the development life cycle, including
• Unit testing—for developing and testing individual programs
• Integration testing—for testing how individual programs
interoperate
• User acceptance testing—for end user testing prior to production
status
• Quality assurance—for shaking out program bugs
• Education—for training end users how to work the application
system
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Procedures are
required for migrating database objects
and programs from
environment to
environment.
When multiple environments exist, procedures are required for migrating database objects and programs from environment to environment. Specific guidelines are needed to accomplish migration in a manner conducive
to the usage of each environment. For example, what data volume is required
for each environment and how is data integrity to be assured when testing
activity occurs? Should data be migrated, or just the database structures?
How should existing data in the target environment be treated—should it
be kept, or overlaid with new data? Comprehensive migration procedures
should be developed to address these types of questions.
The migration and turnover procedures should document the information required before any database object or program can be migrated from
one environment to the next. At a minimum, information will be required
about the requester, when and why the objects should be migrated, and
the appropriate authorization to approve the migration. To ensure the success of the migration, the DBA should document the methods used for the
migration and record the verification process.
Creating the Database Environment
Design Review Guidelines
All database applications should be subjected to a design review at various stages of their development. Design reviews are important to ensure
proper application design, construction, and performance. Design reviews
can take many forms. Chapter 6, “Design Reviews,” offers a comprehensive
discussion.
Operational Support Standards
Operational support
assures that applications are run according to schedule.
Operational support is defined as the part of the IT organization that
oversees the database environment and assures that applications are run
according to schedule. Sufficient operational support must be available to
administer a database environment effectively. The operational support
staff is usually the first line of defense against system problems. Program
failures, hardware failures, and other problems are first identified by operational support before specialists are called to resolve the problems.
Standards should be developed to ensure that the operational support
staff understands the special requirements of database applications. Whenever possible, operational support personnel should be trained to resolve
simple database-related problems without involving the DBA because the
DBA is a more expensive resource.
DBMS Education
103
DBMS Education
Organizations using DBMS technology must commit to ongoing technical
education classes for DBAs, programmers, and system administrators. Provide a catalog of available courses covering all aspects of DBMS usage. At a
minimum, the following courses should be made available:
• DBMS Overview: a one-day management-level class that covers the
basics of DBMS
• Data Modeling and Database Design: a thorough course covering
conceptual, logical, and physical database design techniques for DAs
and DBAs
• Database Administration: in-depth technical classes for DBAs, SAs,
and systems programmers
• Introduction to SQL: an introductory course on the basics of SQL
for every DBMS user
• Advanced SQL: an in-depth course on complex SQL development
for DBAs and programmers
• Database Programming: an in-depth course for application programmers and systems analysts that teaches students how to write
programs that use the DBMS
Commit to ongoing
technical education
classes.
Each of these courses should be available for each DBMS installed in
your organization. Furthermore, provide training for any other databaserelated functionality and software such as proper use of database utilities,
query and reporting tools, and DBA tools.
DBMS education can be delivered using a variety of methods, including
instructor-led courses, computer-based training, Web-based training, and
distance learning. Sources for DBMS education include DBMS vendors, ISVs,
consultants (large and small, international and local), and training specialists (such as Themis and ProTech).
Finally, be sure to make the DBMS reference material available to every
user. Most vendors offer their DBMS reference manuals in an online format
using Adobe Acrobat files or Windows Help. Be sure that each user is given
a copy of the manuals or that they are available in a central location to
minimize the amount of time DBAs will have to spend answering simple
questions that can be found in the DBMS documentation.
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Summary
Comprehensive advance planning is required to create an effective database environment. Care must be taken to select the correct DBMS technology, implement an appropriate DBMS upgrade strategy, develop useful
database standards, and ensure the ongoing availability of education for
database users. By following the guidelines in this chapter, you can achieve
an effective database environment for your organization.
Nevertheless, setting up the database environment is only the beginning. Once it is set up, you will need to actively manage the database environment to ensure that databases are created properly, used correctly, and
managed for performance and availability. Read on to discover how the
DBA can accomplish these tasks.
Review
1. Why should database standards be implemented and what are the risks
associated with their lack?
2. What are the potential risks of upgrading to a new DBMS release without a plan?
3. What is the difference between a version and a release of a DBMS?
4. Name the three TPC benchmarks and describe how they differ from
one another.
5. Describe the four levels of DBMS architecture in terms of the type and
nature of processing to which each is best suited.
6. What are the factors to be considered when calculating total cost of
ownership (TCO) for a DBMS?
7. Name five requirements that must be planned for when installing a
new DBMS.
8. Describe the difference between software that supports a DBMS
release and software that exploits a DBMS release.
9. How many standard abbreviations should be supported for a single
term? Why?
Suggested Reading
105
10. What is wrong with the following SQL code for creating a relational
table? (Do not approach this question from a syntax perspective; consider it, instead, in terms of database naming standards.)
CREATE TABLE tg7r5u99_p
(c1
INTEGER NOT NULL,
c2
CHAR(5) NOT NULL,
c9
DATE)
;
Bonus Question
Your DBMS vendor, MegaDataCorp, just announced the general availability
of the latest and greatest version of MDC, the DBMS you use. MDC Version
9 supports several new features that your users and developers have been
clamoring for over the past year. You are currently running MDC Version
7.3. Prepare a short paper discussing your plans for upgrading to MDC Version 9, and outline the potential benefits and risks of your upgrade plan.
Suggested Reading
Blaha, Michael R. A Manager’s Guide to Database Technology. Upper
Saddle River, NJ: Prentice Hall (2001). ISBN 0-13-030418-2.
Connolly, Thomas, and Carolyn Begg. Database Systems: A Practical
Approach to Design, Implementation, and Management. 4th ed. Harlow, England: Addison-Wesley (2004). ISBN 978-0-321-29401-2.
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Index
NOTES:
Page numbers ending with an italic f (e.g. 192f ) indicate tables or figures.
Numbers containing a lowercase n (e.g. 301n or 432n.5) indicate a footnote.
24/24 availability, 270–271
80/20 (Pareto) rule, 302
99.999% availability, 273–274
100 Year Archive Requirements Survey, 503n
A
Abbreviations, standards for, 96
Absolute positioning, 383–385
Access (Microsoft), 767
Access paths, 187
Accessibility, DBA to coworkers, 745
Accessing data. See Data access.
Accounts. See Logins.
ACID (atomicity, consistency, isolation, and durability) properties, 205–206
Acquire/release specification, 218
Actian Corporation, 764
Active databases, 426
Active metadata sources, 690
Actuate, 773
Adabas (Software AG), 764
Adaptive Ltd., 772
Adaptive Server Enterprise, 64
AD/Cycle (IBM), 695
Adding objects. See ALTER statements.
Adelphia, 485
Adjectives as
attributes, 116, 124
entities, 115
Adjust tables, data page layouts, 592
ADLC (application development life cycle),
9–10, 12
ADO.NET, 194–195
Advanced analytics, 269–270
853
854
Index
AES (Advanced Encryption Standard), 472
Agile Modeling, 783
"Airline magazine" syndrome, 266
ALL privileges, 458–459
Allen Systems Group, 770, 772
Allied agents, 321–322
Allocation pages, data page layouts, 589
Allocation units, data page layouts, 589
ALLOW UPDATES parameter, 345
ALTER statements
changing database structures, 250–252,
252–253
changing management, 701–703
limitations, 252–253
purpose of, 250–252
ALTER TABLE statements, 436–437
AlwaysOn features, 285
Analytical processing versus transaction processing, 638–640
Analytics
advanced, 269–270
availability requirements, 268–270
benefits of, 269
DBA rule of thumb, 741–742
tools for, 721–724
ANSI Web site, 782
APIs, SQL, 192–193
Applets, 196–197
Application DBA, 34–35
Application development life cycle (ADLC),
9–10, 12
Application Security, 770
Application servers, 209–210, 664
Application time, 179–180
Applications. See also Database applications.
availability problems, 279–280
backing up, 516–517
code, design review, 238
complexity, upgrading the DBMS, 88
criticality of, ranking, 562–563
DBA staffing requirements, 38–39
development standards, 100
infrastructure design, 193–194
integration, 624–625
Java, 196–197
performance, 312, 711–713. See also Relational
optimization; SQL tuning.
Approach (Lotus), 767
Aquafold, 770
Archiving database logs, 77–78, 339, 529. See also
Backup.
Archiving databases
100 Year Archive Requirements Survey, 503n
data life cycle, 499–500
definition, 500
e-discovery, effects on DBA, 506–507
hardware independence, 503–505
hardware obsolescence, 504
overview, 500–505
versus purging databases, 501
requirements, 503–505
software independence, 503–505
system components, 505–506
Archiving databases, data retention
overview, 498
scope, determining, 501–503
Associative entities, 127
Atomicity
definition, 758
transactions, 205–206
Atomicity, consistency, isolation, and durability
(ACID) properties, 205–206
Attributes
adjectives as, 116, 124
data types, 116
definition, 115
discovering, 124–125
domains, 116
missing values, 119–120
naming conventions, 116–119
nouns as, 124
nulls, 119–120
prepositional phrases as, 124
purpose, 115–116
transforming to columns, 142–143
values, 119
Auditing
security, 477–478
tools for, 717–719
Auditing databases
common questions, 495
comprehensive methods, 494
data access tracking, 490–493
guidelines, 492–493
Index
log-based auditing, 493–495
network sniffing, 494–495
noninvasive methods, 494
overview, 490–493
parsing database logs, 493–495
privileged users, 495–496
regulatory requirements, 491
selective methods, 494
tapping requests, 494–495
techniques for, 493–495
trace-based auditing, 493–495
Authentication, 452
Authority. See also Privileges; Security.
LBAC (label-based access control), 463–465
Authority, granting privileges
centralized administration, 457
database object privileges, 459
DCL (Data Control Language), 456–457
decentralized administration, 457
overview, 456–457
procedure privileges, 460
program privileges, 460
to PUBLIC authority, 460–461
system privileges, 459–460
table privileges, 458–459
types of privileges, 457–458. See also specific
types.
Authority, revoking privileges
cascading REVOKEs, 462, 468
chronology and REVOKEs, 462–463
overview, 461
Authorization. See also Privileges; Security.
availability problems, 280
database administration tasks, 24–25
database administrator, 467
database maintenance, 467
for groups, 468
operations control, 467
for roles, 466, 468
security administrator, 467, 468
system administrator, 467
Automatic summary tables, 652–653
Automation
change management, 245
DBA functions, for availability, 290–291
DBA rule of thumb, 737–739
Autonomy, distributed databases, 626
855
Availability. See also Downtime.
"airline magazine" syndrome, 266
change management, 246
components of, 267–268
database administration tasks, 24
DBA staffing requirements, 38
definition, 267
versus downtime, 273
driving factors, 266–267
"fast food" mentality, 266
Internet databases, 676–677
Internet time, 266
manageability, 267
overview, 265–267
versus performance, 267
recoverability, 267
reliability, 267
response time, 266
serviceability, 268
Availability, ensuring
automating DBA functions, 290–291
clustering technology, 292–295
database architecture, 296
DB2 Data Sharing, 295
high-availability features, 291
load balancing, 293
nondisruptive utilities, 288–289
NoSQL, 296
online database reorganization, 288–289
performing routine maintenance, 288–289
recommended strategy, 287
Availability, problems
application problems, 279–280
authorization problems, 280
cluster failover techniques, 276
data corruption, 280–281
data replication and propagation failures, 283
DBA mistakes, 284, 286
DBMS software failure, 279
disk outages, 278
human error, 284, 286
loss of data, 282–283
loss of database objects, 281–282
loss of entire database, 277
loss of the data center, 274–275
maintenance outages, 286–287
network problems, 275
856
Index
Availability, problems (continued )
operating system failure, 279
planned outages, 286–287
recovery issues, 284
SAN failure, 278
security problems, 280
server hardware failure, 276
server performance, 283–284
standby systems, 276, 277
system memory failure, 276
unplanned outages, 286–287
Availability, requirements
24/24, 270–271
across time zones, 270–271
advanced analytics, 269–270
analytics, 268–270
business intelligence, 268–270
data warehousing, 270
decision support, 268–270
five nines, 273–274, 292
full time, 270–271
IT complexity, 271
maintenance window, 268
MTBF (mean time between failure), 273–274
overview, 268
Availability, tools. See also Standby databases.
AlwaysOn features, 285
Database Definition on Demand, 289–290
DB2 HADR (high-availability disaster recovery), 285
RAC (Real Application Clusters), 294
REORG, 288–289
B
Bachmann E/R method, 112
Background processes, 326
Backup. See also Archiving; Disaster planning;
Recovery.
application failure, 516–517
concurrent access issues, 525–527
COPY utility, 525
data movement, 535
data warehouse, 656–657
database administration tasks, 26–27
database failure types, 516–517
database logs, 529
database objects, 523–524
DBMS control, 524–525
differential, 521
documenting your strategy, 536
DSN1COPY utility, 552
frequency, determining, 518
full image copy, 521–523
heterogeneous database migration, 534–535
hot versus cold, 527
image copies, guidelines, 519–520
importance of, 515–516
incremental, 521–523
indexes, 524
instance failure, 516–517, 533, 550
media failure, 517, 550
object definitions, 536–537
overview, 517–520
regulatory compliance, 508
release upgrades, 534
scheduling, 531–533
SQL Server transaction logs, 530
subsystem failure, 533, 550
tools for, 714–715
transaction failure, 516–517, 550
Backup, alternatives to
disk mirroring, 556–557
exporting data, 534–535
logical backups, 534–535
redundant data, 555–556
replication, 555–556
snapshot replication, 555–556
standby databases, 277, 554–555
storage management software, 535–536, 547
symmetric replication, 555–556
unloading data, 534–535
Backup, consistency
creating a recovery point, 528–529
definition, 29
overview, 527–528
quiesce point, 528
QUIESCE utility, 528
Backup files, data integrity, 411
BACKUP LOG command, 530
Batch processing, 221–222
Benchmarks, 65–66. See also Performance.
Big Data movement, 55–56
Big Three DBMS vendors, 762
BIND command, 477
Index
Binding check constraints, 424
Bitemporal support, 179
Bitmap indexes, 155–156
Bitmaps, data page layouts, 589
Blind men and an elephant, 108
Block size, optimizing database performance,
364–365
Blocks, recovering, 553
Blogs, 780–781
BMC Software, 769
Booch, Grady, 113
Bradmark Technologies, 770
Bridge architecture drivers, 673
b-tree index, 154–155
Buffer pools, 78–79
Bulk data movement, 623–625. See also Distributed databases.
Bulk-logged recovery, 340, 540
Bunker Hill Corporation, 770
Business intelligence
availability, 268–270
tool vendors, 773
tools for, 721–724
Business Intelligence Network, 783
Business logic, 664–666
Business metadata, 689
Business service interruption, risk of, 561–563
Business time, 179–180
Business-critical applications, 562
C
CA Technologies, Inc., 770, 772
Cache
database log, 330
Internet structure, 330
memory usage, displaying, 413–414
procedure, 329–330, 335
program, 79
sort, 330
system performance, 328–330
Cache, data
definition, 78–79
system performance, 329–330, 332–335
Callable routines, 192
Candidate keys, indexes, 152
Candle Corporation, 770
Capacity planning, tools for, 313
857
Cardett Associates, 773
Cardinality, 112
Careers in DBA
DBAjobs.com, 782
demand for DBAs, 4
evaluating a job offer, 14–15
salaries, 4–6
sample job posting, 785–791
skill and knowledge requirements, 788–790
typical responsibilities, 786–788
workload, 6
Carnival blogs, 781
Cartesian products, 402
Cascading DROPs, 251, 701–703
Cascading REVOKEs, 462, 468
Cassandra, 56
Catalog query and analysis tools, 705–707
CDB Software, 770
CD/DVD storage, DBMS requirements, 77
Centralized data management model, 668
Centralized processing, 666–667
Certegy Check Services, Inc., 496
Certification
and job performance, 57
overview, 56–58
sources of, 58
Change management
automation, 245
availability, 246
checklists, 260
coordinating databases with applications,
260–261
DBA scripts, 262
free space, changing, 255–256
impact analysis, 245
indexes, recreating, 257n
intelligence, 245
overview, 243–244
perspective of the DBA, 246–247
planning analysis, 245
proactivity, 245
quick, efficient delivery, 246
reasons for change, 244
regulatory compliance, 261–262, 508
reliable, predictable processes, 246
requesting changes, 258–260
sample scenarios, 254–257
858
Index
Change management (continued )
standardized procedures, 245
success factors, 244–246
tools for, 254, 701–703
Change management, database structures
adding columns, 255, 256. See also ALTER
statements.
ALTER statements, 250–252, 252–253
cascading DROPs, 251
changing objects, 250–252
comparing structures, 257–258
CREATE statements, 250–252
creating objects, 250–252
in database change management, 250–253
DROP statements, 250–252
dropping objects, 250–252
overview, 250–252
removing objects. See DROP statements.
Change management, types of change
applications, 249–250
DBMS software, 248
hardware configuration, 248
logical design, 248–249
overview, 247
physical database structures, 250
physical design, 248–249
Change requests, 258–260
Check conditions, 420
Check constraints
benefits of, 420–421
binding, 424
check conditions, 420
constraint names, 420
definition, 28, 419
examples, 421–423
nulls, 423–426
versus referential integrity, 441–442
relational nulls, 423–426
rules, 424
semantic data integrity, 419–426
CHECK utility (DB2), 411
CHECKALLOC option, 413
CHECKCATALOG option, 413
CHECKDB option, 413
CHECKFILEGROUP option, 413
Checkpoint/restart, tools for, 725
CHECKTABLE option, 412
Chen E/R method, 112
Child tables, referential integrity, 433–434
CKPT (checkpoint) process, 326
Client computers, 665
Client-based drivers, 673
Client/server computing. See also Database connectivity; Network traffic.
application servers, 664
applications, types of, 667–670
business logic, 664–666
centralized data management model, 668
centralized processing, 666–667
client computers, 665
cooperative processing, 667
database management systems, 664–666
database servers, 664
decentralized user presentation model, 668
definition, 663, 665
distributed data management model, 668–669
distributed processing, 666–667
distributed user presentation model, 667–668
distributing tasks across a network, 668
fat clients, 670
file servers, 664
multitier implementation, 669–670
network traffic, 670–674
performance problems, 670–674
presentation logic, 664–666
print servers, 664
recommended hardware, 666
server computers, 665–666
software layers, 664–666
thin clients, 670
Cloud computing, effect on DBAs, 53–55
Cloud database systems, 74–75
Cluster failover techniques, 276
Cluster ratios, 369
Clustering. See also Interleaving data.
definition, 71, 94
indexes, 159–160
optimizing database performance, 356–358
shared-disk, 72
shared-nothing, 71–72
standards, 94
technology for availability, 292–295
types of, 71–72
COBIT, 509–510
Index
CODASYL (Conference on Data Systems
Languages), 754–755
Codd, E. F., 128
Code
design review, 238
memory usage, displaying, 413
Code generators
creating SQL, 191–192
SQL tuning, 405
Cogit, 770
Cold backup, 527
Column-oriented data models, 756
Columns
adding, 251, 255, 256
constraints, 144
deleting, 251
fixed-length, 144
identity property, 145
nullability, specifying, 144
ordering, 146
transforming attributes to, 142–143
unique identifiers for, 145
variable length, 144
COM, SQL, 193
Combined tables, optimizing database performance, 356
COMMIT statements
batch processing, 221–222
saving transaction changes, 205
SQL tuning, 404–405
two-phase, 631
COMMITTED READ isolation, 216–217
Communications, standards, 98
Compliance, tools for, 716–721
Comprehensive auditing methods, 494
Compression
data warehouse, 644
database design, 149–150
disaster planning, backup, 575
optimizing database performance, 361–362
performance tuning, 314
tools for, 726–727
Computer Associates, 773
Computer Associates International, 771
Compuware Corporation, 770
Conceptual data modeling, 125–128
Conceptual design review, 233–235
859
Concurrency, unloading data, 619
Concurrency control, purpose of, 758
Conference on Data Systems Languages
(CODASYL), 754–755
config.ora file, 325
Configuring the DBMS. See also Installing the
DBMS; Upgrading the DBMS.
default parameters, 80
performance tuning. See System performance,
DBMS installation and configuration.
system parameters, 80
Confio Software, 770
Connection pooling, 674
Connectivity. See Database connectivity.
Consistency, transactions, 206
Consistency checking, 412–413
Constraint names, 420
Constraints
check, 28
columns, 144
data integrity, 28
enforcing while loading data, 615
referential, 28
unique, 28
Consultants, Web sites, 779–780
Consumption sources, 330–331
Contention
performance factor, 301
performance monitoring and tuning, 23
system performance, 341–342
Contingency planning. See Disaster planning.
Control files, 325
Converting data types while loading data, 616
Cooperative processing, 667
COPY utility, 525
Copying data. See also Loading data; Unloading
data.
bulk data movement, 623–625
EXPORT utility, 622–623
IMPORT utility, 622–623
to multiple databases. See Distributed
databases.
CoSort/IRI, 773
Cost-based optimization versus rule-based, 344
Costs of
CPU, relational optimization, 376
of data breaches, 450
860
Index
Costs of (continued )
I/O, relational optimization, 376
ownership, 67
performance, across the ADLC, 307
poor data quality, 488, 489
regulatory compliance, 485
regulatory non-compliance, 488
upgrading the DBMS, 84, 85
CouchDB databases, 56, 766
CPU parallelism, 391
CREATE statements, 250–252
CREATE TABLE statements, 436–437
Creating objects. See CREATE statements.
Critical applications, 562–563
Criticality of data, ranking, 562–563
Cursor, SQL, 190
Cursor stability, 216–217
D
DA (data administration), 15–18, 19
DAMA (Data Management Association), Web site,
783
Darwin Professional Underwriters, 450
Data. See also Backup; Disaster planning;
Recovery.
abstraction levels, DBMS, 757
breaches, 449–450
cleansing, 645–649
compression, 644
content, 654
corruption, 280–281
definition, 686
dictionaries, 695–696
encryption. See Encryption.
freshness, 654
independence, 757
latency, 574, 654
length, semantic data integrity, 417–418
moving. See Moving data.
placement, distributed databases, 629
privacy, policies and statutes, 11
profiling, 489, 719–720
protection, tools for, 716–721
quality, 488–489, 648. See also Data integrity.
rate of growth, 581
record layouts, data page layouts, 590
replication and propagation failures, 283
rows, data page layouts, 588–589
security, DBMS, 758
stewardship, 688
usage, 655
Data access
DBMS, 758–759
to noncurrent versions, 177–180
tracking, 490–493
Data administration (DA), 15–18, 19
Data Administration Newsletter, 782
Data administration standards, 98–99
Data and Technology Today blog, 781
Data Control Language (DCL), 456–457
Data Definition Language (DDL), 177, 250–252
Data Dictionary. See System catalog.
Data Encryption Standard (DES), 472
Data files, 325
Data governance. See also Regulatory
compliance.
IT Governance Institute, 509
overview, 489–490
tools for, 716–721
Data Governance blog, 781
Data integrity. See also Data, quality.
backup consistency, 29
constraints, 28
data cleansing, 646
data warehouse, 646
database administration tasks, 27–29
DBMS, 758–759
index consistency, 29
pointer consistency, 29
problems, loading data, 615
types of, 409–410
Data integrity, database structure
backup files, 411
consistency checking, 412–413
database checking, 413
headers, 411
memory usage, 413–414
page header corruption, 411
problem management, 411–414
types of problems, 410–411
utilities for, 411–414
Data integrity, semantic
check constraints, 419–426
data length, 417–418
Index
data types, 417–418
default values, 419
DQS (Data Quality Services), 415
entity integrity, 416–417
example, 28
overview, 414–415
primary key constraints, 416–417
triggers, 426–433
UDT (user-defined data types), 418–419
unique constraints, 417
unique entity identification, 416–417
Data life cycle, 499–500
Data Management Association (DAMA), Web site,
783
Data mart, 638
Data masking and obfuscation. See also
Encryption.
definition, 496–497
encryption, 497
nulling out, 498
number and date variance, 497
shuffling, 497
substitution, 497
table-to-table synchronization, 498
techniques for, 497–498
tools for, 720
Data mining, 639
Data modeling
concepts, 108–113
conceptual, 125–128
DA (data administration), 17–18
DBA tasks, 33
definition, 107
enterprise data model, 109
E/R (entity relationship diagram), 110–113
homonyms, 118
importance of, 107
issues, 135–136
logical, 125–128
physical, 125–128
rules for, 110
synonyms, 118
tool vendors, 771–772
tools for, 700–701
types of, 125–128
Data modeling, components
attributes, 115–119
entities, 113–115
861
keys, 120–122
relationships, 122–123
Data models
CODASYL (Conference on Data Systems
Languages), 754–755
column-oriented, 756
DBMS, 754–755, 756
definition, 754
denormalization, 163
hierarchical, 754–755
network, 754–755
NoSQL system, 756
object-oriented, 754–755
operations, 754
relational, 754–755
relations, 755
structure, 754
Data page layouts
allocation pages, 589
allocation units, 589
bitmaps, 589
data record layouts, 590
data rows, 588–589
header information, 592
index key values, 592
index page layouts, 592–594
offset and adjust tables, 592
offset tables, 588–590
overview, 588–589
page header, 588–589
page pointer, 592
row data, 590
row header, 590
row length, 592
sample, 589
space page map, 589
table size, calculating, 591–592
transaction logs, 594–595
Data resource management (DRM), 40–42
Data retention
DBA source materials, rule of thumb, 736–737
disaster planning backup, 571
Data sets. See Files and data sets.
Data spaces, database design, 148
Data types
attributes, 116
converting, while loading data, 616
semantic data integrity, 417–418
862
Index
Data warehouse
administrators, 36–37
analytical versus transaction processing,
638–640
availability, 270
data mining, 639
definition, 637–638
design, 641–644
dimensions, 639
DSS (decision support systems), 639
facts, 639
Information Center, 640
metadata, 688
OLAP (online analytical processing), 639
OLAP versus OLTP, 640
tools for, 721–724
Data warehouse, administering
backup and recovery, 656–657
data cleansing, 645–649
data compression, 644
data content, 654
data freshness, 654
data integrity problems, 646
data latency, 654
data movement, 644–645
data quality issues, 648
data usage, 655
data warehouse design, 641–644
denormalization, 643
financial chargeback, 655–656
focus on technology, 641
identifying unused data, 655
meeting business requirements, 657
metadata, 654
operational problems, 648–649
overview, 640–641
purging data, 655
scalability, 649
size issues, 649
snowflake schema, 643
standardizing default values, 647
star schema, 641–643
Data warehouse, performance
automatic summary tables, 652–653
data management, 650
extract performance, 650
indexes, 651
materialized query tables, 652–653
materialized views, 653
monitoring, 652
perspectives on, 650
query performance, 650
server performance, 650
The Data Warehousing Information Center, 783
The Data Warehousing Institute, 783
Database administration. See also DBA (database
administrator).
importance of, 3–4
management discipline, 9–14
Database administration tasks. See also specific
tasks.
availability, 24
backup and recovery, 26–27
data integrity, 27–29
database design, 21–22
governance and regulatory compliance, 26
jack-of-all-trades, 29–31
performance monitoring and tuning, 22–23
security and authorization, 24–25
Database administrator (DBA). See DBA (database
administrator).
Database applications, designing. See also Design
review; SQL (Structured Query Language);
Transactions.
ADO.NET, 194–195
application infrastructure, 193–194
hardware environment, 193–194
issues, 186
J2EE (Java 2 Enterprise Edition), 195–196, 198
Java program types, 196–197
.NET framework, 194–195, 198
overview, 185–186
Ruby on Rails, 198
software environment, 193–194
Database architects, DBAs as, 32–33
Database connectivity. See also Client/server
computing; Internet; Network traffic; Web
services.
application servers, 664
business issues, 662
client/server computing, 663–666
database servers, 664
downsizing, 662
file servers, 664
history of, 661–662
print servers, 664
Index
rightsizing, 662
upsizing, 662
Database Definition on Demand, 289–290
Database design. See also Indexes; Views.
compression, 149–150
data spaces, 148
database administration tasks, 21–22
domains, transforming to data types,
143–144
for e-business, 677–680
entities, transforming to tables, 142
filegroups, 149
logical model to physical database, 141–150
overview, 141–142
physical data structure, 147–150
primary keys, 144
raw files, 149
referential constraints, 146–147
referential integrity, 146–147
row size, specifying, 148
storage requirements, 148
tablespaces, 148
temporal requirements, 177–180
Database design, columns
constraints, 144
fixed-length, 144
identity property, 145
nullability, specifying, 144
ordering, 146
transforming attributes to, 142–143
unique identifiers for, 145
variable length, 144
Database drivers, 672–674
Database environments. See also specific
environments.
education, 101
integration testing, 101
multiplatform issues, 42–43
production versus test, 44–46
quality assurance testing, 101
unit testing, 101
user acceptance testing, 101
Database files, Oracle, 325
Database gateways, 671–672
Database ID. See Users, names.
Database logs
active, 529
archiving, 77–78, 339, 529
863
backing up, 529, 530
bulk-logged recovery, 340
configuring, 338–339, 340
DBMS, 758
definition, 336
disabling, 341
disabling while loading data, 617
disaster planning, backup, 570–571
filling up, 339
full recovery, 340
log archival process, 529
log off-loading, 339
log-based auditing, 493–495
"out of space" conditions, 339–341
placement for optimizing performance, 363
during recovery, 338, 340
recovery models, 340
selecting candidates for, 339–341
simple recovery, 340
system checkpoints, 337
system performance, 336–341
transaction logs, 336
types of information on, 337
write-ahead, 337
Database management system (DBMS). See DBMS
(database management system).
Database performance. See also Optimizing database performance; Reorganizing databases;
SQL tuning.
80/20 (Pareto) rule, 302
versus availability, 267
common problems, 302–304
contention, 301
cost, across the ADLC, 307
definition, 23, 300–302
diagnosing, 302–304
estimating, 307–308
guidelines, 315–316
historical trends, 308
main factors, 301–302
overview, 299–302
resources, 301
SLM (service-level management), 308–311
throughput, 301
tools for, 711
tracker tables, 308
tuning SQL, 303–304
workload, 301
864
Index
Database performance, managing
analysis, 305
components of, 304–306
definition, 304–306
versus monitoring, 304–306
overview, 304–306
reactive versus proactive, 306
Database performance, monitoring
contention, 23
database administration tasks, 22–23
factors affecting, 22–23
resources, 22
throughput, 22
tools for, 313
workload, 22
Database performance, tuning
application, 312
caching, 314
capacity planning, 313
compression, 314
contention, 23
database, 312
database administration tasks, 22–23
estimation, 313
factors affecting, 22–23
monitoring, 313
reorganizing databases, 314
resources, 22
sorting, 314
SQL analysis and tuning, 313
system, 311
throughput, 22
tools for, 313–315
workload, 22
Database servers
definition, 664
hosting, 675
location, upgrading, 88
Database Site portal, 781
Database Trends and Applications, 779
Database views. See Views.
Database wire drivers, 674
Database writer (DBWR) process, 326
Database-coupled application logic, 46–50
Databases
architecture for availability, 296
change management. See Change management.
checking for data integrity, 413
comparison, tools for, 703–704
DBA staffing requirements, 37
versus DBMS, 7–8
definition, 7, 753–754
dropping, 250–252
links, 94
logic, managing, 46
maintenance, authorization, 467
management systems, 664–666
object privileges, 459
objects, backing up, 523–524
Oracle, 325
structures, comparing, 257–258
tools for. See Tools.
users, security, 455–456
DataBee, 771
Datanamic, 771
DB2 (IBM)
blogs, 780
IDUG (International DB2 User Group), 740, 783
nonstandard database objects, 94
vendor contact, 63
Web site, 778
DB2 Catalog. See System catalog.
DB2 Data Sharing, 295
DB2 EDM pools, 335
DB2 HADR (high-availability disaster recovery), 285
DBA (database administrator). See also Database
administration.
authorization, 467
versus DA, 15–18, 19, 21
a day in the life of, 12–14
demand for, 4
description, 1–3
job scope, defining, 42–43
jobs. See Careers in DBA.
multiplatform issues, 42–43
reporting structures, 40–42
responsibilities, 12, 786–788
versus SA, 21
skill and knowledge requirements, 788–790
staffing, 37–40
standards and procedures, 98–99
tools for. See Tools, for DBAs.
typical responsibilities, 786–788
workload, 6, 12–14
Index
DBA (database administrator), rules of thumb
accessibility to coworkers, 745
analysis, 741–742
automation, 737–739
being prepared, 743
calm in the face of adversity, 742–743
documenting your work, 735–736
effective use of resources, 745–746
focus, 741–742
investing in professional advancement, 747–748
retaining source materials, 736–737
sharing knowledge, 739–741
simplification, 741–742
technical education, 746–747
Twitter, as a resource, 741
understanding your business, 743–745
user group associations, 740
DBA (database administrator), types of
application, 34–35
data modeler, 33
data warehouse administrator, 36–37
database analysts, 33
database architects, 32–33
performance analysts, 36
system, 31–32
task-oriented, 36
technical focus versus business, 31–32
DBA Direct, 779
DBAjobs.com, 782
dBase, 767
DBCC utility, options, 412–414
DBE Software, 771
DBI Software, 771
dbMaestro, 771
DBMS (database management system)
architectures, 68–71
atomicity, 758
availability problems, 279
buying. See Vendors, DBMS.
clustering. See Clustering.
concurrency control, 758. See also Locking.
data abstraction levels, 757
data access, 758–759
data independence, 757
data integrity, 758–759
data models, 754–755, 756
data security, 758
865
versus database, 7–8
database logging, 758
definition, 8, 753–754
departmental architecture, 70
durability, 758
enterprise architecture, 69
mobile architecture, 70
organizational strategy. See Strategies for DBMS.
personal architecture, 70
proliferation, 73
upgrading, 87–88
vendors. See Vendors, DBMS.
DBWR (database writer) process, 326
DCL (Data Control Language), 456–457
DDL (Data Definition Language), 177, 250–252
Deadlock detection, 341
Deadlocks, 214–215, 342
Debugging, tools for, 726
Decentralized user presentation model, 668
Decision support, availability, 268–270
Decision support systems (DSS), 639
Defragmenting indexes, 413
DELETE privileges, 458–459
DELETE rule, 435–436
DELETE statements
modifying temporal data, 180
in triggers, 429
DELETE trigger, 438–441
Deleting objects. See also DROP statements.
columns, 251
purging data, data warehouses, 655
purging databases, versus archiving, 501
rows, 435–436
Denormalization
benefits, evaluating, 175
combined tables, 168
data warehouse, 643
derivable data, 170–171
description, 160–161
evaluating the need for, 161–162, 174–175
hierarchies, 171–173
identifying candidates for, 162–163
Internet databases, 680
issues, 161–162
logical data models, 163
mirror tables, 165
optimizing database performance, 355–356
866
Index
Denormalization (continued )
overview, 161–163
physical implementation requirements, 173
prejoined tables, 164
redundant data, 168–169
repeating groups, 169–170
report tables, 164–165
speed tables, 172–173
split tables, 165–166
splitting text columns, 166–168
types of, 174
Density, relational optimization, 377
Departmental DBMS architectures, 70
Deprecated features, 85n.7
Derivable data, 170–171, 356
Derived data, storing versus calculating, 170–171
DES (Data Encryption Standard), 472
Design review
guidelines, 102, 228–229
output, 239–240
overview, 227–228
purpose of, 228
Design review, participants
knowledge and skills required, 232
leader of, 229–230
mediator, 230–231
mentorship and knowledge transfer, 240–241
recommended personnel, 231
remote staff, 232
scribe, 230
Design review, types of
in the ADLC, 234
code, 238
conceptual, 233–235
logical, 235
organizational, 237
overview, 233
physical, 236
post-implementation, 239
pre-implementation, 239
Designing
applications. See Database applications,
designing.
databases. See Database design.
Determinant, 135
Devices, naming conventions, 364
Diagramming entity relationships. See E/R (entity
relationship diagram).
Differential backup, 521
Dimensions, data warehouse, 639
Direct index lookup, 383
Dirty read, 216–217
DISABLE option, 477
Disabling
database logs, 341
passwords, 453
Disaster, definition, 559–560
Disaster planning. See also Backup; Recovery.
business-critical applications, 562
critical applications, 562–563
criticality of data, ranking, 562–563
lengthy outages, 568
need for, 559–563
noncritical applications, 563
prevention, 575–576
required applications, 563
very critical applications, 562
Web sites about, 576
Disaster planning, backup
compression, 575
data latency, 574
data retention, 571
database logs, 570–571
encryption, 575
important files and data, 574–575
indexes, 570
order of recovery, 574
over a WAN (wide-area network), 573
post-recovery image copies, 575
remote mirroring, 573
standby databases, 573
storage management software, 572–573
on tape, 570–571
Disaster planning, recovery
off-site locations, 564
personnel, 569
plan content, 566
recovery site, choosing, 564
rehearsing, 567–569
team members, 569
testing your plan, 567–569, 574
written plans, 564–566
Disaster planning, risk
assessing, 561–563
business service interruption, 561–563
categories of, 561
Index
financial loss, 561–563
legal responsibilities, 561–563
Discovering attributes and entities, 124–125
Disk drives
MTBF (mean time between failures), 580
overview, 580
Disk storage
DBMS requirements, 76–78
SSDs (solid state devices) versus traditional
disks, 323–324
system performance, 322–324
Disks. See also Storage management.
allocation, optimizing database performance,
364
fragmentation, 595
JBOD (just a bunch of disks), 604
mirroring, as a backup/recovery alternative,
556–557
outages, 278
performance improvement, 584–585
raw partitions versus file systems, 586–587
SCSI (small computer system interface), 605
short-stroking, 584–585
size terminology, 582
storage management option, 596
striping, 597
usage spikes, 580
DISTINCT clause, 387
Distributed data
accessing, 630–631
distributed request, 631
distributed unit of work, 631
DRDA (Distributed Relational Database Architecture), 629–630
placement for optimum performance, 363–364
RDA (Remote Database Access), 629–630
remote requests, 630–631
remote unit of work, 630–631
standards, 629–630
two-phase COMMIT, 631
Distributed data management model, 668–669
Distributed databases. See also Bulk data movement; Copying data; Moving data.
autonomy, 626
characteristics of, 626
data placement, 629
definition, 626
environment, setting up, 627–629
867
federated multidatabase schemes, 627
isolation, 626
performance problems, 632–633
system performance, 344
transparency, 626
unfederated multidatabase schemes, 627
usage guidelines, 629
Distributed processing, 666–667
Distributed request, 631
Distributed unit of work, 631
Distributed user presentation model, 667–668
Distributing tasks across a network, 668
Document Type Definition (DTD), 204
Documentation
DBA activities, 735–736
online standards manuals, 727–728
Domains
attributes, 116
transforming to data types, 143–144
Downsizing, and database connectivity, 662
Downtime. See also Availability.
versus availability, 273
cost of, 271–273
DBA staffing requirements, 38
negative publicity, 272
DQS (Data Quality Services) (Microsoft), 415
DRDA (Distributed Relational Database Architecture), 629–630
Drivers
JDBC, 673–674
ODBC, 192, 673
DRM (data resource management), 40–42
DROP statements
cascading DROPs, 251, 701–703
in database change management, 250–252
Dropped database objects, recovering, 552–553
Dropping
database objects, 250–252
tables, 250–252
DSN1COPY utility, 552
DSNZPARM parameter, 80n.4
DSS (decision support systems), 639
DTD (Document Type Definition), 204
Duplicate values, relational optimization, 377
Durability
DBMS, 758
transactions, 206
Dynamic SQL, 201
868
Index
E
Ebbers, Bernard, 485
E-business. See also Internet.
effects on DBAs, 50–51
infrastructure, 52
E-discovery, effects on DBA, 506–507
EDM pools, 335
Education
database environment, 101
recommended courses, 103
E-Government Act, 484–485
80/20 (Pareto) rule, 302
Elephant and blind men, 108
Embarcadero Technologies, 770–771
Embedded SQL, 191–192, 201
ENABLE option, 477
Encoding scheme, specifying, 620
Encryption. See also Data masking and
obfuscation.
data at rest, 472
data in transit, 472
data masking and obfuscation, 497
disaster planning, backup, 575
overview, 470, 472
techniques for, 472
transparent, 473
wallets, 473
End-to-end performance, tools for, 713–714
Enron Corporation, 485
Enterprise data model, 109
Enterprise DBMS architectures, 69
Entities. See also Relationships.
adjectives as, 115
associative, 127
definition, 113
discovering, 124–125
instances, 115
naming conventions, 113
nouns as, 115, 124
transforming to tables, 142
Entity integrity, 416–417
Entity occurrences, 115
Environments, system. See Database
environments.
Epsilon, data breach, 449
E/R (entity relationship diagram)
Bachmann method, 112
cardinality, 112
Chen method, 112
definition, 110
diagramming methods, 111–113
example, 111
Information Engineering method, 112
Martin method, 112
Ross method, 112
Rumbaugh method, 112
UML (Unified Modeling Language), 113
Error correction coding, 599
Estimating
memory requirements, 331–332
performance, 307–308
tools for, 313
ETL (extract, transfer, load), 623–625, 721–723
ETL tool vendors, 773
E-vailability, 676–677
EXCEPT clause, 388
Exclusive locks, 213
EXECUTE privileges, 460
EXPLAIN command, 394–398, 712
Exploiting versus supporting, 91
EXPORT utility, 622–623. See also UNLOAD
utility.
Exporting data
backup/recovery alternative, 534–535
EXPORT utility, 622–623
EXtensible Markup Language (XML), 204
External security, 478–480
Extract performance, 650
F
Fabian Pascal's site, 779
Facts, data warehouse, 639
Fallback planning, 92
"Fast food" mentality, 266
Fat clients, 670
Fault tolerance, 601–602
Federal Rules of Civil Procedure (FRCP), 506–507
Federated multidatabase schemes, 627
Fiber channel, storage management option, 605
File extents, reorganizing databases, 366
File servers, database connectivity, 664
File systems versus raw partitions, 586–587
Filegroups
database design, 149
definition, 94
standards, 94
Index
FileMaker, 767
Files and data sets. See also Storage management.
optimal placement, 584–586
overview, 583–584
placement and allocation, optimizing database
performance, 362–364
temporary database files, 587
Fill factor. See Free space.
Financial chargeback, 655–656
Financial loss, risk of, 561–563
Financial Modernization Act of 1999, 484–485
Firing triggers, 428–429
FISMA (Federal Information Security Management Act), 485
Five-nines availability, 273–274, 292
Fixed-length columns, 144
Fixpacks and maintenance, 480–481
Floating-point data
loading, 616
unloading data, 620
Focus, DBA rule of thumb, 741–742
FORCEPLAN option, 398–399
Forcing access path choices, 398–399
Foreign key perspective, 434–435
Foreign key values, 434–436
Foreign keys, indexes, 151
Forrester Research, 450
Fragmentation
disks, 595
indexes, 595
reorganizing databases, 366
FRCP (Federal Rules of Civil Procedure), 506–507
Free space
changing, 255–256
optimizing database performance, 360–361
FREEPAGE parameter, 360
Full image copy, 521–523
Full recovery, 340, 540
Full-time availability, 270–271
G
Gerstner, Lou, 581
Giga Research Group, 582
GLB (Gramm-Leach-Bliley) Act, 484–485, 491
Governance. See Data governance.
Grandite, 772
GRANT statements, 456–457
869
Granularity
locks, 210–211, 219–220
triggers, 431–432
GROUP BY clause, 388
Groups, authorization, 468
"Guilty until proven innocent," 13
H
Hadoop databases, 766
Hardware
configuration for system performance,
322–324
environment, designing, 193–194
issues, strategies for, 73–74
requirements, installing the DBMS, 76
Hash function, 389, 390
Hash joins, 379
Hashed access, 389–390
Hashing, randomizing, 158
HBase databases, 56, 766
Header information, data page layouts, 592
Headers, data integrity, 411
Health Net Federal Services, 450
Heterogeneous database migration, 534–535
Hibernate, ORM library, 200
Hierarchical data models, 754–755
Hierarchies, 171–173
HIPAA (Health Insurance Portability and
Accountability Act), 484–485, 491
Hit Software, 771
Homonyms, in data modeling, 118
Horizontal restriction, 469
Hostile databases, 678–679
Hosting database servers, 675
Hot backup, 527
Human error, availability problems, 284, 286
100 Year Archive Requirements Survey, 503n
Hybrid joins, 379
I
IBM Corporation
DB2 Web site, 778
DBMS vendor, 63–64, 762, 765
rate of data growth, 581
tool vendor, 772, 773
IBM Data Management, 779
IDC Corporation, 581
870
Index
IDE (integrated development environment),
191–192
Identity property, columns, 145
Identity values, system performance, 344
Idera, 771
IDMS (Cullinet), 765
IDUG (International DB2 User Group), 740, 783
IIUG (International Informix Users Group), 740, 783
ILM (information life cycle management), 606
Image copies
backup guidelines, 519–520
backups, unloading data from, 619
disaster planning, post-recovery, 575
Impact analysis, change management, 245
IMPORT utility, 622–623. See also LOAD utility.
Importing data, 622–623
IMS (IBM), 765
Incremental backup, 521–523
Independent Oracle Users Group (IOUG), 740
Index covering, 386–387
Indexed access, 382–389
Indexes
absence of, 151
avoiding, 354
avoiding sorts, 387–388
backup, 524
based on workload, 152
bitmap, 155–156
b-tree, 154–155. See also Partitioned index;
Reverse key index.
candidate keys, 152
clustering, 159–160
consistency, 29
costs of, 153–154
data warehouse, 651
defragmenting, 413
designing, 150–154
disaster planning, backup, 570
file placement, 584
foreign keys, 151
fragmentation, 595
indexing by object, 152
index-only access, 152
key values, 592
leaf pages, 155
locking, 212
nodes, 155
optimal number per table, 353
optimizing database performance, 352–355
ordered, 157
overloading, 355
page layouts, 592–594
partitioned, 157. See also b-tree index.
primary keys, 151
recovery, 550–551
recreating, 257n
reorganizing, 369–370
reverse key, 156–157. See also b-tree index.
screening, 386
size, calculating, 592–594
sorting, 152
table scans, 151
unused, dropping, 153
Indexing by object, 152
Index-only access, 152, 386–387
Informatica, 773
Information, definition, 687
Information Builders, 773
Information Center, 640
Information Engineering, E/R method, 112
Information life cycle management (ILM), 606
Information Management, 779
Information Schema. See System catalog.
Informix, 763
IIUG (International Informix Users Group),
740, 783
vendor contact, 64
Web site, 778
InfoTel Corporation, 771
Ingres, 763–764
INIT.ORA, 80n.4
Inner table, 379
INSERT privileges, 458–459
INSERT rule, 434–436
INSERT statements
modifying temporal data, 180
recording in the transaction log, 341
in triggers, 429
INSERT trigger, 438–441
Installing the DBMS. See also Configuring the
DBMS; Upgrading the DBMS.
connecting to infrastructure software, 81
hardware requirements, 76
memory requirements, 78–79
Index
in multiple environments, 82
performance tuning. See System performance,
DBMS installation and configuration.
prerequisites, 75–76
storage requirements, 76–78
verifying the install, 81
Instance failure, backup, 516–517, 533, 550
Instances
entities, 115
Oracle databases, 325
INSTEAD OF trigger, 432
Integrated development environment (IDE),
191–192
Integrated metadata sources, 690
Integration testing, 101
Integrity. See Data integrity; RI (referential
integrity).
Intelligence, change management, 245
Intent locks, 213
Interconnected databases, 676–680
Interleaving data. See also Clustering.
optimizing database performance, 360
performance design, 160
International DB2 User Group (IDUG), 740, 783
International Informix Users Group (IIUG), 740,
783
International issues, Internet databases, 679
International Oracle Users Group, 783
International Sybase User Group (ISUG), 740, 783
Internet, and e-business
effect on DBAs, 50–52
infrastructure, 52
Internet, database connectivity. See also Web
services.
availability, 676–677
denormalization, 680
designing for e-business, 677–680
effect on DBA duties, 676–680
e-vailability, 676–677
hostile databases, 678–679
hosting database servers, 675
interconnected databases, 676–680
international issues, 679
Internet time, 677
key design, 679
normalization, 679
RAD (rapid application development), 677
871
Internet resources
blogs, 780–781
database portals, 781–782
industry standards, 782
jobs, 782
mailing lists, 776–778
Usenet newsgroups, 775–776
Internet resources, Web sites
consultants, 779–780
magazines, 778–779
Mullins, Craig, 780
user group associations, 740
vendors, 778
Internet time, 266, 677
INTERSECT clause, 388
Invasive performance tools, 710
I/O parallelism, 390–391
IOUG (Independent Oracle Users Group), 740
ISO Web site, 782
Isolation
distributed databases, 626
levels, 216–218
transactions, 206
ISQL, 81n.5
ISUG (International Sybase User Group), 740, 783
IT complexity, and availability, 271
IT Governance Institute, 509
J
J2EE (Java 2 Enterprise Edition), 195–196, 198
Jack-of-all-trades, 29–31
Jacobson, Ivar, 113
Java
applets, 196–197
applications, 196–197
choosing a program type, 196–197
Hibernate, ORM library, 200
LINQ (Language Integration Query), 200
NHibernate, ORM library, 200
program types, 196–197
servlets, 196–197
JBOD (just a bunch of disks), 604
JDBC (Java Database Connectivity)
bridge architecture drivers, 673
client-based drivers, 673
database wire drivers, 674
drivers, 673–674
872
Index
JDBC (Java Database Connectivity) (continued )
network protocol architecture drivers,
673–674
overview, 192–193
Pure Java drivers, 673–674
Type 1 drivers, 673
Type 2 drivers, 673
Type 3 drivers, 673–674
Type 4 drivers, 673
Job scheduling, security, 479
Jobs in DBA. See Careers in DBA.
Join order, 381
Joining tables
hash join, 379
hybrid join, 379
inner table, 379
join order, 381
merge-scan join, 379–380
nested-loop join, 379–380
outer table, 379
qualifying rows, 380
relational optimization, 379–381
Joins, SQL, 189
K
Kernel memory usage, displaying, 413
Keys
candidate, 115, 121
description, 120
designing for Internet connectivity, 679
foreign, 121–122
primary, 121
Knowledge, definition, 687
Kozlowski, Dennis, 485
L
Lay, Ken, 485
LBAC (label-based access control), 463–465
Leader, design review, 229–230
Leaf distance, reorganizing databases, 370
Leaf pages, 155
Legal responsibilities, risks, 561–563
LGWR (log writer) process, 326
Life cycle
ADLC (application development life cycle),
9–10, 12
data, 499–500
LIKE logical operator, 403–404
LIMIT parameter, 620–621
LINQ (Language Integration Query), 200
List servers, 777
Listservs. See Mailing lists.
Load balancing, 293
LOAD parameters, 620
LOAD utility, 614–618, 621–622. See also IMPORT
utility.
Loading data. See also Unloading data.
for application test beds, 621–622
converting data types, 616
data integrity problems, 615
describing the input file, 615
disabling logging, 617
efficiency, 617–618
enforcing constraints, 615
firing triggers, 615
floating-point data, 616
LOAD utility, 614–618, 621–622
nulls, 616
Lock duration
acquire/release specification, 218
definition, 215
isolation level, 216–218
SKIP LOCKED DATA parameter, 219
skipping locked rows, 219
Lock escalation, 219–220
Lock suspensions, 341
Locking
COMMITTED READ isolation, 216–217
cursor stability, 216–217
deadlocks, 214–215
description, 210
dirty read, 216–217
exclusive locks, 213
granularity, 210–211, 219–220
index entries, 212
intent locks, 213
levels. See Granularity.
minimizing problems, 220
passwords, 453
phantoms, 218
read locks, 212–213
REPEATABLE READ isolation, 217
SERIALIZABLE isolation, 218
shared locks, 212–213
Index
system performance, 341–342
time outs, 213–214
types of locks, 212–213
UNCOMMITTED READ isolation, 216–217
update locks, 213
write locks, 212–213
Log writer (LGWR) process, 326
Logging. See Database logs.
Logical backups, 534–535
Logical data independence, 757
Logical data modeling, 125–128
Logical design review, 235
Logical models, converting to a physical database,
141–150
Logic-oriented security, 470
Logins
administration, rules of thumb, 453, 455
definition, 455–456
limiting, 455
required information, 452–453
Loss of
data, 282–283
data center, 274–275
database objects, 281–282
entire database, 277
Lotus, 767
LPARS (Logical PARtitions), 295n
M
Magazines, Web sites, 778–779
Mailing lists, 776–778
Main-memory database management systems
(MMDBMSs), 596
Maintenance
outages, availability problems, 286–287
patches for Oracle databases, 480–481
scheduling for availability, 288–289
window, availability, 268
Manageability, availability, 267
Mapping physical files to database tables,
350–352
Martin E/R method, 112
Masking data. See Data masking and
obfuscation.
Master Data Services. See SQL Server.
Matching index scan, 383–385
Materialized query tables, 652–653
Materialized views, 653
Mean time between failures (MTBF)
availability, 273–274
disk drives, 580
Media failure, backup, 517, 550
Mediator, design review, 230–231
Memory, requirements
buffer pools, 78–79
data cache, 78–79
installing the DBMS, 78–79
program cache, 79
Memory, system performance
caches, 328–330
consumption sources, 330–331
data cache, 329–330, 332–333
data integrity, 413–414
database log cache, 330
DB2 EDM pools, 335
estimating sufficient, 331–332
Internet structure cache, 330
procedure cache, 329–330, 335
sort cache, 330
MEMUSAGE option, 413–414
Merge-scan joins, 379–380
Message queuing software, 624–625
Messaging software, 624–625
Metadata
active sources, 690
business metadata, 689
data, definition, 686
data dictionaries, 695–696
data stewardship, 688
data warehouse, 654
data warehousing, 688
definition, 16, 488
examples, 16–17
information, definition, 687
integrated sources, 690
knowledge, definition, 687
nonsubvertible sources, 690
overview, 685–686
repositories, 691–695
sources for, 690
strategy for, 687–688
system catalog, 689–691
technology metadata, 689
types of, 689–691
873
874
Index
Microsoft Corporation
DBMS vendor, 63, 762, 767
tool vendor, 772
Middleware, 192–193
Migration. See Upgrading the DBMS.
Mirror tables, 356
Mirroring, 597
MMDBMSs (main-memory database management
systems), 596
Mobile DBMS architectures, 70
Mobile platforms, effect on DBAs, 53–55
ModelRight, 772
mongoDB, 56, 766
Monitoring
data warehouse performance, 652
SP_MONITOR procedure, 345–346
system-level performance, 345–346
Monitoring, database performance
contention, 23
database administration tasks, 22–23
factors affecting, 22–23
optimization, 23
resources, 22
throughput, 22
tools for, 313
workload, 22
Monotonic page splits, 358–359
Moving data. See also EXPORT utility; IMPORT
utility; Loading data; Unloading data.
backup, 535
bulk movement, 623–625
data warehouses, 644–645
EXPORT utility, 622–623
IMPORT utility, 622–623
to multiple databases. See Distributed databases.
tool vendors, 773
MTBF (mean time between failures)
availability, 273–274
disk drives, 580
Mullins, Craig, Web site, 780
Multi-index access, 387
Multiple platforms, strategies for, 61–62
Multitier implementation, 669–670
MySQL, 64, 765
N
Naming conventions
attributes, 116–119
databases, 93–96
devices, 364
entities, 113
NAS (network-attached storage), 605, 606
Nested triggers, 343–344, 429
Nested-loop joins, 379–380
.NET framework, 194–195, 198
NetIQ, 771
Network data models, 754–755
Network protocol architecture drivers, 673–674
Network traffic
availability problems, 275
connection pooling, 674
database drivers, 672–674
database gateways, 671–672
performance problems, 670–671
sniffing, 494–495
Newsgroups, 775–776
NHibernate, ORM library, 200
99.999% availability, 273–274
NIST Web site, 782
Nodes, 155
Noncritical applications, 563
Noninvasive auditing methods, 494
Nonmatching index scan, 385
Nonstandard database objects, 94
Nonsubvertible metadata sources, 690
Normal forms
1NF (first normal form), 129
2NF (second normal form), 129, 131, 132
3NF (third normal form), 132–133
4NF (fourth normal form), 134
5NF (fifth normal form), 134
atomic, 129
BCNF (Boyce Codd normal form), 134
examples, 130–131
Normal page splits, 358–359
Normalization
definition, 128
goals of, 128
Internet databases, 679
mapping logical to physical, 135
Normalized data model, 133–134
NoSQL
for availability, 296
data models, 756
DBMS vendors, 765–766
effect on DBAs, 55–56
Index
Nouns as
attributes, 124
entities, 115, 124
Nullability, specifying, 144
Nulling out, data masking, 498
Nulls
attributes, 119–120
check constraints, 423–426
loading data, 616
Number and date variance, data masking, 497
O
Obfuscation. See Data masking and obfuscation.
Object definitions, backup, 536–537
Object Management Group, 783
Object migration, tools for, 704–705
Object orientation
data models, 754–755
DBMS vendors, 766
ORM (object-relational mapping), 200
relational databases, 199–200
SQL, 199–200
SQL (Structured Query Language), 199–200
Object Store (Progress Software), 766
Object-relational mapping (ORM), 200
Obsessive-Compulsive Data Quality blog, 781
ODBC (Object Database Connectivity)
callable routines, 192
definition, 192
drivers, 192, 673
overview, 192–193
Off-loading logs, 339, 529
Offset tables, 588–590, 592
Off-site disaster recovery, 547
Off-site locations, disaster planning, 564
OLAP (online analytical processing), 639, 640
The OLAP Council, 783
OLAP tool vendors, 773
OLE DB, 193
100 Year Archive Requirements Survey, 503n
Online database reorganization, 288–289
Online resources. See Internet resources.
Ontos, 766
Open database objects, system performance, 336
The Open Group, 783
Open-source software
belief system, 764–765
choosing, 64
875
DBMS vendors, 764
definition, 764
vendors, 764–765
Operating system failure, availability problems, 279
Operating system support, strategies for, 65
Operational support, standards, 102
Operations, data models, 754
Operations control, authorization, 467
Optimizer, 374
Optimizing database performance. See also Database performance; Relational optimization;
Reorganizing databases.
cost-based versus rule-based, 344
database performance, managing, 305
performance monitoring and tuning, 23
split tables, 356
Optimizing database performance, techniques for
block size, 364–365
clustering, 356–358
combined tables, 356
compression, 361–362
database log placement, 363
denormalizing tables, 355–356
derivable data, 356
disk allocation, 364
distributed data placement, 363–364
file placement and allocation, 362–364
free space, 360–361
indexing, 352–355
interleaving data, 360. See also Clustering.
mapping physical files to database tables,
350–352
mirror tables, 356
monotonic page splits, 358–359
normal page splits, 358–359
overview, 349–350
page size, 364–365
page splitting, 358–359
parallelism, 351
partitioning, 350–352
physical denormalization, 356
prejoined tables, 355
raw partition versus file system, 351–352
redundant data, 356
repeating groups, 356
report tables, 355
speed tables, 356
split tables, 356
876
Index
OR logical operator, 403
Oracle Corporation
DBMS vendor, 63, 762
nonstandard database objects, 94
vendor contact, 63, 772
Oracle Corporation (Hyperion), 773
Oracle Magazine, 779
Oracle program
blogs, 780
IOUG (Independent Oracle Users Group), 740
Web site, 778
Oracle program, architecture
background processes, 326
CKPT (checkpoint) process, 326
config.ora file, 325
control files, 325
data files, 325
database files, 325
databases, 325
DBWR (database writer) process, 326
file categories, 325
instances, 325
LGWR (log writer) process, 326
Oracle processes, 326
overview, 325–327
parameter files, 325
PGA (program global area), 326
physical structures, 325
PMON (process monitor) process, 326
processes, 326
RECO (recover) process, 326
redo log buffer, 326
redo log files, 325
server processes, 326
SGA (system global area), 326
SMON (system monitor) process, 326
sort area, 326
user processes, 326
Oracle transportable tablespaces, 625
ORDER BY clause, 388
Ordered indexes, 157
Ordering columns, 146
Organization type, effect on DBMS strategy, 65
Organizational design review, 237
ORM (object-relational mapping), 200
"Out of space" log conditions, 339–341
Outer table, 379
Overloading indexes, 355
P
Page header
corruption, 411
data page layouts, 588–589
Page pointer, data page layouts, 592
Page size, optimizing database performance,
364–365
Page splits
optimizing database performance, 358–359
reorganizing databases, 366
Pages, recovering, 553
Paradox, 767
Parallel access, 390–391
Parallelism
CPU, 391
I/O, 390–391
optimizing database performance, 351
system, 391
Parameter files, Oracle, 325
Parent tables, 433–435
Pareto (80/20) rule, 302
Parity bits, 597
Parsing database logs, 493–495
Partial recovery, 542–543
Partition scans, 381–382
Partitioned index, 157. See also b-tree index.
Partitioning, 350–352
Passwords. See also Security.
changing, 453
creating, 454
definition, 452
disabling, 453
embedding in code, 479
guidelines for, 454
limiting, 455
locking, 453
Patches
critical updates, 480–481
for Oracle databases, 480–481
security alerts, 480–481
PCI (Payment Card Industry) DSS (Data Security
Standard), 485, 491
PCTFREE parameter, 360
Performance. See also Applications, performance;
Database performance; System performance.
benchmarks, 65–66
DBA staffing requirements, 38
gains from upgrading the DBMS, 85
Index
management, tools for, 708–714
monitoring, tools for, 709–710
RAID levels, 603
Performance analysts, DBAs as, 36
Performance problems
client/server computing, 670–674
distributed databases, 632–633
network traffic, 670–671
Permissions. See Privileges.
Personal computing, effect on DBAs, 53–55
Personal DBMS architectures, 70
Personnel, disaster planning, 569
PGA (program global area), 326
Phantoms, 218
Physical data
dependence, 376
independence, 757
modeling, 125–128
Physical denormalization, 356
Physical design review, 236
PII (Personally Identifiable Information), 497
PIT (point-in-time) recovery, 542–543, 545
Planning
change management, 245
for disaster. See Disaster planning.
outages, 286–287
SQL, 201
storage capacity, 608–609
Plans (DB2), 94
PLAN_TABLE, 395–398
PMON (process monitor) process, 326
Poet, 766
Pointer consistency, 29
Pointers for very large objects, 410–411
Point-in-time recovery, 27
Ponemon Institute, 450
PostgreSQL, 765
Post-implementation design review, 239
Powersoft, 772
Pre-implementation design review, 239
Prejoined tables, 355
Prepositional phrases, as attributes, 124
Presentation logic, 664–666
Primary key constraints, 416–417
Primary key perspective, 435–436
Primary keys
database design, 144
indexes, 151
877
Print servers, database connectivity, 664
Privacy. See Data, privacy.
Privacy Rights Clearinghouse, 449–450
Privileged users, auditing, 495–496
Privileges. See also Authority; Authorization;
Security.
monitoring and reporting, 465
types of, 457–458
Privileges, granting
centralized administration, 457
database object privileges, 459
DCL (Data Control Language), 456–457
decentralized administration, 457
overview, 456–457
procedure privileges, 460
program privileges, 460
to PUBLIC authority, 460–461
system privileges, 459–460
table privileges, 458–459
Privileges, revoking
cascading REVOKEs, 462, 468
chronology and REVOKEs, 462–463
overview, 461
Proactive performance, 306
Proactivity, change management, 245
Procedural DBAs
duties of, 49
effect on DBAs, 46–50
managing database logic, 46
procedural database objects, 48, 49
role of, 49–50
stored procedures, 47, 48–50
triggers, 47, 48–50
UDFs (user-defined functions), 47, 48–50
Procedure privileges, 460
Procedures (programmatic). See Triggers.
Procedures (standards). See Standards and
procedures.
Process monitor (PMON) process, 326
Processes, Oracle, 326
Professional advancement, DBA rule of thumb,
747–748
Professional Association for SQL Server, 740,
783
Professional certification. See Certification.
Profiling data, 489
Program global area (PGA), 326
Program privileges, 460
878
Index
Programming and development, tools for, 724–726
Progress Software, 766
Propagation, 623–624, 722
PUBLIC authority, 460–461
Pure Java drivers, 673–674
Purging data, data warehouse, 655
Purging databases, versus archiving, 501
The Pythian Group, 779, 781
Q
Qualifying rows, 380
Quality assurance testing, 101
Quality of data. See Data, quality; Data integrity.
Queries
analysis, 378–379
performance, 650
tools for, 723–724
XML data, 203–205
Query rewrite, 392–393
Quest Software, 771
Quiesce point, 528
QUIESCE utility, 528
R
RAC (Real Application Clusters), 294
RAD (rapid application development), 677
RAID (redundant array of independent disks)
definition, 597
disk striping, 597
error correction coding, 599
fault tolerance, 601–602
mirroring, 597
parity bits, 597
storage type, choosing, 603–604
striping, 597
RAID levels
performance, 603
RAID-0, 597–598
RAID-0+1, 602
RAID-1, 598
RAID-2, 599
RAID-3, 599
RAID-4, 600
RAID-5, 600–601
RAID-6, 601
RAID-10, 601
RAID-50, 602
Raw files, database design, 149
Raw partitions versus file systems, 351–352,
586–587
RDA (Remote Database Access), 629–630
Read efficiency, 333–335
Read locks, 212–213
RECO (recover) process, 326
Recover to current, 26–27
RECOVER utility, 553–554
Recoverability
availability, 267
goals of, 509–510
Recover-to-current recovery, 541
Recovery. See also Backup; Disaster planning.
availability problems, 284
basic steps, 540–541
broken blocks or pages, 553
bulk-logged, 540
COBIT, 509–510
common reasons for, 548
data warehouse, 656–657
database administration tasks, 26–27
database logs, 338, 340
designing for, 533–534
dropped database objects, 552–553
duration of, 518, 549
full, 540
importance of, 515–516
indexes, 550–551
models, 340
objects, 534
optimum strategy, 547–549
options, determining, 538–539
overview, 537–538
planning for, 551
point-in-time recovery, 27
recover to current, 26–27
RECOVER utility, 553–554
regulatory compliance, 508
RMAN (Recovery Manager), 525–526
rows, 534
simple, 540
SQL Server models, 540
test databases, populating, 553–554
testing your plan, 551
tools for, 714–715
transaction recovery, 27
types of, 26–27
UNLOAD utility, 553–554
Index
Recovery, alternatives to
disk mirroring, 556–557
redundant data, 555–556
replication, 555–556
snapshot replication, 555–556
standby databases, 554–555
symmetric replication, 555–556
Recovery, types of
matching to failure type, 549
off-site disaster, 547
partial, 542–543
PIT (point-in-time), 542–543, 545
recover to current, 541
to a recovery point, 543–544
REDO, 545–547
selecting, 548
transaction, 544–545
UNDO, 545–546
Recovery Manager (RMAN), 525–526
Red Gate Software, 771
Redman, Thomas C., 489
Redo log buffer, 326
Redo log files, 325
REDO recovery, 545–547
Redundant array of independent disks (RAID).
See RAID (redundant array of independent
disks).
Redundant data
backup/recovery alternative, 555–556
database design, 168–169
optimizing database performance, 356
Reference customers, 68
Referential constraints, 28, 146–147, 433
Referential integrity (RI). See RI (referential
integrity).
Regulatory compliance. See also Data governance; specific regulations.
best practices, 509
change management, 261–262
COBIT, 509–510
a collaborative approach to, 486–488
costs of compliance, 485
costs of non-compliance, 488
DBA tasks, 26, 487–488
importance to DBAs, 487–488
overview, 483–485
prosecution for non-compliance, 485
recoverability, 509–510
REINDEX option, 413
Relational Architects, 771
Relational closure, 189–191
Relational data models, 754–755
Relational databases
application design issues, 373–374
object orientation, 199–200
Relational nulls, 423–426
Relational optimization
CPU costs, 376
database statistics, 376–378
definition, 375
density, 377
design issues, 374
duplicate values, 377
I/O costs, 376
joining tables, 379–381
optimizer, 374
physical data dependence, 376
query analysis, 378–379
query rewrite, 392–393
rule-based optimization, 393–394
view access, 391–392
view materialization, 392
view merging, 392
Relational optimization, access path choices
absolute positioning, 383–385
avoiding sorts, 387–388
CPU parallelism, 391
direct index lookup, 383
forcing, 398–399
hashed access, 389–390
index covering, 386–387
index screening, 386
indexed access, 382–389
index-only access, 386–387
I/O parallelism, 390–391
matching index scan, 383–385
multi-index access, 387
nonmatching index scan, 385
parallel access, 390–391
partition scans, 381–382
relative positioning, 385
reviewing, 394–398
system parallelism, 391
table scans, 381–382
tablespace scans, 381–382
Relations, data models, 755
879
880
Index
Relationships, 122–123
Relationships between entities
cardinality, 122–123
definition, 122
degree. See Cardinality.
description, 122
discovering, 124–125
optionality, 123
verbs as, 124
Relative positioning, 385
Release schedules, effect on DBMS strategy, 68
Release upgrades, backup, 534
Releases versus versions, 82–87
Reliability, availability, 267
Remote Database Access (RDA), 629–630
Remote mirroring, disaster planning, 573
Remote requests, 630–631
Remote unit of work, 630–631
Removing. See Deleting.
REORG, 288–289
REORG utility, 368–369
Reorganizing databases. See also Database
performance; Optimizing database
performance.
automation, 371
causes of disorganization, 365–369
cluster ratios, 369
determining the need for, 369
disorganized tablespace, 367–368
ensuring availability, 288–289
file extents, 366
fragmentation, 366
gathering statistics, 370
indexes, 369–370
leaf distance, 370
manually, 368–369
online, 288–289
page splits, 366
row chaining, 366
row migration, 366
tools for, 314
unclustered data, 366
utilities for, 368–369
REPAIR utility (DB2), 411–412
REPEATABLE READ isolation, 217
Repeating groups
denormalization, 169–170
optimizing database performance, 356
Replication
backup/recovery alternative, 555–556
bulk data movement, 623–624
tools, 722
Report tables, 355
Reporting, tools for, 723–724
Repositories, 691–695
Repository Manager (IBM), 695
Repository tools, vendors, 772–773
Required applications, 563
Resources
effective use of, DBA rule of thumb, 745–746
performance factor, 301
performance monitoring and tuning, 22
Response time, 266
Responsive Systems, 771
REST (representational state transfer), 681
Reverse key index, 156–157
Reviewing access path choices, 394–398
REVOKE statements, 456–457, 461
RI (referential integrity)
versus check constraints, 441–442
child tables, 433–434
DBMS support for, 438
definition, 433
deleting rows, 435–436
foreign key perspective, 434–435
foreign key values, 434–436
overview, 146–147, 433–434
parent tables, 433–435
primary key perspective, 435–436
versus program logic, 441–442
referential constraints, 433
relationships, setting up, 436–437
rules, 434–436
rules of thumb, 442–444
self-referencing constraints, 437
system-managed, 441
tools for, 705
with triggers, 438–441
user-managed, 441
Riak, 56
Richard Foote's Oracle Blog, 780
Rigas, John, 485
Rigas, Tony, 485
Rightsizing, and database connectivity, 662
Risk, disaster planning
assessing, 561–563
Index
business service interruption, 561–563
categories of, 561
financial loss, 561–563
legal responsibilities, 561–563
Risk management
tools for, 716–721
upgrading the DBMS, 84–86
RMAN (Recovery Manager), 525–526
Rocket Software, 771
Roles and responsibilities
authorization by, 466, 468
standards, 96–98, 97
Ross E/R method, 112
Row-level triggers, 432
Rows
chaining, 366
data page layouts, 590
deleting, 435–436
headers, data page layouts, 590
length, data page layouts, 592
migration, 366
recovering, 534
size, specifying, 148
Ruby on Rails, 198
Rule-based optimization
versus cost-based, 344
relational optimization, 393–394
Rules. See also specific rules.
check constraints, 424
definition, 94
referential integrity, 434–436
standards, 94
Rumbaugh, James, 113
Rumbaugh E/R method, 112
RUNSTATS utility, 377–378
S
SA (system administration), 20, 21
Salaries of DBAs, 4–6
SAN (storage area network), 278, 604–605, 606
SAP (Business Objects), 773
Sarbanes-Oxley (SOX) Act, 483, 485, 491
SAS Institute, 773
Scalability
data warehouse, 649
effect on DBMS strategy, 66
Scribe, design review, 230
Scripts, change management, 262
881
SCSI (small computer system interface), 605
SearchDataManagement portal, 781
SearchOracle portal, 781
SearchSQLServer portal, 781
Secured Hash Algorithm (SHA-1), 472
Security. See also Authority; Encryption; Passwords; Privileges.
administrator authorization, 467, 468
auditing, 477–478
authentication, 452
availability problems, 280
basics, 451–455
centralizing, 26
costs of data breaches, 450
data breaches, 449–450
data theft (example), 496
database administration tasks, 24–25
database users, 455–456
external threats, 478–480
fixpacks and maintenance, 480–481
horizontal restriction, 469
job scheduling, 479
logic-oriented, 470
non-DBA, 480
options for system performance, 344
replacement tools for, 721
scope of the problem, 449–450
sensitive data sets, 478–479
standards, 100–101
with stored procedures, 470
tools for, 720–721
user names, 456
using views for, 468–470
vertical restriction, 469
Security, login
administration, rules of thumb, 453, 455
definition, 455–456
limiting, 455
required information, 452–453
Security, passwords
changing, 453
creating, 454
definition, 452
disabling, 453
embedding in code, 479
guidelines for, 454
limiting, 455
locking, 453
882
Index
SEGUS Inc., 771
SEI Web site, 782
SELECT INTO statements, 341
SELECT INTO/BULKCOPY option, 341
SELECT privileges, 458–459
Selective auditing methods, 494
Self-referencing constraints, 437
Semantic data integrity. See Data integrity,
semantic.
Semantic integrity, 28
Serena, 773
SERIALIZABLE isolation, 218
Server processes, 326
Servers. See also Client/server computing; SQL
Server (Microsoft).
application, 664
availability problems, 276, 283–284
database, 664
definition, 665–666
file, 664
hardware failure, availability problems, 276
list, 777
performance, 283–284, 650
print, 664
transaction, 207–210
Servers, database
definition, 664
hosting, 675
location, upgrading, 88
Service level agreements (SLAs), 38
Serviceability, availability, 268
Service-level management (SLM), 308–311
Service-oriented architecture (SOA), 680
Servlets, 196–197
Set theory, SQL, 190
Set-at-a-time processing, 189–191
SGA (system global area), 326
SHA-1 (Secured Hash Algorithm), 472
SHA-256 hashing, 472
Shared locks, 212–213
Shared-disk clustering, 72, 294
Shared-nothing clustering, 71–72, 294
Sharing knowledge, DBA rule of thumb, 739–741
SHOWPLAN command, 394–398, 712
Shuffling, data masking, 497
Silos, in a fractured environment, 310–311
Simple Object Access Protocol (SOAP), 680
SIMPLE parameter, 620–621
Simple recovery, 340, 540
Simplification, DBA rule of thumb, 741–742
Size terminology, data storage, 582
Skilling, Jeff, 485
SKIP LOCKED DATA parameter, 219
Skipping
interim releases, 86–87
locked rows, 219
SLAs (service level agreements), 38
SLM (service-level management), 308–311
Small computer system interface (SCSI), 605
SMON (system monitor) process, 326
Snapshot replication, 555–556
SNIA (Storage Networking Industry Association),
503n, 783
Snowflake schema, data warehouse, 643
SOA (service-oriented architecture), 680
SOAP (Simple Object Access Protocol), 680
Softbase Systems Inc., 771
Software AG, 764
Software environment, designing, 193–194
SoftwareOnZ LLC, 771
Solid state devices (SSDs), 323–324, 596
SolidDB (IBM), 596
Sort area, 326
Sorting
avoiding, 387–388
indexes, 152
SQL tuning, 404
tools for, 314
SOX (Sarbanes-Oxley) Act, 483, 485, 491
Space management. See also Storage
management.
monitoring usage, 587–588
tools for, 726
Space management, data page layouts
allocation pages, 589
allocation units, 589
bitmaps, 589
data record layouts, 590
data rows, 588–589
header information, 592
index key values, 592
index page layouts, 592–594
offset and adjust tables, 592
offset table, 588–589
Index
offset tables, 590
overview, 588–589
page header, 588–589
page pointer, 592
row data, 590
row header, 590
row length, 592
sample, 589
space page map, 589
table size, calculating, 591–592
transaction logs, 594–595
Space page map, data page layouts, 589
SP_CONFIGURE procedure, 80n.4
Speed tables, optimizing database performance,
356
Split tables
horizontally split, 166
overview, 165–166
vertically split, 166
Splitting text columns, 166–168
SP_MONITOR procedure, 345–346
SPUFI, 81n.5
SQData, 773
SQL (Structured Query Language)
access paths, 187
APIs, 192–193
benefits of, 188
binding, 477
callable routines, 192
code, design review, 238
coding for performance, 202–203
COM, 193
creating with code generators, 191–192
cursor, 190
definition, 186–187
dynamic, 201
embedded, 201
embedding in programs, 191–192
JDBC (Java Database Connectivity), 192–193
joins, 189
middleware, 192–193
object orientation, 199–200
ODBC (Object Database Connectivity),
192–193
OLE DB, 193
overview, 186–188
planned, 201
883
query analysis, 378–379, 713
query rewrite, 392–393
querying XML data, 203–205
relational closure, 189–191
set theory, 190
set-at-a-time processing, 189–191
SQL/XML, 204
standalone, 201
standards Web site, 782–783
static, 201
subqueries, 189
syntax, 187
types of, 200–201
unplanned, 201
usage considerations, 188, 202
XQuery language, 204
SQL injection attacks
examples, 474
overview, 201–202, 473–475
preventing, 475–476
static versus dynamic SQL, 476
SQL Is Your Friend blog, 780
SQL Marklar blog, 780
SQL Rockstar blog, 780
SQL Server (Microsoft)
filegroups, 149
nonstandard database objects, 94
Professional Association for SQL Server, 740
transaction logs, backup, 530
vendor contact, 63
Web site, 778
SQL Server Pro, 779
SQL tuning
basic steps, 399–400
Cartesian products, 402
code generators, 405
COMMIT frequency, 404–405
finding problem statements, 303–304,
406–407
LIKE logical operator, 403–404
OR logical operator, 403
overview, 202–203
rules of thumb, 400–406
sorts, 404
stored procedures, 405–406
tools for, 313
SQL...User Group portal, 782
884
Index
SQL/XML, 204
SSDs (solid state devices), 323–324, 596
Standalone SQL, 201
Standardizing default values, data warehouse, 647
Standards and procedures
abbreviations, 96
application development, 100
clusters, definition, 94
communications, 98
data administration, 98–99
database links, definition, 94
database naming conventions, 93–96
definition, 93
design review guidelines, 102
distributed data, 629–630
filegroups, definition, 94
importance of, 93
Internet resources, 782
migration and turnover, 101–102
nonstandard database objects, 94
online manuals, 727–728
operational support, 102
plans, definition, 94
roles and responsibilities, 96–98, 97
rules, definition, 94
security, 100–101
storage groups, definition, 94
system administration, 100
Standby databases
availability problems, 276, 277
backup/recovery alternative, 554–555
versus backups, 277
DB2 HADR (high-availability disaster recovery), 285
definition, 276
disaster planning, backup, 573
Oracle, 277
Star schema, data warehouse, 641–643
Statement-level triggers, 432
Static SQL, 201
Storage. See specific media.
Storage area network (SAN), 278, 604–605, 606
Storage groups, 94
Storage management. See also Files and data sets;
Space management; specific media.
capacity planning, 608–609
cool data, 607–608
dormant data, 607–608
fragmentation, 595
goals for, 583
hot data, 607–608
integrity versus availability, 580
multitemperature data, 607–608
overview, 579–583
rate of data growth, 581–582
size terminology, 582
warm data, 607–608
Storage management, media options. See also
specific media.
disk, 596
fiber channel, 605
JBOD (just a bunch of disks), 604
MMDBMSs (main-memory database management systems), 596
NAS (network-attached storage), 605, 606
overview, 596
SAN (storage area network), 604–605, 606
SCSI disks, 605
SSDs (solid state devices), 596
tape, 596
tiered storage, 606–608
Storage management, software
backup/recovery alternative, 535–536, 547
disaster planning, backup, 572–573
Storage Networking Industry Association (SNIA),
503n, 783
Storage requirements
database design, 148
installing the DBMS, 76–78
Stored procedures
procedural DBAs, 47, 48–50
as security tools, 470
SQL tuning, 405–406
Strategies for DBMS
benchmarks, TPC, 65–66
choosing a DBMS, 63–68. See also Vendors,
DBMS.
cloud database systems, 74
cost of ownership, 67
DBMS architectures, 68–71
DBMS clustering, 71–73
DBMS proliferation, 73
factors affecting, 65–68
hardware issues, 73–74
Index
multiple platforms, 61–62
operating system support, 65
organization type, 65
product complexity, 68
reference customers, 68
release schedules, 68
scalability, 66
technical support, 67
tool availability, 66
Striping, 597
Structural data integrity. See Data integrity, database structure.
Structure, data models, 754
Structured Query Language (SQL). See SQL
(Structured Query Language).
Subqueries, SQL, 189
Substitution, data masking, 497
Subsystem failure, backup, 533, 550
Suppliers. See Vendors.
Support polices for old releases, 89
Supporting versus exploiting, 91
Swartz, Mark, 485
Sybase Inc.
ISUG (International Sybase User Group), 740,
783
vendor contact, 64, 763
Web site, 778
Symmetric replication, 555–556
Synonyms, in data modeling, 118
Sysplex (IBM), 294–295
System administration (SA), 20, 21
System administration standards, 100
System administrators
authorization, 467
limiting number of, 468
System catalog, 342–343, 689–691
System catalog tables, 345
System DBAs, 31–32
System global area (SGA), 326
System memory failure, 276
System monitor (SMON) process, 326
System monitoring, 345–346
System parallelism, 391
System performance
allied agents, 321–322
DBMS components, 324
disk storage and I/O, 322–324
885
hardware configuration, 322–324
operating system interaction, 320–321
overview, 319–320
tools for, 709–710
System performance, DBMS installation and
configuration
cache, 328–330
configuration types, 327–328
contention, 341–342
data cache, 329–330, 332–335
database log cache, 330
database logs, 336–341
deadlock detection, 341
deadlocks, 342
defaults, 344
distributed database, 344
guidelines, 344
identity values, 344
Internet structure cache, 330
lock suspensions, 341
locking, 341–342
memory, 328–332
nested trigger calls, 343–344
open database objects, 336
optimization, cost-based versus rule-based,
344
procedure cache, 329–330, 335
read efficiency, 333–335
sample options, 343–344
security options, 344
sort cache, 330
system catalog, 342–343
time-outs, 342
System privileges, 459–460
System time, 179–180
System-managed referential integrity, 441
T
Table editors, 707–708
Table scans, 151, 381–382
Tables
adjust, 592
combined, 168
dropping, 250–252
mirror, 165
naming conventions, 95–96
offset, 592
886
Index
Tables (continued )
prejoined, 164
privileges, 458–459
report, 164–165
size, calculating, 591–592
size control, 585
speed, 172–173
split, 165–166
storage requirements, calculating, 590–592
Sybase segments, 585
Tablespace
database design, 148
disorganized, 367–368
scans, 381–382
Table-to-table synchronization, 498
Tamino (Software AG), 764
Tape storage. See also Storage management.
DBMS requirements, 77
disaster planning, backup, 570–571
storage management option, 596
WORM (write once, read many) technology,
596
Tapping requests, 494–495
Task-oriented DBAs, 36
TBCHECK utility (Informix), 411
TDES (Triple DES), 472
Team members, disaster planning and recovery,
569
Technical education, DBA rule of thumb, 746–747
Technical support, effect on DBMS strategy, 67
Technology, effects on DBAs
Big Data movement, 55–56
cloud computing, 53–55
database-coupled application logic, 46–50
Internet and e-business, 50–52
managing database logic, 46–50
mobile platforms, 53–55
NoSQL, 55–56
personal computing, 53–55
procedural DBAs, 46–50
Technology metadata, 689
Technology silos, in a fractured environment,
310–311
TechTarget, 781
Temporal data support, 177–180
Temporal database systems, data integrity,
444–446
Temporal requirements, database design, 177–180
Teradata Corporation, 64, 607, 763
Teradata Magazine, 779
Test beds, loading/unloading data for, 621–622
Test databases, populating, 553–554
Testing
disaster planning, recovery, 567–569, 574
recovery plans, 551
tools for, 725
Thin clients, 670
Throughput
performance factor, 301
performance monitoring and tuning, 22
Tibbetts, Hollis, 488
Tier-1 DBMS vendors, 63, 762
Tier-2 DBMS vendors, 64, 763
Tiered storage, 606–608
Time outs, locks, 213–214
Time zones, availability across, 270–271
Time-outs, system performance, 342
TimesTen (Oracle), 596
Tool vendors. See Vendors, tools.
Tools, for. See also specific tools.
capacity planning, 313
catalog query and analysis, 705–707
checkpoint/restart, 725
compliance, 716–721
debugging, 726
end-to-end performance, 713–714
replication, 722
repositories, 772–773
trending, 719
utility management, 716
Tools, for availability. See also Standby databases.
AlwaysOn features, 285
Database Definition on Demand, 289–290
DB2 HADR (high-availability disaster recovery), 285
effect on DBMS strategy, 66
RAC (Real Application Clusters), 294
REORG, 288–289
Tools, for DBAs
analytics, 721–724
application performance, 711–713
auditing tools, 717–719
availability, effect on DBMS strategy, 66
backup and recovery, 714–715
benefits of, 699–700
business intelligence, 721–724
Index
catalog query and analysis, 705–707
catalog visibility, 706
change management, 254, 701–703
checkpoint/restart, 725
compliance, 716–721
compression, 726–727
cost justification, 702, 731
data integrity, 411–414
data masking, 720
data modeling and design, 700–701
data profiling, 719–720
data protection, 716–721
data warehousing, 721–724
database comparison, 703–704
database performance, 711
database utilities, 715–716
DBA staffing requirements, 39
debugging, 726
end-to-end performance, 713–714
ETL (extract, transfer, load), 721–723
governance, 716–721
homegrown, 732–733
invasive performance tools, 710
native versus third-party, 728
object migration, 704–705
online standards manuals, 727–728
performance management, 708–714
performance monitor, 709–710
programming and development, 724–726
propagation, 722
query, 723–724
reorganizing databases, 368–369
replication, 722
reporting, 723–724
RI (referential integrity), 705
risk management, 716–721
security replacement, 721
security tools, 720–721
space management, 726
system performance, 709–710
table editors, 707–708
testing, 725
trending, 719
types of, 699–700
utility management, 716
vendors, evaluating, 729–732
Tools, vendors for. See also specific vendors.
business intelligence tools, 773
887
data modeling tools, 771–772
data movement tools, 773
DBA tools, 729–732, 770–771
ETL tools, 773
OLAP tools, 773
repository tools, 772–773
TP (transaction processing) system, 207–209
TPC (Transaction Processing Performance Council), 66–67
Trace-based auditing, 493–495
Tracker tables, 308
Transaction failure, backup, 516–517, 550
Transaction logs. See also Database logs.
backing up, 530
data page layouts, 594–595
file placement, 585
The Transaction Processing Council, 783
Transaction processing monitor, 207–209
Transaction recovery, 27, 544–545
Transaction servers, 207–209
Transaction time, 179–180
Transactions
ACID properties, 205–206
application servers, 209–210
atomicity, 205–206
consistency, 206
definition, 205
durability, 206
example, 206–207
guidelines, 207
isolation, 206
TP (transaction processing) system, 207–209
transaction processing monitor, 207–209
transaction servers, 207–209
UOW (unit of work), 207
Transition tables, 430–431
Transition variables, 430–431
Transparency, distributed databases, 626
Transparent encryption, 473
Transportable tablespaces (Oracle), 625
Treehouse Software, 773
Trending, tools for, 719
Triggers
active databases, 426
definition, 426
DELETE, 438–441
example, 431
firing, 428–429
888
Index
Triggers (continued )
firing while loading data, 615
granularity, 431–432
implementing referential integrity, 429–430
INSERT, 438–441
INSTEAD OF, 432
multiple on same table, 428–429
nested, 429
overview, 426–428
procedural DBAs, 47, 48–50
referential integrity, 438–441
row level, 432
semantic data integrity, 426–433
statement level, 432
transition tables, 430–431
transition variables, 430–431
UPDATE, 438–441
Triple DES (TDES), 472
TRUNC LOG ON CHKPT option, 340, 530
TRUNCATE TABLE statements, 341
Tuning performance. See Database performance,
tuning.
Turnover, standards, 101–102
TUSC, 779
24/24 availability, 270–271
Twitter, as a resource, 741
Two-phase COMMIT, 631
Tyco, 485
Type 1 drivers, 673
Type 2 drivers, 673
Type 3 drivers, 673–674
Type 4 drivers, 673
U
UDFs (user-defined functions), 47, 48–50
UDT (user-defined data types), 418–419
UML (Unified Modeling Language), 113, 114
Unclustered data, reorganizing databases, 366
UNCOMMITTED READ isolation, 216–217
UNDO recovery, 545–546
Unfederated multidatabase schemes, 627
UNION clause, 388
Unique constraints, 28, 417
Unique entity identification, 416–417
Unique identifiers for columns, 145
Unit testing, database environment, 101
UNLOAD utility, 553–554, 618–621, 621–622. See
also EXPORT utility.
Unloading data. See also Loading data.
for application test beds, 621–622
backup/recovery alternative, 534–535
concurrency, 619
encoding scheme, specifying, 620
floating-point data, 620
generating LOAD parameters, 620
from image copy backups, 619
LIMIT parameter, 620–621
limiting, 620–621
number of rows, specifying, 620–621
partial unload, 620–621
selection criteria, specifying, 620–621
SIMPLE parameter, 620–621
UNLOAD utility, 618–621, 621–622
from views, 621
WHEN clause, 620–621
Unplanned outages, 286–287
Unplanned SQL, 201
UOW (unit of work), 207
Update locks, 213
UPDATE privileges, 458–459
UPDATE rule, 434–436
UPDATE statements
modifying temporal data, 180
in triggers, 429
UPDATE STATISTICS command, 377–378
UPDATE trigger, 438–441
Upgrading the DBMS. See also Configuring the
DBMS; Installing the DBMS.
application complexity, 88
benefits of, 83–84
costs, 84, 85
database server location, 88
DBA staff skill set, 90
DBMS environment complexity, 87–88
deprecated features, 85n.7
fallback planning, 92
features and complexity, 87
migration standards, 101–102
migration verification, 92
organizational style, 89–90
overview, 82–87
performance gains, 85
platform support, 90–91
risks, 84–86
skipping interim releases, 86–87
strategy for, 92
Index
support polices for old releases, 89
supporting software, 91
supporting versus exploiting, 91
vendor reputation, 89
versions versus releases, 82–87
Upsizing, and database connectivity, 662
U.S. Public...Protection Act of 2002, 483
Usenet newsgroups, 775–776
User acceptance testing, database environment,
101
User processes, 326
User-defined data types (UDT), 418–419
User-defined functions (UDFs), 47, 48–50
User-managed referential integrity, 441
Users
DBA staffing requirements, 38, 39
group associations, 740
names, 456
privileged, auditing, 495–496
security, 455–456
Utility management, tools for, 716
Utility programs. See Tools; specific programs.
V
V$ tables, 370
Valid time, 179–180
Variable-length columns, 144
Vendors
evaluating, 729–732
reputation, importance of, 89
Vendors, DBMS
Actian Corporation, 764
Big Three, 762
dBase, 767
FileMaker, 767
IBM Corporation, 762
Informix, 763
Ingres, 763–764
Lotus, 767
main groups, 761–762
Microsoft, 762, 767
NoSQL systems, 765–766
object-oriented systems, 766
Ontos, 766
open-source systems, 764
Oracle Corporation, 762
PC-based systems, 766–767
889
Poet, 766
Progress Software, 766
Software AG, 764
Sybase Inc., 763
Teradata Corporation, 763
tier 1, 63, 762
tier 2, 64, 763
Web sites for, 778
Vendors, tools. See also specific vendors.
business intelligence tools, 773
data modeling tools, 771–772
data movement tools, 773
DBA tools, 729–732, 770–771
ETL tools, 773
OLAP tools, 773
repository tools, 772–773
Verifying the DBMS install, 81
Versions versus releases, 82–87
Vertical restriction, 469
Very critical applications, 562
View access, relational optimization, 391–392
View materialization, relational optimization,
392
View merging, relational optimization, 392
Views
description, 175–176
as security tools, 468–470
unloading data from, 621
uses for, 176–177
Visible Systems, 772
Vision Solutions, 773
Visual Insights, 773
Volatility, DBA staffing requirements, 39
VPD (Virtual Private Database) (Oracle), 471
W
Wallets, 473
WAN (wide-area network), disaster planning,
573
Web Farming site, 783
Web resources. See Internet resources.
Web services. See also Database connectivity;
Internet.
definition, 680
REST (representational state transfer), 681
SOA (service-oriented architecture), 680
SOAP (Simple Object Access Protocol), 680
890
Index
WHEN clause, 620–621
White Sands Technology, Inc., 771
Wide-area network (WAN), disaster planning, 573
Winter Corporation, 581–582
WITH GRANT OPTION, 457
Workload
performance factor, 301
performance monitoring and tuning, 22
WorldCom, 485
Write locks, 212–213
Write-ahead logs, 337
X
XML (eXtensible Markup Language), 204
XML data, querying, 203–205
The XML portal, 783
XQuery language, 204
Y
Yevich, Lawson & Associates, 779
Z
z/OS, data sharing, 295
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