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E-raamat: Database Tuning: Principles, Experiments, and Troubleshooting Techniques

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Tuning your database for optimal performance means more than following a few short steps in a vendor-specific guide. For maximum improvement, you need a broad and deep knowledge of basic tuning principles, the ability to gather data in a systematic way, and the skill to make your system run faster. This is an art as well as a science, and Database Tuning: Principles, Experiments, and Troubleshooting Techniques will help you develop portable skills that will allow you to tune a wide variety of database systems on a multitude of hardware and operating systems. Further, these skills, combined with the scripts provided for validating results, are exactly what you need to evaluate competing database products and to choose the right one.

* Forward by Jim Gray, with invited chapters by Joe Celko and Alberto Lerner
* Includes industrial contributions by Bill McKenna (RedBrick/Informix), Hany Saleeb (Oracle), Tim Shetler (TimesTen), Judy Smith (Deutsche Bank), and Ron Yorita (IBM)
* Covers the entire system environment: hardware, operating system, transactions, indexes, queries, table design, and application analysis
* Contains experiments (scripts available on the author's site) to help you verify a system's effectiveness in your own environment
* Presents special topics, including data warehousing, Web support, main memory databases, specialized databases, and financial time series
* Describes performance-monitoring techniques that will help you recognize and troubleshoot problems

Arvustused

"For the novice, this book gives sage advice on the performance issues of SQL-level logical database design that cuts across all systems. For me at least, the physical database design was particularly interesting, because the book presents the implications of design choices on IBM, Oracle, and Microsoft systems. These systems are quite different internally, and the book's example will surprise even the systems' implementers."Jim Gray, Microsoft

"Shasha and Bonnet prove the value of applying timeless principles to everchanging technology. The unique wealth of practical ideas, facts, and examples equip database practitioners "in the trenches" like no other resource. Chapter 2 alone is worth the price of the book."Bob Badour, Online Curmudgeon

Muu info

* Forward by Jim Gray, with invited chapters by Joe Celko and Alberto Lerner * Includes industrial contributions by Bill McKenna (RedBrick/Informix), Hany Saleeb (Oracle), Tim Shetler (TimesTen), Judy Smith (Deutsche Bank), and Ron Yorita (IBM) * Covers the entire system environment: hardware, operating system, transactions, indexes, queries, table design, and application analysis * Contains experiments (scripts available on the author's site) to help you verify a system's effectiveness in your own environment * Presents special topics, including data warehousing, Web support, main memory databases, specialized databases, and financial time series * Describes performance-monitoring techniques that will help you recognize and troubleshoot problems
Foreword ix
Preface xix
Basic Principles
1(8)
The Power of Principles
1(1)
Five Basic Principles
2(5)
Think Globally; Fix Locally
2(1)
Partitioning Breaks Bottlenecks
3(1)
Start-Up Costs Are High; Running Costs Are Low
4(1)
Render unto Server What Is Due unto Server
5(1)
Be Prepared for Trade-Offs
6(1)
Basic Principles and Knowledge
7(2)
Tuning the Guts
9(68)
Goal of
Chapter
9(1)
Locking and Concurrency Control
9(27)
Correctness Considerations
12(4)
Lock Tuning
16(20)
Logging and the Recovery Subsystem
36(13)
Principles of Recovery
37(5)
Tuning the Recovery Subsystem
42(7)
Operating System Considerations
49(10)
Scheduling
50(2)
Database Buffer
52(2)
How Much Memory Is Economical
54(2)
Multiprogramming Level
56(1)
Files: Disk Layout and Access
57(2)
Hardware Tuning
59(18)
Tuning the Storage Subsystem
59(7)
Enhancing the Hardware Configuration
66(5)
Bibliography
71(3)
Exercises
74(3)
Index Tuning
77(46)
Goal of
Chapter
77(1)
Types of Queries
77(4)
Key Types
81(1)
Data Structures
81(8)
Structures Provided by Database Systems
82(5)
Data Structures for In-Memory Data
87(2)
Sparse Versus Dense Indexes
89(1)
To Cluster or Not to Cluster
90(12)
Evaluation of Clustering Indexes
92(4)
Nonclustering Indexes
96(4)
Composite Indexes
100(2)
Joins, Foreign Key Constraints, and Indexes
102(3)
Avoid Indexes on Small Tables
105(1)
Summary: Table Organization and Index Selection
105(5)
Distributing the Indexes of a Hot Table
110(1)
General Care and Feeding of Indexes
111(12)
Bibliography
115(1)
Exercises
116(7)
Tuning Relational Systems
123(42)
Goal of
Chapter
123(1)
Table Schema and Normalization
124(13)
Preliminary Definitions
124(1)
Some Schemes Are Better Than Others
125(2)
Normalization by Example
127(2)
A Practical Way to Design Relations
129(2)
Functional Dependency Test
131(1)
Tuning Normalization
131(5)
Tuning Denormalization
136(1)
Clustering Two Tables
137(1)
Aggregate Maintenance
138(2)
Record Layout
140(3)
Query Tuning
143(15)
Minimizing DISTINCTs
151(2)
Rewriting of Nested Queries
153(5)
Triggers
158(7)
Uses of Triggers
158(2)
Trigger Performance
160(1)
Bibliography
161(1)
Exercises
162(3)
Communicating with the Outside
165(20)
Talking to the World
165(2)
Client-Server Mechanisms
167(1)
Objects, Application Tools, and Performance
168(3)
Beware of Small Objects
169(2)
Beware of Application Development Tools
171(1)
Tuning the Application Interface
171(8)
Avoid User Interaction Within a Transaction
172(1)
Minimize the Number of Round-Trips Between the Application and the Database Server
172(2)
Retrieve Needed Columns Only
174(1)
Retrieve Needed Rows Only
175(1)
Minimize the Number of Query Compilations
176(3)
Bulk Loading Data
179(1)
Accessing Multiple Databases
180(5)
Bibliography
183(2)
Case Studies from Wall Street
185(28)
Techniques for Circumventing Superlinearity
185(3)
Perform Data Integrity Checks at Input Time
188(1)
Distribution and Heterogeneity
188(5)
Interoperability with Other Databases
188(2)
Global Systems
190(2)
Managing Connections Socialistically in a Distributed Setting
192(1)
Trading Space for Time in History-Dependent Queries
193(1)
Chopping to Facilitate Global Trades
194(1)
Clustering Index Woes
195(1)
Beware the Optimization
195(1)
Disaster Planning and Performance
196(5)
Keeping Nearly Fixed Data Up to Date
201(1)
Deletions and Foreign Keys
202(1)
Partitioning Woes: The Hazards of Meaningful Keys
203(1)
The Problem of Time
203(10)
Present Value
203(1)
Regular Time Series and Statistics
204(1)
Irregular Time Series and Frequency Counting
205(1)
Bitemporality
206(1)
What to Do with Time
207(2)
Bibliography
209(1)
Exercises
210(3)
Troubleshooting
213(30)
Alberto Lerner
Introduction
213(4)
A Consumption Chain Approach
214(3)
The Three Questions
217(1)
How to Gather Information: The Tools
217(9)
Query Plan Explainers
217(4)
Performance Monitors
221(2)
Event Monitors
223(1)
Now What?
224(2)
Queries from Hell
226(5)
Finding ``Suspicious'' Queries
226(1)
Analyzing a Query's Access Plan
227(2)
Profiling a Query Execution
229(2)
Are DBMS Subsystems Working Satisfactorily?
231(5)
Disk Subsystem
231(2)
Buffer (Cache) Manager
233(1)
Logging Subsystem
234(1)
Locking Subsystem
235(1)
Is the DBMS Getting All It Needs?
236(4)
Checking on CPU
237(1)
Checking on Disks and Controllers
237(2)
Checking on Memory
239(1)
Checking the Network
239(1)
Conclusion
240(3)
Bibliography
240(3)
Tuning E-Commerce Applications
243(18)
Goal
243(1)
E-commerce Architecture
243(3)
Tuning the E-commerce Architecture
246(4)
Caching
246(3)
Connection Pooling
249(1)
Indexing
249(1)
Case Study: Shop Comparison Portal
250(3)
Capacity Planning in a Nutshell
253(8)
Capacity Planning Essentials
254(2)
What to Purchase
256(1)
Bibliography
257(1)
Exercises
258(3)
Celko on Data Warehouses: Techniques, Successes, and Mistakes
261(14)
Joe Celko
Early History
261(1)
Forget What the Elders Taught You
262(5)
Building a Warehouse Is Hard
267(1)
The Effect on the Bottom Line
268(7)
Wal-Mart
269(2)
Supervalu
271(2)
Harrah's
273(2)
Data Warehouse Tuning
275(26)
What's Different About Data Warehouses
275(14)
Uses of Data Warehouses
276(2)
Technology for Data Warehousing
278(11)
Tuning for Customer Relationship Management Systems
289(5)
Federated Data Warehouse Tuning
294(1)
Product Selection
295(6)
Bibliography
297(2)
Exercises
299(2)
Appendix A: REAL-TIME DATABASES 301(4)
A.1 Overview
301(2)
A.2 Replicated State Machine Approach
303(2)
Appendix B: TRANSACTION CHOPPING 305(20)
B.1 Assumptions
305(2)
B.2 Correct Choppings
307(5)
B.3 Finding the Finest Chopping
312(3)
B.4 Optimal Chopping Algorithm
315(2)
B.5 Application to Typical Database Systems
317(2)
B.5.1 Chopping and Snapshot Isolation
318(1)
B.6 Related Work
319(6)
Bibliography
323(2)
Appendix C: TIME SERIES, ESPECIALLY FOR FINANCE 325(12)
C.1 Setting Up a Time Series Database
326(1)
C.2 Fame
327(2)
C.3 S-Plus
329(1)
C.4 SAS
329(1)
C.5 KDB
330(2)
C.6 Oracle 8i Time Series
332(1)
C.7 Features You Want for Time Series
332(1)
C.8 Time Series Data Mining
333(4)
Appendix D: UNDERSTANDING ACCESS PLANS 337(12)
D.1 Data Access Operators
339(3)
D.2 Query Structure Operators
342(4)
D.3 Auxiliary Operators
346(3)
Bibliography
348(1)
Appendix E: CONFIGURATION PARAMETERS 349(12)
E.1 Oracle
350(4)
E.2 SQL Server
354(1)
E.3 DB2 UDB
355(6)
Glossary 361(26)
Index 387


Dennis Shasha is the author or coauthor of seven books, including this book's predecessor Database Tuning: A principal Approach (Prentice Hall) and Out of Their Minds: The Lives and Discoveries of 15 Great Computer Scientists (Copernius/Springer-Verlag), numerous journal and conference papers, and four patents. He also writes monthly puzzle columns for Scientific American and Dr. Dobb's Journal. Philippe Bonnet is an experiment database researcher. He directs code development of the open source object-relational database system Predator developed at Cornell.
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