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High Performance MySQL: Optimization, Backups, Replication, and More (2nd Edition)

2008-08-28 10:32:28

High Performance MySQL 的2008年新版,即第二版.
涵盖5.1版.

High Performance MySQL is the definitive guide to building fast, reliable systems with MySQL. Written by noted experts with years of real-world experience building very large systems, this book covers every aspect of MySQL performance in detail, and focuses on robustness, security, and data integrity. High Performance MySQL teaches you advanced techniques in depth so you can bring out MySQL's full power. Learn how to design schemas, indexes, queries and advanced MySQL features for maximum performance, and get detailed guidance for tuning your MySQL server, operating system, and hardware to their fullest potential. You'll also learn practical, safe, high-performance ways to scale your applications with replication, load balancing, high availability, and failover. This second edition is completely revised and greatly expanded, with deeper coverage in all areas. Major additions include: Emphasis throughout on both performance and reliability Thorough coverage of storage engines, including in-depth tuning and optimizations for the InnoDB storage engine Effects of new features in MySQL 5.0 and 5.1, including stored procedures, partitioned databases, triggers, and views A detailed discussion on how to build very large, highly scalable systems with MySQL New options for backups and replication Optimization of advanced querying features, such as full-text searches Four new appendices The book also includes chapters on benchmarking, profiling, backups, security, and tools and techniques to help you measure, monitor, and manage your MySQL installations.

目录
Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
1. MySQL Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
MySQL’s Logical Architecture 1
Concurrency Control 3
Transactions 6
Multiversion Concurrency Control 12
MySQL’s Storage Engines 14
2. Finding Bottlenecks: Benchmarking and Profiling . . . . . . . . . . . . . . . . . . . . . 32
Why Benchmark? 33
Benchmarking Strategies 33
Benchmarking Tactics 37
Benchmarking Tools 42
Benchmarking Examples 44
Profiling 54
Operating System Profiling 76
3. Schema Optimization and Indexing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Choosing Optimal Data Types 80
Indexing Basics 95
Indexing Strategies for High Performance 106
An Indexing Case Study 131
Index and Table Maintenance 136
Normalization and Denormalization 139
Speeding Up ALTER TABLE 145
Notes on Storage Engines 149
vi | Table of Contents
4. Query Performance Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
Slow Query Basics: Optimize Data Access 152
Ways to Restructure Queries 157
Query Execution Basics 160
Limitations of the MySQL Query Optimizer 179
Optimizing Specific Types of Queries 188
Query Optimizer Hints 195
User-Defined Variables 198
5. Advanced MySQL Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
The MySQL Query Cache 204
Storing Code Inside MySQL 217
Cursors 224
Prepared Statements 225
User-Defined Functions 230
Views 231
Character Sets and Collations 237
Full-Text Searching 244
Foreign Key Constraints 252
Merge Tables and Partitioning 253
Distributed (XA) Transactions 262
6. Optimizing Server Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
Configuration Basics 266
General Tuning 271
Tuning MySQL’s I/O Behavior 281
Tuning MySQL Concurrency 295
Workload-Based Tuning 298
Tuning Per-Connection Settings 304
7. Operating System and Hardware Optimization . . . . . . . . . . . . . . . . . . . . . . . 305
What Limits MySQL’s Performance? 306
How to Select CPUs for MySQL 306
Balancing Memory and Disk Resources 309
Choosing Hardware for a Slave 317
RAID Performance Optimization 317
Storage Area Networks and Network-Attached Storage 325
Using Multiple Disk Volumes 326
Network Configuration 328
Table of Contents | vii
Choosing an Operating System 330
Choosing a Filesystem 331
Threading 334
Swapping 334
Operating System Status 336
8. Replication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
Replication Overview 343
Setting Up Replication 347
Replication Under the Hood 355
Replication Topologies 362
Replication and Capacity Planning 376
Replication Administration and Maintenance 378
Replication Problems and Solutions 388
How Fast Is Replication? 405
The Future of MySQL Replication 407
9. Scaling and High Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
Terminology 410
Scaling MySQL 412
Load Balancing 436
High Availability 447
10. Application-Level Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457
Application Performance Overview 457
Web Server Issues 460
Caching 463
Extending MySQL 470
Alternatives to MySQL 471
11. Backup and Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472
Overview 473
Considerations and Tradeoffs 477
Managing and Backing Up Binary Logs 486
Backing Up Data 488
Recovering from a Backup 499
Backup and Recovery Speed 510
Backup Tools 511
Scripting Backups 518
viii | Table of Contents
12. Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521
Terminology 521
Account Basics 522
Operating System Security 541
Network Security 542
Data Encryption 550
MySQL in a chrooted Environment 554
13. MySQL Server Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557
System Variables 557
SHOW STATUS 558
SHOW INNODB STATUS 565
SHOW PROCESSLIST 578
SHOW MUTEX STATUS 579
Replication Status 580
INFORMATION_SCHEMA 581
14. Tools for High Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583
Interface Tools 583
Monitoring Tools 585
Analysis Tools 595
MySQL Utilities 598
Sources of Further Information 601
A. Transferring Large Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603
B. Using EXPLAIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607
C. Using Sphinx with MySQL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623
D. Debugging Locks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 650
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 659

Performance Tuning for Content Manager

2008-08-27 21:42:03

This IBM Redbook deals with performance tuning for IBM DB2 Content Manager Version 8 for Multiplatforms. It is aimed at architects, designers, and system administrators of Content Manager systems.

The book starts with an introduction to performance tuning basics, and define performance and how it is measured. We describe performance methodology and the performance improvement process, along with a set of general guidelines you should use when planning a new system or maintaining and improving an existing system.

After a summary of best practices for Content Manager system performance in a check list, we go into detail about tuning the operating system, DB2, WebSphere Application Server, and Tivoli Storage Manager for Content Manager.

In addition, we include discussion about performance monitoring, analysis, and tracing. Our troubleshooting guidance uses real-life scenarios, and there is a case study to further show you how to troubleshoot. At the end, we include Content Manager maintenance information to ensure that your system is performing at its best.

Written for architects, developers, and system administrators, this book serves as a guide to help you from day one of the system planning and channel you through the right path for a successful running system.

Table of Contents

Part 1. Architecture and technology overview
Chapter 1. Content Manager
Chapter 2. Content Manager base products

Part 2. Performance tuning overview and planning
Chapter 3. Performance tuning basics
Chapter 4. Planning for performance
Chapter 5. Designing and configuring for performance

Part 3. Performance tuning details
Chapter 6. Best practices for Content Manager system performance
Chapter 7. Tuning operating systems for Content Manager
Chapter 8. Tuning DB2 for Content Manager
Chapter 9. Tuning WebSphere for Content Manager
Chapter 10. Tuning TSM for Content Manager

Part 4. Monitoring, troubleshooting, and maintenance
Chapter 11. Performance monitoring, analysis, and tracing
Chapter 12. Troubleshooting performance problems
Chapter 13. Case study
Chapter 14. Maintenance

Appendix A. Performance tuning guidelines for a Document Manager system

Beginning SQL Server 2008 for Developers: From Novice to Professional

2008-08-18 21:36:10

SQL SERVER 2008 的好书.

目录

About the Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii
About the Technical Reviewer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xix
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxi
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii
■CHAPTER 1 SQL Server 2008 Overview and Installation . . . . . . . . . . . . . . . . . . . . . 1
■CHAPTER 2 SQL Server Management Studio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
■CHAPTER 3 Database Design and Creation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
■CHAPTER 4 Security and Compliance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
■CHAPTER 5 Defining Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
■CHAPTER 6 Creating Indexes and Database Diagramming . . . . . . . . . . . . . . . . 151
■CHAPTER 7 Database Backups, Recovery, and Maintenance . . . . . . . . . . . . . . 181
■CHAPTER 8 Working with the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
■CHAPTER 9 Building a View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
■CHAPTER 10 Stored Procedures and Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
■CHAPTER 11 T-SQL Essentials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355
■CHAPTER 12 Advanced T-SQL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
■CHAPTER 13 Triggers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
■CHAPTER 14 SQL Server 2008 Reporting Services . . . . . . . . . . . . . . . . . . . . . . . . . 439
■INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459

Beginning SQL Server 2008 for Developers.From Novice to Professional

2008-08-17 13:56:43

SQL Server 2008 is a first–rate database management system. It offers more capability than any previous release of SQL Server. More than just a classic relational database management system, SQL Server 2008 includes exciting and powerful features that make it useful for everything from large corporate data warehouses to ad hoc departmental databases. You’ll find enhanced support for XML, new support for spatial data, transparent data encryption, a policy–based management system, and more.

Author and developer Robin Dewson will show you the way from beginner to SQL Server 2008 professional. Learn to install SQL Server 2008 and navigate around Management Studio before getting right to the heart of mastering fundamental SQL Server 2008 tasks: creating tables, storing data, securing data, and retrieving it again. Dewson ensures you’ll be fully prepared to use all the basics and create a solid foundation for your own projects.

Don’t forget about backups! Your database will house important data, so backing up is essential to protect yourself from inevitable hardware failure. Dewson walks you through SQL Server 2008’s easy–to–use backup and recovery feature set, giving you the grounding that you need in order to set up a reliable plan for recovery in your own environment.

Learn to use Transact–SQL, a full–blown procedural language that is built right into the database system. Transact–SQL is the key to unlocking everything that SQL Server 2008 has to offer. Using Transact–SQL, you can write centrally encapsulated business logic through the use of stored procedures, automatically trigger processing through the use of triggers, and manipulate data within the server without having to move data back and forth across the network.

Finally, you’ll learn a bit about SQL Server 2008 Reporting Services, a powerful tool that allows enterprise reporting. Reporting Services enables you to develop and serve reports across your organization and even to business partners outside your company. Reporting Services also gives end users the ability to create their own reports, helping them transform business data into valuable, usable information to guide their day–to–day decisions.

SQL Server 2008 Transact-SQL Recipes

2008-08-17 09:15:37

SQL Server 2008 好书

Product Description

SQL Server 2008 Transact–SQL Recipes: A Problem–Solution Approach is an example–based guide to the Transact–SQL language that is at the core of SQL Server 2008. Learn to create databases, insert and update data, generate reports, secure your data, and more. Author Joseph Sack takes common Transact–SQL tasks and breaks them down into a problem/solution format that is quick and easy to read so that you can get the job done fast when the pressure is on.

* Focused on solutions: Look up what you need to do. Learn how to do it. Do it.
* Current: Newly updated for SQL Server 2008.
* Comprehensive: Covers 30 different Transact–SQL problem domains.

What you’ll learn

* Create databases, tables, and indexes.
* Query and manipulate data.
* Store and manage XML inside the database.
* Move business logic into the database.
* Encrypt data and capture changes for compliance purposes.
* Implement Full–Text Search.
* Interface with Service Broker.
* And more!

Who is this book for?

Developers who use Microsoft SQL Server 2008 as their back–end database. Database administrators who create, manage, and secure those databases.

目录：

About the Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxv
About the Technical Reviewer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxvii
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxix
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxxi
nCHAPTER 1 SELECT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
nCHAPTER 2 Perform, Capture, and Track Data Modifications . . . . . . . . . . . . . . . . . . . . . 63
nCHAPTER 3 Transactions, Locking, Blocking, and Deadlocking . . . . . . . . . . . . . . . . . . 115
nCHAPTER 4 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
nCHAPTER 5 Indexes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
nCHAPTER 6 Full-Text Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
nCHAPTER 7 Views . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
nCHAPTER 8 SQL Server Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
nCHAPTER 9 Conditional Processing, Control-of-Flow, and Cursors . . . . . . . . . . . . . . . 307
nCHAPTER 10 Stored Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325
nCHAPTER 11 User-Defined Functions and Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343
nCHAPTER 12 Triggers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
nCHAPTER 13 CLR Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401
nCHAPTER 14 XML, Hierarchies, and Spatial Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419
nCHAPTER 15 Hints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449
nCHAPTER 16 Error Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459
nCHAPTER 17 Principals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
nCHAPTER 18 Securables, Permissions, and Auditing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501
nCHAPTER 19 Encryption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547
nCHAPTER 20 Service Broker. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 579
iv
nCHAPTER 21 Configuring and Viewing SQL Server Options . . . . . . . . . . . . . . . . . . . . . . . 615
nCHAPTER 22 Creating and Configuring Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621
nCHAPTER 23 Database Integrity and Optimization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669
nCHAPTER 24 Maintaining Database Objects and Object Dependencies . . . . . . . . . . . . 687
nCHAPTER 25 Database Mirroring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 697
nCHAPTER 26 Database Snapshots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 717
nCHAPTER 27 Linked Servers and Distributed Queries . . . . . . . . . . . . . . . . . . . . . . . . . . . . 723
nCHAPTER 28 Query Performance Tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739
nCHAPTER 29 Backup and Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 789
nINDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 823

SQL Server 2005安装使用教程

2008-08-12 09:23:16

通过本教程的学习，帮助您对ＳＱＬ　ＳＥＲＶＥＲ　２００５的安装配置有很好的了解。
　　　　　　　　　　　　　目录
１．　ＳＱＬ　ＳＥＲＶＥＲ　２００５介绍
　　１．１ＳＱＬ　ＳＥＲＶＥＲ　２００５的版本组件
　　１．２　安装ＳＱＬ　ＳＥＲＶＥＲ　２００５的硬件要求
１．３　ＳＱＬ　ＳＥＲＶＥＲ　２００５安全配置。
２．ＳＱＬ　ＳＥＲＶＥＲ　２００５版本比较
３．ＳＱＬ　ＳＥＲＶＥＲ　２００５的主要指标参数
４．ＳＱＬ　ＳＥＲＶＥＲ　２００５的安装步骤
５．ＳＱＬ　ＳＥＲＶＥＲ　２００５安装过程

SAS GRAPHIC FOR JAVA

2008-08-11 22:38:52

2007. SAS? Graphics for Java: Examples Using SAS? AppDev Studio? and the Output Delivery System. Cary,
NC: SAS Institute Inc.
SAS? Graphics for Java: Examples Using SAS? AppDev Studio? and the Output Delivery System
Copyright ? 2007, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-59047-693-2
All rights reserved. Produced in the United States of America.
For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or
transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the
prior written permission of the publisher, SAS Institute Inc.
For a Web download or e-book: Your use of this publication shall be governed by the terms established by
the vendor at the time you acquire this publication.
U.S. Government Restricted Rights Notice: Use, duplication, or disclosure of this software and related
documentation by the U.S. government is subject to the Agreement with SAS Institute and the restrictions set
forth in FAR 52.227-19, Commercial Computer Software-Restricted Rights (June 1987).
SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513.
1st printing, May 2007
SAS? Publishing provides a complete selection of books and electronic products to help customers use SAS
software to its fullest potential. For more information about our e-books, e-learning products, CDs, and hardcopy
books, visit the SAS Publishing Web site at support.sas.com/pubs or call 1-800-727-3228.
SAS? and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS
Institute Inc. in the USA and other countries. ? indicates USA registration.
Other brand and product names are registered trademarks or trademarks of their respective companies.

Acknowledgments ix
Introduction xi
Part 1 SAS AppDevStudio 1
Chapter 1 Getting Started with SAS AppDev Studio 3
1.1 Tag Libraries for SAS AppDev Studio 3
1.2 Getting Ready to Add Graphs to Your SAS AppDev Studio
Project 8
1.3 Your Data 10
1.3.1 Tips and Information 11
Chapter 2 SAS AppDev Studio Custom Tags and Attributes for
Basic Graphs 13
2.1 SAS AppDev Studio 2 Tags 15
2.1.1 sasads:Bar 15
2.1.2 sasads:Combination 16
2.1.3 sasads:Pie 16
2.1.4 sasads:Scatter 17
2.1.5 sasads:SegmentedBar 17
2.2 SAS AppDev Studio 3 Tags 18
2.2.1 sas:BarChart 18
2.2.2 sas:BarLineChart 19
2.2.3 sas:LineChart 20
2.2.4 sas:LinePlot 21
2.2.5 sas:PieChart 22
2.2.6 sas:RadarChart 23
2.2.7 sas:ScatterPlot 24
2.3 Common Attributes 25

Chapter 3 SAS AppDev Studio 3 Graph Model Tags 39
3.1 BarChartModel 40
3.2 BarLineChartModel 50
3.3 LineChartModel 64
3.4 LinePlotModel 67
3.5 PieChartModel 74
3.6 RadarChartModel 87
3.7 ScatterPlotModel 92
3.7.1 Baselines 97
Chapter 4 Nested Tags for Graph Models 99
4.1 Axis Models 100
4.1.1 Response Axis Baseline Models 107
4.1.2 Corresponding Graph Models 108
4.1.3 Column and Row Axis Models 110
4.2 Legends 111
4.2.1 Corresponding Graph Models 113
4.3 Line Style Tags 113
4.3.1 Corresponding Graph Models 116
4.4 Text Style Tags 116
4.4.1 Corresponding Graph Models 117
4.5 AxisWallModel 118
4.6 BackgroundFillStyle 119
4.6.1 Corresponding Graph Models 122
4.7 DataElementStyle 123
4.8 DataTipModel 123
4.9 SubgroupLabelModel 124
Chapter 5 Supporting Tags 125
5.1 Fill Tags 126
5.2 Line Tags 130
5.2.1 AxisLineStyle, GridLineStyle, StrokeLineStyle,
FrameLineStyle, and OutlineLineStyle
5.2.2 BasicStroke 133

5.3 Text Tags 133
5.3.1 Font 133
5.3.2 LabelTextStyle and ValueTextStyle 134
5.3.3 TextStyle 136
5.3.4 ShadowStyle 136
5.4 Tick Mark Tags 136
5.5 Miscellaneous Tags 137
5.5.1 DiscreteFillColor 137
5.5.2 MarkerStyle 137
5.5.3 ReferenceLineModel 140
Part 2 Output Delivery System 143
Chapter 6 Important Concepts for Getting Started with ODS
and Java 145
6.1 Java Scriptlet Code 146
6.2 General JSP Structure 146
6.3 General JSP Requirements 148
6.4 Connecting and Data Extraction 148
6.5 A Few Last Notes about Data 151
Chapter 7 Creating Graphs 153
7.1 Types of Bar Charts 154
7.1.1 Horizontal Bar Charts 154
7.1.2 Vertical Bar Charts 155
7.2 Types of Pie Charts 156
7.2.1 Pie Charts 157
7.2.2 Donut Charts 158
7.2.3 Star Charts 159
7.3 Contour Plots 159
7.4 Types of Maps 160
7.4.1 Block Maps 160
7.4.2 Choropleth Maps 161
7.4.3 Prism Maps 162
7.4.4 Surface Maps 163
7.5 Types of Plots 163
7.5.1 Bubble Plots 164
7.5.2 Plots 165

7.6 Three-Dimensional Graphs 166
7.6.1 Scatter Plots 166
7.6.2 Surface Plots 167
Chapter 8 Parameters for Colors 169
8.1 ODS Parameters 170
8.1.1 Non-supported parameters 181
8.2 GOPTIONS 182
8.2.1 Non-supported options 186
8.3 PROC GCHART 186
8.3.1 Summary 192
8.3.2 Non-supported parameters 193
8.4 PROC GCONTOUR 193
8.4.1 Summary 197
8.5 PROC GMAP 197
8.5.1 Summary 199
8.6 PROC GPLOT 199
8.6.1 Summary 204
8.7 PROC G3D 204
8.7.1 Summary 205
8.7.2 Non-supported parameters 205
Chapter 9 Parameters for Text 207
9.1 ODS Parameters 208
9.1.1 Non-supported parameters 213
9.2 GOPTIONS 214
9.2.1 Non-supported parameters 217
9.3 PROC GCHART 217
9.3.1 Summary 225
9.3.2 Non-supported parameters 226
9.4 PROC GCONTOUR 227
9.4.1 Summary 231
9.5 PROC GMAP 232
9.5.1 Summary 234
9.6 PROC GPLOT 234
9.6.1 Summary 238

9.7 PROC G3D 239
9.7.1 Summary 240
Chapter 10 Other Parameters 241
10.1 PROC GCHART 242
10.1.1 Summary 264
10.1.2 Non-supported parameters 267
10.2 PROC GCONTOUR 268
10.2.1 Non-supported parameters 272
10.3 PROC GMAP 273
10.3.1 Summary 277
10.3.2 Non-supported parameters 278
10.4 PROC GPLOT 278
10.4.1 Summary 289
10.4.2 Non-supported parameters 289
10.5 PROC G3D 290
10.5.1 Summary 298
10.5.2 Non-supported parameters 298
Part 3 Putting It Together 299
Chapter 11 Final Reports 301
11.1 Report 1: Using SAS AppDev Studio 3 Tags 301
11.2 Report 2: Using ODS 307
11.3 Conclusions 310
Appendix A SAS/GRAPH Samples and WORK Data Sets 313
References 315
Index 317

SQL语言艺术

2008-08-07 16:47:49

资深SQL专家Stephane Faroult倾力打造，软件架构设计》作者温昱最新译作，巧妙借鉴《孙子兵法》的智慧结晶。传授25年的SQL性能与调校经验，深入探讨9种常见查询方案及其性能。
　　“一部SQL力作。对于在其他书中止步于理论的难点，本书提供了实际的经验技巧，效果卓然。”
　　　　　　——Sean Hull，资深咨询顾问，Heavyweight百联网集团
　　“一本真正‘聪明’的SQL书，注重实践而非课堂上的理论，解决数据库专业人员遇到的问题。”
　　　　　——Anlhony Molinaro，首席数据库工程师，Wi reless Generation公司
　　你是否把数据库应用看作一场战役？你是否把数据看作一排排需要筛选并打退的敌军纵队？SQL专家Stephane Faroult就是这么做的。
　　《SQL语言艺术》的作者St6phane Faroult借用《孙子兵法》的智慧处理SQL性能方面的问题。开发数据库应用好比一场战役，设计即战略，而每次数据库访问就是与敌军在战术上的对决。
　　Stephane对SQL性能问题的论述，视角独特，一丝不苟。如何才能更好地使用SQL?本书结合一线实践的案例，强调了：
应从最开始就综合设计数据库和应用的性能。“只强调某个最重要方面的设计是错误的”。
应避免只考虑单个SQL语句。“关注总的目标，SQL语句再好也挽救不了糟糕的处理流程”。
必须明白为哪些字段建立索引、为何建立索引。“索引过多是设计不确定的表现”。
Stephane还对你的实际工作提出了具体建议。九种SQL经典查询方案，以及对其性能影响的讨论，非常便于实践。书中有一章专门讨论树状结构，可帮助你解决层次结构数据的问题。另外，当你必须基于别人的数据库设计进行工作时，“精于计谋：挽救响应时间”这一章会助你成功。

SPSS : clementine 7.0用户手册（第三版）

2008-08-04 10:37:00

中文翻译的clementine使用手册,写得比较全面、详细。虽然clementine已经有更新的版本，但基本使用方法没有变。参考中文手册，比看英文的更容易上手些。推荐做数据挖掘的人可以参考一下。
【目录】
第1 章CLEMENTINE 概述.................... 12
1.1 启动...............12
1.1.1 安装Clementine...............................12
1.1.2 启动Clementine...............................14
1.2 CLEMENTINE 一览.....................................15
1.2.1 Clementine 界面...................................16
1.2.2 在Clementine 中使用鼠标..............18
1.2.3 利用快捷键......................................18
1.2.4 Clementine 中获得帮助.......................19
1.3 CLEMENTINE 选项设置.............................20
1.3.1 系统选项20
1.3.2 默认目录的设置..............................21
1.3.3 用户选项的设置..............................21
1.4 CLEMENTINE 自动化.................................25
第2 章CLEMENTINE 7.0 版本的新功能........................................ 26
2.1 欢迎...............26
2.2 新特征...........26
2.2.1 支持CRISP-DM...............................26
2.2.2 有关CLEM 表达式帮助.................28
2.2.3 界面友好性的增强..........................29
2.2.4 标准化功能......................................29
2.2.5 更强大的源节点..............................30
2.2.6 新图形...30
2.2.7 字段选择器......................................31
2.2.8 树形阅读器......................................32
2.2.9 批处理模式......................................32
2.2.10 技术的增强......................................33
2.3 从CLEMENTINE 6.5 以来的变化..............33
2.3.1 批处理模式......................................33
2.3.2 输出.......34
2.3.3 改进的脚本......................................34
2.3.4 更为灵活的超级节点......................34
2.3.5 改变数据储存..................................35
2.3.6 被要求的功能..................................35
2.3.7 兼容性问题......................................36
第3 章数据挖掘入门............................... 38
3.1 数据挖掘回顾38
3.2 机器学习技术38
3.2.1 神经网络38
3.2.2 规则归纳39
3.2.3 Kohonen 网络.......................................40
3.2.4 关联规则41
3.2.5 统计模型43
3.2.6 聚类模型43
3.3 潜在数据挖掘应用评估..........................44
3.3.1 数据是可以得到的吗？..................44
3.3.2 数据包含所需要了解的属性吗？..45
3.3.3 数据是否有噪声？..........................45
3.3.4 数据的数量够吗？..........................45
3.3.5 可以获得关于数据的专家知识吗？........................................45
3.4 数据挖掘的策略......................................45
3.4.1 CRISP －DM 过程模型........................46
3.5 小技巧...........47
3.5.1 归纳，神经网络，或统计模型？..47
3.5.2 数据均衡吗？..................................48
3.5.3 抽样.......48
3.5.4 异常的收集......................................48
第4 章构建数据流................................... 49
4.1 概要...............49
4.2 建立数据流（BUILDING DATA STREAM）.........................................49
4.2.1 节点的操作......................................50
4.2.2 数据流的操作..................................58
4.2.3 运行数据流......................................64
4.2.4 保存数据流......................................64
4.2.5 装载文件65
4.2.6 映射数据流......................................65
第5 章处理缺失值................................... 70
5.1 总论...............70
5.2 指定缺失值...70
5.3 处理缺失值...71
5.3.1 处理带缺失值的记录......................72
5.3.2 处理带缺失值的字段......................72
5.4 针对缺失值的CLEM 函数.....................73
5.4.1 关于删除记录的注意事项..............74
第6 章源节点. 75
6.1 概要...............75
6.2 变量文件节点（VARIABLE FILE NODE） 75
6.2.1 为变量文件节点设置选项（Setting Options for Variable File Node ）.............................76
6.3 固定文件节点（FIXED FILE NODE） ......77
6.3.1 为固定文件节点设置选项（Setting Options for the Fixed File Node ）...........................77
6.4 为文本区设置数据存储（SETTING DATA STORAGE FOR TEXT FIELDS） ...................................78
6.5 数据库节点（DATABASE NODE） ...........79
6.5.1 设置数据库节点选项（Setting Database Node Options ）......80
6.5.2 添加数据库连接（Adding a Database Connection ）..............80
6.5.3 选择数据表（Selecting a Database Table ）.............................81
6.5.4 数据库查询（Querying the Database ）...................................82
6.6 SPSS 导入节点（SPSS IMPORT NODE） 82
6.7 SAS 导入节点（SAS IMPORT NODE）....83
6.7.1 为SAS 导入节点设置选项(Setting Option for the SAS Import Node) ................................84
6.8 用户输入节点（USER INPUT NODE） .....84
6.8.1 为用户输入节点设置选项（Setting Options for the User Input Node ）...........................85
6.9 一般源节点条目（COMMON SOURCE NODE TABS） ........................87
6.9.1 在源节点中设置数据类型（Setting Data Type in the Source Node ）...............................87
6.9.2 在源节点处过滤字段......................89
第7 章记录操作节点............................... 91
7.1 记录操作概述91
7.2 选择节点（SELECT NODE） ....................91
7.3 抽样节点（SAMPLE NODE） ...................92
7.3.1 抽样节点选项..................................93
7.4 均衡节点(BALANCE NODE)......................93
7.4.1 均衡节点的设置选项......................94
7.5 聚合节点（AGGREGATE NODE）.............94
7.5.1 聚合节点的设置选项......................95
7.6 排序节点(SORT NODE) .............................96
7.7 合并节点（MERGE NODE） ....................97
7.7.1 指定合并方法和关键字段..............97
7.7.2 从合并节点过滤字段......................98
7.7.3 设置输入顺序并加上标签..............99
7.8 追加节点（APPEND NODE） .................100
7.8.1 设置追加选项................................101
7.9 区分节点.....101
第8 章字段操作节点............................. 102
8.1 总论.............102
8.2 类型节点（TYPE NODE）......................102
8.2.1 数据类型........................................103
8.2.2 什么是实例化？............................105
8.2.3 读取数据值....................................106
8.2.4 检查类型值....................................110
8.2.5 设定字段方向................................ 111
8.2.6 复制类属性....................................112
8.3 过滤节点(FILTER NODE) ........................112
8.3.1 设定过滤节点的选项....................113
8.4 导出节点(DERIVE NODE) .......................115
8.4.1 设置导出节点的基本选项............115
8.4.2 导出多重字段................................116
8.4.3 设置导出规则选项........................118
8.4.4 设置导出标记选项........................119
8.4.5 设置导出设置节点选项................120
8.4.6 设定导出状态选项........................121
8.4.7 设置导出计数选项........................122
8.4.8 设置导出条件选项........................123
8.5 填充节点.....124
8.5.1 用填充节点转换存储值................126
8.6 设置标记节点........................................126
8.6.1 设置标记节点的设置选项............127
8.7 历史节点.....128
8.7.1 历史节点的设置选项....................128
第9 章建立CLEM 表达式................... 130
9.1 什么是CLEM？ ....................................130
9.1.1 值及数据类型................................130
9.1.2 表达式及条件................................131
9.2 使用表达式构建器................................132
9.2.1 获取表达式构建器（accessing the expression builder ）.......132
9.2.2 构造表达式（creating expressions ）......................................133
9.2.3 选择函数（Selecting Functions ）.133
9.2.4 选择字段、参数以及全局变量（Selecting Fields ，Parameters ， and Global Variables ）
9.2.5 选择变量值（Selecting Values ）..134
9.2.6 检查CLEM 表达式（Checking CLEM Expressions ）...........135
9.3 CLEM 函数类型....................................135
9.4 CLEM 的常见用法(COMMON USES OF CLEM)...............................136
9.4.1 对字符串的操作（Working with Strings ）...........................136
9.4.2 处理空和缺失值（Handing Blanks and Missing Values ）.....137
9.4.3 处理数字（Working with Numbers ）......................................137
9.4.4 处理时间和日期（Working with Times and Dates ）..............137
第10 章图节点......................................... 139
10.1 概述.............139
10.1.1 层叠图表(Overlay Graphs)............139
10.1.2 3 －D 图像......................................141
10.1.3 动画效果(Animation).....................141
10.2 建立图(BUILDING GRAPHS) ..................142
10.2.1 为图表设定输出选项(Setting Output Options for Graphs) ....142
10.2.2 设置图外观选项(Setting Appearance Options for Graphs) ....142
10.3 使用图表.....144
10.3.1 一般图表窗口选项........................145
10.4 点图节点(PLOT NODE) ............................146
10.4.1 为点图节点设置选项（Setting Options for the Plot Node ）.148
10.4.2 使用点图(using a plot graph) ......150
10.5 多点图节点（MULTIPLOT NODE） .......153
10.5.1 为多点图节点设置选项（Setting Options for the Multiplot Node ）...............................153
10.5.2 使用一个多点图（Using a Multiplot Graph ）.......................154
10.6 分布节点（DISTRIBUTION NODE） .......155
10.6.1 设置分布节点选项（Setting Options for the Distribution Node ）..................................155
10.6.2 使用一个分布图（Using a Distribution Graph ）..................156
10.7 直方图节点（HISTOGRAM NODE）.......157
10.7.1 设置直方图节点更多选项（Setting Additional Options for the Histogram Node ）.......158
10.7.2 使用一个直方图（Using a Histogram Graph ）....................158
10.8 堆积图节点COLLECTION NODE.............161
10.8.1 设置堆积图节点的更多选项（Setting Additional Options for the Collection Node ）....162
10.8.2 堆积图的使用（Using a Collection Graph ）.........................162
10.9 WEB 图节点..164
10.9.1 设置Web 图节点选项（Setting Options for the Web Node ）165
10.9.2 设置Web 图节点的更多选项（Setting Additional Options for the Web Node ）.............166
10.9.3 Web 图节点的外观选项（Appearance Options for the Web Plot ）.................................167
10.9.4 Web 图像的使用（Using a Web Graph ）...............................168
10.10 评估图表节点（EVALUATION CHART NODE）...........................171
10.10.1 置评估图表节点选项（Setting Options for the Evaluation Chart Node ）..................173
10.10.2 读取模型评估的结果（Reading the Results of a Model Evaluation ）........................175
10.10.3 一个评估图表的使用（Using an Evaluation Chart ）.......176
第11 章建模节点..................................... 177
11.1 建模节点概述........................................177
11.1.1 建模节点字段选项........................177
11.2 神经网络节点........................................179
11.2.1 神经网络节点模型选项................180
11.2.2 神经网络节点的附加选项............182
11.2.3 神经网络节点高级选项——快速方法..................................184
11.2.4 神经网络节点高级选项——动态方法..................................184
11.2.5 神经网络节点高级选项——多重方法..................................185
11.2.6 神经网络节点高级选项——修剪方法..................................186
11.2.7 神经网络节点高级选项——RBFN 方法...............................187
11.2.8 神经网络节点高级选项——彻底修剪方法..........................188
11.2.9 神经网络节点学习比率................188
11.3 KOHENEN 节点.......................................188
11.3.1 Kohenen 节点模型选项................189
11.3.2 Kohenen 节点高级选项................190
11.4 C5.0 节点.....192
11.4.1 C5.0 节点模型选项.......................193
11.4.2 错误归类损失选项........................194
11.5 线性回归节点........................................195
11.5.1 线性回归节点模型选项................196
11.5.2 线性回归节点高级选项................197
11.5.3 线性回归节点单步选项................198
11.5.4 线性回归节点输出选项................198
11.6 广义规则归纳节点................................199
11.6.1 广义规则归纳节点模型选项........200
11.7 APRIORI 节点.........................................201
11.7.1 Apriori 节点模型选项..................201
11.7.2 Apriori 节点高级选项..................202
11.8 K-MEANS 节点.......................................204
11.8.1 K-Means 节点建模选项...............205
11.8.2 K-Means 节点高级选项...............206
11.9 逻辑斯谛回归节点................................206
11.9.1 逻辑斯谛回归节点模型选项........207
11.9.2 逻辑斯谛回归节点高级选项........208
11.9.3 逻辑斯谛回归节点收敛选项........209
11.9.4 逻辑斯谛回归输出选项................210
11.10 因子分析/主成分节点.......................211
11.10.1 因子分析/ 主成分节点模型选项.........................................212
11.10.2 因子分析/ 主成分节点高级选项.........................................213
11.10.3 因子分析/ 主成分节点旋转选项.........................................214
11.11 两步聚类节点....................................215
11.11.1 两步聚类型节点模型选项............216
11.12 分类回归树节点................................217
11.12.1 分类回归树节点模型选项........218
11.12.2 ??类回归树节点高级选项........218
11.12.3 分类回归树节点终止选项........220
11.12.4 分类回归树节点先验概率选项221
11.13 序列节点..222
11.13.1 序列节点字段选项....................223
11.13.2 序列节点模型选项....................225
11.13.3 序列节点高级选项....................226
第12 章输出节点..................................... 228
12.1 输出节点概述........................................228
12.2 使用输出.....228
12.3 输出浏览菜单........................................229
12.3.1 发布到Web ....................................230
12.4 输出节点输出条目................................230
12.5 表格节点.....231
12.5.1 表格节点设置条目........................232
12.5.2 表格节点格式条目........................232
12.5.3 表格浏览器....................................233
12.6 矩阵节点.....234
12.6.1 矩阵节点设置条目........................234
12.6.2 矩阵节点外观条目........................236
12.6.3 矩阵输出浏览器............................237
12.7 分析节点.....237
12.7.1 分析节点analysis 条目.................238
12.7.2 分析输出浏览器............................239
12.8 统计量节点..240
12.8.1 统计量节点设置条目....................241
12.8.2 统计量输出浏览器........................242
12.9 质量节点.....243
12.9.1 质量节点质量条目........................244
12.9.2 质量节点输出浏览器....................244
12.10 报告节点..246
12.10.1 报告节点模板条目....................246
12.10.2 报告节点输出浏览器................247
12.11 设置全局节点....................................248
12.11.1 设置全局节点设置条目............248
12.12 方案发布节点（SOLUTION PUBLISHER NODE） .........................249
12.12.1 为方案发布节点设置选项........250
12.13 数据库输出节点................................250
12.13.1 数据库节点输出条目................251
12.14 平面文件节点....................................252
12.14.1 平面文件输出条目....................252
12.15 SPSS 输出节点.................................253
12.15.1 SPSS 输出节点输出条目..............253
12.16 SAS 输出节点....................................254
12.16.1 SAS 输出节点输出条目................254
12.17 EXCEL 节点.........................................255
12.17.1 Excel 节点输出条目......................255
12.18 SPSS 程序节点.................................255
12.18.1 SPSS 程序节点语法条目..............256
12.18.2 SPSS 程序输出浏览器..................257
12.19 应用软件帮助....................................258
第13 章生成模型..................................... 259
13.1 生成模型概述........................................259
13.2 在生成模型选项板中利用生成模型进行操作...............................259
13.3 在数据流中使用生成模型....................261
13.4 使用生成模型浏览器............................261
13.5 生成网络节点........................................262
13.5.1 生成的神经网络总结条目............263
13.5.2 从神经网络中生成一个过滤节点264
13.6 生成KOHONEN 节点..............................264
13.6.1 生成的Kohonen 网络summary 条目.....................................265
13.7 生成的K-MEANS 节点...........................266
13.7.1 生成的K-Means 模型条目...........267
13.7.2 生成的K-Means 总结条目...........268
13.8 LOGISTIC 回归方程节点.........................268
13.8.1 Logistic 回归方程总结条目..........269
13.8.2 高级Logistic 回归输出.................271
13.9 线性回归方程节点................................272
13.9.1 线性回归等式总结条目................272
13.9.2 线性回归方程的高级输出............274
13.10 因子方程节点....................................275
13.10.1 因子方程模型条目....................275
13.10.2 因子方程总结条目....................276
13.10.3 因子方程高级输出....................278
13.11 未精练的规则模型............................279
13.11.1 未精练规则的模型条目............279
13.11.2 未精练规则的总结条目............280
13.11.3 生成规则集................................281
13.12 生成的规则集节点............................281
13.12.1 生成的规则集模型条目............282
13.12.2 生成的规则集总结条目............284
13.13 生成的决策树节点............................284
13.13.1 决策树模型条目........................285
13.13.2 决策树浏览条目........................288
13.13.3 决策树总结条目........................289
13.13.4 从决策树生成规则集................290
13.13.5 改进的C5.0 模型......................291
13.14 生成两步聚类节点............................291
13.14.1 生成的两步模型条目................292
13.14.2 生成的两步总结条目................293
13.14.3 生成的序列规则节点................293
13.14.4 序列规则模型条目....................294
13.14.5 序列规则的总结条目................296
13.14.6 从序列规则节点生成规则超级节点..................................297
第14 章输出模型..................................... 299
14.1 模型输出概论........................................299
14.1.1 模型的输出....................................299
14.2 PMML 输出.300
14.3 C 代码输出..300
14.3.1 输出C5.0 决策树和规则集..........300
14.3.2 输出网络（Exporting Nets ）........301
14.3.3 输出径向基函数网络网络（Exporting Radial Basis Function (RBF) Nets ）.................303
14.3.4 输出Kohonen 网络........................305
14.3.5 输出K-Means 模型（Exporting K-Means Models ）.............307
14.3.6 字段名（Field Names ）................308
14.3.7 模型输出的错误代码（Error Codes for Model Export ）......309
第15 章超级节点..................................... 310
15.1 概要.............310
15.2 超级节点类型（TYPES OF SUPERNODES） .....................................310
15.3 创建一个超级节点（CREATING A SUPERNODE） ..........................312
15.3.1 嵌套超级节点（Nesting SuperNodes ）..................................314
15.3.2 有效超级节点举例（Examples of Valid SuperNodes ）.........314
15.3.3 无效超级节点举例（Examples of Invalid SuperNodes ）......315
15.4 编辑超级节点（EDITING A SUPERNODE） .....................................316
15.4.1 修改超级节点的类型（Modifying SuperNode Type ）...........317
15.4.2 注释和重命名超级节点（Annotating and Renaming SuperNodes ）..............................317
15.4.3 超级节点参数（SuperNode Parameters ）.............................318
15.4.4 超级节点和缓存（SuperNodes and Caching ）......................321
15.4.5 超级节点和脚本（SuperNodes and Scripting ）....................322
15.5 保存并装载超级节点（SAVING AND LOADING SUPERNODES） ....323
第16 章建立项目和报告......................... 324
16.1 项目介绍（INTRODUCTION TO PROJECTS）.....................................324
CRISP-DM 观察方式....................................325
Classes 观察窗口（Classes View ）..............325
16.2 建立项目（BUILDING A PROJECT）.......326
16.2.1 创建新项目（Creating a New Project ）................................326
16.2.2 添加到项目中（Adding to a Project ）...................................326
16.2.3 设置项目属性（Setting Project Properties ）.........................328
16.2.4 评注项目（Annotating a Project ）.........................................328
16.2.5 对象属性（Object Properties ）....330
16.2.6 关闭项目（Closing a Project ）....330
16.3 创建报告（BUILDING A REPORT）........330
16.3.1 生成报告（Generating Reports ）.331
16.3.2 保存和输出报告（Saving and Exporting Reports ）..............332
第17 章批处理模式（BATCH MODE EXECUTION）................. 335
17.1 批处理模式一览（INTRODUCTION TO BATCH MODE） ..................335
17.2 在批处理模式下工作（WORKING IN BATCH MODE） ...................335
17.2.1 软件调用（Invoking the Software ）.......................................335
17.2.2 使用命令行参数（Using Command Line Arguments ）.........336
17.2.3 批处理模式日志文件（Batch Mode Log Files ）...................336
17.2.4 批处理模式中的脚本编程（Scripting in Batch Mode ）.......336
17.2.5 在批处理模式中使用参数（Using Parameters in Batch Mode ）...................................337
17.2.6 在批处理模式下输出（Working with Output in Batch Mode ）......................................338
第18 章CLEMENTINE 中的脚本编程... 339
18.1 脚本编程介绍........................................339
18.1.1 脚本类型........................................339
18.2 在用户界面上进行脚本编程.................340
18.2.1 在流中使用脚本............................340
18.2.2 在超级节点中使用脚本................342
18.2.3 使用独立脚本................................343
18.3 以批处理模式编写脚本........................345
第19 章CLEMENTINE 外部模块接口.. 346
19.1 介绍.............346
19.2 运行CEMI ..346
19.3 系统体系结构........................................346
19.4 规范说明文件........................................347
19.4.1 参数.....348
19.4.2 外部程序........................................348
19.4.3 命令行选项....................................348
19.4.4 编辑对话框....................................348
19.4.5 输入和输出字段............................349
19.4.6 输入和输出文件............................349
19.4.7 元文件..349
19.4.8 结果.....350
19.4.9 返回代码........................................350
19.5 限制.............350
19.6 规范说明文件示例................................350
19.6.1 节点说明........................................351
19.6.2 核心说明........................................351
19.6.3 参数.....351
19.6.4 执行.....352
19.6.5 选项.....352
19.6.6 控件.....353
19.6.7 输出字段........................................354
19.6.8 输出数据........................................354
19.6.9 返回代码........................................354
19.6.10 完整的规范文件........................355
19.7 CEMI 节点管理.....................................357
19.7.1 增加CEMI 节点............................358
19.7.2 清除CEMI 节点............................358
19.8 编写外部程序的技巧............................358
第20 章应用示例..................................... 360
20.1 概况.............360
20.2 状态监测示例........................................360
20.2.1 审视数据........................................361
20.2.2 数据准备........................................363
20.2.3 学习.....364
20.2.4 测试.....365
20.3 欺诈稽查示例........................................366
20.3.1 数据获取........................................366
20.3.2 数据探索........................................367
20.3.3 训练神经网络................................370
20.3.4 总结.....372
20.4 零售业示例..372
20.4.1 数据审核........................................373
20.4.2 学习和测试....................................376
20.5 市场购物篮分析示例............................377
20.5.1 获取数据........................................377
20.5.2 购物内容关联分析........................378
20.5.3 客户细分........................................381
20.5.4 总结.....383

PLSQLDev6.0用户指南

2008-08-03 21:10:52

PL/SQL Developer 6.0 用户指南,适合新手上路,本书是公司内部资料，所以没有出版社，没有作者。
目录
目录 3
1. 介绍.....................................8
2. 安装.....................................12
2.1 系统需求................................12
2.2 工作站安装..............................12
2.3 基于服务器安装..........................12
2.4 脚本安装................................13
2.5 卸载 PL/SQL DEVELOPER ..................13
3. 编写程序.................................14
3.1 创建程序................................14
3.2 保存程序................................15
3.3 修改程序................................16
3.4 编译程序................................16
4. 测试程序.................................18
4.1 创建测试脚本............................18
4.2 运行测试脚本............................19
4.3 变量类型................................20
4.4 保存测试脚本............................21
4.5 跟踪运行时间错误........................22
4.6 包声明和 JAVA 会话声明..................22
4.7 查看结果集..............................23
4.8 查看 DBMS_OUTPUT........................23
4.9 查看 HTP 输出...........................23
4.10 调试...................................23
4.11 跟踪运行...............................27
5. 优化.....................................29
5.1 使用解释计划窗口........................29
5.2 自动统计................................30
5.3 PL/SQL 概览图...........................31
5.4 SQL 跟踪................................32
6. 专用 SQL.................................34
6.1 使用 SQL 窗口...........................34
6.2 结果表格处理............................35
6.3 实例模式查询............................39
6.4 连接查询................................40
6.5 置换变量................................41
6.6 更新数据库..............................42
6.7 查看和编辑 XMLTYPE 列...................43
6.8 直接查询导出............................43
6.9 保存 SQL 脚本...........................43
6.10 创建标准查询...........................44
7. 命令窗口.................................45
7.1 输入 SQL 语句和命令.....................45
7.2 开发命令文件............................46
7.3 支持命令................................47
8. 创建与修改非 PL/SQL 对象.................50
8.1 表定义编辑器............................50
8.2 序列定义编辑器..........................62
8.3 同义词定义编辑器........................62
8.4 库定义编辑器............................63
8.5 目录定义编辑器..........................63
8.6 作业定义编辑器..........................64
8.7 队列定义编辑器..........................64
8.8 队列表定义编辑器........................65
8.9 用户定义编辑器..........................66
8.10 角色定义编辑器.........................69
8.11 概要文件定义编辑器.....................70
8.12 数据库连接定义编辑器...................70
9. 报告.....................................71
9.1 标准报告................................71
9.2 定制报告................................72
9.3 变量....................................73
9.4 精制版面................................77
9.5 风格库..................................84
9.6 选项....................................84
9.7 报告菜单................................86
10. 工程....................................87
10.1 创建一个新工程.........................87
10.2 保存工程...............................88
10.3 添加源文件到工程.......................88
10.4 添加数据库对象到工程...................88
10.5 用工程项目工作.........................89
10.6 编译工程...............................89
11. 任务项目................................91
11.1 创建任务项目...........................92
11.2 编辑任务项目...........................92
11.3 关闭任务项目...........................93
11.4 删除任务项目...........................93
12. 窗口、数据库会话和事务..................94
12.1 会话模式...............................94
12.2 运行于多路会话或双路会话模式...........94
13. 浏览对象................................95
13.1 使用浏览器.............................95
13.2 浏览器过滤器...........................100
13.3 浏览器文件夹...........................101
14. 首选项..................................104
14.1 ORACLE – 连接..........................105
14.2 ORACLE – 选项..........................106
14.3 ORACLE – 调试器........................107
14.4 ORACLE – 输出..........................108
14.5 ORACLE – 跟踪..........................109
14.6 ORACLE – 概览图........................109
14.7 ORACLE – 登录历史......................111
14.8 用户界面 – 选项....................... 113
14.9 用户界面 – 工具栏..................... 115
14.10 用户界面 – 浏览器.....................116
14.11 用户界面 – 编辑器.....................117
14.12 用户界面 – 字体.......................119
14.13 用户界面 – 代码助手...................120
14.14 用户界面 – 键配置.....................121
14.15 用户界面 – 外观.......................122
14.16 用户界面 – 日期/时间..................123
14.17 窗口类型 – 程序窗口...................124
14.18 窗口类型 – SQL 窗口...................126
14.19 窗口类型 – 测试窗口...................128
14.20 窗口类型 – 计划窗口...................128
14.21 工具 – 差异...........................128
14.22 工具 – 数据生成器.....................129
14.23 工具 – 任务列表.......................130
14.24 工具 – 重新调用声明...................130
14.25 文件 – 目录...........................131
14.26 文件 – 扩展名.........................132
14.27 文件 – 备份...........................133
14.28 文件 – HTML/XML.......................134
14.29 其它 – 打印...........................135
14.30 其它 – 更新与消息.....................136
14.31 首选项集..............................137
15. 工具....................................139
15.1 浏览器.................................139
15.2 查找数据库对象.........................140
15.3 编译无效对象...........................141
15.4 导出表.................................142
15.5 导入表.................................145
15.6 导出用户对象...........................147
15.7 文本导入器.............................148
15.8 数据生成器.............................151
15.9 比较用户对象...........................155
15.10 事件监视器............................157
15.11 会话..................................158
15.12 自定义工具............................159
16. 编辑器..................................165
16.1 选择功能...............................165
16.2 列选择.................................165
16.3 指引线.................................166
16.4 代码助手...............................166
16.5 重新调用语句...........................167
16.6 专用复制...............................168
16.7 前后关系敏感帮助.......................169
16.8 数据库对象弹出式菜单...................169
16.9 解释计划...............................169
16.10 宏....................................169
16.11 代码目录..............................171
16.12 代码层次..............................172
16.13 超链接导航............................172
16.14 浏览按钮..............................173
17. 大数据编辑器............................174
17.1 编辑纯文本.............................175
17.2 编辑 RTF...............................175
17.3 编辑 XML...............................176
17.4 编辑图象...............................177
17.5 编辑十六进制数据.......................177
17.6 调用外部查看器或编辑器.................179
18. 查询设计器..............................181
18.1 创建新的 SELECT 语句...................181
18.2 修改现有的SELECT 语句..................184
18.3 处理查询定义...........................184
18.4 查询设计器首选项.......................185
19. PL/SQL 美化器...........................187
19.1 定义选项...............................187
19.2 定义规则...............................188
19.3 使用美化器.............................189
20. 模板....................................190
20.1 模板窗口...............................190
20.2 使用模板...............................191
20.3 创建和修改模板.........................192
21. 窗口列表................................197
22. 授权....................................198
22.1 允许授权...............................198
22.2 定义授权...............................199
22.3 禁止授权...............................200
23. 帮助系统................................201
23.1 MS 帮助文件............................201
23.2 HTML 手册..............................201
24. 定制....................................205
24.1 首选项.................................205
24.2 窗口版面...............................205
24.3 在线文档...............................205
24.4 命令行参数.............................207
24.5 SQL、PL/SQL、命令、JAVA 和 XML 关键词..209
24.6 插件...................................209

数据库基础视频

2008-07-11 12:15:16

Flash全程教学,通俗易懂

SQL.Server.2005集成服务指导手册(数据库实例)

2008-07-09 11:49:13

《SQL Server 2005集成服务指导手册》

内客包括:

- 有 CHM 和 PDF 格式书
- Practice Files
- Sample databases

分二次上传
1.SQL.Server.2005集成服务指导手册+实例
2.SQL.Server.2005集成服务指导手册(数据库实例)

《SQL Server 2005集成服务指导手册》共分14章，以SQL Server2005的管理、应用为核心，从了解数据库在网站中的重要性和认识SQL Server2005入手，全面介绍了SQL Server2005的安装、配置、结构化查询语言、数据库和表的管理、数据备份与恢复、数据安全管理、XML支持、数据库报表服务、数据库常用管理工具、网站数据库访问、网站数据库应用实例等内容。从内容上紧扣SQL Server2005的新特性、新功能、新技术，以详尽的实例，深入浅出地介绍了SQL Server2005在数据库管理和网站应用方面的能力。

SQL.Server.2005集成服务指导手册+实例

2008-07-09 09:06:32

先进数据挖掘技术（Advanced Data Mining Techniques2008）

2008-07-06 13:51:44

1 Introduction...............................................................................................3
What is Data Mining?..........................................................................5
What is Needed to Do Data Mining.....................................................5
Business Data Mining..........................................................................7
Data Mining Tools ...............................................................................8
Summary..............................................................................................8
2 Data Mining Process.................................................................................9
CRISP-DM ..........................................................................................9
Business Understanding.............................................................11
Data Understanding ...................................................................11
Data Preparation ........................................................................12
Modeling ...................................................................................15
Evaluation..................................................................................18
Deployment................................................................................18
SEMMA.............................................................................................19
Steps in SEMMA Process..........................................................20
Example Data Mining Process Application.......................................22
Comparison of CRISP & SEMMA....................................................27
Handling Data....................................................................................28
Summary............................................................................................34
3 Memory-Based Reasoning Methods.......................................................39
Matching ............................................................................................40
Weighted Matching....................................................................43
Distance Minimization.......................................................................44
Software.............................................................................................50
Summary............................................................................................50
Appendix: Job Application Data Set..................................................51
4 Association Rules in Knowledge Discovery........................................... 53
Market-Basket Analysis.....................................................................55
Market Basket Analysis Benefits...............................................56
Demonstration on Small Set of Data ......................................... 57
Real Market Basket Data ................................................................... 59
The Counting Method Without Software ..................................62
Conclusions........................................................................................68
5 Fuzzy Sets in Data Mining...................................................................... 69
Fuzzy Sets and Decision Trees .......................................................... 71
Fuzzy Sets and Ordinal Classification ............................................... 75
Fuzzy Association Rules....................................................................79
Demonstration Model ................................................................80
Computational Results...............................................................84
Testing .......................................................................................84
Inferences...................................................................................85
Conclusions........................................................................................86
6 Rough Sets .............................................................................................. 87
A Brief Theory of Rough Sets ........................................................... 88
Information System....................................................................88
Decision Table ...........................................................................89
Some Exemplary Applications of Rough Sets................................... 91
Rough Sets Software Tools................................................................93
The Process of Conducting Rough Sets Analysis.............................. 93
1 Data Pre-Processing................................................................94
2 Data Partitioning .....................................................................95
3 Discretization ..........................................................................95
4 Reduct Generation ..................................................................97
5 Rule Generation and Rule Filtering ........................................ 99
6 Apply the Discretization Cuts to Test Dataset...................... 100
7 Score the Test Dataset on Generated Rule set (and
measuring the prediction accuracy) ...................................... 100
8 Deploying the Rules in a Production System ....................... 102
A Representative Example...............................................................103
Conclusion .......................................................................................109
7 Support Vector Machines ..................................................................... 111
Formal Explanation of SVM............................................................112
Primal Form.............................................................................114
Dual Form................................................................................114
Soft Margin..............................................................................114
Non-linear Classification .................................................................115
Regression................................................................................116
Implementation ........................................................................116
Kernel Trick.............................................................................117
Use of SVM – A Process-Based Approach .....................................118
Support Vector Machines versus Artificial Neural Networks .........121
Disadvantages of Support Vector Machines....................................122
8 Genetic Algorithm Support to Data Mining .........................................125
Demonstration of Genetic Algorithm ..............................................126
Application of Genetic Algorithms in Data Mining ........................131
Summary..........................................................................................132
Appendix: Loan Application Data Set.............................................133
9 Performance Evaluation for Predictive Modeling ................................137
Performance Metrics for Predictive Modeling ................................137
Estimation Methodology for Classification Models ........................140
Simple Split (Holdout).....................................................................140
The k-Fold Cross Validation............................................................141
Bootstrapping and Jackknifing ........................................................143
Area Under the ROC Curve.............................................................144
Summary..........................................................................................147
10 Applications of Methods ....................................................................151
Memory-Based Application.............................................................151
Association Rule Application ..........................................................153
Fuzzy Data Mining ..........................................................................155
Rough Set Models............................................................................155
Support Vector Machine Application ..............................................157
Genetic Algorithm Applications......................................................158
Japanese Credit Screening .......................................................158
Product Quality Testing Design...............................................159
Customer Targeting .................................................................159
Medical Analysis .....................................................................160
Predicting the Financial Success of Hollywood Movies ................. 162
Problem and Data Description.................................................163
Comparative Analysis of the Data Mining Methods ............... 165
Conclusions......................................................................................167
Bibliography ............................................................................................ 169
Index ........................................................................................................ 177

SQL Server 2000 数据库设计权威指南

2008-06-20 09:23:37

【编辑推荐】
SQL Server 2000是最新且功能最强的Microsoft的数据仓储和关系数据库管理系统。
本书阐述了能够让数据库设计得更加有效地应用SQL Server 2000全部功能的技术要点。本收没有沿用传统的关系数据库设计方法，而是从“现实世界”的角度考虑设计。为此，书中提供了一个完整的案例研究以阐明：从最初客户需求的收集，到逻辑模型的开发，直到系统的全部实现。
本书的使用对象：
本书的阅读对象是那些希望对常见的关系数据库设计问题有更多了解的开发人员。本书在帮助读者熟悉SQL Server和Transact-SQL语言的同时,还着重强调了作为一个有经验的数据库程序员应该掌握的关系数据为理论和设计方面的相关知识。
主要内容：
数据库设计方法概要，包括OLAP和OLTP
介绍关系数据库设计模型
规范化
利用视图、触发器和存储过程确保数据的完整性
用户自定义函数和约束
事务处理
硬件环境和满足设计需求
设计实现中的测试
【内容简介】
本书介绍了实现一个数据库的整个过程，从概念到设计，从表的生成到表的存取。此外，还提供了在实际应用中所需的必要知识。全书分为两大部分。第1部分包含了数据库的逻辑设计，第2部分讨论了数据库的物理设计及其实现。每一部分的开始都有一个引言，包含了该章的内容提要等信息。
通过阅读本书可以使你对SQL Server数据库设计的理解提升到更高的层次上。
本书适合数据库结构设计人员、数据库实现人员以及数据库程序员阅读。

【目录】
译者序
前言
第1部分逻辑设计
第1章数据库设计方法引论
第2章收集数据库项目的信息
第3章数据库基本概念
第4章实体、属性、联系和业务规则
第5章数据模型化
第6章规范化技术
第7章高级规范化
第8章结束逻辑设计阶段
第2部分物理设计与实现
第9章设计物理结构
第10章设计与实现基本的物理结构
第11章数据完整性
第12章高级数据存取与修改技术
第13章确定硬件需求
第14章完成项目
附录A Codd提出的RDBMS的12项准则

Teach Yourself SQL in 24 Hours 4th Edition (24小时自学SQL 第四版 2008最新版)

2008-06-20 09:20:32

In just 24 lessons of one hour or less, you will learn professional
techniques to design and build efficient databases and query them to
extract useful information. Using a straightforward, step-by-step
approach, each lesson builds on the previous one, allowing you to learn
the essentials of ANSI SQL from the ground up.

Example code demonstrates the authors’ professional techniques, while
exercises written for MySQL offer the reader hands-on learning with an
open-source database. Included are advanced techniques for using views,
managing transactions, database administration, and extending SQL.

Step-by-step instructions carefully walk you through the most common SQL
tasks.
Q&As, Quizzes, and Exercises at the end of each chapter help you test
your knowledge.
Notes and Tips point out shortcuts and solutions.
New terms are clearly defined and explained.

Learn how to…
- Use SQL-2003, the latest standard for the Structured Query Language
- Design and deploy efficient, secure databases
- Build advanced queries for information retrieval
- Sort, group, and summarize information for best presentation
- Tune databases and queries for maximum performance
- Understand database administration and security techniques

For more than ten years the authors have studied, applied, and
documented the SQL standard and its application to critical database
systems.

Ryan Stephens and Ron Plew are entrepreneurs, speakers, and cofounders
of Perpetual Technologies, Inc. (PTI), a fast-growing IT management and
consulting firm which specializes in database technologies. They taught
database courses for Indiana University—Purdue University in
Indianapolis for five years and have authored more than a dozen books on
Oracle, SQL, database design, and the high availability of critical
systems.

Arie D. Jones is Senior SQL Server database administrator and analyst
for PTI. He is a regular speaker at technical events and has authored
several books and articles.

Introduction................................................................................ 1
Part I: A SQL Concepts Overview
HOUR 1 Welcome to the World of SQL ........................................................ 7
Part II: Building Your Database
HOUR 2 Defining Data Structures ............................................................. 27
3 Managing Database Objects ........................................................ 41
4 The Normalization Process .......................................................... 61
5 Manipulating Data .................................................................... 73
6 Managing Database Transactions................................................. 87
Part III: Getting Effective Results from Queries
HOUR 7 Introduction to the Database Query ............................................ 101
8 Using Operators to Categorize Data............................................. 117
9 Summarizing Data Results from a Query ..................................... 141
10 Sorting and Grouping Data........................................................ 151
11 Restructuring the Appearance of Data ......................................... 165
12 Understanding Dates and Times ................................................. 185
Part IV: Building Sophisticated Database Queries
HOUR 13 Joining Tables in Queries ........................................................... 203
14 Using Subqueries to Define Unknown Data................................... 221
15 Combining Multiple Queries into One ......................................... 235
Part V: SQL Performance Tuning
HOUR 16 Using Indexes to Improve Performance ........................................ 253
17 Improving Database Performance ............................................... 265
Part VI: Using SQL to Manage Users and Security
HOUR 18 Managing Database Users ......................................................... 283
19 Managing Database Security...................................................... 297
Part VII: Summarized Data Structures
HOUR 20 Creating and Using Views and Synonyms..................................... 313
21 Working with the System Catalog ............................................... 329
Part VIII: Applying SQL Fundamentals in Today’s World
HOUR 22 Advanced SQL Topics ................................................................ 343
23 Extending SQL to the Enterprise, the Internet, and the Intranet........ 359
24 Extensions to Standard SQL........................................................ 369
Part IX: Appendixes
A Common SQL Commands ......................................................... 381
B Using MySQL for Exercises ......................................................... 387
C Answers to Quizzes and Exercises ................................................ 391
D CREATE TABLE Statements for Book Examples ................................ 435
E INSERT Statements for Data in Book Examples .............................. 437
F Bonus Exercises ........................................................................ 441
Glossary.................................................................................. 447
Index ..................................................................................... 451

数据挖掘论文收藏(10篇)

2008-06-18 20:37:00

压缩包中10篇有关数据挖掘的论文，题目如下所示：
1、多媒体数据集中的数据挖掘：系统框架和方法.pdf
2、基于数据挖掘的模块评估法.pdf
3、基于数据挖掘技术的高校管理决策支持系统.pdf
4、空间数据挖掘技术.pdf
5、空间数据挖掘与发展趋势研究.pdf
6、数据挖掘及其应用研究回顾.pdf
7、数据挖掘技术及其应用简介.pdf
8、数据挖掘技术在商业银行中的应用研究.pdf
9、数据挖掘在商务中的应用.pdf
10、遗传算法在数据挖掘中的应用.pdf
建议使用最新版的Adobe Reader 8打开该PDF文档。

数据挖掘：概念与技术（英文影印版·第2版）

2008-06-17 23:05:43

Chapter 1 Introduction 1
1.1 What Motivated Data Mining? Why Is It Important? 1
1.2 So, What Is Data Mining? 5
1.3 Data Mining桹n What Kind of Data? 9
1.3.1 Relational Databases 10
1.3.2 Data Warehouses 12
1.3.3 Transactional Databases 14
1.3.4 Advanced Data and Information Systems and Advanced
Applications 15
1.4 Data Mining Functionalities梂hat Kinds of Patterns Can Be
Mined? 21
1.4.1 Concept/Class Description: Characterization and
Discrimination 21
1.4.2 Mining Frequent Patterns, Associations, and Correlations 23
1.4.3 Classification and Prediction 24
1.4.4 Cluster Analysis 25
1.4.5 Outlier Analysis 26
1.4.6 Evolution Analysis 27
1.5 Are All of the Patterns Interesting? 27
1.6 Classification of Data Mining Systems 29
1.7 Data Mining Task Primitives 31
1.8 Integration of a Data Mining System with
a Database or DataWarehouse System 34
1.9 Major Issues in Data Mining 36
ix
x Contents
1.10 Summary 39
Exercises 40
Bibliographic Notes 42
Chapter 2 Data Preprocessing 47
2.1 Why Preprocess the Data? 48
2.2 Descriptive Data Summarization 51
2.2.1 Measuring the Central Tendency 51
2.2.2 Measuring the Dispersion of Data 53
2.2.3 Graphic Displays of Basic Descriptive Data Summaries 56
2.3 Data Cleaning 61
2.3.1 Missing Values 61
2.3.2 Noisy Data 62
2.3.3 Data Cleaning as a Process 65
2.4 Data Integration and Transformation 67
2.4.1 Data Integration 67
2.4.2 Data Transformation 70
2.5 Data Reduction 72
2.5.1 Data Cube Aggregation 73
2.5.2 Attribute Subset Selection 75
2.5.3 Dimensionality Reduction 77
2.5.4 Numerosity Reduction 80
2.6 Data Discretization and Concept Hierarchy Generation 86
2.6.1 Discretization and Concept Hierarchy Generation for
Numerical Data 88
2.6.2 Concept Hierarchy Generation for Categorical Data 94
2.7 Summary 97
Exercises 97
Bibliographic Notes 101
Chapter 3 DataWarehouse and OLAP Technology: An Overview 105
3.1 What Is a DataWarehouse? 105
3.1.1 Differences between Operational Database Systems
and Data Warehouses 108
3.1.2 But, Why Have a Separate Data Warehouse? 109
3.2 A Multidimensional Data Model 110
3.2.1 From Tables and Spreadsheets to Data Cubes 110
3.2.2 Stars, Snowflakes, and Fact Constellations:
Schemas for Multidimensional Databases 114
3.2.3 Examples for Defining Star, Snowflake,
and Fact Constellation Schemas 117
Contents xi
3.2.4 Measures: Their Categorization and Computation 119
3.2.5 Concept Hierarchies 121
3.2.6 OLAP Operations in the Multidimensional Data Model 123
3.2.7 A Starnet Query Model for Querying
Multidimensional Databases 126
3.3 DataWarehouse Architecture 127
3.3.1 Steps for the Design and Construction of Data Warehouses 128
3.3.2 A Three-Tier Data Warehouse Architecture 130
3.3.3 Data Warehouse Back-End Tools and Utilities 134
3.3.4 Metadata Repository 134
3.3.5 Types of OLAP Servers: ROLAP versus MOLAP
versus HOLAP 135
3.4 DataWarehouse Implementation 137
3.4.1 Efficient Computation of Data Cubes 137
3.4.2 Indexing OLAP Data 141
3.4.3 Efficient Processing of OLAP Queries 144
3.5 From DataWarehousing to Data Mining 146
3.5.1 Data Warehouse Usage 146
3.5.2 From On-Line Analytical Processing
to On-Line Analytical Mining 148
3.6 Summary 150
Exercises 152
Bibliographic Notes 154
Chapter 4 Data Cube Computation and Data Generalization 157
4.1 Efficient Methods for Data Cube Computation 157
4.1.1 A Road Map for the Materialization of Different Kinds
of Cubes 158
4.1.2 Multiway Array Aggregation for Full Cube Computation 164
4.1.3 BUC: Computing Iceberg Cubes from the Apex Cuboid
Downward 168
4.1.4 Star-cubing: Computing Iceberg Cubes Using
a Dynamic Star-tree Structure 173
4.1.5 Precomputing Shell Fragments for Fast High-Dimensional
OLAP 178
4.1.6 Computing Cubes with Complex Iceberg Conditions 187
4.2 Further Development of Data Cube and OLAP
Technology 189
4.2.1 Discovery-Driven Exploration of Data Cubes 189
4.2.2 Complex Aggregation at Multiple Granularity:
Multifeature Cubes 192
4.2.3 Constrained Gradient Analysis in Data Cubes 195
xii Contents
4.3 Attribute-Oriented Induction桝n Alternative
Method for Data Generalization and Concept Description 198
4.3.1 Attribute-Oriented Induction for Data Characterization 199
4.3.2 Efficient Implementation of Attribute-Oriented Induction 205
4.3.3 Presentation of the Derived Generalization 206
4.3.4 Mining Class Comparisons: Discriminating between
Different Classes 210
4.3.5 Class Description: Presentation of Both Characterization
and Comparison 215
4.4 Summary 218
Exercises 219
Bibliographic Notes 223
Chapter 5 Mining Frequent Patterns, Associations, and Correlations 227
5.1 Basic Concepts and a Road Map 227
5.1.1 Market Basket Analysis: A Motivating Example 228
5.1.2 Frequent Itemsets, Closed Itemsets, and Association Rules 230
5.1.3 Frequent Pattern Mining: A Road Map 232
5.2 Efficient and Scalable Frequent Itemset Mining Methods 234
5.2.1 The Apriori Algorithm: Finding Frequent Itemsets Using
Candidate Generation 234
5.2.2 Generating Association Rules from Frequent Itemsets 239
5.2.3 Improving the Efficiency of Apriori 240
5.2.4 Mining Frequent Itemsets without Candidate Generation 242
5.2.5 Mining Frequent Itemsets Using Vertical Data Format 245
5.2.6 Mining Closed Frequent Itemsets 248
5.3 Mining Various Kinds of Association Rules 250
5.3.1 Mining Multilevel Association Rules 250
5.3.2 Mining Multidimensional Association Rules
from Relational Databases and Data Warehouses 254
5.4 From Association Mining to Correlation Analysis 259
5.4.1 Strong Rules Are Not Necessarily Interesting: An Example 260
5.4.2 From Association Analysis to Correlation Analysis 261
5.5 Constraint-Based Association Mining 265
5.5.1 Metarule-Guided Mining of Association Rules 266
5.5.2 Constraint Pushing: Mining Guided by Rule Constraints 267
5.6 Summary 272
Exercises 274
Bibliographic Notes 280
Contents xiii
Chapter 6 Classification and Prediction 285
6.1 What Is Classification? What Is Prediction? 285
6.2 Issues Regarding Classification and Prediction 289
6.2.1 Preparing the Data for Classification and Prediction 289
6.2.2 Comparing Classification and Prediction Methods 290
6.3 Classification by Decision Tree Induction 291
6.3.1 Decision Tree Induction 292
6.3.2 Attribute Selection Measures 296
6.3.3 Tree Pruning 304
6.3.4 Scalability and Decision Tree Induction 306
6.4 Bayesian Classification 310
6.4.1 Bayes?Theorem 310
6.4.2 Na飗e Bayesian Classification 311
6.4.3 Bayesian Belief Networks 315
6.4.4 Training Bayesian Belief Networks 317
6.5 Rule-Based Classification 318
6.5.1 Using IF-THEN Rules for Classification 319
6.5.2 Rule Extraction from a Decision Tree 321
6.5.3 Rule Induction Using a Sequential Covering Algorithm 322
6.6 Classification by Backpropagation 327
6.6.1 A Multilayer Feed-Forward Neural Network 328
6.6.2 Defining a Network Topology 329
6.6.3 Backpropagation 329
6.6.4 Inside the Black Box: Backpropagation and Interpretability 334
6.7 Support Vector Machines 337
6.7.1 The Case When the Data Are Linearly Separable 337
6.7.2 The Case When the Data Are Linearly Inseparable 342
6.8 Associative Classification: Classification by Association
Rule Analysis 344
6.9 Lazy Learners (or Learning from Your Neighbors) 347
6.9.1 k-Nearest-Neighbor Classifiers 348
6.9.2 Case-Based Reasoning 350
6.10 Other Classification Methods 351
6.10.1 Genetic Algorithms 351
6.10.2 Rough Set Approach 351
6.10.3 Fuzzy Set Approaches 352
6.11 Prediction 354
6.11.1 Linear Regression 355
6.11.2 Nonlinear Regression 357
6.11.3 Other Regression-Based Methods 358
xiv Contents
6.12 Accuracy and Error Measures 359
6.12.1 Classifier Accuracy Measures 360
6.12.2 Predictor Error Measures 362
6.13 Evaluating the Accuracy of a Classifier or Predictor 363
6.13.1 Holdout Method and Random Subsampling 364
6.13.2 Cross-validation 364
6.13.3 Bootstrap 365
6.14 Ensemble Methods桰ncreasing the Accuracy 366
6.14.1 Bagging 366
6.14.2 Boosting 367
6.15 Model Selection 370
6.15.1 Estimating Confidence Intervals 370
6.15.2 ROC Curves 372
6.16 Summary 373
Exercises 375
Bibliographic Notes 378
Chapter 7 Cluster Analysis 383
7.1 What Is Cluster Analysis? 383
7.2 Types of Data in Cluster Analysis 386
7.2.1 Interval-Scaled Variables 387
7.2.2 Binary Variables 389
7.2.3 Categorical, Ordinal, and Ratio-Scaled Variables 392
7.2.4 Variables of Mixed Types 395
7.2.5 Vector Objects 397
7.3 A Categorization of Major Clustering Methods 398
7.4 Partitioning Methods 401
7.4.1 Classical Partitioning Methods: k-Means and k-Medoids 402
7.4.2 Partitioning Methods in Large Databases: From
k-Medoids to CLARANS 407
7.5 Hierarchical Methods 408
7.5.1 Agglomerative and Divisive Hierarchical Clustering 408
7.5.2 BIRCH: Balanced Iterative Reducing and Clustering
Using Hierarchies 412
7.5.3 ROCK: A Hierarchical Clustering Algorithm for
Categorical Attributes 414
7.5.4 Chameleon: A Hierarchical Clustering Algorithm
Using Dynamic Modeling 416
7.6 Density-Based Methods 418
7.6.1 DBSCAN: A Density-Based Clustering Method Based on
Connected Regions with Sufficiently High Density 418
Contents xv
7.6.2 OPTICS: Ordering Points to Identify the Clustering
Structure 420
7.6.3 DENCLUE: Clustering Based on Density
Distribution Functions 422
7.7 Grid-Based Methods 424
7.7.1 STING: STatistical INformation Grid 425
7.7.2 WaveCluster: Clustering Using Wavelet Transformation 427
7.8 Model-Based Clustering Methods 429
7.8.1 Expectation-Maximization 429
7.8.2 Conceptual Clustering 431
7.8.3 Neural Network Approach 433
7.9 Clustering High-Dimensional Data 434
7.9.1 CLIQUE: A Dimension-Growth Subspace Clustering Method 436
7.9.2 PROCLUS: A Dimension-Reduction Subspace Clustering
Method 439
7.9.3 Frequent Pattern朆ased Clustering Methods 440
7.10 Constraint-Based Cluster Analysis 444
7.10.1 Clustering with Obstacle Objects 446
7.10.2 User-Constrained Cluster Analysis 448
7.10.3 Semi-Supervised Cluster Analysis 449
7.11 Outlier Analysis 451
7.11.1 Statistical Distribution-Based Outlier Detection 452
7.11.2 Distance-Based Outlier Detection 454
7.11.3 Density-Based Local Outlier Detection 455
7.11.4 Deviation-Based Outlier Detection 458
7.12 Summary 460
Exercises 461
Bibliographic Notes 464
Chapter 8 Mining Stream, Time-Series, and Sequence Data 467
8.1 Mining Data Streams 468
8.1.1 Methodologies for Stream Data Processing and
Stream Data Systems 469
8.1.2 Stream OLAP and Stream Data Cubes 474
8.1.3 Frequent-Pattern Mining in Data Streams 479
8.1.4 Classification of Dynamic Data Streams 481
8.1.5 Clustering Evolving Data Streams 486
8.2 Mining Time-Series Data 489
8.2.1 Trend Analysis 490
8.2.2 Similarity Search in Time-Series Analysis 493
xvi Contents
8.3 Mining Sequence Patterns in Transactional Databases 498
8.3.1 Sequential Pattern Mining: Concepts and Primitives 498
8.3.2 Scalable Methods for Mining Sequential Patterns 500
8.3.3 Constraint-Based Mining of Sequential Patterns 509
8.3.4 Periodicity Analysis for Time-Related Sequence Data 512
8.4 Mining Sequence Patterns in Biological Data 513
8.4.1 Alignment of Biological Sequences 514
8.4.2 Hidden Markov Model for Biological Sequence Analysis 518
8.5 Summary 527
Exercises 528
Bibliographic Notes 531
Chapter 9 Graph Mining, Social Network Analysis, and Multirelational
Data Mining 535
9.1 Graph Mining 535
9.1.1 Methods for Mining Frequent Subgraphs 536
9.1.2 Mining Variant and Constrained Substructure Patterns 545
9.1.3 Applications: Graph Indexing, Similarity Search, Classification,
and Clustering 551
9.2 Social Network Analysis 556
9.2.1 What Is a Social Network? 556
9.2.2 Characteristics of Social Networks 557
9.2.3 Link Mining: Tasks and Challenges 561
9.2.4 Mining on Social Networks 565
9.3 Multirelational Data Mining 571
9.3.1 What Is Multirelational Data Mining? 571
9.3.2 ILP Approach to Multirelational Classification 573
9.3.3 Tuple ID Propagation 575
9.3.4 Multirelational Classification Using Tuple ID Propagation 577
9.3.5 Multirelational Clustering with User Guidance 580
9.4 Summary 584
Exercises 586
Bibliographic Notes 587
Chapter 10 Mining Object, Spatial, Multimedia, Text, andWeb Data 591
10.1 Multidimensional Analysis and Descriptive Mining of Complex
Data Objects 591
10.1.1 Generalization of Structured Data 592
10.1.2 Aggregation and Approximation in Spatial and Multimedia Data
Generalization 593
Contents xvii
10.1.3 Generalization of Object Identifiers and Class/Subclass
Hierarchies 594
10.1.4 Generalization of Class Composition Hierarchies 595
10.1.5 Construction and Mining of Object Cubes 596
10.1.6 Generalization-Based Mining of Plan Databases by
Divide-and-Conquer 596
10.2 Spatial Data Mining 600
10.2.1 Spatial Data Cube Construction and Spatial OLAP 601
10.2.2 Mining Spatial Association and Co-location Patterns 605
10.2.3 Spatial Clustering Methods 606
10.2.4 Spatial Classification and Spatial Trend Analysis 606
10.2.5 Mining Raster Databases 607
10.3 Multimedia Data Mining 607
10.3.1 Similarity Search in Multimedia Data 608
10.3.2 Multidimensional Analysis of Multimedia Data 609
10.3.3 Classification and Prediction Analysis of Multimedia Data 611
10.3.4 Mining Associations in Multimedia Data 612
10.3.5 Audio and Video Data Mining 613
10.4 Text Mining 614
10.4.1 Text Data Analysis and Information Retrieval 615
10.4.2 Dimensionality Reduction for Text 621
10.4.3 Text Mining Approaches 624
10.5 Mining theWorld WideWeb 628
10.5.1 Mining the Web Page Layout Structure 630
10.5.2 Mining the Web抯 Link Structures to Identify
Authoritative Web Pages 631
10.5.3 Mining Multimedia Data on the Web 637
10.5.4 Automatic Classification of Web Documents 638
10.5.5 Web Usage Mining 640
10.6 Summary 641
Exercises 642
Bibliographic Notes 645
Chapter 11 Applications and Trends in Data Mining 649
11.1 Data Mining Applications 649
11.1.1 Data Mining for Financial Data Analysis 649
11.1.2 Data Mining for the Retail Industry 651
11.1.3 Data Mining for the Telecommunication Industry 652
11.1.4 Data Mining for Biological Data Analysis 654
11.1.5 Data Mining in Other Scientific Applications 657
11.1.6 Data Mining for Intrusion Detection 658
xviii Contents
11.2 Data Mining System Products and Research Prototypes 660
11.2.1 How to Choose a Data Mining System 660
11.2.2 Examples of Commercial Data Mining Systems 663
11.3 Additional Themes on Data Mining 665
11.3.1 Theoretical Foundations of Data Mining 665
11.3.2 Statistical Data Mining 666
11.3.3 Visual and Audio Data Mining 667
11.3.4 Data Mining and Collaborative Filtering 670
11.4 Social Impacts of Data Mining 675
11.4.1 Ubiquitous and Invisible Data Mining 675
11.4.2 Data Mining, Privacy, and Data Security 678
11.5 Trends in Data Mining 681
11.6 Summary 684
Exercises 685
Bibliographic Notes 687
Appendix An Introduction to Microsoft抯 OLE DB for
Data Mining 691
A.1 Model Creation 693
A.2 Model Training 695
A.3 Model Prediction and Browsing 697
Bibliography 703

Accelerated SQL Server 2008

2008-06-17 13:58:19

The expert tuition and approach to rapid learning in Accelerated SQL Server 2008, one of the first SQL Server 2008 books available, will enable SQL Server and other database professionals to make the leap to the latest release of Microsoft's flagship database management system quickly. Take full advantage of the new features of SQL Server 2008, know what tools are available, and quickly realize the power and ease of use that SQL Server 2008 has to offer.
*Lightning quick introduction to SQL Server 2008
*Written by top experts in the field
*Provides a solid grounding in key features and technologies
What you'll learn
*Manage SQL Server installations through the brand new Declarative Management Framework.
*Protect yourself from downtime with high availability features such as failover clustering.
*Speed your applications by taking advantage of new performance enhancement features in SQL Server 2008.
*Find what you need using full text search.
*Store, retrieve, and manage XML in the database.
*Derive competitive advantage from business intelligence tools such as Analysis Services and Reporting Services.