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9780672310775

Oracle Data Warehousing Unleashed

by ; ; ; ; ; ;
  • ISBN13:

    9780672310775

  • ISBN10:

    0672310775

  • Format: Paperback
  • Copyright: 1997-10-01
  • Publisher: Sams
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Summary

Teaches how to: Plan and initialize your data warehouse; Tune your data warehouse at all levels from kernel parameters and memory management to loads and scrubs. Includes practical tips for implementing data quality, data integration, and data scrubbing. Paper.

Table of Contents

Introduction xxv
Part I Initialization and Project Planning 3(98)
1 Motivation for Building a Data Warehouse
3(20)
What Is a Data Warehouse?
5(1)
What a Data Warehouse Is Not
5(3)
User Access to Data: A Historical Perspective
6(1)
Summary of Historical Data Access Problems
7(1)
The Data Warehouse Context: Facilitate Business
8(2)
Why Oracle?
10(1)
Business Drivers for the Data Warehouse
11(3)
Technical Drivers
14(5)
Solving the Integration Problem
14(5)
Be Prepared
19(3)
Scope and Complexity
20(1)
Political Battles
20(1)
Inadequate Funding
20(1)
Data Integration and Data Semantics
21(1)
Different Methodology
21(1)
Different Skill Set
21(1)
Data Access
22(1)
Summary
22(1)
2 Data Warehouse Architecture
23(14)
Six Steps to Develop the Architecture
24(1)
The Data Warehouse Infrastructure
25(6)
Data Warehouse System Infrastructure
26(2)
Metadata
28(1)
Data Discovery
29(1)
Data Acquisition
29(1)
Data Distribution
29(1)
User Access
30(1)
Sybase IQ
31(1)
Data Management Architecture: Data Layers
31(3)
Ongoing Maintenance: Warehouse Infrastructure
34(1)
Summary
35(2)
3 Methodology and Project Management
37(30)
What Is a Methodology?
38(1)
Why the Data Warehouse Methodology Is Different
39(1)
Sample Data Warehouse Methodology
40(15)
Project Roles
40(5)
Phase One: Define Objectives and Scope
45(2)
Phase Two: Define Architecture
47(1)
Phase Three: Begin to Build Infrastructure
48(1)
Phase Four: Begin First Iteration
49(3)
Phase Five: Set Up Ongoing Maintenance Processes, First Iteration
52(1)
Phase Six: Set Up User Analysis Environment, First Iteration
53(1)
Phase Seven: Release First Iteration, Begin Second Iteration
54(1)
Customizing the Methodology
55(4)
Changing Terms
56(1)
Using Individual Interviews Instead of JAD Sessions
57(1)
Changes You Should Never Make
58(1)
Project Management: The Art of Finding Problems
59(2)
Setting and Resetting Expectations
61(1)
Critical Success Factors
61(1)
The Heart of a Champion (with the Strength of a Gorilla)
61(1)
Public Relations: Delighting the End User
62(3)
Data Discovery
62(1)
Initial Requirements
63(1)
Sizing and Long Range Sizing Plan
63(1)
Metadata and Data Dictionaries
63(1)
Logical Data Model
64(1)
Extraction and/or Transformation Software
64(1)
Populating the Data Warehouse
65(1)
End-User Involvement
65(1)
Helpful Hints for Data Warehouse Project Managers
65(1)
Summary
66(1)
4 Surefire Ways to Make Your Warehouse Fail
67(34)
What Is a Fatal Error (or What Is Project Success)?
70(1)
Fatal Errors--A Non-Exhaustive List
71(16)
Neglect Executive Sponsorship
71(1)
Avoid Sharing the Project with an End-User Project Manager
71(2)
Limit End-User Involvement
73(1)
Use a Classic "Waterfall" Project Methodology
74(1)
Use a Technical Project Manager without Data Warehouse Experience
75(1)
Freeze the Specification as Early as Possible
75(1)
Work Multiple Projects in Parallel
76(1)
Simultaneously Implement Operational Systems and Related Warehouses
76(1)
Postpone or Avoid Metadata
77(1)
Focus on Technology First
77(2)
Create Your Own Data Warehouse Software
79(1)
Rely on Unproved Technology
80(1)
Rely on "Silver Bullet" Technology
80(2)
Run OLAP on Top of the Operational Database
82(1)
Run the Data Warehouse Database on the Server for the Operational System
83(1)
Use Normalized Data Structures
83(1)
Define a Complex Warehouse Architecture
84(1)
Skimp on Disk Storage
85(1)
Ignore Data Movement Metrics
86(1)
Defer Disaster Planning
87(1)
Mistakes That Cause Pain
87(1)
How You Can Contribute to Project Success
88(7)
The Executive Suite
89(1)
The End-User Department(s)
90(1)
Project Managers and Project Leaders
90(1)
IT/IS Management (Also for Consulting Managers)
91(3)
Technical Team Members (Whether in IT/IS or in a Consulting Organization)
94(1)
Summary
95(6)
Part II Preparation: Integration and Cleansing 101(104)
5 Data Integration: The Challenges
101(18)
Traditional Development
102(7)
Data Marts: Propagation of Data Chaos
105(3)
Mainframe Extracts
108(1)
PCs and Client/Server Development
108(1)
Heterogeneous Technologies
109(1)
The Compelling Need for Semantic Integration
110(2)
The Ramifications of Not Performing Semantic Integration
110(1)
Same Fact? How Can You Be Sure?
111(1)
Lack of Flexibility
112(1)
Semantic Problems
113(2)
Word Meaning
113(1)
Unit of Measure
113(1)
Level of Accuracy
113(1)
Format
113(1)
Timeliness
114(1)
Solution: Integration and Prevention
115(2)
Summary
117(2)
6 Defining Your Data
119(32)
Qualities of Good Definitions
120(1)
Definitions as Business Rules
120(1)
Two Different Kinds of Definitions
121(6)
Data Element Definitions
122(1)
Business Term Definitions
122(1)
Bringing the Two Definitions Together
123(2)
Stepping Toward the Future
125(2)
Discrepancies Between the Present and the Past
127(3)
Changing Relationships
128(1)
Changing Unique Identifiers
128(1)
Historical Definitions and Names
129(1)
Tracking Historical Fields
129(1)
Subject Areas
130(1)
Defining Entities
131(3)
Issues with Addresses
133(1)
Defining Attributes
134(11)
Attribute Naming
134(1)
Abbreviations as Attributes
135(1)
Issues with Names as Attributes
135(1)
Format
135(1)
Database Naming Conventions
135(1)
Oracle Objects
136(8)
Physical DDL Storage/Maintenance
144(1)
Data Validation
145(1)
About Data Stewardship
145(4)
Problems with Data Stewardship
146(1)
The Magilla Gorilla Factor
147(2)
Summary
149(2)
7 Metadata
151(26)
What Is Metadata?
152(1)
Types of Metadata
152(10)
Control Metadata
153(1)
Change Control in the Data Warehouse
153(8)
Business Metadata: Ideal World Scenario
161(1)
The Metadata Project
162(1)
The Metadata Repository
163(1)
Buy, Build, or Extend?
163(2)
What Buying a Repository "Buys You"
163(1)
What to Look for in Repositories
164(1)
Typical Metadata Elements
165(3)
The Metadata Coalition's Metamodel
167(1)
Extending a Repository
168(1)
Integrating Metadata from Disparate Tools
169(1)
The Metadata Coalition
170(2)
The Electronics Industries Association's CASE Data Interchange Format (CDIF)
172(1)
Other Integration Strategies
172(1)
Creative Customization
172(1)
Single Vendor Solutions
172(1)
Vendor Partnerships
173(1)
Metadata Access: Query Tools
173(2)
Summary
175(2)
8 Data Quality and Scrubbing
177(28)
How Does Bad Data Affect the Business?
178(3)
Poor Business Decisions
178(1)
Wasting Money
178(1)
Lost Information
178(3)
Defining Data Quality
181(2)
Situations That Highlight Dirty Data
183(3)
Merging Data Sources
183(1)
Integration of Information: Cross Referencing
184(1)
Mailing List Merging
185(1)
Application Merging
185(1)
Acquisition of Another Company
186(1)
The Data Cleansing Process
186(6)
Step 1: Data Discovery and Sleuthing
187(1)
Step 2: Categorize/Classify
188(1)
Step 3: Decide Action/Document
188(2)
Step 4a: Create Transforms/Generate Scrub Code
190(1)
Step 4b: Change Business Processes or Legacy Systems
190(1)
Step 5: Scrub Error Handling
191(1)
Step 6: Check for Metadata Drift Over Time
192(1)
Determining Data Meanings
192(2)
Two Different Kinds of Problems: Field versus Value
192(1)
Embedded Values: One Column, Different Values
193(1)
Subtypes and Supertypes
194(1)
Types of Transforms
194(2)
Determining the Source of Record
194(1)
One Column, Different Sources
194(1)
Synonyms
195(1)
Homonyms
195(1)
Data Cleansing Tools
196(5)
Sleuthing/Discovery Tools
196(1)
Extract/Transform/Code: Scrub Tools
197(2)
Tools That Address Specific Problems
199(1)
Which Is Best?
199(2)
Documentation and Metadata
201(1)
Summary
202(3)
Part III Logical and Physical Database Design 205(166)
9 Data Modeling Techniques and Options
205(28)
The Overall Design Process
207(1)
What Is Logical Design?
207(2)
Star Schema Design
208(1)
Database Design 101
209(1)
The Normalization Process
209(11)
Normal Forms
209(7)
Other Normalization Factors
216(3)
Benefits of Normalization
219(1)
Drawbacks of Normalization
219(1)
Normalization as the Baseline for Warehouse Design
220(1)
Denormalizing the Database
220(11)
Advantages of Denormalization
220(1)
Disadvantages of Normalization
221(1)
Guidelines
221(1)
Basic Denormalization Techniques
222(3)
Changing Column Definition
225(3)
Redefining Tables
228(1)
Data Partitioning/Fragmentation
228(3)
Referential Integrity in a Data Warehouse
231(1)
Summary
232(1)
10 Dimensions and Query Hierarchies
233(14)
Scales and Measurements
234(2)
Range of a Scale
236(1)
Granularity and Precision
236(1)
Types of Scales
237(2)
Nominal Scales
237(1)
Absolute Scales
237(1)
Ordinal Scales
237(1)
Rank Scales
238(1)
Quantitative Scales
238(1)
Interval Scales
238(1)
Ratio Scales
238(1)
Scale Conversion
239(1)
Derived Units
240(1)
Dimensions
240(1)
Hierarchies
241(1)
Hints for Constructing Dimensions and Hierarchies
242(1)
Use Existing Standards
242(1)
Avoid NULLS
243(1)
Translate Codes for the User
243(1)
Keep the Codes in the Database
243(1)
Cubes, Drills, and Clusters
243(3)
Summary
246(1)
11 Star Schema and Variants
247(20)
Mid-Level Design
248(1)
The Shape of a Star Schema
249(6)
Drill Downs Across Dimensions
254(1)
Problem Hierarchies: Time
255(2)
Snowflake Schema
257(4)
Constellation Schema
261(3)
Drilling to Another Fact Table
262(2)
Common Dimensions in Data Warehouses
264(1)
Star Schema Optimization
264(2)
Tuning Tips for Regular Star Optimization (Release 7.2 and Higher)
264(1)
Star Transformation Optimization Tips
265(1)
Summary
266(1)
12 Spatial Data: A Very Special Dimension
267(10)
What Is So Special About Spatial Data?
269(4)
Oracle's Spatial Data Option
273(2)
HHCODE: A Slick Way to Formulate N-Dimension Spatial Intersections
273(1)
How Does HHCODE Work?
274(1)
Other Key Features of the Spatial Data Option
275(1)
Summary
275(2)
13 Storage Concerns and Planning
277(40)
Approaches to Storage Planning
278(6)
The Analytic Approach
278(1)
The Empirical Approach
278(1)
The Incremental Approach
278(1)
How to Slam-Dunk an Initial Estimate
279(3)
Re-Estimate Regularly!
282(1)
Planning for the Long Haul
283(1)
Analyzing Your Storage Requirements
284(14)
Extract Storage Requirements
284(1)
Data Cleaning Storage Requirements
285(1)
Data Transformation Storage Requirements
286(1)
Sort Workspace
287(1)
Loads Use Storage Too!
288(1)
The Operational Data Store (ODS)
289(1)
The Main Warehouse Database
289(2)
Data Marts
291(3)
Query Workspace and Front-End Tools
294(1)
Query Results and Report Distribution
294(1)
Ancillary Data
294(1)
Archival Data
295(1)
Backup Data
295(2)
Operating System Paging and Swap Space
297(1)
Physical Storage Planning
298(13)
Datatypes
298(1)
Calculating Theoretical Size of Database Objects
299(2)
Storage Types
301(8)
Physically Locating Your Data
309(1)
Old Style Physical Tuning
309(1)
RAID 5 Makes It Easier--But Not Free
309(2)
Test Your Storage Plan!
311(3)
Monitoring Storage Utilization
314(1)
Summary
315(2)
14 Physical Database Design
317(20)
Design Is About Trade-Offs
318(5)
Denormalize, Normalize, Overnormalize
318(3)
Special Tables
321(1)
Star Schema
322(1)
Level of Detail (Granularity) Affects Physical Design
323(1)
Partitioning Tables
324(4)
Partition Views and Parallelism
324(2)
Partitioned Tables
326(2)
Partitioning on Dimensions Other Than Time
328(1)
Oracle Physical Design Considerations
328(8)
Consider Using Parallel Technology
328(1)
Memory Management
329(1)
Striping and Object Placement
330(1)
Read-Only Tablespaces
331(1)
Rollback Segments
332(1)
Freelists
332(1)
Indexes
332(1)
Reclaim Space by Utilizing ALTER TABLE DEALLOCATE
332(2)
Explore the Hidden Parameters
334(1)
Define Temporary Tablespaces as TEMPORARY
335(1)
SORT_AREA_SIZE
336(1)
Summary
336(1)
15 Exploiting Parallel Technology
337(14)
SMP Versus MPP
338(1)
Oracle Parallel Server
339(3)
Pinging: The P Word
340(2)
How Many Freelists Do You Need?
342(1)
Parallel Query Option (PQO)
342(7)
Skewing
343(1)
The Optimizer
343(5)
Distribution of Data to Maximize Parallelization
348(1)
Summary
349(2)
16 Indexes
351(20)
Indexes
352(5)
B*-Tree Indexes
352(2)
B-Tree Index Advantages
354(1)
Disadvantages
355(1)
CREATE INDEX Syntax
356(1)
Bitmap Indexes
357(5)
What Is a Bitmap Index?
358(1)
When to Use Bitmap Indexes
358(2)
CREATE BITMAP INDEX Syntax
360(1)
Restrictions (Features!)
360(1)
Bitmap Query
361(1)
Bitmap INIT.ORA Parameters
361(1)
Hash Clusters
362(5)
CREATE CLUSTER Syntax
362(1)
Hash Cluster Parameters
363(3)
Pre-Allocation of Space for a Hash Cluster
366(1)
Hash Cluster Advantages
366(1)
Hashing Disadvantages
366(1)
Partitioned Indexes
367(1)
Summary
367(4)
Part IV Management of a Data Warehouse 371(94)
17 Security
371(16)
Privileges
372(3)
System Privileges
372(1)
Object Privileges
373(2)
Data Dictionary Tables
375(3)
Listing of User Privileges
375(1)
Listing of System Privileges
376(1)
Listing of Object Privileges
376(1)
Column Privilege Listing
377(1)
ALTER USER
378(1)
Roles
378(7)
Creating Roles
379(1)
Granting Privileges to Roles
379(1)
Granting Roles to Users or Roles
380(1)
Enabling Roles
380(1)
Enabling Roles by Setting Default Roles
380(1)
Predefined Roles
381(1)
Revoking Privileges from Roles
382(1)
Revoking Roles from Users or Roles
382(1)
Dropping Roles
382(1)
Data Dictionary Role Views
383(2)
New Oracle8 Feature Regarding Passwords
385(1)
Summary
385(2)
18 Backup and Recovery
387(20)
Developing a Backup Strategy
388(3)
Backup Strategies in NOARCHIVELOG Mode
389(1)
Backup Strategies in ARCHIVELOG Mode
390(1)
Types of Backups
391(1)
Performing Database Backups
391(4)
Listing the Files for Backup
391(2)
Performing Full Offline Backups
393(1)
Performing Online Partial Backups
394(1)
More About ARCHIVELOG Mode
395(3)
Enabling ARCHIVELOG Mode
396(1)
Steps to Enabling ARCHIVELOG Mode
397(1)
Checking Archive Status
397(1)
Control File Backup
398(1)
Database Recovery
398(6)
Redo Log Information
399(1)
Recovery Types
400(2)
Media Recovery
402(1)
Control File Recovery
402(1)
Instance Recovery
402(1)
NOARCHIVELOG Recovery
403(1)
Recovery Tablespaces/Data Files
403(1)
Summary
404(3)
19 Loads
407(24)
Designing Loads
408(2)
Data Consistency
410(2)
Load Consistency
410(1)
Referential Integrity
411(1)
Freezing Time Variant Data
412(1)
Designing Load Process Streams
412(2)
Load Windows
414(1)
Common Load Problems
415(1)
Load Quality Assurance
416(1)
Back Out, Recovery, Restart
417(1)
Speeding Up Loads
418(4)
Technology Alternatives
422(2)
Capacity Planning for Loads
424(5)
Disk Storage Capacity
424(1)
Disk and Tape Throughput Capacity
425(1)
Network Capacity
426(1)
Mainframe Channel, Front-End Processor, and Communication Processor Capacity
426(3)
Summary
429(2)
20 Tuning Loads and Scrubs
431(12)
Why Are Loads and Scrubs Always a Performance Problem?
432(1)
Trade-Offs
433(1)
Analyze the Load/Scrub Process
433(1)
Optimizing Loads
434(2)
Is the Initial Load Representative of Ominous Things to Come?
434(1)
Extracts and Data Movement
434(1)
Dealing with Incremental Loads
435(1)
SQL*Loader Options
435(1)
Loading in Parallel
436(1)
Third-Party Load Products
436(1)
Network Issues
436(2)
Network Protocol Options
437(1)
Network Strategy for an ODS
437(1)
Scrub Code Tuning
438(3)
Do What You Can on the Source System
438(1)
Dealing with Computed Fields
439(1)
Aggregate Processing Creativity
440(1)
What Do You Do About Referential Integrity?
440(1)
Use Common Tuning Techniques
441(1)
Resorting to a 3GL
442(1)
Summary
442(1)
21 Memory Tuning and Other DBA Tuning Considerations
443(22)
System Global Area
444(12)
The Shared Pool
447(5)
Data Block Buffer
452(4)
Other Memory Considerations
456(2)
Size of Database Buffer
456(1)
Tuning for Sorts
457(1)
Utilities and Other Server Tuning
458(4)
UTLBSTAT and UTLESTAT
458(1)
Rule-Based versus Cost-Based Optimizer
459(2)
PCTFREE
461(1)
Server Manager
462(1)
Summary
462(3)
Part V Data Access 465(174)
22 Using the Intranet
465(14)
PC and Spreadsheet: Killer Combo of the 1980s
466(1)
Data Warehouse and the Internet: Killer Combo for the 1990s?
466(1)
An Introduction to the Technologies of the Internet
467(3)
What Is an Intranet?
470(3)
Why Use an Intranet?
473(1)
Connecting a Database to the Intranet
474(1)
Oracle Web Server
475(1)
Publishing and Delivery of Data Warehouse Data to the Intranet
476(1)
Querying the Data Warehouse Data from the Intranet
476(1)
Summary
477(2)
23 Front-End Tools
479(42)
What Is a Front-End Tool?
482(1)
Front-End Tool Terminology
483(2)
Multi-Dimensional
483(1)
OLAP
484(1)
Slice and Dice
485(1)
Drill
485(1)
Traditional Programming Languages
485(2)
Types of Tools
487(2)
End-User Tools Versus Front-End Development Tools
487(1)
Ad Hoc Query
487(1)
Report Writers
487(1)
EIS Tools
488(1)
Data Mining Tools
488(1)
Web Browser-Based Tools
489(1)
Sample Front-End Tools
489(4)
Oracle Discoverer
489(2)
Oracle Express
491(1)
Oracle Developer 2000
491(1)
BusinessObjects
492(1)
DataMiner
492(1)
WebIntelligence
492(1)
Impromptu and Power Play
493(1)
Scenario
493(1)
Developing the User Layer
493(1)
Front-End Tool Performance Issues
494(5)
The Correct Performance Tuning Method
495(1)
Tuning the Back-End
496(1)
Sort Performance Problems
496(1)
Query Optimization
497(1)
Data Movement
497(1)
Memory Allocation
498(1)
Ease of Use: A Different Kind of Performance Tuning
498(1)
Selecting Front-End Tools
499(15)
Selection Approach
500(7)
Selection Criteria
507(4)
A Word on the RFx
511(2)
Information Sources
513(1)
Tools for Requirements Gathering
514(2)
Tools Administration
516(3)
Summary
519(2)
24 Data Mining
521(22)
Data Mining Applications
522(2)
Data Mining Approaches and Models
524(1)
The Methods Behind Data Mining
524(9)
Decision Trees
525(1)
Simple Descriptive Statistics
526(2)
Linear (and Other) Regression Analysis
528(1)
Cluster Analysis
529(1)
Fuzzy Logic
530(1)
Neural Networks
531(2)
How Data Mining Fits with Data Warehousing
533(3)
Implementation Road Map
536(1)
Database Design Issues
536(2)
Product Selection
538(3)
Summary
541(2)
25 Tuning Queries
543(44)
The Optimizer
544(4)
Rule-Based Optimization
545(1)
Cost-Based Optimization
545(1)
Collecting Statistics
546(1)
Analyzing Tables
546(1)
Analyzing Indexes
547(1)
Cost Optimization Goal
548(1)
Query Optimization Techniques
548(9)
Hints Overview
548(2)
Index Usage
551(1)
Index Usage Examples
551(1)
Index Suppression
551(1)
Index Suppression Examples
552(1)
Forcing Index Suppression
552(1)
Forcing Index Usage
553(1)
GROUP BY
553(1)
Query Restructuring
554(1)
Query Optimization--OR / UNION
555(1)
Query Optimization--NOT EXISTS
555(1)
Query Optimization--Combine
556(1)
EXPLAIN_PLAN
557(19)
The PLAN_TABLE
557(1)
Setting Up a Plan
558(2)
EXPLAIN_PLAN Operations
560(16)
TKPROF
576(7)
How to Run TKPROF
576(3)
TKPROF Syntax
579(2)
Interpreting the TKPROF Results
581(2)
Query Tuning for the Star Schema
583(3)
Tuning Tips for Regular Star Optimization (Releases 7.2 and Higher)
584(1)
Star Transformation Optimization Tips
585(1)
Summary
586(1)
26 Data Marts
587(28)
Types of Data Marts
589(19)
Satellite Data Marts
590(3)
Feeder Data Marts
593(2)
Partition Data Marts
595(1)
The Mini-Warehouse Data Mart
596(4)
Independent Data Marts
600(6)
Mixed Data Mart Architectures
606(2)
Building a Data Mart
608(2)
Tools for Data Marts
610(2)
Data Mart Implementation Tools
610(1)
The Oracle Data Mart Suite
611(1)
Oracle Express and Data Marts
611(1)
Data Mart Extremes--Some Perspective
612(1)
Summary
613(2)
27 Operational Data Store and the Operational Environment
615(24)
Major Limitation of the Data Warehouse: Updates
616(1)
What's the Difference?
617(1)
Architectures of DW and ODS
618(3)
Should the ODS Be Updated Directly?
621(1)
Determining the Source of Record
622(2)
Reverse Scrubs
624(2)
Avoid Moving the Source of Record to the ODS
626(2)
Edits Revisited
628(1)
Three Tier Architecture: Linking the Data Warehouse to the Operational Environment
629(1)
The Role of Metadata
630(1)
Integrating the ODS, Data Warehouse, and Operational Environment: Rule Diagnostics
631(2)
Implementing the Metadata Link
633(2)
Summary
635(4)
Part VI Appendixes 639(26)
A Data Warehouse Checklists for Project Managers
639(6)
Critical Success Factors for Data Warehousing
640(1)
Key Tasks and Deliverables
641(1)
Eight Major Phases in Building the Data Warehouse
642(1)
Reference Task Checklist
642(3)
B Survey of Tool Vendors
645(4)
C Survey of Conferences and Seminars
649(4)
Regular Conferences Specializing in Oracle
650(1)
Regular Conferences Specializing in Data Warehouse/Databases
650(1)
Other Conferences and Seminars of Interest
651(2)
D Survey of Publications and Journals
653(4)
Interesting Data Warehouse-Oriented Web Sites
655(2)
E Oracle8 Features for Data Warehousing
657(4)
Partition Tables
658(1)
More Parallel Features
658(1)
Fast Full Index Scan
659(1)
Bitmap Indexes
659(1)
Star Optimization
659(1)
Star Transformation Optimization
660(1)
Backup and Recovery
660(1)
Object Features
660(1)
F References
661(4)
Index 665

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