IBM DB2 Version 10

Name: IBM DB2 Version 10
Brand: McGraw-Hill Education
Price: 46.29 EUR
Availability: OnlineOnly

Paul Zikopoulos(Autor*in)

McGraw-Hill Education (Verlag)

1. Auflage

Erschienen am 8. Mai 2012

240 Seiten

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978-0-07-180296-3 (ISBN)

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Inhalt

Intro
Contents
Foreword
Acknowledgments
About This Book
1 If You've Got Only 15 Minutes: An Overview of DB2 10
DB2 Gets Faster Still: Performance
Storage Optimization
Time Travel Query with Bitemporal Data Management
Database Lockdown
Big Data and the Cloud
High Availability
And a Lot More.
2 Get More Out of Your Disks: The Even More Storage-Optimized DB2
DB2 Multitemperature Management
Looking Back: Allocating Storage Prior to DB2 10
DB2 Storage Groups Change the Game
Using Storage Groups
Multitemperature Storage in Action: A Usage Scenario
Bringing It All Together: A Summary of Multitemperature Data Management in DB2 10
Looking Back: A Quick Recap of Compression in Past DB2 Releases
DB2 Compression: An Anthology of Compression Techniques Across Previous Versions of DB2
The Inflection Point: DB2 9.1 Row Compression
It Goes Autonomic: DB2 9.5 Compression
DB2 9.7: Compression Finds a Higher Gear
Looking Forward: What You Can Expect with Compression in DB2 10
The Inspiration for Adaptive Compression
Working with Adaptive Compression
The "Your Results Might Vary" Section: Our Adaptive Compression Tests
Miscellaneous Space Enhancements
Wrapping It Up
3 Lockdown: An Even More Secure DB2
Looking Back: Traditional RCAC Methods in DB2
The Database View Approach to Database Lockdown
The Application-Based Security Approach to Database Lockdown
Label-Based Access Control
Looking Forward: What You Can Expect with RCAC in DB2 10
Working with DB2 RCACs
Putting Row Permissions and Column Masks to Work
The Inside Track: Our Hints and Tips to Get Going Fast
Dependencies
Performance
Three-Tier Application Models
Wrapping It Up
4 Time Traveling with DB2: Bitemporal Data Management for Ultimate Business Accuracy and Compliance
The Business Need for Temporal Data Management
Looking Forward: Temporal Data Management in DB2 10
The Benefits of Time Travel Query
Understanding System Time, Business Time, and Temporal Tables
Recording and Accessing History with System Time
Creating a Table with System Time and Versioning
Inserting Data into a Table with System Time
Updating and Deleting Data in a Table with System Time
Querying a Table with System Time
Tracking Effective Dates with Business Time
Creating a Table with Business Time
Inserting Data into a Table with Business Time
Updating and Deleting Data in a Table with Business Time
Querying a Table with Business Time
Bitemporal Tables: Working with System Time and Business Time
Creating a Bitemporal Table
Inserting, Updating, and Deleting Data in a Bitemporal Table
Querying a Bitemporal Table
The DB2 Time Machine: Autopilot for Time Travel Queries
Using Autopilot for System Time
Using Autopilot for Business Time
Usage Guidelines for the Autopilot
The Inside Track: Our Hints and Tips to Get Going Fast
Migrating a Table Without Timestamp Columns
Migrating a Table with Timestamp Columns
Wrapping It Up
5 The (Yet Again) Even Faster DB2
The Not-so-Little Engine that Could: Scaling Your Workloads with DB2 10
Intra-partition Parallelism "Reloaded"
DB2 pureScale Folded into DB2 for Ultimate Scale Out
Table Partitioning Enhancements
ATTACH Goes Online to Boost Table Availability During Data Roll-in Operations
Faster Data Roll-in Through SET INTEGRITY. IMMEDIATE UNCHECKED
Performance Assurance: Using Workload Management Dispatcher for SLA Attainment
CPU Shares and Limits
Finding Another Gear: Continuous, Online, High-Speed Data Ingest
How Continuous Data Ingest Looks on the Inside
Getting to Know Continuous Data Ingest
RUNSTATS Performance and Other Enhancements
Sampling for Index Statistics
Readahead Prefetching During Index Statistics Collection
General Path Length Reduction
Grab Bag of Other RUNSTATS Improvements
Statistical Views
Partial Statviews Matching
Column Group Statistics Gathered on Statistical Views
Automatic Statistics Collection for Statistical Views
Expressions on Statistical Views
Index Improvements
Jump Scan (Multi-Range Index Scan) Enhancements
Readahead Data and Index Prefetching
Zigzag Joins
Miscellaneous Internal Optimization Improvements
6 The Even More Available DB2
Before We Begin: Be Careful for the Things You Plan and Don't Plan
DB2 pureScale Availability Enhancements
Getting to Table Space-Level Granularity for Recovery Operations
Odds and Ends that Add Up to Better DB2 pureScale Availability
DB2 High Availability and Disaster Enhancements
Take Control of Your Availability Needs
Understanding HADR Synchronization Controls
HADR Standby Databases
Log Archive Management in an HADR Environment
Semi-dynamic HADR Configuration Parameters
Availability Odds and Ends
InfoSphere Replication Server Enhancements
Roving HA
7 A Big Data World: The Even More Extensible DB2
Looking Forward: How DB2 Helps to Tame the Big Data Problem
Faster XML Processing
Efficient Text Search
The DB2 10 Resource Description Framework: A Good Thing that Comes in Threes
DB2 and the IBM Big Data Platform
The IBM Big Data Platform
Hadoop for the "DB2 Person"
Wrapping It Up
8 Ease of Use: The Even More Manageable DB2
The Top Ten: DB2 10 Ease-of-Use Enhancements
Number 1: Compression Adapts to the Data
Number 2: Time Travel Query and Temporal Tables
Number 3: Temperature-Driven Data Placement
Number 4: Row and Column Access Control
Number 5: Built-in SQL Global Variables
Number 6: Built-in SQL Functions
Number 7: Performance
Number 8: Managing Database Configurations and Recovery
Number 9: Tools Unite!
Number 10: HADR Delay and Log Spool are Cool
9 The Ultimate Elastic Operating Model: DB2 in the Cloud
Getting to Know Cloud Computing
The DB2 CloudReady Computing Strategy
Virtualization Is Key
Database Room to Let: Multitenancy
Cloud Is a Business Model, so Licensing Matters
IBM Workload Deployer and DB2 in a Private Cloud
Virtual System Patterns
Virtual Application Patterns
Wrapping It Up
10 DB2 Compatibility for Easy Migration
The Quest for 100%: New DB2 10 Compatibility Features
More Flexible Triggers
Locally Declared Data Types and Procedures
New Scalar Functions
Wrapping It Up
Additional Skills Resources

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