DB2 10.5 with BLU Acceleration

DB2 10.5 with BLU Acceleration

by Paul Zikopoulos, Sam Lightstone, Matthew Huras, Aamer Sachedina, George Baklarz
Released October 2013
Publisher(s): McGraw-Hill
ISBN: 9780071823548

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Book description

UPGRADE TO THE NEW GENERATION OF DATABASE SOFTWARE FOR THE ERA OF BIG DATA!

If big data is an untapped natural resource, how do you find the gold hidden within? Leaders realize that big data means all data, and are moving quickly to extract more value from both structured and unstructured application data. However, analyzing this data can prove costly and complex, especially while protecting the availability, performance and reliability of essential business applications.

In the new era of big data, businesses require data systems that can blend always-available transactions with speed-of-thought analytics. DB2 10.5 with BLU Acceleration provides this speed, simplicity, and affordability while making it easier to build next-generation applications with NoSQL features, such as a mongo-styled JSON document store, a graph store, and more. Dynamic in-memory columnar processing and other innovations deliver faster insights from more data, and enhanced pureScale clustering technology delivers high-availability transactions with application-transparent scalability for business continuity.

With this book, you'll learn about the power and flexibility of multiworkload, multi-platform database software. Use the comprehensive knowledge from a team of DB2 developers and experts to get started with the latest DB2 trial version you can download at ibm.com/developerworks/downloads/im/db2/.

Stay up to date on DB2 by visiting ibm.com/db2/.

Table of contents

  1. Cover 
  2. Title Page
  3. Copyright Page
  4. About the Authors
  5. Contents at a Glance
  6. Contents 
  7. Foreword
  8. Acknowledgments
  9. Introduction
  10. Chapter 1: All Aboard! 15-Minute DB2 10.5 Tour Starts Here
    1. What Was Delivered: A Recap of DB2 10.1
      1. DB2 10.1 Delivered Performance Improvements
      2. DB2 10.1 Delivered Even Lower Storage Costs
      3. DB2 10.1 Delivered Improved Availability and Scalability
      4. DB2 10.1 Delivered More Security for Multitenancy
      5. DB2 10.1 Delivered the Dawn of DB2 NoSQL Support
      6. DB2 10.1 Delivered Even More Oracle Compatibility
      7. DB2 10.1 Delivered Temporal Data Management
    2. Introducing DB2 10.5: The Short Tour
      1. DB2 with BLU Acceleration
      2. A Final Thought Before You Delve into the Wild BLU Yonder
    3. DB2 pureScale Goes Ultra HA, DR, and More…
    4. DB2 as a JavaScript Object Notation Document Store
    5. Oracle Compatibility
    6. Tools, Tools, Tools
    7. Wrapping It Up…
  11. Chapter 2: DB2 pureScale Reaches Even Higher
    1. In Case It’s Your First Time… Recapping DB2 pureScale
    2. You Can Put DB2 pureScale in More Places
    3. DB2 pureScale Gets Even More Available
      1. DB2 pureScale Gets High Availability Disaster Recovery
      2. Keep on Rolling, Rolling, Rolling: DB2 Fix Pack Updates Go Online
      3. Adding Members Online
    4. Cross-Topology Backup and Restore
    5. Workload Consolidation in a DB2 pureScale Environment
    6. Explicit Hierarchical Locking
    7. Wrapping It Up…
  12. Chapter 3: BLU Acceleration: Next-Generation Analytics Technology Will Leave Others “BLU” with Envy
    1. What Is BLU Acceleration?
      1. Next-Generation Database for Analytics
      2. Seamlessly Integrated
      3. Hardware Optimized
    2. Convince Me to Take BLU Acceleration for a Test Drive
      1. Pedal to the Floor: How Fast Is BLU Acceleration?
      2. From Minimized to Minuscule: BLU Acceleration Compression Ratios
      3. Where Will I Use BLU Acceleration?
    3. How BLU Acceleration Came to Be: The Seven Big Ideas
      1. Big Idea Number 1: KISS It
      2. Big Idea Number 2: Actionable Compression and Computer-Friendly Encoding
      3. Big Idea Number 3: Multiplying the Power of the CPU
      4. Big Idea Number 4: Parallel Vector Processing
      5. Big Idea Number 5: Get Organized…by Column
      6. Big Idea Number 6: Dynamic In-Memory Processing
      7. Big Idea Number 7: Data Skipping
      8. Seven Big Ideas Optimize the Hardware Stack
    4. When Seven Big Ideas Deliver One Incredible Opportunity
    5. Under the Hood: A Quick Peek Behind the Scenes of BLU Acceleration
      1. BLU Acceleration Is a New Format for the Bytes in a Table, NOT a New Database Engine
      2. The Day In and Day Out of BLU Acceleration
      3. Informational Constraints, Uniqueness, and BLU Acceleration
      4. Getting the Data to BLU: Ingestion in a BLU Acceleration Environment
      5. Automated Workload Management That Is BLU-Aware
      6. Querying Column-Organized and Row-Organized Tables
      7. The Maintenance-Free Life of a BLU Acceleration Table
      8. Getting to BLU-Accelerated Tables
    6. Ready, Set, Go! Hints and Tips We Learned Along the Way
      1. First Things First: Do This!
      2. Automated Memory Tuning
      3. For Optimal Compression Results…
      4. Data Statistics? Don’t Bother, We’ve Got It Covered
      5. INSERT Performance
      6. How to Skip More: Get the Most Out of Data Skipping
      7. A NextGen Database Does Best with the Latest Hardware
      8. Memory, Memory, and More Memory
      9. Converting Your Row-Organized Tables into Column-Organized Tables
    7. Wrapping It Up…
  13. Chapter 4: Miscellaneous Performance and SQL Compatibility Enhancements
    1. Expression-Based Indexes
      1. Get Faster: Query Processing Before and After DB2 10.5 with Support for Index Expressions
      2. Expression-Based Indexes Make Application Development Easier
    2. Excluding NULL Keys from Indexes
      1. Index NULL Exclusion Simplifies Application Development
      2. When 2 + 2 = 4: Getting Even Richer Semantics by Combining Features
    3. Random Ordering for Index Columns
      1. To Random Order an Index Column or Not to Random Order an Index Column…That Is the Question
    4. More Data on a Row: Extended Row Size
  14. Chapter 5: Miscellaneous Availability Enhancements
    1. Better Online Space Reclamation for Insert Time Clustering Tables
      1. Understanding Insert Time Clustering Tables—A Primer
      2. What’s New for Insert Time Clustered Tables in DB2 10.5
    2. Other DB2 10.5 Reorganization Enhancements
      1. Fastpath! Collapsing Overflow and Pointer Records
      2. Support for Adaptive Compression with Online, In-place Reorganization
      3. Support for ADMIN_MOVE_TABLE Routine with Referential Constraints
    3. Wrapping It Up…
  15. Chapter 6: DB2 10.5: New Era Applications
    1. What’s in the NoSQL Name?
    2. DB2 pureXML: Where DB2 First Dipped Its “Toe” in the NoSQL Pool
    3. DB2 as a Graph Database: RDF, SPARQL, and Other Shiny Things
    4. DB2 as a JSON Document Store
      1. What Does JSON Look Like? JSON Document Structure
      2. Frequent Application Changes
      3. Flexible Data Interchange
      4. Document Store Databases
      5. Manipulating JSON Documents with DB2
    5. Wrapping It Up…

Product information

  • Title: DB2 10.5 with BLU Acceleration
  • Author(s): Paul Zikopoulos, Sam Lightstone, Matthew Huras, Aamer Sachedina, George Baklarz
  • Release date: October 2013
  • Publisher(s): McGraw-Hill
  • ISBN: 9780071823548