Managing Ever-Increasing Amounts of Data with IBM DB2 for z/OS: Using Temporal Data Management, Archive Transparency, and the DB2 Analytics Accelerator

Managing Ever-Increasing Amounts of Data with IBM DB2 for z/OS: Using Temporal Data Management, Archive Transparency, and the DB2 Analytics Accelerator

by Mehmet Cuneyt Goksu, Claire McFeely, Craig McKellar, Xiao Hui Wang
Released September 2015
Publisher(s): IBM Redbooks
ISBN: 9780738440965

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Book description

IBM® DB2® Version 11.1 for z/OS® (DB2 11 for z/OS or just DB2 11 throughout this book) is the fifteenth release of DB2 for IBM MVS™. The DB2 11 environment is available either for new installations of DB2 or for migrations from DB2 10 for z/OS subsystems only.

This IBM Redbooks® publication describes enhancements that are available with DB2 11 for z/OS. The contents help database administrators to understand the new extensions and performance enhancements, to plan for ways to use the key new capabilities, and to justify the investment in installing or migrating to DB2 11.

Businesses are faced with a global and increasingly competitive business environment, and they need to collect and analyze ever increasing amounts of data (Figure 1). Governments also need to collect and analyze large amounts of data. The main focus of this book is to introduce recent DB2 capability that can be used to address challenges facing organizations with storing and analyzing exploding amounts of business or organizational data, while managing risk and trying to meet new regulatory and compliance requirements.

This book describes recent extensions to DB2 for z/OS in V10 and V11 that can help organizations address these challenges.

Table of contents

  1. Front cover
  2. Notices
    1. Trademarks
  3. IBM Redbooks promotions
  4. Preface
    1. Authors
    2. Now you can become a published author, too!
    3. Comments welcome
    4. Stay connected to IBM Redbooks
  5. Part 1 Temporal data management
  6. Chapter 1. Temporal data management overview
    1. 1.1 Overview
      1. 1.1.1 Periods
      2. 1.1.2 System-period temporal tables
      3. 1.1.3 Application-period temporal tables
      4. 1.1.4 Bitemporal tables
      5. 1.1.5 Choosing the right type of temporal table
  7. Chapter 2. System-period temporal tables
    1. 2.1 Overview
    2. 2.2 Relationship of a system-period temporal table to the associated history table
    3. 2.3 Moving from traditional to system-period temporal tables
      1. 2.3.1 Creating new tables
      2. 2.3.2 The history table and version enabling
      3. 2.3.3 Enabling versioning for an existing non-temporal table
      4. 2.3.4 Querying a system-period temporal table
      5. 2.3.5 Enabling versioning for an application managed temporal table
      6. 2.3.6 Other scenarios for migrating to system-period temporal tables
    4. 2.4 The who, what, and how of my row (audit columns)
      1. 2.4.1 Additional considerations for audit information and delete operations
      2. 2.4.2 The “who”, “what”, and “how” in action
    5. 2.5 Querying a system-period temporal table
      1. 2.5.1 System-period temporal table query examples
    6. 2.6 General restrictions with system-period data versioning
    7. 2.7 Utilities
      1. 2.7.1 LISTDEF
      2. 2.7.2 UNLOAD
      3. 2.7.3 LOAD
    8. 2.8 Recovery
  8. Chapter 3. Application-period temporal tables
    1. 3.1 Overview and benefits
    2. 3.2 Using application-period temporal tables
      1. 3.2.1 New concept of a BUSINESS_TIME period
      2. 3.2.2 Defining a BUSINESS_TIME period
      3. 3.2.3 Extensions to primary keys, unique constraints, and unique indexes
      4. 3.2.4 Temporal UPDATE and DELETE rules
      5. 3.2.5 Queries for application-period temporal tables
      6. 3.2.6 BUSINESS_TIME period restrictions
      7. 3.2.7 Utilities
    3. 3.3 Case study: an application-period table in action
      1. 3.3.1 Create an application-period temporal table
      2. 3.3.2 Step-by-step usage scenarios
  9. Chapter 4. Bitemporal tables
    1. 4.1 Overview
    2. 4.2 Where application-period meets system-period temporal
      1. 4.2.1 Using bitemporal tables in data manipulation statements
    3. 4.3 Extending an application-period temporal table to become a bitemporal table
    4. 4.4 Bitemporal tables in action
      1. 4.4.1 Create a bitemporal table
      2. 4.4.2 Step-by-step usage scenarios
      3. 4.4.3 Bitemporal queries
  10. Chapter 5. Additional considerations
    1. 5.1 Temporal support for views
      1. 5.1.1 Queries
      2. 5.1.2 Data change operations on views
      3. 5.1.3 Query of a view using a period specification for SYSTEM_TIME
      4. 5.1.4 Query on a view using a period specification for BUSINESS_TIME
      5. 5.1.5 Data change operations on temporal views
    2. 5.2 Time travel: Temporal special registers
      1. 5.2.1 Two temporal special registers
      2. 5.2.2 Enabling or disabling the temporal special registers
      3. 5.2.3 How temporal registers affect queries
      4. 5.2.4 How temporal affects UPDATE and DELETE statements
      5. 5.2.5 How temporal special registers affect statements in user-defined functions
    3. 5.3 Auditing with temporal tables
      1. 5.3.1 Overview and benefit
      2. 5.3.2 Using non-deterministic generated expression columns
      3. 5.3.3 Detailed explanation of the preceding example
    4. 5.4 Performance
      1. 5.4.1 CURRENT TEMPORAL SYSTEM_TIME special register
      2. 5.4.2 Performance summary on temporal support
  11. Part 2 IBM DB2 archive transparency
  12. Chapter 6. DB2 archive transparency overview
    1. 6.1 Challenges with historical data
    2. 6.2 How DB2 archive transparency works
  13. Chapter 7. DB2 archive transparency concepts
    1. 7.1 Overview
    2. 7.2 What is transparent archiving?
    3. 7.3 Enabling transparent archiving
      1. 7.3.1 Create an archive table
      2. 7.3.2 Enable transparent archiving
    4. 7.4 Archive transparency controls
      1. 7.4.1 Archive transparency bind options
      2. 7.4.2 Archive transparency built-in global variables
      3. 7.4.3 Data change operations when the target is an archive-enabled table
      4. 7.4.4 Rules for deleting from an archive-enabled table
    5. 7.5 Query from an archive-enabled table
      1. 7.5.1 Querying the current data only
      2. 7.5.2 Transparently querying the current and archive data
    6. 7.6 Disable archiving for an archive-enabled table
    7. 7.7 Using an archive timestamp with archive transparency
    8. 7.8 Summary
  14. Chapter 8. Case study: Using archive transparency
    1. 8.1 Sample application with step-by-step guidance
    2. 8.2 Define a table to enable transparent archiving
      1. 8.2.1 Creating the archive table
      2. 8.2.2 Moving data from the active table to the archive table
      3. 8.2.3 Loading data into the archive table
      4. 8.2.4 Deleting data from specific partitions of an archive-enabled table
    3. 8.3 Enabling archive transparency
    4. 8.4 Mechanics of moving data from an archive-enabled table to an archive table
    5. 8.5 Querying data from an archive-enabled table
  15. Part 3 DB2 Analytics Accelerator
  16. Chapter 9. DB2 Analytics Accelerator overview
    1. 9.1 Overview
    2. 9.2 Variations for using the DB2 Analytics Accelerator
      1. 9.2.1 Accelerator-shadow table
      2. 9.2.2 Accelerator-archived table
      3. 9.2.3 Accelerator-only table
      4. 9.2.4 Using temporal tables and DB2 Analytics Accelerator together
      5. 9.2.5 Using archive transparency and the DB2 Analytics Accelerator together
      6. 9.2.6 Using a row change timestamp column with archive transparency and the DB2 Analytics Accelerator
  17. Chapter 10. DB2 Analytics Accelerator High Performance Storage Saveroverview
    1. 10.1 Overview
    2. 10.2 What is High Performance Storage Saver?
      1. 10.2.1 Restrictions
    3. 10.3 Online data archiving
      1. 10.3.1 Archive data process and operations
      2. 10.3.2 Accessing archived data
      3. 10.3.3 Restoring an archived partition from the accelerator
  18. Chapter 11. Case study: Using the DB2 Analytics Accelerator
    1. 11.1 System setup of application with an accelerator
    2. 11.2 Moving and storing archived data with an accelerator
    3. 11.3 Querying archived data
  19. Part 4 Creating an integrated solution
  20. Chapter 12. Case study: Combining DB2 temporal data management with the DB2 Analytics Accelerator
    1. 12.1 Using the DB2 Analytics Accelerator with application-period temporal tables
      1. 12.1.1 Step-by-step scenario
      2. 12.1.2 Define an application-period temporal table
      3. 12.1.3 Adding an application-period temporal table into DB2 Analytics Accelerator
      4. 12.1.4 How are queries processed when data exists on an accelerator?
      5. 12.1.5 How are data change statements processed?
      6. 12.1.6 Archiving parts of an application-period temporal table to the DB2 Analytics Accelerator
      7. 12.1.7 How are queries processed?
  21. Chapter 13. Case study: Combining archive transparency with the DB2 Analytics Accelerator 
    1. 13.1 Overview
    2. 13.2 Enabling an archive-enabled table and archive table for acceleration
    3. 13.3 Querying an accelerator-shadow table
    4. 13.4 Moving archived partitions to the accelerator as an accelerator-archived table
    5. 13.5 Querying both an accelerator-shadow table and an accelerator-archived table
  22. Glossary
  23. Related publications
    1. Online resources
    2. Help from IBM
  24. Back cover

Product information

  • Title: Managing Ever-Increasing Amounts of Data with IBM DB2 for z/OS: Using Temporal Data Management, Archive Transparency, and the DB2 Analytics Accelerator
  • Author(s): Mehmet Cuneyt Goksu, Claire McFeely, Craig McKellar, Xiao Hui Wang
  • Release date: September 2015
  • Publisher(s): IBM Redbooks
  • ISBN: 9780738440965