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  1. Preface
  2. Introduction to PowerExchange Bulk Data Movement
  3. PowerExchange Listener
  4. Adabas Bulk Data Movement
  5. Datacom Bulk Data Movement
  6. DB2 for i5/OS Bulk Data Movement
  7. DB2 for Linux, UNIX, and Windows Bulk Data Movement
  8. DB2 for z/OS Bulk Data Movement
  9. IDMS Bulk Data Movement
  10. IMS Bulk Data Movement
  11. Microsoft SQL Server Bulk Data Movement
  12. Oracle Bulk Data Movement
  13. Sequential File Bulk Data Movement
  14. VSAM Bulk Data Movement
  15. Writing Data with Fault Tolerance
  16. Monitoring and Tuning Options

Bulk Data Movement Guide

Bulk Data Movement Guide

Data Maps Caching

Data Maps Caching

You can configure PowerExchange to cache data maps defined for nonrelational
z/OS
data sources on the system where the data maps are used by a single PowerExchange Listener job or by multiple PowerExchange Listener and netport jobs.
You cannot use data maps caching with IMS netport jobs.
When you enable data maps caching, PowerExchange retrieves data maps from
job-level
memory rather than by accessing the data maps file. By eliminating accesses to the data maps file, data maps caching improves performance.
When you enable data maps caching, you can decrease initialization time by 0.1 second in addition to the performance improvements that you achieve through connection pooling. Data maps caching can be of use when many short transactions are completed for each second. However, if you run long-running bulk data movement sessions and initialization time is a small part of the overall processing time, data maps caching might not give you any performance benefits.
To enable and configure data maps caching, define DBMOVER statements on the system where the PowerExchange Listener or netport jobs run. You can configure PowerExchange to run data maps caching in either
single-job
mode or
multiple-jobs
mode.

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