Table of Contents

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  1. Preface
  2. Understanding Pipeline Partitioning
  3. Partition Points
  4. Partition Types
  5. Pushdown Optimization
  6. Pushdown Optimization Transformations
  7. Real-time Processing
  8. Commit Points
  9. Row Error Logging
  10. Workflow Recovery
  11. Stopping and Aborting
  12. Concurrent Workflows
  13. Grid Processing
  14. Load Balancer
  15. Workflow Variables
  16. Parameters and Variables in Sessions
  17. Parameter Files
  18. FastExport
  19. External Loading
  20. FTP
  21. Session Caches
  22. Incremental Aggregation
  23. Session Log Interface
  24. Understanding Buffer Memory
  25. High Precision Data
  26. POWERCENTERHELP

Advanced Workflow Guide

Advanced Workflow Guide

Use n:n Partitions

Use n:n Partitions

You may be able to improve performance for a sorted Joiner transformation by using
n:n
partitions. When you use
n:n
partitions, the Joiner transformation reads master and detail rows concurrently and does not need to cache all of the master data. This reduces memory usage and speeds processing. When you use 1:
n
partitions, the Joiner transformation caches all the data from the master pipeline and writes the cache to disk if the memory cache fills. When the Joiner transformation receives the data from the detail pipeline, it must then read the data from disk to compare the master and detail pipelines.


Updated July 04, 2018