Table of Contents

Search

  1. Preface
  2. Understanding Pipeline Partitioning
  3. Partition Points
  4. Partition Types
  5. Pushdown Optimization
  6. Pushdown Optimization and 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

Partitioning Sorter Transformations

Partitioning Sorter Transformations

If you configure multiple partitions in a session that uses a Sorter transformation, the Integration Service sorts data in each partition separately. The Workflow Manager lets you choose hash auto-keys, key-range, or pass-through partitioning when you add a partition point at the Sorter transformation.
Use hash-auto keys partitioning when you place the Sorter transformation before an Aggregator transformation configured to use sorted input. Hash auto-keys partitioning groups rows with the same values into the same partition based on the partition key. After grouping the rows, the Integration Service passes the rows through the Sorter transformation. The Integration Service processes the data in each partition separately, but hash auto-keys partitioning accurately sorts all of the source data because rows with matching values are processed in the same partition. You can delete the default partition point at the Aggregator transformation.
Use key-range partitioning when you want to send all rows in a partitioned session from multiple partitions into a single partition for sorting. When you merge all rows into a single partition for sorting, the Integration Service can process all of the data together.
Use pass-through partitioning if you already used hash partitioning in the pipeline. This ensures that the data passing into the Sorter transformation is correctly grouped among the partitions. Pass-through partitioning increases session performance without increasing the number of partitions in the pipeline.


Updated July 04, 2018