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 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

Advanced Workflow Guide

Advanced Workflow Guide

Round-Robin Partition Type

Round-Robin Partition Type

In round-robin partitioning, the PowerCenter Integration Service distributes blocks of data to one or more partitions. Each partition processes rows based on the number and size of the blocks.
Use round-robin partitioning when you do not need to group data among partitions. In a pipeline that reads data from file sources of different sizes, use round-robin partitioning to distribute blocks of rows between the partitions.
The following figure shows a mapping where round-robin partitioning helps distribute rows before they enter a Filter transformation:
This mapping includes a source, a series of transformations, and a target. Round-robin partitioning distributes data evenly at the Filter transformation.
The session based on this mapping reads item information from three flat files of different sizes:
  • Source file 1: 80,000 rows
  • Source file 2: 5,000 rows
  • Source file 3: 15,000 rows
When the PowerCenter Integration Service reads the source data, the first partition begins processing 80% of the data, the second partition processes 5% of the data, and the third partition processes 15% of the data.
To distribute the workload more evenly, set a partition point at the Filter transformation and set the partition type to round-robin. The PowerCenter Integration Service distributes the data so that each partition processes approximately one-third of the data.

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