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Table of Contents

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  1. Preface
  2. Mappings
  3. Mapplets
  4. Mapping Parameters
  5. Where to Assign Parameters
  6. Mapping Outputs
  7. Generate a Mapping from an SQL Query
  8. Dynamic Mappings
  9. How to Develop and Run a Dynamic Mapping
  10. Dynamic Mapping Use Cases
  11. Mapping Administration
  12. Export to PowerCenter
  13. Import From PowerCenter
  14. Performance Tuning
  15. Pushdown Optimization
  16. Partitioned Mappings
  17. Developer Tool Naming Conventions

Developer Mapping Guide

Developer Mapping Guide

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Restrictions for Partitioned Transformations

Restrictions for Partitioned Transformations

Some transformations that support partitioning require specific configurations. If a mapping enabled for partitioning contains a transformation with an unsupported configuration, the Data Integration Service uses one thread to run the transformation. The Data Integration Service can use multiple threads to process the remaining mapping pipeline stages.
The following transformations require specific configurations to support partitioning:
  • Aggregator transformations must include a group by port. Aggregator transformations must not include a pass-through port. Aggregator transformations must not include numeric functions that calculate running totals and averages on a row-by-row basis.
  • Expression transformations must not include the following types of functions or variables:
    • Numeric functions that calculate running totals and averages on a row-by-row basis.
    • Special functions that might return different results when multiple threads process the transformation.
    • Local variables that depend on the value of a previous row.
  • Decision, Java, and SQL transformations must have the
    Partitionable
     property enabled.
  • Joiner transformations must include a join condition that uses an equality operator. If the join condition includes multiple equality conditions, the conditions must be combined using the AND operator.
  • Rank transformations must include a group by port.
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