Table of Contents

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  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Data Preview on Transformations

Data Preview on Transformations

When you use a transformation as the preview point, the Spark engine might process the data preview job differently.
When you choose a transformation as the preview point, the Spark engine might not maintain the sorted order when you configure the
Maintain row order
property.
Rank transformation
When you choose a Rank transformation as the preview point for data preview on the Spark engine, row order is maintained.
Sorter transformation
To maintain sorted row order when you preview data with a Sorter transformation before the preview point in a mapping, configure preferences to show all rows.
  1. From the
    Window
    menu, open
    Preferences
    .
  2. Navigate to
    Informatica
    Run Configurations
    Data Viewer
    .
  3. In the
    Results
    tab, find the
    Rows
    section and select
    Show all rows
    .
Transformations with multiple output groups
When you preview data using the Spark engine, you cannot use the following transformations as preview points when the transformations are configured with multiple output groups:

    Normalizer

    Router

    Update Strategy



Updated September 28, 2020