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

Python Transformation in a Streaming Mapping

Python Transformation in a Streaming Mapping

Streaming mappings have additional processing rules that do not apply to batch mappings.
Consider the following restrictions:
  • When you close a Jep instance, you might not be able to call CPython modules.
  • Do not use the names
    inRowsList
    and
    outRowsList
    in the Python code. These names are reserved for the Scala code that the Spark engine uses to interact with the Python environment.


Updated September 28, 2020