Table of Contents


  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

Complex Ports in Transformations

Complex Ports in Transformations

You can create complex ports in some transformations that are supported on the Spark and Databricks Spark engines. Read and Write transformations can represent ports that pass hierarchical data as complex data types.
You can create complex ports in the following transformations:
  • Aggregator
  • Expression
  • Filter
  • Java
  • Joiner
  • Lookup
  • Normalizer
  • Router
  • Sorter
  • Union
The Databricks Spark engine does not support the Java transformation.
The Read and Write transformations can read and write hierarchical data in complex files. To read and write hierarchical data, the Read and Write transformations must meet the following requirements:
  • The transformation must be based on a complex file data object.
  • The data object read and write operations must project columns as complex data types.


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