Table of Contents


  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings
  4. Sources
  5. Targets
  6. Transformations
  7. Data Preview
  8. Cluster Workflows
  9. Profiles
  10. Monitoring
  11. Hierarchical Data Processing
  12. Hierarchical Data Processing Configuration
  13. Hierarchical Data Processing with Schema Changes
  14. Intelligent Structure Models
  15. Stateful Computing
  16. Connections
  17. Data Type Reference
  18. 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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