Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Connections
  4. Mappings in the Hadoop Environment
  5. Mapping Objects in the Hadoop Environment
  6. Processing Hierarchical Data on the Spark Engine
  7. Stateful Computing on the Spark Engine
  8. Monitoring Mappings in the Hadoop Environment
  9. Mappings in the Native Environment
  10. Profiles
  11. Native Environment Optimization
  12. Data Type Reference
  13. Complex File Data Object Properties
  14. Function Reference
  15. Parameter Reference

Complex Ports in Transformations

Complex Ports in Transformations

You can create complex ports in some transformations that are supported on the Spark engine. 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
  • Joiner
  • Lookup
  • Normalizer
  • Router
  • Sorter
  • Union
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.


Updated November 09, 2018