Table of Contents


  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. 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
  • Java
  • 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 October 23, 2019