Table of Contents

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

User Guide

User Guide

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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