Table of Contents

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  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

Transformation Data Type Support in a Hadoop Environment

Transformation Data Type Support in a Hadoop Environment

The following table shows the Informatica transformation data type support in a Hadoop environment:
Transformation Data Type
Support
Array
Supported*
Bigint
Supported
Binary
Supported
Date/Time
Supported
Decimal
Supported
Double
Supported
Integer
Supported
Map
Supported*
String
Supported
Struct
Supported*
Text
Supported
timestampWithTZ
Not supported
* Supported only on the Spark engine.


Updated October 23, 2019