Table of Contents

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  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Transformation Data Type Support in a Non-native Environment

Transformation Data Type Support in a Non-native Environment

The following table shows the Informatica transformation data type support on non-native run-time engines:
Transformation Data Type
Engine
Array
  • Spark
  • Databricks Spark
Bigint
  • Blaze
  • Spark
  • Databricks Spark
Binary
  • Blaze
  • Spark
Date/Time
  • Blaze
  • Spark
  • Databricks Spark
Decimal
  • Blaze
  • Spark
  • Databricks Spark
Double
  • Blaze
  • Spark
  • Databricks Spark
Integer
  • Blaze
  • Spark
  • Databricks Spark
Map
  • Spark
  • Databricks Spark
String
  • Blaze
  • Spark
  • Databricks Spark
Struct
  • Spark
  • Databricks Spark
Text
  • Blaze
  • Spark
  • Databricks Spark
timestampWithTZ
Not supported


Updated September 28, 2020