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

Data Masking Transformation in the Hadoop Environment

Data Masking Transformation in the Hadoop Environment

The Data Masking transformation behavior is the same on the Blaze, Spark, and Hive engines.
The Data Masking transformation might process data differently in the native environment and in a Hadoop environment.
Mapping validation fails in the following situations in a Hadoop environment:
  • The transformation is configured for repeatable expression masking.
  • The transformation is configured for unique repeatable substitution masking.


Updated October 23, 2019