Table of Contents

Search

  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

Rules and Guidelines for Mappings in a Non-native Environment

Rules and Guidelines for Mappings in a Non-native Environment

When you run mappings in a non-native environment, some differences in processing and configuration apply. You can run mappings in a non-native environment on the Blaze, Spark, or Databricks Spark engine. Consider the following rules and guidelines when you run mappings in the native and non-native environments.


Updated September 28, 2020