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. Data Preview
  8. Cluster Workflows
  9. Profiles
  10. Monitoring
  11. Hierarchical Data Processing
  12. Hierarchical Data Processing Configuration
  13. Hierarchical Data Processing with Schema Changes
  14. Intelligent Structure Models
  15. Stateful Computing
  16. Appendix A: Connections
  17. Appendix B: Data Type Reference
  18. Appendix C: Function Reference

Big Data Management Engines

Big Data Management Engines

When you run a big data mapping, you can choose to run the mapping in the native environment or in a non-native environment, such as Hadoop or Databricks. When you validate a mapping, you can validate it against one or all of the engines. The Developer tool returns validation messages for each engine.
When you run a mapping in the native environment, the Data Integration Service in the Informatica domain runs the mapping. When you run the mapping in a non-native environment, the Data Integration Service pushes the run-time processing to a compute cluster in the non-native environment.
When you run the mapping in a non-native environment, the Data Integration Service uses a proprietary rule-based methodology to determine the best engine to run the mapping. The rule-based methodology evaluates the mapping sources and the mapping logic to determine the engine. The Data Integration Service translates the mapping logic into code that the engine can process, and it transfers the code to the engine.
The following image shows the processing environments and the run-time engines in the environments:


Updated July 10, 2020