Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Connections
  4. Mappings in the Hadoop Environment
  5. Mapping Objects in the Hadoop Environment
  6. Processing Hierarchical Data on the Spark Engine
  7. Stateful Computing on the Spark Engine
  8. Monitoring Mappings in the Hadoop Environment
  9. Mappings in the Native Environment
  10. Profiles
  11. Native Environment Optimization
  12. Data Type Reference
  13. Complex File Data Object Properties
  14. Function Reference
  15. Parameter 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 a Hadoop environment. If you run the mapping in a Hadoop environment, the mapping will run on the Blaze engine, the Spark engine, or the Hive engine.
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.
You can then choose to run the mapping in the native environment or in the Hadoop environment. When you run the mapping in the native environment, the Data Integration Service processes the mapping logic. When you run the mapping in the Hadoop 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.


Updated December 13, 2018