Table of Contents


  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

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 one of the following job execution engines:
  • Blaze engine
  • Spark engine
  • Hive engine
For more information about how Big Data Management uses each engine to run mappings, workflows, and other tasks, see the chapter about Big Data Management Engines.

Updated October 23, 2019