Table of Contents

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  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

Hive Mappings

Hive Mappings

Based on the mapping environment, you can read data from or write data to Hive.
In a native environment, you can read data from Hive. To read data from Hive, complete the following steps:
  1. Create a Hive connection.
  2. Configure the Hive connection mode to access Hive as a source or target.
  3. Use the Hive connection to create a data object to read from Hive.
  4. Add the data object to a mapping and configure the mapping to run in the native environment.
You can write to Hive in a Hadoop environment. To write data to Hive, complete the following steps:
  1. Create a Hive connection.
  2. Configure the Hive connection mode to access Hive as a source or target.
  3. Use the Hive connection to create a data object to write to Hive.
  4. Add the data object to a mapping and configure the mapping to run in the Hadoop environment.
You can define the following types of objects in a Hive mapping:
  • A Read Transformation to read data from Hive
  • Transformations
  • A target or an SQL data service. You can write to Hive if you run the mapping in a Hadoop cluster.
Validate and run the mapping. You can deploy the mapping and run it or add the mapping to a Mapping task in a workflow.


Updated September 28, 2020