Table of Contents


  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

Updating Hive Targets with an Update Strategy Transformation

Updating Hive Targets with an Update Strategy Transformation

For mappings that run on the Spark engine, you can use Hive MERGE statements to perform Update Strategy tasks. When a query uses a MERGE statement instead of INSERT, UPDATE or DELETE statements, processing is more efficient.
To use Hive MERGE, select
for the option in the Advanced Properties of the Update Strategy transformation.
The mapping ignores the Hive MERGE option and the Data Integration Service uses INSERT, UPDATE and DELETE to perform the operation under the following scenarios:
  • The mapping runs on the Blaze engine.
  • Hive MERGE is restricted on the Hadoop distribution.
The mapping log contains results of the operation, including whether restrictions affected results.
When the update affects partitioning or bucketing columns, updates to the columns are omitted.
The Developer tool and the Data Integration Service do not validate against this restriction. If the Update Strategy expression violates these restrictions, the mapping might produce unexpected results.


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