Table of Contents

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  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

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
true
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 Blaze or Hive.
  • In scenarios where MERGE is restricted by Hive implementation on particular Hadoop distributions.
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.


Updated October 23, 2019