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

Lookup Transformation Support on the Hive Engine

Lookup Transformation Support on the Hive Engine

If you add a data object that uses Sqoop as a Lookup transformation in a mapping, the Data Integration Service does not run the mapping through Sqoop. It runs the mapping through JDBC.
When you a run mapping that contains a Lookup transformation, the Data Integration Service creates lookup cache .jar files. Hive copies the lookup cache .jar files to the following temporary directory:
. The Hive parameter
determines the location of the temporary directory. You can delete the lookup cache .jar files specified in the LDTM log after the mapping completes to retrieve disk space.

Mapping Validation

Mapping validation fails in the following situations:
  • The cache is configured to be shared, named, persistent, dynamic, or uncached. The cache must be a static cache.
  • The lookup is a relational Hive data source.
Mappings fail in the following situations:
  • The lookup is unconnected.