Big Data Management User Guide > Mapping Transformations in the Hadoop Environment > Lookup Transformation in the Hadoop Environment
  

Lookup Transformation in the Hadoop Environment

The Lookup transformation processing in the Hadoop environment depends on the engine that runs the transformation.

Lookup Transformation Support on the Blaze Engine

Mapping validation fails in the following situations:
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.

Lookup Transformation Support on the Spark Engine

Some processing rules for the Spark engine differ from the processing rules for the Data Integration Service.

Mapping Validation

Mapping validation fails in the following situations:
The mapping fails in the following situation:

Multiple Matches

When you choose to return the first, last, or any value on multiple matches, the Lookup transformation returns any value.
If you configure the transformation to report an error on multiple matches, the Spark engine drops the duplicate rows and does not include the rows in the logs.

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:/tmp/<user_name>/hive_resources . The Hive parameter hive.downloaded.resources.dir 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:
Mappings fail in the following situations: