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

Validation Environments

Validation Environments

The properties in the
Validation Environments
indicate whether the Developer tool validates the mapping definition for the native execution environment or the Hadoop execution environment.
You can configure the following properties for the
Validation Environments
Default environment. The Data Integration Service runs the mapping in a native environment.
Run the mapping in the Hadoop environment. The Data Integration Service pushes the transformation logic to the Hadoop cluster through a Hadoop connection. The Hadoop cluster processes the data. Select the engine to process the mapping. You can select the Blaze, Spark, or Hive engines.
You can use a mapping parameter to indicate the execution environment. When you select the execution environment, click
Assign Parameter
. Configure a string parameter. Set the default value to Native or Hadoop.
When you validate the mapping, validation occurs for each engine that you choose in the
Validation Environments
. The validation log might contain validation errors specific to each engine. If the mapping is valid for at least one mapping, the mapping is valid. The errors for the other engines appear in the validation log as warnings. If the mapping is valid for multiple Hadoop engines, you can view the execution plan to determine which engine will run the job. You can view the execution plan in the
Data Viewer
The following image shows validation errors for the Blaze, Spark, and Hive engines:

Updated October 23, 2019