Table of Contents

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  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

Validation Environments

Validation Environments

The properties in the
Validation Environments
indicate whether the Developer tool validates the mapping definition for the native or non-native execution environment.
You can configure the following properties for the
Validation Environments
:
Native
Default environment. The Data Integration Service runs the mapping in a native environment.
Hadoop
Run the mapping in the Hadoop environment. The Data Integration Service pushes the transformation logic to the Hadoop cluster through a Hadoop connection. Select the engine to process the mapping. You can select the Blaze or Spark engine.
Databricks
Run the mapping in the Databricks environment. The Data Integration Service pushes the transformation logic to the Databricks cluster through a Databricks connection. The Databricks cluster processes the mapping on the Databricks Spark engine.
You can use a mapping parameter to indicate the execution environment for the mapping. When you select the execution environment, click
Assign Parameter
. Configure a string parameter. Set the default value to native, hadoop, or spark-databricks.
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 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
view.
The following image shows a sample validation log:
The image shows the validation log view. Errors in information messages appear under the mappings that they apply to.


Updated September 28, 2020