Table of Contents

Search

  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

Mapping Output Binding

Mapping Output Binding

You can configure mapping outputs for standalone mappings or mappings that are a part of a workflow. You can bind persisted mapping outputs to use them in subsequent runs of the mapping or workflow.

Standalone Deployed Mappings

You can persist a mapping output in the Model repository for mappings that run in the native environment or on the Spark engine. You can bind a mapping output to a mapping parameter to pass the value of the output to the mapping the next time you run the mapping.
For more information about mapping outputs in standalone mappings, see the "Mapping Outputs" chapter in the
Developer Mapping Guide
.

Mapping Tasks in Workflows

If you add a mapping to a workflow that runs on the Spark or Blaze engine, you can configure mapping outputs. You can persist a mapping output in the Model repository to assign the persisted output to a Mapping task input, or you can bind a mapping output to a workflow variable to pass the value of the output to other tasks in the workflow. The mappings that run on these engines provide the total number of target, source, and error rows.
You cannot use the SUM aggregation type in mapping outputs on the Spark engine.
For more information about mapping outputs in workflow Mapping tasks, see the "Mapping Task" chapter in the
Developer Workflow Guide
.

0 COMMENTS

We’d like to hear from you!