Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings
  4. Sources
  5. Targets
  6. Transformations
  7. Data Preview
  8. Cluster Workflows
  9. Profiles
  10. Monitoring
  11. Hierarchical Data Processing
  12. Hierarchical Data Processing Configuration
  13. Hierarchical Data Processing with Schema Changes
  14. Intelligent Structure Models
  15. Stateful Computing
  16. Connections
  17. Data Type Reference
  18. Function Reference

Workflows that Run Mappings in a Non-native Environment

Workflows that Run Mappings in a Non-native Environment

You can add a mapping that you configured to run in a non-native environment to a Mapping task in a workflow. When you deploy and run the workflow, the Mapping task runs the mapping.
You might decide to run a mapping from a workflow so that you can make decisions during the workflow run. You can configure a workflow to run multiple mappings in sequence or in parallel. You can configure a workflow to send emails that notify users about the status of the Mapping tasks.
If you add a mapping to a workflow that runs on the Spark engine, you can also 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.
You cannot use the SUM aggregation type in mapping outputs on the Spark engine.
For more information about mapping outputs, see the "Mapping Task" chapter in the
Developer Workflow Guide
.
When a Mapping task runs a mapping configured to run on the Blaze engine, do not assign the Mapping task outputs to workflow variables. Mappings that run on the Blaze engine do not provide the total number of target, source, and error rows. When a Mapping task includes a mapping that runs on the Blaze engine, the task outputs contain a value of zero (0).


Updated January 20, 2020