Table of Contents

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  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

Workflows that Run Mappings in a Hadoop Environment

Workflows that Run Mappings in a Hadoop Environment

You can add a mapping that you configured to run in a Hadoop 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.
When a Mapping task runs a mapping configured to run in a Hadoop environment, do not assign the Mapping task outputs to workflow variables. Mappings that run in a Hadoop environment do not provide the total number of target, source, and error rows. When a Mapping task includes a mapping that runs in a Hadoop environment, the task outputs contain a value of zero (0).


Updated October 23, 2019