Preface
Introduction to Informatica Big Data Management
Mappings
Sources
Targets
Transformations
Data Preview
Cluster Workflows
Profiles
Monitoring
Hierarchical Data Processing
Hierarchical Data Processing Configuration
Hierarchical Data Processing with Schema Changes
Intelligent Structure Models
Stateful Computing
Appendix A: Connections
Appendix B: Data Type Reference
Appendix C: Function Reference
- Function Support in a Non-native Environment
- Function and Data Type Processing
  - Rules and Guidelines for Spark Engine Processing

User Guide

10.2.2
- 10.5.7
- 10.5.6
- 10.5.5
- 10.5.4
- 10.5.3
- 10.5.2
- 10.5.1
- 10.5
- 10.4.1
- 10.4.0
- 10.2.2 HotFix 1
- 10.2.2 Service Pack 1
- 10.2.1

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Deploy and Run the Workflow

After you complete the cluster workflow, deploy and run the workflow.

You can monitor AWS and Azure cluster workflows on the web console. If you configured a log location, view the logs at the location that you configured in the Create Cluster task properties.

You can monitor Databricks cluster workflows on the Databricks workspace.

You can also monitor Data Integration Service jobs in the Administrator tool.

After the workflow begins executing tasks, the task to provision the cluster may take several minutes.

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Table of Contents

User Guide

User Guide

Deploy and Run the Workflow

Deploy and Run the Workflow