Preface
Introduction to Informatica Big Data Management
Mappings in the Hadoop Environment
Mapping Sources in the Hadoop Environment
Mapping Targets in the Hadoop Environment
Mapping Transformations in the Hadoop Environment
Processing Hierarchical Data on the Spark Engine
Configuring Transformations to Process Hierarchical Data
Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
Stateful Computing on the Spark Engine
Monitoring Mappings in the Hadoop Environment
Mappings in the Native Environment
Profiles
Native Environment Optimization
Cluster Workflows
Connections
Data Type Reference
Function Reference
- Function Support in the Hadoop Environment
- Function and Data Type Processing
  - Rules and Guidelines for Spark Engine Processing
  - Rules and Guidelines for Hive Engine Processing
Parameter Reference
- Parameters Overview
- Parameter Usage

Big Data Management User Guide

10.2.1
- 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
- 10.2.2

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Deploy and Run the Workflow

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

You can monitor cluster provisioning tasks on the AWS or Azure 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 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

Big Data Management User Guide

Big Data Management User Guide

Deploy and Run the Workflow

Deploy and Run the Workflow