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

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Sources in a Hadoop Environment

You can push a mapping to the Hadoop environment that includes a source from the native environment or from the Hadoop environment. Some sources have limitations when you reference them in the Hadoop environment.

You can run mappings with the following sources in a Hadoop environment:

Complex file sources

Flat file sources

HBase sources

Hive sources

Intelligent structure model sources

ODBC sources

Relational sources

Sqoop sources

When a mapping runs in the Hadoop environment, an HDFS source or a Hive source cannot reside on a remote cluster. A remote cluster is a cluster that is remote from the machine that the Hadoop connection references in the mapping.

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Table of Contents

Big Data Management User Guide

Big Data Management User Guide

Sources in a Hadoop Environment

Sources in a Hadoop Environment