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  • Data Engineering Integration 10.2.1
  • All Products

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

Big Data Management User Guide

Big Data Management User Guide

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Mappings in the Hadoop Environment Overview

Mappings in the Hadoop Environment Overview

Configure the Hadoop run-time environment in the Developer tool to optimize mapping performance and process data that is greater than 10 terabytes. In the Hadoop environment, the Data Integration Service pushes the processing to nodes on a Hadoop cluster. When you select the Hadoop environment, you can also select the engine to push the mapping logic to the Hadoop cluster.
You can run standalone mappings, mappings that are a part of a workflow in the Hadoop environment.
Based on the mapping logic, the Hadoop environment can use the following engines to push processing to nodes on a Hadoop cluster:
  • Informatica Blaze engine. An Informatica proprietary engine for distributed processing on Hadoop.
  • Spark engine. A high performance engine for batch processing that can run on a Hadoop cluster or on a Spark standalone mode cluster.
  • Hive engine. A batch processing engine that uses Hadoop technology such as MapReduce or Tez.
    Effective in version 10.2.1, the MapReduce mode of the Hive run-time engine is deprecated, and Informatica will drop support for it in a future release. The Tez mode remains supported.
When you configure the mapping, Informatica recommends that you select all engines. The Data Integration Service determines the best engine to run the mapping during validation. You can also choose to select which engine the Data Integration Service uses. You might select an engine based on whether an engine supports a particular transformation or based on the format in which the engine returns data.
When you run a mapping in the Hadoop environment, you must configure a Hadoop connection for the mapping. When you edit the Hadoop connection, you can set the run-time properties for the Hadoop environment and the properties for the engine that runs the mapping.
You can view the execution plan for a mapping to run in the Hadoop environment. View the execution plan for the engine that the Data Integration Service selects to run the mapping.
You can monitor Hive queries and the Hadoop jobs in the Monitoring tool. Monitor the jobs on a Hadoop cluster with the YARN Web User Interface or the Blaze Job Monitor web application.
The Data Integration Service logs messages from the DTM, the Blaze engine, the Spark engine, and the Hive engine in the run-time log files.
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