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  • Common Content for Data Engineering 10.2.2 Service Pack 1
  • All Products

Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings
  4. Sources
  5. Targets
  6. Transformations
  7. Cluster Workflows
  8. Profiles
  9. Monitoring
  10. Hierarchical Data Processing
  11. Hierarchical Data Processing Configuration
  12. Hierarchical Data Processing with Schema Changes
  13. Intelligent Structure Models
  14. Stateful Computing
  15. Connections
  16. Data Type Reference
  17. Function Reference

User Guide

User Guide

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Sqoop Mappings in a Hadoop Environment

Sqoop Mappings in a Hadoop Environment

You can use a JDBC connection that is enabled for Sqoop connectivity to import a Sqoop source or Sqoop target and create a mapping. You can run Sqoop mappings on the Blaze and Spark engines.
If you use Cloudera Connector Powered by Teradata or Hortonworks Connector for Teradata, you can run mappings on the Blaze or Spark engines. If you use MapR Connector for Teradata, you can run mappings on the Spark engine.
In the mapping, you can specify additional Sqoop arguments and disable the Sqoop connector.
If you add or delete a Type 4 JDBC driver .jar file required for Sqoop connectivity from the
externaljdbcjars
 directory, changes take effect after you restart the Data Integration Service. If you run the mapping on the Blaze engine, changes take effect after you restart the Data Integration Service and Blaze Grid Manager. When you run the mapping for the first time, you do not need to restart the Data Integration Service and Blaze Grid Manager. You need to restart the Data Integration Service and Blaze Grid Manager only for the subsequent mapping runs.
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