Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Connections
  4. Mappings in the Hadoop Environment
  5. Mapping Objects in the Hadoop Environment
  6. Processing Hierarchical Data on the Spark Engine
  7. Stateful Computing on the Spark Engine
  8. Monitoring Mappings in the Hadoop Environment
  9. Mappings in the Native Environment
  10. Profiles
  11. Native Environment Optimization
  12. Data Type Reference
  13. Complex File Data Object Properties
  14. Function Reference
  15. Parameter Reference

Hadoop Utilities

Hadoop Utilities

Big Data Management uses third-party Hadoop utilities such as Sqoop to process data efficiently.
Sqoop is a Hadoop command line program to process data between relational databases and HDFS through MapReduce programs. You can use Sqoop to import and export data. When you use Sqoop, you do not need to install the relational database client and software on any node in the Hadoop cluster.
To use Sqoop, you must configure Sqoop properties in a JDBC connection and run the mapping in the Hadoop environment. You can configure Sqoop connectivity for relational data objects, customized data objects, and logical data objects that are based on a JDBC-compliant database. For example, you can configure Sqoop connectivity for the following databases:
  • Aurora
  • Greenplum
  • IBM DB2
  • IBM DB2 for z/OS
  • Microsoft SQL Server
  • Netezza
  • Oracle
  • Teradata
The Model Repository Service uses JDBC to import metadata. The Data Integration Service runs the mapping in the Hadoop run-time environment and pushes the job processing to Sqoop. Sqoop then creates map-reduce jobs in the Hadoop cluster, which perform the import and export job in parallel.

Specialized Sqoop Connectors

When you run mappings through Sqoop, you can use the following specialized connectors:
OraOop
You can use OraOop with Sqoop to optimize performance when you read data from or write data to Oracle. OraOop is a specialized Sqoop plug-in for Oracle that uses native protocols to connect to the Oracle database.
You can configure OraOop when you run Sqoop mappings on the Spark and Hive engines.
Teradata Connector for Hadoop (TDCH) Specialized Connectors for Sqoop
You can use the following TDCH specialized connectors for Sqoop when you read data from or write data to Teradata:
  • Cloudera Connector Powered by Teradata
  • Hortonworks Connector for Teradata (powered by the Teradata Connector for Hadoop)
Cloudera Connector Powered by Teradata and Hortonworks Connector for Teradata are specialized Sqoop plug-ins that Cloudera and Hortonworks provide for Teradata. These TDCH Sqoop Connectors use native protocols to connect to the Teradata database.
You can configure the Cloudera Connector Powered by Teradata and Hortonworks Connector for Teradata when you run Sqoop mappings on the Blaze and Spark engines.
For information about running native Teradata mappings with Sqoop, see the
Informatica PowerExchange for Teradata Parallel Transporter API User Guide
.


Updated November 09, 2018