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. Monitoring Mappings in the Hadoop Environment
  7. Mappings in the Native Environment
  8. Profiles
  9. Native Environment Optimization
  10. Data Type Reference
  11. Function Reference
  12. Parameter Reference
  13. Multiple Blaze Instances on a Cluster

Targets in a Hadoop Environment

Targets in a Hadoop Environment

You can push a mapping to the Hadoop environment that includes a target 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 targets in a Hadoop environment:
  • Complex files
  • Flat file (native)
  • Greenplum
  • HBase
  • HDFS flat file
  • Hive
  • IBM DB2
  • Netezza
  • ODBC
  • Oracle
  • Sqoop targets
  • Teradata
A mapping that runs with the Spark engine can have partitioned Hive target tables but it cannot have bucketed targets.
When a mapping runs in the Hadoop environment, an HDFS target or a Hive target 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.


Updated July 03, 2018