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. Data Preview
  8. Cluster Workflows
  9. Profiles
  10. Monitoring
  11. Hierarchical Data Processing
  12. Hierarchical Data Processing Configuration
  13. Hierarchical Data Processing with Schema Changes
  14. Intelligent Structure Models
  15. Stateful Computing
  16. Appendix A: Connections
  17. Appendix B: Data Type Reference
  18. Appendix C: Function Reference

Hive Sources on Hadoop

Hive Sources on Hadoop

You can include Hive sources in an Informatica mapping that runs in the Hadoop environment.
Consider the following limitations when you configure a Hive source in a mapping that runs in the Hadoop environment:
  • A mapping fails to run when you have Unicode characters in a Hive source definition.
  • The 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.
  • The third-party Hive JDBC driver does not return the correct precision and scale values for the Decimal data type. As a result, when you import Hive tables with a Decimal data type into the Developer tool, the Decimal data type precision is set to 38 and the scale is set to 0. Consider the following configuration rules and guidelines based on the version of Hive:
    • Hive 0.11. Accept the default precision and scale for the Decimal data type in the Developer tool.
    • Hive 0.12. Accept the default precision and scale for the Decimal data type in the Developer tool.
    • Hive 0.12 with Cloudera CDH 5.0. You can configure the precision and scale fields for source columns with the Decimal data type in the Developer tool.
    • Hive 0.13 and above. You can configure the precision and scale fields for source columns with the Decimal data type in the Developer tool.
    • Hive 0.14 or above. The precision and scale used for the Decimal data type in the Hive database also appears in the Developer tool.
A mapping that runs on the Spark engine can have partitioned Hive source tables and bucketed sources.


Updated July 10, 2020