Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Connections
  4. Mappings in a Hadoop Environment
  5. Mapping Objects in a Hadoop Environment
  6. Mappings in the Native Environment
  7. Profiles
  8. Native Environment Optimization
  9. Data Type Reference
  10. Function Reference
  11. Parameter Reference

Hive Sources

Hive Sources

You can include Hive sources in an Informatica mapping that runs in a Hadoop environment.
Consider the following limitations when you configure a Hive source in a mapping that runs in a Hadoop environment:
  • The Data Integration Service can run pre-mapping SQL commands against the source database before it reads from a Hive source. When you run a mapping with a Hive source in a Hadoop environment, references to a local path in pre-mapping SQL commands are relative to the Data Integration Service node. When you run a mapping with a Hive source in the native environment, references to local path in pre-mapping SQL commands are relative to the Hive server node.
  • A mapping fails to validate when you configure post-mapping SQL commands. The Data Integration Service does not run post-mapping SQL commands against a Hive source.
  • A mapping fails to run when you have Unicode characters in a Hive source definition.
  • 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 with the Spark engine can have partitioned Hive source tables and bucketed sources.
Consider the following limitations when you configure a Hive source in a mapping that runs with the Blaze engine:
  • Hive sources for a Blaze mapping include the TEXT, Sequence, Avro, RC, ORC, and Parquet storage formats.
  • The TEXT storage format in a Hive source for a Blaze mapping can support ASCII characters as column delimiters and the newline characters as a row separator. You cannot use hex values of ASCII characters. For example, use a semicolon (;) instead of 3B.
  • You cannot define an SQL override in the Hive source for a Blaze mapping.
  • Hive sources for a Blaze mapping cannot use bucketed tables.


Updated July 03, 2018