Table of Contents


  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Hive Targets on Hadoop

Hive Targets on Hadoop

A mapping run in the Hadoop environment can write to a Hive target. When you write to a Hive target, consider the processing differences for functionality such as table types, DDL queries, and bucketing.

Hive Table Types

A Hive target can be an internal table or an external table. Internal Hive tables are managed by Hive and are also known as managed tables. External Hive tables are tables managed by an external source such as HDFS, Amazon S3, or Microsoft Azure Blob Storage.
When a mapping creates or replaces a Hive table, the type of table that the mapping creates depends on the run-time engine that you use to run the mapping:
  • On the Blaze engine, mappings create managed tables.
  • On the Spark engine, mappings create external tables.

DDL Queries

For mappings that run on the Spark engine or the Blaze engine, you can create a custom DDL query that creates or replaces a Hive table at run time. However, with the Blaze engine, you cannot use a backtick (`) character in the DDL query. The backtick character is required in HiveQL when you include special characters or keywords in a query.


The Spark engine can write to bucketed Hive targets. Bucketing and partitioning of Hive tables can improve performance by reducing data shuffling and sorting.

Hortonworks HDP 3.1

Hortonworks HDP 3.1 uses ACID-enabled ORC targets by default and uses ACID for all managed tables. If you do not want to use ACID-enabled tables, use external tables.


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