Table of Contents


  1. Preface
  2. Part 1: Version 10.4.1
  3. Part 2: Version 10.4.0
  4. Part 3: Version 10.2.2
  5. Part 4: Version 10.2.1
  6. Part 5: Version 10.2
  7. Part 6: Version 10.1.1
  8. Part 7: Version 10.1



Effective in version 10.2.2, you can use the following new Sqoop features:
Incremental data extraction support
You can configure a Sqoop mapping to perform incremental data extraction based on an ID or timestamp. With incremental data extraction, Sqoop extracts only the data that changed since the last data extraction. Incremental data extraction increases the mapping performance.
Vertica connectivity support
You can configure Sqoop to read data from a Vertica source or write data to a Vertica target.
Spark engine optimization for Sqoop pass-through mappings
When you run a pass-through mapping with a Sqoop source on the Spark engine, the Data Integration Service optimizes mapping performance in the following scenarios:
  • You write data to a Hive target that was created with a custom DDL query.
  • You write data to an existing Hive target that is either partitioned with a custom DDL query or partitioned and bucketed with a custom DDL query.
  • You write data to an existing Hive target that is both partitioned and bucketed.
--infaownername argument support
You can configure the --infaownername argument to indicate whether Sqoop must honor the owner name for a data object.
For more information, see the
Informatica Big Data Management 10.2.2 User Guide


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