Table of Contents

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  1. Preface
  2. Introduction to Big Data Streaming
  3. Big Data Streaming Configuration
  4. Sources in a Streaming Mapping
  5. Targets in a Streaming Mapping
  6. Streaming Mappings
  7. Window Transformation
  8. Appendix A: Connections
  9. Appendix B: Data Type Reference
  10. Appendix C: Sample Files

Big Data Streaming User Guide

Big Data Streaming User Guide

Microsoft SQL Server Data Types

Microsoft SQL Server Data Types

Informatica supports the following Microsoft SQL Server data types when you use Sqoop:
  • Bigint
  • Bit
  • Char
  • Datetime
  • Datetime2
  • Decimal
  • Float
  • Image
  • INT
  • Money
  • Nchar
  • Ntext
  • Numeric
  • Nvarchar
  • Real
  • Smalldatetime
  • Smallint
  • Smallmoney
  • Sysname
  • Timestamp
  • Tinyint
  • Uniqueidentifier
  • Varbinary
  • Varchar

Rules and Guidelines for Sqoop Microsoft SQL Server Data Types

Consider the following rules and guidelines when you configure Microsoft SQL Server data types when you use Sqoop in a streaming mapping:
  • Use the Varbinary data type if the target table that you write to has a column of binary data type because Spark DataFrame does not have a corresponding data type to match its native type and the mapping might throw a runtime exception.
  • Use the Varbinary data type only if you have imported the table while creating the relational target or you selected the
    Create or replace table at runtime
    property in the Advance properties. Spark DataFrame does not have a corresponding data type to match its native type.
  • If you export timestamp data, an error occurs as the timestamp data is automatically generated by the database. Use the datetime data type.