Table of Contents


  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Flat File Sources

Flat File Sources

A mapping that is running in a Hadoop environment can read a flat file source from a native environment.
Consider the following limitations when you configure the mapping to read a flat file source:
  • You cannot use an indirect source type.
  • The row size in a flat file source cannot exceed 190 MB.
  • You cannot use a command to generate or to transform flat file data and send the output to the flat file reader at run time.

Updated October 23, 2019