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

Flat File Sources on Hadoop

Flat File Sources on Hadoop

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.


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