Table of Contents


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

File Targets on Hadoop

File Targets on Hadoop

A mapping that runs in the Hadoop environment can process complex files and flat files.
To write large volumes of data, you can connect a complex file target to write data to a directory of files that have the same format and properties. You can read compressed binary files.
You can write to complex files in the following storage types in the Hadoop environment:
  • Amazon Simple Storage Service (Amazon S3)
  • Hadoop Distributed File System (HDFS)
  • MapR File System (MapR-FS)
  • Microsoft Azure Blob Storage (Azure Blob Storage)
  • Microsoft Azure Data Lake Store (ADLS)


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