Table of Contents

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  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

Complex File Targets on MapR-FS

Complex File Targets on MapR-FS

Use a PowerExchange for HDFS connection to read data from MapR-FS data objects.
The following table shows the complex files that a mapping can process within MapR-FS storage in the Hadoop environment:
File Type
Supported Formats
Supported Engines
Avro
  • Flat
  • Hierarchical
    1 2
  • Blaze
  • Spark
JSON
  • Flat
    1
  • Hierarchical
    1 2
  • Blaze
  • Spark
ORC
  • Flat
  • Spark
Parquet
  • Flat
  • Hierarchical
    1 2
  • Blaze
  • Spark
1
To run on the Blaze engine, the complex file data object must be connected to a Data Processor transformation.
2
To run on the Spark engine, the complex file read operation must be enabled to project columns as complex data type.


Updated July 10, 2020