Table of Contents

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  1. Preface
  2. Introduction to Data Transformation
  3. Data Processor Transformation
  4. Wizard Input and Output Formats
  5. Relational Input and Output
  6. XMap
  7. Libraries
  8. Schema Object
  9. Command Line Interface
  10. Scripts
  11. Parsers
  12. Script Ports
  13. Document Processors
  14. Formats
  15. Data Holders
  16. Anchors
  17. Transformers
  18. Actions
  19. Serializers
  20. Mappers
  21. Locators, Keys, and Indexing
  22. Streamers
  23. Validators, Notifications, and Failure Handling
  24. Validation Rules
  25. Custom Script Components

Data Transformation User Guide

Data Transformation User Guide

Optimizing Large COBOL File Processing in the Hadoop Environment

Optimizing Large COBOL File Processing in the Hadoop Environment

You can optimize how a mapping with a complex file reader and a Data Processor transformation processes large COBOL files in the Hadoop environment.
In order to optimize large COBOL file processing, you must be able to use a regular expression to split the records. If the COBOL file can be split with a regular expression, you can define an input parameter for the complex file reader that provides a regular expression that determines how to split record processing in the Hadoop environment.