Table of Contents

Search

  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. Cleanse transformation
  8. Data Masking transformation
  9. Data Services transformation
  10. Deduplicate transformation
  11. Expression transformation
  12. Filter transformation
  13. Hierarchy Builder transformation
  14. Hierarchy Parser transformation
  15. Hierarchy Processor transformation
  16. Input transformation
  17. Java transformation
  18. Java transformation API reference
  19. Joiner transformation
  20. Labeler transformation
  21. Lookup transformation
  22. Machine Learning transformation
  23. Mapplet transformation
  24. Normalizer transformation
  25. Output transformation
  26. Parse transformation
  27. Python transformation
  28. Rank transformation
  29. Router transformation
  30. Rule Specification transformation
  31. Sequence Generator transformation
  32. Sorter transformation
  33. SQL transformation
  34. Structure Parser transformation
  35. Transaction Control transformation
  36. Union transformation
  37. Velocity transformation
  38. Verifier transformation
  39. Web Services transformation

Transformations

Transformations

Hierarchical to relational data processing

Hierarchical to relational data processing

In a mapping that converts hierarchical data to relational output, you can process one hierarchical input group and write the data to multiple relational output groups. The output data can be written as normalized relational data or to delimited flat files.
The following image shows an example mapping:
The mapping contains a Source transformation that is connected to a Hierarchy Processor transformation that is connected to two Target transformations.
In this mapping, the data source is a complex file containing customer and order data. The data flows into two relational files: a file with customer data and a file with order data.

0 COMMENTS

We’d like to hear from you!