Table of Contents

Search

  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Normalizer Example Input and Output Groups

Normalizer Example Input and Output Groups

After you modify the input hierarchy, the Normalizer transformation has one input group and one default output group. You need to reorganize the output ports into two groups. You need one group that contains the Store information and one group that contains the Sales information.
The input group contains a port for each field in the source. The output group contains ports for the store fields and port for the multiple-occurring SalesByQuarter field. The output group also contains a generated column ID,
GCID_SalesByQuarter
, that corresponds to the multiple-occurring SalesByQuarter field.
To return the quarterly sales to a different target, create a new group in the
Overview
view. In the Output1 group, add the following fields:
StoreID SalesByQuarter GCID_SalesByQuarter
Update the default output group. Remove the following fields:
SalesByQuarter GCID_SalesByQuarter
The following image shows the input group and output groups in the
Overview
view:
The Ports tab of the Properties view shows the Normalizer transformation input group and 2 output groups. One group contains the StoreID,StoreName, City, District, and Manager. The other group contains StoreID, SalesByQuarter, and the GCID_SalesByQuarter index.
The StoreID is the generated key that links the Store information with the Sales information. Verify that both output groups return the StoreID.

0 COMMENTS

We’d like to hear from you!