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Table of Contents

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  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

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Example - Hierarchical to Relational Transformation

Example - Hierarchical to Relational Transformation

The Logistics department of the Harrinder Shipping company must process shipment data. They need to transform inventory and customer data from hierarchical format into relational data that they can store in database tables.
They need to create a mapping that transforms hierarchical data into relational data. The organization inventory system generates shipment inventory data in hierarchical format. The mapping needs to use a Hierarchical to Relational transformation that inputs shipment data and outputs the details in a usable relational format.
The Shipments input is in hierarchical format. The Shipment element contains sub-elements with customer and inventory data for each shipment: 

      
Shipments

     Shipment
    	 Items
	      Item_Name
	      Inventory_ID
     	Customer
	      Customer_Name
	      Customer_ID
	      Customer_Address
In the relational output, the Customer_ID element is a primary key in the Customer table, and is a Foreign key in the Shipment table.
Customer_ID
Customer_Name
Customer_Address
3543766
Tony Birch
6 Moby Drive
6342562
Sujita Man
22 Dan Street
6471862
Dwayne Horace
7 Jafendar Boulevard
7265204
Carmela Perez
23 Dan Street
4559672
Delilah Soraya
28 Jafendar Boulevard
Shipment_ID
Inventory_Item
Customer_ID
9173327437
908274
7265204
9174562342
553439
7265204
8484526471
546584
3543766
7023847265
908274
3543766
9174596725
553439
3543766
The following image shows the mapping in this example:
Create a mapping with hierarchical input, relational output, and a Hierarchical to Relational transformation.
The mapping contains the following objects:
Read_input
The source that contains the path to the file with hierarchical data. Reads billing data from an XML file.
Shipping_Transform
A Hierarchical to Relational transformation that transforms XML input into relational output.
Write_Output2
A target that stores part of the transformed data, the Customer table, in relational format.
Write_Output3
A second target that stores another part of the transformed data, the Shipment table, in relational format.
The mapping uses the
Read_input
 flat file to input the target path for the hierarchical input. The mapping processes and transforms the data with the
Shipping_Transform
 transformation. Then the mapping stores the output in the two output targets.
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