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

Flatten Struct

Flatten Struct

The transformation flattens a struct into a field of the data type of the elements in the struct. To flatten a struct data type, all the struct elements must be of the same data type. The transformation creates a row for each element in the struct data type.
For example, you want to flatten the following struct field:
customer_address{ city : string state : string zip : string }
The table contains the following values:
Name
customer_address
Clara
{ New York NY 10032 }
When you flatten the struct port, the output is as follows:
Name
customer_address
GCID_customer_address
Clara
New York
1
Clara
NY
2
Clara
10032
3
When the struct elements are of different data types and at least the first two elements are of the same data type, you can flatten the struct data for consecutive elements of the same data type. To extract consecutive struct elements of the same data type, edit the Occurs value. The value must be a positive integer greater than 1. For example, a struct emp_address contains the following elements:
emp_address{ city : string state : string zip : int country : string }
You can define the value of Occurs to 2 to extract city and state struct elements. If you define the value as 3 or 4, the mapping validation fails.

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