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 Map

Flatten Map

The transformation flattens a map into two fields for the key and value elements in the map. For a map field that you flattened, you cannot change the value of Occurs from Auto to an integer value.
For example, you want to flatten the following map field emp_sal with a string key and an array of integer values:
<emp_name -> [base_sal, bonus, commision]>
The following image shows the map field that you want to flatten in the Normalizer view:
 The Normalizer view shows a string field emp_id and a map field emp_sal. The value of Occurs for the string and map fields is 1.
The table contains the following values:
emp_id
emp_sal
12200
<Greg -> [4000, 1000, 500]>
12201
<Patricia -> [3800, 1500, 1000]>
When you flatten the map port, the output returns a string field for the map key and an array field for the map value as follows:
emp_id
emp_sal_Key
emp_sal_Value
GCID_emp_salary
12200
Greg
[4000, 1000, 500]
1
12201
Patricia
[3800, 1500, 1000]
1
The following image shows the map field that is flattened to a string key field and an array value field in the Normalizer view:
 The Normalizer view shows the map field emp_sal that is flattened to a string field emp_sal_Key and an array field emp_sal_Value with a type configuration string []. A flatten icon is displayed next to the flattened fields. The value of Occurs for the flattened field emp_sal is Auto.
The following image shows the Output group in the Ports view:
 The Ports view of the Normalizer transformation shows an input group with a string port emp_id and a map port emp_sal. The output group contains a string port emp_id, the flattened fields of the map port emp_sal, and a bigint port GCID_emp_sal. The flattened fields of the map port are emp_sal_key of type string and emp_sal_Value of type array with a type configuration string [].

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