Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. B2B transformation
  8. Cleanse transformation
  9. Data Masking transformation
  10. Data Services transformation
  11. Deduplicate transformation
  12. Expression transformation
  13. Filter transformation
  14. Hierarchy Builder transformation
  15. Hierarchy Parser transformation
  16. Hierarchy Processor transformation
  17. Input transformation
  18. Java transformation
  19. Java transformation API reference
  20. Joiner transformation
  21. Labeler transformation
  22. Lookup transformation
  23. Machine Learning transformation
  24. Mapplet transformation
  25. Normalizer transformation
  26. Output transformation
  27. Parse transformation
  28. Python transformation
  29. Rank transformation
  30. Router transformation
  31. Rule Specification transformation
  32. Sequence transformation
  33. Sorter transformation
  34. SQL transformation
  35. Structure Parser transformation
  36. Transaction Control transformation
  37. Union transformation
  38. Velocity transformation
  39. Verifier transformation
  40. Web Services transformation

Transformations

Transformations

Flatten selected array

Flatten selected array

When you add an incoming array of primitives to the output, you can flatten the selected array into a field of the same data type.
When you flatten a selected array, it creates one record for each element in the array.

Example of flattening an array

You want to extract the description information from a nested array of maintenance records. The description information is in an array of strings. You want to flatten the output into a string field.
Add the description array to the output group and choose
Flatten Selected Array
.
The following image shows the incoming and output fields:
The image shows the Hierarchy Processor tab of the Hierarchy Processor transformation. The Incoming Fields panel contains one group with the following field: vehicle (array). The vehicle array contains the following fields: make (string), model (string) insurance (struct), and maintenance (array). The insurance struct contains the following fields: company (string) and policy_num (string). The maintenance array contains the following fields: date (string) and description (array of strings). The Output Fields panel contains the following field: description (string).
The output contains one record for each occurrence of description in the incoming data.
For example, the incoming data contains the following record:
[ { "vehicle": [ { "make": "Toyota", "model": "Corolla", "insurance": { "company": "Allstate", "policy_num": "AS12876" }, "maintenance": [ { "date": "01/01/2020", "description": ["oil filter1", "oil filter2"] }, { "date": "01/08/2020", "description": ["tire rotation1", "tire rotation2"] } ] }, { "make": "Toyota", "model": "RAV4", "insurance": { "company": "Allstate", "policy_num": "AS2033" }, "maintenance": [ { "date": "01/02/2020", "description": ["air filter replacement1", "air filter replacement2"] }, { "date": "01/08/2020", "description": ["battery replacement1", "battery replacement2"] } ] } ] } ]
Data Integration
creates the following output records, one for each occurrence of description in the incoming data:
{"description":"oil filter1"} {"description":"oil filter2"} {"description":"tire rotation1"} {"description":"tire rotation2"} {"description":"air filter replacement1"} {"description":"air filter replacement2"} {"description":"battery replacement1"} {"description":"battery replacement2"}

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