Table of Contents


  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. B2B transformation
  7. Aggregator 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 Generator 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



Running a mapping with JSON data

Running a mapping with JSON data

To run a mapping that contains a Hierarchy Processor transformation with JSON-formatted data, you need to use a mapping task.

Reading JSON input

When you read JSON data, the input files can be based on a schema with multiple lines or on a schema with a single line.
The following sample shows a JSON schema on a single line:
{"Name":"Tom","Street":"2100 Seaport Blvd","City":"Redwood City","State":"CA","Country":"USA","Zip":"94063"}
The following sample shows a JSON schema that spans across multiple lines:
{ "Name": "Tom", "Surname": "Day", "City": "Redwood City", "State": "CA", "Country": "USA", "Zip": "94063" }
By default, the Hierarchy Processor transformation reads each JSON schema as a single line. To read input that spans across multiple lines, you can configure the formatting options in the Source transformation to read multiple-line JSON files.

Writing JSON output

When you write JSON data, you can write each output record to a separate file, or you can write all output records to one file.
By default, each output record is written to a separate file. To write the output records to one JSON-formatted file, set the following Spark session property in the mapping task:
Session Property Name
Session Property Value


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