Table of Contents


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