Table of Contents

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  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

Transformations

Transformations

Sequence Generator transformation rules and guidelines

Sequence Generator transformation rules and guidelines

Consider the following guidelines when you create a Sequence Generator transformation:
  • When you map the NEXTVAL or CURRVAL output fields, ensure that the data type of the mapped field is appropriate.
  • When you run the mapping in the Mapping Designer, the current value is not saved so each time you run the mapping, it begins with the initial value.
  • When you run the task in the
    mapping
    task wizard, you can edit the current value to start the sequence with a specified value.
  • You cannot use a Sequence Generator transformation in a mapplet.
  • To use the Sequence Generator transformation in advanced mode, the Secure Agent must run on a virtual machine.
  • In advanced mode, generated values might not increase monotonically. Values are generated based on the order that the Spark engine processes the data.
  • A self-service cluster might intermittently fail to connect to the agent, which can cause the mapping to fail. Error messages related to this appear in the session logs.

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