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

Dynamic cache updates

Dynamic cache updates

When the
mapping
task reads a row, it changes the lookup cache depending on the results of the lookup query and the Lookup transformation properties that you define. The
mapping
task assigns a value to the NewLookupRow return field that indicates the action it takes.
The following table lists the possible NewLookupRow values:
NewLookupRow Value
Description
0
Mapping
task does not update or insert the row in the cache.
1
Mapping
task inserts the row into the cache.
2
Mapping
task updates the row in the cache.
You can use the NewLookupRow values in downstream transformations.

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