Table of Contents

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  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

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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