Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. Cleanse transformation
  8. Data Masking transformation
  9. Data Services transformation
  10. Deduplicate transformation
  11. Expression transformation
  12. Filter transformation
  13. Hierarchy Builder transformation
  14. Hierarchy Parser transformation
  15. Hierarchy Processor transformation
  16. Input transformation
  17. Java transformation
  18. Java transformation API reference
  19. Joiner transformation
  20. Labeler transformation
  21. Lookup transformation
  22. Machine Learning transformation
  23. Mapplet transformation
  24. Normalizer transformation
  25. Output transformation
  26. Parse transformation
  27. Python transformation
  28. Rank transformation
  29. Router transformation
  30. Rule Specification transformation
  31. Sequence Generator transformation
  32. Sorter transformation
  33. SQL transformation
  34. Structure Parser transformation
  35. Transaction Control transformation
  36. Union transformation
  37. Velocity transformation
  38. Verifier transformation
  39. 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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