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. Deduplicate transformation
  9. Expression transformation
  10. Filter transformation
  11. Hierarchy Builder transformation
  12. Hierarchy Parser transformation
  13. Hierarchy Processor transformation
  14. Input transformation
  15. Java transformation
  16. Java transformation API reference
  17. Joiner transformation
  18. Labeler transformation
  19. Lookup transformation
  20. Mapplet transformation
  21. Normalizer transformation
  22. Output transformation
  23. Parse transformation
  24. Python transformation
  25. Rank transformation
  26. Router transformation
  27. Rule Specification transformation
  28. Sequence Generator transformation
  29. Sorter transformation
  30. SQL transformation
  31. Structure Parser transformation
  32. Transaction Control transformation
  33. Union transformation
  34. Velocity transformation
  35. Verifier transformation
  36. Web Services transformation

Transformations

Transformations

Active and passive transformations

Active and passive transformations

A transformation can be active or passive.
An active transformation can change the number of rows that pass through the transformation. For example, the Filter transformation is active because it removes rows that do not meet the filter condition.
A passive transformation does not change the number of rows that pass through the transformation.
You can connect multiple branches to a downstream passive transformation when all transformations in the branches are passive.
You cannot connect multiple active transformations or an active and a passive transformation to the same downstream transformation or transformation input group. You might not be able to concatenate the rows. An active transformation changes the number of rows, so it might not match the number of rows from another transformation.
For example, one branch in a mapping contains an Expression transformation, which is passive, and another branch contains an Aggregator transformation, which is active. The Aggregator transformation performs aggregations on groups, such as sums, and reduces the number of rows. If you connect the branches,
Data Integration
cannot combine the rows from the Expression transformation with the different number of rows from the Aggregator transformation. Use a Joiner transformation to join the two branches.