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

Comparison to Joiner transformation

Comparison to Joiner transformation

A Union transformation can merge data from multiple sources but does not combine data based on a join condition or remove duplicate rows, like a Joiner transformation.
The following table identifies some key differences between the Union transformation and Joiner transformation, which also merges data from multiple sources. Factor these differences into your mapping design:
Requirement
Union transformation
Joiner transformation
Remove duplicate rows
No. You can use a Router or Filter transformation downstream from the Union transformation to remove duplicates.
Yes
Combine records based on a join condition
No. The Union Transformation is equivalent to a UNION ALL statement in SQL, which combines data vertically from multiple sources.
Yes. The Joiner transformation supports Normal, Right Outer, Left Outer, and Full Outer JOINs.
Include multiple input groups
Yes. You can define multiple input groups and one output group.
Yes. You can define two input groups, Master and Detail.
Include heterogeneous sources
Yes
No
Merge different data types
All of the source columns must have similar data types. The number of columns in each source must be the same.
At least one column in the sources to be joined must have the same data type.
Generate transactions
No
Yes