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. B2B transformation
  8. Chunking transformation
  9. Cleanse transformation
  10. Data Masking transformation
  11. Data Services transformation
  12. Deduplicate transformation
  13. Expression transformation
  14. Filter transformation
  15. Hierarchy Builder transformation
  16. Hierarchy Parser transformation
  17. Hierarchy Processor transformation
  18. Input transformation
  19. Java transformation
  20. Java transformation API reference
  21. Joiner transformation
  22. Labeler transformation
  23. Lookup transformation
  24. Machine Learning transformation
  25. Mapplet transformation
  26. Normalizer transformation
  27. Output transformation
  28. Parse transformation
  29. Python transformation
  30. Rank transformation
  31. Router transformation
  32. Rule Specification transformation
  33. Sequence transformation
  34. Sorter transformation
  35. SQL transformation
  36. Structure Parser transformation
  37. Transaction Control transformation
  38. Union transformation
  39. Vector Embedding transformation
  40. Velocity transformation
  41. Verifier transformation
  42. Web Services transformation

Transformations

Transformations

Update columns for relational targets

Update columns for relational targets

You can configure one or more fields as update columns in relational targets. Update columns are columns that uniquely identify rows in the target table. The mapping task uses them to update, upsert, or delete data in the target.
Configure update columns when the target table does not contain a primary key and the mapping uses an update, upsert, or delete operation. When you select more than one update column, the mapping uses the AND operator with the update columns to identify matching rows.
When you run the mapping, it uses the field mapping to match rows in the upstream transformations to the target table. If the
mapping
task matches an incoming row to multiple target rows, it performs the specified task operation on all matched target rows.
When you use a parameter for the target connection or target object, you can configure update columns in the
mapping
task.

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