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

Joiner transformation

Joiner transformation

The Joiner transformation can join data from two related heterogeneous sources. For example, you can use the Joiner transformation to join account information from flat files with data from the Salesforce Account object.
The Joiner transformation joins data based on the join conditions and the join type. A join condition matches fields between the two sources. You can create multiple join conditions. A join type defines the set of data that is included in the results.
When you link a transformation to the Joiner transformation, you connect it to the Master or Detail group. To improve job performance, connect the transformation that represents the smaller data set to the Master group.
To join more than two sources in a mapping, you can use multiple Joiner transformations. You can join the output from the Joiner transformation with another source pipeline. You can add Joiner transformations to the mapping until you join all source pipelines.
Field name conflicts can occur when you join sources with matching field names. You can resolve the conflict in one of the following ways:
  • Create a field name conflict resolution.
  • Rename matching fields in an upstream transformation.
  • Pass data through an Expression transformation to rename fields.

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We’d like to hear from you!
Yogesh Almiya - June 14, 2023

How do implement OR logic in Joiner transformation?

 

Informatica Documentation Team - June 21, 2023

Hi Yogesh Almiya,

We've confirmed with our QA team that when you enter multiple join conditions, they cannot be "OR"ed together. Instead, you can use multiple Joiner transformations for the individual conditions and try to simulate the "OR" that way.