Table of Contents


  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. B2B transformation
  7. Aggregator transformation
  8. Cleanse transformation
  9. Data Masking transformation
  10. Data Services transformation
  11. Deduplicate transformation
  12. Expression transformation
  13. Filter transformation
  14. Hierarchy Builder transformation
  15. Hierarchy Parser transformation
  16. Hierarchy Processor transformation
  17. Input transformation
  18. Java transformation
  19. Java transformation API reference
  20. Joiner transformation
  21. Labeler transformation
  22. Lookup transformation
  23. Machine Learning transformation
  24. Mapplet transformation
  25. Normalizer transformation
  26. Output transformation
  27. Parse transformation
  28. Python transformation
  29. Rank transformation
  30. Router transformation
  31. Rule Specification transformation
  32. Sequence Generator transformation
  33. Sorter transformation
  34. SQL transformation
  35. Structure Parser transformation
  36. Transaction Control transformation
  37. Union transformation
  38. Velocity transformation
  39. Verifier transformation
  40. Web Services transformation



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.


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.