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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

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Variable fields

Variable fields

A variable field defines calculations and stores data temporarily. You can use variable fields in the Expression and Aggregator transformations.
You might use variables to perform the following tasks:
  • Temporarily store data.
  • Simplify complex expressions.
  • Store values from prior rows.
  • Compare values.
For example, you want to generate a mailing list by concatenating first and last names, and then merging the name with the address data. To do this, you might create a variable field, FullName, that concatenates the First and Last fields. Then, you create an expression field, NameAddress, to concatenate the FullName variable field with the Address field.
Mappings don't pass the results of a variable field to the data flow. To use data from a variable field in the data flow, create an expression field for the variable field output. In the preceding example, to pass the concatenated first and last name to the data flow, create a FullName_out expression field. And then, use the FullName variable field as the expression for the field.
You can't use variables to store values from a prior row in a mapping in advanced mode. To compare the current row with a previous row for stateful computation, use a window function in the expression.
0 COMMENTS
We’d like to hear from you!
Alessio Giordani - March 26, 2024

Hello documentation team,

can you please add to the description that in Advance DI mode, variables cannot be used to store values from prior rows?

In advanced mode to compare the current row with the previous row for stateful computation, you can use the window function in the expression 

https://docs.informatica.com/integration-cloud/data-integration/current-version/transformations/expression-transformation/window-functions.html

Regards,

Alessio

     

    Informatica Documentation Team - March 26, 2024

    Hi Alessio Giordani,

    Thanks for bringing this to our attention! We're working on this issue and will update the documentation in a future release.