Communities
A collaborative platform to connect and grow with like-minded Informaticans across the globe
Product Communities
Connect and collaborate with Informatica experts and champions
Discussions
Have a question? Start a Discussion and get immediate answers you are looking for
User Groups
Customer-organized groups that meet online and in-person. Join today to network, share ideas, and get tips on how to get the most out of Informatica
Get Started
Community Guidelines
Knowledge Center
Troubleshooting documents, product guides, how to videos, best practices, and more
Knowledge Base
One-stop self-service portal for solutions, FAQs, Whitepapers, How Tos, Videos, and more
Support TV
Video channel for step-by-step instructions to use our products, best practices, troubleshooting tips, and much more
Documentation
Information library of the latest product documents
Velocity (Best Practices)
Best practices and use cases from the Implementation team
Learn
Rich resources to help you leverage full capabilities of our products
Trainings
Role-based training programs for the best ROI
Certifications
Get certified on Informatica products. Free, Foundation, or Professional
Product Learning Paths
Free and unlimited modules based on your expertise level and journey
Resources
Library of content to help you leverage the best of Informatica products
Tech Tuesdays Webinars
Most popular webinars on product architecture, best practices, and more
Product Availability Matrix
Product Availability Matrix statements of Informatica products
SupportFlash
Monthly support newsletter
Support Documents
Informatica Support Guide and Statements, Quick Start Guides, and Cloud Product Description Schedule
Product Lifecycle
End of Life statements of Informatica products
Informatica Demos
Simulation-driven learning modules
Ideas
Events
Change Request Tracking
Marketplace
English
  • Data Integration
  • All Products

Table of Contents

Search

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

Transformations

Transformations

Back Next

Source filtering and sorting

Source filtering and sorting

You can configure the Source transformation to filter or sort data before the data enters the data flow. Use the source query options to filter or sort source data.
Configure the query options on the
Source
 tab of the Source transformation. Expand the
Query Options
 section, and configure the filter and sort conditions.
You can use the following source query options:
Filter
Filter source data to limit the amount of source data that enters the data flow. You can create the following types of filters:
  • Non-parameterized. Select the source field and configure the operator and value to use in the filter. When you configure more than one filter, the task applies the filter expressions in the listed order with an AND operator between the filters.
  • Completely parameterized. Use a parameter for a filter expression and define the filter expression in the task.
  • Advanced. Create complex expressions that use AND, OR, or nested conditions. The expression that you enter becomes the WHERE clause in the query used to retrieve records from the source. You can use source fields, input and in-out parameters, or system variables in the expression.
    For example, you can use an input parameter for one of the fields, and select it when the task runs. You can reuse the same parameter in an Expression transformation to create a field expression and also in the Target transformation. Or, you can you an in-out parameter in the expression to retrieve rows that have been updated since the last run.
    For more information about system variables, see
    Function Reference
    . For more information about parameters, see
    Mappings
    .
    You can convert simple non-parameterized data filters to an advanced data filter, but you cannot convert an advanced data filter to simple data filters.
Sort
You can sort source data to provide sorted data to the mapping. For example, you can improve task performance when you provide sorted data to an Aggregator transformation that uses sorted data.
When you sort data, you select one or more source fields. When you select more than one source field, the task sorts the fields in the listed order.
Data in each field is sorted in ascending order. If you want to sort in descending order, you can use the Sorter transformation.
You can use parameters for the sort fields and define the sort fields in the task.
0 COMMENTS
We’d like to hear from you!
Sam Greene - August 17, 2022

I would appreciate more documentation on the advanced filter option.  My use case is checking a destination table for the max date and then querying a source table to find data newer than my max date.  What syntax is valid in the advanced editor, could I used a unconnected lookup and reference the value.  The advanced editor doesn't have the same reference functionality as the expression builder, so it is difficult to tell what is possible. 

Informatica Documentation Team - August 17, 2022

​​​​​​​Hi Sam Greene. There is some additional information about advanced filters in the topic Data Filters in Tasks. We’re working to address the comments you entered about your use case and about adding additional information to this section of the documentation and will get back to you. Thanks, Informatica Documentation team

Informatica Documentation Team - August 20, 2022

Hi again Sam Greene. We've checked with our QA team and they recommend that you use an in-out parameter to store the max date for data that has been loaded to the target during each mapping run. In-out parameters can be used in a Filter transformation or in the source filter to ensure that you are only reading rows that were not processed during the previous mapping run. You can find more information about in-out parameters in the "In-out parameters" topic in Mappings. Using an unconnected lookup is probably not the best approach in this case since your source data is not static.

If you need further help with your specific use case, please reach out to Informatica Global Customer Support.

We will file a documentation enhancement request to add more information about valid syntax in the advanced filter editor.

Thanks, Informatica Documentation team