Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Aggregator Transformation
  4. Custom Transformation
  5. Custom Transformation Functions
  6. Data Masking Transformation
  7. Data Masking Examples
  8. Expression Transformation
  9. External Procedure Transformation
  10. Filter Transformation
  11. HTTP Transformation
  12. Identity Resolution Transformation
  13. Java Transformation
  14. Java Transformation API Reference
  15. Java Expressions
  16. Java Transformation Example
  17. Joiner Transformation
  18. Lookup Transformation
  19. Lookup Caches
  20. Dynamic Lookup Cache
  21. Normalizer Transformation
  22. Rank Transformation
  23. Router Transformation
  24. Sequence Generator Transformation
  25. Sorter Transformation
  26. Source Qualifier Transformation
  27. SQL Transformation
  28. Using the SQL Transformation in a Mapping
  29. Stored Procedure Transformation
  30. Transaction Control Transformation
  31. Union Transformation
  32. Unstructured Data Transformation
  33. Update Strategy Transformation
  34. XML Transformations

Transformation Guide

Transformation Guide

Using Group Filter Conditions

Using Group Filter Conditions

You can test data based on one or more group filter conditions. You create group filter conditions on the Groups tab using the Expression Editor. You can enter any expression that returns a single value. You can also specify a constant for the condition. A group filter condition returns TRUE or FALSE for each row that passes through the transformation, depending on whether a row satisfies the specified condition. Zero (0) is the equivalent of FALSE, and any non-zero value is the equivalent of TRUE. The Integration Service passes the rows of data that evaluate to TRUE to each transformation or target that is associated with each user-defined group.
For example, you have customers from nine countries, and you want to perform different calculations on the data from only three countries. You might want to use a Router transformation in a mapping to filter this data to three different Expression transformations.
There is no group filter condition associated with the default group. However, you can create an Expression transformation to perform a calculation based on the data from the other six countries.
The following figure shows a mapping with a Router transformation that filters data based on multiple conditions:
The mapping contains a source, a SQL transformation, a Router transformation, four user-defined groups, and four targets. The Router transformation filters the data from the user-defined groups and passes the data to the targets.
Since you want to perform multiple calculations based on the data from three different countries, create three user-defined groups and specify three group filter conditions on the Groups tab.
The following table shows group filter conditions that filter customer data:
Group Name
Group Filter Condition
France
customer_name=‘France’
Japan
customer_name=‘Japan’
USA
customer_name=‘USA’
In the session, the Integration Service passes the rows of data that evaluate to TRUE to each transformation or target that is associated with each user-defined group, such as Japan, France, and USA. The Integration Service passes the row to the default group if
all
of the conditions evaluate to FALSE. If this happens, the Integration Service passes the data of the other six countries to the transformation or target that is associated with the default group. If you want the Integration Service to drop all rows in the default group, do not connect it to a transformation or a target in a mapping.
The Router transformation passes data through each group that meets the condition. So, if data meets three output group conditions, the Router transformation passes the data through three output groups.
For example, you configure the following group conditions in a Router transformation:
Group Name
Group Filter Condition
Output Group 1
employee_salary > 1000
Output Group 2
employee_salary > 2000
When the Router transformation processes an input row data with employee_salary=3000, it routes the data through output groups 1 and 2.

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