Router Transformation Examples
You might use a Router transformation in one of the following ways:
- •Group inventory items by different price categories and route each group to different target tables based on conditions that test for low, medium, and high prices.
- •Group data by different country attributes and route each group to different target tables based on conditions that test for the continent.
For example, your source includes data for customers in different regions. You want to configure a marketing campaign with variants for customers in the North America, Asia Pacific, and EMEA regions. All other customers see the default ad campaign. In this case, you can use a Router transformation to apply the conditions and filter the data to four different Target transformations.
The following figure shows a mapping with a Router transformation that filters data based on these conditions:
You create two output groups and specify two group filter conditions on the Output Groups tab as shown in this table:
Group Name | Group Filter Condition |
|---|
NA | region = ‘NA’ |
EMEA | region = ‘EMEA’ |
APAC | region = ‘APAC’ |
In this case, the default group would include data for all customers who are not in the North America, EMEA, or APAC regions.
Also note that a Router transformation passes data through all output groups that meet the filter condition. In the following example, the conditions test for an employee salary threshold and the filter conditions for the two output groups overlap:
Group Name | Group Filter Condition |
|---|
Group1 | employee_salary > 20000 |
Group2 | employee_salary > 30000 |
When the Router transformation processes an input row data with employee_salary=35000, it routes the data through output groups 1 and 2.
If you want to pass the data through a single output group, define the filter conditions so they do not overlap. For example, change Group1 to employee_salary <= 30000.
