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. Deduplicate transformation
  9. Expression transformation
  10. Filter transformation
  11. Hierarchy Builder transformation
  12. Hierarchy Parser transformation
  13. Hierarchy Processor transformation
  14. Input transformation
  15. Java transformation
  16. Java transformation API reference
  17. Joiner transformation
  18. Labeler transformation
  19. Lookup transformation
  20. Mapplet transformation
  21. Normalizer transformation
  22. Output transformation
  23. Parse transformation
  24. Python transformation
  25. Rank transformation
  26. Router transformation
  27. Rule Specification transformation
  28. Sequence Generator transformation
  29. Sorter transformation
  30. SQL transformation
  31. Structure Parser transformation
  32. Transaction Control transformation
  33. Union transformation
  34. Velocity transformation
  35. Verifier transformation
  36. Web Services transformation

Transformations

Transformations

Router transformation examples

Router transformation examples

You can use a Router transformation to complete the following tasks:
  • Group data by different country attributes and route each group to different target tables based on conditions that test for the region.
  • 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.

Example 1: Route data to different targets by region.

Your source includes data for customers in different regions. You want to configure a marketing campaign with variants for customers in the North America region, the Europe, Middle East, and Africa region, and the Asia Pacific region. All other customers see the default ad campaign. Use a Router transformation to route the data to four different Target transformations.
The following figure shows a mapping with a Router transformation that filters data based on these conditions:
The Router transformation routes customer data to different targets based on region, either NA, EMEA, or APAC. The transformation routes data for other regions to the default target.
Create three output groups and specify the group filter conditions on the
Output Groups
tab as shown in the following table:
Group Name
Condition
NA
region = ‘NA’
EMEA
region = ‘EMEA’
APAC
region = ‘APAC’
The default group includes data for all customers that are not in the NA, EMEA, or APAC region.

Example 2: Route some rows to multiple output groups.

The Router transformation passes data through all output groups that meet the filter condition. In the following example, the conditions test for a price threshold, but the filter conditions for the two output groups overlap:
Group Name
Condition
PriceGroup1
item_price > 100
PriceGroup2
item_price > 500
When the Router transformation processes an input row with item_price=510, it routes the row to both output groups.
If you want to pass the data through a single output group, define the filter conditions so that they do not overlap. For example, you might change the filter condition for PriceGroup1 to item_price <= 500.