Table of Contents

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  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

Rank transformation fields

Rank transformation fields

A Rank transformation inherits incoming fields from the upstream transformation. When you create a Rank transformation,
Data Integration
also creates a RANKINDEX output field.
The Rank transformation uses the following fields:
Incoming fields
Incoming fields appear on the
Incoming Fields
tab. By default, the Rank transformation inherits all incoming fields from the upstream transformation. If you do not need to use all of the incoming fields, you can define field rules to include or exclude certain fields. For more information about field rules, see Field rules.
RANKINDEX
After the Rank transformation identifies all rows that belong to a top or bottom rank, it assigns rank index values.
Data Integration
creates the RANKINDEX field to store the rank index value for each row in a group.
For example, you create a Rank transformation to identify the five retail stores in the company with the highest monthly gross sales. The store with the highest sales receives a rank index of 1. The store with the next highest sales receives a rank index of 2, and so on. If two stores have the same gross sales, they receive the same rank index, and the transformation skips the next rank index.
For example, in the following data set, the Long Beach and Anaheim stores have the same gross sales, so they are assigned the same rank index:
RANKINDEX
STORE
GROSS_SALES
1
Long Beach
100000
1
Anaheim
100000
3
Riverside
90000
4
Chula Vista
80050
When measuring a bottom rank, such as the 10 lowest priced products in the inventory, the Rank transformation assigns a rank index from lowest to highest. Therefore, the least expensive item receives a rank index of 1.
The RANKINDEX is an output field. It appears on the
Incoming Fields
tab of the downstream transformation.

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