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. 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

Rank transformation

Rank transformation

The Rank transformation selects the top or bottom range of data. Use the Rank transformation to return the largest or smallest numeric values in a group. You can also use the Rank transformation to return strings at the top or bottom of the mapping sort order.
For example, you can use a Rank transformation to select the top 10 customers by region. Or, you might identify the three departments with the lowest expenses in salaries and overhead.
The Rank transformation differs from the transformation functions MAX and MIN because the Rank transformation returns a group of values, not just one value. While the SQL language provides many functions designed to handle groups of data, identifying top or bottom strata within a set of rows is not possible using standard SQL functions.
The Rank transformation is an active transformation because it can change the number of rows that pass through it. For example, you configure the transformation to select the top 10 rows from a source that contains 100 rows. In this case, 100 rows pass into the transformation but only 10 rows pass from the Rank transformation to the downstream transformation or target.
When you run a mapping that contains a Rank transformation,
Data Integration
caches input data until it can perform the rank calculations.
To use the Rank transformation, you need the appropriate license.