Table of Contents

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  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Macro Transformation
  30. Match Transformation
  31. Match Transformations in Field Analysis
  32. Match Transformations in Identity Analysis
  33. Normalizer Transformation
  34. Merge Transformation
  35. Parser Transformation
  36. Python Transformation
  37. Rank Transformation
  38. Read Transformation
  39. Relational to Hierarchical Transformation
  40. REST Web Service Consumer Transformation
  41. Router Transformation
  42. Sequence Generator Transformation
  43. Sorter Transformation
  44. SQL Transformation
  45. Standardizer Transformation
  46. Union Transformation
  47. Update Strategy Transformation
  48. Web Service Consumer Transformation
  49. Parsing Web Service SOAP Messages
  50. Generating Web Service SOAP Messages
  51. Weighted Average Transformation
  52. Window Transformation
  53. Write Transformation
  54. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Rank Transformation Overview

Rank Transformation Overview

The Rank transformation is an active transformation that limits records to a top or bottom range. Use a Rank transformation to return the largest or smallest numeric value in a port or group. Or use a Rank transformation to return the strings at the top or the bottom of a mapping sort order.
During a mapping run, the Data Integration Service caches input data until it can perform the rank calculations.
The Rank transformation differs from the transformation functions MAX and MIN. The Rank transformation returns a group of top or bottom values, not just one value. For example, use a Rank transformation to select the top 10 salespersons in a given territory. Or, to generate a financial report, you might use a Rank transformation to identify the three departments with the lowest expenses in salaries and overhead. 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.
You connect all ports representing the same row set to the transformation. The rows that fall within that rank, based on some measure you set when you configure the transformation, pass through the Rank transformation.
As an active transformation, the Rank transformation might change the number of rows passed through it. You might pass 100 rows to the Rank transformation, but select to rank only the top 10 rows. The top 10 rows pass from the Rank transformation to another transformation.
You can connect ports from one transformation to the Rank transformation. You can also create local variables and write non-aggregate expressions.

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