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. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Key Generator Transformation Overview

Key Generator Transformation Overview

The Key Generator transformation is an active transformation that organizes records into groups based on data values in a column that you select. Use this transformation to sort records before passing them to the Match transformation.
The Key Generator transformation uses a grouping strategy to create group keys for the column you select. The strategies are String, Soundex, and NYSIIS. Records with common values in the selected field have a common group key value. The Match transformation processes records with common group key values together. This enables faster duplicate analysis in the Match transformation.
The number of comparison operations that the Match transformation must perform grows exponentially with the number of records in the data set. This exponential growth can consume significant amounts of computing resources. By creating group keys, the Key Generator transformation enables the Match transformation to compare records in smaller groups, which reduces processing time.
When you perform field matching, select a column for group key generation that is likely to provide useful groups for your matching needs. For example, a Surname column is likely to provide more meaningful group key data than a Forename column. But do not use the Surname column if you intend to select that column for duplicate analysis in the Match transformation.
The Key Generator transformation can also create a unique ID for each record. Each record that enters the Match transformation must contain a unique ID. Use the Key Generator transformation to create IDs for your data if none exist.

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