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

Update Strategy Transformation Overview

Update Strategy Transformation Overview

The Update Strategy transformation is an active transformation that flags a row for insert, update, delete, or reject. Use an Update Strategy transformation to control changes to existing rows in a target based on a condition that you apply.
As an active transformation, the Update Strategy transformation might change the number of rows passed through it. The Update Strategy transformation tests each row to see if it meets a particular condition, and then flags the row accordingly. The transformation passes rows that it flags for insert, update, or delete to the next transformation. You can configure the transformation to pass rows flagged for reject to the next transformation or to drop rows flagged for reject.
For example, you might use the Update Strategy transformation to flag all customer rows for update when the mailing address has changed. Or, you might flag all employee rows for reject for people who no longer work for the organization.
You can use an Update Strategy transformation to write results to a relational database target when the mapping runs on the Spark engine. The mapping uses a JDBC connection string.

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