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  • Informatica Data Quality 10.4.0
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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

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Dynamic Lookup Cache Overview

Dynamic Lookup Cache Overview

Use a dynamic lookup cache to keep the cache synchronized with the target.
You can use a dynamic cache with a relational lookup or flat file lookup.
The Integration Service builds the dynamic lookup cache when it processes the first lookup request. It queries the cache based on the lookup condition for each row that passes into the transformation. The Integration Service updates the lookup cache when it processes each row.
Based on the results of the lookup query, the row type, and the Lookup transformation properties, the Integration Service performs one of the following actions on the dynamic lookup cache when it reads a row from the source:
Inserts the row into the cache
The Integration Service inserts the row when the row is not in the cache and you configured the Lookup transformation to insert rows into the cache. You can configure the transformation to insert rows into the cache based on input ports or generated sequence IDs. The Integration Service flags the row as insert.
Updates the row in the cache
The Integration Service updates the row when the row exists in the cache and you configured the Lookup transformation to update rows in the cache. The Integration Service updates the row in the cache based on the input ports. The Integration Service flags the row as an update row.
Makes no change to the cache
The Integration Service makes no change when the row exists in the cache and you configured the Lookup transformation to insert new rows only. Or, the row is not in the cache and you specified to update existing rows only. Or, the row is in the cache, but based on the lookup condition, nothing changes. The Integration Service flags the row as unchanged.
Based on the value of the NewLookupRow, you can also configure a Router or Filter transformation with the dynamic Lookup transformation to route insert or update rows to the target table. You can route unchanged rows to another target table or flat file, or you can drop them.
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