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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. 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

Back Next

Cache Partitioning for Lookups

Cache Partitioning for Lookups

Cache partitioning creates a separate cache for each partition that processes an Aggregator, Joiner, Rank, or Lookup transformation. Cache partitioning increases mapping performance because each partition queries a separate cache in parallel.
When the Integration Service creates partitions for a mapping, it might use cache partitioning for partitioned Lookup transformations.
The Integration Service uses cache partitioning for connected Lookup transformations when the following conditions are true:
  • The lookup condition contains only equality operators.
  • When the connected Lookup transformation looks up data in a relational table, and the database is configured for case-sensitive comparison.
The Integration Service does not use cache partitioning for unconnected Lookup transformations.
When the Integration Service does not use cache partitioning for a Lookup transformation, all partitions of the Lookup transformation share the same cache. Each partition queries the same cache serially.
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