Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. Cleanse transformation
  8. Data Masking transformation
  9. Data Services transformation
  10. Deduplicate transformation
  11. Expression transformation
  12. Filter transformation
  13. Hierarchy Builder transformation
  14. Hierarchy Parser transformation
  15. Hierarchy Processor transformation
  16. Input transformation
  17. Java transformation
  18. Java transformation API reference
  19. Joiner transformation
  20. Labeler transformation
  21. Lookup transformation
  22. Machine Learning transformation
  23. Mapplet transformation
  24. Normalizer transformation
  25. Output transformation
  26. Parse transformation
  27. Python transformation
  28. Rank transformation
  29. Router transformation
  30. Rule Specification transformation
  31. Sequence Generator transformation
  32. Sorter transformation
  33. SQL transformation
  34. Structure Parser transformation
  35. Transaction Control transformation
  36. Union transformation
  37. Velocity transformation
  38. Verifier transformation
  39. Web Services transformation

Transformations

Transformations

Static and dynamic lookup comparison

Static and dynamic lookup comparison

You might want to use dynamic cache instead of a static cache if the source might contain duplicate private keys. Or, you might want to use a dynamic cache when the source contains a large table of data to optimize performance.
Data Integration
processes lookup conditions differently based on whether you configure the Lookup transformation to use a static or dynamic cache.
The following table compares a Lookup transformation that uses a static cache to a Lookup transformation that uses a dynamic cache:
Static Lookup Cache
Dynamic Lookup Cache
The cache does not change during the task run.
The task inserts or updates rows in the cache as it passes rows to the target.
You can use a flat file, relational database, and other connection types such as Salesforce for lookup.
You cannot use a flat file or Salesforce connection type.
When the lookup condition is true, the task returns a value from the lookup table or cache.
When the condition is not true, the task returns the default value.
When the lookup condition is true, the task either updates the row in the cache and target or leaves the cache unchanged. This indicates that the row is in the cache and target table.
When the lookup condition is not true, the task either inserts the row in the cache and target or leaves the cache unchanged based on the row type. This indicates that the row is not in the cache or target table.

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