Table of Contents

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

Transformations

Transformations

Rank caches

Rank caches

When you run a mapping that contains a Rank transformation,
Data Integration
creates data and index cache files to run the transformation. By default,
Data Integration
stores the cache files in the directory entered in the Secure Agent $PMCacheDir property for the Data Integration Server.
You can change the cache directory and cache sizes on the
Advanced
tab of the Rank transformation.
Data Integration
creates the following caches for the Rank transformation:
  • Data cache that stores row data based on the group by fields.
  • Index cache that stores group values as configured in the group by fields.
When you run a mapping that contains a Rank transformation,
Data Integration
compares an input row with rows in the data cache. If the input row out-ranks a cached row,
Data Integration
replaces the cached row with the input row. If you configure the Rank transformation to rank across multiple groups,
Data Integration
ranks incrementally for each group that it finds.
If you create multiple partitions in the Source transformation,
Data Integration
creates separate caches for each partition.

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