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. Deduplicate transformation
  9. Expression transformation
  10. Filter transformation
  11. Hierarchy Builder transformation
  12. Hierarchy Parser transformation
  13. Hierarchy Processor transformation
  14. Input transformation
  15. Java transformation
  16. Java transformation API reference
  17. Joiner transformation
  18. Labeler transformation
  19. Lookup transformation
  20. Mapplet transformation
  21. Normalizer transformation
  22. Output transformation
  23. Parse transformation
  24. Python transformation
  25. Rank transformation
  26. Router transformation
  27. Rule Specification transformation
  28. Sequence Generator transformation
  29. Sorter transformation
  30. SQL transformation
  31. Structure Parser transformation
  32. Transaction Control transformation
  33. Union transformation
  34. Velocity transformation
  35. Verifier transformation
  36. 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.