Table of Contents

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  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Rank Transformation on the Blaze Engine

Rank Transformation on the Blaze Engine

Some processing rules for the Blaze engine differ from the processing rules for the Data Integration Service.
The data cache for the Rank transformation is optimized to use variable length to store binary and string data types that pass through the Rank transformation. The optimization is enabled for record sizes up to 8 MB. If the record size is greater than 8 MB, variable length optimization is disabled.
When variable length is used to store data that passes through the Rank transformation in the data cache, the Rank transformation is optimized to use sorted input and a pass-through Sorter transformation is inserted before the Rank transformation in the run-time mapping. To view the Sorter transformation, view the optimized mapping or view the execution plan in the Blaze validation environment.
During data cache optimization, the data cache and the index cache for the Rank transformation are set to Auto. The sorter cache for the Sorter transformation is set to the same size as the data cache for the Rank transformation. To configure the sorter cache, you must configure the size of the data cache for the Rank transformation.


Updated September 28, 2020