Table of Contents

Search

  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings in the Hadoop Environment
  4. Mapping Sources in the Hadoop Environment
  5. Mapping Targets in the Hadoop Environment
  6. Mapping Transformations in the Hadoop Environment
  7. Processing Hierarchical Data on the Spark Engine
  8. Configuring Transformations to Process Hierarchical Data
  9. Processing Unstructured and Semi-structured Data with an Intelligent Structure Model
  10. Stateful Computing on the Spark Engine
  11. Monitoring Mappings in the Hadoop Environment
  12. Mappings in the Native Environment
  13. Profiles
  14. Native Environment Optimization
  15. Cluster Workflows
  16. Connections
  17. Data Type Reference
  18. Function Reference
  19. Parameter Reference

Rank Transformation Support on the Blaze Engine

Rank Transformation Support on the Blaze Engine

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 October 23, 2019