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This release includes the following non-Spark enhancements:
Support for processing semantic models containing one or more advanced hierarchies
Intelligent selection of the mechanism for dataset validation and preview (JDBC or Spark)
Support for a high number of columns in the semantic model
Support for processing semantic models in Single Node Installer deployments
Support for pushing the SQL-based expressions filters on dimension columns to MDX
Support for the latest Kubernetes version across all Clouds (AWS: EKS, Azure: AKS, GCP: GKE)
Support of Shared Query Engine based deployment in Azure and AWS Marketplace
Support for primary key validation in semantic model processing is available. Users can enable the inclusion of erroneous data in error messages and system logs by setting the kyvos.publish.error.data property to true. By default, this property is set to false.
Pruning support is available for advanced filtering scenarios, enhancing query performance optimization. To enable advanced pruning, set the kyvos.query.enable.advancedPruning property to true. By default, this property is set to false.
Support for pushing SQL expression filters on dimension columns to the MDX engine. Previously, filters based on SQL expressions could not be pushed to the Query Engine (QE) via the MDX flow. With this release, Kyvos now enables pushing such filters to the MDX engine.
Support for reading cuboids from HDFC (on-premises cluster) with LRU cache.
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