Query Request Routing Between Analytical Engines
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Solution Overview
Problem
Conventional business software frameworks face performance issues due to the use of multidimensional models for report generation, leading to increased runtime overhead, memory errors, and reduced speed, especially when advanced analytical capabilities are not required.
Innovation Solution
Implement a method to analyze query requests at runtime and distribute tasks among analytical reporting engines of varying complexity, using full complexity engines only when necessary and reduced complexity engines for simpler tasks, thereby optimizing resource usage and reducing overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a full complexity analytical engine (OLAP engine) is used for all report generation tasks, then advanced multidimensional reporting capabilities are available, but runtime overhead increases substantially and performance decreases
Solution Approach 1:
The patent segments the analytical engine functionality into multiple engines with different complexity levels. A full complexity OLAP engine is divided into distinct functional components that can be selectively deployed. Simpler reporting tasks are handled by lightweight engines without OLAP overhead, while complex multidimensional tasks are routed to the full OLAP engine. This segmentation resolves the contradiction by providing full analytical capabilities only when needed, thereby maintaining high query response speed for simple tasks.
Solution Approach 2:
The patent implements dynamic engine selection based on the complexity of the reporting task. The system analyzes the report definition and user requirements at runtime to determine the appropriate engine complexity level. This dynamic adaptation allows the system to switch between lightweight and full-featured analytical engines, ensuring optimal performance for each specific task while maintaining versatility across different reporting scenarios.
2Adaptability or versatility
If a full complexity analytical engine is used for all tasks, then complete analytical functions are available, but runtime resources are consumed inefficiently
Solution Approach 1:
The patent applies partial action by deploying only the necessary analytical engine capabilities required for each specific task. Instead of always activating the full OLAP engine with all its analytical functions, the system uses lightweight engines for tasks that require only basic reporting capabilities. This partial deployment significantly reduces runtime resource consumption while maintaining complete analytical function availability when needed through the full complexity engine.
3Ease of operation
If OLAP engine is used for simple reporting tasks, then report generation is possible, but substantial runtime overhead occurs due to metadata provisioning, surrogate identifier generation, and deeper call stacks
Solution Approach 1:
The patent extracts the essential report generation functionality from the full OLAP engine and implements it in separate lightweight reporting engines. These extracted components handle basic reporting tasks without the overhead of OLAP-specific features such as complex metadata provisioning, surrogate identifier generation, and deep call stacks. This extraction resolves the contradiction by maintaining report generation capability while eliminating unnecessary runtime overhead for simple tasks.
Data Source
AI summary
Runtime performance of report generation and other response to query requests can be improve using a report analyzer that can parse the query request and distribute the necessary analytical task among two or more analytical engines of varying levels of complexity.