Runtime Framework for Multidimensional Analytical Metadata
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Solution Overview
Problem
Existing OLAP systems face challenges in efficiently executing multidimensional analytical metadata due to the need for determining appropriate execution environments and handling various calculation patterns, which can lead to inefficiencies in data processing and execution.
Innovation Solution
A runtime framework is generated by analyzing multidimensional analytical metadata to determine calculation patterns, identifying executable conditions, and executing subsets in either an in-memory computing engine or application server based on these conditions, ensuring optimal execution environments for different data operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single execution engine is used for all multidimensional analytical metadata, then system complexity is reduced, but execution efficiency and adaptability to different calculation patterns deteriorate
Solution Approach 1:
The system dynamically selects execution engines based on calculation patterns rather than using a static single engine. The runtime framework analyzes metadata to determine the appropriate execution engine (in-memory computing engine for calculation scenario executable subsets, application server for inexecutable subsets), allowing the system to adapt its execution strategy to different data operations and improve processing efficiency while maintaining manageable complexity through automated decision-making
Solution Approach 2:
The execution system is segmented into multiple specialized execution engines (in-memory computing engine and application server) that handle different types of calculation patterns. The runtime framework divides multidimensional analytical metadata into executable and inexecutable subsets based on calculation scenarios, routing each subset to the most appropriate engine, thereby improving overall system productivity without requiring users to manage the complexity directly
2Productivity
If execution environment determination is automated through runtime framework, then execution efficiency improves, but system complexity and overhead increase
Solution Approach 1:
The runtime framework performs self-service by automatically analyzing multidimensional analytical metadata and determining the appropriate execution environment without requiring manual intervention. The system autonomously identifies calculation patterns, classifies subsets as executable or inexecutable, and routes them to appropriate engines, thereby improving execution efficiency while managing framework complexity through automated self-determination rather than external configuration
Solution Approach 2:
The runtime framework incorporates feedback mechanisms where the analysis of calculation patterns and execution results informs future execution decisions. The system learns from the determination of executable versus inexecutable subsets and optimizes routing decisions, improving execution efficiency over time while the feedback loop manages complexity by using observed performance data rather than requiring pre-configured complex rules
Data Source
AI summary
In an embodiment, the runtime framework is responsible for executing multidimensional analytical metadata in a runtime environment that is determined by the runtime framework. To generate such a runtime framework, the received multidimensional analytical metadata is analyzed to determine a type of an associated calculation pattern. Based upon the type, subsets of the multidimensional analytical metadata and corresponding runtime decision rules are determined. To execute the subsets, executable conditions corresponding to the multidimensional analytical metadata are identified. Based upon the executable conditions, the calculation pattern associated with the multidimensional analytical metadata is executed by executing the associated subsets, and the runtime framework is generated. The runtime framework determines calculation scenario executable subsets and calculation scenario inexecutable subsets that are associated with the multidimensional analytical metadata, and executes the subsets in their respective engines.