Hierarchical Dimension Join Operations via Intermediary Data Structures
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Solution Overview
Problem
Current database systems lack the capability to perform join operations on hierarchical dimensions, limiting the ability to efficiently categorize and aggregate data stored in such dimensions, especially when the query processor does not support these operations.
Innovation Solution
A system that includes a query generator capable of performing join operations on hierarchical dimensions by determining a level in the hierarchy and generating queries to combine data sets based on that level, allowing for the creation of calculated dimensions and aggregating data in an intermediary structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the query processor does not support join operations on hierarchical dimensions, then the database system maintains simplicity and existing architecture integrity, but the capability to efficiently categorize and aggregate hierarchical data is lost
Solution Approach 1:
The patent introduces an intermediary component (query generator or preprocessing module) that translates hierarchical dimension join requests into standard join operations. This intermediary handles the complexity of hierarchical relationships without requiring modifications to the core query processor, thus maintaining system simplicity while enabling advanced functionality.
Solution Approach 2:
The patent segments the query processing functionality by separating hierarchical dimension handling from the main query processor. The hierarchical dimension operations are extracted into a distinct module or layer, allowing the core query processor to remain unchanged and simple while the segmented component provides enhanced join operation capabilities.
2Ease of manufacture
If join operations on hierarchical dimensions are implemented without modifying existing databases or query processors, then system compatibility and ease of deployment are improved, but the complexity of implementing join operations on hierarchical data structures increases
Solution Approach 1:
The patent applies preliminary action by pre-processing hierarchical dimension data into a format suitable for standard join operations. This preprocessing step converts hierarchical relationships into flat structures or intermediate representations that can be joined using conventional methods, thereby avoiding modifications to existing systems while managing implementation complexity through advance preparation.
Solution Approach 2:
The patent creates copies or representations of hierarchical dimension data in a format compatible with standard join operations. By copying hierarchical data into an intermediary structure that preserves relationships but allows conventional joining, the system achieves compatibility with existing query processors without requiring complex modifications to the original hierarchical storage structure.
3Adaptability or versatility
If data is aggregated in an intermediary structure rather than directly in the database, then query flexibility and data visualization capabilities are enhanced, but the time and computational resources required for data processing increase
Solution Approach 1:
The patent uses preliminary action by pre-aggregating hierarchical dimension data into an intermediary structure before query execution. This pre-computation stores aggregated results in advance, allowing queries to retrieve pre-processed data rather than performing complex aggregations in real-time, thus reducing query processing time while maintaining flexibility through the structured intermediary representation.
Data Source
AI summary
Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives from a client device a request for data stored in a database categorized based on a hierarchical dimension. The hierarchical dimension is configured to store values from a plurality of values organized in a hierarchy comprising a plurality of levels. The program further generates an intermediary data structure by combining a first set of the data stored in the database and a second set of data based on a level in the hierarchy. The program also generates results for the request by aggregating the data in the intermediary data structure based on the level in the hierarchy. The program further provides the results for the request to the client device.