Multidimensional Cube Viewer Incremental Update
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Solution Overview
Problem
Current OLAP systems experience performance degradation due to frequent queries and re-rendering of data when users interact with cube views, leading to increased burden on multidimensional database servers and poor user experience, especially in network environments.
Innovation Solution
A novel multidimensional data storage (MDDS) cube viewer that separates cube data and presentation data, using intelligent caching and querying to efficiently update and render views by identifying changes and retrieving only necessary data, thereby reducing redundant queries and improving rendering efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system retrieves and re-renders complete cube data each time a user requests additional data, then the cube database can provide accurate and complete data, but the multidimensional database server burden increases and performance deteriorates
Solution Approach 1:
The patent segments the cube data into multiple partitions and implements incremental retrieval, where only the required partition is fetched based on the user's specific request. This avoids retrieving the entire cube data set, thereby reducing server burden while maintaining data accuracy for the requested portion.
Solution Approach 2:
The system pre-processes and stores cube data in a partitioned structure that enables efficient incremental retrieval. By organizing data beforehand into manageable partitions with appropriate indexing, the system can quickly retrieve only the necessary data without performing complete data retrieval and re-rendering operations.
2Reliability
If the system performs frequent queries and complete re-rendering of cube data, then the displayed data remains up-to-date, but the user experience deteriorates due to slow response times
Solution Approach 1:
The system performs partial data retrieval by fetching only the specific partition needed for the current view rather than the entire cube data. This partial action maintains data freshness for the displayed information while significantly reducing the time required for data retrieval and rendering operations.
Solution Approach 2:
The patent implements local quality by optimizing the data retrieval process for the specific region or partition being viewed. The system adjusts its query strategy to retrieve data with appropriate granularity for the current view requirements, avoiding unnecessary data transfer and processing time.
3Quantity of substance
If the system downloads large sets of cube data repeatedly in network environments, then complete data is available for analysis, but network bandwidth is wasted and performance suffers
Solution Approach 1:
The system extracts and retrieves only the necessary partition of cube data required for the current analysis view, rather than downloading the complete data set. This extraction approach maintains data completeness for the requested information while minimizing network bandwidth consumption by excluding unnecessary data transfers.
Solution Approach 2:
The cube data is pre-partitioned and organized on the server side with metadata that enables efficient identification and retrieval of specific partitions. This preliminary organization allows the system to request only the necessary data portions over the network, reducing bandwidth waste while ensuring complete data availability for the current analytical needs.
Data Source
AI summary
Some embodiments provide a method for updating a cube view relating to a cube stored in a cube data storage. The method displays the cube view by rendering a first cube data set relating to a first set of entities associated with the cube. The method receives a user interaction with the cube view that identifies a second set of entities associated with the cube. The method renders a second cube data set related to the second set of entities. The method then uses results of the rendering of the second cube data set to modify only a first part of the cube view while maintaining a second part of the cube view that is based on the rendering of the first cube data set.