Smart Cube Caching for Dynamic Report Data Fetching
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Solution Overview
Problem
Current data retrieval methods, such as those used in online analytical processing (OLAP) cubes, are inefficient due to the need to repeatedly process and transmit large datasets, especially when joining static tables, which consumes significant time and resources.
Innovation Solution
Implementing a dynamic fetching process that utilizes smart cubes to cache viscous attributes locally, allowing reports to retrieve only non-viscous attributes from remote databases, thereby reducing the need for extensive table joining and data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static tables are processed and transmitted repeatedly for OLAP cube operations, then complete data processing can be performed, but significant time and resources are consumed
Solution Approach 1:
The patent pre-processes and stores attribute data in a smart cube structure before it is needed for report generation. Viscous attributes are cached in memory, and the smart cube is prepared in advance with all necessary attribute relationships, eliminating the need to join static tables repeatedly during report operations.
Solution Approach 2:
The system creates a buffer layer (smart cube) that cushions the impact of repeated data access by caching viscous attributes in memory. This buffer absorbs the demand for repeated data retrieval, preventing the need to repeatedly access and join static tables from the database.
2Reliability
If large datasets are transmitted repeatedly from remote databases, then complete data can be retrieved, but bandwidth usage and resource requirements increase
Solution Approach 1:
The patent extracts only the necessary viscous attributes from the complete dataset and stores them in the smart cube. During report generation, only the required non-viscous attributes are retrieved from the remote database, while viscous attributes are obtained from the local smart cube, significantly reducing bandwidth usage.
Solution Approach 2:
The system creates a copy of the smart cube structure in memory that contains cached viscous attributes. This copy allows rapid access to frequently used attribute data without repeatedly transmitting the complete dataset from the remote database, reducing network bandwidth consumption.
Data Source
AI summary
Disclosed are methods, systems, and computer-readable medium for providing report results. Viscous attributes and non-viscous may be identified. A smart cube may be received and may include viscous values for the viscous attributes. The smart cube may be stored at a local cache. A report associated with an organization may be initiated. A runtime generation of the report may be generated based on initiating the report. The report may call a viscous attribute from the viscous attributes and call a non-viscous attribute from the non-viscous attributes. The runtime generation may be modified to remove the viscous attribute from the runtime generation. A viscous value for the viscous attribute may be retrieved from the smart cube at the local cache. The modified runtime generation may be executed to retrieve a non-viscous value for the non-viscous attribute from a remote database and a report result may be provided.