DaSL Compiler for Mobile Data Visualization
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Solution Overview
Problem
Existing methods for visualizing large data sets on mobile devices are limited by display resolution, pixel count, and network bandwidth, leading to uninterpretable data points and requiring complex, resource-intensive SQL queries that are sensitive to database schema changes.
Innovation Solution
The use of a Business Intelligence Data Specification Language (DaSL) for efficient extreme visualization, which involves extracting an input schema, generating a DaSL query, and compiling it into a calculation plan and topology cursors to process data in an in-memory database, reducing resource usage and enabling real-time processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional SQL queries are used for data aggregation, then data processing can be performed, but the query complexity and resource consumption increase significantly
Solution Approach 1:
The patent transforms complex SQL queries into a specialized domain-specific language (DaSL) with simplified syntax and semantics optimized for data aggregation and extreme visualization. This language parameter change reduces query complexity while maintaining processing capability, allowing users to express complex data aggregation operations with simpler, more intuitive constructs that are automatically optimized by the system.
Solution Approach 2:
The patent introduces an intermediary DaSL layer between the user and the database system. This intermediary language serves as a mediator that translates high-level visualization requirements into optimized database operations, reducing the complexity burden on users while maintaining efficient data processing through automatic query optimization and execution planning.
2Reliability
If complex SQL queries are used for data aggregation, then data processing capability is maintained, but sensitivity to database schema changes increases
Solution Approach 1:
The DaSL is designed with abstracted parameters and operations that are decoupled from specific database schema structures. This parameter abstraction allows queries to remain stable and robust even when underlying database schemas change, as the DaSL layer provides a stable interface that insulates users from schema volatility while maintaining reliable data processing.
Solution Approach 2:
The DaSL is designed as a universal language that can work with multiple database schemas and structures. This universality makes the language robust to schema changes, as it provides consistent semantics and operations across different data organization patterns, reducing sensitivity to specific schema implementations while maintaining reliable query execution.
3Quantity of substance
If data aggregation is performed for extreme visualization, then data points can be reduced for display, but processing time increases without real-time capability
Solution Approach 1:
The system performs preliminary actions by pre-computing aggregation results and caching them in optimized data structures. This preliminary processing reduces the time required for real-time visualization queries, as the heavy aggregation work is done in advance and can be quickly retrieved or incrementally updated when data changes, enabling real-time interactive visualization.
Solution Approach 2:
The DaSL enables efficient data aggregation by changing the processing parameters through specialized operators and execution plans optimized for visualization workloads. These parameter optimizations include efficient binning operations, aggregation strategies, and memory management that reduce processing time while achieving the necessary data reduction for extreme visualization on mobile devices.
4Loss of information
If large data sets are transferred to mobile devices for visualization, then complete data can be displayed, but network bandwidth acts as a bottleneck
Solution Approach 1:
The system extracts and transfers only the essential aggregated results needed for visualization to the mobile device, rather than transferring complete large datasets. This extraction principle reduces network bandwidth consumption and energy usage by mobile devices, while still providing sufficient data for meaningful extreme visualization through techniques like sampling, aggregation, and selective data transfer.
Data Source
AI summary
The present disclosure describes methods, systems, and computer program products for enabling extreme visualization for large data sets stored in a database. One computer-implemented method includes receiving a request for an input schema to feed to a data specification language (DaSL) and a metadata outline of typed objects exposed by a database view identified in the request, requesting extraction of the input schema and metadata outline from the database, creating an instance of a DaSL compiler based upon the input schema, generating, by a computer, a DaSL query corresponding to objects selected from the metadata outline, requesting compilation of the DaSL query, and receiving a calculation plan and topology cursors responsive to the compilation of the DaSL query.