Graphical Database Query Modeling for Performance Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Database query languages are underutilized due to developers' lack of awareness of their features, fear of modifying existing code, and complexity, leading to inefficient queries and poor performance in database-intense applications.
Innovation Solution
A graphical modeling platform that generates and presents graphical models of database query statements, allowing developers to visualize and optimize queries, identify errors, and provide suggestions for improvement, while integrating seamlessly with existing source code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If developers use complex database query language features, then query optimization and performance improve, but code complexity and difficulty of modification increase
Solution Approach 1:
The patent segments the database query language into distinct graphical components (tables, columns, joins, filters, aggregations) that can be independently visualized and manipulated. This segmentation allows developers to understand and optimize complex queries by breaking them down into manageable visual elements, reducing the perceived complexity while maintaining optimization capability.
Solution Approach 2:
The patent transitions from one-dimensional text-based query representation to two-dimensional graphical visualization, adding a spatial dimension to query understanding. This dimensional change enables developers to perceive query structure, data relationships, and optimization opportunities more intuitively, balancing complexity with optimization capability.
2Productivity
If developers modify existing query code to utilize language features, then query efficiency improves, but risk of destabilizing running code increases
Solution Approach 1:
The patent creates a graphical copy or model of the existing query statement that can be analyzed and optimized without directly modifying the original code. Developers can experiment with optimizations in the graphical representation, validate changes, and only apply proven improvements to the actual query code, reducing the risk of destabilizing running systems.
Solution Approach 2:
The patent enables preliminary analysis and optimization planning through graphical visualization before actual code modification. Developers can identify optimization opportunities, understand query execution plans, and prepare optimization strategies in advance, ensuring that modifications are well-planned and less likely to cause instability.
3Ease of operation
If developers simplify query code, then ease of understanding improves, but query performance deteriorates
Solution Approach 1:
The patent applies local quality by providing detailed graphical representations for specific query components that need optimization while maintaining overall query simplicity. The visualization highlights only the relevant parts of complex queries (such as inefficient joins or missing indexes) without requiring developers to understand the entire query structure in depth, thus maintaining ease of operation while improving performance.
Data Source
AI summary
Example embodiments involve a system, computer-readable storage medium storing at least one program, and computer-implemented method for graphical modeling and editing of database query statements. The method may include accessing a database query statement, and generating an abstract syntax tree (AST) representing a syntactic structure of the database query statement. The method may further include generating a graphical model of the database query statement based on the AST, and rendering the graphical model.