Dynamic Query Compilation Using Query Property-Based Rule Skipping
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Solution Overview
Problem
Executing queries over large amounts of data can involve long processing times, and conventional query optimization methods can sometimes increase processing time by performing unnecessary optimization steps.
Innovation Solution
Implement dynamic query compilation techniques that identify and skip or modify stages and rewrite rules based on query properties, such as parse tree and query plan, to reduce compilation time and computational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional query optimization methods are applied, then query processing completeness is improved, but query compilation time increases due to unnecessary optimization steps
Solution Approach 1:
The patent implements dynamic query compilation that adapts the optimization process based on query properties. The system analyzes query characteristics and dynamically determines which optimization stages to apply, transforming the static conventional approach into a flexible dynamic system that adjusts compilation depth according to specific query needs, thereby reducing unnecessary optimization steps while maintaining processing completeness
Solution Approach 2:
The patent changes the parameters of the compilation process by introducing query property-based decision-making. It monitors query characteristics and adjusts compilation parameters dynamically, selecting appropriate optimization stages based on query properties. This parameter change approach allows the system to reduce compilation time by skipping unnecessary optimization stages while maintaining query processing quality
2Productivity
If comprehensive optimization stages are performed, then query execution efficiency is improved, but computational costs increase
Solution Approach 1:
The patent applies partial action by performing only the necessary optimization stages required for each specific query rather than executing all optimization stages universally. The system identifies query properties and applies optimization partiality, performing only the subset of optimization stages that will actually benefit the given query, thereby reducing computational costs while maintaining execution efficiency
Solution Approach 2:
The patent segments the optimization process into distinct stages and selectively applies only those stages relevant to the specific query properties. By dividing the comprehensive optimization process into separable stages and choosing which stages to execute based on query characteristics, the system reduces unnecessary computational overhead while preserving the efficiency benefits of appropriate optimization
Data Source
AI summary
Techniques for reducing query compilation time are described. Dynamic compilation behavior based on query properties can reduce time and computational costs. For example, the techniques can identify stages and rewrite rules to skip or modify in the compilation process based on, among other things, properties of the parse tree and the query plan.