Query Analysis Server Optimizes Database Resource Utilization
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Solution Overview
Problem
Database queries often inefficiently consume computing resources due to user-generated queries with high execution runtimes or errors, leading to non-optimal resource utilization and long wait times for end users.
Innovation Solution
A query analysis server intercepts and analyzes database queries using prediction models to predict success or failure, preventing execution of queries predicted to fail and providing recommendations for modifying queries to improve resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If database servers process multiple queries concurrently, then query processing speed improves, but computing resource consumption increases
Solution Approach 1:
The system performs preliminary analysis of queries before execution using prediction models to forecast resource consumption and execution success. This preliminary action allows the system to identify and prevent resource-intensive failing queries before they consume database server resources, thereby enabling safer concurrent processing of multiple queries.
2Adaptability or versatility
If users create custom queries with limited expertise, then query flexibility improves, but query execution efficiency deteriorates
Solution Approach 1:
The system implements feedback mechanisms where prediction model results are communicated back to users about their query performance. The system provides recommendations for query optimization based on predicted outcomes, allowing users to improve their query efficiency while maintaining the flexibility to create custom queries according to their specific needs.
3Use of energy by moving object
If database administrators manually monitor and terminate queries, then resource utilization improves, but operational complexity increases
Solution Approach 1:
The system implements self-service automation where prediction models automatically analyze incoming queries, predict their resource consumption and success probability, and make decisions about query execution or termination without human intervention. This replaces manual administrator monitoring with an autonomous system that continuously optimizes resource utilization through automated prediction and decision-making.
4Use of energy by moving object
If queries are processed sequentially in a queue, then computing resource consumption decreases, but wait time increases
Solution Approach 1:
The system performs preliminary prediction analysis in the query queue before execution, identifying queries with high success probability and low resource consumption. These pre-screened queries can be safely executed concurrently or prioritized, reducing wait times while maintaining efficient resource consumption. The preliminary action transforms the sequential queue into a smart filtering mechanism.
Data Source
AI summary
The present disclosure provides various devices, systems, and methods that can improve and/or optimize the computing resource utilization of database servers. For example, according to one aspect, the present disclosure provides a method that includes intercepting queries submitted for execution by a database server and applying a set of object values for each of the queries to a prediction model to predict success or failure of the execution of each of the queries. The method can further include preventing the execution of the queries that are predicted to fail and forwarding the queries that are predicted to succeed to the database server for execution.