Automated Query Retry System for Database Reliability
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Solution Overview
Problem
Traditional database management systems are costly, resource-intensive, and susceptible to data loss during power outages or disasters, and they struggle with query execution failures due to intermittent faults and software regressions.
Innovation Solution
The implementation of automated query retry systems in database platforms that analyze query failures to distinguish between intermittent faults and software regressions, allowing for targeted retry attempts on different software versions and execution nodes to identify and resolve issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional database management systems are used, then data storage and access capabilities are provided, but the systems are costly, resource-intensive, and susceptible to data loss during power outages or disasters
Solution Approach 1:
The patent introduces an automated query retry system that acts as an intermediary between the query execution system and failure conditions. When a query fails due to intermittent faults, the retry system automatically re-executes the query without requiring complex infrastructure changes or manual intervention, thereby preventing data loss while maintaining system simplicity
Solution Approach 2:
The system performs preliminary classification of query failures into intermittent faults versus software regressions before retrying. By analyzing failure patterns in advance and only retrying queries classified as intermittent faults, the system prevents unnecessary retries that could worsen software regression issues while still protecting against data loss from transient failures
2Reliability
If automated query retry is implemented, then query reliability is enhanced, but the system must distinguish between intermittent faults and software regressions
Solution Approach 1:
The patent segments the failure analysis process into distinct components: failure detection, failure classification (intermittent fault vs. software regression), and conditional retry decision-making. This segmentation allows the system to handle each aspect separately, making the overall complex task of distinguishing failure types more manageable through modular analysis
3Reliability
If queries are retried on different software versions and execution nodes, then system errors are identified, but the complexity of managing multiple versions and nodes increases
Solution Approach 1:
The system changes parameters such as software version and execution node when retrying queries, but only after classifying the failure as potentially retryable. This parameter variation allows the system to identify whether failures are due to specific version bugs or node issues, improving error identification accuracy while managing complexity through conditional parameter changes rather than universal multi-version deployment
Data Source
AI summary
Disclosed herein are embodiments of systems and methods for query-attempt processing in a database environment. In an embodiment, a database platform receives a query, and operates a first query manager of the database platform to manage a first attempt to execute the query. Based on determining that the attempt to execute the query was unsuccessful, the database platform identifies a second query manager of the database platform as implementing a same version of the database platform as the first query manager, and operates the second query manager to manage a first retry attempt to execute the query.