Database Query Result Signatures for Post-Deployment Validation
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Solution Overview
Problem
Existing database systems lack comprehensive validation after deployment, leading to undetected inconsistencies that result in incorrect query results being returned to users, particularly in fast-paced deployment scenarios like cloud-provided services.
Innovation Solution
Implement a database engine that generates signatures for query results using a per-row hash function, storing these signatures in a key-value store for comparison across different versions, and a correctness verifier to detect inconsistencies by matching these signatures, generating reports and performing remediation when mismatches are found.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If validation testing is performed only during development stages, then development time and resource allocation are optimized, but undetected inconsistencies remain in deployed database systems leading to incorrect query results
Solution Approach 1:
The patent creates a copy of the database system with identical structure and data, running parallel validation tests on this copy to detect inconsistencies without affecting the production system. This allows comprehensive post-deployment validation while maintaining system reliability.
Solution Approach 2:
The patent introduces an intermediary validation layer that compares query results from the production database against expected results or alternative query plans. This intermediary mechanism detects inconsistencies without requiring complete system redesign.
2Reliability
If comprehensive validation tests are implemented post-deployment, then inconsistency detection capability is enhanced, but system overhead and processing time increase
Solution Approach 1:
The patent implements partial validation by selecting specific query types or data subsets for post-deployment validation rather than validating all queries comprehensively. This approach enhances inconsistency detection for critical operations while minimizing overall system overhead.
Solution Approach 2:
The patent employs periodic validation testing at scheduled intervals rather than continuous validation, allowing the system to maintain high processing efficiency between validation cycles while still detecting inconsistencies regularly.
3Measurement precision
If multiple validation checks are performed on each query result, then result accuracy is improved, but processing speed and response time deteriorate
Solution Approach 1:
The patent performs preliminary validation checks during query planning and execution preparation stages, identifying potential inconsistencies before full query execution. This approach verifies critical aspects early while allowing fast execution paths for validated query patterns.
Solution Approach 2:
The patent replaces traditional mechanical validation methods with signature-based verification and hashing techniques that compute validation metrics in constant time, substituting complex multi-step verification with efficient mathematical operations.
Data Source
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AI summary
The automatic detection of inconsistencies in a database system is described. A first signature and a second signature are received. The first signature is a signature of a result of a first execution of the query against a database by a first version of database engine program code. The second signature is a signature of a result of a second execution of the query by a second version of the database engine program code. A determination is made of whether the first signature and the second signature match. In response to the first signature and the second signature failing to match, an inconsistency report regarding at least one of the first or second versions of the database engine program code is generated and remediation regarding at least one of the first or second versions of the database engine program code is performed.