Database Validation Module for SQL Resource Control
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Solution Overview
Problem
Relational databases face challenges in efficiently managing and validating SQL instructions to prevent resource overutilization, leading to performance issues and potential unauthorized access.
Innovation Solution
A database system with a validation module that includes parser-based and plan validators to analyze SQL instructions, checking for resource-intensive operations and inconsistencies, and generates validation indications to prevent performance issues and unauthorized access by filtering instructions before they reach the database engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If access limitations are implemented to prevent resource overutilization, then database system resource usage is controlled, but the complexity of the system increases and legitimate access may be hindered
Solution Approach 1:
The validation module performs preliminary analysis of SQL instructions before they are executed by the database engine. By checking for resource-intensive operations and potential security issues in advance, the system can prevent harmful queries without requiring complex runtime controls or access limitations.
Solution Approach 2:
The validation module acts as an intermediary component between the SQL interface and the database engine. It receives SQL instructions, validates them against security and performance criteria, and either allows or blocks execution. This mediator approach provides fine-grained control without requiring broad access limitations that would increase system complexity.
2Reliability
If comprehensive validation of SQL instructions is performed, then security and performance are improved, but processing time increases
Solution Approach 1:
The validation module performs partial validation by focusing only on specific high-risk patterns and resource-intensive operations rather than analyzing every aspect of each SQL instruction. This selective approach provides sufficient security and performance protection while minimizing the time overhead associated with comprehensive validation.
Solution Approach 2:
The system changes the parameter of validation depth by adjusting which types of SQL operations are validated based on risk levels. Common, low-risk operations receive minimal validation, while suspicious or resource-intensive operations undergo more thorough analysis, optimizing the balance between security and processing time.
Data Source
AI summary
In an example, a database system may be configured to validate relational database instructions using a plurality of validators. In some examples, validation may be pre-production for relational database instructions based on simulated user inputs and/or file, such as plan files (e.g., PL/SQL (procedural language/structured query language) files). In some examples, validation may be in production for relational database instructions based on system views of a database engine.


