Data Structure Maintenance via Segmented Locking and Threshold-Based Error Detection
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Solution Overview
Problem
Traditional data structure maintenance techniques face challenges such as locking entire structures during changes, complex operations impacting performance, and error identification methods affecting system performance, especially in multi-tenant databases.
Innovation Solution
Implementing methods to block parallel operations on specific portions of a data structure during maintenance, recalculating derived data structures after updates, and identifying errors only when system resource utilization is below a threshold to enhance efficiency and functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire data structure is locked while a change is being made to preserve data integrity, then data integrity is maintained, but system performance and availability are reduced
Solution Approach 1:
The patent applies segmentation by dividing the data structure into multiple portions or segments. Instead of locking the entire data structure during changes, the system identifies and locks only the specific portion being modified. This allows other portions of the data structure to remain accessible and operable concurrently, thereby maintaining data integrity for the modified portion while preserving overall system performance.
Solution Approach 2:
The patent implements local quality by applying different access control characteristics to different portions of the data structure. When a change is made to a specific portion, only that portion is locked with exclusive access, while other portions maintain their normal read-access characteristics. This localized approach ensures data integrity for the modified section without degrading system-wide performance.
2Adaptability or versatility
If complex changes are made to the data structure to improve functionality, then data maintenance capability is enhanced, but operation time and system response are increased
Solution Approach 1:
The patent applies preliminary action by pre-identifying the specific portion of the data structure that will be modified before executing the change operation. The system determines in advance which portion needs to be locked and which can remain accessible, allowing complex changes to be executed efficiently without unnecessary delays from locking entire structures or performing redundant validation operations.
3Measurement precision
If error identification methods are applied to validate data changes, then data accuracy is improved, but system performance is negatively impacted
Solution Approach 1:
The patent implements local quality in error identification by validating only the specific portion of the data structure that is being modified, rather than validating the entire data structure. The system identifies errors within the context of the modified portion only, which significantly reduces the computational overhead and time required for validation while maintaining adequate data accuracy for the changes being made.
Data Source
AI summary
There are provided mechanisms and methods for maintaining data stored in a data structure. These mechanisms and methods for maintaining data stored in a data structure can provide maintenance operations with improved efficiency, functionality, etc.