Database Cluster Key Type Assignment for Conflict Detection
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Solution Overview
Problem
Conventional methods for synchronizing data in database clusters often result in excessive false positives due to the detection of conflicts from concurrent modifications of related resources by unrelated transactions, leading to inefficient transaction management.
Innovation Solution
A method that assigns key types (exclusive, semi-exclusive, or shared) to keys referenced by transactions based on their modification actions and dependency relationships, followed by a certification process to identify and resolve conflicts, ensuring accurate synchronization without rolling back non-conflicting transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional synchronization detection methods are used to ensure data consistency, then reliability is improved, but false positives increase leading to reduced productivity
Solution Approach 1:
The patent segments the key set into multiple subsets and assigns different key types (exclusive, semi-exclusive, shared) to different keys based on their modification patterns. This segmentation allows the system to differentiate between conflicting and non-conflicting transactions, reducing false positives while maintaining data consistency for actually conflicting operations.
Solution Approach 2:
The patent applies different key types (exclusive, semi-exclusive, shared) to different keys based on their specific characteristics and usage patterns. This local differentiation enables more precise conflict detection - exclusive keys provide strong consistency where needed, while shared keys allow concurrent access where safe, thereby reducing false positives and improving overall transaction throughput.
2Reliability
If all keys including dependency keys are referenced to detect conflicts, then reliability is improved, but device complexity increases due to excessive false positives
Solution Approach 1:
The patent segments keys into different categories (exclusive, semi-exclusive, shared) based on their modification patterns and dependency relationships. This segmentation allows the system to reference only relevant keys for conflict detection rather than all possible dependency keys, reducing synchronization overhead while maintaining accurate conflict detection for actually conflicting transactions.
Solution Approach 2:
The patent applies different key types to different keys based on their local characteristics - whether they are modified by the current transaction, modified by other transactions, or only depended upon. This local quality approach enables the system to reference only the necessary subset of keys for each transaction, reducing the complexity of synchronization without compromising conflict detection accuracy.
Data Source
AI summary
A method for use in a database cluster is provided. A given transaction is executed at a first given node of the database cluster. The first given node identifies one or more keys referenced by the given transaction. The first given node then assigns a key type to each of the one or more keys referenced by the given transaction. Accordingly, the key type is selected from a group including: exclusive; semi-exclusive; and/or shared.