Distributed Analytical Database Lineage Checking for Corruption Repair
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Distributed databases face increased failure probability due to the complexity of their components, leading to data corruption that is difficult to detect and mitigate, affecting query results and database availability.
Innovation Solution
A method and system for detecting data inconsistencies in distributed databases by analyzing lineage events across components, identifying corruption, its cause, and propagation, and enabling automatic repair when possible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed database systems use multiple interconnected components for elasticity and scalability, then productivity and scalability are improved, but reliability deteriorates due to increased failure probability
Solution Approach 1:
The patent implements a feedback mechanism by continuously monitoring lineage events from multiple distributed components and analyzing them to detect data inconsistencies. The consistency checking engine receives feedback from various database operations (inserts, updates, deletes, merges) and automatically identifies when data corruption occurs, enabling the system to maintain reliability despite the complexity of distributed architecture.
Solution Approach 2:
The patent introduces a consistency checking engine as an intermediary component that mediates between the distributed database components and the data integrity requirements. This engine collects lineage events from various components, analyzes them for consistency, and detects corruption without requiring changes to the core distributed database architecture, thus maintaining both scalability and reliability.
2Reliability
If distributed database systems increase coordination among components for consistency, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the consistency checking function into discrete, manageable components. The system divides data into lineage events from different operations (inserts, updates, deletes, merges) and processes them through modular consistency rules. Each rule handles specific operation types independently, reducing the complexity of coordinating consistency across the entire distributed system while maintaining reliable data integrity checks.
3Reliability
If the system implements comprehensive consistency checking across all components, then reliability is improved, but productivity decreases due to increased coordination overhead
Solution Approach 1:
The patent applies partial action by implementing consistency checking selectively based on operation types. The system uses different consistency rules for different operations (e.g., specific rules for inserts, updates, deletes, and merges) and only applies the necessary level of checking for each operation. This approach provides comprehensive corruption detection where needed while avoiding excessive coordination overhead for operations that require less stringent checking, thus maintaining query performance.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Embodiments described herein are directed to detecting data inconsistencies within a distributed database and identifying the cause thereof. For example, lineage events are emitted from different components of the distributed system that operate on various data files. A consistency checking engine analyzes these events and detects inconsistencies with respect to the data files. The embodiments described herein checks the integrity of the database and assists in understanding the root cause in case of a corruption. Moreover, it provides the timeline for the corruption and whether it is repairable or not. These properties enable determining the right time to restore the customer's database or the right set of actions to repair the corruption. In case of repairable corruption, the correct compensating repair actions may be applied.