Selective Database Recovery Using UNDO REDO Queues
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Solution Overview
Problem
Current database recovery methods are limited in their ability to selectively roll-forward or roll-back data, often requiring entire tables or files to be processed, leading to prolonged downtime and loss of referential integrity, and do not allow for automated detection and correction of corruption.
Innovation Solution
The implementation of UNDO and REDO methods using an enhanced Shadowbase data replication engine, which allows for selective rollback or roll-forward of corrupted data while maintaining referential integrity and enabling the database to remain active during the process, using Undo and Redo Queues to manage and apply changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional database recovery methods are used to restore corrupted data, then the database can be returned to a correct state, but the entire database or large portions must be processed, leading to prolonged downtime and loss of referential integrity
Solution Approach 1:
The patent segments the database recovery process by identifying and isolating only the corrupted data portions that need recovery. Instead of processing the entire database, the system divides the recovery task into specific corrupted segments, allowing other parts of the database to remain accessible and maintaining referential integrity among unaffected data elements.
Solution Approach 2:
The patent applies local quality by treating different portions of the database differently based on their corruption status. Corrupted segments receive recovery processing while uncorrupted segments remain in their current state, allowing the database to maintain partial functionality and referential integrity during the recovery process.
2Reliability
If traditional database recovery methods are used, then corrupted data can be restored, but the database must be taken offline, resulting in loss of availability and increased downtime
Solution Approach 1:
The patent implements a dynamic recovery approach where the database can transition between different operational states. The system allows the database to remain partially online and accessible during recovery operations, dynamically adjusting which portions are available based on their recovery status, thereby maintaining availability while ensuring data integrity.
3Reliability
If manual detection and correction of database corruption are performed, then corruption can be identified and fixed, but the process is time-consuming and requires human intervention, increasing recovery time
Solution Approach 1:
The patent implements self-service by enabling the database system to automatically detect, identify, and correct its own corruption without human intervention. The system autonomously performs integrity checks, identifies corrupted segments, and applies appropriate recovery operations, thereby maintaining high detection accuracy while dramatically improving recovery speed and productivity.
Solution Approach 2:
The patent employs feedback mechanisms where the system continuously monitors database integrity, detects corruption through automated checks, and uses this information to trigger recovery operations. The feedback loop enables rapid automated response to corruption events, improving both detection accuracy and recovery speed by eliminating manual intervention delays.
Data Source
AI summary
A corrupted database is returned to a correct state by rolling forward or backward through a change queue and applying changes to the database in a selective manner. Changes that did not cause the corruption are applied without modification when rolling forward or are skipped when rolling backward. Changes that caused corruption are addressed when rolling forward, such as by being ignored or modified and then applied. Changes that caused corruption are corrected when rolling backward.