Inode Recovery via Extension Table Validation
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Solution Overview
Problem
Data loss in storage products due to missing metadata, such as inodes, leads to interruptions in data read/write paths and potential loss of volume-level data, as existing solutions often result in deletion of associated data, causing unexpected data loss.
Innovation Solution
A method for data recovery that determines if a missing inode is recoverable by comparing it with the inode table and extension table, acquires associated data, and reconstructs the inode to maintain data consistency and prevent volume loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing solutions delete associated data when metadata is missing, then data consistency is maintained, but data loss occurs
Solution Approach 1:
The patent performs preliminary validation of the inode table before deleting associated data. By checking whether the inode truly exists or is merely missing, the system可以避免 deleting data that could be recovered, thus preventing unnecessary data loss while maintaining consistency
Solution Approach 2:
The patent converts the potentially harmful action of deleting associated data into a beneficial recovery process. By validating the inode table first, the system identifies cases where data can be recovered instead of deleted, turning a data loss scenario into a data recovery opportunity
2Productivity
If the inode table is validated without checking extension table, then validation speed is improved, but data recovery accuracy deteriorates
Solution Approach 1:
The patent segments the validation process into two distinct stages: first validating the inode table structure, then checking the extension table for recoverable data. This segmentation allows the system to maintain fast initial validation while performing precise recovery checks only when necessary
Solution Approach 2:
The patent performs preliminary validation of the inode table before conducting the more time-consuming extension table check. This preliminary action filters out cases that don't require recovery, improving overall efficiency while maintaining accuracy for cases that do need recovery
Data Source
AI summary
Techniques for data recovery involve determining, based on a relationship between a missing inode in an inode table and a data logical address in an extension table, whether the inode is a target inode that is able to be recovered. The techniques further involve acquiring, in response to a determination that the inode is the target inode, associated data corresponding to the target inode. The techniques further involve recovering the inode based on the acquired associated data. Accordingly, volume-level data loss can be avoided, a data loss rate of a storage product can be reduced, and user satisfaction can be enhanced.