File System Baseline Generation via Inode Table Copying
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Solution Overview
Problem
The existing methods for initializing a file system baseline are time-consuming and computationally intensive, particularly for deep directory structures, which can leave a file system vulnerable to data disasters during the disaster recovery process.
Innovation Solution
The approach involves using an inode table to retrieve and compile object identifiers from inodes instead of walking the namespace, allowing for faster identification and compilation of file system objects, thereby enabling quicker baseline generation for disaster recovery and other data services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If namespace traversal is used to identify file system objects, then complete object identification is achieved, but time consumption and computational intensity increase significantly
Solution Approach 1:
The patent creates a copy of the inode table data structure to store file system object information. Instead of traversing the entire namespace hierarchy, the system copies relevant inode information into this data structure, enabling faster object identification while maintaining completeness of the baseline.
2Reliability
If namespace traversal is used to identify file system objects, then all objects are captured, but computational intensity increases
Solution Approach 1:
The system copies inode table information into a specialized data structure that enables efficient object identification without requiring complete namespace traversal. This copying approach reduces computational intensity while ensuring all file system objects are captured for the baseline.
3Manufacturing precision
If deep directory structures are processed using namespace traversal, then accurate baseline is generated, but the process becomes vulnerable to data disasters
Solution Approach 1:
The patent performs preliminary action by creating an initial baseline using the copied inode table data structure before full namespace traversal is completed. This allows the system to establish a baseline faster, reducing the window of vulnerability to data disasters while maintaining accuracy through subsequent refinement.
Data Source
AI summary
Example implementations relate to identifying file system objects of a file system for generating an initial baseline of the file system. In an example, an inode table of the file system is retrieved. Modes included in the inode table correspond respectively to file system objects of the file system. Attributes, including an object identifier and a time attribute, are extracted from each of the inodes of the inode table. A compilation of the object identifiers from the extracted attributes are provided to a service that generates the initial baseline of the file system using the compilation.