File System Analytics Rule Generation Numbering
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Solution Overview
Problem
Current file system analytics software faces inaccuracies and inefficiencies due to toggling and modifying analytics rules, as well as simultaneous file and directory operations, leading to inconsistencies in analytics property values across distributed data storage systems.
Innovation Solution
Implementing a canonical rule generation number system that associates each set of analytics rules with a specific time period, ensuring that analytics property values are accurately propagated and reported by comparing rule generation numbers stored in nodes with the current rule generation number, thereby avoiding double-counting and ensuring correctness across changes and concurrent operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If analytics rules are toggled or modified, then analytics software can adapt to changing requirements, but analytics property values become inaccurate during propagation
Solution Approach 1:
The system performs preliminary actions by capturing analytics property values at the moment a rule change is detected, before the rule change propagates through the distributed system. This preliminary capture ensures that the snapshot taken is consistent with the old rules, preventing accuracy issues during transition.
Solution Approach 2:
The patent introduces an intermediary mechanism (rule change detection and snapshot capture system) that mediates between the old and new analytics rules. This intermediary ensures that property values are captured at a consistent state before rule changes take effect, resolving the contradiction between adaptability and accuracy.
2Productivity
If simultaneous file and directory operations occur, then system productivity is improved, but inconsistency is introduced in analytics property values
Solution Approach 1:
The system performs preliminary detection of rule changes and captures property value snapshots before concurrent operations can introduce inconsistencies. This preliminary action creates a consistent baseline that remains valid even as simultaneous operations occur.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors for rule changes and operation completions, then validates that analytics property values remain consistent with the captured snapshots. This feedback loop ensures reliability while allowing high productivity operations to proceed.
3Loss of time
If analytics property values are propagated across the distributed directory tree, then analytics data is kept current, but double-counting and inaccuracies occur during transitions
Solution Approach 1:
The system captures analytics property values in advance, before rule changes propagate through the distributed directory tree. This preliminary snapshot ensures that subsequent propagation operations work from a consistent baseline, preventing double-counting and inaccuracies while maintaining data freshness.
Solution Approach 2:
The patent creates copies of analytics property values at the time of rule change detection. These snapshots are then used as the authoritative source for propagation, ensuring that the distributed directory tree receives consistent values without double-counting, while the system can quickly propagate these copied values to maintain freshness.
Data Source
AI summary
Methods, non-transitory machine readable media, and computing devices that ensure correctness of file system analytics are disclosed. With this technology, a first generation number for a volume is incremented in response to a modification of a rule set that defines properties of objects of a file system associated with the volume. A determination is made when a second generation number in a first inode for a first one of the objects matches the first generation number. The first inode is identified based on a traversal of a directory tree associated with the file system. The modified rule set is applied to the properties for the first one of the objects to obtain values, when the second generation number fails to match the first generation number. Analytics data is output after the traversal has completed. The analytics data is generated in response to a query and is based on the values.