Incremental Metadata Aggregation for File Storage Systems
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Solution Overview
Problem
Companies face challenges in managing expanding data storage needs, particularly with unstructured data, due to difficulties in assessing deep directory structures and maintaining organized storage systems, often leading to inefficiencies such as overflowing storage capacity and disrupted workflows.
Innovation Solution
A system comprising a processor and memory that employs a scanner component to traverse data structures, collect node data, and generate aggregated metadata, reducing database accesses and improving data organization through incremental aggregation of metadata in file storage systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional storage expansion approaches are used to meet growing data needs, then storage capacity increases, but system complexity and cost increase
Solution Approach 1:
The patent segments the monolithic storage system into a hierarchical structure with root directories, subdirectories, and leaf nodes. Each node is independently managed with its own metadata, allowing incremental processing and reduced complexity when managing large volumes of data. This segmentation enables the system to handle storage expansion without proportionally increasing overall system complexity.
2Ease of operation
If deep directory structures are used to organize large amounts of data, then data organization improves, but difficulty in assessing and managing the structure increases
Solution Approach 1:
The patent implements feedback mechanisms through metadata aggregation that rolls up information from leaf nodes to parent directories. This provides continuous feedback about storage utilization, data distribution, and capacity metrics at each hierarchical level, making it easier to assess and manage deep directory structures without increasing complexity.
Solution Approach 2:
The patent introduces metadata as an intermediary layer between the physical directory structure and the management interface. This metadata layer abstracts the complexity of deep hierarchical structures, providing simplified views and metrics that make assessment and management easier while preserving the organizational benefits of deep directories.
3Quantity of substance
If storage systems are allowed to fill to capacity, then available storage space maximizes utilization, but workflow disruption and data access issues occur
Solution Approach 1:
The patent performs preliminary actions by proactively monitoring storage capacity through incremental metadata aggregation and generating alerts or automated responses before storage fills to capacity. This allows preventive archiving, data lifecycle management, or capacity planning actions to be taken in advance, avoiding workflow disruptions that would occur if storage were allowed to completely fill.
4Productivity
If incremental metadata aggregation is implemented, then database access requirements reduce, but processing complexity increases
Solution Approach 1:
The patent applies partial action by implementing incremental metadata aggregation that processes only the portions of the directory structure that have changed since the last aggregation. Rather than reprocessing the entire structure, it performs partial updates, reducing database access requirements while managing processing complexity through targeted, selective processing of affected nodes.
Data Source
AI summary
The described technology is generally directed towards incremental aggregation of metadata for a file storage system. According to an embodiment, a system can comprise a memory and a processor that can execute the components stored in the memory. The components can comprise a scanner component that can accessing a data structure storage component that can store a first data structure, and a branch of the first data structure can comprise a node that comprises at least one descendent link to a descendant node. The scanner component can further traverse from a first node to a second node by employing a first descendent link. Further, the method comprises a data collector that can collect node data from the first node and the second node. The system can further comprise a rollup data generator to aggregate, upon occurrence of a condition, the node data, resulting in aggregated node data.