Schema-Based Memory Data Segmentation for Storage Optimization
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Solution Overview
Problem
Existing data management approaches lead to inefficiencies due to dynamic access patterns and the need to manage data across different storage tiers, resulting in complexities and resource misallocation.
Innovation Solution
A schema-based approach that identifies stale data and transfers it to persistent storage, reducing the active in-memory footprint, while maintaining data integrity and relationships across storage tiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored in memory device for fast access, then access speed is improved, but memory usage increases and data cannot be persisted
Solution Approach 1:
The patent segments data into frequently accessed and infrequently accessed portions, storing the former in memory and the latter in persistent storage. This segmentation allows the system to optimize for both speed and memory usage by placing only necessary data in fast memory.
Solution Approach 2:
The patent extracts infrequently accessed data from memory and stores it in persistent storage, thereby reducing memory usage while maintaining fast access to frequently accessed data. The schema-based approach identifies which data portions can be extracted without impacting performance.
2Ease of operation
If entire page is moved between memory and persistent storage, then storage management is simplified, but efficiency decreases due to moving unnecessary data
Solution Approach 1:
The patent divides data into schema-based segments (frequently accessed and infrequently accessed) rather than moving entire pages. This allows selective transfer of only necessary data portions between memory and persistent storage, improving efficiency while maintaining manageable storage operations.
Solution Approach 2:
The patent applies different storage strategies to different portions of data based on their access characteristics. Frequently accessed data portions are kept in memory while infrequently accessed portions are stored in persistent storage, optimizing the system for both speed and efficiency.
3Stability of the object's composition
If data is organized in hierarchical tree structure, then data relationships are preserved, but access patterns become complex and unpredictable
Solution Approach 1:
The patent introduces a schema as an intermediary layer that sits between the hierarchical data structure and the storage system. The schema translates complex hierarchical relationships into simple access patterns, allowing the system to preserve data relationships while achieving predictable, efficient access to frequently and infrequently accessed data portions.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, identifying a plurality of parameters for managing data in relation to an execution of an application, monitoring access to the data, determining, based on the monitoring, that first data that is located in a memory of the processing system has not been accessed in an amount of time that is greater than a first threshold, resulting in a first determination, determining, based on the plurality of parameters and the first determination, that the first data is a candidate for transfer to a persistent storage device, resulting in a second determination, and based on the second determination, causing the first data to be transferred to the persistent storage device. Other embodiments are disclosed.