Data Aging via Grading Attributes for Storage Layering
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Solution Overview
Problem
Current database management systems lack an efficient method to segregate data from database tables based on access frequency, leading to suboptimal storage solutions that do not align with the actual usage patterns, resulting in inefficient resource allocation and potential performance issues.
Innovation Solution
A process that segregates data into different layers based on access frequency, utilizing storage mechanisms like RAM, HDD, and SSD, with grading attributes determining the appropriate storage location, and a data aging object to group related tables for unified layering and storage, prioritizing storage devices based on cost and access patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored uniformly across storage devices without segmentation, then storage management is simple, but storage efficiency and access performance deteriorate
Solution Approach 1:
The patent segments data into different layers (hot, warm, cold) based on access frequency and stores each layer in appropriate storage devices (RAM, SSD, HDD). This segmentation resolves the contradiction by improving storage efficiency through optimized data placement while managing complexity through automated grading attributes and layering rules.
Solution Approach 2:
The patent implements dynamic data layering where data automatically transitions between storage layers based on access patterns and grading attributes. This dynamic approach improves storage efficiency by adapting to changing access requirements while the automated system manages the complexity of transitions.
2Speed
If frequently accessed data is stored in high-performance storage (RAM/SSD), then access speed improves, but storage cost increases
Solution Approach 1:
The patent applies local quality by placing frequently accessed data (hot layer) in high-performance storage (RAM/SSD) while storing infrequently accessed data (cold layer) in lower-cost storage (HDD). This resolves the contradiction by optimizing access speed for critical data while minimizing storage costs for less critical data through differentiated storage quality.
Solution Approach 2:
The patent changes the storage parameter (performance vs. cost) based on data access characteristics by using grading attributes to categorize data into different layers. Hot data uses high-performance storage while cold data uses cost-effective storage, resolving the speed-cost tradeoff through parameter adaptation.
3Productivity
If data is segregated into multiple layers based on access frequency, then storage optimization improves, but system complexity increases
Solution Approach 1:
The patent implements self-service through automated data layering where the system automatically assigns grading attributes, determines data layers, and manages storage placement without manual intervention. This resolves the contradiction by achieving optimized resource allocation through automation, which manages the complexity internally rather than requiring external management overhead.
Solution Approach 2:
The patent performs preliminary action by pre-defining grading attributes and layering rules that automatically guide data placement and transitions. This preliminary configuration resolves the contradiction by establishing the optimization framework in advance, allowing the system to automatically manage complex data segregation without ongoing manual complexity.
Data Source
AI summary
According to an embodiment of the present disclosures, systems, methods, and non-transitory computer-readable mediums having program instructions thereon, provide for process of segregating data from database tables into different layers depending on the frequency of access to the data—so that each layer of the data can be stored in an appropriate storage mechanism. For example, infrequently-accessed data can be stored in a hard disk drive (HDD) and frequently-accessed can be stored in random-access memory (RAM). Further, the data can also be stored in a sold-state drive (SSD) or other memory-storing devices. In an embodiment, grading attributes are used to layer the data and, accordingly, segregate the data into appropriate storage mechanisms.