Database Cache Segmentation for Storage Efficiency
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Solution Overview
Problem
Conventional database storage systems face inefficiencies due to increased useless reading from low-speed storage when handling large data areas, leading to performance deterioration, as they often discard unused data from large storage areas, necessitating repeated reads from low-speed storage when different micro areas are accessed.
Innovation Solution
A storage system and data cache method that prioritize reading and writing data in smaller units using a high-speed memory and larger units in low-speed storage, focusing on caching only the required columns, thereby reducing unnecessary reads from low-speed storage and enhancing memory cache efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is handled as a large area unit from low-speed storage to improve cache efficiency, then cache hit rate improves, but access latency increases due to reading unnecessary data
Solution Approach 1:
The patent segments data into different granularity levels: large-area units for storage management and small micro-area units for caching. When data is read from low-speed storage, only the specific micro-area needed for the query is extracted and cached, rather than caching the entire large-area unit. This segmentation allows the system to maintain cache efficiency while minimizing access latency by reading only necessary data portions.
2Speed
If cache size is increased to reduce access latency, then access speed improves, but cache efficiency deteriorates due to data area waste
Solution Approach 1:
The patent applies local quality by making the cache granularity adaptable to access patterns. Frequently accessed micro-areas are cached at fine granularity, while less frequently accessed data is managed at coarse granularity. This allows the cache to optimize for speed on hot data paths while maintaining overall efficiency by not wasting cache space on cold data that wouldn't be accessed anyway.
3Reliability
If data is read in small units from low-speed storage to improve cache efficiency, then cache efficiency improves, but productivity decreases due to increased reading operations
Solution Approach 1:
The patent implements preliminary action by pre-caching micro-areas that are likely to be accessed based on query patterns and access frequency analysis. Before actual queries are executed, the system identifies and caches frequently accessed data portions in advance. This preliminary caching reduces the need for repeated reads from low-speed storage during query execution, thereby maintaining cache efficiency while improving overall productivity.
Data Source
AI summary
A database management system identifies a required column which is required for executing the query, reads out data of the identified required column from a storage device, and executes the query based on the data of the required column. When reading out the data of the required column, the database management system preferentially reads out the data of the required column from a high-speed storage device storing the data of the required column among a memory, a second storage, and a first storage, stores, in the memory, data of the second data size unit including the data of the required column used for executing the query, and, when the data of the required column is read out from the first storage, stores the data of the second data size unit in the memory and stores the read-out data of the first data size unit in the second storage.