Data Caching Method with Hot Spot Detection
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Solution Overview
Problem
In distributed storage systems, traditional data caching methods lead to inefficient use of storage resources due to cache pollution, where frequently accessed data is not prioritized, and network bandwidth and storage overhead are high due to large caching granularity.
Innovation Solution
A data caching method that transmits data to the cache apparatus based on access frequency and time, using a Hot Spot Detection module to separate hot and cold data, and dynamically adjusts cache occupancy by clearing less-accessed data, ensuring only frequently accessed data is stored in the cache apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data are imported into the cache apparatus on demand using traditional caching methods, then the cache apparatus can respond to user requests, but storage resources of the cache apparatus are occupied by newly imported data that may not be frequently accessed, reducing storage resource utilization efficiency
Solution Approach 1:
The system performs preliminary actions by proactively caching data from storage apparatuses into the cache apparatus before actual user requests occur. The server monitors access patterns and pre-loads data that is likely to be accessed, transforming the traditional reactive caching model into a proactive one that improves both storage utilization and access efficiency.
Solution Approach 2:
The caching strategy dynamically adjusts based on real-time access patterns. The server continuously monitors which data are frequently accessed and adapts the caching decisions accordingly, making the cache apparatus flexible and responsive to changing data access requirements rather than following a static caching policy.
2Quantity of substance
If the cache apparatus has limited capacity and imports new data, then it can store more varied data, but existing data in the cache apparatus must be replaced, potentially replacing frequently accessed data with less important data
Solution Approach 1:
The system implements feedback mechanisms where the server continuously monitors data access patterns and uses this information to make informed caching decisions. Access frequency and timing information are fed back into the caching strategy, allowing the system to prioritize caching data that is actually being accessed and to replace data that is no longer frequently used, thereby optimizing both cache capacity utilization and access time.
Solution Approach 2:
The caching strategy changes parameters such as cache retention time and priority levels based on observed access patterns. Data that shows high access frequency or temporal locality are assigned higher priority and longer retention times, while data with low access frequency are replaced more quickly, allowing the cache apparatus to dynamically optimize its contents for current access requirements.
3Device complexity
If caching granularity is large in distributed storage mode, then data scattering arrangement can be simplified, but network bandwidth and storage read/write overhead increase, reducing operation efficiency
Solution Approach 1:
The system segments data into smaller granular units that can be independently cached and managed. Instead of caching large data blocks, the server identifies and caches specific data segments or blocks that are frequently accessed, reducing the amount of data that needs to be transmitted over the network and stored in the cache apparatus, thereby reducing network bandwidth consumption and storage overhead while maintaining manageable complexity.
Data Source
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AI summary
Disclosed in the present disclosure is a data caching method and apparatus, the data caching method includes the following steps: receiving a data request message sent by a user terminal; if detecting that a cache apparatus does not include the target access data requested by the data request message, then sending the target access data in a storage apparatus to the user terminal; extracting parameter information of the target access data in the storage apparatus, and determining whether the parameter information matches a preset parameter condition; and, if the parameter information matches the preset parameter condition, then transmitting the target access data to the cache apparatus.