Selective Feature Caching for Data Query Optimization
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Solution Overview
Problem
Current data processing systems face inefficiencies in caching data due to the limited size of cache memory, as they typically cache all feature information, leading to increased processing time and resource utilization.
Innovation Solution
A system and method that selects a characteristic value for each feature dimension, caching only the feature values unequal to this characteristic value, allowing for efficient querying by performing searches in the cache memory and generating query results based on established relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If all feature information is cached in the cache memory, then data querying speed is improved, but the cache memory size requirement increases and cache efficiency decreases
Solution Approach 1:
The patent extracts and caches only the distinctive feature values (those not equal to the characteristic value) while leaving the characteristic value uncached. This selective extraction approach caches only the necessary portion of data, reducing cache memory size requirements while maintaining fast query performance for both cached and non-cached values through the established corresponding relationship.
Solution Approach 2:
Instead of caching all feature information (excessive action), the patent implements partial caching by storing only feature values that differ from the characteristic value. This partial action approach optimizes cache memory utilization, improving cache efficiency and reducing the quantity of cached data while still enabling efficient data retrieval.
2Reliability
If all feature information is cached, then data processing completeness is improved, but cache efficiency and resource utilization worsen
Solution Approach 1:
The patent extracts only the essential distinctive feature values for caching, removing the redundancy of storing identical characteristic values for all entities. This extraction ensures data processing completeness is maintained through the corresponding relationship while significantly improving cache efficiency by reducing the total volume of cached data.
Solution Approach 2:
The patent changes the caching parameter from caching all feature values to caching only those values that differ from the characteristic value. This parameter change optimizes cache efficiency and resource utilization while maintaining data processing completeness through the established correspondence between cached values and their associated entities.
3Measurement precision
If more feature dimensions are cached, then data querying accuracy is improved, but the amount of cached data increases beyond limited cache capacity
Solution Approach 1:
The patent extracts and caches only the distinctive feature values across multiple feature dimensions, removing the burden of caching redundant characteristic values. This enables more feature dimensions to be cached within limited cache capacity while maintaining data querying accuracy, as the corresponding relationship ensures complete information retrieval.
Solution Approach 2:
The patent applies partial caching action across multiple feature dimensions, caching only the necessary distinctive values rather than all values for each dimension. This partial approach allows the system to handle more feature dimensions within limited cache capacity while preserving data querying accuracy through the established corresponding relationships.
Data Source
AI summary
A method for querying data is provided. The method may include determining a characteristic value of a selected feature dimension among feature values of the selected feature dimension of plurality of entities and establishing a corresponding relationship between the characteristic value and the selected feature dimension. The method may also include caching the corresponding feature value into a cache memory for each entity having a feature value of the selected feature dimension being unequal to the characteristic value, and leaving the corresponding feature value without caching for each entity having a feature value of the selected feature dimension being equal to the characteristic value. The method may further include performing a first search in the cache memory to produce a first search result in response to a query request related to the plurality of entities, and generating a query result based on the corresponding relationship and the first search result.