Data Arrangement Program for Database Processing Efficiency
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Solution Overview
Problem
Existing data arrangement technologies face inefficiencies in processing time due to the concentration of similar record data sets in computational resources, leading to increased processing times when query data is similar to record data.
Innovation Solution
A data arrangement program that calculates similarity between record data sets using subspace clustering and projected clustering techniques to distribute record data across computational resources, preventing the concentration of similar data sets and optimizing processing times by generating a similarity matrix and using the Gale-Shapley algorithm for stable matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If record data sets are distributed to computational resources to equalize processing times, then processing efficiency is improved, but query processing time increases when similar data sets are concentrated in the same resource
Solution Approach 1:
The system performs preliminary calculations to determine similarity between query data and record data before actual processing. By pre-calculating similarity metrics and using this information to guide data distribution decisions, the system avoids concentrating similar data sets in the same computational resource, thereby preventing increased processing times during query execution.
Solution Approach 2:
The system continuously monitors processing times and similarity metrics, using this feedback to dynamically adjust data distribution. When similar data sets are identified, the system redistributes them across different computational resources to maintain optimal processing efficiency and prevent time losses during query processing.
2Device complexity
If similar record data sets are concentrated in the same computational resource, then data arrangement is simplified, but processing time increases due to similar query-record data pairs
Solution Approach 1:
The system applies different distribution strategies to different computational resources based on local characteristics. By calculating similarity metrics for each query-record data pair and using this information to make localized distribution decisions, the system achieves optimal data arrangement that minimizes processing time without requiring complex global optimization.
Data Source
AI summary
A data arrangement apparatus executes a process request on data stored in a database, calculates similarity of a process in a combination of the process request and the data, divides the data in such a manner as to distribute the similarity and processes a process request accepted for the divided data.