一种用于并发场景的多维度实时数据分析方法
By monitoring data skewness and access frequency deviations, and optimizing node granularity and the number of virtual nodes, the problems of uneven data distribution and node load imbalance in high-concurrency scenarios were solved, thereby improving request processing efficiency and data analysis stability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-29
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies lack the ability to dynamically monitor and optimize data distribution balance, node load status, and adjustment effects in high-concurrency scenarios, leading to increased data request processing latency and decreased data analysis stability.
By monitoring data skewness and access frequency deviations, physical node types are determined, and node optimization is performed. This includes adjusting node granularity and the number of virtual nodes to optimize data distribution and resource utilization, including dynamic adjustments based on SQL execution time and load saturation.
It improves request processing efficiency and real-time analysis stability in high-concurrency scenarios, avoids resource waste caused by indiscriminate adjustments, and ensures efficient and stable operation and resource utilization of distributed clusters.
Smart Images
Figure CN121387551B_ABST
Abstract
Citation Information
Patent Citations
Data request processing method and device applied to high-concurrency scenario
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