基于动态元数据标识与DAG优化的数据编织系统及方法
By using dynamic metadata identification and a DAG-optimized data weaving system, the problem of insufficient flexibility in metadata management and task scheduling is solved, achieving efficient resource allocation and task scheduling, and improving the overall performance and responsiveness of the system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING DETA JINGYAO INFORMATION TECH CO LTD
- Filing Date
- 2025-04-03
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies lack flexibility in metadata management, DAG task scheduling, and multi-source data federated queries, leading to resource waste and response delays. In particular, they cannot achieve efficient allocation of computing resources and task scheduling under dynamically changing workloads.
A data weaving system based on dynamic metadata identification and DAG optimization is adopted. By establishing a multi-dimensional scheduling model, using priority weight coefficients, resource elasticity factors and data lineage correlation, and combining genetic algorithms to optimize task scheduling, dynamic task fragmentation and resource allocation are achieved, thereby enhancing the system's flexibility and responsiveness.
It improved resource utilization, reduced data processing latency, significantly enhanced multi-source query performance and overall system efficiency, and ensured real-time task scheduling and efficient resource utilization.
Smart Images
Figure CN120492137B_ABST