面向工业时序数据管理与分析融合的数据模型转换OA

In industrial internet of things(IIoT)scenarios,device monitoring data are typically stored in the form of time-series data and modeled using hierarchical path structures to facilitate point management and access;however,this modeling approach does not directly support multidimensional analysis based on relational models and often requires complex ETL transformations.To address the model-level conflict between time-series data management and analysis in industrial settings,this paper proposes a unified time-series data model.The model leverages a hierarchical tree structure for flexible data ingestion and storage,while offering multidimensional analytical capabilities through a classical relational model view.We implement this approach systematically in the industrial time-series database Apache IoTDB,enabling a single dataset to support both monitoring and analytical requirements.