Cross-type data calculation and sharing method, system, and device and a calculation and sharing method

Abstract

The embodiment of the invention provides a cross-type data calculation and sharing method, a system, a device and a calculation and sharing method, comprising: extracting a plurality of first data anda plurality of second data from a data acquisition platform, normalizing each of the first data types to obtain a plurality of normalized first data; Defining an expression data point table includingone or more preset expressions; Based on the plurality of normalized first data, the plurality of second data, and the plurality of time data, acquiring a plurality of shared data by calculating oneor more preset expressions in the expression data point table. The embodiment of the invention can plan a unified data minimum unit, and can improve the synchronization, service applicability, effectiveness and reliability of the data. Through the preset expression to calculate the shared data, it can process the data based on the business requirements and reduce the load of the system.

Description

technical field [0001] Embodiments of the present invention relate to the field of big data sharing, and more specifically, to a cross-type data computing and sharing method, system, and device. Background technique [0002] In the entire urban rail transit system, it includes multiple systems, such as the professional monitoring system of the line, the signal system of the line, the automatic fare collection system and sorting system of the line, the special business system, the office system, the asset system and the interaction with external agencies system etc. These systems provide different types of data. [0003] Specifically, the professional monitoring system of the line mainly provides the operating status, operating mode, and fault alarm information of the professional electromechanical equipment in the rail transit. It has the characteristics of high real-time performance, strong professionalism, and large data volume. Intuitively, it is reflected that when the...

AI Technical Summary

Problems solved by technology

Data that has not been processed based on business requirements is inefficient to use. For a certain business requirement, access and association of multiple data tables are involved, which will have an adverse impact on the system load and the efficiency of data reading.

The business system has serious inconveniences in the comprehensive display, analysis, and utilization of data. At the same time, as the data scale continues to increase after the new line is connected, there are great hidden dangers in the complexity and stability of the subsequent system expansion.

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