Broken line caching method based on different acquisition scenes

Abstract

The invention discloses a broken line caching method based on different acquisition scenes. The method comprises the following steps: carrying out different processing according to different data acquisition source types and exception types, when the data acquisition source is a database, recording the abnormality starting time and trying to reconnect when abnormality occurs, continuing to acquirethe data until the connection is recovered, outputting a data loss report when the data acquisition source is of a protocol push type and the abnormal type is that the data acquisition source side isabnormal, and when the data acquisition source is a protocol push type and the exception type is storage database side exception, by the data acquisition module, normally acquiring data according toconfiguration requirements, stores the data in a specified temporary memory, and sending a connection request to the storage database according to a predetermined period until the connection with thestorage database returns to normal. According to the invention, different disconnection caching mechanisms can be adopted according to different configuration information, when the data is collected from the time sequence database, the integrity of the data can be automatically ensured in a database caching mode.

Description

technical field [0001] The invention belongs to the technical field of data collection, and relates to a disconnection cache method in different collection scenarios. Background technique [0002] With the development of science and technology, data information has become more and more important, which can not only reflect the status of business operations, but also assist in improving production efficiency and operating decisions. Data acquisition occupies an important position in the entire power plant information system, and the stability of its working state is very important to the main equipment. With the complexity and diversity of business scenarios, when multiple databases and data collection protocols are used at the same time, it is currently an important problem to perform data supplementary collection in a timely manner when abnormal data collection occurs. The research on data collection exceptions focuses on a specific specific application scenario. Usually, ...

AI Technical Summary

Problems solved by technology

[0003] In academia and industry, there are already many methods for dealing with data collection anomalies. Most of the anomaly research based on data collection focuses on a single scenario, and there are certain deficiencies in the ability to supplement data collection.

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