A method, device and system for storing time series data

Abstract

The present application provides a method for storing time-series data, which includes the following steps: receiving time-series data, according to the attribute information of the time-series data, according to the preset aggregation rules, aggregating and updating the corresponding time in the receiving buffer in the memory Sequence data; send the time series data stored in the receiving buffer to the archiving buffer in the memory; according to the relationship between the time corresponding to the time characteristic value of each archiving time period determined according to the requirements of archiving accuracy and the current time , according to the aggregation rule, aggregate the corresponding time series data in the archive buffer to form the time series data to be stored, and store it in the archive buffer; store the time series data to be stored in a non-volatile medium . It can realize fast real-time aggregation of time series data and real-time multi-precision archiving and storage, which can meet the needs of subsequent applications for multi-precision query.

Description

technical field [0001] This application relates to a method for storing data, in particular to a method and device for storing time-series data, a method and device for aggregating time-series data, and a method and device for archiving and storing time-series data. It relates to a system for storing time series data. Background technique [0002] In addition to the function of archiving and storing data, the large-scale data system also provides the query function of the historical data stored in the archive. Various indicator data. These indicator data are periodically generated for monitoring objects and belong to time series data. The data system will archive and store these time series data generated by the monitoring system, and provide the system maintenance personnel or users with the function of querying these data. [0003] When archiving and storing existing data systems, the original time series data is usually stored or used to calculate and store time series...

AI Technical Summary

Problems solved by technology

Therefore, the existing data system can only provide a single-precision historical data query function

[0004] However, for the query of historical data, in many cases, it is necessary to query data with more than one precision. For example, for the query of historical data with a large time span, the accuracy of the required data may be lower. For historical data with a short time span For queries, the accuracy of the required data may be higher, and for the current and recent data, the accuracy of the data required for the query is the highest

[0005] In addition, single-precision data storage may have negative effects due to different query time spans. For example, for high-precision stored data, if the query time span is long, the response speed will be slow due to the large amount of data to be provided. problems; for low-precision stored data, the query time span is short, and the data cannot reflect the real situation due to the small amount of data that can be provided

[0006] It can be seen that the single-precision storage and query methods of time series data in existing data systems cannot meet the needs of multi-precision queries

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