Time series data storage method and device, server and storage medium

Abstract

The embodiment of the invention discloses a time series data storage method and a device, a server and a storage medium, and belongs to the field of databases. The method comprises the steps of obtaining to-be-stored data collected by target equipment; determining an equipment logic primary key corresponding to the target equipment according to the equipment identifier of the target equipment andthe data type of the to-be-stored data; determining a target logic group and a target database according to the device logic primary key and a timestamp corresponding to the to-be-stored data, the target database belonging to the target logic group, and the target logic group including a plurality of databases; and writing the to-be-stored data into a target array in a target database under the target logic group. In the method of the invention, when the data are increased, the horizontal capacity expansion can be completed by only adding one or more logic groups, the historical data do not need to be migrated, the horizontal capacity expansion process is simple, and the data are distributed and stored in the plurality of databases under the target logic group, so that the hotspot problemcaused by centralized operation for a single database is avoided.

Description

technical field [0001] The embodiments of the present application relate to the field of databases, and in particular to a time series data storage method, device, server and storage medium. Background technique [0002] Time-series data refers to the data sequence recorded in chronological order by the same indicator, and a time-series database is a specialized database for storing and managing time-series data. [0003] In related technologies, time-series databases adopt different storage strategies for different data types. Usually, each storage strategy contains multiple storage areas for storing data in different time ranges, and regularly compresses data files through log files in the storage areas. , when reading data, the system finds the hit area according to the instruction, decompresses the relevant data files, merges the required data in sequence, and returns the final result. [0004] However, the traditional time-series database only considers the data storag...

AI Technical Summary

Problems solved by technology

[0004] However, the traditional time-series database only considers the data storage and compression strategy. When the data increases, it is necessary to create a new database and migrate the relevant historical data to the new database. The workload of horizontal expansion is large and wastes resources.

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