Time series data storage method based on dynamic weight balance time series database cluster

Abstract

The invention provides a time-series data storage method based on a dynamic weight-balanced time-series database cluster, comprising: a time-series database cluster configuration cluster interface, a publish-subscribe message system cluster, a reader and m time-series databases; For virtual buckets, the allocation interval segment is determined for each virtual bucket; the time-series database selection algorithm based on dynamic weight balancing time-series database cluster is used to determine the target time-series database and store the data. The present invention provides a time-series data storage method based on a dynamic weight-balanced time-series database cluster, which is used in a scenario where the cloud of the Internet of Things stores data collected by a large number of devices, and can solve the problem of storage space waste caused by serious unbalanced storage data of various time-series databases in the current cluster and clustering. Difficulty scaling out. Through the present invention, the data collected by the Internet of Things equipment can be uniformly stored in each time series database in the time series database cluster, thereby improving user experience.

Description

technical field [0001] The invention belongs to the technical field of time series data storage, and in particular relates to a time series data storage method based on a dynamic weight balancing time series database cluster. Background technique [0002] The IoT system needs to use the time series database in the cloud to store massive data collected by devices for application query and analysis. Influx-proxy, as a cluster solution for the time series database (influxdb), solves the problem that the single-machine version of the time series database cannot store a large amount of data collected by devices. Because influx-proxy allocates data to be stored by devices to collect data for each time series database in the time series database cluster based on the hash algorithm, there is a serious imbalance in the amount of data stored by each time series database in the time series database cluster. SUMMARY OF THE INVENTION [0003] In view of the defects existing in the pri...

AI Technical Summary

Problems solved by technology

Influx-proxy, as a cluster solution for time series database (influxdb), solves the problem that the stand-alone version of time series database cannot store massive data collected by devices

Because influx-proxy allocates the equipment to be stored for each time-series database in the time-series database cluster based on the hash algorithm to collect data, there is a problem that the amount of data stored in each time-series database in the time-series database cluster is seriously unbalanced

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