Time sequence data storage method based on dynamic weight equalization time sequence database cluster
A technology of dynamic weights and time series data, applied in database indexing, digital data processing, structured data retrieval, etc., can solve the problems of unbalanced data volume and the inability of stand-alone version time series database to store massive data collected by equipment, so as to improve The effect of user experience
Active Publication Date: 2022-04-29
BEIJING ICHINAE SCI & TECH CO LTD
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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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[0044] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0045] The present invention provides a time-series data storage method based on a dynamic weight-balanced time-series database cluster. Based on the method, data collected by Internet of Things devices can be uniformly stored in each time-series database influxdb in the time-series database cluster, which is mainly used in the Internet of Things The system's cloud stores the scenario of collecting data from massive IoT devices, refer to figure 1 , including the following steps:
[0046] Step 1, time series database influxdb cluster configuration cluster interface influ...
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The invention provides a time sequence data storage method based on a dynamic weight balance time sequence database cluster. The time sequence data storage method comprises the steps that the time sequence database cluster configures a cluster interface, a message publishing and subscribing system cluster, a reader-writer and m time sequence databases; when the cluster interface is started, n virtual buckets are initialized and generated, and a distribution interval section is determined for each virtual bucket; and determining a target time sequence database by adopting a time sequence database selection algorithm based on a dynamic weight equalization time sequence database cluster, and storing data. The invention provides a time sequence data storage method based on a dynamic weight equalization time sequence database cluster, which is used for a scene that an internet of things cloud stores data acquired by mass equipment, and can solve the problems of storage space waste and difficulty in transverse expansion of the cluster caused by serious imbalance of data stored in each time sequence database in the current cluster. According to the invention, the data collected by the Internet of Things equipment can be uniformly stored in each time sequence database in the time sequence database cluster, so that the user experience is improved.
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-balanced time-series database cluster. Background technique [0002] The Internet of Things system needs to use a time-series database to store massive equipment collection data in the cloud for application query and analysis. 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. Since the influx-proxy allocates the devices to be stored to collect data for each time-series database in the time-series database cluster based on the hash algorithm, there is a problem that the amount of data stored in each time-series database in the time-series database cluster is seriously unbalanced. Contents of the invention [0003] Aiming at the defects in the prior a...
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Login to View More IPC IPC(8): G06F16/22G06F16/2458
CPCG06F16/22G06F16/2474
Inventor 刘涛瞿洪桂陈文彬涂刚
Owner BEIJING ICHINAE SCI & TECH CO LTD