Efficient online time sequence database installation and deployment system and method

Abstract

The invention discloses an efficient online time sequence database installation and deployment system and method.The system comprises a database management unit and a server node unit, and the database management unit is used for uploading database version installation packages in a fragmented mode and providing creation, editing and application of parameter templates; creating a stand-alone or cluster time sequence database instance according to the information input by the user; and the server node unit is used for performing unified management on server nodes and ensuring that the database runs in a stable environment. Through automatic and modular design, rapid and stable time sequence database deployment is realized, and the operation and maintenance efficiency of the system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of time series databases, and particularly to an efficient online time series database installation and deployment system and method. Background Art

[0002] With the rapid development of technologies such as the Internet of Things and big data, time series databases are increasingly widely used in various industries. However, the existing installation and deployment process of time series databases is relatively cumbersome, the database version management is chaotic, upgrading and maintenance are difficult, the server node management is not unified, the resource utilization rate is low, the database instance deployment process is complex and error-prone, resulting in a relatively high system operation and maintenance cost. Therefore, it is necessary to study an efficient and reliable time series database installation and deployment method. Summary of the Invention

[0003] The purpose of the present invention is to provide an efficient online time series database installation and deployment system and method, aiming to solve the problems of low efficiency and easy error in the installation and deployment process of time series databases in the prior art. Through an automated and modular design, the present invention realizes fast and stable deployment of time series databases and improves the system operation and maintenance efficiency.

[0004] The present invention is implemented by the following technical solutions: An efficient online time series database installation and deployment system includes a database management unit and a server node unit. The database management unit is used to upload the database version installation package in slices, and provide the creation, editing and application of parameter templates, and create a single-machine or cluster time series database instance according to the information input by the user; the server node unit is used to uniformly manage the server nodes and ensure that the database runs in a stable environment.

[0005] Further, the database management unit includes a database version management module. The database version management module is used to upload the database version installation package in slices. The installation package includes two parts. One part is the database itself installation program and script, and the other part is the parameter template of this database version; the slice upload is as follows: first upload in slices, and merge the completed files, then take out this parameter template file, and parse out the parameter list of this database version. The parameters in the parameter list include one or more of parameter name, parameter default value, parameter recommended value and parameter description.

[0006] Further, the database management unit further includes a database version parameter template management module. The database version parameter template management module is used to create, edit and apply parameter templates, and ensure the consistency and standardization of database parameters through template management.

[0007] Furthermore, the database management unit also includes a database instance management module, which creates a stand-alone or cluster time series database instance according to information input by the user, thereby reducing the manual configuration process.

[0008] Furthermore, the server node unit includes a server node management module, which is used to uniformly manage server nodes, including: one or more of node name, node IP, node port number, node status, node user name and node authentication method.

[0009] Furthermore, the server node unit also includes a server node environment monitoring tool module, which includes operating system monitoring, network monitoring and storage monitoring to ensure that the database runs in a stable environment. By selecting a server node, the user automatically adapts a list of time series database versions that can be installed on the node.

[0010] An efficient online time series database installation and deployment method is implemented based on the above-mentioned efficient online time series database installation and deployment system, and includes the following steps: Install the database version by uploading in pieces; Configure the database version parameter template; Manage and monitor server nodes in real time; Create a time series database instance.

[0011] Furthermore, configuring the database version parameter template includes the following steps: Configuration parameter name; Select the database version, and the parameter list of the corresponding database version will be automatically displayed; User saved.

[0012] Furthermore, managing and real-time monitoring the server nodes includes the following steps: Configure the information required for node management. After the configuration is completed, perform a connection test based on the configuration information, using jsch technology to implement it; At preset intervals, these configured node information is monitored in real time. First, according to the configuration information, jsch technology is used to connect to the node server to obtain the session. Then, the shell script path of the external configuration file is dynamically obtained to obtain the InputStream stream of the file. The IoUtil.readUtf8 method is used to obtain the shell script content in the InputStream stream. Finally, jsch is used to execute the exec command to execute the general shell script. After successful execution, the execution success information is returned. This information is parsed to obtain the node operating system type, CPU architecture type, CPU information, memory information and disk information, so as to realize real-time monitoring of the server node information.

[0013] Furthermore, creating a time series database instance includes the following steps: The user enters the instance name and selects the service type; The user selects a service node, triggers the service environment detection tool, and automatically identifies the appropriate time series database version; According to the automatically adapted time series database version, obtain the database version parameter template list; Once the user saves the data, the system automatically creates a database instance on the server.

[0014] The beneficial effects of the present invention are: Efficiency: The online installation and deployment process reduces the difficulty of installation, greatly improves the installation and deployment efficiency of the time series database, and reduces costs.

[0015] Stability: The various modules of the system work together to ensure the stable operation of the database, while also facilitating maintenance and upgrades.

[0016] Scalability: Supports stand-alone and cluster modes, and can be expanded according to actual needs.

[0017] Parameter template management: Improves the consistency and standardization of database parameters and reduces management difficulty.

[0018] Version control: Easily upgrade, downgrade, and roll back database versions to ensure that the database always runs on the appropriate version.

[0019] Real-time monitoring: Quasi-real-time monitoring of the operating status of service nodes and timing libraries to ensure system stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0021] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0023] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0024] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0025] See also Figure 1 ,An efficient online time series database installation and deployment system adopts a modular design: including a database version management module, a database version parameter template management module, a server node management module, a server node environment detection module, and a database instance management module.

[0026] The database version management module uploads the database version installation package in pieces to achieve efficient and stable file upload and transmission. The installation package is divided into two parts, one is the database installation program and script, and the other is the parameter template of the database version. First, the piece-by-piece upload is completed and the files are merged. Then the template file is taken out and the parameter list of the database version is parsed. The parameters include parameter name, parameter default value, parameter recommended value, parameter description, etc. Secondly, the required environmental standards of the database version (including operating system version, CPU type and number of cores, memory size, disk type and size, network configuration, port availability, etc.) are configured for user reference, and friendly prompts are given. The following example explains: First, select the database version installation package, for example: (XuguTSDB-2.1.0_20241125-release-linux-x64.tar.gz).

[0027] Then, according to the name of the database version installation package, the operating system version and CPU architecture can be analyzed through regular expressions. The required environment standards are filled in by default. The operating system version is Linux, the CPU architecture is X64, the default minimum number of cores is 4, the memory size is 4G, the disk type is SSD, the space size is 10G, the network configuration is Gigabit Network, etc.

[0028] Finally, the user saves the file, triggering the shard upload of the database version installation package. After the shard upload is successful, the shard file is merged, the parameter list is analyzed, and the database version V2.1.0_20241125-linux-x64 is analyzed according to the database version name. After the upload is successful, the installation package path and the environmental standards required for the database version are merged, and this information is stored in the database.

[0029] The database version parameter template management module provides the creation, editing and application functions of parameter templates. Through template management, it ensures the consistency and standardization of database parameters and reduces manual configuration errors. The following is an example of the creation steps: First, configure the parameter name; Secondly, select the database version, and the parameter list of the corresponding database version will be automatically displayed. During this process, users can freely configure the parameter values; Once the user saves the file, the database version is created.

[0030] The server node management module manages the server nodes in a unified manner, including node name, node IP, node port number, node status (including online, offline, fault, used to monitor the availability of nodes in real time), node user name, node authentication method (password or private key), etc. It mainly includes the following steps: First, configure the information required by the node management module. After the configuration is completed, the connection test can be performed according to the configuration information, and the jsch technology is used to implement it; Secondly, the configured node information is monitored in real time every 30 seconds. First, according to the configuration information, the jsch technology is used to connect to the node server to obtain the session. Then, the shell script path of the external configuration file is dynamically obtained to obtain the InputStream stream of the file. The IoUtil.readUtf8 method is used to obtain the shell script content in the InputStream stream. Then, jsch is used to execute the exec command to execute the general shell script. After successful execution, the execution success information is returned. This information is parsed to obtain the node operating system type, CPU architecture type, CPU information, memory information, disk information and other information to achieve real-time monitoring of the server node information.

[0031] The server node environment monitoring tool module includes operating system monitoring, network monitoring, storage monitoring, etc., to ensure that the database runs in a stable environment. When the user selects a server node, it automatically adapts a list of time series database versions that can be installed on the node, including: defining the node environment information class; defining the database version compatibility requirement class, which is obtained based on the adapted time series library version information, and this information has been configured in the database version management; defining the database version performance indicator class; the optimal selector class, which mainly checks whether the node environment is compatible with the version, calculates the node version performance, selects the optimal version method, etc. (rules can be defined according to actual conditions).

[0032] Specific example verification Server node environment information: NodeEnvironment: - nodeId: "node123" -cpuCores: 8 - memorySize: 16384 (16GB) - diskSize: 500 (500GB) - os: "Linux" - networkLatency: 10 (10ms).

[0033] Database version compatibility requirements: VersionCompatibilities: - versionId: "V2.1.020241125-linux-x64" minCpuCores: 4 minMemorySize: 8192 (8GB) minDiskSize: 100 (100GB) supportedOs: ["Linux"]; - versionId: "V2.0.020231015-linux-x64" minCpuCores: 2 minMemorySize: 4096 (4GB) minDiskSize: 50 (50GB) supportedOs: ["Linux"]; - versionId: "V2.2.020251231-mac-x64" minCpuCores: 6 minMemorySize: 12288 (12GB) minDiskSize: 200 (200GB) supportedOs: ["Windows"].

[0034] Database version performance metrics: VersionPerformances: - versionId: "V2.1.020241125-linux-x64" performanceScore: 90 cpuUsage: 0.6 (60%) memoryUsage: 0.5 (50%) diskUsage: 0.3 (30%) networkLatencyScore: 80; - versionId: "V2.0.020231015-linux-x64" performanceScore: 85 cpuUsage: 0.7 (70%) memoryUsage: 0.6 (60%) diskUsage: 0.4 (40%) networkLatencyScore: 70; - versionId: "V2.2.020251231-windows-x64" performanceScore: 95 cpuUsage: 0.5 (50%) memoryUsage: 0.4 (40%) diskUsage: 0.2 (20%) networkLatencyScore: 90.

[0035] Select the optimal process and output the results: Filter out versions that are compatible with the server node environment: “V2.1.020241125-linux-x64” is compatible; “V2.0.020231015-linux-x64” is compatible; "V2.2.020251231-windows-x64" is incompatible (because the operating system does not match); Calculate the total performance score for each compatible version: The total score of “V2.1.020241125-linux-x64” = 90 (performance score) + 60 (CPU usage) +50 (memory usage) + 30 (disk usage) + 80 (network latency score) = 320; The total score of “V2.0.020231015-linux-x64” = 85 + 70 + 60 + 40 + 70 = 315; Select the version with the highest total score as the best version: The best version is "V2.1.020241125-linux-x64" with a total score of 320.

[0036] In the database instance management module, the system automatically creates a stand-alone or cluster time series database instance based on the information entered by the user, without the need for complex manual configuration. The following are the specific steps: The user enters the instance name and selects the service type (stand-alone or cluster); The user selects a service node, triggers the service environment detection module tool, and automatically identifies the appropriate time series database version; According to the automatically adapted time series database version, obtain the database version parameter template list, and the user can freely select one; Users can freely modify database configuration parameters; Once the user saves the data, the system automatically creates a database instance on the server.

[0037] Based on the above steps, users can select database instances, automatically start and stop the database instances, and the system can automatically back up the database instances regularly. Based on the backed-up database instances, users can select backup files by themselves, and the system automatically performs recovery operations. When the performance of the time series database is insufficient, you can expand the capacity based on the data instance, and when the performance of the time series database is excessive, you can shrink the capacity.

[0038] Based on the above embodiments, the present invention has at least the following technical effects: Efficiency: The online installation and deployment process reduces the difficulty of installation, greatly improves the efficiency of installation and deployment of the time series database, and reduces costs. Stability: The various modules of the system work together to ensure the stable operation of the database, while also facilitating maintenance and upgrades. Scalability: Supports stand-alone and cluster modes, and can be expanded according to actual needs. Parameter template management: Improves the consistency and standardization of database parameters and reduces management difficulty. Version control: Conveniently upgrade, downgrade, and roll back the database version to ensure that the database always runs on the appropriate version. Real-time monitoring: Quasi-real-time monitoring of the service node and time series library operation status to ensure that the system is stable and reliable.

[0039] For the aforementioned embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily required by the present application.

[0040] The above embodiments describe the basic principles and main features of the present invention and the advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the changes and modifications made by those skilled in the art shall be within the scope of protection of the appended claims of the present invention without departing from the spirit and scope of the present invention.

Claims

1. An efficient online time series database installation and deployment system, characterized in that: It includes a database management unit and a server node unit. The database management unit is used to upload the database version installation package in segments, and provide the creation, editing and application of parameter templates, and create a stand-alone or cluster time series database instance according to the information entered by the user; The server node unit is used to uniformly manage the server nodes and ensure that the database runs in a stable environment.

2. The efficient online time series database installation and deployment system according to claim 1, characterized in that: The database management unit includes a database version management module, which is used to upload the database version installation package in pieces. The installation package includes two parts, one is the database installation program and script itself, and the other is the parameter template of the database version; the piece-by-piece uploading is: first upload the pieces and merge the completed files, then take out the parameter template file, and parse out the parameter list of the database version, the parameters in the parameter list include one or more of the parameter name, parameter default value, parameter recommended value and parameter description.

3. The efficient online time series database installation and deployment system according to claim 2, characterized in that: The database management unit also includes a database version parameter template management module, which is used to create, edit and apply parameter templates, and ensure the consistency and standardization of database parameters through template management.

4. The efficient online time series database installation and deployment system according to claim 3, characterized in that: The database management unit also includes a database instance management module, which creates a single-machine or cluster time series database instance according to information input by a user, thereby reducing the manual configuration process.

5. The efficient online time series database installation and deployment system according to claim 1, characterized in that: The server node unit includes a server node management module, which is used to uniformly manage server nodes, including: one or more of node name, node IP, node port number, node status, node user name and node authentication method.

6. The efficient online time series database installation and deployment system according to claim 5, characterized in that: The server node unit also includes a server node environment monitoring tool module, which includes operating system monitoring, network monitoring and storage monitoring to ensure that the database runs in a stable environment. By selecting a server node, the user automatically adapts a list of time series database versions that can be installed on the node.

7. An efficient online time series database installation and deployment method, implemented based on an efficient online time series database installation and deployment system according to any one of claims 1 to 6, characterized in that: The steps include: Install the database version by uploading in pieces; Configure the database version parameter template; Manage and monitor server nodes in real time; Create a time series database instance.

8. The efficient online time series database installation and deployment method according to claim 7, characterized in that: Configuring the database version parameter template includes the following steps: Configuration parameter name; Select the database version, and the parameter list of the corresponding database version will be automatically displayed; User saved.

9. The efficient online time series database installation and deployment method according to claim 7, characterized in that: Managing server nodes and real-time monitoring includes the following steps: Configure the information required for node management. After the configuration is completed, perform a connection test based on the configuration information, using jsch technology to implement it; At preset intervals, these configured node information is monitored in real time. First, according to the configuration information, jsch technology is used to connect to the node server to obtain the session. Then, the shell script path of the external configuration file is dynamically obtained to obtain the InputStream stream of the file. The IoUtil.readUtf8 method is used to obtain the shell script content in the InputStream stream. Finally, jsch is used to execute the exec command to execute the general shell script. After successful execution, the execution success information is returned. This information is parsed to obtain the node operating system type, CPU architecture type, CPU information, memory information and disk information, so as to realize real-time monitoring of the server node information.

10. The efficient online time series database installation and deployment method according to claim 7, characterized in that: Creating a time series database instance includes the following steps: The user enters the instance name and selects the service type; The user selects a service node, triggers the service environment detection tool, and automatically identifies the appropriate time series database version; According to the automatically adapted time series database version, obtain the database version parameter template list; Once the user saves the data, the system automatically creates a database instance on the server.

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