CN110688125A - Deployment method and system of big data platform - Google Patents
Deployment method and system of big data platform Download PDFInfo
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- CN110688125A CN110688125A CN201910804121.4A CN201910804121A CN110688125A CN 110688125 A CN110688125 A CN 110688125A CN 201910804121 A CN201910804121 A CN 201910804121A CN 110688125 A CN110688125 A CN 110688125A
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Abstract
The invention discloses a deployment method of a big data platform, wherein in the deployment process of the big data platform, sub-modules in the big data platform are installed, and the installation progress information of the sub-modules in the big data platform is stored; if the sub-modules in the big data platform fail to be installed, acquiring installation progress information of the sub-modules in the big data platform; analyzing the position information of a target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform; according to the position information, skipping the sub-modules in the successfully installed big data platform, and reinstalling the target sub-modules from the positions where the installation fails, so that the deployment time of the big data platform is reduced, and the deployment efficiency of the data platform is improved; the invention also provides a deployment system of the big data platform.
Description
Technical Field
The present application relates to the field of big data platforms, and in particular, to a deployment method and system for a big data platform.
Background
In the big data era, people increasingly rely on big data platforms. The large data platform needs a technician to deploy the large data platform, in the deployment process of the large data platform, after the configuration of the cluster environment is completed, the node environment module, the database module, the configuration module and the starting module need to be installed, the condition of installation failure can occur in the installation process of the sub-modules in the large data platform, once the condition of installation failure occurs, all the sub-modules in the large data platform need to be restarted to be installed, the parts which are successfully installed cannot be skipped, the parts which are successfully installed are subjected to secondary installation, the deployment time of the large data platform is prolonged, and the deployment efficiency of the large data platform is reduced.
Disclosure of Invention
In view of the above, a deployment method and system for a big data platform are needed.
The invention provides a deployment method of a big data platform, which comprises the following steps:
installing the sub-modules in the big data platform, and storing installation progress information of the sub-modules in the big data platform;
if the sub-modules in the big data platform fail to be installed, acquiring installation progress information of the sub-modules in the big data platform;
analyzing the position information of a target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform;
and skipping the sub-modules in the successfully installed big data platform according to the position information, and reinstalling the target sub-modules from the positions where the installation fails.
Optionally, the method further includes:
and if the target sub-module is successfully reinstalled, continuing to install the next sub-module of the target sub-module in the big data platform.
Optionally, after analyzing the position information of the sub-module in the big data platform with failed installation according to the installation progress information of the sub-module in the big data platform, the method further includes:
skipping the position of the failed installation, and continuing to install from the next sub-module of the target sub-module in the big data platform;
and after the installation is finished, the step of skipping the sub-modules in the successfully installed big data platform according to the position information and reinstalling the target sub-modules from the positions where the installation fails is executed.
Optionally, the sub-modules in the big data platform are:
any combination of the node environment module, the database module, the configuration module and the starting module.
Optionally, before the installing the big data platform sub-module, the method further includes:
acquiring information input by a user, calling a preset program, generating configuration information from the information input by the user, and configuring the cluster environment by using the configuration information.
The invention also provides a deployment system of the big data platform, which comprises the following components:
the device comprises an installation unit, an acquisition unit and an analysis unit;
the installation unit is used for installing the sub-modules in the big data platform and storing the installation progress information of the sub-modules in the big data platform;
the obtaining unit is used for obtaining the installation progress information of the sub-modules in the big data platform if the installation unit fails to install the sub-modules in the big data platform;
the analysis unit is used for analyzing the position information of the target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform acquired by the acquisition unit, and calling the installation unit, and the installation unit skips the sub-modules in the big data platform which are successfully installed according to the position information and reinstalls the target sub-module from the position with failed installation.
Optionally, the mounting unit is further configured to:
and if the target sub-module is successfully reinstalled, continuing to install the next sub-module of the target sub-module in the big data platform.
Optionally, the mounting unit is further configured to:
skipping the position of the failed installation, and continuing to install from the next sub-module of the target sub-module in the big data platform;
and after the installation is finished, the operation of skipping the sub-modules in the successfully installed big data platform according to the position information and reinstalling the target sub-modules from the positions where the installation fails is executed.
Optionally, the sub-modules in the big data platform are:
any combination of the node environment module, the database module, the configuration module and the starting module.
Optionally, the deployment system of the big data platform further includes:
the configuration unit is used for acquiring information input by a user, calling a preset program, generating configuration information from the information input by the user, and configuring the cluster environment by using the configuration information.
Compared with the prior art, the invention has at least the following advantages:
the invention provides a deployment method of a big data platform, which is characterized in that in the installation process of sub-modules in the big data platform, the installation progress information of the sub-modules in the big data platform is saved, when at least one sub-module in the big data platform fails to be installed, the installation progress information of the sub-module is obtained, the installation progress information of the sub-module is analyzed to obtain the position information of the sub-module, according to the position information, skipping the sub-modules in the successfully installed big data platform, and reinstalling the sub-modules from the positions of the sub-modules, thereby avoiding the problems that in the prior art, once at least one of the sub-modules in the big data platform fails to be installed, all the sub-modules in the big data platform need to be installed again, so that the deployment time of the big data platform is reduced, and the deployment efficiency of the big data platform is improved.
Furthermore, before the sub-modules in the big data platform are installed, the configuration of the cluster environment by using the configuration files is automatically completed by calling the relevant background programs, so that the problem that in the prior art, technicians need to manually upload the configuration files to configure the cluster environment is avoided, the deployment time of the big data platform is further reduced, and the deployment efficiency of the big data platform is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a flowchart of a deployment method of a big data platform according to an embodiment of the present disclosure;
fig. 2 is a flowchart of another deployment method for a big data platform according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a deployment method of a big data platform according to an embodiment of the present disclosure;
fig. 4 is a flowchart of a deployment method of a big data platform according to an embodiment of the present disclosure;
fig. 5 is a diagram of an example of a deployment system of a big data platform according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present invention better understood by those skilled in the art, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides a deployment method of a big data platform, in the deployment process of the big data platform, after the cluster environment configuration is completed, a node environment module, a database module, a configuration module and a starting module need to be installed, the condition of installation failure can occur in the installation process of sub-modules in the big data platform, because the installation progress information of the sub-modules in the big data platform is not stored in the prior art, once the condition of installation failure occurs, all the sub-modules in the big data platform need to be restarted to be installed, the successfully installed parts cannot be skipped, the successfully installed parts are subjected to secondary installation, and the deployment efficiency of the big data platform is reduced. Therefore, the application provides a deployment method of the big data platform, so as to reduce the deployment time of the big data platform and improve the deployment efficiency of the big data platform.
The first embodiment of the method comprises the following steps:
referring to fig. 1, the figure is a flowchart of a deployment method of a big data platform according to an embodiment of the present application.
The deployment method of the big data platform provided by the embodiment of the application comprises the following steps:
step 101: and installing the sub-modules in the big data platform, and storing the installation progress information of the sub-modules in the big data platform.
In the optional method, the sub-modules in the big data platform are installed by calling corresponding programs of the background, and the installation progress information of the sub-modules in the big data platform is stored.
As an implementation mode, a background installation program is called, a node environment module, a database module, a configuration module and a starting module are installed, and installation progress information of the node environment module, the database module, the configuration module and the starting module is stored.
It should be noted that the sub-module in the big data platform may be a combination of any of the node environment module, the database module, the configuration module, and the start module.
Step 102: and if the sub-modules in the big data platform fail to be installed, acquiring installation progress information of the sub-modules in the big data platform.
In the process of installing the sub-modules in the big data platform, if the sub-modules in the big data platform are failed to be installed, the installation progress information of the sub-modules in the big data platform, which is saved in the step 101, is obtained.
As an implementation manner, in the process of installing the node environment module, the database module, the configuration module, and the start module, if it is detected that the database module is installed unsuccessfully, the installation progress information of the sub-module in the big data platform, which is saved in step 101, is obtained.
It should be noted that the module that fails to be installed may also be at least one of the node environment module, the configuration module, and the start module.
Step 103: and analyzing the position information of the target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform.
And analyzing the position information of the target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform obtained in the step 102.
As an implementation manner, when the database module is failed to be installed, the position information of the database module is analyzed according to the installation progress information of the sub-module in the big data platform acquired in the step 102.
It should be noted that the module that fails to be installed may also be at least one of the node environment module, the configuration module, and the start module, and the target sub-module is a sub-module in the big data platform that fails to be installed.
Step 104: and skipping the sub-modules in the successfully installed big data platform according to the position information, and reinstalling the target sub-modules from the positions where the installation fails.
And skipping the sub-modules in the successfully installed big data platform according to the position information obtained in the step 103, not performing secondary installation on the sub-modules, and reinstalling the sub-modules with failed installation from the positions with failed installation.
As an implementation manner, according to the position information of the database module analyzed in step 103, the sub-module in the large data platform that has been successfully installed is skipped, and the database module is reinstalled.
It should be noted that the target module is a module that fails to be installed, and the target module in the above embodiment may be at least one of the node environment module, the database module, the configuration module, and the start module, which is not limited herein.
The second method embodiment:
referring to fig. 2, in the deployment method of the big data platform provided in the embodiment of the present application, on the basis of the first method embodiment, after step 204, there are added:
step 205: and if the target sub-module is successfully reinstalled, continuing to install the next sub-module of the target sub-module in the big data platform.
And after the target sub-module is successfully reinstalled, continuing to install the next sub-module of the target sub-module.
As an embodiment, the target sub-module may be the database module, and if the database module is installed successfully after being reinstalled, the target sub-module continues to be installed from a next sub-module of the database module.
It should be noted that the target sub-module may also be at least one of the node environment module, the configuration module and the start module, the write-one sub-module may be another sub-module except the target module, and if the target module is the database module, the next sub-module may be any one of the node environment module, the configuration module and the start module.
The third method embodiment:
referring to fig. 3, in the deployment method of the big data platform provided in the embodiment of the present application, on the basis of the first method embodiment, after step 303, there are added:
step 304: and skipping the position of the failed installation, and continuing the installation from the next submodule of the target submodule in the big data platform.
And after the position information of the target sub-module in the big data platform is obtained, skipping the target sub-module, and continuing to install from the next sub-module of the target sub-module.
As an embodiment, the target sub-module may be the database module, and during the process of installing the sub-module in the large data platform, the database module is skipped, and the next sub-module of the database module is started to be installed continuously.
The method comprises the following steps:
referring to fig. 4, in the deployment method of the big data platform provided in the embodiment of the present application, on the basis of the first method embodiment, before the sub-modules in the big data platform are installed, the following steps are added:
step 401: acquiring information input by a user, calling a second preset program, generating configuration information from the information input by the user, and configuring the cluster environment by using the configuration information.
In an optional method, the acquiring of the information input by the user may be information input on a human-computer interaction UI interface, call a corresponding program in a background, process the acquired information input by the user, and then configure the cluster environment by using the processed information.
As an implementation mode, a user inputs a user name, a password, an installation package name and node network IP address information on a webpage interface, clicks a submission button on a webpage, calls a background program, generates a configuration file by using the user name, the password, the installation package name and the node network IP address information, and automatically completes the configuration of a cluster environment according to the configuration file.
In the deployment method of the big data platform provided by the embodiment of the application, in the installation process of the sub-modules in the big data platform, the installation progress information of the sub-modules in the big data platform is stored, when at least one sub-module in the big data platform fails to be installed, the installation progress information of the sub-module is obtained, the installation progress information of the sub-module is analyzed to obtain the position information of the sub-module, according to the position information, skipping the sub-modules in the successfully installed big data platform, and reinstalling the sub-modules from the positions of the sub-modules, thereby avoiding the problems that in the prior art, once at least one of the sub-modules in the big data platform fails to be installed, all the sub-modules in the big data platform need to be installed again, so that the deployment time of the big data platform is reduced, and the deployment efficiency of the big data platform is improved. Furthermore, before the sub-modules in the big data platform are installed, the configuration of the cluster environment by using the configuration files is automatically completed by calling the relevant background programs, so that the problem that in the prior art, technicians need to manually upload the configuration files to configure the cluster environment is avoided, the deployment time of the big data platform is further reduced, and the deployment efficiency of the big data platform is improved.
Based on the deployment method of the big data platform provided above, the embodiment of the present application further provides a deployment system of the big data platform, which will be explained and explained below with reference to the accompanying drawings.
The embodiment of the system is as follows:
referring to fig. 5, the deployment system of a big data platform provided in the embodiment of the present application includes: an installation unit 501, an acquisition unit 502, a parsing unit 503, and a configuration unit 504.
The installation unit 501 is configured to install the sub-modules in the big data platform, and store installation progress information of the sub-modules in the big data platform.
As an implementation manner, the installation unit 501 invokes a background installation program, installs the node environment module, the database module, the configuration module, and the start module, and stores installation progress information of the node environment module, the database module, the configuration module, and the start module.
The obtaining unit 502 is configured to obtain installation progress information of the sub-modules in the big data platform if the installation unit fails to install the sub-modules in the big data platform;
as an implementation manner, in the process of installing the node environment module, the database module, the configuration module, and the start module, if it is detected that the database module is installed unsuccessfully, the installation progress information of the sub-module in the big data platform, which is saved in step 101, is obtained.
The analyzing unit 503 is configured to analyze position information of a target sub-module in the big data platform, where the installation fails, according to the installation progress information of the sub-module in the big data platform, which is obtained by the obtaining unit, and call the installing unit 501, where the installing unit 501 skips the sub-module in the big data platform, which has been successfully installed, according to the position information, and reinstalls the target sub-module from the position where the installation fails.
As an implementation manner, the target sub-module is a sub-module in the large digital platform that fails to be installed, the target sub-module may be the database module, the analyzing unit 503 analyzes the position of the database module according to the installation progress information of the database module obtained by the obtaining unit 502, the installing unit 501 is called, and the installing unit 501 skips over a sub-module in the large digital platform that has been successfully installed, and reinstalls the database module.
The configuration unit 504 is configured to obtain information input by a user, invoke a second preset program, generate configuration information from the information input by the user, and configure the cluster environment by using the configuration information by the configuration unit 504.
As an implementation manner, a user inputs a user name, a password, an installation package name, and node network IP address information on a web interface, clicks a submit button on a web page, calls a background program, generates a configuration file by using the user name, the password, the installation package name, and the node network IP address information, and the configuration unit 504 automatically completes configuration of a cluster environment according to the configuration file.
In an optional method, the installation unit 501 is further configured to skip a location where installation fails, and continue installation from a next sub-module of the target sub-module in the big data platform;
and after the installation is finished, the operation of skipping the sub-modules in the successfully installed big data platform according to the position information and reinstalling the target sub-modules from the positions where the installation fails is executed.
In an optional method, the installation unit 501 is further configured to continue installation from a next sub-module of the target sub-module in the big data platform if the target sub-module is re-installed successfully.
It should be noted that the target sub-module is a sub-module in the large digital platform that fails to be installed, and may be at least one of the node environment module, the database module, the configuration module, and the start module.
The deployment system of the big data platform provided by the embodiment of the application comprises: an installation unit 501, an acquisition unit 502, an analysis unit 503, and a configuration unit 504, where the installation unit 501 installs any combination of the node environment module, the database module, the configuration module, and the boot module, and stores installation progress information of the node environment module, the database module, the configuration module, and the boot module, when at least one of the node environment module, the database module, the configuration module, and the boot module fails to be installed, the acquisition unit 502 acquires the installation progress information, the analysis unit 503 analyzes position information of a sub-module in the large data platform that fails to be installed according to the installation progress information, the installation unit 501 skips a part that has been successfully installed according to the position information, and re-installs the sub-module in the large data platform that fails to be installed from a position where the installation fails, the deployment time of the big data platform is reduced, and the deployment efficiency of the big data platform is improved. Further, the configuration unit 504 generates a configuration file according to the parameter information input by the user by calling the background program, and automatically completes the configuration of the cluster environment according to the configuration file, thereby reducing manual operation, further reducing the deployment time of the big data platform, and increasing the deployment efficiency of the big data platform.
It should be noted that, in the present specification, all the embodiments are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system and apparatus embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related aspects. The above-described embodiments of the system and apparatus are merely illustrative, and units described as separate parts may or may not be physically separate, and parts shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner. Although the preferred embodiments of the present invention have been described above, the present invention is not limited thereto. Those skilled in the art can make many possible variations and modifications to the disclosed embodiments, or modify equivalent embodiments, using the methods and techniques disclosed above, without departing from the scope of the claimed embodiments. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the protection scope of the technical solution of the present invention, unless the content of the technical solution of the present invention is departed from.
Claims (10)
1. A deployment method of a big data platform is characterized by comprising the following steps:
installing the sub-modules in the big data platform, and storing installation progress information of the sub-modules in the big data platform;
if the sub-modules in the big data platform fail to be installed, acquiring installation progress information of the sub-modules in the big data platform;
analyzing the position information of a target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform;
and skipping the sub-modules in the successfully installed big data platform according to the position information, and reinstalling the target sub-modules from the positions where the installation fails.
2. The method of claim 1, further comprising:
and if the target sub-module is successfully reinstalled, continuing to install the next sub-module of the target sub-module in the big data platform.
3. The method according to claim 1, wherein after analyzing the position information of the sub-module in the big data platform with failed installation according to the installation progress information of the sub-module in the big data platform, the method further comprises:
skipping the position of the failed installation, and continuing to install from the next sub-module of the target sub-module in the big data platform;
and after the installation is finished, the step of skipping the sub-modules in the successfully installed big data platform according to the position information and reinstalling the target sub-modules from the positions where the installation fails is executed.
4. The method of claim 1, wherein the sub-modules in the big data platform are:
any combination of the node environment module, the database module, the configuration module and the starting module.
5. The method of claim 1, further comprising, prior to said installing the big data platform sub-module:
acquiring information input by a user, calling a preset program, generating configuration information from the information input by the user, and configuring the cluster environment by using the configuration information.
6. A deployment system for a big data platform, comprising:
the device comprises an installation unit, an acquisition unit and an analysis unit;
the installation unit is used for installing the sub-modules in the big data platform and storing the installation progress information of the sub-modules in the big data platform;
the obtaining unit is used for obtaining the installation progress information of the sub-modules in the big data platform if the installation unit fails to install the sub-modules in the big data platform;
the analysis unit is used for analyzing the position information of the target sub-module in the big data platform with failed installation according to the installation progress information of the sub-modules in the big data platform acquired by the acquisition unit, and calling the installation unit, and the installation unit skips the sub-modules in the big data platform which are successfully installed according to the position information and reinstalls the target sub-module from the position with failed installation.
7. The system of claim 6, wherein the mounting unit is further configured to:
and if the target sub-module is successfully reinstalled, continuing to install the next sub-module of the target sub-module in the big data platform.
8. The system of claim 6, wherein the mounting unit is further configured to:
skipping the position of the failed installation, and continuing to install from the next sub-module of the target sub-module in the big data platform;
and after the installation is finished, the operation of skipping the sub-modules in the successfully installed big data platform according to the position information and reinstalling the target sub-modules from the positions where the installation fails is executed.
9. The system of claim 6, wherein the sub-modules in the big data platform are:
any combination of the node environment module, the database module, the configuration module and the starting module.
10. The system of claim 6, further comprising:
the configuration unit is used for acquiring information input by a user, calling a preset program, generating configuration information from the information input by the user, and configuring the cluster environment by using the configuration information.
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Application publication date: 20200114 |