CN114756252A - Method, device, equipment and medium for installing and configuring client outside big data cluster - Google Patents

Method, device, equipment and medium for installing and configuring client outside big data cluster Download PDF

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Publication number
CN114756252A
CN114756252A CN202210395805.5A CN202210395805A CN114756252A CN 114756252 A CN114756252 A CN 114756252A CN 202210395805 A CN202210395805 A CN 202210395805A CN 114756252 A CN114756252 A CN 114756252A
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big data
client
data cluster
target
client node
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刘洋
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Jinan Inspur Data Technology Co Ltd
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Jinan Inspur Data Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/60—Software deployment
    • G06F8/61—Installation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/34—Network arrangements or protocols for supporting network services or applications involving the movement of software or configuration parameters 

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Abstract

The application discloses a method, a device, equipment and a medium for installing and configuring a client outside a big data cluster, wherein the method comprises the following steps: acquiring preset configuration information of a big data cluster, and configuring client nodes outside the big data cluster by using the preset configuration information; installing a target client corresponding to a target big data service in the big data cluster on the client node, and configuring the client node by using a configuration file of the target big data service; and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster. By the method and the device, the client nodes outside the big data cluster are configured, the client installation configuration efficiency and the usability outside the big data cluster are improved, the execution efficiency of the task to be operated is improved, and the error risk is reduced.

Description

Method, device, equipment and medium for installing and configuring client outside big data cluster
Technical Field
The invention relates to the technical field of big data, in particular to a method, a device, equipment and a medium for installing and configuring a client outside a big data cluster.
Background
With the continuous enlargement of the large data cluster scale, the running tasks are continuously increased, so that the business program related to the business to be shipped can be more quickly submitted to the large data cluster, and the requirement on the client side outside the large data cluster is more prominent. The current installation and configuration method of a client outside a big data cluster is complex and messy, and has no unified method and steps, so that the problems of low overall working efficiency, high installation and configuration difficulty, difficulty in troubleshooting and the like are caused.
In summary, how to provide a uniform client installation configuration method for a client node outside a big data cluster is a problem to be solved at present.
Disclosure of Invention
In view of this, an object of the present invention is to provide a method, an apparatus, a device, and a medium for client installation configuration outside a big data cluster, which can provide a unified method for client installation configuration for client nodes outside the big data cluster. The specific scheme is as follows:
in a first aspect, the present application discloses a method for installing and configuring a client outside a big data cluster, including:
acquiring preset configuration information of a big data cluster, and configuring client nodes outside the big data cluster by using the preset configuration information;
Installing a target client corresponding to a target big data service in the big data cluster on the client node, and configuring the client node by using a configuration file of the target big data service;
and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster.
Optionally, the obtaining of the preset configuration information of the big data cluster includes:
and acquiring local source information, domain name information, JDK version information and system time of the big data cluster to obtain preset configuration information.
Optionally, the configuring, by using the preset configuration information, the client node outside the big data cluster includes:
updating a current local source of the client node with the local source information;
obtaining a host list comprising the domain name information and adding the host list to the client node;
acquiring a JDK installation package corresponding to the JDK version information, and installing the JDK installation package to the client node;
adjusting the current time of the client node based on the system time.
Optionally, the adjusting the current time of the client node based on the time information includes:
adjusting the current time of the client node based on the system time and using the preset time synchronization software of the client node.
Optionally, in the process of installing, by the client node, a target client corresponding to a target big data service in the big data cluster, the method further includes:
if the number of the target clients corresponding to the target big data service in the big data cluster is multiple, determining the installation sequence among the multiple target clients, and sequentially installing the multiple target clients on the client node based on the installation sequence.
Optionally, the method for installing and configuring a client outside the big data cluster further includes:
establishing a privacy-free communication between the big data cluster and the client node.
Optionally, the setting, by a global variable, the command of the target client to a global command so that before the target client accesses the big data cluster by the global command, further includes:
monitoring the working state of a firewall of the client node;
And if the working state is the opening state, closing the firewall so that the target client can access the big data cluster through the global command.
In a second aspect, the present application discloses a client installation configuration apparatus outside a big data cluster, including:
the information configuration module is used for acquiring preset configuration information of the big data cluster and configuring client nodes outside the big data cluster by using the preset configuration information;
the client installation module is used for installing a target client corresponding to a target big data service in the big data cluster on the client node and configuring the client node by using a configuration file of the target big data service;
and the command setting module is used for setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster.
In a third aspect, the present application discloses an electronic device, comprising:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the client installation configuration method outside the big data cluster disclosed in the foregoing.
In a fourth aspect, the present application discloses a computer readable storage medium for storing a computer program; wherein the computer program when executed by a processor implements the steps of the above-disclosed client installation configuration method outside a big data cluster.
Therefore, the method and the device for configuring the client nodes outside the big data cluster acquire the preset configuration information of the big data cluster, and configure the client nodes outside the big data cluster by using the preset configuration information; installing a target client corresponding to a target big data service in the big data cluster on the client node, and configuring the client node by using a configuration file of the target big data service; and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster. Therefore, the method includes the steps of firstly obtaining preset configuration information of a big data cluster, configuring client nodes outside the big data cluster by using the preset configuration information, then installing target clients corresponding to target big data services on the client nodes, configuring the client nodes by using corresponding configuration files, and finally setting commands of the target clients as global commands so that the client nodes can access the big data cluster through the global commands and submit corresponding tasks to be run. Therefore, by the unified client installation configuration method outside the big data cluster, the client installation configuration efficiency and the usability are improved, the execution efficiency of the task to be operated is effectively improved, and the error risk is reduced.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a client installation configuration method outside a big data cluster according to the present disclosure;
FIG. 2 is a flow chart of a specific method for configuring client installation outside a big data cluster, as disclosed herein;
FIG. 3 is a schematic diagram of a specific big data cluster external client installation configuration disclosed in the present application;
FIG. 4 is a schematic diagram of a client installation configuration device outside a big data cluster according to the present disclosure;
fig. 5 is a block diagram of an electronic device disclosed in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present invention, and not all 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 current installation and configuration method of a client outside a big data cluster is complex and disorderly, and has no unified method and steps, so that the problems of low overall working efficiency, high installation and configuration difficulty, difficulty in troubleshooting and the like are caused. Therefore, the embodiment of the application discloses a method, a device, equipment and a medium for installing and configuring a client outside a big data cluster, and can provide a uniform method for installing and configuring the client aiming at a client node outside the big data cluster.
Referring to fig. 1, an embodiment of the present application discloses a client installation configuration method outside a big data cluster, where the method includes:
step S11: the method comprises the steps of obtaining preset configuration information of a big data cluster, and configuring client nodes outside the big data cluster by utilizing the preset configuration information.
In this embodiment, it is necessary to obtain preset configuration information of the big data cluster, and configure a client node outside the big data cluster by using the preset configuration information, so that the configured relevant parameter information of the client node corresponds to the parameter information of the big data cluster for subsequent communication.
Step S12: and installing a target client corresponding to the target big data service in the big data cluster on the client node, and configuring the client node by using the configuration file of the target big data service.
In this embodiment, according to actual needs, a corresponding target client is installed in the client node, where the target client is a client corresponding to a target big data service in a big data cluster. And then finding a configuration file corresponding to the target big data service in the big data cluster, and configuring the client node by using the configuration file, namely synchronously configuring the big data service in the big data cluster to the client node so that the client node can normally access the service in the big data cluster.
Step S13: and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster.
In this embodiment, in order to facilitate the target client to submit the task to the big data cluster, the command of the target client needs to be set as the global command through the global variable, so that the target client accesses the big data cluster through the global command and submits the task to be executed to the big data cluster. It should be noted that, before the setting the command of the target client as the global command through the global variable so that the target client accesses the big data cluster through the global command, the method further includes: monitoring the working state of a firewall of the client node; and if the working state is the opening state, closing the firewall so that the target client accesses the big data cluster through the global command. It will be appreciated that the present embodiment requires the firewall of the client node to be shut down to secure the client node's communication access with the large data cluster. Specifically, the working state of the firewall of the client node is monitored first, and if the working state of the firewall is the open state, the firewall is closed. The firewall may also be ensured to be in a closed state by disabling SELinux and looking at the SELinux state. The SELinux is a Mandatory Access Control (MAC) system provided in the Linux kernel.
In this embodiment, the method for installing and configuring a client outside a big data cluster further includes: establishing a privacy-free communication between the big data cluster and the client node. Because the client node and the same system as the cluster node are installed and the IP address and hostname (host name) are configured, in order to ensure the cluster node to communicate with the client node network, the management node of the big data cluster is configured with the secret by ssh-copy-id root @ clientIP, wherein the clientIP is the IP address of the client node. In this way, normal communication between all nodes of the cluster and the client node is ensured.
Therefore, the method and the device for configuring the client nodes outside the big data cluster acquire the preset configuration information of the big data cluster, and configure the client nodes outside the big data cluster by using the preset configuration information; installing a target client corresponding to a target big data service in the big data cluster on the client node, and configuring the client node by using a configuration file of the target big data service; and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster. Therefore, the method includes the steps of firstly obtaining preset configuration information of a big data cluster, configuring client nodes outside the big data cluster by using the preset configuration information, then installing target clients corresponding to target big data services on the client nodes, configuring the client nodes by using corresponding configuration files, and finally setting commands of the target clients as global commands so that the client nodes can access the big data cluster through the global commands and submit corresponding tasks to be run. Therefore, by the unified client installation configuration method outside the big data cluster, the client installation configuration efficiency and the usability are improved, the execution efficiency of the task to be operated is effectively improved, and the error risk is reduced.
Referring to fig. 2, the embodiment of the present application discloses a specific method for configuring client installation outside a big data cluster, and compared with the previous embodiment, the present embodiment further describes and optimizes the technical solution. The method specifically comprises the following steps:
step S21: and acquiring local source information, domain name information, JDK version information and system time of the big data cluster to obtain preset configuration information.
In this embodiment, the preset configuration information may include, but is not limited to, local source information, domain name information, JDK version information, and system time of the big data cluster, and specifically, refer to fig. 3.
Step S22: updating a current local source of the client node with the local source information.
In this embodiment, a local source of the cluster needs to be configured at the client node, so as to ensure that the big data service can be downloaded and installed normally. The method specifically comprises the following steps: local sources of the client node are emptied first, and then the local sources of the big data cluster management node are all copied to corresponding positions of the client node to update the current local sources of the client node.
Step S23: obtaining a host list comprising the domain name information and adding the host list to the client node.
In this embodiment, the domain names of all nodes in the cluster need to be configured at the client node, and it is ensured that the client node can access each node in the big data cluster through the domain name, which may specifically be: and viewing host list (hosts list) information at the big data cluster management node, and adding the queried hosts list information to the hosts list of the client node. The hosts table is used for storing the domain names of the commonly used website hosts and the corresponding IP addresses.
Step S24: and acquiring a JDK installation package corresponding to the JDK version information, and installing the JDK installation package to the client node.
In this embodiment, JDK with the same version as that in the cluster needs to be configured at the client node to ensure that the environment variable is available. The method specifically comprises the following steps: querying JDK version information in the big data cluster, acquiring a JDK installation package corresponding to the JDK version information, and downloading a JDK installation package file at a client node; and decompressing the downloaded installation package to a corresponding position, configuring a global environment variable, and detecting and viewing JDK version information.
Step S25: adjusting the current time of the client node based on the system time.
In this embodiment, the adjusting the time of the client node to be consistent with the time in the cluster may include: adjusting the current time of the client node based on the system time and using the preset time synchronization software of the client node. It can be understood that, firstly, the preset time synchronization software is installed on the client node, then the big data cluster management node is set as a time synchronization source, the current time of the client node is controlled to be consistent with the big data cluster time, and the preset time synchronization software is started to keep the time synchronization between the client node and the big data cluster time.
Step S26: and installing a target client corresponding to the target big data service in the big data cluster on the client node, and configuring the client node by using the configuration file of the target big data service.
In this embodiment, in the process of installing, by the client node, the target client corresponding to the target big data service in the big data cluster, the method further includes: if the number of the target clients corresponding to the target big data service in the big data cluster is multiple, determining the installation sequence among the multiple target clients, and sequentially installing the multiple target clients on the client node based on the installation sequence. That is, if the client node needs to install a plurality of target clients corresponding to the big data service, it is necessary to ensure the dependency relationship between the target clients, and install the target clients in sequence according to the dependency relationship, where the dependency relationship indicates the installation sequence between the target clients.
Step S27: and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster.
For a more specific processing procedure of the step S27, reference may be made to corresponding contents disclosed in the foregoing embodiments, and details are not repeated here.
As can be seen, in this embodiment of the present application, the preset configuration information of the big data cluster may include local source information, domain name information, JDK version information, and system time, and the preset configuration information is used to configure the client node, specifically, the local source information is used to update the current local source of the client node; acquiring a host list comprising domain name information, and adding the host list to a client node; acquiring a JDK installation package corresponding to the JDK version information, and installing the JDK installation package to a client node; the current time of the client node is adjusted based on the system time and using the client node's pre-set time synchronization software. And in the process of installing the target clients corresponding to the target big data service in the big data cluster by the client node, if the number of the target clients corresponding to the target big data service in the big data cluster is multiple, determining the installation sequence among the multiple target clients, and sequentially installing the multiple target clients at the client node based on the installation sequence. Therefore, by the unified client installation configuration method outside the big data cluster, the client installation configuration efficiency and the usability are improved, the maintenance cost is reduced, the problem is conveniently checked, the execution efficiency of the task to be operated is effectively improved, the error risk is reduced, and the stability and the usability of the product are improved.
Referring to fig. 4, an embodiment of the present application discloses a client installation configuration apparatus outside a big data cluster, where the apparatus includes:
the information configuration module 11 is configured to acquire preset configuration information of a big data cluster, and configure a client node outside the big data cluster by using the preset configuration information;
a client installation module 12, configured to install, at the client node, a target client corresponding to a target big data service in the big data cluster, and configure the client node by using a configuration file of the target big data service;
and the command setting module 13 is configured to set a command of the target client as a global command through a global variable, so that the target client accesses the big data cluster through the global command and submits a task to be run to the big data cluster.
Therefore, the method and the device for configuring the client nodes outside the big data cluster acquire the preset configuration information of the big data cluster, and configure the client nodes outside the big data cluster by using the preset configuration information; installing a target client corresponding to a target big data service in the big data cluster on the client node, and configuring the client node by using a configuration file of the target big data service; and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster. Therefore, the method includes the steps of firstly obtaining preset configuration information of a big data cluster, configuring client nodes outside the big data cluster by using the preset configuration information, then installing target clients corresponding to target big data services on the client nodes, configuring the client nodes by using corresponding configuration files, and finally setting commands of the target clients as global commands so that the client nodes can access the big data cluster through the global commands and submit corresponding tasks to be run. Therefore, by the unified client installation configuration method outside the big data cluster, the client installation configuration efficiency and the usability are improved, the execution efficiency of the task to be operated is effectively improved, and the error risk is reduced.
In some specific embodiments, the information configuring module 11 may specifically include:
and the information acquisition unit is used for acquiring the local source information, the domain name information, the JDK version information and the system time of the big data cluster so as to obtain the preset configuration information.
In some specific embodiments, the information configuring module 11 may specifically include:
a local source configuration unit for updating a current local source of the client node with the local source information;
a domain name configuration unit, configured to obtain a host list including the domain name information, and add the host list to the client node;
the JDK configuration unit is used for acquiring the JDK installation package corresponding to the JDK version information and installing the JDK installation package to the client node;
a time configuration unit for adjusting the current time of the client node based on the system time.
In some specific embodiments, the time configuration unit may specifically include:
and the time adjusting unit is used for adjusting the current time of the client node based on the system time by utilizing the preset time synchronization software of the client node.
In some specific embodiments, in the process of installing the module 12 by the client, specifically, the method may further include:
And the installation unit is used for determining the installation sequence among the target clients if the number of the target clients corresponding to the target big data service in the big data cluster is multiple, and sequentially installing the target clients in the client node based on the installation sequence.
In some specific embodiments, the installing and configuring device for a client outside the big data cluster may further include:
a privacy-exempt communication unit to establish privacy-exempt communication between the big data cluster and the client node.
In some specific embodiments, before the command setting module 13, the method may further include:
the state monitoring unit is used for monitoring the working state of a firewall of the client node;
and the firewall closing unit is used for closing the firewall if the working state is the opening state so that the target client can access the big data cluster through the global command.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The method specifically comprises the following steps: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input output interface 25, and a communication bus 26. The memory 22 is configured to store a computer program, and the computer program is loaded and executed by the processor 21 to implement relevant steps in the method for configuring a client installation outside a big data cluster executed by an electronic device disclosed in any of the foregoing embodiments.
In this embodiment, the power supply 23 is configured to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and an external device, and a communication protocol followed by the communication interface is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited herein; the input/output interface 25 is configured to acquire external input data or output data to the outside, and a specific interface type thereof may be selected according to specific application requirements, which is not specifically limited herein.
The processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 21 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor, where the main processor is a processor for Processing data in a wake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the display screen. In some embodiments, the processor 21 may further include an AI (Artificial Intelligence) processor for processing a calculation operation related to machine learning.
In addition, the storage 22 is used as a carrier for storing resources, and may be a read-only memory, a random access memory, a magnetic disk or an optical disk, etc., the resources stored thereon include an operating system 221, a computer program 222, data 223, etc., and the storage may be a transient storage or a permanent storage.
The operating system 221 is used for managing and controlling each hardware device on the electronic device 20 and the computer program 222, so as to implement the operation and processing of the mass data 223 in the memory 22 by the processor 21, which may be Windows, Unix, Linux, or the like. The computer program 222 may further include a computer program that can be used to perform other specific tasks in addition to the computer program that can be used to perform the client installation configuration method for large data clusters executed by the electronic device 20 disclosed in any of the foregoing embodiments. The data 223 may include data received by the electronic device and transmitted from an external device, or may include data collected by the input/output interface 25 itself.
Further, an embodiment of the present application further discloses a computer-readable storage medium, where a computer program is stored in the storage medium, and when the computer program is loaded and executed by a processor, the method steps executed in the client installation configuration process outside the big data cluster and disclosed in any of the foregoing embodiments are implemented.
In the present specification, the embodiments are described in a progressive manner, and each embodiment focuses on differences from other embodiments, and the same or similar parts between the embodiments are referred to each other. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should also be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The method, apparatus, device and medium for installing and configuring a client outside a big data cluster provided by the present invention are introduced in detail, and a specific example is applied in the present document to explain the principle and the implementation of the present invention, and the description of the above embodiment is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (10)

1. A client installation configuration method outside a big data cluster is characterized by comprising the following steps:
acquiring preset configuration information of a big data cluster, and configuring client nodes outside the big data cluster by using the preset configuration information;
installing a target client corresponding to a target big data service in the big data cluster on the client node, and configuring the client node by using a configuration file of the target big data service;
and setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster.
2. The method according to claim 1, wherein the obtaining of the preset configuration information of the big data cluster includes:
and acquiring local source information, domain name information, JDK version information and system time of the big data cluster to obtain preset configuration information.
3. The method according to claim 2, wherein the configuring the client node outside the big data cluster by using the preset configuration information includes:
Updating a current local source of the client node with the local source information;
obtaining a host list comprising the domain name information and adding the host list to the client node;
acquiring a JDK installation package corresponding to the JDK version information, and installing the JDK installation package to the client node;
adjusting the current time of the client node based on the system time.
4. The method of claim 3, wherein the adjusting the current time of the client node based on the time information comprises:
adjusting the current time of the client node based on the system time and using the preset time synchronization software of the client node.
5. The method according to claim 1, wherein in the process of installing the target client corresponding to the target big data service in the big data cluster by the client node, the method further comprises:
if the number of the target clients corresponding to the target big data service in the big data cluster is multiple, determining the installation sequence among the multiple target clients, and sequentially installing the multiple target clients on the client node based on the installation sequence.
6. The method for client installation configuration outside a big data cluster according to claim 1, further comprising:
establishing a privacy-free communication between the big data cluster and the client node.
7. The method for client installation configuration outside a big data cluster according to any of claims 1 to 6, wherein before the target client accesses the big data cluster through the global command, the method further comprises:
monitoring the working state of a firewall of the client node;
and if the working state is the opening state, closing the firewall so that the target client accesses the big data cluster through the global command.
8. An installation configuration device for a client outside a big data cluster, comprising:
the information configuration module is used for acquiring preset configuration information of the big data cluster and configuring the client nodes outside the big data cluster by using the preset configuration information;
the client installation module is used for installing a target client corresponding to a target big data service in the big data cluster on the client node and configuring the client node by using a configuration file of the target big data service;
And the command setting module is used for setting the command of the target client to be a global command through a global variable so that the target client can access the big data cluster through the global command and submit a task to be operated to the big data cluster.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for executing the computer program to implement the steps of the client installation configuration method outside a large data cluster according to any of claims 1 to 7.
10. A computer-readable storage medium for storing a computer program; wherein the computer program when executed by a processor implements the steps of a client installation configuration method outside a large data cluster as claimed in any one of claims 1 to 7.
CN202210395805.5A 2022-04-15 2022-04-15 Method, device, equipment and medium for installing and configuring client outside big data cluster Pending CN114756252A (en)

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