CN117806674A - Distributed storage cluster deployment method, electronic equipment and storage medium - Google Patents
Distributed storage cluster deployment method, electronic equipment and storage medium Download PDFInfo
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Abstract
The application provides a distributed storage cluster deployment method, electronic equipment and a storage medium, which relate to the technical field of computers, wherein each data node can be deployed into a corresponding node pool according to the server model and the operating system type of each data node, then a corresponding instance upgrade package is determined according to the node pool corresponding to any data node, and the instance upgrade package is deployed for any data node in the node pool, so that the hybrid deployment of heterogeneous nodes of the distributed storage cluster is realized, the deployment of the instance upgrade package to unmatched data nodes can be prevented, and the problems of downtime, abnormal functions and the like occur after the data node is upgraded are completed.
Description
Technical Field
The present disclosure relates to the field of distributed storage, and in particular, to a distributed storage cluster deployment method, an electronic device, and a storage medium.
Background
Distributed storage is a data storage technology that uses disk space on each machine over a network and forms a virtual storage device from these dispersed storage resources, with data being stored in a dispersed manner on each distributed node.
When an instance upgrade package is deployed for heterogeneous nodes of a distributed storage cluster, once the instance upgrade package is deployed to unmatched data nodes, problems such as downtime and abnormal functions can occur after the data nodes are upgraded.
Disclosure of Invention
In order to solve the problems in the prior art, the embodiment of the application provides a distributed storage cluster deployment method, electronic equipment and a storage medium, which can realize hybrid deployment of heterogeneous nodes of the distributed storage cluster and prevent the problems of downtime, abnormal functions and the like after an instance upgrade package is deployed to unmatched data nodes, which cause the data nodes to be upgraded.
In a first aspect, an embodiment of the present application provides a distributed storage cluster deployment method, applied to a cluster server, where the method includes:
controlling metadata nodes to send deployment request messages to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
controlling the metadata nodes to deploy the data nodes to corresponding node pools based on the server model and the operating system type sent by the data nodes;
and determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool.
In one possible implementation, the node pool includes a software node pool corresponding to an operating system type and a hardware node pool corresponding to a server model.
In a possible implementation manner, the determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool includes:
determining a corresponding cluster software upgrading packet according to a software node pool corresponding to any data node;
deploying the cluster software upgrading package for any data node in the software node pool, so that the data node in the software node pool performs cluster software upgrading;
the cluster software upgrade package is compiled based on an object code segment, wherein the object code segment is a code segment corresponding to an operating system type corresponding to any software node pool.
In a possible implementation manner, the determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool includes:
determining a corresponding server capacity upgrade package according to a hardware node pool corresponding to any data node;
and deploying the server capacity upgrading package for any data node in the hardware node pool, so that the data node in the hardware node pool can carry out server capacity upgrading.
In one possible implementation, before the control metadata node sends the deployment request message to at least one data node, the method further comprises:
setting at least one software node pool, wherein each software node pool in the at least one software node pool corresponds to one operating system type;
setting at least one hardware node pool, wherein each hardware node pool in the at least one hardware node pool corresponds to a server model.
In a second aspect, an embodiment of the present application provides a distributed storage cluster deployment apparatus, where the apparatus includes:
the control unit is used for controlling the metadata nodes to send deployment request messages to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
the first deployment unit is used for controlling the metadata nodes to deploy the data nodes to corresponding node pools based on the server model and the operating system type sent by the data nodes;
and determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool.
In a third aspect, an embodiment of the present application provides a distributed storage cluster deployment method, applied to a metadata node, where the method includes:
sending a deployment request message to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
based on the server model and the operating system type sent by each data node, deploying each data node to a corresponding node pool, so that a cluster server determines a corresponding instance upgrade package according to the node pool corresponding to any data node, and deploys the instance upgrade package for any data node in the node pool.
In a fourth aspect, an embodiment of the present application provides a distributed storage cluster deployment apparatus, where the apparatus includes:
a first sending unit, configured to send a deployment request message to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
the second deployment unit is used for deploying each data node to a corresponding node pool based on the server model and the operating system type sent by each data node, so that the cluster server determines a corresponding instance upgrade package according to the node pool corresponding to any data node, and deploys the instance upgrade package for any data node in the node pool.
In a fifth aspect, an embodiment of the present application provides a distributed storage cluster deployment method, applied to a data node, where the method includes:
receiving a deployment request message sent by a metadata node;
sending a server model and an operating system type to the metadata node;
and receiving an instance upgrade package issued by a cluster server, and upgrading an instance according to the instance upgrade package, wherein the instance upgrade package is issued by the cluster server according to a node pool corresponding to the data node.
In one possible implementation manner, the instance upgrade package includes a cluster software upgrade package and a server capability upgrade package, and the upgrading the instance according to the instance upgrade package includes:
upgrading the cluster software according to the cluster software upgrading package; the cluster software upgrade package is compiled based on a target code segment, wherein the target code segment is a code segment corresponding to an operating system type corresponding to any data node;
and upgrading the server capacity according to the server capacity upgrading packet.
In a sixth aspect, an embodiment of the present application provides a distributed storage cluster deployment apparatus, where the apparatus includes:
the receiving unit is used for receiving the deployment request message sent by the metadata node;
a second sending unit, configured to send a server model and an operating system type to the metadata node;
and the upgrading unit is used for receiving an instance upgrading packet issued by the cluster server and upgrading the instance according to the instance upgrading packet, wherein the instance upgrading packet is issued by the cluster server according to the node pool corresponding to the data node.
In a seventh aspect, embodiments of the present application provide an electronic device comprising a memory and a processor, the memory having stored thereon a computer program executable on the processor, the computer program, when executed by the processor, implementing the method of any of the first aspects.
In an eighth aspect, embodiments of the present application provide a computer-readable storage medium having stored therein a computer program which, when executed by a processor, implements the method of any one of the first aspects.
The technical scheme provided by the embodiment of the application at least brings the following beneficial effects:
according to the distributed storage cluster deployment method, the electronic equipment and the storage medium, each data node can be deployed into the corresponding node pool according to the server model and the operating system type of each data node, the corresponding instance upgrade package is determined according to the node pool corresponding to any data node, the instance upgrade package is deployed for any data node in the node pool, hybrid deployment of heterogeneous nodes of the distributed storage cluster is achieved, the problem that after the data node is upgraded, downtime, abnormal functions and the like are caused can be prevented.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an example of a container/virtual machine deployment cluster according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an example bare metal deployment cluster provided in an embodiment of the present application;
fig. 3 is an application scenario diagram of a distributed storage cluster deployment method provided in an embodiment of the present application;
FIG. 4 is a flowchart of a distributed storage cluster deployment method according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a distributed storage cluster deployment node pool according to an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a distributed storage cluster deployment cluster software upgrade package according to an embodiment of the present application;
FIG. 7 is a schematic diagram of a distributed storage cluster deployment hardware capability upgrade package according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a distributed storage cluster deployment device according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of another distributed storage cluster deployment apparatus according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of another distributed storage cluster deployment apparatus according to an embodiment of the present application;
fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail below with reference to the accompanying drawings, wherein it is apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It should be noted that the terms "comprises" and "comprising," along with their variants, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Distributed storage is a data storage technology that uses disk space on each machine over a network and forms a virtual storage device from these dispersed storage resources, with data being stored in a dispersed manner on each distributed node. Compared with the centralized storage server for storing all data, the distributed storage can meet the requirement of large-scale storage application, and the system reliability, availability and access efficiency are improved, and the system is easy to expand.
Traditional distributed storage cluster deployment methods require that instances be deployed on servers of the same environmental conditions. However, in practical applications, there are scenarios where distributed storage clusters exist with different operating systems, different processor architectures, different server vendors produce different models of physical devices, such as the above-mentioned cluster node hybrid deployment scenario with comprehensive differences. In general, to support hybrid deployment of servers with the above-described differences, virtual machine or container technologies are often employed.
As shown in fig. 1, cluster instances in the cluster nodes may be deployed on a container or virtual machine, which in turn, may be used to adapt underlying server hardware and coordinate server resources to achieve a hybrid deployment of the disparate cluster nodes. However, a container or virtual machine is an executable program, and itself consumes hardware resources of a server such as processor resources and hard disk resources.
As shown in fig. 2, in the distributed storage cluster deployment method provided by the embodiment of the present application, a middle layer such as a container and a virtual machine may not be introduced, so that a cluster instance may be deployed on each data node directly. The cluster instance is directly deployed on the bare machine, so that the starting speed of the cluster instance can be remarkably improved while avoiding the performance loss caused by a container or a virtual machine. However, when an instance upgrade package is deployed for heterogeneous nodes of a distributed storage cluster, once the instance upgrade package is deployed to unmatched data nodes, problems such as downtime and abnormal functions can occur after the data nodes are upgraded.
Based on this, according to the distributed storage cluster deployment method, the electronic device and the storage medium provided by the embodiment of the application, each data node can be deployed into a corresponding node pool according to the server model and the operating system type of each data node, then a corresponding instance upgrade package is determined according to the node pool corresponding to any data node, and the instance upgrade package is deployed for any data node in the node pool, so that hybrid deployment of heterogeneous nodes of the distributed storage cluster is realized, and the problem that downtime, abnormal functions and the like occur after the data node is upgraded is prevented from being deployed to unmatched data nodes.
In the following, some simple descriptions are first provided for application scenarios applicable to the technical solutions of the embodiments of the present application, and it should be noted that the application scenarios described below are only used to illustrate the embodiments of the present application and are not limiting. In specific implementation, the technical scheme provided by the embodiment of the application can be flexibly applied according to actual needs.
Referring to fig. 3, an application scenario diagram of an embodiment of the present application is shown. The user 10 can log in to a cluster platform maintained by a cluster server through client software installed in the user equipment 11 to complete the deployment of the distributed storage cluster.
The client may be a browser of a web page, or may be an application client installed in a mobile user device, such as a mobile phone, a tablet computer, or the like.
The user equipment 11 and the metadata node 12 are communicatively connected by a network, which may be a local area network, a wide area network, etc. The user equipment 11 may be a convenient device (e.g. a mobile phone, a tablet, a notebook, etc.), or may be a personal computer (PC, personal Computer), and the metadata node 12 and the data node 13 may be any device capable of providing internet services.
One possible form of communication between the user device 11 and the metadata server 12 is that the user 10 may log onto the cluster platform, send a data operation instruction of the user to the metadata server 12 through the communication network, and perform a corresponding data operation on the data node 13 connected to the metadata server 12 according to the data operation instruction.
Fig. 4 shows a flowchart of a distributed storage cluster deployment method provided in an embodiment of the present application, where the method may be applied to a cluster server that maintains a cluster platform, as shown in fig. 4, and the distributed storage cluster deployment method may include the following steps:
in step S401, the control metadata node sends a deployment request message to at least one data node, so that each data node sends a server model and an operating system type to the metadata node.
In an optional implementation manner, when the distributed storage cluster is a nano-tube cluster node, the metadata node can be controlled to actively send a deployment request message to the data node through a network, the data node with a cluster instance receives the deployment request message, the self server model and the operating system type can be sent to the metadata node, the metadata node receives the server model and the operating system type sent by the data node, the server model and the operating system type are configured in the cluster instance, the nano-tube flow of the cluster node is completed, and the node is online.
In step S402, the control metadata node deploys each data node to a corresponding node pool based on the server model and the operating system type sent by each data node.
The distributed storage cluster has only one independent capacity pool, and after the cluster nodes are online, the distributed storage cluster can uniformly incorporate the storage capacity of each data node into the capacity pool management. Further, each data node can be deployed to a corresponding node pool for management respectively according to the type of the server and the type of the operating system sent by each data node.
The node pool is used for mounting each data node according to the type of the server and the type of the operating system sent by each data node.
Illustratively, the node pool may be divided into a software node pool and a hardware node pool, the software node pool may be divided according to the operating system, and specifically, data nodes of the same operating system may be divided into the same software node pool. The hardware node pool can be divided according to server hardware information, and specifically, data nodes with the same server model can be divided into the same hardware node pool.
The following takes fig. 5 as an example to describe in detail the deployment mode of the distributed storage cluster node pool in the embodiment of the present application. For ease of illustration, the data nodes above are described as nodes.
Fig. 5 is a schematic diagram of a distributed storage cluster deployment node pool according to an embodiment of the present application, where, as shown in fig. 5, an operating system configured by a node 1 and a node 2 is an operating system a, and an operating system configured by a node 3 and a node 4 is an operating system B, then the node 1 and the node 2 are allocated to the software node pool 1, and the node 3 and the node 4 are allocated to the software node pool 2. Then, a hardware node pool is allocated to each node, the server model of the node 1 is X, then the node 1 can be allocated to the hardware node pool 1, the server models of the node 2, the node 3 and the node 4 are Y, and then the node 2, the node 3 and the node 4 can be allocated to the hardware node pool 2.
It should be specifically noted that the operating system may include, but is not limited to, various mainstream operating systems, such as CentOS, ubuntu, openEuler, and the like, and similarly, the server model may be a product model corresponding to different physical devices produced by various server manufacturers, which is not limited in this application.
Step S403, determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool.
In an optional implementation manner, after each data node is deployed to a corresponding node pool, a corresponding software cluster package can be determined according to a software node pool corresponding to any data node, and a cluster software upgrading package is deployed for any data node in the software node pool, so that the data nodes in the software node pool are subjected to cluster software upgrading.
Fig. 6 is a schematic diagram of a distributed storage cluster deployment cluster software upgrade package provided in an embodiment of the present application, where, as shown in fig. 6, assuming that a distributed storage cluster deploys two nodes of different operating systems in a mixed manner, namely, a node 1 and a node 2 configured with an operating system a, and a node 3 and a node 4 configured with an operating system B, then the node 1 and the node 2 are assigned to a software node pool 1, and the node 3 and the node 4 are assigned to a software node pool 2. When the cluster software is updated by the distributed storage cluster, the cluster software upgrading package can be split into a cluster software upgrading package A and a cluster software upgrading package B, which correspond to the software node pool 1 and the software node pool 2 respectively. Further, the cluster software upgrade package a and the cluster software upgrade package B may be respectively issued to the software node pool 1 and the software node pool 2, so that each node completes the upgrade of the cluster software.
When the distributed storage cluster provides cluster software upgrade packages for different software node pools, in order to realize the compiling of a set of code compatible multi-operating system, the compiling can be performed by adopting a conditional compiling and pre-compiling head mode. Specifically, static codes such as a distributed storage cluster protocol can be precompiled into a dependency library, then code segments of different operating systems are selected to compile executable programs, and then the dependency library is combined to compile a cluster software upgrade package. For example, for the node 1 and the node 2 in the software node pool 1 where the operating system a is configured, the code segment corresponding to the operating system a may be selected for compiling, an executable program for the node in the software node pool 1 where the operating system a is configured is compiled, and then, by combining with the precompiled dependency library, the cluster software upgrade package a may be compiled. For another example, for the node 3 and the node 4 of the operating system B configured in the software node pool 2, the code segment corresponding to the operating system B may be selected for compiling, the executable program for the node of the operating system B configured in the software node pool 2 is compiled, and then the cluster software upgrade package B may be compiled by combining with the precompiled dependency library, so as to implement a set of code compatible multi-operating system compiling.
When the cluster software is upgraded, the cluster software upgrading packet can be matched with the corresponding node pool and then issued to the node managed by the node pool. Therefore, the problems that after the node is upgraded, the node cannot be started, the service function is abnormal, the system is abnormal, the server is down and the like are effectively avoided, and the distributed storage cluster service is affected.
Similarly, when the distributed storage cluster deploys a server capability upgrade package for each node so that each node upgrades the server capability, the distributed storage cluster can determine the corresponding server capability upgrade package according to a hardware node pool corresponding to any data node, and deploy the server capability upgrade package for any data node in the hardware node pool.
Fig. 7 shows a schematic diagram of a deployment hardware capability upgrade package of a distributed storage cluster provided in an embodiment of the present application, as shown in fig. 7, if a distributed storage cluster is mixedly deployed with nodes of two different server types, namely, node 1 with a server type X, and nodes 2, 3 and 4 with a server type Y, then node 1 is attributed to a hardware node pool 1, node 2, node 3 and node 4 are attributed to a hardware node pool 2, and when the distributed storage cluster upgrades the server capability, the hardware capability upgrade package can be split into a hardware capability upgrade package a and a hardware capability upgrade package B. Further, the hardware capability upgrading package a and the hardware capability upgrading package B may be respectively issued to the hardware node pool 1 and the hardware node pool 2, so that each node completes upgrading of the hardware capability of the server.
When the hardware capability is upgraded, the hardware capability upgrading packet can be matched to the corresponding node pool and then issued to the node managed by the node pool. Therefore, the problems that after the node is upgraded, the node cannot be started, the service function is abnormal, the system is abnormal, the server is down and the like are effectively avoided, and the distributed storage cluster service is influenced.
Based on the same inventive concept, the embodiment of the present invention further provides a structural schematic diagram of a distributed storage cluster deployment device, as shown in fig. 8, where the distributed storage cluster deployment device includes:
a control unit 801, configured to control the metadata node to send a deployment request message to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
a first deployment unit 802, configured to control the metadata node to deploy each data node to a corresponding node pool based on the server model and the operating system type sent by each data node;
and determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool.
Based on the same inventive concept, another structural schematic diagram of a distributed storage cluster deployment device is also provided in the embodiment of the present invention, as shown in fig. 9, where the distributed storage cluster deployment device includes:
a first sending unit 901, configured to send a deployment request message to at least one data node, so that each data node sends a server model and an operating system type to a metadata node;
the second deployment unit 902 is configured to deploy each data node to a corresponding node pool based on the server model and the operating system type sent by each data node, so that the cluster server determines a corresponding instance upgrade package according to the node pool corresponding to any data node, and deploys the instance upgrade package for any data node in the node pool.
Based on the same inventive concept, another structural schematic diagram of a distributed storage cluster deployment device is further provided in the embodiment of the present invention, as shown in fig. 10, where the distributed storage cluster deployment device includes:
a receiving unit 1001, configured to receive a deployment request message sent by a metadata node;
a second sending unit 1002, configured to send a server model and an operating system type to the metadata node;
and the upgrade unit 1003 is configured to receive an instance upgrade package issued by the cluster server, and upgrade the instance according to the instance upgrade package, where the instance upgrade package is issued by the cluster server according to a node pool corresponding to the data node.
Based on the same inventive concept, the embodiments of the present application also provide an electronic device, which may be, for example, the cluster server above. The electronic device comprises at least a memory for storing data and a processor, wherein for the processor for data processing, the processing may be implemented with a microprocessor, a CPU, a GPU (Graphics Processing Unit, a graphics processing unit), a DSP or an FPGA. For the memory, the memory stores operation instructions, which may be computer executable codes, to implement each step in the flow of the distributed storage cluster deployment method in the embodiment of the present application.
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 11, the electronic device 1100 includes a memory 1101, a processor 1102, a data acquisition module 1103, and a bus 1104. The memory 1101, the processor 1102 and the data acquisition module 1103 are all connected by a bus 1104, and the bus 1104 is used for transferring data among the memory 1101, the processor 1102 and the data acquisition module 1103.
The memory 1101 may be used to store software programs and modules, and the processor 1102 executes the software programs and modules stored in the memory 1101 to perform various functional applications and data processing of the electronic device 1100, and as in the embodiments herein, provides a distributed storage cluster deployment method. The memory 1101 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, application programs of at least one application, and the like; the storage data area may store data created according to the use of the electronic device 1100, and the like. In addition, the memory 1101 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.
The processor 1102 is a control center of the electronic device 1100, utilizes the bus 1104 and various interfaces and lines to connect the various parts of the overall electronic device 1100, performs various functions of the electronic device 1100 and processes data by running or executing software programs and/or modules stored in the memory 1101, and invoking data stored in the memory 1101. Optionally, the processor 1102 may include one or more processing units, such as a CPU, GPU (Graphics Processing Unit ), digital processing unit, or the like.
The embodiments of the present application further provide a computer readable storage medium, where computer executable instructions are stored, where the computer program when executed by a processor may be used to implement the distributed storage cluster deployment method described in any embodiment of the present application.
In some possible embodiments, various aspects of the distributed storage cluster deployment method provided herein may also be implemented in the form of a program product comprising program code for causing a computer device to perform the steps of the distributed storage cluster deployment method according to various exemplary embodiments of the present application described herein above when the program product is run on a computer device, e.g., the computer device may perform the flow of the distributed storage cluster deployment method as shown in fig. 4.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. A distributed storage cluster deployment method, applied to a cluster server, comprising:
controlling metadata nodes to send deployment request messages to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
controlling the metadata nodes to deploy the data nodes to corresponding node pools based on the server model and the operating system type sent by the data nodes;
and determining a corresponding instance upgrade package according to a node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool.
2. The method of claim 1, wherein the node pools comprise a software node pool corresponding to an operating system type and a hardware node pool corresponding to a server model.
3. The method according to claim 2, wherein the determining the corresponding instance upgrade package according to the node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool, includes:
determining a corresponding cluster software upgrading packet according to a software node pool corresponding to any data node;
deploying the cluster software upgrading package for any data node in the software node pool, so that the data node in the software node pool performs cluster software upgrading;
the cluster software upgrade package is compiled based on an object code segment, wherein the object code segment is a code segment corresponding to an operating system type corresponding to any software node pool.
4. The method according to claim 2, wherein the determining the corresponding instance upgrade package according to the node pool corresponding to any data node, and deploying the instance upgrade package for any data node in the node pool, includes:
determining a corresponding server capacity upgrade package according to a hardware node pool corresponding to any data node;
and deploying the server capacity upgrading package for any data node in the hardware node pool, so that the data node in the hardware node pool can carry out server capacity upgrading.
5. The method of claim 1, wherein before the control metadata node sends the deployment request message to the at least one data node, the method further comprises:
setting at least one software node pool, wherein each software node pool in the at least one software node pool corresponds to one operating system type;
setting at least one hardware node pool, wherein each hardware node pool in the at least one hardware node pool corresponds to a server model.
6. A distributed storage cluster deployment method, applied to metadata nodes, the method comprising:
sending a deployment request message to at least one data node, so that each data node sends a server model and an operating system type to the metadata node;
based on the server model and the operating system type sent by each data node, deploying each data node to a corresponding node pool, so that a cluster server determines a corresponding instance upgrade package according to the node pool corresponding to any data node, and deploys the instance upgrade package for any data node in the node pool.
7. A distributed storage cluster deployment method, applied to a data node, the method comprising:
receiving a deployment request message sent by a metadata node;
sending a server model and an operating system type to the metadata node;
and receiving an instance upgrade package issued by a cluster server, and upgrading an instance according to the instance upgrade package, wherein the instance upgrade package is issued by the cluster server according to a node pool corresponding to the data node.
8. The method of claim 7, wherein the instance upgrade package comprises a cluster software upgrade package and a server capability upgrade package, the upgrading an instance according to the instance upgrade package comprising:
upgrading the cluster software according to the cluster software upgrading package; the cluster software upgrade package is compiled based on a target code segment, wherein the target code segment is a code segment corresponding to an operating system type corresponding to any data node;
and upgrading the server capacity according to the server capacity upgrading packet.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program executable on the processor, which when executed by the processor, implements the method of any of claims 1-5 or claim 6 or claims 7-8.
10. A computer-readable storage medium having a computer program stored therein, characterized in that: the computer program, when executed by a processor, implements the method of any one of claims 1 to 5 or claim 6 or claims 7 to 8.
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