CN114281367A - Big data platform deployment method and system for trust and creation environment - Google Patents
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Abstract
The invention discloses a big data platform deployment method and a system facing to a trust creating environment, belonging to the technical field of trust creating big data, and the realization of the method comprises the following processes: 1) constructing an installation package according to software and hardware information to be deployed; 2) starting the installation package medium transmission and management service; 3) initializing all nodes of the environment according to the script provided by the management service; 4) carrying out role division on the environment nodes; 5) automatically installing a big data platform; 6) performing function test on the platform through the management service; 7) and carrying out performance test and performance optimization on the platform through the management service. The invention can be adapted to different domestic CPUs and operating systems, improves the deployment efficiency, realizes the rapid deployment and delivery of the large data platform, avoids the problems of uncontrollable manual adaptation process, easy error and inconvenient management due to excessive labor resource waste in the adaptation scene.
Description
Technical Field
The invention relates to the technical field of trust creation big data, in particular to a trust creation environment-oriented big data platform deployment method and a trust creation environment-oriented big data platform deployment system.
Background
The innovative development of information technology application is a current national strategy and is also a new kinetic energy of national economic development under the current situation. The innovation is to solve the safety problem in nature, that is, to change the safety problem into controllable, research, developable and producible. The development of the trust and creation industry becomes the key for the economic digital transformation and the promotion of the development of an industrial chain, starts from the aspects of introduction of a technical system, strengthening the industry foundation, strengthening the guarantee capability and the like, promotes the trust and creation industry to root on the ground locally, drives the transformation of the traditional IT information industry, meanwhile, with the arrival of a big data era, the application of data has penetrated into various industries, the big data technology brings a new thinking angle for enterprise business analysis and industry development, and the influence and promotion of the data on the social development can be fully stimulated.
The information creation environment refers to an environment which is independently developed based on a domestic CPU and a domestic operating system under the background of information technology application innovation. Since the trusted industry is still in the development stage, the related standards are not unified, and various problems exist in the process of adapting software and hardware. Generally, human intervention and continuous trial and error are needed in the process of adapting to the trust and creation environment, different big data assemblies are compiled and debugged aiming at different software and hardware environments, a large amount of human resources are consumed in the process, and the period is long.
In the background of rapid development of big data and trusted technology, a big data platform deployment method capable of rapidly adapting to different trusted CPUs and operating systems is needed to improve delivery efficiency.
Disclosure of Invention
The technical task of the invention is to provide a big data platform deployment method and system facing to the trusted environment, which can adapt to different domestic CPUs and operating systems, improve deployment efficiency, realize quick deployment and delivery of the big data platform, and avoid the problems of uncontrollable manual adaptation process, easy error and inconvenient management due to the excessive labor resources wasted in adaptation scenes.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a big data platform deployment method facing a trust and creation environment is realized by the following processes:
1) constructing an installation package according to software and hardware information to be deployed;
2) starting the installation package medium transmission and management service;
3) initializing all nodes of the environment according to the script provided by the management service;
4) carrying out role division on the environment nodes;
5) automatically installing a big data platform;
6) performing function test on the platform through the management service;
7) and carrying out performance test and performance optimization on the platform through the management service.
The method can realize the automatic deployment of the big data platform in the trusted environment, and realize the processes of construction of the installation package, management service starting, node initialization, platform deployment, function test, performance test, delivery and use. The adaptation process is greatly shortened, and the rapid delivery is realized.
Preferably, the installation package is constructed according to the version information of the CPU, the operating system and the operating system of the environment to be deployed; the process comprises big data packets of various types which are compiled, and field adaptation in the deployment process is avoided.
The components needing to be compiled can be compiled in advance according to different combinations, and the compiled components are put in storage for use in subsequent construction of the installation package after the compiling is finished, so that the recompilation and debugging in the deployment process are avoided.
Preferably, the management service includes an instance management service, a big data application service, a task execution service, a task management service, a function test service, and a performance test service;
the instance management service is mainly responsible for instance management, namely big data cluster management, and supports multi-instance deployment and management, including service start-stop, configuration and monitoring alarm in a cluster;
the big data application service provides a visual operation page, realizes resource management, authority management, tenant management, backup and recovery management of components such as hdfs, hbase, hive, kafka and the like, simplifies the operation difficulty of a user, and provides another easy-to-use operation mode except client operation;
the task execution service is used for controlling the nodes in an ssh mode to realize deployment operation on each node;
the task management service is responsible for responsibility task scheduling, task state, task logs and task retry management, and finally realizes deployment of tasks by calling the task execution service;
the function test service is responsible for carrying out function test on the whole example after the example deployment is finished, carrying out test by using a prepared automatic test script and issuing a function test report;
and the performance test service is responsible for performing performance test on the whole instance after the instance deployment is finished, performing performance test by using the prepared automatic test script and issuing a performance test report, wherein the performance test script can be expanded, and the performance test requirement is gradually improved according to the actual requirement.
Preferably, the initialization of all nodes of the environment is performed according to the script provided by the management service, that is, the initialization script is downloaded after the management service is started, the script is uploaded to all nodes in the environment, and then the script is executed on each node to complete the initialization of the nodes; the initialization process mainly comprises the following steps:
checking software and hardware information, and if the provided information is inconsistent with that in construction, failing and prompting errors;
the method comprises the steps of carrying out pre-installation inspection on an installation package, inspecting whether the installation package of each large data assembly provided in the installation package can be normally installed on a node or not, prompting an error if the installation package cannot be normally installed, and constructing a patch package after the installation package needs to be adapted again to avoid errors in the actual installation process;
data disc checking, namely detecting which data discs exist in each node, and formatting and mounting the data discs according to a uniform processing specification;
and newly adding related system deployment users, creating a subsequent related deployment user by each node, and initializing a public key for mutual trust operation.
Preferably, the role division is performed on the environment nodes, and the environment nodes comprise basic service nodes and big data service nodes;
the basic service node deployment component comprises openldap, kerberos and a database; the big data service node deployment component comprises hadoop, hbase, hive, kafka, spark, zookeeper and anger.
Preferably, the big data platform is automatically installed, platform deployment is carried out according to node planning, task execution service and task management service through management service,
if the deployment fails, the task log can be checked through the task management service, and the deployment task is completed by using a retry function provided by task management after manual intervention according to log information;
after deployment is completed, the instance can be used by the instance management service.
Preferably, the management service is used for carrying out function test on the platform, an automatic test script is arranged in the platform, whether the function of the deployed example is normal is tested, and a test report is issued after the test is finished;
the management service is used for carrying out performance test and performance tuning on the platform, each big data assembly performance test script is arranged in the management service, performance test is carried out according to the deployed examples, a performance test report is issued, a performance tuning document is provided, and performance optimization can be carried out on the examples according to the performance test report.
The method supports various software and hardware combinations, provides a visual operation page, automatically completes the deployment of the large data platform, and improves the deployment and operation and maintenance efficiency.
The invention also claims a big data platform deployment system facing the trust and creation environment, which realizes the big data platform deployment method facing the trust and creation environment;
the system comprises a construction service module, a medium transmission module and a management service module, wherein the construction service module is used for constructing an installation package according to software and hardware information to be deployed; the medium transmission module is used for uploading the constructed installation package to a management node of the information creation environment and starting the management service module;
the system also comprises a node initialization module, a platform deployment module, a function test module and a performance test module.
The invention also claims a big data platform deployment device facing the trusted environment, which comprises: at least one memory and at least one processor;
the at least one memory to store a machine readable program;
the at least one processor is used for calling the machine readable program and executing the trust-oriented environment large data platform deployment method.
The present invention also claims a computer readable medium having stored thereon computer instructions that, when executed by a processor, cause the processor to perform the above described trust environment-oriented big data platform deployment method.
Compared with the prior art, the big data platform deployment method and system facing the trust and creation environment have the following beneficial effects:
the method and the system support different software and hardware combinations of CPUs and operating systems, and carry out centralized compiling adaptation on each big data component in advance according to different combinations without carrying out manual adaptation in a delivery environment, thereby saving the research and development time;
the instance management service supports multi-instance deployment, and one set of management service can complete deployment and management of multiple sets of environments, so that deployment resources are saved, management efficiency is improved, and operation and maintenance cost is reduced;
the task management service is provided, all operations are issued in a task form, the full life cycle tracking management is carried out on each task, and the task state, the task log and the task retry function provided by the task management service can well assist the task execution;
the function test function is provided, the function test can be carried out after the platform deployment is finished, and the delivered platform is ensured to be normally usable;
the performance test service is provided, the performance test can be performed after the platform is deployed, the optimization suggestion is provided while the platform performance is displayed, and the platform quality is guaranteed.
Drawings
FIG. 1 is a diagram of a big data platform deployment system architecture for a trusted environment according to an embodiment of the present invention;
fig. 2 is an overall deployment flowchart of the trust-oriented environment-oriented big data platform deployment method provided by the embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
A deployment system and method of big data platform facing to trusted environment, the method supports the combination selection of multiple CPU models and operating systems; multi-instance deployment can be realized only by deploying one set of management service; the automatic deployment of a big data platform is supported, and the full life cycle management of the deployment process is realized through a task management service; the function test is carried out after the platform is deployed, so that the normal operation of the platform is ensured; and the performance test is carried out after the platform is deployed, and the efficient operation of the platform is ensured.
Compiling can be carried out on each component needing to be compiled in advance according to different combinations, and the compiled components are put in storage for use in the subsequent construction of an installation package after the compiling is finished, so that the recompilation and debugging in the deployment process are avoided; the embodiment management is supported, so that the overall management of the deployment resources is better performed, the operation and maintenance efficiency is improved, and the deployment resources are saved; full lifecycle management of the deployment process may be achieved through the task management service.
An automatic test script is built in, so that automatic function test is realized, manual test is not needed, and the test efficiency is improved; the performance test scripts of all big data assemblies are built in, extension is supported, personalized performance tests can be carried out according to requirements, performance tuning can be carried out according to test results, and efficient operation of the platform is guaranteed.
The method comprises the following concrete implementation processes:
firstly, an installation package is constructed,
the installation package is constructed according to the version information of the CPU, the operating system and the operating system of the environment to be deployed, the process comprises various types of compiled big data packages, and field adaptation in the deployment process is avoided.
Secondly, the service of the installation package medium transmission and management node is started,
the constructed installation package needs to be uploaded to a management node of a trusted environment, management service starting can be completed only by executing a starting script after uploading is completed, detection of software and hardware information can be completed in the starting process, and execution can be successful only when the software and hardware information is provided to be matched with that in construction.
The management service is composed of instance management service, big data application service, task execution service, task management service, function test service and performance test service:
1. the instance management service is mainly responsible for instance management, namely big data cluster management, and supports multi-instance deployment and management. The method comprises the steps of starting and stopping, configuring and monitoring alarm of the service in the cluster.
2. The big data application service provides a visual operation page, can realize the resource management, the authority management, the tenant management, the backup and recovery management and other operations of the components such as hdfs, hbase, hive, kafka and the like, greatly simplifies the operation difficulty of a user, and provides another easy-to-use operation mode except the operation of a client.
3. And the task execution service controls the nodes in an ssh mode to realize the deployment operation on each node.
4. And the task management service is responsible for task scheduling, task states, task logs and task retry management, and finally realizes task deployment by calling the task execution service.
5. And the function test service is responsible for carrying out function test on the whole instance after the instance deployment is finished, carrying out test by using a prepared automatic test script and issuing a function test report.
6. And the performance test service is responsible for performing performance test on the whole instance after the instance deployment is finished, performing performance test by using the prepared automatic test script and issuing a performance test report, wherein the performance test script can be expanded, and the performance test requirement is gradually improved according to the actual requirement.
Thirdly, initializing all nodes of the environment according to the script provided by the management service,
the management service may download the initialization script after it is started, upload the script to all nodes in the environment, and then execute the script on each node to complete the node initialization.
The initialization process mainly comprises the following steps:
s1, checking software and hardware information, and if the provided information is inconsistent with that in construction, failing and prompting an error;
s2, pre-installation inspection of the installation package, namely, whether the installation package of each big data assembly provided in the installation package can be normally installed on the node is inspected, if the installation package can not be normally installed, an error is prompted, a patch package is constructed again after the adaptation is carried out again, and the error is avoided in the actual installation process;
s3, data disc checking, which data discs exist in each node are detected, and formatting and mounting are carried out according to a uniform processing specification;
s4, newly adding related system deployment users, each node creates a subsequent related deployment user, and initializes a public key for mutual trust operation.
And fourthly, dividing the roles of the environment nodes into basic service nodes and big data service nodes.
The method mainly comprises the steps that the role of a large data platform node is planned in advance, and basic service nodes are mainly deployed with components such as openldap, kerberos and databases; the big data service node mainly deploys components such as hadoop, hbase, hive, kafka, spark, zookeeper, anger and the like.
Fifthly, the large data platform is automatically installed,
and if the deployment fails, the task log can be checked through the task management service, and the deployment task is completed by using a retry function provided by task management after manual intervention according to log information. After deployment is completed, the instance can be used by the instance management service.
And sixthly, performing function test on the platform function through the management service, wherein an automatic test script is arranged in the service, so that whether the function of the deployed example is normal can be automatically tested, and a test report can be provided after the test is finished.
And seventhly, performing performance test and performance optimization on the platform performance through the management service, wherein the service is internally provided with performance test scripts of all big data assemblies, the performance test can be actually performed according to deployment completion, a performance test report is provided after the performance test is completed, and meanwhile, a performance optimization document is provided, and performance optimization can be performed on the instance by contrasting with the performance test report.
The steps can realize the automatic deployment of the big data platform in the trusted environment, and realize the processes of construction of the installation package, starting of the management service, initialization of the nodes, deployment of the platform, function test, performance test and delivery and use. The adaptation process is greatly shortened, and the rapid delivery is realized.
The embodiment of the invention also provides a big data platform deployment system facing the trusted environment, which comprises a construction service module, a medium transmission module and a management service module, wherein the construction service module is used for constructing an installation package according to software and hardware information to be deployed; the medium transmission module is used for uploading the constructed installation package to a management node of the information creation environment and starting the management service module;
the system also comprises a node initialization module, a platform deployment module, a function test module and a performance test module.
The system realizes the trust-oriented environment-oriented big data platform deployment method in the embodiment of the invention.
The embodiment of the invention also provides a big data platform deployment device facing the trusted environment, which comprises: at least one memory and at least one processor;
the at least one memory to store a machine readable program;
the at least one processor is configured to call the machine-readable program to execute the trust-oriented environment big data platform deployment method according to the above embodiment of the present invention.
Embodiments of the present invention further provide a computer-readable medium, where computer instructions are stored, and when executed by a processor, cause the processor to execute the trust-creation-environment-oriented big data platform deployment method described in the above embodiments of the present invention. Specifically, a system or an apparatus equipped with a storage medium on which software program codes that realize the functions of any of the above-described embodiments are stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program codes stored in the storage medium.
In this case, the program code itself read from the storage medium can realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.
Examples of the storage medium for supplying the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD + RW), a magnetic tape, a nonvolatile memory card, and a ROM. Alternatively, the program code may be downloaded from a server computer via a communications network.
Further, it should be clear that the functions of any one of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform a part or all of the actual operations based on instructions of the program code.
Further, it is to be understood that the program code read out from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then causes a CPU or the like mounted on the expansion board or the expansion unit to perform part or all of the actual operations based on instructions of the program code, thereby realizing the functions of any of the above-described embodiments.
While the invention has been shown and described in detail in the drawings and in the preferred embodiments, it is not intended to limit the invention to the embodiments disclosed, and it will be apparent to those skilled in the art that various combinations of the code auditing means in the various embodiments described above may be used to obtain further embodiments of the invention, which are also within the scope of the invention.
Claims (10)
1. A big data platform deployment method facing a trust and creation environment is characterized in that the method is realized by the following processes:
1) constructing an installation package according to software and hardware information to be deployed;
2) starting the installation package medium transmission and management service;
3) initializing all nodes of the environment according to the script provided by the management service;
4) carrying out role division on the environment nodes;
5) automatically installing a big data platform;
6) performing function test on the platform through the management service;
7) and carrying out performance test and performance optimization on the platform through the management service.
2. The deployment method of the big data platform facing the trusted environment as claimed in claim 1, wherein the installation package is constructed according to version information of CPU, os and os of the environment to be deployed; the process comprises the steps of compiling various types of big data packets, and avoiding field adaptation in the deployment process;
and compiling each component needing to be compiled according to different combinations in advance, and warehousing the components for use in the subsequent construction of the installation package after the compiling is finished.
3. The trust-oriented environment big data platform deployment method according to claim 1 or 2, wherein the management service comprises instance management service, big data application service, task execution service, task management service, functional test service, and performance test service;
the instance management service is mainly responsible for instance management, namely big data cluster management, and supports multi-instance deployment and management, including service start-stop, configuration and monitoring alarm in a cluster;
the big data application service provides a visual operation page, realizes resource management, authority management, tenant management, backup and recovery management of the components, simplifies the operation difficulty of a user, and provides another easy-to-use operation mode except client operation;
the task execution service is used for controlling the nodes in an ssh mode to realize deployment operation on each node;
the task management service is responsible for responsibility task scheduling, task state, task logs and task retry management, and finally realizes deployment of tasks by calling the task execution service;
the function test service is responsible for carrying out function test on the whole example after the example deployment is finished, carrying out test by using a prepared automatic test script and issuing a function test report;
and the performance test service is responsible for performing performance test on the whole instance after the instance deployment is finished, performing performance test by using the prepared automatic test script and issuing a performance test report, wherein the performance test script can be expanded, and the performance test requirement is gradually improved according to the actual requirement.
4. The big data platform deployment method facing the trusted environment as claimed in claim 1 or 2, wherein the initialization of all nodes in the environment is performed according to the script provided by the management service, that is, the initialization script is downloaded after the management service is started, the script is uploaded to all nodes in the environment, and then the script is executed on each node to complete the initialization of the node; the initialization process mainly comprises the following steps:
checking software and hardware information, and if the provided information is inconsistent with that in construction, failing and prompting errors;
the method comprises the steps of carrying out pre-installation inspection on an installation package, inspecting whether the installation package of each large data assembly provided in the installation package can be normally installed on a node or not, prompting an error if the installation package cannot be normally installed, and constructing a patch package after the installation package needs to be adapted again to avoid errors in the actual installation process;
data disc checking, namely detecting which data discs exist in each node, and formatting and mounting the data discs according to a uniform processing specification;
and newly adding related system deployment users, creating a subsequent related deployment user by each node, and initializing a public key for mutual trust operation.
5. The big data platform deployment method facing the trusted environment as claimed in claim 1 or 2, wherein the role division is performed on environment nodes, and comprises a basic service node and a big data service node;
the basic service node deployment component comprises openldap, kerberos and a database; the big data service node deployment component comprises hadoop, hbase, hive, kafka, spark, zookeeper and anger.
6. The trust-oriented environment big data platform deployment method of claim 3, wherein the big data platform is automatically installed, and platform deployment is performed according to node planning, task execution service and task management service through management service,
if the deployment fails, the task log can be checked through the task management service, and the deployment task is completed by using a retry function provided by task management after manual intervention according to log information;
after deployment is completed, the instance can be used by the instance management service.
7. The big data platform deployment method facing the trust and creation environment as claimed in claim 1 or 2, wherein the platform is functionally tested through management service, an automatic test script is built in, whether the function of the deployed instance is normal is tested, and a test report is issued after the test is completed;
the management service is used for carrying out performance test and performance tuning on the platform, each big data assembly performance test script is arranged in the management service, performance test is carried out according to the deployed examples, a performance test report is issued, a performance tuning document is provided, and performance optimization can be carried out on the examples according to the performance test report.
8. A big data platform deployment system facing a trusted environment, which is characterized by implementing the big data platform deployment method facing the trusted environment of any one of claims 1 to 7;
the system comprises a construction service module, a medium transmission module and a management service module, wherein the construction service module is used for constructing an installation package according to software and hardware information to be deployed; the medium transmission module is used for uploading the constructed installation package to a management node of the information creation environment and starting the management service module;
the system also comprises a node initialization module, a platform deployment module, a function test module and a performance test module.
9. A big data platform deployment device facing a trusted environment is characterized by comprising: at least one memory and at least one processor;
the at least one memory to store a machine readable program;
the at least one processor, configured to invoke the machine readable program to perform the method of any of claims 1 to 7.
10. A computer readable medium having stored thereon computer instructions which, when executed by a processor, cause the processor to perform the method of any of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115437696A (en) * | 2022-08-04 | 2022-12-06 | 北京海联捷讯科技股份有限公司 | Self-adaptive configuration method of trusted platform and terminal assistant |
| CN118093448A (en) * | 2024-04-29 | 2024-05-28 | 浪潮云信息技术股份公司 | Full test method, equipment and medium based on core function of information creation operating system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115437696A (en) * | 2022-08-04 | 2022-12-06 | 北京海联捷讯科技股份有限公司 | Self-adaptive configuration method of trusted platform and terminal assistant |
| CN118093448A (en) * | 2024-04-29 | 2024-05-28 | 浪潮云信息技术股份公司 | Full test method, equipment and medium based on core function of information creation operating system |
| CN118093448B (en) * | 2024-04-29 | 2024-08-09 | 浪潮云信息技术股份公司 | Full test method, equipment and medium based on core function of information creation operating system |
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