CN111158704A - Model establishing method, deployment flow generation method, device and electronic equipment - Google Patents
Model establishing method, deployment flow generation method, device and electronic equipment Download PDFInfo
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Abstract
Embodiments of a model building method, a deployment flow generating method, an apparatus, and an electronic device are provided in the present specification. The deployment flow generation method comprises the following steps: generating a deployment file package of the application program to be deployed according to the package rule; and inputting the deployment file package into the trained deployment flow model to obtain a deployment flow. The embodiment of the specification can improve the deployment efficiency of the application program by packaging the rule and the trained deployment flow model.
Description
Technical Field
The embodiment of the specification relates to the technical field of computers, in particular to a model establishing method, a deployment process generating device and electronic equipment.
Background
In order for a business server to implement a particular business function, applications may be deployed into the business server as needed. Generally, the development of an application from a developer to deploy the application to a business server requires multiple links of application submission, information construction submission and application deployment. However, since each link required for deploying the application to the service server is independent of each other, different users are required to complete the deployment respectively, and since each link has a relatively close relationship, the users in charge of each link communicate with each other through documents, oral voices and the like to confirm related information, and then the operation of a specific link can be finally completed on related equipment, so that the complexity of deploying the application to the service server is high, and the application deployment efficiency is low.
Disclosure of Invention
The embodiment of the specification provides a model establishing method, a deployment flow generating method, a device and electronic equipment, so as to improve the deployment efficiency of an application program.
In order to achieve the above purpose, one or more embodiments in the present specification provide the following technical solutions.
According to a first aspect of one or more embodiments of the present specification, there is provided a model building method including: splitting sample data into deployment units, wherein the sample data comprises deployment file packages of sample application programs; clustering the deployment units to obtain at least one class cluster; determining a group package rule of the cluster according to the deployment unit under the cluster; and establishing a deployment process model according to the deployment mode of the deployment unit, wherein the deployment process model and the group package rule are used for deploying the application program to be deployed.
According to a second aspect of one or more embodiments of the present specification, there is provided a deployment flow generation method including: generating a deployment file package of the application program to be deployed according to the package rule; and inputting the deployment file package into the trained deployment flow model to obtain a deployment flow.
According to a third aspect of one or more embodiments of the present specification, there is provided a model building apparatus including: the system comprises a splitting unit, a deploying unit and a processing unit, wherein the splitting unit is used for splitting sample data into deploying units, and the sample data comprises deploying file packages of a sample application program; the clustering unit is used for clustering the deployment units to obtain at least one cluster; the determining unit is used for determining the group package rule of the cluster according to the deployment unit under the cluster; the establishing unit is used for establishing a deployment process model according to the deployment mode of the deployment unit, and the deployment process model and the group package rule are used for deploying the application program to be deployed.
According to a fourth aspect of one or more embodiments of the present specification, there is provided a deployment flow generation apparatus including: the generating unit is used for generating a deployment file package of the application program to be deployed according to the package rule; and the input unit is used for inputting the deployment file package into the trained deployment process model to obtain a deployment process.
According to a fifth aspect of one or more embodiments of the present specification, there is provided an electronic device including: at least one processor; a memory storing program instructions configured to be suitable for execution by the at least one processor, the program instructions comprising instructions for performing the method of the first or second aspect.
As can be seen from the technical solutions provided in the embodiments of the present specification, a deployment file package of an application program to be deployed may be generated according to a package rule; the deployment file package can be input to the trained deployment process model to obtain a deployment process. Therefore, the deployment efficiency of the application program can be improved by packaging the rules and the trained deployment flow model.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a model building method according to an embodiment of the present disclosure;
FIG. 2 is a flowchart of a deployment flow generation method according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a deployment flow generation system in one embodiment of the present description;
fig. 4 is a functional structure diagram of a model building apparatus according to an embodiment of the present disclosure;
fig. 5 is a functional structure diagram of a deployment flow generation apparatus according to an embodiment of the present specification;
fig. 6 is a functional structure diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.
The present specification provides one embodiment of a model building method.
The model building method can be applied to electronic equipment. The electronic device includes, but is not limited to, a server, a desktop personal computer, or a server cluster composed of a plurality of servers. In some scenario examples, the model building method may be applied to a deployment platform. The deployment platform is used for deploying the application program on a large host computer, a business server or other equipment. Deployment of an application may include operations to bring the application into use, such as installation of the application, setting of environment variables, and the like.
Please refer to fig. 1. The model building method may include the following steps.
Step S12: and splitting the sample data into deployment units.
In some embodiments, the sample data may comprise a deployment package for a sample application. The deployment package may include an installation package for the application. The deployment package may include at least one of an executable, a script, and a parameter of the application. In practical applications, a developer may write source program codes of an application program according to requirements, and the source program codes may include files of job flow, scripts, parameters and the like in addition to source codes which need to be compiled into executable codes. The deployment file package can be obtained by packaging the executable code, the job flow, the script, the parameters and the like. The file type of the deployment package may be a compressed file type such as zip or war.
In some embodiments, the electronic device may parse the sample data to identify deployment units therein. The deployment unit may be a minimum deployment unit of the sample data in a deployment process. The deployment unit may be one file or a file set including a plurality of files. For example, the electronic device may parse the sample data, and use each file (or a file set) obtained through parsing as a deployment unit. Of course, the electronic device may determine the deployment unit in other manners.
In some embodiments, the electronic device may obtain a plurality of sample data from a sample data pool; each sample data may be split into at least one deployment unit.
Step S14: and clustering the deployment units to obtain at least one class cluster.
In some embodiments, each class cluster may include at least one deployment unit. Each deployment unit in the class cluster has the same or similar deployment mode in the deployment process of the application program, and for example, the deployment unit is deployed after a certain environment variable is set or a certain component is installed. Each class cluster may correspond to a file type, which may be, for example, ws, java, ear, dump, or shell, etc.
In some embodiments, the electronic device may employ any clustering algorithm to cluster the plurality of deployment units obtained by splitting, so as to obtain at least one class cluster. The Clustering algorithm includes, but is not limited to, K-Means Clustering algorithm, DBSCAN (sensitivity-Based Spatial Clustering of Applications with Noise) Clustering algorithm, hierarchical Clustering algorithm, etc.
Step S16: and determining a group package rule of the cluster according to the deployment units under the cluster.
In some embodiments, the electronic device may analyze and summarize a group package rule of each class cluster according to a deployment unit under each class cluster, where the group package rule indicates a position of a file corresponding to a file type of the class cluster in a deployment file package.
In some embodiments, different sample applications have different package specifications, and a package rule can be obtained by analyzing and summarizing the deployment units in the deployment file packages of the different sample applications, and the package rule can be used as the package specification when the deployment file package is generated. Therefore, the set of package rules may be used to deploy the application program to be deployed, and specifically, may be used to generate a deployment file package of the application program to be deployed.
Further, the electronic device may further determine a directory policy corresponding to the file type according to each group package rule, where the directory policy indicates a directory location of a file corresponding to the file type in the deployment package.
Step S18: and establishing a deployment flow model according to the deployment mode of the deployment unit.
In some embodiments, the electronic device may obtain a deployment manner of a deployment unit in sample data; the deployment flow model can be established according to the deployment mode of the deployment unit in the sample data. Specifically, the electronic device may train the deployment process model according to the deployment mode of the deployment unit, so as to establish the deployment process model. For example, the electronic device may train the deployment process model in an unsupervised learning manner, so as to establish the deployment process model.
In some embodiments, the deployment process model may be used to deploy the application to be deployed, and specifically, may be used to generate a deployment process of the application to be deployed. The deployment process model may be any type of model, such as a PU Learning model, a neural network model, a support vector machine model, a bayesian model, or the like.
In some embodiments, the electronic device may split the sample data into deployment units; clustering can be carried out on the deployment units to obtain at least one class cluster; the group package rule of the cluster can be determined according to the deployment units under the cluster; the deployment flow model can be established according to the deployment mode of the deployment unit. The deployment process of the application program can be rapidly generated by using the package rule and the deployment process model.
The present specification provides one embodiment of a deployment flow generation method.
The deployment flow generation method can be applied to electronic equipment. The electronic device includes, but is not limited to, a server, a desktop personal computer, or a server cluster composed of a plurality of servers. In some scenario examples, the deployment flow generation method may be applied to a deployment platform. The deployment platform is used for deploying the application program on a large host computer, a business server or other equipment. Deployment of an application may include operations to bring the application into use, such as installation of the application, setting of environment variables, and the like.
Please refer to fig. 2. The deployment flow generation method may include the following steps.
Step S22: and generating a deployment file package of the application program to be deployed according to the package rule.
In some embodiments, a developer may write source program code of an application to be deployed according to requirements, where the source program code may include files such as job flow, scripts, parameters, and the like, in addition to source code that needs to be compiled into executable code. The electronic device can obtain a source program code of the application program to be deployed; the source program code of the application program to be deployed can be packaged according to at least one packaging rule, so that a deployment file package of the application program to be deployed is obtained. The application program to be deployed may include a completely new application program and a new version of the application program. The deployment package may include an installation package.
Further, each group package rule may correspond to a directory policy. The directory policy indicates a directory location of a file in the deployment package corresponding to the file type. Thus, the electronic device can package the source program code of the application program to be deployed according to at least one directory policy to obtain a deployment file package.
Step S24: and inputting the deployment file package into the trained deployment flow model to obtain a deployment flow.
In some embodiments, the electronic device may input a deployment package of the application program to be deployed to the trained deployment process model, so as to obtain a deployment process of the application program to be deployed. Specifically, the electronic device may input a deployment package of the application to be deployed to the trained deployment process model to obtain an executable file, where the executable file may include the deployment process. The electronic device can run the executable file to realize the deployment of the deployment file package. The file format of the executable file may be a script file, for example. Of course, the electronic device may input the deployment package of the application to be deployed to the trained deployment process model to obtain files in other forms, such as text files.
In some embodiments, the electronic device may further add the deployment file package of the application to be deployed as sample data to a sample data pool, so as to determine the package rule again according to the sample data pool and train the deployment process model again, which may continuously improve the accuracy of the package rule and the accuracy of the deployment process model.
In some embodiments, the electronic device may generate a deployment file package of the application program to be deployed according to a package rule; the deployment file package can be input to the trained deployment process model to obtain a deployment process. This may improve the deployment efficiency of the application.
An example scenario for deploying a process generation system is described below.
Please refer to fig. 3. The deployment procedure generation system may include a machine learning module and a group package module.
The machine learning module may include a classification calculation unit, a rule induction unit, a model building unit, and a calculation unit. The classification calculation unit is used for receiving input sample data; splitting sample data into deployment units; and clustering the deployment units to obtain at least one class cluster. The rule induction unit is used for determining the group package rule of the class cluster according to the deployment unit under the class cluster. The model establishing unit is used for establishing a deployment process model according to the deployment mode of the deployment unit. The computing unit is used for receiving an input deployment file package of the application program to be deployed, inputting the deployment file package into the deployment process model, and obtaining a deployment process of the application program to be deployed.
The group package module may include a directory policy unit and a group package unit. The target standardization unit is used for determining the directory policy according to the group package rule. The group packaging unit is used for receiving a source program code of an application program to be deployed; and according to the directory strategy, packaging the source program code of the application program to be deployed to obtain a deployment file package of the application program to be deployed.
The deployment flow generation system of the scene example adopts artificial intelligence to split a packet structure of sample data, extracts different types of deployment flows, can automatically analyze the characteristics of modules of an application program to be deployed by machine learning analysis modeling, completes the deployment flow design of the application program by learning calculation, and automatically generates the deployment flow of the application program.
Specifically, the deployment process generation system can achieve the following technical effects.
(1) The deployment process is generated quickly, the time of developers is greatly reduced, and meanwhile, personnel errors are avoided. The deployment process needing manual design is generated through an automatic means, so that the time for designing by developers can be greatly reduced, the time cost is saved, and meanwhile, the deployment process is automatically generated, so that the design errors caused by the developers can be effectively avoided.
(2) The method is carried out according to a uniform method, and the generated deployment flow has high normalization and usability. The minimum deployment processes are standardized, the directory strategies of the application programs are unified, the packaging structure is uniform, the minimum deployment process set can be generated through machine learning, and the method is high in standardization and high in usability.
(3) The deployment process of the unified mode reduces the deployment difficulty of maintenance engineers. In general, one maintenance engineer needs to maintain a plurality of application programs, and a deployment process generated in a unified mode is adopted, so that the understanding of the maintenance engineer is enhanced, the deployment difficulty of the maintenance engineer is reduced, and a specific problem is more easily positioned after a problem occurs in deployment.
(4) Based on the application of an artificial intelligence algorithm and a big data technology, an optimal automatic deployment scheme is found out from a traditional historical deployment mode, and the intelligent implementation of automatic deployment can be realized on the basis of ensuring the deployment accuracy and usability.
(5) The overall quality of the software is improved, good tools are used, the standardized process is adopted, human intervention can be minimized, the time for waiting for someone to do something can be saved, and once the human intervention is removed, the quality can be more predictable and better.
Please refer to fig. 4. The embodiment of the present specification provides an embodiment of a model building apparatus, which includes the following units.
The splitting unit 32 is configured to split sample data into deployment units, where the sample data includes a deployment file package of a sample application program;
the clustering unit 34 is configured to cluster the deployment units to obtain at least one class cluster;
a determining unit 36, configured to determine a group package rule of the class cluster according to the deployment unit under the class cluster;
the establishing unit 38 is configured to establish a deployment process model according to a deployment manner of the deployment unit, where the deployment process model and the group package rule are used to deploy the application program to be deployed.
Please refer to fig. 5. The embodiment of the present specification provides an embodiment of a deployment flow generation apparatus, which includes the following units.
The generating unit 42 is configured to generate a deployment file package of the application program to be deployed according to the package rule;
and the input unit 44 is configured to input the deployment file package into the trained deployment process model to obtain a deployment process.
An embodiment of a terminal device of the present specification is described below. Fig. 6 is a schematic diagram of the hardware configuration of the terminal device in this embodiment. As shown in fig. 6, the terminal device may include one or more processors (only one shown), memory, and a transmission module. Of course, it is understood by those skilled in the art that the hardware structure shown in fig. 6 is only an illustration, and does not limit the hardware structure of the terminal device. In practice the terminal device may also comprise more or fewer component elements than those shown in fig. 6; or have a different configuration than that shown in fig. 6.
The memory may comprise high speed random access memory; alternatively, non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory may also be included. Of course, the memory may also comprise a remotely located network memory. The remotely located network storage may be connected to the blockchain client through a network such as the internet, an intranet, a local area network, a mobile communications network, or the like. The memory may be used to store program instructions or modules of application software, such as the program instructions or modules of the embodiments corresponding to fig. 1 or fig. 2 in this specification.
The processor may be implemented in any suitable way. For example, the processor may take the form of, for example, a microprocessor or processor and a computer-readable medium that stores computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, an embedded microcontroller, and so forth. The processor may read and execute the program instructions or modules in the memory.
The transmission module may be used for data transmission via a network, for example via a network such as the internet, an intranet, a local area network, a mobile communication network, etc.
This specification also provides one embodiment of a computer storage medium. The computer storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache (Cache), a Hard Disk (HDD), a Memory Card (Memory Card), and the like. The computer storage medium stores computer program instructions. The computer program instructions when executed implement: the program instructions or modules of the embodiments corresponding to fig. 1 or fig. 2 in this specification.
It should be noted that, in the present specification, each embodiment is described in a progressive manner, and the same or similar parts in each embodiment may be referred to each other, and each embodiment focuses on differences from other embodiments. In addition, it is understood that one skilled in the art, after reading this specification document, may conceive of any combination of some or all of the embodiments listed in this specification without the need for inventive faculty, which combinations are also within the scope of the disclosure and protection of this specification.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most popular applications. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
From the above description of the embodiments, it is clear to those skilled in the art that the present specification can be implemented by software plus a necessary general hardware platform. Based on such understanding, the technical solutions of the present specification may be essentially or partially implemented in the form of software products, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments of the present specification.
The description is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
While the specification has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the specification that do not depart from the spirit of the specification, and it is intended that the appended claims include such variations and modifications that do not depart from the spirit of the specification.
Claims (10)
1. A method of model building comprising:
splitting sample data into deployment units, wherein the sample data comprises deployment file packages of sample application programs;
clustering the deployment units to obtain at least one class cluster;
determining a group package rule of the cluster according to the deployment unit under the cluster;
and establishing a deployment process model according to the deployment mode of the deployment unit, wherein the deployment process model and the group package rule are used for deploying the application program to be deployed.
2. The method of claim 1, wherein each cluster class corresponds to a file type, the method further comprising:
and determining a directory policy corresponding to the file type according to the group package rule.
3. The method of claim 1, further comprising:
and acquiring a plurality of sample data from the sample data pool.
4. The method of claim 1, wherein the building a deployment process model according to the deployment mode of the deployment unit comprises:
and training the deployment flow model according to the deployment mode of the deployment unit.
5. A deployment flow generation method, comprising:
generating a deployment file package of the application program to be deployed according to the package rule;
and inputting the deployment file package into the trained deployment flow model to obtain a deployment flow.
6. The method of claim 5, further comprising:
and adding the deployment file package as sample data into a sample data pool so as to train the deployment process model again according to the sample data pool.
7. The method of claim 5, the deployment flow comprising an executable file; the method further comprises the following steps:
and running the executable file to realize the deployment of the deployment file package.
8. A model building apparatus comprising:
the system comprises a splitting unit, a deploying unit and a processing unit, wherein the splitting unit is used for splitting sample data into deploying units, and the sample data comprises deploying file packages of a sample application program;
the clustering unit is used for clustering the deployment units to obtain at least one cluster;
the determining unit is used for determining the group package rule of the cluster according to the deployment unit under the cluster;
the establishing unit is used for establishing a deployment process model according to the deployment mode of the deployment unit, and the deployment process model and the group package rule are used for deploying the application program to be deployed.
9. A deployment flow generation apparatus, comprising:
the generating unit is used for generating a deployment file package of the application program to be deployed according to the package rule;
and the input unit is used for inputting the deployment file package into the trained deployment process model to obtain a deployment process.
10. An electronic device, comprising:
at least one processor;
a memory storing program instructions configured for execution by the at least one processor, the program instructions comprising instructions for performing the method of any of claims 1-7.
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| CN108897571A (en) * | 2018-06-29 | 2018-11-27 | 北京金山数字娱乐科技有限公司 | Program is packaged dispositions method, device, system, electronic equipment and storage medium |
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