Data processing method for cloud computing system

文档序号:1937569 发布日期:2021-12-07 浏览:9次 中文

阅读说明:本技术 一种用于云计算系统的数据处理方法 (Data processing method for cloud computing system ) 是由 吴剑波 王庆东 关玉蓉 姜国松 陆正武 朱晓明 于 2021-09-11 设计创作,主要内容包括:本申请公开了一种用于云计算系统的数据处理方法,采集数据并传输至云计算系统;采集数据并传输至云计算系统;对采集到的数据进行处理;将处理后的数据分类储存;对存储的数据进行管理和调度;根据用户个性化需要展示对应数据。可以在大数据中更加准确的展示出用户需要的内容,同时通过数据处理,可以对数据进行分析挖掘,从而可以展示更加深层的数据,也可以提高数据的关联度,解决了现有的云计算系统的数据处理方法在处理数据时数据分类不清晰的问题,使得云计算系统中的数据处理后分类更加明确,从而使得用户在数据检索完成后,会得到相关度较高的数据内容,通过虚拟化技术可以帮助用户快速了解所需内容,提高了数据的检索效率。(The application discloses a data processing method for a cloud computing system, which comprises the steps of collecting data and transmitting the data to the cloud computing system; collecting data and transmitting the data to a cloud computing system; processing the acquired data; storing the processed data in a classified manner; managing and scheduling the stored data; and displaying the corresponding data according to the personalized needs of the user. The content required by the user can be displayed more accurately in the big data, and meanwhile, through data processing, the data can be analyzed and mined, so that deeper data can be displayed, the association degree of the data can also be improved, the problem that data classification is not clear when the data processing method of the existing cloud computing system processes the data is solved, the classification of the data in the cloud computing system is more definite after the data is processed, the data content with higher correlation degree can be obtained after the data retrieval of the user is completed, the user can be helped to quickly know the required content through a virtualization technology, and the data retrieval efficiency is improved.)

1. A data processing method for a cloud computing system, characterized by: the data processing method of the cloud computing system comprises the following steps:

(1) collecting data and transmitting the data to a cloud computing system;

(2) processing the acquired data;

(3) storing the processed data in a classified manner;

(4) managing and scheduling the stored data;

(5) and displaying the corresponding data according to the personalized needs of the user.

2. The data processing method for the cloud computing system according to claim 1, wherein: in the step (1), a large amount of data is acquired through the terminal collecting device, the acquired data is directly transmitted to the data acquisition module of the cloud computing system, and at the moment, the data acquisition module in the cloud computing system performs primary classification on the data.

3. The data processing method for the cloud computing system according to claim 1, wherein: in the step (1), the collected data is divided into five categories of text data, audio, video, picture and position information, corresponding data contents are transmitted to a text data module, an audio module, a video data module, a picture information module and a position information module, and the classified data are processed.

4. The data processing method for the cloud computing system according to claim 1, wherein: the data processing in the step (2) comprises data preprocessing and data analysis, wherein the data preprocessing comprises decoding processing, data filling processing and noise cleaning processing.

5. The data processing method for the cloud computing system according to claim 1, wherein: the data analysis in the step (2) comprises a splitting unit, a mapping unit, an output unit and a merging storage unit, and the classified data is split, mapped and merged.

6. The data processing method for the cloud computing system according to claim 1, wherein: and (3) correspondingly performing data preprocessing and data analysis processing on the classified data in the step (2) respectively, and transmitting the data to a storage module.

7. The data processing method for the cloud computing system according to claim 1, wherein: the data storage module in the step (3) comprises a first-level storage module, a second-level storage module and a third-level storage module, the first-level storage module, the second-level storage module and the third-level storage module are separated according to the upper level and the lower level, the second-level storage module comprises the third-level storage module, and the data can be classified finely when the first-level storage module and the third-level storage module reach.

8. The data processing method for the cloud computing system according to claim 1, wherein: and (4) managing the data stored in the step (4) by a management scheduling module, wherein the management scheduling module comprises an access scheduling module, a content publishing module, a storage management module and a data backup module, managing access of a user, publishing of system content, data storage and data backup, and ensuring the effective time of the data by the data backup.

9. The data processing method for the cloud computing system according to claim 1, wherein: and (5) the cloud computing system storage module is connected with the application interface module through the management scheduling module, data of the cloud computing system are scheduled and managed through data instructions issued by the application interface, and corresponding data are displayed step by step according to the instructions.

10. The data processing method for the cloud computing system according to claim 1, wherein: and (5) the application interface module comprises a data storage interface module, a space leasing interface module, a public resource interface module, a multi-user data sharing interface module and a data backup query interface module.

Technical Field

The application relates to a data processing method, in particular to a data processing method for a cloud computing system.

Background

Cloud computing is one of distributed computing, which means that huge data computing processing programs are decomposed into countless small programs through a network cloud, then the small programs are processed and analyzed through a system consisting of a plurality of servers to obtain results and the results are returned to users, the cloud computing is simple distributed computing, task distribution is solved, the computing results are merged, a service related to information technology, software and the Internet is provided, a plurality of computing resources are gathered, automatic management is achieved through the software, resources can be rapidly provided only by few people participating and maintaining, the core of the cloud computing is that a plurality of computer resources can be coordinated together, and by means of the technology, processing of tens of thousands of data can be completed in a short time, so that powerful network services are achieved.

With the popularization and development of the internet, a data processing method of a cloud computing system is rapidly developed, when the data is processed by the existing data processing method of the cloud computing system, the data cannot be clearly classified, the relevance of the fed-back data is reduced after the data is processed and when a user inquires the data, and due to the fact that the classification and processing means are not enough after the data is collected, part of deep data cannot be mined easily, and the retrieval and display effect of the data is affected. Therefore, a data processing method for a cloud computing system is proposed to solve the above problems.

Disclosure of Invention

The embodiment provides a data processing method for a cloud computing system, which is used for solving the problem that data classification is unclear when the data processing method for the cloud computing system processes data in the prior art.

According to an aspect of the present application, there is provided a data processing method for a cloud computing system, the data processing method for the cloud computing system including the steps of:

(1) collecting data and transmitting the data to a cloud computing system;

(2) processing the acquired data;

(3) storing the processed data in a classified manner;

(4) managing and scheduling the stored data;

(5) and displaying the corresponding data according to the personalized needs of the user.

Further, in the step (1), a large amount of data is acquired through the terminal collecting device, the acquired data is directly transmitted to the data acquisition module of the cloud computing system, and at the moment, the data acquisition module in the cloud computing system preliminarily classifies the data.

Furthermore, the collected data in the step (1) is divided into five categories of text data, audio, video, picture and position information, corresponding data contents are transmitted to a text data module, an audio module, a video data module, a picture information module and a position information module, and the classified data are processed.

Further, the data processing in step (2) includes data preprocessing and data parsing, and the data preprocessing includes a decoding process, a data padding process and a noise cleaning process.

Further, the data analysis in step (2) includes a splitting unit, a mapping unit, an output unit, and a merging storage unit, and the data after classification is split, mapped, and merged.

Further, in the step (2), the classified data is respectively and correspondingly subjected to data preprocessing and data analysis processing, and then is transmitted to the storage module.

Further, the data storage module in the step (3) includes a first-level storage module, a second-level storage module and a third-level storage module, and the data storage module is separated according to the upper level and the lower level, the second-level storage module includes the third-level storage module, the first-level storage module includes the second-level storage module, and when the data reaches the third-level storage module, the data can be classified in a finer manner.

Furthermore, the data classified and stored in the step (4) is managed by a management scheduling module, the management scheduling module comprises an access scheduling module, a content publishing module, a storage management module and a data backup module, the access of the user, the publishing of the system content, the data storage and the data backup are managed, and the effective time of the data can be ensured through the data backup.

Further, the cloud computing system storage module in the step (5) is connected with the application interface module through the management scheduling module, data of the cloud computing system are scheduled and managed through data instructions issued by the application interface, and corresponding data are displayed step by step according to the instructions.

Further, the application interface module in step (5) includes a data storage interface module, a space lease interface module, a common resource interface module, a multi-user data sharing interface module, and a data backup query interface module.

Through the embodiment of the application, classified processing and storage are adopted, the collected data are classified, processed and stored, subsequent query and display are facilitated, the content required by a user can be displayed more accurately in big data through analysis and storage management of a large amount of data, meanwhile, the data can be analyzed and mined through data processing, further deeper data can be displayed, the association degree of the data can be improved, the problem that the data classification is not clear when the data are processed by a data processing method of an existing cloud computing system is solved, the classification is more clear after the data are processed in the cloud computing system, and therefore the user can obtain the data content with higher association degree after the data retrieval is completed, the user can be helped to quickly know the required content through a virtualization technology, and the data retrieval efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.

Fig. 1 is a schematic flow chart of an embodiment of the present application.

Detailed Description

In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, 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.

In this application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.

Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.

Furthermore, the terms "mounted," "disposed," "provided," "connected," and "sleeved" are to be construed broadly. For example, it may be a fixed connection, a removable connection, or a unitary construction; can be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements or components. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

The data processing method in this embodiment may be applied to a host computer, for example, the following host computer convenient to move is provided in this embodiment.

The computer comprises a computer host, a USB interface is arranged on the front surface of the computer host and the end part close to the computer host, a speaker jack is arranged on the right side of the USB interface and positioned on the front surface of the computer host, a power supply button is arranged on the right side of the speaker jack and positioned on the front surface of the computer host, an indicator lamp is arranged on the right side of the power supply button and positioned on the front surface of the computer host, heat dissipation holes are uniformly arranged at the center of the left side wall of the computer host, a threaded hole is arranged at the bottom of the computer host, a universal wheel component is connected with the threaded hole and comprises a threaded rod and a universal wheel, the threaded rod is vertically connected with the center of the end surface of the universal wheel, the threaded rod is connected inside the threaded hole, a handle placing groove is arranged on the end surface of the computer host and the edge positioned on the back surface of the computer host, the inside of handle standing groove is and lie in the main frame and install flexible handle, the tip of flexible handle is provided with flexible handle control button, USB interface, speaker jack, power button, pilot lamp are respectively through wire electric connection on the control mainboard in the main frame inside, the louvre sets up for the axis symmetry based on the main frame, the screw hole is seted up four and is seted up respectively in the four corners department of main frame bottom, four the screw hole correspondence is connected with four universal wheel subassemblies, the threaded rod is threaded connection and dismantled and assembled with the connected mode of screw hole, the universal wheel adopts lockable universal wheel, flexible handle is the flexible handle on the draw-box.

Of course, the present embodiment can also be used for other computer hosts. Here, details are not repeated, and the data processing method according to the embodiment of the present application is described below.

Referring to fig. 1, a data processing method for a cloud computing system includes the following steps:

(1) collecting data and transmitting the data to a cloud computing system;

(2) processing the acquired data;

(3) storing the processed data in a classified manner;

(4) managing and scheduling the stored data;

(5) and displaying the corresponding data according to the personalized needs of the user.

In the step (1), a large amount of data is acquired through the terminal collecting device, the acquired data is directly transmitted to the data acquisition module of the cloud computing system, the data acquisition module in the cloud computing system performs primary classification on the data at the moment, and after the data acquisition module receives the data, the data acquisition module performs primary classification on the large amount of collected data according to the primary identification.

In the step (1), the collected data is divided into five categories of text data, audio, video, picture and position information, corresponding data contents are transmitted to a text data module, an audio module, a video data module, a picture information module and a position information module, and the classified data are processed.

The data processing in the step (2) comprises data preprocessing and data analysis, wherein the data preprocessing comprises decoding processing, data filling processing and noise cleaning processing.

The data analysis in the step (2) includes a splitting unit, a mapping unit, an output unit and a merging storage unit, and the data after classification is split, mapped and merged, wherein the data splitting means that logically unified and integrated data is split into smaller physical units which can be independently managed for storage, so as to facilitate reconstruction, recombination and recovery, and improve the efficiency of creating indexes and sequential scanning, the data mapping relates to a process of matching data fields from one database to another database, is an important component of an ETL process, and can promote data migration, data integration and other important data management tasks, and the data integration is a data integration mode of loading collected different data to a new data source after sorting, cleaning and conversion, and providing a unified data view for data consumers.

And (3) correspondingly performing data preprocessing and data analysis processing on the classified data in the step (2), transmitting the classified data to a storage module, and performing corresponding splitting, mapping and other processing on the data of the text data module, the audio module, the video data module, the picture information module and the position information module, wherein the video data module comprises part of audio data.

The data storage module in the step (3) comprises a first-level storage module, a second-level storage module and a third-level storage module, the first-level storage module, the second-level storage module and the third-level storage module are separated according to the upper level and the lower level, the second-level storage module comprises the third-level storage module, when the first-level storage module reaches the third-level storage module, data can be finely classified, the data are classified according to daily needs of human beings in a classified mode, the data are classified according to the upper-level and lower-level inclusion modes, after the data are sequentially advanced, the required data can be quickly and accurately searched, and the data of each level comprise data keywords of the corresponding level.

And (4) managing the data which are classified and stored in the step (4) through a management scheduling module, wherein the management scheduling module comprises an access scheduling module, a content issuing module, a storage management module and a data backup module, managing the access of the user, the issuing of the system content, the data storage and the data backup, ensuring the effective time of the data through the data backup, identifying the instruction accessed by the user through the access scheduling module, identifying the instruction, scheduling the data of the corresponding level according to the instruction, displaying the data of the corresponding level, preferentially displaying the related data with high criticality, then issuing the content according to the needs of the system, judging the criticality of the data according to the access amount of the data, and backing up and maintaining the related data after the corresponding criticality is reached.

And (5) the cloud computing system storage module is connected with the application interface module through the management scheduling module, data of the cloud computing system are scheduled and managed through data instructions issued by the application interface, corresponding data are displayed step by step according to the instructions, the position source of the access port is judged through the management scheduling module, keywords with high relevancy are provided for the access source, and the management scheduling module schedules and displays contents in the storage module to the interface module between the storage module and the interface module.

And (5) the application interface module comprises a data storage interface module, a space leasing interface module, a public resource interface module, a multi-user data sharing interface module and a data backup query interface module, and the source of the data access is judged, if the access word of the public resource system provides related data content according to the corresponding service content of the public resource, the multi-user data sharing interface can provide more extensive related data.

It is well within the skill of those in the art to implement, without undue experimentation, the present application is not directed to software and process improvements, as they relate to circuits and electronic components and modules.

The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

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