CN116633952B - Data processing system and processing method for pasture - Google Patents
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- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/70—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in livestock or poultry
Abstract
The application belongs to the technical field of big data intelligence, and particularly relates to a data processing system and a processing method for pasture, wherein the data processing system for pasture comprises the following components: the host performs local mapping on the read-write operation data on the public cloud, and the host sends the operation data to the local cloud for storage; the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent to the read-write server for read-write, and the private cloud performs classified storage according to the suffix of the unified data code; the method can save the data to the local cloud, maximally improve the save quantity, play a role in encrypting the data on one hand, ensure the accuracy of the data on the other hand, reduce the calculated quantity of the private cloud to the data, improve the data transmission speed, avoid the phenomenon of packet loss caused by data overflow, avoid the data loss even if the public cloud is stopped, and check the data to judge whether delay exists.
Description
Technical Field
The application belongs to the technical field of big data intelligence, and particularly relates to a data processing system and a processing method for pasture.
Background
At present, a data processing system for pastures mainly adopts a cloud service platform, the cloud service platform is realized by a host and a public cloud, data is directly stored in the public cloud, the host only plays a role in operation, the host does not provide a local storage function or only provides a simple storage function, the data is generally not encrypted and classified due to small memory of the host, and the data can be covered regularly.
Meanwhile, the public cloud has the risk of data leakage, meanwhile, packet loss and delay phenomena exist between the public cloud and the host, on one hand, the safety of data storage is reduced, and on the other hand, the data is inaccurate.
Therefore, there is a need to develop a new pasture data processing system and processing method to solve the above problems.
Disclosure of Invention
The application aims to provide a data processing system and a data processing method for pastures.
In order to solve the above technical problems, the present application provides a data processing system for pasture, which includes: public cloud, host computer, local cloud, read-write server and private cloud; the public cloud is used for reading and writing operation data and cloud time data, the host locally maps the operation data read and written on the public cloud, and the host sends the operation data to the local cloud for storage; the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent into the read-write server for reading and writing, the read-write server sends the unified data code into the private cloud, and the private cloud performs classified storage according to the suffix of the unified data code; and when the host calls the corresponding unified data code through the read-write server, the host decomposes the unified data code into local time data and operation data.
Further, the host compares the decomposed local time data and operation data with cloud time data and operation data on the public cloud.
Further, the decomposed local time data and operation data are compared with cloud time data and operation data on the public cloud.
Further, the public cloud includes: the virtual machine is operated and used for reading and writing operation data and cloud time data; and the cloud database is used for storing the operation data and the cloud time data.
Further, the operation virtual machine and the cloud database are established through a public server.
Further, the common server is provided with a capacitance monitoring module for feeding back capacitance signals.
Further, the host converts the operation data into decimal data.
Further, the host computer converts the local time data into decimal data.
Further, the host randomly inserts the local time data into the operation data with the exception of the suffix segment to form a unified data code.
Further, the private cloud includes: the characteristic database is used for judging the suffixes of the unified data codes; and the classification storage library is used for storing the unified data codes in a classified manner.
Further, the classification repository includes: a plurality of storage virtual machines; each storage virtual machine is used for storing one type of data set respectively; and the characteristic database judges the category of the unified data codes according to the suffixes of the unified data codes so as to store the corresponding unified data codes into the corresponding storage virtual machines.
Further, the classification repository is split into storage virtual machines, and each storage virtual machine is cured.
In another aspect, the present application provides a method for processing a data processing system for pasture, comprising: the method comprises the steps that public cloud read-write operation data and cloud time data are subjected to local mapping by a host, and the host sends the operation data to the local cloud for storage; the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent to the read-write server for reading and writing, the read-write server sends the unified data code to the private cloud, and the private cloud carries out classified storage according to the suffix of the unified data code; when the host calls the corresponding unified data code through the read-write server, the host decomposes the unified data code into local time data and operation data.
Further, the decomposed local time data and operation data on the host are compared with cloud time data and operation data on the public cloud.
Further, the processing method adopts the data processing system for pasture.
The application has the beneficial effects that the read-write operation data on the public cloud is subjected to local mapping through the host, the data can be stored to the local cloud, the storage quantity is improved to the maximum extent, the local time data can be inserted into the operation data to form a unified data code, on one hand, the function of encrypting the data is realized, on the other hand, the accuracy of the data is ensured, the problem that the data is inaccurate due to delay between the public cloud and the host is solved, the data is sent into the private cloud for classified storage through the read-write server as a transfer station, the calculation amount of the private cloud to the data can be reduced, the data transmission speed is improved, the packet loss phenomenon caused by data overflow is avoided, the data is not lost even if the public cloud is stopped, and meanwhile, the data is checked and judged whether the delay exists or not.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic block diagram of a data processing system for pasture according to the present application;
FIG. 2 is a block diagram of the data processing system for pasture according to the present application;
FIG. 3 is a flow chart of unified data code formation of the present application;
FIG. 4 is a block diagram of the structure of a classification repository of the present application;
fig. 5 is a flow chart of a processing method of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Embodiment 1, in this embodiment, as shown in fig. 1 to 5, this embodiment provides a data processing system for pasture, which includes: public cloud, host computer, local cloud, read-write server and private cloud; the public cloud is used for reading and writing operation data and cloud time data, the host locally maps the operation data read and written on the public cloud, and the host sends the operation data to the local cloud for storage; the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent into the read-write server for reading and writing, the read-write server sends the unified data code into the private cloud, and the private cloud performs classified storage according to the suffix of the unified data code; and when the host calls the corresponding unified data code through the read-write server, the host decomposes the unified data code into local time data and operation data.
In this embodiment, the host performs local mapping on the operation data read and written on the public cloud, so that the storage quantity can be maximally improved, local time data can be inserted into the operation data to form a unified data code, on one hand, the function of encrypting the data is achieved, on the other hand, the accuracy of the data is guaranteed, the problem that the data is inaccurate due to delay between the public cloud and the host is solved, the data is sent into the private cloud to be classified and stored through the read-write server serving as a transfer station, the calculation amount of the private cloud to the data can be reduced, the data transmission speed is improved, the packet loss phenomenon caused by data overflow is avoided, even if the public cloud is stopped, the data is not lost, and meanwhile, whether the delay exists is checked and judged.
In this embodiment, the public cloud may be OpenStack, ali cloud, tencent cloud, hua cloud, or AWS.
In this embodiment, the host compares the resolved local time data and operation data with cloud time data and operation data on the public cloud.
In this embodiment, verification data can be implemented on a local host, and because delay and packet loss are likely to occur when operation data is transmitted to and stored in a public cloud, the operation data is firstly used for searching operation data matched with the operation data on the public cloud, if the operation data is not found in the public cloud, packet loss is indicated, if the operation data is found in the public cloud, after the operation data is found in the public cloud, the local time data is compared with cloud time data, if the local time data is consistent with the cloud time data, the operation data is indicated to be not delayed, otherwise, the operation data is indicated to be delayed, and a function of verifying the data is implemented.
In this embodiment, the resolved local time data and operation data are compared with cloud time data and operation data on the public cloud.
In this embodiment, the verification data can be implemented on the public cloud, and since there is a possibility of delay and packet loss when the operation data is transmitted to the public cloud for storage, the operation data matched with the operation data is firstly searched on the public cloud, if the operation data is not searched on the public cloud, packet loss is indicated, if the operation data is not searched on the public cloud, the local time data is compared with the cloud time data, if the local time data is consistent with the cloud time data, no delay is indicated, otherwise, the delay is indicated, and the function of verifying the data is implemented.
In this embodiment, the public cloud includes: the virtual machine is operated and used for reading and writing operation data and cloud time data; and the cloud database is used for storing the operation data and the cloud time data.
In this embodiment, the operation virtual machine and the cloud database are established through a public server.
In this embodiment, the virtual machine is operated to be accessed by the host in a software form, so as to implement a data read-write function.
In this embodiment, the common server is provided with a capacitance monitoring module for feeding back a capacitance signal.
In this embodiment, the host determines whether the cloud database can read and write data normally through the feedback capacitance signal.
In this embodiment, the host converts the operation data into decimal data.
In this embodiment, the host computer converts the local time data into decimal data.
In the embodiment, the operation data and the local time data are converted into decimal data, so that data unification can be realized, and subsequent processing of the operation data and the local time data is convenient.
In this embodiment, the host randomly inserts the local time data into the operation data except for the suffix segment to form a unified data code.
In this embodiment, the local time data is randomly inserted into the operation data except the suffix segment, so that the formed unified data code is safer, and meanwhile, the suffix segment in the operation data is reserved, so that the type of the unified data code can be conveniently judged.
In this embodiment, the read-write server is used as a transfer station, and a server with a higher protocol is selected to meet the data read-write and transmission requirements.
In this embodiment, the private cloud includes: the characteristic database is used for judging the suffixes of the unified data codes; and the classification storage library is used for storing the unified data codes in a classified manner.
In this embodiment, the suffix of the unified data code may be a file type, a resource class, and the like, and may be set according to actual use conditions.
In this embodiment, the classification repository includes: a plurality of storage virtual machines; each storage virtual machine is used for storing one type of data set respectively; and the characteristic database judges the category of the unified data codes according to the suffixes of the unified data codes so as to store the corresponding unified data codes into the corresponding storage virtual machines.
In this embodiment, the classification repository is split into storage virtual machines, and each storage virtual machine is cured.
At present, the virtual machines of the private cloud are integrated, when data are transmitted to the private cloud, the private cloud can separate out one virtual machine to receive the data, but the data are not classified, the data exceed the capacity of the virtual machine, at the moment, the private cloud expands the capacity of the virtual machine, but the private cloud is separated out of the virtual machine and the capacity of the virtual machine for a certain time, and the data transmission is not interrupted, so that the phenomenon of packet loss caused by data overflow exists in the process, in the embodiment, the classified storage library is directly separated into n storage virtual machines to be solidified, each storage virtual machine corresponds to one data group, on one hand, the data classification is realized, on the other hand, the processes of separating out the virtual machine and the capacity of the virtual machine are omitted, the problem of packet loss caused by data overflow is solved, and the stability of data storage is improved.
Embodiment 2, on the basis of embodiment 1, this embodiment provides a processing method of a data processing system for pasture, including: the method comprises the steps that public cloud read-write operation data and cloud time data are subjected to local mapping by a host, and the host sends the operation data to the local cloud for storage; the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent to the read-write server for reading and writing, the read-write server sends the unified data code to the private cloud, and the private cloud carries out classified storage according to the suffix of the unified data code; when the host calls the corresponding unified data code through the read-write server, the host decomposes the unified data code into local time data and operation data.
In this embodiment, the resolved local time data and operation data on the host are compared with cloud time data and operation data on the public cloud.
In this example, the data processing system for pasture as provided in example 1 was used as the processing method.
In summary, the method and the system can store the operation data read and written on the public cloud to the local cloud through the host, maximize the storage capacity, insert the local time data into the operation data to form the unified data code, on one hand, play a role in encrypting the data, on the other hand, ensure the accuracy of the data, overcome the problem that the data is inaccurate due to delay between the public cloud and the host, send the data into the private cloud for classified storage through the read-write server as a transfer station, reduce the calculation amount of the private cloud to the data, improve the data transmission speed, avoid the phenomenon of packet loss caused by data overflow, and even if the public cloud stops, the data is not lost, and meanwhile check and judge whether the delay exists.
The components (components not illustrating the specific structure) selected in the present application are common standard components or components known to those skilled in the art, and the structures and principles thereof are known to those skilled in the art through technical manuals or through routine experimental methods.
In the description of embodiments of the present application, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.
In the description of the present application, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
With the above-described preferred embodiments according to the present application as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present application. The technical scope of the present application is not limited to the description, but must be determined according to the scope of claims.
Claims (12)
1. A data processing system for pasture, comprising:
public cloud, host computer, local cloud, read-write server and private cloud; wherein the method comprises the steps of
The public cloud is used for reading and writing operation data and cloud time data, the host performs local mapping on the operation data read and written on the public cloud, and the host sends the operation data to the local cloud for storage;
the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent into the read-write server for reading and writing, the read-write server sends the unified data code into the private cloud, and the private cloud performs classified storage according to the suffix of the unified data code; and
when the host invokes the corresponding unified data code through the read-write server, the host decomposes the unified data code into local time data and operation data;
comparing the decomposed local time data and operation data with cloud time data and operation data on public cloud on the host;
and comparing the decomposed local time data and operation data with cloud time data and operation data on the public cloud.
2. The data processing system for pasture as set forth in claim 1, wherein,
the public cloud includes:
the virtual machine is operated and used for reading and writing operation data and cloud time data;
and the cloud database is used for storing the operation data and the cloud time data.
3. A data processing system for pasture as in claim 2, wherein,
and the operation virtual machine and the cloud database are established through a public server.
4. The data processing system for pasture as in claim 3, wherein,
the common server is provided with a capacitance monitoring module for feeding back capacitance signals.
5. The data processing system for pasture as set forth in claim 1, wherein,
the host converts the operation data into decimal data.
6. The data processing system for pasture as recited in claim 5, wherein,
the host computer converts the local time data into decimal data.
7. The data processing system for pasture as recited in claim 6, wherein,
the host randomly inserts the local time data into the operation data except the suffix segment to form a unified data code.
8. The data processing system for pasture as set forth in claim 1, wherein,
the private cloud includes:
the characteristic database is used for judging the suffixes of the unified data codes;
and the classification storage library is used for storing the unified data codes in a classified manner.
9. The data processing system for pasture as recited in claim 8, wherein,
the classification repository includes: a plurality of storage virtual machines;
each storage virtual machine is used for storing one type of data set respectively;
and the characteristic database judges the category of the unified data codes according to the suffixes of the unified data codes so as to store the corresponding unified data codes into the corresponding storage virtual machines.
10. The data processing system for pasture as recited in claim 9, wherein,
splitting the classification repository into storage virtual machines, and solidifying the storage virtual machines.
11. A method of processing a data processing system for pasture, comprising:
the method comprises the steps that public cloud read-write operation data and cloud time data are subjected to local mapping by a host, and the host sends the operation data to the local cloud for storage;
the host inserts the local time data into the operation data to form a unified data code, so that the unified data code is sent to the read-write server for reading and writing, the read-write server sends the unified data code to the private cloud, and the private cloud carries out classified storage according to the suffix of the unified data code; and
when the host invokes the corresponding unified data code through the read-write server, the host decomposes the unified data code into local time data and operation data;
comparing the decomposed local time data and operation data on the host with cloud time data and operation data on the public cloud;
and comparing the decomposed local time data and operation data with cloud time data and operation data on the public cloud.
12. A method of processing a data processing system for pasture as claimed in claim 11, characterized in that a data processing system for pasture as claimed in any one of claims 1-10 is used.
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