CN115756968A

CN115756968A - Network-based data backup method and system and cloud platform

Info

Publication number: CN115756968A
Application number: CN202211533844.3A
Authority: CN
Inventors: 蔡俊涛
Original assignee: Longgang Yantai Technology Consulting Co ltd
Current assignee: Xi'an Huoda Network Technology Co ltd
Priority date: 2022-12-02
Filing date: 2022-12-02
Publication date: 2023-03-07
Anticipated expiration: 2042-12-02
Also published as: CN115756968B

Abstract

According to the network-based data backup method, system and cloud platform provided by the embodiment of the invention, when data backup processing is carried out, all data information in an internet service information log is not mechanically and directly backed up, but a backup guidance change record of a target service data backup item is determined according to the internet service information log, and the backup guidance change record can reflect the data update change condition of the target service data backup item in the operation process and the self-adaptive change condition of backup guidance appointed by the data update change condition. On the basis, the data backup processing of the target business data backup project can be flexibly and intelligently guided by utilizing the backup guidance change record, so that the efficiency of data backup processing is improved, and unnecessary resource waste and occupation are reduced.

Description

Network-based data backup method and system and cloud platform

Technical Field

The invention relates to the technical field of data processing, in particular to a data backup method and system based on a network and a cloud platform.

Background

Data backup is the basis of disaster recovery, and refers to a process of copying all or part of a data set from a hard disk or an array of an application host to another storage medium in order to prevent data loss caused by misoperation of a system or system failure.

The traditional data backup mainly adopts a built-in or external tape unit for cold backup. However, this method can only prevent human failures such as misoperation, and the recovery time is long.

With the continuous development of the technology, the amount of data is increased, and a few enterprises begin to adopt network backup. Network backups are typically implemented by specialized data storage management software in conjunction with corresponding hardware and storage devices. At present, the demand for efficiency and intelligence of data backup is higher and higher, but most data backup technologies have difficulty meeting the demand.

Disclosure of Invention

In order to solve the technical problems in the related art, the invention provides a data backup method and system based on a network and a cloud platform.

In a first aspect, an embodiment of the present invention provides a network-based data backup method, which is applied to a data backup cloud platform, and the method includes: determining a backup guidance change record of a target service data backup item according to the acquired internet service information log; and carrying out data backup processing on the target service data backup item by using the backup guidance change record.

It can be seen that, when performing data backup processing, all data information in the internet service information log is not mechanically and directly backed up, but a backup guidance change record of a target service data backup item is determined according to the internet service information log, and the backup guidance change record can reflect a data update change condition of the target service data backup item in an operation process and an adaptive change condition of backup guidance designated for the data update change condition. On the basis, the data backup processing of the target business data backup project can be flexibly and intelligently guided by utilizing the backup guidance change record, so that the efficiency of data backup processing is improved, and unnecessary resource waste and occupation are reduced.

For some preferred embodiments, the determining, according to the obtained internet service information log, a backup guidance change record of a target service data backup item includes: calling an internet service information log, and sampling at least two groups of service information backup applications from the internet service information log by combining with a configured sampling strategy; refining the data item element field of each service data backup item in each service information backup application, and then respectively determining the data item state information and the data item key words of each service data backup item in each service information backup application; determining candidate service data backup items matched with the same target service data backup item in the at least two groups of service information backup applications by combining the data item element fields, the data item state information and the data item keywords of the service information backup applications; and determining the backup guidance change record of the target business data backup item by combining the data item state information of the candidate business data backup item corresponding to the target business data backup item in the at least two groups of business information backup applications respectively.

It can be seen that by abstracting the data item element field, the data item state information and the data item key word of the business data backup item from the business information backup application, determining a plurality of business data backup items matching the same target business data backup item, and determining the backup guidance change record of the same target business data backup item, from another perspective, the data item element field, the data item state information and the data item key word are comprehensively processed, and the backup guidance change record of the target business data backup item is determined by combining the description contents, so that the efficiency of determining the personalized customization of the data backup execution strategy of the business data backup item and the comprehensiveness of the backup guidance change record of the target business data backup item are improved, and the efficiency and the intelligentization degree of data backup can be improved.

For some preferred embodiments, the at least two sets of service information backup applications include a first service information backup application and a second service information backup application, and the first service information backup application and the second service information backup application are service information backup applications having time sequential contact; the determining, by combining the data item element field, the data item state information, and the data item keyword of each service information backup application, the candidate service data backup items matching the same target service data backup item in the at least two sets of service information backup applications includes: determining at least one first service data backup item in the first service information backup application and at least one second service data backup item in the second service information backup application; for each first service data backup item, determining a backup item association degree between the first service data backup item and each second service data backup item by combining data item state information, data item keywords and data item element fields of the first service data backup item in the first service information backup application and data item state information, data item keywords and data item element fields of each second service data backup item in the second service information backup application; and determining the first service data backup item and the second service data backup item which are matched with the same target service data backup item by combining the association degree of the backup items, and determining the first service data backup item and the second service data backup item which are matched with the same target service data backup item as the candidate service data backup items.

Therefore, considering that a plurality of service data backup items may exist in each service information backup application, for each first service data backup item, the association degree of the backup item with each second service data backup item can be determined by combining the data item state information, the data item keywords and the data item element fields, so that the comprehensive coverage processing of each first service data backup item can be realized, the analysis omission of the items can be avoided, and the accuracy of determining the candidate service data backup items can be improved.

For some preferred embodiments, the determining, for each first service data backup item, a backup item association degree between the first service data backup item and each second service data backup item in combination with the data item status information, the data item keyword, and the data item element field of the first service data backup item in the first service information backup application and the data item status information, the data item keyword, and the data item element field of each second service data backup item in the second service information backup application includes: regarding each first service data backup item, determining at least one second target service data backup item from the second service information backup application in combination with the data item element field, the data item state information and at least one target description content in the data item key words; determining the association degree of the backup items between the first service data backup item and the second target service data backup item by combining the data item element field, the data item state information and the data item key word; the determining, in combination with the association degree of the backup items, the first service data backup item and the second service data backup item that match the same target service data backup item, and determining the first service data backup item and the second service data backup item that match the same target service data backup item as the candidate service data backup items, includes: and determining the first service data backup item and the second target service data backup item which are matched with the same target service data backup item by combining the association degree of the backup items between the first service data backup item and the second target service data backup item, and determining the first service data backup item and the second target service data backup item which are matched with the same target service data backup item as the candidate service data backup items.

It can be seen that, for each first service data backup item, at least one second target service data backup item in the second service information backup application is determined by combining not less than one target description content in the data item element field, the data item state information and the data item keyword, and from another perspective, the influence range of the second service data backup item in the second service information backup application can be simplified by combining not less than one target description content, so that the efficiency of calculating the association degree can be improved, and the timeliness of determining the association degree of the backup items between the first service data backup item and each second service data backup item can be guaranteed.

For some preferred embodiments, the determining, for each first service data backup item, not less than one second target service data backup item from the second service information backup application in combination with not less than one target description content in the data item element field, the data item status information, and the data item keyword includes: determining the item state association degree of the first service data backup item and each second service data backup item by combining the data item state information of the first service data backup item in the first service information backup application and the data item state information of each second service data backup item in the second service information backup application with respect to each first service data backup item under the condition that the difference value of the acquisition time sequence of the first service information backup application and the second service information backup application is smaller than the preconfigured time sequence difference; determining whether the item state association degree of the first business data backup item and each second business data backup item reaches a first set index; and determining a second business data backup item corresponding to the item state association degree reaching the first set index as the second target business data backup item.

It can be seen that, by determining whether the item state association degree of the first service data backup item and each second service data backup item reaches the first set index, and determining the second service data backup item corresponding to the item state association degree reaching the first set index as the second target service data backup item, from another perspective, the second service data backup item corresponding to the item state association degree not reaching the first set index is deleted, so that the timeliness degree of determining the second target service data backup item can be improved.

For some preferred embodiments, the determining, for each first service data backup item, not less than one second target service data backup item from the second service information backup application in combination with not less than one target description content in the data item element field, the data item status information, and the data item keyword includes: determining, for each first service data backup item, an item keyword association degree between the first service data backup item and each second service data backup item in combination with a data item keyword of the first service data backup item and a data item keyword of each second service data backup item; determining whether the item keyword association degree between the first business data backup item and each second business data backup item reaches a second set index; and determining a second business data backup item corresponding to the item keyword association degree reaching the second set index as the second target business data backup item.

It can be seen that, not limited to the above rule for simplifying the influence range of the second business data backup item by the first setting index, the second business data backup item corresponding to the item keyword association degree that reaches the second setting index may also be determined as a second target business data backup item, and from another perspective, the second business data backup item corresponding to the item keyword association degree that does not reach the second setting index may be deleted, so that the rule for determining the second target business data backup item has more choices, and the timeliness for determining the second target business data backup item may be improved.

For some preferred embodiments, the determining, in combination with the backup item association degree, the first service data backup item and the second service data backup item that match the same target service data backup item includes: determining whether linkage processing is finished between the first business data backup item and each second business data backup item or not by combining the association degree of the backup items and the first item processing guide information; and determining the first service data backup item and the second service data backup item which are subjected to linkage processing as the first service data backup item and the second service data backup item which are matched with the same target service data backup item.

Therefore, by combining the association degree of the backup items and the processing guide information of the first item, the item combination analysis is performed on the first service data backup items and each second service data backup item, so that the accuracy and the reliability of the item combination analysis can be improved, and the accuracy of determining the first service data backup items and the second service data backup items matching the same target service data backup items can be improved.

For some preferred embodiments, the determining, for the first service data backup item and the second service data backup item to be subjected to linkage processing, the first service data backup item and the second service data backup item that match the same target service data backup item includes: determining the first service data backup item and the second service data backup item which are subjected to linkage processing as a service data backup item set; and under the condition that the number of the business data backup item sets is not less than two, combining second item processing guide information, determining a target business data backup item set from a plurality of business data backup item sets, and determining a first business data backup item and a second business data backup item in the target business data backup item set as the first business data backup item and the second business data backup item which are matched with the same target business data backup item.

Therefore, under the condition that the number of the service data backup item sets is not less than two, the target service data backup item set is determined by combining the second item processing guide information, and from another point of view, the target service data backup item set with the highest adaptation degree can be determined from the plurality of service data backup item sets, so that the accuracy of calculating the first service data backup item and the second service data backup item which are matched with the same target service data backup item can be improved.

For some preferred embodiments, after determining the backup guidance change record of the target service data backup item in combination with the data item status information of the candidate service data backup item corresponding to the target service data backup item in the plurality of service information backup applications, the method further includes: and determining a data backup execution strategy of the target business data backup item by combining the backup guidance change record of the target business data backup item.

Therefore, the data backup execution strategy is determined by combining the complete backup guidance change record of the target service data backup item, so that the precision of determining the data backup execution strategy can be improved, the targeted data backup can be conveniently performed by combining the data backup execution strategy, and the data backup efficiency is improved.

For some preferred embodiments, the performing, by using the backup guidance change record, data backup processing on the target business data backup item includes: and carrying out data backup processing on the target service data backup items based on the data backup execution strategy.

Therefore, the targeted data backup is performed by combining the data backup execution strategy, so that the data backup efficiency can be improved.

In a second aspect, the invention further provides a network-based data backup system, which includes a data backup cloud platform and a data service end, which are in communication with each other; the data backup cloud platform is used for determining a backup guidance change record of a target service data backup project according to the acquired internet service information log; and carrying out data backup processing on the target service data backup item by using the backup guidance change record.

In a third aspect, the present invention further provides a data backup cloud platform, including a processor and a memory; the processor is in communication with the memory, and the processor is configured to read the computer program from the memory and execute the computer program to implement the method described above.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

Fig. 1 is a schematic flowchart of a network-based data backup method according to an embodiment of the present invention.

Fig. 2 is a schematic diagram of a communication architecture of a network-based data backup system according to an embodiment of the present invention.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

The method embodiment provided by the embodiment of the invention can be executed in a data backup cloud platform, a computer device or a similar arithmetic device. Taking the example of running on a data backup cloud platform, the data backup cloud platform 10 may include one or more processors 102 (the processors 102 may include but are not limited to processing devices such as a microprocessor MCU or a programmable logic device FPGA), and a memory 104 for storing data, and optionally, the data backup cloud platform may further include a transmission device 106 for communication functions. It can be understood by those of ordinary skill in the art that the above structure is only an illustration, and does not limit the structure of the data backup cloud platform. For example, the data backup cloud platform 10 may also include more or fewer components than shown above, or have a different configuration than shown above.

The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as a computer program corresponding to a network-based data backup method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the above-mentioned method. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 104 may further include memory located remotely from processor 102, which may be connected to data backup cloud platform 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the data backup cloud platform 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used to communicate with the internet in a wireless manner.

Based on this, please refer to fig. 1, where fig. 1 is a schematic flowchart of a data backup method based on a network according to an embodiment of the present invention, and the method is applied to a data backup cloud platform and further includes the following technical solutions.

Step one, determining a backup guidance change record of a target service data backup item according to the acquired internet service information log.

And secondly, performing data backup processing on the target service data backup item by using the backup guidance change record.

Based on the first step and the second step, when the data backup process is performed, all data information in the internet service information log is not directly mechanically backed up, but a backup guidance change record of a target service data backup item is determined according to the internet service information log, and the backup guidance change record can reflect the data update change condition of the target service data backup item in the operation process and the self-adaptive change condition of the backup guidance designated by the data update change condition. On the basis, the data backup processing of the target business data backup project can be flexibly and intelligently guided by using the backup guidance change record, so that the efficiency of data backup processing is improved, and unnecessary resource waste and occupation are reduced.

The following description is directed to exemplary/non-limiting embodiments of step one and step two. Regarding step one, the implementation manner may include the technical solutions described in step 11 to step 14.

And step 11, calling the Internet service information log, and sampling at least two groups of service information backup applications from the Internet service information log by combining with the configured sampling strategy.

In some non-limiting examples, those skilled in the art will appreciate that the configured sampling policy may be a dynamically configured information log sampling interval (sampling time step), a dynamically configured number of information log samples, a dynamically configured sampling start time, and the like.

In some non-limiting examples, when at least two sets of service information backup applications are sampled, the internet service information log may be split according to a log text analysis rule, and service information backup applications may be sampled from the internet service information log according to a configured sampling strategy, so as to determine at least two sets of service information backup applications from the internet service information log. The internet service information log can be obtained by at least one data backup processing system/server/platform, and the number of the data backup processing systems/servers/platforms can be two.

In other non-limiting examples, the internet service information log may be data information interactive contents of various web3.0 services, and such data information interactive contents have certain value and importance, and thus, related data backup needs to be performed. For example, the internet service information log may be e-commerce interactive content, digital office interactive content, intelligent medical interactive content, and the like, and those skilled in the art may flexibly select an application environment of the internet service information log.

And step 12, refining the data item element field of each service data backup item in each service information backup application, and then respectively determining the data item state information and the data item key words of each service data backup item in each service information backup application.

In some exemplary aspects, the data item element field may be understood as a feature vector/description array abstracted by a dynamically configured feature mining scheme for reflecting detailed features of different business data backup items.

In some non-limiting examples, feature mining is one of the key techniques in the web3.0 joint technology, and may be implemented in conjunction with an AI algorithm. For example, the data item element field may be refined by a dynamically configured feature mining model, which may be an AI algorithm that is selectable by a technical unit in the art to implement the present solution.

On the basis of the above, the data item status information may be obtained through visualization processing by the item capture unit, and the data item status information may include location unit information of the business data backup item, where the location unit information of the business data backup item includes a first unit size (such as a unit vertical size) and a second unit size (such as a unit horizontal size) of a location unit of the business data backup item, and a unit label of the location unit of the business data backup item and a distribution of 4 unit key points of the item capture unit, and from another perspective, the visual location data of the item capture unit is equivalent to the data item status information.

Further, the data item keyword may be understood as an item category corresponding to the service data backup item, for example, personal user data, enterprise user data, office file resources, or system data information.

On the basis, after at least two groups of service information backup applications are obtained, the state analysis of service data backup items and the endowment of keywords of the service data backup items can be respectively carried out on each service information backup application, so that the data item state information and the data item keywords of each service data backup item are obtained from the service information backup applications.

In some non-limiting examples, the status analysis of the service data backup item and the keyword assignment of the service data backup item related to the service information backup application are implemented by manual assignment, so that the accuracy of the determined data item status information and the data item keyword can be ensured, or configured AI algorithms respectively used for performing the status analysis of the service data backup item and the keyword assignment of the service data backup item can be used, so that the accuracy of the status analysis of the service data backup item and the keyword assignment of the service data backup item can be improved.

It can be understood that, when performing the status analysis of the service data backup items and the keyword assignment of the service data backup items on the service information backup application, considering that there may be interference in the service information backup application, such interference information may not be considered.

And step 13, determining candidate service data backup items matched with the same target service data backup item in the at least two groups of service information backup applications by combining the data item element fields, the data item state information and the data item key words of the service information backup applications.

It can be understood that after the data item element field, the data item state information, and the data item keyword in each service information backup application are obtained, the data item element field, the data item state information, and the data item keyword in each service information backup application may be used to perform item combination analysis and matching on each service data backup item corresponding to different service information backup applications, respectively, to determine candidate service data backup items belonging to the same target service data backup item.

Taking a service data backup item in a service information backup application1 and a service data backup item in a service information backup application2 as examples, the service information backup application1 includes a service data backup item project _ a1, a service data backup item project _ a2, and a service data backup item project _ a3, the service information backup application2 includes a service data backup item project _ b1, a service data backup item project _ b2, and a service data backup item project _ b3, and if the service data backup application is processed by linking a data item element field, data item state information, and a service data backup item attribute of each service data backup item, it is found that the service data backup item project _ a1 and the service data backup item project _ b1 correspond to the same target service data backup item, service data backup project _ a2 and service data backup project _ b2 are corresponding to the same target service data backup project, service data backup project _ a3 and service data backup project _ b3 are corresponding to the same target service data backup project, that is, service data backup project _ a1 and service data backup project _ b1 belong to candidate service data backup projects of target service data backup project object 1 respectively existing in service information backup application1 and service information backup application2, further, service data backup project _ a2 and service data backup project _ b2 belong to candidate service data backup projects of target service data backup project object 2 respectively existing in service information backup application1 and service information backup application2, service data project _ a3 and service data backup project _ b3 belong to candidate service data backup project of target service data backup project object 3 respectively existing in service information backup application1 and service information backup application1 respectively And candidate service data backup items existing in the service information backup application 2.

And step 14, determining the backup guidance change record of the target business data backup item by combining the data item state information of the candidate business data backup item corresponding to the target business data backup item in the at least two groups of business information backup applications respectively.

Further, the backup guidance change record of the target business data backup item may be understood as a data information update condition of the target business data backup item, and may be represented in a form of a related characteristic relationship network, so that characteristics of data to be backed up of the target business data backup item may be summarized, and thus an update record of the target business data backup item (for example, a data information content change of a file resource item at each time interval) is determined based on a global angle, and the update record may provide a reference for data backup.

It can be understood that, after determining the candidate service data backup items corresponding to the target service data backup items in each service information backup application in association, the data information update/backup guidance update summary and other processing may be performed through the data item status information of each candidate service data backup item in the internet service information log to which the candidate service data backup item belongs, so as to determine the backup guidance change record of the target service data backup item.

For some preferred embodiments, for step 13, the at least two sets of service information backup applications include a first service information backup application and a second service information backup application, and the first service information backup application and the second service information backup application are service information backup applications that are in time contact with each other; when determining candidate service data backup items matching the same target service data backup item in the at least two sets of service information backup applications in combination with the data item element field, the data item state information, and the data item keyword of each service information backup application, the method may further include the contents described in the following steps 131 to 133.

Step 131, determining at least one first service data backup item in the first service information backup application and at least one second service data backup item in the second service information backup application.

Further, for the timeliness of the project processing, the plurality of service information backup applications may be clustered, every two uninterrupted service information backup applications are taken as a group to become a group of service information backup applications with time sequential contact, from another perspective, each service information backup application may be split into two groups of service information backup applications with time sequential contact, the service information backup applications with time sequential contact include the two uninterrupted service information backup applications, for the service information backup applications with time sequential contact, any service information backup application may be taken as a first service information backup application, the other service information backup application may be taken as a second service information backup application, and then, according to the data project element field, the data project state information and the data project key words, it may be determined that at least one first service data backup project in the first service information backup application in the service information backup applications with time sequential contact and at least one second service data project in the second service information backup application in the service information backup applications with time sequential contact are not less than one.

Step 132, for each first service data backup item, determining a backup item association degree between the first service data backup item and each second service data backup item by combining the data item state information, the data item keyword, and the data item element field of the first service data backup item in the first service information backup application, and the data item state information, the data item keyword, and the data item element field of each second service data backup item in the second service information backup application.

It can be understood that, for each first service data backup item in the first service information backup application, in order to obtain a second service data backup item of the same target service data backup item corresponding to the first service data backup item through accurate linkage processing, item combination analysis needs to be performed on the first service data backup item and each second service data backup item in the second service information backup application, and during item linkage processing, the association degree of the backup items between the first service data backup item and each second service data backup item can be determined by combining the data item state information, the data item keywords, and the data item element fields of the first service data backup item and each second service data backup item.

Step 133, determining the first service data backup item and the second service data backup item matching the same target service data backup item in combination with the backup item association degree, and determining the first service data backup item and the second service data backup item matching the same target service data backup item as the candidate service data backup items.

For example, the association degree of the backup items may reflect the similarity between two service data backup items, and in view of this, after the association degree of the backup items is determined, the first service data backup items and each second service data backup item may be subjected to item combination analysis according to the association degree of the backup items between each first service data backup item and each second service data backup item, so as to determine the first service data backup item and the second service data backup item that match the same target service data backup item, and from another perspective, the first service data backup item and the second service data backup item with the largest association degree of the backup items are determined as the same target service data backup item, so as to improve the accuracy of determining the candidate service data backup items.

Illustratively, because a plurality of service data backup items may exist in each service information backup application, for each first service data backup item, the data item state information, the data item keywords, and the data item element fields may be combined to determine the backup item association degree between each second service data backup item, so that a comprehensive overlay processing (traversal processing) on each first service data backup item may be implemented, which may avoid item analysis omission, and may further facilitate improving the precision of determining candidate service data backup items.

For some preferred embodiments, because a plurality of service data backup items may exist in each service information backup application, for each first service data backup item in the first service information backup application, the backup item association degree between the first service data backup item and each second service data backup item needs to be determined, so that the calculation overhead of the backup item association degree is relatively large. With respect to steps 132 and 133, when determining the association degree of the backup items between the first service data backup item and each second service data backup item, and determining the first service data backup item and the second service data backup item matching the same target service data backup item in combination with the association degree of the backup items, and determining the first service data backup item and the second service data backup item matching the same target service data backup item as the candidate service data backup items, steps 21 to 23 may be included.

And step 21, regarding each first service data backup item, determining at least one second target service data backup item from the second service information backup application by combining the data item element field, the data item state information and at least one target description content in the data item key words.

Further, the second target service data backup item is not less than one of a plurality of second service data backup items in the second service information backup application. From another perspective, by combining the data item element field, the data item state information, and the data item keyword, with not less than one target description content (description content can be understood as different types of feature information), it is determined that there is not less than one second target service data backup item, and from another perspective, by not less than one target description content, it is possible to simplify the influence range of the second service data backup item to be subjected to item combination analysis in the second service information backup application (local service information backup application), so as to improve the efficiency of association calculation, and ensure the timeliness of determining the association degree of the backup item between the first service data backup item and each second service data backup item.

And step 22, determining the association degree of the backup items between the first service data backup item and the second target service data backup item by combining the data item element field, the data item state information and the data item key word.

Step 23, determining the first service data backup item and the second target service data backup item matching the same target service data backup item by combining the backup item association degree between the first service data backup item and the second target service data backup item, and determining the first service data backup item and the second target service data backup item matching the same target service data backup item as the candidate service data backup item.

In some non-limiting examples, when determining the association degree of the backup item between the first business data backup item and the second target business data backup item, the field similarity between the first business data backup item and the second target business data backup item may be determined by first combining the data item element field of the first business data backup item in the first business information backup application and the data item element field of the second target business data backup item in the second business information backup application.

In some non-limiting examples, cosine similarity between two data item element fields may be determined in combination with a data item element field of the first service data backup item in the first service information backup application and a data item element field of the second target service data backup item in the second service information backup application, and field similarity between the first service data backup item and the second target service data backup item may be determined in combination with the cosine similarity.

Further, the item state association degree of the first service data backup item and the second target service data backup item is determined by combining the data item state information of the first service data backup item in the first service information backup application and the data item state information of the first target service data backup item in the second service information backup application.

For example, the item state association degree between the first service data backup item and the second target service data backup item may be determined by a relative position tag indicated by the data item state information, and from another perspective, it is determined whether the visual positioning data of the first service data backup item and the visual positioning data of the second target service data backup item are changes matching different moments of the same service data backup item, from the data information change characteristics of the service data backup items.

For example, the data item status information may include location unit information of a service data backup item, where the location unit information of the service data backup item includes a first unit size and a second unit size of a location unit of the service data backup item, and a unit label of the location unit of the service data backup item, and regarding the first unit size, the second unit size and the unit label of the location unit of the service data backup item, the first unit size, the second unit size and the unit label of the location unit of the service data backup item may be determined by obtaining relative position labels of four unit areas of the location unit of the service data backup item, such as the relative position label in the service information backup application or the relative position label further after conversion through the relative position labels.

For some examples, the determining the item state association degree through the data item state information may be determining the similarity of the positioning units of the first and second target business data backup items by combining a first unit size and a second unit size of a positioning unit of a business data backup item of the first business data backup item and a first unit size and a second unit size of a positioning unit of a business data backup item of the second target business data backup item, and determining the key distribution similarity of the first and second target business data backup items by combining an item capture unit tag of the first business data backup item and an item capture unit tag of the second target business data backup item.

For some preferred embodiments, under the condition that the item-state association includes the positioning-unit similarity and the key-distribution similarity, when determining the item-state association, the item-state association may be obtained by combining a confidence coefficient corresponding to the positioning-unit similarity and a confidence coefficient corresponding to the key-distribution similarity.

Further, the data item keyword of the first service data backup item in the first service information backup application and the data item keyword of the first target service data backup item in the second service information backup application may be combined to determine the item keyword association degree between the first service data backup item and the second target service data backup item.

For some examples, in conjunction with a data item key, it may be determined whether the first business data backup item and the second target business data backup item are the same or similar business data backup items. In some non-limiting examples, further, a comparison analysis may be performed on the service data backup item category of the first service data backup item and the service data backup item category of the second target service data backup item through a service data backup item category of the first service data backup item to determine whether the first service data backup item and the second target service data backup item are directed to the same or almost the same service data backup item, if the first service data backup item and the second target service data backup item are directed to the same or almost the same service data backup item, the value of L1 and L2 may be reflected by "L1", and if the first service data backup item and the second target service data backup item are not directed to the same or almost the same service data backup item, the value of L2 may be unlimited.

It can be understood that, after the field similarity, the item state association degree, and the item keyword association degree are obtained, the backup item association degree between the first service data backup item and the second target service data backup item may be determined according to a first eccentricity coefficient corresponding to the field similarity, a second eccentricity coefficient corresponding to the item state association degree, and a third eccentricity coefficient corresponding to the item keyword association degree. From another perspective, after the field similarity, the item state association degree, and the item keyword association degree are obtained, a first eccentricity coefficient corresponding to the field similarity, a second eccentricity coefficient corresponding to the item state association degree, and a third eccentricity coefficient corresponding to the item keyword association degree may be obtained, and a final backup item association degree of the first service data backup item and the second target service data backup item may be determined according to a weighting result after a product of the backup item association degree and the corresponding eccentricity coefficient.

It can be understood that after the last backup item association degree of the first service data backup item and the second target service data backup item is obtained, whether the first service data backup item and the second target service data backup item are the same target service data backup item may be determined according to the last backup item association degree, for example, under the condition that the last backup item association degree is greater than a set determination value, the first service data backup item and the second target service data backup item are considered as the same target service data backup item, and the first service data backup item and the second target service data backup item matching the same target service data backup item are determined as the candidate service data backup items.

For some preferred embodiments, regarding step 21, when determining, in relation to each first service data backup item, not less than one second target service data backup item from the second service information backup application in combination with not less than one target description content in the data item element field, the data item status information, and the data item keyword, the following steps 211 to 213 may be included.

Step 211, determining, for each first service data backup item, an item state association degree between the first service data backup item and each second service data backup item, in combination with data item state information of the first service data backup item in the first service information backup application and data item state information of the second service data backup item in the second service information backup application, under a condition that a difference between acquisition timing sequences of the first service information backup application and the second service information backup application is smaller than a preconfigured timing sequence difference.

In some non-limiting examples, if the difference between the collection time sequences of the first service information backup application and the second service information backup application is smaller than a preconfigured time sequence difference, it may be determined that the state descriptions of the first service data backup item and the second service data backup item belonging to the same target service data backup item in the two service information backup applications are relatively similar, and based on this, the item state association degree between the first service data backup item and each second service data backup item may be determined first.

Step 212, determining whether the item status association degree of the first service data backup item and each second service data backup item reaches a first set index. The first set index may be 0.9, 0.95, or the like.

Step 213, determining a second service data backup item corresponding to the item state association degree reaching the first set index as the second target service data backup item.

It can be understood that, if the item state association degree between the first service data backup item and each second service data backup item reaches the first set index, it is considered that the two service data backup items belong to the same service data backup item or belong to similar service data backup items, based on which, the second service data backup item corresponding to the item state association degree reaching the first set index can be determined as the second target service data backup item, so that the number of item linkage processing can be actively reduced, and from another perspective, when the subsequent item linkage processing and the backup item association degree are determined, it is not necessary to determine other second service data backup items except the second target service data backup item, which is convenient for realizing efficient item linkage processing.

In some embodiments, for step 21, the number of item linkage processes may also be reduced by combining data item keywords, which exemplarily include the following steps 21a to 21c.

Step 21a, regarding each first service data backup item, determining an item keyword association degree between the first service data backup item and each second service data backup item by combining a data item keyword of the first service data backup item and a data item keyword of each second service data backup item.

Step 21b, determining whether the item keyword association degree between the first service data backup item and each second service data backup item reaches a second set index. The second setting index may be 0.92, 0.97, or the like.

And step 21c, determining a second service data backup item corresponding to the item keyword association degree reaching the second set index as the second target service data backup item.

For example, for a first business data backup item (e.g., a government-enterprise office file resource), a second business data backup item includes an enterprise office file resource, a remote office file resource, and system data information, when performing item combination analysis, since the association degree of the item keyword between the government-enterprise office file resource and the system data information is small, it is not necessary to determine the system data information as a second target business data backup item for determining the association degree of the backup item. And for the enterprise office file resources in the second business data backup project, the business data backup project is often determined to be similar to the government and enterprise office file resources, and then the business data backup project can be determined to be a second target business data backup project.

Therefore, if the item keyword association degree of the first service data backup item and each second service data backup item reaches a first set index, the two service data backup items are considered to belong to the same service data backup item or to belong to similar service data backup items, and in this case, the second service data backup item corresponding to the item keyword association degree reaching the first set index can be determined as the second target service data backup item, so that the number of item linkage processing can be actively reduced.

For some preferred embodiments, for step 133, when determining, in combination with the backup item association degree, that the first business data backup item and the second business data backup item match the same target business data backup item, the following steps 1331 to 1332 may be included.

Step 1331, determining whether the linkage processing between the first business data backup item and each second business data backup item is completed or not by combining the backup item association degree and the first item processing guide information.

Step 1332, determining the first service data backup item and the second service data backup item which complete the linkage processing as the first service data backup item and the second service data backup item matching the same target service data backup item.

Further, the first item processing guidance information may be Hungarian algorithms. The binary Algorithm may be combined with Hungarian Algorithm to realize the item linkage processing of the first service data backup item and each second service data backup item.

For some examples, under the condition that both the first service data backup item and the second service data backup item are one, according to the association degree of the backup items between the first service data backup item and the second service data backup item, it may be determined whether the linkage processing is completed, and if the linkage processing is completed, the first service data backup item and the second service data backup item may be determined as the same target service data backup item.

Further, for each first business data backup item, if a plurality of second business data backup items similar to the first business data backup item exist in the second business information backup application, the first business data backup item and the second business data backup item corresponding to the same target business data backup item may be determined by the following, and from another perspective, for step 1332, when the first business data backup item and the second business data backup item which complete the linkage processing are determined to match the first business data backup item and the second business data backup item of the same target business data backup item, the following steps 13321 to 13322 may be included.

Step 13321, determining the first service data backup item and the second service data backup item which are subjected to linkage processing as a service data backup item set.

Step 13322, under the condition that the number of the service data backup item sets is not less than two, determining a target service data backup item set from a plurality of service data backup item sets in combination with second item processing guide information, and determining a first service data backup item and a second service data backup item in the target service data backup item set as the first service data backup item and the second service data backup item matching the same target service data backup item. The second item processing guidance information may be understood as Hungarian Algorithm.

Further, each service data backup item in the first service information backup application1 and the second service information backup application2 is taken as an example for description in the following.

For example, the first service information backup application1 includes a service data backup item project _ a1, a service data backup item project _ a2, a service data backup item project _ a3, and a service data backup item project _ a4, and the second service information backup application2 includes a service data backup item project _ b1, a service data backup item project _ b2, a service data backup item project _ b3, and a service data backup item project _ b4, where the service data backup item set includes:

project_a1-project_b1、

project_a1-project_b2、

project_a2-project_b2、

project_a2-project_b3、

project_a3-project_b1、

project_a3-project_b2、

and project _ a4-project _ b3.

From another perspective, the reference elements, i.e., project _ a1, project _ a2, project _ a3, project _ a4, project _ b1, project _ b2, project _ b3 and project _ b4, perform numerical matching on each reference element according to the association degree of backup items between two service data backup items in each service data backup item set (e.g., project _ a1, project _ a2 and project _ a3 are assigned with 0.9, project _ a4 is assigned with 0.2, and project _ b1, project _ b2, project _ b3 and project _ b4 are assigned with 0), and in combination with the second item processing guide information, it can be determined that the target service data backup item set includes:

project_a1-project_b1、

project_a2-project_b3、

and project _ a3-project _ b2, so that project _ a1 and project _ b1 are the same business data backup item, project _ a2 and project _ b3 are the same business data backup item, and project _ a3 and project _ b2 are the same business data backup item.

And determining a target business data backup item set by combining the second item processing guide information under the condition that the number of the business data backup item sets is not less than two, and determining the target business data backup item set with the highest adaptation degree from a plurality of business data backup item sets from another perspective, so that the accuracy of calculating the first business data backup item and the second business data backup item which match the same target business data backup item can be improved.

The following is another network-based data backup method provided in the embodiment of the present invention, which is different from the above network-based data backup method to some extent, and the method for processing the service data backup item provided in the embodiment of the present invention further includes step 15.

And step 15, determining a data backup execution strategy of the target business data backup item by combining the backup guidance change record of the target business data backup item.

Further, the data backup execution policy may include: policy type, backup mode, and backup object.

It can be understood that after the backup guidance change record of the target business data backup item is obtained, a data backup execution strategy can be determined through the backup guidance change record, and then targeted data backup processing is performed based on the data backup execution strategy. Based on this, in some independent embodiments, after determining the data backup execution policy of the target business data backup item in combination with the backup guidance change record of the target business data backup item described in step 15, performing data backup processing on the target business data backup item by using the backup guidance change record described in step two includes: and performing data backup processing on the target service data backup item based on the data backup execution strategy.

The data backup processing may be performed on the target service data backup item according to the policy type, the backup mode, and the backup object, which is not described herein again.

In some embodiments, after performing the data backup process on the target business data backup item based on the data backup execution policy, the method may further include: performing data backup upgrading based on a backup optimization instruction sent aiming at a data backup processing result; and the data backup processing result is obtained after data backup processing is carried out on the target service data backup item.

For example, the existing backup technology may be combined to perform backup processing on the related data information of the target service data backup item, then the request end of the data backup checks whether the data backup processing result meets the requirement, and if not, the request end of the data backup may send a backup optimization instruction to instruct the data backup cloud platform to perform data backup optimization, thereby forming a closed-loop data backup chain.

In some embodiments, the upgrading of the data backup based on the backup optimization indication sent for the data backup processing result may include the following: obtaining a backup optimization clause set in the backup optimization instruction; respectively performing local backup requirement mining and non-local backup requirement mining on the plurality of backup optimization feedbacks in the backup optimization clause set to obtain a local backup requirement mining result and a non-local backup requirement mining result; performing first requirement selection on the local backup requirement mining result through a first preset requirement analysis rule to obtain a first backup requirement characteristic diagram comprising a local backup requirement; selecting a second requirement on the non-local backup requirement mining result through a second preset requirement analysis rule to obtain a second backup requirement characteristic diagram comprising the non-local backup requirement; sorting the first backup requirement characteristic diagram and the second backup requirement characteristic diagram to obtain a target backup requirement characteristic diagram matched with a target backup requirement in the backup optimization clause set; the target backup requirements comprise at least one of local backup requirements and non-local backup requirements; determining an overall backup requirement corresponding to the backup optimization clause set based on the target backup requirement characteristic graph; and carrying out data backup upgrading according to the integral backup requirement. For example, the set backup requirements with the highest backup requirement request frequency can be determined as the whole backup requirements through the target backup requirement characteristic diagram, so that the efficiency and the intelligent degree of secondary backup can be improved.

In some embodiments that may be independent, the performing local backup requirement mining and non-local backup requirement mining on the plurality of backup optimization feedbacks in the backup optimization clause set respectively to obtain a local backup requirement mining result and a non-local backup requirement mining result includes: respectively carrying out local backup requirement mining on the plurality of backup optimization feedbacks in the backup optimization clause set to obtain local backup requirement mining information in each backup optimization feedback and initial backup requirement types corresponding to each local backup requirement mining information; determining a local backup requirement mining result based on local backup requirement mining information and corresponding initial backup requirement types in each backup optimization feedback; and respectively carrying out non-local backup requirement mining on the plurality of backup optimization feedbacks in the backup optimization clause set to obtain a non-local backup requirement mining result. By the design, the mining result of the local backup requirement and the mining result of the non-local backup requirement can be accurately and completely determined.

In some embodiments that may be independent, the mining of non-local backup requirements for the plurality of backup optimization feedbacks in the backup optimization clause set to obtain a non-local backup requirement mining result includes: performing strategy type identification on the plurality of backup optimization feedbacks in the backup optimization clause set respectively to obtain strategy type identification results corresponding to the backup optimization feedbacks respectively; respectively carrying out backup expectation prediction on a plurality of backup optimization feedbacks in the backup optimization clause set to obtain backup expectation prediction results respectively corresponding to the backup optimization feedbacks; associating the strategy type identification result corresponding to the same event with the backup expected prediction result; and performing non-local backup demand mining processing based on the backup expected prediction result associated with the target strategy type identification result in the backup optimization clause set to obtain a non-local backup demand mining result.

Based on the same or similar inventive concepts, please refer to fig. 2 in combination, and a schematic diagram of an architecture of a network-based data backup system 30 is also provided, which includes a data backup cloud platform 10 and a data service end 20 that communicate with each other, and the data backup cloud platform 10 and the data service end 20 implement or partially implement the technical solutions described in the above method embodiments when running.

Further, a computer-readable storage medium is provided, on which a program is stored which, when being executed by a processor, carries out the above-mentioned method.

In the embodiments provided in the embodiments of the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus and method embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part.

The functions may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a network device, or the like) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.

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

Claims

1. A network-based data backup method is applied to a data backup cloud platform, and comprises the following steps:

determining a backup guidance change record of a target service data backup item according to the acquired internet service information log;

and carrying out data backup processing on the target service data backup item by using the backup guidance change record.

2. The method according to claim 1, wherein the determining a backup guidance change record of the target service data backup item according to the obtained internet service information log comprises:

calling an internet service information log, and sampling at least two groups of service information backup applications from the internet service information log by combining with a configured sampling strategy; refining the data item element field of each service data backup item in each service information backup application, and then respectively determining the data item state information and the data item key words of each service data backup item in each service information backup application;

determining candidate service data backup items matched with the same target service data backup item in the at least two groups of service information backup applications by combining the data item element fields, the data item state information and the data item keywords of the service information backup applications; and determining the backup guidance change record of the target business data backup item by combining the data item state information of the candidate business data backup item corresponding to the target business data backup item in the at least two groups of business information backup applications respectively.

3. The method according to claim 2, wherein the at least two sets of service information backup applications include a first service information backup application and a second service information backup application, and the first service information backup application and the second service information backup application are service information backup applications having time-sequential contact;

the determining, by combining the data item element field, the data item state information, and the data item keyword of each service information backup application, a candidate service data backup item matching the same target service data backup item in the at least two sets of service information backup applications includes:

determining at least one first service data backup item in the first service information backup application and at least one second service data backup item in the second service information backup application;

for each first service data backup item, determining a backup item association degree between the first service data backup item and each second service data backup item by combining data item state information, data item keywords and data item element fields of the first service data backup item in the first service information backup application and data item state information, data item keywords and data item element fields of each second service data backup item in the second service information backup application;

and determining the first service data backup item and the second service data backup item which are matched with the same target service data backup item by combining the association degree of the backup items, and determining the first service data backup item and the second service data backup item which are matched with the same target service data backup item as the candidate service data backup items.

4. The method of claim 3, wherein the determining, for each first service data backup item, a backup item association degree between the first service data backup item and each second service data backup item in combination with the data item status information, the data item key word and the data item element field of the first service data backup item in the first service information backup application and the data item status information, the data item key word and the data item element field of each second service data backup item in the second service information backup application comprises: regarding each first service data backup item, determining at least one second target service data backup item from the second service information backup application in combination with the data item element field, the data item state information and at least one target description content in the data item key words; determining the association degree of the backup items between the first service data backup item and the second target service data backup item by combining the data item element field, the data item state information and the data item key word;

the determining, in combination with the association degree of the backup items, the first service data backup item and the second service data backup item that match the same target service data backup item, and determining the first service data backup item and the second service data backup item that match the same target service data backup item as the candidate service data backup items, includes: and determining the first service data backup item and the second target service data backup item which are matched with the same target service data backup item by combining the correlation degree of the backup items between the first service data backup item and the second target service data backup item, and determining the first service data backup item and the second target service data backup item which are matched with the same target service data backup item as the candidate service data backup items.

5. The method of claim 4, wherein the determining, for each first service data backup item, not less than one second target service data backup item from the second service information backup application in combination with not less than one target description content in the data item element field, the data item status information, and the data item keyword comprises:

determining the item state association degree of the first service data backup item and each second service data backup item by combining the data item state information of the first service data backup item in the first service information backup application and the data item state information of each second service data backup item in the second service information backup application with respect to each first service data backup item under the condition that the difference value of the acquisition time sequence of the first service information backup application and the second service information backup application is smaller than the preconfigured time sequence difference;

determining whether the item state association degree of the first business data backup item and each second business data backup item reaches a first set index;

and determining a second business data backup item corresponding to the item state association degree reaching the first set index as the second target business data backup item.

6. The method according to claims 1-4, wherein said determining, for each first service data backup item, not less than one second target service data backup item from the second service information backup application in combination with not less than one target description content in the data item element field, the data item status information, and the data item keyword comprises:

determining, for each first service data backup item, an item keyword association degree between the first service data backup item and each second service data backup item in combination with a data item keyword of the first service data backup item and a data item keyword of each second service data backup item;

determining whether the item keyword association degree between the first business data backup item and each second business data backup item reaches a second set index;

and determining a second business data backup item corresponding to the item keyword association degree reaching the second set index as the second target business data backup item.

7. The method according to claim 3, wherein said determining, in combination with the backup item association degree, the first service data backup item and the second service data backup item that match the same target service data backup item comprises: determining whether linkage processing is finished between the first business data backup item and each second business data backup item or not by combining the backup item association degree and the first item processing guide information; determining the first service data backup item and the second service data backup item which are subjected to linkage processing as the first service data backup item and the second service data backup item which are matched with the same target service data backup item;

wherein, the determining the first service data backup item and the second service data backup item matching the same target service data backup item for the first service data backup item and the second service data backup item which will complete the linkage processing includes: determining the first service data backup item and the second service data backup item which are subjected to linkage processing as a service data backup item set; and under the condition that the number of the business data backup item sets is not less than two, combining second item processing guide information, determining a target business data backup item set from a plurality of business data backup item sets, and determining a first business data backup item and a second business data backup item in the target business data backup item set as the first business data backup item and the second business data backup item which are matched with the same target business data backup item.

8. The method of claim 2,

after determining the backup guidance change record of the target business data backup item in combination with the data item state information of the candidate business data backup item corresponding to the target business data backup item in the at least two groups of business information backup applications, the method further comprises: determining a data backup execution strategy of the target business data backup item in combination with the backup guidance change record of the target business data backup item;

the data backup processing is performed on the target service data backup item by using the backup guidance change record, and the data backup processing comprises the following steps: and performing data backup processing on the target service data backup item based on the data backup execution strategy.

9. A data backup system based on a network is characterized by comprising a data backup cloud platform and a data service end which are communicated with each other;

the data backup cloud platform is used for determining a backup guidance change record of a target service data backup project according to the acquired internet service information log; and carrying out data backup processing on the target service data backup item by using the backup guidance change record.

10. A data backup cloud platform is characterized by comprising a processor and a memory; the processor is communicatively connected to the memory, and the processor is configured to read the computer program from the memory and execute the computer program to implement the method of any one of claims 1 to 8.