A method and system for local backup processing of cloud data

Abstract

The present invention provides a cloud data local backup processing method and system, which belongs to the field of data security technology, and specifically includes: determining the historical update times and update data volume of the update user in the report by different update users in the update data of the report, and determining the user update evaluation amount of the update user based on the historical update times and update data volume of the report by the update user, obtaining the storage data and update data of the backup table of the server corresponding to the different update users, and determining the best matching user of the report in combination with the user update evaluation amounts of different update users, and backing up the report to the server corresponding to the best matching user according to the local backup frequency, thereby further ensuring the reliability of the operation and maintenance management of the server.

Description

Technical Field

[0001] The present invention belongs to the field of data security technology, and in particular relates to a method and system for local backup processing of cloud data. Background Art

[0002] In order to achieve collaborative processing of reports for different branches and different personnel of different power companies, basic functions such as exclusive editing, shared editing, document management, my team, message notification, etc. can be realized through the construction of data analysis components. However, at the same time, since the report data is stored in the cloud, how to achieve local backup of report data and realize secure storage management of report data has become a technical problem that needs to be solved urgently.

[0003] In order to solve the above technical problems, the invention patent CN202211378806.5 "A data backup method, system and related components for edge nodes" takes into account the differences in the distance of the data to be backed up from different edge nodes to different backup locations, backup time, and backup data volume, and determines differentiated backup strategies according to the level of the data to be backed up, thereby ensuring high availability of data backup in edge nodes. However, it is not difficult to find through analysis that the following technical problems exist:

[0004] Due to the differences in report types, there are certain differences in the users who are responsible for updating the data of different electricity reports. At the same time, due to the differences in update frequencies of different users, when performing backup processing of electricity reports, if the above factors are not taken into consideration to determine the backup node, the reliability of the stored data cannot be guaranteed because the storage of the user's updated report data on different servers is too scattered, which will also make operation and maintenance management more difficult.

[0005] In response to the above technical problems, the present invention provides a method and system for local backup processing of cloud data. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for local backup processing of cloud data is provided.

[0008] A method for local backup of cloud data, characterized by comprising:

[0009] S1 determines the historical update times of the report through the update data of the report, and determines the local backup frequency of the report in combination with the time intervals of different historical update times and the update data volume;

[0010] S2 determines the historical update times and update data volume of the update user in the report through the update data of different update users in the report, and determines the user update evaluation amount of the update user based on the historical update times and update data volume of the update user in the report;

[0011] S3: determining whether there is a matching update user for the report based on the user update evaluation amounts of different update users of the report and the deviation of the user update evaluation amounts of different update users; if so, backing up the report to the server corresponding to the matching update user according to the local backup frequency; if not, proceeding to the next step;

[0012] S4 obtains the storage data and update data of the backup table of the server corresponding to different update users, and determines the best matching user of the report in combination with the user update evaluation amount of different update users, and backs up the report to the server corresponding to the best matching user according to the local backup frequency.

[0013] The beneficial effects of the present invention are:

[0014] 1. Determine the local backup frequency of the report based on the historical update times of the report, the time intervals between different historical update times, and the amount of updated data, thereby ensuring the real-time backup processing of reports with high update frequency and large update data volume, avoiding the technical problem of low security of report data due to low backup processing efficiency, and reducing unnecessary waste of server storage space.

[0015] 2. The best matching user for the report is determined by updating the storage data and update data of the backup table of the server corresponding to the updating user and the user update evaluation amount of different updating users. Not only the storage space of the existing storage backup table of the server corresponding to the updating user and the impact of the update frequency on the storage space of the server are taken into consideration, but also the correlation degree between the updating user and the update data of the report is taken into consideration to realize the screening of the best matching user for the report, thereby improving the reliability of the operation and maintenance management of the server.

[0016] A further technical solution is that the update data of the report is determined by parsing the update log of the report.

[0017] A further technical solution is to determine the local backup frequency of the report based on the frequency of major data changes and the frequency of basic data changes of the report, specifically including:

[0018] The frequency of data changes in the report is obtained by correcting the frequency of basic data changes according to the frequency of major data changes in the report, and the local backup frequency of the report is determined based on the interval corresponding to the frequency of data changes in the report.

[0019] A further technical solution is that the method for determining the best matching user of the report is:

[0020] Determine different backup table update frequencies and update data volumes of different update times by updating data of the backup table of the server corresponding to different update users, and determine different backup table update storage evaluation volumes based on different backup table update frequencies and update data volumes of different update times;

[0021] Dividing the backup table into different backup processing data volume intervals by the update storage evaluation amount, and determining the storage evaluation amount of the server corresponding to the different update users according to the number of backup tables in different backup processing data volume intervals, the storage space occupied by different backup tables and the update storage evaluation amount;

[0022] The comprehensive user evaluation amounts of different update users are determined according to the storage evaluation amounts of the servers corresponding to different update users and the user update evaluation amounts of different update users, and the best matching user of the report is determined through the comprehensive user evaluation amounts of different update users.

[0023] A further technical solution is to determine the best matching user of the report by using the comprehensive user evaluation amounts of different updating users, specifically including:

[0024] The updated user corresponding to the maximum comprehensive user evaluation amount is taken as the best matching user for the report.

[0025] On the other hand, the present invention provides a computer system, comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, the above-mentioned method for local backup processing of cloud data is executed.

[0026] Other features and advantages will be described in the following description, and partly become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0027] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0029] Figure 1 is a flow chart of a method for processing local backup of cloud data;

[0030] Figure 2 is a flow chart of a method for determining a local backup frequency of a report;

[0031] Figure 3 is a flow chart of a method for determining a user update evaluation amount for an update user. DETAILED DESCRIPTION

[0032] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present invention will be comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar structures, and thus their detailed description will be omitted.

[0033] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0034] Example 1

[0035] To solve the above problems, according to one aspect of the present invention, Figure 1 According to one aspect of the present invention, a method for local backup processing of cloud data is provided, which is characterized by specifically comprising:

[0036] S1 determines the historical update times of the report through the update data of the report, and determines the local backup frequency of the report in combination with the time intervals of different historical update times and the update data volume;

[0037] Specifically, the update data of the report is determined by parsing the update log of the report.

[0038] Specifically, Figure 2 As shown, the method for determining the local backup frequency of the report is:

[0039] Determining the number of major updates in the historical update times according to the update data amounts of different historical update times of the report;

[0040] Determining the frequency of major data changes in the report based on the number of major updates of the report, the time intervals between different adjacent major updates, and the amount of updated data at different major updates;

[0041] Determine the frequency of change of basic data of the report by the number of historical updates of the report, the time intervals between different adjacent historical updates, and the amount of updated data at different historical updates;

[0042] The local backup frequency of the report is determined based on the frequency of major data changes and the frequency of basic data changes of the report.

[0043] Further, the local backup frequency of the report is determined based on the frequency of major data changes and the frequency of basic data changes of the report, specifically including:

[0044] The frequency of data changes in the report is obtained by correcting the frequency of basic data changes according to the frequency of major data changes in the report, and the local backup frequency of the report is determined based on the interval corresponding to the frequency of data changes in the report.

[0045] In another embodiment, the method for determining the local backup frequency of the report is:

[0046] Obtain the historical update number of the report, determine whether the historical update number of the report is greater than the preset update number, if so, proceed to the next step, if not, determine the local backup frequency of the report based on the preset backup frequency;

[0047] Determine the number of major updates in the historical update times by using the update data amounts of different historical update times of the report, and judge whether the number of major updates of the report meets the requirement, if so, proceed to the next step, if not, determine the local backup frequency of the report based on the preset backup frequency;

[0048] Determine the frequency of major data changes of the report based on the number of major updates of the report, the time intervals between different adjacent major update times, and the amount of updated data at different major update times, and judge whether the frequency of major data changes of the report meets the requirements, if so, proceed to the next step, if not, determine the local backup frequency of the report based on the preset backup frequency;

[0049] Determine the frequency of basic data changes of the report by the number of historical updates of the report, the time intervals between different adjacent historical update times, and the amount of updated data at different historical update times, and judge whether the frequency of basic data changes of the report meets the requirements, if so, proceed to the next step, if not, determine the local backup frequency of the report based on the preset backup frequency;

[0050] The local backup frequency of the report is determined based on the frequency of major data changes and the frequency of basic data changes of the report.

[0051] In another embodiment, the method for determining the local backup frequency of the report is:

[0052] S11 obtains the historical update times of the report, and determines whether the historical update times of the report are less than the update times limit value, if so, proceeds to step S13, if not, proceeds to the next step;

[0053] S12: obtaining the update data volume of the report, determining whether the update data volume of the report meets the requirement, if yes, proceeding to the next step, if no, determining the local backup frequency of the report based on the preset backup frequency;

[0054] S13 determines the number of major updates in the historical update times according to the update data amounts of different historical update times of the report, and judges whether the number of major updates of the report meets the requirement, if so, proceeds to the next step, if not, determines the local backup frequency of the report based on the preset backup frequency;

[0055] S14: determining the frequency of major data changes of the report based on the number of major updates of the report, the time intervals between different adjacent major updates, and the update data volumes of different major updates, and determining the frequency of basic data changes of the report based on the number of historical updates of the report, the time intervals between different adjacent historical updates, and the update data volumes of different historical updates;

[0056] S15 determines the local backup frequency of the report based on the frequency of major data changes and the frequency of basic data changes of the report.

[0057] Further, judging whether the update data volume of the report meets the requirement specifically includes:

[0058] When the updated data volume of the report is within a preset data volume range, it is determined that the updated data volume of the report meets the requirement.

[0059] S2 determines the historical update times and update data volume of the update user in the report through the update data of different update users in the report, and determines the user update evaluation amount of the update user based on the historical update times and update data volume of the update user in the report;

[0060] Specifically, Figure 3 As shown, the method for determining the user update evaluation amount of the updating user is:

[0061] Determine the data update frequency of the updating user by using the historical update times of the updating user on the report and the time intervals of different historical update times;

[0062] Determine the data change assessment amount of the updating user based on the updated data amount of the updating user in the report, the updated data amounts of different historical update times, and the historical update times when the updated data amount is greater than a preset data amount;

[0063] The user update evaluation amount of the updating user is determined according to the data update frequency and the data change evaluation amount of the updating user.

[0064] S3: determining whether there is a matching update user for the report based on the user update evaluation amounts of different update users of the report and the deviation of the user update evaluation amounts of different update users; if so, backing up the report to the server corresponding to the matching update user according to the local backup frequency; if not, proceeding to the next step;

[0065] Specifically, determining whether there is a matching update user for the report includes:

[0066] Taking the updating user with the largest user update evaluation amount as the screening updating user, and determining the basic matching degree of the screening updating user according to the user update evaluation amount of the screening updating user;

[0067] Determine update similar users of the screened update user by the deviation between user update evaluation amounts of different update users and the user update evaluation amount of the screened update user, and determine the matching degree correction amount of the screened update user by the number of update similar users of the screened update user and the deviation between user update evaluation amounts of different update users and the user update evaluation amount of the screened update user;

[0068] The matching degree of the screened update user is determined according to the matching degree correction amount of the screened update user and the basic matching degree, and based on the matching degree, it is determined whether the screened update user is a matching update user of the report.

[0069] It should be noted that determining whether the screening update user is a matching update user of the report based on the matching degree specifically includes:

[0070] When the matching degree of the screened update user is greater than a preset matching degree, the screened update user is determined to be a matching update user of the report.

[0071] In another embodiment, determining whether there is a matching update user for the report specifically includes:

[0072] The updating user with the largest user update evaluation amount is used as the screening updating user, and the basic matching degree of the screening updating user is determined according to the user update evaluation amount of the screening updating user, and it is judged whether the basic matching degree of the screening updating user meets the requirement, if so, proceeding to the next step, if not, determining that there is no matching updating user in the report;

[0073] Determine the evaluation deviations of different update users by comparing the user update evaluations of different update users with the deviations of the user update evaluations of the screened update users, and judge whether there are update users whose evaluation deviations do not meet the requirements. If so, determine that there are no matching update users in the report. If not, proceed to the next step.

[0074] Determine the update similar users of the screened update users according to the evaluation deviations of different update users, determine the comprehensive deviation of the update similar users of the screened update users according to the number of update similar users of the screened update users and the evaluation deviations of different update similar users, judge whether the comprehensive deviation of the update similar users of the screened update users meets the requirements, if so, determine that there is no matching update user in the report, if not, proceed to the next step;

[0075] The evaluation deviations of different update users are obtained, and the matching degree of the screened update user is determined in combination with the comprehensive deviations of update similar users of the screened update user and the basic matching degree, and based on the matching degree, it is determined whether the screened update user is a matching update user of the report.

[0076] In another embodiment, determining whether there is a matching update user for the report specifically includes:

[0077] Judging whether there is an update user whose user update evaluation amount is greater than a set threshold value through the user update evaluation amounts of different update users, if so, proceeding to the next step, if not, determining that there is no matching update user in the report;

[0078] Taking the update users whose user update evaluation amount is greater than the set threshold as suspected matching users, judging whether the number of the suspected matching users meets the requirement, if so, proceeding to the next step, if not, determining that there is no matching update user in the report;

[0079] The update user with the largest user update evaluation amount is used as the screening update user, and the evaluation deviation amounts of different update users are determined by the deviation amounts of the user update evaluation amounts of different update users and the user update evaluation amount of the screening update user, to determine whether there is a suspected matching user whose evaluation deviation amount does not meet the requirements, if so, proceed to the next step, if not, determine that the screening update user is the matching update user of the report;

[0080] Determine the update similar users of the screened update users according to the evaluation deviations of different update users, and determine the comprehensive deviation of the update similar users of the screened update users according to the number of update similar users of the screened update users and the evaluation deviations of different update similar users;

[0081] The evaluation deviations of different update users are obtained, and the matching degree of the screened update user is determined in combination with the comprehensive deviations of update similar users of the screened update user and the basic matching degree, and based on the matching degree, it is determined whether the screened update user is a matching update user of the report.

[0082] S4 obtains the storage data and update data of the backup table of the server corresponding to different update users, and determines the best matching user of the report in combination with the user update evaluation amount of different update users, and backs up the report to the server corresponding to the best matching user according to the local backup frequency.

[0083] Specifically, the method for determining the best matching user of the report is:

[0084] Determine different backup table update frequencies and update data volumes of different update times by updating data of the backup table of the server corresponding to different update users, and determine different backup table update storage evaluation volumes based on different backup table update frequencies and update data volumes of different update times;

[0085] Dividing the backup table into different backup processing data volume intervals by the update storage evaluation amount, and determining the storage evaluation amount of the server corresponding to the different update users according to the number of backup tables in different backup processing data volume intervals, the storage space occupied by different backup tables and the update storage evaluation amount;

[0086] The comprehensive user evaluation amounts of different update users are determined according to the storage evaluation amounts of the servers corresponding to different update users and the user update evaluation amounts of different update users, and the best matching user of the report is determined through the comprehensive user evaluation amounts of different update users.

[0087] Further, determining the best matching user of the report through comprehensive user evaluations of different updating users specifically includes:

[0088] The updated user corresponding to the maximum comprehensive user evaluation amount is taken as the best matching user for the report.

[0089] In another embodiment, the method for determining the best matching user of the report is:

[0090] Obtaining the user update evaluation amount of the updating user, determining whether the user update evaluation amount of the updating user is less than the average of the user update evaluation amounts of all the updating users, if so, determining that the updating user does not belong to the best matching user of the report, if not, proceeding to the next step;

[0091] Determine the storage volume of the backup price of the server corresponding to the updated user according to the storage data of the backup price of the server corresponding to the updated user, and judge whether the storage volume of the backup price of the server corresponding to the updated user is greater than a preset storage volume threshold. If so, determine that the updated user does not belong to the best matching user of the report. If not, proceed to the next step.

[0092] Determine different backup table update frequencies and update data volumes of different update times by updating data of the backup table of the server corresponding to different update users, and determine different backup table update storage evaluation volumes based on different backup table update frequencies and update data volumes of different update times;

[0093] The backup table is divided into different backup processing data volume intervals by the update storage assessment amount, and the storage assessment amount of the server corresponding to the different update users is determined according to the number of backup tables in different backup processing data volume intervals, the storage space occupied by different backup tables and the update storage assessment amount, and it is judged whether the storage assessment amount of the server corresponding to the update user meets the requirement, if so, proceed to the next step, if not, it is determined that the update user does not belong to the best matching user of the report;

[0094] The comprehensive user evaluation amounts of different update users are determined according to the storage evaluation amounts of the servers corresponding to different update users and the user update evaluation amounts of different update users, and the best matching user of the report is determined through the comprehensive user evaluation amounts of different update users.

[0095] Example 2

[0096] On the other hand, the present invention provides a computer system, comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: the processor executes the above-mentioned method for local backup processing of cloud data when running the computer program.

[0097] Through the above embodiments, the present application achieves the following technical effects:

[0098] 1. Determine the local backup frequency of the report based on the historical update times of the report, the time intervals between different historical update times, and the amount of updated data, thereby ensuring the real-time backup processing of reports with high update frequency and large update data volume, avoiding the technical problem of low security of report data due to low backup processing efficiency, and reducing unnecessary waste of server storage space.

[0099] 2. The best matching user for the report is determined by updating the storage data and update data of the backup table of the server corresponding to the updating user and the user update evaluation amount of different updating users. Not only the storage space of the existing storage backup table of the server corresponding to the updating user and the impact of the update frequency on the storage space of the server are taken into consideration, but also the correlation degree between the updating user and the update data of the report is taken into consideration to realize the screening of the best matching user for the report, thereby improving the reliability of the operation and maintenance management of the server.

[0100] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0101] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for local backup of cloud data, characterized in that: Specifically include: Determine the historical update times of the report through the update data of the report, and determine the local backup frequency of the report in combination with the time intervals of different historical update times and the update data volume; Determine the historical update times and update data volume of the update user in the report through the update data of different update users in the report, and determine the user update evaluation amount of the update user based on the historical update times and update data volume of the update user in the report; Determine whether there is a matching update user for the report based on the user update evaluation amounts of different update users of the report and the deviation of the user update evaluation amounts of different update users; if so, back up the report to the server corresponding to the matching update user according to the local backup frequency; if not, proceed to the next step; The storage data and update data of the backup table of the server corresponding to different update users are obtained, and the best matching user of the report is determined in combination with the user update evaluation amount of different update users. The report is backed up to the server corresponding to the best matching user according to the local backup frequency, thereby ensuring the real-time backup processing of reports with high update frequency and large update data volume.

2. The method for local backup of cloud data according to claim 1, characterized in that: The update data of the report is determined by parsing the update log of the report.

3. The method for local backup of cloud data according to claim 1, characterized in that: The method for determining the local backup frequency of the report is: Determining the number of major updates in the historical update times according to the update data amounts of different historical update times of the report; Determining the frequency of major data changes in the report based on the number of major updates of the report, the time intervals between different adjacent major updates, and the amount of updated data at different major updates; Determine the frequency of change of basic data of the report by the number of historical updates of the report, the time intervals between different adjacent historical updates, and the amount of updated data at different historical updates; The local backup frequency of the report is determined based on the frequency of major data changes and the frequency of basic data changes of the report.

4. The method for local backup of cloud data according to claim 3, characterized in that: The local backup frequency of the report is determined based on the frequency of major data changes and the frequency of basic data changes of the report, specifically including: The frequency of data changes in the report is obtained by correcting the frequency of basic data changes according to the frequency of major data changes in the report, and the local backup frequency of the report is determined based on the interval corresponding to the frequency of data changes in the report.

5. The method for local backup of cloud data according to claim 1, characterized in that: The method for determining the user update evaluation amount of the updating user is: Determine the data update frequency of the updating user by using the historical update times of the updating user on the report and the time intervals of different historical update times; Determine the data change assessment amount of the updating user based on the updated data amount of the updating user in the report, the updated data amounts of different historical update times, and the historical update times when the updated data amount is greater than a preset data amount; The user update evaluation amount of the updating user is determined according to the data update frequency and the data change evaluation amount of the updating user.

6. The method for local backup of cloud data according to claim 1, characterized in that: Determine whether there is a matching update user for the report, specifically including: Taking the updating user with the largest user update evaluation amount as the screening updating user, and determining the basic matching degree of the screening updating user according to the user update evaluation amount of the screening updating user; Determine update similar users of the screened update user by the deviation between user update evaluation amounts of different update users and the user update evaluation amount of the screened update user, and determine the matching degree correction amount of the screened update user by the number of update similar users of the screened update user and the deviation between user update evaluation amounts of different update users and the user update evaluation amount of the screened update user; The matching degree of the screened update user is determined according to the matching degree correction amount of the screened update user and the basic matching degree, and based on the matching degree, it is determined whether the screened update user is a matching update user of the report.

7. The method for local backup of cloud data according to claim 6, characterized in that: Determining whether the screening update user is a matching update user of the report based on the matching degree specifically includes: When the matching degree of the screened update user is greater than a preset matching degree, the screened update user is determined to be a matching update user of the report.

8. The method for local backup of cloud data according to claim 1, characterized in that: The method for determining the best matching user of the report is: Determine different backup table update frequencies and update data volumes of different update times by updating data of the backup table of the server corresponding to different update users, and determine different backup table update storage evaluation volumes based on different backup table update frequencies and update data volumes of different update times; Dividing the backup table into different backup processing data volume intervals by the update storage evaluation amount, and determining the storage evaluation amount of the server corresponding to the different update users according to the number of backup tables in different backup processing data volume intervals, the storage space occupied by different backup tables and the update storage evaluation amount; The comprehensive user evaluation amounts of different update users are determined according to the storage evaluation amounts of the servers corresponding to different update users and the user update evaluation amounts of different update users, and the best matching user of the report is determined through the comprehensive user evaluation amounts of different update users.

9. The method for local backup of cloud data according to claim 8, characterized in that: Determining the best matching user for the report by using comprehensive user evaluations of different updating users specifically includes: The updated user corresponding to the maximum comprehensive user evaluation amount is taken as the best matching user for the report.

10. A computer system comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, a method for local backup processing of cloud data as described in any one of claims 1-9 is executed.

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