Data processing method, device and medium

Abstract

The application provides a data processing method, device and medium. The method comprises the following steps: periodically determining a system factor corresponding to an application system to be inspected, the system factor comprising one or more of an application system disaster level, application system failure information, an application system new-old level, and application system historical inspection information; determining an inspection weight coefficient corresponding to the application system to be inspected according to the system factor; determining an inspection type and an inspection plan corresponding to the application system to be inspected according to the inspection weight coefficient; performing data verification on backup data corresponding to the application system to be inspected according to the inspection type and the inspection plan; if the backup data corresponding to the application system to be inspected fails the verification, generating backup data verification failure prompt information according to the application system to be inspected and the corresponding inspection type, and sending the backup data verification failure prompt information to a user device. The method provided by the application improves the accuracy and efficiency of backup data verification and reduces the verification cost.

Description

Technical Field

[0001] This application relates to the field of data processing, and more particularly to a data processing method, apparatus, and medium. Background Technology

[0002] With the development of internet technology, data has become increasingly important, and data backup is the most important means of ensuring enterprise data security. The verification of backup data has also become increasingly important.

[0003] There are two main existing methods for verifying backup data: One is backup media availability verification, which checks the readability of the backup storage media to prevent backup data from becoming unavailable due to media failure. Backup media availability sampling checks are quick and simple to implement, but their verification and assurance of the final availability of backup data are weaker than backup data recoverability verification. The other is backup data recoverability verification, which verifies whether backup data can fully meet actual production needs. This typically requires loading the backup data into a system environment consistent with the production environment. Compared to backup media availability verification, backup data recoverability verification takes longer and is more complex, but the verification effect is better. The backup data recoverability verification process includes backup media availability verification. In existing technologies, operators manually judge based on application system configurations and other factors to select the specific verification method. However, manual selection has low accuracy, leading to low data verification efficiency and increased verification costs.

[0004] Therefore, a data processing solution is needed that is accurate, efficient, and low-cost for backup data verification. Summary of the Invention

[0005] This application provides a data processing method, apparatus, and medium to solve the technical problems of low accuracy and efficiency, and high cost of existing backup data verification.

[0006] Firstly, this application provides a data processing method, including:

[0007] The system factors corresponding to the application systems to be sampled are periodically determined. The system factors include one or more of the following: application system disaster recovery level, application system fault information, application system newness level, and application system historical sampling information.

[0008] The sampling weight coefficient corresponding to the application system to be sampled is determined based on the system factor.

[0009] Based on the sampling weight coefficient, determine the sampling type and sampling plan corresponding to the application system to be sampled;

[0010] According to the sampling type and sampling plan, the backup data corresponding to the application system to be sampled is verified.

[0011] If the backup data verification of the application system to be inspected fails, a backup data verification failure prompt message is generated based on the application system to be inspected and the corresponding inspection type, and the backup data verification failure prompt message is sent to the user equipment.

[0012] In one possible implementation, determining the system factor corresponding to the application system to be sampled specifically includes:

[0013] Determine the disaster recovery level of the application system to be sampled;

[0014] Based on the number of failures of the application system to be inspected within a first preset time period, the corresponding application system failure information is determined;

[0015] Based on the configuration information of the application system to be inspected, the newness level of the application system to be inspected is determined. The configuration information includes one or more of the following: application system version, hardware device model, and backup data file name.

[0016] Based on the number of times the application system to be inspected is inspected within a second preset time period, the corresponding historical inspection information of the application system is determined.

[0017] In one possible implementation, determining the sampling weight coefficient corresponding to the application system to be sampled based on the system factor specifically includes:

[0018] Based on the preset correspondence between disaster recovery levels and scores, determine the first score corresponding to the disaster recovery level of the application system;

[0019] Based on the preset correspondence between fault information and scores, determine the second score corresponding to the fault information of the application system;

[0020] Based on the preset correspondence between the old and new levels and scores, the third score corresponding to the old and new levels of the application system is determined;

[0021] Based on the preset correspondence between sampling information and scores, the fourth score corresponding to the historical sampling information of the application system is determined.

[0022] The sampling weight coefficient corresponding to the application system to be sampled is determined using the following formula:

[0023] F = aA + bB + cC + dD

[0024] Wherein, F represents the sampling weight coefficient, A represents the first score, B represents the second score, C represents the third score, D represents the fourth score, and a, b, c, and d all represent proportional constants.

[0025] In one possible implementation, determining the sampling type and sampling plan corresponding to the application system to be sampled based on the sampling weight coefficient specifically includes:

[0026] For each application system to be sampled, determine whether the sampling weight coefficient is greater than or equal to a preset weight coefficient threshold; if yes, the sampling type corresponding to the application system to be sampled is backup data recovery sampling; if no, the sampling type corresponding to the application system to be sampled is backup media sampling.

[0027] Based on the sampling type and the sampling weight coefficient, the sampling cycle corresponding to the application system to be sampled and the sampling initiation time corresponding to each sampling cycle are determined.

[0028] Based on each application system to be inspected, the sampling period corresponding to each application system to be inspected, and the sampling initiation time corresponding to each sampling period, a sampling plan is generated for the application system to be inspected.

[0029] In one possible implementation, the step of verifying the backup data corresponding to the application system to be inspected according to the inspection type and inspection plan specifically includes:

[0030] For each sampling initiation time in the sampling plan, determine the application system to be sampled corresponding to the sampling initiation time, and the sampling type corresponding to the application system to be sampled.

[0031] Determine whether the sampling type is a backup media sampling inspection;

[0032] If so, determine the backup data storage medium corresponding to the application system to be sampled; according to the sampling period and the sampling initiation time corresponding to each sampling period, send a data read request to the backup data storage medium; if backup data is read, the backup data verification is successful; if backup data is not read, the backup data verification fails.

[0033] If not, determine the backup data storage medium and database type corresponding to the application system to be sampled; determine the database to be verified based on the database type; send a data read request to the backup data storage medium and load the read backup data into the database to be verified; if the read backup data is successfully loaded, the backup data verification is successful; if no backup data is read or the read backup data is not successfully loaded, the backup data verification fails.

[0034] In one possible implementation, when the sampling type is a backup data recovery sampling, after determining the database to be verified based on the database type, the method further includes:

[0035] Store the initial state of the database to be verified;

[0036] After verifying the backup data corresponding to the application system to be sampled, the method further includes:

[0037] The database to be verified is initialized based on its initial state.

[0038] In one possible implementation, after verifying the backup data corresponding to the application system to be sampled, the method further includes:

[0039] The system stores one or more of the following for each application system to be sampled: application system name, application system disaster recovery level, application system new / old level, sampling cycle, sampling initiation time, sampling type, data verification result, and error message corresponding to data verification failure.

[0040] Secondly, this application provides a terminal device, including:

[0041] The weight determination module is used to periodically determine the system factors corresponding to the application system to be sampled. The system factors include one or more of the following: application system disaster recovery level, application system fault information, application system newness level, and application system historical sampling information; and determine the sampling weight coefficient corresponding to the application system to be sampled based on the system factors.

[0042] The sampling inspection processing module is used to determine the sampling type and sampling plan corresponding to the application system to be inspected based on the sampling inspection weight coefficient.

[0043] The data verification module is used to verify the backup data corresponding to the application system to be inspected according to the sampling type and sampling plan; if the backup data verification of the application system to be inspected fails, a backup data verification failure prompt message is generated according to the application system to be inspected and the corresponding sampling type, and the backup data verification failure prompt message is sent to the user equipment.

[0044] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0045] The memory stores computer-executed instructions;

[0046] The processor executes computer execution instructions stored in the memory to implement the above method.

[0047] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the above-described method.

[0048] The data processing method, equipment, and media provided in this application can first periodically determine the sampling weight coefficients corresponding to the application systems to be sampled based on system factors such as the application system's disaster recovery level, application system fault information, application system's newness level, and application system's historical sampling information; then, based on the sampling weight coefficients, determine the sampling type and sampling plan corresponding to the application systems to be sampled; and finally, based on the sampling type and sampling plan, automatically perform data verification on the backup data corresponding to the application systems to be sampled.

[0049] This configuration allows for the automatic assignment of different sampling weight coefficients to different application systems based on system factors, and the matching of corresponding sampling types. No manual judgment is required, which not only improves the automation and intelligence of data verification but also enhances its accuracy and efficiency. It avoids inaccurate data verification or low efficiency caused by inaccurate manual judgment, thereby reducing data verification costs. Furthermore, the sampling plan for each application system can be determined based on the sampling weight coefficients. Then, data verification can be automatically performed on the backup data corresponding to the application system according to the sampling type and plan. This configuration further enhances the automation and intelligence of data verification, thereby improving its efficiency. Attached Figure Description

[0050] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0051] Figure 1This is a flowchart of a data processing method according to an embodiment of this application;

[0052] Figure 2 This is a schematic diagram of the structure of a terminal device according to an embodiment of this application;

[0053] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0054] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0055] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0056] First, let me explain the terms used in this application:

[0057] Backup data refers to a collection or copy of data at a specific point in time stored on other non-volatile storage media to prevent data loss.

[0058] Backup media refers to the non-volatile physical storage medium on which backup data is stored.

[0059] It should be noted that the data processing methods, equipment, and media of this application can be used in the financial field, as well as in any other field. The application areas of the data processing methods, equipment, and media of this application are not limited.

[0060] With the development of internet technology, technologies such as AI, blockchain, cloud computing, and big data are flourishing. Especially with the advancement of digital transformation, data is becoming increasingly important and is increasingly becoming the lifeline for enterprises. Data loss can cause incalculable losses to enterprises and users, and data backup is the most important means of ensuring enterprise data security. To prevent data loss due to human error or system failure, enterprises invest significant manpower and resources to copy important data from application hosts and other hard drives or arrays to other backup storage media in real time or periodically. However, if the backup storage media is damaged, or if there are flaws in the data backup process, it may be impossible to read or restore the data when it needs to be recovered. Therefore, it is necessary to verify backup data regularly.

[0061] There are two main existing methods for verifying backup data. One is backup media availability verification: this involves checking the readability of the backup storage media to prevent backup data from becoming unavailable due to media failure. Backup media availability sampling checks are quick and simple to implement, but their verification and assurance of the final availability of backup data are less robust than those for backup data recoverability verification.

[0062] Another type is backup data recoverability verification: this is a check to verify whether backup data can meet the actual needs of production. It typically requires loading the backup data into a system environment consistent with the production environment. Compared to backup media availability verification, backup data recoverability verification takes longer and is more complex, but the verification results are better. The backup data recoverability verification process includes the backup media availability verification content.

[0063] In existing technologies, data verification involves operators making manual judgments based on application system configurations and other factors to select the appropriate verification method. However, manual selection is inaccurate, leading to low verification efficiency and increased costs.

[0064] Based on this technical problem, the inventive concept of this application is to provide a data processing method that is accurate, efficient, and low-cost in backing up data verification.

[0065] Specifically, the following steps are taken: First, based on system factors such as the application system's disaster recovery level, application system fault information, application system's age level, and application system's historical sampling information, the sampling weight coefficient corresponding to the application system to be sampled is determined. Then, based on the sampling weight coefficient, the sampling type and sampling plan corresponding to the application system to be sampled are determined. Finally, based on the sampling type and sampling plan, the backup data corresponding to the application system to be sampled is automatically verified.

[0066] This configuration allows for the automatic assignment of different sampling weight coefficients to different application systems based on system factors, and the matching of corresponding sampling types. No manual judgment is required, which not only improves the automation and intelligence of data verification but also enhances its accuracy and efficiency. It avoids inaccurate data verification or low efficiency caused by inaccurate manual judgment, thereby reducing data verification costs. Furthermore, the sampling plan for each application system can be determined based on the sampling weight coefficients. Then, data verification can be automatically performed on the backup data corresponding to the application system according to the sampling type and plan. This configuration further enhances the automation and intelligence of data verification, thereby improving its efficiency.

[0067] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0068] Example 1

[0069] Figure 1 This is a flowchart of a data processing method provided in an embodiment of this application. The executing entity of the data processing method provided in this embodiment can be a data processing device or a terminal device integrating a data processing device (hereinafter referred to as: terminal device). This embodiment describes the data processing method with the terminal device as the executing entity. Figure 1 As shown, the data processing method may include the following steps:

[0070] S101: Periodically determine the system factors corresponding to the application system to be sampled. The system factors may include one or more of the following: application system disaster recovery level, application system fault information, application system newness level, and application system historical sampling information.

[0071] In this embodiment, the application system to be sampled and its corresponding system factors can be updated periodically according to the actual application system in the terminal device. For example, new application systems can be added and offline application systems can be deleted.

[0072] In this embodiment, the system factors can be related to the possible causes of problems with the backup data. Those skilled in the art can flexibly set these factors based on their experience in actual operation. For example, they can include the application system disaster recovery level, application system fault information, application system new and old level, application system historical sampling information, etc. No restrictions are imposed here.

[0073] In this embodiment, disaster recovery refers to the use of scientific and technological means and methods to establish a systematic data emergency response mechanism in advance to cope with the occurrence of disasters. Application system disaster recovery is built on the basis of data-level disaster recovery, which involves replicating the application system, that is, building another application support system in an off-site disaster recovery center. The support system includes a data backup system, a backup data processing system, a backup network system, etc. Application-level disaster recovery can provide application system takeover capability, that is, in the event of a failure in the production center, the disaster recovery center can take over the application, thereby minimizing system downtime and improving business continuity. The application system disaster recovery level can utilize the existing technology for classifying disaster recovery for various application systems.

[0074] In one possible implementation, determining the system factor corresponding to the application system to be sampled in step S101 above may include: determining the disaster recovery level of the application system to be sampled; determining the corresponding application system fault information based on the number of faults of the application system to be sampled within a first preset time period; determining the new / old level of the application system to be sampled based on the configuration information of the application system to be sampled, wherein the configuration information includes one or more of the following: application system version, hardware device model, and backup data file name; and determining the corresponding historical sampling information of the application system based on the number of samplings of the application system to be sampled within a second preset time period.

[0075] In this embodiment, the disaster recovery level of the application system to be sampled can be determined by using the existing technology to classify the disaster recovery levels of each application system, that is, by obtaining the disaster recovery level of each application system from the "application system service catalog" of the terminal device.

[0076] Application system fault information can be the number of faults of the application system to be inspected within a first preset time period, and can be obtained from the "production fault event database" of the terminal equipment.

[0077] The age rating of an application system can be determined by whether the system to be inspected is old or new, or by classifying the age of the system according to different levels. The age rating of an application system can be determined by the configuration information of the system to be inspected. The configuration information of each application system can be obtained from the "application configuration library" of the terminal device to determine the age rating of the application system.

[0078] The historical sampling information of the application system can be whether the application system to be sampled has been sampled within a second preset time period, which can be obtained from the historical sampling data.

[0079] In this embodiment, the first preset duration can be flexibly set by those skilled in the art; for example, the first preset duration can be one year or two years, without any limitation. Similarly, the second preset duration can be flexibly set by those skilled in the art; for example, the first preset duration can be one year or two years, without any limitation. The first preset duration and the second preset duration can be the same or different. The configuration information can be flexibly set by those skilled in the art based on experience; for example, the configuration information can be one or more of the following: application system version, hardware device model, and backup data file name, without limitation.

[0080] In this embodiment, by calling the historical data stored in each module of the terminal device, the disaster recovery level, fault information, new and old levels, and historical sampling information of the application system to be sampled can be easily and conveniently determined, i.e., system factors.

[0081] S102: Determine the sampling weight coefficient corresponding to the application system to be sampled based on the system factor.

[0082] In one possible implementation, step S102 above, which determines the sampling weight coefficient corresponding to the application system to be sampled based on the system factor, may include:

[0083] S1021: Based on the preset correspondence between disaster recovery levels and scores, determine the first score corresponding to the disaster recovery level of the application system.

[0084] S1022: Determine the second score corresponding to the application system fault information based on the preset correspondence between fault information and scores.

[0085] S1023: Based on the preset correspondence between the old and new levels and scores, determine the third score corresponding to the old and new levels of the application system.

[0086] S1024: Based on the preset correspondence between sampling information and scores, determine the fourth score corresponding to the historical sampling information of the application system.

[0087] S1025: Determine the sampling weight coefficient corresponding to the application system to be sampled using the following formula (1):

[0088] F = aA + bB + cC + dD (1)

[0089] Where F represents the sampling weight coefficient, A represents the first score, B represents the second score, C represents the third score, D represents the fourth score, and a, b, c and d all represent proportional constants.

[0090] In this embodiment, the four proportionality constants a, b, c, and d can be the same or different. Those skilled in the art can set them flexibly. For example, F = 0.5A + 0.25B + 0.5C + D.

[0091] For example, Table 1 shows the correspondence between system factors and scores, as shown in Table 1 below:

[0092] Table 1

[0093]

[0094]

[0095] In this embodiment, different correspondences between system factors and scores can be preset. After obtaining the system factors of the application system to be sampled, the scores corresponding to the system factors of the application system to be sampled can be determined simply and accurately, and the sampling weight coefficient can be calculated accordingly.

[0096] S103: Determine the sampling type and sampling plan for the application system to be sampled based on the sampling weight coefficient.

[0097] In one possible implementation, step S103 above, which determines the sampling type and sampling plan corresponding to the application system to be sampled based on the sampling weight coefficient, may include:

[0098] S1031: For each application system to be sampled, the sampling type corresponding to the application system to be sampled is determined according to the sampling weight coefficient.

[0099] S1032: Based on the sampling type and sampling weight coefficient, determine the sampling cycle corresponding to the application system to be sampled, and the sampling initiation time corresponding to each sampling cycle.

[0100] S1033: Generate a sampling plan for each application system to be sampled, based on each application system to be sampled, the sampling period corresponding to each application system to be sampled, and the sampling initiation time corresponding to each sampling period.

[0101] In this embodiment, the sampling period can be annual, quarterly, or monthly, and those skilled in the art can set it flexibly according to actual conditions. The sampling initiation time can be set arbitrarily according to the sampling period, and there is no limitation here. Preferably, the sampling initiation time can be set in conjunction with the sampling periods of all application systems to be sampled, so as to balance the number of application systems sampled within a certain period of time.

[0102] In this embodiment, the sampling type and sampling period for each application system to be sampled can be determined based on the sampling weight coefficient, and the corresponding sampling initiation time can be determined based on the sampling period. This setup improves the accuracy and efficiency of data verification for the application systems to be sampled, avoids data verification using inappropriate sampling types, and thus saves data verification costs. Furthermore, based on each application system to be sampled, its corresponding sampling period, and the sampling initiation time for each sampling period, a sampling plan is generated for each application system to be sampled. This allows the terminal system to automatically perform data verification on the application systems to be sampled according to the sampling plan, further improving data verification efficiency.

[0103] In one possible implementation, the step S1031 above, which determines the sampling type of the application system to be sampled based on the sampling weight coefficient, may include: determining whether the sampling weight coefficient is greater than or equal to a preset weight coefficient threshold; if yes, the sampling type of the application system to be sampled is backup data recovery sampling; if no, the sampling type of the application system to be sampled is backup media sampling.

[0104] In this embodiment, the weighting coefficient threshold can be flexibly set by those skilled in the art according to actual conditions, and no restrictions are imposed here.

[0105] In this embodiment, backup media sampling inspection refers to checking the readability of backup storage media to prevent backup data from becoming unavailable due to backup media failure. Backup media availability sampling inspection requires little time and has a simple implementation mechanism, but its verification and assurance of the final availability of backup data is less robust than that of backup data recoverability verification.

[0106] Backup data recovery sampling inspection refers to the check conducted to verify whether backup data can fully meet actual production needs. This typically requires loading the backup data into a system environment consistent with the production environment. Compared to backup media availability verification, backup data recoverability verification takes longer and has a more complex process, but the verification results are better. The backup data recoverability verification process includes backup media availability verification.

[0107] In this embodiment, the sampling type of the application system to be sampled can be determined simply and accurately based on the preset weight coefficient threshold.

[0108] S104: Based on the sampling inspection type and sampling inspection plan, perform data verification on the backup data corresponding to the application system to be sampled.

[0109] In one possible implementation, step S104 above, which verifies the backup data corresponding to the application system to be sampled according to the sampling type and sampling plan, may include:

[0110] S1041: For each sampling initiation time in the sampling plan, determine the application system to be sampled corresponding to the sampling initiation time, and the sampling type corresponding to the application system to be sampled.

[0111] S1042: Determine whether the sampling inspection type is backup media sampling inspection;

[0112] S1043: If so, determine the backup data storage medium corresponding to the application system to be sampled; according to the sampling period and the sampling initiation time corresponding to each sampling period, send a data read request to the backup data storage medium; if the backup data is read, the backup data verification is successful; if the backup data is not read, the backup data verification fails.

[0113] S1044: If not, determine the backup data storage medium and database type of the application system to be sampled; determine the database to be verified based on the database type; send a data read request to the backup data storage medium and load the read backup data into the database to be verified; if the read backup data is successfully loaded, the backup data verification is successful; if the backup data is not read or the read backup data is not successfully loaded, the backup data verification fails.

[0114] In this implementation, application systems to be sampled can be sampled sequentially according to the order in which the sampling is initiated. Furthermore, the number of applications requiring daily sampling can be dynamically displayed based on the set sampling cycle and sampling initiation time.

[0115] In this implementation, if backup data is not read, i.e., the data verification of the application system to be sampled fails, the error information fed back during the process can be acquired and saved. Similarly, if backup data is not read or the read backup data is not successfully loaded, the error information fed back during the process can also be acquired and saved.

[0116] In this embodiment, during the data verification process of the backup data corresponding to the application system to be sampled, operations such as pausing and terminating can be performed. After data verification, the data verification results, feedback error information, and the sampling end time can be saved and output.

[0117] In this embodiment, when the sampling inspection type is backup data recovery sampling inspection, the backup data stored in the backup data storage medium needs to be loaded into the database to be verified. The database type of the database to be verified needs to be consistent with the database type of the data storage of the application system to be sampled, that is, the database environment is the same.

[0118] In this embodiment, by sequentially sampling the application systems to be inspected according to the order in which the sampling was initiated, the data verification of the application systems can be carried out in an orderly manner. Furthermore, by performing corresponding data verification on the application systems to be inspected according to different sampling types, the accuracy and efficiency of data verification can be improved.

[0119] In one possible implementation, when the sampling type is a backup data recovery sampling, after determining the database to be verified based on the database type, it may also include: storing the initial state of the database to be verified.

[0120] After verifying the backup data of the application system to be sampled, the process may also include: initializing the database to be verified based on its initial state.

[0121] In this embodiment, after data verification is performed using the database to be verified, the database to be verified needs to be initialized to prevent data contamination.

[0122] In one possible implementation, after verifying the backup data corresponding to the application system to be sampled, the system may further include storing one or more of the following: application system name, application system disaster recovery level, application system new / old level, sampling cycle, sampling initiation time, sampling type, data verification result, and error information corresponding to data verification failure for each application system to be sampled.

[0123] In this embodiment, after verifying the backup data corresponding to the application system to be inspected, the data generated in the process can be stored to facilitate staff in finding the inspection results and records of a specific application system. The inspection results and records can be output to staff in the form of views or reports.

[0124] S105: If the backup data verification of the application system to be inspected fails, a backup data verification failure message is generated based on the application system to be inspected and the corresponding inspection type, and the backup data verification failure message is sent to the user equipment.

[0125] In this embodiment, if the backup data verification for a certain application system fails, a backup data verification failure prompt message can be generated based on the application system's name and other information, as well as the sampling type, and output to the user to prompt the user to take appropriate measures in a timely manner. The application system's name and sampling type are provided to help the user find the reason for the verification failure.

[0126] In this embodiment, the sampling weight coefficients for the application systems to be sampled are first determined based on system factors such as the application system's disaster recovery level, application system fault information, application system's age level, and historical sampling information. Then, based on these sampling weight coefficients, the sampling type and sampling plan for each application system are determined. Finally, based on the sampling type and plan, the backup data for the application systems to be sampled is automatically verified. This setup automatically assigns different sampling weight coefficients to different application systems based on system factors and matches them with appropriate sampling types, eliminating the need for manual judgment. This not only improves the automation and intelligence of data verification but also enhances its accuracy and efficiency, avoiding inaccurate or inefficient data verification due to inaccurate manual judgment, thereby reducing data verification costs. Furthermore, the sampling plan for each application system can be determined based on the sampling weight coefficients, and then the backup data for that application system can be automatically verified according to the sampling type and plan. This setup further improves the automation and intelligence of data verification, thereby increasing its efficiency.

[0127] The data processing method of this application is described below with a specific embodiment.

[0128] Example 2

[0129] In one specific embodiment, a bank needs to periodically verify the backup data of its various systems. The specific data processing procedure is as follows:

[0130] The first step is for the terminal device to obtain the disaster recovery level of each application system from the "Application System Service Catalog"; obtain the application system fault information from the "Production Fault Event Database"; obtain the configuration information of each application system from the "Application Configuration Database" and determine the old and new application system levels of each application system accordingly; and obtain the historical sampling records of each application system from the historical sampling records.

[0131] The second step involves the terminal device determining the sampling weight coefficient for the application system to be sampled based on the system factors.

[0132] The third step is for the terminal device to determine the sampling type corresponding to each application system based on the weight coefficient threshold, and to determine the sampling cycle corresponding to the application system to be sampled, as well as the sampling initiation time corresponding to each sampling cycle, based on the sampling type and the sampling weight coefficient.

[0133] The fourth step is for the terminal device to generate a sampling plan for each application system to be sampled, based on the sampling period for each application system to be sampled and the sampling initiation time for each sampling period.

[0134] The fifth step involves the terminal device verifying the data of each application system sequentially according to the sampling plan and the corresponding sampling type.

[0135] Step 6: The terminal device stores and outputs one or more of the following for each application system to be sampled: application system name, application system disaster recovery level, application system new / old level, sampling cycle, sampling initiation time, sampling type, data verification result, and error message corresponding to data verification failure.

[0136] Figure 2 This is a schematic diagram of the structure of a terminal device according to an embodiment of this application, as shown below. Figure 2 As shown, the terminal device includes: a weight determination module 21, a sampling processing module 22, and a data verification module 23. The weight determination module 21 is used to determine the system factors corresponding to the application system to be sampled. These system factors include one or more of the following: application system disaster recovery level, application system fault information, application system new / old level, and application system historical sampling information. Based on the system factors, the module determines the sampling weight coefficient corresponding to the application system to be sampled. The sampling processing module 22 is used to determine the sampling type and sampling plan corresponding to the application system to be sampled based on the sampling weight coefficient. The data verification module 23 is used to verify the backup data corresponding to the application system to be sampled based on the sampling type and sampling plan. In one embodiment, the specific functions of the terminal device can be described in steps S101-S105 of Embodiment 1, and will not be repeated here.

[0137] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application, as shown below. Figure 3 As shown, the electronic device includes: a processor 101, and a memory 102 communicatively connected to the processor 101; the memory 102 stores computer-executable instructions; the processor 101 executes the computer-executable instructions stored in the memory 102 to implement the steps of the data processing methods in the above-described method embodiments.

[0138] The electronic device can be standalone or part of a terminal device, and the processor 101 and memory 102 can utilize existing hardware of the terminal device.

[0139] In the aforementioned electronic device, the memory 102 and the processor 101 are electrically connected directly or indirectly to enable data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines, such as a bus connection. The memory 102 stores computer-executable instructions that implement data access control methods, including at least one software functional module that can be stored in the memory 102 in the form of software or firmware. The processor 101 executes various functional applications and data processing by running the software programs and modules stored in the memory 102.

[0140] The memory 102 may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 102 stores programs, which are executed by the processor 101 upon receiving execution instructions. Furthermore, the software programs and modules within the memory 102 may include an operating system, which may include various software components and / or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.) and can communicate with various hardware or software components to provide an operating environment for other software components.

[0141] Processor 101 can be an integrated circuit chip with signal processing capabilities. The aforementioned processor 101 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor.

[0142] An embodiment of this application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the steps of the various method embodiments of this application.

[0143] An embodiment of this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the various method embodiments of this application.

[0144] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the appended claims.

[0145] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A data processing method, characterized in that, include: The system factors corresponding to the application systems to be sampled are periodically determined. The system factors include: application system disaster recovery level, application system fault information, application system newness level, and application system historical sampling information. The sampling weight coefficient corresponding to the application system to be sampled is determined based on the system factor. The step of determining the sampling type and sampling plan corresponding to the application system to be sampled based on the sampling weight coefficient specifically includes: For each application system to be sampled, determine whether the sampling weight coefficient is greater than or equal to a preset weight coefficient threshold; if yes, the sampling type corresponding to the application system to be sampled is backup data recovery sampling; if no, the sampling type corresponding to the application system to be sampled is backup media sampling. Based on the sampling type and the sampling weight coefficient, the sampling cycle corresponding to the application system to be sampled and the sampling initiation time corresponding to each sampling cycle are determined. Based on each application system to be inspected, the sampling period corresponding to each application system to be inspected, and the sampling initiation time corresponding to each sampling period, a sampling plan is generated for the application system to be inspected. According to the sampling type and sampling plan, the backup data corresponding to the application system to be sampled is verified. If the backup data verification of the application system to be inspected fails, a backup data verification failure prompt message is generated according to the application system to be inspected and the corresponding inspection type, and the backup data verification failure prompt message is sent to the user equipment. The determination of the system factors corresponding to the application system to be sampled specifically includes: Determine the disaster recovery level of the application system to be sampled; Based on the number of failures of the application system to be inspected within a first preset time period, the corresponding application system failure information is determined; Based on the configuration information of the application system to be inspected, the newness level of the application system to be inspected is determined. The configuration information includes one or more of the following: application system version, hardware device model, and backup data file name. Based on the number of times the application system to be inspected is inspected within a second preset time period, the corresponding historical inspection information of the application system is determined. The step of determining the sampling weight coefficient corresponding to the application system to be sampled based on the system factor specifically includes: Based on the preset correspondence between disaster recovery levels and scores, determine the first score corresponding to the disaster recovery level of the application system; Based on the preset correspondence between fault information and scores, determine the second score corresponding to the fault information of the application system; Based on the preset correspondence between the old and new levels and scores, the third score corresponding to the old and new levels of the application system is determined; Based on the preset correspondence between sampling information and scores, the fourth score corresponding to the historical sampling information of the application system is determined. The sampling weight coefficient corresponding to the application system to be sampled is determined using the following formula: Among them, the This represents the sampling weighting coefficient, the... Indicates the first score, the stated Indicates the second score, the Indicates the third score, the Indicates the fourth score, the and Both represent proportionality constants.

2. The method according to claim 1, characterized in that, The step of verifying the backup data corresponding to the application system to be inspected according to the sampling type and sampling plan specifically includes: For each sampling initiation time in the sampling plan, determine the application system to be sampled corresponding to the sampling initiation time, and the sampling type corresponding to the application system to be sampled. Determine whether the sampling type is a backup media sampling inspection; If so, determine the backup data storage medium corresponding to the application system to be sampled; according to the sampling period and the sampling initiation time corresponding to each sampling period, send a data read request to the backup data storage medium; if backup data is read, the backup data verification is successful; if backup data is not read, the backup data verification fails. If not, determine the backup data storage medium and database type corresponding to the application system to be sampled; determine the database to be verified based on the database type; send a data read request to the backup data storage medium and load the read backup data into the database to be verified; if the read backup data is successfully loaded, the backup data verification is successful; if no backup data is read or the read backup data is not successfully loaded, the backup data verification fails.

3. The method according to claim 2, characterized in that, When the sampling inspection type is backup data recovery sampling inspection, after determining the database to be verified according to the database type, the method further includes: Store the initial state of the database to be verified; After performing data verification on the backup data corresponding to the application system to be sampled, the method further includes: The database to be verified is initialized based on its initial state.

4. The method according to claim 2, characterized in that, After performing data verification on the backup data corresponding to the application system to be sampled, the method further includes: The system stores one or more of the following for each application system to be sampled: application system name, application system disaster recovery level, application system new / old level, sampling cycle, sampling initiation time, sampling type, data verification result, and error message corresponding to data verification failure.

5. A terminal device, characterized in that, include: The weight determination module is used to periodically determine the system factors corresponding to the application system to be sampled. The system factors include: application system disaster recovery level, application system fault information, application system newness level, and application system historical sampling information; and determine the sampling weight coefficient corresponding to the application system to be sampled based on the system factors. The sampling inspection processing module is used to determine the sampling type and sampling plan corresponding to the application system to be inspected based on the sampling weight coefficient. Specifically, it includes: for each application system to be inspected, determining whether the sampling weight coefficient is greater than or equal to a preset weight coefficient threshold; if yes, the sampling type corresponding to the application system to be inspected is backup data recovery sampling inspection; if no, the sampling type corresponding to the application system to be inspected is backup media sampling inspection; determining the sampling period corresponding to the application system to be inspected and the sampling initiation time corresponding to each sampling period based on the sampling type and the sampling weight coefficient; and generating the sampling plan corresponding to the application system to be inspected based on each application system to be inspected, the sampling period corresponding to each application system to be inspected, and the sampling initiation time corresponding to each sampling period. The data verification module is used to verify the backup data corresponding to the application system to be inspected according to the sampling type and sampling plan; if the backup data verification of the application system to be inspected fails, a backup data verification failure prompt message is generated according to the application system to be inspected and the corresponding sampling type, and the backup data verification failure prompt message is sent to the user equipment. The weight determination module is further used to: determine the disaster recovery level of the application system corresponding to the application system to be sampled; Based on the number of failures of the application system to be inspected within a first preset time period, the corresponding application system failure information is determined; Based on the configuration information of the application system to be inspected, the newness level of the application system to be inspected is determined. The configuration information includes one or more of the following: application system version, hardware device model, and backup data file name. Based on the number of times the application system to be inspected is inspected within a second preset time period, the corresponding historical inspection information of the application system is determined. The weight determination module is further configured to: Based on the preset correspondence between disaster recovery levels and scores, determine the first score corresponding to the disaster recovery level of the application system; Based on the preset correspondence between fault information and scores, determine the second score corresponding to the fault information of the application system; Based on the preset correspondence between the old and new levels and scores, the third score corresponding to the old and new levels of the application system is determined; Based on the preset correspondence between sampling information and scores, the fourth score corresponding to the historical sampling information of the application system is determined. The sampling weight coefficient corresponding to the application system to be sampled is determined using the following formula: Among them, the This represents the sampling weighting coefficient, the... Indicates the first score, the stated Indicates the second score, the Indicates the third score, the Indicates the fourth score, the and Both represent proportionality constants.

6. An electronic device, comprising a processor and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 4.

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