Recovery verification method and device for backup database cluster, equipment, medium and program product

Abstract

The invention provides a recovery verification method and device for a backup database cluster, equipment, a medium and a program product, which can be applied to the technical field of finance. The method comprises the following steps: obtaining performance monitoring indexes of source database clusters in a preset time period, wherein the source database clusters are in one-to-one correspondence with backup database clusters in a backup database cluster list; based on the performance monitoring index, determining a recovery verification priority for the backup database cluster; based on the recovery verification priority, a recovery verification plan is generated, and the recovery verification plan is used for indicating data recovery verification to be carried out on a preset number of backup database clusters to be recovered and verified from a preset moment; based on the data volume of the backup data of the backup database cluster to be recovered and verified, determining a recovery verification type, the recovery verification type being used for indicating whether to perform full recovery verification on the backup data; and based on the recovery verification type and the recovery verification plan, generating a recovery verification task and executing the recovery verification task.

Description

Technical Field

[0001] The present disclosure relates to the field of financial technology, specifically to the field of data backup technology, and more specifically to a recovery verification method, device, equipment, medium and program product for backing up a database cluster. Background Art

[0002] Database cluster backup is a key strategy to ensure data security and business continuity. It is a common disaster recovery technology in the financial industry that can restore data and database functions in the event of hardware failure, data loss, system crash or other disasters. In order to ensure the availability of the backup data of the database cluster, the availability of the backup data is generally verified through manual recovery according to the maintenance plan.

[0003] In the process of implementing the embodiments of the present disclosure, it was found that although the automatic recovery verification method can be used to recover and verify the database, when dealing with a large amount of data in the database cluster, there are still problems such as low recovery verification efficiency and low accuracy of recovery verification results. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a recovery verification method, apparatus, device, medium and program product for backing up a database cluster.

[0005] According to a first aspect of the present disclosure, a recovery verification method for a backup database cluster is provided, comprising: obtaining performance monitoring indicators of a source database cluster within a preset time period, wherein the source database cluster corresponds one-to-one to a backup database cluster in a backup database cluster list; determining a recovery verification priority for the backup database cluster based on the performance monitoring indicator; generating a recovery verification plan based on the recovery verification priority for the backup database cluster, wherein the recovery verification plan is used to indicate that data recovery verification is to be performed on a preset number of backup database clusters to be recovered and verified starting from a preset time; determining a recovery verification type based on the data volume of the backup data of the backup database cluster to be recovered and verified, wherein the recovery verification type is used to indicate whether to perform full recovery verification on the backup data; and generating a recovery verification task based on the recovery verification type and the recovery verification plan and executing the recovery verification task.

[0006] According to an embodiment of the present disclosure, based on performance monitoring indicators, a recovery verification priority for a backup database cluster is determined, including: based on different pre-divided indicator value intervals, determining a target indicator value interval that matches the indicator value of the performance monitoring indicator; based on pre-configured weight values ​​corresponding to different indicator value intervals, determining a target weight value corresponding to the target indicator value interval; and based on the target weight value corresponding to the target indicator value interval, determining the recovery verification priority for the backup database cluster.

[0007] According to an embodiment of the present disclosure, performance monitoring indicators include: query rate per second, data volume, number of tables and central processing unit utilization rate; the recovery verification method for backing up a database cluster also includes: dividing the indicator values ​​of query rate per second, data volume, number of tables and central processing unit utilization rate into different indicator value intervals; and configuring corresponding weight values ​​for different indicator value intervals.

[0008] According to an embodiment of the present disclosure, the target indicator value interval includes a query rate per second value interval, a data volume value interval, a table quantity value interval, and a central processing unit usage rate value interval; based on the target weight value corresponding to the target indicator value interval, the recovery verification priority for the backup database cluster is determined, including: for each source database cluster, according to the weight value corresponding to the query rate per second value interval, the weight value corresponding to the data volume value interval, the weight value corresponding to the table quantity value interval, and the weight value corresponding to the central processing unit usage rate value interval, determine the first level value; and according to the first level value corresponding to each source database cluster, sort the backup database cluster list in descending order to obtain the recovery verification priority for the backup database cluster.

[0009] According to an embodiment of the present disclosure, based on a recovery verification type and a recovery verification plan, a recovery verification task is generated and executed, including: when it is determined that the recovery verification type indicates that full recovery verification is not performed on the backup data, the number of rows of each data table in the source database cluster that matches the backup database cluster to be recovered and verified and the amount of data in the data table are obtained; based on the number of rows of each data table and the amount of data in the data table, a recovery verification priority for the data table is determined; based on the recovery verification priority for the data table, a list of data tables for sampling is generated; a data table that meets a preset condition is filtered from the list of data tables as a target data table; and based on the target data table and the recovery verification plan, a recovery verification task is generated and executed.

[0010] According to an embodiment of the present disclosure, a recovery verification task includes a recovery task and a verification task; based on a target data table and a recovery verification plan, a recovery verification task is generated and the recovery verification task is executed, including: based on identification information of the target data table, matching a target backup data table from a backup database cluster that matches the target data table; generating a recovery task according to the backup data in the target backup data table and the recovery verification plan, and executing the recovery task, wherein the recovery task is used to indicate a task of restoring the backup data in the target backup data table starting from a preset time in a containerized data recovery verification environment, the containerized data recovery verification environment being pre-deployed based on the type of the backup database cluster; and in the case of determining that the recovery task is successfully executed, generating a verification task for verifying the backup data in the target backup data table in the containerized data recovery verification environment, and executing the verification task.

[0011] According to an embodiment of the present disclosure, a recovery verification priority for a data table is determined based on the number of rows of each data table and the amount of data in the data table, including: for each data table: based on pre-configured weight values ​​for different intervals of row numbers, determining a weight value for an interval of row numbers that matches the number of rows of the data table; based on pre-configured weight values ​​for different intervals of data volume, determining a weight value for an interval of data volume that matches the amount of data in the data table; determining a second-level value based on the weight value for the interval of row numbers that matches the number of rows of the data table and the weight value for the interval of data volume that matches the amount of data in the data table; and based on the second-level value corresponding to each data table, sorting the data tables in the backup database cluster to be recovered and verified in descending order to obtain a recovery verification priority for the data table.

[0012] According to an embodiment of the present disclosure, the backup database cluster to be restored and verified is a backup database cluster that has not been restored and verified within the recovery verification cycle; the recovery verification method for the backup database cluster also includes: when it is determined that the recovery verification task has been completed, updating the mark of the backup database cluster to be restored and verified in the backup database cluster list.

[0013] A second aspect of the present disclosure provides a recovery verification device for a backup database cluster, including: an acquisition module, used to obtain performance monitoring indicators of a source database cluster within a preset time period, wherein the source database cluster corresponds one-to-one to the backup database cluster in the backup database cluster list; a first determination module, used to determine the recovery verification priority for the backup database cluster based on the performance monitoring indicator; a generation module, used to generate a recovery verification plan based on the recovery verification priority for the backup database cluster, wherein the recovery verification plan is used to indicate that data recovery verification is performed on a preset number of backup database clusters to be recovered and verified starting from a preset time; a second determination module, used to determine a recovery verification type based on the data volume of the backup data of the backup database cluster to be recovered and verified, wherein the recovery verification type is used to indicate whether to perform full recovery verification on the backup data; and an execution module, used to generate a recovery verification task based on the recovery verification type and the recovery verification plan and execute the recovery verification task.

[0014] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0015] The fourth aspect of the present disclosure further provides a computer-readable storage medium having a computer program or instructions stored thereon, which implements the steps of the above method when the above computer program or instructions are executed by a processor.

[0016] The fifth aspect of the present disclosure further provides a computer program product, including a computer program or instructions, which implement the steps of the above method when the above computer program or instructions are executed by a processor.

[0017] According to an embodiment of the present disclosure, the recovery verification priority of the backup database cluster is determined based on the performance monitoring indicators of the source database cluster within a preset time period, and then based on the recovery verification priority, a recovery verification plan is generated, that is, from the backup database cluster list, it is determined for which backup database clusters to perform data recovery verification, and the first screening is completed. Based on the data volume of the backup data of the determined backup database cluster to be recovered and verified, it is determined whether it is a full verification or a partial verification, and the second screening is completed, and the recovery verification task is generated and executed. Since the backup database clusters in the entire backup database cluster list are not fully recovered and verified, but are recovered and verified based on two screenings, the recovery verification time can be shortened and the recovery verification efficiency can be improved. In addition, the first screening can screen important database clusters for recovery verification based on performance monitoring indicators, give priority to ensuring the availability of backup data of important database clusters, and improve disaster recovery performance. The second screening can further perform sampling verification on database clusters with large data volumes while ensuring that the database clusters are important clusters, further improving the recovery verification efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0019] Figure 1 The application scenario diagram of the recovery verification method, apparatus, device, medium and program product for backing up a database cluster according to an embodiment of the present disclosure is schematically shown;

[0020] Figure 2 A flowchart of a recovery verification method for backing up a database cluster according to an embodiment of the present disclosure is schematically shown;

[0021] Figure 3 A flowchart of a recovery verification method for backing up a database cluster according to another embodiment of the present disclosure is schematically shown;

[0022] Figure 4 A flowchart of a recovery verification method for backing up a database cluster according to another embodiment of the present disclosure is schematically shown;

[0023] Figure 5 A structural block diagram of a recovery verification device for backing up a database cluster according to an embodiment of the present disclosure is schematically shown; and

[0024] Figure 6A block diagram of an electronic device suitable for implementing a recovery verification method for a backup database cluster according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0025] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0026] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0027] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0028] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0029] It should be noted that in the embodiments of the present disclosure, certain software, components, models and other existing solutions in the industry may be mentioned, which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present disclosure, but it does not mean that the applicant has or will necessarily use the solution.

[0030] In the technical solution of the present disclosure, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0031] In the scenario of using personal information for automated decision-making, the methods, devices, and systems provided by the embodiments of the present disclosure provide users with corresponding operation portals for users to choose to agree or reject the automated decision-making results; if the user chooses to reject, the expert decision-making process will be entered. The expression "automated decision-making" here refers to the activity of automatically analyzing and evaluating a person's behavioral habits, interests and hobbies, or economic, health, credit status, etc. through computer programs, and making decisions. The expression "expert decision-making" here refers to the activity of making decisions by people who specialize in a certain field, have specialized experience, knowledge and skills, and have reached a certain level of professionalism.

[0032] In the process of implementing the embodiments of the present disclosure, it was found that although the automatic recovery verification method can be used to perform recovery verification on the database, when dealing with a large amount of data in the database cluster, there are still problems such as low recovery verification efficiency and low accuracy of recovery verification results. For example, although automatic recovery verification reduces manual intervention, in a database cluster with a huge amount of data, the verification process may require a lot of time and resources. The recovery and comparison operations of the full amount of data may become very time-consuming, resulting in reduced efficiency of recovery verification. For large-scale data sets, automatic recovery verification may only be verified for a portion of the data samples, which may result in the verification results being unable to fully represent the status of the entire database cluster. If the sample is not selected properly, key data may be missed, thereby reducing the accuracy and reliability of recovery verification.

[0033] Embodiments of the present disclosure provide a recovery verification method, apparatus, device, medium, and program product for a backup database cluster. The method includes: obtaining performance monitoring indicators of a source database cluster within a preset time period, wherein the source database cluster corresponds one-to-one to a backup database cluster in a backup database cluster list; determining a recovery verification priority for the backup database cluster based on the performance monitoring indicators; generating a recovery verification plan based on the recovery verification priority for the backup database cluster, wherein the recovery verification plan is used to indicate that data recovery verification is performed on a preset number of backup database clusters to be recovered and verified starting from a preset time; determining a recovery verification type based on the amount of backup data of the backup database cluster to be recovered and verified, wherein the recovery verification type is used to indicate whether to perform full recovery verification on the backup data; and generating a recovery verification task and executing the recovery verification task based on the recovery verification type and the recovery verification plan.

[0034] Figure 1 The application scenario diagram of the recovery verification method, apparatus, device, medium and program product for backing up a database cluster according to an embodiment of the present disclosure is schematically shown.

[0035] like Figure 1 As shown, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0036] The user can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0037] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0038] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0039] It should be noted that the recovery verification method for backing up a database cluster provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the recovery verification device for backing up a database cluster provided in the embodiment of the present disclosure can generally be set in the server 105. The recovery verification method for backing up a database cluster provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the recovery verification device for backing up a database cluster provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0040] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0041] The following will be based on Figure 1 The scene described by Figure 2~Figure 4 The recovery verification method for backing up a database cluster in the disclosed embodiment is described in detail.

[0042] Figure 2 The flowchart of the recovery verification method for backing up a database cluster according to an embodiment of the present disclosure is schematically shown.

[0043] like Figure 2 As shown, the recovery verification method for backing up a database cluster in this embodiment includes operations S210 to S250.

[0044] In operation S210, performance monitoring indicators of a source database cluster within a preset time period are obtained.

[0045] In operation S220 , a recovery verification priority for the backup database cluster is determined based on the performance monitoring indicator.

[0046] In operation S230 , a recovery verification plan is generated based on the recovery verification priority for the backup database cluster.

[0047] In operation S240 , a recovery verification type is determined based on the data volume of the backup data of the backup database cluster to be recovered and verified.

[0048] In operation S250, based on the recovery verification type and the recovery verification plan, a recovery verification task is generated and the recovery verification task is executed.

[0049] According to an embodiment of the present disclosure, the source database cluster corresponds to the backup database cluster in the backup database cluster list. The source database cluster can be used for business operations and application interactions. The backup database cluster is a copy of the source database cluster and can be used to recover data in the event of data loss, damage or disaster. The backup database cluster is not used for daily business operations. In the database backup system, all backup database clusters can be stored in the backup database cluster list. The backup database cluster list can be obtained through the database backup system to obtain information about the backup database cluster.

[0050] According to an embodiment of the present disclosure, the information of the backup database cluster may include but is not limited to the type of the backup database cluster, the number of databases in the backup database cluster, the size of the databases in the backup database cluster, the number of data tables in the backup database cluster, the data size of the data tables in the backup database cluster, etc.

[0051] According to an embodiment of the present disclosure, the source database cluster can be determined based on the information of the backup database cluster. The source database cluster can be monitored by configuring a monitoring system. Based on the monitoring data obtained by monitoring, the performance monitoring index of the source database cluster within a preset time period is obtained. The performance monitoring index is used to indicate the processing of business operations by the source database cluster.

[0052] According to an embodiment of the present disclosure, the preset time period may be determined based on actual accuracy and efficiency of the recovery verification, and may include, for example, but is not limited to, one week from the time of the recovery verification.

[0053] According to an embodiment of the present disclosure, the recovery verification priority for the backup database cluster may be used to indicate the importance of the backup database cluster requiring recovery verification.

[0054] For example, when it is determined that the performance monitoring indicator indicates that the source database cluster processes frequent business operations, it can be determined that the importance of the backup database cluster corresponding to the source database cluster requiring recovery verification is high, that is, the priority of the recovery verification for the backup database cluster is high. When it is determined that the performance monitoring indicator indicates that the source database cluster processes fewer business operations, it can be determined that the importance of the backup database cluster corresponding to the source database cluster requiring recovery verification is low, that is, the priority of the recovery verification for the backup database cluster is low.

[0055] According to an embodiment of the present disclosure, a recovery verification plan is used to indicate that data recovery verification is performed on a preset number of backup database clusters to be recovered and verified starting from a preset time. The preset number can be determined based on the actual accuracy and efficiency of the recovery verification and the number of backup database clusters in the backup database cluster list. The backup database clusters in the backup database cluster list may include a mark for indicating whether recovery verification has been performed in the recovery verification cycle. A preset number of backup database clusters to be recovered and verified can be determined from the backup database cluster list according to the recovery verification priority for the backup database cluster, and then a recovery verification plan is generated.

[0056] According to an embodiment of the present disclosure, the recovery verification type may be used to indicate whether to perform full recovery verification on the backup data.

[0057] According to an embodiment of the present disclosure, the data volume of the backup data of the backup database cluster to be recovered and verified can be compared with a data volume threshold. If it is greater than the threshold, it can be determined that the recovery verification type indicates that the backup data is not fully recovered and verified. If it is not greater than the threshold, it can be determined that the recovery verification type indicates that the backup data is fully recovered and verified.

[0058] According to an embodiment of the present disclosure, when it is determined that the recovery verification type indicates that full recovery verification is not performed on the backup data, a recovery verification task for not performing full recovery verification on the backup data can be generated according to the recovery verification plan, and the recovery verification task can be executed at a preset time in the recovery verification cycle.

[0059] According to an embodiment of the present disclosure, the recovery verification priority of the backup database cluster is determined based on the performance monitoring indicators of the source database cluster within a preset time period, and then based on the recovery verification priority, a recovery verification plan is generated, that is, from the backup database cluster list, it is determined for which backup database clusters to perform data recovery verification, and the first screening is completed. Based on the data volume of the backup data of the determined backup database cluster to be recovered and verified, it is determined whether it is a full verification or a partial verification, and the second screening is completed, and the recovery verification task is generated and executed. Since the backup database clusters in the entire backup database cluster list are not fully recovered and verified, but are recovered and verified based on two screenings, the recovery verification time can be shortened and the recovery verification efficiency can be improved. In addition, the first screening can screen important database clusters for recovery verification based on performance monitoring indicators, give priority to ensuring the availability of backup data of important database clusters, and improve disaster recovery performance. The second screening can further perform sampling verification on database clusters with large data volumes while ensuring that the database clusters are important clusters, further improving the recovery verification efficiency.

[0060] Figure 3A flowchart of a recovery verification method for backing up a database cluster according to another embodiment of the present disclosure is schematically shown.

[0061] In the process of implementing the embodiments of the present disclosure, it is found that if the recovery verification priority of the backup database cluster is not determined reasonably, the recovery verification resource allocation will be unreasonable, which will lead to resource waste and even reduce disaster recovery performance and increase business risks.

[0062] Based on this, in an embodiment of the present disclosure, performance monitoring indicators may include: query rate per second, data volume, number of tables, and CPU usage.

[0063] The recovery verification method for backing up the database cluster can include the above Figure 2 In addition to the operations S210 to S250 shown, operations S310 to S320 may also be included.

[0064] In operation S310, the index values ​​of the query rate per second, the data volume, the number of tables, and the CPU usage rate are divided into different index value intervals.

[0065] In operation S320, corresponding weight values ​​are configured for different index value intervals respectively.

[0066] According to an embodiment of the present disclosure, the number of divided indicator value intervals may be determined according to the characteristics and functions of different performance monitoring indicators.

[0067] According to an embodiment of the present disclosure, the query rate per second (QPS), the amount of data, the number of tables, and the central processing unit (CPU) usage rate may be divided into N intervals, respectively, and a different weight value may be configured for each interval.

[0068] For example, the recovery verification priority can be determined according to the product of the weight values ​​of the four performance monitoring indicators. The larger the weight value, the higher the priority.

[0069] According to the embodiments of the present disclosure, by dividing the index value interval, when the query rate per second is high, the data volume is large, the number of tables is large, and the CPU usage rate is high, it can be quickly determined that the source database cluster frequently processes business operations. By performing recovery verification on the backup database cluster corresponding to the source database cluster that frequently processes business operations, it can be ensured that the important backup database cluster is restored and verified first, and the recovery verification resources are reasonably used to reduce unnecessary resource waste, ensure disaster recovery performance, and reduce business risks.

[0070] According to the embodiments of the present disclosure, for the above Figure 2The operation S220 shown, determining the recovery verification priority for the backup database cluster based on the performance monitoring indicator, may include the operation of: determining a target indicator value interval that matches the indicator value of the performance monitoring indicator based on different indicator value intervals divided in advance. Determining a target weight value corresponding to the target indicator value interval based on weight values ​​corresponding to different indicator value intervals configured in advance. Determining the recovery verification priority for the backup database cluster based on the target weight value corresponding to the target indicator value interval.

[0071] According to an embodiment of the present disclosure, for the same type of performance monitoring indicators, different indicator value intervals can be pre-divided, and weight values ​​can be configured for the different indicator value intervals.

[0072] For example, for performance monitoring indicator 1, N indicator value intervals can be pre-divided, and then the indicator value of the obtained performance monitoring indicator 1 is matched with the N indicator value intervals to obtain the target indicator value interval. The weight value corresponding to the target indicator value interval is determined as the target weight value. Based on the source database cluster with a high target weight value, it can be determined that the recovery verification priority of the backup database cluster corresponding to the source database cluster is high. N is an integer greater than or equal to 1.

[0073] According to an embodiment of the present disclosure, the target indicator value interval may include a query rate per second value interval, a data volume value interval, a table volume value interval, and a CPU usage value interval.

[0074] According to an embodiment of the present disclosure, based on the target weight value corresponding to the target index value interval, determining the recovery verification priority for the backup database cluster may include the following operations: for each source database cluster, determining the first level value according to the weight value corresponding to the query rate per second value interval, the weight value corresponding to the data volume value interval, the weight value corresponding to the table volume value interval, and the weight value corresponding to the CPU usage rate value interval. According to the first level value corresponding to each source database cluster, the backup database cluster list is sorted in descending order to obtain the recovery verification priority for the backup database cluster.

[0075] For example, QPS is divided into three intervals: 0-1000, with a weight of 1; 1001-2000, with a weight of 2; and greater than 2001, with a weight of 3. Data volume is divided into three intervals: 0-100GB, with a weight of 1; 101-500GB, with a weight of 2; and greater than 500GB, with a weight of 3. The number of tables is divided into three intervals: 0-100, with a weight of 1; 101-1000, with a weight of 2; and greater than 1000, with a weight of 3. CPU usage is divided into three intervals: 0-10%, with a weight of 1; 11%-40%, with a weight of 2; and greater than 40%, with a weight of 3. If the QPS of source database cluster A is 500, the data volume is 200GB, the number of tables is 50, and the CPU usage is 15%, then the first-level value of backup database cluster A corresponding to source database cluster A is 4. By analogy, if the first level value of backup database cluster B corresponding to source database cluster B is 3, and the first level value of backup database cluster C corresponding to source database cluster C is 2, then the recovery verification priority for the backup database clusters can be backup database cluster A>backup database cluster B>backup database cluster C.

[0076] According to the embodiments of the present disclosure, when the indicator value of the performance monitoring indicator is obtained, the importance of the backup database cluster can be quickly and accurately determined based on matching the indicator value with the pre-divided indicator value interval, the allocation of recovery verification resources can be optimized, the efficiency of recovery verification can be improved, unnecessary waste of resources can be reduced, disaster recovery performance can be guaranteed, and business risks can be reduced.

[0077] According to the embodiments of the present disclosure, for the above Figure 2 The operation S250 shown, based on the recovery verification type and the recovery verification plan, generates a recovery verification task and executes the recovery verification task, which may include the following operations: when it is determined that the recovery verification type indicates that full recovery verification is not performed on the backup data, obtain the number of rows of each data table in the source database cluster that matches the backup database cluster to be recovered and verified and the amount of data in the data table. Based on the number of rows of each data table and the amount of data in the data table, determine the recovery verification priority for the data table. Based on the recovery verification priority for the data table, generate a data table list for sampling. Filter the data table that meets the preset conditions from the data table list as the target data table. Based on the target data table and the recovery verification plan, generate a recovery verification task and execute the recovery verification task.

[0078] According to an embodiment of the present disclosure, when it is determined that the number of rows in a data table is large and the amount of data in the data table is large, it can be determined that the recovery verification priority of the data table is high. The order of the data tables in the data table list used for sampling is determined according to the recovery verification priority of the data tables. For example, it can be but not limited to arranging the data tables with high recovery verification priority at the front position of the data table list used for sampling.

[0079] According to an embodiment of the present disclosure, the preset conditions may be determined based on the actual accuracy and efficiency of the recovery verification, for example, may include but not be limited to screening the first N data tables in the data table list.

[0080] According to the embodiments of the present disclosure, since the amount of data in the backup database cluster to be restored and verified is large, if the full amount is verified, the restoration and verification will take a long time. Therefore, by performing sampling verification on the data tables in the backup database cluster to be restored and verified, the efficiency of restoration and verification can be improved.

[0081] According to an embodiment of the present disclosure, a recovery verification task may include a recovery task and a verification task. Based on a target data table and a recovery verification plan, a recovery verification task is generated and the recovery verification task is executed, which may include the following operations: Based on the identification information of the target data table, a target backup data table is matched from a backup database cluster that matches the target data table. A recovery task is generated based on the backup data in the target backup data table and the recovery verification plan, and the recovery task is executed. When it is determined that the recovery task is successfully executed, a verification task for verifying the backup data in the target backup data table in a containerized data recovery verification environment is generated, and the verification task is executed.

[0082] According to an embodiment of the present disclosure, the identification information of the target data table may include but is not limited to the table name and the like.

[0083] According to an embodiment of the present disclosure, the source database cluster is configured in a production environment, and the backup database cluster is configured in a backup environment.

[0084] According to an embodiment of the present disclosure, a recovery task is used to indicate a task of recovering backup data in a target backup data table from a preset time in a containerized data recovery verification environment, and the containerized data recovery verification environment is pre-deployed based on the type of the backup database cluster. For example, containerization technology can be used in advance according to the type of the backup database cluster to quickly provide a corresponding containerized data recovery verification environment.

[0085] According to an embodiment of the present disclosure, by pre-deploying a containerized data recovery verification environment corresponding to the type of backup database cluster, the problem of time-consuming construction of the recovery verification environment can be avoided, and then rapid recovery and verification can be completed in combination with the backup data in the determined target backup data table.

[0086] In the process of implementing the embodiments of the present disclosure, it was found that although the recovery verification efficiency can be improved by sampling and verifying the data tables in the backup database cluster to be recovered and verified, if the sampling of the data tables is unreasonable, it will lead to unreasonable allocation of recovery verification resources, thereby causing waste of resources and even reducing disaster recovery performance and increasing business risks.

[0087] Based on this, in an embodiment of the present disclosure, based on the number of rows of each data table and the amount of data in the data table, determining the recovery verification priority for the data table may include the following operations: for each data table: based on the pre-configured weight values ​​of different row number intervals, determining the weight value of the row number interval that matches the number of rows in the data table. Based on the pre-configured weight values ​​of different data amount intervals, determining the weight value of the data amount interval that matches the data amount of the data table. Determine the second level value based on the weight value of the row number interval that matches the number of rows in the data table and the weight value of the data amount interval that matches the data amount of the data table. According to the second level value corresponding to each data table, sort the data tables in the backup database cluster to be recovered and verified in descending order to obtain the recovery verification priority for the data table.

[0088] According to the embodiments of the present disclosure, the number of rows in a data table may be divided into different intervals based on expert experience, and a corresponding weight value may be configured for each interval.

[0089] According to the embodiments of the present disclosure, the number of rows and the amount of data in a data table can be divided into M intervals, and different weights can be configured for each interval. The recovery verification priority for the data table can be determined based on the weight product of the two dimensions of the number of rows and the amount of data in the data table. The larger the weight, the higher the priority. For example: the number of rows in a data table can be divided into 2 intervals: 0-1 million, with a weight value of 1; if it exceeds 1 million, the weight value is 2. The amount of data in a data table can be divided into 2 intervals: 0-10GB, with a weight value of 1; if it exceeds 10GB, the weight value is 2. If the number of rows in data table 1 is 800,000 and the amount of data in the data table is 5GB, then the second level value of data table 1 is 1. M is an integer greater than or equal to 1.

[0090] According to the embodiments of the present disclosure, by dividing the number of rows and the amount of data in a data table into intervals, it is possible to quickly determine the importance of the data table, that is, the recovery verification priority for the data table, when it is determined that the number of rows and the amount of data in the data table are large. It is possible to ensure that the backup data of important backup data tables in the important backup database cluster are restored and verified first while speeding up the efficiency of recovery verification, reasonably use recovery verification resources to reduce unnecessary resource waste, ensure disaster recovery performance, and reduce business risks.

[0091] Figure 4 A flowchart of a recovery verification method for backing up a database cluster according to yet another embodiment of the present disclosure is schematically shown.

[0092] like Figure 4 As shown, in this embodiment, the recovery verification method for backing up a database cluster may include operations S401 to S412.

[0093] In operation S401, a backup database cluster list is obtained.

[0094] In operation S402, the query rate per second, data volume, number of tables, and CPU usage of the source database cluster within a preset time period are obtained.

[0095] In operation S403 , a recovery verification priority for the backup database cluster is determined based on the query rate per second, the amount of data, the number of tables, and the CPU usage.

[0096] According to an embodiment of the present disclosure, different index value intervals can be respectively divided for the index values ​​of query rate per second, data volume, number of tables, and CPU usage rate. Corresponding weight values ​​are respectively configured for different index value intervals. For each source database cluster, a first level value is determined according to the weight value corresponding to the query rate per second value interval, the weight value corresponding to the data volume value interval, the weight value corresponding to the table number value interval, and the weight value corresponding to the CPU usage value interval; and according to the first level value corresponding to each source database cluster, the backup database cluster list is sorted in descending order to obtain the recovery verification priority for the backup database cluster.

[0097] In operation S404, a recovery verification plan is generated.

[0098] According to an embodiment of the present disclosure, the recovery verification plan is used to instruct to perform data recovery verification on a preset number of backup database clusters to be recovered and verified starting from a preset time.

[0099] In operation S405 , it is determined whether the amount of backup data of the backup database cluster to be restored and verified exceeds a data amount threshold.

[0100] According to an embodiment of the present disclosure, when it is determined that the amount of backup data of the backup database cluster to be restored and verified exceeds the data amount threshold, operation S406 is performed to perform sampling restoration and verification. When it is determined that the amount of backup data of the backup database cluster to be restored and verified does not exceed the data amount threshold, operation S407 is performed to perform full restoration and verification.

[0101] According to an embodiment of the present disclosure, a specific method for sampling recovery verification may include: obtaining the number of rows and the amount of data in each data table in a source database cluster that matches the backup database cluster to be recovered and verified; determining the recovery verification priority for the data table based on the number of rows and the amount of data in the data table; generating a data table list for sampling based on the recovery verification priority for the data table; and filtering a data table that meets a preset condition from the data table list as a target data table. A specific method for full recovery verification may include: obtaining all data tables in the backup database cluster to be recovered and verified, and using them as target data tables.

[0102] In operation S408 , a containerized data recovery verification environment is provided.

[0103] In operation S409, the backup data is restored.

[0104] According to an embodiment of the present disclosure, the backup data in the target data table determined in operation S407 or operation S406 may be restored in the containerized data recovery verification environment provided in operation S408 .

[0105] In operation S410, backup data is verified.

[0106] According to an embodiment of the present disclosure, in a case where it is determined that operation S409 is completed in restoring the backup data, operation S410 is performed.

[0107] In operation S411, backup data is cleaned up.

[0108] According to an embodiment of the present disclosure, when it is determined that the verification of the backup data in operation S410 is completed, operation S411 is performed to clean up the backup data in the containerized data recovery verification environment.

[0109] In operation S412, a recovery verification report is generated.

[0110] According to an embodiment of the present disclosure, a recovery verification report may be generated based on the recovery and verification conditions. The recovery verification report may include but is not limited to the start time, end time, information of the restored backup database cluster, recovery results, verification results, etc.

[0111] According to an embodiment of the present disclosure, the recovery verification method for backing up a database cluster provided by the present disclosure can at least partially solve the problems of low recovery verification efficiency and low accuracy of recovery verification results when processing a huge amount of data in a database cluster.

[0112] According to another embodiment of the present disclosure, the backup database cluster to be restored and verified is a backup database cluster that has not been restored and verified within the restoration and verification cycle. Figure 2 In addition to the operations S210 to S250 shown, the following operation may be further included: when it is determined that the recovery verification task has been completed, updating the mark of the backup database cluster to be recovered and verified in the backup database cluster list.

[0113] According to an embodiment of the present disclosure, after the recovery verification task is executed, the mark of the backup database cluster to be recovered and verified, which indicates that recovery verification has not been performed in the recovery verification cycle, can be updated to a mark which indicates that recovery verification has been performed in the recovery verification cycle.

[0114] According to the embodiments of the present disclosure, updating the mark after executing the recovery verification task can avoid repeated recovery verification of the backup database cluster that has completed the recovery verification task, thereby avoiding unnecessary waste of recovery verification resources.

[0115] Based on the above-mentioned recovery verification method for backup database cluster, the present disclosure also provides a recovery verification device for backup database cluster. Figure 5 The device is described in detail.

[0116] Figure 5 The structural block diagram of the recovery verification device for backing up a database cluster according to an embodiment of the present disclosure is schematically shown.

[0117] like Figure 5 As shown, the recovery verification device 500 for backing up a database cluster in this embodiment includes an acquisition module 510 , a first determination module 520 , a generation module 530 , a second determination module 540 and an execution module 550 .

[0118] The acquisition module 510 is used to acquire the performance monitoring index of the source database cluster within a preset time period, wherein the source database cluster corresponds to the backup database cluster in the backup database cluster list one by one.

[0119] The first determination module 520 is used to determine the recovery verification priority for the backup database cluster based on the performance monitoring indicator.

[0120] The generating module 530 is used to generate a recovery verification plan based on the recovery verification priority for the backup database cluster, wherein the recovery verification plan is used to instruct to perform data recovery verification on a preset number of backup database clusters to be recovered and verified starting from a preset time.

[0121] The second determination module 540 is used to determine the recovery verification type based on the data volume of the backup data of the backup database cluster to be recovered and verified, wherein the recovery verification type is used to indicate whether to perform full recovery verification on the backup data.

[0122] The execution module 550 is used to generate a recovery verification task and execute the recovery verification task based on the recovery verification type and the recovery verification plan.

[0123] According to an embodiment of the present disclosure, the first determination module 520 may include: an interval determination subunit, a weight value determination subunit, and a first priority determination subunit. The interval determination subunit is used to determine a target indicator value interval that matches the indicator value of the performance monitoring indicator based on different indicator value intervals divided in advance. The weight value determination subunit is used to determine a target weight value corresponding to the target indicator value interval based on weight values ​​corresponding to different indicator value intervals pre-configured. The first priority determination subunit is used to determine the recovery verification priority for the backup database cluster based on the target weight value corresponding to the target indicator value interval.

[0124] According to an embodiment of the present disclosure, the performance monitoring index may include: query rate per second, data volume, number of tables and CPU usage rate; the recovery verification device 500 for backing up the database cluster may also include: an interval division module and a weight value configuration module. The interval division module is used to divide the index values ​​of query rate per second, data volume, number of tables and CPU usage rate into different index value intervals. The weight value configuration module is used to configure corresponding weight values ​​for different index value intervals.

[0125] According to an embodiment of the present disclosure, the target indicator value interval may include a query rate per second value interval, a data volume value interval, a table quantity value interval, and a central processing unit usage value interval; based on the target weight value corresponding to the target indicator value interval, determining the recovery verification priority for the backup database cluster may include: for each source database cluster, determining the first level value according to the weight value corresponding to the query rate per second value interval, the weight value corresponding to the data volume value interval, the weight value corresponding to the table quantity value interval, and the weight value corresponding to the central processing unit usage value interval; and according to the first level value corresponding to each source database cluster, sorting the backup database cluster list in descending order to obtain the recovery verification priority for the backup database cluster.

[0126] According to an embodiment of the present disclosure, the execution module 550 may include: an acquisition subunit, a second priority determination subunit, a list generation subunit, a target data table screening subunit, and a task generation execution subunit. The acquisition subunit is used to obtain the number of rows of each data table and the amount of data in the data table in the source database cluster that matches the backup database cluster to be recovered and verified when it is determined that the recovery verification type indicates that the backup data is not to be fully recovered and verified. The second priority determination subunit is used to determine the recovery verification priority for the data table based on the number of rows of each data table and the amount of data in the data table. The list generation subunit is used to generate a data table list for sampling based on the recovery verification priority for the data table. The target data table screening subunit is used to screen a data table that meets preset conditions from the data table list as a target data table. The task generation execution subunit is used to generate a recovery verification task and execute the recovery verification task based on the target data table and the recovery verification plan.

[0127] According to an embodiment of the present disclosure, a recovery verification task may include a recovery task and a verification task; based on a target data table and a recovery verification plan, generating a recovery verification task and executing the recovery verification task may include: based on identification information of the target data table, matching the target backup data table from a backup database cluster that matches the target data table; generating a recovery task according to the backup data in the target backup data table and the recovery verification plan, and executing the recovery task, wherein the recovery task is used to indicate a task of restoring the backup data in the target backup data table starting from a preset time in a containerized data recovery verification environment, and the containerized data recovery verification environment is pre-deployed based on the type of the backup database cluster; and when it is determined that the recovery task is successfully executed, generating a verification task for verifying the backup data in the target backup data table in the containerized data recovery verification environment, and executing the verification task.

[0128] According to an embodiment of the present disclosure, determining the recovery verification priority for a data table based on the number of rows of each data table and the amount of data in the data table may include: for each data table: determining a weight value for a row number interval that matches the number of rows of the data table based on pre-configured weight values ​​for different row number intervals; determining a weight value for a data volume interval that matches the amount of data of the data table based on pre-configured weight values ​​for different data volume intervals; determining a second level value based on the weight value for the row number interval that matches the number of rows of the data table and the weight value for the data volume interval that matches the amount of data of the data table; and sorting the data tables in the backup database cluster to be recovered and verified in descending order based on the second level value corresponding to each data table to obtain a recovery verification priority for the data table.

[0129] According to an embodiment of the present disclosure, the backup database cluster to be restored and verified is a backup database cluster that has not been restored and verified within the restoration and verification cycle; the restoration and verification device 500 for the backup database cluster may also include an update module. The update module is used to update the mark of the backup database cluster to be restored and verified in the backup database cluster list when it is determined that the restoration and verification task has been completed.

[0130] According to an embodiment of the present disclosure, any multiple modules among the acquisition module 510, the first determination module 520, the generation module 530, the second determination module 540 and the execution module 550 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the acquisition module 510, the first determination module 520, the generation module 530, the second determination module 540 and the execution module 550 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware and firmware or in a suitable combination of any of them. Alternatively, at least one of the acquisition module 510, the first determination module 520, the generation module 530, the second determination module 540 and the execution module 550 may be at least partially implemented as a computer program module, which may perform a corresponding function when executed.

[0131] Figure 6 A block diagram of an electronic device suitable for implementing a recovery verification method for a backup database cluster according to an embodiment of the present disclosure is schematically shown.

[0132] like Figure 6 As shown, the electronic device 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 to a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0133] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0134] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the input / output (I / O) interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0135] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0136] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 602 and / or RAM 603 described above and / or one or more memories other than ROM 602 and RAM 603.

[0137] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method provided by the embodiment of the present disclosure.

[0138] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 601. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0139] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0140] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, apparatus, module, unit, etc. described above can be implemented by a computer program module.

[0141] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0142] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0143] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0144] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A recovery verification method for a backup database cluster, characterized in that: The method comprises: Acquire performance monitoring indicators of a source database cluster within a preset time period, wherein the source database cluster corresponds one-to-one to the backup database clusters in the backup database cluster list; Based on the performance monitoring indicator, determining a recovery verification priority for the backup database cluster; Based on the recovery verification priority for the backup database cluster, generating a recovery verification plan, wherein the recovery verification plan is used to instruct to perform data recovery verification on a preset number of backup database clusters to be recovered and verified starting from a preset time; Determining a recovery verification type based on the amount of backup data of the backup database cluster to be recovered and verified, wherein the recovery verification type is used to indicate whether to perform full recovery verification on the backup data; and Based on the recovery verification type and the recovery verification plan, a recovery verification task is generated and executed.

2. The method according to claim 1, characterized in that The determining, based on the performance monitoring indicator, a recovery verification priority for the backup database cluster includes: Determine a target indicator value interval that matches the indicator value of the performance monitoring indicator based on different indicator value intervals divided in advance; Determining a target weight value corresponding to the target indicator value interval based on pre-configured weight values ​​corresponding to different indicator value intervals; and Based on the target weight value corresponding to the target index value interval, a recovery verification priority for the backup database cluster is determined.

3. The method according to claim 2, characterized in that The performance monitoring indicators include: query rate per second, data volume, number of tables and CPU usage; The method further comprises: Dividing the index values ​​of the query rate per second, the data volume, the number of tables, and the CPU usage rate into different index value intervals; and Corresponding weight values ​​are configured for different index value intervals respectively.

4. The method according to claim 3, characterized in that The target indicator value intervals include query rate per second value intervals, data volume value intervals, table volume value intervals, and CPU usage value intervals; The determining, based on the target weight value corresponding to the target index value interval, the recovery verification priority for the backup database cluster includes: For each of the source database clusters, determine a first level value according to the weight value corresponding to the query rate per second value interval, the weight value corresponding to the data volume value interval, the weight value corresponding to the table volume value interval, and the weight value corresponding to the CPU usage rate value interval; as well as According to the first level value corresponding to each of the source database clusters, the backup database cluster list is sorted in descending order to obtain a recovery verification priority for the backup database cluster.

5. The method according to any one of claims 1 to 4, characterized in that: The generating a recovery verification task based on the recovery verification type and the recovery verification plan and executing the recovery verification task includes: When it is determined that the recovery verification type indicates that full recovery verification is not performed on the backup data, the number of rows and the amount of data in each data table in the source database cluster matching the backup database cluster to be recovered and verified are obtained; Determining a recovery verification priority for each of the data tables based on the number of rows in the data tables and the amount of data in the data tables; generating a data table list for sampling based on the recovery verification priority for the data table; Selecting a data table that meets a preset condition from the data table list as a target data table; and Based on the target data table and the recovery verification plan, the recovery verification task is generated and executed.

6. The method according to claim 5, characterized in that The recovery verification task includes a recovery task and a verification task; The generating the recovery verification task based on the target data table and the recovery verification plan and executing the recovery verification task includes: Based on the identification information of the target data table, matching a target backup data table from a backup database cluster matching the target data table; generating the recovery task according to the backup data in the target backup data table and the recovery verification plan, and executing the recovery task, wherein the recovery task is used to indicate a task of recovering the backup data in the target backup data table starting from the preset time in a containerized data recovery verification environment, wherein the containerized data recovery verification environment is pre-deployed based on the type of the backup database cluster; and If it is determined that the recovery task is successfully executed, the verification task for verifying the backup data in the target backup data table in the containerized data recovery verification environment is generated, and the verification task is executed.

7. The method according to claim 5, characterized in that The determining, based on the number of rows of each of the data tables and the amount of data in the data tables, a recovery verification priority for the data tables includes: For each of the data tables: Determine, based on pre-configured weight values ​​of different row number intervals, a weight value of a row number interval that matches the number of rows in the data table; Determining a weight value of a data volume interval that matches the data volume of the data table based on pre-configured weight values ​​of different data volume intervals; determining a second level value according to a weight value of a row number interval matching the number of rows of the data table and a weight value of a data volume interval matching the data volume of the data table; and According to the second level value corresponding to each of the data tables, the data tables in the backup database cluster to be restored and verified are sorted in descending order to obtain a restoration and verification priority for the data tables.

8. The method according to claim 1, characterized in that The backup database cluster to be restored and verified is a backup database cluster that has not been restored and verified within the restoration and verification cycle; The method further comprises: When it is determined that the recovery verification task has been completed, the mark of the backup database cluster to be recovered and verified in the backup database cluster list is updated.

9. A recovery verification device for a backup database cluster, characterized in that: The device comprises: An acquisition module, used to acquire performance monitoring indicators of a source database cluster within a preset time period, wherein the source database cluster corresponds one-to-one to a backup database cluster in a backup database cluster list; A first determination module, configured to determine a recovery verification priority for the backup database cluster based on the performance monitoring indicator; A generating module, configured to generate a recovery verification plan based on the recovery verification priority for the backup database cluster, wherein the recovery verification plan is used to instruct to perform data recovery verification on a preset number of backup database clusters to be recovered and verified starting from a preset time; A second determination module is used to determine a recovery verification type based on the amount of backup data of the backup database cluster to be recovered and verified, wherein the recovery verification type is used to indicate whether to perform full recovery verification on the backup data; and An execution module is used to generate a recovery verification task and execute the recovery verification task based on the recovery verification type and the recovery verification plan.

10. An electronic device, comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

Images