Cross-data-center data backup method and device based on operation and maintenance arrangement

Abstract

The invention relates to a cross-data-center data backup method and device based on operation and maintenance arrangement, and relates to the technical field of data security. The method comprises the following steps: in response to a triggering instruction of a data backup task, determining at least two candidate backup transfer machines from each selectable data center; obtaining load condition description information corresponding to each candidate backup transfer machine, and calculating to obtain a priority score corresponding to each candidate backup transfer machine according to the numerical value of each index in the load condition description information; according to the priority score, screening out each pre-selected backup transfer machine from each candidate backup transfer machine, and randomly determining a transfer machine from each pre-selected backup transfer machine as a target backup transfer machine; and sending the copy data of the to-be-backed-up data to the target backup transfer machine from the first data center so as to issue the copy data of the to-be-backed-up data to the second data center through the target backup transfer machine. By adopting the method, the cross-data-center data backup efficiency can be improved.

Description

Technical Field

[0001] The present application relates to technical fields such as data security, data disaster recovery, and recovery, and in particular to a cross-data center data backup method, apparatus, computer equipment, computer-readable storage medium, and computer program product based on operation and maintenance orchestration. Background Art

[0002] In the early days, data backup was often performed in a master-slave mode. Taking the data backup process of the open source database MySQL as an example, it is often necessary to build a master-slave architecture MySQL database, with the slave node playing a backup role, and the master and slave nodes are deployed in the same data center. When the master node fails, ORC and other technologies are used to achieve master-slave switching, thereby ensuring that the master node can provide normal external services.

[0003] As the scale of business systems continues to expand and data security and management requirements become increasingly stringent, the traditional single data center master-slave architecture can no longer meet the needs. In this case, the master-slave node is deployed in different data centers (i.e., across data centers), and the slave node acts as a backup node.

[0004] However, the master-slave architecture across data centers brings some challenges, such as complicated data backup and network latency. Therefore, the current data backup methods across data centers have the problem of low backup efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide a cross-data center data backup method, device, computer equipment, computer-readable storage medium and computer program product based on operation and maintenance orchestration, which can improve the efficiency of cross-data center data backup in response to the above technical problems.

[0006] In a first aspect, an embodiment of the present application provides a data backup method across data centers based on operation and maintenance orchestration. The method comprises:

[0007] In response to a trigger instruction of a data backup task, at least two candidate backup transfer machines are determined from each optional data center; the backup transfer machine is a server in the optional data center that can be used for data transfer;

[0008] Obtaining load condition description information corresponding to each of the candidate backup transfer machines, and calculating the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load condition description information;

[0009] According to the priority score, pre-selected backup transfer machines are selected from the candidate backup transfer machines, and a transfer machine is randomly determined from the pre-selected backup transfer machines as a target backup transfer machine;

[0010] The copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

[0011] In one embodiment, the step of selecting the pre-selected backup transfer machines from the candidate backup transfer machines according to the priority scores includes:

[0012] For any transfer machine among the candidate backup transfer machines, if the restricted index of any transfer machine does not exceed the upper limit, sort any transfer machine that does not exceed the upper limit according to the size of the priority score;

[0013] According to the result of the sorting, a preset number of the pre-selected backup transfer machines with the highest sorting are selected from each of the transfer machines;

[0014] Among them, the restricted indicators include the number of server instances and disk capacity utilization; the indicators in the load situation description information include CPU load, the disk capacity utilization, memory utilization and network channel bandwidth utilization.

[0015] In one embodiment, the step of calculating the priority score corresponding to each candidate backup transfer machine according to the values ​​of each indicator in the load condition description information includes:

[0016] The actual operation status of each candidate backup transfer machine is evaluated to obtain a resource occupation score; the resource occupation score is used to characterize the situation that the computing resources of each backup transfer machine are occupied by the data backup task;

[0017] The priority score corresponding to each candidate backup transfer machine is calculated based on the resource occupancy score and the value of each indicator in the load situation description information.

[0018] In one embodiment, the method further comprises:

[0019] Obtaining the current execution status of the data backup task;

[0020] When the execution status is that the backup task is not completed and a task addition request for the data backup task is detected, the resource occupation score is increased;

[0021] When the execution status is that the backup task is completed, the resource occupation score is lowered.

[0022] In one embodiment, the method further comprises:

[0023] Obtaining a backup template corresponding to the data backup task;

[0024] The data storage period policy corresponding to the data backup task is obtained by reading from the backup template, so as to determine a default storage period for the data to be backed up from the data storage period policy;

[0025] Acquire the actual storage time of the backed-up data corresponding to the data to be backed up, and if the actual storage time is longer than the default storage period, delete the backed-up data, or transfer the backed-up data from the first storage space to the second storage space;

[0026] The storage cost of the second storage space is less than that of the first storage space.

[0027] In one embodiment, the method further comprises:

[0028] Constructing a status list for performing operation and maintenance orchestration on the data backup task;

[0029] When each backup node processing the data backup task completes the corresponding node task, automatically reporting the task completion status information corresponding to the data backup task;

[0030] In response to the task completion status information reported by each backup node, a backup status detection instruction is generated for each backup node to confirm the actual backup status and update the status list.

[0031] In a second aspect, the present application also provides a cross-data center data backup device based on operation and maintenance orchestration. The device comprises:

[0032] A candidate backup transfer machine determination module is used to determine at least two candidate backup transfer machines from each optional data center in response to a trigger instruction of a data backup task; the backup transfer machine is a server in the optional data center that can be used for data transfer;

[0033] A priority calculation module, used to obtain the load situation description information corresponding to each of the candidate backup transfer machines, and calculate the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load situation description information;

[0034] A target backup transfer machine determination module, configured to select pre-selected backup transfer machines from the candidate backup transfer machines according to the priority score, and randomly determine a transfer machine from the pre-selected backup transfer machines as a target backup transfer machine;

[0035] The backup module is used to send the copy data of the data to be backed up from the first data center to the target backup transfer machine, so as to send the copy data of the data to be backed up to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

[0036] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0037] In response to a trigger instruction of a data backup task, at least two candidate backup transfer machines are determined from each optional data center; the backup transfer machine is a server in the optional data center that can be used for data transfer;

[0038] Obtaining load condition description information corresponding to each of the candidate backup transfer machines, and calculating the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load condition description information;

[0039] According to the priority score, pre-selected backup transfer machines are selected from the candidate backup transfer machines, and a transfer machine is randomly determined from the pre-selected backup transfer machines as a target backup transfer machine;

[0040] The copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

[0041] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0042] In response to a trigger instruction of a data backup task, at least two candidate backup transfer machines are determined from each optional data center; the backup transfer machine is a server in the optional data center that can be used for data transfer;

[0043] Obtaining load condition description information corresponding to each of the candidate backup transfer machines, and calculating the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load condition description information;

[0044] According to the priority score, pre-selected backup transfer machines are selected from the candidate backup transfer machines, and a transfer machine is randomly determined from the pre-selected backup transfer machines as a target backup transfer machine;

[0045] The copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

[0046] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0047] In response to a trigger instruction of a data backup task, at least two candidate backup transfer machines are determined from each optional data center; the backup transfer machine is a server in the optional data center that can be used for data transfer;

[0048] Obtaining load condition description information corresponding to each of the candidate backup transfer machines, and calculating the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load condition description information;

[0049] According to the priority score, pre-selected backup transfer machines are selected from the candidate backup transfer machines, and a transfer machine is randomly determined from the pre-selected backup transfer machines as a target backup transfer machine;

[0050] The copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

[0051] The above-mentioned cross-data center data backup method, device, computer equipment, storage medium and computer program product based on operation and maintenance orchestration first respond to the trigger instruction of the data backup task, determine at least two candidate backup transfer machines from each optional data center, and then obtain the load situation description information corresponding to each candidate backup transfer machine, and calculate the priority score corresponding to each candidate backup transfer machine according to the value of each indicator in the load situation description information, and then select each pre-selected backup transfer machine from each candidate backup transfer machine according to the priority score, and randomly select each pre-selected backup transfer machine from each pre-selected backup transfer machine. A transfer machine is determined as the target backup transfer machine, and finally the copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; by determining the available backup transfer machines from the optional data centers, and screening them by priority scores, and randomly determining them after screening, the target backup transfer machine is obtained, which realizes the operation and maintenance orchestration layer and unified scheduling for the backup transfer machine, and supports deployment scenarios from a single data center to cross-data centers and even cross-regional deployments, thereby improving the backup efficiency in cross-data center scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] FIG1 is an application environment diagram of a cross-data center data backup method based on operation and maintenance orchestration in one embodiment;

[0054] Figure 2 The figure is a flow chart of a cross-data center data backup method based on operation and maintenance orchestration in one embodiment;

[0055] Figure 3 It is a flowchart of a cross-data center data backup method based on operation and maintenance orchestration in another embodiment;

[0056] Figure 4 is an architectural diagram of a data center in one embodiment;

[0057] Figure 5 is a cross-data center architecture diagram in one embodiment;

[0058] Figure 6 It is an overall architecture diagram in one embodiment;

[0059] Figure 7It is a structural block diagram of a cross-data center data backup device based on operation and maintenance orchestration in one embodiment;

[0060] FIG8 is a diagram showing the internal structure of a computer device in one embodiment;

[0061] FIG. 9 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0064] The cross-data center data backup method based on operation and maintenance orchestration provided in the embodiment of the present application can be applied in the application environment shown in Figure 1. The terminal 102 communicates with the server 104 through a network.

[0065] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0066] In one embodiment, Figure 2 As shown, a data backup method across data centers based on operation and maintenance orchestration is provided, and the method is applied to the terminal 102 in FIG. 1 as an example for description, including the following steps:

[0067] S201, in response to a trigger instruction of a data backup task, determining at least two candidate backup hubs from each optional data center.

[0068] The data backup task is a task required for data backup, and the backup transfer machine is a server in an optional data center that can be used for data transfer.

[0069] Specifically, the optional data center is a data center that can select a backup transit machine. The backup transit machine is generally deployed near the data center. It can be the same data center as the data source or the same data center as the storage-side object storage, depending on the specific architecture design and business needs.

[0070] Generally, currently available servers in optional data centers can serve as candidate backup hubs.

[0071] S202, obtaining load situation description information corresponding to each candidate backup transfer machine, and calculating the priority score corresponding to each candidate backup transfer machine according to the value of each indicator in the load situation description information.

[0072] The indicators in the load description information include CPU load, disk capacity utilization, memory utilization, and network channel bandwidth utilization.

[0073] For example, the priority score is recorded as F(x), F(x) = f1 CPU load + f2 Disk capacity usage + f3 Memory usage + f4 Network channel bandwidth utilization. f1, f2, f3, f4 and n are adjusted by the user based on actual operation and maintenance conditions.

[0074] S203, screening out pre-selected backup transfer machines from the candidate backup transfer machines according to the priority scores, and randomly determining a transfer machine from the pre-selected backup transfer machines as a target backup transfer machine.

[0075] The pre-selected backup transfer machine is a selected transfer machine, and the target backup transfer machine is a randomly determined transfer machine.

[0076] Exemplarily, after calculation, the operation and maintenance orchestration obtains the top N servers according to F(x), and then uses a random algorithm to obtain any one of them, that is, the scheduled backup transfer machine.

[0077] S204: Send the copy data of the data to be backed up from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine.

[0078] The data to be backed up refers to the data to be backed up, and the replicated data refers to the data obtained by replicating the data to be backed up. Cross-data center means that the first data center and the second data center are different data centers.

[0079] For example, the operation and maintenance orchestration sends the corresponding executable file to the server where the slave node of the database is located according to the database type, and runs the executable file. The executable file first copies the backup file and sends it to the backup transfer machine through the backup. The backup transfer machine compresses the received backup file and then encrypts it using the national encryption algorithm. The backup transfer machine uploads the encrypted and compressed backup file to the object storage, where the selection of the object storage is calculated and sent by the operation and maintenance orchestration.

[0080] In the above-mentioned cross-data center data backup method based on operation and maintenance orchestration, first, in response to the trigger instruction of the data backup task, at least two candidate backup transfer machines are determined from each optional data center, and then the load situation description information corresponding to each candidate backup transfer machine is obtained, and the priority score corresponding to each candidate backup transfer machine is calculated according to the value of each indicator in the load situation description information, and then the pre-selected backup transfer machines are screened out from each candidate backup transfer machine according to the priority score, and a transfer machine is randomly determined from each pre-selected backup transfer machine as the target backup transfer machine, and finally the copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; by determining the available backup transfer machines from the optional data centers, and screening them by priority scores, and randomly determining them after screening, the target backup transfer machine is obtained, and the operation and maintenance orchestration layer and unified scheduling for the backup transfer machine are realized, and support single data center to cross-data center and even cross-region deployment scenarios, thereby improving the backup efficiency in the cross-data center scenario.

[0081] In one embodiment, pre-selected backup transit machines are screened out from candidate backup transit machines based on priority scores, including: for any transit machine among the candidate backup transit machines, when the restricted index of any transit machine does not exceed the upper limit, any transit machine that does not exceed the upper limit is sorted according to the size of the priority score; based on the sorting result, a preset number of pre-selected backup transit machines with a high ranking are screened out from any transit machine.

[0082] The restricted indicators include the number of server instances and disk capacity utilization; the indicators in the load description information include CPU load, disk capacity utilization, memory utilization and network channel bandwidth utilization. Any transfer machine is any transfer machine among the candidate backup transfer machines.

[0083] For example, a batch of IP lists are obtained from the backup transfer machine according to monitoring, and the acquisition algorithm is as follows: F(x) = f1 CPU load + f2 Disk capacity usage + f3 Memory usage + f4 Network channel bandwidth utilization, algorithm boundary conditions: the number of instances on the server cannot exceed n; disk usage cannot exceed 80%. Among them, f1, f2, f3, f4 and n are adjusted by the user according to the actual operation and maintenance situation. After calculation, the operation and maintenance orchestration obtains the top N servers according to F (x), and then uses a random algorithm to obtain any one of them, that is, the scheduled backup transfer machine.

[0084] In this embodiment, first, for any transfer machine among the candidate backup transfer machines, if the restricted index of any transfer machine does not exceed the upper limit, any transfer machine that does not exceed the upper limit is sorted according to the size of the priority score, and then according to the result of the sorting, a preset number of pre-selected backup transfer machines with the top ranking are screened out from each transfer machine, the priority is calculated through various indicators, and the backup transfer machines are screened based on the priority, thereby ensuring the accuracy of the backup transfer machine screening, and further ensuring the efficiency of using the backup transfer machine for data backup.

[0085] In one embodiment, the priority score corresponding to each candidate backup transfer machine is calculated based on the numerical value of each indicator in the load situation description information, including: evaluating the actual operating status of each candidate backup transfer machine to obtain a resource occupancy score; calculating the priority score corresponding to each candidate backup transfer machine based on the resource occupancy score and the numerical value of each indicator in the load situation description information.

[0086] The resource occupation score is used to characterize the situation that each backup transfer machine is occupied by the data backup task. Specifically, based on the previous embodiment, two environments, pre-occupancy and resource release, are introduced. The acquisition algorithm is as follows: F(x) = f1 CPU load + f2 Disk capacity usage + f3 Memory usage + f4 Network channel bandwidth + f5. f5 represents pre-occupied resources, which are globally recorded using operation and maintenance orchestration.

[0087] In this embodiment, the actual operating status of each candidate backup transfer machine is first evaluated to obtain a resource occupancy score, and then the priority score corresponding to each candidate backup transfer machine is calculated based on the resource occupancy score and the values ​​of each indicator in the load condition description information; the priority is calculated by using each indicator and the resource occupancy score, and the backup transfer machines are screened using the priority, thereby ensuring the accuracy of the backup transfer machine screening and further ensuring the efficiency of data backup using the backup transfer machine.

[0088] In one embodiment, the method also includes: obtaining the execution status of the current data backup task; when the execution status is that the backup task has not been completed and a task increase request for the data backup task is detected, increasing the resource occupancy score; when the execution status is that the backup task has been completed, lowering the resource occupancy score.

[0089] For example, when the backup is not finished and a new backup task is added, the pre-occupied resource f5 will continue to increase. When the backup is finished, the operation and maintenance orchestration will release the resource. After calculation, the operation and maintenance orchestration obtains the top N servers according to F(x), and then uses a random algorithm to obtain any one of them, that is, the scheduled backup transfer machine.

[0090] In this embodiment, the execution status of the current data backup task is first obtained, and then when the execution status is that the backup task has not been completed and a task increase request for the data backup task is detected, the resource occupancy score is increased, and then when the execution status is that the backup task is completed, the resource occupancy score is lowered; through real-time monitoring of the task execution status, the resource occupancy score is dynamically adjusted, and the factor of resource occupation during task execution is successfully introduced into the priority calculation process, thereby ensuring the accuracy of backup transfer machine screening, and further ensuring the efficiency of data backup using the backup transfer machine.

[0091] In one embodiment, the method also includes: obtaining a backup template corresponding to the data backup task; reading a data retention period policy corresponding to the data backup task from the backup template to determine a default retention period for the data to be backed up from the data retention period policy; obtaining an actual retention period of the backed-up data corresponding to the data to be backed up, and if the actual retention period is greater than the default retention period, deleting the backed-up data, or transferring the backed-up data from the first storage space to the second storage space.

[0092] The storage cost of the second storage space is less than that of the first storage space. The storage space may refer to storage space on different types of storage media. Generally, different storage media have different storage unit prices.

[0093] For example, a full database backup is used for rapid recovery after a database crash. Therefore, the data is kept fresh for 7 days by default (adjustable based on business needs). Data that has been kept fresh for more than 7 days is considered cold data and is downgraded by the operation and maintenance orchestration. Cold data can be deleted based on business needs to reduce the file storage load, or the cold data can be transferred to a cheaper storage medium.

[0094] In this embodiment, first, a backup template corresponding to the data backup task is obtained, and then the data retention period policy corresponding to the data backup task is read from the backup template to determine the default retention period for the data to be backed up from the data retention period policy, and finally the actual retention period of the backed-up data corresponding to the data to be backed up is obtained. When the actual retention period is longer than the default retention period, the backed-up data is deleted or transferred. Through the data retention period policy, the separation of cold and hot data is achieved, and the maintenance cost and storage cost are reduced.

[0095] In one embodiment, the method also includes: constructing a status list for performing operation and maintenance orchestration on data backup tasks; automatically reporting task completion status information corresponding to the data backup task when each backup node processing the data backup task has completed the corresponding node task; and generating a detection backup status instruction for each backup node in response to the task completion status information reported by each backup node to confirm the actual backup status and update the status list.

[0096] The state list is a state table that needs to be established and maintained during the operation and maintenance orchestration process; the backup node can be any processing node that processes the data backup task.

[0097] For example, when using asynchronous non-blocking backup, the operation and maintenance orchestration maintains a state table. After issuing the policy, there is no need to pay attention to the changes in the backup process status in real time, but it is automatically reported through the underlying backup node. When the backup node has not reported for a certain period of time, the operation and maintenance orchestration will issue a command to detect the backup status. If it fails, the previous step will be rescheduled.

[0098] In this embodiment, a status list for operation and maintenance orchestration of data backup tasks is first constructed, and then, when each backup node processing the data backup task completes the corresponding node task, the task completion status information corresponding to the data backup task is automatically reported, and finally, in response to the task completion status information reported by each backup node, a detection backup status instruction for each backup node is generated to confirm the actual backup status and update the status list; by setting and updating the status list, operation and maintenance orchestration is realized, and the completion status of the task in the status list is used to select the time to detect each backup node, thereby reducing the waste of resources in maintaining heartbeat connections or scheduled scanning processes, improving the resource utilization efficiency of the scheduling process, and thereby ensuring the efficiency of data backup using backup transfer machines.

[0099] In another embodiment, Figure 3 As shown, a cross-data center data backup method based on operation and maintenance orchestration is provided, including the following steps:

[0100] S301, in response to a trigger instruction of a data backup task, determining at least two candidate backup hubs from each optional data center.

[0101] S302: Obtain load description information corresponding to each candidate backup transfer machine.

[0102] S303: Evaluate the actual operating status of each candidate backup transfer machine to obtain a resource occupancy score.

[0103] S304: Calculate the priority score corresponding to each candidate backup transfer machine according to the resource occupancy score and the value of each indicator in the load situation description information.

[0104] S305 , when the restricted index of any transfer machine does not exceed the upper limit, sort any transfer machine that does not exceed the upper limit according to the priority score.

[0105] S306, according to the sorting result, select a preset number of pre-selected backup transfer machines with top rankings from any transfer machines.

[0106] S307: randomly determine a transfer machine from each pre-selected backup transfer machine as a target backup transfer machine.

[0107] S308: Send the copy data of the data to be backed up from the first data center to the target backup hub, so as to send the copy data of the data to be backed up to the second data center.

[0108] It should be noted that the specific limitations of the above steps can be found in the above specific limitations of a cross-data center data backup method based on operation and maintenance orchestration, which will not be repeated here.

[0109] In the prior art, the backup of the open source database MySQL, which is commonly used by IT companies, is used as an example to explain. In the early days, a master-slave architecture MySQL database was often built, and the slave node played a backup role. Moreover, the master and slave nodes were deployed in the same data center. Figure 4 When the master node fails, ORC (Orchestrator, a management tool for MySQL master-slave node switching) and other technologies are used to implement master-slave switching, thereby ensuring that the master node can provide normal external services.

[0110] As the scale of business systems continues to expand and data security and management requirements become increasingly stringent, the traditional single data center master-slave architecture can no longer meet the needs. At this time, the master-slave node is generally deployed in different data centers (i.e., across data centers), and the slave node acts as a backup node, such as Figure 5As shown in the figure. Among them, cross-data center means 2 or more data centers. The main advantages of this architecture include: 1) Improved data security. By backing up data to another data center, the risk of data loss due to natural disasters, human errors or hardware failures can be greatly reduced. 2) Enhanced fault tolerance. Even if one data center fails, the slave node in another data center can still take over the service to ensure business continuity. However, the master-slave architecture across data centers also brings some challenges, such as complicated data backup and network latency.

[0111] In the practice of MySQL backup, operation and maintenance personnel often need to perform secondary development or customization based on existing backup tools (such as logical backup tools mysqldump, mydumper, and physical backup tools such as xtrabackup) according to the needs of the actual production environment to ensure the efficiency, reliability and flexibility of the backup strategy.

[0112] Therefore, there are many problems in the prior art, including:

[0113] (1) High coupling: Each technology is developed for a specific database, and it is difficult to be compatible with other databases. In the production environment of a data center of a certain power utility company, there are multiple databases, such as Oracle and MySQL. If a backup system is built for each database, information chimneys will be generated, and operation and maintenance costs will also be increased.

[0114] (2) Low security: Existing backup technologies often back up and store directly on the database server. When the server goes down, the backup files may be lost. In addition, the disk capacity is limited, horizontal expansion is difficult, and long-term backup tasks cannot be stored.

[0115] (3) Narrow application scenarios: Existing technology scenarios are often targeted at single data center scenarios. If there are cross-data center or even cross-region scenarios (data centers are deployed in different regions of the world), they cannot cope with them. Because there are problems such as transmission speed and transmission security, there is no universal solution.

[0116] (4) Low fault tolerance: If the backup process fails midway, the backup must be restarted. Some technical solutions introduce management and control software, which will bring another problem. When there are too many backup processes, it will cause congestion and affect transmission performance.

[0117] (5) Poor compatibility: The development teams of general databases and big data are different, and the backup processes are not compatible with each other, resulting in a waste of resources.

[0118] (6) High cost: Cold and hot data are stored together and cannot be separated, resulting in high maintenance and storage costs.

[0119] Among them, the most critical issue is how to solve the problem of cross-data center scenarios, improve data backup security, fault tolerance, and compatibility of the entire backup process, and reduce coupling and operation and maintenance costs.

[0120] Based on this, the embodiment of the present application provides a data backup method across data centers based on operation and maintenance orchestration, as shown below. Figure 6 , a cross-data center data backup method based on operation and maintenance orchestration is described in detail with a specific embodiment. It is worth noting that the following description is only an exemplary description and not a specific limitation on the application.

[0121] The cross-data center data backup method based on operation and maintenance orchestration provided in this application is also called a cross-data center data backup method based on operation and maintenance orchestration, which is mainly used to solve the full backup problem of databases (TP libraries (Transaction Processing Database, transaction processing databases, caches, etc.) and metadata of big data components in cross-data center scenarios.

[0122] The cross-data center data backup method based on operation and maintenance orchestration provided in this application is applicable to database (including various TP libraries, such as Oracle, MySQL, etc.), cache (such as Redis, etc.) and big data component metadata (Zookeeper / Hive metadata, etc.) backup scenarios in cross-data center and even cross-region scenarios.

[0123] On the access side, a shielding layer is introduced to be compatible with different data sources (databases, caches, metadata of big data components) in a dynamic hot-swappable manner, thereby improving applicability, decoupling data sources, and reducing operation and maintenance costs; dynamic hot-swappable means that the system can dynamically add, remove, or replace different types of data sources (such as databases, caches, metadata of big data components) without stopping the system, without affecting the overall system operation. Specifically, the introduction of a shielding layer on the access side allows the metadata backup requirements of different data sources to be handled through dynamic hot-swappable methods. On the transmission side, self-developed algorithms are used to solve problems such as transmission efficiency and transmission equipment overload; on the storage side, multiple object storage media such as Ceph (Ceph Distributed File System) and Alibaba Cloud OSS (Alibaba Cloud Object Storage Service) are supported, and the separation of hot and cold data is supported. On the scheduling side, the entire backup process is uniformly scheduled by the upper-level operation and maintenance orchestration, supporting multiple functions such as failure retry, asynchronous non-blocking backup, and script scheduling. The overall architecture of a cross-data center data backup method and device based on operation and maintenance orchestration is as follows: Figure 6Among them, operation and maintenance orchestration is a software system based on a process engine (such as flowable, etc.) to support service scheduling.

[0124] The cross-data center data backup method based on operation and maintenance orchestration provided in this application involves a complete link of a backup process. Here, MySQL backup is taken as an example, and other data sources are similar. The complete link of a backup process specifically includes:

[0125] (1) The operation and maintenance orchestration has integrated the backup template. Each time a new database cluster is connected, the metadata information of the scheduling object needs to be configured in advance on the operation and maintenance orchestration through the visual interface, including the frequency of backup execution (this application specifically refers to full backup, which is generally based on the day), the execution object (the basic information of MySQL to be backed up, such as the cluster name, database type, etc.), the data retention cycle strategy (for the separation of hot and cold data), etc. (2) The operation and maintenance orchestration schedules a suitable backup transfer machine through calculation and sends the nc command (Netcat, network pipe) to enable the backup transfer machine to randomly start a listening port. (3) The operation and maintenance orchestration sends the corresponding executable file (Shell script, Python script, Jar package, etc.) to the server where the slave database node is located according to the database type and runs the executable file. The executable file first copies the backup file (including metadata files, etc.) (copy command) and sends it to the backup transfer machine through the backup. (4) The backup transfer machine compresses the received backup file and then encrypts it using the national encryption algorithm. (5) The backup hub uploads the encrypted and compressed backup files to the object storage, where the choice of object storage is calculated and issued by the operation and maintenance orchestration.

[0126] Among them, the backup transfer machine corresponds to Figure 6 The backup transfer layer is a server with relatively large disk capacity, which is used to compress backup files.

[0127] In the cross-data center data backup method based on operation and maintenance orchestration provided in this application, the backup transfer machine deployment and scheduling strategy specifically includes:

[0128] (1) Backup transfer machine deployment strategy

[0129] The backup transfer machine itself does not deploy any services or database instances. In cross-data center scenarios, a number of devices with relatively large disk capacity are generally reserved in each data center or in nearby data centers for backup transfer.

[0130] The backup transfer machine is generally deployed near the data center, which can be the same data center as the data source or the same data center as the storage-side object storage, depending on the specific architecture design and business needs.

[0131] In cross-data center scenarios, backup hubs are usually located in data centers close to the data source, so that backup data can be received faster and data transmission latency can be reduced. On the other hand, backup data can be compressed and encrypted before being uploaded to remote object storage, which ensures data security and reliability. Therefore, backup hubs must consider both proximity to the data center of the data source for fast data backup and proximity to the object storage data center for efficient upload of backup data.

[0132] (2) Scheduling strategy for backup transfer machines

[0133] (a) Obtaining the backup transfer machine IP list

[0134] Based on the configured backup database information, the operation and maintenance orchestration queries the CMDB (configuration management database) to obtain the IP list of available backup transfer machines in the corresponding area of ​​the database slave node.

[0135] (b) Traditional backup transfer machine scheduling algorithm

[0136] The current practice is mostly to obtain the server with the lowest vacancy rate based on the IP list of the monitoring backup transfer machine. However, this method has a big problem. In practice, there are often many backup tasks being scheduled at the same time, which will cause everyone to be scheduled to the same server, resulting in server overload and shutdown or program abnormality.

[0137] (c) Improved backup transfer machine scheduling algorithm provided by this application

[0138] First, a list of IP addresses is obtained from the backup transfer machine based on monitoring. The acquisition algorithm is as follows:

[0139] F(x) = f1 CPU load + f2 Disk capacity usage + f3 Memory usage + f4 Network channel bandwidth utilization, the boundary conditions of the algorithm: the number of instances on the server cannot exceed n; the disk usage cannot exceed 80%. Among them, f1, f2, f3, f4 and n are adjusted by the user according to the actual operation and maintenance situation.

[0140] After calculation, the operation and maintenance orchestration obtains the top N servers according to F(x), and then uses a random algorithm to obtain any one of them, which is the scheduled backup transfer machine.

[0141] (d) Further improved backup transfer machine scheduling algorithm provided by this application

[0142] The core is to introduce two environments, pre-occupancy and resource release, based on (c). The acquisition algorithm is as follows:

[0143] F(x) = f1 CPU load + f2 Disk capacity usage + f3 Memory usage + f4 Network channel bandwidth + f5. f5 represents pre-occupied resources, which are globally recorded using operation and maintenance orchestration.

[0144] When the backup is not finished and a new backup task is added, the pre-occupied resource f5 will continue to increase. When the backup is finished, the operation and maintenance orchestration will release the resource.

[0145] After calculation, the operation and maintenance orchestration obtains the top N servers according to F(x), and then uses a random algorithm to obtain any one of them, which is the scheduled backup transfer machine.

[0146] In the cross-data center data backup method based on operation and maintenance orchestration provided in this application, the data retention cycle strategy specifically includes:

[0147] Full database backup is used for rapid recovery after a database crash. Therefore, data is stored for a certain period of time, which is usually 7 days by default (adjustable based on business needs). Data stored for more than 7 days is considered cold data and is downgraded by the operation and maintenance orchestration. Based on business needs, you can choose to (1) delete the cold data to reduce the file storage load or (2) transfer the cold data to a cheaper storage medium.

[0148] In the cross-data center data backup method based on operation and maintenance orchestration provided in this application, non-blocking backup specifically includes:

[0149] Figure 6 Each step in the process takes a long time to execute, possibly several hours. If the operation and maintenance orchestration maintains a heartbeat connection with the backup node in real time or periodically scans the backup process nodes below to determine the next step, this will consume resources. This method is not a big problem when the scale is relatively small, but when the concurrency is large and the backup task is heavy, it is easy to drag down the operation and maintenance orchestration service.

[0150] The improved method provided by this application uses asynchronous non-blocking backup. The operation and maintenance orchestration maintains a state table. After issuing the strategy, there is no need to pay attention to the changes in the backup process status in real time, but it is automatically reported through the underlying backup node. When the backup node has not reported for a certain period of time, the operation and maintenance orchestration will issue a command to detect the backup status. If it fails, the previous step will be rescheduled.

[0151] The advantages of the cross-data center data backup method based on operation and maintenance orchestration provided by this application are:

[0152] (1) Low coupling: This application supports multiple data sources to access databases (including various TP libraries, such as Oracle, MySQL, etc.), caches (such as Redis, etc.) and metadata of big data components (Zookeeper / Hive metadata, etc.). There is no need to maintain a backup system specifically for each database, thus reducing operation and maintenance costs.

[0153] (2) High security: The backup files are stored in a dedicated distributed file system, which can be expanded horizontally indefinitely in theory and supports multi-copy backup. There is no need to worry about the backup files being unable to be restored after a crash.

[0154] (3) Wide range of adaptability scenarios: Supports deployment scenarios ranging from single data center to cross-data center and even cross-region deployment.

[0155] (4) High fault tolerance: The operation and maintenance orchestration layer uniformly schedules and manages the backup tasks of the lower layers, and can perform retries on failures to improve the backup success rate.

[0156] (5) Good compatibility: It unifies database, cache and big data metadata backup, reduces duplication and improves resource utilization. It also uses non-blocking backup, with high overall backup performance. Big data metadata backup is different from big data component backup. On the one hand, the metadata capacity is relatively small. On the other hand, if the metadata is lost, the cluster cannot be started.

[0157] (6) Low cost: Through the data retention cycle strategy, the hot and cold data can be separated, reducing maintenance and storage costs.

[0158] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0159] Based on the same inventive concept, the embodiment of the present application also provides a cross-data center data backup device based on operation and maintenance orchestration for implementing the cross-data center data backup method based on operation and maintenance orchestration involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more cross-data center data backup device embodiments based on operation and maintenance orchestration provided below can refer to the limitations of the cross-data center data backup method based on operation and maintenance orchestration above, and will not be repeated here.

[0160] In one embodiment, Figure 7 As shown, a cross-data center data backup device based on operation and maintenance orchestration is provided, including: a candidate backup transfer machine determination module 701, a priority calculation module 702, a target backup transfer machine determination module 703, and a backup module 704, wherein:

[0161] The candidate backup transfer machine determination module 701 is used to determine at least two candidate backup transfer machines from each optional data center in response to the trigger instruction of the data backup task; the backup transfer machine is a server in the optional data center that can be used for data transfer;

[0162] The priority calculation module 702 is used to obtain the load situation description information corresponding to each candidate backup transfer machine, and calculate the priority score corresponding to each candidate backup transfer machine according to the value of each indicator in the load situation description information;

[0163] The target backup transfer machine determination module 703 is used to select each pre-selected backup transfer machine from each candidate backup transfer machine according to the priority score, and randomly determine a transfer machine from each pre-selected backup transfer machine as the target backup transfer machine;

[0164] The backup module 704 is used to send the copy data of the data to be backed up from the first data center to the target backup transfer machine, so as to send the copy data of the data to be backed up to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

[0165] In one embodiment, the device is used to: for any transfer machine among the candidate backup transfer machines, when the restricted indicator of any transfer machine does not exceed the upper limit, sort any transfer machine that does not exceed the upper limit according to the size of the priority score; based on the result of the sorting, filter out a preset number of pre-selected backup transfer machines with the highest ranking from each transfer machine.

[0166] In one embodiment, the device is used to: evaluate the actual operating status of each candidate backup transfer machine to obtain a resource occupancy score; the resource occupancy score is used to characterize the situation in which each backup transfer machine's computing resources are occupied by data backup tasks; based on the resource occupancy score and the values ​​of each indicator in the load situation description information, calculate the priority score corresponding to each candidate backup transfer machine.

[0167] In one embodiment, the device is used to: obtain the execution status of the current data backup task; when the execution status is that the backup task has not been completed and a task increase request for the data backup task is detected, increase the resource occupancy score; when the execution status is that the backup task is completed, lower the resource occupancy score.

[0168] In one embodiment, the device is used to: obtain a backup template corresponding to a data backup task; read a data retention period policy corresponding to the data backup task from the backup template to determine a default retention period for the data to be backed up from the data retention period policy; obtain an actual retention period of the backed-up data corresponding to the data to be backed up, and if the actual retention period is greater than the default retention period, delete the backed-up data, or transfer the backed-up data from the first storage space to the second storage space.

[0169] In one embodiment, the method also includes: constructing a status list for performing operation and maintenance orchestration on data backup tasks; automatically reporting task completion status information corresponding to the data backup task when each backup node processing the data backup task has completed the corresponding node task; and generating a detection backup status instruction for each backup node in response to the task completion status information reported by each backup node to confirm the actual backup status and update the status list.

[0170] Each module in the above cross-data center data backup device based on operation and maintenance orchestration can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module above.

[0171] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG8. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data backup method across data centers based on operation and maintenance orchestration is implemented.

[0172] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG9. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a data backup method across data centers based on operation and maintenance orchestration is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0173] Those skilled in the art will understand that the structures shown in FIGS. 8 and 9 are merely block diagrams of partial structures related to the scheme of the present application, and do not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device may include more or fewer components than those shown in the figures, or combine certain components, or have a different arrangement of components.

[0174] In one embodiment, a computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps in the above method embodiments are implemented.

[0175] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0176] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0177] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0178] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0179] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A cross-data center data backup method based on operation and maintenance orchestration, characterized in that: The method comprises: In response to a trigger instruction of a data backup task, at least two candidate backup transfer machines are determined from each optional data center; the backup transfer machine is a server in the optional data center that can be used for data transfer; Obtaining load condition description information corresponding to each of the candidate backup transfer machines, and calculating the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load condition description information; According to the priority score, pre-selected backup transfer machines are selected from the candidate backup transfer machines, and a transfer machine is randomly determined from the pre-selected backup transfer machines as a target backup transfer machine; The copy data of the data to be backed up is sent from the first data center to the target backup transfer machine, so that the copy data of the data to be backed up is sent to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

2. The method according to claim 1, characterized in that The step of selecting pre-selected backup transfer machines from the candidate backup transfer machines according to the priority scores includes: For any transfer machine among the candidate backup transfer machines, if the restricted index of any transfer machine does not exceed the upper limit, sort any transfer machine that does not exceed the upper limit according to the size of the priority score; According to the result of the sorting, a preset number of the pre-selected backup transfer machines with the highest sorting are selected from each of the transfer machines; Among them, the restricted indicators include the number of server instances and disk capacity utilization; the indicators in the load situation description information include CPU load, the disk capacity utilization, memory utilization and network channel bandwidth utilization.

3. The method according to claim 2, characterized in that The step of calculating the priority score corresponding to each candidate backup transfer machine according to the value of each indicator in the load condition description information includes: The actual operation status of each candidate backup transfer machine is evaluated to obtain a resource occupation score; the resource occupation score is used to characterize the situation that the computing resources of each backup transfer machine are occupied by the data backup task; The priority score corresponding to each candidate backup transfer machine is calculated based on the resource occupancy score and the value of each indicator in the load situation description information.

4. The method according to claim 3, characterized in that The method further comprises: Obtaining the current execution status of the data backup task; When the execution status is that the backup task is not completed and a task addition request for the data backup task is detected, the resource occupation score is increased; When the execution status is that the backup task is completed, the resource occupation score is lowered.

5. The method according to claim 1, characterized in that: The method further comprises: Obtaining a backup template corresponding to the data backup task; The data storage period policy corresponding to the data backup task is obtained by reading from the backup template, so as to determine a default storage period for the data to be backed up from the data storage period policy; Obtaining an actual storage time of the backed-up data corresponding to the data to be backed up, and if the actual storage time is greater than the default storage period, deleting the backed-up data, or transferring the backed-up data from the first storage space to the second storage space; The storage cost of the second storage space is less than that of the first storage space.

6. The method according to claim 1, characterized in that The method further comprises: Constructing a status list for performing operation and maintenance orchestration on the data backup task; When each backup node processing the data backup task completes the corresponding node task, automatically reporting the task completion status information corresponding to the data backup task; In response to the task completion status information reported by each backup node, a backup status detection instruction is generated for each backup node to confirm the actual backup status and update the status list.

7. A data backup device across data centers based on operation and maintenance orchestration, characterized in that: The device comprises: A candidate backup transfer machine determination module is used to determine at least two candidate backup transfer machines from each optional data center in response to a trigger instruction of a data backup task; the backup transfer machine is a server in the optional data center that can be used for data transfer; A priority calculation module, used to obtain the load situation description information corresponding to each of the candidate backup transfer machines, and calculate the priority score corresponding to each of the candidate backup transfer machines according to the values ​​of each indicator in the load situation description information; A target backup transfer machine determination module, configured to select pre-selected backup transfer machines from the candidate backup transfer machines according to the priority score, and randomly determine a transfer machine from the pre-selected backup transfer machines as a target backup transfer machine; The backup module is used to send the copy data of the data to be backed up from the first data center to the target backup transfer machine, so as to send the copy data of the data to be backed up to the second data center through the target backup transfer machine; the first data center and the second data center are different data centers.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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