A cloud data center server data backup method and related equipment

Abstract

The present application provides a cloud data center server data backup method and related equipment. The method determines a backup reference block and a sliding backup window for the data to be backed up, divides the sliding backup window into multiple sliding backup intervals, uses the same sliding backup interval as the backup reference block as the backup transition window, determines an adaptive backup ratio based on the sliding backup window and the backup transition window, updates the backup reference block, and thereby obtains multiple backup reference blocks, multiple backup transition windows, and multiple adaptive backup ratios. A backup reference library for the data to be backed up is established based on all the backup reference blocks, all the backup transition windows, and all the adaptive backup ratios. When a target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library. Using the solution of the present application, adaptive backup of user-generated cloud data can be performed, reducing the data backup burden on the cloud data center server.

Description

Technical Field

[0001] The present application relates to the field of data backup technology, and in particular to a cloud data center server data backup method and related equipment. Background Art

[0002] Data backup refers to copying data from one location to another location or media to prevent data loss, damage, or accidental deletion. When performing data backup, the source data is copied and stored in one or more backup targets to provide a backup copy of the source data. The backup target can be a local storage device (such as a hard drive, tape library, etc.) or a cloud storage service.

[0003] Cloud data center server data refers to various data stored on cloud data center servers. A cloud data center is a centralized computing resource pool composed of large servers and network equipment for storing, processing, and managing large amounts of data. The data stored in a cloud data center includes: private files of individual users, applications, databases, media files, log records, sensor data, etc. of corporate users. In the existing technology, cloud data center server data backup is a key data management measure. However, as the data generated by users continues to increase, the storage space required for backup data also increases dramatically. If, as in the past, a unified backup solution is used to back up the data stored by all users of the cloud data center server, and adaptive backup cannot be flexibly performed for each user, the storage burden of the cloud data center server will be increased. Therefore, how to adaptively back up the cloud data generated by users and reduce the data backup burden of the cloud data center server has become a problem faced by the industry. Summary of the Invention

[0004] Based on this, the present application provides a cloud data center server data backup method and related equipment for adaptively backing up user-generated cloud data.

[0005] In a first aspect, the present application provides a cloud data center server data backup method, comprising the following steps:

[0006] Obtain the target user's historical cloud data in the cloud service center, extract hot data from the historical cloud data, and obtain the data to be backed up;

[0007] Determining a backup reference block and a sliding backup window for the data to be backed up;

[0008] Dividing the sliding backup window into a plurality of sliding backup intervals, and determining whether one of the plurality of sliding backup intervals is the same as the backup reference block;

[0009] If none of the multiple sliding backup intervals is identical to the backup reference block, updating the backup reference block until one of the multiple sliding backup intervals is found to be identical to the updated backup reference block;

[0010] If one of the multiple sliding backup intervals is identical to the backup reference block, the sliding backup interval identical to the backup reference block is used as a backup transition window, and an adaptive backup ratio is determined for backing up data corresponding to the backup transition window based on the sliding backup window and the backup transition window; the backup reference block is continuously updated until the initial reference capacity of the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows, and multiple adaptive backup ratios;

[0011] A backup reference library of the data to be backed up is established by all backup reference blocks, all backup transition windows and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0012] In some embodiments, extracting hot data from the historical cloud data to obtain the data to be backed up specifically includes:

[0013] Obtain the target user's access records in the cloud data center;

[0014] Perform data analysis on target users’ access records in cloud data centers;

[0015] Dividing the historical cloud data into cold data and hot data based on the result of data analysis;

[0016] Extract the divided hot data and obtain the data to be backed up;

[0017] The cold data is stored separately and a backup library of the cold data is established.

[0018] In some embodiments, establishing the cold data backup repository specifically includes:

[0019] Setting a life cycle management period of the cold data according to a value threshold of the cold data;

[0020] configuring a storage medium for the cold data according to characteristics of the cold data;

[0021] Archiving the cold data according to a storage cost threshold of the cold data;

[0022] A backup library for the cold data is established according to the life management cycle, the configured storage medium, and the archiving processing method.

[0023] In some embodiments, updating the backup reference block specifically includes:

[0024] If none of the sliding backup intervals is the same as the backup reference block, subtracting one data unit from the initial reference capacity of the backup reference block in order from the back to the front to complete the update;

[0025] Re-searching, if none of the multiple sliding backup intervals is the same as the updated backup reference block, subtracting one data unit from the initial reference capacity of the updated backup reference block in the order from the back to the front, and completing the next update;

[0026] The process continues in this way until a sliding backup interval is found that is the same as the updated backup reference block.

[0027] In some embodiments, the sliding backup window is composed of hot data to be backed up and the storage capacity of the corresponding sliding window.

[0028] In some embodiments, a backup reference library of the data to be backed up is established using all backup reference blocks, all backup transition windows, and all adaptive backup ratios. When a target user generates new cloud data, adaptively backing up the new cloud data based on the backup reference library specifically includes:

[0029] A backup reference block library is established from all backup reference blocks, and the position of each transition sliding backup interval that is the same as the backup reference block is marked;

[0030] A backup reference block library is established from all backup reference blocks, and the position of each backup transition window that is the same as the backup reference block is marked;

[0031] Establishing data guidance relationships between all backup reference blocks and corresponding backup transition windows, and establishing a data guidance library based on all data guidance relationships;

[0032] A backup reference library of the data to be backed up is established based on the data guide library, the backup reference block library and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0033] In some embodiments, establishing data reference relationships between all backup reference blocks and corresponding backup transition windows, and establishing a data reference library based on all data reference relationships specifically includes:

[0034] For each backup reference block, determining positions of all backup transition windows identical to the backup reference block in the sliding backup window;

[0035] Determine the position range of the backup reference block in the sliding backup window according to the positions of all backup transition windows;

[0036] generating a data reference entry according to the identifier of the backup reference block and the position range of the backup reference block in the sliding backup window, wherein the data reference entry is a data reference relationship;

[0037] The generated data guide entry is added to the data guide library, thereby obtaining the data guide library.

[0038] In a second aspect, the present application provides a cloud data center server data backup system, comprising:

[0039] An acquisition module is used to acquire the historical cloud data of the target user in the cloud service center, extract hot data from the historical cloud data, and obtain the data to be backed up;

[0040] A processing module, configured to determine a backup reference block and a sliding backup window for the data to be backed up;

[0041] a processing module, configured to divide the sliding backup window into a plurality of sliding backup intervals, and determine whether one of the plurality of sliding backup intervals is the same as the backup reference block;

[0042] a processing module, configured to update the backup reference block if none of the plurality of sliding backup intervals is identical to the backup reference block, until a sliding backup interval among the plurality of sliding backup intervals is found to be identical to the updated backup reference block;

[0043] a processing module configured to, if one of the plurality of sliding backup intervals is identical to the backup reference block, use the sliding backup interval identical to the backup reference block as a backup transition window, determine an adaptive backup ratio for backing up data corresponding to the backup transition window based on the sliding backup window and the backup transition window, continue updating the backup reference block until the initial reference capacity of the updated backup reference block is equal to zero, thereby obtaining a plurality of backup reference blocks, a plurality of backup transition windows, and a plurality of adaptive backup ratios;

[0044] The execution module is used to establish a backup reference library of the data to be backed up based on all backup reference blocks, all backup transition windows and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0045] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned cloud data center server data backup method when executing the computer program.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-mentioned cloud data center server data backup method.

[0047] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0048] In the cloud data center server data backup method and related equipment provided by the present application, the historical cloud data of the target user in the cloud service center is first obtained, and the hot data in the historical cloud data is extracted to obtain the data to be backed up; the backup reference block and the sliding backup window of the data to be backed up are determined; the sliding backup window is divided into multiple sliding backup intervals, and it is determined whether there is a sliding backup interval in the multiple sliding backup intervals that is the same as the backup reference block; if none of the multiple sliding backup intervals is the same as the backup reference block, the backup reference block is updated until one of the multiple sliding backup intervals is found to be the same as the updated backup reference block; if If there is a backup reference block that is identical to the backup reference block, the sliding backup interval that is identical to the backup reference block is used as the backup transition window, and the adaptive backup ratio when backing up the data corresponding to the backup transition window is determined based on the sliding backup window and the backup transition window; the backup reference block is continuously updated until the initial reference capacity in the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows and multiple adaptive backup ratios; a backup reference library of the data to be backed up is established by all the backup reference blocks, all the backup transition windows and all the adaptive backup ratios, and when the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0049] It can be seen that in the present application, a backup reference library of the data to be backed up is established through all backup reference blocks, all backup transition windows and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library; first, a unique identifier is assigned to each backup reference block, and a backup reference block library is established based on all backup reference blocks and corresponding identifiers. Establishing a backup reference block library can better utilize storage space; secondly, for each backup reference block, the positions of all backup transition windows that are the same as the backup reference block in the sliding backup window are determined; then, the position range of the backup reference block in the sliding backup window is determined based on the positions of all backup transition windows, and a data guide entry is generated based on the identifier of the backup reference block and the position range of its backup reference block in the sliding backup window (the data guide entry is the data guide relationship), and then the generated data guide entry is added to the data guide library to obtain the data guide library. , by referencing at different locations through the guidance relationship, repeated data blocks only need to be stored once, without the need for repeated storage, and data can be quickly located and restored, thereby improving data access efficiency; finally, the data guidance relationship in the data guidance library and the backup reference block in the backup reference block library and the corresponding identifier are used as a reference for backing up new data, and a corresponding code is generated. When the user needs to restore the data, data restoration is performed based on the corresponding code, the data guidance relationship in the data guidance library, the backup reference block in the backup reference block library and the corresponding identifier, and for each backup reference block in the backup reference block library, the adaptive backup ratio of the backup reference block in the restored data is calculated. If the adaptive backup ratio of the backup reference block in the restored data is equal to the initial adaptive backup ratio of the backup reference block, the restored data is sent to the target user. In summary, adaptive backup of cloud data generated by users can be achieved, reducing the data backup burden of cloud data center servers. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flowchart of a cloud data center server data backup method in some embodiments of the present application;

[0051] Figure 2 A schematic diagram of a process for establishing a data guidance library in some embodiments of the present application;

[0052] Figure 3 This is a structural block diagram of a cloud data center server data backup system in some embodiments of the present application;

[0053] Figure 4 This is a diagram of the internal structure of a computer device in some embodiments of the present application. DETAILED DESCRIPTION

[0054] The core of this application is to obtain the historical cloud data of the target user in the cloud service center, extract the hot data in the historical cloud data, obtain the data to be backed up, determine the backup reference block and the sliding backup window of the data to be backed up, divide the sliding backup window into multiple sliding backup intervals, and judge whether there is a sliding backup interval in the multiple sliding backup intervals that is the same as the backup reference block. If none of the multiple sliding backup intervals is the same as the backup reference block, the backup reference block is updated until one of the multiple sliding backup intervals is found to be the same as the updated backup reference block. If one of the multiple sliding backup intervals is the same as the backup reference block, the sliding backup area that is the same as the backup reference block is updated. The time interval is used as a backup transition window, and the adaptive backup ratio when backing up the data corresponding to the backup transition window is determined according to the sliding backup window and the backup transition window; the backup reference block is continuously updated until the initial reference capacity in the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows and multiple adaptive backup ratios, and establishing a backup reference library of the data to be backed up by all the backup reference blocks, all the backup transition windows and all the adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library. In summary, the cloud data generated by the user can be adaptively backed up, thereby reducing the data backup burden of the cloud data center server.

[0055] In order to better understand the above technical solution, the following will be combined with the accompanying drawings and specific implementation methods to describe the above technical solution in detail. Figure 1 , which is an exemplary flow chart of a cloud data center server data backup method according to some embodiments of the present application. The cloud data center server data backup method 100 mainly includes the following steps:

[0056] In step 101, the historical cloud data of the target user in the cloud service center is obtained, and the hot data in the historical cloud data is extracted to obtain the data to be backed up.

[0057] In specific implementation, the historical cloud data of the target user in the cloud service center can be obtained in the following way: after obtaining access rights from the target user, the historical cloud data of the target user in the cloud service center can be obtained from the logs and activity history records provided by the cloud service center.

[0058] In some embodiments, extracting hot data from the historical cloud data to obtain the data to be backed up specifically includes:

[0059] Obtain the target user's access records in the cloud data center;

[0060] Perform data analysis on target users’ access records in cloud data centers;

[0061] Dividing the historical cloud data into cold data and hot data based on the result of data analysis;

[0062] Extract the divided hot data and obtain the data to be backed up;

[0063] The cold data is stored separately and a backup library of the cold data is established.

[0064] It should be noted that the access records in this application include: data access frequency, recent access time, data size and other records; the data analysis refers to the analysis of the importance of existing data based on historical data; in specific implementation, the corresponding importance can be set according to the data access frequency, recent access time, and data size (for example: scoring, the scoring range is 0 to 10, the closer to 10, the more important the data, the closer to 0, the less important the data), and data with an importance greater than or equal to a preset scoring threshold is classified as hot data, and data with an importance less than a preset scoring threshold is classified as cold data, where the scoring threshold can be set according to the specific situation. In other embodiments, other methods can also be used to divide the data stored by users in the cloud data center into cold data and hot data, which is not specifically limited here.

[0065] In addition, during specific implementation, the cold data can be stored separately and a backup library of the cold data can be established based on the nature, storage requirements, budget, and recovery speed of the cold data. For example, the life management cycle of the cold data can be set according to the value threshold of the cold data, and then the storage medium of the cold data can be configured according to the characteristics of the cold data. Then, the cold data can be archived according to the storage cost threshold of the cold data. Finally, a backup library of the cold data can be established based on the life management cycle, the configured storage medium, and the archiving method. In other embodiments, a threshold can be determined based on business needs and the value of the data, and the threshold can be used to determine whether the cold data needs life cycle management. The cold data can be divided into different levels or areas according to the value threshold of the cold data. Then, a retention threshold of the cold data can be set according to the value threshold of the cold data, and an automatic trigger can be set. When the life management cycle of the cold data exceeds the retention threshold, the automatic trigger is triggered to automatically delete the stored cold data. In other embodiments, other methods can also be used to implement this, which will not be repeated here.

[0066] In step 102, a backup reference block and a sliding backup window of the data to be backed up are determined.

[0067] In specific implementation, the sliding backup window is composed of the hot data to be backed up and the storage capacity of the corresponding sliding window. The sliding backup window represents a window for storing the hot data to be backed up, which can be used for sliding backup of the currently processed data to be backed up, and can accommodate a certain number of characters or bytes. The backup reference block is composed of the reference hot data and the initial reference capacity of the corresponding reference window; as a preferred embodiment, determining the backup reference block and the sliding backup window of the data to be backed up can be implemented in the following manner, namely: the data amount of the data to be backed up can be set to the storage capacity of the sliding backup window, and then half of the storage capacity of the sliding backup window can be set as the initial reference capacity of the backup reference block. In other embodiments, other methods can also be used to set the backup reference block and the sliding backup window, which will not be repeated here.

[0068] In step 103, the sliding backup window is divided into a plurality of sliding backup intervals, and it is determined whether one of the plurality of sliding backup intervals is the same as the backup reference block.

[0069] In some embodiments, dividing the sliding backup window into multiple sliding backup intervals may be achieved by the following method:

[0070] The first N data in the sliding backup window are used as the first sliding backup interval;

[0071] The second data to the N+1th data in the sliding backup window are used as the next sliding backup interval;

[0072] The same process is repeated until all data in the sliding backup window are divided into corresponding sliding backup intervals, thereby obtaining multiple sliding backup intervals.

[0073] In specific implementation, N in this application can be set according to the size of the initial reference capacity in the backup reference block; among them, by identifying and utilizing the backup reference block, the redundancy in the hot data can be effectively eliminated and the storage space of the cloud data center server can be reduced.

[0074] In addition, during specific implementation, it is determined whether one of the multiple sliding backup intervals is the same as the backup reference block, that is, relative to each sliding backup interval, it is determined whether the hot data in the sliding backup interval is the same as the hot data in the sliding backup interval; wherein, when multiple sliding backup intervals are the same as the backup reference block, only one backup reference block can be stored, and the backup reference block can be referenced in other sliding backup intervals, which can save storage space and further improve the storage efficiency of the cloud data center server.

[0075] It should be noted that in this application, when the amount of data that the cloud data center server needs to process is reduced, the read and write operation speed can be faster, while reducing the burden on the cloud data center server storage device. During the data transmission process, by transmitting only one backup reference block and the sliding backup interval that references the block, the data transmission time and bandwidth requirements can be reduced, which is especially beneficial for operations such as remote backup, replication and migration of data.

[0076] In step 104 , if none of the plurality of sliding backup intervals is identical to the backup reference block, the backup reference block is updated until a sliding backup interval is found that is identical to the updated backup reference block.

[0077] In some embodiments, the backup reference block may be updated in the following manner:

[0078] If none of the sliding backup intervals is the same as the backup reference block, subtracting one data unit from the initial reference capacity of the backup reference block in order from the back to the front to complete the update;

[0079] Re-searching, if none of the multiple sliding backup intervals is the same as the updated backup reference block, subtracting one data unit from the initial reference capacity of the updated backup reference block in the order from the back to the front, and completing the next update;

[0080] The process continues in this way until a sliding backup interval is found that is the same as the updated backup reference block.

[0081] It should be noted that in the present application, by dynamically adjusting the size of the backup reference block, redundancy in the data can be more accurately identified and eliminated; wherein, a larger backup reference block size may cover a smaller reference window, resulting in incomplete elimination of redundancy. Therefore, gradually reducing the size of the backup reference block can identify redundancy in a more fine-grained manner and improve the effect of eliminating data redundancy. Moreover, gradually reducing the size of the backup reference block can further optimize the storage space utilization of the cloud data center server. A smaller reference window size can better adapt to the repetitive patterns of different data and reduce storage redundancy, which can further reduce storage requirements and improve the storage efficiency of the cloud data center server. When data is damaged or lost, a smaller backup reference block can speed up the data recovery process. In addition, since the backup reference block is shared in multiple sliding backup intervals, the consistency and integrity of the data can be improved.

[0082] In step 105, if one of the multiple sliding backup intervals is the same as the backup reference block, the sliding backup interval that is the same as the backup reference block is used as a backup transition window, and the adaptive backup ratio when backing up the data corresponding to the backup transition window is determined based on the sliding backup window and the backup transition window; the backup reference block is continued to be updated until the initial reference capacity in the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows and multiple adaptive backup ratios.

[0083] In the following embodiment, the adaptive backup ratio for backing up data corresponding to the backup transition window according to the sliding backup window and the backup transition window may be determined using the following formula:

[0084]

[0085] Wherein, l represents the adaptive backup ratio when backing up the data corresponding to the backup transition window, ζ represents the data length from the first hot data in the sliding backup window to the first hot data in the backup transition window, Indicates the data length from the last hot data in the sliding backup window to the last hot data in the backup transition window.

[0086] It should be noted that the adaptive backup ratio in the present application indicates the degree of deviation of the backup transition window in the sliding backup window. When the adaptive backup ratio is larger, the degree of deviation of the backup transition window in the sliding backup window is greater. When the adaptive backup ratio is smaller, the degree of deviation of the backup transition window in the sliding backup window is smaller. The adaptive backup ratio can also be used to reflect the relative position of the corresponding data in the backup transition window in the sliding backup window.

[0087] In specific implementation, after determining the adaptive backup ratio, continue to subtract one data unit from the size of the initial reference capacity in the backup reference block in order from back to front, and continue to judge whether one of the multiple sliding backup intervals is the same as the updated backup reference block, repeat steps 104 and 105 to obtain a new backup reference block, a new backup transition window and a new adaptive backup ratio until the initial reference capacity of the backup reference block is equal to zero.

[0088] In step 106, a backup reference library of the data to be backed up is established based on all backup reference blocks, all backup transition windows, and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0089] In some embodiments, a backup reference library of the data to be backed up is established using all backup reference blocks, all backup transition windows, and all adaptive backup ratios. When a target user generates new cloud data, adaptive backup of the new cloud data based on the backup reference library can be implemented in the following manner, namely:

[0090] A backup reference block library is established from all backup reference blocks, and the position of each backup transition window that is the same as the backup reference block is marked;

[0091] Establishing data guidance relationships between all backup reference blocks and corresponding backup transition windows, and establishing a data guidance library based on all data guidance relationships;

[0092] A backup reference library of the data to be backed up is established based on the data guide library, the backup reference block library and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0093] In some embodiments, the establishment of a backup reference block library from all backup reference blocks may be implemented in the following manner, namely:

[0094] Assign a unique identifier to each backup reference block;

[0095] A backup reference block library is established based on all backup reference blocks and corresponding identifiers.

[0096] In specific implementation, the UUID generator in the existing technology can be used to generate an identifier for each backup reference block; or a corresponding hash value can be generated based on the hot data in the backup reference block, and the hash value can be used as the identifier of the corresponding backup reference block; in other embodiments, other methods can also be used to assign a unique identifier to the backup reference block, which is not limited here.

[0097] In some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is a schematic diagram of a process for establishing a data guidance library in some embodiments of the present application. In this embodiment, data guidance relationships between all backup reference blocks and corresponding backup transition windows are established. Establishing the data guidance library from all data guidance relationships can be achieved using the following steps:

[0098] In step 1021, for each backup reference block, positions of all backup transition windows identical to the backup reference block in the sliding backup window are determined;

[0099] In step 1022, the position range of the backup reference block in the sliding backup window is determined based on the positions of all backup transition windows;

[0100] In step 1023, a data reference entry is generated according to the identifier of the backup reference block and the position range of the backup reference block in the sliding backup window, wherein the data reference entry is a data reference relationship;

[0101] In step 1024, the generated data guide entry is added to the data guide library, thereby obtaining the data guide library.

[0102] In specific implementation, MapReduce, Hive or Pig in big data processing technology can be used to generate data guide entries based on the identifier of the backup reference block and the position range of its backup reference block in the sliding backup window. In other embodiments, other methods can also be used to generate data guide entries, which are not limited here.

[0103] It should be noted that in this application, by establishing a backup reference block library, storage space can be better utilized; duplicate data blocks only need to be stored once and referenced at different locations through guidance relationships without the need for repeated storage. By establishing a data guidance library, data can be quickly located and restored, thereby improving data access efficiency; at the same time, since the data guidance library records the location of the backup reference blocks, the integrity and consistency of the data can be verified.

[0104] In specific implementation, a backup reference library of the data to be backed up is established based on the data guide library, the backup reference block library and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library, that is: the data guide library, the backup reference block library and all adaptive backup ratios are combined into a backup reference library for hot data, and each adaptive backup ratio is used as the initial adaptive backup ratio of the corresponding backup reference block in the backup library; wherein, the data guide relationship in the data guide library and the backup reference block in the backup reference block library and the corresponding identifier are used as a reference when backing up new data, and a corresponding code is generated; when the target user needs to restore data , performing data recovery based on the corresponding code, the data guidance relationship in the data guidance library, the backup reference block in the backup reference block library, and the corresponding identifier; for each backup reference block in the backup reference block library, calculating the adaptive backup ratio of the backup reference block in the recovery data; if the adaptive backup ratio of the backup reference block in the recovery data is equal to the initial adaptive backup ratio of the backup reference block, sending the recovery data to the target user; if the adaptive backup ratio of the backup reference block in the recovery data is not equal to the initial adaptive backup ratio of the backup reference block, regenerating new recovery data, and repeating the above steps until the adaptive backup ratio of the backup reference block in the new recovery data is equal to the initial adaptive backup ratio of the backup reference block.

[0105] It should be noted that when restoring data in this application, by comparing the adaptive backup ratio of the backup reference block in the restored data with the initial adaptive backup ratio of the backup reference block, it is possible to detect whether the data has been restored normally, thereby improving the accuracy of data recovery.

[0106] In addition, in another aspect of the present application, in some embodiments, the present application provides a cloud data center server data backup system, referring to Figure 3 , which is a schematic diagram of exemplary hardware and / or software of a cloud data center server data backup system according to some embodiments of the present application. The cloud data center server data backup system 300 includes: an acquisition module 301, a processing module 302, and an execution module 303, which are described as follows:

[0107] Acquisition module 301, in this application, acquisition module 301 is mainly used to obtain the historical cloud data of the target user in the cloud service center, extract the hot data in the historical cloud data, and obtain the data to be backed up;

[0108] Processing module 402, in this application, the processing module 402 is used to determine the backup reference block and the sliding backup window of the data to be backed up;

[0109] In the present application, the processing module 402 is further configured to divide the sliding backup window into a plurality of sliding backup intervals, and determine whether one of the plurality of sliding backup intervals is the same as the backup reference block;

[0110] In the present application, the processing module 402 is further configured to update the backup reference block if none of the plurality of sliding backup intervals is identical to the backup reference block, until a sliding backup interval among the plurality of sliding backup intervals is found to be identical to the updated backup reference block;

[0111] In the present application, the processing module 402 is further configured to, if one of the multiple sliding backup intervals is identical to the backup reference block, use the sliding backup interval identical to the backup reference block as a backup transition window, determine an adaptive backup ratio for backing up data corresponding to the backup transition window based on the sliding backup window and the backup transition window, continue updating the backup reference block until the initial reference capacity of the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows, and multiple adaptive backup ratios.

[0112] Execution module 403. In this application, execution module 403 is mainly used to establish a backup reference library of the data to be backed up based on all backup reference blocks, all backup transition windows and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

[0113] Each module in the aforementioned cloud data center server data backup system can be implemented in whole or in part through 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 computer device's memory in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0114] In addition, in one embodiment, the present application provides a computer device, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. 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 computer program in the non-volatile storage medium. The database of the computer device is used to store data on a cloud data center server data backup method. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a cloud data center server data backup method is implemented.

[0115] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0116] In one embodiment, a computer device is also provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps in the above-mentioned cloud data center server data backup method embodiment are implemented.

[0117] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which, when executed by a processor, implements the steps in the above-mentioned cloud data center server data backup method embodiment.

[0118] In one embodiment, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps of the aforementioned cloud data center server data backup method embodiment.

[0119] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented 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 memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. 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).

[0120] In summary, in the cloud data center server data backup method and related equipment disclosed in the embodiments of the present application, first, the historical cloud data of the target user in the cloud service center is obtained, the hot data in the historical cloud data is extracted, the data to be backed up is obtained, the backup reference block and the sliding backup window of the data to be backed up are determined, the sliding backup window is divided into multiple sliding backup intervals, and it is judged whether there is a sliding backup interval in the multiple sliding backup intervals that is the same as the backup reference block. If none of the multiple sliding backup intervals is the same as the backup reference block, the backup reference block is updated until one of the multiple sliding backup intervals is found to be the same as the updated backup reference block. If one of the multiple sliding backup intervals is the same as the backup reference block, The same sliding backup interval as the backup reference block is used as the backup transition window, and the adaptive backup ratio when backing up the data corresponding to the backup transition window is determined according to the sliding backup window and the backup transition window; the backup reference block is continuously updated until the initial reference capacity in the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows and multiple adaptive backup ratios, and establishing a backup reference library for the data to be backed up based on all the backup reference blocks, all the backup transition windows and all the adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library, so that the cloud data generated by the user can be adaptively backed up, reducing the data backup burden of the cloud data center server.

[0121] The technical features of the above embodiments can 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.

[0122] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A cloud data center server data backup method, characterized in that: The steps include: Obtain the target user's historical cloud data in the cloud service center, extract hot data from the historical cloud data, and obtain the data to be backed up; Determining a backup reference block and a sliding backup window for the data to be backed up; Dividing the sliding backup window into a plurality of sliding backup intervals, and determining whether one of the plurality of sliding backup intervals is the same as the backup reference block; If none of the multiple sliding backup intervals is identical to the backup reference block, updating the backup reference block until one of the multiple sliding backup intervals is found to be identical to the updated backup reference block; If one of the multiple sliding backup intervals is identical to the backup reference block, the sliding backup interval identical to the backup reference block is used as a backup transition window, and an adaptive backup ratio is determined for backing up data corresponding to the backup transition window based on the sliding backup window and the backup transition window; the backup reference block is continuously updated until the initial reference capacity of the updated backup reference block is equal to zero, thereby obtaining multiple backup reference blocks, multiple backup transition windows, and multiple adaptive backup ratios; A backup reference library of the data to be backed up is established by all backup reference blocks, all backup transition windows and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

2. The method according to claim 1, wherein Extracting hot data from the historical cloud data to obtain the data to be backed up specifically includes: Obtain the target user's access records in the cloud data center; Perform data analysis on target users’ access records in cloud data centers; Dividing the historical cloud data into cold data and hot data based on the result of data analysis; Extract the divided hot data and obtain the data to be backed up; The cold data is stored separately and a backup library of the cold data is established.

3. The method according to claim 2, wherein Establishing the backup library of the cold data specifically includes: Setting a life cycle management period of the cold data according to a value threshold of the cold data; configuring a storage medium for the cold data according to characteristics of the cold data; Archiving the cold data according to a storage cost threshold of the cold data; A backup library for the cold data is established according to the life management cycle, the configured storage medium, and the archiving processing method.

4. The method according to claim 1, wherein Updating the backup reference block specifically includes: If none of the sliding backup intervals is the same as the backup reference block, subtracting one data unit from the initial reference capacity of the backup reference block in order from the back to the front to complete the update; Re-searching, if none of the multiple sliding backup intervals is the same as the updated backup reference block, subtracting one data unit from the initial reference capacity of the updated backup reference block in the order from the back to the front, and completing the next update; The process continues in this way until a sliding backup interval is found that is the same as the updated backup reference block.

5. The method according to claim 1, wherein The sliding backup window is composed of hot data to be backed up and the storage capacity of the corresponding sliding window.

6. The method according to claim 1, wherein A backup reference library of the data to be backed up is established based on all backup reference blocks, all backup transition windows, and all adaptive backup ratios. When a target user generates new cloud data, adaptively backing up the new cloud data based on the backup reference library specifically includes: A backup reference block library is established from all backup reference blocks, and the position of each backup transition window that is the same as the backup reference block is marked; Establishing data guidance relationships between all backup reference blocks and corresponding backup transition windows, and establishing a data guidance library based on all data guidance relationships; A backup reference library of the data to be backed up is established based on the data guide library, the backup reference block library and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

7. The method according to claim 6, wherein Establishing data guidance relationships between all backup reference blocks and corresponding backup transition windows, and establishing a data guidance library based on all data guidance relationships specifically includes: For each backup reference block, determining positions of all backup transition windows identical to the backup reference block in the sliding backup window; Determine the position range of the backup reference block in the sliding backup window according to the positions of all backup transition windows; generating a data reference entry according to the identifier of the backup reference block and the position range of the backup reference block in the sliding backup window, wherein the data reference entry is a data reference relationship; The generated data guide entry is added to the data guide library, thereby obtaining the data guide library.

8. A cloud data center server data backup system, characterized in that: include: An acquisition module is used to acquire the historical cloud data of the target user in the cloud service center, extract hot data from the historical cloud data, and obtain the data to be backed up; A processing module, configured to determine a backup reference block and a sliding backup window for the data to be backed up; a processing module, configured to divide the sliding backup window into a plurality of sliding backup intervals, and determine whether one of the plurality of sliding backup intervals is the same as the backup reference block; a processing module, configured to update the backup reference block if none of the plurality of sliding backup intervals is identical to the backup reference block, until a sliding backup interval among the plurality of sliding backup intervals is found to be identical to the updated backup reference block; a processing module configured to, if one of the plurality of sliding backup intervals is identical to the backup reference block, use the sliding backup interval identical to the backup reference block as a backup transition window, determine an adaptive backup ratio for backing up data corresponding to the backup transition window based on the sliding backup window and the backup transition window, continue updating the backup reference block until the initial reference capacity of the updated backup reference block is equal to zero, thereby obtaining a plurality of backup reference blocks, a plurality of backup transition windows, and a plurality of adaptive backup ratios; The execution module is used to establish a backup reference library of the data to be backed up based on all backup reference blocks, all backup transition windows and all adaptive backup ratios. When the target user generates new cloud data, the new cloud data is adaptively backed up based on the backup reference library.

9. 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 cloud data center server data backup method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the cloud data center server data backup method according to any one of claims 1 to 7 are implemented.

Images