WO2025098218A1 - Data object backup method and apparatus, device, and medium - Google Patents

Abstract

A data object backup method and apparatus, a device, and a medium. The method comprises: acquiring data object resource information and a set matching rule list, wherein the data object resource information comprises the classification dimensions and categories of data objects, as well as a data object list; on the basis of the set matching rule list, determining a corresponding target data object list from the data object resource information; on the basis of the set matching rule list, determining a corresponding backup plan; and on the basis of the backup plan, backing the target data object list up to obtain a backup result of the target data object list. The present solution can dynamically match data backup plans for backup on the basis of changes in data objects, achieving better backup management.

Description

Data object backup method, device, equipment and medium

This application claims priority to the Chinese patent application filed with the China Patent Office on November 8, 2023, with application number 202311484914.5, the entire contents of which are incorporated by reference into this application.

Technical Field

The present application relates to the technical field of data disaster recovery, for example, to a data object backup method, device, equipment and medium.

Background Art

In recent years, with the continuous advancement of digital transformation, data has become an increasingly important asset within organizations. In order to better manage and use data, more and more industries have proposed data classification requirements and specifications. It is worth noting that data objects often need to be periodically counted to determine the latest classification of data.

Backup is an essential means to deal with information technology (IT) risks and is inextricably linked to data. The categories and levels of data objects change dynamically (such as the popularity of data, the importance of data, etc.), and different categories of data objects often require different recovery point objectives (RPO), that is, different backup plans. In traditional backup systems, data objects and backup plans are often strongly bound, and backup plans cannot dynamically adapt to changes in data object categories, which brings management burdens to backup operation and maintenance personnel.

Summary of the invention

The present application provides a data object backup method, apparatus, equipment and medium, which can dynamically match the data backup plan to perform backup according to the changes of the data object, so as to better manage the backup and help operation and maintenance personnel improve the efficiency of disaster recovery management.

According to one aspect of the present application, a data object backup method is provided, comprising:

Obtaining data object resource information and setting a matching rule list; wherein the data object resource information includes classification dimensions, categories, and data object lists of data objects;

Determining a corresponding target data object list from the data object resource information based on the set matching rule list;

Determine a corresponding backup plan according to the set matching rule list;

The target data object list is backed up according to the backup plan to obtain a backup result of the target data list.

Optionally, determining a corresponding target data object list from the data object resource information based on the set matching rule list includes:

Create a list of empty data objects;

Determining a corresponding target data object from the data object list based on the set matching rule list;

The target data object is placed into an empty data object list to obtain a target data object list.

Optionally, determining a corresponding target data object from the data object list based on the set matching rule list includes:

Traversing the data objects in the data list;

Comparing the traversed data object with a plurality of set matching rules in the set matching rule list;

In response to the traversed data object meeting at least one set matching rule, the traversed data object is determined as a target data object.

Optionally, determining the traversed data object as a target data object includes:

In response to the traversed data object meeting at least two set matching rules, the data object is determined as a target data object of the set matching rule with the highest priority among the at least two set matching rules.

Optionally, determining a corresponding target data object from the data object list based on the set matching rule list includes:

Sorting the set matching rules in the set matching rule list in order of priority from high to low;

The corresponding target data object is determined from the data object list based on the sorted set matching rule list.

Optionally, the corresponding data object list is determined based on the sorted set matching rule list. The target data objects include:

Traversing the data objects in the data list;

Reading the setting matching rules from the sorted setting matching rule list in sequence, and comparing the traversed data object with the read setting matching rules;

In response to the data object meeting the set matching rule that has been read, determining the data object as a target data object of the set matching rule that has been read, stopping reading the set matching rule, and continuing to traverse the next data object;

In response to the data object not meeting the set matching rule that has been read, continue to read the next set matching rule, and return to perform the operation of comparing the traversed data object with the read set matching rule until the traversal of the data object is completed.

Optionally, the set matching rule is formed by combining matching conditions of at least two classification dimensions through set logic; the set logic includes: at least one of: AND logic, NOT logic, and OR logic; the classification dimensions are the same dimension or different dimensions.

According to another aspect of the present application, a data object backup device is provided, comprising:

An acquisition module, configured to acquire data object resource information and set a matching rule list; wherein the data object resource information includes classification dimensions, categories and data object lists of data objects;

a target data object determination module, configured to determine a corresponding target data object list from the data object resource information based on the set matching rule list;

A backup plan determination module, configured to determine a corresponding backup plan according to the set matching rule list;

The target data object backup module is configured to back up the target data object list according to the backup plan to obtain a backup result of the target data object list.

According to another aspect of the present application, an electronic device is provided, the electronic device comprising:

at least one processor; and

a memory communicatively connected to the at least one processor; wherein,

The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the present application. The data object backup method described in any embodiment.

According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the data object backup method described in any embodiment of the present application when executed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a data object backup method provided according to Embodiment 1 of the present application;

FIG2 is a flow chart of a data object backup method provided according to Embodiment 2 of the present application;

3 is a schematic diagram of the structure of a data object backup device provided according to Embodiment 3 of the present application;

FIG4 is a schematic diagram of the structure of an electronic device provided according to a fourth embodiment of the present application.

DETAILED DESCRIPTION

The terms "first", "second", and "target" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

Embodiment 1

FIG1 is a flow chart of a data object backup method provided according to Embodiment 1 of the present application. This embodiment is applicable to the case of backing up various data objects. The method can be executed by a data object backup device. The data object backup device can be implemented in the form of hardware and/or software. The data object backup device can be configured in an electronic device with data processing capabilities. As shown in FIG1 , the method includes:

It can be executed by the backup system, and can form resource information after hierarchical and classified management of various data objects within the information technology (IT) system. It can be called by the backup system through an open application programming interface (API), so that the backup plan can be configured based on the data category. When the data object to be backed up belongs to the specified category, the backup plan will trigger the backup of this data object.

S110: Obtain data object resource information and set a matching rule list.

The data object may be any data object in an IT system. The objects may be virtual machines or database instances. The set matching rule list may be a pre-set matching rule list. The set matching rule list in this embodiment may include a set number of matching rules. The set number may be set according to actual needs. Exemplarily, the set matching rule list in this embodiment may include ten matching rules.

Among them, the data object resource information includes the classification dimension, category and data object list of the data object. The classification dimension can be understood as the dimension for classifying and setting the data object. In this embodiment, the data objects can be divided into different categories according to different classification dimensions. Exemplarily, the classification dimension may include dimensions such as data popularity, data importance, data volume, data creation time and data owner. The category can be the category obtained by dividing the data object according to the classification dimension. In this embodiment, obtaining the data object resource information can be understood as the operation of synchronizing the data object resource information. In this embodiment, when backing up the data object, the latest data object resource information is synchronized. Since the data objects in the resource information may change at any time, the data objects may be added or removed, and the categories of the data objects in different dimensions may also change at any time. Therefore, before the backup plan is triggered, the resource information will be synchronized first to obtain the latest data object resource information, so as to ensure the accuracy of the backup object.

Optionally, when the classification dimension is set to data heat, the data object can be divided into three categories: hot, warm and cold according to the data heat dimension. In this embodiment, the category to which the data object belongs under the data heat dimension can be determined according to the access frequency of a data object within a set time period. When the frequency of accessing a certain data object exceeds the set range, the category to which the certain data object belongs is hot. The importance of data can be divided into categories such as core, important, general and secondary. The classification dimension in this embodiment can be set according to actual needs. The data object in this embodiment can belong to multiple categories under different dimensions. Exemplarily, a data object is classified as "hot" under the dimension of "data heat" and as "core" under the dimension of "importance". The data object list can be understood as all data objects included in the system. In this embodiment, resource information such as classification dimensions, categories and data object lists of data objects in the system and a pre-set matching rule list can be obtained. In the matching rules of this embodiment, one or more categories of a set classification dimension in the data object resource information, or multiple categories of multiple set classification dimensions can be added, which can be configured according to actual needs.

In this embodiment, optionally, the setting matching rule can be formed by combining the matching conditions of at least two classification dimensions through setting logic; the setting logic includes: at least one of: AND logic, NOT logic, and OR logic; the classification dimensions are the same dimension or different dimensions.

The matching condition can be understood as a category condition determined from at least two classification dimensions. Exemplarily, the matching condition can be the "core" category in the "importance" classification dimension. In this embodiment, the matching rules can be pre-set based on the backup device so that the data object can configure the corresponding backup plan based on the matching rules. The set matching rules in this embodiment can be used to match and filter out all data objects that meet specific rules.

Optionally, in this embodiment, multiple categories under the same classification dimension can be added to one matching rule, and the categories can be in an "or" relationship. For example, the importance of a data object is "core" or "important". In this embodiment, multiple categories under different classification dimensions can be added to one matching rule, and the categories can be specified as "and" or "or" relationships. Exemplarily, the importance of a data object is a category of "core" or the heat of the data is a category of "hot"; the importance of a data object is a category of "core" and the heat of the data is a category of "hot".

In this embodiment, through such a setting, each matching rule in the matching rule list can be flexibly configured according to actual business needs, so as to facilitate the backup of data objects.

S120: Determine a corresponding target data object list from the data object resource information based on the set matching rule list.

The target data object list may include multiple target data objects. The target data object list in this embodiment may correspond to the set matching rule list.

In this embodiment, matching can be performed from data object resource information according to each matching rule in the set matching rule list, and the data object that meets the matching rule is used as the target data object corresponding to the matching rule, thereby determining the target data object corresponding to each matching rule to obtain a target data object list.

S130: Determine a corresponding backup plan according to the set matching rule list.

Among them, the backup plan can be pre-configured according to each matching rule in the set matching rule list. The backup plan can back up the data object. In this embodiment, the backup plan can include the backup time and the backup type. The backup type can include incremental backup and full backup. Exemplarily, the backup plan can be a full backup at 20:00 every day, and an incremental backup every 4 hours. Each matching rule in this embodiment can correspond to a backup plan. Each matching rule in this embodiment is pre-configured with a corresponding backup plan, and the corresponding backup plan can be determined according to each matching rule in the set matching rule list.

S140: Back up the target data object list according to the backup plan to obtain a backup result of the target data list.

The backup plan matching rules in this embodiment correspond to the binding. When the backup plan is triggered, the data object resource information can be automatically synchronized and the data objects can be screened and matched. After all the target data objects under the corresponding matching rules are obtained, the backup operation is performed.

In this embodiment, a backup plan corresponding to each matching rule can be determined according to the set matching rule list, and each target data in the target data list can be backed up according to the determined backup plan, so that the backup result corresponding to each target data in the target data list can be obtained.

The embodiment of the present application obtains data object resource information and sets a matching rule list; wherein, The object resource information includes the classification dimension, category and data object list of the data object; the corresponding target data object list is determined from the data object resource information based on the set matching rule list; the corresponding backup plan is determined according to the set matching rule list; the target data object list is backed up according to the backup plan to obtain the backup result of the target data list. The embodiment of the present application can dynamically match the data backup plan to perform backup according to the change of the data object, so as to better perform backup management and help operation and maintenance personnel improve the efficiency of disaster recovery management.

Embodiment 2

FIG2 is a flow chart of a data object backup method provided according to the second embodiment of the present application. This embodiment is modified based on the above embodiment. Specifically, based on the set matching rule list, a corresponding target data object list is determined from the data object resource information, including: creating an empty data object list; based on the set matching rule list, a corresponding target data object is determined from the data object list; and the target data object is placed in the empty data object list to obtain the target data object list. As shown in FIG2, the method includes:

S210: Obtain data object resource information and set a matching rule list.

The data object resource information includes the classification dimensions, categories and data object lists of the data objects.

S220: Create an empty data object list.

The empty data object list can be understood as a blank data object list. In this embodiment, an empty data object list can be created to store target data objects corresponding to each matching rule in the set matching rule list.

S230: Determine a corresponding target data object from the data object list based on the set matching rule list.

The target data object may be a data object that meets each matching condition in the matching rule.

In this embodiment, based on each setting matching rule in the setting matching rule list, each data object can be traversed from the data object list to determine the target data object corresponding to each setting matching rule.

In this embodiment, optionally, determining a corresponding target data object from a data object list based on a set matching rule list includes: traversing the data objects in the data list; comparing the traversed data object with a plurality of set matching rules in the set matching rule list; and determining the traversed data object as a target data object in response to the traversed data object satisfying at least one set matching rule.

The set matching rule list includes a set number of set matching rules. The traversed data object is compared with each set matching rule in the set matching rule list, specifically, it can be determined whether the data object meets the matching condition in the matching rule, that is, meets the category in the set classification dimension contained in the matching rule.

In this embodiment, all data objects in the data list obtained from the data object resource information can be traversed, and the traversed data objects can be compared with each set matching rule in the set matching rule list. In response to the traversed data object satisfying at least one set matching rule, the traversed data object can be determined as the target data object corresponding to the set matching rule.

Through such a setting in this embodiment, all data objects can be traversed, so that the corresponding matching rules can be determined according to the changes in data categories. When the data object category changes, the corresponding matching rules can be determined according to the changed data object, thereby facilitating the execution of the corresponding backup plan.

In this embodiment, optionally, determining the traversed data object as the target data object includes: in response to the traversed data object satisfying at least two set matching rules, determining the data object as the target data object of the set matching rule with the highest priority among the at least two set matching rules.

Among them, at least two setting matching rules can be understood as two or more setting matching rules. In this embodiment, all data objects in the system are traversed, and the data object may simultaneously satisfy multiple setting matching rules in the setting matching rule list. The priority can be pre-set for the setting matching rule.

In this embodiment, in response to the traversed data object meeting at least two set matching rules, the data object may be determined as a target data object corresponding to the set matching rule with the highest priority among the at least two set matching rules.

Since all data objects are traversed in this embodiment, considering that a data object may satisfy multiple matching rules at the same time, there may be a conflict problem that one data object is associated with multiple backup plans. Therefore, in this embodiment, the corresponding priority can be set for the matching rule, and it is set according to the actual situation. When a data object satisfies a matching rule with a high priority, it will be determined as the target data object of the matching rule with the highest priority. Correspondingly, the backup operation of this data object will only be triggered by the backup plan associated with the matching rule with a high priority.

Through such a setting in this embodiment, the priority of the set matching rules can be set. When a data object satisfies multiple set matching rules at the same time, the target data object will be determined according to the priority. When the data object satisfies the matching rule with a high priority, it will no longer match the matching rule with a low priority, thereby avoiding the situation where the data object corresponds to multiple set matching rules.

In this embodiment, optionally, determining the corresponding target data object from the data object list based on the set matching rule list includes: sorting the set matching rules in the set matching rule list in descending order of priority; and selecting the corresponding target data object from the data object list based on the sorted set matching rule list. Determine the corresponding target data object.

In this embodiment, the setting matching rules may be sorted in order of priority first, and the corresponding target data object is determined based on the sorted setting matching rule list.

Optionally, in this embodiment, the setting matching rules in the setting matching rule list can be sorted in descending order of priority, and then the data object list is traversed according to each setting matching rule in the sorted setting matching rule list to determine the corresponding target data objects.

In this embodiment, optionally, determining the corresponding target data object from the data object list based on the sorted setting matching rule list includes: traversing the data objects in the data list; reading the setting matching rules from the sorted setting matching rule list in sequence, and comparing the traversed data objects with the read setting matching rules; in response to the data object meeting the read setting matching rules, determining the data object as the target data object of the read setting matching rules, stopping reading the setting matching rules, and continuing to traverse the next data object; in response to the data object not meeting the read setting matching rules, continuing to read the next setting matching rule, and returning to perform the operation of comparing the traversed data object with the read setting matching rules until the data object traversal is completed.

The next data object may be understood as the next data object of the current data object in the data list, and the next set matching rule may be understood as the next set matching rule of the current set matching rule in the order of priority.

In this embodiment, the setting matching rules are read sequentially from the sorted setting matching rule list, and the setting matching rules can be read one by one from the setting matching rule list in descending order of priority. In this embodiment, the traversed data object is compared with the read setting matching rule, which can be understood as a process of comparing the traversed data object with the matching condition in the setting matching rule to determine whether it meets the matching condition.

In the process of confirming the data object list in this embodiment, it is necessary to traverse all data objects under the resource information, and compare and match each set matching rule in sequence according to the priority sorting order. In response to the data object matching the set matching rule with a higher priority, continue to confirm the next data object. In response to the data object matching the set matching rule that currently needs to be confirmed, this data object can be confirmed as the target data object of the set matching rule that has been read, until all data objects are traversed, and all data objects that meet the set matching rule are obtained.

Optionally, in this embodiment, the data objects in the data list can be traversed; the setting matching rules can be read from the sorted setting matching rule list in sequence, and the traversed data objects can be compared with the read setting matching rules. In response to the read data object meeting the read setting matching rules, the data object can be determined as the target data object of the read setting matching rules, and the reading of the setting matching rules can be stopped, and the next data object can be traversed continuously, and the setting matching rules can be read continuously for the next data object and compared. In response to the data object not meeting the set matching rule read, continue to read the next set matching rule, and return to continue to perform the operation of comparing the traversed data object with the read set matching rule until the data object traversal is completed.

Through such a setting in the present embodiment, data objects and matching rules can be traversed separately to determine the target data objects corresponding to each set matching rule, so as to respond to changes in data objects to match the set matching rules, thereby performing corresponding backups, while saving the daily adjustment work of the backup plan and simplifying operation and maintenance.

S240: Put the target data object into an empty data object list to obtain a target data object list.

The target data object list may include multiple target data objects. Each target data object in the target data object list may correspond to each matching rule in the set matching rule list. In this embodiment, the target objects that meet each set matching rule may be put into the empty data object list to obtain the target data object list.

S250: Determine a corresponding backup plan according to the set matching rule list.

For example, in this embodiment, an example of a backup plan corresponding to the matching rule configuration in the matching rule list is shown in Table 1:

Table 1

S260: Back up the target data object list according to the backup plan to obtain a backup result of the target data list.

In this embodiment, the corresponding matching rules can be matched according to the categories in the classification dimension of the data object, so that the corresponding backup plan can be configured for the setting matching rules, so that the backup plan can be automatically adjusted, meeting the demand for dynamically adjusting the RPO of the data object according to the classification results.

In the embodiment of the present application, data object resource information is obtained and a matching rule list is set; wherein the data object resource information includes the classification dimension, category and data object list of the data object; an empty data object list is created; the corresponding target data object is determined from the data object list based on the set matching rule list; the target data object is placed in the empty data object list to obtain the target data object list; the corresponding backup plan is determined according to the set matching rule list; the target data object list is backed up according to the backup plan to obtain the backup result of the target data list. The embodiment of the present application can dynamically match the data backup plan to perform backup according to the change of the data object, so as to better perform backup management and help operation and maintenance personnel improve the efficiency of disaster recovery management.

Embodiment 3

FIG3 is a schematic diagram of the structure of a data object backup device provided according to Embodiment 3 of the present application.

As shown in FIG3 , the device comprises:

The acquisition module 310 is configured to acquire data object resource information and set a matching rule list.

The data object resource information includes the classification dimensions, categories and data object lists of the data objects.

The target data object determination module 320 is configured to determine a corresponding target data object list from the data object resource information based on a set matching rule list.

A backup plan determination module 330, configured to determine a corresponding backup plan according to a set matching rule list;

The target data object backup module 340 is configured to back up the target data object list according to the backup plan to obtain a backup result of the target data object list.

Optionally, the target data object determination module 320 includes:

Empty list creation unit, set to create an empty data object list;

a target data object determination unit, configured to determine a corresponding target data object from a data object list based on a set matching rule list;

The data object list obtaining unit is configured to put the target data object into an empty data object list to obtain a target data object list.

Optionally, the target data object determination unit includes:

A data object traversal subunit is configured to traverse the data objects in the data list;

A comparison subunit, configured to compare the traversed data object with a plurality of set matching rules in a set matching rule list;

The first target object determination subunit is configured to determine the traversed data object as a target data object in response to the traversed data object meeting at least one set matching rule.

Optionally, the first target object determination subunit is configured to determine the traversed data object as the target data object in the following manner: in response to the traversed data object satisfying at least two set matching rules, determining the data object as the target data object of the set matching rule with the highest priority among the at least two set matching rules.

Optionally, the target data object determination unit includes:

A sorting subunit is configured to sort the set matching rules in the set matching rule list in descending order of priority;

The second target object determination subunit is configured to determine the corresponding target data object from the data object list based on the sorted set matching rule list.

Optionally, the second target object determination subunit is configured to determine the corresponding target data object from the data object list based on the sorted setting matching rule list in the following manner: traversing the data objects in the data list; reading the setting matching rules from the sorted setting matching rule list in sequence, and comparing the traversed data objects with the read setting matching rules; in response to the data object satisfying the read setting matching rules, determining the data object as the target data object of the read setting matching rules, stopping reading the setting matching rules, and continuing to traverse the next data object; in response to the data object not satisfying the read setting matching rules, continuing to read the next setting matching rule, and returning to perform the operation of comparing the traversed data object with the read setting matching rules until the data object traversal is completed.

Optionally, the setting matching rule is formed by combining the matching conditions of at least two classification dimensions through setting logic; the setting logic includes: at least one of: AND logic, NOT logic, and OR logic; the classification dimensions are the same dimension or different dimensions.

A data object backup device provided in an embodiment of the present application can execute a data object backup method provided in any embodiment of the present application, and has functional modules and beneficial effects corresponding to the execution method.

Embodiment 4

FIG4 is a schematic diagram of the structure of an electronic device provided according to Embodiment 4 of the present application. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples.

As shown in FIG. 4 , the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the ROM 12 or the computer program loaded from the storage unit 18 to the RAM 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.

A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special processing components with processing and computing capabilities. Some examples of the processor 11 include a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a data object backup method.

In some embodiments, the data object backup method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed on electronic device 10 via ROM 12 and/or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data object backup method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the data object backup method in any other appropriate manner (e.g., by means of firmware).

Various implementations of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various implementations may be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. The method may include: being implemented in one or more computer programs, which may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special-purpose or general-purpose programmable processor, which may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions/operations specified in the flow charts and/or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer readable storage medium may include an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN), blockchain network, and the Internet.

A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services.

It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved.

Claims (10)

A data object backup method, comprising: Obtaining data object resource information and setting a matching rule list; wherein the data object resource information includes classification dimensions, categories, and data object lists of data objects; Determining a corresponding target data object list from the data object resource information based on the set matching rule list; Determine a corresponding backup plan according to the set matching rule list; The target data object list is backed up according to the backup plan to obtain a backup result of the target data list. The method according to claim 1, wherein the determining a corresponding target data object list from the data object resource information based on the set matching rule list comprises: Create a list of empty data objects; Determining a corresponding target data object from the data object list based on the set matching rule list; The target data object is put into an empty data object list to obtain a target data object list. The method according to claim 2, wherein determining the corresponding target data object from the data object list based on the set matching rule list comprises: Traversing the data objects in the data list; Comparing the traversed data object with a plurality of set matching rules in the set matching rule list; In response to the traversed data object meeting at least one set matching rule, the traversed data object is determined as a target data object. The method according to claim 3, wherein determining the traversed data object as the target data object comprises: In response to the traversed data object meeting at least two set matching rules, the data object is determined as a target data object of the set matching rule with the highest priority among the at least two set matching rules. The method according to claim 2, wherein determining the corresponding target data object from the data object list based on the set matching rule list comprises: Sorting the set matching rules in the set matching rule list in order of priority from high to low; The corresponding target data object is determined from the data object list based on the sorted set matching rule list. The method according to claim 5, wherein determining the corresponding target data object from the data object list based on the sorted set matching rule list comprises: Traversing the data objects in the data list; Reading the setting matching rules from the sorted setting matching rule list in sequence, and comparing the traversed data object with the read setting matching rules; In response to the data object meeting the set matching rule that has been read, determining the data object as a target data object of the set matching rule that has been read, stopping reading the set matching rule, and continuing to traverse the next data object; In response to the data object not meeting the set matching rule that has been read, continue to read the next set matching rule, and return to perform the operation of comparing the traversed data object with the read set matching rule until the traversal of the data object is completed. According to the method according to claim 1, the set matching rules are formed by combining the matching conditions of at least two classification dimensions through set logic; the set logic includes: at least one of: AND logic, NOT logic, and OR logic; the classification dimensions are the same dimension or different dimensions. A data object backup device, comprising: An acquisition module, configured to acquire data object resource information and set a matching rule list; wherein the data object resource information includes classification dimensions, categories and data object lists of data objects; a target data object determination module, configured to determine a corresponding target data object list from the data object resource information based on the set matching rule list; A backup plan determination module, configured to determine a corresponding backup plan according to the set matching rule list; The target data object backup module is configured to back up the target data object list according to the backup plan to obtain a backup result of the target data object list. An electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the data object backup method according to any one of claims 1 to 7. A computer-readable storage medium stores computer instructions, wherein the computer instructions are used to enable a processor to implement the data object backup method according to any one of claims 1 to 7 when executed.