Data processing method and device

Abstract

The invention discloses a data processing method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: in response to received update information for a first software version, obtaining a first data version identifier corresponding to the first software version; the update information indicates a second data version identifier; obtaining a task change record of each data version identifier between the first data version identifier and the second data version identifier; and updating a first data version corresponding to the first data version identifier to a second data version corresponding to the second data version identifier according to the task change record of each data version identifier. According to the embodiment, the error rate of data upgrading through manual operation is reduced, the efficiency and accuracy of data upgrading are improved, and the consistency of the data version and the software version is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and apparatus for data processing. Background Technology

[0002] In the development and iteration of software systems such as intelligent chatbot systems, it is necessary to develop and maintain various types of data. Different software versions support different sets of functions and have different corresponding data models. Multiple environments may deploy different software versions, and it is necessary to maintain the correspondence between data and software versions to ensure data upgrades in multiple environments.

[0003] In related technologies, manual documentation is used to track data changes during software upgrades. However, this method is prone to problems such as data omissions and sequence errors, which is not conducive to long-term continuous data maintenance and management and makes it difficult to ensure the consistency between data and software versions. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a data processing method and apparatus that can reduce the error rate of manual data upgrades, improve the efficiency and accuracy of data upgrades, and ensure the consistency between data versions and software versions.

[0005] To achieve the above objectives, according to one aspect of the present invention, a data processing method is provided, comprising:

[0006] In response to receiving update information for a first software version, a first data version identifier corresponding to the first software version is obtained; the update information indicates a second data version identifier.

[0007] Obtain the task change record for each data version identifier between the first data version identifier and the second data version identifier;

[0008] Based on the task change record for each data version identifier, update the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier.

[0009] Optionally, obtaining the task change record for each data version identifier between the first data version identifier and the second data version identifier includes:

[0010] Obtain the data source type corresponding to the first software version;

[0011] Obtain each data version identifier between the first data version identifier and the second data version identifier;

[0012] The task change record is determined based on the data source type to identify each data version.

[0013] Optionally, before obtaining the task change record for each data version identifier between the first data version identifier and the second data version identifier, the method further includes: creating a task change record for the data version identifier; the data version identifier has a corresponding software version;

[0014] The task change record for creating the data version identifier includes:

[0015] In response to the detected software version creation instruction, a data version identifier corresponding to the software version is created;

[0016] A data change task is created based on the data version identifier; the data change task indicates the target data source;

[0017] Execute the data change task for the target data source to create a task change record for the data version identifier.

[0018] Optionally, before creating the task change record for the data version identifier, the method further includes:

[0019] Obtain the task execution result of the data change task;

[0020] The task execution result indicates that the data change task was successfully executed; wherein, the task change record includes the data source type corresponding to the target data source.

[0021] Optionally, a data change task is created based on the data version identifier, including:

[0022] The data change operation is determined based on the data version identifier;

[0023] The task type is determined based on the data change operation;

[0024] Determine the target data source based on the task type;

[0025] The data change task is created based on the task type and the target data source.

[0026] Optionally, the task type is determined based on the data change operation, including:

[0027] If the data change operation indicates a database change operation, the task type is determined to be a data change task;

[0028] If the data change operation indicates a model file change operation, the task type is determined to be a file-type change task;

[0029] If the data change operation indicates a change operation that modifies data or a data table in a coded manner, the task type is determined to be a coded change task.

[0030] Optionally, updating the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier based on the task change record of each data version identifier includes:

[0031] The task change records for each data version identifier are used to determine each change task and the execution order of each change task.

[0032] Each change task is executed according to the execution order to update the first data version to the second data version.

[0033] According to another aspect of the present invention, a data processing apparatus is provided, comprising:

[0034] The first acquisition module, in response to receiving update information for a first software version, acquires a first data version identifier corresponding to the first software version; the update information indicates a second data version.

[0035] The second acquisition module acquires the task change record of each data version identifier between the first data version identifier and the second data version identifier;

[0036] The update module updates the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier based on the task change record of each data version identifier.

[0037] According to another aspect of the present invention, an electronic device is provided, comprising:

[0038] One or more processors;

[0039] Storage device for storing one or more programs.

[0040] When the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method provided by the present invention.

[0041] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the data processing method provided by the present invention.

[0042] One embodiment of the above invention has the following advantages or beneficial effects: The data processing method of this embodiment, upon receiving update information for a first software version, obtains the corresponding first data version identifier, while the update information indicates a second data version identifier; then, it upgrades from the first data version to the second data version by obtaining the task change record for each data version identifier between the first and second data version identifiers. This method achieves data version updates and upgrades through the task change record of each data version identifier. By tracking data changes, it completely replicates the data upgrade steps of the data version, completing the data upgrade, effectively reducing the error rate of manual operations, improving the efficiency and accuracy of data upgrades, ensuring the consistency between data versions and software versions, and facilitating long-term continuous data maintenance and management.

[0043] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0044] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein:

[0045] Figure 1 This is a schematic diagram of the main flow of a data processing method according to an embodiment of the present invention;

[0046] Figure 2 This is a schematic diagram of the main flow of another data processing method according to an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the main flow of another data processing method according to an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of the main flow of another data processing method according to an embodiment of the present invention;

[0049] Figure 5 This is a schematic diagram of the main modules of a data processing apparatus according to an embodiment of the present invention;

[0050] Figure 6 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied;

[0051] Figure 7 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0052] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0053] Figure 1 This is a schematic diagram of the main flow of a data processing method according to an embodiment of the present invention, as shown below. Figure 1 As shown, the data processing method includes the following steps:

[0054] Step S101: In response to receiving update information for the first software version, obtain the first data version identifier corresponding to the first software version; the update information indicates the second data version identifier;

[0055] Step S102: Obtain the task change record for each data version identifier between the first data version identifier and the second data version identifier;

[0056] Step S103: Update the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier according to the task change record of each data version identifier.

[0057] In this embodiment of the invention, the data processing method can be applied to the data upgrade corresponding to the software system during software upgrade, which can ensure the consistency between the data and the software version. The software system can be a dialogue system, such as an intelligent dialogue robot system, that is, using an intelligent robot to conduct dialogue.

[0058] In this embodiment of the invention, after receiving update information for the first software version, a first data version identifier corresponding to the first software version is obtained. The first software version can be the software version of the software system to be upgraded, and the first data version is the data version of the software system to be upgraded. The update information indicates a second data version identifier of the software system, that is, the upgraded data version identifier of the software system. The second data version identifier corresponds to the second software version, which is the upgraded software version of the software system. That is, when the software system is upgraded, it is upgraded from the first software version to the second software version. Correspondingly, the first data version must also be upgraded to the second data version to ensure the consistency between the software version and the data version and to ensure the stable operation of the software system.

[0059] In this embodiment of the invention, the first software version and the first data version can also be empty. The update information can be the installation instructions for the software system in the new deployment environment, so as to upgrade the second software version and the corresponding second data version according to the installation instructions. That is, the update information can be the installation instructions for the software system in the new deployment environment, or it can be the update instructions or upgrade instructions for the software system in the already deployed environment.

[0060] In this embodiment of the invention, after obtaining the first data version identifier and the second data version identifier, each data version identifier between the two data version identifiers can be determined based on the first data version identifier and the second data version identifier. That is, the task change record of each data version identifier that needs to be upgraded to during the process of upgrading from the first data version to the second data version is obtained, so as to use the task change record of each data version identifier to upgrade the data version and upgrade the first data version to the second data version.

[0061] In this embodiment of the invention, obtaining the task change record of each data version identifier between the first data version identifier and the second data version identifier includes: obtaining the data source type corresponding to the first software version; obtaining each data version identifier between the first data version identifier and the second data version identifier; and determining the task change record of each data version identifier according to the data source type.

[0062] In this embodiment of the invention, the software system of the data processing method is configured as a first deployment environment. Task change records for each data version identifier between the first and second data versions can be obtained from other deployment environments, and these records are imported into the first deployment environment for data version upgrades. First, the data source type corresponding to the first software version is obtained, i.e., the data source type of the first deployment environment. Then, other deployment environments with the same data source type as the first deployment environment are obtained. Task change records for each data version identifier between the first and second data version identifiers can then be obtained from these other deployment environments. These other deployment environments can be one or more. That is, when the software system upgrades in other deployment environments, it records the upgrade process for each data version, i.e., creates task change records for each data version identifier for use in data upgrades.

[0063] In this embodiment of the invention, before obtaining the task change record of each data version identifier between the first data version identifier and the second data version identifier, the method further includes: creating a task change record of the data version identifier; the data version identifier has a corresponding software version.

[0064] Among them, such as Figure 2 As shown, the task change record for creating a data version identifier includes:

[0065] Step S201: In response to the detected software version creation command, create a data version identifier corresponding to the software version;

[0066] Step S202: Create a data change task based on the data version identifier; the data change task indicates the target data source;

[0067] Step S203: Perform a data change task for the target data source to create a task change record with a data version identifier.

[0068] In this embodiment of the invention, before obtaining the task change record for each data version identifier, the task change record for each data version identifier already exists in other deployment environments. That is, data upgrades for each data version have been completed in other deployment environments, and task change records for each data version identifier have been created. Specifically, the creation process for the task change record for each data version identifier involves monitoring the software version in the current deployment environment. When a software version creation instruction is detected, i.e., a software version upgrade is detected, the corresponding data version is created. This involves creating information for the upgraded data version corresponding to the upgraded software version. The upgraded data version information includes the identifier of the upgraded data version, which corresponds to the identifier of the upgraded software version. Based on the data version identifier, a corresponding data change task can be created. This data change task indicates the target data source, allowing the data change task to be executed against the target data source, creating the task change record for that data version identifier, and thus obtaining the task change records for each data version identifier. The task change record can include one or more of the following information: task type, task data, data source type, data version identifier, and task change time. The task type includes query-type change tasks, file-type change tasks, data-type change tasks, and coding-type change tasks. The task data is determined according to the task type. For example, for query-type change tasks, the task data includes the query statement (such as an SQL statement); for file-type change tasks, the task data includes the file upload path information; and for coding-type change tasks, the task data includes the code block identifier, extended parameters, etc. The data source type is the business type corresponding to the data source, such as retrieval type, configuration type, etc.

[0069] In this embodiment of the invention, before creating a task change record for a data version identifier, the method further includes: obtaining the task execution result of the data change task; determining that the task execution result indicates that the data change task was successfully executed; wherein, the task change record includes a data source type corresponding to the target data source.

[0070] In this embodiment of the invention, the target data source can be a data storage location, such as a target database and its address. Based on the target data source, a corresponding data engine can be determined. Using the data engine, a data change task can be executed on the target data source, yielding the corresponding task execution result. The task execution result can indicate whether the data change task was executed successfully or failed. If the task execution result indicates successful execution, a task change record for that data version is created. If the task execution result indicates failed execution, an error message is returned, indicating the reason for the failure. Different data sources may use different data engines to operate different resources in different deployment environments, such as caches, message queues, and databases (e.g., MySQL, Oracle).

[0071] In embodiments of the present invention, such as Figure 3 As shown, creating a data change task based on the data version identifier includes:

[0072] Step S301: Determine the data change operation based on the data version identifier;

[0073] Step S302: Determine the task type based on the data change operation;

[0074] Step S303: Determine the target data source based on the task type;

[0075] Step S304: Create a data change task based on the task type and target data source.

[0076] In this embodiment of the invention, when creating a data change task based on a data version identifier, the data change operation is first determined based on the data version identifier. The data version identifier indicates the information of the upgraded data version. Since the upgraded software version indicates the function set, it can be determined whether a data upgrade is required based on the function set. If a data upgrade is required, the information of the upgraded data version may include the data upgrade requirement, i.e., the data change requirement, corresponding to the function set. Based on the data change requirement, the data change operation can be determined. The data change requirement indicates the information that needs to be changed. Based on the information that needs to be changed, the data change operation to be performed can be determined. The data change operation may include data table changes, field changes, data changes in the data table, index changes, etc., and may also include model file changes, corpus file changes, etc.

[0077] For example, in a dialogue system, i.e., an intelligent chatbot system, each dialogue system can create multiple intelligent robots according to different business scenarios. Each intelligent robot can be configured with different dialogue scripts, and each dialogue script includes multiple responses. Each intelligent robot and its corresponding multiple responses are stored in an answer data table. Each intelligent robot has a corresponding robot data table to store relevant information about that intelligent robot. The robot data table and the answer data table are linked through the intelligent robot's identifier. For example, in the first data version, the answer data table only includes the simple answers of that intelligent robot. In the second data version, it is necessary to add answer formats, such as adding carousel answers or multiple answer formats. At this time, it is necessary to add fields to distinguish different answer formats. At this time, the data in both the answer data table and the answer data table have changed. That is, the data change operation includes data table changes, field changes, and data changes in the data table.

[0078] In this embodiment of the invention, the task type can be determined based on the data change operation, which may include: if the data change operation indicates a database change operation, the task type is determined to be a data-related change task. The database can be a relational database or a non-relational database. For relational databases such as DDL and DLM, the data change operation can be a data table change, field change, data change, index change, etc., and the data-related change task is a query-related change, i.e., an SQL (Structured Query Language) change task. For non-relational databases such as ES and Redis, the data change operation can be an index change, data change, etc., and the task type is a data-related change task. If the data change operation indicates a model file change operation, the task type is determined to be a file-related change task. The model file is external data that the system depends on. Changes to the model file require the creation of a file-related change task, which depends on local storage or an object storage engine. If the data change operation indicates a change operation that modifies data or a data table in an coded manner, i.e., a data model change operation, the task type is determined to be a coding-related change task. If the modeling of existing data changes and requires complex changes, it can be achieved by creating a coding-related change task.

[0079] In this embodiment of the invention, after determining the task type, the associated target data source is determined based on the task type, and the corresponding data version identifier is also determined. Prior to this, data sources corresponding to different task types need to be pre-configured, so that the target data source corresponding to the task type can be determined based on the first deployment environment. After determining the target data source, a data change task is created based on the task type and the target data source. The task data can be determined based on the task type and the target data source; different task types correspond to different task data. For example, for an SQL-type change task, the task data is an SQL statement, which can indicate the target data source and the fields to be changed in the target data source. For a file-type change task, the task data can include storage path information, i.e., the location where the model file needs to be uploaded. For a coding-type change task, the task data can include the identifier of the code block, and may also include extended parameters corresponding to the code block. Then, the data change task is executed using the data engine corresponding to the target data source, so that a task change record for the data version is created after the data change task is successfully executed.

[0080] In embodiments of the present invention, such as Figure 4 As shown, based on the task change record of each data version identifier, the first data version corresponding to the first data version identifier is updated to the second data version corresponding to the second data version identifier, including:

[0081] Step S401: Determine each change task and the execution order of each change task based on the task change record of each data version identifier;

[0082] Step S402: Execute each change task according to the execution order to update the first data version to the second data version.

[0083] In this embodiment of the invention, corresponding change tasks can be created based on the task change records of each data version identifier. Specifically, the task change records of each data version identifier from other deployment environments are imported into the first deployment environment. Within the first deployment environment, corresponding change tasks are created based on these records, thereby creating various change tasks from the first data version to the second data version. The execution order of each change task can be determined based on the data version identifier or the time of the task change in the task table change record for each data version. By executing each change task according to the execution order, the first data version is progressively upgraded to the second data version. Efficient data upgrades are achieved by copying the task change records (i.e., the upgrade steps) for each data version.

[0084] In this embodiment of the invention, the data processing method can be implemented by a software system, which may include an application data layer, a data engine layer, and a version management layer. The application data layer includes a data change component, such as changes to relational databases, changes to non-relational databases, changes to model files, and changes to data relationships through coding. The data engine layer includes data operation engines corresponding to different data sources, used to operate different resources in different deployment environments. The version management layer is responsible for managing data versions, archiving task change records, etc.

[0085] The data processing method of this invention, upon receiving update information for a first software version, obtains the corresponding first data version identifier, while the update information indicates a second data version identifier. Then, it upgrades from the first data version to the second data version by acquiring the task change records for each data version identifier between the first and second data version identifiers. This method achieves data version updates and upgrades through the task change records of each data version identifier. By tracking data changes, it completely replicates the data upgrade steps, completing the data upgrade and effectively reducing the error rate of manual operations. This improves the efficiency and accuracy of data upgrades, ensures the consistency between data versions and software versions, and is beneficial for long-term, continuous data maintenance and management.

[0086] According to another aspect of the embodiments of the present invention, such as Figure 5 As shown, a data processing apparatus 500 is provided, comprising:

[0087] The first acquisition module 501, in response to receiving update information for the first software version, acquires a first data version identifier corresponding to the first software version; the update information indicates a second data version identifier;

[0088] The second acquisition module 502 acquires the task change record of each data version identifier between the first data version identifier and the second data version identifier;

[0089] The update module 503 updates the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier based on the task change record of each data version identifier.

[0090] In this embodiment of the invention, the second acquisition module 502 is further configured to: acquire the data source type corresponding to the first software version; acquire each data version identifier between the first data version identifier and the second data version identifier; and determine the task change record of each data version identifier according to the data source type.

[0091] In this embodiment of the invention, the second acquisition module 502 is further configured to: create a task change record for a data version identifier before acquiring the task change record for each data version identifier between the first data version identifier and the second data version identifier; the data version identifier has a corresponding software version;

[0092] The second acquisition module 502 is further configured to: in response to the detected software version creation instruction, create a data version identifier corresponding to the software version; create a data change task based on the data version identifier; the data change task indicates the target data source; and execute the data change task for the target data source to create a task change record for the data version identifier.

[0093] In this embodiment of the invention, the second acquisition module 502 is further configured to: acquire the task execution result of the data change task before creating the task change record of the data version identifier; determine that the task execution result indicates that the data change task was successfully executed; wherein, the task change record includes the data source type corresponding to the target data source.

[0094] In this embodiment of the invention, the second acquisition module 502 is further configured to: determine a data change operation based on a data version identifier; determine a task type based on a data change operation; determine a target data source based on the task type; and create a data change task based on the task type and the target data source.

[0095] In this embodiment of the invention, the second acquisition module 502 is further configured to: if the data change operation indicates a database change operation, determine the task type as a data-related change task; if the data change operation indicates a model file change operation, determine the task type as a file-related change task; if the data change operation indicates a change operation that modifies data or a data table in an encoded manner, determine the task type as an encoded change task.

[0096] In this embodiment of the invention, the update module 503 is further configured to: determine each change task and the execution order of each change task according to the task change record of each data version identifier; execute each change task according to the execution order, and update the first data version to the second data version.

[0097] According to another aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method provided by the present invention.

[0098] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the data processing method provided by the present invention.

[0099] Figure 6 An exemplary system architecture 600 is shown, in which a data processing method or data processing apparatus to which embodiments of the present invention can be applied is illustrated.

[0100] like Figure 6 As shown, system architecture 600 may include terminal devices 601, 602, and 603, a network 604, and a server 605. Network 604 serves as the medium for providing communication links between terminal devices 601, 602, and 603 and server 605. Network 604 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0101] Users can use terminal devices 601, 602, and 603 to interact with server 605 via network 604 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 601, 602, and 603, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0102] Terminal devices 601, 602, and 603 can be various electronic devices with displays and web browsing capabilities, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0103] Server 605 can be a server that provides various services, such as a backend management server that supports shopping websites browsed by users using terminal devices 601, 602, and 603 (for example only). The backend management server can analyze and process data such as received product information query requests, and feed back the processing results (such as target push information, product information - for example only) to the terminal devices.

[0104] It should be noted that the data processing method provided in the embodiments of the present invention is generally executed by server 605, and correspondingly, the data processing device is generally disposed in server 605.

[0105] It should be understood that Figure 6 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0106] The following is for reference. Figure 7 It shows a schematic diagram of the structure of a computer system 700 suitable for implementing a terminal device of the present invention. Figure 7 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0107] like Figure 7As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 702 or programs loaded from storage section 708 into random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the system 700. The CPU 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0108] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0109] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711. When the computer program is executed by central processing unit (CPU) 701, it performs the functions defined above in the system of this invention.

[0110] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0111] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0112] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor can be described as including a first acquisition module, a second acquisition module, and an update module. The names of these modules do not necessarily limit the module itself; for example, the first acquisition module can also be described as "a module that, in response to receiving update information for a first software version, acquires a first data version identifier corresponding to the first software version."

[0113] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs, which, when executed by the device, cause the device to include: in response to receiving update information for a first software version, acquiring a first data version identifier corresponding to the first software version; the update information indicating a second data version identifier; acquiring a task change record for each data version identifier between the first data version identifier and the second data version identifier; and updating the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier according to the task change record for each data version identifier.

[0114] According to the technical solution of this embodiment of the invention, the data processing method of this embodiment, upon receiving update information for a first software version, obtains the corresponding first data version identifier, while the update information indicates a second data version identifier; then, it upgrades from the first data version to the second data version by obtaining the task change record of each data version identifier between the first and second data version identifiers. This method achieves data version updates and upgrades through the task change record of each data version identifier. By tracking data changes, it completely replicates the data upgrade steps of the data version, completing the data upgrade, effectively reducing the error rate of manual operations, improving the efficiency and accuracy of data upgrades, ensuring the consistency between data versions and software versions, and facilitating long-term continuous data maintenance and management.

[0115] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of data processing, characterized by, The method comprises the following steps: in response to receiving update information for a first software version, obtaining a first data version identifier corresponding to the first software version; the update information indicates a second data version identifier; obtaining a task change record of each data version identifier between the first data version identifier and the second data version identifier; updating the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier according to the task change record of each data version identifier.

2. The method of claim 1, wherein, The method for obtaining the task change record of each data version identifier between the first data version identifier and the second data version identifier comprises the following steps: obtaining a data source type corresponding to the first software version; obtaining each data version identifier between the first data version identifier and the second data version identifier; determining the task change record of each data version identifier according to the data source type.

3. The method of claim 1, wherein, Before obtaining the task change record of each data version identifier between the first data version identifier and the second data version identifier, the method further comprises the following steps: creating a task change record of the data version identifier; the data version identifier has a corresponding software version; The method for creating the task change record of the data version identifier comprises the following steps: in response to monitoring a creation instruction of the software version, creating the data version identifier corresponding to the software version; creating a data change task according to the data version identifier; the data change task indicates a target data source; executing the data change task for the target data source to create the task change record of the data version identifier.

4. The method of claim 3, wherein, Before creating the task change record of the data version identifier, the method further comprises the following steps: obtaining a task execution result of the data change task; determining that the task execution result indicates that the data change task is executed successfully; wherein the task change record comprises a data source type corresponding to the target data source.

5. The method of claim 3, wherein, The method for creating a data change task according to the data version identifier comprises the following steps: determining a data change operation according to the data version identifier; determining a task type according to the data change operation; determining a target data source according to the task type; creating the data change task according to the task type and the target data source.

6. The method of claim 5, wherein, The method for determining a task type according to the data change operation comprises the following steps: if the data change operation indicates a change operation of a database, determining that the task type is a data type change task; if the data change operation indicates a change operation of a model file, determining that the task type is a file type change task; if the data change operation indicates a change operation of modifying data or a data table in an encoded manner, determining that the task type is an encoding type change task.

7. The method of claim 1, wherein, The method for updating the first data version corresponding to the first data version identifier to the second data version corresponding to the second data version identifier according to the task change record of each data version identifier comprises the following steps: determining each change task and an execution order of each change task according to the task change record of each data version identifier; executing each change task according to the execution order to update the first data version to the second data version.

8. An apparatus for data processing, characterized by The method comprises the following steps: The first obtaining module, in response to receiving update information for a first software version, obtains a first data version identifier corresponding to the first software version; the update information indicates a second data version identifier; The second obtaining module obtains a task change record of each data version identifier between the first data version identifier and the second data version identifier; The updating module updates a first data version corresponding to the first data version identifier to a second data version corresponding to the second data version identifier according to the task change record of each data version identifier.

9. An electronic device, comprising: comprising: one or more processors; a memory device for storing one or more programs, when the one or more programs are executed by the one or more processors, so that the one or more processors implement the method as claimed in any one of claims 1-7.

10. A computer readable medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the method as claimed in any one of claims 1-7. The program is executed by the processor to implement the method as claimed in any one of claims 1-7.

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