Data export strategy generation method and device, equipment and medium

Abstract

The invention discloses a data export strategy generation method and device, equipment and a medium. The invention relates to the technical field of artificial intelligence. The method comprises the steps of obtaining a current parameter configuration variable and a current scene demand corresponding to a target data export task; determining a target data processing strategy based on the current scene demand, and determining a target parameter template in a preset parameter template library; performing data processing on the current parameter configuration variable based on a target data processing strategy to obtain target parameter configuration data corresponding to the target data export task; and performing filling processing on the target parameter configuration data based on the target parameter template to obtain a basic data export strategy corresponding to the target data export task, and summarizing and processing each basic data export strategy to obtain a target data export strategy corresponding to the target data export task. According to the technical scheme, different database data can be exported according to different demand scenes, and the adaptability and accuracy of exported data are improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of artificial intelligence technology, and in particular to a data export strategy generation method and device, equipment and medium. BACKGROUND

[0002] In the field of information technology, as the core of data storage and management, the export of database data is a common requirement in daily operation and maintenance, data analysis, system integration and report generation scenarios. Therefore, how to export data from the database becomes very important.

[0003] The existing data export technology usually adopts the original data export method, which directly and row by row outputs the original data in the database after the user selects the target data table or query result through the export tool.

[0004] However, the original data export method has obvious limitations and inadaptability in many practical application scenarios, and needs to rely on the technical ability of the user for post-processing, which not only is inefficient, but also is difficult to guarantee the accuracy and consistency of the data. Therefore, how to improve the adaptability and accuracy of the exported data is a problem to be solved at present. SUMMARY

[0005] Embodiments of the present application provide a data export strategy generation method, device, equipment and medium to solve the problem of low adaptability and accuracy of database data export.

[0006] In a first aspect, the embodiments of the present application provide a data export strategy generation method, comprising:

[0007] Obtaining the current parameter configuration variable and the current scene requirement corresponding to the target data export task;

[0008] Determining the target data processing strategy corresponding to the target data export task based on the current scene requirement, and determining the target parameter template corresponding to the target data export task in the preset parameter template library;

[0009] Performing data processing on the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task;

[0010] Performing filling processing on the target parameter configuration data based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task, and processing each basic data export strategy to obtain the target data export strategy corresponding to the target data export task.

[0011] In a second aspect, the embodiments of the present application also provide a data export strategy generation device, comprising:

[0012] a data acquisition module, configured to acquire a current parameter configuration variable corresponding to a target data export task and a current scene requirement;

[0013] a template matching module, configured to determine a target data processing strategy corresponding to the target data export task based on the current scene requirement, and determine a target parameter template corresponding to the target data export task in a preset parameter template library;

[0014] a data processing module, configured to perform data processing on the current parameter configuration variable based on the target data processing strategy to obtain target parameter configuration data corresponding to the target data export task;

[0015] a strategy generation module, configured to perform filling processing on the target parameter configuration data based on the target parameter template to obtain a basic data export strategy corresponding to the target data export task, and aggregate and process each basic data export strategy to obtain a target data export strategy corresponding to the target data export task.

[0016] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the data export strategy generation method according to any of the embodiments of the present application when executing the program.

[0017] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and the program is executable on a processor to implement the data export strategy generation method according to any of the embodiments of the present application.

[0018] In a fifth aspect, a computer program product is provided, which includes a computer program, and the computer program is executable on a processor to implement the data export strategy generation method according to any of the embodiments of the present application.

[0019] In the embodiment of the present application, the current parameter configuration variable and the current scene requirement corresponding to the target data export task are obtained. Then, the target data processing strategy corresponding to the target data export task is determined based on the current scene requirement, and the target parameter template corresponding to the target data export task is determined in the preset parameter template library. Further, the target parameter configuration data corresponding to the target data export task is obtained by performing data processing on the current parameter configuration variable based on the target data processing strategy. Finally, the target parameter template is filled with the target parameter configuration data to obtain the basic data export strategy corresponding to the target data export task, and the target data export strategy corresponding to the target data export task is obtained by processing each basic data export strategy. Since different parameter templates are adapted according to different requirement scenes to export different database data, the adaptability and accuracy of the exported data are improved. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0021] Figure 1 A flowchart of a data export strategy generation method provided by the embodiment of the present application is shown in the figure.

[0022] Figure 2 A flowchart of another data export strategy generation method provided by the embodiment of the present application is shown in the figure.

[0023] Figure 3 A flowchart of an optional data export strategy generation method provided by the embodiment of the present application is shown in the figure.

[0024] Figure 4 A structural schematic diagram of a data export strategy generation device provided by the embodiment of the present application is shown in the figure.

[0025] Figure 5 A structural schematic diagram of an electronic device for implementing the data export strategy generation method of the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0026] The present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application. In addition, it should be noted that only the parts related to the present application are shown in the drawings for convenience of description, but not all the structures.

[0027] It should be noted that similar labels and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", "target" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. The acquisition, storage, use, processing and the like of data in the technical solution of the present application comply with the relevant provisions of national laws and regulations. It should be noted that in the embodiments of the present application, some existing industry solutions such as software, components, models and the like may be mentioned, which should be considered as exemplary, and the purpose is only to illustrate the feasibility of the implementation of the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the related content of the solution.

[0028] Figure 1 A flowchart of a data export strategy generation method provided by an embodiment of the present application. The embodiment can be applicable to the adaptive export of data in a database. The method can be executed by a data export strategy generation device, which can be realized in the form of hardware and / or software. For example, it can be configured in an electronic device. As shown in the figure, the method comprises: Figure 1

[0029] S101, acquiring a current parameter configuration variable corresponding to a target data export task and a current scene requirement.

[0030] The data export task can refer to an executable object encapsulating complete data export logic and configuration. Generally, the data export task can include data source, extraction object and export location information. The data source can specify which database or data table to obtain data from. The extraction object can specify the export data to be exported. The export location can specify the storage path of the export data. The target data export task can refer to the data export task to be implemented at the current time. Generally, the target data export task can be determined according to actual application requirements, which is not limited in the embodiments of the present application. The parameter configuration variable can refer to a variable quantity that is not determined in the task definition, but is transmitted from the outside when the task is executed each time. For example, the parameter configuration variable can be a character used to uniformly identify parameters of the same attribute of the database. The current parameter configuration variable can refer to the parameter configuration variable corresponding to the target data export task.

[0031] ​Optionally, the current parameter configuration variable includes: a current table configuration variable, a current table field configuration variable and a current table condition configuration variable. A table can refer to a basic unit of storing data in a database. Generally, a table can be a two-dimensional structure composed of rows and columns, and the table defines an entity of storing data. Each table is generally used to store similar information. The table configuration variable can refer to the parameter configuration variable corresponding to the database table. For example, the table configuration variable can be represented as table. The current table configuration variable can refer to the table configuration variable corresponding to the target data export task at the current time. A table field can refer to the attribute or characteristic of the database table. Generally, a table field is a column in the database table, and each table field has a name and a data type, which specifies the type and meaning of the stored data. The table field configuration variable can refer to the parameter configuration variable corresponding to the table field in the database. For example, the table field configuration variable can be represented as char. The current table field configuration variable can refer to the table field configuration variable corresponding to the target data export task at the current time. A table condition can refer to a rule for limiting the export logic of the exported data. For example, the table condition can be used to filter which rows of data in the table should be taken out or exported. The table condition configuration variable can refer to the parameter configuration variable corresponding to the table condition in the database. For example, the table condition configuration variable can be represented as condition. The current table condition configuration variable can refer to the table condition configuration variable corresponding to the target data export task at the current time.

[0032] The scene requirement can refer to a specific data processing application scenario corresponding to the data export task. The current scene requirement can refer to the scene requirement corresponding to the target data export task at the current time. Optionally, the current scene requirement includes: a table field export scene, a field value export scene and a table condition export scene. The table field export scene can refer to a scene of processing the table field corresponding to the target data export task. The field value can refer to the specific data content stored in the table field. Generally, the field value can be the data in each cell of each column in the table field. The field value export scene can refer to a scene of processing the table field value corresponding to the target data export task. The table condition export scene can refer to a scene of processing the table condition corresponding to the target data export task.

[0033] S102, determining a target data processing strategy corresponding to the target data export task based on the current scene requirement, and determining a target parameter template corresponding to the target data export task in a preset parameter template library.

[0034] The data processing strategy can refer to a pre-set strategy for adaptively adjusting data. Generally, the data processing strategy mainly includes a strategy for data adjustment of field values. The target data processing strategy can refer to a data processing strategy corresponding to the target data export task under the current scenario requirement. Optionally, if the current scenario requirement is a field value export scenario, the target data processing strategy includes a time update strategy, a unique identifier matching strategy, a global replacement strategy, and a local replacement strategy. The time update strategy can refer to a rule for defining a real-time update process of time field values. The unique identifier can refer to a code for uniquely and non-repeatedly identifying data content. For example, in a database for storing contract data, the unique identifier can be a contract code. The unique identifier matching strategy can refer to a rule for defining the export logic of the unique identifier. The global replacement strategy can refer to a rule for defining the data volume of the exported data. The local replacement strategy can refer to a rule for defining the data content of the exported data.

[0035] The parameter template can refer to a pre-set template for standardized storage of each type of parameter configuration variable. Generally, different types of parameter configuration variables correspond to different parameter templates. The pre-set parameter template library can refer to a pre-set database for storing each parameter template corresponding to different types of parameter configuration variables. It is worth noting that in the embodiments of the present application, different data export tasks can share the same pre-set parameter template library. The target parameter template can refer to a parameter template in the pre-set parameter template library matched with the target data export task. For example, the target parameter template can be a table field template, a table field value template, and a table condition template.

[0036] S103, data processing of the current parameter configuration variable based on the target data processing strategy to obtain target parameter configuration data corresponding to the target data export task.

[0037] The parameter configuration data can refer to configuration data obtained after data processing according to the data processing strategy. The target parameter configuration data can refer to parameter configuration data corresponding to the target data export task.

[0038] S104, filling processing of the target parameter configuration data based on the target parameter template to obtain a basic data export strategy corresponding to the target data export task, and summarizing processing of each basic data export strategy to obtain a target data export strategy corresponding to the target data export task.

[0039] The data export strategy can be a rule for limiting a data export process in a database. For example, the data export strategy can be a query statement or an insert statement indicating the data export process. The basic data export strategy can refer to a data export strategy corresponding to each target parameter configuration data obtained initially. Generally, the number of basic data export strategies corresponding to the target data export task is consistent with the number of current scene requirements, and one current scene requirement corresponds to one basic data export strategy. The target data export strategy can refer to a final data export strategy obtained by splicing each basic data export strategy corresponding to the same target data export task.

[0040] In the embodiment of the application, the current parameter configuration variable corresponding to the target data export task and the current scene requirement are obtained. Then, the target data processing strategy corresponding to the target data export task is determined based on the current scene requirement, and the target parameter template corresponding to the target data export task is determined in the preset parameter template library. Further, the target parameter configuration data corresponding to the target data export task is obtained by performing data processing on the current parameter configuration variable based on the target data processing strategy. Finally, the target parameter configuration data is filled in the target parameter template to obtain the basic data export strategy corresponding to the target data export task, and the target data export strategy corresponding to the target data export task is obtained by processing the basic data export strategies. Since different parameter templates are adapted according to different requirement scenes to export different database data, the adaptability and accuracy of the exported data are improved.

[0041] Figure 2 The flowchart of another method for generating a data export strategy provided in the embodiment of the application is provided. The embodiment is based on the above-mentioned embodiment and is refined. In the embodiment, the "obtaining the current parameter configuration variable corresponding to the target data export task" is refined, and can specifically include: obtaining the current data export requirement corresponding to the target data export task, and determining the basic parameter configuration variable corresponding to the target data export task based on the current data export requirement; and declaring the processing of the basic parameter configuration variable to obtain the current parameter configuration variable corresponding to the target data export task. As shown in FIG. 8, the method includes: Figure 2

[0042] S201, obtaining the current data export requirement corresponding to the target data export task, and determining the basic parameter configuration variable corresponding to the target data export task based on the current data export requirement.

[0043] ​The data export requirement can refer to information for comprehensively describing the exported data. Generally, the data export requirement can specify information such as where to export data from, what to export, how to process data, in what form, who to deliver, and the like. The current data export requirement can refer to a data export requirement established at the current time. Generally, the current data export requirement can be determined according to the business target of a business personnel in an actual application scenario. The basic parameter configuration variable can refer to a parameter configuration variable obtained initially. For example, the description information contained in the current data export requirement can be taken as the basic parameter configuration variable. Generally, the description information of the same attribute feature can be numbered and sorted as the basic parameter configuration variable. That is, the description information of the same table is represented by the same character and is uniformly numbered and sorted, the description information of the same table field is represented by the same character and is uniformly numbered and sorted, the description information of the same table field value is represented by the same character and is uniformly numbered and sorted, and the description information of the same table condition is represented by the same character and is uniformly numbered and sorted. For example, taking the current data export requirement as an example of exporting the field values under the fields a and b in table A, the basic parameter configuration variable can be determined as table 1, field 1, field 2, field value 1, and field value 2.

[0044] It is worth noting that the character representation corresponding to the description information of different attribute features should be different, the character representation corresponding to the description information of the same attribute feature should be consistent, and the numbering corresponding to each description information under the same attribute feature should be unique.

[0045] S202, declaring processing the basic parameter configuration variable to obtain a current parameter configuration variable corresponding to a target data export task.

[0046] The declaration processing can refer to an operation for standardizing the configuration of the basic parameter configuration variable. Generally, the declaration processing can create a formal and structured input interface for the data export task, which is the cornerstone of professionalization, automation, security, and ease of use of the data export process. For example, taking the above example as an example, the basic parameter configuration variable is table 1, field 1, field 2, field value 1, and field value 2, and the current parameter configuration variable obtained by using the keyword character to declare and process the basic parameter configuration variable can be table 1, char 1, char 2, value 1, and value 2.

[0047] Specifically, after determining the current data export requirement corresponding to the target data export task, the current data export requirement can be parsed first to determine various description information contained in the current data export requirement, and the description information is configured as a basic parameter variable. Then, the basic parameter variable is declared to obtain the current parameter configuration variable corresponding to the target data export task. In this way, by declaring specific data content as a variable form, a systematic object can be provided for the subsequent data export process, and an effective basis can be provided for the subsequent data processing operation.

[0048] S203, acquire the current scene requirement corresponding to the target data export task.

[0049] S204, determine the target data processing strategy corresponding to the target data export task based on the current scene requirement, and determine the target parameter template corresponding to the target data export task in the preset parameter template library.

[0050] Specifically, after obtaining the current parameter configuration variable corresponding to the target data export task, the current scene requirement corresponding to the target data export task can also be acquired. Then, the target data processing strategy corresponding to the target data export task is determined according to the current scene requirement, and the target parameter template corresponding to the target data export task is matched in the preset parameter template library according to the current scene requirement. For example, taking the field value export scene as an example, the target data processing strategy including the time update strategy, the unique identifier matching strategy, the global replacement strategy and the local replacement strategy can be determined according to the field value export scene, and the table field value template is determined as the target parameter template in the preset parameter template library. In this way, an effective basis is provided for subsequent operations.

[0051] It is worth noting that in the embodiment of the application, if the current scene requirement is a table field export scene, a table field template can be directly determined as the target parameter template in the preset parameter template library without the process of determining the target data processing strategy. Similarly, if the current scene requirement is a table condition export scene, a table condition template can be directly determined as the target parameter template in the preset parameter template library without the process of determining the target data processing strategy.

[0052] In an optional embodiment, before the target data processing strategy corresponding to the target data export task is determined based on the current scene requirement, and the target parameter template corresponding to the target data export task is determined in the preset parameter template library, the method further includes:

[0053] Step a1, acquiring the original export statement corresponding to the target data export task.

[0054] The export statements can refer to standard languages and instructions for interacting with a relational database. For example, the export statements can be Structured Query Language (SQL) statements. Generally, the export statements can include query statements and insert statements. Query statements are used to obtain data from a database, but do not change the data itself. Insert statements are used to add new records to a target database table. The original export statements can refer to export statements generated according to the common statement structures in the prior art. Generally, the original export statements can include original query statements and original insert statements.

[0055] For example, taking contract storage as a real-world application scenario, the data table in the target data export task is shown in Table 1 below. This table contains the following identifiers: ID, Contract Number (CONTNO), Bank Identifier (BANKID), Business Kind (BUSIKIND), Branch Identifier (BRANID), Value (VALUE), and Last Deal Date (LASTDEALDATE). ID is the primary key of the table, used to uniquely identify each record. CONTNO uniquely identifies a contract or agreement and can serve as a unique identifier. BANKID identifies a specific financial institution and is usually a foreign key, linked to a financial institution information table. BUSIKIND distinguishes different business types. BRANID identifies a specific branch of a financial institution and is usually a foreign key, linked to a branch table. VALUE represents the core value associated with this record. LASTDEALDATE records the date of the last business operation related to this contract. The target data export task includes the following current data export requirement: to export the records in the table with the field value "6000", "6001", "6002" and "6003" under the BUSIKIND field to the target table. The original query statement in the original export statement can be: `Select CONTNO,BANKID,BUSIKIND,BRANID,VALUE,LASTDEALDATE from table where BUSIKIND in ('6000','6001','6002','6003')`; correspondingly, the original insert statement can be: `insert into table (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE) values('10001235456','10331001','6000','000','11231', '2024-11-6 16:09')`; `insertinto table (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)`. values('10001235457','10331002','6000','000','11232', '2024-11-6 16:09');insert intotable (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)values('10001235458','10331003','6001','100','11233','2024-11-6 16:09'); insert intotable (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)values('10001235459','10331004','6001','000','11234','2024-11-6 16:09');insert intotable (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)values('10001235460','10331005','6002','200','11235','2024-11-6 16:09'); insert intotable (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)values('10001235461','10331006','6003','300','11236','2024-11-6 16:09'); insert intotable (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)values('10001235462','10331007','6000','000','11237','2024-11-6 16:09'); insert intotable (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)values('10001235463','10331008','6000','000','11238','2024-11-6 16:09'). ;

[0056] Table 1. Database tables corresponding to the target data export task

[0057]

[0058] It is worth noting that, in the embodiments of the present invention, the data tables in the target data export task are all authorized data tables that have been legally obtained under this application scenario, and the embodiments of the present invention will not elaborate on this further.

[0059] Step a2: Based on preset variable extraction rules, the original exported statement is segmented to determine the set of statement segments corresponding to the target data export task.

[0060] Here, the preset variable extraction rules refer to pre-defined strategies for identifying variable content in the original exported statement. For example, preset variable extraction rules can be constructed based on keywords. Continuing with the example above, the preset variable extraction rules could be to identify the `where` clause in the original query statement, identify `insert intotable` and `values` clauses in the original insert statement, and segment the statement according to the keywords, taking the segment after the keyword as the segmentation result corresponding to that keyword. Statement segmentation refers to the segmentation result obtained after segmenting the original exported statement according to the preset variable extraction rules. The statement segment set refers to the set of all statement segments corresponding to the same original exported statement.

[0061] For example, continuing from the above example, the original query statement in the original export statement is: `Select CONTNO,BANKID,BUSIKIND,BRANID,VALUE,LASTDEALDATE from table where BUSIKIND in ('6000','6001','6002','6003')`, and the original insert statement is: `insert into table (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE) values ​​('10001235456','10331001','6000','000','11231', '2024-11-6 16:09')`. The preset variable extraction rule is to identify the `where` clause in the original query statement and the `insert into` clause in the original insert statement. Using the keywords `table` and `values`, and segmenting the statement according to the position of the keyword, taking the segment following the keyword as the segmentation result corresponding to that keyword, the corresponding statement segments could be: `insert into (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE), values ​​('10001235456','10331001','6000','000','11231', '2024-11-6 16:09')` and `where busikind in ('6000','6001','6002','6003')`.

[0062] Step a3: Extract variables from the target statement segments in the statement segmentation set based on preset keyword identifiers, and determine the original parameter configuration variables corresponding to the target statement segments.

[0063] The preset keyword identifier can refer to pre-defined symbols used for summarizing and identifying sentence segments. For example, the preset keyword identifier can be an identifier consistent with the keywords used for sentence segmentation in the preset variable extraction rules. The target sentence segment can refer to the selected sentence segment for variable extraction. For example, the target sentence segment can be any sentence segment in the set of sentence segments.

[0064] Here, the original parameter configuration variable can refer to the variable obtained from the initial configuration. For example, continuing from the previous example, if the preset keyword identifier is "where", and the target statement segment corresponding to this preset keyword identifier is: `where busikind in('6000','6001','6002','6003')`, then the original parameter configuration variable corresponding to this target statement segment can be determined as: `condition`. Similarly, if the preset keyword identifier is "insert into table", and the target statement segment corresponding to this preset keyword identifier is: `insert into table (CONTNO,BANKID,BUSIKIND,BRANID, VALUE,LASTDEALDATE)`, then the original parameter configuration variable corresponding to this target statement segment can be determined as `char`. If the preset keyword identifier is values, and the target statement segment corresponding to the preset keyword identifier is values ​​('10001235456','10331001','6000','000','11231', '2024-11-6 16:09'), then the original parameter configuration variable corresponding to the target statement segment can be determined as value.

[0065] Step a4: Combine and process the target statement segments and their corresponding original parameter configuration variables to obtain the basic parameter templates corresponding to the target data export task, and summarize and process each basic parameter template to obtain a preset parameter template library.

[0066] The basic parameter template refers to the parameter template obtained by replacing the corresponding positions in the target statement segment using the original parameter configuration variables. For example, continuing from the above example, the basic parameter template can be: insert intotable(char), values(value), and where condition.

[0067] Specifically, before generating the data export strategy, the corresponding raw export statements can be generated based on the target data export task. Then, the raw export statements are segmented according to preset variable extraction rules to determine the set of statement segments corresponding to the target data export task. Further, variables are extracted from the target statement segments in the statement segment set based on preset keyword identifiers to determine the original parameter configuration variables corresponding to the target statement segments. Finally, the original parameter configuration variables are filled into the corresponding target statement segments to obtain the basic parameter templates corresponding to the target data export task. These basic parameter templates are then aggregated and processed to obtain a preset parameter template library. This provides a valid foundation for the subsequent data export strategy generation process, resulting in variable-transformed parameter templates.

[0068] It is worth noting that, in this embodiment of the invention, the construction process of each basic parameter template in the preset parameter template library only needs to be executed once; that is, each target data export task shares the same preset parameter template library. This improves the generation efficiency of data export strategies.

[0069] S205. If the target data processing strategy is a time update strategy, then obtain the current system timestamp and the base timestamp corresponding to the current parameter configuration variable.

[0070] The system timestamp can refer to a numerical or string representation used to uniquely identify a specific moment in a computer system. The current system timestamp refers to the system timestamp corresponding to the current moment. The base timestamp refers to the timestamp contained in the current parameter configuration variable. Typically, the base timestamp can be a timestamp recorded in a database table.

[0071] S206. Update the base timestamp based on the current system timestamp to obtain the target parameter configuration data corresponding to the target data export task.

[0072] Specifically, in the scenario of exporting field values, if the target data processing strategy is a time-update strategy, the current system timestamp corresponding to the computer system can be obtained first, and the base timestamp in the current parameter configuration variable can be determined. Then, the base timestamp is updated using the current system timestamp to obtain the target parameter configuration data corresponding to the target data export task. This solves the requirement that the timestamp field of the target database table should use real-time time, providing a valid foundation for subsequent data processing.

[0073] For example, as shown in Table 1 above, in the scenario of exporting field values, if the target data processing strategy is a time update strategy and the current system timestamp is November 6, 2024, then the base timestamp corresponding to the current parameter configuration variable can be determined, that is, the field value under the field LASTDEALDATE, and the current system timestamp can be used to perform time update to obtain the database table under the time update strategy as shown in Table 2.

[0074] Table 2 Database tables under the time update strategy

[0075]

[0076] S207. If the target data processing strategy is a unique identifier matching strategy, then obtain the target unique identifier set corresponding to the target data export task and the current unique identifier contained in the current parameter configuration variable.

[0077] Here, the target unique identifier can refer to the unique identifier that needs to be stored in the exported data. The target unique identifier set can refer to the set of all target unique identifiers in the target database where the exported data is stored. The current unique identifier can refer to the unique identifier contained in the current parameter configuration variable. For example, as shown in Table 1 above, the current unique identifier can be CONTNO.

[0078] S208. Based on the target unique identifier set, perform data matching on the current unique identifier to generate a data matching result, and process the current unique identifier based on the data matching result to obtain the target parameter configuration data corresponding to the target data export task.

[0079] The data matching result can refer to the matching result obtained after matching the target unique identifier set with the current unique identifier. For example, the data matching result can be a null value or a serial number corresponding to a unique identifier in the target unique identifier set that matches the current unique identifier, such as an ID. The processing can refer to the operation of adapting and adjusting the serial number of the current unique identifier. For example, if the data matching result is a null value, the processing can be an operation of adding the total number of serial numbers in the target unique identifier set as an offset to the serial number of the current unique identifier as a new serial number for the current unique identifier. If the data matching result is a specific serial number, the processing can be an operation of adjusting the serial number of the current unique identifier to match the specific serial number of the data matching result.

[0080] For example, following Table 2 above, in the scenario of exporting field values, if a target database table is used to store the exported data, as shown in Table 3 below. Taking the current unique identifier as 10001235456 as an example, by matching the target unique identifier set with the current unique identifier, the data matching result is null. This indicates that the target database table does not contain the current unique identifier. If the data is exported as is, the field value corresponding to the current unique identifier 10001235456 will be imported into the unique identifier 10003335125, resulting in data corruption. Therefore, it is necessary to process the current unique identifier according to the target unique identifier set to ensure the accuracy of the data export process.

[0081] Table 3. One type of target database table corresponding to the target data export task.

[0082]

[0083] Specifically, in the scenario of exporting field values, if the target data processing strategy is a unique identifier matching strategy, the set of target unique identifiers corresponding to the target data export task can be obtained first, and the current unique identifier contained in the current parameter configuration variable can be determined. Then, the current unique identifier is used to search for data in the set of target unique identifiers to obtain the data matching result. Finally, based on the data matching result, the current unique identifier is processed to obtain the target parameter configuration data corresponding to the target data export task. This solves the problem of the target database table not containing the current unique identifier, providing a valid foundation for subsequent data processing.

[0084] S209. If the target data processing strategy is a global replacement strategy, then the current parameter configuration variable is marked as the target parameter configuration data corresponding to the target data export task.

[0085] Specifically, in the scenario of exporting field values, if the target data processing strategy is a global replacement strategy, then all current parameter configuration variables can be directly marked as the target parameter configuration data corresponding to the target data export task. This ensures that all data to be imported into the target database can replace the corresponding fields in the target database table, providing a solid foundation for subsequent data processing.

[0086] For example, following the example above and as shown in Table 2, in the scenario of exporting field values, if the target data processing strategy is a global replacement strategy, another target database table for storing the exported data is shown in Table 4 below. Then, all field values ​​corresponding to the BUSIKIND, BRANID, and VALUE fields in Table 2 can be imported into the target database table to completely replace the field values ​​corresponding to the unique identifiers in the target database table that correspond to the BUSIKIND, BRANID, and VALUE fields in Table 2, thereby ensuring data consistency.

[0087] Table 4. Another target database table corresponding to the target data export task.

[0088]

[0089] S210. If the target data processing strategy is a local replacement strategy, then the current parameter configuration variable is modified based on the preset data change conditions to obtain the target parameter configuration data corresponding to the target data export task.

[0090] The preset data change conditions refer to pre-defined rules used to limit the process of changing field values. Typically, the preset data change conditions can be determined based on actual application needs; this embodiment of the invention does not impose specific limitations on this. For example, a preset data change condition could be to modify the field values ​​of the remaining fields corresponding to one or more fields to other values. For instance, as shown in Table 2 above, a preset data change condition could be to modify the value field corresponding to busikind=6000 and braid=000 to 21231.

[0091] Specifically, in the scenario of exporting field values, if the target data processing strategy is a partial replacement strategy, preset data change conditions can be used to modify the current parameter configuration variables to obtain the target parameter configuration data corresponding to the target data export task. This ensures that the exported data meets the data change requirements, providing a valid foundation for subsequent data processing.

[0092] It is worth noting that, in this embodiment of the invention, if the current scenario requires exporting table fields or field values, then there is no need to perform the target data processing strategy; the current parameter configuration variable can be directly marked as the target parameter configuration data. Furthermore, the execution flow of the time update strategy, unique identifier matching strategy, global replacement strategy, and local replacement strategy can be executed in parallel or sequentially; this embodiment of the invention does not impose specific limitations on this.

[0093] S211. Based on the target parameter template, the target parameter configuration data is populated to obtain the basic data export strategy corresponding to the target data export task, and the basic data export strategies are summarized and processed to obtain the target data export strategy corresponding to the target data export task.

[0094] Specifically, after obtaining the target parameter configuration data and corresponding target parameter template for the target data export task, the target parameter template can be used to populate the target parameter configuration data to obtain the basic data export strategy for the target data export task. Then, the various basic data export strategies are concatenated to obtain the target data export strategy for the target data export task. Thus, the final executable data export strategy is obtained. For example, continuing from the previous example, if the target parameter configuration data for the target data export task is char1, char2, char3, value1, value2, value3, and condition1, and the corresponding target parameter template is: insert into table(char), values(value), and where condition, then a basic data export strategy of the form: insert into table(char1, char2, char3), values(value1, value2, value3), and where condition1 can be generated. Finally, the various basic data export strategies are concatenated to obtain a target data export strategy of the form: insert into table(char1, char2, char3) values(value1, value2, value3) where condition1.

[0095] It is worth noting that, in this embodiment of the invention, the target parameter configuration data value1, value2, and value3 are configuration parameters processed by the target data processing strategy. If the execution flow of the time update strategy, the unique identifier matching strategy, the global replacement strategy, and the local replacement strategy is executed in parallel, then after generating each target parameter configuration data separately and filling the target parameter configuration data using the target parameter template, the results after filling need to be assembled, thereby obtaining the basic data export strategy corresponding to the field value export scenario.

[0096] S212. Dynamically execute the target data export strategy to obtain the target export data corresponding to the target data export task.

[0097] Among them, the target exported data can refer to the database data exported after executing the target data export strategy.

[0098] Specifically, after obtaining the target data export strategy, this strategy can be dynamically executed. This yields the target export data corresponding to the target data export task, providing a valid foundation for subsequent operations.

[0099] In this embodiment of the invention, the current data export requirement corresponding to the target data export task is obtained, the basic parameter configuration variables corresponding to the target data export task are determined based on the current data export requirement, and the processing of the basic parameter configuration variables is declared to obtain the current parameter configuration variables corresponding to the target data export task. Further, the current scenario requirement corresponding to the target data export task is obtained, the target data processing strategy corresponding to the target data export task is determined based on the current scenario requirement, and the target parameter template corresponding to the target data export task is determined in the preset parameter template library. If the target data processing strategy is a time update strategy, the current system timestamp and the basic timestamp corresponding to the current parameter configuration variables are obtained, and the basic timestamp is updated based on the current system timestamp to obtain the target parameter configuration data corresponding to the target data export task. If the target data processing strategy is a unique identifier matching strategy, the target unique identifier set corresponding to the target data export task and the current unique identifier contained in the current parameter configuration variables are obtained. Data matching is performed on the current unique identifier based on the target unique identifier set to generate a data matching result, and the current unique identifier is processed based on the data matching result to obtain the target parameter configuration data corresponding to the target data export task. If the target data processing strategy is a global replacement strategy, the current parameter configuration variable is marked as the target parameter configuration data corresponding to the target data export task. If the target data processing strategy is a local replacement strategy, the current parameter configuration variable is modified based on preset data change conditions to obtain the target parameter configuration data corresponding to the target data export task. Then, the target parameter configuration data is populated based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task, and the various basic data export strategies are summarized to obtain the target data export strategy corresponding to the target data export task. Finally, the target data export strategy is dynamically executed to obtain the target exported data corresponding to the target data export task. Because different parameter templates are adapted to different requirement scenarios to export different database data, the adaptability and accuracy of the exported data are improved.

[0100] Figure 3This is a flowchart illustrating an optional data export strategy generation method provided by an embodiment of the present invention. Specifically, firstly, the current data export requirements and current scenario requirements corresponding to the target data export task are obtained, and basic parameter configuration variables corresponding to the target data export task are determined based on the current data export requirements. Next, the basic parameter configuration variables are processed to obtain the current parameter configuration variables corresponding to the target data export task. Then, the current scenario requirements are judged. If the current scenario requirement is a table field export scenario, the current parameter configuration variables are marked as target parameter configuration data. The table field template corresponding to the table field export scenario is determined from a preset parameter template library, and the target parameter configuration data is populated using the table field template to obtain the table field export strategy corresponding to the target data export task. If the current scenario requirement is a table condition export scenario, the current parameter configuration variables are marked as target parameter configuration data. The table condition template corresponding to the table condition export scenario is determined from a preset parameter template library, and the target parameter configuration data is populated using the table condition template to obtain the table condition export strategy corresponding to the target data export task. If the current scenario requires exporting field values, the corresponding table field value template is determined from the preset parameter template library, and the target data processing strategy for the target data export task is determined according to the current scenario requirements. If the target data processing strategy is a time update strategy, the current system timestamp and the base timestamp corresponding to the current parameter configuration variable are obtained, and the base timestamp is updated based on the current system timestamp to obtain the target parameter configuration data corresponding to the target data export task. If the target data processing strategy is a unique identifier matching strategy, the target unique identifier set corresponding to the target data export task and the current unique identifier contained in the current parameter configuration variable are obtained. Data matching is performed on the current unique identifier based on the target unique identifier set to generate a data matching result, and the current unique identifier is processed based on the data matching result to obtain the target parameter configuration data corresponding to the target data export task. If the target data processing strategy is a global replacement strategy, the current parameter configuration variable is marked as the target parameter configuration data corresponding to the target data export task. If the target data processing strategy is a local replacement strategy, the current parameter configuration variable is modified based on preset data change conditions to obtain the target parameter configuration data corresponding to the target data export task. Next, the table field value templates are used to populate the configuration data for each target parameter, resulting in table field value export sub-strategies. These sub-strategies are then assembled to obtain the table field value export strategy corresponding to the target data export task. Further, the table field export strategy, table field value export strategy, and table condition export strategy are sequentially concatenated according to a pre-defined aggregation method to obtain the target data export strategy corresponding to the target data export task. The pre-defined aggregation method can be a built-in database aggregation method; this embodiment of the invention does not impose specific limitations on it.Finally, the target data export strategy is dynamically executed to obtain the target exported data corresponding to the target data export task.

[0101] Figure 4 This is a schematic diagram of a data export strategy generation apparatus provided in an embodiment of the present invention. This apparatus can execute the data export strategy generation methods involved in the above embodiments. The apparatus can be implemented in software and / or hardware, such as... Figure 4 As shown, the data export strategy generation device specifically includes: a data acquisition module 310, a template matching module 320, a data processing module 330, and a strategy generation module 340.

[0102] Among them, the data acquisition module 310 is used to acquire the current parameter configuration variables and current scenario requirements corresponding to the target data export task;

[0103] The template matching module 320 is used to determine the target data processing strategy corresponding to the target data export task based on the current scenario requirements, and to determine the target parameter template corresponding to the target data export task in the preset parameter template library.

[0104] Data processing module 330 is used to process the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task;

[0105] The strategy generation module 340 is used to fill the target parameter configuration data based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task, and to summarize and process each basic data export strategy to obtain the target data export strategy corresponding to the target data export task.

[0106] In this embodiment of the invention, the current parameter configuration variables and current scenario requirements corresponding to the target data export task are obtained. Then, based on the current scenario requirements, the target data processing strategy corresponding to the target data export task is determined, and the target parameter template corresponding to the target data export task is determined from a preset parameter template library. Further, data processing is performed on the current parameter configuration variables based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task. Finally, the target parameter configuration data is populated based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task, and the various basic data export strategies are summarized to obtain the target data export strategy corresponding to the target data export task. Because different parameter templates are adapted to different requirement scenarios, and different database data is exported, the adaptability and accuracy of the exported data are improved.

[0107] Optionally, the data acquisition module 310 can be used for:

[0108] Obtain the current data export requirements corresponding to the target data export task, and determine the basic parameter configuration variables corresponding to the target data export task based on the current data export requirements;

[0109] The declaration processes the basic parameter configuration variables to obtain the current parameter configuration variables corresponding to the target data export task.

[0110] Optional, the current parameter configuration variables include: current table configuration variables, current table field configuration variables, and current table condition configuration variables.

[0111] Optional, current scenario requirements include: table field export scenarios, field value export scenarios, and table condition export scenarios.

[0112] Optionally, the data export strategy generation device may further include: a template construction module, used to: obtain the original export statement corresponding to the target data export task before determining the target data processing strategy corresponding to the target data export task based on the current scenario requirements and determining the target parameter template corresponding to the target data export task in the preset parameter template library; segment the original export statement based on preset variable extraction rules to determine the statement segment set corresponding to the target data export task; extract variables from the target statement segments in the statement segment set based on preset keyword identifiers to determine the original parameter configuration variables corresponding to the target statement segments; combine and process the target statement segments and the corresponding original parameter configuration variables to obtain the basic parameter template corresponding to the target data export task, and summarize and process each basic parameter template to obtain the preset parameter template library.

[0113] Optionally, if the current scenario requires exporting field values, the target data processing strategy includes: a time update strategy, a unique identifier matching strategy, a global replacement strategy, and a local replacement strategy.

[0114] Optionally, if the target data processing strategy is a time update strategy, the data processing module 330 can be specifically used to: obtain the current system timestamp and the base timestamp corresponding to the current parameter configuration variable; update the base timestamp based on the current system timestamp to obtain the target parameter configuration data corresponding to the target data export task.

[0115] Optionally, if the target data processing strategy is a unique identifier matching strategy, the data processing module 330 can be specifically used to: obtain the target unique identifier set corresponding to the target data export task and the current unique identifier contained in the current parameter configuration variable; perform data matching on the current unique identifier based on the target unique identifier set to generate a data matching result, and process the current unique identifier based on the data matching result to obtain the target parameter configuration data corresponding to the target data export task.

[0116] Optionally, if the target data processing strategy is a global replacement strategy, the data processing module 330 can be specifically used to: mark the current parameter configuration variable as the target parameter configuration data corresponding to the target data export task.

[0117] Optionally, if the target data processing strategy is a local replacement strategy, the data processing module 330 can be specifically used to: change the current parameter configuration variable based on preset data change conditions to obtain the target parameter configuration data corresponding to the target data export task.

[0118] Optionally, the data export strategy generation device may further include: a post-processing module, used to dynamically execute the target data export strategy after the summary processing of each basic data export strategy to obtain the target data export strategy corresponding to the target data export task, so as to obtain the target exported data corresponding to the target data export task.

[0119] The data export strategy generation apparatus provided in this embodiment of the invention can execute the data export strategy generation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0120] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 5 As shown, the electronic device includes a processor 410, a memory 420, an input device 430, and an output device 440; the number of processors 410 in the electronic device can be one or more. Figure 5 Taking a processor 410 as an example; the processor 410, memory 420, input device 430, and output device 440 in the electronic device can be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.

[0121] The memory 420, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the data export strategy generation method in this embodiment of the invention (e.g., the data acquisition module 310, template matching module 320, data processing module 330, and strategy generation module 340 in the data export strategy generation device). The processor 410 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory 420, thereby implementing the aforementioned data export strategy generation method.

[0122] The memory 420 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. Furthermore, the memory 420 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 420 may further include memory remotely located relative to the processor 410, which can be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0123] Input device 430 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the electronic device. Output device 440 may include display devices such as a display screen.

[0124] This invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform a method for generating a data export strategy, the method comprising:

[0125] Obtain the current parameter configuration variables and current scenario requirements corresponding to the target data export task;

[0126] Based on the current scenario requirements, determine the target data processing strategy corresponding to the target data export task, and determine the target parameter template corresponding to the target data export task in the preset parameter template library;

[0127] Based on the target data processing strategy, the current parameter configuration variable is processed to obtain the target parameter configuration data corresponding to the target data export task;

[0128] The target parameter configuration data is populated based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task. The basic data export strategies are then aggregated and processed to obtain the target data export strategy corresponding to the target data export task.

[0129] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the method operations described above, but can also execute related operations in the data export strategy generation method provided in any embodiment of the present invention.

[0130] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0131] It is worth noting that in the embodiments of the above-mentioned data export strategy generation device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0132] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements a data export strategy generation method as provided in any embodiment of this application.

[0133] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0134] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for generating a data export strategy, characterized in that, include: Obtain the current parameter configuration variables and current scenario requirements corresponding to the target data export task; Based on the current scenario requirements, determine the target data processing strategy corresponding to the target data export task, and determine the target parameter template corresponding to the target data export task in the preset parameter template library; Based on the target data processing strategy, the current parameter configuration variable is processed to obtain the target parameter configuration data corresponding to the target data export task; The target parameter configuration data is populated based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task. The basic data export strategies are then aggregated and processed to obtain the target data export strategy corresponding to the target data export task.

2. The method according to claim 1, characterized in that, The current parameter configuration variables corresponding to the target data export task include: Obtain the current data export requirements corresponding to the target data export task, and determine the basic parameter configuration variables corresponding to the target data export task based on the current data export requirements; The declaration processes the basic parameter configuration variables to obtain the current parameter configuration variables corresponding to the target data export task.

3. The method according to claim 1, characterized in that, The current parameter configuration variables include: current table configuration variables, current table field configuration variables, and current table condition configuration variables.

4. The method according to claim 1, characterized in that, The current scenario requirements include: table field export scenario, field value export scenario, and table condition export scenario.

5. The method according to claim 1, characterized in that, Before determining the target data processing strategy corresponding to the target data export task based on the current scenario requirements, and determining the target parameter template corresponding to the target data export task in the preset parameter template library, the method further includes: Obtain the original export statement corresponding to the target data export task; Based on preset variable extraction rules, the original exported statement is segmented to determine the set of statement segments corresponding to the target data export task. Based on preset keyword identifiers, variables are extracted from the target statement segments in the statement segmentation set to determine the original parameter configuration variables corresponding to the target statement segments; The target statement segments and their corresponding original parameter configuration variables are combined and processed to obtain the basic parameter templates corresponding to the target data export task, and the various basic parameter templates are summarized and processed to obtain a preset parameter template library.

6. The method according to claim 4, characterized in that, If the current scenario requirement is a field value export scenario, then the target data processing strategy includes: time update strategy, unique identifier matching strategy, global replacement strategy, and local replacement strategy.

7. The method according to claim 6, characterized in that, If the target data processing strategy is a time-update strategy, then the step of processing the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task includes: Get the current system timestamp and the base timestamp corresponding to the current parameter configuration variable; The base timestamp is updated based on the current system timestamp to obtain the target parameter configuration data corresponding to the target data export task.

8. The method according to claim 6, characterized in that, If the target data processing strategy is a unique identifier matching strategy, then the step of processing the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task includes: Obtain the set of target unique identifiers corresponding to the target data export task and the current unique identifiers contained in the current parameter configuration variables; Based on the target unique identifier set, the current unique identifier is matched to generate a data matching result. Based on the data matching result, the current unique identifier is processed to obtain the target parameter configuration data corresponding to the target data export task.

9. The method according to claim 6, characterized in that, If the target data processing strategy is a global replacement strategy, then the step of processing the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task includes: The current parameter configuration variable is marked as the target parameter configuration data corresponding to the target data export task.

10. The method according to claim 6, characterized in that, If the target data processing strategy is a local replacement strategy, then the step of processing the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task includes: Based on preset data change conditions, the current parameter configuration variables are modified to obtain the target parameter configuration data corresponding to the target data export task.

11. The method according to claim 1, characterized in that, After summarizing and processing the various basic data export strategies to obtain the target data export strategy corresponding to the target data export task, the method further includes: The target data export strategy is dynamically executed to obtain the target exported data corresponding to the target data export task.

12. A data export strategy generation apparatus, characterized in that, include: The data acquisition module is used to acquire the current parameter configuration variables and current scenario requirements corresponding to the target data export task. The template matching module is used to determine the target data processing strategy corresponding to the target data export task based on the current scenario requirements, and to determine the target parameter template corresponding to the target data export task in the preset parameter template library. The data processing module is used to process the current parameter configuration variable based on the target data processing strategy to obtain the target parameter configuration data corresponding to the target data export task; The strategy generation module is used to populate the target parameter configuration data based on the target parameter template to obtain the basic data export strategy corresponding to the target data export task, and to summarize and process each basic data export strategy to obtain the target data export strategy corresponding to the target data export task.

13. An electronic device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements a method for generating a data export strategy as described in any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for generating the data export strategy as described in any one of claims 1-11.

15. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for generating the data export strategy as described in any one of claims 1-11.

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