Data field processing method and device, equipment, storage medium and program product

Abstract

The invention discloses a data field processing method and device, equipment, a storage medium and a program product, and relates to the technical field of computers.The method comprises the steps that in response to a service line creating operation for a target service, at least one target service line corresponding to the target service is obtained; obtaining at least one business data model corresponding to each target business line in response to an association operation for a plurality of data sources corresponding to the target business line; in response to a selection operation for the data model, determining a target data model corresponding to a target service line from the at least one service data model, and extracting service data matched with the target service line according to the target data model; in response to a configuration operation for the field verification rule, determining a target verification rule corresponding to the target data model; and verifying the data field of the business data according to the target verification rule to obtain a data field verification result. By implementing the technical scheme, accurate verification for the business data field is realized.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and more specifically to methods, apparatus, devices, storage media, and program products for processing data fields. Background Technology

[0002] Currently, data field validation suffers from numerous issues, including missing validation criteria, limited data acquisition capabilities, and a lack of unified validation rules, making accurate data field verification difficult. Consequently, it is primarily implemented through code development or external platforms. However, code development is costly and struggles to handle complex business scenarios, while external platforms lack visual debugging for rule configuration, and to ensure data security, they typically cannot access all data. Therefore, achieving accurate data field verification is an urgent problem to be solved. Summary of the Invention

[0003] In view of this, the present invention provides a method, apparatus, device, storage medium and program product for processing data fields, so as to solve the problem of difficulty in accurately verifying data fields.

[0004] In a first aspect, the present invention provides a method for processing data fields, comprising: in response to a business line creation operation for a target business, obtaining at least one target business line corresponding to the target business; in response to an association operation for multiple data sources corresponding to the target business line, obtaining at least one business data model corresponding to each target business line; in response to a data model selection operation, determining a target data model corresponding to the target business line from the at least one business data model, and extracting business data matching the target business line according to the target data model; in response to a field validation rule configuration operation, determining a target validation rule corresponding to the target data model; and validating the data fields of the business data according to the target validation rule to obtain a data field validation result.

[0005] Secondly, the present invention provides a data field processing apparatus, comprising: a business line creation module, configured to, in response to a business line creation operation for a target business, obtain at least one target business line corresponding to the target business; a data model creation module, configured to, in response to an association operation for multiple data sources corresponding to the target business lines, obtain at least one business data model corresponding to each target business line; a business data association module, configured to, in response to a data model selection operation, determine the target data model corresponding to the target business line from the at least one business data model, and extract business data matching the target business line according to the target data model; a rule configuration module, configured to, in response to a field validation rule configuration operation, determine the target validation rule corresponding to the target data model; and a field validation module, configured to validate the data fields of the business data according to the target validation rule, and obtain data field validation results.

[0006] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the data field processing method described in the first aspect or any corresponding embodiment thereof.

[0007] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the data field processing method described in the first aspect or any corresponding embodiment thereof.

[0008] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the data field processing method described in the first aspect or any corresponding embodiment thereof.

[0009] The data field processing method, apparatus, device, storage medium, and program product provided in this invention support the flexible creation of business lines for target businesses. By associating multiple data sources corresponding to each target business line, at least one business data model corresponding to each target business line is obtained. This allows for the selection of the target data model corresponding to the target business line based on actual needs, enabling the acquisition of business data using the target data model. Thus, the ability to acquire business data is no longer limited to direct database connections or simple cross-table access, ensuring the capability to acquire business data. By configuring target validation rules to match the target data model with the target validation rules, a unified target validation rule can be used to validate the fields of business data, improving the configuration flexibility of the target validation rule. Subsequently, by validating the data fields of the business data according to the target validation rules, accurate verification of the business data fields can be achieved. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0011] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention;

[0012] Figure 2 This is a flowchart illustrating a data field processing method according to an embodiment of the present invention;

[0013] Figure 3This is a schematic diagram of business line management according to an embodiment of the present invention;

[0014] Figure 4 This is a schematic diagram illustrating the creation of a service line according to an embodiment of the present invention;

[0015] Figure 5 This is a schematic diagram of data model management according to an embodiment of the present invention;

[0016] Figure 6 This is a schematic diagram illustrating the creation of a data model according to an embodiment of the present invention;

[0017] Figure 7 This is a schematic diagram illustrating the configuration of a data model according to an embodiment of the present invention;

[0018] Figure 8 This is another configuration diagram of the data model according to an embodiment of the present invention;

[0019] Figure 9 This is a flowchart illustrating a method for processing another data field according to an embodiment of the present invention;

[0020] Figure 10 This is a schematic diagram of business scenario management according to an embodiment of the present invention;

[0021] Figure 11 This is a schematic diagram illustrating the creation of a business scenario according to an embodiment of the present invention;

[0022] Figure 12 This is a schematic diagram of rule binding according to an embodiment of the present invention;

[0023] Figure 13 This is a schematic diagram of rule management according to an embodiment of the present invention;

[0024] Figure 14 This is a schematic diagram illustrating rule creation according to an embodiment of the present invention;

[0025] Figure 15 This is a flowchart illustrating another data field processing method according to an embodiment of the present invention;

[0026] Figure 16 This is a debugging diagram according to an embodiment of the present invention;

[0027] Figure 17 This is an alarm diagram according to an embodiment of the present invention;

[0028] Figure 18 This is another alarm diagram according to an embodiment of the present invention;

[0029] Figure 19 This is a schematic diagram of the operating architecture according to an embodiment of the present invention;

[0030] Figure 20 This is a structural block diagram of a data field processing apparatus according to an embodiment of the present invention;

[0031] Figure 21 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0033] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0034] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0035] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0036] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0037] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0038] Currently, the following core issues exist in data field validation: (1) Lack of field value correctness validation: Due to changes in business logic, required fields are missing or incorrect (e.g., the missing cpt_rotation_weight field causes a P0 incident); (2) Lack of field consistency validation: Cross-table data association logic is complex and cannot handle list-type data; (3) Limited data source acquisition capability: Relies on direct database connection or simple cross-table, and cannot support remote procedure call (RPC) data acquisition and complex batch calls; (4) Insufficient flexibility in rule configuration: Lack of a unified rule engine to support complex validation logic (e.g., custom functions, multi-field joint validation), which makes it difficult to perform efficient, flexible and accurate data field verification.

[0039] In related technologies, implementation is mainly achieved through code development or external platforms. However, code development is mainly implemented by hard-coding the verification logic through scheduled tasks, which has high development costs and is difficult to cope with complex business scenarios. External platforms do not support RPC data acquisition (databases cannot be directly connected in business scenarios due to security reasons, so RPC must be used to obtain data), have weak complex cross-table association capabilities, rule configuration depends on code, and lack visual debugging tools.

[0040] Based on this, the technical solution disclosed herein provides a visual configuration interface for flexible configuration of business lines, data models, and validation rules. This overcomes the challenges posed by changes in business logic, such as missing or incorrect required fields and incomplete consistency checks between fields. By utilizing the target data model to acquire business data, the ability to acquire business data is no longer limited to direct database connections or simple cross-table queries, ensuring the capability to acquire business data. The use of unified target validation rules for business data field validation enhances the configuration flexibility of these rules. Furthermore, validating the data fields of business data according to the target validation rules enables precise verification of business data fields.

[0041] As an optional application scenario of this invention, such as Figure 1 As shown, the application scenario includes electronic device 101 and data verification system 102, which is deployed in electronic device 101.

[0042] Specifically, the data verification system 102 includes a business line management module, a data model management module, a business scenario management module, a rule management module, and a debugging module. The business line management module is used for configuring business lines; the data model management module is used for associating multiple data sources in the data model; the business scenario management module is used for configuring the verification rules and business data models associated with business scenarios under each business line; the rule management module is used for configuring field verification rules associated with each data model; and the debugging module is used for performing debugging to determine the compatibility of the rules with the business scenarios.

[0043] The business line management module, data model management module, business scenario management module, rule management module, and debugging module all possess computing resources or computing capabilities. Electronic device 101 can be a device with computing capabilities; for example, it may be equipped with a processor and memory, and may also be equipped with a dedicated accelerator (such as a graphics processing unit (GPU)). Furthermore, the electronic device can store and maintain data. Examples of electronic devices may include supercomputers, personal computers, laptop computers, in-vehicle computing devices, mobile devices (such as smartphones, tablets, etc.), or combinations thereof. It should be understood that the electronic device described herein is merely exemplary and not limiting; other different types of electronic devices may also be used.

[0044] According to an embodiment of the present invention, a method for processing data fields is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0045] This embodiment provides a method for processing data fields, which can be used in electronic devices such as computers and tablets. Figure 2 This is a flowchart of a data field processing method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0046] Step S201: In response to the business line creation operation for the target business, at least one target business line corresponding to the target business is obtained.

[0047] The electronic device is equipped with a data verification system. This system provides a verification configuration interface 1. A business line management control 11 is configured in the verification configuration interface 1. Triggering the business line management control 11 displays the business line display page 12, such as... Figure 3 As shown. The verification configuration interface 1 can respond to the trigger operation of the technical personnel on the business line management control 11, display the configured business line list on the business line display page 12, and at the same time, the business line display page 12 displays the business line creation control 13.

[0048] The target business is the business that currently requires data validation, such as the brand business. The target business line is the business line configured for the target business, such as the brand placement business line, brand platform business line, brand packaging business line, etc., corresponding to the brand business. Different business lines have different business line identifiers. The business line creation operation is an operation triggered to create a business line for the target business.

[0049] Specifically, the business line creates control 13 (such as...). Figure 3 The “New Business Line” control shown can respond to the trigger operation of the technical personnel on the business line creation control 13 to execute the business line creation process, create the target business line according to the business line creation process, and display the created target business line on the business line display page 12.

[0050] It should be noted that each business line displayed on the business line display page 12 has a corresponding "Search / Modify" control and a "Delete" control. The "Search / Modify" control allows viewing or adjusting the corresponding business line; the "Delete" control deletes the corresponding business line. During the deletion process, a secondary deletion confirmation message can be generated to prevent accidental deletion of business lines.

[0051] Step S202: In response to the association operation of multiple data sources corresponding to the target business line, at least one business data model corresponding to each target business line is obtained.

[0052] In the verification configuration interface 1, set the data model management control 15. Triggering the data model management control 15 displays the model display page 16, such as... Figure 5 As shown. The verification configuration interface 1 can respond to the trigger operation of the technical personnel on the data model management control 15, and display the list of created data models on the model display page 16. At the same time, the model display page 16 is equipped with a data model creation control 17.

[0053] The data source provides data for business lines. Multiple data sources support the association and integration of business data, and the data sources can be accessed via Remote Procedure Call (RPC) requests. Different target business lines can be bound to corresponding data models to retrieve business data; the business data model is the data model bound to the target business line.

[0054] Specifically, the data model creation control 17 (such as...) Figure 3 The “Add Data Model” control shown can respond to the trigger operation of the technical personnel on the data model creation control 17 to execute the data model creation process, associate multiple data sources according to the data model creation process, and display the created business data model on the model display page 16.

[0055] It should be noted that each data model displayed on model display page 16 has a corresponding "View / Modify / Debug" control and a "Delete" control. The "View / Modify / Debug" control allows for viewing, adjusting, or debugging of the corresponding data model; the "Delete" control deletes the corresponding data model. During the deletion process, a secondary deletion confirmation message can be generated to prevent accidental deletion of data models.

[0056] Step S203: In response to the selection operation for the data model, determine the target data model corresponding to the target business line from at least one business data model, and extract the business data that matches the target business line according to the target data model.

[0057] In the verification configuration interface 1, configure the business scenario management control 19. Triggering the business scenario management control 19 displays the business scenario display page 20, such as... Figure 10 As shown. The verification configuration interface 1 can respond to the trigger operation of the technical personnel on the business scenario management control 19, and display a list of business scenarios under the existing business lines on the business scenario display page 20. The business scenario display page 20 is also equipped with a data model selection control 21.

[0058] Specifically, the data model selection control 21 can respond to the trigger operation of the technicians and select the target data model corresponding to the current target business line from the existing business data models. If the target data model is enabled, the business data corresponding to each business scenario under the target business line is extracted according to the target data model.

[0059] It should be noted that each business scenario under the target business line displayed on the business scenario display page 20 corresponds to a specific "Query / Modify" control, "Query / Bind Rule" control, "Start / Stop" control, "Debug" control, "Run" control, "Run Record" control, and "Delete" control. The "Query / Modify" control allows viewing and editing data for the corresponding business scenario; the "Query / Bind Rule" control allows viewing rules for the corresponding business scenario and binding rules under the same data model; the "Start / Stop" control controls the start or pause of the data model corresponding to the business scenario; the "Debug" control redirects to the debugging page to perform business data retrieval and debugging; the "Run" control executes the manual running process; the "Run Record" control displays the business data retrieval results; and the "Delete" control deletes the corresponding business scenario. During the deletion process, a secondary deletion confirmation message can be generated to prevent accidental deletion of business scenarios.

[0060] Step S204: In response to the configuration operation for field validation rules, determine the target validation rule corresponding to the target data model.

[0061] In the verification configuration interface 1, set the rule management control 22. By triggering the rule management control 22, the rule display page 23 is displayed, such as... Figure 13As shown. The verification configuration interface 1 can respond to the trigger operation of the technical personnel on the rule management control 22, and display the list of created rules on the rule display page 23. At the same time, the rule display page 23 is equipped with a rule configuration control 24.

[0062] Target validation rules are rules used to validate data fields in business data. Specifically, rule configuration control 24 (such as...) Figure 13 The "Add New Rule" button shown can respond to the triggering operation of technical personnel to execute the rule configuration process, create the verification rule according to the rule configuration process, and display the created target verification rule on the rule display page 23.

[0063] It should be noted that each target validation rule displayed on rule display page 23 has a corresponding "View / Modify" control and a "Delete" control. The "View / Modify" control allows you to view or adjust the corresponding validation rule; the "Delete" control allows you to delete the corresponding validation rule. During the deletion process, a secondary deletion confirmation message can be generated to prevent accidental deletion of validation rules.

[0064] Step S205: Validate the data fields of the business data according to the target validation rules to obtain the data field validation results.

[0065] According to the target verification rules, the field values ​​of each data field of the extracted business data are verified for correctness, and the consistency between fields is verified. The field verification results for each data field of the business data are obtained, so as to achieve accurate verification of each data field of the business data through the field verification results.

[0066] The data field processing method provided in this embodiment supports the flexible creation of business lines for target businesses. By associating multiple data sources corresponding to each target business line, at least one business data model is obtained for each target business line. This allows for the selection of the target data model corresponding to the target business line based on actual needs, enabling the acquisition of business data using the target data model. Thus, the ability to acquire business data is no longer limited to direct database connections or simple cross-table queries, ensuring the capability to acquire business data. By configuring target validation rules to match the target data model with the target validation rules, a unified target validation rule can be used to validate the fields of the business data, improving the configuration flexibility of the target validation rule. Subsequently, validating the data fields of the business data according to the target validation rules enables accurate verification of the business data fields.

[0067] This embodiment provides a method for processing data fields, which can be used in electronic devices such as computers and tablets. Figure 9This is a flowchart of a data field processing method according to an embodiment of the present invention, such as... Figure 9 As shown, the process includes the following steps:

[0068] Step S301: In response to the business line creation operation for the target business, at least one target business line corresponding to the target business is obtained.

[0069] Specifically, step S301 includes:

[0070] Step S3011: In response to the business line creation operation for the target business, the business line editing page is displayed, which includes an attribute editing area.

[0071] As described above, the business line display page 12 shows a business line creation control 13. This control 13 can respond to trigger operations by technical personnel, displaying the business line editing page 14. Figure 4 As shown, the business line editing page 14 includes an attribute editing area 141 and a business line editing status control 142, such as "View / Edit Business Line". The control description of the business line editing status control 142 can be automatically updated according to "Create Business Line" and "View / Modify Business Line".

[0072] Step S3012: In response to the attribute editing operation in the attribute editing area, generate business attribute information.

[0073] Business attribute information refers to the characteristic attributes possessed by a business line, specifically including the business line name and description. Attribute editing operations are the operations performed by technical personnel to edit the attributes of a target business line, such as... Figure 4 As shown, the attribute editing area 141 includes a business line name editing area and a business line description editing area. The business line name editing area can respond to the editing operations of technical personnel and generate the business line name corresponding to the target business line; the business line description editing area can respond to the editing operations of technical personnel and generate the business line description corresponding to the target business line.

[0074] Step S3013: Based on the business line identifier and business attribute information, generate the target business line corresponding to the target business.

[0075] Different business line identifiers are assigned to different business lines of the target business. The business lines are assembled according to the business line identifiers and business attribute information to complete the creation of the target business lines. The created target business lines are then displayed in the business line list on the business line display page 12.

[0076] In some optional implementations, step S301 above further includes: in response to the configuration operation for management permissions, determining the management permissions of the business lines corresponding to each target business line.

[0077] Business line management permissions are used to represent the control permissions available for a business line, namely, the permissions to add, delete, modify, and query all concepts within that business line. For example... Figure 4 As shown, a management permission configuration area 143 is set in the business line editing page 14. In this management permission configuration area 143, management objects can be configured so that the configured objects have the control permissions of the business line. There can be one or more management objects, and no specific limitation is made here.

[0078] Accordingly, the management permission configuration area can respond to management permission configuration operations by technical personnel, generating the corresponding business line management permissions for the target business line based on these operations. Then, the business line management permissions can be assembled into the business lines to display the management objects corresponding to each target business line in the business line list on the business line display page 12, such as... Figure 3 As shown.

[0079] By configuring management permissions, the management permissions corresponding to each business line are made independent, ensuring the information security of each business line.

[0080] In some optional implementations, an alarm configuration area 144 is provided in the business line editing page 14, where alarm configuration can be performed, such as sending alarm information to the collaborative application in the form of cards or to relevant monitored objects. At the same time, alarm information is recorded for historical record tracing. The collaborative application supports searching for the alarm notification group identifiers that have been joined through links.

[0081] The business line editing page 14 includes a monitoring information configuration area 145, where duty schedules can be configured to allocate relevant monitoring objects appropriately. The duty schedule also supports navigation to create new schedules or search for existing ones.

[0082] In some optional implementations, the above method further includes:

[0083] Step a1: Display the set of business lines corresponding to the target business.

[0084] Step a2, in response to a search operation on the set of business lines, determines the search results for the target business line from the set of business lines.

[0085] A business line set is a collection of all business lines created for a target business. A business line set may contain one or more business lines and can be represented as a list of business lines, such as... Figure 3 As shown.

[0086] The search operation is performed on business lines. The business line display page 12 includes an identifier search control 121 and a name search control 122. Specifically, by triggering the identifier search control 121 and entering the corresponding business line identifier, a precise search for the business line can be performed based on the identifier, filtering out one or more business lines matching the identifier from the business line set. Conversely, by triggering the name search control 122 and entering the corresponding business line name, a fuzzy search for the business line can be performed based on the name, filtering out one or more business lines matching the name from the business line set. Thus, by supporting searches for business lines in different ways, the flexibility of viewing business lines is improved.

[0087] It should be noted that each business line displayed on the business line display page 12 has a corresponding "search / edit" control and a "delete" control. Triggering the "search / edit" control allows access to the business line editing page 14 to view or adjust the corresponding business line information; triggering the "delete" control executes the deletion of the corresponding business line. During the deletion process, a secondary deletion confirmation message can be generated to prevent accidental deletion of business lines.

[0088] Step S302: In response to the association operation of multiple data sources corresponding to the target business line, at least one business data model corresponding to each target business line is obtained.

[0089] Specifically, step S302 includes:

[0090] Step S3021: In response to the data model creation operation, display the data model creation page, which includes a model attribute editing area and a model structured language editing area.

[0091] As described above, the model display page 16 shows a data model creation control 17, which can respond to trigger operations by technicians and display the data model creation page 18. Figure 6 As shown, the data model creation page 18 includes a model attribute editing area 181 and a model structured language editing area 182. The model attribute editing area 181 is used to configure the basic attribute information of the data model, and the model structured language editing area 182 is used to configure the abstract syntax tree of the data model in a structured language.

[0092] like Figure 6 As shown, the data model creation page 18 also includes a model editing status control 183, such as "View / Edit / Debug Data Model". The control description of this model editing status control 183 can be automatically updated based on "Add Data Model" or "View / Modify / Debug Data Model".

[0093] Step S3022: In response to the model attribute editing operation in the model attribute editing area, obtain the data model attribute information.

[0094] Data model attribute information refers to the characteristic attributes possessed by a data model, specifically including the data model name and description. Model attribute editing operations are the operations performed by technical personnel to edit the attributes of the data model, such as... Figure 6 As shown, the model attribute editing area 181 includes a model name editing area and a model description editing area. The model name editing area can respond to the editing operations of technicians and generate the model name corresponding to the data model; the model description editing area can respond to the editing operations of technicians and generate the model description corresponding to the data model.

[0095] Step S3023: In response to the data source request association operation in the model structured language editing area, obtain the association information between multiple data sources.

[0096] Association information is used to associate multiple data sources. This association information can be determined by the call order of various RPC requests and the association relationships between the results of each RPC request. The data source request association operation is an operation that associates data sources based on relevant RPC call information, such as... Figure 6 As shown, the model structured language editing area 182 can respond to the technical personnel's description operations for the association of various RPCs. For example, it can use JSON to describe the abstract syntax tree (ASL) of the data model, so as to associate various data sources through the abstract syntax tree (ASL) and obtain the association information between multiple data sources.

[0097] In some optional implementations, step S3023 above includes:

[0098] Step b1: In response to the call configuration operation generated for each data source request, determine the call information between each data source request.

[0099] Step b2: Obtain the request identifier corresponding to each data source request.

[0100] Step b3: In response to the information association operation based on the call information, associate the various data source requests according to the request identifier to obtain the association information.

[0101] The configuration call operation is a configuration operation performed on a data source request; the call information includes relevant information during the data source request call, including normal call, result processing, and the call relationship before and after the data source request. The request identifier is a unique identifier for the data source request.

[0102] Based on the call information between data source requests, the data source requests are associated according to the request identifiers corresponding to each data source request. Therefore, the model structured language editing area 182 can respond to information association operations generated by technicians, using the configured call information between data source requests and combining it with the request identifier to assemble all information belonging to that request identifier, forming associated information between multiple data sources.

[0103] It should be noted that the order of calls between the various data source request methods and the correlation between the request results of each data source are predefined. The order of calls is used to generate useful but unrelated request result data, while the correlation is used to assemble a batch of related business datasets based on the request result data.

[0104] In a specific example, the configuration operation mainly includes data source request information configuration and data format configuration. The data source request information configuration records relevant information during the data source request call, while the data format configuration is used to group and transform data based on the request identifier.

[0105] Specifically, such as Figure 7 As shown, the data source request information configuration includes the configuration of the Next field, Meta field, Req field, Result field, and Batch field.

[0106] The Next field is used to indicate the list of nodes that should be called next after the data source request (RPC) call is completed, such as ["A1","B2","C3"]. The last node to be called does not need to have Next set.

[0107] The Meta field represents the metadata required for a data source request (RPC) call, used to prepare the necessary conditions for sending the request. It has subfields PSM, Method, Cluster, Version of the PSM IDL, and Branch of the PSM IDL. Each subfield is filled according to its corresponding type and required rules.

[0108] The Req field is used to define the specific values ​​of the call parameters for a data source request (RPC). The logic generated here is used to complete the request assembly. The Req field can define any subfield of the input parameters required for the data source request call.

[0109] The Result field is used to process the response result after the data source request (RPC) call is completed. It has two subfields: ResponseGetPath and ResultMapKey. The ResponseGetPath subfield is used to obtain the specific data from the Response result (such as where the data is retrieved from and where the retrieved data is placed). The value of the ResultMapKey subfield is used to identify which key in the temporary Map that is temporarily stored.

[0110] The `Batch` field is used to address the issue of limiting the number of batch calls for certain APIs during large-scale calls. For example, Nebula limits the number of batch API requests to 200; exceeding 200 results in an error. The `Batch` field has subfields `ReqGetPath`, `Num`, `Concurrency`, and `RespMergePath`. `ReqGetPath` indicates which field should be split during batch processing; `Num` indicates the number of requests in each batch, typically determined by the API limit; `Concurrency` indicates the maximum concurrent batch calls, with requests exceeding this limit waiting for the preceding calls to complete; and `RespMergePath` indicates which field should be used to assemble the batch call results into a single `Response`.

[0111] Specifically, such as Figure 8 As shown, the data format configuration includes the configuration of the Self field and the DataBind field. The Self field has three subfields: FieldKey, FieldType, and ObjIDGetPath. The FieldKey subfield represents the key where the data is stored; the FieldType subfield represents the data type, including single types where values ​​are stored as structs and list types where values ​​are stored as lists[structs]; the ObjIDGetPath subfield represents the key ID, used to globally identify data relationships and is a globally unique identifier for the data.

[0112] The DataBind field has three subfields: ParentFieldKey, ParentGetPath, and SelfGetPath. The ParentFieldKey subfield indicates which data's FieldKey needs to be bound to, and FieldKey is the FieldKey in the Self field. The ParentGetPath subfield indicates the data in which the bound field is located and its position within that data. The SelfGetPath subfield indicates the position of the bound field within its own data.

[0113] By defining the call order and relationships of data source requests through an abstract syntax tree, in order to support complex batch processing, multiple data sources are associated to flexibly assemble multiple data sources in the same data model, thereby enabling the acquisition of comprehensive business data and improving the ability to acquire business data.

[0114] Step S3024: Integrate the data model attribute information and association information to generate at least one business data model corresponding to the target business line.

[0115] The data model attribute information and the association information between multiple data sources are fused to assemble the data model, complete the creation of any business data model, and display the created business data model in the data model list on the data model creation page 18.

[0116] In some alternative implementations, the data model creation page includes a model parameter debugging area, and the method further includes: obtaining the debugging result of the target data model in response to a model debugging operation generated in the model parameter debugging area.

[0117] like Figure 6 As shown, the data model creation page 18 includes a model parameter debugging area 184, which is used to input debugging parameters, which are the input parameters of the first data source request, to obtain data according to the abstract syntax tree (ASL).

[0118] The debugging results are used to represent the detailed information in the process of requesting according to the Abstract Syntax Tree (ASL) and the detailed information in the results. They mainly include two parts: the call information of the data source request (RPC) and the result information. The call information of the data source request is the input parameters and brief result information of the actual call of each data source request, and the result information is the finally obtained related dataset.

[0119] Specifically, the model parameter debugging area 184 can respond to the input of debugging parameters by technicians. After the debugging parameters are input, the model debugging operation is triggered to execute the model debugging process according to the debugging parameters, obtain the debugging results of the target data model, and display the debugging results in the result display area of ​​the data model creation page 18, such as... Figure 6 As shown.

[0120] By debugging the data model, the model parameters can be adjusted to ensure the data acquisition capability of the data model.

[0121] In some optional implementations, the model display page 16 includes a business line selection control 161, a model identifier search control 162, and a model name search control 163. Specifically, by triggering the business line selection control 161 to select the corresponding business line, all data models under that business line can be filtered out; by triggering the model identifier search control 162 to perform a precise search for data models, one or more target data models matching the model identifier can be filtered out from all data models under the business line; by triggering the model name search control 163 to input the corresponding model name, a fuzzy search for data models can be performed based on the model name, one or more target data models matching the model name can be filtered out from all data models under the business line.

[0122] It should be noted that each data model displayed on the model display page 16 has a corresponding "Query / Modify / Debug" control and a "Delete" control. Triggering the "Query / Modify / Debug" control allows access to the data model creation page 18 to view, adjust, or debug the corresponding data model information; triggering the "Delete" control executes the deletion of the corresponding data model. During the deletion process, a secondary deletion confirmation message can be generated to prevent accidental deletion of the data model.

[0123] Step S303: In response to the data model selection operation, determine the target data model corresponding to the target business line from at least one business data model, and extract business data matching the target business line according to the target data model. For details, please refer to [link to details]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0124] Step S304: In response to the configuration operation for field validation rules, determine the target validation rules corresponding to the target data model. For details, please refer to [link to relevant documentation]. Figure 2 Step S204 of the illustrated embodiment will not be described again here.

[0125] Step S305: Validate the data fields of the business data according to the target validation rules to obtain the data field validation results. For details, please refer to [link to relevant documentation]. Figure 2 Step S205 of the illustrated embodiment will not be described again here.

[0126] The data field processing method provided in this embodiment supports visual configuration of business attribute information, enabling flexible configuration of business lines according to the actual needs of the target business. It supports the use of structured languages ​​to associate data source requests, allowing multiple data sources to be associated within the same data model, thus automatically splitting batches of data source requests and performing corresponding data assembly.

[0127] This embodiment provides a method for processing data fields, which can be used in electronic devices such as computers and tablets. Figure 15 This is a flowchart of a data field processing method according to an embodiment of the present invention, such as... Figure 15 As shown, the process includes the following steps:

[0128] Step S401: In response to the business line creation operation for the target business, at least one target business line corresponding to the target business is obtained. For details, please refer to [link to relevant documentation]. Figure 3 Step S301 of the illustrated embodiment will not be described again here.

[0129] Step S402: In response to the association operation for multiple data sources corresponding to the target business line, at least one business data model corresponding to each target business line is obtained. For details, please refer to [link to details]. Figure 3 Step S302 of the illustrated embodiment will not be described again here.

[0130] Step S403: In response to the selection operation for the data model, determine the target data model corresponding to the target business line from at least one business data model, and extract the business data that matches the target business line according to the target data model.

[0131] Specifically, step S403 includes:

[0132] Step S4031: In response to the creation operation for business information, display the business information creation page, which includes the first data model configuration area.

[0133] As described above, the business scenario display page 20 shows a business line creation control 13, which is used to create business scenarios under the target business line. The business line creation control 13 can respond to trigger operations by technical personnel, displaying the business information creation page 131. Figure 11 As shown, the business information creation page 131 includes a first data model configuration area 211 and a business information configuration area 212. The first data model configuration area 211 is used to configure the data model for the current business information, while the business information configuration area 212 is used to configure the basic attribute information of the business information, including the business scenario name and business scenario description.

[0134] like Figure 11 As shown, the business information creation page 131 also includes a business information editing status control 213, such as "View / Edit Business Scenario". The control description of this business information editing status control 213 can be automatically updated based on "Add Business Information", "Query / Modify Business Information", etc.

[0135] Step S4032: In response to the model selection operation generated in the first data model configuration area, a target data model is determined from at least one business data model.

[0136] The target data model is the business data model bound to the current business information. The model selection operation is an action performed by technical personnel to choose a business data model, such as... Figure 11 As shown, a data model selection control is provided in the first data model configuration area 211. The data model selection control can respond to the selection operation of the technician and select the target data model that is suitable for the current business information from multiple business data models.

[0137] Step S4033: In response to the scheduling configuration operation for the target service line, determine the data scheduling parameters for the target service line.

[0138] Data scheduling parameters are used to control the scheduling process of business information created under a target business line, such as scheduling business data once every day. Scheduling configuration is an operation performed by technical personnel to configure parameters for business information created under the target business line.

[0139] like Figure 11 As shown, the business information creation page 131 has a scheduling configuration area 214. The scheduling configuration area 214 can respond to the technical personnel's configuration operations on scheduling parameters and generate data scheduling parameters corresponding to the business information under the target business.

[0140] Step S4034: Using the target data model, extract business data according to the data scheduling parameters.

[0141] By combining multiple data sources associated with the target data model, and because the target data model sets the input parameters for the first data source request, it can control the scope of business data acquisition. Based on data scheduling parameters, the target data model is used to extract business data within the corresponding range from multiple associated data sources.

[0142] By configuring corresponding target data models for target business lines, the scope of business data acquisition can be controlled using these target data models. This allows for flexible configuration of data acquisition methods, greatly enhancing the ability to acquire business data.

[0143] In one optional implementation, triggering the "Query / Bind Rules" control can access the rule viewing page for business information, such as... Figure 12 As shown, the rule viewing page includes a populate area for business scenario names, which can be automatically filled based on the selection. Additionally, the page contains two rule selection boxes: one automatically displays all rules of the data model to which the business scenario belongs (rules already selected for the business scenario are checked by default); the other displays the rules selected for the current business scenario.

[0144] Step S404: In response to the configuration operation for the field validation rules, determine the target validation rules corresponding to the target data model.

[0145] Specifically, step S404 includes:

[0146] In step S4041, in response to the creation operation for the validation rule, a rule creation page is displayed, which includes a second data model configuration area and a rule configuration area.

[0147] As described above, the rule display page 23 shows a rule configuration control 24, which can respond to trigger operations by technical personnel and display the rule creation page 231. Figure 14 As shown, the rule creation page 231 includes a second data model configuration area 251 and a rule configuration area 252. The second data model configuration area 251 is used to configure the business data model corresponding to the target business line, and the rule configuration area 252 is used to configure the field validation rules for the business data.

[0148] like Figure 14 As shown, the rule creation page 231 also includes a rule editing status control 253, such as "View / Edit Rule". The control description of this rule editing status control 253 can be automatically updated based on "Add Rule" and "View / Edit". The rule creation page 231 also includes a rule attribute configuration area 254, which is used to configure the basic attribute information of the rule, including the rule name and rule description.

[0149] Step S4042: In response to the model configuration operation generated in the second data model configuration area, determine the target data model corresponding to the rule to be configured.

[0150] The target data model is the business data model bound to the currently configured rules. Model configuration is an operation performed by technical personnel to select a data model. For example... Figure 14 As shown, a data model selection control is provided in the second data model configuration area 251. This data model selection control can respond to the selection operation of technicians and select the target data model bound to the current verification rule from multiple business data models.

[0151] Step S4043: In response to the rule configuration operation generated in the rule configuration area, generate target validation rules that match the target data model.

[0152] Rule configuration is an operation performed by technical personnel to configure validation rules, such as... Figure 14As shown, the rule configuration area 252 includes a pre-filtering area and a verification area. The pre-filtering area can respond to editing operations by technical personnel and generate filter expressions; the verification area can respond to editing operations by technical personnel and generate abnormal alarm information. The filter expressions and abnormal alarm information are assembled to form the corresponding target verification rules.

[0153] By supporting the configuration of corresponding target verification rules for the target data model, the business data obtained by the target data model can be verified using the target verification rules, thereby further improving the verification accuracy of the business data.

[0154] In some optional implementations, the rule configuration area includes an expression configuration area and a data value configuration area, and step S4043 above includes:

[0155] Step c1: In response to the rule expression configuration operation generated in the expression configuration area, generate the target expression corresponding to the target data model.

[0156] Step c2, in response to the numerical configuration operation generated in the data value configuration area, obtains the target data value corresponding to the target expression.

[0157] Step c3: Assemble the target expression and target data value to generate the target validation rule.

[0158] like Figure 14 As shown, the pre-filter area of ​​rule configuration area 252 includes an expression configuration area. The rule expression configuration operation is an operation performed by technicians to edit rule expressions. Specifically, rule expressions can include ordinary arithmetic (such as addition, subtraction, multiplication, division, bitwise AND, bitwise OR, XOR, exponentiation, modulo, left shift, and right shift), comparison (such as greater than, equal to, less than, less than or equal to, identical equal to, not equal to, regular expression matching, regular expression non-matching, etc.), logical operations (such as logical OR, logical AND, etc.), and user-defined function operations (i.e., the values ​​of two input parameter expressions, such as allGt, lenEq, allLt, containsAll, containsAny, etc.). The expression configuration area can respond to the technicians' editing operations, and the target rule expression is composed of ordinary arithmetic, comparison, logical operations, and user-defined function operations.

[0159] like Figure 14 As shown, the pre-filter area of ​​rule configuration area 252 has a data value configuration area. The value configuration operation is the operation of technicians to extract values ​​for rule expressions.

[0160] Specifically, numerical values ​​can include: constant identifier "#" (no path lookup is needed, it directly corresponds to the specific data), root of path lookup "$" (will start the path expression), value retrieval for list data "[:]" (numbers can be before and after the colon, indicating the value of the array index range, closed before and after), value retrieval for list data at index "[index]" (returns null if the maximum index is exceeded), value retrieval for map data "[*]", and custom data retrieval identifier "@" (such as @Uniq to remove duplicates from list results; @MapKeys to retrieve all keys of Map, multiple functions can be nested; @Int64 to convert the corresponding data to a number in Int64 format; @String to convert the corresponding data to a string; @MinuteDurationByNow to represent the time interval from now, the time unit can be minutes min, the timestamp is in seconds, etc.).

[0161] The data value configuration area can respond to editing operations by technical personnel, defining the values ​​corresponding to the target rule expression according to the numerical value method. Then, the target rule expression and its corresponding target data value are assembled to obtain the complete target verification rule.

[0162] Specifically, when configuring rules using strings, string variables are represented by ""; list types are represented by "[]", with elements separated by ",". Character types do not require adding "" to each element. For example, a character list should be written as: [Information Flow, Open Screen], not ['Information Flow', 'Open Screen']. The paths of the fields to be compared are enclosed in "{}", such as "{$.phoneNumbers[0:0].type}". Expressions are strictly executed according to the priority of "()". Multiple expressions are connected using "&&" and "||", etc.

[0163] By configuring pre-filtering and verification of business data, it supports single-field verification, multi-field joint verification, and custom verification, thereby realizing multi-dimensional verification of business data, which is conducive to achieving accurate field verification.

[0164] In some optional implementations, the above method further includes: jointly debugging the target verification rules and business scenarios to ensure the accuracy of the target verification rule configuration. Specifically, rule and business scenario debugging controls 25 are set in the verification configuration interface 1, and the debugging page 26 is displayed by triggering the rule and business scenario debugging controls 25, such as... Figure 16 As shown.

[0165] The debugging page 26 includes a business scenario selection control 261, which is used to select the business scenario under the target business line to be debugged. During the selection of the business scenario, the request parameters of the selected business scenario will be included by default. Here, the scope can be narrowed by modifying the request parameters so that only the business data of interest can be requested.

[0166] Debugging page 26 includes a rule selection control 262, used to select the rules to be debugged. By default, it displays all validation rules under the data model of the selected business scenario and selects the rules for the selected business scenario. You can narrow the scope here, selecting only the rules you are interested in for debugging. After debugging is complete, the debugging results 263 are displayed on debugging page 26.

[0167] Step S405: Validate the data fields of the business data according to the target validation rules to obtain the data field validation results. For details, please refer to [link to relevant documentation]. Figure 2 Step S205 of the illustrated embodiment will not be described again here.

[0168] Step S406: If the data field validation result indicates that the business data is abnormal, then display the location of the abnormality in the business data, as well as the data model and field validation rules associated with the business data.

[0169] After data field validation is completed, if the validation result indicates an anomaly in the business data, an alarm page will be displayed. For example... Figure 17 As shown, the alarm page displays the location of the abnormal business data (e.g., the first row shows the abnormal business scenario), the data model associated with the abnormal business data (e.g., the second row shows the associated data model), and the corresponding field validation rules (e.g., the third row shows the abnormal rule name). It can also display the abnormal ID identifier under the field validation rules, and multiple abnormal rules can be displayed in a tiled format; other auxiliary information, such as environment, logs, and duty personnel, can also be displayed.

[0170] Step S407: If the data field validation result indicates that the amount of business data exceeds the limit, then display the limit parameter information of the business data.

[0171] Exceedance parameter information is used to characterize the extent to which business data exceeds limits, such as business identifiers and upper limit thresholds. Specifically, after data field validation is completed, if the data field validation result indicates that the amount of business data exceeds the limit, an alarm page will be displayed. For example, when the field validation result indicates that the number of business scenarios exceeds the limit, an alarm page will pop up. Figure 18 As shown, when the number of queries exceeds the threshold, the alarm page displays the specific business data exceeding the limit (i.e., the number of queries). It can also display the business data of the number of key business identifiers (IDs) obtained and the business data of the upper limit threshold, which can be used to help determine the extent to which the business data exceeds the limit.

[0172] The data field processing method provided in this embodiment triggers an anomaly alarm and displays corresponding alarm information when the data field validation result indicates abnormal business data, making it easier to clarify the details of the abnormal data and take appropriate handling measures. When the data field validation result indicates that the amount of business data exceeds the limit, an over-limit alarm is triggered to enable call rate limiting, thereby achieving dynamic rate limiting.

[0173] As a specific application embodiment of the present invention, such as Figure 19 The illustrated operational architecture diagram includes a presentation layer, an interface layer, a business logic layer, and a data layer, providing basic capabilities such as tag management, alarm services, traffic overload control, and access control. Specifically, technical personnel can create business lines, data models, and validation rules through the management backend in the presentation layer. The management backend connects to the business logic layer via an RPC interface in the interface layer. Correspondingly, the business logic layer responds to the creation operations performed by technical personnel, executing business line management functions according to business line creation logic, data acquisition functions according to data model creation logic, and rule management functions according to rule creation logic. Simultaneously, it stores the created data models and business scenario information in the database of the data layer.

[0174] Technical personnel can manually trigger the debugging of data models, business scenarios under business lines, and validation rules through the data validation system interface at the presentation layer. This allows them to associate the debugged data models with the business scenarios under business lines, extract associated business data through the data models, verify the extracted business data using validation rules, obtain the corresponding validation data, and store the validation data in the corresponding database.

[0175] Alternatively, a scheduled task can be set up through the data validation system at the presentation layer. This scheduled task can trigger the asynchronous retrieval of business data corresponding to the business scenario and perform field validation on the asynchronously retrieved data. If abnormal data is found in the validated data, batch alarm processing or individual alarm processing can be performed on the abnormal data, and the abnormal data can be stored.

[0176] Experimental data verification shows that using the data verification system for business data field verification improves field verification efficiency (shortening the field verification development cycle by 70% and increasing batch interface call efficiency by 4 times); reduces costs by avoiding the maintenance costs of scheduled task verification in multiple business scenarios, saving server resources, supporting the reuse of existing data models for rapid rule creation within the same business, and reducing redundant development; and improves accuracy and timeliness by reducing rule verification time from hours to minutes through real-time debugging, sending alarms promptly and displaying issues, ensuring timely verification of relevant fields.

[0177] This embodiment also provides a data field processing apparatus for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0178] This embodiment provides a data field processing device, such as... Figure 20 As shown, it includes:

[0179] The business line creation module 501 is used to respond to the business line creation operation for the target business and obtain at least one target business line corresponding to the target business.

[0180] The data model creation module 502 is used to respond to the association operation of multiple data sources corresponding to the target business line and obtain at least one business data model corresponding to each target business line.

[0181] The business data association module 503 is used to respond to the selection operation for the data model, determine the target data model corresponding to the target business line from at least one business data model, and extract the business data that matches the target business line according to the target data model.

[0182] The rule configuration module 504 is used to determine the target validation rule corresponding to the target data model in response to the configuration operation for the field validation rule.

[0183] The field validation module 505 is used to validate the data fields of business data according to the target validation rules and obtain the data field validation results.

[0184] In some alternative implementations, the business line creation module 501 includes:

[0185] The first page display unit is used to respond to the business line creation operation for the target business and display the business line editing page, which includes an attribute editing area.

[0186] The attribute editing unit is used to generate business attribute information in response to attribute editing operations in the attribute editing area.

[0187] The business line assembly unit is used to generate the target business line corresponding to the target business based on the business line identifier and business attribute information.

[0188] In some optional implementations, the business line creation module 501 further includes:

[0189] The management permission configuration unit is used to respond to configuration operations for management permissions and determine the management permissions for each target business line.

[0190] In some optional implementations, the business line creation module 501 further includes:

[0191] The display unit is used to display the set of business lines corresponding to the target business.

[0192] The search unit is used to determine the target business line search results from the business line set in response to a search operation on the business line set.

[0193] In some alternative implementations, the data model creation module 502 includes:

[0194] The second page display unit is used to respond to the data model creation operation and display the data model creation page, which includes a model attribute editing area and a model structured language editing area.

[0195] The model attribute editing unit is used to obtain data model attribute information in response to model attribute editing operations in the model attribute editing area.

[0196] The association unit is used to respond to data source request association operations in the model structured language editing area and obtain association information between multiple data sources.

[0197] The fusion unit is used to fuse data model attribute information and association information to generate at least one business data model corresponding to the target business line.

[0198] In some optional implementations, the aforementioned associated unit includes:

[0199] The call configuration subunit is used to respond to call configuration operations generated for each data source request and to determine the call information between each data source request.

[0200] The identifier acquisition sub-unit is used to obtain the request identifier corresponding to each data source request.

[0201] The information association subunit is used to respond to information association operations based on call information, and associate various data source requests according to the request identifier to obtain association information.

[0202] In some optional implementations, the data model creation page includes a model parameter debugging area, and the aforementioned data model creation module 502 further includes:

[0203] The debugging unit is used to respond to model debugging operations generated in the model parameter debugging area and obtain the debugging results of the target data model.

[0204] In some optional implementations, the business data association module 503 includes:

[0205] The third page display unit is used to respond to the creation operation of business information and display the business information creation page, which includes the first data model configuration area.

[0206] A model selection unit is used to determine a target data model from at least one business data model in response to a model selection operation generated in the first data model configuration area.

[0207] The scheduling configuration unit is used to determine the data scheduling parameters of the target business line in response to the scheduling configuration operation for the target business line.

[0208] The data extraction unit is used to extract business data according to the data scheduling parameters using the target data model.

[0209] In some optional implementations, the rule configuration module 504 includes:

[0210] The fourth page display unit is used to respond to the creation operation of validation rules and display the rule creation page, which includes the second data model configuration area and the rule configuration area.

[0211] The model configuration unit is used to determine the target data model corresponding to the rule to be configured in response to the model configuration operation generated in the second data model configuration area.

[0212] The rule configuration unit is used to generate target validation rules that match the target data model in response to rule configuration operations generated in the rule configuration area.

[0213] In some optional implementations, the rule configuration area includes an expression configuration area and a data value configuration area, and the rule configuration unit includes:

[0214] The expression configuration subunit is used to generate the target expression corresponding to the target data model in response to the rule expression configuration operation generated in the expression configuration area.

[0215] The numerical configuration subunit is used to obtain the target data value corresponding to the target expression in response to the numerical configuration operation generated in the data value configuration area.

[0216] The information assembly subunit is used to assemble the target expression and the target data value to generate the target verification rules.

[0217] In some alternative embodiments, the above-described apparatus further includes:

[0218] The first anomaly display module is used to display the location of the anomaly in the business data, as well as the data model and field validation rules associated with the business data, if the data field validation result indicates that the business data is abnormal.

[0219] The second anomaly display module is used to display the excess parameter information of the business data if the data field validation result indicates that the amount of business data exceeds the limit.

[0220] The data field processing apparatus provided in this disclosure can execute the data field processing method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects of the execution method. It supports the flexible creation of business lines for target businesses. By associating multiple data sources corresponding to each target business line, at least one business data model corresponding to each target business line is obtained. This allows for the selection of the target data model corresponding to the target business line according to actual needs, enabling the acquisition of business data using the target data model. Thus, the ability to acquire business data is no longer limited to direct database connections or simple cross-table connections, ensuring the capability to acquire business data. By configuring target validation rules to match the target data model with the target validation rules, a unified target validation rule can be used to validate the fields of business data, improving the configuration flexibility of the target validation rules. Furthermore, by validating the data fields of the business data according to the target validation rules, accurate verification of the business data fields can be achieved.

[0221] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0222] Figure 21 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure.

[0223] The following is a detailed reference. Figure 21 This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present disclosure. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0224] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 21 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0225] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory 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 a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the data field processing method of embodiments of this disclosure.

[0226] Figure 21 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0227] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the data field processing methods shown in the above embodiments are implemented.

[0228] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0229] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for processing a data field, characterized in that, The method includes: In response to a business line creation operation for a target business, at least one target business line corresponding to the target business is obtained; In response to the association operation of multiple data sources corresponding to the target business line, at least one business data model corresponding to each target business line is obtained; In response to a selection operation for a data model, a target data model corresponding to the target business line is determined from at least one of the business data models, and business data matching the target business line is extracted according to the target data model. In response to the configuration operation for the field validation rules, the target validation rules corresponding to the target data model are determined; The data fields of the business data are validated according to the target validation rules to obtain the data field validation results.

2. The method according to claim 1, characterized in that, The step of responding to a business line creation operation for a target business and obtaining at least one target business line corresponding to the target business includes: In response to a business line creation operation for the target business, a business line editing page is displayed, which includes an attribute editing area; In response to an attribute editing operation in the attribute editing area, business attribute information is generated; Based on the business line identifier and the business attribute information, the target business line corresponding to the target business is generated.

3. The method according to claim 2, characterized in that, Also includes: In response to configuration operations for management permissions, determine the management permissions for each of the target business lines.

4. The method according to claim 2, characterized in that, Also includes: Display the set of business lines corresponding to the target business; In response to a search operation on the set of business lines, the search results for the target business line are determined from the set of business lines.

5. The method according to claim 1, characterized in that, The step of responding to the association operation for multiple data sources corresponding to the target business line, and obtaining at least one business data model corresponding to each target business line, includes: In response to a data model creation operation, a data model creation page is displayed, which includes a model attribute editing area and a model structured language editing area; In response to the model attribute editing operation in the model attribute editing area, data model attribute information is obtained; In response to the data source request association operation in the model structured language editing area, association information between multiple data sources is obtained; By integrating the data model attribute information and the association information, at least one business data model corresponding to the target business line is generated.

6. The method according to claim 5, characterized in that, In response to a data source request association operation in the model structured language editing area, association information between multiple data sources is obtained, including: In response to the call configuration operation generated by each of the data source requests, determine the call information between the various data source requests; Obtain the request identifier corresponding to each of the aforementioned data source requests; In response to the information association operation based on the call information, each of the data source requests is associated according to the request identifier to obtain the association information.

7. The method according to claim 5 or 6, characterized in that, The data model creation page includes a model parameter debugging area, and the method further includes: In response to the model debugging operation generated in the model parameter debugging area, the debugging result of the target data model is obtained.

8. The method according to claim 1, characterized in that, The step of determining the target data model corresponding to the target business line from at least one of the business data models in response to a selection operation for a data model includes: In response to an operation to create business information, a business information creation page is displayed, the business information creation page including a first data model configuration area; In response to a model selection operation generated in the first data model configuration area, the target data model is determined from at least one of the business data models.

9. The method according to claim 8, characterized in that, The step of extracting business data that matches the target business line according to the target data model includes: In response to a scheduling configuration operation for the target service line, the data scheduling parameters for the target service line are determined; The business data is extracted using the target data model and according to the data scheduling parameters.

10. The method according to claim 1, characterized in that, The step of determining the target validation rule corresponding to the target data model in response to the configuration operation for the field validation rule includes: In response to the creation operation for the validation rule, a rule creation page is displayed, which includes a second data model configuration area and a rule configuration area; In response to the model configuration operation generated in the second data model configuration area, the target data model corresponding to the rule to be configured is determined; In response to a rule configuration operation generated in the rule configuration area, a target verification rule matching the target data model is generated.

11. The method according to claim 10, characterized in that, The rule configuration area includes an expression configuration area and a data value configuration area. The step of generating target validation rules that match the target data model in response to a rule configuration operation generated in the rule configuration area includes: In response to the rule expression configuration operation generated in the expression configuration area, a target expression corresponding to the target data model is generated; In response to a numerical configuration operation generated in the data value configuration area, the target data value corresponding to the target expression is obtained; The target expression and the target data value are assembled to generate the target verification rule.

12. The method according to claim 1, characterized in that, Also includes: If the data field validation result indicates that the business data is abnormal, then the location of the abnormality in the business data, as well as the data model and field validation rules associated with the business data, will be displayed. And / or, if the data field verification result indicates that the amount of business data exceeds the limit, then the excess parameter information of the business data is displayed.

13. A data field processing apparatus, characterized in that, The device includes: A business line creation module is used to respond to a business line creation operation for a target business and obtain at least one target business line corresponding to the target business. The data model creation module is used to respond to the association operation of multiple data sources corresponding to the target business line to obtain at least one business data model corresponding to each target business line. A business data association module is used to respond to a selection operation for a data model, determine the target data model corresponding to the target business line from at least one of the business data models, and extract business data that matches the target business line according to the target data model. The rule configuration module is used to determine the target validation rule corresponding to the target data model in response to the configuration operation for the field validation rule; The field validation module is used to validate the data fields of the business data according to the target validation rules and obtain the data field validation results.

14. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the data field processing method of any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the processing method of the data field according to any one of claims 1 to 12.

16. A computer program product, characterized in that, It includes computer instructions for causing a computer to perform the processing method for the data field according to any one of claims 1 to 12.

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