Class C expression-based rule formulation calculation method and system

Abstract

The invention relates to a rule formulation calculation method and system based on a class C expression. The method comprises the following steps that data connection is established between a data warehouse and each field of ERP, and required data are extracted from each field of ERP regularly by using data extraction, conversion and loading ETL tools and a data synchronization technology; performing association and aggregation operation on the integrated data based on business requirements and analysis dimensions according to ERP field data extracted by a data warehouse, and generating a data wide table; a grammar system suitable for business rule description is constructed on the basis of a class C expression, and a user freely combines grammar and variables according to business rule requirements through a graphical interface or a text editing mode to generate a job task; and when the generated task operation is executed, extracting corresponding data from the data wide table, mapping the data to a variable of the operation task, loading a formula corresponding to the grammar, and outputting a corresponding calculation result.

Description

Technical Field

[0001] The present application relates to the field of database technology, and more specifically, to a rule-formulated calculation method and system based on C-like expressions. Background Art

[0002] In the widespread application of enterprise resource planning (ERP) systems, the complexity of data processing and rule calculation has become increasingly prominent. Traditional calculation methods often rely on hard coding to implement business rules, which has many limitations.

[0003] On the one hand, the hard-coding method makes the business rules and the code tightly coupled. When the business requirements change, the code must be modified and go through a cumbersome release and launch process, which not only consumes a lot of time and manpower costs, but may also introduce new errors and reduce system stability.

[0004] On the other hand, traditional computing methods lack flexibility and scalability. The business rules of different enterprises or different development stages of the same enterprise vary significantly, and hard coding is difficult to adapt to diverse needs. Moreover, as the ERP system covers more areas, such as material requirement planning (MRP), master data, warehousing, operations and inventory centers, the amount of data has increased dramatically. The performance bottleneck of traditional computing methods is becoming more and more prominent when processing large-scale complex data, and the computing efficiency is low, which cannot meet the real-time and accuracy requirements of enterprises.

[0005] Furthermore, traditional systems have defects in data management. There is a lack of efficient mechanisms for data extraction, conversion, and loading, making it difficult to ensure data timeliness and integrity. At the same time, data tracking and auditing capabilities are weak. When data problems arise, it is difficult to trace the source, and it is impossible to locate the root cause and solve it in time, affecting data quality and decision reliability.

[0006] Existing technologies such as the Chinese patent number "CN117314267A" disclose a data-driven model building method for business applications that can be quickly configured. The method includes S1, obtaining metadata; S2, obtaining factors based on the metadata; S3, the factors form restrictions through comparison operators; S4, generating SQL statements based on metadata, factors and restrictions, encapsulating them into a model and executing them to obtain indicator calculation results. The invention encapsulates and forms a model for calculating indicators based on metadata, factors and restrictions. The model supports online development and takes effect immediately after configuration is completed without redeploying the system. In addition, each department has many personalized needs in the management process, and each need requires the system to be redeployed, which affects the efficiency of indicator calculation.

[0007] The problem with the above-mentioned prior art is that the method is weak in data problem tracing and monitoring, which affects the credibility of data and the scientific nature of decision-making. In addition, the method still requires technical personnel to develop and configure online, and the timeliness of data processing cannot be guaranteed. Summary of the invention

[0008] In order to solve the above technical problems, the present invention proposes a rule-formulated calculation method and system based on C-like expressions.

[0009] The technical solution of the present invention is as follows:

[0010] The present invention proposes a rule-formulated calculation method based on a C-like expression, comprising the following steps:

[0011] Step S1, the data warehouse is connected to the data in various ERP fields, and the required data is regularly extracted from various ERP fields using data extraction, transformation and loading (ETL) tools and data synchronization technology; the ERP fields include: material demand planning (MRP) field, master data field, warehousing field, operation field and inventory center;

[0012] Step S2: Based on the data of various fields of ERP extracted from the data warehouse, the integrated data is associated and aggregated based on business needs and analysis dimensions to generate a data wide table;

[0013] Step S3, building a grammar system suitable for business rule description based on C-like expressions, and users can freely combine grammars and variables to generate job tasks according to business rule requirements through a graphical interface or text editing method;

[0014] Step S4, when the generated task job is executed, the corresponding data is extracted from the data wide table and mapped to the variables of the job task, and the formula corresponding to the syntax is loaded to output the corresponding calculation result.

[0015] As a preferred implementation, the data warehouse uses change data capture CDC technology to monitor changes in data sources in various fields of ERP in real time. Once data is inserted, updated or deleted, it is immediately captured and loaded into the data warehouse by combining with the message queue Kafka to avoid data loss or repeated loading.

[0016] As a preferred implementation, a data tracking and auditing mechanism is established in the data warehouse to record the source, conversion process and usage of data; through log recording and data lineage analysis technology, the root cause of data problems can be quickly located and the data change history can be traced.

[0017] As a preferred implementation, by setting the fields and indexes of the data wide table, data sharing and reuse efficiency is improved, and data redundancy and inconsistency are reduced.

[0018] As a preferred implementation, the job tasks are generated by freely combining syntax and variables according to business rule requirements; wherein the variables are divided into static variables and dynamic variables, the static variables remain unchanged during the entire calculation process, and the dynamic variables change dynamically according to the calculation cycle or other business conditions.

[0019] As a preferred implementation, when the generated task job is executed, the corresponding data is extracted from the data wide table and mapped to the variables of the job task, and the formula corresponding to the syntax is loaded to output the corresponding calculation result, which specifically includes the following steps:

[0020] Batch obtain variable corresponding data from the data wide table, and accurately map the fields in the data wide table to the object attributes in the memory according to the definition of the variables in the formula through data mapping technology; load the custom formula of the corresponding market from the configuration center or database, and parse it into a syntax tree structure;

[0021] Use the syntax parser to perform syntax check on the loaded formula to ensure that the formula complies with the predefined syntax rules; if syntax errors are found, error information is fed back to the user to prompt the user to make corrections; dynamically convert the formula according to the task requirements, by identifying the placeholders in the formula and replacing the placeholders with actual values ​​based on the current calculation information, and dynamically adjust the relevant parameters according to the time period in the business rules;

[0022] The reflection principle is used to parse the formula, and the variables in the formula are replaced with the actual object attribute values ​​according to the mapping relationship between the variables and the object attributes. Then the formula syntax tree structure is used to parse and execute the calculation operations in sequence to obtain the calculation results.

[0023] On the other hand, the present invention also provides a rule-formulated computing system based on a C-like expression, comprising:

[0024] Data warehouse establishment module, data connection between data warehouse and various ERP fields, using ETL tools and data synchronization technology to regularly extract required data from various ERP fields; ERP fields include: MRP field, master data field, warehousing field, operation field and inventory center;

[0025] The data wide table generation module generates data wide tables by associating and aggregating the integrated data based on business needs and analysis dimensions according to the data in various fields of ERP extracted from the data warehouse;

[0026] The job task generation module builds a grammar system suitable for business rule description based on C-like expressions. Users can freely combine grammars and variables to generate job tasks according to business rule requirements through a graphical interface or text editing.

[0027] The job task calculation module extracts the corresponding data from the data wide table and maps it to the variables of the job task when the generated task job is executed, and loads the formula corresponding to the syntax to output the corresponding calculation result.

[0028] As a preferred implementation, the data warehouse in the data warehouse establishment module uses change data capture CDC technology to monitor changes in data sources in various fields of ERP in real time. Once data is inserted, updated or deleted, it is immediately captured and loaded into the data warehouse by combining with the message queue Kafka to avoid data loss or repeated loading.

[0029] On the other hand, the present invention further provides an electronic device having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program implements a rule-formulated calculation method based on a C-like expression as described in any embodiment of the present invention.

[0030] On the other hand, the present invention also provides a computer-readable medium for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement a rule-formulated calculation method based on C-like expressions as described in any embodiment of the present invention.

[0031] The present invention has the following beneficial effects:

[0032] 1. Significantly improved performance: The job is distributed and controlled using coroutines, and each market is calculated concurrently. It only takes 8 minutes to generate the entire market. The traditional solution is estimated to be around 60-120 minutes. As the business scale grows, the amount of data in various fields of ERP is increasing. It is estimated that one year after the launch, the time required to generate the entire market will increase to 12-15 minutes. If the business needs to improve performance again, MRP's own services can achieve performance improvement through coroutine processing at the detailed data level, historical data archiving of large data tables, server upgrades, and cluster deployment.

[0033] 2. High scalability: The MRP service can freely control the performance improvement space, overcome the delay problem of calling third-party interfaces in the traditional mode, and the need to limit the flow and frequency to avoid affecting the service performance in other areas and the expansion of operation logs. Each time the interface is called, it is necessary to record parameters and return values.

[0034] 3. Timely meet the needs of business changes: In the scenario of business logic change, there is no need to release the code online. Users can customize formulas and adjust strategies at any time; reduce the IT personnel resources invested in each business change; formulas are more intuitive and clear than codes, and businesses can independently and efficiently confirm existing logic without contacting developers for assistance. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 This is a schematic diagram of the method flow of Example 1;

[0037] Figure 2 This is a schematic diagram of the data wide table fields;

[0038] Figure 3 This is a schematic diagram of variable attributes in a job task;

[0039] Figure 4 This is a flow chart of dynamic conversion of task execution formula in Example 1. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0042] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0043] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0044] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0045] Embodiment 1:

[0046] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be combined with the specific embodiments of the present application and refer to the attached Figure 1 , clearly and completely describe the technical solution of the present invention.

[0047] To solve the problems in the prior art, the present invention provides a rule-formulated calculation method based on a C-like expression, comprising the following steps:

[0048] Step S1, the data warehouse is connected to the data in various ERP fields, and the required data is regularly extracted from various ERP fields using data extraction, transformation and loading (ETL) tools and data synchronization technology; the ERP fields include: material demand planning (MRP) field, master data field, warehousing field, operation field and inventory center;

[0049] The data warehouse uses change data capture CDC technology to monitor changes in data sources in various fields of ERP in real time. Once data is inserted, updated or deleted, it is immediately captured and loaded into the data warehouse by combining with the message queue Kafka to avoid data loss or repeated loading.

[0050] In this embodiment:

[0051] In the process of loading data from various business systems into the data warehouse, CDC technology can obtain data changes in the source system in real time, and load these changed data into the data warehouse in a timely manner to ensure that the data in the data warehouse is always up to date.

[0052] When data synchronization needs to be maintained between multiple systems, CDC technology can effectively capture data changes in one system and synchronize these changes to other systems.

[0053] Through the capabilities of the data warehouse, data is aggregated into the data warehouse field, replacing the method of obtaining data from various ERP fields through multiple interfaces, eliminating the isolation between fields. Some simple business logic processing is placed at the data warehouse level to reduce the logical operations of actual job operations, and to a certain extent reduce the complexity of custom task operation formulas.

[0054] A data tracking and auditing mechanism is established in the data warehouse to record the source, conversion process and usage of the data; through log recording and data lineage analysis technology, the root cause of data problems can be quickly located and the data change history can be traced.

[0055] In this embodiment: by capturing changes in data, the enterprise can audit the operation history of the data to ensure that the use and modification of the data complies with the company's regulations and relevant laws and regulations.

[0056] Step S2: Based on the data of various fields of ERP extracted from the data warehouse, the integrated data is associated and aggregated based on business needs and analysis dimensions to generate a data wide table;

[0057] By setting the fields and indexes of the data wide table, data sharing and reuse efficiency is improved, and data redundancy and inconsistency are reduced.

[0058] In this embodiment, data in various fields of ERP need to be preloaded and placed on the data warehouse wide table through certain business logic. The fields of the data wide table are as follows: Figure 2 As shown. This data wide table can be used not only for delivery planning operations, but also for other business scenarios, including quickBI purposes and algorithm model data sources.

[0059] Step S3, building a grammar system suitable for business rule description based on C-like expressions, and users can freely combine grammars and variables to generate job tasks according to business rule requirements through a graphical interface or text editing method;

[0060] The described free combination of syntax and variables generates job tasks according to business rule requirements; wherein variables are divided into static variables and dynamic variables, static variables remain unchanged during the entire calculation process, and dynamic variables change dynamically according to the calculation cycle or other business conditions.

[0061] In this embodiment: the generated job task calculation formula consists of syntax plus variables; the syntax is implemented based on the C-like expression, and is derived from the basic syntax of if (condition, expression 1, expression 2). Variables are divided into static variables and dynamic variables, which are closely related to the actual business scenario. Variables can be regarded as attributes of a sku, such as Figure 3 shown.

[0062] Step S4, when the generated task job is executed, the corresponding data is extracted from the data wide table and mapped to the variables of the job task, and the formula corresponding to the syntax is loaded to output the corresponding calculation result.

[0063] When the generated task job is executed, the corresponding data is extracted from the data wide table and mapped to the variables of the job task, and the formula corresponding to the syntax is loaded to output the corresponding calculation result, which specifically includes the following steps:

[0064] Step S401, batch obtain variable corresponding data from the data wide table, and accurately map the fields in the data wide table to the object attributes in the memory according to the definition of the variables in the formula through data mapping technology; load the custom formula corresponding to the market from the configuration center or database, and parse it into a syntax tree structure;

[0065] Step S402, using a syntax parser to perform syntax check on the loaded formula to ensure that the formula complies with predefined syntax rules; if a syntax error is found, error information is fed back to the user to prompt the user to make corrections; the formula is dynamically converted according to the task requirements, by identifying the placeholders in the formula and replacing the placeholders with actual values ​​in combination with the current calculation information, and at the same time, the relevant parameters are dynamically adjusted according to the time period in the business rules;

[0066] Step S403, using the reflection principle to parse the formula, replacing the variables with actual object attribute values ​​according to the mapping relationship between the variables and the object attributes in the formula, and then parsing and executing the calculation operations in sequence according to the formula syntax tree structure to obtain the calculation result.

[0067] In this embodiment, the task operation includes the following steps when it is executed:

[0068] The first step is to preload data. Get the batch data corresponding to the task variables from the data wide table, format it, map the fields of the data wide table to the attributes of the object according to the variables in the formula, and load it into memory.

[0069] The second step is to obtain the task formula, use the syntax parser to check the loaded formula syntax, and perform dynamic conversion

[0070] In the process of calculating the 48 data results of 48 weeks, the latest formula is converted by week, and the latest data of the corresponding week is loaded in real time for calculation.

[0071] For example, in the process of calculating the 48 data results of 48 weeks, the latest formula is converted by week, and the latest data of the corresponding week is loaded in real time for calculation. Given the current inventory and weekly shipment data for the next 48 weeks, it is necessary to predict the inventory from the 2nd week to the next 48 weeks. Then start the calculation from the 2nd week, the inventory of the 2nd week = the inventory of the 1st week - the shipment number of the 2nd week, and then calculate the inventory of the 3rd week = the inventory of the 2nd week - the shipment number of the 3rd week, and then calculate the inventory of the 4th week = the inventory of the 3rd week - the shipment number of the 4th week, and so on, and finally calculate the 48 inventory data of 48 weeks. The logic of dynamic conversion of formulas is as follows: Figure 4 shown.

[0072] The third step is to retrieve the object data from the memory, use the reflection principle to parse the formula, map the variables to the object attributes, and parse the various syntax of the formula, including addition, subtraction, multiplication and division operations, and finally calculate the result.

[0073] At the same time, the real-time calculation results are written into the current object attributes to implement the dynamic calculation mentioned in step 2. For example, when calculating the number of shipments and inventory in the second week, first get the number of shipments in the second week, write the W2 shipment number into the object, and then calculate the inventory in the second week = the inventory in the first week - the number of shipments in the second week; after getting the number of shipments in the third week, write the W3 shipment number into the object, and then calculate the inventory in the third week = the inventory in the second week - the number of shipments in the third week; and so on to get the final calculation result.

[0074] Embodiment 2:

[0075] This embodiment provides a rule-formulated computing system based on a C-like expression, including:

[0076] Data warehouse establishment module, data connection between data warehouse and various ERP fields, using ETL tools and data synchronization technology to regularly extract required data from various ERP fields; ERP fields include: MRP field, master data field, warehousing field, operation field and inventory center;

[0077] The data wide table generation module generates data wide tables by associating and aggregating the integrated data based on business needs and analysis dimensions according to the data in various fields of ERP extracted from the data warehouse;

[0078] The job task generation module builds a grammar system suitable for business rule description based on C-like expressions. Users can freely combine grammars and variables to generate job tasks according to business rule requirements through a graphical interface or text editing.

[0079] The job task calculation module extracts the corresponding data from the data wide table and maps it to the variables of the job task when the generated task job is executed, and loads the formula corresponding to the syntax to output the corresponding calculation result.

[0080] Embodiment three:

[0081] This embodiment provides an electronic device having a computer program stored thereon, wherein when the computer program is executed by a processor, a rule-formulated calculation method based on a C-like expression as described in any embodiment of the present invention is implemented.

[0082] Embodiment 4:

[0083] This embodiment provides a computer-readable medium for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement a rule-formulated calculation method based on C-like expressions as described in any embodiment of the present invention.

[0084] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0085] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0086] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0087] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0088] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A rule-formulated calculation method based on C-like expressions, characterized in that: The following steps are involved: Step S1, the data warehouse is connected to each field of ERP, and the required data is regularly extracted from each field of ERP using data extraction, transformation and loading (ETL) tools and data synchronization technology; The ERP fields include: Material Requirements Planning (MRP) field, Master Data field, Warehousing field, Operations field and Inventory Center; Step S2: Based on the data of various fields of ERP extracted from the data warehouse, the integrated data is associated and aggregated based on business needs and analysis dimensions to generate a data wide table; Step S3, building a grammar system suitable for business rule description based on C-like expressions, and users can freely combine grammars and variables to generate job tasks according to business rule requirements through a graphical interface or text editing method; Step S4, when the generated task job is executed, the corresponding data is extracted from the data wide table and mapped to the variables of the job task, and the formula corresponding to the syntax is loaded to output the corresponding calculation result.

2. A rule-formulated calculation method based on a C-like expression according to claim 1, characterized in that: The data warehouse uses change data capture CDC technology to monitor changes in data sources in various fields of ERP in real time. Once data is inserted, updated or deleted, it is immediately captured and loaded into the data warehouse by combining with the message queue Kafka to avoid data loss or repeated loading.

3. The rule-formulated calculation method based on C-like expressions according to claim 1, characterized in that: A data tracking and auditing mechanism is established in the data warehouse to record the source, conversion process and usage of the data; through log recording and data lineage analysis technology, the root cause of data problems can be quickly located and the data change history can be traced.

4. A rule-formulated calculation method based on a C-like expression according to claim 1, characterized in that: By setting the fields and indexes of the data wide table, data sharing and reuse efficiency is improved, and data redundancy and inconsistency are reduced.

5. The rule-formulated calculation method based on C-like expressions according to claim 1, characterized in that: The described free combination of syntax and variables generates job tasks according to business rule requirements; wherein variables are divided into static variables and dynamic variables, static variables remain unchanged during the entire calculation process, and dynamic variables change dynamically according to the calculation cycle or other business conditions.

6. A rule-formulated calculation method based on a C-like expression according to claim 1, characterized in that: When the generated task job is executed, the corresponding data is extracted from the data wide table and mapped to the variables of the job task, and the formula corresponding to the syntax is loaded to output the corresponding calculation result, which specifically includes the following steps: Batch obtain the data corresponding to the variables from the data wide table, and use data mapping technology to accurately map the fields in the data wide table to the object attributes in the memory according to the definition of the variables in the formula; Load the custom formula for the corresponding market from the configuration center or database and parse it into a syntax tree structure; Use the syntax parser to perform syntax check on the loaded formula to ensure that the formula complies with the predefined syntax rules; if syntax errors are found, error information is fed back to the user to prompt the user to make corrections; dynamically convert the formula according to the task requirements, by identifying the placeholders in the formula and replacing the placeholders with actual values ​​based on the current calculation information, and dynamically adjust the relevant parameters according to the time period in the business rules; The reflection principle is used to parse the formula, and the variables in the formula are replaced with the actual object attribute values ​​according to the mapping relationship between the variables and the object attributes. Then the formula syntax tree structure is used to parse and execute the calculation operations in sequence to obtain the calculation results.

7. A rule-formulated computing system based on C-like expressions, characterized in that: include: Data warehouse establishment module, data connection between data warehouse and various fields of ERP, using ETL tools and data synchronization technology to regularly extract required data from various fields of ERP; The various areas of ERP include: MRP area, master data area, warehousing area, operations area and inventory center; The data wide table generation module generates data wide tables by associating and aggregating the integrated data based on the data in various fields of ERP extracted from the data warehouse and business needs and analysis dimensions; The job task generation module builds a grammar system suitable for business rule description based on C-like expressions. Users can freely combine grammars and variables to generate job tasks according to business rule requirements through a graphical interface or text editing. The job task calculation module extracts the corresponding data from the data wide table and maps it to the variables of the job task when the generated task job is executed, and loads the formula corresponding to the syntax to output the corresponding calculation result.

8. According to a rule-formulated computing system based on class C expressions as described in claim 7: the data warehouse in the data warehouse establishment module uses change data capture CDC technology to monitor changes in data sources in various fields of ERP in real time. Once data is inserted, updated or deleted, it is immediately captured and combined with the message queue Kafka to load the incremental data into the data warehouse to avoid data loss or repeated loading.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for calculating by formulating rules based on C-like expressions as described in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements a rule-formulated calculation method based on a C-like expression as described in any one of claims 1 to 6.

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