Data processing method, device and equipment and computer readable storage medium

Abstract

The invention discloses a data processing method, device and equipment and a computer readable storage medium, and the method comprises the steps: obtaining a rule element corresponding to a target business rule in a calculation rule table through a calculation model when a calculation operation corresponding to the target business rule in the calculation rule table is detected; performing data extraction operation on source data corresponding to a target business rule through a calculation model based on an entry class corresponding to the target business rule in the rule elements to obtain a data extraction result; performing data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule; and storing the target data based on the calculation rule table through a calculation model. According to the invention, the method can achieve the multiplexing of the rules of the same processing logic among different business rules, reduces the system risk caused by the frequent change of the business rules, reduces the development cost, and improves the efficiency of settlement and settlement.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, device, equipment and computer-readable storage medium. Background Art

[0002] Clearing and delivery is the integration of transaction data in various dimensions such as transaction type and delivery time. Currently, the logic of clearing and delivery is often hard-coded according to actual business rules. This results in repeated coding of the same processing logic between different business rules, which is not conducive to the business's rapid response to changes in clearing and delivery rules. In addition, modifications have a wide impact and high business risks.

[0003] Therefore, how to improve the reuse of the same processing logic between different business rules, reduce the system risks caused by frequent changes in business rules, and reduce development costs is a problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of this application is to provide a data processing method, device, equipment and computer-readable storage medium, aiming to solve the technical problem of how to improve the reuse of the same processing logic between different business rules, reduce the system risks caused by frequent changes in business rules, and reduce development costs.

[0005] To achieve the above object, the present application provides a data processing method, which comprises the following steps:

[0006] When a calculation operation corresponding to a target business rule in the calculation rule table is detected, a rule element corresponding to the target business rule is obtained in the calculation rule table through a calculation model;

[0007] Performing a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result;

[0008] Performing a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule;

[0009] The target data is stored based on the calculation rule table through a calculation model.

[0010] Furthermore, the step of performing a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through the calculation model to obtain the data extraction result includes:

[0011] Obtaining data extraction logic rules based on the entry class corresponding to the target business rule in the rule element through the calculation model;

[0012] A data extraction operation is performed on the source data corresponding to the target business rule based on the data extraction logic rule through a calculation model to obtain a data extraction result.

[0013] Furthermore, the step of performing a data conversion operation on the data extraction result based on the calculation rule table through the calculation model to obtain the target data corresponding to the target business rule includes:

[0014] Obtaining the data conversion logic rule corresponding to the target business rule in the calculation rule table based on the source data and the data target corresponding to the target business rule through the calculation model;

[0015] The target data is obtained by performing data conversion on the data extraction result based on the data conversion logic rule through the calculation model.

[0016] Furthermore, the data conversion logic rules include data mapping rules, product conversion rules and date conversion rules, and the step of performing data conversion on the data extraction result based on the data conversion logic rules through the calculation model to obtain the target data includes:

[0017] Mapping the field data of the data extraction result to the field data of the target data based on the data mapping rule through a calculation model;

[0018] Based on the product conversion rule, the securities account number in the data extraction result is converted into the product number of the target data by means of a calculation model;

[0019] The settlement institution settlement date and the system settlement date corresponding to the target data are determined by a calculation model based on the date conversion rule.

[0020] Furthermore, the step of performing a storage operation on the target data based on the calculation rule table by using a calculation model includes:

[0021] Obtaining, through a calculation model and based on target data, a data storage logic rule corresponding to the target business rule in the calculation rule table;

[0022] The target data is stored based on the data storage logic rules through a calculation model.

[0023] Furthermore, when the calculation operation corresponding to the business rule in the calculation rule table is detected, before the step of obtaining the rule element corresponding to the business rule in the calculation rule table through the calculation model, the data processing method further includes:

[0024] When a rule setting request is received, obtaining a rule element of a business rule to be set corresponding to the rule setting request;

[0025] The calculation rule table is updated based on the rule elements of the business rule to be set.

[0026] Furthermore, the rule elements of the business rules to be set include rule name, source data, target data, settlement institution settlement date rule, system settlement date rule and entry class.

[0027] In addition, to achieve the above-mentioned purpose, the present application also provides a data processing device, the data processing device comprising:

[0028] An acquisition module, configured to, when detecting a calculation operation corresponding to a target business rule in a calculation rule table, acquire a rule element corresponding to the target business rule in the calculation rule table through a calculation model;

[0029] An extraction module, used to perform a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result;

[0030] A conversion module, used to perform a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule;

[0031] A storage module is used to perform storage operation on the target data based on the calculation rule table through a calculation model.

[0032] In addition, to achieve the above-mentioned purpose, the present application also provides a data processing device, which includes: a memory, a processor, and a data processing program stored in the memory and executable on the processor, and the data processing program implements the steps of the aforementioned data processing method when executed by the processor.

[0033] In addition, to achieve the above-mentioned purpose, the present application also provides a computer-readable storage medium, on which a data processing program is stored, and when the data processing program is executed by a processor, the steps of the aforementioned data processing method are implemented.

[0034] The present application detects the calculation operation corresponding to the business rule in the calculation rule table, obtains the rule element corresponding to the business rule in the calculation rule table through the calculation model; then, based on the entry class corresponding to the business rule in the rule element, the calculation model performs a data extraction operation on the source data corresponding to the business rule to obtain the data extraction result; then, based on the calculation rule table, the calculation model performs a data conversion operation on the data extraction result to obtain the target data corresponding to the business rule; then, based on the calculation rule table, the calculation model performs a storage operation on the target data, and the calculation model calls the logic rules of the three major execution actions of extraction, conversion and storage in the calculation rule table to process the source data of the clearing and delivery, extracts it from the original transaction data according to the corresponding clearing and delivery business rule, aggregates it into the data actually required by the business by processing and converting the extracted data, and automatically stores it in the database corresponding to the clearing and delivery system, and automatically calls the corresponding logic rules in the calculation rule table to realize the reuse of rules with the same processing logic among different business rules, thereby reducing the system risk caused by frequent changes in business rules, reducing development costs, and improving the efficiency of clearing and delivery.

[0035] This application adopts a general computing model in conjunction with data rule configuration to structure the delivery data and isolate the changes between various rules to reduce system risks. At the same time, the computing model is used to abstract the three major steps of extraction, conversion, and storage to achieve maximum reuse of the same processing logic between different business rules, thereby reducing the cost of development investment. When the degree of rule change is basically the same, the development investment is reduced by about 30%, which greatly reduces development costs and improves the efficiency of clearing and delivery. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0038] Figure 1 A flowchart of the first embodiment of the data processing method of the present application is provided;

[0039] Figure 2 This is a schematic diagram of the module structure of the data processing device according to an embodiment of the present application;

[0040] Figure 3 This is a schematic diagram of the module structure of the data processing device according to an embodiment of the present application.

[0041] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0042] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0044] The main solution of the present application is: when a calculation operation corresponding to a business rule in a calculation rule table is detected, the rule element corresponding to the business rule is obtained in the calculation rule table through a calculation model; based on the entry class corresponding to the business rule in the rule element, a data extraction operation is performed on the source data corresponding to the business rule to obtain a data extraction result; based on the calculation rule table, a data conversion operation is performed on the data extraction result to obtain the target data corresponding to the business rule; based on the calculation rule table, a storage operation is performed on the target data through the calculation model.

[0045] At present, clearing and settlement is the integration of transaction data in terms of transaction type, settlement time and other dimensions. At present, the logic of clearing and settlement is often hard-coded according to actual business rules. There is a situation where the same processing logic is repeatedly coded between different business rules, which is not conducive to the business to quickly respond to changes in clearing and settlement rules. In addition, the scope of impact when modifying is large and the business risk is high. Therefore, how to improve the reuse of the same processing logic between different business rules, reduce the system risk caused by frequent changes in business rules, and reduce development costs is a problem that needs to be solved urgently.

[0046] The present application processes the source data of clearing and delivery by calling the logic rules of extraction, conversion and storage of three major execution actions in the calculation rule table through the calculation model, extracts the data from the original transaction data according to the corresponding clearing and delivery business rules, aggregates the extracted data into the data actually required by the business by processing and converting it, and automatically stores it in the database corresponding to the clearing and delivery system. By automatically calling the corresponding logic rules in the calculation rule table, the rules of the same processing logic can be reused among different business rules, thereby reducing the system risks brought about by frequent changes in business rules, reducing development costs, and improving the efficiency of clearing and delivery.

[0047] It should be noted that the execution subject of this embodiment may be a data processing device, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a data processing device capable of realizing the above functions, etc., and this embodiment does not specifically limit this. The following takes the data processing device as the execution subject as an example to illustrate this embodiment and the following embodiments.

[0048] Based on this, this application proposes a data processing method of the first embodiment, please refer to Figure 1 , the data processing method includes steps S101 to S104:

[0049] Step S101, when a calculation operation corresponding to a target business rule in a calculation rule table is detected, a rule element corresponding to the target business rule is obtained in the calculation rule table through a calculation model;

[0050] In this embodiment, business rules and calculation rule tables for various businesses that require clearing and settlement are pre-set in the calculation model. The business rules include multiple data extraction logic rules, multiple data conversion logic rules, and multiple data storage logic rules. The calculation rule table includes rule elements of multiple data extraction logic rules, multiple data conversion logic rules, and multiple data storage logic rules. The business rules of each business include a data extraction logic rule, a data conversion logic rule, and a data storage logic rule. The rule elements of the business rules include rule name, source data, target data, settlement agency settlement date rule, system settlement date rule, and entry class (rule processing entry class), etc.

[0051] In a feasible implementation manner, before step S101, the data processing method may further include steps a1 to a2:

[0052] Step a1, when a rule setting request is received, obtaining the business rule to be set corresponding to the rule setting request;

[0053] Step a2: updating the calculation rule table based on the business rules to be set.

[0054] In this embodiment, a calculation rule table corresponding to the calculation model is pre-set. Specifically, when a rule setting request is received, the rule elements of the business rules to be set corresponding to the rule setting request are obtained, and the calculation rule table is updated based on the rule elements of the business rules to be set, wherein the rule elements of the business rules to be set include rule name, source data, target data, settlement agency settlement date rule, system settlement date rule and entry class. Of course, the business rules to be set may also include a rule activation switch. By pre-setting the calculation rule table, rules with the same processing logic can be reused among different business rules.

[0055] In this embodiment, when a calculation operation corresponding to a target business rule in a calculation rule table is detected, the calculation model calls the calculation rule table and obtains the rule elements corresponding to the target business rule in the calculation rule table, including the rule name, source data, target data, settlement institution settlement date rule, system settlement date rule, and entry class.

[0056] It should be noted that when performing clearing and delivery, clearing and delivery can be performed according to all rules that have been enabled in the calculation rule table. For example, it is determined whether there are unprocessed target business rules in the calculation rule table. If there are unprocessed target business rules in the calculation rule table, the rule elements of the target business rules are obtained, and subsequent clearing and delivery processing is performed based on the rule elements. Alternatively, when it is determined that there are unprocessed target business rules in the calculation rule table, the calculation operation corresponding to the target business rule is triggered, and then it is determined that the calculation operation corresponding to the target business rule in the calculation rule table is detected.

[0057] Step S102, performing a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result;

[0058] In this embodiment, after obtaining the rule elements corresponding to the target business rules, the computing model obtains the entry class corresponding to the target business rules in the rule elements, and performs a data extraction operation on the source data corresponding to the target business rules based on the entry class to obtain a data extraction result. In a feasible implementation, step S102 may further include steps b1 to b2:

[0059] Step b1, obtaining data extraction logic rules based on the entry class corresponding to the target business rule in the rule element through a calculation model;

[0060] Step b2: performing data extraction operations on the source data corresponding to the target business rules based on the data extraction logic rules through the calculation model to obtain data extraction results.

[0061] In this embodiment, after obtaining the rule elements corresponding to the target business rules, the computing model obtains the data extraction logic rules based on the entry class corresponding to the target business rules in the rule elements, and the computing model performs data extraction operations on the source data corresponding to the target business rules based on the data extraction logic rules to obtain data extraction results. For example, the data extraction logic rules may include a cleaning class corresponding to the target business rules, and the source data is cleaned and filtered by running the logic code of the cleaning class, and the data required by the target business rules is extracted from the cleaned source data based on the specific data extraction rules in the data extraction logic rules to obtain data extraction results.

[0062] It should be noted that, for different businesses, since the extracted data are not the same, different data extraction logic rules can be set for different businesses.

[0063] Step S103, performing a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule;

[0064] In this embodiment, when the data extraction results are obtained, the calculation model performs data conversion operations on the data extraction results based on the calculation rule table to obtain the target data corresponding to the target business rules; specifically, the calculation model obtains the data conversion logic rules corresponding to the target business rules in the calculation rule table according to the source data and the data target, and performs data conversion on the data extraction results based on the data conversion logic rules to obtain the target data.

[0065] Step S104: storing the target data using a calculation model based on the calculation rule table.

[0066] In this embodiment, after obtaining the target data, the calculation model performs a storage operation on the target data based on the calculation rule table. Specifically, by obtaining the data storage logic rule in the calculation rule table, the target data is stored according to the data storage logic rule to achieve automatic storage of the business data corresponding to the target business rule. In a feasible implementation, step S104 may also include steps c1 to c2:

[0067] Step c1, obtaining the data storage logic rule corresponding to the target business rule in the calculation rule table based on the target data through the calculation model;

[0068] Step c2: performing storage operation on the target data based on the data storage logic rules through a calculation model.

[0069] In this embodiment, after obtaining the target data, the calculation model obtains the data storage logic rules corresponding to the target business rules in the calculation rule table based on the target data, and performs storage operations on the target data based on the data storage logic rules. For example, the data storage logic rules include a storage class, and the storage class implements the warehousing logic of the target data. The calculation model performs storage operations on the target data by calling the logic code of the storage class.

[0070] It should be noted that the logic code corresponding to the data storage logic rule can reuse the old business logic, automatically select the corresponding storage logic code to execute according to the target data, and persist the target data in the warehouse.

[0071] The data processing method proposed in this embodiment, when detecting the calculation operation corresponding to the business rule in the calculation rule table, obtains the rule element corresponding to the business rule in the calculation rule table through the calculation model; then, based on the entry class corresponding to the business rule in the rule element, the calculation model performs a data extraction operation on the source data corresponding to the business rule to obtain the data extraction result; then, based on the calculation rule table, the calculation model performs a data conversion operation on the data extraction result to obtain the target data corresponding to the business rule; then, based on the calculation rule table, the calculation model performs a storage operation on the target data, and the calculation model calls the logic rules of the three major execution actions of extraction, conversion and storage in the calculation rule table to process the source data of clearing and settlement, extracts it from the original transaction data according to the corresponding clearing and settlement business rule, aggregates it into the data actually required by the business by processing and converting the extracted data, and automatically stores it in the database corresponding to the clearing and settlement system, and automatically calls the corresponding logic rules in the calculation rule table, so that the rules of the same processing logic can be reused among different business rules, thereby reducing the system risk caused by the frequent changes of business rules, reducing the development cost, and improving the efficiency of clearing and settlement.

[0072] This application adopts a general computing model in conjunction with data rule configuration to structure the delivery data and isolate the changes between various rules to reduce system risks. At the same time, the computing model is used to abstract the three major steps of extraction, conversion, and storage to achieve maximum reuse of the same processing logic between different business rules, thereby reducing the cost of development investment. When the degree of rule change is basically the same, the development investment is reduced by about 30%, which greatly reduces development costs and improves the efficiency of clearing and delivery.

[0073] In a feasible implementation, step S103 may include steps S201 to S202:

[0074] Step S201, obtaining the data conversion logic rule corresponding to the target business rule in the calculation rule table based on the source data and the data target corresponding to the target business rule through the calculation model;

[0075] Step S202, performing data conversion on the data extraction result based on the data conversion logic rule through the calculation model to obtain the target data.

[0076] In this embodiment, when the data extraction result is obtained, the calculation model obtains the data conversion logic rule corresponding to the target business rule in the calculation rule table according to the source data and the data target, and performs data conversion on the data extraction result based on the data conversion logic rule to obtain the target data, so as to achieve accurate conversion of the source data and obtain the target data. In a feasible implementation, the data conversion logic rule includes data mapping rules, product conversion rules and date conversion rules, and step S202 may include steps d1 to d3:

[0077] Step d1, mapping the field data of the data extraction result to the field data of the target data based on the data mapping rule by means of a calculation model;

[0078] Step d2, converting the securities account number in the data extraction result into the product number of the target data based on the product conversion rule by using a calculation model;

[0079] Step d3, determining the settlement institution settlement date and system settlement date corresponding to the target data based on the date conversion rule through a calculation model.

[0080] In this embodiment, when the data extraction result is obtained, the calculation model obtains the data mapping rules, product conversion rules and date conversion rules in the data conversion logic rules. Based on the data mapping rules, the calculation model maps the field data of the data extraction result to the field data of the target data to achieve direct mapping of the fields of the source data and the target data. At the same time, based on the product conversion rules, the calculation model converts the securities account number in the data extraction result to the product number of the target data; based on the date conversion rules, the calculation model determines the settlement agency settlement date and system settlement date corresponding to the target data. For example, the calculation model calculates the settlement agency settlement date and system settlement date of the target data according to the settlement agency settlement date rules and the system settlement date rules.

[0081] It should be noted that data conversion logic rules can also be used to aggregate and net out the extracted data by transaction parties to improve collection efficiency.

[0082] Below we take the actual Shanghai-Hong Kong Stock Connect corporate behavior fee rules as an example.

[0083] First, set the corresponding rules, agree that the settlement date of the clearing institution is S+0, the system settlement date rule is S+0, the source data is the HK_JSMX file, the target data is CLR_DATA, and the entry class is ExtractHkShHkScHl. The data extraction logic rule depends on the entry class ExtractHkShHkScHl to implement specific data extraction rules and extract the data required by the rule from the HK_JSMX file.

[0084] The data conversion logic rule depends on the source data HK_JSMX and the target data CLR_DATA in the rule. The calculation model determines the corresponding conversion class according to the source and target. In addition to the direct mapping of the source and target fields, the conversion class also implements the logic of converting the HK_JSMX securities account number to the CLR_DATA product number, and calculates the settlement institution settlement date and system settlement date of CLR_DATA according to the settlement institution settlement date rules and system settlement date rules. The data storage logic rule only depends on the target data CLR_DATA in the rule. The calculation model determines the corresponding storage class according to the target, and the storage class mainly implements the warehousing logic of CLR_DATA.

[0085] When clearing and settlement is being carried out, the calculation model reads the behavior fee rules (target business rules) of the Shanghai-Hong Kong Stock Connect Company from the rule table, triggers the three actions of extraction, conversion, and storage in sequence, and converts the data in the HK_JSMX table that meets the requirements of the rules into the CLR_DATA data required by the system. At the same time, the payment data of all rules can be directly generated based on CLR_DATA, and the actual settlement and transfer actions can be completed.

[0086] The data processing method proposed in this embodiment obtains the data conversion logic rule corresponding to the target business rule in the calculation rule table based on the source data and the data target corresponding to the target business rule through the calculation model; then, the data extraction result is converted based on the data conversion logic rule through the calculation model to obtain the target data. The source data can be accurately converted into the target data according to the data conversion logic rule, thereby further improving the efficiency of clearing and delivery.

[0087] The present application also provides a data processing device. Figure 2 , the data processing device comprises:

[0088] An acquisition module 10 is used to, when a calculation operation corresponding to a target business rule in a calculation rule table is detected, acquire a rule element corresponding to the target business rule in the calculation rule table through a calculation model;

[0089] An extraction module 20 is used to perform a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result;

[0090] A conversion module 30, configured to perform a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule;

[0091] The storage module 40 is used to store the target data based on the calculation rule table through a calculation model.

[0092] The data processing device provided in the embodiment of the present application adopts the data processing method in the above embodiment, which can solve the technical problem of how to improve the reuse of the same processing logic between different business rules, reduce the system risks caused by frequent changes in business rules, and reduce development costs. Compared with the prior art, the beneficial effects of the data processing device provided in the embodiment of the present application are the same as the beneficial effects of the data processing method provided in the above embodiment, and other technical features in the data processing device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0093] The present application provides a data processing device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the data processing method in the above-mentioned embodiment 1.

[0094] Reference below Figure 3 , which shows a schematic diagram of the structure of a data processing device suitable for implementing an embodiment of the present application. The data processing device in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The data processing device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0095] like Figure 3As shown, the data processing device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the data processing device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the data processing device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a data processing device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0096] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0097] The data processing device provided by the present application adopts the data processing method in the above embodiment, which can solve the technical problem of how to improve the reuse of the same processing logic between different business rules, reduce the system risks caused by frequent changes in business rules, and reduce development costs. Compared with the prior art, the beneficial effects of the data processing device provided by the present application are the same as the beneficial effects of the data processing method provided by the above embodiment, and the other technical features in the data processing device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0098] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0099] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0100] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the data processing method in the above-mentioned embodiment.

[0101] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0102] The computer-readable storage medium may be included in a data processing device, or may exist independently without being incorporated into a data processing device.

[0103] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by a data processing device, the data processing device: when detecting a calculation operation corresponding to a target business rule in a calculation rule table, obtains a rule element corresponding to the target business rule in the calculation rule table through a calculation model; performs a data extraction operation on the source data corresponding to the target business rule based on an entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result; performs a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain the target data corresponding to the target business rule; performs a storage operation on the target data based on the calculation rule table through a calculation model.

[0104] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0105] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0107] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned data processing method, and can solve the technical problems of how to improve the reuse of the same processing logic between different business rules, reduce the system risks caused by frequent changes in business rules, and reduce development costs. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the data processing method provided by the above-mentioned embodiment, and will not be repeated here.

[0108] An embodiment of the present application provides a computer program product, including a computer program, which implements the steps of the above-mentioned data processing method when executed by a processor.

[0109] The computer program product provided by the present application can solve the technical problem of how to improve the reuse of the same processing logic between different business rules, reduce the system risks caused by frequent changes in business rules, and reduce development costs. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as the beneficial effects of the data processing method provided by the above embodiment, and will not be repeated here.

[0110] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A data processing method, characterized in that: The data processing method comprises the following steps: When a calculation operation corresponding to a target business rule in the calculation rule table is detected, a rule element corresponding to the target business rule is obtained in the calculation rule table through a calculation model; Performing a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result; Performing a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule; The target data is stored based on the calculation rule table through a calculation model.

2. The data processing method according to claim 1, characterized in that: The step of performing a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through the calculation model to obtain the data extraction result includes: Obtaining data extraction logic rules based on the entry class corresponding to the target business rule in the rule element through the calculation model; A data extraction operation is performed on the source data corresponding to the target business rule based on the data extraction logic rule through a calculation model to obtain a data extraction result.

3. The data processing method according to claim 1, characterized in that: The step of performing a data conversion operation on the data extraction result based on the calculation rule table through the calculation model to obtain the target data corresponding to the target business rule includes: Obtaining the data conversion logic rule corresponding to the target business rule in the calculation rule table based on the source data and the data target corresponding to the target business rule through the calculation model; The target data is obtained by performing data conversion on the data extraction result based on the data conversion logic rule through the calculation model.

4. The data processing method according to claim 3, characterized in that: The data conversion logic rules include data mapping rules, product conversion rules and date conversion rules. The step of performing data conversion on the data extraction result based on the data conversion logic rules by using the calculation model to obtain the target data includes: Mapping the field data of the data extraction result to the field data of the target data based on the data mapping rule through a calculation model; Based on the product conversion rule, the securities account number in the data extraction result is converted into the product number of the target data by means of a calculation model; The settlement institution settlement date and the system settlement date corresponding to the target data are determined by a calculation model based on the date conversion rule.

5. The data processing method according to claim 1, characterized in that: The step of performing a storage operation on the target data based on the calculation rule table by using a calculation model comprises: Obtaining, through a calculation model and based on target data, a data storage logic rule corresponding to the target business rule in the calculation rule table; The target data is stored based on the data storage logic rules through a calculation model.

6. The data processing method according to any one of claims 1 to 5, characterized in that: When the calculation operation corresponding to the business rule in the calculation rule table is detected, before the step of obtaining the rule element corresponding to the business rule in the calculation rule table through the calculation model, the data processing method further includes: When a rule setting request is received, obtaining a rule element of a business rule to be set corresponding to the rule setting request; The calculation rule table is updated based on the rule elements of the business rule to be set.

7. The data processing method according to claim 6, characterized in that: The rule elements of the business rules to be set include rule name, source data, target data, settlement institution settlement date rule, system settlement date rule and entry class.

8. A data processing device, characterized in that: The data processing device comprises: An acquisition module, configured to, when detecting a calculation operation corresponding to a target business rule in a calculation rule table, acquire a rule element corresponding to the target business rule in the calculation rule table through a calculation model; An extraction module, used to perform a data extraction operation on the source data corresponding to the target business rule based on the entry class corresponding to the target business rule in the rule element through a calculation model to obtain a data extraction result; A conversion module, used to perform a data conversion operation on the data extraction result based on the calculation rule table through a calculation model to obtain target data corresponding to the target business rule; A storage module is used to perform storage operation on the target data based on the calculation rule table through a calculation model.

9. A data processing device, characterized in that: The data processing device comprises: a memory, a processor, and a data processing program stored in the memory and executable on the processor, wherein the data processing program implements the steps of the data processing method according to any one of claims 1 to 7 when executed by the processor.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data processing program, and when the data processing program is executed by a processor, the steps of the data processing method according to any one of claims 1 to 7 are implemented.

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