CN113159951A - Financial data clearing method, device, equipment and storage medium - Google Patents
Financial data clearing method, device, equipment and storage medium Download PDFInfo
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- CN113159951A CN113159951A CN202110445535.XA CN202110445535A CN113159951A CN 113159951 A CN113159951 A CN 113159951A CN 202110445535 A CN202110445535 A CN 202110445535A CN 113159951 A CN113159951 A CN 113159951A
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Abstract
The invention belongs to the technical field of finance, and discloses a financial data clearing method, a financial data clearing device, financial data clearing equipment and a financial data clearing storage medium. The method comprises the steps of obtaining a user instruction to be executed, wherein the user instruction is used for constructing a clearing process of preset target data; calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the function modules are operation nodes for performing data operation on the target data in a clearing process; constructing data interaction logic among the functional modules according to the user instruction; and performing data clearing on the target data through at least two functional modules and data interaction logics among the functional modules. Because the functional modules are constructed in advance and stored in the module database, complete financial data clearing service can be formed through the functional modules and data interaction logic among the functional modules, and the financial data clearing service can be constructed without compiling complex service codes.
Description
Technical Field
The invention relates to the technical field of finance, in particular to a financial data clearing method, device, equipment and storage medium.
Background
In the financial field, especially in the securities field, clearing business handling is very important for security dealer daily operations, but the financial data clearing system in the prior art faces many problems in the development and upgrade processes:
long demand response time: if a financial data clearing system of a prior security dealer purchases platform products developed by a scientific and technological company, clearing service logic and clearing service algorithms are integrated in codes, development and upgrading mainly depend on the development of the scientific and technological company, and when a new service or a new requirement exists, a service worker needs to popularize service knowledge, explain input and output to a scientific and technological company developer first, and then the development process can be started, so that the time is long;
customization is difficult to achieve: a platform product developed by a technology company is generally a vending product, and triggered by cost-effectiveness ratio and maintenance convenience, the technology company generally integrates a plurality of user requirements, selects a compromise scheme to implement, and a dealer hardly obtains a customized version of the dealer;
the cost pressure is large: the platform product that cites science and technology company development generally cites the expense comparatively rationally in initial stage, but if the later stage produces the demand change, science and technology company's charge can increase by a wide margin, and it is higher to last operation expense cost, and the general function of platform product of science and technology company development is redundant, needs to purchase whole platform product for a small part of function sometimes, leads to the cost more to be on the high side, and expense pressure is big.
The version quality is not high: in the existing system platform development mode, developers of a science and technology company need to be familiar with financial clearing services while being familiar with technology, but in practice, the developers of the science and technology company still have developers with insufficient industry experience, and when the developers blend clearing service logic into codes in the development process, the developers often lose one another and cannot understand the developed clearing services, so that the version quality is low, the rework is more, and a lot of time is wasted;
relying on external procurement: after the selected scientific and technological company of securities dealer, generally can have the cooperation of longer time with the scientific and technological company, the improvement level and the development of scientific and technological company oneself have very big influence to the stable operation of securities dealer, if the personnel of scientific and technological company often flow, can lead to response time extension, quality of service to descend, lead to the daily operation of securities dealer to receive very big influence, can lead to securities dealer to have to purchase the scientific and technological company even to guarantee the stability of daily operation.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a financial data clearing method, a financial data clearing device, financial data clearing equipment and a storage medium, and aims to solve the technical problem that in the prior art, financial data clearing business is difficult to develop and upgrade.
To achieve the above object, the present invention provides a financial data clearing method, comprising the steps of:
acquiring a user instruction to be executed, wherein the user instruction is used for constructing a clearing process of preset target data;
calling at least two functional modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the functional modules are operation nodes for performing data operation on the target data in the clearing process;
constructing data interaction logic among the functional modules according to the user instruction;
and performing data clearing on the target data through the at least two functional modules and data interaction logics among the functional modules.
Preferably, the functional modules and the data interaction logic between the functional modules are all written in advance by a domain specific language and packaged into an independent operation module.
Preferably, the step of calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction includes:
extracting a flow construction statement in the user instruction;
analyzing the flow construction statement through a preset semantic analysis model to obtain a functional module identifier, wherein the preset semantic analysis model is a model obtained by training a flow construction statement sample set;
searching at least two functional modules corresponding to the functional module identification in a preset module database according to the functional module identification;
correspondingly, the step of constructing the data interaction logic between the functional modules according to the user instruction includes:
and analyzing the flow construction statement through the preset semantic analysis model to obtain data interaction logic among the functional modules.
Preferably, the step of performing data clearing on the target data through the at least two functional modules and the data interaction logic between the functional modules includes:
extracting a data request path and a data conversion rule identifier in the user instruction;
constructing a data clearing flow according to the at least two functional modules and the data interaction logic between the functional modules;
sending a data acquisition request to the data request path to acquire the target data;
searching a conversion rule of data to be processed according to the data conversion rule identification, and converting the target data into the data to be processed based on the conversion rule of the data to be processed;
and performing data clearing on the data to be processed according to the data clearing flow.
Preferably, after the step of performing data clearing on the data to be processed according to the data clearing flow, the method further includes:
constructing a data clearing task according to the data request path, the data conversion rule identification and the data clearing process;
storing the data clearing task into a data clearing task library;
and when a clearing trigger condition exists in the user instruction, setting the clearing trigger condition as a task trigger condition of the data clearing task, wherein when the task trigger condition is triggered, the data clearing task is automatically executed.
Preferably, before the step of sending a data obtaining request to the data request data to obtain the target data, the method further includes:
carrying out feasibility verification on the data clearing process;
when the feasibility verification passes successfully, executing the step of sending a data acquisition request to the data request data to acquire the target data;
when the feasibility verification fails, acquiring a failure reason of the feasibility verification failure;
and generating an interactive logic recommendation scheme according to the failure reason, generating a failure judgment report according to the failure reason and the interactive logic recommendation scheme, and displaying the failure judgment report to a user.
Preferably, after the step of performing data clearing on the data to be processed according to the data clearing flow, the method further includes:
acquiring a data clearing result generated when the function of each functional module in the data clearing flow is executed;
searching for an output data conversion rule according to the data conversion rule identifier;
and converting the data clearing result into a standard clearing result according to the output data conversion rule.
And generating a clearing report according to the standard clearing result, and displaying the clearing report.
In addition, in order to achieve the above object, the present invention also provides a financial data clearing apparatus, including the following modules:
the instruction acquisition module is used for acquiring a user instruction to be executed, wherein the user instruction is used for constructing a liquidation process of preset target data;
the function acquisition module is used for calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the function modules are operation nodes for performing data operation on the target data in the clearing process;
the logic construction module is used for constructing data interaction logic among the functional modules according to the user instruction;
and the data clearing module is used for clearing the data of the target data through the at least two functional modules and the data interaction logic between the functional modules.
Further, to achieve the above object, the present invention also provides a financial data clearing apparatus including: a processor, a memory and a financial data clearing program stored on said memory and operable on said processor, said financial data clearing program when executed implementing the steps of the financial data clearing method as described above.
Further, to achieve the above object, the present invention also proposes a computer-readable storage medium having stored thereon a financial data clearing program which, when executed by a processor, implements the steps of the financial data clearing method as described above.
The method comprises the steps of obtaining a user instruction to be executed, wherein the user instruction is used for constructing a clearing process of preset target data; calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the function modules are operation nodes for performing data operation on the target data in a clearing process; constructing data interaction logic among the functional modules according to the user instruction; and performing data clearing on the target data through at least two functional modules and data interaction logics among the functional modules. Because the functional modules are constructed in advance and stored in the module database, complete financial data clearing service can be formed through the functional modules and data interaction logic among the functional modules, and the financial data clearing service can be constructed without compiling complex service codes.
Drawings
Fig. 1 is a schematic structural diagram of an electronic device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart diagram illustrating a first embodiment of a financial data clearing method according to the present invention;
FIG. 3 is a flowchart illustrating a second embodiment of a financial data clearing method according to the present invention;
FIG. 4 is a schematic flow chart diagram illustrating a third embodiment of a financial data clearing method according to the present invention;
fig. 5 is a block diagram showing the construction of the first embodiment of the financial data liquidation apparatus of the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a financial data clearing device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the electronic device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the electronic device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a financial data clearing program.
In the electronic apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the electronic device of the present invention may be provided in the financial data clearing device, and the electronic device calls the financial data clearing program stored in the memory 1005 through the processor 1001 and executes the financial data clearing method provided by the embodiment of the present invention.
An embodiment of the present invention provides a financial data clearing method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the financial data clearing method according to the present invention.
In this embodiment, the financial data clearing method includes the steps of:
step S10: and acquiring a user instruction to be executed, wherein the user instruction is used for constructing a clearing process of preset target data.
It should be noted that, the executing subject of this embodiment may be the financial data clearing device, and the financial data clearing device may be an electronic device such as a personal computer, a server, and the like, and may also be other devices that can implement the same or similar functions.
It should be noted that the instruction may be code for notifying the computer to perform a special operation, and the user instruction may be an instruction issued by the user for notifying the financial data clearing apparatus to perform a clearing process for constructing the preset target data. The target data may be acquired according to a user instruction, or may be acquired in advance and stored in a preset storage space, where the preset storage space may be a data storage tool such as a database.
Step S20: and calling at least two functional modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the functional modules are operation nodes for performing data operation on the target data in the clearing process.
It should be noted that the user instruction may include information such as a module identifier of the functional module, and when receiving the user instruction, the financial data clearing device may analyze the user instruction, obtain the module identifier in the user instruction, and search the corresponding functional module in the module database through the module identifier. The module database may include a plurality of pre-constructed functional modules, and the functional modules may be operation nodes in the clearing process, for example: a commission charge calculating module, a fund charge calculating module and other functional modules.
It can be understood that when the functional modules in the module database cannot meet actual requirements, the corresponding functional modules can be added to the module database according to actual requirements.
Step S30: and constructing data interaction logic among the functional modules according to the user instruction.
It should be noted that the data interaction logic may be found in the preset storage space according to the data interaction logic identifier in the user instruction, or may be constructed according to the logic construction data included in the user instruction, and when the data interaction logic is constructed according to the logic construction data included in the user instruction, the constructed data interaction logic may be further stored in the preset storage space. The user instruction may include multiple data interaction logic identifiers, the data interaction logic may be a connection relationship between the functional modules, and the connection relationship may include a functional module operation sequence, a data storage attribute, and an attribute transfer, for example: the function module A operates firstly, calculates the operation result when the operation is finished, stores the operation result into the attribute B, transmits the attribute B to the function module C, and further calculates according to the received attribute B by the function module C.
Further, in order to facilitate using the extension, the functional modules and the data interaction logic between the functional modules in this embodiment may be pre-written and packaged into an independent operation module by using a domain-specific language.
It should be noted that a domain-specific language (DSL) refers to a computer language that is dedicated to a certain application program domain. The functional modules written and packaged into the independent operation module through the domain specific language or the data interaction logic among the functional modules are beneficial to expansion, and when the existing functional modules or the data interaction logic among the functional modules cannot meet the requirements, a new functional module can be generated only by setting according to the configurable items reserved by the independent operation module.
In practical use, when a new functional module needs to be added, a new functional module can be formed only by setting the types of input data and output data of the functional module and then defining discount setting, basic cost, cost calculation formula and the like, without writing complex software codes. Similarly, when a new data interaction logic needs to be added, a new data interaction logic can be formed only by setting a data transmission mode, a data transmission field and the like between the two functional modules.
For example: the basic costs can be set when a functional module needs to be built: CFM _ QTY (number of deals), CFM _ PRICE (PRICE of deals), CFM _ AMT (amount of deals), TRANS _ FEE (FEE for passing a house), COMMISON (FEE for handling), etc.;
the fee calculation formula may be set as follows:
the calculation formula of the number of the deals is CFM _ QTY ═ PAY _ D (the number of the deals is the number of the deals in the receiving and paying direction);
the bargaining PRICE calculation formula is CFM _ PRICE (bargaining PRICE is CFM _ PRICE);
the bargaining amount calculation formula is CFM _ AMT (CFM _ QTY) CFM _ AMT (PAY _ D) (bargaining amount) bargaining price (payment direction);
the calculation formula of the FEE of passing the house is TRANS _ FEE ═ CFM _ AMT ═ RATE ═ DISCOUNT @ -1 (FEE of passing the house is the sum of friendship ═ RATE ═ DISCOUNT @ -1);
the formula of the commission fee is 'commission fee' CFM _ AMT 'RATE' DISCOUNT '1 (commission amount' tariff 'DISCOUNT' 1).
It should be noted that, if a plurality of cost calculation formulas are arranged in one functional module, a formula execution sequence can be set for each cost calculation formula, after the formula execution sequence is set, each cost calculation formula can be sorted according to the formula execution sequence, and then executed in sequence according to the sorting, and the cost calculation formula in the back of the sorting can directly refer to the calculation result of the cost calculation formula in the front of the sorting as the data needed by the formula calculation.
Step S40: and performing data clearing on the target data through the at least two functional modules and data interaction logics among the functional modules.
It can be understood that after each functional module is determined according to the user instruction, each functional module can be connected according to the data interaction logic constructed by the user instruction, so that a complete financial data clearing service can be formed, and the data clearing can be performed on the target data by executing the financial data clearing service.
In the embodiment, a user instruction to be executed is obtained, wherein the user instruction is used for constructing a clearing process of preset target data; calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the function modules are operation nodes for performing data operation on the target data in a clearing process; constructing data interaction logic among the functional modules according to the user instruction; and performing data clearing on the target data through at least two functional modules and data interaction logics among the functional modules. Because the functional modules are constructed in advance and stored in the module database, complete financial data clearing service can be formed through the functional modules and data interaction logic among the functional modules, and the financial data clearing service can be constructed without compiling complex service codes.
Referring to fig. 3, fig. 3 is a flowchart illustrating a financial data clearing method according to a second embodiment of the present invention.
Based on the first embodiment, in step S20, the financial data clearing method in this embodiment specifically includes:
step S201: and extracting a flow construction statement in the user instruction.
It should be noted that the flow building statement may be a statement describing the financial data clearing service in natural language.
Step S202: and analyzing the flow construction statement through a preset semantic analysis model to obtain a functional module identifier, wherein the preset semantic analysis model is a model obtained by training a flow construction statement sample set.
It should be noted that the preset semantic analysis model may be a neural network model or a machine learning model obtained by training a sentence sample set using a flow construction method. The flow construction statement sample set can comprise a large number of flow construction statement samples, the flow construction statement samples can be constructed by flow construction statements, functional module identifications corresponding to the flow construction statements and data interaction logic identifications among the functional modules, and the trained preset semantic analysis model can identify the corresponding functional module identifications and the data interaction logic identifications among the functional modules according to the input flow construction statements. The preset semantic analysis model may include a natural language dictionary to facilitate parsing of the flow construction statements, and the natural language dictionary may include vocabularies, entries, phrases, and the like of the extracted financial clearing field, for example: noun vocabularies used for describing service main bodies, service varieties, service occurrence places and time, service products, service expenses and the like, and verb vocabularies used for describing service behaviors.
Step S203: and searching at least two functional modules corresponding to the functional module identification in a preset module database according to the functional module identification.
It can be understood that the functional module identifier of each functional module is unique and fixed in the module database, so that the functional module identifier identified by the preset semantic analysis model can search the corresponding functional module in the preset module database, and in actual use, because of actual business needs, the number of the functional modules involved in the process construction statement is generally multiple, so that the number of the functional module identifiers identified by the preset semantic analysis model can also be multiple, and in the same way, the number of the searched functional modules can also be multiple, that is, at least two.
Correspondingly, step S30 in this embodiment may include:
step S30': and analyzing the flow construction statement through the preset semantic analysis model to obtain data interaction logic among the functional modules.
It can be understood that the related data interaction logic identifier can be obtained by identifying the flow construction statement through the preset semantic analysis model, and the corresponding data interaction logic can be obtained by searching the data interaction logic identifier in the preset storage space.
It should be noted that the current model algorithm can ensure that the success rate of recognition is extremely high, but the success rate of recognition is not 100%, and a functional module and a data interaction logic which are determined by recognizing a flow building statement through a preset semantic analysis model are inevitable to have errors, so that in order to improve user experience, after the flow building statement is recognized through the semantic analysis model, a modification instruction from a user can be received, and the recognized functional module and the data interaction logic are adjusted.
In the embodiment, the preset semantic analysis model is introduced to analyze the flow construction statements in the user instruction, the corresponding function modules are searched and called in the function module library according to the data interaction logic identifiers and the function module identifiers output by the preset semantic analysis model, and the data interaction logic of each function module is determined according to the data interaction logic identifiers, so that the financial data clearing method can support financial data clearing according to the flow construction statements described by natural language, the use difficulty of the user is reduced, and the user experience is improved.
Referring to fig. 4, fig. 4 is a flowchart illustrating a financial data clearing method according to a third embodiment of the present invention.
Based on the first embodiment, in step S40, the financial data clearing method in this embodiment specifically includes:
step S401: and extracting a data request path and a data conversion rule identifier in the user instruction.
The data request path may be a path for requesting target data, and the data request path may be an access path of a data request interface or a path for storing data. The data conversion rule identification may be an identification of a data conversion rule stored in a preset storage space. The data conversion rule can be pre-constructed and stored in a preset storage space. The data transformation rules may specify the target data format and the association of data fields in the target data format with data fields in the source data, for example: if the source data field is "JGFSRQ" and the target data field "SEND _ DATE", the data corresponding to the field "JGFSRQ" in the source data may be converted into the format corresponding to the target data field "SEND _ DATE" and stored in the field, and data conversion operations such as data rounding may also be performed during the conversion process.
Step S402: and constructing a data clearing flow according to the at least two functional modules and the data interaction logic among the functional modules.
It is understood that the data interaction logic may include data transmission rules among the functional modules, and a complete data clearing process may be formed by connecting a plurality of functional modules according to the data interaction logic.
Step S403: and sending a data acquisition request to the data request path to acquire the target data.
It can be understood that, when the data request path is an access path of the data request interface, the data request interface may send a data acquisition request to the data request interface, and when receiving the data acquisition request, the data request interface may return a corresponding data acquisition response, analyze the data acquisition response, and extract content of a response body, so as to obtain the target data.
Further, in order to improve the reliability of the data clearing method, before step S403 in this embodiment, the method may further include:
carrying out feasibility verification on the data clearing process; when the feasibility verification passes successfully, executing the step of sending a data acquisition request to the data request data to acquire the target data; when the feasibility verification fails, acquiring a failure reason of the feasibility verification failure; and generating an interactive logic recommendation scheme according to the failure reason, generating a failure judgment report according to the failure reason and the interactive logic recommendation scheme, and displaying the failure judgment report to a user.
It should be noted that, from a technical point of view, the function modules may be connected to each other through data interaction logic, but from an actual service point of view, the function modules may not be connected at will, and when the connection is not reasonable, the data may be calculated, but a logical error or a service error may occur, which may result in a clearing failure. When the corresponding prohibition rule is matched, the failure reason may be displayed according to the prohibition rule, and an interactive logic recommendation scheme is generated for the data clearing flow based on the failure reason, for example: deleting the execution position of partial functional modules or adjusting the execution position of the functional modules in the data clearing flow, and the like. The prohibition rule can be obtained by statistics of a data clearing process which is executed in a failure history, and can also be set by a user.
Step S404: and searching a conversion rule of the data to be processed according to the data conversion rule identification, and converting the target data into the data to be processed based on the conversion rule of the data to be processed.
It can be understood that a plurality of data conversion rules may be stored in the preset storage space, each data conversion rule may have a fixed and unique identifier, and the corresponding data conversion rule may be searched in the preset storage space according to the identifier of the data conversion rule and the searched data conversion rule may be used as the data conversion rule to be processed. The format of the target data can be converted through the conversion rule of the data to be processed so as to obtain the data to be processed.
It should be noted that, if necessary, the target data may also be screened according to the to-be-processed data conversion rule, and after the screening is completed, the target data is converted into to-be-processed data.
Step S405: and performing data clearing on the data to be processed according to the data clearing flow.
It can be understood that the data clearing process may include a complete data clearing service, and data to be processed is performed according to the data clearing process, so that data clearing can be completed.
Further, in order to recycle the constructed data clearing process and improve the work efficiency, after step S405 in this embodiment, the method may further include:
constructing a data clearing task according to the data request path, the data conversion rule identification and the data clearing process; storing the data clearing task into a data clearing task library; and when a clearing trigger condition exists in the user instruction, setting the clearing trigger condition as a task trigger condition of the data clearing task, wherein when the task trigger condition is triggered, the data clearing task is automatically executed.
It can be understood that, if the data clearing process needs to be reconstructed every time, the data clearing process is very complicated, and the work efficiency is not high, so that when the data clearing process is determined to be correctly executed, the data clearing task can be constructed according to the data clearing process and the data conversion rule identifier, the data clearing task is stored in the data clearing task library, and when the same data clearing process is required to be performed subsequently, the data clearing task library can be directly searched and called without reconstructing the data clearing process again, so that the work efficiency can be improved.
It should be noted that when the frequency of use of the data clearing task is high, such as every day or every week, a task trigger condition may be set for the data clearing task, and the financial data clearing setting automatically executes the data clearing task when it is checked that the task trigger condition is satisfied, so that when the clearing trigger condition is detected to exist in the user instruction, the clearing trigger condition may be set as the task trigger condition of the data clearing task.
It can be understood that when the clearing trigger condition does not exist in the user instruction, the data clearing task can be directly stored in the data clearing task library, the task trigger condition is not set temporarily, and when the subsequent user needs to execute the data clearing task repeatedly, the modification instruction can be sent, the data clearing task is searched in the data clearing task library according to the modification instruction, and the task trigger condition is set for the data clearing task.
It should be noted that the task triggering condition may be a timing execution, for example: ten am per day or ten am per week on monday weeks; conditional execution is also possible, for example: and the task A is executed when the normal execution is finished.
Further, in order to facilitate debugging to find an error, after step S40, the method may further include:
acquiring a data clearing result generated when the function of each functional module in the data clearing flow is executed; searching for an output data conversion rule according to the data conversion rule identifier; and converting the data clearing result into a standard clearing result according to the output data conversion rule. And generating a clearing report according to the standard clearing result, and displaying the clearing report.
It should be noted that each functional module has a corresponding function, and can execute a corresponding operation flow, and when the function of one functional module is completed, a corresponding data clearing result can be generated, and according to the data conversion rule identification, the output data conversion rule can be searched in the preset storage space, the data clearing result generated by each functional module is standardized to obtain a standard clearing result, and then a clearing report is generated according to the standard clearing result, so that a user can quickly determine the final clearing result of the result set obtained by the execution of each functional module.
It can be understood that, when a plurality of function modules execute corresponding functions in sequence, if the function execution of a certain function module is abnormal, the function of the next function module is not continuously executed, but the data clearing result of the function module is directly recorded, the data clearing result is converted into a standard clearing result, a clearing report is regenerated, the clearing report is displayed to a user, the user is enabled to quickly determine the function module with the abnormal function execution, and the user can quickly find the reason for the abnormal clearing execution.
In the embodiment, the data request path and the data conversion rule identifier in the user instruction are extracted; constructing a data clearing flow according to the at least two functional modules and the data interaction logic between the functional modules; sending a data acquisition request to the data request path to acquire the target data; searching a conversion rule of data to be processed according to the data conversion rule identification, and converting the target data into the data to be processed based on the conversion rule of the data to be processed; performing data clearing on the data to be processed according to the data clearing flow; and after the construction of the data clearing process for clearing the financial data, the data clearing task is constructed and stored according to the data conversion rule identification and the data clearing process, so that the constructed data clearing process can be repeatedly utilized, and the working efficiency is improved.
Furthermore, an embodiment of the present invention further provides a storage medium having a financial data clearing program stored thereon, where the financial data clearing program, when executed by a processor, implements the steps of the financial data clearing method as described above.
Referring to fig. 5, fig. 5 is a block diagram showing the construction of a first embodiment of the financial data liquidation apparatus of the present invention.
As shown in fig. 5, the financial data clearing apparatus according to the embodiment of the present invention includes:
an instruction obtaining module 501, configured to obtain a user instruction to be executed, where the user instruction is used to construct a liquidation process of preset target data;
a function searching module 502, configured to, based on the user instruction, call at least two function modules corresponding to the user instruction in a preset module database, where the function modules are operation nodes for performing data operation on the target data in the clearing process;
a logic construction module 503, configured to construct a data interaction logic between the functional modules according to the user instruction;
and the data clearing module 504 is configured to perform data clearing on the target data through the at least two functional modules and data interaction logic between the functional modules.
In the embodiment, a user instruction to be executed is obtained, wherein the user instruction is used for constructing a clearing process of preset target data; calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the function modules are operation nodes for performing data operation on the target data in a clearing process; constructing data interaction logic among the functional modules according to the user instruction; and performing data clearing on the target data through at least two functional modules and data interaction logics among the functional modules. Because the functional modules are constructed in advance and stored in the module database, complete financial data clearing service can be formed through the functional modules and data interaction logic among the functional modules, and the financial data clearing service can be constructed without compiling complex service codes.
Further, the function search module 502 is further configured to extract a flow construction statement in the user instruction; analyzing the flow construction statement through a preset semantic analysis model to obtain a functional module identifier, wherein the preset semantic analysis model is a model obtained by training a flow construction statement sample set; searching at least two functional modules corresponding to the functional module identification in a preset module database according to the functional module identification;
the logic construction module 503 is further configured to analyze the flow construction statement through the preset semantic analysis model to obtain a data interaction logic between the functional modules.
Further, the data clearing module 504 is further configured to extract a data request path and a data conversion rule identifier in the user instruction; constructing a data clearing flow according to the at least two functional modules and the data interaction logic between the functional modules; sending a data acquisition request to the data request path to acquire the target data; searching a conversion rule of data to be processed according to the data conversion rule identification, and converting the target data into the data to be processed based on the conversion rule of the data to be processed; and performing data clearing on the data to be processed according to the data clearing flow.
Further, the data clearing module 504 is further configured to construct a data clearing task according to the data request path, the data conversion rule identifier, and the data clearing process; storing the data clearing task into a data clearing task library; and when a clearing trigger condition exists in the user instruction, setting the clearing trigger condition as a task trigger condition of the data clearing task, wherein when the task trigger condition is triggered, the data clearing task is automatically executed.
Further, the data clearing module 504 is further configured to perform feasibility verification on the data clearing process; when the feasibility verification passes successfully, executing the step of sending a data acquisition request to the data request data to acquire the target data; when the feasibility verification fails, acquiring a failure reason of the feasibility verification failure; and generating an interactive logic recommendation scheme according to the failure reason, generating a failure judgment report according to the failure reason and the interactive logic recommendation scheme, and displaying the failure judgment report to a user.
Further, the data clearing module 504 is further configured to obtain a data clearing result generated when the function of each functional module in the data clearing flow is executed; searching for an output data conversion rule according to the data conversion rule identifier; and converting the data clearing result into a standard clearing result according to the output data conversion rule. And generating a clearing report according to the standard clearing result, and displaying the clearing report.
It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited thereto.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may refer to the financial data clearing method provided in any embodiment of the present invention, and are not described herein again.
Further, it is to be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method of financial data clearance, comprising:
acquiring a user instruction to be executed, wherein the user instruction is used for constructing a clearing process of preset target data;
calling at least two functional modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the functional modules are operation nodes for performing data operation on the target data in the clearing process;
constructing data interaction logic among the functional modules according to the user instruction;
and performing data clearing on the target data through the at least two functional modules and data interaction logics among the functional modules.
2. The financial data clearing method according to claim 1 wherein the functional modules and the data interaction logic between the functional modules are pre-programmed and packaged into independent operational modules in a domain specific language.
3. The financial data clearing method according to claim 1 wherein said step of calling at least two function modules corresponding to said user's instruction in a preset module database based on said user's instruction comprises:
extracting a flow construction statement in the user instruction;
analyzing the flow construction statement through a preset semantic analysis model to obtain a functional module identifier, wherein the preset semantic analysis model is a model obtained by training a flow construction statement sample set;
searching at least two functional modules corresponding to the functional module identification in a preset module database according to the functional module identification;
correspondingly, the step of constructing the data interaction logic between the functional modules according to the user instruction includes:
and analyzing the flow construction statement through the preset semantic analysis model to obtain data interaction logic among the functional modules.
4. The financial data clearing method of claim 1 wherein said step of data clearing said target data through said at least two functional modules and data interaction logic between functional modules comprises:
extracting a data request path and a data conversion rule identifier in the user instruction;
constructing a data clearing flow according to the at least two functional modules and the data interaction logic between the functional modules;
sending a data acquisition request to the data request path to acquire the target data;
searching a conversion rule of data to be processed according to the data conversion rule identification, and converting the target data into the data to be processed based on the conversion rule of the data to be processed;
and performing data clearing on the data to be processed according to the data clearing flow.
5. The financial data clearing method according to claim 4, wherein said step of data clearing said data to be processed according to said data clearing process is followed by further comprising:
constructing a data clearing task according to the data request path, the data conversion rule identification and the data clearing process;
storing the data clearing task into a data clearing task library;
and when a clearing trigger condition exists in the user instruction, setting the clearing trigger condition as a task trigger condition of the data clearing task, wherein when the task trigger condition is triggered, the data clearing task is automatically executed.
6. The financial data clearing method according to claim 4 wherein said step of sending a data acquisition request to said data request data to obtain said target data is preceded by the step of:
carrying out feasibility verification on the data clearing process;
when the feasibility verification passes successfully, executing the step of sending a data acquisition request to the data request data to acquire the target data;
when the feasibility verification fails, acquiring a failure reason of the feasibility verification failure;
and generating an interactive logic recommendation scheme according to the failure reason, generating a failure judgment report according to the failure reason and the interactive logic recommendation scheme, and displaying the failure judgment report to a user.
7. The financial data clearing method according to claim 4, wherein said step of data clearing said data to be processed according to said data clearing process is followed by further comprising:
acquiring a data clearing result generated when the function of each functional module in the data clearing flow is executed;
searching for an output data conversion rule according to the data conversion rule identifier;
and converting the data clearing result into a standard clearing result according to the output data conversion rule.
And generating a clearing report according to the standard clearing result, and displaying the clearing report.
8. A financial data clearing apparatus, comprising:
the instruction acquisition module is used for acquiring a user instruction to be executed, wherein the user instruction is used for constructing a liquidation process of preset target data;
the function acquisition module is used for calling at least two function modules corresponding to the user instruction in a preset module database based on the user instruction, wherein the function modules are operation nodes for performing data operation on the target data in the clearing process;
the logic construction module is used for constructing data interaction logic among the functional modules according to the user instruction;
and the data clearing module is used for clearing the data of the target data through the at least two functional modules and the data interaction logic between the functional modules.
9. A financial data clearing apparatus, comprising: a processor, a memory and a financial data clearing program stored on the memory and operable on the processor, which when executed performs the steps of the financial data clearing method as claimed in any one of claims 1-7.
10. A computer-readable storage medium, having stored thereon a financial data clearing program which, when executed by a processor, implements the steps of the financial data clearing method according to any one of claims 1-7.
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