Financial data management method and device, equipment, storage medium and program product

Abstract

The invention discloses a financial data management method, device and equipment, a storage medium and a program product, which can be applied to the field of financial science and technology. The method comprises the following steps: acquiring an application message of a financial application; if the message type of the application message is a rule configuration class, performing message survival judgment on the application message to obtain a message survival judgment result; determining an application rule storage mode of the financial application according to the message survival judgment result, and generating and storing rule configuration information of the financial application based on the application rule storage mode; and if the message type of the application message is a resource calling type, determining an application resource storage mode of the financial application, and based on the application resource storage mode, generating and storing resource calling information of the financial application. According to the technical scheme, storage optimization of the financial data is achieved, and convenience, efficiency and accuracy of financial data query are improved.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to financial data governance methods, devices, equipment, storage media and program products. Background Art

[0002] Financial data is a big data stream with business value that is sent to the monitoring gateway in real time by the application nodes of financial applications according to the actual operation status. The operation status of application nodes can be obtained through analysis, statistics, and query of financial data, and it can also be used to analyze the possible security risks of existing application nodes, as well as the functional scenarios that can be optimized and the production benefits of existing functions. The existing financial data processing method is to write the acquired financial data into the distributed message server through the monitoring gateway, and then use the distributed message server to generate a distributed database table, establish a distributed library table view, and query the financial data directly through the distributed database table.

[0003] However, financial data is obtained by financial applications based on actual production activities, and the amount of data is usually as high as 10 terabytes after years of real calls. When querying data through a distributed database, only hourly data query services are supported when the data volume is too large, which means that in the case of distributed storage, querying and statistics of financial data requires a lot of manpower and material resources. At the same time, errors may occur in querying and statistics of financial data due to the large amount of data, which has a great impact on production activities.

[0004] Therefore, how to optimize the storage of financial data and improve the convenience, efficiency and accuracy of financial data query and statistics through financial data governance has become a topic that technical personnel in this field urgently need to study. Summary of the invention

[0005] The present invention provides a financial data management method, apparatus, equipment, storage medium and program product to optimize the storage of financial data according to the storage method of each financial application message type, and improve the convenience, efficiency and accuracy of financial data query statistics.

[0006] According to one aspect of the present invention, a financial data governance method is provided, comprising:

[0007] Get application messages of financial applications;

[0008] If the message type of the application message is a rule configuration class, performing a message survival judgment on the application message to obtain a message survival judgment result;

[0009] Determine, according to the message survival judgment result, a storage method of application rules of the financial application, and generate and store rule configuration information of the financial application based on the application rule storage method;

[0010] If the message type of the application message is a resource call type, then the application resource storage method of the financial application is determined, and based on the application resource storage method, resource call information of the financial application is generated and stored.

[0011] According to another aspect of the present invention, there is provided a financial data management device, comprising:

[0012] An application message acquisition module, used to acquire application messages of financial applications;

[0013] A message survival judgment module, used for performing message survival judgment on the application message if the message type of the application message is a rule configuration class, and obtaining a message survival judgment result;

[0014] A rule configuration information generating module, used to determine the storage mode of the application rules of the financial application according to the message survival judgment result, and generate and store the rule configuration information of the financial application based on the application rule storage mode;

[0015] The resource call information generation module is used to determine the application resource storage method of the financial application if the message type of the application message is a resource call class, and generate and store the resource call information of the financial application based on the application resource storage method.

[0016] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the financial data governance method described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the financial data governance method described in any embodiment of the present invention when executed.

[0021] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the financial data governance method described in any embodiment of the present invention is implemented.

[0022] The technical solution of the embodiment of the present invention obtains the application message of the financial application; if the message type of the application message is a rule configuration class, the application message is judged for message survival to obtain the message survival judgment result; according to the message survival judgment result, the storage method of the application rules of the financial application is determined, and based on the application rule storage method, the rule configuration information of the financial application is generated and stored; if the message type of the application message is a resource call class, the application resource storage method of the financial application is determined, and based on the application resource storage method, the resource call information of the financial application is generated and stored. This technical solution can determine the storage method of each message type according to the message type of each financial application message, and generate and store the corresponding financial data according to the storage method, thereby optimizing the storage of financial data and improving the convenience, efficiency and accuracy of querying and counting financial data; it solves the problem in the prior art that financial data is written into a distributed database through a distributed message server, and it is difficult to query and count financial data due to the large amount of data, and it is easy to make errors.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a financial data management method provided according to the first embodiment of the present invention;

[0026] Figure 2 is a flow chart of a financial data governance method provided according to Embodiment 2 of the present invention;

[0027] Figure 3 is a schematic diagram of the structure of a financial data management device provided according to Embodiment 3 of the present invention;

[0028] Figure 4 It is a schematic diagram of the structure of an electronic device for implementing the financial data management method of an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 A flowchart of a financial data management method is provided for the first embodiment of the present invention. This embodiment is applicable to the situation where the efficiency of querying and counting financial data is extremely low due to the excessive amount of financial data. The method can be executed by a financial data management device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110. Obtain application messages of financial applications.

[0034] In the production process of financial activities, various technologies and tools are usually used to improve the efficiency of financial business operations and the ability to manage business risks. Among them, application messages can refer to the process of information exchange or notification through the message transmission mechanism in the application tool. Specifically, the actual operation status of the financial application node can be obtained in real time through application messages.

[0035] Specifically, financial applications may include applications that provide technical services such as mobile payments, banking automation, and financial market infrastructure. Furthermore, they can be obtained through application messages of financial applications to obtain node data that supports various technical service applications, providing more business-valuable information for financial activities.

[0036] S120: If the message type of the application message is a rule configuration type, a message survival judgment is performed on the application message to obtain a message survival judgment result.

[0037] Among them, the rule configuration class can refer to the message type used to set and manage application rules in financial applications, which can specifically include current limiting rules and fuse rules. Among them, the current limiting rules can be rules for setting the operating permissions of each functional module in the financial application. For example, the access permissions of the user or role who logs in to the financial application can be pre-configured through the current limiting rules to achieve the restriction of the operating permissions of each functional module in the financial application, such as only being able to read financial resource data, or being able to pre-configure the operating permissions for reading and modifying financial resource data. Among them, the fuse rules can be used to set the maximum number of failures of the service or operation of each functional module in the financial application. For example, the maximum number of trial and error times for the operation of the functional module of the financial application can be set through the fuse rules. For example, when the user operates the financial application, the user's identity information needs to be verified. The maximum number of times the user's identity is authenticated can be set through the fuse rules, and when the verification number is exceeded, the user's operating permissions are restricted to prevent interference with the stable operation of the financial application due to excessive erroneous operations.

[0038] Among them, the message survival judgment of the application message can specifically be a process of determining whether the application message of the rule configuration class is effective and can process the operations performed through the financial application. Specifically, when the application message obtained is a message for configuring the rules of the financial application, it is determined whether the rules configured by the application message are configured and can process the operations performed by the financial application, and the result of the rule configuration is obtained. Exemplarily, continuing the above example, if the application message can be a fuse rule configuration message that sets the number of user identity authentication to three times, then the survival judgment of the fuse rule can be performed. Specifically, it can be determined by inputting three wrong identity authentication information to determine whether the operation of verifying the user identity is subject to permission restrictions, thereby determining the message survival judgment result of the application message. The specific number of trial and error can be pre-set by the technician based on experience, and this embodiment does not impose specific restrictions.

[0039] Optionally, a message survival judgment is performed on the application message to obtain a message survival judgment result, including: determining the message timing time of the application message of the rule configuration class; judging whether the application message of the node survival class of the financial application is received according to the message timing time; if so, the message survival judgment result is that the message survives; if not, the message survival judgment result is that the message does not survive.

[0040] The message timing time may refer to a preset time for determining whether a rule configuration application message is invalid.

[0041] Among them, the application message of the node survival class can be information for monitoring the survival status of the rule configuration message in the financial application. Specifically, the timing time can be set in advance in the rule configuration class application message, wherein the timing time can be the maximum survival time set for the rule configuration class application message, such as one day or one week, or the heartbeat time set for the rule configuration class message, such as 30 seconds or 60 seconds. The specific timing time can be pre-set by the technician based on experience. Exemplarily, if it is determined that the message timing time of the rule configuration class application message is the maximum survival time and the survival time is one week, it can be considered that the node survival class application message of the financial application can be received within one week, and the message survival judgment result is determined to be the message survival. If it exceeds one week, the message survival judgment result of the rule configuration class application message can be automatically considered to be the message not surviving; if it is determined that the message timing time of the rule configuration class application message is the heartbeat time and the heartbeat time is 30 seconds, it can be judged whether the node survival class application message of the financial application is received within 30 seconds. If so, the message survival judgment result is the message survival; if not, the message survival judgment result is the message not surviving. This embodiment does not make specific restrictions on this.

[0042] This technical solution can set the message timing of rule configuration application messages, determine the message survival status of the rule configuration application messages according to the timing, and obtain the message status of application messages of financial applications to achieve the classification of rule configuration application messages, thereby improving the efficiency of financial data statistical queries based on application messages.

[0043] S130. Determine a storage method for application rules of the financial application according to a result of the message survival judgment, and generate and store rule configuration information of the financial application based on the storage method for the application rules.

[0044] Among them, the application rule storage method can be a solution for recording application rules in financial applications based on the business needs and system architecture of the application. The specific application rule storage method can include file storage, relational database storage, cache storage, etc.

[0045] Among them, the rule configuration information may refer to the parameters of the business processing rules or execution logic rules of different application nodes defined in the financial application. Specifically, when the financial application message of the rule configuration class is in effect and can process the operation performed by the financial application, the storage method of the application rules in the financial application is obtained, and according to the storage method of the application rules, the rule parameters in the financial application are converted into a storage method that conforms to the application rules of the financial application and stored. Exemplarily, continuing the above example, if the application rule storage method of the financial application is stored in a file, the application message of the configuration fuse rule, when operating in the financial application, the maximum number of trial and error times of user identity authentication is three, can be converted into JSON (JavaScript Object Notation), YAML (YetAnother Markup Language), XML (Extensible Markup Language) and other formats and stored, and this embodiment does not make specific restrictions on this.

[0046] Optionally, according to the message survival judgment result, the application rule storage method of the financial application is determined, and based on the application rule storage method, the rule configuration information of the financial application is generated and stored, including: if the message survival judgment result is that the message survives, then determine the first application function module of the configuration rule corresponding to the configuration application message; generate the rule configuration information of the financial application according to the module identifier of the first application function module, the application identifier of the financial application and the rule type of the configuration rule; and store the rule configuration information of the financial application.

[0047] The first application function module may be a financial application function module for executing the configuration rules of the rule configuration class application message pair, and the first application function module may be an identity information verification module, which may be used to execute the fuse class rules, that is, when the number of errors in user identity authentication exceeds three times, the operation authority for identity authentication is restricted. The module identifier may be an identifier for locating the module, such as the module identifier of the identity information verification module may be a.

[0048] Among them, the application identifier of a financial application can be a unique identifier used to identify a financial application that provides specific technical services. For example, continuing with the above example, the application identifier of a financial application that provides mobile payment can be A, the application identifier of a financial application that provides banking automation can be B, and the application identifier of a financial application that provides financial market infrastructure services can be C.

[0049] Specifically, when there is a surviving rule configuration class application message in a financial application, the application identifier of the financial application, the module identifier of the first application function module corresponding to the application message, and the rule type of the configuration rule are obtained, and then the rule configuration parameters of the financial application are generated and stored. Exemplarily, continuing the above example, if the rule configuration class application message, when the number of errors in user identity authentication exceeds three times, the operation authority for identity authentication is restricted when it is in a surviving state, then the application identifier B corresponding to the financial application providing banking business automation can be obtained, the module identifier corresponding to the first application function module being the identity information verification module is a, and the rule type of the configuration rule is a fuse class rule, then the rule configuration information of the financial application rule can be generated accordingly, and stored in accordance with the application rule storage method of the financial application, and stored in the file storage format, and this embodiment is not specifically limited by comparison.

[0050] This technical solution, according to the result of the application message survival judgment, is that the message survives, and the application message is a rule configuration message, then the rule configuration parameters of the financial application can be generated and stored through the detailed information corresponding to the configuration message. This achieves optimized storage of financial data, thereby improving the convenience and efficiency of statistical query of financial data.

[0051] S140: If the message type of the application message is a resource call type, determine an application resource storage method of the financial application, and generate and store resource call information of the financial application based on the application resource storage method.

[0052] The resource call class may be a message type used to call financial data resources in a financial application. The application resource storage method may be a strategy and technical method for storing financial data resources in a financial application. The application resource storage method may specifically include local storage, cloud storage, and database storage, which may be pre-set by technical personnel based on experience.

[0053] Among them, resource call information may refer to the data and operation records of calling the financial data stored in the financial application by executing different operations in the financial application. Specifically, it may include operation types, such as read and update operations, time information, such as operations to call financial data resources in a specific time period such as every week, resource framework, and caller information.

[0054] Specifically, when the acquired financial application message is a message of the resource call type, a data operation record of calling the financial data resource according to the resource call type message can be generated and stored according to the storage method of the financial data resources in the financial application. Exemplarily, the resource call type application message can be that the application manager reads the call log of the financial data stored in the database at a fixed time every week. In this case, the resource call information with the operation type of reading, the time information of every Wednesday and the caller being the application manager can be generated and stored in the database. This embodiment does not impose specific restrictions on this.

[0055] Optionally, determine an application resource storage method for the financial application, and based on the application resource storage method, generate and store resource calling information of the financial application, including: determining a second application function module in the financial application that calls the application resource corresponding to the application message, and judging the resource framework of the application resource called by the second application function module; generating resource calling information of the financial application according to the module identifier of the second application function module, the application identifier of the financial application, and the framework type of the resource framework; and storing the resource calling information of the financial application.

[0056] The second application function module may refer to an application function module that performs a call operation on a financial data resource. Specifically, the first application function module and the second application function module may be the same or different.

[0057] The resource framework may be an architecture for managing and scheduling financial data resources in financial applications, and may specifically include a computing resource framework, a storage resource framework, and a network resource framework.

[0058] Specifically, when the application message is a resource call message, the second application function module in the financial application that calls the financial data resource corresponding to the resource call message is determined, and the resource call information of the financial application is generated and stored according to the application identifier of the financial application, the module identifier of the second application function module and the framework type of the resource framework. Exemplarily, continuing the above example, the financial application can be an application that provides financial market infrastructure services, and the application identifier of the financial application can be C, the framework type of the resource framework is a network resource framework, and the second application function module is a customer service and support module and the corresponding module identifier is b, then the resource call information of the financial application can be generated and stored accordingly, and this implementation does not impose specific restrictions on this.

[0059] This technical solution can determine the module identifier of the application function module that calls the financial data resource, the application identifier of the financial application, and the resource framework type of the calling resource when the application message is a resource calling message, generate and store the resource calling information of the financial application. It realizes the classification of financial data according to the message type of the application message, thereby optimizing the storage structure of financial data and improving the convenience and efficiency of financial data query and statistics.

[0060] The information collected in this embodiment, such as user-related information, is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good customs, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0061] The technical solution of the embodiment of the present invention obtains the application message of the financial application; if the message type of the application message is a rule configuration class, the application message is judged for message survival to obtain the message survival judgment result; according to the message survival judgment result, the storage method of the application rules of the financial application is determined, and based on the application rule storage method, the rule configuration information of the financial application is generated and stored; if the message type of the application message is a resource call class, the application resource storage method of the financial application is determined, and based on the application resource storage method, the resource call information of the financial application is generated and stored. This technical solution can determine the storage method of each message type according to the message type of each financial application message, and generate and store the corresponding financial data according to the storage method, thereby optimizing the storage of financial data and improving the convenience, efficiency and accuracy of querying and counting financial data; it solves the problem in the prior art that financial data is written into a distributed database through a distributed message server, and it is difficult to query and count financial data due to the large amount of data, and it is easy to make errors.

[0062] Embodiment 2

[0063] Figure 2 This is a flowchart of a financial data management method provided in Embodiment 2 of the present invention. Figure 2 This is a flow chart of a financial data management method provided in the second embodiment of the present invention. Based on the above embodiments, this embodiment further optimizes the above financial data management method.

[0064] Furthermore, after the step of "generating and storing resource call information of financial applications", add the step of "obtaining resource call information of financial applications within a preset time range; determining at least one reference application function module that calls a resource framework of the same framework type based on the resource call information; determining the module resource messages called by each reference application function module within the historical time range; inputting the resource call messages of each reference application function module into the pre-trained traffic allocation model to obtain the traffic allocation results of each reference application function module output by the model; and performing traffic allocation on the reference application function module based on the traffic allocation results." to improve the way of governing financial data. Figure 2 As shown, the method includes:

[0065] S210: Obtain application messages of financial applications.

[0066] S220: If the message type of the application message is a rule configuration type, a message survival judgment is performed on the application message to obtain a message survival judgment result.

[0067] S230. Determine a storage method for application rules of the financial application according to the message survival judgment result, and generate and store rule configuration information of the financial application based on the application rule storage method.

[0068] S240: If the message type of the application message is a resource call type, determine an application resource storage method of the financial application, and generate and store resource call information of the financial application based on the application resource storage method.

[0069] S250: Obtain resource call information of the financial application within a preset time range.

[0070] Specifically, the resource call information of the financial application within a preset time range can be determined based on the generated and stored resource call information. The preset time range can refer to a fixed time period, which can be a week or a month. The specific preset time range can be set by the technician according to actual needs.

[0071] S260: Determine, according to the resource calling information, at least one reference application function module that calls a resource framework of the same framework type.

[0072] Specifically, the resource framework in the resource call information can be obtained, and the framework type of the resource framework can be determined, and then according to the framework type of the resource framework, at least one financial application function module of the same framework type can be determined to be called. For example, within a preset time range, the resource call message obtained includes the function module D, the function module E and the function module F, and the resource framework type of the called resource can be a multi-layer data framework. Furthermore, it can also be determined that the resource call information corresponding to the function module E and the function module F includes a call to a multi-layer data resource, and the function module E and the function module F are determined to be reference application function modules.

[0073] S270: Determine the module resource messages called by each reference application function module within a historical time range.

[0074] Specifically, the module resource calling information of the financial application within the historical time range can also be determined based on the generated and stored resource calling information, wherein the historical time range can be the previous week or the previous month, and can be pre-set by technical personnel according to needs.

[0075] S280: Input the resource call message of each reference application function module into the pre-trained traffic allocation model to obtain the traffic allocation result of each reference application function module output by the model.

[0076] Specifically, the resource calling information corresponding to each reference application function module can be used as the model input of the traffic allocation model, and the traffic allocation model can be used to allocate traffic to each reference function module, so as to obtain the traffic allocation result corresponding to each reference function model as the model output of the traffic allocation model. Traffic can be allocated to the application function modules according to different resource calling information.

[0077] Optionally, the model training method of the traffic allocation model is as follows: obtain the historical resource call messages corresponding to each application function module of the financial application at each historical time node, and obtain at least one model training sample; generate label data of the standard traffic allocation of each model training sample; input each model training sample and its corresponding label data into a preset prediction network model to obtain the predicted traffic allocation output by the model; according to the standard traffic allocation and the predicted traffic allocation, perform model training on the prediction network model until the model training end conditions are met to obtain the traffic allocation model.

[0078] Among them, the standard traffic allocation can be based on known historical data or preset rules, and the standard traffic allocation mode can be determined according to actual needs. It can be manually set by technical personnel based on experience.

[0079] Specifically, historical data of financial applications are collected, including call information of functional modules and corresponding resource usage, wherein the historical data can be obtained through system logs, monitoring tools or traffic analysis platforms. Then, the resource call messages of functional modules collected at each historical time point constitute a training sample, wherein each sample can represent the resource consumption of different modules at a certain time node. According to known historical data or preset rules, the label data of the standard traffic allocation of each model training sample is generated, and then, the historical training samples and the corresponding standard traffic allocation label data are input into the model to the preset prediction network model, and the prediction network model is trained to obtain the predicted traffic allocation output by the model. Specifically, the prediction network model can learn the mapping relationship from input data to output data by optimizing the loss function, wherein the optimized loss function includes mean square error and cross entropy, etc., which can be set by technical personnel based on experience.

[0080] Furthermore, the predicted traffic distribution value output by the trained prediction network model can be compared with the standard traffic distribution label, and the error between the predicted traffic distribution value and the standard traffic distribution label can be calculated. The parameters of the prediction network model are continuously adjusted through the optimization algorithm to minimize the error until the model convergence condition is reached. It can be considered that the model training end condition is reached and the traffic distribution model is obtained. The optimization algorithm can include gradient descent and adaptive gradient algorithm, etc. The model convergence condition can be that the error value is lower than a preset threshold, which can be preset by the technician based on experience.

[0081] This technical solution can input the historical resource call messages of each application function module and the corresponding standard traffic allocation label data into the preset prediction network model to obtain the traffic allocation model and the traffic allocation results corresponding to each application function module. Furthermore, the traffic usage of each financial application node can be planned according to the traffic allocation results, which improves the utilization rate of traffic resources and further improves the operation and maintenance efficiency of financial applications.

[0082] S290. Based on the traffic allocation result, traffic is allocated to the reference application function module.

[0083] Specifically, the traffic of each reference application function module can be allocated according to the traffic allocation result obtained by each reference function module through the traffic allocation model. For example, continuing the above example, the reference application function module includes a reference application function module E and a reference application function module F, wherein the traffic allocation result obtained by the reference application function module E through the traffic allocation model is 50M / S, and the traffic allocation result obtained by the reference application function module F through the traffic allocation model is 66M / S; then 50M / S of traffic can be allocated to the reference application function module E, and 66M / S of traffic can be allocated to the reference application function F. This example does not impose any specific restrictions on this.

[0084] The technical solution of the embodiment of the present invention is to obtain the application message of the financial application; if the message type of the application message is a rule configuration class, then the application message is judged for message survival to obtain the message survival judgment result; according to the message survival judgment result, the application rule storage method of the financial application is determined, and based on the application rule storage method, the rule configuration information of the financial application is generated and stored; if the message type of the application message is a resource call class, then the application resource storage method of the financial application is determined, and based on the application resource storage method, the resource call information of the financial application is generated and stored. Then, the resource call information of the financial application within a preset time range is obtained; according to the resource call information, at least one reference application function module that calls a resource framework of the same framework type and the module resource messages called by each reference application function module within the historical time range are determined; the resource call messages of each reference application function module are input into the pre-trained traffic allocation model to obtain the traffic allocation results of each reference application function module output by the model, and the traffic is allocated to the reference application function module. This technical solution can filter and aggregate the resource call information of each application node of the financial application to form an effective statistical view for governing the resource call information of the financial application, and then by utilizing the traffic allocation rules for each application node in the financial application, it can achieve maximum utilization of the traffic when each application node makes resource calls, improve the utilization rate of traffic resources, and further improve the operation and maintenance efficiency of the financial application.

[0085] Embodiment 3

[0086] Figure 3 The structure diagram of a financial data management device provided in the third embodiment of the present invention is shown in FIG. The financial data management device provided in the embodiment of the present invention can be applied to the situation where the efficiency of querying and counting financial data is extremely low due to the excessive amount of financial data. The financial data management device can be implemented in the form of hardware and / or software, such as Figure 3 As shown, it specifically includes: an application message acquisition module 310, a message survival judgment module 320, a rule configuration information generation module 330 and a resource call information generation module 340. Among them,

[0087] The application message acquisition module 310 is used to acquire application messages of financial applications.

[0088] The message survival judgment module 320 is used to perform message survival judgment on the application message if the message type of the application message is a rule configuration type, and obtain a message survival judgment result.

[0089] The rule configuration information generating module 330 is used to determine the storage method of the application rules of the financial application according to the message survival judgment result, and generate and store the rule configuration information of the financial application based on the application rule storage method.

[0090] The resource call information generation module 340 is used to determine the application resource storage mode of the financial application if the message type of the application message is a resource call class, and generate and store the resource call information of the financial application based on the application resource storage mode.

[0091] This technical solution obtains application messages of financial applications; if the message type of the application message is a rule configuration type, the application message is judged for message survival to obtain a message survival judgment result; according to the message survival judgment result, the storage method of the application rules of the financial application is determined, and based on the application rule storage method, the rule configuration information of the financial application is generated and stored; if the message type of the application message is a resource call type, the application resource storage method of the financial application is determined, and based on the application resource storage method, the resource call information of the financial application is generated and stored. This technical solution can determine the storage method of each message type according to the message type of each financial application message, and generate and store the corresponding financial data according to the storage method, thereby optimizing the storage of financial data and improving the convenience, efficiency and accuracy of querying and counting financial data; it solves the problem in the prior art that financial data is written into a distributed database through a distributed message server, and it is difficult to query and count financial data due to the large amount of data, and it is prone to errors.

[0092] Optionally, the message survival judgment module 320 is specifically used to:

[0093] Determine the message timing of the application message of the rule configuration class;

[0094] According to the message timing time, determining whether an application message of the node survival class of the financial application is received;

[0095] If yes, the message survival judgment result is that the message survives;

[0096] If not, the message survival judgment result is that the message does not survive.

[0097] Optionally, the rule configuration information generating module 330 is specifically used to:

[0098] If the message survival judgment result is that the message survives, determining a first application function module that configures a configuration rule corresponding to the application message;

[0099] Generate rule configuration information of the financial application according to the module identifier of the first application function module, the application identifier of the financial application and the rule type of the configuration rule; IP address;

[0100] The rule configuration information of the financial application is stored.

[0101] Optionally, the resource call information generating module 340 is specifically used to:

[0102] Determine a second application function module in the financial application that calls the application resource corresponding to the application message, and determine a resource framework of the application resource called by the second application function module;

[0103] Generate resource call information of the financial application according to the module identifier of the second application function module, the application identifier of the financial application, and the framework type of the resource framework;

[0104] The resource calling information of the financial application is stored.

[0105] Optionally, the device further includes a flow distribution allocation module and a flow distribution model training module;

[0106] Optionally, a flow distribution module is used to:

[0107] After generating and storing the resource calling information of the financial application, obtaining the resource calling information of the financial application within a preset time range;

[0108] Determine, according to the resource calling information, at least one reference application function module that calls a resource framework of the same framework type;

[0109] Determine the module resource messages called by each of the reference application function modules within a historical time range;

[0110] Inputting resource call messages of each reference application function module into a pre-trained traffic allocation model to obtain traffic allocation results of each reference application function module output by the model;

[0111] Based on the traffic allocation result, traffic is allocated to the reference application function module.

[0112] Optional, traffic distribution model training module, used to:

[0113] Obtain historical resource call messages corresponding to each application function module of the financial application at each historical time node, and obtain at least one model training sample;

[0114] Generating label data of standard flow distribution of each of the model training samples;

[0115] Inputting each of the model training samples and their corresponding label data into a preset prediction network model to obtain the predicted traffic distribution output by the model;

[0116] According to the standard traffic distribution and the predicted traffic distribution, the predicted network model is trained until the model training end condition is met to obtain a traffic distribution model.

[0117] The financial data management device provided in the embodiment of the present invention can execute the financial data management method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0118] Embodiment 4

[0119] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0120] like Figure 4 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0121] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0122] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as the financial data governance method.

[0123] In some embodiments, the financial data governance method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the financial data governance method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to perform the financial data governance method in any other appropriate manner (e.g., by means of firmware).

[0124] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0125] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0126] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0127] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0128] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0129] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0130] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0131] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A financial data governance method, characterized in that: include: Get application messages of financial applications; If the message type of the application message is a rule configuration class, performing a message survival judgment on the application message to obtain a message survival judgment result; Determine, according to the message survival judgment result, a storage method of application rules of the financial application, and generate and store rule configuration information of the financial application based on the application rule storage method; If the message type of the application message is a resource call type, then the application resource storage method of the financial application is determined, and based on the application resource storage method, resource call information of the financial application is generated and stored.

2. The method according to claim 1, characterized in that The performing message survival judgment on the application message to obtain a message survival judgment result includes: Determine the message timing of the application message of the rule configuration class; According to the message timing time, determining whether an application message of the node survival class of the financial application is received; If yes, the message survival judgment result is that the message survives; If not, the message survival judgment result is that the message does not survive.

3. The method according to claim 1, characterized in that The determining, according to the message survival judgment result, the storage method of the application rules of the financial application, and generating and storing the rule configuration information of the financial application based on the application rule storage method, includes: If the message survival judgment result is that the message survives, determining a first application function module that configures a configuration rule corresponding to the application message; generating rule configuration information of the financial application according to the module identifier of the first application function module, the application identifier of the financial application, and the rule type of the configuration rule; The rule configuration information of the financial application is stored.

4. The method according to claim 1, characterized in that: The determining the application resource storage mode of the financial application, and generating and storing the resource calling information of the financial application based on the application resource storage mode, includes: Determine a second application function module in the financial application that calls the application resource corresponding to the application message, and determine a resource framework of the application resource called by the second application function module; Generate resource call information of the financial application according to the module identifier of the second application function module, the application identifier of the financial application, and the framework type of the resource framework; The resource calling information of the financial application is stored.

5. The method according to claim 1, characterized in that After generating and storing the resource calling information of the financial application, the method further includes: Obtaining resource call information of the financial application within a preset time range; Determine, according to the resource calling information, at least one reference application function module that calls a resource framework of the same framework type; Determine the module resource messages called by each of the reference application function modules within a historical time range; Inputting resource call messages of each reference application function module into a pre-trained traffic allocation model to obtain traffic allocation results of each reference application function module output by the model; Based on the traffic allocation result, traffic is allocated to the reference application function module.

6. The method according to claim 5, characterized in that The model training method of the traffic distribution model is as follows: Obtain historical resource call messages corresponding to each application function module of the financial application at each historical time node, and obtain at least one model training sample; Generating label data of standard flow distribution of each of the model training samples; Inputting each of the model training samples and their corresponding label data into a preset prediction network model to obtain the predicted traffic distribution output by the model; According to the standard traffic distribution and the predicted traffic distribution, the predicted network model is trained until the model training end condition is met to obtain a traffic distribution model.

7. A financial data management device, characterized in that: include: An application message acquisition module, used to acquire application messages of financial applications; A message survival judgment module, used for performing message survival judgment on the application message if the message type of the application message is a rule configuration class, and obtaining a message survival judgment result; A rule configuration information generating module, used to determine the storage mode of the application rules of the financial application according to the message survival judgment result, and generate and store the rule configuration information of the financial application based on the application rule storage mode; The resource call information generation module is used to determine the application resource storage method of the financial application if the message type of the application message is a resource call class, and generate and store the resource call information of the financial application based on the application resource storage method.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so as to enable the at least one processor to execute the financial data governance method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the financial data governance method described in any one of claims 1-6 when executed by a processor.

10. A computer program product, characterized in that The computer program product comprises a computer program which, when executed by a processor, implements the financial data governance method according to any one of claims 1 to 6.

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