Event Modeling Method, Apparatus, Computer Device, and Storage Medium

Abstract

The present application relates to an event modeling method, apparatus, computer device, and storage medium. The method includes: obtaining service attribute information of a data sender; locating a target service area to which the data sender belongs in a service architecture according to the service attribute information; parsing the service attribute information to determine service events included in the data sender and event types corresponding to the service events; and establishing an event model according to the target service area, service events, and corresponding event types, instructing the data sender to perform data processing according to the event model. Using this method can improve data processing efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular, to an event modeling method, apparatus, computer device, and storage medium. Background Art

[0002] With the development of Internet technology, under the trend of explosive growth of data information, the data transmission between the upstream data generation end and the downstream business (data) application system is becoming more and more frequent, which poses higher requirements for the data processing method in the data transmission process.

[0003] In traditional data processing methods, it is necessary to batch-divide the data stream at the data generation end according to preset dimensions. After the data transmission channel receives the data of the same batch, data processing operations such as business theme classification are performed on the data of the same batch, and then the data of the same business theme domain after processing is transmitted to the corresponding downstream business application system.

[0004] However, the method of processing data in batches requires waiting for the completion of receiving the data of the same batch before data processing can be performed. In the face of real-time data, the method of batch data processing affects the timeliness of data. Summary of the Invention

[0005] Based on this, it is necessary to provide an event modeling method, apparatus, computer device, and storage medium for the above technical problems.

[0006] An event modeling method, the method comprising:

[0007] Obtain the business attribute information of the data transmission party;

[0008] Locate the target business area to which the data transmission party belongs in the business architecture according to the business attribute information;

[0009] Analyze the business attribute information to determine the business events included in the data transmission party and the event types corresponding to the business events;

[0010] Establish an event model according to the target business area, the business events, and the corresponding event types, and instruct the data transmission party to perform data processing according to the event model.

[0011] In one embodiment, the determining the association relationship between the business behaviors corresponding to any business scenario of the data generation party according to the event data processing logic of any business scenario included in the business attribute information of the data generation party includes:

[0012] Analyze the event data processing logic of any business scenario included in the business attribute information of the data producer, and obtain all business behaviors of the data producer in any of the business scenarios and the processing order of the business behaviors;

[0013] For each business behavior, determine the actor and the action command to obtain the behavior attribute information of each business behavior;

[0014] According to the preset aggregation rules and sub-domain division rules, aggregate and sub-domain divide the behavior attribute information of the business behaviors, and determine the association relationships between the business behaviors included in each aggregation sub-domain.

[0015] In one embodiment, the method further includes:

[0016] Based on the logical relationships between the business events included in the event model, establish the mapping relationships between the event model and each level of the event database;

[0017] Store the event model in the target level of the event database.

[0018] In one embodiment, the data transfer party is a data consumer. Analyzing the business attribute information to determine the business events included in the data transfer party and the event types corresponding to the business events includes:

[0019] Analyze the business attribute information of the data consumer, and screen the target business scenarios of the data consumer from the set of business scenarios in the target business domain according to the business attribute information;

[0020] In the event database, determine the business events included in the target business scenario and the event types corresponding to the business events.

[0021] In one embodiment, determining the business events included in the target business scenario and the event types corresponding to the business events in the event database includes:

[0022] Analyze the business behaviors included in the target business scenario and the processing order of the business behaviors;

[0023] According to the business behaviors and the processing order of the business behaviors, in the hierarchical directory corresponding to the target business domain of the event database, determine the business events corresponding to the business behaviors and the event types corresponding to the business events.

[0024] An event modeling device, the device includes:

[0025] An acquisition module, configured to acquire the business attribute information of the data transfer party;

[0026] A positioning module, configured to locate the target business area to which the data transmitter belongs in the business architecture according to the service attribute information;

[0027] A determination module, configured to analyze the service attribute information to determine the service events included in the data transmitter and the event types corresponding to the service events;

[0028] A creation module, configured to establish an event model according to the target business area, the service events, and the corresponding event types, and instruct the data transmitter to perform data processing according to the event model.

[0029] In one embodiment, the determination module is further configured to determine the association relationship between the service behaviors corresponding to any service scenario in the service attribute information of the data generation party according to the event data processing logic of any service scenario;

[0030] According to the association relationship between the service behaviors, determine the service events and the event types of the service events in any service scenario of the data generation party in the target business area.

[0031] A computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are implemented:

[0032] Obtain the service attribute information of the data transmitter;

[0033] According to the service attribute information, locate the target business area to which the data transmitter belongs in the business architecture;

[0034] Analyze the service attribute information to determine the service events included in the data transmitter and the event types corresponding to the service events;

[0035] According to the target business area, the service events, and the corresponding event types, establish an event model, and instruct the data transmitter to perform data processing according to the event model.

[0036] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0037] Obtain the service attribute information of the data transmitter;

[0038] According to the service attribute information, locate the target business area to which the data transmitter belongs in the business architecture;

[0039] Analyze the service attribute information to determine the service events included in the data transmitter and the event types corresponding to the service events;

[0040] Based on the target business domain, the business event, and the corresponding event type, an event model is established to instruct the data transmitter to process data according to the event model.

[0041] The above event modeling method, apparatus, computer device, and storage medium obtain the business attribute information of the data transmitter; based on the business attribute information, locate the target business domain to which the data transmitter belongs in the business architecture; analyze the business attribute information to determine the business events included in the data transmitter and the event types corresponding to the business events; based on the business events and the corresponding event types, establish an event model to instruct the data transmitter to process data according to the event model. By using this method, by generating an event model, the data processing relationship between the data to be transmitted by the data transmitter is determined, and the data transmitter is reversely instructed to perform data processing transformation, thereby improving the data processing efficiency. Brief Description of the Drawings

[0042] Figure 1 It is a schematic diagram of the hierarchical architecture of the event processing platform in an embodiment;

[0043] Figure 2 It is a schematic flowchart of the event modeling method in an embodiment;

[0044] Figure 3 It is a schematic flowchart of the steps for determining the business events of the data producer in an embodiment;

[0045] Figure 4 It is a flowchart of the steps for determining the association relationship between the business behaviors of the data producer in an embodiment;

[0046] Figure 5 It is a schematic flowchart of the event analysis based on the DDD methodology in an embodiment;

[0047] Figure 6 It is a schematic flowchart of the method for establishing a mapping relationship with the event database in an embodiment;

[0048] Figure 7 It is a schematic diagram of the mapping relationship established with the event database in an embodiment;

[0049] Figure 8 It is a schematic flowchart of the steps for screening the target business scenarios of the data consumer in an embodiment;

[0050] Figure 9 It is a schematic diagram of the target business scenario in the financial field in an embodiment;

[0051] Figure 10 It is a schematic diagram of the first-level classification target of the standard event database in the financial field in an embodiment;

[0052] Figure 11 It is a flow diagram for determining the steps of the data consumer business event in an embodiment;

[0053] Figure 12 It is a flow diagram of the event modeling method in an embodiment;

[0054] Figure 13 It is a structural block diagram of the event modeling device in an embodiment;

[0055] Figure 14 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0056] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0057] In an embodiment, an event processing platform is provided. The event processing platform is built based on mainstream big data components such as Apache Flink and Apache Kafka. As Figure 1 shown, it includes an event management service layer, an event message processing service layer, and an event message queue service layer. For each service layer of the event processing platform, there is a corresponding management module for data management. In this embodiment, the event processing platform is used to implement the event modeling method. When the business processing requirements of the data producer in the data transmission party are connected to the event processing platform, the event processing platform generates an event model (i.e., an event template), and according to the event model, it instructs the data producer to transmit the real-time data to be transmitted to the event processing platform in real time according to the requirements of the event model. When the data subscription requirements of the data consumer in the data transmission party are transmitted to the event processing platform, the event processing platform can also obtain the corresponding business event data based on the mapping relationship in the event database through the determined target event model according to the data subscription requirements.

[0058] In this embodiment, as Figure 2 shown, an event modeling method is provided. The event modeling method is applied to the above-mentioned event processing platform and is used to generate an event model. Specifically, in this embodiment, an example is given where the event processing platform to which the event modeling method belongs is deployed on a server. It can be understood that the event processing platform can also be deployed on a terminal, or can be deployed in a system including a terminal and a server, and is realized through the interaction between the terminal and the server. Therefore, the device main body of the event processing platform is not limited in this embodiment. In this embodiment, whether the event processing platform is deployed on a server or a terminal device is collectively referred to as a computer device for the convenience of scheme migration. The specific event modeling method includes the following steps:

[0059] Step 201: Obtain the business attribute information of the data transfer party.

[0060] In implementation, the data transfer process involves two parties. The event processing platform in this embodiment accesses this data transfer process, establishes communication connections with the two data transfer parties, and then can select at least one of the two data transfer parties for event modeling. Specifically, the two data transfer parties include a data generation party and a data consumption party. The computer device obtains the business attribute information of the data transfer party (data generation party and / or data consumption party), and performs event modeling based on the business attribute information of the data transfer party. Among them, the business attribute information is obtained from the operation logs of the data transfer party, and the business attribute information is the logical process information for processing event services in each business scenario of the data transfer party in its respective business field and the event data information generated in the logical process.

[0061] For example, if the data transfer party is a specific application product "Yinji Tong" among the upstream data generation parties, the business attribute information that can be obtained by the event processing platform deployed on the computer device includes: fund account information, fund redemption information, fund subscription information, fund cancellation information, etc. in the fund trading business scenario of the Yinji Tong system (a fund product sales application product), fund account balance information, fund unit net value information, etc. in the fund query business scenario, and the logical process between various event services of the "Yinji Tong" product, such as first subscribing to a fund and then redeeming the fund. In summary, the business attribute information of the data transfer party can be any data information generated during the data processing of the data transfer party or related to the data processing process. The embodiments of the present application do not limit the business attribute information of the data transfer party.

[0062] Step 202: Locate the target business field to which the data transfer party belongs in the business architecture according to the business attribute information.

[0063] In implementation, the computer device locates the target business field to which the data transfer party belongs in the business architecture according to the business attribute information. Specifically, taking the financial field of a bank as an example, the computer device locates the target business field (which can also be called the service field) to which the data transfer party (for example, the fund distribution product "Yinji Tong") belongs in the overall banking business architecture according to the BIAN (Banking Industry Architecture Network) methodology. Furthermore, the position of the function of the data transfer party product in the overall business process of the enterprise is determined.

[0064] Step 203: Analyze the business attribute information to determine the business events included in the data transfer party and the event types corresponding to the business events.

[0065] In implementation, when the business area to which the data transmitter belongs is determined, the computer device further analyzes the business attribute information of the data transmitter to determine the business events included in the data transmitter and the event types corresponding to the business events in the target business area. Specifically, there are two different processing methods for the two types of data transmitters.

[0066] Method 1: If the data transmitter is a data producer (i.e., the upstream application system), the computer device determines the location (target business area) of the data producer in the enterprise business architecture based on the BIAN methodology, further analyzes the business attribute information of the data producer through the DDD (Domain-Driven-Design) methodology, determines the specific business behaviors of the data producer in each business scenario of the target business area, and then, based on the domain events corresponding to the specific business behaviors, performs event aggregation and sub-domain division to determine the business events of the data producer and the event types corresponding to the business events. Among them, the process of analyzing events based on the DDD methodology to determine business events and the event types of the business events will be further described in detail below and will not be elaborated here.

[0067] Method 2: If the data transmitter is a data consumer (i.e., the downstream application system), the computer device determines the location (target business area) of the data consumer in the enterprise architecture based on the BIAN methodology, further analyzes the domain events corresponding to the target business area included in the business attribute information, maps the domain events to the business topics at the corresponding levels in the standard event database according to the ownership and hierarchical relationships, and determines the business events of the data consumer in the target business area and the event types corresponding to the business events. The specific process of determining business events and event types will be further described in detail below and will not be elaborated here.

[0068] Step 204: Establish an event model based on the target business area, business events, and corresponding event types, and instruct the data transmitter to process data according to the event model.

[0069] In implementation, the computer device establishes an event model of the data transmitter according to the business events in each business scenario of the data transmitter in the target business domain and the event types corresponding to the business events. Furthermore, the computer device can instruct the data transmitter to perform data processing transformation according to the event model, so that the data transmitter can clarify the access conditions of the event processing platform and meet the data requirements of the event processing platform. Specifically, the data producer performs data processing based on the event model of the event processing platform to realize the real-time transmission of the data to be transmitted to the event processing platform. The data consumer performs data collection and consumption based on the event model of the event processing platform, and establishes a mapping relationship between the data subscription requirements and the data of the event processing platform (business event data stored in the event database), so as to realize real-time data subscription.

[0070] In the above event modeling method, the computer device obtains the business attribute information of the data transmitter; according to the business attribute information, locates the target business domain to which the data transmitter belongs in the business architecture. Then, further analyzes the business attribute information to determine the business events included in the data transmitter and the event types corresponding to the business events. According to the target business domain, business events and corresponding event types, an event model is established to instruct the data transmitter to perform data processing according to the event model. By adopting this method, by generating an event model, the data processing relationship between the data to be transmitted by the data transmitter is determined, and the data transmitter is reversely instructed to perform data processing transformation, thereby improving the data processing efficiency.

[0071] In one embodiment, as Figure 3 shown, the specific processing process of event analysis based on the DDD methodology in step 203 includes the following steps:

[0072] Step 301, according to the event data processing logic of any business scenario included in the business attribute information of the data producer, determine the association relationship between the various business behaviors corresponding to any business scenario of the data producer.

[0073] In implementation, for the case where the data transmitter is the data producer, the event processing platform deployed on the computer device further analyzes the event processing logic in any business scenario included in the business attribute information of the data producer according to the determined target business domain to which the data producer belongs, and identifies the event nodes, the triggering conditions of the event nodes, and the data transfer conditions of each event in the entire event processing process, etc. Furthermore, the computer device determines the association relationship between the various business behaviors corresponding to any business scenario of the data producer based on this.

[0074] Step 302, according to the association relationship between the various business behaviors, determine the business events and the event types of the business events in any business scenario of the data producer in the target business domain.

[0075] In implementation, based on the association relationships among business actions in a specific business scenario obtained by the computer device through DDD methodology analysis, the computer device aggregates, divides subdomains, and defines bounded contexts (bounded definition) for the event data corresponding to the business actions, and thereby performs event definition and event classification to determine the business events and the event types of the business events in any business scenario in the target business domain by the data producer.

[0076] Optionally, in each business scenario of the data producer, for the collaborative interaction business scenario of the data producer, it is also possible to directly perform event analysis using DDD methodology without determining the target business domain.

[0077] In this embodiment, by analyzing the business attribute information of the data producer, the business events and the event types of the business events of the data producer are redefined, as well as the rules and classification criteria for the same business event, so as to retroactively transform the data producer according to the rules and criteria to improve the real-time data transmission timeliness of the data producer.

[0078] In one embodiment, as Figure 4 shown, the specific processing procedure of step 301 includes:

[0079] Step 401, analyze the event data processing logic of any business scenario included in the business attribute information of the data producer to obtain all business actions and the business action processing sequence of the data producer in any business scenario.

[0080] In implementation, for each business scenario included in the data producer, based on the positioning of the data producer in the overall business architecture, under the determined target business domain, using the business attribute information of the data producer in that target business domain as the common language and business process for applying DDD methodology, the computer device completes the event modeling analysis of domain-driven design (DDD). Specifically, the computer device analyzes the event data processing logic of any business scenario included in the business attribute information of the data producer to obtain all business actions and the business action processing sequence of the data producer in any business scenario. As Figure 5 shown, when analyzing the event data processing logic of any business scenario, each business action and the processing sequence among the business actions included in that business scenario are sorted out according to each input data and the corresponding output data in the event data processing logic. Among them, the event processing logic can be obtained from the operation log of the data producer, and in the operation log, the actor, action command of each event node (business action) of the data producer, and the processing sequence among each event node (business action) are recorded.

[0081] Step 402, determine the actor and action command for each business action to obtain the action attribute information of each business action.

[0082] In implementation, the computer device extracts the actor and action command corresponding to a specific business action in the data producer of the event data processing logic, and obtains the action attribute information of each business action. For example Figure 5 As shown, the analyzed action attribute information includes the specific business content generated by executing this business action, who caused this business action, the conditions triggering this business action, the action command (command) corresponding to this business action, etc. The embodiments of the present application do not make limitations

[0083] Among them, each business action corresponds to a domain event in the specific business scenario of the data transmission party in the target business domain. The domain event represents an event occurring in the target business domain to which it belongs. Therefore, the business action in the present application can also refer to the domain event. Furthermore, the obtained action attribute information of each business action is also the event attribute information characterizing the corresponding domain event

[0084] Step 403, according to the preset aggregation rule and sub-domain division rule, aggregate and sub-domain divide the action attribute information of the business action, and determine the association relationship between the business actions included in each aggregated sub-domain

[0085] In implementation, the computer device aggregates and sub-domain divides the action attribute information of the business action according to the preset aggregation rule and sub-domain division rule, and classifies all domain events included in the overall application system of the data producer according to the aggregation result and the divided sub-domains, and determines the association relationship between the business actions included in each aggregated sub-domain. Among them, the preset aggregation rule and sub-domain division rule can be obtained by the computer device training event aggregation and sub-domain division using the historical data of multiple data producer application products for the classification discrimination network, and can be used for the model of aggregation and sub-domain division. Furthermore, the discrimination rules relied on in the model are used as the preset event aggregation rule and sub-domain division rule

[0086] In one embodiment, as Figure 6 shown, the method further includes

[0087] Step 601, based on the logical relationship between the business events included in the event model, establish the mapping relationship between each level of the event model and the event database

[0088] Step 602, store the event model to the target level of the event database

[0089] In implementation, the computer device aggregates and sub-domain divides the domain events to obtain the business events of the data producer, and then obtains the event model corresponding to the business events. Then, the computer device establishes the mapping relationship between each level of the event model and the event database, asFigure 7 As shown, the computer device maps and stores the logical relationships among the business events included in the event model to the corresponding levels in the event database to generate a standard event database. The hierarchical directory of this standard event database is presented as the event classification directory of the target business domain based on the mapping relationship. Specifically, the subdomains divided when determining business events are used as the initial classification criteria for business events and mapped to the first-level categories in the database, and the aggregation results included in each subdomain are mapped to the second-level categories in the database.

[0090] In one embodiment, as Figure 8 shown, in addition to event modeling for the upstream data producers, the event processing platform can also perform event modeling for downstream data consumers. Therefore, when the data transmitter is a data consumer, the specific processing process of step 203 includes the following steps:

[0091] Step 801, parse the business attribute information of the data consumer, and screen the target business scenarios of the data consumer from the set of business scenarios in the target business domain according to the business attribute information.

[0092] In practice, the business attribute information of the data consumer is the logical process information for processing event services in each business scenario of the data consumer in the affiliated business domain and the event data information generated in the logical process. Therefore, the computer device determines the set of business scenarios included by the data consumer in the target business domain according to the business attribute information of the data consumer, and screens the target business scenarios from the set of business scenarios according to the preset scenario screening rules. Among them, the preset scenario screening rule is the real-time data processing requirement rule, that is, whether there is a real-time data processing requirement in this business scenario. Therefore, the target business scenario screened according to this real-time data processing requirement rule is the real-time data processing business scenario. This real-time data processing business scenario is used as the event-driven business scenario of the event processing platform in this embodiment for event modeling to meet the real-time data processing requirement.

[0093] Specifically, common real-time data processing business scenarios include:

[0094] 1. Observation

[0095] The observation scenario is used to monitor the process of the overall data transmitter system, identify special business behaviors (regular behaviors not marked with preset behavior marks), and generate alarm information when special business behaviors are sent in the business process of the data consumer.

[0096] 2. Information dissemination

[0097] 3. Dynamic operation behavior business scenario

[0098] The dynamic operation behavior business scenario is to react to business events. As part of a business transaction, it realizes low-latency decision-making and quickly responds to threats and opportunities. Event processing is usually used to dynamically drive system execution to respond to incoming events.

[0099] 4. Active diagnostics business scenario

[0100] The active diagnostics business scenario is to actively perform fault diagnosis based on the alarm information output in the observed business scenario and solve the fault problems.

[0101] 5. Predictive processing business scenario

[0102] The predictive processing business scenario is to identify upcoming business events and eliminate or mitigate the negative impacts brought by these business events.

[0103] In summary, the above several common real-time data processing scenarios can be used as event-driven business scenarios applicable to the event processing platform. Therefore, when the computer device faces data consumers, event modeling can be carried out based on this event-driven business scenario.

[0104] Step 802, in the event database, determine the business events included in the target business scenario and the event types corresponding to the business events.

[0105] In implementation, for the selected event-driven business scenarios, determine the business events and the event types corresponding to the business events under each business scenario. For example, taking the banking industry as an example, the event-driven business scenarios in the banking industry, such as Figure 9 shown, may include: intelligent application business scenario, intelligent risk control business scenario, intelligent marketing business scenario, and intelligent operation and maintenance business scenario. Each business scenario (event-driven scenario) corresponds to a type of domain event, and the domain event is the event corresponding to the specific business behavior in each business scenario. Establish a mapping relationship between the domain events under each business scenario and the hierarchical classification events in the event database, that is, determine the business events of the data consumer under this business scenario and the event types of the business events.

[0106] Among them, the event database developed for the financial field can cover the standard event set of the financial field, and the data assets in the event database are available and shareable. The event (theme) classification of the event database is based on the original classification rules of data warehouse technology and the event classification of the financial field where it is located, forming a financial field event model, such asFigure 10 As shown, the event themes included in the event model are parties, agreements, products and services, events, channels, geographical regions, assets, marketing (business direction), finance and risks, etc. At the same time, it also takes into account the collaborative interaction events of non-financial themes.

[0107] The secondary event classification of the standard event database in the financial field is shown in Table 1 below:

[0108] Table 1

[0109]

[0110]

[0111] According to the secondary event classification directory and the mapping relationship between the data consumer and the standard event database, the specific business events and event types can be further determined.

[0112] In one embodiment, as Figure 11 shown, the specific processing process of determining business events and event types in the event database in step 802 includes the following steps:

[0113] Step 1101, analyze the business behaviors and the order of business behavior processing included in the target business scenario.

[0114] Step 1102, according to the business behaviors and the order of business behavior processing, determine the business events corresponding to the business behaviors and the event types corresponding to the business events in the hierarchical directory corresponding to the target business area of the event database.

[0115] In implementation, the computer device analyzes the business behaviors and the order of business behavior processing included by the data consumer in the target business scenario, and then, based on the hierarchical classification relationship of the business behaviors and the order of business behavior processing, establishes a mapping relationship with the hierarchical directory corresponding to the target business area of the event database, and queries and determines the standard business events corresponding to the business behaviors and the event types corresponding to the business events according to the mapping relationship.

[0116] Optionally, the event processing platform provided in this embodiment applied to the event modeling method, after being deployed on the server, can be used to implement data transmission and communication between the data producer and the data consumer. The functions of each service layer of the specifically built event processing platform are shown in Table 2 below:

[0117] Table 2

[0118]

[0119] In the above embodiments, as Figure 12As shown, for the data producer (event producer) and data consumer (event consumer), event modeling is performed based on the BIAN methodology and / or the DDD methodology to obtain an event model, and a mapping relationship is established between the event model and the event database. Finally, the established event model is integrated into the event processing platform (i.e., Figure 12 the event platform in

[0120] It should be understood that although Figures 2 to 4 , Figure 6 , Figure 8 , Figure 11 each step in the flowchart of Figures 2 to 4 , Figure 6 , Figure 8 , Figure 11 is shown in sequence according to the indication of the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise clearly stated in this article, there is no strict order limit for the execution of these steps, and these steps can be executed in other orders. Moreover,

[0121] In one embodiment, as Figure 13 shown, an event modeling device 1300 is provided, including: an acquisition module 1310, a positioning module 1320, a determination module 1330, and a creation module 1340, where:

[0122] The acquisition module 1310 is configured to acquire the business attribute information of the data transmission party;

[0123] The positioning module 1320 is configured to locate the target business area to which the data transmission party belongs in the business architecture according to the business attribute information;

[0124] The determination module 1330 is configured to parse the business attribute information to determine the business events included in the data transmission party and the event types corresponding to the business events;

[0125] The creation module 1340 is configured to establish an event model according to the target business area, business events, and corresponding event types, and instruct the data transmission party to perform data processing according to the event model.

[0126] In one embodiment, the determining module 1330 is further configured to determine the association relationship between each business behavior corresponding to any business scenario of the data generating party according to the event data processing logic of any business scenario included in the business attribute information of the data generating party;

[0127] According to the association relationship between each business behavior, determine the business events in any business scenario of the data generating party in the target business domain and the event types of the business events.

[0128] In one embodiment, the determining module 1330 is further configured to parse the event data processing logic of any business scenario included in the business attribute information of the data generating party to obtain all business behaviors of the data generating party in any business scenario and the processing sequence of the business behaviors;

[0129] For each business behavior, determine the behavior subject and the behavior command to obtain the behavior attribute information of each business behavior;

[0130] According to the preset aggregation rule and sub - domain division rule, perform aggregation and sub - domain division on the behavior attribute information of the business behaviors to determine the association relationship between each business behavior included in each aggregation sub - domain.

[0131] In one embodiment, the apparatus 1300 further includes: a mapping module, configured to establish a mapping relationship between each level of the event model and the event database based on the logical relationship between each business event included in the event model; store the event model to the target level of the event database.

[0132] In one embodiment, the data transmitting party is a data consuming party, and the determining module 1330 is specifically configured to parse the business attribute information of the data consuming party, and screen the target business scenario of the data consuming party from the set of business scenarios in the target business domain according to the business attribute information;

[0133] In the event database, determine the business events included in the target business scenario and the event types corresponding to the business events.

[0134] In one embodiment, the determining module 1330 is further configured to parse the business behaviors included in the target business scenario and the processing sequence of the business behaviors;

[0135] According to the business behaviors and the processing sequence of the business behaviors, in the hierarchical directory corresponding to the target business domain of the event database, determine the business events corresponding to the business behaviors and the event types corresponding to the business events.

[0136] For the specific limitations of the event modeling device 1300, reference can be made to the limitations on the event modeling method in the foregoing text, which will not be elaborated here. Each module in the above event modeling device 1300 can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0137] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 14 shown. The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store business event data, business attribute information data, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements an event modeling method.

[0138] Those skilled in the art can understand that Figure 14 the structure shown in

[0139] is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0140] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, it implements the steps in each of the above method embodiments.

[0141] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0142] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0143] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. An event modeling method, characterized in that, The method is applied to an event processing platform, and the method includes: Obtain business attribute information from the operation logs of the data transfer party. The business attribute information is the logical process information for processing event services in each business scenario of the data transfer party in its affiliated business domain and the event data information generated in the logical process. Locate the target business domain to which the data transfer party belongs in the business architecture according to the business attribute information. When the data transfer party is a data generation party, determine the association relationship between each business behavior corresponding to any business scenario of the data generation party according to the event data processing logic of any business scenario included in the business attribute information of the data generation party. Determine the business events and the event types of the business events in any business scenario of the data generation party in the target business domain according to the association relationship between each business behavior. When the data transfer party is a data consumption party, analyze the business attribute information of the data consumption party, and screen the target business scenario of the data consumption party from the set of business scenarios in the target business domain according to the business attribute information. In the event database, determine the business events included in the target business scenario and the event types corresponding to the business events. Establish an event model according to the target business domain, the business events, and the corresponding event types, and instruct the data transfer party to perform data processing according to the event model.

2. The method according to claim 1, characterized in that The determining the association relationship between each business behavior corresponding to any business scenario of the data generation party according to the event data processing logic of any business scenario included in the business attribute information of the data generation party includes: Analyze the event data processing logic of any business scenario included in the business attribute information of the data generation party to obtain all business behaviors and the processing order of the business behaviors of the data generation party in any business scenario. Determine the behavior subject and behavior command for each business behavior to obtain the behavior attribute information of each business behavior. Aggregate and sub-domain partition the behavior attribute information of the business behaviors according to the preset aggregation rules and sub-domain partition rules to determine the association relationship between each business behavior included in each aggregation sub-domain.

3. The method according to claim 1, wherein The method further includes: Establish a mapping relationship between the event model and each level of the event database based on the logical relationship between the business events included in the event model. Store the event model in the target level of the event database.

4. The method according to claim 1, characterized in that The determining the business events included in the target business scenario and the event types corresponding to the business events in the event database includes: Analyze the business behaviors and the processing order of the business behaviors included in the target business scenario. According to the business behaviors and the processing order of the business behaviors, determine the business events corresponding to the business behaviors and the event types corresponding to the business events in the hierarchical directory corresponding to the target business domain of the event database.

5. An event modeling device, characterized in that, The device includes: An acquisition module, configured to acquire business attribute information from the operation log of a data transfer party, where the business attribute information is the logical process information of processing event services in each business scenario of the data transfer party in its affiliated business field and the event data information generated in the logical process; A positioning module, configured to locate the target business field to which the data transfer party belongs in the business architecture according to the business attribute information; When the data transfer party is a data generation party, a determination module, configured to determine the association relationship between each business behavior corresponding to any business scenario of the data generation party according to the event data processing logic of any business scenario included in the business attribute information of the data generation party; According to the association relationship between each business behavior, determine the business events and the event types of the business events of the data generation party in any business scenario in the target business field; When the data transfer party is a data consumption party, a determination module, configured to parse the business attribute information of the data consumption party, and screen the target business scenario of the data consumption party from the set of business scenarios in the target business field according to the business attribute information; In the event database, determine the business events included in the target business scenario and the event types corresponding to the business events; A creation module, configured to establish an event model according to the target business field, the business events, and the corresponding event types, and instruct the data transfer party to perform data processing according to the event model.

6. The device according to claim 5, wherein The determination module is further configured to: Parse the event data processing logic of any business scenario included in the business attribute information of the data generation party, and obtain all business behaviors and the processing sequence of the business behaviors of the data generation party in any business scenario; For each business behavior, determine the behavior subject and the behavior command, and obtain the behavior attribute information of each business behavior; According to the preset aggregation rule and sub-domain division rule, perform aggregation and sub-domain division on the behavior attribute information of the business behaviors, and determine the association relationship between each business behavior included in each aggregation sub-domain.

7. The device according to claim 5, characterized in that The apparatus further includes: A mapping module, configured to establish a mapping relationship between each level of the event model and the event database based on the logical relationship between each business event included in the event model; store the event model to the target level of the event database.

8. The device according to claim 5, characterized in that, The determination module is further configured to parse the business behaviors and the processing sequence of the business behaviors included in the target business scenario; according to the business behaviors and the processing sequence of the business behaviors, determine the business events corresponding to the business behaviors and the event types corresponding to the business events in the hierarchical directory corresponding to the target business field of the event database.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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