Business data processing method, electronic equipment and storage medium

Abstract

The invention discloses a business data processing method, electronic equipment and a storage medium. The method comprises the following steps: acquiring a gateway log of a microservice gateway; event activity information is determined based on the gateway log, the event activity information comprises a plurality of events and event attribute information of the plurality of events, the event attribute information comprises service attributes, and the service attributes are used for representing attributes depended by the same event to execute service logic or attributes depended by interaction between different events; and generating process case information based on the event activity information, the process case information being used for determining a target event set, the target event set being obtained by screening a plurality of events, and the target event set cooperating to complete the target business process. The technical problem that business process cases are difficult to identify due to the fact that logs in a civil aviation passenger service system lack clear business process starting and ending marks is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and in particular to a business data processing method, electronic device, and storage medium. Background Art

[0002] As a highly interconnected industry, the civil aviation industry involves many participants, including passengers, agents, airlines and airports. The interaction between these participants forms complex and diverse business scenarios. As an important service provider in the industry, China Civil Aviation Information Network Co., Ltd. (hereinafter referred to as Air China) provides civil aviation passenger service systems covering domestic and foreign markets, providing services to more than 40 domestic airlines and more than 400 airlines worldwide. It also provides comprehensive system services to more than 200 domestic airports, more than 80 overseas airports and 6,000 agencies.

[0003] The civil aviation passenger service system not only covers the entire process of ticket sales and services, but also supports a variety of complex civil aviation passenger business scenarios to meet the diverse needs of passengers. These business scenarios are huge in number, involve cross-enterprise characteristics, affect all aspects of the upstream and downstream, involve both internal processes and interactions with external parties, and place higher requirements on the system.

[0004] Although traditional business process management (BPM) methods introduce business process management systems to sort out and optimize processes, they face problems such as long implementation cycles and frequent scenario updates when dealing with complex businesses in the civil aviation industry, which leads to a gradual increase in the gap between actual business and process models, thus affecting the accuracy and efficiency of the business. In recent years, process mining has received widespread attention as an emerging technology. It automatically discovers and builds business process models by analyzing event data in information systems. However, in actual enterprise environments, especially in civil aviation passenger service systems, it is difficult to obtain complete event logs due to the complexity of log data. These logs usually span multiple software, applications, and even enterprise boundaries, resulting in a lack of necessary case information in user access records, making it difficult to directly use them for process mining.

[0005] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0006] The embodiments of the present invention provide a business data processing method, an electronic device, and a storage medium to at least solve the technical problem of difficulty in identifying business process cases due to the lack of clear business process start and end marks in the log of the civil aviation passenger service system.

[0007] According to one aspect of an embodiment of the present invention, a business data processing method is provided, comprising: obtaining a gateway log of a microservice gateway; determining event activity information based on the gateway log, wherein the event activity information includes multiple events and event attribute information of the multiple events, wherein the event attribute information includes business attributes, and the business attributes are used to characterize the attributes on which the same event depends for executing business logic or the attributes on which interactions between different events depend; generating process case information based on the event activity information, wherein the process case information is used to determine a target event set, wherein the target event set is screened from multiple events, and the target event set collaborates to complete a target business process.

[0008] Further, event activity information is determined based on the gateway log: multiple events are determined based on the gateway log; message information of the multiple events is determined based on the gateway log, wherein the message information includes at least one of the following: request message, response message; business attributes of the multiple events are determined based on the message information to obtain event attribute information; multiple events and event attribute information are determined to be event activity information.

[0009] Furthermore, the event attribute information also includes read-write attributes, which include read attributes and write attributes. The read-write attributes are used to determine whether the execution operation of the event is a read operation or a write operation. Process case information is generated based on the event activity information, including: traversing the first event set to determine the second event set, the first event set being the set of all events in the event activity information, and the read-write attributes of multiple events in the second event set are all write attributes; based on the events in the second event set, traversing the first event set to determine the third event set, wherein the third event set includes multiple associated events, and the business attributes of the associated events are the same as the business attributes of the events in the second event set; and determining the third event set as process case information.

[0010] Furthermore, based on the events in the second event set, the first event set is traversed to determine the third event set, including: establishing an event activity list based on the first event set; searching for related events in the event activity list according to the sliding path using a sliding window; and determining that the searched related events are the third event set.

[0011] Furthermore, the event attribute information includes a time attribute, and the time attribute includes a timestamp of the event. Determining the third event set as process case information includes: obtaining a time filtering rule, wherein the time filtering rule is used to determine the events in the third event set whose timestamp intervals with the events in the second event set are within a preset time period; filtering the third event set based on the time filtering rule to obtain the process case information.

[0012] Furthermore, before determining the service attributes of the plurality of events based on the message information, the service data processing method includes: normalizing the time format in the message information.

[0013] Further, determining a plurality of events based on the gateway log includes: performing data extraction processing on the gateway log to obtain a plurality of events.

[0014] According to another aspect of an embodiment of the present invention, an electronic device is provided, including: a memory storing an executable program; and a processor for running the program, wherein the business data processing method in each embodiment of the present invention is executed when the program is running.

[0015] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the business data processing method in each embodiment of the present invention.

[0016] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the business data processing method in each embodiment of the present invention is implemented.

[0017] In the embodiment of the present invention, the method of analyzing the microservice gateway log is adopted to extract and standardize the business attributes in the event activity information, so as to achieve the purpose of automatically identifying and generating civil aviation business process case information, thereby realizing the accurate screening of the target event set from the massive events to collaboratively complete the specific business process, greatly improving the technical effect of the efficiency and accuracy of business process identification and analysis, and further solving the technical problem of difficulty in identifying business process cases due to the lack of clear business process start and end marks in the logs of the civil aviation passenger service system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of a business data processing method according to one embodiment of the present invention;

[0020] Figure 2 is a flow chart of a business data processing method according to one embodiment of the present invention;

[0021] Figure 3 is a schematic diagram of a PDC service process according to an embodiment of the present invention;

[0022] Figure 4 is a structural block diagram of a control device of a business data processing method according to one embodiment of the present invention;

[0023] Figure 5 It is a flowchart of a business data processing method according to another embodiment of the present invention. DETAILED DESCRIPTION

[0024] 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.

[0025] 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.

[0026] According to an embodiment of the present invention, a method embodiment of a business data processing method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0027] Figure 1 is a flow chart of a method for processing business data according to one embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0028] Step S10, obtaining the gateway log of the microservice gateway;

[0029] Optionally, obtaining the gateway log of the microservice gateway usually involves the following steps:

[0030] Log collection: As the unified entry point for all microservice requests and responses, the microservice gateway records detailed information of each service call by configuring the log framework or using the built-in logging function, including but not limited to timestamp, user ID, microservice name, detailed content of HTTP requests and responses, business-critical attributes, etc.

[0031] Log transmission: Log information needs to be transmitted from the gateway to a centralized log management system or storage system in real time or periodically. This can be achieved through the integration of log transmission tools or cloud services to ensure reliable storage and centralized management of log data.

[0032] Log parsing and standardization: The collected raw log data may have different formats. Log parsing tools are needed to parse the logs and convert unstructured logs into standardized structured data, such as JSON format. In this step, parsing rules need to be defined, key business attributes need to be extracted, synonym disambiguation needs to be performed, and data format needs to be unified for subsequent event case identification.

[0033] Log storage and management: The parsed log data will be stored in a log management system or a dedicated log database to provide a data basis for subsequent data analysis and process mining. Log storage needs to consider data persistence, query efficiency, and security.

[0034] Step S12, determining event activity information based on the gateway log, the event activity information including multiple events and event attribute information of the multiple events, the event attribute information including business attributes, the business attributes are used to characterize the attributes on which the same event execution business logic depends or the attributes on which the interaction between different events depends;

[0035] Event activity information is a key data structure for tracking and understanding business processes in the civil aviation microservice gateway. It contains a series of events that occurred over a period of time and their respective attribute information. Each event has its own specific event attribute information, which includes but is not limited to timestamp, event ID, microservice name, event type (read or write), and key business attributes. Business attributes are the core components of event attribute information. They are directly related to business logic and data and are used to characterize key information involved in business processes.

[0036] like Figure 2 As shown, the preprocessing steps for determining event activity information based on gateway logs are as follows:

[0037] Data extraction: Extract event information from the gateway log, including basic attributes such as timestamp, event ID, microservice name, and business attributes carried in request and response messages.

[0038] Normalization: Standardize and unify the format of the extracted business attributes to ensure the consistency of the same business attributes in different microservice messages, such as the naming differences of flight numbers and the unified format of date and time.

[0039] Identify key business attributes: Attributes that are essential for the execution of business processes are key business attributes. Information entropy is a statistical indicator that measures the uncertainty of attribute information. When determining key business attributes, the importance of each attribute to the business process can be evaluated by calculating the information entropy of each attribute. The higher the attribute information entropy, it usually means that the attribute varies more in different events, the more significant the impact on the business process, and it is more likely to be a key business attribute. In addition to information entropy calculation, the knowledge and experience of business experts can also be introduced to set weights for each attribute. The weight reflects the contribution of the attribute to the business process, and high-weighted attributes should be given higher priority in case identification. Weight setting can be based on methods such as expert review, historical data analysis, or AI model prediction.

[0040] Synonym disambiguation: handles the diversity of business attribute names and normalizes attributes with the same business meaning but different names through expert review or AI-assisted scoring.

[0041] Through the above preprocessing process, the original, disorganized gateway log data can be converted into a structured, standardized event set to facilitate faster determination of event activity information.

[0042] In step S12, the above-mentioned business attributes are used to characterize the attributes that the business logic of the same event execution depends on, that is, within a single business event, it is necessary to rely on specific business attributes to ensure the correctness and effectiveness of the operation. For example, in the "query flight inventory" event, information such as flight number, departure date, departure place and destination are required. This information constitutes the basic conditions for the query operation and ensures that the inventory data of the relevant flights can be accurately obtained from the database. This information (flight number, departure date, etc.) is the business attribute that the event depends on when it is executed. They ensure the correct execution of the business logic and avoid erroneous operations or invalid queries.

[0043] Specifically, business attributes are also used to establish connections between different events, and to achieve data transmission and business logic consistency by sharing certain specific attribute information. For example, when the "query flight inventory" event is followed by the "book flight seats" event, the interaction between them requires the use of information such as the flight number and departure date in the previous event ("query flight inventory") to ensure that the reserved seats match the queried inventory, avoiding invalid booking attempts. These attributes that are passed between different events and used for decision-making or operations are the business attributes that the interactions between events rely on. They act as a bridge between different business activities, allowing the entire business process to proceed smoothly and for various microservices to collaborate based on a common data context.

[0044] In this way, the business logic of each event can be analyzed more carefully and key business operation points can be identified, which is helpful for optimizing the calling paths between microservices, reducing unnecessary service calls and improving efficiency.

[0045] Step S14, generating process case information based on the event activity information, wherein the process case information is used to determine a target event set, the target event set is obtained by screening multiple events, and the target event set collaborates to complete the target business process.

[0046] In step S14, process case information is generated based on event activity information, aiming to identify and construct a complete business process from a large amount of event records. The target event set is a set of specific events obtained by screening and analyzing multiple events, which together constitute a PDC business process case, that is, a complete target business process.

[0047] Through the above steps S10 to S14, in an embodiment of the present invention, the method of analyzing the microservice gateway log is adopted to extract and standardize the business attributes in the event activity information, so as to achieve the purpose of automatically identifying and generating civil aviation business process case information, thereby realizing the accurate screening of the target event set from the massive events to collaboratively complete the specific business process, greatly improving the technical effect of the efficiency and accuracy of business process identification and analysis, and further solving the technical problem of difficulty in identifying business process cases due to the lack of clear business process start and end marks in the logs of the civil aviation passenger service system.

[0048] As an optional implementation, in step S12, determining event activity information based on the gateway log includes:

[0049] Step S121, determining multiple events based on the gateway log;

[0050] In the microservice architecture of civil aviation business, each microservice call or operation will leave a record in the gateway log, including the call timestamp, operation type (read / write), service name, event ID, and operator or user identity information. Assuming that the log records the basic information shown in Table 1, each line of the log corresponds to an event, that is, 4 events are determined from the gateway log: event ID1, passenger query flight details; event ID2, passenger purchase prepaid baggage; event ID3, passenger process payment; event ID4, confirm the purchase result of prepaid baggage.

[0051] Table 1: Basic log information.

[0052]

[0053] Step S122, determining message information of multiple events based on the gateway log, wherein the message information includes at least one of the following: a request message and a response message;

[0054] Specifically, detailed request and response information is extracted from the message of each event. This includes request messages and response messages. In the microservice architecture, when a client or upstream service sends a request to a downstream service, it carries a series of business parameters and operation instructions. These parameters and instructions constitute the request message, which is used to start or trigger the business logic of the downstream service. When the downstream service processes the request of the upstream service, it returns a response message. The response message contains the result, status, and possible error information of the service processing, which is used to inform the upstream service whether the operation is successful and its specific results. Typically, log entries will include the "request" and "response" keywords, or the "REQ" and "RES" fields to distinguish between request messages and response messages.

[0055] Specifically, for the four events extracted in step S121, their message information is further analyzed: the request message of event ID1 contains flight number = 5103, departure date = 2024-08-01, departure place = PVG, destination = AMS; the response message of event ID2 confirms that the baggage purchase is successful, including the number of baggage = 2, baggage type = standard, and purchase status = success; the request message of event ID3 involves payment amount = 800, payment method = credit card, and the response message confirms that the payment is successful; the response message of event ID4 again confirms that the purchase status of the prepaid baggage = success, and passenger ID = 123456. These message information describes the specific business operations and results of each event in more detail.

[0056] Step S123, determining the service attributes of multiple events based on the message information to obtain event attribute information;

[0057] Specifically, attributes directly related to the business process are extracted from the message information, which are called business attributes. For example, flight number, departure date, fare, passenger ID, seat number, etc. From the message information of step S122, we can determine the following business attributes: flight number: 5103; departure date: 2024-08-01; departure point: PVG; destination: AMS; passenger ID: 123456; number of luggage: 2; luggage type: standard; purchase status: successful; payment amount: 800; payment method: credit card. These business attributes together constitute the event attribute information.

[0058] Step S124: determining that the multiple events and event attribute information are event activity information.

[0059] Specifically, the multiple events determined in step S121 and the detailed event attribute information parsed in step S123 are combined together to form event activity information. This is usually a table (as shown in Table 2) in which each event is associated with its timestamp, operation type, service name, operator information and business attributes.

[0060] Table 2: Event activity information.

[0061]

[0062]

[0063] Through the above steps, we have successfully extracted event activity information from the gateway log, which provides basic data for subsequent process case identification and business process optimization.

[0064] It needs to be further explained that if Figure 3As shown in the figure, it is a schematic diagram of a complete PDC business process. The overall business processing process adopts three steps: data preparation, process execution, and result inspection. Then, small business processes form larger business processes and finally achieve business goals. Therefore, a business process that includes at least three stages of plan-execution-check is defined as an atomic process, referred to as a PDC business process. Each PDC business process needs to prepare data for the Plan plan first. The core of the process is the Do execution, and the Check must be performed after the execution. In the PDC business process, the read and write types of business event activities are the focus. In the data preparation stage, there are read-type event activities, while in the execution stage, there are write-type event activities. The final inspection stage is also a read-type event activity. The write-type event activity is the core of the entire business process. There are also some variant forms in the PDC business process. For example, the read activity can be repeated multiple times. In addition, in order to provide more detailed data, the plan and inspection stages may be composed of multiple different read activities, and the execution stage may also be a combination of multiple write activities. In a PDC business process, each event activity revolves around the same business key attribute, which can be an order number, flight number, passenger number, etc. A more complex business process is composed of several sub-processes, each of which is organized in the pattern of <read activity, write activity, read activity>.

[0065] As an optional implementation, the event attribute information further includes read-write attributes, which include read attributes and write attributes. The read-write attributes are used to determine whether the execution operation of the event is a read operation or a write operation. In step S14, process case information is generated based on the event activity information, including:

[0066] Step S141, traversing the first event set to determine the second event set, the first event set being a set of all events in the event activity information, and the read and write attributes of the multiple events in the second event set are all write attributes;

[0067] Specifically, the first event set is a set of all events in the event activity information, that is, it includes all events extracted from the gateway log. In step S141, the algorithm will traverse this event set and filter out events with write attributes, which usually represent key operations (DO execution) in the PDC business process. The screening results will constitute the second event set, that is, the set of all events with write attributes.

[0068] Step S142, based on the events in the second event set, traverse the first event set to determine a third event set, wherein the third event set includes a plurality of associated events, and the business attributes of the associated events are the same as the business attributes of the events in the second event set;

[0069] Specifically, based on the determined second event set, the algorithm is applied to traverse the first event set, and the sliding time window size is set to find read events with the same business attributes as the events in the second event set. These read events usually occur before or after write events and are used to prepare data or verify the results of write operations. They constitute the read operation part of the business process. The selected associated read events will form a third event set together with the write events in the second event set, that is, a set of all read and write events with the same business attributes as the write events.

[0070] Step S143: determine that the third event set is process case information.

[0071] Specifically, the third set of events constitutes a complete business process case. In this way, we can identify the various stages of the business process, such as the start, intermediate operations, and end verification.

[0072] By distinguishing read and write attributes, we can more accurately identify key operations in business processes, which has a significant effect on optimizing database access strategies, reducing data redundancy, and improving system response speed. Through the above steps, we can not only identify complete business process cases, but also understand the logical relationship and time sequence between events in the cases, providing valuable information for subsequent process mining and business optimization.

[0073] As an optional implementation, in step S142, based on the events in the second event set, the first event set is traversed to determine the third event set, including:

[0074] Step S1421, establishing an event activity list based on the first event set;

[0075] Specifically, all event information extracted from the gateway log, i.e., the first event set, is further organized into an event activity list. This list will be arranged in chronological order of events, including event ID, microservice name, timestamp, type (read or write), business attributes, etc. By constructing an event activity list, we can more conveniently traverse and search events. As shown in Table 3, the event activity list established based on the first event set shows that there are 7 events in total, of which e2, e4, and e6 events are write events, which together constitute the second event set.

[0076] Table 3: List of event activities.

[0077]

[0078]

[0079] Step S1422, using the sliding window to search for related events in the event activity list according to the sliding path;

[0080] Specifically, a sliding window technique is used to search the event activity list for read operation events related to write operations in the second event set (all events with write attributes). The sliding window size can be adjusted according to business characteristics and event frequency, for example, set to 10 seconds, 60 seconds or longer to ensure that read operations associated with write operations can be found within a reasonable range, and the sliding path is usually performed in chronological order.

[0081] Specifically, taking write event e2 (flight number 5103) as an example, we choose a sliding window size of 30 seconds, which means that we will search for read events within 30 seconds before and after the occurrence of write event e2 to determine the read events related to e2. The sliding window first starts from 30 seconds before e2, that is, from event e1, and then moves backward until it includes e2 and e5. The events in the sliding window are: e1, e2, e4 (ignore. This event is a write event), e5, and events e1 and e5 are determined to be associated events of event e2. For write event e4, the sliding search path also determines the associated read events e1 and e5; and for write event e6 (flight number = 5159), the sliding window determines the associated read event e7.

[0082] Step S1423: determine that the searched associated event is a third event set.

[0083] Specifically, all read events related to write events searched by the sliding window are determined as the third event set. That is, in this embodiment, events e1, e5, and e7 together constitute the third event set. The third event set is process case information, which is used to complete the target business process (i.e., a complete PDC business process), and outputs a standard event activity file in XES format for the PDC business process.

[0084] The XES standard uses a three-level structure of Log, Trace, and Event to represent log data, and each layer of the structure has its specific function. Log: This is the highest level of the XES log structure, representing the entire log file. It can contain multiple traces, that is, a set of specific paths in the business process. Log is used to encapsulate all metadata related to the log, such as the creation time of the log, the description of the log, etc. Trace: Located below the Log level, each Trace represents a business case or a complete business process path. It can be composed of multiple Events, recording all events of a specific process. For example, the entire process of a passenger from querying flights, booking seats to checking in can be regarded as a Trace. Event: This is the lowest level in the XES structure, representing a specific event in the log, such as the call of a microservice, the read and write operations of data, etc. Each Event contains a set of attributes.

[0085] This structured design of the XES standard is very suitable for describing and analyzing business processes under the microservice architecture, especially when it is necessary to identify a specific business process from the event sequences of multiple different work numbers. In the business process case identification of the civil aviation microservice network management, the log will contain the event information of all work numbers, and through the case identification algorithm, the event sequences belonging to the same business process can be combined into a trace, even if these events are executed by different work numbers. Finally, all identified traces are converted into log objects in the XES format to form an XES file, which can accurately represent a specific business process case.

[0086] Through the above steps, we can not only identify read events that are closely related to write events, but also build a complete PDC business process case, which is helpful for subsequent business process analysis and optimization. Each case represents a business process case around a specific flight number, and records the sequence of read and write operations in the case and their time sequence in detail. This method based on sliding windows and associated event search can effectively handle complex business scenarios across microservices and improve the accuracy and efficiency of case identification.

[0087] As an optional implementation manner, the event attribute information includes a time attribute, the time attribute includes a timestamp of the event, and determining that the third event set is process case information includes:

[0088] Obtaining a time screening rule, wherein the time screening rule is used to determine events in the third event set whose timestamp intervals with events in the second event set are within a preset time period;

[0089] Specifically, the time screening rules usually include a preset time period △t, which is used to define the time interval between the read event and the write event. This preset time period can be adjusted according to the business characteristics and system performance. For example, in the civil aviation business scenario, considering the consistency of user operations and system response time, the preset time period may be set to 30 seconds to 5 minutes. The setting of the preset time period is intended to ensure the logical correlation between read and write events and avoid mistaking unrelated events for part of the same business process case.

[0090] The third event set is screened based on the time screening rule to obtain process case information.

[0091] Specifically, for each write event, we search for read events within the range of △t before and after its timestamp. Only those read events whose timestamp intervals fall within the preset time period will be retained and become part of the process case information. In this way, we can ensure that the selected third event set not only has the same business attributes, but is also closely related in time.

[0092] Through the above steps, the third event set is filtered based on the time filtering rules, so that we can exclude those read operations that are irrelevant in time or have too long time intervals. We can ensure that the process case information is not only consistent in business attributes, but also coherent in time sequence, avoiding interference from irrelevant events and improving the accuracy and effectiveness of process case information identification.

[0093] As an optional implementation, before determining the service attributes of multiple events based on the message information, the service data processing method includes: normalizing the time format in the message information.

[0094] Specifically, normalizing the time format in the message information is an important preprocessing step, which ensures that the timestamps of all events are in a consistent format, which facilitates subsequent operations such as event sorting, time interval calculation, and process case identification. The purpose of time format normalization is to eliminate format differences caused by different microservices, systems, or logging methods, and convert all timestamps into a unified format that is easy to compare and operate.

[0095] Normalizing the time format in the message information includes the following steps:

[0096] Time format recognition: First, the algorithm needs to be able to recognize different formats of timestamps in message information. Common formats may include "YYYY-MM-DD HH:MM:SS", "YYYYMMDDHHMMSS", "HH:MM:SS YYYY-MM-DD", etc.

[0097] Parse the original time format: For each recognized time format, use the corresponding parsing function to convert the time string into a time object or timestamp format.

[0098] Convert to a unified format: Convert the parsed time object or timestamp to a unified format, such as "YYYY-MM-DD HH:MM:SS". The choice of a unified format should be based on the needs of subsequent processing to ensure accurate time comparison and calculation.

[0099] Format verification and exception handling: During the conversion process, the format and range of the time data need to be verified to ensure the validity and consistency of all timestamps. For time formats that cannot be parsed or abnormal timestamps, there should be an appropriate mechanism to handle them, such as logging, ignoring, or setting default values.

[0100] Through the above steps, the event format is normalized, which greatly improves the efficiency and accuracy of data processing and facilitates the time series analysis of events in subsequent steps.

[0101] As an optional implementation, in step S121, determining multiple events based on the gateway log includes: performing data extraction processing on the gateway log to obtain multiple events.

[0102] Specifically, first, extract the records containing microservice calls from the gateway log. These records usually contain the call time, caller information, the name of the called service, the event ID, and detailed request and response messages. Convert each such record into an event, where the structure of the event should include: timestamp, work number, service name, event ID, event type (read or write), and detailed information of the request / response message. Use a parser or other corresponding tools to parse the business attribute information contained in the request / response message and convert it into a key-value pair form (attribute: data value). Each business attribute will correspond to a key, and its specific value will be used as the value. For example, business attributes such as flight number, departure date, and cabin class will be parsed and stored as a key-value pair structure such as {"fl ightNumber":"5103","departureDate":"2024-08-01","classId":"L"}. After the message information is parsed, it is necessary to distinguish whether the value in the key-value pair is a categorical variable or a numerical variable. Categorical variables are attributes with finite value ranges, such as airline codes, cabin classes, airport codes, etc. The values ​​of these attributes vary within a certain range and can be simply enumerated. Numerical variables include e-ticket numbers, order numbers, seat numbers, etc. These usually have a large value range and may belong to an infinite set, which is not suitable for simple enumeration, but can be sorted to analyze their distribution or change trends.

[0103] Through the above steps, the gateway log is processed for data extraction and the original log data is converted into structured event information, which reduces the time and complexity of data preprocessing, facilitates subsequent analysis and mining, and ensures the accuracy and efficiency of the entire identification process.

[0104] Figure 5 is a flowchart of another method for processing business data according to one embodiment of the present invention. Figure 5 As shown, the method comprises the following steps:

[0105] Step S501, obtaining the gateway log of the microservice gateway;

[0106] Step S502, determining multiple events based on the gateway log;

[0107] Step S503, determining message information of multiple events based on the gateway log, wherein the message information includes at least one of the following: a request message and a response message;

[0108] Step S504, determining the service attributes of multiple events based on the message information, and obtaining event attribute information;

[0109] Step S505, determining that the multiple events and event attribute information are event activity information;

[0110] Step S506, traversing the first event set to determine the second event set, the first event set being a set of all events in the event activity information, and the read and write attributes of the multiple events in the second event set are all write attributes;

[0111] Step S507, based on the events in the second event set, traverse the first event set to determine a third event set, wherein the third event set includes a plurality of associated events, and the business attributes of the associated events are the same as the business attributes of the events in the second event set;

[0112] Step S508, determining that the third event set is process case information;

[0113] Step S509, establishing an event activity list based on the first event set;

[0114] Step S510, using the sliding window to search for related events in the event activity list according to the sliding path;

[0115] Step S511, determining that the searched associated event is a third event set;

[0116] Step S512, obtaining a time screening rule, wherein the time screening rule is used to determine the events in the third event set whose timestamp intervals with the events in the second event set are within a preset time period;

[0117] Step S513, filtering the third event set based on the time filtering rule to obtain process case information;

[0118] Step S514, normalizing the time format in the message information;

[0119] Step S515: extract data from the gateway log to obtain multiple events.

[0120] Through the above steps S501 to S515, in an embodiment of the present invention, the method of analyzing the microservice gateway log is adopted to extract and standardize the business attributes in the event activity information, so as to achieve the purpose of automatically identifying and generating civil aviation business process case information, thereby realizing the accurate screening of the target event set from the massive events to collaboratively complete the specific business process, greatly improving the technical effect of the efficiency and accuracy of business process identification and analysis, and further solving the technical problem of difficulty in identifying business process cases due to the lack of clear business process start and end marks in the logs of the civil aviation passenger service system.

[0121] According to an embodiment of the present invention, a device embodiment of a business data processing method is provided. It should be noted that the device can be used to execute the above-mentioned business data processing method.

[0122] Figure 4 FIG. 1 is a structural block diagram of a control device of a business data processing method according to one embodiment of the present invention. Figure 4 As shown, the device comprises:

[0123] Acquisition module 401, used to obtain the gateway log of the microservice gateway;

[0124] Determination module 402, used to determine event activity information based on the gateway log, the event activity information includes multiple events and event attribute information of the multiple events, the event attribute information includes business attributes, and the business attributes are used to characterize the attributes that the same event depends on to execute the business logic or the attributes that different events depend on to interact;

[0125] The control module 403 is used to generate process case information based on the event activity information, wherein the process case information is used to determine a target event set, the target event set is obtained by screening multiple events, and the target event set collaborates to complete the target business process.

[0126] Optionally, the determination module 402 is also used to determine multiple events based on the gateway log; determine the message information of the multiple events based on the gateway log, wherein the message information includes at least one of the following: request message, response message; determine the business attributes of the multiple events based on the message information to obtain event attribute information; determine the multiple events and event attribute information as event activity information.

[0127] Optionally, the event attribute information also includes read-write attributes, which include read attributes and write attributes. The read-write attributes are used to determine whether the execution operation of the event is a read operation or a write operation. The control module 403 is also used to generate process case information based on the event activity information, including: traversing the first event set to determine the second event set, the first event set being a set of all events in the event activity information, and the read-write attributes of multiple events in the second event set are all write attributes; based on the events in the second event set, traversing the first event set to determine the third event set, wherein the third event set includes multiple associated events, and the business attributes of the associated events are the same as the business attributes of the events in the second event set; determining the third event set as process case information.

[0128] Furthermore, the control module 403 is further configured to establish an event activity list based on the first event set; search for associated events in the event activity list according to the sliding path using a sliding window; and determine that the searched associated events are a third event set.

[0129] Furthermore, the event attribute information includes a time attribute, and the time attribute includes a timestamp of the event. The third event set is determined to be process case information. The determination module 402 is also used to obtain a time filtering rule, wherein the time filtering rule is used to determine the events in the third event set whose timestamp intervals with the events in the second event set are within a preset time period; the third event set is filtered based on the time filtering rule to obtain the process case information.

[0130] Furthermore, the acquisition module 401 is also used to normalize the time format in the message information.

[0131] Furthermore, the acquisition module 401 is also used to perform data extraction processing on the gateway log to obtain multiple events.

[0132] It should be noted that the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0133] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0134] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0135] Step S10, obtaining the gateway log of the microservice gateway;

[0136] Step S12, determining event activity information based on the gateway log, the event activity information including multiple events and event attribute information of the multiple events, the event attribute information including business attributes, the business attributes are used to characterize the attributes on which the same event execution business logic depends or the attributes on which the interaction between different events depends;

[0137] Step S14, generating process case information based on the event activity information, wherein the process case information is used to determine a target event set, the target event set is obtained by screening multiple events, and the target event set collaborates to complete the target business process.

[0138] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0139] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0140] Step S10, obtaining the gateway log of the microservice gateway;

[0141] Step S12, determining event activity information based on the gateway log, the event activity information including multiple events and event attribute information of the multiple events, the event attribute information including business attributes, the business attributes are used to characterize the attributes on which the same event execution business logic depends or the attributes on which the interaction between different events depends;

[0142] Step S14, generating process case information based on the event activity information, wherein the process case information is used to determine a target event set, the target event set is obtained by screening multiple events, and the target event set collaborates to complete the target business process.

[0143] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0144] Optionally, in this embodiment, the computer program product may be configured as a computer program for executing the following steps:

[0145] Step S10, obtaining the gateway log of the microservice gateway;

[0146] Step S12, determining event activity information based on the gateway log, the event activity information including multiple events and event attribute information of the multiple events, the event attribute information including business attributes, the business attributes are used to characterize the attributes on which the same event execution business logic depends or the attributes on which the interaction between different events depends;

[0147] Step S14, generating process case information based on the event activity information, wherein the process case information is used to determine a target event set, the target event set is obtained by screening multiple events, and the target event set collaborates to complete the target business process.

[0148] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0149] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0150] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0151] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0152] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0153] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A business data processing method, characterized in that: include: Get the gateway log of the microservice gateway; Determine event activity information based on the gateway log, the event activity information includes multiple events and event attribute information of the multiple events, the event attribute information includes business attributes, and the business attributes are used to characterize the attributes that the same event depends on to execute business logic or the attributes that different events depend on to interact; Process case information is generated based on the event activity information, wherein the process case information is used to determine a target event set, the target event set is obtained by screening the multiple events, and the target event set collaborates to complete a target business process.

2. The business data processing method according to claim 1, characterized in that: Determine event activity information based on the gateway log: determining the plurality of events based on the gateway log; Determining message information of the multiple events based on the gateway log, wherein the message information includes at least one of the following: a request message, a response message; Determine the service attributes of the multiple events based on the message information, and obtain the event attribute information; The multiple events and the event attribute information are determined as the event activity information.

3. The business data processing method according to claim 1, characterized in that: The event attribute information also includes a read-write attribute, and the read-write attribute includes a read attribute and a write attribute, and the read-write attribute is used to determine whether the execution operation of the event is a read operation or a write operation. The process case information is generated based on the event activity information, including: Traversing the first event set to determine a second event set, wherein the first event set is a set of all events in the event activity information, and the read and write attributes of multiple events in the second event set are all write attributes; Based on the events in the second event set, traverse the first event set to determine a third event set, wherein the third event set includes a plurality of associated events, and the business attributes of the associated events are the same as the business attributes of the events in the second event set; The third event set is determined to be the process case information.

4. The business data processing method according to claim 3, characterized in that: Based on the events in the second event set, traversing the first event set to determine a third event set includes: Establishing an event activity list based on the first event set; Searching the associated event in the event activity list according to the sliding path using a sliding window; It is determined that the searched associated events are the third event set.

5. The business data processing method according to claim 3, characterized in that: The event attribute information includes a time attribute, and the time attribute includes a timestamp of the event. Determining that the third event set is the process case information includes: Acquire a time screening rule, wherein the time screening rule is used to determine the events in the third event set whose timestamp intervals with the events in the second event set are within a preset time period; The third event set is screened based on the time screening rule to obtain the process case information.

6. The business data processing method according to claim 2, characterized in that: Before determining the service attributes of the multiple events based on the message information, the service data processing method includes: The time format in the message information is normalized.

7. The business data processing method according to claim 2, characterized in that: Determining the plurality of events based on the gateway log includes: Data extraction processing is performed on the gateway log to obtain the multiple events.

8. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 7 when running.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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