Business data processing method and device, equipment and medium

Abstract

The invention relates to the technical field of data processing, in particular to a business data processing method and device, equipment and a medium, which are applied to a financial scene or a medical scene, and are used for obtaining business data of a plurality of business management systems corresponding to preset businesses and business process relationships and business process types corresponding to the preset businesses. And then classifying the business data based on the business process relationship and the business process type to obtain target business data, monitoring whether the target business data has production and consumption abnormity or not based on a preset monitoring rule, and if the target business data has the production and consumption abnormity, obtaining consumer information related to the abnormal target business data, the consumer information comprises the consumer configuration information and the consumer process identification information, so that the normal circulation of the business process is ensured, the influence of abnormity on the business is reduced, and the data processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a business data processing method, device, equipment and medium. Background Art

[0002] With the rapid expansion of financial or medical services, the amount of related data is also growing continuously. In order to simplify the system maintenance and management process, these business data must be effectively processed. However, during the processing, any failure in any link may cause the business process to be blocked, thus affecting the smooth progress of the business. Therefore, it is crucial to ensure that each link can process data smoothly, so as to ensure the smooth operation of the business process.

[0003] At present, the existing technology is to process data by introducing big data components (such as Kafka). However, these methods are prone to data blockage and component failures during data production, consumption and transmission due to the huge amount of data, which in turn hinders the development of business. Therefore, how to ensure that there are no failures in the data processing process to improve the efficiency of data processing is a technical problem that needs to be solved urgently. Summary of the invention

[0004] Based on this, it is necessary to address the above technical problems. The embodiments of the present invention provide a business data processing method, device, equipment and medium to solve the technical problem that the prior art cannot ensure that no failures occur during data processing, thereby resulting in low data processing efficiency.

[0005] A first aspect of an embodiment of the present application provides a business data processing method, the business data processing method comprising: Acquire business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to the preset businesses, wherein the business process relationships are association relationships between the business data from production to consumption; Classifying the business data based on the business process relationship and the business process type to obtain target business data; Based on preset monitoring rules, determine whether the target business data has production and consumption anomalies; If production and consumption anomalies occur in the target business data, consumer information related to the target business data with the anomaly is obtained, and data processing of the target business data is completed based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information.

[0006] A second aspect of an embodiment of the present application provides a service data processing device, the service data processing device comprising: An acquisition module, used to acquire business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to the preset businesses, wherein the business process relationship is an association relationship between the business data from production to consumption; A classification module, used to classify the business data based on the business process relationship and the business process type to obtain target business data; A judgment module, used to judge whether the target business data has production and consumption anomalies based on preset monitoring rules; A processing module is used to obtain consumer information related to the target business data with the abnormality if production and consumption abnormalities occur in the target business data, and complete data processing of the target business data based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information.

[0007] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the business data processing method as described in the first aspect when executing the computer program.

[0008] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the business data processing method as described in the first aspect is implemented.

[0009] In summary, the present invention provides a business data processing method, device, equipment and medium, which obtains business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to preset businesses, wherein the business process relationship is the association relationship between business data from production to consumption, classifies business data based on the business process relationship and the business process type, obtains target business data, and monitors whether production and consumption anomalies occur in the target business data based on preset monitoring rules. If production and consumption anomalies occur in the target business data, consumer information related to the target business data with the anomaly is obtained, and data processing of the target business data is completed based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information, thereby ensuring the normal flow of business processes, reducing the impact of anomalies on business, and improving data processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technical businesses in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0011] Figure 1 This is an application environment diagram of a business data processing method provided by an embodiment of the present invention; Figure 2 It is a flowchart of a business data processing method provided by an embodiment of the present invention; Figure 3 It is a structural diagram of a business data processing device provided by an embodiment of the present invention; Figure 4 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are 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 technical personnel in this field without creative work are within the scope of protection of the present invention.

[0013] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0014] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0015] As used in the present specification and the appended claims, the term “if” may be interpreted as “when” or “uponce” or “in response to determining”, depending on the context. Similarly, the phrases “if it is determined” or “if matched to [described condition or event]” may be interpreted as meaning “upon determination” or “in response to determination” or “uponce matched to [described condition or event]” or “in response to matching to [described condition or event]”, depending on the context.

[0016] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0017] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0018] It should be understood that the order of execution of the steps in the following embodiments does not imply a precedence of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0019] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0020] See also Figure 1 , is an application environment diagram of a business data processing method provided by an embodiment of the present invention. A business data processing method provided by an embodiment of the present invention can be applied in Figure 1 In the application environment, the client communicates with the server. The client includes but is not limited to PDA, desktop computer, notebook computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA) and other computer devices. The client here is replaced by a business management system. The server can be implemented by an independent server or a server cluster composed of multiple servers. The server can upload and download financial business data, such as loan information, deposit information, insurance information, etc., and then quickly and accurately process the financial business data through this solution.

[0021] See also Figure 2 , is a flow chart of a business data processing method provided by an embodiment of the present invention, such as Figure 2 As shown, the business data processing method can be implemented through the following steps.

[0022] S201: Acquire business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to the preset businesses, wherein the business process relationships are association relationships between the business data from production to consumption.

[0023] In step S201, the preset business includes pension insurance, auto insurance, accident insurance, life insurance or other types of business, etc.; the business process relationship refers to the interconnection and dependency between a series of business activities or processes, that is, the association between business data from production to consumption, for example, the relationship between the production process and the sales process of drugs, after the sales start, it will depend on the inventory provided by the production; the business process type is a standard for classifying business activities or processes, for example, in a medical scenario, the business process type can include patient registration, diagnosis, treatment, payment, hospitalization and other links. From the perspective of business implementation, each different business in this application will include different business processes, and different business processes correspond to different business management systems. For example, the business process corresponding to the pension insurance is: Kafka production->Flume consumption, that is, the business process corresponding to the pension insurance includes two stages, and the business management system corresponding to the business process includes a production management system and a consumption management system. When the preset business is carried out, each business management system will generate business data, such as the business data corresponding to the insurance management system is the insured amount, then the insured amount is 10000, which is the business data corresponding to the insurance management system. In the medical field, the business data may also be gene sequencing data, physical examination data, electronic medical records, etc. This application does not impose any limitations on this.

[0024] In an embodiment of the invention, obtaining service data of multiple service management systems corresponding to preset services includes: Acquire monitoring data from at least one business management system and store the monitoring data in a target location; By preprocessing the monitoring data and the internal indicator data corresponding to the monitoring data, and using preset scripts to extract business data related to the business.

[0025] Specifically, a business management system is a system that stores various data. By obtaining monitoring data from at least one business management system, these monitoring data usually include system performance indicators, operating status, log information, etc., wherein the data reading method can be API call, log file parsing, database query, etc., and this application does not make any restrictions on this. Then, according to factors such as data volume, real-time requirements, cost budget, etc., select a suitable storage method to store the monitoring data to the target location. Common storage methods include hard disk storage, network attached storage (NAS), storage area network (SAN), cloud storage, and distributed storage systems. By preprocessing the monitoring data and the internal indicator data corresponding to the monitoring data, wherein the preprocessing method can be data cleaning, data integration, and data conversion, etc., this application does not make any restrictions on this.

[0026] Since the preset script is convenient for users to select different preset business types on the same management subsystem device, business data related to the business is extracted from the pre-processed monitoring data by using the preset script. Among them, the preset script includes a multi-dimensional acquisition script, such as a collection script that supports different dimensions such as time or business category. At the same time, a control for calling the preset script can also be provided on the preset display interface, that is, a channel for modifying the preset script at any time is provided to facilitate managers to modify the preset script according to business needs at any time. It should be noted that the preset display interface can be used to display business data. Specifically, multiple business data can be displayed in different forms, including different colors, different fonts or different lines, etc., and this application does not make any restrictions on this. Through the above steps, the monitoring data can be monitored and stored in real time, the operating status and performance bottlenecks of the business management system can be timely understood, and timely and accurate information support can be provided for decision-making. Through data preprocessing, redundant and invalid data can be removed to improve the accuracy and reliability of the data.

[0027] In an embodiment of the present application, by obtaining business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to preset businesses, it can help enterprises better understand the business status so that they can subsequently process business data quickly and accurately, thereby promoting the realization of business goals.

[0028] S202: Classify the business data based on the business process relationship and the business process type to obtain target business data.

[0029] In step S202, the target business data is obtained by classifying the business data according to the business process relationship and the business process type, which usually involves operations such as labeling and grouping of data. For example, for messages produced by Kafka, the system may classify them according to information such as the topic and partition of the message. For data consumed by Flume, the system may classify them according to indicators such as the type of consumption source and consumption rate. By classifying the business data, it is possible to locate which specific part of the data processing is blocked, so that data processing can be performed according to the established rules. For example, medical data is classified to determine indicators such as the number of visits, diagnostic accuracy, and treatment costs of different departments, so as to optimize the department layout, improve diagnostic accuracy, and reduce treatment costs.

[0030] In an embodiment of the invention, the business data is classified based on the business process relationship and the business process type to obtain target business data, including: Based on the business process relationship, the business data is initially classified to obtain initially classified business data; The initially classified business data is secondary classified based on the business process type and business attribute to obtain target business data.

[0031] Specifically, understand the relationship between different business processes and identify key business processes, which may include production, sales, customer service, etc., and draw a business process relationship diagram to more clearly see the interdependence and output between each process. Set the standard for initial classification based on the business process relationship. For example, you can classify according to the main process category to which the data belongs, such as "production data", "sales data", "customer feedback data", etc. In this way, you can give the business data a preliminary classification label to form the initial classification business data, and then set specific classification standards according to the business process type and business attributes. For example, "sales data" can be further subdivided into "online sales" and "offline sales", and marked according to the timeliness of sales data (such as real-time data, historical data). By using programs or manual marking, the initially classified business data is reclassified according to the new standards. After completing the secondary classification, more detailed target business data that meets business needs can be obtained. For example, patient visit data, diagnosis data, treatment data, and rehabilitation data are stored in different databases, and the data in each database is divided and classified according to the business process relationship. On the basis of the initial classification, the initially classified business data is further divided according to the business process type (such as outpatient, inpatient, emergency) and business attributes (such as patient attributes, disease attributes, treatment attributes) to obtain more accurate medical data. Through the above steps, the data of each category is ensured to be more orderly and available, which is helpful for further analysis and decision support, and improves the efficiency and accuracy of data query and processing.

[0032] In this embodiment, by classifying business data according to business process relationships and business process types, target business data is obtained so that the system can be more accurately helped to promptly discover and handle abnormal problems in data processing, thereby improving system stability and business processing efficiency.

[0033] S203: Based on preset monitoring rules, determine whether the target business data has production and consumption anomalies.

[0034] In step S203, according to business needs and scenarios, the target business data that needs to be monitored is clarified, such as production volume, consumption volume, inventory volume, equipment status, etc., and then according to historical data, industry standards or business logic, a reasonable threshold or range is set for each monitoring target, such as data exceeding the threshold, abnormal fluctuation, trend change, etc. Among them, the preset monitoring rule is an abnormal monitoring rule preset according to the target business data, which can be set according to the actual situation, and this application does not make any restrictions on this. Based on the preset monitoring rules, it is judged whether the target business data has production and consumption anomalies. If the target business data has production and consumption anomalies, step S204 is executed, that is, the consumer information related to the target business data with anomalies is obtained, and the data processing of the target business data is completed based on the consumer information and the preset consumption processing rules. If the target business data does not have production and consumption anomalies, the process ends, that is, the subsequent steps of the business data processing method will no longer be executed.

[0035] In an embodiment of the invention, judging whether the target business data has production and consumption anomalies based on preset monitoring rules includes: Obtaining data congestion amount of the target service data; Determining whether the data congestion amount is greater than a preset congestion threshold; If the data congestion amount is greater than the preset congestion threshold, determining whether the duration of the data congestion amount meets the preset time threshold; If the duration of the data congestion meets the preset time threshold, it is determined that production and consumption anomalies occur in the target business data.

[0036] Specifically, by obtaining the data congestion amount of the target business data, and then using the congestion threshold set for the user by the preset monitoring rules, it is determined whether the data congestion amount is greater than the preset congestion threshold. If the data congestion amount is greater than the preset congestion threshold, it is determined whether the duration of the data congestion amount meets the preset time threshold. If the duration of the data congestion amount meets the preset time threshold, it is determined that the target business data has production and consumption anomalies, that is, the consumption and production data congestion amount in the previous target business data is compared according to the congestion threshold specified by the monitoring user (data congestion: when data production increases and data consumption has problems or consumption is too slow, it will cause data congestion to increase). When the consumption and production data congestion amount reaches a certain threshold, it is determined that the duration of the data congestion amount Whether the requirement of lasting for a period of time is met, because the increase in data congestion in a short period of time may be due to the increase in users in a short period of time, resulting in an increase in production data. As the consumption time increases, the data congestion will also decrease, so it is necessary to judge whether the accumulation time meets the requirements. For example, if the system detects that the message processing delay time of the order creation link suddenly increases, while the processing time of the payment confirmation link does not change, then it may judge that there is a data processing anomaly in the order creation link, and then determine that the target business data has a production and consumption anomaly, then start to trigger the automatic processing mechanism of the subsequent steps, and perform a series of operations such as updating the configuration or restarting the big data components according to the subsequent functions until there is no data congestion in the data processing process. By monitoring the amount and time of data congestion, the system can respond quickly and identify potential production and consumption anomalies, improving the accuracy of anomaly detection, so that subsequent enterprises can take corresponding measures in a targeted and timely manner to avoid further expansion of abnormal conditions, thereby reducing possible losses.

[0037] In this embodiment, based on preset monitoring rules, abnormal patterns or behaviors that deviate from the normal state in the target business data can be quickly identified, so that production and consumption anomalies can be promptly resolved through subsequent corresponding data processing, reducing the risk of business interruption and improving the stability and reliability of the system.

[0038] S204: If production and consumption anomalies occur in the target business data, consumer information related to the target business data with the anomaly is obtained, and data processing of the target business data is completed based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information.

[0039] In step S204, consumer configuration information refers to the parameters and settings used to configure the consumer client or consumer process to ensure that it is normally connected and works in a specific data stream or message queue. Common configuration information includes: connection information, identity authentication, and consumption parameters; consumer process identification information is an identifier used to uniquely identify and manage consumer processes. This information is usually used to monitor, manage, and troubleshoot the status and behavior of consumers. Common process identification information includes: consumer group ID, consumer instance ID, and process status. When it is clear that the target business data has production and consumption anomalies, extract consumer information related to the target business data from the source of the abnormal data. In medical scenarios, consumer information may include the patient's name, age, gender, contact information, medical record number, medical records, etc. After extracting the consumer information, it needs to be verified to ensure the accuracy and completeness of the information. The preset consumption processing rules may include data cleaning rules, data conversion rules, data verification rules, etc. These rules are designed to ensure the accuracy, consistency and completeness of the data. Among them, the preset consumption processing rules are preset consumption processing rules based on production and consumption anomalies in the target business data. They can be set according to actual conditions. This application does not make any restrictions on this. Then, according to the consumer information and the preset consumption processing rules, the corresponding data processing operations are performed, thereby providing strong data support for enterprises and helping them make more accurate and efficient decisions.

[0040] In one embodiment of the invention, obtaining consumer information related to the target service data having an abnormality includes: Acquire the business service type of the target business data; According to the business service type, consumer information related to the target business data with an exception is obtained according to a specified message delivery queue.

[0041] Specifically, the target business data is identified to determine the business service type of the target business data. The business service type is a way to classify different service functions within an enterprise. For example, the business service type may be "clinical diagnosis and treatment service" or "drug supply service". Then, according to the business service type, a suitable messaging queue is selected, such as RabbitMQ, Kafka, ActiveMQ, etc., wherein the messaging queue is a channel or pipeline used to transmit messages in the system, and different business service types may have different messaging queues. After determining the messaging queue, the consumer information related to the abnormal target business data can be obtained from the messaging queue, which usually involves reading the message in the queue, parsing the message content, and extracting information related to the consumer. The consumer information may also include the consumer's identifier, name, address, contact information, etc., which is helpful for subsequent problem diagnosis, notification or remedial measures. Taking the drug inventory backlog as an example, the corresponding messaging queue is found according to the business service type of "drug supply service". When searching for consumers who receive inventory warning messages in the messaging queue, it may be found that the drug procurement system is still purchasing drugs according to the original plan, and then the consumer information related to the abnormality is found. By following the above steps, you can locate the problem more quickly, which helps reduce the time cost of problem diagnosis and improve the stability and availability of the system.

[0042] In one embodiment of the invention, completing data processing of the target business data based on the consumer information and the preset consumption processing rules includes: Determining a storage location of consumer log information according to the consumer configuration information; Based on the storage location, determining whether the consumer log information meets the consumption condition; If the consumer log information meets the consumption condition, determining the corresponding consumption instance based on the consumer process identification information; The consumed data content in the consumption instance is deleted to obtain a modified consumption instance, so that the modified consumption instance can complete data processing after restarting.

[0043] Specifically, by parsing the consumer configuration information, the storage location of the consumer log information is determined, and then according to the storage location of the consumer log information, the location is accessed to obtain the consumer log information. The consumption condition usually refers to the consumer status and data processing results recorded in the log information. Common consumption conditions include: successful processing: check whether there is a mark of successful processing in the log; error information: check whether there are records that cannot be consumed or abnormal; processing time: determine whether the processing time is within the expected range, etc., which can be set according to actual conditions, and this application does not make any restrictions on this. Then, according to the defined consumption conditions, the consumer log information is parsed to determine whether it meets the conditions. If the consumer log information meets the consumption conditions, the corresponding consumption instance is determined based on the consumer process identification information (such as consumer ID or instance ID). A mapping table of consumer instances can be maintained in the system for quick search. The consumption instance may contain the following information: Consumed data content: record the message or data that has been processed; consumption status: the status of the current consumption instance (such as being processed, completed, failed, etc.). After determining the consumption instance, perform a deletion operation to remove the consumed data content. This can be achieved in the following ways: direct deletion: deleting the consumed data records from the consumption instance; marking deletion: marking the consumed data as deleted, retaining the original data for subsequent audits, etc. This application does not impose any restrictions on this. After the deletion is completed, a corrected consumption instance is formed to ensure that its data status is up to date, and the corrected consumption instance is restarted, that is, according to the actual situation, the running consumption process is stopped, and the consumption instance is restarted through the system management tool or API, so that after the restart, the consumption instance should be able to process data from the latest state to ensure that all unprocessed data can be consumed. This application ensures that only valid data is processed by judging whether the log information meets the consumption conditions, reduces resource waste, promptly identifies and corrects erroneous data in the consumption instance, avoids duplicate consumption or data loss, improves the stability and reliability of the system, ensures the consistency and integrity of business data, and improves the continuity and accuracy of data processing.

[0044] In an embodiment of the invention, judging whether the consumer log information meets the consumption condition based on the storage location includes: Based on the storage location, determining whether the keywords in the consumer log information meet a preset keyword condition, wherein the preset keyword condition is represented by the presence of unconsumable keywords in the consumer log information; If the keyword in the consumer log information meets the preset keyword condition, it is determined that the consumer log information meets the consumption condition.

[0045] Specifically, the preset keyword condition is expressed as the existence of keywords in the consumer log information that cannot be consumed. For example, for consumers of the electronic medical record system, the keywords may include "cannot obtain medical records", "corrupted medical record data", "insufficient permissions to access medical records", etc.; for consumers of the medical imaging system, the keywords may include "image download failure", "cannot parse image data format", "image server connection interruption", etc. According to the consumer configuration information, the specific location where the consumer log information is stored is accessed and the consumer log information under the specified path is read. The consumer log information is traversed, and the keywords in each log record can be checked by string matching or regular expressions, and then according to the defined consumption conditions, it is determined whether the keywords in the consumer log information meet the preset keyword conditions. If the keywords in the consumer log information meet the preset keyword conditions, it is determined that the consumer log information meets the consumption conditions, that is, there is a situation that cannot be consumed. Through keyword monitoring, abnormal situations in consumer logs can be tracked in real time, which is convenient for timely response and targeted data processing, thereby ensuring the normal flow of business processes and not affecting the business.

[0046] In the embodiment of the present application, when production and consumption anomalies occur in the target business data, the source of the problem can be quickly located by obtaining consumer information related to the abnormal data, reducing the troubleshooting time. Data processing based on preset consumption processing rules can ensure the standardization and consistency of data processing, making the processing process faster and more efficient, which not only reduces the need for manual intervention, but also reduces business impact, ensures the consistency and integrity of business data, thereby ensuring that the efficiency and accuracy of data processing are improved.

[0047] In summary, the present invention provides a business data processing method, device, equipment and medium, which obtains business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to preset businesses, wherein the business process relationship is the association relationship between business data from production to consumption, classifies business data based on the business process relationship and the business process type, obtains target business data, and monitors whether production and consumption anomalies occur in the target business data based on preset monitoring rules. If production and consumption anomalies occur in the target business data, consumer information related to the target business data with the anomaly is obtained, and data processing of the target business data is completed based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information, thereby ensuring the normal flow of business processes, reducing the impact of anomalies on business, and improving data processing efficiency.

[0048] See also Figure 3 , Figure 3Schematic diagram of the structure of the service data processing device provided by the embodiment of the present invention. In this embodiment, the terminal includes various units for executing Figure 2 For details, please refer to the steps in the corresponding embodiment. Figure 2 as well as Figure 2 For the convenience of explanation, only the parts related to this embodiment are shown. Figure 3 The business data processing device 30 includes: an acquisition module 31, a classification module 32, a judgment module 33, and a processing module 34.

[0049] The acquisition module 31 is used to acquire the business data of multiple business management systems corresponding to the preset business, as well as the business process relationship and business process type corresponding to the preset business, wherein the business process relationship is the association relationship between the business data from production to consumption; A classification module 32, configured to classify the business data based on the business process relationship and the business process type to obtain target business data; A judgment module 33 is used to judge whether the target business data has production and consumption anomalies based on preset monitoring rules; The processing module 34 is used to obtain consumer information related to the target business data with the abnormality if the target business data has production and consumption anomalies, and complete data processing of the target business data based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information.

[0050] Optionally, the acquisition module 31 is specifically used for: Acquire monitoring data from at least one business management system and store the monitoring data in a target location; By preprocessing the monitoring data and the internal indicator data corresponding to the monitoring data, and using preset scripts to extract business data related to the business.

[0051] Optionally, the classification module 32 is specifically used for: Based on the business process relationship, the business data is initially classified to obtain initially classified business data; The initially classified business data is secondary classified based on the business process type and business attribute to obtain target business data.

[0052] Optionally, the above-mentioned determination module 33 is specifically used for: Obtaining data congestion amount of the target service data; Determining whether the data congestion amount is greater than a preset congestion threshold; If the data congestion amount is greater than the preset congestion threshold, determining whether the duration of the data congestion amount meets the preset time threshold; If the duration of the data congestion meets the preset time threshold, it is determined that production and consumption anomalies occur in the target business data.

[0053] Optionally, the processing module 34 is specifically used for: Acquire the business service type of the target business data; According to the business service type, consumer information related to the target business data with an exception is obtained according to a specified message delivery queue.

[0054] Optionally, the processing module 34 is further used for: Determining a storage location of consumer log information according to the consumer configuration information; Based on the storage location, determining whether the consumer log information meets the consumption condition; If the consumer log information meets the consumption condition, determining the corresponding consumption instance based on the consumer process identification information; The consumed data content in the consumption instance is deleted to obtain a modified consumption instance, so that the modified consumption instance can complete data processing after restarting.

[0055] Optionally, the processing module 34 is further used for: Based on the storage location, determining whether the keywords in the consumer log information meet a preset keyword condition, wherein the preset keyword condition is represented by the presence of unconsumable keywords in the consumer log information; If the keyword in the consumer log information meets the preset keyword condition, it is determined that the consumer log information meets the consumption condition.

[0056] It should be noted that the information interaction, execution process and other contents between the above-mentioned units are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0057] Figure 4 Schematic diagram of the structure of a computer device provided by an embodiment of the present invention. Figure 4 As shown, the computer device of this embodiment includes: at least one processor ( Figure 4 Only one is shown in the figure), a memory, and a computer program stored in the memory and executable on at least one processor, and when the processor executes the computer program, the steps in any of the above-mentioned business data processing method embodiments are implemented.

[0058] The computer device may include, but is not limited to, a processor and a memory. It can be understood by those skilled in the art that Figure 4 These are merely examples of computer devices and do not constitute limitations on the computer devices. The computer devices may include more or fewer components than those shown in the figure, or a combination of certain components, or different components. For example, they may also include a network interface, a display screen, and an input system.

[0059] In one embodiment, a computer-readable storage medium is provided, and when the instructions in the computer-readable storage medium are executed by a processor in a computer device, the computer device can execute the steps of any embodiment of a business data processing method disclosed in the present invention, which will not be repeated here. The computer-readable storage medium can be non-volatile or volatile.

[0060] The processor may be a CPU, or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0061] The memory includes a readable storage medium, an internal memory, etc., wherein the internal memory may be the memory of a computer device, and the internal memory provides an environment for the operation of the operating system and computer-readable instructions in the readable storage medium. The readable storage medium may be a hard disk of a computer device, and in other embodiments, it may also be an external storage device of the computer device, for example, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device. Further, the memory may also include both an internal storage unit of the computer device and an external storage device. The memory is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of a computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0062] It can be understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0063] The technical business in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here. 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.

[0064] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A business data processing method, characterized in that: include: Acquire business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to the preset businesses, wherein the business process relationships are association relationships between the business data from production to consumption; Classifying the business data based on the business process relationship and the business process type to obtain target business data; Based on preset monitoring rules, determine whether the target business data has production and consumption anomalies; If production and consumption anomalies occur in the target business data, consumer information related to the target business data with the anomaly is obtained, and data processing of the target business data is completed based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information.

2. The business data processing method according to claim 1, characterized in that: The classifying the business data based on the business process relationship and the business process type to obtain target business data includes: Based on the business process relationship, the business data is initially classified to obtain initially classified business data; The initially classified business data is secondary classified based on the business process type and business attribute to obtain target business data.

3. The business data processing method according to claim 1, characterized in that: The determining whether the target business data has production and consumption anomalies based on the preset monitoring rules includes: Obtaining data congestion amount of the target service data; Determining whether the data congestion amount is greater than a preset congestion threshold; If the data congestion amount is greater than the preset congestion threshold, determining whether the duration of the data congestion amount meets the preset time threshold; If the duration of the data congestion meets the preset time threshold, it is determined that production and consumption anomalies occur in the target business data.

4. The business data processing method according to claim 1, characterized in that: The acquiring of consumer information related to the target business data having an abnormality includes: Acquire the business service type of the target business data; According to the business service type, consumer information related to the target business data with an exception is obtained according to a specified message delivery queue.

5. The business data processing method according to claim 1, characterized in that: The data processing of the target business data based on the consumer information and the preset consumption processing rules includes: Determining a storage location of consumer log information according to the consumer configuration information; Based on the storage location, determining whether the consumer log information meets the consumption condition; If the consumer log information meets the consumption condition, determining the corresponding consumption instance based on the consumer process identification information; The consumed data content in the consumption instance is deleted to obtain a modified consumption instance, so that the modified consumption instance can complete data processing after restarting.

6. The business data processing method according to claim 5, characterized in that: The determining, based on the storage location, whether the consumer log information meets the consumption condition includes: Based on the storage location, determining whether the keywords in the consumer log information meet a preset keyword condition, wherein the preset keyword condition is represented by the presence of unconsumable keywords in the consumer log information; If the keyword in the consumer log information meets the preset keyword condition, it is determined that the consumer log information meets the consumption condition.

7. The business data processing method according to claim 1, characterized in that: The obtaining of business data of multiple business management systems corresponding to the preset business includes: Acquire monitoring data from at least one business management system and store the monitoring data in a target location; By preprocessing the monitoring data and the internal indicator data corresponding to the monitoring data, and using preset scripts to extract business data related to the business.

8. A business data processing device, characterized in that: include: An acquisition module, used to acquire business data of multiple business management systems corresponding to preset businesses, as well as business process relationships and business process types corresponding to the preset businesses, wherein the business process relationship is an association relationship between the business data from production to consumption; A classification module, used to classify the business data based on the business process relationship and the business process type to obtain target business data; A judgment module, used to judge whether the target business data has production and consumption anomalies based on preset monitoring rules; A processing module is used to obtain consumer information related to the target business data with the abnormality if production and consumption abnormalities occur in the target business data, and complete data processing of the target business data based on the consumer information and preset consumption processing rules, wherein the consumer information includes consumer configuration information and consumer process identification information.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the business data processing method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the business data processing method according to any one of claims 1 to 7 is implemented.

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