Method and device for adjusting service system in service transfer process and processor

Abstract

The invention discloses a method and a device for adjusting a service system in a service transfer process and a processor. The method comprises the steps that in the process that an initial service system transfers an aviation service object to a target service system, first log data and second log data corresponding to an aviation service are obtained, the initial service system is a service system running at the current moment, and the second service system is a service system running at the current moment; the target service system is a service system which replaces the initial service system to operate in the future, the first log data is log data generated in the operation process of the initial service system, and the second log data is log data generated in the operation process of the target service system; determining the similarity between the first log data and the second log data; and determining an adjustment strategy based on the similarity, and adjusting the initial service system and / or the target service system according to the adjustment strategy. The technical problem of low adjustment efficiency of the service system is solved.

Description

Technical Field

[0001] The present invention relates to the field of aviation business transfer system operation and maintenance technology, and in particular to a business system adjustment method, device and processor during a business transfer process. Background Art

[0002] During the business transfer process, the business transfer system connects the initial business system (old system) and the target business system (new system). The operation and maintenance of business transfer data mainly relies on query maintenance and alarm monitoring by operation and maintenance personnel. However, operation and maintenance personnel need to manually query and maintain the business transfer system regularly or as needed. And when the alarm information is overloaded with business transfer data, the operation and maintenance personnel cannot quickly and accurately find the problem, resulting in a waste of resources and reduced efficiency. In addition, when the amount of business transfer data is too large, it is impossible to analyze the business transfer data of the initial business system and the target business system in real time, and it is impossible to quickly locate the fault, resulting in the inability to make timely adjustments to any of the above business systems. Therefore, there is still a technical problem of low adjustment efficiency of the business system.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a method, device and processor for adjusting a business system during a business transfer process, so as to at least solve the technical problem of low adjustment efficiency of the business system.

[0005] According to one aspect of an embodiment of the present invention, a method for adjusting a business system during a business transfer process is provided, and the method may include: in the process of transferring an aviation business object from an initial business system to a target business system, obtaining first log data and second log data corresponding to the aviation business, wherein the initial business system is a business system currently running, and the target business system is a business system that will take over the operation of the initial business system in the future, the first log data is log data generated during the operation of the initial business system, and the second log data is log data generated during the operation of the target business system; determining the similarity between the first log data and the second log data; based on the similarity, determining an adjustment strategy, and adjusting the initial business system and / or the target business system according to the adjustment strategy, wherein the adjustment strategy is used to represent the rules for adjusting the initial business system and / or the target business system.

[0006] Optionally, the method is applied to a business transfer system, the business transfer system is connected to an elastic search engine, the elastic search engine is connected to an initial business system and a target business system, wherein obtaining first log data and second log data corresponding to the aviation business includes: obtaining first initial log data of the initial business system and second initial log data of the target business system through an elastic search engine at a target time interval; performing data cleaning processing on the first initial log data to obtain first log data, and performing data cleaning processing on the second initial log data to obtain second log data, wherein the accuracy of the first log data is higher than the accuracy of the first initial log data, and the accuracy of the second log data is higher than the accuracy of the second initial log data.

[0007] Optionally, the business transfer system includes a task scheduling tool, wherein, before obtaining the first log data of the initial business system and the second log data of the target business system through an elastic search engine at a target time interval, the method also includes: setting an acquisition task according to the target time interval through the task scheduling tool; based on the acquisition path in the acquisition task, obtaining the first initial log data from the initial business system through an elastic search engine, and obtaining the second initial log data from the target business system.

[0008] Optionally, after obtaining the first log data and the second log data corresponding to the aviation business, the method also includes: controlling the business transfer system to transmit the first log data and the second log data to the application operation and maintenance system database; controlling the business transfer system to receive the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, wherein the adjusted first log data is obtained by the application operation and maintenance system database performing structured processing on the first log data, and the adjusted second log data is obtained by the application operation and maintenance system database performing structured processing on the second log data.

[0009] Optionally, determining the similarity between the first log data and the second log data includes: in response to the business transfer system obtaining the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, comparing the adjusted first log data and the adjusted second log data to obtain the similarity.

[0010] Optionally, based on the similarity, an adjustment strategy is determined, including: in response to the similarity between the adjusted first log data and the adjusted second log data being less than or equal to a similarity threshold, determining that the aviation business transfer process is in an abnormal state; based on the abnormal state, generating a corresponding adjustment strategy, wherein the adjustment strategy is a rule for adjusting the abnormal state to a normal state; the method also includes: in response to the similarity between the adjusted first log data and the adjusted second log data being less than or equal to a similarity threshold, generating prompt information, wherein the prompt information can be used to prompt the abnormal state.

[0011] Optionally, the method also includes: in response to adjusting the initial business system and / or the target business system according to the adjustment strategy, collecting first log data of the adjusted initial business system and / or second log data of the adjusted target business system, and comparing the first log data and the second log data to obtain a comparison result; transmitting the comparison result and the similarity before adjusting the initial business system and / or the target business system according to the adjustment strategy to a graphical user display interface associated with the business transfer system, wherein the comparison result and the similarity are rendered and displayed on the graphical user display interface.

[0012] According to another aspect of an embodiment of the present invention, there is also provided a device for adjusting a business system during a business transfer process, comprising: an acquisition unit, for acquiring first log data and second log data corresponding to an aviation business during a process of transferring an aviation business object from an initial business system to a target business system, wherein the initial business system is a business system currently running, and the target business system is a business system that will take over the operation of the initial business system in the future, the first log data is log data generated during the operation of the initial business system, and the second log data is log data generated during the operation of the target business system; a determination unit, for determining the similarity between the first log data and the second log data; an adjustment unit, for determining an adjustment strategy based on the similarity, and adjusting the initial business system and / or the target business system according to the adjustment strategy, wherein the adjustment strategy is used to represent a rule for adjusting the initial business system and / or the target business system.

[0013] According to another aspect of an embodiment of the present invention, a processor is provided for running a program. When the program is run by the processor, a method for adjusting a service system during service transfer is executed.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing any one of the methods for adjusting the business system during the business transfer process.

[0015] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any one of the methods for adjusting the business system during the business transfer process.

[0016] According to another aspect of the embodiment of the present application, a computer program product is also provided. The computer program product includes a computer program, and when the computer program is executed by a processor, the method for adjusting the service system in the service transfer process of the embodiment of the present application is implemented.

[0017] In an embodiment of the present invention, in the process of transferring aviation business objects from the initial business system to the target business system, in order to ensure the accuracy of the subsequent operation of the target business system replacing the initial business system, the first log data and the second log data corresponding to the aviation business can be obtained; the similarity between the first log data and the second log data can be determined; based on the similarity, the adjustment strategy can be determined, and the initial business system and / or the target business system can be adjusted according to the adjustment strategy. In an embodiment of the present invention, the adjustment strategy is automatically determined by the similarity between the log data generated by the business system currently running during the operation process and the log data generated by the target business system taking over the operation of the initial business system in the future, so that the deviation and anomaly of the aviation business object transferred in the business system can be intelligently identified, and a targeted adjustment method is provided, which reduces the frequency and complexity of manual intervention. In addition, the adjustment strategy is not limited to the adjustment of a single business system, but a two-way dynamic adjustment of the initial business system and the target business system, which improves the flexibility and accuracy of the business system transfer process. Thereby, the technical effect of improving the adjustment efficiency of the business system is achieved, and the technical problem of low adjustment efficiency of the business system is solved. 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 method for adjusting a business system during a business transfer process according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of an operation and maintenance device in a data comparison scenario between civil aviation business transfer systems according to an embodiment of the present invention;

[0021] Figure 3 is a structural schematic diagram of an operation and maintenance device in a data comparison scenario between civil aviation business transfer systems according to an embodiment of the present invention;

[0022] Figure 4 is a flow chart of an implementation process of a log basic data analysis module according to an embodiment of the present invention;

[0023] Figure 5 is a flow chart of an operation and maintenance method in a data comparison scenario between civil aviation business transfer systems according to an embodiment of the present invention;

[0024] Figure 6 is a schematic diagram of a system for acquiring data from a background to a storage database according to an embodiment of the present invention;

[0025] Figure 7 is a schematic diagram of a device for adjusting a service system during a service transfer process according to an embodiment of the present invention;

[0026] Figure 8 It is a schematic diagram of an electronic device for a method for adjusting a service system during a service transfer process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] 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.

[0028] 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.

[0029] Example 1

[0030] According to an embodiment of the present invention, an embodiment of a method for adjusting a business system during a business transfer process 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.

[0031] Figure 1 is a flow chart of a method for adjusting a business system during a business transfer process according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0032] Step S102 : in the process of transferring the aviation business object from the initial business system to the target business system, obtaining first log data and second log data corresponding to the aviation business.

[0033] In the technical solution provided in the above step S102 of the embodiment of the present invention, during the transfer of the aviation business object, both the initial business system and the target business system will generate log data. The above log data can be used to record detailed information on the operations of the initial business system and the target business system, including but not limited to the operation time, operation type, operation result, flight number involved, passenger information, etc. The initial business system, that is, the old system, can be the business system running at the current moment. The target business system, that is, the new system, can be the business system that will take over the operation of the initial business system at a future moment. The aviation business object is a specific business entity or business data involved in the aviation business operation, which may include flights, passengers, tickets, baggage, loading information, etc. The aviation business object may be a civil aviation business. In the embodiment of the present invention, the aviation business object is referred to as business. The first log data may be the log data generated by the initial business system during operation. The second log data may be the log data generated by the target business system during operation.

[0034] In this embodiment, by obtaining the first log data and the second log data corresponding to the aviation business in the process of transferring the aviation business object from the initial business system to the target business system, the consistency of the first log data and the second log data can be ensured, the business logic of the initial business system and the target business system can be accurate, and the stable operation and timeliness of emergency response of the initial business system and the target business system can be ensured.

[0035] Optionally, the first log data and the second log data may be collected from various data sources (such as servers, applications, network devices, etc.) through a log collection tool. The log collection tool may obtain the log file path, log format, and transmission method (such as transmission to a specified server via a network) to be collected through a configuration file, which is only an example and is not specifically limited.

[0036] Step S104: determine the similarity between the first log data and the second log data.

[0037] In the technical solution provided in the above step S104 of the embodiment of the present invention, after obtaining the first log data and the second log data corresponding to the aviation business, the similarity between the first log data and the second log data can be determined, that is, the comparison result between the first log data and the second log data.

[0038] In this embodiment, a data comparison algorithm can be applied to calculate the similarity between the first log data and the second log data. It can be based on a direct comparison of the field values ​​of the first log data and the second log data, such as string matching and numerical comparison. It can also be based on a comparison of business logic, such as checking whether the results of the same business operations in the initial business system and the target business system are consistent. For the time series data in the first log data and the second log data, a sequence comparison algorithm, such as dynamic time warping, can be used to evaluate the time series similarity of the log data of the initial business system and the target business system.

[0039] It should be noted that the above-mentioned comparison method of the first log data and the second log data is only for illustration and is not specifically limited here. As long as the method can be used to determine the similarity between the first log data and the second log data, it is within the protection scope of the embodiments of the present invention and will not be explained one by one here.

[0040] In the embodiment of the present invention, determining the similarity between the first log data and the second log data can not only help the airline company monitor and verify the efficiency and integrity of the business system transfer, but also timely discover problems and take measures to ensure the smooth launch of the new system, thereby ensuring business continuity and high quality of passenger services.

[0041] Step S106: determining an adjustment strategy based on the similarity, and adjusting the initial business system and / or the target business system according to the adjustment strategy.

[0042] In the technical solution provided in the above step S106 of the embodiment of the present invention, after determining the similarity between the first log data and the second log data, an adjustment strategy can be determined based on the similarity, and the initial business system and / or the target business system can be adjusted according to the adjustment strategy. The adjustment strategy can be used to represent the rules for adjusting the initial business system and / or the target business system.

[0043] In this embodiment, the similarity between the first log data and the second log data can be analyzed to obtain the result of the comparative analysis. Based on the result of the comparative analysis, the abnormalities in the first log data and the second log data can be identified. For example, it is possible to identify which parts have a lower similarity than expected, which business or operation records are inconsistent between the initial business system and the target business system, and the nature of the inconsistency (such as data errors, logical differences, functional deficiencies, etc.). Once an abnormality is found, a corresponding processing mechanism can be triggered. For example, an alarm is sent to notify the administrator, corrective measures are automatically taken (such as restarting the service, adjusting parameters, etc.), or abnormal information is recorded for subsequent investigation and analysis.

[0044] Optionally, if the abnormal situation is caused by incomplete or delayed synchronization of the first log data and the second log data, the adjustment strategy may include optimizing the synchronization frequency of the first log data and the second log data, checking the transmission link of the first log data and the second log data, optimizing the format conversion rules of the first log data and the second log data, and enhancing the consistency guarantee mechanism of the first log data and the second log data. If the abnormal situation is caused by the logical difference between the initial business system and the target business system when processing the same business, the adjustment strategy may be to modify the business logic of the target business system to make it closer to the logic of the initial business system. Or make necessary adjustments to the business logic of the initial system to meet the requirements of the target business system. If the target business system is missing or wrong in some functions, the adjustment strategy may include implementing functional patches, fixing known errors, introducing new functions, etc. If the reason for the low similarity is the insufficient performance of the target business system, the adjustment strategy may include improving hardware resources, optimizing software configuration, adding load balancing strategies, etc., to improve the response speed and data processing capabilities of the target business system.

[0045] It should be noted that the determination of the above adjustment strategy is only for illustrative purposes and is not specifically limited here. As long as the adjustment strategy can be used to adjust the initial business system and / or the target business system to make the initial business system and / or the target business system better, it is within the protection scope of the embodiments of the present invention.

[0046] In step S102 to step S106 of the embodiment of the present invention, in the process of transferring the aviation business object from the initial business system to the target business system, in order to ensure the accuracy of the subsequent operation of the target business system replacing the initial business system, the first log data and the second log data corresponding to the aviation business can be obtained; the similarity between the first log data and the second log data can be determined; based on the similarity, the adjustment strategy can be determined, and the initial business system and / or the target business system can be adjusted according to the adjustment strategy. In this embodiment, the adjustment strategy is automatically determined by the similarity between the log data generated by the business system currently running during the operation process and the log data generated by the target business system taking over the operation of the initial business system in the future, so that the deviation and anomaly of the aviation business object transferred in the business system can be intelligently identified, and a targeted adjustment method is provided, which reduces the frequency and complexity of manual intervention. In addition, the adjustment strategy is not limited to the adjustment of a single business system, but a two-way dynamic adjustment of the initial business system and the target business system, which improves the flexibility and accuracy of the business system transfer process. Thereby, the technical effect of improving the adjustment efficiency of the business system is achieved, and the technical problem of low adjustment efficiency of the business system is solved.

[0047] The embodiment of the present invention is described in detail below in combination with the above steps.

[0048] As an optional embodiment, the method is applied to a business transfer system, the business transfer system is connected to an elastic search engine, and the elastic search engine is connected to an initial business system and a target business system, wherein step S102, obtaining first log data and second log data corresponding to the aviation business, includes: obtaining first initial log data of the initial business system and second initial log data of the target business system through an elastic search engine at a target time interval; performing data cleaning processing on the first initial log data to obtain first log data, and performing data cleaning processing on the second initial log data to obtain second log data, wherein the accuracy of the first log data is higher than the accuracy of the first initial log data, and the accuracy of the second log data is higher than the accuracy of the second initial log data.

[0049] In this embodiment, the business transfer system is connected to an elastic search engine (ES), which is connected to the initial business system and the target business system, and can collect and process log data from the initial business system and the target business system in real time, thereby ensuring the accuracy and consistency of the log data. If the first log data and the second log data corresponding to the aviation business are to be obtained, the first initial log data of the initial business system and the second initial log data of the target business system can be obtained through the elastic search engine at the target time interval. The first initial log data can be cleaned to obtain the first log data, and the second initial log data can be cleaned to obtain the second log data.

[0050] Optionally, according to a preset target time interval, the business transfer system can obtain the first initial log data of the initial business system and the second initial log data of the target business system from the ES by calling the query interface of the ES or using a log collection tool. The above target time interval can be set based on business requirements and business transfer system performance. For example, the above target time interval is every 10 minutes or every hour, which is only an example and is not specifically limited here.

[0051] Optionally, the collected log data may contain noise, incomplete or erroneous data. Log data can be preprocessed through data cleaning algorithms and tools. For example, duplicate log entries can be removed, malformed data can be corrected, missing values ​​can be filled, etc. The cleaned data will be more accurate and reliable, which is conducive to subsequent analysis and processing.

[0052] As an optional embodiment, the business transfer system includes a task scheduling tool, wherein, before obtaining the first log data of the initial business system and the second log data of the target business system through an elastic search engine at a target time interval, the method also includes: setting an acquisition task according to the target time interval through the task scheduling tool; based on the acquisition path in the acquisition task, obtaining the first initial log data from the initial business system through an elastic search engine, and obtaining the second initial log data from the target business system.

[0053] In this embodiment, the business transfer system may include a task scheduling tool. Before acquiring the first log data of the initial business system and the second log data of the target business system through the elastic search engine at the target time interval, the task scheduling tool may be used to set an acquisition task at the target time interval; based on the acquisition path in the acquisition task, the first initial log data may be acquired from the initial business system through the elastic search engine, and the second initial log data may be acquired from the target business system.

[0054] Optionally, at the initial start-up of the business transfer system, you can use the task scheduling tool of the background server, such as using Python's distributed task queue (Ce lery) or a similar task scheduling framework on the back end, to set up scheduled tasks to ensure that subsequent log data collection, processing and analysis processes are automatically executed within the target time interval.

[0055] Optionally, when a scheduled task is triggered, the business transfer system can respond to the instruction sent by the task scheduling tool and start executing the log data acquisition task. For example, the query interface of ES is called to retrieve the first initial log data of the initial business system and the second initial log data of the target business system according to the preset acquisition path (i.e., index name and time range).

[0056] As an optional embodiment, after obtaining the first log data and the second log data corresponding to the aviation business, the method also includes: controlling the business transfer system to transmit the first log data and the second log data to the application operation and maintenance system database; controlling the business transfer system to receive the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, wherein the adjusted first log data is obtained by the application operation and maintenance system database performing structured processing on the first log data, and the adjusted second log data is obtained by the application operation and maintenance system database performing structured processing on the second log data.

[0057] In this embodiment, after obtaining the first log data and the second log data corresponding to the aviation business, the business transfer system can be controlled to transfer the first log data and the second log data to the application operation and maintenance system database. The business transfer system can be controlled to receive the adjusted first log data and the adjusted second log data from the application operation and maintenance system database. The adjusted first log data can be obtained by the application operation and maintenance system database performing structured processing on the first log data, and the adjusted second log data can be obtained by the application operation and maintenance system database performing structured processing on the second log data. The operation and maintenance system database can be a Blue Whale Operation System (AOS) database.

[0058] Optionally, in the business transfer system, after obtaining the first log data and the second log data from the ES, the above log data can be transmitted to the AOS database. The transmission step may include data format conversion, data transmission configuration and data transmission execution. Data format conversion can ensure that the first log data and the second log data meet the storage format requirements of the AOS database before transmission. The data transmission configuration can configure the rules for data transmission in the business transfer system, including database connection information (such as database address, port, user name and password), the name of the target table, field mapping relationship, etc. The data transmission execution can transfer the first log data and the second log data to the AOS database through a data transmission tool or a programming interface.

[0059] Optionally, after the first log data and the second log data arrive at the AOS database, they can be structured. The interface or driver of the AOS database can be used to store the first log data and the second log data in a structured manner in a database table. According to the characteristics and requirements of the first log data and the second log data, a suitable database table structure can be designed, including field types, indexes, etc., to improve the storage efficiency and query performance of the first log data and the second log data.

[0060] As an optional embodiment, step S104, determining the similarity between the first log data and the second log data, includes: in response to the business transfer system obtaining the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, comparing the adjusted first log data and the adjusted second log data to obtain the similarity.

[0061] In this embodiment, in order to determine the similarity between the first log data and the second log data, the business transfer system can obtain the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, and then compare the adjusted first log data and the adjusted second log data to obtain the similarity.

[0062] Optionally, the adjusted first log data and the adjusted second log data are compared, and time series analysis, pattern matching, statistical analysis and other methods can be used to compare log data in different time periods to identify changing trends, abnormal patterns or potential problems in the log data.

[0063] As an optional embodiment, step S106, based on the similarity, determines the adjustment strategy, including: in response to the similarity between the adjusted first log data and the adjusted second log data being less than or equal to the similarity threshold, determining that the aviation business transfer process is in an abnormal state; based on the abnormal state, generating a corresponding adjustment strategy, wherein the adjustment strategy is a rule for adjusting the abnormal state to a normal state; the method also includes: in response to the similarity between the adjusted first log data and the adjusted second log data being less than or equal to the similarity threshold, generating prompt information, wherein the prompt information can be used to prompt the abnormal state.

[0064] In this embodiment, in the process of determining the adjustment strategy based on similarity, it can be determined that the aviation business transfer process is in an abnormal state when the similarity between the adjusted first log data and the adjusted second log data is less than or equal to the similarity threshold. Based on the abnormal state, a corresponding adjustment strategy for adjusting the abnormal state to a normal state can be generated. When the similarity between the adjusted first log data and the adjusted second log data is less than or equal to the similarity threshold, that is, the aviation business transfer process is in an abnormal state, a prompt message can be generated to prompt the abnormal state.

[0065] Optionally, based on the results of the comparative analysis, anomalies in the log data can be identified. A similarity threshold, rule, or machine learning algorithm can be set to determine whether the log data is abnormal. The similarity threshold can be used to determine whether the similarity between the adjusted first log data and the second log data reaches the expected normal level. For example, the similarity threshold can be set to 90%, indicating that when the similarity is less than 90%, the business transfer process will be considered to be in an abnormal state.

[0066] In an embodiment of the present invention, when the aviation business transfer process is in an abnormal state, in addition to generating an adjustment strategy, the abnormal state is adjusted to a normal state, that is, the similarity of the log data is increased to above the similarity threshold. Prompt information can also be generated. The prompt information may include the specific circumstances of the abnormality (such as the numerical value of the similarity, samples of abnormal data, etc.), possible cause analysis, and recommended treatment measures. The above prompt information can be pushed to relevant operation and maintenance personnel or management personnel in a variety of ways (such as email, text message, system notification, etc.) to ensure that the abnormal state is understood in a timely manner and appropriate actions are taken. This is for example only and is not specifically limited here.

[0067] As an optional embodiment, the method also includes: in response to adjusting the initial business system and / or the target business system according to the adjustment strategy, collecting the first log data of the adjusted initial business system, and / or the second log data of the adjusted target business system, and comparing the first log data and the second log data to obtain a comparison result; transmitting the comparison result and the similarity before adjusting the initial business system and / or the target business system according to the adjustment strategy to a graphical user display interface associated with the business transfer system, wherein the comparison result and the similarity are rendered and displayed on the graphical user display interface.

[0068] In this embodiment, after the initial business system and / or the target business system are adjusted according to the adjustment strategy, the first log data of the adjusted initial business system and / or the second log data of the adjusted target business system can be collected. That is, the business transfer system responds to the system status and collects the adjusted first log data and second log data from the initial business system and the target business system again to ensure the real-time and accuracy of the log data. The first log data and the second log data are compared to obtain a comparison result to comprehensively evaluate the consistency of the first log data and the second log data. The comparison result and the similarity before the initial business system and / or the target business system are adjusted according to the adjustment strategy are transmitted to the graphical user display interface associated with the business transfer system. Among them, the comparison result and the similarity can be rendered and displayed on the graphical user display interface.

[0069] Optionally, the monitoring results of the first log data and the second log data are displayed to the user in a visual manner. A front-end development framework, such as View Update Engine JavaScript Framework (Vue.js), React JavaScript Library (React), etc., can be used in combination with a data visualization library (such as Echarts), to create an intuitive dashboard or report to display the analysis results, abnormal situations, etc. of the first log data and the second log data. At the same time, when an abnormal situation occurs, the business transfer system can send an alarm message to the relevant operation and maintenance personnel or management personnel through email, SMS, instant messaging, etc., so that timely measures can be taken to deal with it.

[0070] Optionally, the rendered comparison results and similarities can be displayed through data visualization, for example, using line graphs, bar graphs, heat maps and other charts to display the comparison results and similarity change trends of the first log data and the second log data, so that operation and maintenance personnel can identify the consistency level and business transfer status of the first log data and the second log data. This is only an example and is not specifically limited here.

[0071] In an embodiment of the present invention, in the process of transferring aviation business objects from the initial business system to the target business system, in order to ensure the accuracy of the subsequent operation of the target business system instead of the initial business system, the first log data and the second log data corresponding to the aviation business can be obtained; the similarity between the first log data and the second log data can be determined; based on the similarity, the adjustment strategy can be determined, and the initial business system and / or the target business system can be adjusted according to the adjustment strategy. In this embodiment, the adjustment strategy is automatically determined by the similarity between the log data generated by the business system currently running during the operation process and the log data generated by the target business system taking over the operation of the initial business system in the future, so that the deviation and anomaly of the aviation business object transferred in the business system can be intelligently identified, and a targeted adjustment method is provided, which reduces the frequency and complexity of manual intervention. In addition, the adjustment strategy is not limited to the adjustment of a single business system, but a two-way dynamic adjustment of the initial business system and the target business system, which improves the flexibility and accuracy of the business system transfer process. Thereby, the technical effect of improving the adjustment efficiency of the business system is achieved, and the technical problem of low adjustment efficiency of the business system is solved.

[0072] Example 2

[0073] Another optional specific implementation is described in detail below.

[0074] At present, the scale of civil aviation business is constantly expanding. The existing civil aviation host system is unable to implement new business scenarios well and quickly under a low-cost budget due to more frequent and diversified business needs. In recent years, concepts such as cloud computing, distributed systems, and microservices have relied on low-cost and open information technology to rebuild business functions similar to the old civil aviation host. However, due to the complexity of civil aviation business scenarios and extremely high requirements for production safety, the newly built system cannot completely replace the existing system, and there are differences in business logic details between the systems, resulting in inconsistent data between the old and new systems due to logical differences during the iteration process, resulting in unsuccessful business processing. In addition, traditional operation and maintenance methods often rely on manual data inspection and comparison, which is not only inefficient, but also prone to errors, and it is difficult to meet the requirements of modern civil aviation information systems for data accuracy and timeliness.

[0075] The present invention proposes an operation and maintenance device in a data comparison scenario between civil aviation business transfer systems based on an AOS platform. The operation and maintenance device automatically collects log data from ES by setting a background timer task, compares the log data through the application data consistency check system (Travel Sky Application Check System, referred to as TACS), and transmits it to the AOS database for storage after cleaning. The operation and maintenance device compares and analyzes the log data in the AOS database, identifies high-urgency abnormal data through preset algorithms and rules, and provides abnormal data repair suggestions and one-key execution functions for the identified abnormal data, and determines the cause and impact range of the abnormal data through data mining and association analysis, and provides corresponding processing suggestions. In addition, when abnormal data appears, the operation and maintenance device can automatically send an alarm message to relevant operation and maintenance personnel or management personnel, so as to take corresponding emergency disposal measures in time to ensure the normal operation of the device. Thereby achieving the technical effect of improving the adjustment efficiency of the business system and solving the technical problem of low adjustment efficiency of the business system.

[0076] The method is further described below.

[0077] In this embodiment, the present invention automatically collects log data from ES and extracts the comparison results of TACS by setting a background timer task. After the log data is cleaned, it can be transmitted to the AOS database for storage and in-depth analysis, and displayed in real time on the large screen so that managers and relevant departments can understand the operating status of the device in a timely manner. High-urgency abnormal data can also be identified through preset algorithms and rules. Once an abnormality is found, repair suggestions and tools are immediately provided to help respond quickly. In addition, through data mining and association analysis, the cause and scope of the abnormal data can be determined, so as to give effective processing suggestions. When abnormal data appears, an alarm message can be automatically sent to relevant operation and maintenance personnel or managers to ensure that emergency measures are taken quickly to ensure the normal operation of the device. Not only can the efficiency and accuracy of monitoring alarms be significantly improved, but also the stable and reliable operation of the production system during the transfer process between the old and new systems can be effectively guaranteed, thereby enhancing overall security and business continuity.

[0078] Figure 2 is a schematic diagram of an operation and maintenance device in a data comparison scenario between civil aviation business transfer systems according to an embodiment of the present invention. Figure 2 As shown, the following steps are included:

[0079] Step S202, obtain ES logs and analyze and process to obtain data.

[0080] In this embodiment, the ES log can be acquired at a frequency higher than the TACS scheduled comparison (as long as the TACS comparison is completed, the comparison result can be regarded as acquired in real time), and the basic data of the log can be analyzed and processed to obtain the basic data for parsing and storage.

[0081] Step S204, output the result and store it in the database.

[0082] In this embodiment, the acquired log basic data can be parsed and stored in the database, cleaned, and stored in the AOS database.

[0083] Figure 3 is a structural diagram of an operation and maintenance device in a data comparison scenario between civil aviation business transfer systems according to an embodiment of the present invention, such as Figure 3 As shown, it includes a log basic data analysis module 302, a fault prompt and review module 304, a large-screen data display module 306 and a monitoring alarm event aggregation module 308.

[0084] The log basic data analysis module 302 can analyze and process the basic data parsed into the log basic data warehouse, and identify high-urgency abnormal data through preset algorithms and rules. The business transfer system can identify and monitor data anomalies relatively promptly, and store the analyzed data and apply it to other modules, helping operation and maintenance personnel to discover problems in a timely manner and assist in solving them.

[0085] The fault prompt and replay module 304 can analyze the data anomalies output by the log basic data analysis module. This module can help the on-duty operation and maintenance personnel quickly find and solve problems by calling the Application Programming Interface (API) of the Application Monitoring System (TAM) or issuing prompt information by itself, thereby reducing the impact of business transfer system failures on the business. After the failure is solved, the module stores relevant data to assist in completing the failure replay, reduce the risk of the failure occurring again under the same circumstances, and provide solutions for the subsequent occurrence of the same problem.

[0086] The large-screen data display module 306 can display the monitoring results on the large-screen data, so that the operation and maintenance personnel and relevant departments can understand the operation status of the business transfer system at any time and make decisions in time.

[0087] The monitoring alarm event aggregation module 308 can automatically send alarm information (or record log monitoring keywords that can trigger TAM alarms and generate application alarm information) to relevant operation and maintenance personnel or management personnel when abnormal data appears, helping them to take emergency measures in time to ensure the normal operation of the system.

[0088] Figure 4 is a flowchart of an implementation process of a log basic data analysis module according to an embodiment of the present invention, such as Figure 4 As shown, the following steps are included:

[0089] Step S402, obtaining basic log data.

[0090] In this embodiment, basic data of log basic data parsing and storage can be obtained.

[0091] Step S404: Analyze and process the basic log data.

[0092] In this embodiment, the basic data parsed and stored in the log basic data can be analyzed and processed.

[0093] Step S406: Identify high-urgency abnormal data through preset algorithms and rules.

[0094] In this embodiment, high-urgency abnormal data can be identified through preset algorithms and rules, and data anomalies can be identified and monitored relatively timely.

[0095] Step S408, classify the abnormal events and store them in a database.

[0096] In this embodiment, high-urgency abnormal data is identified through preset algorithms and rules. After relatively timely identification and monitoring of data anomalies, the analyzed data is stored and applied to other modules to help operation and maintenance personnel discover problems in a timely manner and assist in solving them.

[0097] Figure 5 is a flow chart of an operation and maintenance method in a data comparison scenario between civil aviation business transfer systems according to an embodiment of the present invention. Figure 5 As shown, the following steps are included:

[0098] Step S501: whether to trigger a scheduled task.

[0099] In the technical solution provided by the above step S501 of the embodiment of the present invention, it is determined whether a scheduled task is triggered, and if so, step S502 is executed, otherwise, step S505 is executed.

[0100] Optionally, through the task scheduling tool of the background server, such as using Python's Celery or similar task scheduling framework in the backend, you can set up a scheduled task to ensure that the subsequent log data collection, processing and analysis process is automatically executed at a specific time interval. This can ensure continuous monitoring and processing of log data without manual triggering.

[0101] Step S502: log data collection and extraction.

[0102] In the technical solution provided in the above step S502 of the embodiment of the present invention, the ES log collection tool can be used to collect log data from various data sources (such as servers, applications, network devices, etc.). The above tool can specify the log file path, log format and transmission mode to be collected (such as transmitted to a specified server via the network) through a configuration file. The collected log data will be extracted with key information, such as timestamp, log level, source Internet Protocol (Internet Protocol, referred to as IP), operation type, etc., for subsequent analysis and processing.

[0103] Step S503: whether to perform log data cleaning.

[0104] In the technical solution provided in the above step S503 of the embodiment of the present invention, it is determined whether to perform log data cleaning. If so, step S501 is executed, otherwise, step S504 is executed.

[0105] Optionally, the collected log data may contain noise, incomplete or erroneous data. Preprocess the log data through data cleaning algorithms and tools. For example, remove duplicate log entries, correct malformed data, fill in missing values, etc. You can use Python's data processing library (Pandas) to perform the above operations. The cleaned log data will be more accurate and reliable, which is conducive to subsequent analysis and processing.

[0106] Step S504: storing the log data in the AOS database.

[0107] In the technical solution provided in the above step S504 of the embodiment of the present invention, the cleaned log data can be stored in a specified AOS database. The AOS database can provide efficient data storage and retrieval functions. The log data is stored in a database table in a structured manner using a database interface or driver. According to the characteristics and requirements of the log data, a suitable database table structure can be designed, including field types, indexes, etc., to improve the storage efficiency and query performance of the log data.

[0108] Step S505: analyzing the AOS data.

[0109] In the technical solution provided in the above step S505 of the embodiment of the present invention, log data can be read from the AOS database and compared and analyzed. Time series analysis, pattern matching, statistical analysis and other methods can be used to compare log data of different time periods to find out the changing trends, abnormal patterns or potential problems in the data. For example, compare the log data of the current time period with the historical data to see if there is an abnormal access frequency, an increase in error types, etc. Data analysis tools and libraries, such as Python's Numerical Python (Numer ica l Python, referred to as NumPy) library, machine learning library (Scikit-learn), etc., can be used to analyze and process data.

[0110] Step S506, identifying abnormal data.

[0111] In the technical solution provided in step S506 of the embodiment of the present invention, abnormal data identification can be performed. If there is abnormal data, step S511 is executed, and if there is no abnormal data, step S507 is executed. Thresholds, rules or machine learning algorithms can be set to determine whether the data is abnormal. Once an abnormality is found, the business transfer system will trigger a corresponding processing mechanism.

[0112] Step S507: Whether to trigger the log processing timing.

[0113] In the technical solution provided by the above step S507 of the embodiment of the present invention, it is determined whether the log processing timing is triggered, and if so, step S505 is executed, otherwise, step S508 is executed.

[0114] Step S508: perform data mining and association analysis.

[0115] In the technical solution provided in the above step S508 of the embodiment of the present invention, if the log processing timing is triggered, data mining and association analysis can be performed.

[0116] Step S509: Take a fault snapshot and restore the disk.

[0117] In the technical solution provided in the above step S509 of the embodiment of the present invention, fault snapshot and replay can be performed according to the results of data mining and association analysis.

[0118] Step S510, display the result on the big screen.

[0119] In the technical solution provided in step S510 of the embodiment of the present invention, the monitoring results of the log data are displayed to the user in a visual manner. A front-end development framework (such as Vue.js, React, etc.) can be used in combination with a data visualization library (such as Echarts) to create an intuitive dashboard or report to display the analysis results, abnormal conditions, etc. of the log data.

[0120] Step S511, sending alarm information.

[0121] In the technical solution provided in the above step S511 of the embodiment of the present invention, when an abnormal situation occurs, the business transfer system can send an alarm message to the relevant operation and maintenance personnel or management personnel through email, SMS, instant messaging, etc., so that timely measures can be taken to deal with it. For example, an alarm is sent to notify the administrator, corrective measures are automatically taken (such as restarting the service, adjusting parameters, etc.), or abnormal information is recorded for subsequent investigation and analysis.

[0122] Step S512, determining the cause and impact scope of the abnormal data.

[0123] In the technical solution provided in the above step S512 of the embodiment of the present invention, the cause of the abnormal data and the impact range can be determined according to the alarm information.

[0124] Step S513: providing abnormal data repair suggestions.

[0125] In the technical solution provided in the above step S513 of the embodiment of the present invention, after determining the cause and impact range of the abnormal data, suggestions for repairing the abnormal data may be provided.

[0126] Step S514, perform emergency response.

[0127] In the technical solution provided in the above step S514 of the embodiment of the present invention, emergency processing is performed according to the abnormal data repair suggestion, and the result is displayed on the large screen.

[0128] In a server or operation and maintenance management system, implementing a scheduled call function is crucial to ensuring the timely collection and processing of log data. Figure 6 is a schematic diagram of a system for acquiring data from a background to a storage database according to an embodiment of the present invention, such as Figure 6 As shown, it includes a task publisher module 601, a task scheduler module 602, a message agent module 603, a task consumer module 604, a task consumer module 605, a task consumer module 606, and a storage result module 607.

[0129] The task publisher module 601 generates tasks in the background code and assigns them to the task queue by calling the API, functions and decorators provided by Celery. For example, developers can call Celery's task decorator to define a new task in a specific business logic module when certain conditions are met. The task can be to obtain a specific type of log data, perform data processing operations, etc. For the task of obtaining application logs, Celery-related modules and custom data management modules can be imported. A periodic task can be defined using the decorator used to define periodic tasks in Celery (for example, the @periodic_task decorator), which is executed every 10 minutes. In the task function, a data management module instance can be created, and its methods can be called to obtain application log data within a specific date range, and then subsequent processing can be performed.

[0130] Task scheduler module 602, the beat process of Celly can read the content of the configuration file. In the configuration file, the tasks that need to be executed periodically and the execution frequency can be clearly specified. For example, a task to obtain application logs can be set to be executed once every 10 minutes. The beat process can periodically send the tasks that need to be executed due to the task queue according to the information in the configuration file. In order to ensure the stable operation of the beat process, it can be run on the server as an independent service, and its operating status can be monitored in real time through a monitoring tool. If the beat process fails, an alarm can be issued in time and corresponding recovery measures can be taken.

[0131] Message agent module 603, message agent, also known as message middleware, plays a key role in the entire timed call system. It can accept task messages sent by task producers, store them in queues (such as RabbitMQ) and then distribute them to task consumers in sequence. When configuring a message agent, performance, reliability and scalability need to be considered. For example, parameters such as memory allocation and connection limit of the message agent can be adjusted according to the load situation to improve the ability to process tasks. At the same time, in order to ensure the reliability of the message, the persistence function of the message agent can be enabled to store task messages on disk to prevent the loss of tasks in the event of a system failure.

[0132] Task consumer module 604, task consumer module 605, and task consumer module 606 are respectively task consumer modules on different servers. The execution efficiency can be improved by running multiple consumers on multiple servers. Each consumer is an independent process or thread, which obtains tasks from the task queue and executes them. Consumers can be assigned according to the type and priority of the task to ensure that high-priority tasks can be processed in a timely manner. In order to improve the performance of task consumers, technologies such as parallel processing and asynchronous execution can be used. For example, for the task of obtaining application logs, multiple consumers can be started at the same time. Each consumer is responsible for obtaining log data from different data sources, and then merging the data for subsequent processing, which can improve the collection speed of log data.

[0133] Storage result module 607, after the task is processed, the status information and results need to be saved for subsequent processing. The execution results of the task can be stored in the database or written to the file system. If an error occurs during the execution of the task, the error information also needs to be recorded for subsequent troubleshooting. In order to ensure the reliability of the results, a data backup and recovery mechanism can be adopted. For example, the task results in the database can be regularly backed up to an external storage device to prevent data loss when the database fails. At the same time, an automatic recovery mechanism can also be set up so that when the system fails, the data can be automatically restored from the backup and the unfinished task can be continued.

[0134] In this embodiment, log collection, extraction and cleaning may be performed and stored in the AOS database in a metadata format.

[0135] Optionally, after the scheduled task is triggered, the system collects log data according to preset query conditions such as time range and index name. For example, you can use the Elasticsearch API interface to obtain application log data within a specific time period by specifying parameters such as time range and log index name. When collecting log data, you need to consider the diversity and complexity of data sources. Different applications may use different log formats and storage methods, so it is necessary to develop corresponding log collection plug-ins or scripts to adapt to different data sources. At the same time, in order to improve the collection efficiency, distributed collection, incremental collection and other technologies can be used to reduce the pressure on the data source.

[0136] Optionally, in the collected log data, the comparison log data related to TACS can be further extracted. This step can parse and filter the log content to filter out the key information of the comparison difference that is convenient for storage analysis. For the comparison log data of TACS, it can be extracted according to specific keywords, log levels and other conditions. For example, the keywords in the log, such as "date", "flight", etc., can be matched by regular expressions to filter out the log entries related to the TACS comparison. At the same time, it is also possible to filter out important comparison log information according to the log level, such as information (Information, referred to as INFO), warning (Warning, referred to as WARN), error (error), etc.

[0137] Optionally, the extracted comparison log data may contain noise, incomplete or erroneous data, and cleaning is required to improve data quality. Data such as rows containing specific error representations or garbled characters can be regarded as invalid data. For example, some rules for invalid data can be defined, such as containing specific character sequences, format errors, etc., and these invalid data can be identified and removed through conditional judgment. A unified data format can be defined, such as retaining two decimal places in the data format. For data that does not conform to the standard format, Python's string processing functions and regular expressions can be used to convert it. For example, the string format time (strft ime) function can be used to convert the date and time string into a unified format, and the regular expression replacement (Regular Expression Subst itute, referred to as re.sub) function can be used to replace the data format that does not meet the requirements. Data cleaning can effectively improve the quality and consistency of comparison log data, and provide a reliable data foundation for subsequent data analysis and application.

[0138] Optionally, the cleaned log data is transmitted in the format of metadata and stored in the AOS database. The cleaned log data can be analyzed in detail to understand the field type, length, possible value range and relationship between the data. According to the analysis results, a suitable database table structure can be designed. For example, for the comparison metadata of TACS, a database table containing fields such as flight information, comparison parameters, system A value, system B value, timestamp, task name, etc. can be designed. According to the characteristics of the data and query requirements, the data type and length of each field are determined. For example, the flight number can use the string type, the timestamp can use the time type, and the numerical field can choose the integer or floating point type according to the actual situation. According to common query requirements, the time field and the user identity are created as index fields to improve the query efficiency of the data, especially when querying by time range or user. The index creation function of the database can be used, such as using the create index (CREATEINDEX) statement in the structured query language (MySQL) to create an index. AOS receives the transmitted data, parses it according to the agreed format, and inserts the parsed data into the designed database table. During the data transmission process, data transmission tools or frameworks, such as Kafka, can be used to ensure reliable transmission and efficient storage of data.

[0139] In this embodiment, business data analysis and operation and maintenance applications can be performed based on metadata, including abnormality identification, monitoring display and problem handling. The operation and maintenance device can perform business data analysis through data grouping and classification, abnormal data detection and processing, statistical analysis and problem location.

[0140] Optionally, the metadata is grouped according to the comparison task type field. For example, if there are different types of comparison tasks, such as flight information comparison, passenger data comparison, etc., the metadata is divided into different groups according to the task type.

[0141] Optionally, the abnormal data in the metadata can be accumulated based on the timeline. For example, count the number of abnormal data of a certain task type within a specific time period, or accumulate the abnormal values ​​of a specific indicator. Perform logical judgment to confirm whether the abnormality persists. By comparing data at different time points, determine whether the abnormal situation has always existed or whether there is a trend of aggravation. Determine the urgency of manual processing based on the duration and severity of the abnormality. For example, set different urgency levels, and immediately push high-urgency abnormal situations to the monitoring and alarm system. At the set tolerance range threshold, push the pending exceptions to the monitoring and alarm system. The tolerance range can be set according to business needs and experience, and when the abnormal data exceeds this range, the alarm mechanism is triggered. Further categorize the metadata under different groups. Classification can be performed based on specific attributes or characteristics to better conduct subsequent analysis.

[0142] Optionally, perform statistics such as accumulation, median, and standard deviation on the abnormal situations of different task scenarios within the time range. Through these statistical indicators, you can understand the distribution and trend of abnormal situations. By analyzing the trend of statistical data, locate business scenarios that may have abnormal problems. For example, if the number of abnormal data of a certain task type shows an upward trend, or the standard deviation of a certain indicator is large, it means that there may be problems in the business scenario. Reduce undiscovered business scenarios with unsmooth data synchronization and promote the optimization of business scenarios of the new system. By timely discovering and handling abnormal situations, improve the efficiency and accuracy of data synchronization and optimize business processes.

[0143] Taking the task logic of sorting high-priority alarms according to time sequence as an example, the flight passenger comparison task is called once every 10 minutes, and temporary business data inconsistencies are synchronized through the data synchronization mechanism between systems. When an exception is reported as an error in multiple consecutive comparisons, it is determined that the synchronization mechanism is imperfect and the priority of the exception needs to be increased until the number of exception occurrences exceeds the threshold to trigger manual / automatic processing. When an exception no longer reports an error in the latest alarm, the priority is quickly lowered. At the same time, airports that have already been put into operation can also configure the monitoring priority range to increase the priority of the airports that have already been put into operation, so as to achieve emergency processing at the fastest speed and avoid business handling problems caused by inconsistent data between systems.

[0144] Optionally, in the process of data classification, aggregation and sorting, data can be classified and aggregated according to different dimensions such as time, flight, and passenger. For example, the number of abnormal data per day, week, or month can be counted according to the time dimension; the abnormal conditions of different flights can be counted according to the flight dimension; and the abnormal data of specific passengers can be counted according to the passenger dimension. Through multi-dimensional classification and aggregation, a more comprehensive understanding of the operation can be obtained and potential problem areas can be found. Data can be sorted in ascending or descending order according to indicators such as the frequency of occurrence of specific events and response time. For example, the data can be sorted from high to low according to the frequency of occurrence of events, or from short to long according to the response time. The sorted results can help operation and maintenance personnel quickly identify areas with more serious problems and handle them first. The preset threshold judgment rules can be used. Once a certain indicator exceeds the set threshold, it will be marked as abnormal data. For example, when the network delay exceeds a certain number of milliseconds, it is considered abnormal. At the same time, pattern matching algorithms are also used to identify data that does not conform to the normal pattern. For example, for a specific business process, if the pattern of the data does not conform to the normal situation, it is marked as abnormal.

[0145] Optionally, during the monitoring display process, it can be displayed on a large screen. The large screen display interface can use charts, tables and other forms to intuitively present the identified data differences between the new and old systems. For example, a bar chart can be used to display the number of abnormal data of different task types, and a table can be used to display specific abnormal data items. The abnormal information is sorted according to the urgency, so that the operation and maintenance personnel can quickly focus on the most urgent problems. Among them, the large screen area can be divided into the top area, the middle area and the bottom area. The top area is mainly used to display the overall summary and key indicators such as the system name, current time, and overall operating status. The real-time updated digital dashboard and status indicator can be used to display this information to understand the overall operation status. The middle area is usually the main data display area, which is specially used to place various icons and tables. For example, a line chart can be used to display the changing trend of abnormal data, and a detailed table can be used to display the specific information of abnormal data. The bottom area can be used to display auxiliary information such as the time of data update and copyright information, making the entire large screen display more comprehensive, clear and organized.

[0146] Optionally, in the process of problem handling, it can be carried out through alarm mechanism, emergency disposal measures, data mining and correlation analysis. When abnormal data that reaches the urgency of manual processing is detected, the alarm mechanism can be automatically triggered. The alarm information is sent to relevant operation and maintenance personnel or managers in a timely manner by means of email, SMS, message push and other methods. For example, when an abnormal situation occurs, an email can be automatically sent to the operation and maintenance team, and a SMS can be sent to notify the on-duty personnel at the same time. The relevant operation and maintenance personnel or managers take emergency disposal measures in time according to the alarm information to ensure the normal operation and stability of the system. The on-duty personnel with emergency authority on the front-end large screen can provide detailed abnormal data repair suggestions through the reading device to understand the cause of the problem. For example, when an abnormal situation occurs, the possible cause and solution will be displayed on the large screen. Use the one-key execution function integrated in the front-end large screen to quickly apply these suggestions. For example, for some common problems, a one-key repair button can be set, and the on-duty personnel can quickly take measures to solve the problem. Through data mining and correlation analysis technology, the cause and scope of the abnormal data can be further accurately determined. For example, by analyzing historical abnormal data, the associated factors of the abnormal situation can be found to determine the root cause of the problem. Provide more comprehensive processing suggestions for operation and maintenance personnel to improve the reliability and stability of the system.

[0147] Example 3

[0148] The embodiment of the present invention provides a device for adjusting a business system during a business transfer process. It should be noted that the device for adjusting a business system during a business transfer process of the embodiment of the present invention can be used to perform Figure 1 The following is an introduction to the method for adjusting the service system during service transfer provided by the embodiment of the present invention.

[0149] Figure 7 is a schematic diagram of a device for adjusting a service system during a service transfer process according to an embodiment of the present invention. Figure 7 As shown, the device 700 for adjusting the service system during the service transfer process may include: an acquisition unit 702 , a determination unit 704 and an adjustment unit 706 .

[0150] The acquisition unit 702 is used to acquire first log data and second log data corresponding to the aviation business during the process of transferring the aviation business object from the initial business system to the target business system, wherein the initial business system is the business system currently running, the target business system is the business system that will take over the operation of the initial business system at a future time, the first log data is the log data generated during the operation of the initial business system, and the second log data is the log data generated during the operation of the target business system.

[0151] The determining unit 704 is configured to determine the similarity between the first log data and the second log data.

[0152] The adjustment unit 706 is used to determine an adjustment strategy based on the similarity, and adjust the initial business system and / or the target business system according to the adjustment strategy, wherein the adjustment strategy is used to represent a rule for adjusting the initial business system and / or the target business system.

[0153] The device for adjusting the business system during the business transfer process provided by the embodiment of the present invention acquires the first log data and the second log data corresponding to the aviation business during the process of transferring the aviation business object from the initial business system to the target business system through the acquisition unit 702, wherein the initial business system is the business system running at the current moment, the target business system is the business system that takes over the operation of the initial business system at the future moment, the first log data is the log data generated during the operation of the initial business system, and the second log data is the log data generated during the operation of the target business system; the similarity between the first log data and the second log data is determined by the determination unit 704; the adjustment unit 706 is provided to determine the adjustment strategy based on the similarity, and adjust the initial business system and / or the target business system according to the adjustment strategy, wherein the adjustment strategy is used to represent the rules for adjusting the initial business system and / or the target business system. Thus, the technical effect of improving the adjustment efficiency of the business system is achieved, and the technical problem of low adjustment efficiency of the business system is solved.

[0154] The adjustment device of the business system during the above-mentioned business transfer process may also include a processor and a memory. The above-mentioned units are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0155] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set to control the same device type of devices to be shut down to perform graceful shutdown by adjusting kernel parameters.

[0156] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (fl ash RAM), and the memory includes at least one storage chip.

[0157] The processor contains a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the work efficiency of traders can be improved by adjusting the kernel parameters.

[0158] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0159] Example 4

[0160] According to an embodiment of the present invention, there is further provided a computer-readable storage medium on which a program is stored. When the program is executed by a processor, a method for adjusting a business system during a business transfer process is implemented.

[0161] Example 5

[0162] According to an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the program executes a method for adjusting a business system during a business transfer process when the program is running.

[0163] Example 6

[0164] Figure 8 is a schematic diagram of an electronic device for a method for adjusting a service system during a service transfer process according to an embodiment of the present invention, such as Figure 8 As shown, an embodiment of the present invention further provides an electronic device 800, which includes a processor 801, a memory 802, and a program stored in the memory and executable on the processor 801, and the processor 801 executes the above steps of the embodiment of the present invention.

[0165] Example 7

[0166] The embodiment of the present application also provides a computer program product. Optionally, in this embodiment, the computer program product may include a computer program, and when the computer program is executed by a processor, the method for adjusting the service system in the service transfer process of the embodiment of the present application is implemented.

[0167] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0168] The present invention also provides a computer program product, which, when executed on a data processing device, is suitable for the program of the above steps in the embodiment of the present invention.

[0169] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0170] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0171] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0173] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0174] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0175] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory media such as modulated data signals and carrier waves.

[0176] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0177] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0178] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for adjusting a business system during a business transfer process, characterized in that: include: In the process of transferring the aviation business object from the initial business system to the target business system, first log data and second log data corresponding to the aviation business are obtained, wherein the initial business system is a business system currently running, the target business system is a business system that will take over the operation of the initial business system in the future, the first log data is log data generated during the operation of the initial business system, and the second log data is log data generated during the operation of the target business system; Determining a similarity between the first log data and the second log data; Based on the similarity, an adjustment strategy is determined, and the initial business system and / or the target business system is adjusted according to the adjustment strategy, wherein the adjustment strategy is used to represent a rule for adjusting the initial business system and / or the target business system.

2. The adjustment method according to claim 1, characterized in that: The method is applied to a business transfer system, the business transfer system is connected to an elastic search engine, the elastic search engine is connected to the initial business system and the target business system, wherein obtaining the first log data and the second log data corresponding to the aviation business includes: Acquire, by the elastic search engine, the first initial log data of the initial business system and the second initial log data of the target business system at a target time interval; The first initial log data is cleaned to obtain the first log data, and the second initial log data is cleaned to obtain the second log data, wherein the accuracy of the first log data is higher than the accuracy of the first initial log data, and the accuracy of the second log data is higher than the accuracy of the second initial log data.

3. The adjustment method according to claim 2, characterized in that: The business transfer system includes a task scheduling tool, wherein before acquiring the first log data of the initial business system and the second log data of the target business system through the elastic search engine at a target time interval, the method further includes: Setting the acquisition task according to the target time interval by the task scheduling tool; Based on the acquisition path in the acquisition task, the first initial log data is acquired from the initial business system through the elastic search engine, and the second initial log data is acquired from the target business system.

4. The adjustment method according to claim 2, characterized in that: After acquiring the first log data and the second log data corresponding to the aviation service, the method further includes: Controlling the business transfer system to transmit the first log data and the second log data to an application operation and maintenance system database; Control the business transfer system to receive the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, wherein the adjusted first log data is obtained by the application operation and maintenance system database performing structured processing on the first log data, and the adjusted second log data is obtained by the application operation and maintenance system database performing structured processing on the second log data.

5. The adjustment method according to claim 4, characterized in that: Determining the similarity between the first log data and the second log data includes: In response to the business transfer system acquiring the adjusted first log data and the adjusted second log data from the application operation and maintenance system database, the adjusted first log data and the adjusted second log data are compared to obtain the similarity.

6. The adjustment method according to claim 5, characterized in that: Based on the similarity, an adjustment strategy is determined, including: In response to the similarity between the adjusted first log data and the adjusted second log data being less than or equal to a similarity threshold, determining that the aviation service transfer process is in an abnormal state; Based on the abnormal state, generating the corresponding adjustment strategy, wherein the adjustment strategy is a rule for adjusting the abnormal state to a normal state; The method further includes: in response to the similarity between the adjusted first log data and the adjusted second log data being less than or equal to the similarity threshold, generating prompt information, wherein the prompt information can be used to prompt the abnormal state.

7. The adjustment method according to claim 6, characterized in that: The method further comprises: In response to adjusting the initial business system and / or the target business system according to the adjustment strategy, collecting the first log data of the adjusted initial business system and / or the second log data of the adjusted target business system, and comparing the first log data with the second log data to obtain a comparison result; The comparison result and the similarity before adjusting the initial business system and / or the target business system according to the adjustment strategy are transmitted to a graphical user display interface associated with the business transfer system, wherein the comparison result and the similarity are rendered and displayed on the graphical user display interface.

8. A device for adjusting a business system during a business transfer process, characterized in that: include: an acquisition unit, configured to acquire first log data and second log data corresponding to the aviation service during the process of transferring the aviation service object from the initial service system to the target service system, wherein the initial service system is a service system currently running, the target service system is a service system that will take over the operation of the initial service system in the future, the first log data is log data generated during the operation of the initial service system, and the second log data is log data generated during the operation of the target service system; a determining unit, configured to determine a similarity between the first log data and the second log data; An adjustment unit is used to determine an adjustment strategy based on the similarity, and adjust the initial business system and / or the target business system according to the adjustment strategy, wherein the adjustment strategy is used to represent a rule for adjusting the initial business system and / or the target business system.

9. A processor, characterized in that: The processor is used to run a program, wherein the program, when run by the processor, executes the method for adjusting the business system during the business transfer process described in any one of claims 1 to 7.

10. An electronic device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the method for adjusting the business system during the business transfer process as described in any one of claims 1 to 7.

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