Method and device for adjusting integration strategy of data

Abstract

The invention discloses a method and a device for adjusting an integration strategy of data. The method comprises the steps that first log data corresponding to passenger order data and passenger check-in data in a to-be-integrated state in an integration system is acquired, and the first log data is at least used for representing key information in the passenger order data and key information in the passenger check-in data; according to an integration strategy, the passenger order data and the passenger check-in data are integrated, an integration result is obtained, second log data corresponding to the integration result and an integration state log are obtained, and the integration strategy is used for representing a rule for integrating the passenger order data and the passenger check-in data; determining an integration success rate based on the integration state log, the first log data and the second log data; and determining an adjustment strategy based on the integration success rate, and adjusting the integration strategy according to the adjustment strategy to obtain an adjustment result. The technical problem that the adjustment accuracy of the data integration strategy is low is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and device for adjusting a data integration strategy. Background Art

[0002] With the rapid development of the aviation industry, the amount of passenger order data and passenger check-in data has increased exponentially. In the related art, when the integration strategy of passenger order data and passenger check-in data needs to be adjusted, the integration strategy usually relies on specific field matching. However, in the actual integration process, there are anomalies or inconsistencies in the above fields, and it is difficult to identify the anomalies, which affects the accuracy of the integration strategy adjustment. Therefore, there is still a technical problem of low adjustment accuracy of the data integration strategy.

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

[0004] The embodiment of the present invention provides a method and device for adjusting a data integration strategy, so as to at least solve the technical problem of low adjustment accuracy of the data integration strategy.

[0005] According to one aspect of an embodiment of the present invention, a method for adjusting a data integration strategy is provided, and the method may include: obtaining first log data corresponding to passenger order data and passenger check-in data in a to-be-integrated state in an integration system, wherein the first log data is at least used to represent key information in the passenger order data and key information in the passenger check-in data; integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, and obtaining second log data corresponding to the integration result, and an integration status log, wherein the integration strategy is used to represent a rule for integrating the passenger order data and the passenger check-in data, the second log data is at least used to represent key information in the integration result, and the integration status log is used to represent whether the passenger order data and the passenger check-in data are successfully integrated or failed; determining an integration success rate based on the integration status log, the first log data and the second log data, wherein the integration success rate is used to represent the integration performance of the integration system; determining an adjustment strategy based on the integration success rate, and adjusting the integration strategy according to the adjustment strategy to obtain an adjustment result, wherein the adjustment strategy is used to represent a rule for adjusting the integration strategy.

[0006] Optionally, obtaining first log data corresponding to passenger order data and passenger check-in data in a state to be integrated in the integration system includes: in response to the integration system receiving passenger order data and passenger check-in data in a state to be integrated, identifying corresponding key information from the passenger order data and passenger check-in data respectively; filling the key information, passenger order data and passenger check-in data into a preset data structure to obtain the first log data; the method also includes: based on the first log data, determining at least a first unit data volume and a first peak flow, wherein the first unit data volume is used to represent the data volume of the passenger order data and passenger check-in data received within a unit time, and the first peak flow is used to represent the maximum data volume of the passenger order data and passenger check-in data received within a time interval.

[0007] Optionally, in response to the integration system receiving passenger order data and passenger check-in data in a state to be integrated, after identifying key information from the passenger order data and the passenger check-in data respectively, the method further includes: determining the association between the key information of the passenger order data and the key information of the passenger check-in data; integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, including: based on the association, integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result.

[0008] Optionally, according to the integration strategy, the passenger order data and the passenger check-in data are integrated to obtain an integration result, and the second log data corresponding to the integration result is obtained, including: identifying key information from the integration result, and filling the key information and the integration result into a preset data structure to obtain the second log data; the method also includes: based on the second log data, at least determining a second unit data volume and a second peak flow, wherein the second unit data volume is used to represent the data volume of the integration result integrated within a unit time, and the second peak flow is used to represent the maximum data volume of the integration result integrated within a time interval.

[0009] Optionally, according to the integration strategy, the passenger order data and the passenger check-in data are integrated to obtain the integration result and obtain the integration status log, including: in the process of integrating the passenger order data and the passenger check-in data according to the integration strategy, at least the key steps in the integration process are recorded; after the integration result is obtained, the integration status is recorded; the key steps and the integration status are filled into the preset data structure to obtain the integration status log.

[0010] Optionally, the integration success rate is determined based on the integration status log, the first log data and the second log data, including: determining a first integration result of successful integration and a second integration result of failed integration based on the integration status log, the first log data and the second log data; determining the integration success rate based on the first integration result and the second integration result.

[0011] Optionally, the method also includes: determining the integration performance data of the integration system based on the first unit data volume and the first peak flow of the first log data, and the second unit data volume and the second peak flow of the second log data, as well as the integration success rate, wherein the first unit data volume is used to represent the data volume of passenger order data and passenger check-in data received within a unit time, the first peak flow is used to represent the maximum data volume of passenger order data and passenger check-in data received within a time interval, the second unit data volume is used to represent the data volume of the integration result integrated within a unit time, and the second peak flow is used to represent the maximum data volume of the integration result integrated within the time interval.

[0012] Optionally, the method also includes: in response to the distributed file system receiving the integrated status log, the first log data and the second log data transmitted to the distributed file system, using the distributed file system, structuring the integrated status log, the first log data and the second log data, and saving the structured integrated status log, the first log data and the second log data in the target data table.

[0013] Optionally, based on the integration success rate, an adjustment strategy is determined, including: in response to the integration success rate being lower than an integration success rate threshold, and the integration performance data of the integrated system being lower than the integration performance threshold, based on the target data table, an adjustment strategy is determined; and the integration strategy is adjusted according to the adjustment strategy to obtain an adjustment result so that the integration success rate is greater than or equal to the integration success rate threshold, and the integration performance data is greater than or equal to the integration performance threshold.

[0014] According to another aspect of an embodiment of the present invention, there is also provided a device for adjusting a data integration strategy, comprising: a first acquisition unit, for acquiring first log data corresponding to passenger order data and passenger check-in data in a to-be-integrated state in an integration system, wherein the first log data is at least used to represent key information in the passenger order data and key information in the passenger check-in data; a second acquisition unit, for integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, and acquiring second log data corresponding to the integration result, and an integration status log, wherein the integration strategy is used to represent a rule for integrating the passenger order data and the passenger check-in data, the second log data is at least used to represent key information in the integration result, and the integration status log is used to represent whether the passenger order data and the passenger check-in data are successfully integrated or failed; a determination unit, for determining an integration success rate based on the integration status log, the first log data and the second log data, wherein the integration success rate is used to represent the integration performance of the integration system; an adjustment unit, for determining an adjustment strategy based on the integration success rate, and adjusting the integration strategy according to the adjustment strategy to obtain an adjustment result, wherein the adjustment strategy is used to represent a rule for adjusting the integration strategy.

[0015] 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 data integration strategy.

[0016] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, including 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 data integration strategy.

[0017] 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 data integration strategy of the embodiment of the present application is implemented.

[0018] In an embodiment of the present invention, if it is necessary to adjust the integration strategy, the first log data corresponding to the passenger order data and the passenger check-in data in the integration system that are in a state to be integrated can be obtained; the passenger order data and the passenger check-in data can be integrated according to the integration strategy to obtain the integration result, and the second log data corresponding to the integration result and the integration status log can be obtained; the integration success rate can be determined based on the integration status log, the first log data and the second log data; the adjustment strategy can be determined based on the integration success rate, and the integration strategy can be adjusted according to the adjustment strategy to obtain the adjustment result. In an embodiment of the present invention, by acquiring key information (corresponding to the first log data) in the process of integrating passenger order data and passenger check-in data, the integration system can monitor and record the status of the passenger order data and passenger check-in data before integration in real time, and after integrating the passenger order data and the passenger check-in data, obtain the key information in the integration result (corresponding to the second log data) and the integration result of the passenger order data and the passenger check-in data (corresponding to the integration status log), thereby obtaining the integration performance of the integration system, and adjusting the integration strategy according to the adjustment strategy. The integration system can discover problems in time and dynamically adjust the integration strategy, thereby achieving the technical effect of improving the adjustment accuracy of the data integration strategy and solving the technical problem of low adjustment accuracy of the data integration strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] 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:

[0020] Figure 1 is a flow chart of a method for adjusting a data integration strategy according to an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of a data quality monitoring and analysis system based on a unified recording standard real-time integration system according to an embodiment of the present invention;

[0022] Figure 3 is a structural schematic diagram of a device for adjusting a data integration strategy according to an embodiment of the present invention;

[0023] Figure 4 is a schematic diagram of an electronic device for a method for adjusting a data integration strategy according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] Example 1

[0027] According to an embodiment of the present invention, an embodiment of a method for adjusting a data integration strategy 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.

[0028] Figure 1 is a flow chart of a method for adjusting a data integration strategy according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0029] Step S102, obtaining first log data corresponding to the passenger order data and the passenger check-in data in a state to be integrated in the integration system.

[0030] In the technical solution provided in the above step S102 of the embodiment of the present invention, the first log data corresponding to the passenger order (Passenger Name Record, referred to as PNR) data and the passenger check-in data in the integration system in a state to be integrated can be obtained. The first log data can at least be used to represent the key information in the passenger order data and the key information in the passenger check-in data, such as the passenger identity (Identification, referred to as ID), flight number, departure date, airline code, ticket number, document information, etc. The passenger order data can be civil aviation passenger order data. The passenger check-in (Check In, referred to as CKI) data can be civil aviation passenger check-in data. The integration system can be a unified passenger service (Integrate Record Service, referred to as IRS) system, which is a real-time integration system based on the unified record standard (One Record Standard, referred to as ORS).

[0031] Optionally, the first log data may include not only PNR data and CKI data, but also additional information such as the timestamp, data source identifier, initial status, etc. of the IRS system receiving the PNR data and CKI data, so as to ensure the comprehensiveness and traceability of the first log data.

[0032] It should be noted that the specific information of the first log data is only for illustration and is not specifically limited here. As long as it can be used to reflect the key information in the passenger order data and the passenger check-in data, it is within the protection scope of the embodiment of the present invention.

[0033] Optionally, when the IRS system receives the PNR data and the CKI data, it can identify and extract key information from the PNR data and the CKI data, and obtain the first log data by processing the extracted key information.

[0034] For example, when the IRS system receives PNR data and CKI data, it can identify and extract key fields in the PNR and CKI data, such as passenger ID, flight number, ticket number, etc., and sort the extracted key information according to predetermined sorting rules (for example, it can be sorted in ascending order by passenger ID, or sorted by a combination of flight number and departure date). The sorted key information will be easier to match and integrate.

[0035] It should be noted that the specific information of the first log data is only for illustration and is not specifically limited here. As long as it can be used to reflect the key information in the passenger order data and the passenger check-in data, it is within the protection scope of the embodiment of the present invention.

[0036] Step S104: Integrate the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, and obtain the second log data corresponding to the integration result and the integration status log.

[0037] In the technical solution provided in the above step S104 of the embodiment of the present invention, after obtaining the first log data corresponding to the passenger order data and the passenger check-in data in the integration system in the state to be integrated, the passenger order data and the passenger check-in data can be integrated according to the integration strategy to obtain the integration result. After the integration of the passenger order data and the passenger check-in data is completed, the second log data corresponding to the integration result and the integration status log can be obtained. The integration strategy can be used to represent the rules for integrating the passenger order data and the passenger check-in data. Since the ORS standard can pre-define a series of fields, the corresponding values ​​are found from the passenger order data and the passenger check-in data, and combined together according to a specific format, such as JavaScript Object Notation (JSON) format, to form the integrated data. Then the second log data can at least be used to represent the key information in the integration result. For example, the passenger flight number field, the passenger ID field, etc. The integration status log can be used to indicate whether the passenger order data and the passenger check-in data are successfully integrated or failed. For example, the integration status can include the integration success status, the integration failure status, the integration partial success status, etc.

[0038] Optionally, the integration strategy may include, but is not limited to, matching based on key fields such as the passenger's ID information, ticket number, flight number, and rules for handling abnormal situations such as missing PNR data and CKI data, and mismatched PNR data and CKI data formats. This is only an example and is not specifically limited here. The integration status log can record the results and status of successful or failed integration.

[0039] Step S106: Determine the integration success rate based on the integration status log, the first log data, and the second log data.

[0040] In the technical solution provided in the above step S106 of the embodiment of the present invention, after the passenger order data and the passenger check-in data are integrated according to the integration strategy to obtain the integration result, the second log data corresponding to the integration result, and the integration status log are obtained, the integration success rate can be determined based on the integration status log, the first log data, and the second log data. The integration success rate can be used to indicate the integration performance of the integration system, which can be the percentage of success or failure of the integration data.

[0041] In this embodiment, the integration status log can be analyzed to determine the results of the integration of PNR data and CKI data. The integration status log can record the final status of the integration of each PNR data and CKI data, including success, failure or partial success, and the specific reason for the failure. The first log data (recording the status information of the PNR data and CKI data before integration) and the second log data (recording the key information of the integration result) can be compared to specifically analyze which PNR and CKI data are successfully integrated, which are not integrated, and the reasons for the integration failure.

[0042] Optionally, by determining the integration success rate, the integration strategy can be adjusted in a targeted manner to optimize the PNR data and CKI data processing flow, such as improving the PNR data and CKI data matching rules, enhancing the PNR data and CKI data preprocessing mechanism, etc., to improve the accuracy of the PNR data and CKI data integration.

[0043] For example, the integration status log can be used to count the number of PNR data and CKI data that are successfully integrated within a time period, that is, the amount of data that is successfully integrated, and the total amount of the first log data recorded within a specific time period (such as within an hour or a day), that is, the total amount of PNR data and CKI data to be integrated, can be counted. The integration success rate can be determined by the ratio of the amount of data that is successfully integrated to the total amount of PNR data and CKI data to be integrated.

[0044] Step S108, determining an adjustment strategy based on the integration success rate, and adjusting the integration strategy according to the adjustment strategy to obtain an adjustment result.

[0045] In the technical solution provided in the above step S108 of the embodiment of the present invention, after determining the integration success rate based on the integration status log, the first log data and the second log data, an adjustment strategy can be determined based on the integration success rate, and the integration strategy can be adjusted according to the adjustment strategy to obtain an adjustment result. The adjustment strategy can be used to represent a rule for adjusting the integration strategy.

[0046] In this embodiment, by determining the adjustment strategy based on the integration success rate and continuously iterating and optimizing the integration strategy, the IRS system can better adapt to the complex needs of PNR data and CKI data integration and improve the efficiency and accuracy of PNR data and CKI data integration.

[0047] Optionally, the adjustment strategy can be adjusted by optimizing data matching rules, enhancing data preprocessing, or adjusting by exception processing, etc., to obtain the adjustment result, which is only for example and is not specifically limited here. As long as it is a method that can improve the success rate of data integration, it is within the protection scope of the embodiments of the present invention.

[0048] In steps S102 to S108 of the embodiment of the present invention, if the integration strategy needs to be adjusted, the first log data corresponding to the passenger order data and the passenger check-in data in the integration system that are in a state to be integrated can be obtained; the passenger order data and the passenger check-in data can be integrated according to the integration strategy to obtain the integration result, and the second log data corresponding to the integration result and the integration status log can be obtained; the integration success rate can be determined based on the integration status log, the first log data and the second log data; the adjustment strategy can be determined based on the integration success rate, and the integration strategy can be adjusted according to the adjustment strategy to obtain the adjustment result. In an embodiment of the present invention, by acquiring key information (corresponding to the first log data) in the process of integrating passenger order data and passenger check-in data, the integration system can monitor and record the status of the passenger order data and passenger check-in data before integration in real time, and after integrating the passenger order data and the passenger check-in data, obtain the key information in the integration result (corresponding to the second log data) and the integration result of the passenger order data and the passenger check-in data (corresponding to the integration status log), thereby obtaining the integration performance of the integration system, and adjusting the integration strategy according to the adjustment strategy. The integration system can discover problems in time and dynamically adjust the integration strategy, thereby achieving the technical effect of improving the adjustment accuracy of the data integration strategy and solving the technical problem of low adjustment accuracy of the data integration strategy.

[0049] The embodiment of the present invention is described in detail below in combination with the above steps.

[0050] As an optional embodiment, step S102, obtaining the first log data corresponding to the passenger order data and passenger check-in data in the integration system that are in a state to be integrated, includes: in response to the integration system receiving the passenger order data and passenger check-in data in a state to be integrated, identifying corresponding key information from the passenger order data and the passenger check-in data respectively; filling the key information, the passenger order data and the passenger check-in data into a preset data structure to obtain the first log data; the method also includes: based on the first log data, determining at least a first unit data volume and a first peak flow, wherein the first unit data volume is used to represent the data volume of the passenger order data and the passenger check-in data received within a unit time, and the first peak flow is used to represent the maximum data volume of the passenger order data and the passenger check-in data received within a time interval.

[0051] In this embodiment, in the process of obtaining the first log data corresponding to the passenger order data and the passenger check-in data in the state to be integrated in the integration system, when the integration system receives the passenger order data and the passenger check-in data in the state to be integrated, the corresponding key information can be identified from the passenger order data and the passenger check-in data respectively; the key information, the passenger order data and the passenger check-in data can be filled into the preset data structure to obtain the first log data. Based on the first log data, at least the first unit data volume and the first peak flow can be determined. Among them, the first unit data volume can be used to represent the data volume of the passenger order data and the passenger check-in data received in a unit time, and the first peak flow can be used to represent the maximum data volume of the passenger order data and the passenger check-in data received in a time interval.

[0052] Optionally, the first unit data volume can be calculated according to different time intervals (such as every minute, every hour) to evaluate the throughput of PNR data and CKI data of the I RS system, and to identify the peak and trough periods of PNR data and CKI data reception. The first peak traffic volume can determine the peak capacity of the I RS system to process PNR data and CKI data by counting the maximum values ​​of the PNR data and CKI data reception volume in different time intervals. The first unit data volume and the first peak traffic volume can provide a basis for performance evaluation, extended maintenance and resource planning of the I RS system. For example, if it is detected that the reception volume of PNR data and CKI data in certain time periods far exceeds the average value, adjustments can be made in combination with the first peak traffic volume analysis to cope with high traffic shocks and improve the stability of the I RS system.

[0053] As an optional embodiment, in response to the integration system receiving passenger order data and passenger check-in data in a state to be integrated, after identifying key information from the passenger order data and the passenger check-in data respectively, the method further includes: determining the key information of the passenger order data, and the association relationship between the key information of the passenger check-in data; step S104, integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, including: based on the association relationship, integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result.

[0054] In this embodiment, after the integration system receives passenger order data and passenger check-in data in a state to be integrated and identifies key information from the passenger order data and the passenger check-in data respectively, the key information of the passenger order data and the association between the key information of the passenger check-in data can be determined; in the process of integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain the integration result, the passenger order data and the passenger check-in data can be integrated according to the integration strategy based on the association to obtain the integration result.

[0055] Optionally, by comparing and matching key fields in PNR data and CKI data, such as the passenger's ID number, name, flight number, date, etc., it is possible to determine whether the data records belong to the same passenger, and to check whether the PNR data contains the ticket number information of the electronic ticket (ET). The ET number is an important link between PNR data and ET data, which can ensure that the information of the passenger's order data and the electronic ticket information can be correctly associated. The status information in the CKI data can be identified, such as whether check-in has been completed, baggage information, seat information, etc., to ensure that the latest check-in status is used during integration, so that the successfully matched PNR data and CKI data can be integrated through the integration strategy.

[0056] As an optional embodiment, step S104 integrates the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, and obtains the second log data corresponding to the integration result, including: identifying key information from the integration result, and filling the key information and the integration result into a preset data structure to obtain the second log data; the method also includes: based on the second log data, at least determining a second unit data volume and a second peak flow, wherein the second unit data volume is used to represent the data volume of the integration result integrated per unit time, and the second peak flow is used to represent the maximum data volume of the integration result integrated within a time interval.

[0057] In this embodiment, the passenger order data and the passenger check-in data can be integrated according to the integration strategy to obtain the integration result, and the second log data corresponding to the integration result can be obtained. Key information can be identified from the integration result, and the key information and the integration result can be filled into the preset data structure to obtain the second log data. Based on the second log data, at least the second unit data volume and the second peak flow can be determined. The second unit data volume can be used to represent the data volume of the integration result integrated within a unit time, and the second peak flow can be used to represent the maximum data volume of the integration result integrated within a time interval.

[0058] Optionally, after the IRS system completes the integration of PNR data and CKI data, key information can be identified from the integration result, and the integration result and its key information can be filled into a pre-designed data structure. The above information may include the integrated passenger ID, flight information, integration time, integration status (integration success status or integration failure status), integration result message, etc., for subsequent analysis of the efficiency and quality of the integration process.

[0059] Optionally, the preset data structure is usually a standardized format that is easy to store and process, such as a JSON format, which can ensure the integrity and consistency of the PNR data and the CKI data.

[0060] Optionally, in order to evaluate the data volume of the integration results per unit time, the second log data can be statistically analyzed to determine the data volume of the integration results integrated per unit time and the maximum data volume of the integration results integrated within the time interval. This can help understand the performance limits of the integration process and provide a basis for resource planning and performance optimization.

[0061] As an optional embodiment, step S104 integrates the passenger order data and the passenger check-in data according to the integration strategy, obtains the integration result, and obtains the integration status log, including: in the process of integrating the passenger order data and the passenger check-in data according to the integration strategy, at least the key steps in the integration process are recorded; after the integration result is obtained, the integration status is recorded; the key steps and the integration status are filled into the preset data structure to obtain the integration status log.

[0062] In this embodiment, the passenger order data and the passenger check-in data can be integrated according to the integration strategy to obtain the integration result and the integration status log. In the process of integrating the passenger order data and the passenger check-in data according to the integration strategy, at least the key steps in the integration process can be recorded; after the integration result is obtained, the integration status can be recorded; the key steps and the integration status can be filled into a preset data structure to obtain an integration status log.

[0063] Optionally, according to the pre-designed integration strategy, the key steps or information in the integration process can be recorded. The status of the integration result can be recorded, including whether the integration is successful, the failure reason code (if failed), the ID of the integration result data, the integration completion time and other information. According to the pre-designed data structure, the key steps and integration status can be written into the data stream of the open source distributed stream processing engine Apache Flink, and can be saved to the Hadoop distributed file system (Hadoop Distributed File System, referred to as HDFS) through the storage function in the Flink framework. Hadoop is an open source distributed computing framework that can process large-scale data sets.

[0064] As an optional embodiment, step S106 determines the integration success rate based on the integration status log, the first log data and the second log data, including: determining a first integration result of successful integration and a second integration result of failed integration based on the integration status log, the first log data and the second log data; determining the integration success rate based on the first integration result and the second integration result.

[0065] In this embodiment, in the process of determining the integration success rate based on the integration status log, the first log data and the second log data, the first integration result of successful integration and the second integration result of failed integration can be determined based on the integration status log, the first log data and the second log data; the integration success rate can be determined based on the first integration result and the second integration result.

[0066] Optionally, the integration success rate can be determined by counting the percentages of successful and failed integrations. A high integration success rate indicates that the data processing and integration functions of the I RS system are operating well, the data quality is high, and it can provide accurate passenger service information. A low integration success rate may indicate that the I RS system has data processing problems, data quality problems, or deficiencies in the integration strategy, and the I RS system needs further analysis and optimization.

[0067] As an optional embodiment, the method also includes: determining the integration performance data of the integration system based on the first unit data volume and the first peak flow of the first log data, and the second unit data volume and the second peak flow of the second log data, as well as the integration success rate, wherein the first unit data volume is used to represent the data volume of the passenger order data and the passenger check-in data received within a unit time, the first peak flow is used to represent the maximum data volume of the passenger order data and the passenger check-in data received within a time interval, the second unit data volume is used to represent the data volume of the integration result integrated within a unit time, and the second peak flow is used to represent the maximum data volume of the integration result integrated within a time interval.

[0068] In this embodiment, the integration performance data of the integration system can be determined based on the first unit data volume and the first peak flow of the first log data, the second unit data volume and the second peak flow of the second log data, and the integration success rate. The first unit data volume can be used to represent the data volume of the passenger order data and the passenger check-in data received per unit time, the first peak flow can be used to represent the maximum data volume of the passenger order data and the passenger check-in data received within a time interval, the second unit data volume can be used to represent the data volume of the integration result integrated within a unit time, and the second peak flow can be used to represent the maximum data volume of the integration result integrated within a time interval.

[0069] Optionally, the integrated performance data of the integrated system may include the above-mentioned traffic indicators such as the first unit data volume, the first peak flow rate, the second unit data volume, the second peak flow rate, and the integration success rate, and may also include other key performance indicators such as the average response time, data processing delay, and system resource utilization rate. By comprehensively analyzing the first unit data volume, the first peak flow rate, the second unit data volume, the second peak flow rate, and the integration success rate, a more comprehensive integrated system performance evaluation result may be obtained.

[0070] As an optional embodiment, the method also includes: in response to the distributed file system receiving the integrated status log, the first log data and the second log data being transmitted to the distributed file system, using the distributed file system to structure the integrated status log, the first log data and the second log data, and saving the structured integrated status log, the first log data and the second log data in a target data table.

[0071] In this embodiment, the integrated state log, the first log data, and the second log data can be transmitted to a distributed file system; the integrated state log, the first log data, and the second log data can be structured using the distributed file system, and the structured integrated state log, the first log data, and the second log data can be stored in a target data table. The target data table can be an HBase data table, which is a distributed, column-oriented, non-relational structured query language (NoSQL) database that can store a large amount of structured data.

[0072] Optionally, the distributed file system may be HDFS, and various data generated and stored in the HDFS may be structured and then saved in a HBase data table in a multi-version form.

[0073] As an optional embodiment, step S108, based on the integration success rate, determines an adjustment strategy, including: in response to the integration success rate being lower than the integration success rate threshold, and the integration performance data of the integrated system being lower than the integration performance threshold, determining an adjustment strategy based on the target data table; adjusting the integration strategy according to the adjustment strategy to obtain an adjustment result, so that the integration success rate is greater than or equal to the integration success rate threshold, and the integration performance data is greater than or equal to the integration performance threshold.

[0074] In this embodiment, in the process of determining the adjustment strategy based on the integration success rate, the adjustment strategy can be determined based on the target data table when the integration success rate is lower than the integration success rate threshold and the integration performance data of the integrated system is lower than the integration performance threshold. In the process of adjusting the integration strategy according to the adjustment strategy, the integration strategy can be adjusted according to the adjustment strategy to obtain an adjustment result so that the integration success rate is greater than or equal to the integration success rate threshold and the integration performance data is greater than or equal to the integration performance threshold.

[0075] Optionally, when the monitored integration success rate is lower than the integration success rate threshold, and the integration performance data of the integrated system is lower than the integration performance threshold, it indicates that there are obvious problems with the performance and data quality of the I RS system, and immediate measures need to be taken to adjust and optimize. The integration success rate threshold can be set based on the target performance indicators and business requirements of the I RS system. For example, the integration success rate threshold can be set to 95%. This is only an example and is not specifically limited here. The integration performance threshold can be set comprehensively by numerical values ​​such as the maximum amount of data processed per unit time and the average response time. This is only an example and is not specifically limited here.

[0076] Optionally, using the data warehouse tool HIVE or other data warehouse tools, you can query and analyze the target data table in HDFS to understand the specific reasons for the integration failure and performance bottlenecks. The target data table can include the integration status log, the first log data, the second log data, etc., which record detailed information during the integration process. Through statistical analysis, the main factors leading to low success rate and poor performance can be identified.

[0077] In an embodiment of the present invention, if it is necessary to adjust the integration strategy, the first log data corresponding to the passenger order data and the passenger check-in data in the integration system that are in a state to be integrated can be obtained; the passenger order data and the passenger check-in data can be integrated according to the integration strategy to obtain the integration result, and the second log data corresponding to the integration result and the integration status log can be obtained; the integration success rate can be determined based on the integration status log, the first log data and the second log data; the adjustment strategy can be determined based on the integration success rate, and the integration strategy can be adjusted according to the adjustment strategy to obtain the adjustment result. In an embodiment of the present invention, by acquiring key information (corresponding to the first log data) in the process of integrating passenger order data and passenger check-in data, the integration system can monitor and record the status of the passenger order data and passenger check-in data before integration in real time, and after integrating the passenger order data and the passenger check-in data, obtain the key information in the integration result (corresponding to the second log data) and the integration result of the passenger order data and the passenger check-in data (corresponding to the integration status log), thereby obtaining the integration performance of the integration system, and adjusting the integration strategy according to the adjustment strategy. The integration system can discover problems in time and dynamically adjust the integration strategy, thereby achieving the technical effect of improving the adjustment accuracy of the data integration strategy and solving the technical problem of low adjustment accuracy of the data integration strategy.

[0078] Example 2

[0079] Another optional specific implementation is described in detail below.

[0080] At present, the data volume of civil aviation passenger order data and civil aviation passenger check-in data, which are the data sources of the integration system, cannot be counted. Therefore, it is impossible to accurately know the amount of data received by the system per unit time, and it is impossible to calculate the peak traffic, making it difficult to continuously optimize the system performance. The data volume of ORS data, which is the output result of the integration system, cannot be counted. Therefore, it is impossible to accurately calculate the amount of integrated data generated and output in a certain period of time, resulting in a lack of reference indicators for downstream users when designing their system architecture. When integrating data from different sources, the integration process may fail due to lack of key information, non-standard data format, program abnormalities, etc. Therefore, there are still problems with low quality and low accuracy of integrated data.

[0081] The embodiment of the present invention proposes a data quality monitoring and analysis system based on the IRS system. By pre-embedding logs in the IRS system, cooperating with the open source distributed stream processing engine Flink, HDFS components and data warehouse tools (HIVE), it can completely monitor various abnormal events in the integration process, perform statistical analysis on different types of data volumes, calculate the data integration success rate, and accurately locate and query the problematic data. The above statistical data and query analysis functions also help to further improve the performance and stability of the unified passenger service system, thereby achieving the technical effect of improving the adjustment accuracy of the data integration strategy and solving the technical problem of low adjustment accuracy of the data integration strategy.

[0082] The method is further described below.

[0083] A data quality monitoring and analysis system based on an ORS data standard real-time integration system according to an embodiment of the present invention is used for performance evaluation and expansion maintenance of an ORS system during the production process, and provides data support and evaluation basis for the architecture design and function implementation of downstream user software systems. Figure 2 is a schematic diagram of a data quality monitoring and analysis system based on a unified recording standard real-time integration system according to an embodiment of the present invention. Figure 2 As shown, the data quality monitoring and analysis system 200 includes:

[0084] The passenger data access module 201 is used to access different passenger data, and the passenger data may include PNR data and CKI data.

[0085] Passenger data integration module 202: Passenger data access module 201 sends passenger data to passenger data integration module 202, and passenger data integration module 202 can integrate data storage and transmission, such as real-time and daily data push, user query service.

[0086] The data source input log and statistics module 203 can synchronously save these data and their key information (such as ID value, time, airline, original message, etc.) to HDFS according to the specified data structure when the I RS system accesses the data source of passenger order data and passenger check-in data, and then use the script program to perform statistical analysis on the data according to different rules (time period, airline, etc.) (for example, counting the amount of data received per unit time, calculating peak traffic, etc.).

[0087] Optionally, when the IRS system receives and processes passenger order data and passenger check-in data, the data source input log and statistics module 203 can use the data stream processing mechanism of Apache Flink to convert the above data and its key information (such as ID value, time, airline, original message, etc.) into a specified data structure, and save it to the path specified by HDFS through the storage mechanism of Flink data stream. When performing statistical analysis, the data stored in the HDFS path can be structured and stored in the specified HIVE data table by using SQL. A script program can be used to perform statistics and analysis on the data in the data table. For example, data analysis can be performed according to dimensions such as different time intervals, airlines, or departure airports for use by developers or designers.

[0088] The integrated status log and statistics module 204 is the core part of the IRS system 200. The main functions are concentrated in the passenger data integration module 202, including the integrated log recording function, the integrated log storage function and the integrated log statistical analysis function.

[0089] In this embodiment, the key steps or information in the integration process can be recorded in the passenger data integration module 202 through logs according to pre-designed rules, and the final state of the data integration (e.g., integration success, failure, partial success, etc.) can be recorded according to the rules. If the integration is unsuccessful, the relevant reasons are recorded simultaneously. Table 1 is a comparison table of integration failure codes and reasons according to an embodiment of the present invention. As shown in Table 1, the integration failure reason codes and failure reasons are shown.

[0090] In this embodiment, the Flink data stream processing function can be used to convert the logs and integration status recorded in the previous step into corresponding data structures, and save them to the path specified by HDFS through the storage function in the Flink framework.

[0091] In this embodiment, the integrated log data stored in the HDFS path can be structured and stored in a specified HIVE data table through the SQL language, and then the data in the data table can be counted and analyzed using a script program. It mainly helps developers to classify the types of reasons for integration failure, analyze the situations and scenarios with high failure rates, and solve them in a targeted manner. And compare the data before and after the solution to evaluate the effect of the solution. In addition, through the program script, the amount of data integrated per unit time can be statistically analyzed, so as to calculate the unit time or peak processing speed, evaluate the program execution efficiency, analyze the system performance bottleneck, and evaluate the system optimization plan.

[0092] Table 1 Integration failure codes and reasons comparison table

[0093]

[0094] The integration result output log and statistics module 205 is used to associate and integrate the passenger order data and passenger check-in data according to predetermined rules and conditions (such as passenger ID number, ticket number, flight number and other key fields) in the I RS system, and then save the integrated result data and its key information (such as ID value, time, airline, complete integration result message, etc.) into HDFS according to a pre-designed data structure, and then use the script program to perform statistical analysis on the data according to different rules (time period, airline, etc.) (for example, statistics on the amount of integration result data sent per unit time and peak traffic, etc.).

[0095] In this embodiment, the processing flow of the integration result output log and statistics module 205 is similar to that of the data source input log and statistics module 203. After the IRS system associates and integrates the passenger order data and the passenger check-in data according to predetermined rules and conditions (such as passenger ID number, ticket number, flight number and other key fields), the result data and key information (such as ID value, time, airline, complete integration result message, etc.) can be converted into a specified data structure, and saved to the path specified by HDFS through the storage mechanism of the Flink data stream. When analysis and statistics are required, the integration result data stored in the HDFS path can be structured and stored in the specified HIVE data table through the SQL language, and the data in the data table can be subsequently counted and analyzed using a script program. For example, data analysis can also be performed according to dimensions such as different time intervals, airlines or departure airports for use by IRS system developers and downstream data receivers.

[0096] The data precise positioning and searching module 206 is used to periodically perform structured processing on the above-mentioned data stored in HDFS through the SQL language and save it to the specified HBase data table. Afterwards, if necessary, developers can use the HIVE statistical query tool to execute SQL scripts to search different data tables to obtain the required specific data information. For example, in the case of integration failure, the original message data of passenger orders and passenger check-in can be precisely located and searched in the massive data based on the ID value, date and other information, and the reasons can be analyzed by viewing the specific content of the message, so as to further improve the unit test case.

[0097] In the embodiment of the present invention, through the collaborative work of the passenger data access module 201, the passenger data integration module 202, the data source input log and statistics module 203, the integration status log and statistics module 204, the integration result output log and statistics module 205 and the data precise positioning and search module 206, the data quality monitoring and analysis system 200 can comprehensively and real-time monitor and analyze the data integration quality of the IRS system, not only providing statistical indicators such as data volume and integration success rate, but also ensuring that specific data samples can be quickly located when problems arise, and the data integration strategy can be accurately adjusted, thereby achieving the technical effect of improving the adjustment accuracy of the data integration strategy and solving the technical problem of low adjustment accuracy of the data integration strategy.

[0098] Example 3

[0099] The embodiment of the present invention provides a data integration strategy adjustment device. It should be noted that the data integration strategy adjustment device of the embodiment of the present invention can be used to execute Figure 1 The following is an introduction to the method for adjusting the data integration strategy provided by the embodiment of the present invention.

[0100] Figure 3 is a schematic diagram of a device for adjusting a data integration strategy according to an embodiment of the present invention. Figure 3 As shown, the device 300 for adjusting the data integration strategy may include: a first acquisition unit 302 , a second acquisition unit 304 , a determination unit 306 and an adjustment unit 308 .

[0101] The first acquisition unit 302 is used to acquire first log data corresponding to the passenger order data and the passenger check-in data in the integration system that are in a state to be integrated, wherein the first log data is used to at least represent key information in the passenger order data and key information in the passenger check-in data.

[0102] The second acquisition unit 304 is used to integrate the passenger order data and the passenger check-in data according to the integration strategy, obtain the integration result, and obtain the second log data corresponding to the integration result, as well as the integration status log, wherein the integration strategy is used to represent the rules for integrating the passenger order data and the passenger check-in data, the second log data is used to represent at least the key information in the integration result, and the integration status log is used to indicate whether the integration of the passenger order data and the passenger check-in data is successful or unsuccessful.

[0103] The determination unit 306 is configured to determine an integration success rate based on the integration status log, the first log data, and the second log data, wherein the integration success rate is used to represent the integration performance of the integration system.

[0104] The adjustment unit 308 is used to determine an adjustment strategy based on the integration success rate, and adjust the integration strategy according to the adjustment strategy to obtain an adjustment result, wherein the adjustment strategy is used to represent a rule for adjusting the integration strategy.

[0105] The device for adjusting the data integration strategy provided by the embodiment of the present invention obtains the first log data corresponding to the passenger order data and the passenger check-in data in the integration system in the state to be integrated through the first acquisition unit 302, wherein the first log data is at least used to represent the key information in the passenger order data and the key information in the passenger check-in data; the second acquisition unit 304 integrates the passenger order data and the passenger check-in data according to the integration strategy to obtain the integration result, and obtains the second log data corresponding to the integration result, and the integration status log, wherein the integration strategy is used to represent the rules for integrating the passenger order data and the passenger check-in data, the second log data is at least used to represent the key information in the integration result, and the integration status log is used to represent the success or failure of the integration of the passenger order data and the passenger check-in data; the determination unit 306 determines the integration success rate based on the integration status log, the first log data and the second log data, wherein the integration success rate is used to represent the integration performance of the integration system; the adjustment unit 308 determines the adjustment strategy based on the integration success rate, and adjusts the integration strategy according to the adjustment strategy to obtain the adjustment result, wherein the adjustment strategy is used to represent the rules for adjusting the integration strategy. Thereby, the technical effect of improving the adjustment accuracy of the data integration strategy is achieved, and the technical problem of low adjustment accuracy of the data integration strategy is solved.

[0106] The device for adjusting the data integration strategy may further include a processor and a memory. The above units are stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] Example 4

[0112] 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, the method for adjusting the data integration strategy is implemented.

[0113] Example 5

[0114] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein the method for adjusting the data integration strategy is executed when the program is running.

[0115] Example 6

[0116] Figure 4 is a schematic diagram of an electronic device for adjusting a data integration strategy according to an embodiment of the present invention, such as Figure 4 As shown, an embodiment of the present invention further provides an electronic device 400, which includes a processor 401, a memory 402, and a program stored in the memory and executable on the processor 401, and the processor 401 executes the above steps of the embodiment of the present invention.

[0117] Example 7

[0118] The embodiment of the present application further provides a computer program product. Optionally, in the present 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 data integration strategy of the embodiment of the present application is implemented.

[0119] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0125] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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 data integration strategy, characterized in that: include: Acquire first log data corresponding to the passenger order data and the passenger check-in data in a state to be integrated in the integration system, wherein the first log data is used to at least represent key information in the passenger order data and key information in the passenger check-in data; Integrate the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, and obtain second log data corresponding to the integration result and an integration status log, wherein the integration strategy is used to indicate a rule for integrating the passenger order data and the passenger check-in data, the second log data is used to indicate at least key information in the integration result, and the integration status log is used to indicate whether the passenger order data and the passenger check-in data are integrated successfully or failed; Determine an integration success rate based on the integration status log, the first log data, and the second log data, wherein the integration success rate is used to represent the integration performance of the integration system; Based on the integration success rate, an adjustment strategy is determined, and the integration strategy is adjusted according to the adjustment strategy to obtain an adjustment result, wherein the adjustment strategy is used to represent a rule for adjusting the integration strategy.

2. The adjustment method according to claim 1, characterized in that: Acquiring first log data corresponding to passenger order data and passenger check-in data in a state to be integrated in the integration system, including: In response to the integration system receiving the passenger order data and the passenger check-in data in the to-be-integrated state, identifying the corresponding key information from the passenger order data and the passenger check-in data respectively; Filling the key information, the passenger order data and the passenger check-in data into a preset data structure to obtain the first log data; The method also includes: based on the first log data, determining at least a first unit data volume and a first peak flow, wherein the first unit data volume is used to represent the data volume of the passenger order data and the passenger check-in data received within a unit time, and the first peak flow is used to represent the maximum data volume of the passenger order data and the passenger check-in data received within a time interval.

3. The adjustment method according to claim 2, characterized in that: In response to the integration system receiving the passenger order data and the passenger check-in data in the to-be-integrated state, after identifying the key information from the passenger order data and the passenger check-in data respectively, the method further includes: Determining an association relationship between the key information of the passenger order data and the key information of the passenger check-in data; Integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, including: based on the association relationship, integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain the integration result.

4. The adjustment method according to claim 3, characterized in that: Integrating the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result, and acquiring second log data corresponding to the integration result, including: Identifying the key information from the integration result, and filling the key information and the integration result into the preset data structure to obtain the second log data; The method also includes: based on the second log data, determining at least a second unit data volume and a second peak flow, wherein the second unit data volume is used to represent the data volume of the integration result integrated within the unit time, and the second peak flow is used to represent the maximum data volume of the integration result integrated within the time interval.

5. The adjustment method according to claim 3, characterized in that: Integrate the passenger order data and the passenger check-in data according to the integration strategy to obtain an integration result and obtain an integration status log, including: In the process of integrating the passenger order data and the passenger check-in data according to the integration strategy, at least key steps in the integration process are recorded; After the integration result is obtained through integration, the integration status is recorded; The key steps and the integration status are filled into the preset data structure to obtain the integration status log.

6. The adjustment method according to claim 1, characterized in that: Determining an integration success rate based on the integration status log, the first log data, and the second log data includes: Determine, based on the integration status log, the first log data, and the second log data, a first integration result indicating successful integration and a second integration result indicating failed integration; The integration success rate is determined based on the first integration result and the second integration result.

7. The adjustment method according to claim 6, characterized in that: The method further comprises: The integration performance data of the integration system is determined based on the first unit data volume and the first peak flow of the first log data, the second unit data volume and the second peak flow of the second log data, and the integration success rate, wherein the first unit data volume is used to represent the data volume of the passenger order data and the passenger check-in data received within a unit time, the first peak flow is used to represent the maximum data volume of the passenger order data and the passenger check-in data received within a time interval, the second unit data volume is used to represent the data volume of the integration result integrated within the unit time, and the second peak flow is used to represent the maximum data volume of the integration result integrated within the time interval.

8. The adjustment method according to claim 1, characterized in that: The method further comprises: In response to the distributed file system receiving the integrated status log, the first log data and the second log data, the integrated status log, the first log data and the second log data are structured using the distributed file system, and the structured integrated status log, the first log data and the second log data are saved in a target data table.

9. The adjustment method according to claim 8, characterized in that: Based on the integration success rate, determine the adjustment strategy, including: In response to the integration success rate being lower than an integration success rate threshold and the integration performance data of the integration system being lower than an integration performance threshold, determining the adjustment strategy based on the target data table; The integration strategy is adjusted according to the adjustment strategy to obtain an adjustment result, including: adjusting the integration strategy according to the adjustment strategy to obtain the adjustment result, so that the integration success rate is greater than or equal to the integration success rate threshold, and the integration performance data is greater than or equal to the integration performance threshold.

10. A device for adjusting a data integration strategy, characterized in that: include: A first acquisition unit, configured to acquire first log data corresponding to the passenger order data and the passenger check-in data in a to-be-integrated state in the integration system, wherein the first log data is used to at least represent key information in the passenger order data and key information in the passenger check-in data; a second acquisition unit, configured to integrate the passenger order data and the passenger check-in data according to an integration strategy to obtain an integration result, and to obtain second log data corresponding to the integration result, and an integration status log, wherein the integration strategy is used to indicate a rule for integrating the passenger order data and the passenger check-in data, the second log data is used to indicate at least key information in the integration result, and the integration status log is used to indicate whether the passenger order data and the passenger check-in data are integrated successfully or failed; a determining unit, configured to determine an integration success rate based on the integration status log, the first log data, and the second log data, wherein the integration success rate is used to represent the integration performance of the integration system; An adjustment unit is used to determine an adjustment strategy based on the integration success rate, and adjust the integration strategy according to the adjustment strategy to obtain an adjustment result, wherein the adjustment strategy is used to represent a rule for adjusting the integration strategy.

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