Airline data processing method and device, storage medium and electronic equipment

Abstract

The application provides an airline data processing method and device, a storage medium and an electronic equipment, and comprises the following steps: obtaining airline preset data of an airline; extracting market level data and flight class data from the airline preset data; splitting the flight class data to obtain each data set; obtaining each flight rule file based on each data set and the market level data; extracting a flight identifier from a flight operation instruction of the airline sent by a passenger; determining a flight rule file corresponding to the flight identifier as a target file, determining flight information from the target file, and feeding back the flight information to the passenger. By splitting the flight class data in the airline preset data into multiple flight rule files, when querying the data required by the passenger, the target file is determined in each flight rule file, the flight information is determined from the target file and fed back to the passenger, the entire process does not need to traverse all data in the database, the data acquisition time is reduced, and the performance of the system is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an airline data processing method and apparatus, storage medium and electronic device. Background Technology

[0002] When passengers perform flight inquiries or make cabin reservations, the system needs to match data with pre-set airline data and then provide the corresponding flight information to the passengers.

[0003] Currently, data matching typically involves checking each record in the database one by one until a match is found. However, with the increasing number of airline users, the amount of airline data is growing year by year. This massive data volume leads to a gradual decline in system processing performance, and finding the specific data required by passengers necessitates traversing all the data, which takes a considerable amount of time and further reduces system performance. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide an airline data processing method and apparatus, storage medium and electronic device. When passengers use the present invention to search for flight information, it is not necessary to traverse all the data in the database, thereby shortening the search time, shortening the response time and improving system performance.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] An airline data processing method, comprising:

[0007] Obtain the airline's default data;

[0008] Extract market-level data and flight-level data from the airline's preset data;

[0009] The flight-level data is split into various data sets;

[0010] Based on the aforementioned data sets and the market-level data, each flight rule file is obtained;

[0011] When a flight operation instruction from the airline is received from a passenger, the flight identifier is extracted from the flight operation instruction;

[0012] The flight rules file corresponding to the flight identifier is identified as the target file, the flight information is determined from the target file, and the flight information is fed back to the passenger.

[0013] An airline data processing device, comprising:

[0014] The acquisition unit is used to acquire the airline's preset data;

[0015] The first extraction unit is used to extract market-level data and flight-level data from the airline's preset data;

[0016] The splitting unit is used to split the flight-level data to obtain various data sets;

[0017] The obtaining unit is used to obtain each flight rule file based on each of the data sets and the market-level data;

[0018] The second extraction unit is used to extract the flight identifier from the flight operation instruction sent by the passenger when the passenger sends the flight operation instruction from the airline.

[0019] The determining unit is used to determine the flight rule file corresponding to the flight identifier as the target file, determine the flight information from the target file, and feed the flight information back to the passenger.

[0020] A storage medium comprising stored instructions, wherein, when the instructions are executed, the device in which the storage medium resides executes the airline data processing method as described above.

[0021] An electronic device includes a memory and one or more instructions, wherein one or more instructions are stored in the memory and configured to be executed by one or more processors using the airline data processing method described above.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] This invention provides an airline data processing method, apparatus, storage medium, and electronic device, comprising: acquiring airline preset data; extracting market-level data and flight-level data from the airline preset data; splitting the flight-level data to obtain various data sets; obtaining various flight rule files based on the various data sets and market-level data; when receiving a flight operation instruction from a passenger, extracting the flight identifier from the flight operation instruction; determining the flight rule file corresponding to the flight identifier as the target file, determining flight information from the target file, and feeding the flight information back to the passenger. This invention splits the flight-level data in the airline preset data into multiple flight rule files. When querying the data required by a passenger, it first determines the target file based on the flight identifier in each flight rule file, then determines the flight information from the target file, and finally feeds the flight information back to the passenger. Therefore, it eliminates the need to traverse all data in the database, effectively improving the efficiency of data retrieval, reducing data acquisition time, and improving system performance. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0025] Figure 1 A flowchart of an airline data processing method provided in an embodiment of the present invention;

[0026] Figure 2 A flowchart of a method for processing data sequences to obtain various data sets, provided in an embodiment of the present invention;

[0027] Figure 3 A flowchart for determining split data in each flight data segment of a data sequence, provided as an embodiment of the present invention;

[0028] Figure 4 This is an example diagram illustrating a scenario where airline pre-set data is split to obtain various flight rule files, as provided in an embodiment of the present invention.

[0029] Figure 5 This invention provides an example diagram illustrating a scenario where flight rule files are used to provide passenger feedback information.

[0030] Figure 6 The present invention provides a method flow for determining the split data when splitting flight-level data in an embodiment of the present invention;

[0031] Figure 7 This is a schematic diagram of the structure of an airline data processing device provided in an embodiment of the present invention;

[0032] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] In this application, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0035] Terminology Explanation:

[0036] IC (Inventory Control): The inventory control module in an inventory control system;

[0037] IR (Inventory Rule): The rule management module in an inventory control system;

[0038] DROOLS (JBoss Rules): An open-source business rules engine;

[0039] KEY: A unique value used to identify a single DROOLS file, consisting of the airline, originating flight number, and terminating flight number.

[0040] As the background technology shows, as the amount of system data increases, it takes more time to find data for passengers, which reduces the system's performance.

[0041] In addition to the issues mentioned above, when passengers search for flights or book cabins, the system currently needs to match data with pre-set data from airline users to determine whether a cabin is available for sale. Currently, some systems store data in a database and then load it into memory for matching; others use DROOLS technology, which uses rule files for data matching. However, when using DROOLS technology, the size of the data volume determines the performance of subsequent calculations.

[0042] As more and more airlines use the system, the amount of data they generate also increases year by year. When the amount of data that airlines have pre-set reaches a certain level, the system's performance will become slow, causing passengers to experience slow system response or even timeouts when searching for flights or booking cabins, resulting in the inability to return correct results.

[0043] In scenarios where performance is slow due to excessive pre-set data from airlines, the system can split the data by airline, with each airline using a separate DROOLS file, since the service is provided to airline-specific users. However, when the data volume for a single airline becomes too large, this method of splitting data by airline becomes impractical. Passengers may still experience slow system responses or timeouts when searching for flights or booking cabins, resulting in incorrect results.

[0044] To address the aforementioned problems, this invention provides an airline data processing solution that can split airline preset data into multiple flight rule files, and then perform data matching on a file-by-file basis, eliminating the need to traverse all the data, thereby improving system performance and solving the above-mentioned problems.

[0045] This invention can be used in a wide variety of general-purpose or special-purpose computing environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor devices, distributed computing environments including any of the above devices, etc.

[0046] This invention can be applied to airline processing systems, see reference. Figure 1 The following is a flowchart of an airline data processing method provided by an embodiment of the present invention, which is described in detail below:

[0047] S101. Obtain the airline's preset data.

[0048] To improve the accuracy of subsequent data feedback to passengers, it is necessary to process the pre-set data for each airline.

[0049] Preferably, all airlines' pre-set data is stored in a unified database, while the pre-set data of different airlines needs to be processed separately to obtain the flight rule files of each airline.

[0050] The airline's preset data includes, but is not limited to, flight reservation information for all flights of that airline, as well as flight information for all flights.

[0051] S102. Extract market-level data and flight-level data from airline preset data.

[0052] Preferably, the airline's preset data includes two types of data: one is market-level data, which can also be called market-level preset data, and the other is flight-level data, which can also be called flight-level preset data.

[0053] Market-level data includes route information and seat reservations for each airline's flights, while flight-level data includes information for each airline's flights, such as the origin flight number, destination flight number, departure airport, and arrival airport.

[0054] S103. Split the flight-level data to obtain various data sets.

[0055] Flight-level data contains multiple preset flight data entries, which include, but are not limited to, flight number, departure airport, etc.

[0056] The process of splitting flight-level data into various datasets is described below:

[0057] Retrieve preset data for each flight from the flight-level data;

[0058] The preset data for each flight is broken down to obtain the data for each flight.

[0059] Sort the data for each flight to obtain a data sequence;

[0060] The data sequence is processed to obtain various data sets.

[0061] It should be noted that each dataset contains at least one flight record.

[0062] Preferably, when splitting the flight preset data, the splitting is based on the flight number. The number of flight data entries is equal to the number of flight numbers present in the flight preset data. For example, if the flight preset data contains flight number 123 and flight number 145, then during the splitting, flight data containing flight number 123 and flight data containing flight number 145 are obtained.

[0063] In addition to the flight number, the flight data also includes the airline's logo, the flight's preset data number, and other information.

[0064] For example, when sorting flight data, it is necessary to obtain the flight number of each flight and then sort the flight data in ascending order of flight number, thereby obtaining a data sequence. Preferably, the flight data can also be sorted in descending order of flight number, and the sorting rule can be selected according to actual needs.

[0065] It should be noted that when sorting flight data based on flight number, for flight data with the same flight number, the sorting can be done either by sorting the data number from smallest to largest or by sorting the data number from largest to smallest. For example, for flight data A, flight data B, and flight data C, all with flight number 200, if flight data A has a data number of 2, flight data B has a data number of 1, and flight data C has a data number of 5, then the sorting would be: flight data B, flight data A, flight data C.

[0066] By processing the individual flight data in the data sequence, we can obtain various data sets, each containing at least one flight data set.

[0067] S104. Based on various datasets and market-level data, various flight rule documents are obtained.

[0068] For example, market-level data is configured for each dataset, resulting in a flight rule file for each dataset.

[0069] Furthermore, the present invention can also generate market rule documents with market-level data.

[0070] Preferably, both flight rule documents and market rule documents can be referred to as DROOLS files.

[0071] Each flight rule file contains market-level data, and the corresponding market data can be obtained when each flight rule file is invoked, thereby ensuring the accuracy of the obtained data.

[0072] S105. When a passenger sends a flight operation instruction from the airline, extract the flight identifier from the flight operation instruction.

[0073] Preferably, when passengers perform operations such as flight inquiries and seat reservations, they send flight operation instructions, which include, but are not limited to, airline identifiers and flight identifiers. Based on the airline identifier, the specific airline being operated by the passenger can be identified.

[0074] The flight operation instructions are parsed to obtain the flight identifier, which can be the flight number.

[0075] S106. Determine the flight rules document corresponding to the flight identifier as the target document, extract the flight information from the target document, and provide the flight information to the passengers.

[0076] The specific process of identifying the flight rule file corresponding to the flight identifier as the target file is as follows:

[0077] Obtain the flight number range for each flight rule file;

[0078] The flight number range to which the flight identifier belongs is identified as the target flight number range;

[0079] The flight rule document belonging to the target flight number range is identified as the target document.

[0080] Each flight rule file contains a flight number range. The flight number range of the flight rule file can be determined based on the flight numbers of each flight data in the flight rule file. For example, the flight number with the smallest value in the flight rule file is taken as the minimum value of the flight number range, and the flight number with the largest value in the flight rule file is taken as the maximum value of the flight number range.

[0081] The flight information obtained can include information such as the remaining seats and ticket prices for the flight requested by the passenger.

[0082] It should be noted that there may be cases where no flight rule file corresponding to the flight identifier can be matched. In this case, the market rule file can be matched. If a market rule file is matched, the query information can be obtained from the matched market rule file and then the query information can be fed back to the passenger. If no market rule file is matched, it is returned as is for upstream software to process.

[0083] The method provided in this invention involves: acquiring airline-preset data; extracting market-level data and flight-level data from the airline-preset data; splitting the flight-level data into various data sets; obtaining various flight rule files based on the various data sets and market-level data; extracting flight identifiers from the flight operation instructions sent by passengers when a flight operation instruction from an airline is received; determining the flight rule file corresponding to the flight identifier as the target file; determining flight information from the target file; and feeding the flight information back to the passenger. This invention splits the flight-level data in the airline-preset data into multiple flight rule files. When querying the data required by a passenger, it first determines the target file based on the flight identifier in each flight rule file, then determines the flight information from the target file, and finally feeds the flight information back to the passenger. Therefore, it eliminates the need to traverse all data in the database, effectively improving the efficiency of data retrieval, reducing data acquisition time, and improving system performance.

[0084] In addition, by splitting the airline's preset data into multiple flight rule files, the amount of computation required by the system can be reduced, and the system's processing capacity can be improved.

[0085] Furthermore, the system's rule management module can execute steps S101-S104 to split the airline's preset data into individual airline rule files. The system's rule calculation module executes steps S105-S106 to determine the target file from the individual airline rule files generated by the rule management module, and then determine the flight information from the target file and feed the flight information back to the passengers. The entire process does not require traversing all the data, effectively reducing response time and improving system performance.

[0086] In another embodiment provided by the present invention, reference is made to Figure 2The flowchart of a method for processing data sequences to obtain various data sets, provided by an embodiment of the present invention, is described in detail below:

[0087] S201. Determine whether the number of data in the data sequence is greater than a preset value; if the number of data in the data sequence is greater than the preset value, execute S202; if the number of data in the data sequence is less than or equal to the preset value, execute S204.

[0088] The preset value can be set according to actual needs. The preset value is an integer greater than zero. For example, it can be set to 10.

[0089] The system counts the number of flight data points in the data sequence and then compares this count with a preset value to determine whether the number of flight data points in the data sequence is greater than the preset value.

[0090] S202. Determine the split data in each flight data of the data sequence, and divide the data sequence into a first sequence and a second sequence based on the split data.

[0091] The last data in the first sequence is the split data. In other words, when dividing the data sequence into the first sequence and the second sequence, the cutoff data of the first sequence is the split data.

[0092] S203. Combine the flight data in the first sequence into a data set, take the second sequence as a new data series, and then return to the step of determining whether the number of data in the data series is greater than a preset value.

[0093] S204. Combine the flight data in the data sequence into a data set.

[0094] In another embodiment provided by the present invention, reference is made to Figure 3 The flowchart for determining split data in each flight data of a data sequence, provided by an embodiment of the present invention, is described in detail below:

[0095] S301. Based on preset values, determine target data in the data sequence. The target data is the flight data in the data sequence whose sorting number matches the preset value.

[0096] Preferably, each flight data in the data sequence has a sorting number, which represents the sorting position of the flight data in the data sequence. Specifically, when the sorting number is 1, it means that the flight data is in the first position; when the sorting number is 2, it means that the flight data is in the second position, and so on. This will not be elaborated further here.

[0097] Flight data with the same sorting number as the preset value are identified as target data. In other words, the sorting number that is the same as the preset value is the sorting number that matches the preset value.

[0098] S302. Based on the flight number of the target data, the flight numbers of each flight data in the data sequence preceding the target data, and the flight number of the flight data in the data sequence following the target data, determine the first sequence segmentation data, the second sequence segmentation data, and the third sequence segmentation data.

[0099] In the embodiments provided by the present invention, the process of determining the first sequence segmentation data, the second sequence segmentation data, and the third sequence segmentation data is as follows:

[0100] The flight data preceding the target data in the data sequence is identified as the first data, and the flight data following the target data in the data sequence is identified as the second data;

[0101] When the flight number of the target data, the flight number of the first data, and the flight number of the second data are all different, the target data is determined as the second sequence segmentation data, the first data is determined as the first sequence segmentation data, and the second data is determined as the third sequence segmentation data.

[0102] When the flight number of the target data is the same as the flight number of the first data, and the flight number of the target data is different from the flight number of the second data, each flight data in the data sequence that is before the target data and has a different flight number from the target data is determined as the first data to be selected.

[0103] The first candidate data that is closest to the target data is determined as the first sequence segmentation data;

[0104] The target data is identified as the second sequence segmentation data, and the second data is identified as the third sequence segmentation data;

[0105] When the flight number of the target data is different from the flight number of the first data, and the flight number of the target data is the same as the flight number of the second data, the target data is determined as the third sequence segmentation data;

[0106] The first data is determined as the segmentation data for the second sequence;

[0107] Each flight data in the data sequence that is preceding the first data and has a different flight number from the first data is identified as the second data to be selected;

[0108] The second candidate data that is closest to the first data is determined as the first sequence segmentation data;

[0109] When the flight number of the target data, the flight number of the first data, and the flight number of the second data are all the same, the first data is determined as the third sequence segmentation data;

[0110] Each flight data in the data sequence that is preceding the first data and has a different flight number from the first data is identified as the third data to be selected;

[0111] The third candidate data that is closest to the first data is determined as the second sequence segmentation data;

[0112] Each flight data point in the data sequence that is preceding the second sequence segmentation data and has a different flight number from the second sequence segmentation data is identified as the fourth candidate data.

[0113] The fourth candidate data that is closest to the second sequence segmentation data is determined as the first sequence segmentation data.

[0114] It should be noted that in determining the first, second, and third sequence of data, the scenario of continuous flight data with the same flight number as the target data was fully considered. This reduces the possibility of separating continuous flight data with the same flight number in the future, and puts continuous flight data with the same flight number into one data set as much as possible.

[0115] S303. The difference between the flight number of the second sequence segmented data and the flight number of the first sequence segmented data is determined as the first difference.

[0116] The flight numbers of the second sequence segmented data can be subtracted from the flight numbers of the first sequence segmented data to obtain the first difference.

[0117] S304. The difference between the flight number of the third sequence segmented data and the flight number of the second sequence segmented data is determined as the second difference.

[0118] The second difference can be obtained by subtracting the flight numbers of the third sequence segmented data from the flight numbers of the second sequence segmented data.

[0119] S305. Determine whether the first difference is less than or equal to the second difference. If the first difference is less than or equal to the second difference, execute S306; if the first difference is greater than the second difference, execute S307.

[0120] S306. Determine the second sequence segmentation data as the split data.

[0121] S307. Determine the first sequence segmented data as the split data.

[0122] When the first difference is less than the second difference, it means that the flight number of the second sequence segmented data is closer to the flight number of the first sequence segmented data. Therefore, the second sequence segmented data is determined as the split data. When the first difference is greater than the second difference, it means that the flight number of the second sequence segmented data is closer to the flight number of the third sequence segmented data. Therefore, the first sequence segmented data is used as the split data. This way, flight data with similar flight numbers can be grouped together as much as possible.

[0123] The method provided in this embodiment of the invention can process the airline's preset data to obtain multiple flight rule files. When searching for data for passengers, the target file is first determined in each flight rule file, the flight information is then determined from the target file, and the flight information is then sent to the passenger. Thus, it is not necessary to traverse all the data in the database, reducing the required time, lowering the response time, and improving the system performance.

[0124] Reference Figure 4 This is an example diagram illustrating a scenario where airline pre-set data is split to obtain various flight rule files, as provided in this embodiment of the invention. A detailed explanation follows:

[0125] The system sets up preset data for all airlines. For each airline's preset data, market-level data and flight-level data are extracted. Based on the market-level data and flight-level data, various flight rule files are generated. There are two types of flight rule files: the first type contains only market-level data, and the second type contains both flight data and market-level data. It should be noted that the second type of flight rule file is generated by splitting the flight-level data into various data sets. Each data set contains flight data. Configuring market-level data for each data set yields the second type of flight rule file. The second type of flight rule file contains flight number ranges. The flight number with the smallest value in the flight rule file is used as the minimum value of the flight number range, and the flight number with the largest value in the flight rule file is used as the maximum value of the flight number range.

[0126] All airlines' pre-set data is stored uniformly in a single database. This invention first splits the data according to the airline, and then processes the data of each airline separately.

[0127] Airlines pre-determine two types of data: flight-level data and market-level data. Market-level data constitutes a very small proportion, so it is not further split; only flight-level data is dynamically split.

[0128] Taking Airline B as an example, the data is first divided into two groups: market-level data and flight-level data. Then, based on the flight information in the flight-level data, the flights are reorganized and split into several subgroups (which can be understood as the data sets mentioned above). Finally, a set of pre-defined market-level data is added to the subgrouped flight-level data, while a separate set of market-level data is retained.

[0129] Ultimately, an airline's data will be split into a market-level DROOLS file and several flight-level DROOLS files named after the airline, the origin flight number, and the destination flight number. Each flight-level DROOLS file will include flight data for all flight numbers from the origin flight number to the destination flight number, as well as all market-level data, for the rule calculation module to load and use.

[0130] Reference Figure 5 The following is an example diagram illustrating a scenario where flight rule files are used to provide passenger feedback information, as provided in this embodiment of the invention:

[0131] Step 1: Passengers search for airline flights or book a seat for a specific airline through the airline's official channels or major portal websites.

[0132] Step 2: Based on the received request, the system identifies the corresponding airline (taking airline B as an example) and flight number, determines the KEY, and matches it with the corresponding flight-level DROOLS file. If there is no corresponding KEY for the flight number, it matches the market-level DROOLS file; the KEY here can be a combination of the airline identifier of the airline queried by the passenger and the flight number of the flight within that airline.

[0133] Step 3: If a corresponding DROOLS file is matched, return the corresponding information based on the DROOLS file; if no corresponding DROOLS file is matched, return a message indicating that no matching information was found for processing by the upstream software.

[0134] Reference Figure 6 The method flow for determining the split data when splitting flight-level data according to the embodiments of the present invention is described in detail below:

[0135] S401. Based on preset values, determine the data N in the data sequence. n Data N n-1 And data N n+1 .

[0136] It should be noted that the data N n This refers to flight data in a data sequence whose sorting index equals a preset value. Preferably, the preset value can be n, where n is a positive integer; data N n-1For data sequence located at data N n The previous flight data, data N n+1 For data sequence located at data N n The next flight data. Data N n This can be understood as the target data mentioned above; data N n-1 This can be understood as the first data point mentioned above; data N n+1 This can be understood as the second piece of data mentioned above.

[0137] S402, Determine data N n Flight number, data N n-1 Flight number and data N n+1 Are all flight numbers different? When data N n Flight number, data N n-1 Flight number and data N n+1 When all flight numbers are different, execute S403; when data N n Flight number and data N n-1 The flight numbers are the same, data N n Flight number and data N n+1 When the flight numbers are different, execute S404; when data N n Flight number and data N n-1 The flight numbers are different, data N n Flight number and data N n+1 When the flight numbers are the same, execute S405; when data N n Flight number, data N n-1 Flight number and data N n+1 If all flight numbers are the same, S406 will be operated.

[0138] S403, Determine data N n Flight number and data N n-1 Is the difference between the flight numbers less than the data N? n+1 Flight number and data N n The difference between the flight numbers; when data N n Flight number and data N n-1 The difference between the flight numbers is less than the data N. n+1 Flight number and data N n If the difference is between the flight number and the flight number, execute S407; otherwise, execute S408.

[0139] When data N n Flight number, data N n-1 Flight number and data N n+1 When all flight numbers are different, the data N at this time n This can be understood as the second sequence segmentation of data mentioned above; data Nn-1 This can be understood as the first sequence of data segmentation mentioned above; data N n+1 This can be understood as the third sequence of data segmentation mentioned above.

[0140] S404, Determine data N m1 Determine the data N n Flight number and data N m1 Is the difference between the flight numbers less than the data N? n+1 Flight number and data N n The difference between the flight numbers; when data N n Flight number and data N m1 The difference between the flight numbers is less than the data N. n+1 Flight number and data N n If the difference is between the flight number and the flight number, execute S409; otherwise, execute S410.

[0141] When data N n Flight number and data N n-1 The flight numbers are the same, data N n Flight number and data N n+1 When the flight numbers are different, the data N at this time n+1 This can be understood as the third sequence segmentation of data mentioned above; data N n This can be understood as the second sequence of data segmentation mentioned above.

[0142] In determining the data N m1 At that time, data N m1 For data sequence located at data N n The preceding text is incomplete and contains numerous errors. A more accurate translation would require the full context and a clearer understanding of the intended meaning. n Closest to each other, and the flight number matches the data N. n Flight data with different flight numbers, m1 is data N m1 In the data sequence, the sorting index m1 takes the value of a positive integer; at this time, the data N... m1 This can be understood as the first sequence of data segmentation mentioned above.

[0143] Furthermore, in the data sequence located at data N m1 The next flight data to data N n This can be treated as a data group, where all flight numbers in the data group are the same. Preferably, the flight number in data N is located in the data sequence. m1 The next flight data can be data N. n .

[0144] S405, Determine data N m2 Determine the data N n-1 Flight number and data N m2 Is the difference between the flight numbers less than the data N?n-1 Flight number and data N n The difference between the flight numbers; when data N n-1 Flight number and data N m2 The difference between the flight numbers is less than the data N. n-1 Flight number and data N n If the difference is between the flight numbers, execute S411; otherwise, execute S412.

[0145] When data N n Flight number and data N n-1 The flight numbers are different, data N n Flight number and data N n+1 When the flight numbers are the same, data N n This can be understood as splitting the data into third sequences; data N n-1 This can be understood as the second sequence of data segmentation.

[0146] In determining the data N m2 At that time, data N m2 For data sequence located at data N n-1 The preceding text is incomplete and contains numerous errors. A more accurate translation would require the full context and a clearer understanding of the intended meaning. n-1 Closest to each other, and the flight number matches the data N. n-1 Flight data with different flight numbers, m2 represents data N. m2 In the data sequence, the sorting index m2 takes the value of a positive integer; at this time, the data N... m2 This can be understood as the first sequence of data segmentation mentioned above.

[0147] Furthermore, in the data sequence located at data N m2 The next flight data to data N n-1 This can be treated as a data group, where all flight numbers in the data group are the same. Preferably, the flight number in data N is located in the data sequence. m2 The next flight data can be data N. n-1 .

[0148] S406, Determine data N m3 And data N m4 Determine the data N m4 Flight number and data N m3 Is the difference between the flight numbers less than the data N? m4 Flight number and data N n-1 The difference between the flight numbers; when data N m4 Flight number and data N m3 The difference between the flight numbers is less than the data N. m4 Flight number and data N n-1 If the difference is between the flight numbers, execute S413; otherwise, execute S414.

[0149] When data N n Flight number, data N n-1 Flight number and data N n+1 When all flight numbers are the same, then data N n Data N n-1 And data N n+1 Any data point in the sequence can be understood as the third sequence segmentation data mentioned above.

[0150] In determining the data N m3 And data N m4 At that time, the flight data that is located before the third segment data, is closest to the third segment data, and whose flight number is different from the third segment data is identified as data N. m4 ; The data sequence located at data N m4 The preceding text is incomplete and contains numerous errors. A more accurate translation would require the full context and a clearer understanding of the intended meaning. m4 Closest to each other, and the flight number matches the data N. m4 Different flight data are identified as data N. m3 The data N at this time m4 This can be understood as the second sequence of data splitting mentioned above, where the data N is now... m3 This can be understood as the second sequence of data segmentation mentioned above, where m3 represents the data N. m3 In the data sequence, m3 is a positive integer; m4 is the sorting index of the data N. m4 The sorting index in the data sequence, m4 takes the value of a positive integer.

[0151] Preferably, the data sequence located at data N m4 The next flight data to data N n+1 A data group can be formed where the flight numbers in the data group are the same, that is, they are all flight numbers from the third segmentation data; the data sequence located at data N m3 The next flight data can be data N. n-1 .

[0152] Preferably, the data sequence located at data N m3 The next flight data to data N m4 A data group can be formed where the flight numbers in the data group are the same, which is data N. m4 Flight number; located in data N in the data sequence m3 The next flight data can be data N. m4 .

[0153] S407, Transfer data N n The data has been identified as segmented data.

[0154] S408, Transfer data N n-1The data has been identified as segmented data.

[0155] S409, Transfer data N n The data has been identified as segmented data.

[0156] S410, Transfer data N m The data has been identified as segmented data.

[0157] S411, Transfer data N n-1 The data has been identified as segmented data.

[0158] S412, Transfer data N m2 The data has been identified as segmented data.

[0159] S413, Transfer data N m4 The data has been identified as segmented data.

[0160] S414, Transfer data N m3 The data has been identified as segmented data.

[0161] It should be noted that the segmented data is the last data in the first sequence mentioned above. After generating the DROOLS file of the data set corresponding to the first sequence, the segmented data is the end data of the DROOLS file, and the flight data in the data sequence that is after the segmented data is used as the starting data of the next DROOLS file.

[0162] Each airline has a different amount of pre-set data, so a universal number of DROOLS files cannot be used. This invention uses a universal pre-set value (with dynamically adjustable parameters) to split the data. Thus, for airlines with smaller data volumes, the final number of DROOLS files is smaller; for airlines with larger data volumes, the final number of DROOLS files is larger. Special processing is incorporated during the splitting process to minimize the coverage of flight numbers that are not involved.

[0163] The invention involves two modules: a rule management module and a rule calculation module. After receiving user-preset data, the rule management module stores it in the Oracle database and triggers the generation of DROOLS logic. The rule calculation module loads the DROOLS file and, upon receiving a passenger's request to query flights or reserve cabins, performs data matching and returns the corresponding results.

[0164] The part of this invention that relates to the rule calculation module only involves the determination of the flight number. It obtains the corresponding KEY based on the airline and flight number queried or booked by the passenger, and then performs DROOLS matching to obtain the correct result. The logic is simple and will not be elaborated here.

[0165] To illustrate the process of generating flight rule files, this invention provides a scenario example. Taking airline B as an example, the airline's two-letter code is YY. Flight-level data and market-level data are extracted from airline B's preset data. After splitting airline B's flight-level data, there are 53 flight data entries. The flight data entries are sorted according to the flight number, and the sorting results are shown in Table 1.

[0166]

[0167]

[0168] Table 1

[0169] Each flight data entry includes a serial number and a flight number, such as... Figure 1 As shown, number 1, flight number 1 is the first flight data; number 1, flight number 2 is the second flight data, and so on. No further examples will be given here.

[0170] Assuming a preset value of 10, based on Airline B's market-level data and the flight data in Table 1, the following DROOLS file can be generated:

[0171] DROOLS file 1: YY-1-1832;

[0172] In this file, YY-1-1832 is the name of DROOLS file 1, YY is the airline identifier for airline B, which can be the airline number; 1-1832 is the flight number range of DROOLS file 1, meaning that DROOLS file 1 contains flight data from flight number 1 to flight number 1832. The naming of subsequent DROOLS files can be found in the explanation here.

[0173] For example, since the preset value is 10, it can accommodate a maximum of 10 flight data entries. When judging the 10th flight data entry, the flight numbers of the 10th flight data entry (number 6, flight number 2031), the 11th flight data entry (number 8, flight number 2031), and the 9th flight data entry (number 5, flight number 2031) are all 2301. Therefore, the 9th to 11th flight data entries can be grouped into data group 1, and the flight number of data group 1 is 2301. The flight numbers of the 8th flight data entry (number 6, flight number 2030) and the 7th flight data entry (number 5, flight number 2030) are both 2030. Therefore, the 7th and 8th flight data entries can be grouped into data group 2, and the flight number of data group 2 is 2030.

[0174] The difference between flight number 2030 in data group 2 and flight number 1832 in the 6th flight data (number 12, flight number 1832) is 198. The difference between flight number 2030 in data group 2 and flight number 2031 in data group 1 is 1. The flight numbers in data group 2 are closer to those in data group 1. Therefore, the 6th flight data is taken as the cutoff data. After forming a data set from the 1st to the 6th flight data, market-level data is configured for this data set, resulting in DROOLS file 1, which contains 6 flight data.

[0175] DROOLS file 2: YY-2030-2032;

[0176] The default value is 10. After obtaining DROOLS file 1, processing continues. The flight data following the last flight data (number 12, flight number 1832) in DROOLS file 1 (number 5, flight number 2030) is treated as the first data entry and processed. The flight numbers of the 10th flight data (number 11, flight number 2032), the 11th flight data (number 6, flight number 2033), and the 9th flight data (number 8, flight number 2032) are all different. Similarly, the flight number 2032 in the 10th flight data and the flight number 2033 in the 11th flight data differ by 1, and the flight number 2032 in the 10th flight data and the flight number 2031 in the 9th flight data also differ by 1. The flight number in the 10th flight data is the same distance from both sides of the data. Therefore, the flight data (number 11, flight number 2032) is taken as the cutoff data. Referring to the generation method of DROOLS file 1, DROOLS file 2 is generated. DROOLS file 2 contains 10 flight data.

[0177] DROOLS file 3: YY-2033-2040;

[0178] The flight data following the last flight data (number 11, flight number 2032) in DROOLS file 2 (number 6, flight number 2033) is treated as the first data entry and processed. The flight numbers of the 10th flight data (number 6, flight number 2040), the 11th flight data (number 10, flight number 3000), and the 9th flight data (number 6, flight number 2039) are all different. The flight number of the 10th flight data (2040) and the flight number of the 11th flight data (3000) differ by 960, and the flight number of the 10th flight data (2040) and the flight number of the 9th flight data (2039) differ by 1. The flight number of the 10th flight data is closer to that of the 9th flight data, so the 10th flight data is used as the cutoff data, and the flight number is cut off at 2040, generating DROOLS file 3, which contains 10 flight data entries.

[0179] DROOLS file 4: YY-3000-4206;

[0180] The flight data following the last flight data (number 6, flight number 2040) in DROOLS file 3 (number 10, flight number 3000) is treated as the first data entry and processed. The flight numbers of the 10th flight data (number 20, flight number 4206), the 11th flight data (number 20, flight number 4207), and the 9th flight data (number 20, flight number 4205) are all different. The flight numbers of the 10th flight data (4206) and the 11th flight data (4207) differ by 1, and the flight numbers of the 10th flight data (4206) and the 9th flight data (4205) also differ by 1. Therefore, the flight number of the 10th flight data is the same distance from both ends of the data, so the 10th flight data is taken as the cutoff data, and the flight number is cut off at 4206, generating DROOLS file 4, which contains 10 flight data entries.

[0181] DROOLS file 5: YY-4207-5156;

[0182] The flight data following the last flight data (number 20, flight number 4206) in DROOLS file 4 (number 20, flight number 4207) is treated as the first data entry and processed. The flight numbers of the 10th flight data (number 17, flight number 6523), the 11th flight data (number 16, flight number 7658), and the 9th flight data (number 14, flight number 5156) are all different. The flight number of the 10th flight data (6523) and the flight number of the 11th flight data (7658) differ by 1135, and the flight number of the 10th flight data (6523) and the flight number of the 9th flight data (5156) differ by 1367. The flight number of the 10th flight data is closer to that of the 11th flight data, so the 9th flight data is used as the cutoff data, with the flight number ending at 5156, generating DROOLS file 5, which contains 9 flight data entries.

[0183] DROOLS file 6: YY-6523-9990;

[0184] The flight data following the last flight data (number 14, flight number 5156) in DROOLS file 5 (number 17, flight number 6523) is treated as the first data and processed. Since there are only 8 flight data left, which is less than the preset value of 10, no further judgment is made, and the remaining 8 flight data are directly used to generate DROOLS file 6. That is, DROOLS file 6 contains 8 flight data.

[0185] DROOLS file 7: Market grade;

[0186] DROOLS file 7 is generated based on market-level data from flight B;

[0187] It should be noted that this invention splits the airline's preset data into multiple DROOLS files, and subsequent matching is performed on a file-by-file basis, eliminating the need to traverse all the data. This reduces the matching time of the rule calculation module, thereby reducing response time and achieving the goal of improving performance.

[0188] By applying this invention, the rule management module in the system can dynamically split DROOLS files based on airlines and flight numbers, thereby reducing the amount of data matched by the calculation module and improving its efficiency. The system's rule calculation module no longer performs data matching based on airlines, but instead precisely finds specific DROOLS files for matching based on keys. This invention can dynamically split different airlines into different numbers of files, further optimizing the performance of each airline.

[0189] and Figure 1 Corresponding to the method shown, the present invention also provides an airline data processing device, which is installed in the airline processing system and is used to support... Figure 1 The specific implementation of the method shown.

[0190] Reference Figure 7 The following is a schematic diagram of the structure of an airline data processing device provided in an embodiment of the present invention, and is described in detail below:

[0191] Acquisition unit 501 is used to acquire the airline's preset data;

[0192] The first extraction unit 502 is used to extract market-level data and flight-level data from the airline's preset data;

[0193] The splitting unit 503 is used to split the flight-level data to obtain various data sets;

[0194] The obtaining unit 504 is used to obtain each flight rule file based on each of the data sets and the market-level data;

[0195] The second extraction unit 505 is used to extract the flight identifier from the flight operation instruction sent by the passenger when the passenger sends the flight operation instruction of the airline.

[0196] The determining unit 506 is used to determine the flight rule file corresponding to the flight identifier as the target file, determine the flight information from the target file, and feed the flight information back to the passenger.

[0197] The apparatus provided in this invention acquires airline preset data; extracts market-level data and flight-level data from the airline preset data; splits the flight-level data to obtain various data sets; obtains various flight rule files based on the various data sets and market-level data; when a passenger sends an airline flight operation instruction, it extracts the flight identifier from the flight operation instruction; identifies the flight rule file corresponding to the flight identifier as the target file, determines the flight information from the target file, and then feeds the flight information back to the passenger. This invention splits the flight-level data in the airline preset data into multiple flight rule files. When querying the data required by the passenger, it first determines the target file based on the flight identifier in each flight rule file, then determines the flight information from the target file, and finally feeds the flight information back to the passenger. Therefore, it eliminates the need to traverse all data in the database, effectively improving the efficiency of data retrieval, reducing data acquisition time, and improving system performance.

[0198] In another embodiment of the present invention, the splitting unit 503 of the device includes:

[0199] The first acquisition subunit is used to acquire preset data for each flight in the flight-level data;

[0200] The splitting sub-unit is used to split the preset data of each flight to obtain the data of each flight;

[0201] The sorting subunit is used to sort the flight data to obtain a data sequence;

[0202] The processing subunit is used to process the data sequence to obtain various data sets, each data set containing at least one flight data.

[0203] In another embodiment provided by the present invention, the processing subunit of the device includes:

[0204] The judgment module is used to determine whether the number of data in the data sequence is greater than a preset value;

[0205] The first determining module is used to determine the split data in each flight data of the data sequence when the number of data in the data sequence is greater than a preset value, and to divide the data sequence into a first sequence and a second sequence based on the split data, wherein the last data in the first sequence is the split data.

[0206] The second determining module is used to form a data set from the flight data in the first sequence, take the second sequence as a new data series, and then trigger the judging module to perform the step of judging whether the number of data in the data sequence is greater than a preset value.

[0207] The component module is used to combine the flight data in the data sequence into a data set when the number of data in the data sequence is less than or equal to the preset value.

[0208] In another embodiment of the present invention, the first determining module of the device includes:

[0209] The first determining submodule is used to determine target data in the data sequence based on the preset value, wherein the target data is flight data in the data sequence whose sorting number matches the preset value;

[0210] The second determining submodule is used to determine the first sequence segmentation data, the second sequence segmentation data, and the third sequence segmentation data based on the flight number of the target data, the flight numbers of each flight data in the data sequence preceding the target data, and the flight number of the flight data in the data sequence following the target data;

[0211] The third determining submodule is used to determine the difference between the flight number of the second sequence segmented data and the flight number of the first sequence segmented data as the first difference;

[0212] The fourth determining submodule is used to determine the difference between the flight number of the third sequence segmented data and the flight number of the second sequence segmented data as the second difference;

[0213] The fifth determining submodule is used to determine the second sequence segmentation data as split data when the first difference is less than or equal to the second difference;

[0214] The sixth determining submodule is used to determine the first sequence segmented data as split data when the first difference is greater than the second difference.

[0215] In another embodiment of the present invention, the second determining submodule of the device performs a process of determining first sequence segmentation data, second sequence segmentation data, and third sequence segmentation data based on the flight number of the target data, the flight numbers of each flight data preceding the target data in the data sequence, and the flight number of the flight data following the target data in the data sequence, including:

[0216] The flight data preceding the target data in the data sequence is determined as the first data, and the flight data following the target data in the data sequence is determined as the second data;

[0217] When the flight number of the target data, the flight number of the first data, and the flight number of the second data are all different, the target data is determined as the second sequence segmentation data, the first data is determined as the first sequence segmentation data, and the second data is determined as the third sequence segmentation data.

[0218] When the flight number of the target data is the same as the flight number of the first data, and the flight number of the target data is different from the flight number of the second data, each flight data in the data sequence that is located before the target data and has a different flight number from the target data is determined as the first candidate data;

[0219] The first candidate data that is closest to the target data is determined as the first sequence segmentation data;

[0220] The target data is determined as the second sequence segmentation data, and the second data is determined as the third sequence segmentation data;

[0221] When the flight number of the target data is different from the flight number of the first data, and the flight number of the target data is the same as the flight number of the second data, the target data is determined as the third sequence segmentation data;

[0222] The first data is determined as the second sequence segmentation data;

[0223] Each flight data in the data sequence that is preceding the first data and has a different flight number from the first data is identified as the second data to be selected;

[0224] The second candidate data that is closest to the first data is determined as the first sequence segmentation data;

[0225] When the flight number of the target data, the flight number of the first data, and the flight number of the second data are all the same, the first data is determined as the third sequence segmentation data;

[0226] Each flight data in the data sequence that is preceding the first data and has a different flight number from the first data is identified as the third data to be selected;

[0227] The third candidate data that is closest to the first data is determined as the second sequence segmentation data;

[0228] Each flight data in the data sequence that is located before the second sequence segmentation data and has a different flight number from the second sequence segmentation data is identified as the fourth candidate data;

[0229] The fourth candidate data that is closest to the second sequence segmentation data is determined as the first sequence segmentation data.

[0230] In another embodiment of the present invention, the obtaining unit 504 of the device includes:

[0231] A configuration subunit is used to configure the market-level data for each data set to obtain a flight rule file for each data set.

[0232] In another embodiment of the present invention, the determining unit 506 of the device includes:

[0233] The second acquisition subunit is used to acquire the flight number range of each of the flight rule files;

[0234] The first determining subunit is used to identify the flight number range to which the flight identifier belongs as the target flight number range;

[0235] The second determining subunit is used to determine the flight rule file to which the target flight number range belongs as the target file.

[0236] The specific working process of each unit, subunit, module, and submodule in the airline data processing device for charging piles disclosed in the above embodiments of the present invention can be found in the corresponding content of the airline data processing device method disclosed in the above embodiments of the present invention, and will not be repeated here.

[0237] This invention also provides a storage medium that includes stored instructions, wherein the execution of the instructions controls the device containing the storage medium to perform the aforementioned airline data processing method.

[0238] This invention also provides an electronic device, the structural schematic of which is shown below. Figure 8 As shown, it specifically includes a memory 601 and one or more instructions 602, wherein one or more instructions 602 are stored in the memory 601 and configured to be executed by one or more processors 603 to perform the above-mentioned airline data processing method.

[0239] The specific implementation processes and derivative methods of the above embodiments are all within the protection scope of this invention.

[0240] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0241] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0242] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for processing airline data, characterized in that, include: Obtain the airline's default data; Extract market-level data and flight-level data from the airline's preset data; The flight-level data is split into various data sets; Based on the aforementioned data sets and the market-level data, each flight rule file is obtained; When a flight operation instruction from the airline is received from a passenger, the flight identifier is extracted from the flight operation instruction; The flight rule file corresponding to the flight identifier is identified as the target file, the flight information is determined from the target file, and the flight information is fed back to the passenger. The process of splitting the flight-level data to obtain various data sets includes: Obtain the preset data for each flight from the flight-level data; The preset data for each flight is split to obtain individual flight data; The flight data are sorted to obtain a data sequence; The data sequence is processed to obtain various data sets, each data set containing at least one flight data point; The process of processing the data sequence to obtain various data sets includes: Determine whether the number of data items in the data sequence is greater than a preset value; When the number of data in the data sequence is greater than a preset value, split data is determined from each flight data in the data sequence, and the data sequence is divided into a first sequence and a second sequence based on the split data, with the last data in the first sequence being the split data; The flight data in the first sequence are combined into a data set, the second sequence is taken as a new data series, and then the process returns to the step of determining whether the number of data in the data sequence is greater than a preset value. When the number of data items in the data sequence is less than or equal to the preset value, the data from each flight in the data sequence will be combined into a data set. The step of determining the split data in each flight data segment of the data sequence includes: Based on the preset value, target data is determined in the data sequence, and the target data is flight data in the data sequence whose sorting number matches the preset value; Based on the flight number of the target data, the flight numbers of each flight data in the data sequence preceding the target data, and the flight number of the flight data in the data sequence following the target data, the first sequence segmentation data, the second sequence segmentation data, and the third sequence segmentation data are determined; The difference between the flight number of the second sequence segmentation data and the flight number of the first sequence segmentation data is determined as the first difference; The difference between the flight number of the third sequence segmented data and the flight number of the second sequence segmented data is determined as the second difference; When the first difference is less than or equal to the second difference, the second sequence segmentation data is determined as split data; When the first difference is greater than the second difference, the first sequence segmentation data is determined as split data.

2. The method according to claim 1, characterized in that, The determination of first sequence segmentation data, second sequence segmentation data, and third sequence segmentation data based on the flight number of the target data, the flight numbers of each flight data preceding the target data in the data sequence, and the flight number of the flight data following the target data in the data sequence includes: The flight data preceding the target data in the data sequence is determined as the first data, and the flight data following the target data in the data sequence is determined as the second data; When the flight number of the target data, the flight number of the first data, and the flight number of the second data are all different, the target data is determined as the second sequence segmentation data, the first data is determined as the first sequence segmentation data, and the second data is determined as the third sequence segmentation data. When the flight number of the target data is the same as the flight number of the first data, and the flight number of the target data is different from the flight number of the second data, each flight data in the data sequence that is located before the target data and has a different flight number from the target data is determined as the first candidate data; The first candidate data that is closest to the target data is determined as the first sequence segmentation data; The target data is determined as the second sequence segmentation data, and the second data is determined as the third sequence segmentation data; When the flight number of the target data is different from the flight number of the first data, and the flight number of the target data is the same as the flight number of the second data, the target data is determined as the third sequence segmentation data; The first data is determined as the second sequence segmentation data; Each flight data in the data sequence that is preceding the first data and has a different flight number from the first data is identified as the second data to be selected; The second candidate data that is closest to the first data is determined as the first sequence segmentation data; When the flight number of the target data, the flight number of the first data, and the flight number of the second data are all the same, the first data is determined as the third sequence segmentation data; Each flight data in the data sequence that is preceding the first data and has a different flight number from the first data is identified as the third data to be selected; The third candidate data that is closest to the first data is determined as the second sequence segmentation data; Each flight data in the data sequence that is located before the second sequence segmentation data and has a different flight number from the second sequence segmentation data is identified as the fourth candidate data; The fourth candidate data that is closest to the second sequence segmentation data is determined as the first sequence segmentation data.

3. The method according to claim 1, characterized in that, Based on the respective data sets and the market-level data, each flight rule file is obtained, including: Configure the market-level data for each data set to obtain the flight rule file for each data set.

4. The method according to claim 1, characterized in that, The step of determining the flight rule file corresponding to the flight identifier as the target file includes: Obtain the flight number range for each of the aforementioned flight rule files; The flight number range to which the flight identifier belongs is identified as the target flight number range; The flight rule file to which the target flight number range belongs is identified as the target file.

5. An airline data processing device, characterized in that, include: The acquisition unit is used to acquire the airline's preset data; The first extraction unit is used to extract market-level data and flight-level data from the airline's preset data; The splitting unit is used to split the flight-level data to obtain various data sets; The obtaining unit is used to obtain each flight rule file based on each of the data sets and the market-level data; The second extraction unit is used to extract the flight identifier from the flight operation instruction sent by the passenger when the passenger sends the flight operation instruction from the airline. The determining unit is used to determine the flight rule file corresponding to the flight identifier as the target file, determine the flight information from the target file, and feed the flight information back to the passenger; The splitting unit includes: The first acquisition subunit is used to acquire preset data for each flight in the flight-level data; The splitting sub-unit is used to split the preset data of each flight to obtain the data of each flight; The sorting subunit is used to sort the flight data to obtain a data sequence; A processing subunit is used to process the data sequence to obtain various data sets, each data set containing at least one flight data; The processing subunit includes: The judgment module is used to determine whether the number of data in the data sequence is greater than a preset value; The first determining module is used to determine the split data in each flight data of the data sequence when the number of data in the data sequence is greater than a preset value, and to divide the data sequence into a first sequence and a second sequence based on the split data, wherein the last data in the first sequence is the split data. The second determining module is used to form a data set from the flight data in the first sequence, take the second sequence as a new data series, and then trigger the judging module to perform the step of judging whether the number of data in the data sequence is greater than a preset value. The component module is used to combine the flight data in the data sequence into a data set when the number of data in the data sequence is less than or equal to the preset value; The first determining module includes: The first determining submodule is used to determine target data in the data sequence based on the preset value, wherein the target data is flight data in the data sequence whose sorting number matches the preset value; The second determining submodule is used to determine the first sequence segmentation data, the second sequence segmentation data, and the third sequence segmentation data based on the flight number of the target data, the flight numbers of each flight data in the data sequence preceding the target data, and the flight number of the flight data in the data sequence following the target data; The third determining submodule is used to determine the difference between the flight number of the second sequence segmented data and the flight number of the first sequence segmented data as the first difference; The fourth determining submodule is used to determine the difference between the flight number of the third sequence segmented data and the flight number of the second sequence segmented data as the second difference; The fifth determining submodule is used to determine the second sequence segmentation data as split data when the first difference is less than or equal to the second difference; The sixth determining submodule is used to determine the first sequence segmented data as split data when the first difference is greater than the second difference.

6. A storage medium, characterized in that, The storage medium includes stored instructions, wherein, when the instructions are executed, the device containing the storage medium is controlled to perform the airline data processing method as described in any one of claims 1-4.

7. An electronic device, characterized in that, It includes a memory, and one or more instructions, wherein one or more instructions are stored in the memory and configured to be executed by one or more processors as described in any one of claims 1-4.

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