CN116628110A - Rail transit data processing method and device and data query method - Google Patents
Rail transit data processing method and device and data query method Download PDFInfo
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Abstract
The application discloses a method and a device for processing rail transit data and a data query method. Wherein the method comprises the following steps: collecting system data of a plurality of service systems in a target track traffic system; classifying system data into historical data and real-time data; processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result; generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result. The application solves the technical problem that the rail transit system can only be analyzed from a single dimension due to single data source when the rail transit system is analyzed in the related technology.
Description
Technical Field
The application relates to the technical field of urban rail transit, in particular to a method and a device for processing rail transit data and a data query method.
Background
With the acceleration of urban rail transit construction and the arrival of big data age, the volume of subway basic data information resources in the national range in recent years presents a rapidly growing situation, and meanwhile, various information application demands are more and more complicated, and higher requirements on data service and application supporting capability are provided. When analyzing the track traffic system in the related art, only the data of one service system in the track traffic system is used as a data source, and the data source and the analysis dimension are single.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the application provides a processing method and a device for track traffic data and a data query method, which at least solve the technical problem that the track traffic system can only be analyzed from a single dimension due to single data source when the track traffic system is analyzed in the related technology.
According to an aspect of an embodiment of the present application, there is provided a method for processing rail traffic data, including: collecting system data of a plurality of service systems in a target track traffic system; classifying system data into historical data and real-time data; processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result; generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result.
Optionally, classifying the system data into historical data and real-time data includes: determining the type of an interface corresponding to the system data, wherein the interface is an interface for collecting the system data; and classifying the system data according to the type of the interface to obtain a classification result, wherein the classification result comprises historical data and real-time data.
Optionally, classifying the system data according to the type of the interface includes: if the first type interface and the second type interface exist at the same time, determining the system data corresponding to the first type interface as historical data, and determining the system data corresponding to the second type interface as real-time data; if only one type of interface exists, determining the acquisition frequency corresponding to the interface, determining the system data corresponding to the interface with the acquisition frequency being the first frequency as historical data, and determining the system data corresponding to the interface with the acquisition frequency being the second frequency as real-time data, wherein the acquisition frequency is the frequency for acquiring the system data through the interface, and the first frequency is lower than the second frequency.
Optionally, the processing the historical data through the multi-bin architecture to obtain a first processing result includes: collecting a plurality of historical data into a central data warehouse, acquiring the plurality of historical data in the central data warehouse through a batch processing layer of a multi-bin architecture, carrying out batch processing on the plurality of historical data at the same time to obtain a first processing result, and storing the first processing result in a database of offline data; processing the real-time data through the multi-bin architecture to obtain a second processing result, wherein the processing result comprises: sequentially carrying out stream processing on each real-time data through a speed layer of a multi-bin architecture to obtain a plurality of second processing results, and storing the second processing results in a cache; the data in the database and the cache are used for generating a target view together, and the target view comprises a historical data visual view and a real-time data visual view.
Optionally, generating the historical data visual according to the first processing result includes: classifying the data in the first processing result into passenger flow data, ticket data, driving data and road network basic data; generating a passenger flow thematic visual page according to the passenger flow data; generating a ticket thematic visual page according to the ticket thematic; generating a driving thematic visual page according to driving data; generating a road network foundation thematic visual page according to the road network foundation data; and generating a historical data visual image according to the passenger flow thematic visual image page, the ticket thematic visual image page, the driving thematic visual image page and the road network basic thematic visual image page.
Optionally, generating the real-time data visual according to the second processing result includes: classifying the data in the second processing result into road network scheduling data, road network service data and data for indicating the service state of the ticketing system; generating a visual page of a dispatching service center according to road network dispatching data, generating a visual page of a passenger service center according to road network service data, and generating an automatic ticketing and checking system page according to data for indicating the service state of the ticketing system; and generating a real-time data visual view according to the dispatch service center visual page, the passenger service center visual page and the automatic ticket vending and checking system page.
Optionally, the historical data visual and the real-time data visual are presented in the same interface.
According to another aspect of the embodiment of the present application, there is also provided a data query method, which is applied to a mobile terminal, including: receiving a query request of a target object for querying track traffic data; responding to the inquiry request, determining the mobile terminal sending the inquiry request, and acquiring first identification information of the mobile terminal and second identification information of a user corresponding to the mobile terminal, wherein the second identification information comprises: a user's enterprise mailbox number and a user's mobile phone number; acquiring third identification information of the mobile terminal bound with the data query engine and fourth identification information of a user corresponding to the mobile terminal, and comparing the first identification information and the second identification information with the third identification information and the fourth identification information; if the first identification information is the same as the third identification information and the second identification information is the same as the fourth identification information, determining that the mobile terminal sending the query request is a mobile terminal bound with the data query engine, and sending track traffic data to the data query engine; and if the first identification information is different from the third identification information or the second identification information is different from the fourth identification information, refusing to send the rail traffic data to the data query engine.
According to another aspect of the embodiment of the present application, there is also provided a processing device for track traffic data, including: the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring system data of a plurality of service systems in a target track traffic system; the classification module is used for classifying the system data into historical data and real-time data; the processing module is used for processing the historical data through the multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result; the generation module is used for generating a historical data visual view according to the first processing result and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result.
According to another aspect of the embodiment of the present application, there is also provided a nonvolatile storage medium, in which a computer program is stored, where a device in which the nonvolatile storage medium is located executes the above-mentioned method for processing rail transit data by running the computer program.
According to another aspect of the embodiments of the present application, there is also provided an electronic device including a memory in which a computer program is stored, and a processor configured to process the track traffic data described above by the computer program.
In the embodiment of the application, the system data of a plurality of service systems in a target track traffic system are collected; classifying system data into historical data and real-time data; processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result; generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result, converging and processing key index data acquired from a plurality of data sources by taking the plurality of service systems in the rail transit system as the data sources to generate the processing result, so that the aim of analyzing the rail transit system in multiple dimensions is fulfilled, and generating a historical data billboard and a real-time data billboard according to the processing result to be displayed in the mobile terminal, thereby achieving the aim of facilitating a rail transit system manager to check the running state of the rail transit system, realizing the technical effect of intensively displaying road network running conditions in the mobile device and improving the running management efficiency, and further solving the technical problem that the rail transit system can only be analyzed from a single dimension due to single data source when the rail transit system is analyzed in the related technology.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
fig. 1 is a flowchart of a method of processing rail transit data according to an embodiment of the present application;
FIG. 2 is a flow chart of a data process according to an embodiment of the application;
FIG. 3 is a schematic diagram of a historian sign according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a real-time data sign according to an embodiment of the present application;
FIG. 5 is a workflow diagram of a data query engine according to an embodiment of the application;
FIG. 6 is a schematic diagram of a data query engine page according to an embodiment of the present application;
fig. 7 is a block diagram of a processing apparatus for track traffic data according to an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to better understand the embodiments of the present application, technical terms related to the embodiments of the present application are explained as follows:
several bins architecture (Lambda Architecture): a big data processing architecture capable of integrating offline computing and real-time computing comprises three layers, namely a batch layer (batch layer), a speed layer (speed layer) and a service layer (service layer), and has low latency.
Batch processing: refers to a job that executes a series of programs on a computer without human intervention, and in embodiments of the present application refers to processing historical data for a batch at a particular cycle/time.
Stream (type) processing: the method is to continuously combine new data to obtain a calculation result, and the calculation result is used for processing continuously generated data; in the embodiment of the application, each piece of real-time data is processed one by one in real time.
Cache (cache): a high-speed memory, which has a faster access speed than a general Random Access Memory (RAM), may also refer to a cache memory component in a system for storing data.
Section full rate: in unit time, the ratio of the unidirectional section passenger flow volume of the operation line to the corresponding section passenger mileage; section loading = section passenger flow volume/section capacity 100%.
Section passenger flow volume: and in the counting period, the number of passengers passing between two adjacent stations in a certain direction of the operation line.
Section transport capacity: and the rated transportation capacity of a certain section of the line in one direction is achieved in unit time.
Rate of redemption: the ratio of the actual number of rows to the planned number of rows.
Clear people rate: clear rate per ten thousand kilometers driven = clear number of columns/operation kilometers 10 4 In the statistical period, the actual train running cannot continue to execute passenger carrying service due to faults, accidents and the like, and passengers are cleared from the carriages according to the dispatcher command, wherein the same train is cleared for a plurality of times according to one train.
The disconnection rate: during the statistical period, the train returns to the ground after the train does not complete the task specified by the train operation plan due to the reasons of vehicles, passengers and the like, and the drop rate of ten thousand kilometers per running = drop number/operation kilometer 10 4 。
In the related art, only one service system in the rail transit system is used as a data source, and data analysis can be performed only for a single service system; therefore, the method has the problems that the data source is single, the analysis dimension is single, and the analysis result cannot reflect the real rail transit passenger flow condition. In addition, in the related art, the analysis result can be displayed only on a personal computer (Personal Computer) type terminal but not on a portable mobile terminal, so that the operation manager of the rail transit system is inconvenient to view at any time, and the user experience is reduced. In order to solve this problem, related solutions are provided in the embodiments of the present application, and are described in detail below.
According to an embodiment of the present application, there is provided a method embodiment of a method for processing rail transit data, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of a method for processing rail transit data according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S102, collecting system data of a plurality of service systems in a target track traffic system.
In specific implementation, the method provided by the embodiment of the application is implemented by being installed in the mobile terminal equipment in the form of a system installation package. In step S102, a plurality of service systems in the rail transit system are taken as data sources, and data of the plurality of service systems are collected at the same time, wherein the plurality of service systems at least comprise: and key business systems reflecting the operation condition of the rail traffic, such as a rail traffic command center system (Traffic Control Center, TCC), an automatic ticket vending and checking system (Automatic Fare Collection, AFC), a passenger service system and the like.
Step S104, classifying the system data into history data and real-time data.
In step S104, the collected data is classified according to the real-time data and the historical data, so that the historical data and the real-time data are respectively processed in different processing modes; the history data may be yesterday track traffic data with respect to the date on which the data was collected, or may be track traffic data of the last seven days with respect to the date on which the data was collected. Specifically, whether the historical data or the real-time data is collected can be judged through the type of the interface for collecting the data, and whether the historical data or the real-time data is collected can also be judged through the type of the protocol adopted by the interface for collecting the data.
Step S106, processing the historical data through the multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result.
In step S106, after the collected data is classified into the historical data and the real-time data in step S104, the historical data is processed in different data processing layers of the multi-bin architecture by the multi-bin architecture to obtain a (first) processing result corresponding to the historical data, and the real-time data is processed to obtain a (second) processing result corresponding to the real-time data.
Step S108, generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result.
In step S108, a history data signboard (i.e., a history data visual view) for displaying the history data is generated according to the (first) processing result obtained by processing the history data in step S106, and at the same time, a real-time data signboard (i.e., a real-time data visual view) for displaying the real-time data is generated according to the (second) processing result obtained by processing the real-time data; and the first processing result and the second processing result are jointly used as a data source of the data query engine, so that after the data engine receives the query engine, data meeting the query request can be screened from the data source and displayed, wherein the data query engine can display the data of the track traffic system from multiple dimensions, for example, one piece of data is displayed from three dimensions, namely, a time dimension, a space dimension and a ticket dimension.
Through the steps, the data of a plurality of service systems can be converged, the data are processed in different modes according to the types of the data, and the processing results are displayed in different dimensions; the rail transit system operation manager can observe the overall operation condition of rail transit from multiple dimensions. Meanwhile, the method provided by the steps can be applied to the portable mobile terminal, so that an operation manager of the rail transit system can observe the whole operation condition of rail transit at any time and adjust the operation condition in time.
According to an optional embodiment of the present application, in the step S104, classifying the system data into the history data and the real-time data includes: determining the type of an interface corresponding to the system data, wherein the interface is an interface for collecting the system data; and classifying the system data according to the type of the interface to obtain a classification result, wherein the classification result comprises historical data and real-time data.
In this embodiment, if the interfaces for collecting the historical data and the real-time data are defined as different types of interfaces in advance, the type of the collected system data may be determined according to the type of the interface for collecting the data; or if the interfaces for collecting the historical data and the real-time data are different interfaces of the same type, judging the type of the collected system data according to the type of a protocol adopted by the interfaces or the frequency of the collected data of the interfaces, and classifying the collected system data into the historical data and the real-time data.
Specifically, the classifying the system data according to the type of the interface mentioned in the above embodiment includes: if the first type interface and the second type interface exist at the same time, determining the system data corresponding to the first type interface as historical data, and determining the system data corresponding to the second type interface as real-time data; if only one type of interface exists, determining the acquisition frequency corresponding to the interface, determining the system data corresponding to the interface with the acquisition frequency being the first frequency as historical data, and determining the system data corresponding to the interface with the acquisition frequency being the second frequency as real-time data, wherein the acquisition frequency is the frequency for acquiring the system data through the interface, and the first frequency is lower than the second frequency.
In this embodiment, the method for judging the type of the collected system data according to the type of the interface for collecting the data is as follows: judging the type of an interface for collecting system data, if the interface for collecting the system data is of different types, indicating that different collecting interfaces are designated for historical data and real-time data in advance, for example, defining that the historical data is collected through a first type interface and the real-time data is collected through a second type interface, determining the data collected through the first type interface as the historical data and determining the data collected through the second type interface as the real-time data. If the interfaces for collecting the system data are all the interfaces of the same type, determining the frequency of collecting the system data by each interface, and determining the system data collected by the interface with low frequency for collecting the data as historical data and the system data collected by the interface with high frequency for collecting the data as real-time data because the frequency for collecting the real-time data is higher than the frequency for collecting the historical data. For example, if it is determined that the interface acquisition data has the first frequency and the second frequency higher than the first frequency, the system data acquired by the interface with the acquisition frequency of the first frequency is determined to be historical data, and the system data acquired by the interface with the acquisition frequency of the second frequency is determined to be real-time data.
According to another optional embodiment of the application, the processing of the historical data by the multi-bin architecture to obtain the first processing result comprises: collecting a plurality of historical data into a central data warehouse, acquiring the plurality of historical data in the central data warehouse through a batch processing layer of a multi-bin architecture, carrying out batch processing on the plurality of historical data at the same time to obtain a first processing result, and storing the first processing result in a database of offline data; processing the real-time data through the multi-bin architecture to obtain a second processing result, wherein the processing result comprises: sequentially carrying out stream processing on each real-time data through a speed layer of a multi-bin architecture to obtain a plurality of second processing results, and storing the second processing results in a cache; the data in the database and the cache are used for generating a target view together, and the target view comprises a historical data visual view and a real-time data visual view.
FIG. 2 is a flow chart of data processing, as shown in FIG. 2, in this embodiment, before processing historical data, a large amount of historical data from a plurality of different systems is first stored in a central level data warehouse, when processing the historical data, the central and data warehouses are used as data sources, the historical data is first extracted in batches from the central and data warehouses through an offline acquisition program, the extracted batch historical data is subjected to batch processing at a batch processing layer of a lambda architecture to generate a visual view of the historical data (i.e. a first processing result), and the visual view of the historical data (i.e. the first processing result) is stored in a database. As shown in fig. 2, when processing real-time data, the real-time data obtained by classification is collected in turn by an online collection program according to the generation time of the data to form a message queue to be processed, and each piece of real-time data is processed in turn at the speed layer of the lambda architecture to generate a real-time data visual (i.e. a second processing result), and the real-time data visual (i.e. the second processing result) is stored in a cache of the system. In addition, as shown in fig. 2, when an application program capable of implementing the method for processing rail transit data provided by the embodiment of the present application is installed in a mobile device, the database storing the visual view of historical data (i.e., the first processing result) and the cache storing the visual view of real-time data (i.e., the second processing result) are used together as the database of the application program, so as to generate the visual view of historical data (i.e., the first processing result) and the visual view of real-time data (i.e., the second processing result) displayed in the mobile device.
According to some embodiments of the application, generating a historical data visual view from the first processing result includes: classifying the data in the first processing result into passenger flow data, ticket data, driving data and road network basic data; generating a passenger flow thematic visual page according to the passenger flow data; generating a ticket thematic visual page according to the ticket thematic; generating a driving thematic visual page according to driving data; generating a road network foundation thematic visual page according to the road network foundation data; and generating a historical data visual image according to the passenger flow thematic visual image page, the ticket thematic visual image page, the driving thematic visual image page and the road network basic thematic visual image page.
In some embodiments, the (first) processing results from processing the historical data and the (second) processing results from processing the real-time data are categorized prior to generating the target view (including the historical data view and the real-time data view) due to the different data presented in the historical data view and the real-time data view. Fig. 3 is a schematic diagram of a historical data sign, where the historical data sign is generated based on four types of data including road network basic data, passenger flow data, driving data and ticket data modules, so that before a visual view of the historical data is generated, the (first) processing result of the historical data is divided into four types of passenger flow data, ticket data, driving data and road network basic data, where the road network basic topic module displays basic data capable of reflecting the running condition of a rail transit system, and the method includes: the year passenger traffic data of the rail transit system of the year to which the date of the display view belongs, the total operating mileage of the whole rail transit system up to the day before the date of the display view, the total operating mileage of each line of the rail transit system up to the day before the date of the display view, and the number of operating stations in the rail transit system up to the day before the date of the display view. The passenger flow thematic module displays data capable of reflecting the condition of passengers, including: total passenger traffic of the rail transit system by the day before the date of the display view, number of passenger stops of the rail transit system by the day before the date of the display view, number of passenger transfers of the rail transit system by the day before the date of the display view, and maximum section loading rate of the vehicle in the rail transit system by the day before the date of the display view. The driving thematic module displays data capable of reflecting the running state of a vehicle, and comprises: the rate of positive operation of the vehicle by the day before the date of the display view, the rate of redemption of the train by the day before the date of the display view, the rate of disconnection of the train by the day before the date of the display view, and the rate of clearance of the train by the day before the date of the display view. The ticket special subject module displays data capable of reflecting the payment mode of the ticket, and the ticket special subject module comprises: the proportion of tickets paid by the one-card to the total ticket is used until the day before the date of the display view, the proportion of tickets paid by the internet channel to the day before the date of the display view is the proportion of tickets paid by the entity ticket to the day before the date of the display view is the proportion of tickets paid by other financial channels (such as Renminbi) to the day before the date of the display view is the proportion of tickets paid by the entity ticket. Storing data belonging to the passenger flow data class in a table corresponding to the passenger flow data, storing data belonging to the ticket data class in a table corresponding to the ticket data, storing data belonging to the driving data class in a table corresponding to the driving data, and storing data belonging to the road network basic data class in a table corresponding to the road network data, wherein the historical data visual view displayed in the terminal can comprise the following four pages: the system comprises a passenger flow thematic visual page for displaying passenger flow data, a ticket thematic visual page for displaying ticket data, a driving thematic visual page for displaying driving data and a road network basic thematic page for displaying road network basic data; the visual page of the historical data can be divided into four modules, wherein one module displays passenger flow data, the other module displays ticket data, the other module displays driving data and the other module displays road network basic data.
According to further embodiments of the present application, generating a real-time data visual view from the second processing result includes: classifying the data in the second processing result into road network scheduling data, road network service data and data for indicating the service state of the ticketing system; generating a visual page of a dispatching service center according to road network dispatching data, generating a visual page of a passenger service center according to road network service data, and generating an automatic ticketing and checking system page according to data for indicating the service state of the ticketing system; and generating a real-time data visual view according to the dispatch service center visual page, the passenger service center visual page and the automatic ticket vending and checking system page.
Fig. 4 is a schematic view of a real-time data sign, as shown in fig. 4, the real-time data sign is generated based on scheduling data, service data and data reflecting service states of a ticketing system and a ticketing system, and thus, before the real-time data sign is generated, a (second) processing result of the real-time data is divided into three categories, that is, scheduling data, service data and ticketing system data, wherein the scheduling data is displayed in a scheduling service center module for reflecting real-time operation states of a rail transit system, and includes: the method comprises the steps of displaying road network operation state information on the current day of a view, road network passenger flow information on the current day of the view, road network driving information on the current day of the view, driving information on each line on the current day of the view, passenger flow indexes of each line on the current day of the view, driving indexes of each line on the current day of the view, section full load rate of each line on the current day of the view and predicted passenger flow of each line on the current day of the view. The service data is displayed in the passenger service center module and is used for reflecting the state of the passenger-oriented service system, and the service data comprises the following components: customer service hotline data, such as the number of times a customer dials a customer service hotline, the call duration and the like, and rail transit system mobile terminal data, such as the number of times the rail transit system is accessed at a mobile terminal. The ticket selling and checking system data is displayed on an automatic ticket selling and checking system module, and is used for reflecting the running states of the ticket selling system and the ticket checking system, and comprises the following components: displaying the arrival quantity of each line train on the day, displaying the service data of each ticket gate (AG) on the day, displaying the operation service data of each full-automatic Ticket Vending Machine (TVM) on the day, displaying the service data of each semi-automatic ticket vending machine (BOM) on the day and displaying the service data of each Instant Ticket Vending Machine (ITVM) on the day. Storing data belonging to the dispatch data class in a table corresponding to the dispatch data, storing data belonging to the service data class in a table corresponding to the service data, and storing data belonging to the ticketing/ticketing system service data class in a table corresponding to the ticketing/ticketing system service data, wherein the real-time data visual view displayed in the terminal can comprise the following three pages: a dispatch service center visual page for displaying dispatch data, a passenger service center visual page for displaying service data, and an automated ticketing system page for displaying ticketing system service data; one real-time data visual page can also be divided into three modules, wherein one module displays scheduling data, another module displays service data, and another module displays ticketing/ticketing system service data.
According to an alternative embodiment of the application, the historical data visual and the real-time data visual are presented in the same interface.
In this embodiment, the historical data signboard shown in fig. 3 and the real-time data signboard shown in fig. 4 may be displayed on one display interface of the mobile terminal at the same time, so that a user may observe the operation conditions of the rail transit system reflected by the historical data signboard and the real-time data signboard at the same time; or the historical data bulletin board shown in fig. 3 or the real-time data bulletin board shown in fig. 4 are respectively and independently displayed on the display interface of the mobile terminal, so that a user can more clearly observe the historical data bulletin board or the real-time data bulletin board.
Fig. 5 is a workflow diagram of a data query method according to an embodiment of the present application, where the data query method is applied to a mobile terminal, and includes the following steps:
step S502, a query request for querying track traffic data by a target object is received.
Fig. 6 is a schematic diagram of a data query engine page, in which the query engine receives a query request from an application/target object, where information input by a user (target object) in a search box of the query engine may be used as the query request, and information selected by the user (target object) in an index table in the query engine may also be used as the query request, where the index table in the query engine includes an index table storing yesterday data (fast report data index table) and an index table storing seven past days data (final report data index table).
Step S504, responding to the inquiry request, determining the mobile terminal sending the inquiry request, and acquiring first identification information of the mobile terminal and second identification information of a user corresponding to the mobile terminal, wherein the second identification information comprises: the enterprise mailbox number of the user and the mobile phone number of the user.
After the query engine is downloaded to the mobile terminal, the unique identification information of the mobile terminal and the user of the mobile terminal are bound with the query engine, specifically, the unique code of the mobile terminal or other identification information capable of uniquely identifying the terminal can be bound with the query engine, and the enterprise mailbox of the user using the query engine or other identification information capable of uniquely identifying the user can be bound with the query engine. Accordingly, after the query engine receives the query request in step S504, the identification information (i.e., first identification information) of the mobile terminal that transmitted the query request is first acquired, and the identification information (i.e., second identification information) of the user of the query engine is used to authenticate the terminal and the user that transmitted the query request.
Step S506, the third identification information of the mobile terminal bound with the data query engine and the fourth identification information of the user corresponding to the mobile terminal are obtained, and the first identification information and the second identification information are compared with the third identification information and the fourth identification information.
In step S506, the identification information of the mobile terminal bound to the query engine (i.e., the third identification information) and the identification information of the user bound to the query engine and the mobile terminal where the query engine is located (i.e., the fourth identification information) are acquired, and the identification information of the mobile terminal transmitting the query request (i.e., the first identification information) acquired in step S504 is compared with the identification information of the terminal bound to the query engine (i.e., the third identification information), and the identification information of the user transmitting the query request (i.e., the second identification information) is compared with the identification information of the user bound to the query engine (i.e., the fourth identification information).
Step S508, if the first identification information is the same as the third identification information and the second identification information is the same as the fourth identification information, determining that the mobile terminal sending the query request is a mobile terminal bound with the data query engine, and sending the track traffic data to the data query engine.
In step S508, whether to return the track traffic data to the mobile terminal that sent the query request is determined according to the comparison result obtained by the comparison in step S206; if the identification information (i.e., the first identification information) of the mobile terminal sending the query request is the same as the identification information (i.e., the third identification information) of the mobile terminal binding to the query engine, and the identification information (i.e., the second identification information) of the user using the query engine is the same as the identification information (i.e., the fourth identification information) of the user binding to the query engine, the user sending the query request and the mobile terminal are confirmed to be the user binding to the query engine and the mobile terminal, and the rail traffic data is returned to the mobile terminal sending the query request. When the track traffic data is displayed in the query engine, the query result may be displayed from three dimensions, namely, a time dimension, a space dimension and a ticket dimension, specifically, as shown in fig. 6, the time dimension aspect includes: the page includes dimensions of larger spans such as year, month, week, day, working day, holiday, etc.: small time spans of 2 hours, 1 hour, 30 minutes, 15 minutes, 10 minutes, 5 minutes, and 2 minutes. The spatial dimensions include: the larger dimensions of the whole road network, the designated area, the designated line, the designated station and the like also comprise: a designated one of the halls, a designated one of the gates, a designated one of the train sections, etc. The ticket dimensions include: showing the payment type of the full ticket type, and also showing only two-dimensional code ticket types, showing only one ticket type, showing only one card type and showing only other types of payment ticket types.
Step S510, if the first identification information is different from the third identification information or the second identification information is different from the fourth identification information, refusing to send the track traffic data to the data query engine.
In step S510, if the identification information (i.e., the first identification information) of the mobile terminal transmitting the query request is different from the identification information (i.e., the third identification information) of the mobile terminal binding to the query engine, and the identification information (i.e., the second identification information) of the user using the query engine is different from the identification information (i.e., the fourth identification information) of the user binding to the query engine, it is confirmed that the user transmitting the query request and the mobile terminal are not the user and the mobile terminal binding to the query engine, and the return of the rail traffic data to the mobile terminal transmitting the query request is refused.
Fig. 7 is a block diagram of a processing device for track traffic data according to an embodiment of the present application, as shown in fig. 7, the device includes: the acquisition module 70 is used for acquiring system data of a plurality of service systems in the target track traffic system; a classification module 72 for classifying the system data into historical data and real-time data; the processing module 74 is configured to process the historical data through the several bins architecture to obtain a first processing result, and process the real-time data through the several bins architecture to obtain a second processing result; a generating module 76 for generating a historical data visual view according to the first processing result and a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result.
When the processing device for the rail transit data works, the data of a plurality of service systems of the rail system are collected through the collecting module 70, the system data collected through the collecting module is classified into real-time data and historical data through the classifying module 72, the historical data are respectively processed through the processing module 74 to obtain a processing result (namely a first processing result) of the historical data, and the real-time data are processed to obtain a processing result (namely a second processing result) of the real-time data; finally, the generating module 76 generates a historical data visual view according to the processing result (i.e. the first processing result) of the historical data, generates a real-time data visual view according to the processing result (i.e. the second processing result) of the real-time data, and uses the processing result (i.e. the first processing result) of the historical data and the processing result (i.e. the second processing result) of the real-time data together as a data source of the data query engine.
It should be noted that, the preferred implementation manner of the embodiment shown in fig. 7 may refer to the related description of the embodiment shown in fig. 1, which is not repeated herein.
The embodiment of the application also provides a nonvolatile storage medium, wherein the nonvolatile storage medium stores a computer program, and equipment where the nonvolatile storage medium is located executes the method for processing the rail transit data by running the computer program.
The above-described nonvolatile storage medium is used to store a program that performs the following functions: collecting system data of a plurality of service systems in a target track traffic system; classifying system data into historical data and real-time data; processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result; generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result
The embodiment of the application also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor is set to be a processing method of the rail transit data through the computer program.
The processor in the electronic device is configured to execute a program that performs the following functions: collecting system data of a plurality of service systems in a target track traffic system; classifying system data into historical data and real-time data; processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result; generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining the data source of the data query engine according to the first processing result and the second processing result
Note that each module in the above-described processing device for track traffic data may be a program module (for example, a set of program instructions for implementing a specific function), or may be a hardware module, and the latter may be represented by the following form, but is not limited thereto: the expression forms of the modules are all a processor, or the functions of the modules are realized by one processor.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present application, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the related art or all or part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application, which are intended to be comprehended within the scope of the present application.
Claims (11)
1. A method for processing rail transit data, comprising:
collecting system data of a plurality of service systems in a target track traffic system;
classifying the system data into historical data and real-time data;
processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result;
generating a historical data visual view according to the first processing result, and generating a real-time data visual view according to the second processing result; and determining a data source of a data query engine according to the first processing result and the second processing result.
2. The method of claim 1, wherein classifying the system data into historical data and real-time data comprises:
determining the type of an interface corresponding to the system data, wherein the interface is an interface for collecting the system data;
And classifying the system data according to the type of the interface to obtain a classification result, wherein the classification result comprises the historical data and the real-time data.
3. The method of claim 2, wherein classifying the system data according to the type of the interface comprises:
if a first type interface and a second type interface exist at the same time, determining system data corresponding to the first type interface as the historical data, and determining system data corresponding to the second type interface as the real-time data;
if only one type of interface exists, determining the acquisition frequency corresponding to the interface, determining system data corresponding to the interface with the acquisition frequency being a first frequency as the historical data, and determining system data corresponding to the interface with the acquisition frequency being a second frequency as the real-time data, wherein the acquisition frequency is the frequency of acquiring the system data through the interface, and the first frequency is lower than the second frequency.
4. The method of claim 1, wherein processing the historical data through a multi-bin architecture to obtain a first processing result comprises:
Collecting a plurality of historical data to a central data warehouse, acquiring the historical data from the central data warehouse through a batch processing layer of the multi-bin architecture, carrying out batch processing on the historical data to obtain a first processing result, and storing the first processing result in a database of offline data;
processing the real-time data through the multi-bin architecture to obtain a second processing result, wherein the processing result comprises the following steps: sequentially carrying out stream processing on each real-time data through a speed layer of the multi-bin architecture to obtain a plurality of second processing results, and storing the second processing results in a cache;
the data in the database and the cache are used for generating a target view together, and the target view comprises the historical data visible view and the real-time data visible view.
5. The method of claim 1, wherein generating a historical data view from the first processing result comprises:
classifying the data in the first processing result into passenger flow data, ticket data, driving data and road network basic data;
generating a passenger flow thematic visual page according to the passenger flow data; generating a ticket topic visible page according to the ticket topic; generating a driving thematic visual page according to the driving data; generating a road network basic thematic visual page according to the road network basic data; and
And generating the historical data visual view according to the passenger flow thematic visual page, the ticket thematic visual page, the driving thematic visual page and the road network basic thematic visual page.
6. The method of claim 1, wherein generating a real-time data visual view from the second processing result comprises:
classifying the data in the second processing result into road network scheduling data, road network service data and data for indicating the service state of the ticketing system;
generating a visual page of a dispatching service center according to the road network dispatching data, generating a visual page of a passenger service center according to the road network service data, and generating an automatic ticket vending and checking system page according to the data for indicating the service state of the ticket vending system; and
and generating the real-time data visual view according to the visual page of the dispatch service center, the visual page of the passenger service center and the automatic ticket vending and checking system page.
7. The method of any of claims 1 to 6, wherein the historical data visual view and the real-time data visual view are presented in the same interface.
8. The data query method is applied to the mobile terminal and comprises the following steps:
receiving a query request of a target object for querying track traffic data;
responding to the query request, determining a mobile terminal sending the query request, and acquiring first identification information of the mobile terminal and second identification information of a user corresponding to the mobile terminal, wherein the second identification information comprises: a user's enterprise mailbox number and the user's mobile phone number;
acquiring third identification information of a mobile terminal bound with a data query engine and fourth identification information of a user corresponding to the mobile terminal, and comparing the first identification information and the second identification information with the third identification information and the fourth identification information;
if the first identification information is the same as the third identification information and the second identification information is the same as the fourth identification information, determining that the mobile terminal sending the query request is a mobile terminal bound with the data query engine, and sending the track traffic data to the data query engine;
and if the first identification information is different from the third identification information or the second identification information is different from the fourth identification information, refusing to send the track traffic data to the data query engine.
9. A processing device for track traffic data, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring system data of a plurality of service systems in a target track traffic system;
the classification module is used for classifying the system data into historical data and real-time data;
the processing module is used for processing the historical data through a multi-bin architecture to obtain a first processing result, and processing the real-time data through the multi-bin architecture to obtain a second processing result;
the generation module is used for generating a historical data visual view according to the first processing result and generating a real-time data visual view according to the second processing result; and determining a data source of a data query engine according to the first processing result and the second processing result.
10. A nonvolatile storage medium, wherein a computer program is stored in the nonvolatile storage medium, and wherein a device in which the nonvolatile storage medium is located executes the method for processing rail transit data according to any one of claims 1 to 7 by running the computer program.
11. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of processing rail traffic data according to any one of claims 1 to 7 by means of the computer program.
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