Data Processing Method, Apparatus, Device, and Storage Medium

Abstract

The present disclosure provides a data processing method, apparatus, device, and storage medium, which relate to the field of computer technologies, and specifically to technical fields such as big data, cloud computing, and electronic maps. The data processing method includes: obtaining job materials of each job phase in at least one job phase, where the job materials include element data of at least one map element; generating resume data of each map element in the at least one map element based on the job materials of each job phase, where the resume data includes the element data of the job phases through which each map element has passed in the at least one job phase; and storing the resume data of each map element. The present disclosure can achieve refined data processing.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, specifically to the fields of big data, cloud computing, electronic maps, etc., and particularly relates to a data processing method, apparatus, device, and storage medium. Background Art

[0002] With the development of intelligence, people's travel increasingly depends on electronic maps. To construct accurate electronic maps, it is necessary to first produce map data.

[0003] When producing map data, it can be processed with job materials as the object. Summary of the Invention

[0004] The present disclosure provides a data processing method, apparatus, device, and storage medium.

[0005] According to one aspect of the present disclosure, a data processing method is provided, including: obtaining job materials of each job stage in at least one job stage, where the job materials include element data of at least one map element; generating resume data of each map element in the at least one map element based on the job materials of each job stage, where the resume data includes element data of the job stages passed by the each map element in the at least one job stage; and storing the resume data of each map element.

[0006] According to another aspect of the present disclosure, a data processing apparatus is provided, including: a first obtaining module, configured to obtain job materials of each job stage in at least one job stage, where the job materials include element data of at least one map element; a generating module, configured to generate resume data of each map element in the at least one map element based on the job materials of each job stage, where the resume data includes element data of the job stages passed by the each map element in the at least one job stage; and a first storage module, configured to store the resume data of each map element.

[0007] According to another aspect of the present disclosure, an electronic device is provided, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of the above aspects.

[0008] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, where the computer instructions are used to cause the computer to execute the method according to any one of the above aspects.

[0009] According to another aspect of the present disclosure, there is provided a computer program product including a computer program which, when executed by a processor, implements the method according to any one of the above aspects.

[0010] According to the technical solution of the present disclosure, refined data processing can be achieved.

[0011] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. Description of the Drawings

[0012] The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. Among them:

[0013] Figure 1 is a schematic diagram according to the first embodiment of the present disclosure;

[0014] Figure 2 is a schematic diagram according to the second embodiment of the present disclosure;

[0015] Figure 3 is a schematic diagram according to the third embodiment of the present disclosure;

[0016] Figure 4 is a schematic diagram according to the fourth embodiment of the present disclosure;

[0017] Figure 5 is a schematic diagram according to the fifth embodiment of the present disclosure;

[0018] Figure 6 is a schematic diagram according to the sixth embodiment of the present disclosure;

[0019] Figure 7a is a schematic diagram of a partial process according to the seventh embodiment of the present disclosure;

[0020] Figure 7b is a schematic diagram of another partial process according to the seventh embodiment of the present disclosure;

[0021] Figure 8 is a schematic diagram according to the eighth embodiment of the present disclosure;

[0022] Figure 9 is a schematic diagram of an electronic device for implementing the data processing method of the embodiments of the present disclosure. Detailed Embodiments

[0023] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, descriptions of well-known functions and structures are omitted in the following description for clarity and conciseness.

[0024] Figure 1 is a schematic diagram according to the first embodiment of the present disclosure. This embodiment provides a data processing method, including:

[0025] 101. Obtain the job data of each job stage in at least one job stage, where the job data includes the element data of at least one map element.

[0026] 102. Generate the resume data of each map element in the at least one map element based on the job data of each job stage, where the resume data includes the element data of the job stages that each map element has passed through in the at least one job stage.

[0027] 103. Store the resume data of each map element.

[0028] The execution subject of this embodiment can be a data processing device, and the specific form of the device is not limited. It can be hardware, software, or a combination of both. The device can be located inside an electronic device, and the electronic device can be a user terminal or a server. The server can be a local server or in the cloud, and the user terminal can include mobile devices (such as mobile phones, tablets), wearable devices (such as smart watches, smart bracelets), in-vehicle devices (such as car head units), etc.

[0029] Generally speaking, the method of this embodiment can be applied to the server.

[0030] When producing map data, as Figure 2 shown, the acquisition personnel can collect the environmental data of the real world through the user terminal 201. For example, the acquisition personnel can collect the road images of a certain area through handheld acquisition devices, in-vehicle acquisition devices, etc., and use the road images as the environmental data of the real world. Then, the user terminal 201 can send the collected environmental data of the real world to the server 202, and the server can perform operations based on the collected environmental data of the real world to produce map data.

[0031] From the environmental data of the real world to the map data used to construct the electronic map produced, it can go through at least one job stage (step), and the job stage can also be called a job process, a job step, etc.

[0032] For example, the operation stage may include: warehousing, plan creation, plan completion, plan cancellation, differential stage, verification stage, post - processing stage, etc.

[0033] Among them, warehousing means storing the collected environmental data of the real world into the database.

[0034] Generally speaking, map data can be produced in units of plans, that is, map data for one plan can be produced, and an electronic map can be constructed based on the map data of multiple plans.

[0035] Plan creation means creating map data for a certain area, and a certain area is specified, such as a certain administrative region, a certain geographical indication area, a certain residential community, etc.

[0036] Plan completion, for example, successfully creating map data for a certain area, or creating failure, etc.

[0037] Plan cancellation means canceling the previously created plan.

[0038] In the differential stage, it is a process of using a program to replace manual work to find the differences between the newly added map data and the published map data.

[0039] In the verification stage, it is a process of verifying the map data to be published and removing abnormal data.

[0040] In the post - processing stage, it is an operation for quasi - output after the map data production is completed, such as judging whether to allow data submission and saving.

[0041] Operation materials can also be called operation material files, operation material packages, etc.

[0042] Generally speaking, for a certain plan, the plan can also be further divided. For example, if a certain plan corresponds to an administrative region, the administrative region can also be divided into multiple sub - regions, and each sub - region corresponds to an operation material, that is, the map data of each sub - region can be called an operation material.

[0043] An operation material can include the element data of one or more map elements. If not otherwise specified, multiple means at least two. The operation material can have a specific data format. For example, the element data of the map elements in a certain sub - region can be packed into a file in SQLite format as an operation material. SQLite is a lightweight database.

[0044] Map elements refer to the expressions of specific entities in the real world in the database, and the expressions in the database are, for example, the expressions in the electronic map. That is, map elements can be considered as the basic components of the electronic map.

[0045] Specific entities include, for example, geographical entities, activities at a certain geographical location, etc.

[0046] Geographical entities include, for example: traffic lights, traffic signs, electronic eyes, gas stations, toll stations, landmark buildings, etc.

[0047] Activities at a certain geographical location include, for example: left-turn vehicle guide lines, straight-through vehicle guide lines, right-turn vehicle guide lines, etc. for a certain road condition.

[0048] Taking the geographical entity of a traffic light as an example, the map element refers to the expression of the traffic light in the electronic map. For example, if the traffic light is represented by a certain symbol in the electronic map, then this symbol is the map element corresponding to the traffic light.

[0049] Map elements can be classified into: point elements, line elements, surface elements, etc.

[0050] For example, the map element corresponding to a certain geographical entity (such as a traffic light) in the real world can be called a point element.

[0051] Another example is that the map element corresponding to a certain linear entity (such as a certain road) in the real world can be called a line element.

[0052] Another example is that the map element corresponding to a certain planar entity (such as a certain water surface) in the real world can be called a surface element.

[0053] Unless otherwise specified, the map elements in the embodiments of the present disclosure can be one or more of point elements, line elements, and surface elements.

[0054] The element data of the map element refers to the data describing the map element, which can be specifically divided into meta-information and data content. The meta-information includes, for example: element ID, city name, element type, etc. The element type includes, for example: traffic facility type, landmark building type, etc.

[0055] The data content refers to the content of the specific map data corresponding to the map element. For example, for a certain point element, its data content can include the longitude and latitude information of the geographical entity in the real world corresponding to this point element, etc.

[0056] As described above, a job material can include the element data of at least one map element. Therefore, the job material can be obtained first, and then the job material can be parsed to obtain the element data of each map element included in the at least one map element in the job material.

[0057] After obtaining the element data of each map element, respective corresponding resume data can be generated for each map element.

[0058] For example, if a certain job material includes the element data corresponding to traffic lights and the element data corresponding to traffic cameras, then the resume data corresponding to traffic lights and the resume data corresponding to traffic cameras can be generated.

[0059] The job stages passed by a map element refer to the actual job stages involved by the map element. Since the production process of map data involves many job stages, compared with the complete set of all job stages, the job stages passed by a certain map element may be lost or abnormal, etc.

[0060] For example, assume that at least one job stage for producing map data includes: the first job stage, the second job stage, the third job stage, the fourth job stage, and the fifth job stage.

[0061] The job stages passed by a certain map element may include: the first job stage, the second job stage, the third job stage, and the fourth job stage. At this time, this map element has lost one job stage, that is, the fifth job stage.

[0062] Among them, for the job stages not passed by the map element, such as the fifth job stage, at this time, the element data is empty. Correspondingly, the resume data of this map element in this stage can be set to be empty.

[0063] For the job stages passed by the map element, for example, the first job stage, the element data of this first job stage can be used as the resume data of the first job stage.

[0064] Therefore, the resume data of a certain map element can include the element data of all the job stages passed by this map element. For example, based on the above example, it includes the element data of the first job stage to the fourth job stage.

[0065] It can be understood that the data formats of the resume data and the element data can be different. At this time, the element data can be format-converted, and the format-converted element data can be used as the resume data.

[0066] After obtaining the resume data of each map element, it can be stored.

[0067] The stored resume data of each map element can be used for subsequent viewing, analysis, statistics, and other processing.

[0068] In the embodiments of the present disclosure, by generating the resume data of map elements, it is possible to achieve processing at the map element level. Compared with processing at the job data level, refined data processing can be achieved. In addition, the resume data includes the element data of the job stages through which each map element has passed in the at least one job stage. The job stages through which the map elements have passed can be known through the resume data, thereby reflecting the life cycle of the map elements.

[0069] In some embodiments, obtaining the job data of each job stage in the at least one job stage includes: obtaining the buried point data of each job stage from a preset first message queue, where the buried point data contains the address information of the job data; and obtaining the job data of each job stage based on the address information of the job data.

[0070] Among them, the server for generating map data may include a job platform, where buried points can be preset on the job platform to generate the buried point data of each job stage and push it to the message queue for storage.

[0071] Buried point refers to the related technologies and their implementation processes for capturing, processing, and sending specific user behaviors or events.

[0072] For the sake of distinction, the message queue for storing buried point data may be referred to as the first message queue, such as a kafka queue.

[0073] Among them, the format of the buried point data may be as Figure 3 shown.

[0074] Furthermore, the data therein may be as follows:

[0075] Buried point data:

[0076]

[0077] Among them, pkg is the address information of the job data.

[0078] Specifically, the above address information may be the address information in the file system, and the file system may be, for example, a Network File System (NFS).

[0079] Based on this address information, the job data (pkg) can be obtained from a file system such as NFS, and the job data may be a file in SQLite format.

[0080] By obtaining the job data based on the buried point data, the job data can be obtained in the way of buried points, avoiding the impact on normal operations.

[0081] After obtaining the operation materials, the operation materials can be parsed to obtain the element data of each map element included in the operation materials.

[0082] For a certain map element, the element data of the map element can be as follows:

[0083] Element data:

[0084]

[0085] Among them, step represents the current operation stage, and the specific content can be the operation stage identifier, such as the first operation stage, or it can also be the name of the operation stage, for example, planned end.

[0086] step_data represents the data content of the current operation stage, such as including: the identifier indicating whether the current operation stage is completed, the element type, etc.

[0087] pkg is the information of the operation materials where the map element is located, such as including the identifier, name, etc. of the operation materials.

[0088] id is the element identifier, and different map elements have unique element identifiers.

[0089] timestamp is a time stamp representing the current time.

[0090] After obtaining the element data of each map element in the operation materials of each operation stage, the resume data of each map element can be generated based on the above-mentioned element data.

[0091] In some embodiments, generating the resume data of each map element in the at least one map element based on the operation materials of each operation stage includes: parsing the operation materials of each operation stage to obtain the element data of each map element included in the operation materials; for the same map element, generating the resume data of the same map element based on the element data of the operation stages passed by the same map element.

[0092] Among them, for the same map element, the resume data of the map element can be composed of the element data of the operation stages passed by the map element.

[0093] For example, see Figure 4, assume that the operation phases include a first operation phase, a second operation phase, and a third operation phase. Assume that the operation data of the first operation phase is the first operation data, which includes element data -11, element data -12, and element data -13. The operation data of the second operation phase is the second operation data, which includes element data -21 and element data -22. The operation data of the third operation phase is the third operation data, which includes element data -31 and element data -33. Among them, the element data -ij represents the element data of the j-th map element in the i-th operation phase, where i is a positive integer between [1, M], M is the number of operation phases, j is a positive integer between [1, N], and N is the number of map elements.

[0094] Among them, if a certain map element does not go through a certain operation phase, the element data of this map element in this operation phase is empty. For example, if the second operation phase does not include the element data of the third map element, it means that the third map element does not go through the second operation phase.

[0095] Based on the above example, the resume data of the first map element, the resume data of the second map element, and the resume data of the third map element can be generated respectively. Since the first map element goes through the first operation phase, the second operation phase, and the third operation phase, the resume data of the first map element includes: element data -11, element data -21, and element data -31. Similarly, the resume data of the second map element includes: element data -12 and element data -22, and the resume data of the third map element includes: element data -13 and element data 33.

[0096] By generating the resume data of the same map element based on the element data of the operation phases that the same map element goes through, the resume data can reflect the operation phases that the map element goes through.

[0097] In some embodiments, the method further includes: for each of the operation phases, storing the element data of each map element in the at least one map element into a second message queue; correspondingly, generating the resume data of each map element in the at least one map element based on the operation data of each of the operation phases includes: obtaining the element data of each map element in each of the operation phases from the second message queue; generating the resume data of each map element based on the element data of each map element in each of the operation phases.

[0098] Among them, for the sake of distinction, the message queue for storing element data can be called the second message queue, and the second message queue can also be a kafka queue.

[0099] In each operation stage, by analyzing the operation materials, the element data of each map element corresponding to the operation stage can be obtained.

[0100] For each operation stage, after obtaining the element data of each map element in this operation stage, for each map element, the element data of each map element in this operation stage can be stored respectively. For example, if the first operation stage involves the first map element and the second map element, then the element data of the first map element in the first operation stage and the element data of the second map element in the first operation stage can be stored.

[0101] After obtaining the element data of each map element in each operation stage, for the same map element, based on the element data of the operation stages through which the same map element has passed, the resume data of the same map element can be generated. For specific content, reference can be made to the above processing content for the same map element in the same row.

[0102] By storing the element data of each map element in each operation stage for each operation stage, the element data of each map element in each operation stage can be obtained, thereby generating the resume data of each map element. And, by means of the message queue, the processing efficiency can be improved.

[0103] In some embodiments, it further includes: obtaining a query instruction, where the query instruction contains the identification information of the map element to be queried; in response to the query instruction, in the resume data of each map element, obtaining the resume data of the map element to be queried corresponding to the identification information; displaying the resume data of the map element to be queried.

[0104] That is, this embodiment can provide the functions of querying and displaying the resume data of map elements.

[0105] For example, the resume data of each stored map element includes: the resume data of the first map element, the resume data of the second map element, and the resume data of the third map element. Assuming that the query instruction contains the identification information of the first map element, then the resume data of the first map element can be obtained and displayed.

[0106] By displaying the resume data of the map element to be queried, the transparency of the life cycle of the map element can be realized.

[0107] In some embodiments, the identification information of the map element to be queried is the identification information of the map element selected by the user, and the method further includes: displaying the identification information of the map elements available for selection; in the identification information of the map elements available for selection, determining the identification information of the map element selected by the user.

[0108] That is, this embodiment can provide a selection function for map elements to be queried.

[0109] For example, the identification information of the first map element, the identification information of the second map element, and the identification information of the third map element can be displayed, and specifically, they can be displayed in the form of a list.

[0110] After presenting the above list to the user, assuming the user needs to view the resume data of the first map element, the user can select the identification information of the first map element and send a query. Thus, the query instruction can include the identification information of the first map element. After that, the resume data of the first map element can be obtained and displayed.

[0111] By displaying the identification information of the map elements available for selection, it is convenient for the user to select the map elements to be queried and facilitates the user's operation.

[0112] In some embodiments, the at least one operation stage is an already-operated stage, and the obtaining of the query instruction includes: generating the query instruction in response to an operation exception after the already-operated stage; or, taking the troubleshooting instruction actively initiated by the user after the already-operated stage as the query instruction.

[0113] That is, this embodiment can not only query when problems occur in the production stage, but also troubleshoot problems in advance before the problems occur.

[0114] Among them, Figure 5 is a comparison schematic diagram between an embodiment of the present disclosure and related technologies. Among them, the left side is the implementation process of the related technology. In this embodiment, see Figure 5 On the right side, it can be production feedback problems or that the R & D personnel (RD) actively conduct troubleshooting, that is, actively discover problems.

[0115] For the related technology, a process for troubleshooting the cause of an operation exception scenario can be as follows:

[0116] (1) Production feedback: A large amount of operation data has been in progress and has not entered the completed state;

[0117] (2) To troubleshoot this problem, first check the current operation status in the data table. Among them, the status status = 0 indicates that although the operation data has been completed, the storage process after completion has not been triggered, and the reason needs to be further investigated forward

[0118] (3)Continue to check the service logs and analyze according to the process the reason why the storage step was not reached. Then, the following log was found in the service logs: RMQ start to send message: {"xxx":"yyy"}, indicating that after sending the message to RMQ, it did not come back, that is, the sent message was not consumed. So, continue to further analyze the reason why the message was not consumed.

[0119] Among them, RMQ (Rabbit Message Queue) is a message queue middleware similar to Kafka.

[0120] (4)Check from the monitoring page of RMQ that the number of messages in the message queue has reached more than 30,000, forming a backlog, resulting in the sent messages not being consumed in time. The backlog time can be traced back to at least 1 day ago.

[0121] (5)Finally, after expanding the number of RMQ message-consuming clients, it took 12 hours to consume all the backlogged messages. Fortunately, it was just a backlog and there was no data loss or the like. The impact on production was that the production capacity index lagged.

[0122] From the above process, it can be seen that the problem troubleshooting process in the related technology is very cumbersome.

[0123] In this embodiment, whether it is a production feedback problem or an RD actively discovers a problem, the reason can be directly located based on the buried points. For example, query the resume data corresponding to a certain element ID. The resume data can record the operation stages passed by the map element corresponding to the element ID, as well as the detailed information (such as meta-information) of the passed operation stages. Among them, if a certain operation stage is missing, it means that there is an abnormality in this operation stage. In addition, further analysis and processing can be carried out based on the meta-information (element ID, city name, element type, etc.).

[0124] By querying and displaying the resume data of the map elements before the problems occur in the production stage, problems can be discovered in time, thus ensuring the smooth progress of the production stage.

[0125] The above respectively show embodiments from different perspectives. From the overall perspective, as Figure 6 shown, the system for generating the resume data of map elements and processing the resume data can be called a resume system. The resume system may include: an operation platform, kafka buried points, element parsing service, kafka resume, resume page, index service, storage service, and resume service.

[0126] Combined with Figure 6 the system shown, the present disclosure can also provide an embodiment. The process of this embodiment can be referred toFigure 7a - Figure 7b .

[0127] As Figure 7a shown, the data processing method provided in this embodiment may include:

[0128] 701. The job platform sends the buried point data message to kafka buried point.

[0129] Among them, the message queue for storing the buried point data in the above embodiment is called the first message queue. In this embodiment, the first message queue may be specifically represented by kafka buried point.

[0130] In addition, for the buried point data, it can be encapsulated into a message and then sent. The encapsulated message can be called the buried point data message.

[0131] 702. The element parsing service consumes the buried point data message.

[0132] Among them, the element parsing service can adopt a polling method. For example, it fetches messages from the message queue every 30 seconds. For the message queue, the process of fetching and processing the messages can be called consuming messages.

[0133] Correspondingly, the element parsing service can feedback the confirmation of consumption to kafka buried point.

[0134] 703. The element parsing service downloads and parses the job materials.

[0135] Among them, the address information of the job materials may be included in the buried point data, and the job materials can be downloaded based on this address information.

[0136] The job materials may include the element data of at least one map element. By parsing the job materials, the element data of each map element can be obtained.

[0137] 704. The element parsing service sends the element data message to kafka resume.

[0138] Among them, after obtaining the element data of each map element, for each map element, its element data can be encapsulated into an element data message.

[0139] The message queue for storing the element data can be called the second message queue. That is, in this embodiment, the second message queue may be specifically represented by kafka resume.

[0140] 705. The resume service consumes the element data message.

[0141] 706. The resume service generates the resume data of each map element based on the element data of each map element.

[0142] Among them, for each map element, the element data of the operation stages through which the map element passes can be composed into the resume data of the map element.

[0143] 707. The resume service stores the resume data in the storage service.

[0144] Among them, when storing the resume data, the resume index can also be updated. The resume index is used to indicate the storage location.

[0145] In addition, after generating the resume data, the resume service can also update the index information in the index service (not shown in Figure 7a ). The index information is used for the front-end user to query the resume. For example, the corresponding package ID, plan ID, element type, etc. can be found based on the element ID. Thus, the function of querying the resume data of the map element by the package ID (or other ID) can be derived.

[0146] The above process can realize the storage of the resume data of the map element.

[0147] After that, the inquirer can view the resume data. That is, referring to Figure 7b , the data processing method of this embodiment may further include:

[0148] 708. The resume page sends a query instruction to the storage service through the operation platform and the resume service.

[0149] Among them, the query instruction may include the element ID of the map element to be queried.

[0150] 709. The storage service obtains the corresponding resume data of the map element based on the element ID and feeds it back to the resume page for display.

[0151] Thus, the inquirer can query the resume data of the map element through the resume page.

[0152] Furthermore, the inquirer can perform problem location and other processing through the resume data of the map element.

[0153] For the specific implementation of each step of this embodiment, reference can be made to the relevant descriptions in the above embodiments.

[0154] If there is no specific timing limitation relationship, the timing relationship between the steps is not limited.

[0155] In this embodiment, by processing map elements, refined processing at the map element level is achieved. For some job materials where the job has not been completed yet but the map elements have been processed, the consumption at the map element level can be more accurately counted, reflecting the actual production capacity. Instead of only counting at the job material level, the job production capacity index data is improved, and the efficiency of statistical index data is also enhanced. By displaying the history data of map elements, job anomalies in the production process can be promptly detected, providing a visual analysis platform for troubleshooting anomalies. The problem location link can be more intuitively located, greatly improving the problem troubleshooting efficiency. By storing the history data of map elements, unified data management of the operation process of map elements is realized, and a data subscription function at the map element level is provided for external parties. Other parties can subscribe to corresponding services through this system.

[0156] Figure 8 It is a schematic diagram according to the eighth embodiment of the present disclosure. This embodiment provides a data processing device. As Figure 8 shown, the data processing device 800 includes: a first acquisition module 801, a generation module 802, and a first storage module 803.

[0157] The first acquisition module 801 is configured to acquire job materials for each job stage in at least one job stage, where the job materials include element data of at least one map element; the generation module 802 is configured to generate history data of each map element in the at least one map element based on the job materials for each job stage, where the history data includes element data of the job stages through which each map element has passed in the at least one job stage; the first storage module 803 is configured to store the history data of each map element.

[0158] In some embodiments, the first acquisition module 801 is further configured to: acquire the buried point data for each job stage from a preset first message queue, where the buried point data contains the address information of the job materials; and acquire the job materials for each job stage based on the address information of the job materials.

[0159] In some embodiments, the generation module 802 is further configured to: parse the job materials for each job stage to obtain the element data of each map element included in the job materials; and generate the history data of the same map element based on the element data of the job stages through which the same map element has passed.

[0160] In some embodiments, the apparatus 800 further includes: a second storage module, configured to store, for each of the operation stages, the feature data of each of the at least one map feature into a second message queue; the generation module 802 is further configured to: obtain, from the second message queue, the feature data of each of the map features in each of the operation stages; and generate, based on the feature data of each of the map features in each of the operation stages, the resume data of each of the map features.

[0161] In some embodiments, the apparatus 800 further includes: a second acquisition module, configured to acquire a query instruction, where the query instruction includes identification information of a map feature to be queried; a response module, configured to, in response to the query instruction, acquire, from the resume data of each of the map features, the resume data of the map feature to be queried corresponding to the identification information; and a first display module, configured to display the resume data of the map feature to be queried.

[0162] In some embodiments, the identification information of the map feature to be queried is the identification information of a map feature selected by a user, and the apparatus 800 further includes: a second display module, configured to display the identification information of the map features available for selection; and a determination module, configured to determine, from the identification information of the map features available for selection, the identification information of the map feature selected by the user.

[0163] In some embodiments, the at least one operation stage is a completed operation stage, and the second acquisition module is further configured to: in response to an operation anomaly after the completed operation stage, generate the query instruction; or, in response to a troubleshooting instruction actively initiated by the user after the completed operation stage, use the troubleshooting instruction as the query instruction.

[0164] In the embodiments of the present disclosure, by generating the resume data of map features, processing at the map feature level can be achieved. Compared with processing at the operation data level, refined data processing can be realized. In addition, the resume data includes the feature data of the operation stages through which each of the map features has passed in the at least one operation stage, and the operation stages through which the map features have passed can be known through the resume data, thereby reflecting the life cycle of the map features.

[0165] It can be understood that in the embodiments of the present disclosure, the same or similar content in different embodiments can be referred to each other.

[0166] It can be understood that the "first", "second", etc. in the embodiments of the present disclosure are only used for distinction and do not represent high or low importance, sequence order, etc.

[0167] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information and other processing comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0168] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0169] Figure 9 A schematic block diagram of an exemplary electronic device 900 that can be used to implement the embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital assistant, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0170] As Figure 9 shown, the electronic device 900 includes a computing unit 901, which can execute various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the electronic device 900 can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0171] A plurality of components in the electronic device 900 are connected to the I / O interface 905, including: an input unit 906, such as a keyboard, a mouse, etc.; an output unit 907, such as various types of displays, speakers, etc.; a storage unit 908, such as a magnetic disk, an optical disk, etc.; and a communication unit 909, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 909 allows the electronic device 900 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0172] The computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 executes the various methods and processes described above, such as the data processing method. For example, in some embodiments, the data processing method can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the data processing method described above can be executed. Alternatively, in other embodiments, the computing unit 901 can be configured to execute the data processing method by any other suitable means (e.g., by means of firmware).

[0173] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0174] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program code is executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, executed partially on the machine as an independent software package and partially on a remote machine, or executed entirely on a remote machine or server.

[0175] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0176] To provide for interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0177] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0178] A computer system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system or a server combined with a blockchain.

[0179] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitations are imposed herein.

[0180] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A data processing method, comprising: Obtain the operation data of each operation stage in at least one operation stage, where the operation data includes the element data of at least one map element; Generate the resume data of each map element in the at least one map element based on the operation data of each operation stage, where the resume data includes the element data of the operation stages passed by each map element in the at least one operation stage; Store the resume data of each map element; The generating the resume data of each map element in the at least one map element based on the operation data of each operation stage includes: Analyze the operation data of each operation stage to obtain the element data of each map element included in the operation data; For the same map element, generate the resume data of the same map element based on the element data of the operation stages passed by the same map element.

2. The method according to claim 1, wherein, The obtaining the operation data of each operation stage in at least one operation stage includes: Obtain the buried point data of each operation stage from a preset first message queue, where the buried point data contains the address information of the operation data; Based on the address information of the operation data, obtain the operation data of each operation stage.

3. The method according to any one of claims 1-2, further comprising: For each operation stage, store the element data of each map element in the at least one map element into a second message queue; The generating the resume data of each map element in the at least one map element based on the operation data of each operation stage includes: Obtain the element data of each map element in each operation stage from the second message queue; Generate the resume data of each map element based on the element data of each map element in each operation stage.

4. The method according to any one of claims 1-2, further comprising: Obtain a query instruction, where the query instruction contains the identification information of the map element to be queried; In response to the query instruction, obtain the resume data of the map element to be queried corresponding to the identification information in the resume data of each map element; Display the resume data of the map element to be queried.

5. The method according to claim 4, wherein, The identification information of the map element to be queried is the identification information of the map element selected by the user, and the method further includes: Display the identification information of the map elements available for selection; Determine the identification information of the map element selected by the user from the identification information of the map elements available for selection.

6. The method according to claim 4, wherein, The at least one operation stage is a completed operation stage, and the obtaining the query instruction includes: Generate the query instruction in response to an operation exception after the completed operation stage; or, Use the troubleshooting instruction as the query instruction in response to a troubleshooting instruction actively initiated by the user after the completed operation stage.

7. A data processing apparatus, comprising: A first obtaining module, configured to obtain the operation data of each operation stage in at least one operation stage, where the operation data includes the element data of at least one map element; A generation module, configured to generate history data of each of the at least one map element based on the operation data of each operation stage, where the history data includes element data of the operation stages through which each of the at least one map element has passed in the at least one operation stage; A first storage module, configured to store the history data of each of the at least one map element; The generation module is further configured to: Parse the operation data of each operation stage to obtain the element data of each of the at least one map element included in the operation data; For the same map element, generate the history data of the same map element based on the element data of the operation stages through which the same map element has passed.

8. The apparatus according to claim 7, wherein, The first acquisition module is further configured to: Acquire the buried point data of each operation stage from a preset first message queue, where the buried point data includes the address information of the operation data; Based on the address information of the operation data, acquire the operation data of each operation stage.

9. The device according to any one of claims 7 - 8, further comprising: A second storage module, configured to store, for each operation stage, the element data of each of the at least one map element into a second message queue; The generation module is further configured to: Acquire the element data of each of the at least one map element in each operation stage from the second message queue; Based on the element data of each of the at least one map element in each operation stage, generate the history data of each of the at least one map element.

10. The device according to any one of claims 7 - 8, further comprising: A second acquisition module, configured to acquire a query instruction, where the query instruction includes identification information of a map element to be queried; A response module, configured to, in response to the query instruction, acquire the history data of the map element to be queried corresponding to the identification information in the history data of each of the at least one map element; A first display module, configured to display the history data of the map element to be queried.

11. The device according to claim 10, wherein, The identification information of the map element to be queried is the identification information of the map element selected by the user, and the apparatus further includes: A second display module, configured to display the identification information of the map elements available for selection; A determination module, configured to determine the identification information of the map element selected by the user from the identification information of the map elements available for selection.

12. The device according to claim 10, wherein, The at least one operation stage is an operation stage that has been completed, and the second acquisition module is further configured to: In response to an operation exception after the operation stage that has been completed, generate the query instruction; or In response to a troubleshooting instruction actively initiated by the user after the operation stage that has been completed, use the troubleshooting instruction as the query instruction.

13. An electronic device, comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-6.

14. A non - transitory computer - readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

15. A computer program product, comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 - 6.

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