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

Abstract

The embodiment of the invention provides a vehicle data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: determining N databases according to N vehicle identification codes and original vehicle data; grouping the N databases according to the vehicle identification codes, and determining M database groups; and storing the M database groups by taking the unique identifier corresponding to the preset time period and the name of the database group as a path. It can be understood that each database is in one-to-one correspondence with the vehicle identification codes, and the N databases are also grouped through the vehicle identification codes, so that M database groups are determined. Therefore, when the vehicle data corresponding to the vehicle needs to be called, the storage path corresponding to the vehicle data is quickly determined according to the vehicle identification code, and then the related data of the target vehicle is screened out. In a certain degree, the scanning retrieval amount when the data server side queries the vehicle data is reduced, the scanning retrieval time is shortened, and meanwhile, the performance proportion of the data server side during scanning retrieval is released.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, device, electronic device and storage medium for processing vehicle data. Background Art

[0002] With the popularization of the Internet of Vehicles, vehicle data has shown explosive growth, which has put higher requirements on the storage and export technology of data servers.

[0003] At present, data servers usually use Hadoop Distributed File System (HDFS) to store large-scale vehicle data. All data is continuously written to HDFS, and the file is mapped into a data table by using the data warehouse tool. Then the vehicle data can be queried based on the data table. Specifically, when it is necessary to download the vehicle data of a vehicle for one day, the retrieval process often requires the use of more than 50 CPU cores to query the data of all vehicles on that day (tens of billions of data), scan and filter out the relevant data of the target vehicle, and then merge the data of different data segments.

[0004] It is understandable that in the process of acquiring the above-mentioned vehicle data, it is necessary to scan and retrieve tens of billions of data, which results in high resource usage on the data server and a long scanning and retrieval time.

[0005] It should be pointed out that the information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or suggestion in any form that the information constitutes prior art already known to those skilled in the art. Summary of the invention

[0006] In view of this, the present application provides a vehicle data processing method, device, electronic device and storage medium, so as to solve the problem in the prior art that in the process of acquiring vehicle data, it is necessary to scan and retrieve tens of billions of data, resulting in high resource usage on the data server and a long scanning and retrieval time.

[0007] In a first aspect, an embodiment of the present application provides a method for processing vehicle data, which is applied to a data server, wherein the data server is used to receive vehicle data of N vehicles, where N≥1, and the method includes: Determine N databases according to N vehicle identification codes and original vehicle data, wherein the vehicle data in each of the N databases corresponds one-to-one to the vehicle corresponding to each of the N vehicle identification codes, and the original vehicle data is the vehicle data received by the data service end within a preset time period; Grouping the N databases according to the vehicle identification code to determine M database groups, wherein 1≤M≤N, and each of the N vehicle identification codes corresponds to one of the M database groups; The M database groups are stored using the unique identifier corresponding to the preset time period and the database group name as a path, wherein the database group name is used to represent the correspondence between one or more of the N vehicle identification codes and a corresponding database group.

[0008] In an embodiment of the present application, first, N databases are determined based on N vehicle identification codes and original vehicle data; the N databases are grouped according to the vehicle identification code to determine M database groups; and the M database groups are stored using the unique identifier corresponding to the preset time period and the database group name as the path. It can be understood that since each database corresponds to a vehicle identification code one-to-one, and the N databases are also grouped by the vehicle identification code, M database groups are determined. Therefore, when the vehicle data corresponding to the vehicle needs to be called, the storage path of the corresponding vehicle data is quickly determined according to the vehicle identification code, and then the relevant data of the target vehicle is filtered out. To a certain extent, the amount of scanning and retrieval when the data server queries vehicle data is reduced, the scanning and retrieval time is reduced, and the performance share of the data server during scanning and retrieval is released.

[0009] In a possible implementation, the data server is further used to output the vehicle data of one or more vehicles, and after the unique identifier corresponding to the preset time period and the name of the database group as the path, further includes: In response to a data export operation of a target vehicle within a target preset time period triggered by a user, a target vehicle identification code and a unique identifier corresponding to the target preset time period are determined, wherein the target vehicle identification code is a vehicle identification code corresponding to the target vehicle; Determine a target database group name according to the target vehicle identification code; Determine the target database group using the unique identifier corresponding to the target preset time period and the target database group name as a path; According to the target vehicle identification code, a database corresponding to the target vehicle is determined and output from the target database group.

[0010] In the embodiment of the present application, in response to the data export operation of the target vehicle within the target preset time period triggered by the user, the target vehicle identification code and the unique identifier corresponding to the target preset time period are determined; according to the target vehicle identification code, the target database group name is determined; the target database group is determined with the unique identifier corresponding to the target preset time period and the target database group name as the path; according to the target vehicle identification code, the database corresponding to the target vehicle is determined and output from the target database group. It can be understood that in response to the needs of the user, the path to obtain the database corresponding to the target vehicle data can be directly generated, thereby reducing the amount of scanning and retrieval when the data service end queries the vehicle data, reducing the scanning and retrieval time, and releasing the performance share of the data service end during scanning and retrieval.

[0011] In a possible implementation manner, the unique identifier corresponding to the preset time period is the date and time corresponding to the preset time period.

[0012] In an embodiment of the present application, the unique identifier corresponding to the preset time period is the date and time corresponding to the preset time period, which, to a certain extent, ensures the accuracy of the path used to store the M database groups, thereby reducing the scanning and retrieval time, and at the same time releases the performance share of the data server during scanning and retrieval.

[0013] In a possible implementation, grouping the N databases according to the vehicle identification code to determine M database groups includes: The N databases are grouped according to the hash algorithm model and the vehicle identification code to determine M database groups and a database group name corresponding to each database group, wherein the hash algorithm model is used to output one of the M hash values ​​according to the input vehicle identification code; and the hash value is used as the database group name.

[0014] In the embodiment of the present application, N databases are grouped according to the hash algorithm model and the vehicle identification code, and M database groups and the database group name corresponding to each database group are determined. It can be understood that the N databases can be grouped more evenly based on the hash algorithm model, which can effectively prevent the amount of data in a database group from being too large to a certain extent, thereby reducing the amount of scanning and retrieval when the data server queries vehicle data, reducing the scanning and retrieval time, and releasing the performance share of the data server during scanning and retrieval.

[0015] In a possible implementation, determining the target database group name according to the target vehicle identification code includes: According to the hash algorithm model and the target vehicle identification code, a target database group name is determined, where the target database group name is a hash value corresponding to the target vehicle identification code.

[0016] In the embodiment of the present application, the target database group name is determined according to the hash algorithm model and the target vehicle identification code. It can be understood that since the grouping of N databases is achieved through the hash algorithm model and the vehicle identification code, the name of the target database group can be quickly and accurately determined through the hash algorithm model and the target vehicle identification code, which, to a certain extent, reduces the amount of scanning and retrieval when the data service end queries vehicle data, and reduces the scanning and retrieval time.

[0017] In a possible implementation, the storing M database groups using the unique identifier corresponding to the preset time period and the database group name as a path includes: Compressing the M database groups to determine M database group compression packages; The M database compression packages are stored using the unique identifier corresponding to the preset time period and the database group name as a path.

[0018] In the embodiment of the present application, M database groups are compressed to determine M database group compression packages; the M database compression packages are stored using the unique identifier corresponding to the preset time period and the database group name as the path. It can be understood that compressing the M database groups reduces the storage space occupied by the data server to a certain extent.

[0019] In a possible implementation, the determining the target database group by using the unique identifier corresponding to the target preset time period and the target database group name as a path includes: Retrieve the unique identifier corresponding to the target preset time period and the target database group name as a path to determine whether the target database group exists; When a target database group exists, the target database group is determined by taking the unique identifier corresponding to the target preset time period and the name of the target database group as a path.

[0020] In the embodiment of the present application, the unique identifier corresponding to the target preset time period and the target database group name are first retrieved as the path to determine whether the target database group exists; when the target database group exists, the unique identifier corresponding to the target preset time period and the target database group name are used as the path to determine the target database group. It can be understood that before retrieving the target database according to the determined path, it is first determined whether the target database exists under the path, which to a certain extent reduces the amount of scanning and retrieval when the data service end queries vehicle data, reduces the scanning and retrieval time, and releases the performance share of the data service end during scanning and retrieval.

[0021] In a possible implementation, the method further includes: When the target database group does not exist, a user prompt message is output to prompt the user that the vehicle data of the target vehicle is not stored in the data server.

[0022] In the embodiment of the present application, when the target database group does not exist, the user prompt information is output. It can be understood that since the user prompt information is used to prompt the user that the vehicle data of the target vehicle is not stored in the data server, it can ensure that when the target database group cannot be retrieved, the user is reminded in time, which improves the user experience to a certain extent.

[0023] In a second aspect, an embodiment of the present application provides a vehicle data processing device, which is applied to a data server, wherein the data server is used to receive vehicle data of N vehicles, where N≥1, and the device includes: A database determination module, configured to determine N databases according to N vehicle identification codes and original vehicle data, wherein the vehicle data in each of the N databases corresponds one-to-one to the vehicle corresponding to each of the N vehicle identification codes, and the original vehicle data is the vehicle data received by the data service end within a preset time period; a database group determination module, configured to group the N databases according to the vehicle identification code to determine M database groups, wherein 1≤M≤N, and each of the N vehicle identification codes corresponds to one of the M database groups; The database group storage module is used to store the M database groups using the unique identifier corresponding to the preset time period and the database group name as a path, wherein the database group name is used to represent the correspondence between one or more of the N vehicle identification codes and a corresponding database group.

[0024] In a third aspect, an electronic device is provided in an embodiment of the present application, characterized in that it includes: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes any one of the methods described in the first aspect.

[0025] In a fourth aspect, a computer-readable storage medium is provided in an embodiment of the present application, characterized in that the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described in the first aspect.

[0026] It can be understood that the vehicle data processing device provided in the second aspect, the electronic device provided in the third aspect, and the computer-readable storage medium provided in the fourth aspect are all used to execute the method provided in the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0028] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application.

[0029] Figure 2 A flowchart of a method for processing vehicle data provided in an embodiment of the present application.

[0030] Figure 3 A flowchart of another method for processing vehicle data provided in an embodiment of the present application.

[0031] Figure 4 A schematic diagram of the structure of a vehicle data processing device provided in an embodiment of the present application.

[0032] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0034] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0035] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0036] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0037] To facilitate understanding, a specific application scenario is first exemplified below.

[0038] See also Figure 1 , is a schematic diagram of an application scenario provided by an embodiment of the present application. Figure 1 As shown, the application scenario includes: a vehicle 101 and a data service end 102. The vehicle 101 and the data service end 102 are interconnected through a wireless communication network to transmit information. The communication network can be a local area network or a wide area network transferred through a relay device. When the communication network is a local area network, exemplarily, the communication network can be a short-range communication network such as a wifi hotspot network, a Bluetooth network, a zigbee network or a near field communication (NFC) network. When the communication network is a wide area network, exemplarily, the communication network can be a third-generation wireless telephone technology (3G) network, a fourth-generation mobile communication technology (4G) network, a fifth-generation mobile communication technology (5G) network, a future-evolved public land mobile network (PLMN) or the Internet, etc.

[0039] In actual vehicle driving, the vehicle will upload a large amount of vehicle data (such as vehicle operation data, vehicle condition data, vehicle driving data, vehicle log data, and engine working data, etc.) to the data server for storage, so that the vehicle data can be called when needed later. For example, when a vehicle needs to be diagnosed, the diagnostic data of the vehicle needs to be called from the data server, and then the relevant diagnosis of the vehicle is performed based on the diagnostic data.

[0040] It is understandable that before calling the data, the vehicle data is first stored. At present, the data server usually uses Hadoop Distributed File System (HDFS) to store large-scale vehicle data. All data is continuously written to HDFS, and the file is mapped into a data table by using the data warehouse tool. Then the vehicle data can be queried based on the data table. Specifically, when it is necessary to download the vehicle data of a vehicle for one day, the retrieval process often requires the use of more than 50 CPU cores to query the data of all vehicles on that day (tens of billions of data), scan and filter out the relevant data of the target vehicle, and then merge the data of different data segments.

[0041] It is understandable that in the process of acquiring the above-mentioned vehicle data, it is necessary to scan and retrieve tens of billions of data, which results in high resource usage on the data server and a long scanning and retrieval time.

[0042] In view of the above problems, in an embodiment of the present application, first, N databases are determined based on N vehicle identification codes and original vehicle data; the N databases are grouped according to the vehicle identification code to determine M database groups; and the M database groups are stored using the unique identifier corresponding to the preset time period and the database group name as the path. It can be understood that since each database corresponds to a vehicle identification code one-to-one, and the N databases are also grouped by the vehicle identification code, M database groups are determined. Therefore, when it is necessary to call the vehicle data corresponding to the vehicle, the storage path of the corresponding vehicle data is quickly determined according to the vehicle identification code, and then the relevant data of the target vehicle is filtered out. To a certain extent, the amount of scanning and retrieval when the data server queries the vehicle data is reduced, the scanning and retrieval time is reduced, and the performance share of the data server during scanning and retrieval is released. Specifically, it is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0043] See also Figure 2 , is a flow chart of a method for processing vehicle data provided in an embodiment of the present application. The method can be applied to Figure 1 The application scenarios shown are as follows: Figure 2 As shown, it mainly includes the following steps.

[0044] Step S201: Determine N databases according to N vehicle identification codes and original vehicle data.

[0045] In the embodiment of the present application, N databases are determined based on N vehicle identification codes and original vehicle data. The vehicle data in each of the N databases corresponds one-to-one to the vehicle corresponding to each of the N vehicle identification codes; the original vehicle data is the vehicle data received by the data service end within a preset time period; N≥1.

[0046] Exemplarily, the preset time may be one day, that is, the data service end collects vehicle data (ie, raw vehicle data) for one day and then organizes and stores the raw vehicle data.

[0047] Specifically, the original vehicle data is first acquired, and then the original vehicle data is divided into N databases according to the vehicle identification code.

[0048] In a possible implementation, each database is named as a vehicle identification code. It should be noted that the vehicle identification code of each vehicle is unique, so each database only contains data related to one vehicle and contains all data related to the vehicle in the original data.

[0049] Step S202: grouping the N databases according to the vehicle identification codes to determine M database groups.

[0050] In the embodiment of the present application, after N databases are determined, the N databases are grouped according to the vehicle identification code to determine M database groups, where 1≤M≤N, and each of the N vehicle identification codes corresponds to one of the M database groups.

[0051] It is understandable that when the data server serves a large number of vehicles, in order to further reduce the retrieval volume of the data server, the determined database can be further grouped based on the vehicle identification code.

[0052] Specifically, in one possible implementation, N databases are grouped according to a hash algorithm model and a vehicle identification code to determine M database groups and a database group name corresponding to each database group, wherein the hash algorithm model is used to output one of the M hash values ​​according to an input vehicle identification code; and the hash value is used as the database group name.

[0053] Specifically, in a possible implementation, the hash algorithm model can intercept the last three digits of the vehicle identification code for hash operation; wherein the result value range is [0,999], that is, M is 1000.

[0054] In an embodiment of the present application, N databases can be grouped more evenly based on the hash algorithm model. To a certain extent, this can effectively prevent the amount of data in a certain database group from being too large, thereby reducing the amount of scanning and retrieval when the data server queries vehicle data, reducing the scanning and retrieval time, and at the same time releasing the performance share of the data server during scanning and retrieval.

[0055] Of course, relevant technical personnel in this field can also use other algorithm models, or adjust the hash algorithm model to group N databases according to actual needs, and this application does not impose any specific restrictions on this.

[0056] Step S203: using the unique identifier corresponding to the preset time period and the database group name as a path, M database groups are stored.

[0057] In the embodiment of the present application, after N databases are divided into M database groups, the M database groups are stored using the unique identifier corresponding to the preset time period and the database group name as the path. It can be understood that the database group name is used to represent the correspondence between one or more of the N vehicle identification codes and a corresponding database group.

[0058] In one possible implementation, the unique identifier corresponding to the preset time period is the date and time corresponding to the preset time period. For example, when the preset time period is one day, the unique identifier corresponding to the preset time period may be the date of the day, i.e., 2024 / 12 / 13; when the preset time period is 2 hours, the unique identifier corresponding to the preset time period may be the specific time of the day, i.e., 2024 / 12 / 1 / 15:00-2024 / 12 / 1 / 17:00.

[0059] In an embodiment of the present application, the unique identifier corresponding to the preset time period is the date and time corresponding to the preset time period, which, to a certain extent, ensures the accuracy of the path used to store the M database groups, thereby reducing the scanning and retrieval time, and at the same time releases the performance share of the data server during scanning and retrieval.

[0060] Of course, relevant technicians in this field can also choose other information to represent the unique identifier of the preset time period, and this application does not make any specific restrictions on this.

[0061] Therefore, taking 2024 / 12 / 13 as the unique identifier corresponding to the preset time period and the database name as 100 as an example, the meaning of the unique identifier corresponding to the preset time period and the database group name as the path described above is: under the folder named 2024 / 12 / 13, there are M database groups saved, one of which is named 100.

[0062] In a possible implementation, firstly, the M database groups are compressed to determine the M database group compression packages; the M database compression packages are stored using the unique identifier corresponding to the preset time period and the database group name as the path. It can be understood that compressing the M database groups reduces the storage space occupied by the data server to a certain extent.

[0063] In the embodiment of the present application, since each database corresponds to a vehicle identification code one by one, and the N databases are also grouped by the vehicle identification code, M database groups are determined. Therefore, when the vehicle data corresponding to the vehicle needs to be called, the storage path of the corresponding vehicle data is quickly determined according to the vehicle identification code, and then the relevant data of the target vehicle is filtered out. To a certain extent, the scanning and retrieval amount when the data server queries the vehicle data is reduced, the scanning and retrieval time is reduced, and the performance share of the data server during scanning and retrieval is released.

[0064] In an embodiment of the present application, when the method embodiment corresponding to the above steps S201 to S203 is used to store vehicle data, the following method embodiment may be used to export the vehicle data of the target vehicle.

[0065] Specifically, see Figure 3 , is a flow chart of another method for processing vehicle data provided in an embodiment of the present application. The method can be applied to Figure 1 The application scenarios shown are as follows: Figure 3 As shown, when Figure 2 When storing vehicle data in the illustrated method embodiment, a database corresponding to the target vehicle may be outputted as follows.

[0066] Step S301: In response to a data export operation of a target vehicle within a target preset time period triggered by a user, a target vehicle identification code and a unique identifier corresponding to the target preset time period are determined.

[0067] In an embodiment of the present application, in response to a data export operation of a target vehicle within a target preset time period triggered by a user, a target vehicle identification code and a unique identifier corresponding to the target preset time period are determined.

[0068] For example, when the preset time period is one day, the user wants to export the vehicle data of the target vehicle on 2024 / 12 / 13, and first determines the target vehicle identification code and the unique identifier corresponding to the target preset time period (ie, 2024 / 12 / 13).

[0069] Step S302: Determine the target database group name according to the target vehicle identification code.

[0070] As described in the above embodiment, when storing vehicle data, the database is grouped according to the vehicle identification code to generate M database groups. Since the name of each database group corresponds to the vehicle identification code, in the embodiment of the present application, the target database group name can be determined according to the target vehicle identification code.

[0071] In practical applications, when storing vehicle data, the database is grouped based on a hash algorithm model, and the target database group name also needs to be determined based on the same hash algorithm model.

[0072] Specifically, in a possible implementation, the target database group name is determined according to the hash algorithm model and the target vehicle identification code. It can be understood that since the grouping of N databases is achieved through the hash algorithm model and the vehicle identification code, the name of the target database group can be quickly and accurately determined through the hash algorithm model and the target vehicle identification code, which, to a certain extent, reduces the amount of scanning and retrieval when the data server queries vehicle data, and reduces the scanning and retrieval time.

[0073] Step S303: determine the target database group using the unique identifier corresponding to the target preset time period and the target database group name as a path.

[0074] In the embodiment of the present application, after the unique identifier corresponding to the target preset time period and the target database group name are determined, the target database group is determined as a path.

[0075] Of course, it should be pointed out that when there is a data compression step when storing vehicle data, the relevant files are also decompressed in the process of determining the target database group using the unique identifier corresponding to the target preset time period and the target database group name as the path.

[0076] In actual applications, the path may not exist based on the unique identifier corresponding to the target preset time period and the target database group name, or the target database group does not exist at the end of the path. Therefore, before actually obtaining the target database group, it is first determined whether the target database group exists.

[0077] Specifically, in a possible implementation, a unique identifier corresponding to the target preset time period and a target database group name are retrieved as a path to determine whether a target database group exists; when a target database group exists, the target database group is determined using the unique identifier corresponding to the target preset time period and the target database group name as a path.

[0078] It can be understood that before retrieving the target database according to the determined path, it is first determined whether the target database exists under the path, which to a certain extent reduces the scanning and retrieval amount when the data server queries vehicle data, reduces the scanning and retrieval time, and releases the performance share of the data server during scanning and retrieval.

[0079] In a possible implementation, when the target database group does not exist, a user prompt information is output to prompt the user that the vehicle data of the target vehicle is not stored in the data server. It can be understood that since the user prompt information is used to prompt the user that the vehicle data of the target vehicle is not stored in the data server, it can ensure that when the target database group cannot be retrieved, the user is reminded in time, which improves the user experience to a certain extent.

[0080] Step S304: According to the target vehicle identification code, determine and output a database corresponding to the target vehicle from the target database group.

[0081] In the embodiment of the present application, according to the target vehicle identification code, a database corresponding to the target vehicle is determined and output from the target database group.

[0082] In an embodiment of the present application, in response to user needs, a path to a database corresponding to target vehicle data can be directly generated, thereby reducing the amount of scanning and retrieval when the data server queries vehicle data, reducing the scanning and retrieval time, and releasing the performance share of the data server during scanning and retrieval.

[0083] Corresponding to the above embodiment, the present application also provides a vehicle data processing device. Figure 4 , is a schematic diagram of the structure of a vehicle data processing device provided in an embodiment of the present application, as shown in the figure, a vehicle data processing device 400 is shown. Among them, the vehicle data processing device 400 specifically includes: a database determination module 401, a database group determination module 402 and a database group storage module 403. Specifically, the database determination module is used to determine N databases according to N vehicle identification codes and original vehicle data; the database group determination module is used to group N databases according to the vehicle identification code to determine M database groups; the database group storage module is used to store the M database groups using the unique identifier corresponding to the preset time period and the database group name as the path.

[0084] The specific contents involved in the examples in the implementation of this application can be found in the description of the above method embodiments. For the sake of brevity, they will not be repeated here.

[0085] Corresponding to the above embodiment, the present application also provides an electronic device. Figure 5 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, and the electronic device 500 may include: a processor 501, a memory 502, and a communication unit 503. These components communicate through one or more buses. Those skilled in the art can understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiment of the present invention. It can be a bus structure or a star structure, and can also include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0086] The communication unit 503 is used to establish a communication channel so that the electronic device can communicate with other devices, receive user data sent by other devices or send user data to other devices.

[0087] The processor 501 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It runs or executes software programs, instructions, and / or modules stored in the memory 502, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 501 can only include a central processing unit (CPU). In an embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0088] The memory 502 is used to store the execution instructions of the processor 501. The memory 502 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0089] When the execution instruction in the memory 502 is executed by the processor 501, the electronic device 500 can execute Figure 2 as well as Figure 3 Some or all of the steps in the illustrated embodiments.

[0090] In a specific implementation, the present application further provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment of the simulation scene generation method provided by the present invention. The storage medium may be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0091] In a specific implementation, the present application also provides a computer program product, wherein the computer program product includes executable instructions, and when the executable instructions are executed on a computer, the computer executes part or all of the steps in each embodiment of the simulation scene generation method provided by the present invention.

[0092] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0093] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0094] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0095] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0096] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the device embodiment and the terminal embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

Claims

1. A method for processing vehicle data, characterized in that: Applied to a data server, the data server is used to receive vehicle data of N vehicles, N≥1, the method comprises: Determine N databases according to N vehicle identification codes and original vehicle data, wherein the vehicle data in each of the N databases corresponds one-to-one to the vehicle corresponding to each of the N vehicle identification codes, and the original vehicle data is the vehicle data received by the data service end within a preset time period; Grouping the N databases according to the vehicle identification code to determine M database groups, wherein 1≤M≤N, and each of the N vehicle identification codes corresponds to one of the M database groups; The M database groups are stored using the unique identifier corresponding to the preset time period and the database group name as a path.

2. The method according to claim 1, characterized in that The data service end is further used to output the vehicle data of one or more vehicles, and after the unique identifier corresponding to the preset time period and the name of the database group as the path, further includes: In response to a data export operation of a target vehicle within a target preset time period triggered by a user, a target vehicle identification code and a unique identifier corresponding to the target preset time period are determined, wherein the target vehicle identification code is a vehicle identification code corresponding to the target vehicle; Determine a target database group name according to the target vehicle identification code; Determine the target database group using the unique identifier corresponding to the target preset time period and the target database group name as a path; According to the target vehicle identification code, a database corresponding to the target vehicle is determined and output from the target database group.

3. The method according to claim 1, characterized in that The unique identifier corresponding to the preset time period is the date and time corresponding to the preset time period.

4. The method according to claim 2, characterized in that: The step of grouping the N databases according to the vehicle identification code to determine M database groups includes: The N databases are grouped according to the hash algorithm model and the vehicle identification code to determine M database groups and a database group name corresponding to each database group, wherein the hash algorithm model is used to output one of the M hash values ​​according to the input vehicle identification code; and the hash value is used as the database group name.

5. The method according to claim 4, characterized in that The step of determining a target database group name according to the target vehicle identification code includes: According to the hash algorithm model and the target vehicle identification code, a target database group name is determined, where the target database group name is a hash value corresponding to the target vehicle identification code.

6. The method according to claim 1, characterized in that The storing of M database groups using the unique identifier corresponding to the preset time period and the database group name as a path includes: Compressing the M database groups to determine M database group compression packages; The M database compression packages are stored using the unique identifier corresponding to the preset time period and the database group name as a path.

7. The method according to claim 2, characterized in that The determining the target database group by using the unique identifier corresponding to the target preset time period and the target database group name as a path includes: Retrieve the unique identifier corresponding to the target preset time period and the target database group name as a path to determine whether the target database group exists; When a target database group exists, the target database group is determined by taking the unique identifier corresponding to the target preset time period and the name of the target database group as a path.

8. The method according to claim 7, characterized in that Also includes: When the target database group does not exist, a user prompt message is output to prompt the user that the vehicle data of the target vehicle is not stored in the data server.

9. A vehicle data processing device, characterized in that: Applied to a data service end, the data service end is used to receive vehicle data of N vehicles, N≥1, and the device includes: A database determination module, configured to determine N databases according to N vehicle identification codes and original vehicle data, wherein the vehicle data in each of the N databases corresponds one-to-one to the vehicle corresponding to each of the N vehicle identification codes, and the original vehicle data is the vehicle data received by the data service end within a preset time period; a database group determination module, configured to group the N databases according to the vehicle identification code to determine M database groups, wherein 1≤M≤N, and each of the N vehicle identification codes corresponds to one of the M database groups; The database group storage module is used to store the M database groups using the unique identifier corresponding to the preset time period and the database group name as a path, wherein the database group name is used to represent the correspondence between one or more of the N vehicle identification codes and a corresponding database group.

10. An electronic device, characterized in that: include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 8.

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