Data processing method, computer equipment and program product

Abstract

The invention provides a data processing method, computer equipment and a program product, and the method comprises the steps: obtaining a first data processing task from a source end; the source end comprises any one of a plurality of vehicle ends and / or a plurality of cloud ends; the first data processing task is initiated by calling a target interface in a plurality of data operation interfaces corresponding to the cloud database by the source end, and is used for indicating to carry out data processing on a target file in the cloud database; obtaining a current operation state corresponding to the target file; if the current operation state indicates that the target file is currently subjected to data operation, caching a first data processing task to a corresponding position in a task queue according to a first task priority of the first data processing task compared with each second data processing task in the task queue corresponding to the target file; the second data processing tasks are from different source ends; and in response to the first data processing task extracted from the task queue, executing the first data processing task.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent driving technology, and in particular to a data processing method, a computer device, and a program product. Background Art

[0002] With the rapid development of intelligent driving technology, more and more new energy vehicles are equipped with intelligent driving functions, and the intelligent driving functions available are becoming more and more abundant. The realization of intelligent driving functions is inseparable from the drive of big data. Under the drive of big data, data interaction between the vehicle and the cloud or between the cloud and the cloud is becoming more and more frequent. However, for the existing data interaction methods, not only is there a problem of poor real-time interaction, but also data processing conflicts when multiple terminals initiate data interaction tasks with the cloud at the same time. The disadvantages are quite obvious. Summary of the invention

[0003] The embodiments of the present disclosure at least provide a data processing method, a computer device, and a program product.

[0004] In a first aspect, an embodiment of the present disclosure provides a data processing method, including:

[0005] Acquire a first data processing task from a source end; the source end includes any one of a plurality of vehicle ends and / or a plurality of clouds; the first data processing task is initiated by the source end calling a target interface among a plurality of data operation interfaces corresponding to a cloud database, and is used to instruct data processing of a target file in the cloud database;

[0006] Acquire a current operation status corresponding to the target file; the current operation status is used to indicate whether a data operation is currently being performed on the target file;

[0007] If the current operation status indicates that a data operation is currently being performed on the target file, the first data processing task is cached to a corresponding position in the task queue corresponding to the target file according to a first task priority of the first data processing task compared to each second data processing task in the task queue corresponding to the target file; each second data processing task comes from a different source end;

[0008] In response to extracting the first data processing task from the task queue, executing the first data processing task.

[0009] In this implementation mode, the source end directly calls the unified data operation interface developed for the cloud database to initiate the data processing task, which can realize real-time data processing (for example, real-time data writing, real-time data editing, real-time data query, etc.) of the cloud database, and improves the real-time nature of data interaction. When executing the data processing task, by obtaining the current operation status of the target file targeted by the data processing task, it can be determined whether the target file is currently being operated, that is, whether the data operation is currently being performed on the target file. Then, it can be determined whether the target file can be directly operated and processed according to the current operation status, avoiding the problem of processing conflicts caused by the newly initiated data processing task directly operating and processing the target file when the first initiated data processing task processes the target file. In addition, when it is determined according to the current operation status that the target file is being operated, it means that there are currently second data processing tasks related to the target file and these second data processing tasks are waiting in line for execution. Therefore, by determining the first task priority of the first data processing task obtained and caching it to the corresponding position of the task queue, it can be realized that each processing task is executed in sequence according to the order in the task queue, avoiding the problem of processing conflicts caused by directly executing the first data processing task. And executing each processing task in sequence according to the task queue can ensure the smooth execution of the first data processing task while completing the sequential processing of various concurrent tasks for the same target file, thereby avoiding processing conflicts among multiple concurrent processing tasks.

[0010] In a possible implementation, the method further includes:

[0011] If the current operation state indicates that no data operation is currently being performed on the target file, determining whether there is a third data processing task for the target file;

[0012] If yes, create a task queue corresponding to the target file, and determine the second task priority of the first data processing task and each of the third data processing tasks;

[0013] Execute the data processing task with the highest second task priority, update the current operation status of the target file, and, according to the second task priority, cache other data processing tasks except the one with the highest second task priority to the task queue.

[0014] In this implementation, for a target file that is not currently being operated on, by judging whether there is currently a third data processing task for the target file, it can be determined whether there are currently multiple unexecuted tasks for the same target file. In the case where there are multiple third data processing tasks, by timely creating a task queue and caching the first data processing task and the third data processing task according to the second priority, the sequential processing of each data processing task can be achieved, thereby avoiding processing conflicts among multiple concurrent processing tasks.

[0015] In a possible implementation manner, after determining whether there is a third data processing task for the target file, the method further includes:

[0016] If the third data processing task does not exist, the first data processing task is executed and the current operation status of the target file is updated.

[0017] In this implementation, when there is no third data processing task, it means that there is only one data processing task for the target file, namely the first data processing task. Therefore, by directly executing the first data processing task, the timeliness of the first data processing task can be improved.

[0018] In a possible implementation, obtaining the current operation status corresponding to the target file includes:

[0019] Obtaining a lock status flag corresponding to the target file;

[0020] When the lock status flag is the first flag, determining the current operation status of the target file is that no data operation is currently being performed on the target file; or

[0021] When the lock status flag is the second flag, it is determined that the current operation status of the target file is that data operation is currently being performed on the target file.

[0022] This implementation method can quickly determine the current operation status of the target file by acquiring the lock status identification bit.

[0023] In a possible implementation manner, the first task priority of the first data processing task compared to each of the second data processing tasks is determined according to the following steps:

[0024] Determine the first task priority of the first data processing task according to the time sequence of the timestamps of the first data processing task and each of the second data processing tasks; wherein the timestamp is generated for the first data processing task when the source end initiates the first data processing task; and the timestamps of different first data processing tasks are different.

[0025] This implementation method determines the task priority according to the time sequence of the timestamps, so that the execution sequence of the first data processing task can be consistent with the initiation time sequence relative to each second data processing task, thereby improving the rationality of task priority determination.

[0026] In a possible implementation, the data operation interface includes a data adding interface, a data deleting interface, a data modifying interface and a data querying interface; the data processing task includes at least one of a data adding task, a data deleting task, a data modifying task and a data querying task;

[0027] In a case where the first data processing task includes the data augmentation task, acquiring the data augmentation task includes:

[0028] In response to the source end calling the data adding interface, obtaining the file name and the data to be added input by the source end; the file name is related to at least one of the source end's identification, date information, and location information of the source end;

[0029] The data adding task is generated according to the file name and the data to be added.

[0030] In this implementation, by calling the data adding interface and inputting relevant parameters (ie, the file name and the data to be added), the source end can write data to the target file, thereby improving the real-time performance of data writing.

[0031] In a possible implementation manner, when the first data processing task includes a data modification task, obtaining the data modification task includes:

[0032] In response to the source end calling the data modification interface, using the data query interface, obtaining each database file from the cloud database and feeding it back to the source end;

[0033] Obtaining a modification instruction from the source end for a target file in a database file; the modification instruction includes a modification instruction for the target file or a modification instruction for source data in the target file;

[0034] The data modification task is generated according to the modification instruction.

[0035] This implementation method, when the source end needs to initiate a data modification task, can help the source end accurately determine each database file included in the cloud database by first querying the database file and providing feedback, thereby achieving targeted modification of the database file.

[0036] In a possible implementation manner, when the first data processing task includes a data deletion task, obtaining the data deletion task includes:

[0037] In response to the source end calling the data deletion interface, using the data query interface, obtaining each database file from the cloud database and feeding it back to the source end;

[0038] Obtaining a deletion instruction from the source end for a target file in a database file; the deletion instruction includes a deletion instruction for the target file or a deletion instruction for source data in the target file;

[0039] The data deletion task is generated according to the deletion instruction.

[0040] This implementation method, when the source end needs to initiate a data deletion task, by first querying the database file and providing feedback, can help the source end accurately determine the various database files included in the cloud database, and then achieve targeted deletion of the database files.

[0041] In a second aspect, an optional implementation of the present disclosure further provides a computer device, a processor, and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is used to execute the machine-readable instructions stored in the memory, and when the machine-readable instructions are executed by the processor, the steps of the above-mentioned first aspect, or any possible implementation of the first aspect are performed.

[0042] In a third aspect, an optional implementation of the present disclosure further provides a computer program product, which, when executed, executes the steps of the above-mentioned first aspect, or any possible implementation of the first aspect.

[0043] For a description of the effects of the above-mentioned computer device and computer program product, please refer to the description of the above-mentioned data processing method, which will not be repeated here.

[0044] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following is a brief introduction to the drawings required for use in the embodiments. The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can also be obtained based on these drawings without creative work.

[0046] Figure 1 A flow chart of a data processing method provided by an embodiment of the present disclosure is shown;

[0047] Figure 2 A system block diagram of a multi-vehicle multi-cloud multi-task data processing flow provided by an embodiment of the present disclosure is shown;

[0048] Figure 3 A specific implementation flow chart of a data processing method provided by an embodiment of the present disclosure is shown;

[0049] Figure 4 A schematic diagram of the structure of a computer device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure is not intended to limit the scope of the present disclosure claimed for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

[0051] In addition, the terms "first", "second", etc. in the description and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein.

[0052] The "multiple or several" mentioned in this article refers to two or more. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0053] According to research, the traditional data interaction between the vehicle and the cloud is that the vehicle sends the file including the data to be processed to the cloud through a single task, and the cloud performs secondary processing (such as parsing, unpacking, etc.) on the file through its own operation to obtain the data to be processed, and then uses the data to be processed to perform data processing operations on the cloud database. When the vehicle needs to query data from the cloud database, it needs to send the query request to the cloud, and the cloud queries the data from the cloud database, and then performs secondary processing (such as compression, compilation, etc.) on the queried data through its own operation to obtain the processed data, and finally feeds the processed data back to the vehicle. Due to the existence of secondary processing operations in the whole process, there is a certain delay in the data processing operation, which affects the real-time performance of data processing. In addition, when multiple vehicle terminals concurrently initiate data processing tasks for the same database file, or when there is a conflict between the initiation time and task execution time of different data processing tasks, since there is no reasonable processing mechanism in the cloud, it will cause data processing conflicts during multi-task concurrency, resulting in the failure of data processing task execution.

[0054] Based on the above research, the present disclosure provides a data processing method, a computer device and a program product. The source end can directly call the unified data operation interface developed for the cloud database to initiate the data processing task, so as to realize the real-time data processing (for example, real-time data writing, real-time data editing, real-time data query, etc.) of the cloud database, thereby improving the real-time nature of data interaction. When executing the data processing task, by obtaining the current operation status of the target file targeted by the data processing task, it can be determined whether the target file is currently being operated on, that is, it can be determined whether the data operation is currently being performed on the target file. Furthermore, it can be determined whether the target file can be directly operated on according to the current operation status, so as to avoid the processing conflict caused by the newly initiated data processing task directly operating on the target file when the first initiated data processing task is processing the target file. Furthermore, when it is determined that the target file is being operated on according to the current operation status, it means that there are currently second data processing tasks related to the target file and these second data processing tasks are waiting in line for execution. Therefore, by determining the first task priority of the acquired first data processing task and caching it to the corresponding position of the task queue, it is possible to execute each processing task in sequence according to the order in the task queue, avoiding the problem of processing conflicts caused by directly executing the first data processing task. And by executing each processing task in sequence according to the task queue, it is possible to complete the sequential processing of each concurrent task for the same target file while ensuring the smooth execution of the first data processing task, thereby avoiding processing conflicts of multiple concurrent processing tasks.

[0055] The defects existing in the above solutions are the results obtained by the inventor after practice and careful research. Therefore, the discovery process of the above problems and the solutions proposed by the present disclosure for the above problems below should be the contributions made by the inventor to the present disclosure during the disclosure process.

[0056] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0057] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0058] To facilitate understanding of the present embodiment, a data processing method disclosed in the embodiment of the present disclosure is first introduced in detail. The executor of the data processing method provided in the embodiment of the present disclosure is generally a terminal device or other processing device with certain computing capabilities, wherein the terminal device may be a user equipment (UE), a mobile device, a user terminal, a terminal, a personal digital assistant (PDA), a handheld device, a computer device, etc.; in some possible implementations, the data processing method may be implemented by a processor calling computer-readable instructions stored in a memory.

[0059] The data processing method provided by the embodiment of the present disclosure is described below by taking the execution subject as the cloud as an example.

[0060] like Figure 1 As shown, it is a flowchart of a data processing method provided by an embodiment of the present disclosure, which may include the following steps:

[0061] S101: Obtain a first data processing task from a source end; the source end includes any one of multiple vehicle ends and / or multiple clouds; the first data processing task is initiated by the source end calling a target interface among multiple data operation interfaces corresponding to a cloud database, and is used to instruct data processing of a target file in the cloud database.

[0062] Here, the first data processing task is a task initiated by the source end, which can be used to instruct data processing of the target file in the cloud database, for example, data addition processing, data deletion processing, data modification processing, data query processing, etc. of the target file.

[0063] The source end may be a vehicle end and / or other cloud ends. For example, in an embodiment of the present application, the cloud server used to manage the cloud database may be referred to as the main cloud, and then there may be multiple vehicle ends and multiple sub-clouds communicating with the main cloud to initiate data processing tasks for the cloud database, and then realize data processing of files in the cloud database. That is, the present application can realize vehicle-cloud interconnection under multiple vehicle ends, multiple clouds, and multiple tasks.

[0064] Due to the car-cloud interconnection in the prior art, when the car and the cloud perform data interaction, the cloud does not provide a unified external interface to process the database files in the cloud database, which often causes data delays and troublesome data maintenance. In order to solve this problem, the data processing method provided in the embodiment of the present application first develops a data service module in the cloud, in which multiple unified data operation interfaces developed for the cloud database are provided, and each data operation interface can be directly called by any source end, thereby realizing data processing of the database files in the cloud database, improving the real-time performance of data processing, and protecting the consistency and atomicity of the source end data.

[0065] Different data operation interfaces correspond to different data operation types, and are used to perform different data processing operations on database files. Specifically, data operation types may include data addition type, data modification type, data deletion type, and data query type. Data processing operations may include data addition operation, data modification operation, data deletion operation, and data query operation.

[0066] A data operation interface can be called by multiple source ends simultaneously, different data operation interfaces can be called by different source ends simultaneously, and one source end can call at least one data operation interface simultaneously.

[0067] A data processing task can be initiated by any source end by calling a target interface among multiple data operation interfaces corresponding to the cloud database. The target interface is a data operation interface called when the source end initiates a data processing task. A data processing task is used to instruct data operation processing on a target file in the cloud database. Different data processing tasks can correspond to the same target file or different target files.

[0068] The target file may be any database file in the cloud database. It should be noted that when the data processing task is a data adding task, the target file may be a file that does not exist in the cloud database, and when the task is executed, the target file may be created in the cloud database.

[0069] In an embodiment of the present application, the first data processing task obtained may be one of the data processing tasks initiated concurrently by multiple source terminals, and different data processing tasks may come from at least two of the multiple vehicle terminals and / or at least two of the multiple clouds.

[0070] Exemplarily, the source end may include vehicle ends 1 to n and cloud ends 1 to m, where vehicle end 1 may initiate task 1, vehicle end 2 may initiate task 2, ..., vehicle end n may initiate task n, cloud end 1 may initiate task n+1, cloud end 1 may initiate task n+2, ..., cloud end m may initiate task m; wherein n is a positive integer greater than or equal to 2, and m is a positive integer greater than or equal to n. When each source end synchronously initiates a data processing task to the cloud, the cloud may synchronously obtain the tasks initiated by each source end, and take the tasks initiated by each source end as a first data processing task obtained. Alternatively, when each source end asynchronously initiates a data processing task, for any source end, when the source end initiates a data processing task to the cloud, the cloud may receive the data processing task initiated by the source end and take the data processing task as the first data processing task.

[0071] It can be understood that in the embodiments of the present application, the data processing tasks initiated by multiple source ends can be tasks initiated serially or tasks initiated in parallel. Regardless of whether they are initiated serially or in parallel, they can be processed using the data processing method provided in the embodiments of the present application, and the processing principles are the same. The following text will use the concurrent initiation of multiple data processing tasks as an example for explanation.

[0072] The plurality of data processing tasks may correspond to at least one target file and be used to perform at least one of data adding, deleting, modifying and querying operations on the target file.

[0073] For example, source end 1 initiates data processing task 1 for target file 1 by calling data operation interface 1, source end 2 initiates data processing task 2 for target file 2 by calling data operation interface 1, source end 3 initiates data processing task 3 for target file 1 by calling data operation interface 2, source end 4 initiates data processing task 4 for target file 2 by calling data operation interface 2, source end 5 initiates data processing task 5 for target file 1 by calling data operation interface 3, and source end 6 initiates data processing task 6 for target file 2 by calling data operation interface 4. In this way, the cloud can obtain data processing tasks 1 to 6 initiated in parallel by source ends 1 to 5, and use data processing tasks 1 to 6 as the first data processing tasks obtained.

[0074] S102: Acquire the current operation status corresponding to the target file; the current operation status is used to indicate whether a data operation is currently being performed on the target file.

[0075] Here, the current operation status is the status of the target file, and the status can be used to indicate whether a data operation is currently being performed on the target file, that is, whether a data processing task is currently being performed on the target file.

[0076] For example, when a data processing task is currently being executed for the target file, the current operating state of the target file may be: data operation is currently being executed; conversely, when no data processing task is currently being executed for the target file, the current operating state of the target file may be: data operation is not currently being executed.

[0077] In specific implementation, after obtaining the first data processing task, no matter whether the first data processing task includes one or more, for each first data processing task, the target file to be processed by the first data processing task can be determined, and the current operation status of the target file can be obtained. Among them, if a data processing task is used to process a certain file, it can be said that the file is the target file to be processed by the data processing task. In the case where the first data processing task includes multiple, the target files targeted by the multiple first data processing tasks can be different, or there can be some duplication.

[0078] Exemplarily, for any first data processing task, the current operation status of the target file to be processed by the first data processing task can be determined within the target interface called by the data processing task.

[0079] S103: If the current operation status indicates that the target file is currently being executed with data operations, the first data processing task is cached to a corresponding position in the task queue corresponding to the target file according to the first task priority of the first data processing task compared to each second data processing task in the task queue corresponding to the target file; each second data processing task comes from a different source end.

[0080] Here, the number of the second data processing tasks may be one or more, and each second data processing task may come from a different source end, and the source end of the second data processing task may be the same as or different from the source end of the first data processing task. Each second data processing task is a task for the target file and has not been executed. Each second data processing task may be a data processing task initiated to the cloud concurrently with the first data processing task, or may be a data processing task initiated to the cloud serially.

[0081] The task queue can be a created queue for a target file, and a target file can correspond to a task queue, which is used to store each data processing task to be executed for the target file. In an embodiment of the present application, each data processing task in the task queue is a task for the target file. The first task priority is used to indicate the execution priority of the first data processing task compared to each second data processing task. The processing order of each task cached in the task queue is related to the position of the task in the queue, and the position of the task in the queue is related to the task priority of the task.

[0082] During specific implementation, when the current operation of the target file indicates that the target file is currently being subjected to a data operation, it can be determined whether there is a task queue related to the target file. If not, it can be determined whether there are other data processing tasks for the target file. If there are other data processing tasks, a task queue corresponding to the target file can be created, and the task priorities of the first data processing task and each other data processing task can be determined. The first data processing task and other data processing tasks are cached in the task queue according to the priority and wait for execution. If there are no other data processing tasks, a task queue corresponding to the target file can be directly created, and the first data processing task can be cached in the task queue and wait for execution.

[0083] If there is a task queue related to the target file, it can be determined whether there are cached data processing tasks in the task queue. If so, these tasks can be used as second data processing tasks, and then the first data processing task is determined, compared with the first task priority of each second data processing task, and the first data processing task is cached to the corresponding position of the task queue corresponding to the target file according to the first task priority. The corresponding position here corresponds to the first task priority. For example, if the first task priority indicates that the first data processing task needs to be executed first, the first data processing task can be cached to the starting position of the task queue; if the first task priority indicates that the first data processing task needs to be executed third, the first data processing task can be cached after the second data processing task in the task queue. If there is no cached data processing task in the task queue related to the target file, the first data processing task can be directly cached in the task queue and wait for execution.

[0084] Optionally, if there is a second data processing task in the task queue, it can also be directly determined that the first priority of the first data processing task is lower than the second data processing task, and the first data processing task is cached at the end of the task queue. That is, the first data processing task is located after each second data processing task that already exists in the created task queue.

[0085] S104: In response to extracting the first data processing task from the task queue, executing the first data processing task.

[0086] During specific implementation, each task can be taken out in sequence according to the position of each second data processing task in the task queue corresponding to the target file, and the position of the first data processing task in the task queue, and then the task is executed using the target interface called corresponding to the task. The process of executing the task is to use the task to perform data operations on the target file. Based on the task queue, each data processing task for the same target file can be executed in sequence. When the first data processing task needs to be executed, the first data processing task can be extracted from the task queue. In response to extracting the first data processing task, the first data processing task is executed using the target interface called corresponding to the first data processing task.

[0087] Understandably, since the source end can execute the call data operation interface to initiate the first data processing task, the cloud end can operate the data of the cloud database according to the first data processing task according to the task priority, so the source end can use the unified data operation interface to maintain the data of the cloud database without data processing conflicts, which improves the convenience of data maintenance. Similarly, the cloud end (main cloud end) can also use the data operation interface to perform data maintenance on the files in the cloud database at any time according to the needs of data maintenance.

[0088] Optionally, after all data processing tasks in the task queue corresponding to the target file are completed, if there are no new data processing tasks that need to be added to the task queue at this time, the task queue corresponding to the target file can be deleted, and the current operation status of the target file can be modified to indicate that no data operation is currently being performed on the target file.

[0089] like Figure 2 As shown, it is a system block diagram of a multi-vehicle multi-cloud multi-task data processing flow provided by an embodiment of the present application, wherein the multi-task concurrent module is a data processing task concurrently initiated by multiple source ends using a data operation interface. Figure 2, task 1 initiated by cloud 1, task 2 initiated by cloud 2, task 3 initiated by vehicle end 1, and task 4 initiated by vehicle end 2 are shown. For tasks 1 to 4, they can correspond to any one of data addition, deletion, modification, and query operations. The data service module includes multiple data operation interfaces developed for the cloud database, namely, data addition interface, data deletion interface, data modification interface, and data query interface, and the data service module can be deployed in the cloud. At the same time, for tasks 1 to 4, the corresponding source end can call any one of the data addition interface, data deletion interface, data modification interface, and data query interface in the data service module when initiating the task. Tasks 1 to 4 can be concurrently initiated data processing tasks, and the cloud can process each task as a first data processing task. After receiving the data processing task, each interface in the data service module can perform a queue unified operation on each data processing task according to the target file to be processed by the data processing task. Among them, the queue unified operation can include the operation of caching the data processing tasks in order to the task queue according to the first task priority, and can also include the operation of creating a task queue corresponding to the target file in the following text, and caching the data processing tasks to the task queue according to the second task priority. The remote cloud module is a cloud database management module used to manage the cloud database, which stores multiple database files. Figure 2 Databases 1 to 4 are shown in the figure. For any database, the data processing method provided in the embodiment of the present application can be used for data processing, and the principle of data processing is the same. The cloud can perform data operations on the data in the cloud database according to the task order in the task queue, using the data operation interface corresponding to the data processing task, thereby realizing cloud data maintenance for the cloud database.

[0090] In this way, in view of the limitations of multi-task operations on cloud databases in current intelligent driving scenarios, this application proposes a data processing solution for multi-vehicle, multi-cloud, and multi-task interconnection, which aims to unify the cloud data operation interface through operations such as queue queuing and the current operation status of files, so as to realize unified management of remote cloud databases in multiple vehicle terminals, multiple cloud platforms (i.e., cloud), and multiple task scenarios, and ensure the real-time and fast data interaction. Specifically, the source terminal directly calls the unified data operation interface developed for the cloud database to initiate the data processing task, which can realize real-time data processing (e.g., real-time data writing, real-time data editing, real-time data query, etc.) of the cloud database, and improve the real-time data interaction. When executing the data processing task, by obtaining the current operation status of the target file targeted by the data processing task, it can be accurately determined whether the target file is currently being operated, that is, whether the data operation is being performed on the target file. Then, it can be determined whether the target file can be directly operated and processed according to the current operation status, so as to avoid the processing conflict caused by the newly initiated data processing task directly operating and processing the target file when the first initiated data processing task is processing the target file. Furthermore, when it is determined that the target file is being operated on according to the current operation status, it means that there are currently second data processing tasks related to the target file and these second data processing tasks are waiting in line for execution. Therefore, by determining the first task priority of the acquired first data processing task and caching it to the corresponding position of the task queue, it is possible to execute each processing task in sequence according to the order in the task queue, avoiding the problem of processing conflicts caused by directly executing the first data processing task. And by executing each processing task in sequence according to the task queue, it is possible to complete the sequential processing of each concurrent task for the same target file while ensuring the smooth execution of the first data processing task, thereby avoiding processing conflicts of multiple concurrent processing tasks.

[0091] In one embodiment, after the current operation status of the target file is obtained, it may happen that the current operation status indicates that the target file has not been operated. In this case, the following steps may be performed:

[0092] Step 1: If the current operation status indicates that no data operation is currently being performed on the target file, determine whether there is a third data processing task for the target file.

[0093] Exemplarily, if the current operation status indicates that no data operation is currently being performed on the target file, it can be determined whether there are other data processing tasks for the target file. If so, it can be said that in addition to the first data processing task currently being processed, there are other tasks to be executed for the target file. In order to avoid data operation conflicts, these other data processing tasks for the target file can be first treated as the third data processing task, and the following step two can be executed.

[0094] Step 2: If yes, create a task queue corresponding to the target file, and determine the second task priority of the first data processing task and each third data processing task.

[0095] In a specific implementation, in order to avoid processing conflicts between the first data processing task and the third data processing task, a task queue for the target file can be created. At the same time, the second task priority of the first data processing task and each third data processing task can be determined. The second task priority is used to indicate the execution order between the first data processing task and each third data processing task.

[0096] Step 3: execute the data processing task with the highest second task priority, update the current operation status of the target file, and cache other data processing tasks except the one with the highest second task priority into the task queue according to the second task priority.

[0097] During specific implementation, after determining the second task priority, the data processing task with the highest second task priority can be executed (the task can be the first data processing task or any third data processing task) and the current operation state of the target file is updated from the state indicating that the target file is not currently being executed with data operations to the state indicating that the target file is currently being executed with data operations. At the same time, other data processing tasks other than those with the highest second task priority can also be determined, and according to the second task priority of these data processing tasks, these tasks are cached to the corresponding position of the task queue corresponding to the target file to wait for execution. Then, after the data processing task with the highest second task priority is executed, a task execution completion notification can be sent to the task queue, and the data processing task that has been executed can be deleted from the task queue, and then the data processing task with the next priority can be taken out from the task queue, and then the target interface corresponding to the call of the data processing task can be used to execute the data processing task. By analogy, it is realized that each data processing task in the task queue is executed in sequence according to the second task priority. That is, it can be understood that, for each data processing task in the task queue, the task with the second task priority level at the rear needs to be executed after the task with the second task priority level at the front is completed and after receiving the task execution completion notification sent by the task with the second task priority level at the front. After the last data processing task in the task queue is completed, the current operation state of the target file can be changed from a state indicating that the target file is currently being operated on to a state indicating that the target file is not currently being operated on, and the task queue corresponding to the target file can be deleted.

[0098] In this way, when executing a data processing task with the highest second task priority, modifying the current operating state of the target file can effectively prevent other newly received tasks from modifying the target file at the same time when executing the data processing task, thereby avoiding data processing conflicts.

[0099] In one embodiment, for the above step 1, after determining whether there is a third data processing task for the target file, if there is no third data processing task, the first data processing task is executed and the current operation status of the target file is updated.

[0100] Exemplarily, when there is no third data processing task for the target file, it can be determined that there is only one data processing task for the target file, which is the first data processing task. Therefore, the first data processing task can be directly executed using the target interface corresponding to the call of the first data processing task. At the same time, in order to avoid other newly received tasks for the target file processing the target file at the same time when the first data processing task is executed, the current operation state of the target file can be updated to indicate that the target file is currently being operated on while the first data processing task is executed. After the first data processing task is executed, if there are no other data processing tasks to be executed for the target file, the current operation state of the target file can be updated to indicate that the target file is not currently being operated on.

[0101] In one embodiment, the above S102 may be implemented according to the following steps:

[0102] Obtain the lock status identification bit corresponding to the target file; when the lock status identification bit is the first identification bit, determine that the current operation state of the target file is that no data operation is currently being performed on the target file; or, when the lock status identification bit is the second identification bit, determine that the current operation state of the target file is that data operation is currently being performed on the target file.

[0103] Here, the lock status identification bit can be an identification bit for the database file, which is an identification bit of a software lock. The lock status identification bit can specifically include two values, one is a first identification bit used to indicate that the database file is in an unlocked state, and the other is a second identification bit used to indicate that the database file is in a locked state. The values ​​of the first identification bit and the second identification bit can be set based on experience and are not specifically limited here. When the database file is in an unlocked state, it can be explained that the current operating state of the database file is that the target file is currently not being operated on by data. When the database file is in a locked state, it can be explained that the current operating state of the database file is that the target file is currently being operated on by data.

[0104] Therefore, in a specific implementation, for the first data processing task, the lock status flag corresponding to the target file to be processed by the first data processing task can be obtained in the target interface corresponding to the call of the first data processing task. Then, when the lock status flag is the first flag, it is determined that the current operation state of the target file is that the target file is not currently being operated on. On the contrary, when the lock status flag is the second flag, it is determined that the current operation state of the target file is that the target file is currently being operated on.

[0105] In another optional embodiment, in addition to using the lock status identification bit to determine the current operating state of the target file, the current operating state of the target file can also be determined by detecting whether there is a created task queue for the target file. For example, for each first data processing task, it can be determined whether there is a created task queue for the target file to be processed by the first data processing task. If so, it can be determined that there is a data processing task that is currently being executed or waiting to be executed, and thus the current operating state of the target file can be determined to be that the target file is currently being executed by a data operation, and the first task priority of the first data processing task can be determined and cached in the task queue. Conversely, if there is currently no created task queue, it can be determined that there is currently no data processing task that is being executed or waiting to be executed, and thus the current operating state of the target file can be determined to be that no data operation is currently being executed on the target file.

[0106] Optionally, the current operation state of the target file can also be determined according to the lock state identification bit of the target file and whether there is a created task queue for the target file. Specifically, when the lock state identification bit of the target file is the first identification bit and there is no created task queue for the target file, the current operation state of the target file is determined to be that the target file is not currently being operated on by data; when the lock state identification bit of the target file is the second identification bit and there is a created task queue for the target file, the current operation state of the target file is determined to be that the target file is currently being operated on by data; when the lock state identification bit of the target file is the first identification bit and there is a created task queue for the target file, the current operation state of the target file is determined to be that the target file is not currently being operated on by data, and the created task queue is deleted; when the lock state identification bit of the target file is the second identification bit and there is no created task queue for the target file, the current operation state of the target file is determined to be that the target file is currently being operated on by data.

[0107] like Figure 3 As shown, a specific implementation flow chart of a data processing method provided in an embodiment of the present application may include the following steps:

[0108] Get multiple first data processing tasks, Figure 3 Task 1 to Task n are displayed.

[0109] Different first data processing tasks correspond to one of the operations of adding, deleting, modifying and querying data.

[0110] Determine a target file corresponding to each first data processing task.

[0111] For each target file, it is queried whether the target file is in a locked state, that is, it is queried whether the current operation state of the target file is that data operation is currently being performed.

[0112] If not, a task queue corresponding to the target file can be created, and the task priorities of the first data processing tasks for processing the target file can be determined, and the first data processing task with the highest priority can be executed, and the first data processing tasks other than the first data processing task with the highest priority can be cached to the task queue according to the task priority. In addition, the target file can be placed in a locked state, that is, the current operation state of the target file can be updated to the data operation currently being executed.

[0113] Then, each first data processing task is operated in the order of task priority to implement operations such as adding, deleting, modifying, and querying data in the target file. That is, the target interface corresponding to each first data processing task is used to sequentially execute each first data processing task in the task queue corresponding to the target file. After the first data processing task with a high priority is completed, a task execution completion notification can be sent, and then the first data processing task with the next priority can be taken out from the task queue to continue execution.

[0114] When all the first data processing tasks in the task queue are completed, the target file is unlocked, that is, the current operation state of the target file is updated to the state that no data operation is currently being performed.

[0115] If so, determine the task priority of each first data processing task for processing the target file compared to the second data processing task already existing in the created task queue corresponding to the target file, and cache it to the created task queue corresponding to the target file according to the priority.

[0116] Then, for each data processing task in the created task queue, execution may be started according to the task priority after receiving the task execution completion notification of the data processing task of the previous priority.

[0117] When all data processing tasks in the created task queue are completed, the target file is unlocked, that is, the current operation state of the target file is updated to no data operation being performed.

[0118] Finally, after all target files are unlocked, it can be determined that the multiple acquired data processing tasks are all completed. Figure 3 Task 1 to Task n in the above are all completed.

[0119] In one embodiment, the first task priority of the first data processing task may be determined according to the following steps:

[0120] Determine the first task priority of the first data processing task according to the time sequence of the timestamps of the first data processing task and each second data processing task; wherein the timestamp is generated for the first data processing task when the source end initiates the first data processing task; and different first data processing tasks have different timestamps.

[0121] Here, even if multiple source ends initiate data processing tasks for the target file at the same time, the timestamps of the data processing tasks initiated by each source end are different. The timestamp can be generated for the data processing task when the source end initiates the data processing task, and the timestamps of different data processing tasks are different. Therefore, in the specific implementation, after obtaining the first data processing task, if there is a second data processing task, the task priority of the first data processing task and the second data processing task can be determined according to the timestamp of the first data processing task and the timestamps of each second data processing task, in the order of the timestamps, and the priority of the first data processing task is used as the first task priority. Among them, the earlier the time corresponding to the timestamp, the higher the task priority, and the later the time corresponding to the timestamp, the lower the task priority.

[0122] In one embodiment, the data operation interface includes a data adding interface, a data deleting interface, a data modifying interface and a data querying interface; the data processing task includes at least one of a data adding task, a data deleting task, a data modifying task and a data querying task. The first data processing task, the second data processing task and the third data processing task are all data processing tasks.

[0123] Different data processing tasks are initiated by calling different data processing interfaces. For example, data addition tasks are initiated by calling the data addition interface at the source end, data deletion tasks are initiated by calling the data deletion interface at the source end, data modification tasks are initiated by calling the data modification interface at the source end, and data query tasks are initiated by calling the data query interface at the source end.

[0124] Specifically, when the first data processing task includes a data augmentation task, the data augmentation task may be acquired by the following steps:

[0125] In response to the source end calling the data addition interface, the file name and the data to be added input by the source end are obtained; the file name is related to at least one of the source end's identification, date information and the source end's location information; and a data addition task is generated according to the file name and the data to be added.

[0126] During specific implementation, when the source determines that it is necessary to initiate a data addition task, the data addition interface can be called through the data service module, and the cloud can respond to the call operation and feed back the parameter input indication information to the source. Among them, the parameter input indication information is used to indicate the parameter type required to be input by the source, wherein the parameter type may include the file name type and the newly added data type. Then, the cloud can obtain the file name entered by the source under the file name type, and the data to be added entered under the newly added data type. The file name of the source data is the file name of the database file already in the cloud database, or it can be the file of the database file that needs to be added to the cloud database. The naming rule of the file name can be related to at least one of the source identification, date information and location information of the source. Among them, the identification of different source ends is different, the identification of the source end is used to uniquely identify the source end, the date information can be the current year and month information, year, month and day information, etc., and the location information of the source end can specifically be the location information of the source end.

[0127] Exemplarily, the file name may be source identifier + date information, date information, vehicle location information, location information + date information, source identifier + date information + location information, etc. Among them, by using the location information as the file name, it is possible to store road information (such as lane lines, obstacle areas, road signs, etc.) collected by different vehicles at the same location in a cloud database, thereby laying a good foundation for road mapping.

[0128] After obtaining the file name and the data to be added, the cloud can encapsulate the file name and the data to be added to obtain the data addition task. Here, when the source calls the data addition interface, it is equivalent to calling the function related to the data addition service. The file name and the data to be added input by the source are equivalent to the parameters input for the function. Therefore, after obtaining the file name and the data to be added, the function is encapsulated using the file name and the data to be added, and the data addition task can be obtained.

[0129] Furthermore, when executing the data addition task in the cloud, if there is a target file with the same file name in the cloud database, the data to be added can be written into the target file to implement the data addition task. If there is no target file with the same file name in the cloud database, a target file with the same file name can be created in the cloud database, and then the data to be added can be written into the target file to implement the data addition task.

[0130] In an optional implementation, when the first data processing task includes a data query task, the cloud end responds to the source end calling the data query interface and feeds back the query parameter indication information to the source end. The query parameter indication information is used to indicate the query parameters that need to be input. Then, the cloud end can obtain the query parameters input by the source end and generate a data query task according to the query parameters. Further, the query task can be executed using the data query interface, and the queried data can be fed back to the source end.

[0131] In one embodiment, when the first data processing task includes a data modification task, the data modification task may be acquired by the following steps:

[0132] In response to the source end calling the data modification interface, using the data query interface, each database file is obtained from the cloud database and fed back to the source end; the source end obtains the modification instructions for the target file in the database file; the modification instructions include modification instructions for the target file or modification instructions for the source data in the target file; and a data modification task is generated according to the modification instructions.

[0133] Here, the target file can be any database file, and the modification instruction can be an instruction to modify the original attributes of the target file, or an instruction to modify the source data in the target file. The original attributes of the target file can include information such as file name, file format, file storage location, etc.

[0134] Since the purpose of the data modification operation is to modify the existing data in the cloud database, in order to improve the rationality of the data modification tasks initiated by the source, when the source calls the data modification interface, the cloud can respond to the operation of calling the interface (specifically, it can be a response to the operation of calling the interface function corresponding to the data modification interface), and use the data query interface in the data service module to query the various database files included in the cloud database and the source data in the files, and then feed the database files and source data back to the source.

[0135] Then, after obtaining the database file and source data, the source end can initiate a modification instruction for the target file in the database file. For example, an instruction to change the file name of the target file from the original name to the target name, or an instruction to change the source data in the target file to the target data. Then, the cloud end can obtain the modification instruction initiated by the source end, and encapsulate the modification instruction to obtain a data modification task. After that, the cloud end can use the data modification interface to execute the data modification task, thereby realizing the data modification operation for the target file in the cloud database.

[0136] In another embodiment, when the first data processing task includes a data deletion task, the data deletion task may be acquired by the following steps:

[0137] In response to the source end calling the data deletion interface, using the data query interface, each database file is obtained from the cloud database and fed back to the source end; the source end obtains the deletion instruction for the target file in the database file; the deletion instruction includes the deletion instruction for the target file or the deletion instruction for the source data in the target file; and a data deletion task is generated according to the deletion instruction.

[0138] Here, the target file may be any database file, and the modification instruction may be an instruction to delete the target file, or an instruction to delete source data in the target file.

[0139] Similarly, since the purpose of the data deletion operation is to delete the existing data in the cloud database, in order to improve the rationality of the data deletion task initiated by the source, when the source calls the data deletion interface, the cloud can respond to the operation of calling the interface (specifically, it can be a response to the operation of calling the interface function corresponding to the data deletion interface), and use the data query interface in the data service module to query the various database files included in the cloud database and the source data in the files, and then feed the database files and source data back to the source.

[0140] Then, after obtaining the database file and source data, the source end can initiate a deletion instruction for the target file in the database file. For example, an instruction to delete the target file, or an instruction to delete the source data in the target file. Then, the cloud end can obtain the deletion instruction initiated by the source end, and encapsulate the deletion instruction to obtain a data deletion task. After that, the cloud end can use the data deletion interface to execute the data deletion task, thereby realizing the data deletion operation for the target file in the cloud database.

[0141] In this way, the data modification interface can be used to update the database file while querying the database file. There is no need to initiate a query task first and then an update task (such as a data modification task or a data deletion task) through the source end to update the data, thereby improving the efficiency of data update. Using the data operation interface, the source end can also directly perform data operations on the data in the cloud database, which improves the real-time performance of data operations. As a universal service interface, the data operation interface implements a unified external interface to operate the data, eliminating the need for secondary processing operations. In addition, the defect of being unable to adapt to multiple source-end tasks has been improved, and the same set of data operation interfaces can be reused on different source ends to operate the same target file.

[0142] In general, in order to solve the problems that multiple vehicles, multiple clouds and multiple tasks in intelligent driving scenarios cannot directly access the cloud database through a unified data interface, and concurrent access of multiple tasks will cause data conflicts, poor real-time data interaction, and troublesome data maintenance, the present invention adopts a data service solution for the interconnection of multiple vehicles, multiple clouds and multiple tasks, which uses task queues and lock status flags to unify the external interface of the data service module, can receive data from multiple source platforms (i.e., multiple source terminals), and uniformly operate on database files, thereby ensuring data consistency and atomicity and having protection measures, and improving the effect of fast and efficient data service operations under multiple vehicles, multiple clouds and multiple tasks.

[0143] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0144] Based on the same technical concept, the embodiment of the present application also provides a computer device. Figure 4 FIG. 1 is a schematic diagram of a computer device provided in an embodiment of the present application, including:

[0145] Processor 401 , memory 402 and bus 403 . Among them, the memory 402 stores machine-readable instructions executable by the processor 401, and the processor 401 is used to execute the machine-readable instructions stored in the memory 402. When the machine-readable instructions are executed by the processor 401, the processor 401 performs the following steps: S101: Obtain a first data processing task from a source end; the source end includes any one of multiple vehicle ends and / or multiple clouds; the first data processing task is initiated by the source end calling a target interface among multiple data operation interfaces corresponding to the cloud database, and is used to indicate data processing of a target file in the cloud database; S102: Obtain a current operation status corresponding to the target file; the current operation status is used to indicate whether a data operation is currently being performed on the target file; S103: If the current operation status indicates that the target file is currently being subjected to a data operation, then according to the first task priority of the first data processing task compared to each second data processing task in the task queue corresponding to the target file, the first data processing task is cached to a corresponding position in the task queue corresponding to the target file; each second data processing task comes from a different source end; and S104: In response to extracting the first data processing task from the task queue, execute the first data processing task.

[0146] The above-mentioned memory 402 includes internal memory 4021 and external memory 4022; the memory 4021 here is also called internal memory, which is used to temporarily store the calculation data in the processor 401, as well as the data exchanged with the external memory 4022 such as the hard disk. The processor 401 exchanges data with the external memory 4022 through the internal memory 4021. When the computer device is running, the processor 401 communicates with the memory 402 through the bus 403, so that the processor 401 executes the execution instructions mentioned in the above-mentioned method embodiment.

[0147] The present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the data processing method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0148] The computer program product of the data processing method provided in the embodiments of the present disclosure includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the steps of the data processing method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0149] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK) and the like.

[0150] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0151] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0152] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0153] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, 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, which is stored in a storage medium and includes several instructions for 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 disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0154] If the technical solution of this application involves personal information, the product using the technical solution of this application has clearly informed the personal information processing rules and obtained the individual's voluntary consent before processing the personal information. If the technical solution of this application involves sensitive personal information, the product using the technical solution of this application has obtained the individual's separate consent before processing the sensitive personal information, and at the same time meets the "explicit consent" requirement. For example, on personal information collection devices such as cameras, clear and prominent signs are set to inform that the personal information collection scope has been entered and personal information will be collected. If the individual voluntarily enters the collection scope, it is deemed that he or she agrees to the collection of his or her personal information; or on the device that processes personal information, the personal information processing rules are notified by obvious signs / information, and the individual's authorization is obtained through pop-up information or by asking the individual to upload his or her personal information; among them, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the type of personal information processed.

[0155] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A data processing method, characterized in that: include: Acquire a first data processing task from a source end; the source end includes any one of a plurality of vehicle ends and / or a plurality of clouds; the first data processing task is initiated by the source end calling a target interface among a plurality of data operation interfaces corresponding to a cloud database, and is used to instruct data processing of a target file in the cloud database; Acquire a current operation status corresponding to the target file; the current operation status is used to indicate whether a data operation is currently being performed on the target file; If the current operation status indicates that a data operation is currently being performed on the target file, the first data processing task is cached to a corresponding position in the task queue corresponding to the target file according to a first task priority of the first data processing task compared to each second data processing task in the task queue corresponding to the target file; each second data processing task comes from a different source end; In response to extracting the first data processing task from the task queue, executing the first data processing task.

2. The method according to claim 1, characterized in that: The method further comprises: If the current operation state indicates that no data operation is currently being performed on the target file, determining whether there is a third data processing task for the target file; If yes, create a task queue corresponding to the target file, and determine the second task priority of the first data processing task and each of the third data processing tasks; Execute the data processing task with the highest second task priority, update the current operation status of the target file, and, according to the second task priority, cache other data processing tasks except the one with the highest second task priority to the task queue.

3. The method according to claim 2, characterized in that After determining whether there is a third data processing task for the target file, the method further includes: If the third data processing task does not exist, the first data processing task is executed and the current operation status of the target file is updated.

4. The method according to claim 1, characterized in that: The obtaining of the current operation status corresponding to the target file includes: Obtaining a lock status flag corresponding to the target file; When the lock status flag is the first flag, determining the current operation status of the target file is that no data operation is currently being performed on the target file; or When the lock status flag is the second flag, it is determined that the current operation status of the target file is that data operation is currently being performed on the target file.

5. The method according to any one of claims 1 to 4, characterized in that: Determine the first task priority of the first data processing task compared to each of the second data processing tasks according to the following steps: Determine the first task priority of the first data processing task according to the time sequence of the timestamps of the first data processing task and each of the second data processing tasks; wherein the timestamp is generated for the first data processing task when the source end initiates the first data processing task; and the timestamps of different first data processing tasks are different.

6. The method according to any one of claims 1 to 4, characterized in that: The data operation interface includes a data adding interface, a data deleting interface, a data modifying interface and a data querying interface; the data processing task includes at least one of a data adding task, a data deleting task, a data modifying task and a data querying task; In a case where the first data processing task includes the data augmentation task, acquiring the data augmentation task includes: In response to the source end calling the data adding interface, obtaining the file name and the data to be added input by the source end; the file name is related to at least one of the source end's identification, date information, and location information of the source end; The data adding task is generated according to the file name and the data to be added.

7. The method according to claim 6, characterized in that In the case where the first data processing task includes a data modification task, obtaining the data modification task includes: In response to the source end calling the data modification interface, using the data query interface, obtaining each database file from the cloud database and feeding it back to the source end; Obtaining a modification instruction from the source end for a target file in a database file; the modification instruction includes a modification instruction for the target file or a modification instruction for source data in the target file; The data modification task is generated according to the modification instruction.

8. The method according to claim 6, characterized in that In the case where the first data processing task includes a data deletion task, obtaining the data deletion task includes: In response to the source end calling the data deletion interface, using the data query interface, obtaining each database file from the cloud database and feeding it back to the source end; Obtaining a deletion instruction from the source end for a target file in a database file; the deletion instruction includes a deletion instruction for the target file or a deletion instruction for source data in the target file; The data deletion task is generated according to the deletion instruction.

9. A computer device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is used to execute the machine-readable instructions stored in the memory. When the machine-readable instructions are executed by the processor, the processor executes the steps of the data processing method according to any one of claims 1 to 8.

10. A computer program product, characterized in that When the computer program product is executed by a computer device, the computer device executes the steps of the data processing method according to any one of claims 1 to 8.

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