Data processing method and device, server and storage medium

Abstract

Embodiments of the present application provide a data processing method and device, a server and a storage medium, and relate to the technical field of data processing. The method can quickly determine a data segment corresponding to a device in a specific state from a large amount of data. The method comprises the following steps: when a node data indicating the start or end of a specific state is found in a data sequence uploaded on a target device, a target data queue in which the node data is located is obtained; each data queue in the data sequence is arranged in sequence according to a preset rule; a data segment with the position of the target data queue in the data sequence as end points is extracted from the data sequence, and a data set generated by the target device in the specific state is obtained.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a data processing method, apparatus, server, and storage medium. Background Technology

[0002] With the advent of the big data era, all types of data are experiencing explosive growth, bringing unprecedented opportunities and challenges to the data analysis industry. In the process of data analysis and computation, it is necessary to extract the relevant data from the massive amount of data to support the current calculation.

[0003] For example, in vehicle-to-everything (V2X) applications, intelligent vehicles periodically upload data collected by different sensors to servers or databases. When it is necessary to analyze various indicators of an intelligent vehicle in a certain driving state, it is necessary to extract data related to that driving state from a large amount of data, which often requires a lot of computation and consumes a lot of time and computing resources. Summary of the Invention

[0004] This application provides a data processing method, apparatus, server, and storage medium that can quickly determine the data segment corresponding to a device in a specific state from a large amount of data.

[0005] In a first aspect, embodiments of this application provide a data processing method applied to a server. The method includes: when node data representing the start or end of a specific state is found in a data sequence uploaded by a target device, obtaining a target data queue where the node data is located; wherein, each data queue in the data sequence is arranged sequentially according to a preset rule; extracting a data segment in the data sequence with the position of the target data queue in the data sequence as the endpoint, and obtaining a data set generated by the target device during the existence phase of the specific state.

[0006] The data processing method proposed in this application identifies node data representing the start or end of a specific state within the data, and extracts multiple data queues with the target data queue containing the node data as endpoints. These multiple data queues constitute the data set generated by the target device during the existence phase of the specific state. This data processing method requires minimal computation; it only needs to identify the node data representing the start or end of a specific state to quickly filter the corresponding data set from a large amount of data, saving both time and space costs.

[0007] In one possible implementation, when multiple specific states occur consecutively, and there are multiple node data representing the start or end of a specific state, data segments with the position of the target data queue in the data sequence as endpoints are extracted from the data sequence to obtain the data set generated by the target device during the existence of the specific state, including:

[0008] The data sequence is divided with the target data queue as the endpoint to obtain the data set corresponding to the multiple specific states that occur consecutively in their respective existence stages.

[0009] In one possible implementation, a data segment with the position of the target data queue in the data sequence as its endpoint is extracted from the data sequence to obtain the data set generated by the target device during the specific state duration, including:

[0010] The effect of repeated records in the target data queue on the order of each data queue in the data sequence is obtained;

[0011] Extract multiple data queues with the same permutation order from the data sequence to obtain the data set generated by the target device during the specific state duration.

[0012] In one possible implementation, after obtaining the target data queue where the node data is located, the method further includes:

[0013] Copy the target data queue and mark the copied target data queue;

[0014] Obtaining the influence of the target data queue on the order of each data queue in the data sequence includes:

[0015] The target data queue carrying the tags is merged with the data sequence to obtain the merged sequence;

[0016] The merged data is sorted according to the preset rules, and the order of each data queue is recorded. When the node data indicates the start of a specific state, the target data queue with the label is placed before the target data queue without the label. When the node data indicates the end of a specific state, the target data queue with the label is placed after the target data queue without the label. The order difference between the order of each data queue in the data sequence and the order in the merged sequence is calculated.

[0017] In one possible implementation, multiple data queues with the same permutation order are extracted from the data sequence to obtain the data set generated by the target device during the specific state duration, including:

[0018] Extract multiple data queues with the same sequence difference from the data sequence to obtain the data set generated by the target device during the specific state existence phase.

[0019] In one possible implementation, the preset rules include at least one of the following: arranging data in ascending order of data collection time, arranging data in ascending order of data upload time, or arranging data in the order of first to last upload.

[0020] Secondly, embodiments of this application provide a data processing apparatus, disposed in a server, the apparatus comprising:

[0021] The search module is used to find node data representing the start or end of a specific state in the data sequence uploaded by the target device and obtain the target data queue where the node data is located; wherein, the data queues in the data sequence are arranged sequentially according to a preset rule;

[0022] An extraction module is used to extract data segments from the data sequence with the position of the target data queue in the data sequence as the endpoint, and obtain the data set generated by the target device during the specific state existence phase.

[0023] In one possible implementation, when multiple specific states occur consecutively, there are multiple node data representing the start or end of a specific state; the extraction module is specifically used to divide the data sequence with the target data queue as the endpoint to obtain the data set corresponding to the multiple consecutively occurring specific states in their respective existence stages.

[0024] In one possible implementation, the extraction module includes:

[0025] The ranking submodule is used to obtain the influence of the target data queue on the order of each data queue in the data sequence;

[0026] An extraction submodule is used to extract multiple data queues with the same permutation order in the data sequence, and obtain the data set generated by the target device during the specific state existence phase.

[0027] In one possible implementation, the device further includes:

[0028] A marking module is used to copy the target data queue and mark the copied target data queue;

[0029] The ranking submodule includes:

[0030] The merging subunit is used to merge the target data queue carrying the tag with the data sequence to obtain a merged sequence;

[0031] The sorting subunit is used to sort the merged data according to the preset rules and record the order of each data queue; when the node data indicates the start of a specific state, the target data queue with the label is placed before the target data queue without the label; when the node data indicates the end of a specific state, the target data queue with the label is placed after the target data queue without the label; the calculation subunit is used to calculate the order difference between the order of each data queue in the data sequence and the order in the merged sequence.

[0032] In one possible implementation, the extraction submodule is specifically used to extract multiple data queues with the same sequence difference from the data sequence to obtain the data set generated by the target device during the specific state existence phase.

[0033] In one possible implementation, the preset rules include at least one of the following: arranging data in ascending order of data collection time, arranging data in ascending order of data upload time, or arranging data in the order of first to last upload.

[0034] Thirdly, embodiments of this application provide a server, including: at least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor can execute the method provided in the first aspect by invoking the program instructions.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that cause the computer to perform the method provided in the first aspect.

[0036] It should be understood that the second to fourth aspects of the embodiments of this application are consistent with the technical solutions of the first aspect of the embodiments of this application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation are similar, and will not be described again. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart of the data processing method steps proposed in the embodiments of this application;

[0039] Figure 2 This is an example of an information instruction diagram for data processing according to this application;

[0040] Figure 3 This is a functional block diagram of the data processing device proposed in the embodiments of this application.

[0041] Figure 4 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0042] To better understand the technical solutions in this specification, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0043] It should be understood that the described embodiments are merely some, not all, of the embodiments in this specification. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without inventive effort are within the scope of protection of this specification.

[0044] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this specification. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0045] Figure 1 This is a flowchart of the data processing method steps proposed in the embodiments of this application, as follows: Figure 1 As shown, the steps include:

[0046] Step S11: When node data representing the start or end of a specific state is found in the data sequence uploaded by the target device, the target data queue where the node data is located is obtained; wherein, each data queue in the data sequence is arranged sequentially according to a preset rule.

[0047] A data sequence comprises multiple data queues, and each data queue contains various types of data. The data sequence can be stored on a server or in a database connected to the server.

[0048] The preset rules include at least one of the following: arranging data in ascending order of data collection time, arranging data in ascending order of data upload time, or arranging data in the order of first to last upload.

[0049] The target device periodically uploads data to the server, so the data queue can be sorted based on time or the auto-incrementing ID generated by the uploaded data.

[0050] Table 1:

[0051]

[0052] Table 1 shows a data sequence uploaded by the target device in one example of this application. The data queues in Table 1 include: {1665, 1001, ...} , }、{1666、1001、 , }、{1667、1002、 , }、{1668、1002、 , }

[0053] The target device refers to the computing device that uploads data to the server. The target device can be a vehicle-mounted host, a vehicle-mounted telematics box (TBOX), a mobile phone, etc. The data uploaded by the target device includes various types of data generated during its operation; these include data collected by different sensors installed in the system where the target device resides, or data recorded by the target device during relevant calculations.

[0054] A specific state refers to the state in which the target device or the system containing the target device is executing one or more programs. For example, if the target device is a mobile phone, the specific state could be that the mobile phone is charging, playing a video, or in standby mode; if the target device is a vehicle-mounted network terminal, the specific state could be that the vehicle containing the vehicle-mounted network terminal is in motion, charging, or climbing a hill.

[0055] The node data indicating the start or end of a specific state can be data recorded in the current data sequence or data obtained according to a preset calculation method. For example, the ignition signal uploaded by the vehicle network terminal can be obtained as node data indicating the start of the vehicle's driving state, or the adjustment reference values ​​of the charger's output current and voltage can be obtained as node data indicating the start or end of the vehicle's charging state.

[0056] For example, the target device is an in-vehicle network terminal M, and the system in which the target device resides is an intelligent vehicle system. The intelligent vehicle system may include the in-vehicle network terminal M, an Electronic Control Unit (ECU), a Flow Air Sensor (MAF), a Throttle Position Sensor (TPS), a temperature sensor, a speed sensor, etc. The in-vehicle network terminal M periodically uploads data collected by different sensors to a server, which then analyzes the data in conjunction with data uploaded by roadside units (RSUs) and other vehicles. Assume that the data set A uploaded by the in-vehicle network terminal M every 10ms includes: vehicle speed, engine speed, charging / discharging status, total mileage, vehicle location, etc., and the server database stores multiple data sets A arranged in a specific order. When it is necessary to analyze the data to obtain various indicators of the vehicle during driving, it is necessary to extract the data generated during the vehicle's driving process from the data stored on the server. However, based on the periodically uploaded data from the in-vehicle network terminal M, it is impossible to distinguish the specific parts corresponding to the vehicle's driving process. Furthermore, the data stored on the server also includes data uploaded by roadside units or other vehicles. Therefore, it is necessary to solve the problem of extracting data related to each segment of the vehicle's driving state from the large amount of data stored on the server.

[0057] To address the aforementioned issues, this example employs the data processing method proposed in the embodiments of this application. Node data is searched in the data sequence uploaded by the target device to determine the data queue corresponding to the start or end of a specific state. This allows for the rapid acquisition of data generated in each continuous state, thereby better supporting the analysis of device metrics under a given state.

[0058] In some embodiments of this application, a unique identifier representing the target device can be found in the data as the basis for determining the target object to be extracted and analyzed. For example, a database stores data uploaded by mobile phone A and mobile phone B within a time period U. Based on the device IDs of mobile phone A and mobile phone B contained in each data queue in the data sequence, data from different devices can be accurately distinguished. When it is necessary to analyze data related to mobile phone A, the data queue corresponding to the device ID of mobile phone A is called.

[0059] Step S12: Extract the data segment with the position of the target data queue in the data sequence as the endpoint from the data sequence to obtain the data set generated by the target device during the specific state existence phase.

[0060] In one example of this application, the data set generated by the system where the target device's vehicle-to-everything (V2X) terminal is located during a specific state phase is searched in the data sequence shown in Table 1. The node data representing the start of the vehicle system's driving state is obtained. and When a vehicle is driving in an urban area, the driving state in response to frequent start and brake commands from the user is generally a continuous driving segment. Using the data processing method proposed in this application embodiment, respectively... and Extract data queues for endpoints, extract The data queue and The data segment, comprised of the data queue, obtains data collected by different sensors during the vehicle's first driving phase, used to support the analysis of various indicators during this phase; extraction... The data queue and The data segment, which is composed of the data queue, obtains data collected by different sensors when the vehicle is in the second stage of driving, and is used to support the analysis of various indicators of the vehicle in the second stage of driving.

[0061] In response to the situation where the aforementioned specific states occur consecutively, this application proposes an optional method for executing step S12. When multiple specific states occur consecutively, there are multiple node data representing the start or end of a specific state. The method involves extracting data segments from the data sequence with the position of the target data queue in the data sequence as endpoints, and obtaining the data set generated by the target device during the duration of the specific state. This includes dividing the data sequence with the target data queue as an endpoint to obtain the data set corresponding to the multiple consecutively occurring specific states during their respective durations.

[0062] When multiple specific states occur consecutively, there are multiple node data indicating the start or end of a specific state, and multiple target data queues where the node data is located. By dividing the data sequence with each target data queue as an endpoint, we can obtain multiple consecutive data sets. Each data set includes one or more data queues; each data set corresponds to a specific state.

[0063] Table 2 shows the data sequence uploaded by the vehicle-mounted network terminal in one example of this application. As shown in Table 2, in one example of this application, the vehicle-mounted network terminal B periodically uploads vehicle speed, engine speed, total mileage, and vehicle location to the server. The server responds to user instructions to calculate the driving indicators of the vehicle corresponding to the vehicle-mounted network terminal B within a specified time period, which requires retrieving data segments corresponding to each driving state from the database.

[0064]

[0065] Table 2:

[0066] Assuming the node data representing the start or end of a specific state are Y1R / min, Y2R / min, Y3R / min, and Y4R / min, and using the queues containing Y1R / min, Y2R / min, Y3R / min, and Y4R / min as the dividing endpoints, the data sequence shown in Table 2 is segmented to obtain the first segment of the driving state corresponding to the data set {13305, X1m / s, Y1R / min, ...} km, (101e, 32s)} to {13309, X2m / s, Y2R / min, The data queue between {km, (92e, 32s)} and the data set corresponding to the second segment of driving status are {13310, X3m / s, Y3R / min,} km, (101e, 31s)} to {13311, X4m / s, Y4R / min, The data queue is between km and (102e, 30s).

[0067] This application embodiment also proposes an optional implementation of step S12, "extracting data segments with the position of the target data queue in the data sequence as endpoints, and obtaining the data set generated by the target device during the specific state existence phase";

[0068] Step S121: Obtain the effect of the repeated records of the target data queue on the order of each data queue in the data sequence.

[0069] Given a data queue A in a data sequence, which has a certain permutation number, and assuming that there are N target data queues before data queue A, if the N target data queues are copied in the data sequence, then the permutation number of data queue A in the data sequence will be shifted N positions to the right.

[0070] This application embodiment also proposes an optional method for performing step S121, "obtaining the influence of repeated records of the target data queue on the order of each data queue in the data sequence":

[0071] Step S1211: Copy the target data queue and mark the copied target data queue.

[0072] Step S1212: Merge the target data queue carrying the tag with the data sequence to obtain a merged sequence.

[0073] Step S1213: Sort the merged data according to the preset rules and record the order of each data queue; when the node data represents the start of a specific state, the target data queue carrying the label is placed before the target data queue without the label; when the node data represents the end of a specific state, the target data queue carrying the label is placed after the target data queue without the label. Step S1214: Calculate the order difference between the order of each data queue in the data sequence and its order in the merged sequence.

[0074] Step S122 extracts multiple data queues with the same permutation order from the data sequence to obtain the data set generated by the target device during the specific state existence phase.

[0075] Since the N target data queues are copied in the data sequence, the order number of data queue A in the data sequence will be shifted N positions to the right. Therefore, this application also proposes that step S122 can be implemented by "extracting multiple data queues with the same order difference in the data sequence to obtain the data set generated by the target device during the specific state existence stage".

[0076] Figure 2 This is an example of an information instruction diagram for data processing in this application, such as... Figure 2 As shown in one example of this application, the target device is an in-vehicle network terminal C. The in-vehicle network terminal C periodically uploads data to a server database, and extracts data from the database on the vehicle corresponding to the in-vehicle network terminal C during continuous driving to analyze the driving indicators of the vehicle corresponding to the in-vehicle network terminal C. The steps are as follows:

[0077] K11: Obtain the data sequence C (including vehicle speed, mileage, vehicle, and device status) uploaded by the vehicle-to-everything (V2X) terminal C stored in the database over a period of time, and obtain the data carrying a unique device number, as shown in Table 3:

[0078] Table 3:

[0079]

[0080] K12: Determine whether each data point represents the start or end of a specific state.

[0081] K13: Locate the target data queue in the data sequence C that represents the start of a specific state, and obtain Table 4.

[0082]

[0083] K14: Copy the target data queue, mark the copied target data queue, and merge the marked copied target data queue with the original data sequence to obtain Table 5.

[0084] Table 5:

[0085]

[0086] K15: Sort the merged data sequence according to the time recorded in each data queue, and mark the sorting as RN1 to obtain Table 6.

[0087]

[0088]

[0089] K16: Filter the data queue with tags, sort the original data sequence, and denote the sorting tag as RN2 to obtain Table 7.

[0090] Table 7:

[0091]

[0092] K17: Calculate the difference between RN1 and RN2 corresponding to the same data queue, and obtain Table 8.

[0093] Table 8:

[0094]

[0095] K18: Divide multiple data queues with the same values ​​for RN1-RN2 into a data set to obtain the data corresponding to the vehicle network terminal C during multiple consecutive driving processes.

[0096] The data processing method proposed in this application only needs to scan the data once and calculate the relevant statistical analysis indicators, without needing to calculate the complex relationships between the data.

[0097] Figure 3 This is a functional block diagram of the data processing device proposed in the embodiments of this application. The data processing device is installed in a server, such as... Figure 3 As shown, the device includes:

[0098] The search module 31 is used to find node data representing the start or end of a specific state in the data sequence uploaded by the target device and obtain the target data queue where the node data is located; wherein, the data queues in the data sequence are arranged sequentially according to a preset rule;

[0099] Extraction module 32 is used to extract data segments with the position of the target data queue in the data sequence as the endpoint, and obtain the data set generated by the target device during the specific state existence phase.

[0100] Figure 3The data processing apparatus provided in the illustrated embodiments can be used to execute this specification. Figures 1 to 2 The implementation principle and technical effects of the method embodiment shown can be further referred to the relevant description in the method embodiment.

[0101] Optionally, when multiple specific states occur consecutively, there are multiple node data representing the start or end of a specific state; the extraction module is specifically used to divide the data sequence with the target data queue as the endpoint to obtain the data set corresponding to the multiple consecutively occurring specific states in their respective existence stages.

[0102] Optionally, the extraction module includes:

[0103] The ranking submodule is used to obtain the influence of the target data queue on the order of each data queue in the data sequence;

[0104] An extraction submodule is used to extract multiple data queues with the same permutation order in the data sequence, and obtain the data set generated by the target device during the specific state existence phase.

[0105] Optionally, the device further includes:

[0106] A marking module is used to copy the target data queue and mark the copied target data queue;

[0107] The ranking submodule includes:

[0108] The merging subunit is used to merge the target data queue carrying the tag with the data sequence to obtain a merged sequence;

[0109] The sorting subunit is used to sort the merged data according to the preset rules and record the order of each data queue; when the node data indicates the start of a specific state, the target data queue with the label is placed before the target data queue without the label; when the node data indicates the end of a specific state, the target data queue with the label is placed after the target data queue without the label; the calculation subunit is used to calculate the order difference between the order of each data queue in the data sequence and the order in the merged sequence.

[0110] Optionally, the extraction submodule is specifically used to extract multiple data queues with the same sequence difference from the data sequence to obtain the data set generated by the target device during the specific state existence phase.

[0111] Optionally, the preset rules include at least one of the following: arranging data in ascending order of data collection time, arranging data in ascending order of data upload time, or arranging data in the order of first to last upload.

[0112] The apparatus provided in the above embodiments is used to execute the technical solutions of the above method embodiments. Its implementation principle and technical effects can be further referred to the relevant descriptions in the method embodiments, and will not be repeated here.

[0113] The apparatus provided in the above embodiments may be, for example, a chip or a chip module. The apparatus provided in the above embodiments is used to execute the technical solutions of the above-described method embodiments. Its implementation principles and technical effects can be further referred to the relevant descriptions in the method embodiments, and will not be repeated here.

[0114] Regarding the modules / units included in the various devices described in the above embodiments, they can be software modules / units, hardware modules / units, or a combination of both. For example, for devices applied to or integrated into a chip, all modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs running on a processor integrated within the chip, while the remaining modules / units can be implemented using hardware methods such as circuits. For devices applied to or integrated into a chip module, all modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using software programs. The software program runs on the processor integrated inside the chip module, and the remaining modules / units can be implemented using hardware methods such as circuits. For each device applied to or integrated into an electronic terminal device, each of its modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components within the electronic terminal device. Alternatively, at least some modules / units can be implemented using software programs that run on the processor integrated inside the electronic terminal device, and the remaining (if any) modules / units can be implemented using hardware methods such as circuits.

[0115] Figure 4 This is a schematic diagram of the structure of a server provided in an embodiment of this application. The server 400 includes a processor 410, a memory 411, and a computer program stored in the memory 411 and executable on the processor 410. When the processor 410 executes the program, it implements the steps in the aforementioned method embodiment. The electronic device provided in this embodiment can be used to execute the technical solution of the method embodiment shown above. Its implementation principle and technical effects can be further referred to the relevant descriptions in the method embodiment, which will not be repeated here.

[0116] This application provides a computer-readable storage medium that stores computer instructions that cause the computer to execute this specification. Figures 1-2 The data processing method provided in the illustrated embodiment. A computer-readable storage medium may refer to a non-volatile computer storage medium.

[0117] The aforementioned computer-readable storage medium may be any combination of one or more computer-readable media. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used by or in connection with an instruction execution system, apparatus, or device.

[0118] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0119] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, radio frequency (RF), etc., or any suitable combination thereof.

[0120] Computer program code for performing the operations described herein can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as "C" or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0121] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0122] In the description of the embodiments in this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0123] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this specification, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0124] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this specification includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which the embodiments of this specification pertain.

[0125] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0126] It should be noted that the terminals involved in the embodiments of this application may include, but are not limited to, personal computers (PCs), personal digital assistants (PDAs), wireless handheld devices, tablet computers, mobile phones, MP3 players, MP4 players, etc.

[0127] In the several embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0128] Furthermore, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0129] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this specification. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0130] The above description is merely a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of protection of this specification.

Claims

1. A data processing method, characterized by, The method comprises: When a node data representing the beginning or end of a specific state is found in a data sequence uploaded on a target device, a target data queue where the node data is located is obtained; wherein each data queue in the data sequence is arranged in turn according to a preset rule; A data segment with the position of the target data queue in the data sequence as end points is extracted from the data sequence, and a data set generated by the target device in the specific state is obtained, wherein the data set comprises one or more data queues, and each data set corresponds to a specific state; After obtaining the target data queue where the node data is located, the method further comprises: copying the target data queue and marking the copied target data queue; obtaining the influence of the target data queue on the arrangement sequence position of each data queue in the data sequence, comprising: merging the target data queue carrying the mark with the data sequence to obtain a merged sequence; sorting the merged data according to the preset rule and recording the sequence position of each data queue; when the node data represents the beginning of a specific state, the target data queue carrying the mark is arranged before the target data queue without carrying the mark; when the node data represents the end of a specific state, the target data queue carrying the mark is arranged after the target data queue without carrying the mark; calculating the sequence difference value of the sequence position of each data queue in the data sequence and the sequence position in the merged sequence.

2. The method of claim 1, wherein, When a plurality of specific states occur continuously, the node data representing the beginning or end of a specific state is a plurality, and the data segment with the position of the target data queue in the data sequence as end points is extracted from the data sequence to obtain the data set generated by the target device in the specific state, comprising: dividing the data sequence with the target data queue as end points to obtain the data set corresponding to the plurality of specific states occurring continuously in their respective persistence stages.

3. The method of claim 1, wherein, extracting a data segment with the position of the target data queue in the data sequence as end points from the data sequence to obtain a data set generated by the target device in the specific state, comprising: obtaining the influence of repeated recording of the target data queue on the arrangement sequence position of each data queue in the data sequence; extracting a plurality of data queues with the same arrangement sequence position influence in the data sequence to obtain a data set generated by the target device in the specific state.

4. The method of claim 1, wherein, extracting a plurality of data queues with the same arrangement sequence position influence in the data sequence to obtain a data set generated by the target device in the specific state, comprising: extracting a plurality of data queues with the same sequence difference value in the data sequence to obtain a data set generated by the target device in the specific state.

5. The method according to any of claims 1 to 4, characterized in that, The preset rule comprises at least one of arranging in the order from small to large according to the data acquisition time, arranging in the order from small to large according to the data upload time, or arranging in the order from first to last according to the data upload.

6. A data processing apparatus, characterized by The device comprises: The searching module is configured to, when a node data indicating a beginning or an end of a specific state is found in a data sequence on a target device, obtain a target data queue in which the node data is located; wherein each data queue in the data sequence is arranged in sequence according to a preset rule; The extracting module is configured to extract, in the data sequence, a data segment with the target data queue in the data sequence as an end point, to obtain a data set generated by the target device in a specific state duration, the data set including one or more data queues, and each data set corresponding to a specific state; The device further comprises: The marking module is configured to copy the target data queue and mark the copied target data queue; The extracting module comprises a ranking sub-module, and the ranking sub-module comprises: The merging sub-unit is configured to merge the target data queue carrying the mark and the data sequence to obtain a merged sequence; The sorting sub-unit is configured to sort the merged data according to the preset rule and record a sequence position of each data queue; when the node data indicates a beginning of a specific state, the target data queue carrying the mark is arranged before the target data queue not carrying the mark; when the node data indicates an end of a specific state, the target data queue carrying the mark is arranged after the target data queue not carrying the mark; and the calculating sub-unit is configured to calculate a sequence difference value of a sequence position of each data queue in the data sequence and a sequence position in the merged sequence.

7. The apparatus of claim 6, wherein, When a plurality of specific states occur continuously, the node data indicating a beginning or an end of a specific state is a plurality of node data; and the extracting module is specifically configured to divide the data sequence with the target data queue as an end point to obtain data sets corresponding to the plurality of specific states occurring continuously in respective durations.

8. A server, comprising: at least one processor; and at least one memory connected with the processor, characterized in that the memory stores program instructions executable by the processor, and the processor invoking the program instructions can execute the method according to any one of claims 1 to 5.

9. A computer-readable storage medium storing computer instructions, wherein, The computer instructions enable the computer to execute the method according to any one of claims 1 to 5.

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