Streaming media data classification statistical method, device, equipment and medium

Abstract

The invention provides a streaming media data classification statistics method and device, equipment and a medium, and relates to the technical field of data classification statistics, and the method comprises the steps: obtaining target streaming media data and a video service feature tag used for representing the service feature of the target streaming media data; generating a first streaming media feature tag according to the target streaming media data and the video service feature tag; acquiring a plurality of pieces of real-time streaming media data and second streaming media feature tags corresponding to the real-time streaming media data; taking real-time streaming media data corresponding to a second streaming media feature tag matched with the first streaming media feature tag from the multiple pieces of real-time streaming media data as target real-time streaming media data; and associating the target real-time streaming media data with the video service feature tag corresponding to the first streaming media feature tag, and counting the traffic of the target real-time streaming media data. According to the invention, classification and statistics of SIP traffic and real-time media stream traffic of different media stream receiver entities are realized.

Description

Technical Field

[0001] The present application relates to the technical field of data classification and statistics, and in particular to a method, device, equipment and medium for streaming media data classification and statistics. Background Art

[0002] The existing methods for classifying and counting streaming media data generally rely on video security exchange systems outside the platform for statistics. In addition, the classification and statistical standards of video security exchange systems of different manufacturers are diverse and different and cannot be unified. The platform's docking with video security exchange systems of multiple manufacturers requires independent customized development, which increases the difficulty of use. In order to achieve unified classification and statistics of media stream data, compatible docking with different video security exchange systems, and reduce the difficulty of implementation, it is necessary to implement a traffic-based media stream data classification and statistics solution.

[0003] The prior art lacks a solution for counting media flow data by traffic classification. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a streaming media data classification and statistics method, device, equipment and medium to solve the above-mentioned problems existing in the prior art, and can identify the streaming media data category during a signaling session and classify and count the streaming media data.

[0005] In a first aspect, a streaming media data classification and statistics method is provided, which may include: Acquire target streaming media data and a video service feature tag for characterizing service features of the target streaming media data; Generate a first streaming media feature tag according to the target streaming media data and the video service feature tag; Acquire multiple pieces of real-time streaming media data and second streaming media feature tags corresponding to each piece of real-time streaming media data; From the plurality of pieces of real-time streaming media data, taking the real-time streaming media data corresponding to the second streaming media feature tag matching the first streaming media feature tag as the target real-time streaming media data; The target real-time streaming media data is associated with the video service feature tag corresponding to the first streaming media feature tag, and the flow size of the target real-time streaming media data is counted.

[0006] In an optional implementation, the method for acquiring the video service feature tag includes: Acquire registration information of a media server, a streaming media receiver, and a SIP server; wherein the registration information includes: an IP address of the media server, an IP address of the streaming media receiver, and a SIP signaling port for the streaming media receiver and the media server to negotiate streaming media data; The video service feature tag is generated based on the IP address of the media server, the IP address of the streaming media receiver, and the SIP signaling port.

[0007] In an optional implementation, generating a first streaming media feature tag according to the target streaming media data and the video service feature tag includes: Parsing the target streaming media data to obtain a session identifier and a SIP application layer protocol; The first streaming media feature tag is generated based on the session identifier, the IP address of the streaming media receiver, the IP address of the media server, the SIP signaling port and the SIP application layer protocol.

[0008] In an optional implementation, after generating the first streaming media feature tag, the method further includes: A third streaming media feature tag corresponding to the first streaming media feature tag is generated based on the SIP application layer protocol and the session identifier.

[0009] In an optional implementation, the method for acquiring each second streaming media feature tag includes: For any real-time streaming media data, the real-time streaming media data is parsed to obtain a session identifier of the real-time streaming media data, an IP address of a media server and an RTP application layer protocol; A second streaming media feature tag of the real-time streaming media data is generated based on the session identifier, the IP address of the media server and the RTP application layer protocol.

[0010] In an optional implementation, from a plurality of pieces of real-time streaming media data, taking the real-time streaming media data corresponding to the second streaming media feature tag matching the first streaming media feature tag as the target real-time streaming media data includes: If the second streaming media feature tag of any real-time streaming media data is the same as the third streaming media feature tag corresponding to the first streaming media feature tag, the real-time streaming media data is used as the target real-time streaming media data.

[0011] In an optional implementation, the method further includes: The flow size of target real-time streaming media data associated with different video service feature tags is counted to obtain classification statistics results of the streaming media data.

[0012] In a second aspect, a streaming media data classification and statistics device is provided, which may include: An acquisition unit, used for acquiring target streaming media data and a video service feature tag for characterizing service features of the target streaming media data; A generating unit, configured to generate a first streaming media feature tag according to the target streaming media data and the video service feature tag; A matching unit is used to obtain a plurality of real-time streaming media data and a second streaming media feature tag corresponding to each real-time streaming media data; from the plurality of real-time streaming media data, the real-time streaming media data corresponding to the second streaming media feature tag that matches the first streaming media feature tag is used as the target real-time streaming media data; The classification unit is used to associate the target real-time streaming media data with the video service feature tag corresponding to the first streaming media feature tag, and to count the flow size of the target real-time streaming media data.

[0013] In a third aspect, an electronic device is provided, the electronic device comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; The processor is used to implement any method step described in the first aspect when executing the program stored in the memory.

[0014] In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, any method step described in the first aspect is implemented.

[0015] The present application identifies streaming media data during a signaling session without caring about the specific data content, and not only realizes the statistics of the flow size of streaming media data, but also realizes the classification and statistics of SIP flow and real-time media flow flow of different media flow receiver entities.

[0016] This application is based on the GB / T28181 protocol standard and is applicable to the classified statistics of media stream traffic data generated by all video data exchange systems that comply with this standard; it can accurately identify the SIP protocol signaling sessions and the corresponding negotiated media stream data in the traffic data, and associate them with the device IP and SIP signaling listening port registered by the video business party, so as to realize the classified statistics of media stream data according to the video business party. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1A flow chart of a streaming media data classification and statistics method provided in an embodiment of the present application; Figure 2 A schematic diagram of a streaming media data classification and statistics method provided in an embodiment of the present application; Figure 3 An architectural diagram of a streaming media data classification and statistics method provided in an embodiment of the present application; Figure 4 A structural diagram of a streaming media data classification and statistics device provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] The streaming media data classification and statistics method provided in the embodiment of the present application is applied to a multimedia communication system, and is used to count the categories of streaming media data and the traffic under different categories during each session. The multimedia communication system includes a streaming media receiver, a SIP server, a media server, and a streaming media sender; Media server, a central node for storing, processing and distributing multimedia content; A streaming media sender is a device or software application that generates and transmits real-time or pre-recorded audio / video data streams. A streaming media sender can be a smartphone, a camera and microphone on a computer, or a professional-grade broadcasting device. It is used to transmit streaming media to a media server or other receivers via network protocols (such as RTP / RTCP).

[0021] The streaming media receiver is a terminal device or application that decodes and displays the streaming media from the sender. It can be any platform that can play audio and video content, such as smart TVs, mobile applications, web browsers, etc. It is used to parse the data packets received from the sender or media server and restore them to a form that can be viewed or listened to. SIP server is used to create, modify and terminate sessions between two or more participating endpoints; SIP server acts as an intermediary to transmit invitations, responses and other messages between user agents (UA) to help establish communication connections.

[0022] In a single streaming media communication process, the SIP signaling port for streaming media data negotiation between the streaming media receiver and the SIP server is fixed and unique, and the port for real-time streaming media transmission between the streaming media receiver and the media server obtained after negotiation is also unique. Therefore, this application realizes the classification and statistics of SIP traffic and real-time streaming media traffic of different streaming media receiver entities by combining the SIP signaling port registered by the streaming media receiver on the SIP server.

[0023] The streaming media data classification and statistics method provided in the embodiment of the present application can be applied in a server or in a terminal with strong computing power. The server can be a physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms. The terminal can be a user equipment (User Equipment, UE) such as a mobile phone, a smart phone, a laptop, a digital broadcast receiver, a personal digital assistant (PDA), a tablet computer (PAD), a handheld device, a vehicle-mounted device, a wearable device, a computing device or other processing equipment connected to a wireless modem, a mobile station (Mobile Station, MS), a mobile terminal (Mobile Terminal), etc. The terminal and the server can be directly or indirectly connected through a wired or wireless communication method, which is not limited in this application.

[0024] The preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. In addition, the embodiments and features in the embodiments of the present application may be combined with each other if there is no conflict.

[0025] Figure 1 A flow chart of a streaming media data classification and statistics method provided in an embodiment of the present application. Figure 1 As shown, the method may include: Step S110: acquiring target streaming media data and a video service feature tag for characterizing service features of the target streaming media data; and generating a first streaming media feature tag according to the target streaming media data and the video service feature tag.

[0026] In an embodiment of the present application, a method for obtaining a video service feature tag includes: obtaining registration information of a media server, a streaming media receiver, and a SIP server, and generating a video service feature tag based on the IP address of the media server, the IP address of the streaming media receiver, and the SIP signaling port.

[0027] Specifically, the registration information includes: the IP address of the media server, the IP address of the streaming media receiver, and the SIP signaling port for the streaming media receiver and the media server to negotiate streaming media data.

[0028] In an embodiment of the present application, the first streaming media feature tag and the second streaming media feature tag both include data such as source IP address, source port, destination IP address, destination port, application layer protocol, transport layer protocol and timestamp; the source IP address and source port of the first streaming media feature tag and the second streaming media feature tag are both the IP address and corresponding port of the streaming media receiver; and the destination IP address, destination port and application layer protocol of the first streaming media feature tag are respectively the IP address, SIP signaling port and SIP protocol of the SIP server; the destination IP address, destination port and application layer protocol of the second streaming media feature tag are respectively the IP address, port and RPT protocol or RTCP of the media server; the transport layer protocol of the first streaming media feature tag and the second streaming media feature tag are both UDP protocols.

[0029] In the embodiment of the present application, generating a first streaming media feature tag according to target streaming media data and a video service feature tag includes: The target streaming media data is parsed to obtain a session identifier and a SIP application layer protocol; a first streaming media feature tag is generated based on the session identifier, an IP address of a streaming media receiver, an IP address of a media server, a SIP signaling port, and a SIP application layer protocol.

[0030] In an embodiment of the present application, a first streaming media feature tag is obtained by parsing the traffic data (i.e., target streaming media data) between a media receiver and a SIP server; a second streaming media feature tag is obtained by parsing the traffic data (i.e., target real-time streaming media data) between a media receiver and a media server.

[0031] In the embodiment of the present application, the session identifier is the CALL-ID generated when the media receiver sends a request to the SIP server; the session identifiers of different media receivers in different session communications are different and unique. The session identifier can not only determine the unique media receiver, but also determine which session communication the media receiver has with the SIP server.

[0032] The embodiment of the present application parses the corresponding streaming media data to obtain the first streaming media feature tag and the second streaming media feature tag, thereby simplifying complex traffic data into specific tag data, improving the data transmission and storage speed, and thus ensuring the efficiency of association analysis.

[0033] In an embodiment of the present application, after generating the first streaming media feature tag, the method further includes: generating a third streaming media feature tag corresponding to the first streaming media feature tag based on the SIP application layer protocol and the session identifier; specifically, the third streaming media feature tag includes: session identifier, IP address of the media server, port, transport layer protocol and timestamp, etc.

[0034] Step S120, obtaining multiple pieces of real-time streaming media data and second streaming media feature tags corresponding to each piece of real-time streaming media data; from the multiple pieces of real-time streaming media data, taking the real-time streaming media data corresponding to the second streaming media feature tag matching the first streaming media feature tag as the target real-time streaming media data.

[0035] In an embodiment of the present application, the target streaming media data and the real-time streaming media data are both acquired or generated through a traffic probe, and specifically include information such as the data sending source IP address, source port, destination IP address, destination port, application layer protocol, transport layer protocol, protocol content and timestamp.

[0036] In an embodiment of the present application, a method for acquiring a second streaming media feature tag includes: For any real-time streaming media data, the real-time streaming media data is parsed to obtain the session identifier of the real-time streaming media data, the IP address of the media server and the RTP application layer protocol; based on the session identifier, the IP address of the media server and the RTP application layer protocol, a second streaming media feature tag of the real-time streaming media data is generated.

[0037] In the embodiment of the present application, the second streaming media feature tag also includes: the port transport layer protocol and timestamp of the media server, etc.

[0038] In an embodiment of the present application, when multiple real-time streaming media data are received, it is necessary to select streaming media data of the same media receiver in the same session from the multiple real-time streaming media data, and complete the matching of the real-time streaming media data by comparing the third streaming media feature tag and the second streaming media feature tag. If the third streaming media feature tag and the second streaming media feature tag are the same, it means that the real-time streaming media data corresponding to the second streaming media feature tag is the streaming media data of the same media receiver in the same session, and the real-time streaming media data is used as the target real-time streaming media data. Step S130: Associating the target real-time streaming media data with the video service feature tag corresponding to the first streaming media feature tag, and counting the flow size of the target real-time streaming media data.

[0039] In an embodiment of the present application, the target real-time streaming media data is associated with the corresponding video service feature tag, so that different real-time streaming media data are classified according to different video service feature tags; the flow size of the target real-time streaming media data under different video service feature tags is counted to obtain the flow of the streaming media data of the corresponding video service party.

[0040] In an embodiment of the present application, the number of media receivers may be one or more, and the above steps are performed for each session of each media receiver to determine the traffic data of the corresponding video service party (ie, the media receiver, the SIP server, and the media server).

[0041] The streaming media data classification and statistics method of the embodiment of the present application is applied during the SIP protocol signaling session before the SIP protocol signaling session ends, and is used to count the negotiated media stream protocol data and associate and match it with the identifier of the SIP protocol traffic data, thereby realizing classification statistics and finally associating the data with the corresponding video service party.

[0042] like Figure 2-Figure 3 As shown, the streaming media data classification and statistics method of the embodiment of the present application includes: First, obtain multi-terminal streaming media traffic data (use traffic probes to push the detected streaming media data to the kakfa server), and obtain the traffic data of the SIP protocol video signaling session in chronological order; secondly, based on the 200 OK video signaling session traffic, generate video streaming media traffic feature labels; finally, match and count the video streaming media traffic feature labels with subsequent multi-terminal streaming media traffic data.

[0043] In the embodiment of the present application, the video streaming media traffic feature tag is matched and counted with subsequent multi-terminal streaming media traffic data, including: Identify that the application layer protocol is SIP, the protocol content contains 200 OK data, parse the protocol content, obtain the transmission feature data of the negotiated media stream, including the data sender IP address, sender port, receiver IP address, receiver port, application layer protocol, transport layer protocol, etc., and generate a streaming media traffic feature label A (i.e., the first streaming media feature label); Continue to analyze and process subsequent media stream flow data to obtain flow feature information, including sender IP address, sender port, receiver IP address, receiver port, application layer protocol, transport layer protocol, etc., and generate streaming media flow feature label B (i.e., second streaming media feature label); Streaming media traffic feature labels A and B are correlated and analyzed. If label B is consistent with label A (that is, the first streaming media feature label and the third streaming media feature label generated based on the first streaming media feature label are the same), the traffic size in feature label B is counted and attributed to the video business side traffic of the Antelope Border Security Centralized Control Platform that contains feature A information.

[0044] Corresponding to the above method, the embodiment of the present application also provides a streaming media data classification and statistics device, such as Figure 4 As shown, the streaming media data classification and statistics device includes: An acquisition unit 410 is used to acquire target streaming media data and a video service feature tag used to characterize service features of the target streaming media data; A generating unit 420, configured to generate a first streaming media feature tag according to target streaming media data and a video service feature tag; The matching unit 430 is used to obtain a plurality of real-time streaming media data and a second streaming media feature tag corresponding to each of the real-time streaming media data; from the plurality of real-time streaming media data, the real-time streaming media data corresponding to the second streaming media feature tag that matches the first streaming media feature tag is used as the target real-time streaming media data; The classification unit 440 is used to associate the target real-time streaming media data with the video service feature tag corresponding to the first streaming media feature tag, and to count the flow size of the target real-time streaming media data.

[0045] The functions of each functional unit of the streaming media data classification and statistics device provided in the above embodiments of the present application can be realized through the above method steps. Therefore, the specific working process and beneficial effects of each unit in the streaming media data classification and statistics device provided in the embodiments of the present application are not repeated here.

[0046] The present application also provides an electronic device, such as Figure 5 As shown, it includes a processor 510 , a communication interface 520 , a memory 530 and a communication bus 540 , wherein the processor 510 , the communication interface 520 , and the memory 530 communicate with each other via the communication bus 540 .

[0047] Memory 530, for storing computer programs; The processor 510 is used to execute the program stored in the memory 530 to implement the following steps: Obtain target streaming media data and a video service feature label for characterizing service features of the target streaming media data; Generate a first streaming media feature tag according to the target streaming media data and the video service feature tag; Acquire multiple pieces of real-time streaming media data and second streaming media feature tags corresponding to each piece of real-time streaming media data; From the plurality of pieces of real-time streaming media data, the real-time streaming media data corresponding to the second streaming media feature tag matching the first streaming media feature tag is used as the target real-time streaming media data; The target real-time streaming media data is associated with the video service feature tag corresponding to the first streaming media feature tag, and the flow size of the target real-time streaming media data is counted.

[0048] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0049] The communication interface is used for communication between the above electronic device and other devices.

[0050] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0051] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0052] The implementation methods and beneficial effects of the components of the electronic device in the above embodiments to solve the problems can be seen in Figure 1 The various steps in the illustrated embodiment are implemented, therefore, the specific working process and beneficial effects of the electronic device provided by the embodiment of the present application are not repeated here.

[0053] In another embodiment provided in the present application, a computer-readable storage medium is provided, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes any of the streaming media data classification and statistics methods in the above embodiments.

[0054] In another embodiment provided by the present application, a computer program product including instructions is also provided, which, when executed on a computer, enables the computer to execute any of the streaming media data classification and statistics methods in the above embodiments.

[0055] Those skilled in the art will appreciate that the embodiments in the present application can be provided as methods, systems, or computer program products. Therefore, the embodiments in the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments in the present application can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0056] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0057] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0058] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0059] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present application.

[0060] Obviously, those skilled in the art can make various changes and modifications to the embodiments in the present application without departing from the spirit and scope of the embodiments in the present application. Thus, if these modifications and variations of the embodiments in the present application fall within the scope of the claims and their equivalents in the embodiments of the present application, the embodiments of the present application are also intended to include these modifications and variations.

Claims

1. A streaming media data classification and statistics method, characterized in that: Applied in a processor, the method comprises: Acquire target streaming media data and a video service feature tag for characterizing service features of the target streaming media data; Generate a first streaming media feature tag according to the target streaming media data and the video service feature tag; Acquire multiple pieces of real-time streaming media data and second streaming media feature tags corresponding to each piece of real-time streaming media data; From the plurality of pieces of real-time streaming media data, taking the real-time streaming media data corresponding to the second streaming media feature tag matching the first streaming media feature tag as the target real-time streaming media data; The target real-time streaming media data is associated with the video service feature tag corresponding to the first streaming media feature tag, and the flow size of the target real-time streaming media data is counted.

2. The method according to claim 1, characterized in that The method for obtaining the video service feature label includes: Acquire registration information of a media server, a streaming media receiver, and a SIP server; wherein the registration information includes: an IP address of the media server, an IP address of the streaming media receiver, and a SIP signaling port for the streaming media receiver and the media server to negotiate streaming media data; The video service feature tag is generated based on the IP address of the media server, the IP address of the streaming media receiver, and the SIP signaling port.

3. The method according to claim 2, characterized in that Generating a first streaming media feature tag according to the target streaming media data and the video service feature tag includes: Parsing the target streaming media data to obtain a session identifier and a SIP application layer protocol; The first streaming media feature tag is generated based on the session identifier, the IP address of the streaming media receiver, the IP address of the media server, the SIP signaling port and the SIP application layer protocol.

4. The method according to claim 3, characterized in that After generating the first streaming media feature tag, the method further includes: A third streaming media feature tag corresponding to the first streaming media feature tag is generated based on the SIP application layer protocol and the session identifier.

5. The method according to claim 4, characterized in that The method for obtaining the characteristic labels of each second streaming media includes: For any real-time streaming media data, the real-time streaming media data is parsed to obtain a session identifier of the real-time streaming media data, an IP address of a media server and an RTP application layer protocol; A second streaming media feature tag of the real-time streaming media data is generated based on the session identifier, the IP address of the media server and the RTP application layer protocol.

6. The method according to claim 5, characterized in that From the plurality of pieces of real-time streaming media data, taking the real-time streaming media data corresponding to the second streaming media feature tag matching the first streaming media feature tag as the target real-time streaming media data, comprising: If the second streaming media feature tag of any real-time streaming media data is the same as the third streaming media feature tag corresponding to the first streaming media feature tag, the real-time streaming media data is used as the target real-time streaming media data.

7. The method according to claim 5, characterized in that The method further comprises: The flow size of target real-time streaming media data associated with different video service feature tags is counted to obtain classification statistics results of the streaming media data.

8. A streaming media data classification and statistics device, characterized in that: The device comprises: An acquisition unit, used for acquiring target streaming media data and a video service feature tag for characterizing service features of the target streaming media data; A generating unit, configured to generate a first streaming media feature tag according to the target streaming media data and the video service feature tag; A matching unit is used to obtain a plurality of real-time streaming media data and a second streaming media feature tag corresponding to each real-time streaming media data; from the plurality of real-time streaming media data, the real-time streaming media data corresponding to the second streaming media feature tag that matches the first streaming media feature tag is used as the target real-time streaming media data; The classification unit is used to associate the target real-time streaming media data with the video service feature tag corresponding to the first streaming media feature tag, and to count the flow size of the target real-time streaming media data.

9. An electronic device, characterized in that: The electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; A processor, for implementing any of the methods described in claims 1-7 when executing a program stored in a memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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