Online operation flow data monitoring system and method based on big data

Abstract

The invention discloses an online operation flow data monitoring system and method based on big data, and relates to the field of flow data monitoring. The method comprises the following steps: acquiring an online operation traffic data packet corresponding to a traffic acquisition type by adopting a data acquisition tool; classifying the online operation flow data packets according to the flow acquisition type, and acquiring online operation flow classification data packets; processing the online operation traffic classification data packets to obtain a standard first operation traffic data node threshold value, and further obtaining abnormal online operation traffic classification data packets and normal online operation traffic classification data packets in the online operation traffic classification data packets; performing traffic analysis on the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet to obtain a corresponding online operation traffic curve graph, and obtaining an optimal online operation traffic putting decision according to the online operation traffic curve graph; according to the invention, the accuracy of obtaining the optimal online operation traffic delivery decision is improved.

Description

Technical Field

[0001] The present invention relates to the field of traffic data monitoring, and specifically to an online operation traffic data monitoring system and method based on big data. Background Art

[0002] Online operation traffic refers to the access and interaction data obtained through the Internet, which are usually associated with the activities of websites, applications, or other online platforms; in digital marketing and e-commerce, online operation traffic is one of the important indicators for evaluating the health and success of online businesses;

[0003] Online operation requires monitoring and analyzing various data, and then obtaining online operation traffic data and judging the operation status of the store, so as to make corresponding adjustments and optimizations to the store;

[0004] However, in the prior art, due to the large amount of access and interaction data obtained through the Internet, and different acquisition devices and source channels, it is impossible to accurately and completely obtain the access and interaction data; due to the large amount of access and interaction data, it is impossible to quickly process and analyze the access and interaction data, and it is impossible to obtain accurate online operation decisions; therefore, an online operation traffic data monitoring system and method based on big data are provided. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides an online operation traffic data monitoring system and method based on big data;

[0006] The object of the present invention can be achieved by the following technical solutions: An online operation traffic data monitoring system based on big data includes a data center, and the data center is wirelessly communicatively connected to an operation traffic data acquisition module, an operation traffic processing module, and an operation traffic analysis module;

[0007] The data center is used for storing data related to online operation traffic;

[0008] The operation traffic data acquisition module is used for collecting online operation traffic data packets corresponding to the traffic acquisition type by using data acquisition tools;

[0009] The operation traffic processing module is used for setting an operation traffic classification unit and an operation traffic separation unit;

[0010] The operation traffic classification unit is used for classifying the online operation traffic data packets according to the traffic acquisition type to obtain online operation traffic classified data packets;

[0011] The operation traffic separation unit is used to obtain the standard first operation traffic data node threshold, and then obtain the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet in the online operation traffic classification data packet;

[0012] The operation traffic analysis module is used to perform traffic analysis on the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet respectively, obtain the corresponding online operation traffic curve graph, and then obtain the optimal online operation traffic delivery decision.

[0013] Furthermore, the process of the operation traffic data acquisition module acquiring online operation traffic data includes:

[0014] Set a data acquisition tool importer in the operation traffic data acquisition module, which is used to import the data acquisition tool for acquiring online operation traffic data, obtain the corresponding data acquisition type of the data acquisition tool, and perform data connection between the data acquisition type and the corresponding data acquisition tool to generate a data acquisition tool data set. Then, integrate several data acquisition tool data sets to obtain a data acquisition tool data packet;

[0015] Obtain several online operation traffic acquisition platforms, obtain all traffic acquisition types corresponding to the online operation traffic acquisition platforms, and perform data connection between the traffic acquisition type and the corresponding online operation traffic acquisition platform to generate the corresponding online operation traffic acquisition platform database. Then, integrate several online operation traffic acquisition platform databases to obtain an online operation traffic acquisition platform data packet, and send it to the data center for storage;

[0016] Set the first acquisition time point, denoted as t L , where L represents the traffic acquisition type; compare the traffic acquisition type in the online operation traffic acquisition platform database with the data acquisition type in the data acquisition tool data packet, obtain the data acquisition type that is the same as the traffic acquisition type, and then obtain the corresponding data acquisition tool of the data acquisition type. Schedule the corresponding data acquisition tool from the data acquisition tool package and transmit it to the corresponding online operation traffic acquisition platform for data acquisition to obtain the first platform operation traffic data corresponding to the first acquisition time point, and denote it as f tL Integrate the first platform operation traffic data corresponding to the online operation traffic acquisition platform to obtain the corresponding platform operation traffic data;

[0017] And send the platform operation traffic data to perform data connection with the online operation traffic acquisition platform data packet and the online operation traffic acquisition platform to generate an online operation traffic data packet, and send it to the data center for storage.

[0018] Further, the process by which the operation traffic classification unit obtains the online operation traffic classification data packet includes:

[0019] Extract and integrate the first platform operation traffic data corresponding to the same traffic acquisition type in the online operation traffic data packet according to the traffic acquisition type, obtain the online operation traffic classification data packet, and send it to the operation traffic separation unit.

[0020] Further, the process by which the operation traffic separation unit obtains the standard first operation traffic data node threshold includes:

[0021] Generate the first platform operation traffic data node from the first platform operation traffic data in the online operation traffic classification data packet, obtain the first acquisition time point corresponding to the first platform operation traffic data node, use the first acquisition time point as the X-axis and the first platform operation traffic data as the Y-axis to establish a first rectangular coordinate system, and then mark the first platform operation traffic data node in the first rectangular coordinate system;

[0022] Divide the first acquisition time point into six acquisition time periods, obtain the corresponding time period normal distribution according to the acquisition time period, and denote it as X ∼ N(μ i , σ i 2 ), where μ i and σ i 2 respectively represent a mathematical expectation and variance that the random first acquisition time point of the i-th acquisition time period follows, i represents the acquisition time period number, and i = 1, 2, 3, 4, 5, 6;

[0023] That is, the formula for obtaining the time period normal distribution diagram is:

[0024]

[0025] where F(t L ) represents the standard first operation traffic data node threshold obtained at the first acquisition time point corresponding to the traffic acquisition type in the time period normal distribution diagram.

[0026] Further, the process for obtaining the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet includes:

[0027] Compare the first platform operation traffic data corresponding to the first acquisition time point with the corresponding standard first operation traffic data node threshold:

[0028] If Then mark the corresponding first platform operation traffic data node as a normal online operation traffic data node, obtain the first platform operation traffic data corresponding to the normal online operation traffic data node and perform data integration, and then obtain the normal online operation traffic classification data packet in the online operation traffic classification data packet;

[0029] If Then mark the corresponding first platform operation traffic data node as an abnormal online operation traffic data node, obtain the first platform operation traffic data corresponding to the abnormal online operation traffic data node and perform data integration, and then obtain the abnormal online operation traffic classification data packet in the online operation traffic classification data packet.

[0030] Further, the process by which the operation traffic analysis module obtains the online operation traffic curve graph includes:

[0031] Connect the normal online operation traffic data nodes and abnormal online operation traffic data nodes corresponding to the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet respectively according to the first collection time point sequence, and generate a normal online operation traffic curve graph and an abnormal online operation traffic curve graph respectively;

[0032] The online operation traffic curve graph includes a normal online operation traffic curve graph and an abnormal online operation traffic curve graph.

[0033] Further, the process by which the operation traffic analysis module obtains the optimal online operation traffic decision includes:

[0034] Obtain the operation traffic data difference between the first platform operation traffic data corresponding to the abnormal online operation traffic data node in the abnormal online operation traffic curve graph and the threshold of the corresponding standard first operation traffic data node, denoted as And display it on the corresponding abnormal online operation traffic data node;

[0035] Obtain the maximum value of the operation traffic data difference, and then obtain the corresponding first collection time point and traffic acquisition type. According to the first collection time point and traffic acquisition type, obtain the corresponding normal first platform operation traffic data node in the normal online operation traffic curve graph, and then obtain the corresponding online operation traffic acquisition platform, which is marked as the optimal online operation traffic acquisition platform;

[0036] According to the optimal online operation traffic acquisition platform, obtain the optimal online operation traffic delivery decision corresponding to the traffic acquisition type, and mark the corresponding normal online operation data node as red.

[0037] The optimal online operation traffic delivery decision includes the optimal online operation traffic acquisition platform and the first collection time point.

[0038] Further, it includes the following steps:

[0039] Step 1: Use a data collection tool to collect the online operation traffic data packet corresponding to the traffic acquisition type;

[0040] Step 2: Classify the online operation traffic data packet according to the traffic acquisition type to obtain the online operation traffic classification data packet; process the online operation traffic classification data packet to obtain the standard first operation traffic data node threshold, and then obtain the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet in the online operation traffic classification data packet;

[0041] Step 3: Perform traffic analysis on the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet respectively to obtain the corresponding online operation traffic curve graph, and then obtain the optimal online operation traffic delivery decision.

[0042] Further, a management module is set up. The management module is used to set the online operation traffic data monitoring period column, which is used to monitor the online operation traffic curve graph in real time, obtain the changing first platform operation traffic data node, and update the optimal online operation traffic delivery decision;

[0043] Set the monitoring time in the online operation traffic data monitoring period column, monitor the online operation traffic curve graph according to the monitoring time, obtain the abnormal online operation traffic data node newly added to the abnormal online operation traffic curve graph, obtain the normal online operation traffic data node corresponding to the normal online operation traffic curve graph and generate the changing first platform operation traffic data node, and then update the optimal online operation traffic delivery decision according to the changing first platform operation traffic data node.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] 1. Obtain the traffic acquisition type corresponding to the online operation traffic acquisition platform, and use the corresponding data collection tool according to the traffic acquisition type, which improves the acquisition accuracy and the data collection speed;

[0046] 2. Obtain the standard first operation traffic data node threshold, and obtain the corresponding threshold according to different acquisition time periods, different online operation traffic acquisition platforms, and different traffic acquisition types, which improves the accuracy of online operation traffic data analysis;

[0047] 3. Set different monitoring times in the online operation traffic data monitoring period column, and monitor the online operation traffic data according to the monitoring time on the online operation traffic data monitoring period column, which improves the accuracy of obtaining the optimal online operation traffic delivery decision. Description of the Drawings

[0048] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0049] Figure 1 It is the schematic diagram of the present invention.

[0050] Figure 2 It is the flowchart of the present invention. Detailed implementation manners

[0051] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0052] Please refer to as Figure 1 As shown, this embodiment provides an online operation traffic data monitoring system based on big data, including a data center, and the monitoring center is wirelessly communicatively connected to an operation traffic data collection module, an operation traffic processing module, an operation traffic analysis module, and a management module;

[0053] The data center is used to store data related to online operation traffic;

[0054] The operation traffic data collection module is used to collect online operation traffic data packets corresponding to the traffic acquisition type by using a data collection tool;

[0055] The operation traffic processing module is used to set an operation traffic classification unit and an operation traffic separation unit;

[0056] The operation traffic classification unit is used to classify the online operation traffic data packets according to the traffic acquisition type to obtain online operation traffic classification data packets;

[0057] The operation traffic separation unit is used to obtain the standard first operation traffic data node threshold, and then obtain the abnormal online operation traffic classification data packets and normal online operation traffic classification data packets in the online operation traffic classification data packets;

[0058] The operation traffic analysis module is used to perform traffic analysis on the normal online operation traffic classification data packets and abnormal online operation traffic classification data packets respectively, obtain the corresponding online operation traffic curve graphs, and then obtain the best online operation traffic placement decision;

[0059] The management module is used to set the monitoring period column for online operation traffic data, monitor the online operation traffic curve graph in real time, obtain the first platform operation traffic data nodes of changes, and update the optimal online operation traffic investment decision;

[0060] The operation traffic data collection module is used to collect online operation traffic data. The processing process of the operation traffic data collection module is as follows:

[0061] S1: Set a data collection tool importer in the operation traffic data collection module, which is used to import the data collection tool for collecting online operation traffic data and generate a data collection tool data packet;

[0062] S2: Obtain several online operation traffic acquisition platforms, transmit the data collection tool package to the online operation traffic acquisition platforms for data collection, and then obtain the online operation traffic data packet;

[0063] For S1, further limitation is needed. The step S1 is realized through the following process:

[0064] Obtain the data collection types corresponding to the data collection tools, connect the data collection types with the corresponding data collection tools for data connection, generate a data collection tool data set, and then integrate several data collection tool data sets to obtain a data collection tool data packet;

[0065] In one embodiment, it should be further noted that the data collection tools include but are not limited to Google Analytics, Adobe Analytics, Mixpanel, Heap Analytics, and Matomo (formerly Piwik), etc.;

[0066] For S2, further limitation is needed. The step S2 is realized through the following process:

[0067] Obtain all the traffic acquisition types corresponding to the online operation traffic acquisition platforms, connect the traffic acquisition types with the corresponding online operation traffic acquisition platforms for data connection, generate the corresponding online operation traffic acquisition platform database; then integrate several online operation traffic acquisition platform databases to obtain the online operation traffic acquisition platform data packet, and send it to the data center for storage;

[0068] The traffic acquisition types include direct search links, paid advertising links, social media traffic, and email marketing traffic;

[0069] Set the first collection time point, denoted as t L, where L represents the traffic acquisition type; compare the traffic acquisition type in the online operation traffic acquisition platform database with the data acquisition type in the data collection tool data packet to obtain the data acquisition type that is the same as the traffic acquisition type, and then obtain the data collection tool corresponding to the data acquisition type, and schedule the corresponding data collection tool from the data collection tool package and transmit it to the corresponding online operation traffic acquisition platform for data collection, obtain the first platform operation traffic data corresponding to the first collection time point, and record it as f tL Integrate the first platform operation traffic data corresponding to the online operation traffic acquisition platform to obtain the corresponding platform operation traffic data;

[0070] Obtain the platform operation traffic data corresponding to all online operation traffic acquisition platforms in the online operation traffic acquisition platform data packet, and send the platform operation traffic data to the online operation traffic acquisition platform data packet and the online operation traffic acquisition platform for data connection to generate an online operation traffic data packet, and send it to the data center for storage;

[0071] In the above embodiment, it should be further noted that the first collection time point is used to represent the collection time point within 24 hours of a day; further, the online operation traffic acquisition platform includes but is not limited to Baidu, Google, Xiaohongshu, Douyin, etc.; obtain the traffic acquisition type corresponding to the online operation traffic acquisition platform, and adopt the corresponding data collection tool according to the traffic acquisition type to improve the collection accuracy and the speed of collecting data;

[0072] The process for the operation traffic classification unit to obtain the online operation traffic classification data packet includes:

[0073] Extract and integrate the first platform operation traffic data corresponding to the same traffic acquisition type in the online operation traffic data packet according to the traffic acquisition type to obtain the online operation traffic classification data packet, and send it to the operation traffic separation unit;

[0074] It should be further noted that in one embodiment, the platform operation traffic data obtained by each online operation traffic acquisition platform is obtained by one or more data collection tools to obtain one or more traffic acquisition types. Therefore, classify and integrate the platform operation traffic data obtained by each online operation traffic acquisition platform, obtain the online operation traffic classification data packet for classification processing, and improve the analysis speed of the online operation traffic data;

[0075] The operation traffic separation unit is used to obtain the online operation traffic classification data packet, and the processing process of the operation traffic separation unit is as follows:

[0076] SS1: Generate the first platform operation traffic data node from the first platform operation traffic data in the online operation traffic classification data packet, establish the first rectangular coordinate system, and obtain the standard first operation traffic data node threshold;

[0077] SS2: Analyze the first platform operation traffic data node according to the standard first operation traffic data node threshold to obtain the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet;

[0078] For SS1, it needs to be further defined that the process of obtaining the standard first operation traffic data node threshold includes:

[0079] Obtain the first collection time point corresponding to the first platform operation traffic data node, use the first collection time point as the X-axis and the first platform operation traffic data as the Y-axis to establish the first rectangular coordinate system, and then mark the first platform operation traffic data node in the first rectangular coordinate system;

[0080] Divide the first collection time point into six collection time periods, obtain the corresponding time period normal distribution according to the collection time period, and denote it as X~N(μ i , σ i 2 ), where μ i represents a mathematical expectation that the random first collection time point in the i-th collection time period follows, and σ i 2 represents a variance that the random first collection time point in the i-th collection time period follows, i represents the collection time period number, and i = 1, 2, 3, 4, 5, 6; then generate the corresponding time period normal distribution image:

[0081] That is, the formula for obtaining the time period normal distribution diagram is:

[0082]

[0083] Among them, F(t L ) represents the standard first operation traffic data node threshold obtained by the first collection time point corresponding to the traffic acquisition type in the time period normal distribution diagram;

[0084] For SS2, it needs to be further defined that the process of obtaining the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet includes:

[0085] Compare the first platform operation traffic data corresponding to the first collection time point with the corresponding standard first operation traffic data node threshold:

[0086] If Then mark the corresponding first - platform operation traffic data node as a normal online operation traffic data node, obtain the first - platform operation traffic data corresponding to the normal online operation traffic data node and perform data integration, and then obtain the normal online operation traffic classification data packet in the online operation traffic classification data packet;

[0087] If Then mark the corresponding first - platform operation traffic data node as an abnormal online operation traffic data node, obtain the first - platform operation traffic data corresponding to the abnormal online operation traffic data node and perform data integration, and then obtain the abnormal online operation traffic classification data packet in the online operation traffic classification data packet;

[0088] In the above - mentioned embodiment, the four collection time periods include (0:00 - 6:00), (6:00 - 11:00), (11:00 - 13:00), (13:00 - 16:00), (16:00 - 18:00), and (18:00 - 24:00); Further, due to different traffic acquisition types of different platforms in different time periods, the obtained online operation traffic data is different. Therefore, according to different collection time periods, different online operation traffic acquisition platforms, and different traffic acquisition types, the corresponding thresholds are obtained, and then the traffic data is analyzed, which improves the accuracy of online operation traffic data analysis;

[0089] The process by which the operation traffic analysis module is used to obtain the corresponding online operation traffic curve graph includes:

[0090] Connect the normal online operation traffic data nodes and abnormal online operation traffic data nodes corresponding to the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet respectively according to the order of the first collection time point, and generate a normal online operation traffic curve graph and an abnormal online operation traffic curve graph respectively;

[0091] The online operation traffic curve graph includes a normal online operation traffic curve graph and an abnormal online operation traffic curve graph;

[0092] The process by which the operation traffic analysis module is used to obtain the best online operation traffic delivery decision includes:

[0093] Obtain the operation traffic data difference between the first - platform operation traffic data corresponding to the abnormal online operation traffic data node in the abnormal online operation traffic curve graph and the threshold of the corresponding standard first operation traffic data node, denoted as And display the operation traffic data difference on the abnormal online operation traffic data node corresponding to the abnormal online operation traffic curve graph;

[0094] Obtain the maximum value of the difference in operation traffic data, and then obtain the corresponding first collection time point and traffic acquisition type. According to the first collection time point and traffic acquisition type, obtain the corresponding normal first platform operation traffic data node in the normal online operation traffic curve diagram, and then obtain the corresponding online operation traffic acquisition platform;

[0095] According to the best online operation traffic acquisition platform, obtain the best online operation traffic investment decision corresponding to the traffic acquisition type, and mark the corresponding normal online operation data node as red in the normal online operation traffic curve diagram;

[0096] The best online operation traffic investment decision includes the best online operation traffic acquisition platform and the first collection time point.

[0097] In the above embodiment, it should be further noted that the online operation traffic curve diagram can not only obtain the best online operation traffic investment decision, but also obtain the worst online operation traffic decision, whether the online operation traffic is stable, etc.; it can make better decisions on the online operation traffic;

[0098] The management module is used to obtain the changed first platform operation traffic data node. The processing process of the management module is as follows:

[0099] Set the monitoring time in the online operation traffic data monitoring period column. Monitor the online operation traffic curve diagram according to the monitoring time, obtain the newly added abnormal online operation traffic data node in the abnormal online operation traffic curve diagram, obtain the corresponding normal online operation traffic data node in the normal online operation traffic curve diagram and generate the changed first platform operation traffic data node, and then update the best online operation traffic investment decision according to the changed first platform operation traffic data node;

[0100] It should be further noted that in the specific implementation process, set different monitoring times in the online operation traffic data monitoring period column, and monitor the online operation traffic data according to the monitoring time on the online operation traffic data monitoring period column to improve the accuracy of obtaining the best online operation traffic investment decision.

[0101] As Figure 2 shown, the present invention is a method for monitoring online operation traffic data based on big data, including the following steps:

[0102] Step 1: Use a data collection tool to collect the online operation traffic data packet corresponding to the traffic acquisition type;

[0103] Step 2: Classify the online operation traffic data packets according to the traffic acquisition type to obtain the online operation traffic classification data packets; process the online operation traffic classification data packets to obtain the standard first operation traffic data node thresholds, and then obtain the abnormal online operation traffic classification data packets and normal online operation traffic classification data packets in the online operation traffic classification data packets;

[0104] Step 3: Perform traffic analysis on the normal online operation traffic classification data packets and abnormal online operation traffic classification data packets respectively to obtain the corresponding online operation traffic curve graphs, and then obtain the optimal online operation traffic delivery decisions.

[0105] The features and exemplary embodiments of various aspects of the present application will be described in detail below. For the purpose of making the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in combination with the accompanying drawings and specific embodiments; it should be understood that the specific embodiments described herein are only intended to explain the present application, rather than limiting the present application; for those skilled in the art, the present application can be implemented without some of these specific details; the above description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0106] The above embodiments are only used to illustrate the technical methods of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical methods of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An online operation traffic data monitoring system based on big data, including a data center, characterized in that, The data center, the operation traffic data acquisition module, the operation traffic processing module, and the operation traffic analysis module; The data center is used to store online operation traffic-related data; The operation traffic data acquisition module is used to collect online operation traffic data packets corresponding to the traffic acquisition type by using a data acquisition tool; The operation traffic processing module is used to set up an operation traffic classification unit and an operation traffic separation unit; The operation traffic classification unit is used to classify the online operation traffic data packets according to the traffic acquisition type to obtain online operation traffic classification data packets; The operation traffic separation unit is used to process the online operation traffic classification data packets to obtain the standard first operation traffic data node threshold, and then obtain the abnormal online operation traffic classification data packets and the normal online operation traffic classification data packets in the online operation traffic classification data packets; The operation traffic analysis module is used to perform traffic analysis on the normal online operation traffic classification data packets and the abnormal online operation traffic classification data packets respectively to obtain the corresponding online operation traffic curve graphs, and then obtain the optimal online operation traffic delivery decision; 2. The online operation traffic data monitoring system based on big data according to claim 1, characterized in that, The process of the operation traffic data acquisition module collecting online operation traffic data includes: Setting up a data acquisition tool importer in the operation traffic data acquisition module, which is used to import the data acquisition tool for collecting online operation traffic data, obtain the data acquisition type corresponding to the data acquisition tool, and perform data connection between the data acquisition type and the corresponding data acquisition tool to generate a data acquisition tool data set. Then, integrate several data acquisition tool data sets to obtain a data acquisition tool data packet; Obtaining several online operation traffic acquisition platforms, obtaining all traffic acquisition types corresponding to the online operation traffic acquisition platforms, and performing data connection between the traffic acquisition type and the corresponding online operation traffic acquisition platform to generate the corresponding online operation traffic acquisition platform database. Then, integrate several online operation traffic acquisition platform databases to obtain an online operation traffic acquisition platform data packet, and send it to the data center for storage; Set the first collection time point, denoted as t L , where L represents the traffic acquisition type; compare the traffic acquisition type in the online operation traffic acquisition platform database with the data acquisition type in the data acquisition tool data packet, obtain the data acquisition type that is the same as the traffic acquisition type, and then obtain the data acquisition tool corresponding to the data acquisition type, and schedule the corresponding data acquisition tool from the data acquisition tool package and transmit it to the corresponding online operation traffic acquisition platform for data acquisition, obtain the first platform operation traffic data corresponding to the first collection time point, and denote it as f tL , perform data integration on the first platform operation traffic data corresponding to the online operation traffic acquisition platform to obtain the corresponding platform operation traffic data; And send the platform operation traffic data to the online operation traffic acquisition platform data packet for data connection with the online operation traffic acquisition platform to generate an online operation traffic data packet, and send it to the data center for storage.

3. A big data-based online operation traffic data monitoring system according to claim 2, characterized in that, The process of the operation traffic classification unit obtaining the online operation traffic classification data packet includes: Extract and integrate the first platform operation traffic data corresponding to the same traffic acquisition type in the online operation traffic data packet according to the traffic acquisition type to obtain the online operation traffic classification data packet, and send it to the operation traffic separation unit.

4. An online operation traffic data monitoring system based on big data according to claim 3, characterized in that, The process of the operation traffic separation unit obtaining the standard first operation traffic data node threshold includes: Generate a first platform operation traffic data node from the first platform operation traffic data in the online operation traffic classification data packet, obtain the first acquisition time point corresponding to the first platform operation traffic data node, use the first acquisition time point as the X-axis and the first platform operation traffic data as the Y-axis to establish a first rectangular coordinate system, and then mark the first platform operation traffic data node in the first rectangular coordinate system; Divide the first acquisition time point into six acquisition time periods, obtain the corresponding normal distribution of the time period according to the acquisition time period, and denote it as X~N(μ i , σ i 2 ), where μ i and σ i 2 respectively represent a mathematical expectation and variance that the random first acquisition time point in the i-th acquisition time period follows. i represents the acquisition time period number, and i = 1, 2, 3, 4, 5, 6; That is, the formula for obtaining the normal distribution graph of the time period is as follows: Among them, F(t L ) represents the standard first operation traffic data node threshold obtained at the first acquisition time point corresponding to the traffic acquisition type in the normal distribution graph of the time period.

5. A big data-based online operation traffic data monitoring system according to claim 4, characterized in that The process by which the operation traffic separation unit obtains the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet includes: Comparing the first platform operation traffic data corresponding to the first collection time point with the corresponding standard first operation traffic data node threshold: If then mark the corresponding first platform operation traffic data node as a normal online operation traffic data node, obtain the first platform operation traffic data corresponding to the normal online operation traffic data node and perform data integration, and then obtain the normal online operation traffic classification data packet in the online operation traffic classification data packet; If then mark the corresponding first platform operation traffic data node as an abnormal online operation traffic data node, obtain the first platform operation traffic data corresponding to the abnormal online operation traffic data node and perform data integration, and then obtain the abnormal online operation traffic classification data packet in the online operation traffic classification data packet.

6. The online operation traffic data monitoring system based on big data according to claim 5, characterized in that, The process by which the operation traffic analysis module obtains the online operation traffic curve graph includes: Connecting the normal online operation traffic data nodes and the abnormal online operation traffic data nodes corresponding to the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet respectively according to the order of the first collection time point, and generating a normal online operation traffic curve graph and an abnormal online operation traffic curve graph respectively; The online operation traffic curve graph includes a normal online operation traffic curve graph and an abnormal online operation traffic curve graph.

7. An online operation traffic data monitoring system based on big data according to claim 6, characterized in that, The process by which the operation traffic analysis module obtains the optimal online operation traffic decision includes: Obtain the difference between the first platform operation traffic data corresponding to the abnormal online operation traffic data node in the abnormal online operation traffic curve graph and the operation traffic data threshold of the corresponding standard first operation traffic data node, and denote it as and display it on the corresponding abnormal online operation traffic data node; Obtaining the maximum value of the operation traffic data difference, and then obtaining the corresponding first collection time point and traffic acquisition type, obtaining the corresponding normal first platform operation traffic data node in the normal online operation traffic curve graph according to the first collection time point and traffic acquisition type, and then obtaining the corresponding online operation traffic acquisition platform, which is marked as the optimal online operation traffic acquisition platform; Obtaining the optimal online operation traffic delivery decision corresponding to the traffic acquisition type according to the optimal online operation traffic acquisition platform, and marking the corresponding normal online data node as red; The optimal online operation traffic delivery decision includes the optimal online operation traffic acquisition platform and the first collection time point.

8. A method for monitoring online operation traffic data based on big data, which is applied to a system for monitoring online operation traffic data based on big data as described in any one of claims 1-7, and is characterized in that, It includes the following steps: Step 1: Using a data collection tool to collect the online operation traffic data packet corresponding to the traffic acquisition type; Step 2: Classifying the online operation traffic data packet according to the traffic acquisition type to obtain the online operation traffic classification data packet; processing the online operation traffic classification data packet to obtain the standard first operation traffic data node threshold, and then obtaining the abnormal online operation traffic classification data packet and the normal online operation traffic classification data packet in the online operation traffic classification data packet; Step 3: Conducting traffic analysis on the normal online operation traffic classification data packet and the abnormal online operation traffic classification data packet respectively to obtain the corresponding online operation traffic curve graph, and then obtaining the optimal online operation traffic delivery decision.

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