Business component troubleshooting method and device, equipment, medium and product

Abstract

The application discloses a service component troubleshooting method and device, equipment, medium and product. The method comprises the following steps: listening to the user traffic data generated by the independent stations in the first group and the second group in the first station group due to the execution of the first service link of the preset service function, and storing the user traffic data into the first and second data buckets; wherein the first group calls the function plug-in provided by the service component, and the second group does not call the function plug-in; listening to the user traffic data generated by each independent station in the second station group due to the execution of the second service link, and storing the user traffic data into the first and second data buckets; respectively calculating the user traffic indexes of the service components which have been applied and not applied according to the user traffic data in the two data buckets; and judging whether the gap between the same user traffic indexes reaches the preset condition, and outputting the control information for indicating the offline of the service component when the condition is reached, so that the effective troubleshooting effect is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of e-commerce information, in particular to a business component troubleshooting method and a corresponding device, computer equipment, computer readable storage medium, and computer program product. BACKGROUND

[0002] An e-commerce platform contains various business functions, each of which usually includes multiple business links. By providing or updating business components corresponding to each business function, these business functions can be continuously improved, enabling the services provided by the e-commerce platform to be continuously upgraded and iterated.

[0003] There are many business components online on a daily basis on an e-commerce platform, and they are scattered in multiple departments. It is relatively difficult to grasp the online performance of business components, especially in the cross-border e-commerce field. Each online store is configured as an independent site, and each independent site may independently configure one or several functional plug-ins in the business components, further complicating the grasp of the online performance of business components. Therefore, how to determine the online performance of each business component is a problem worth studying in the field of cross-border e-commerce.

[0004] In the traditional way, the user traffic data of each business component is tested on multiple single stores to comprehensively determine the online performance of the business component. This method is difficult to adapt to the case where the business component is composed of multiple parts, and each part is configured in a different business link. For example, some independent sites are configured with functional plug-ins corresponding to the first business link of the business component, but some independent sites are not configured with this business link. For the same business function, some business links apply to part of the access requests of the same independent site, while other access requests of the same independent site are not applied.

[0005] In view of these flexible and variable situations, how to effectively investigate the comprehensive performance of the same business component in the cross-border e-commerce platform station group, and thus effectively control the configuration and use of the business component, is the motivation for the applicant to propose the present application. SUMMARY

[0006] The primary purpose of the present application is to solve at least one of the above problems and provide a business component troubleshooting method and a corresponding device, computer equipment, computer readable storage medium, and computer program product.

[0007] To achieve each purpose of the present application, the present application adopts the following technical solutions:

[0008] A business component troubleshooting method provided to adapt to one of the purposes of the present application includes the following steps:

[0009] The user traffic data generated by the first group of independent stations in the first station group and the second group of independent stations in the second station group due to the execution of the first business link of the preset business function is monitored and stored into the first data bucket and the second data bucket; wherein the first group of independent stations generates corresponding user traffic data by calling the function plug-in provided by the business component, and the second group of independent stations generates corresponding user traffic data without calling the function plug-in provided by the business component;

[0010] The user traffic data generated by each independent station in the second station group due to the execution of the second business link of the business function is monitored, and the user traffic data generated by each independent station by applying the processing algorithm provided by the business component is stored into the first data bucket, and the user traffic data of each independent station without applying the processing algorithm provided by the business component is stored into the second data bucket;

[0011] The user traffic indicators of the business component that have been applied and not applied are respectively counted according to the user traffic data in the first data bucket and the second data bucket;

[0012] It is judged whether the gap between the same user traffic indicators of the first data bucket and the second data bucket reaches a preset condition, and when the preset condition is reached, control information for indicating that the business component is offline is output.

[0013] In a deepened embodiment, the user traffic indicators of the business component that have been applied and not applied are respectively counted according to the user traffic data in the first data bucket and the second data bucket, including the following steps:

[0014] According to the user traffic data in the first data bucket, the user traffic data generated by the first station group and the second station group respectively is fused according to the same parameters to determine the user traffic indicators, so that the user traffic indicators are used to indicate the information reflected after the function component and the processing algorithm of the business component are applied;

[0015] According to the user traffic data in the second data bucket, the user traffic data generated by the first station group and the second station group respectively is fused according to the same parameters to determine the user traffic indicators, so that the user traffic indicators are used to indicate the information reflected without applying the function component and the processing algorithm of the business component.

[0016] In a deepened embodiment, it is judged whether the gap between the same user traffic indicators of the first data bucket and the second data bucket reaches a preset condition, and when the preset condition is reached, control information for indicating that the business component is offline is output, including the following steps:

[0017] The first curve data changing along time is fitted according to the time when the user traffic indicators are generated.

[0018] fitting the user traffic indicators of the second data buckets along time according to the time when the user traffic indicators are generated to obtain second curve data changing along time;

[0019] determining a time range when the business component is applied to the independent sites online, and comparing the difference data between the first curve data and the second curve data in the time range;

[0020] comparing whether the difference data is lower than a preset threshold, and when it is lower than the preset threshold, considering that the preset condition is reached, and outputting control information for indicating the business component offline.

[0021] In an extended embodiment, after the step of outputting the control information for indicating the business component offline, the method comprises the following steps:

[0022] generating an offline control instruction of the business component according to the control information;

[0023] in response to the offline control instruction, querying target independent sites in which the business component is enabled from all independent sites pre-registered to the e-commerce platform;

[0024] releasing configuration binding information of the business component for each of the target independent sites, and realizing the offline of the business component of the corresponding target independent site.

[0025] In a preferred embodiment, the user traffic indicator is a click rate indicator or a conversion rate indicator.

[0026] In a preferred embodiment, the business function is a commodity online search function of the e-commerce platform, and correspondingly, the first business link is a front-end business link for executing commodity search, and the second business link is a back-end business link for sorting and outputting commodity search results generated by the first business link.

[0027] A service component troubleshooting device provided for adapting to one of the purposes of the present application, comprising: a first monitoring module, a second monitoring module, an index statistics module, and a decision control module, wherein the first monitoring module is configured to monitor user traffic data generated by independent sites in a first group and a second group in a first station group due to execution of a first service link of a preset service function, and store the user traffic data to a first data bucket and a second data bucket; wherein the independent sites in the first group generate corresponding user traffic data by calling a function plug-in provided by a service component, and the independent sites in the second group generate corresponding user traffic data without calling the function plug-in provided by the service component; the second monitoring module is configured to monitor user traffic data generated by each independent site in a second station group due to execution of a second service link of the service function, and store user traffic data generated by each independent site by applying a processing algorithm provided by the service component to the first data bucket, and store user traffic data of each independent site without applying the processing algorithm provided by the service component to the second data bucket; the index statistics module is configured to respectively calculate user traffic indexes of the service component that have been applied and not applied according to user traffic data in the first data bucket and the second data bucket; and the decision control module is configured to determine whether a gap between the same user traffic indexes of the first data bucket and the second data bucket reaches a preset condition, and output control information for indicating that the service component is offline when the preset condition is reached.

[0028] In a deepened embodiment, the index statistics module comprises: a first statistics submodule configured to calculate the user traffic indexes according to the user traffic data in the first data bucket by fusing the user traffic data generated by the first station group and the second station group respectively according to the same parameters, so that the user traffic indexes are used to indicate information reflected after applying the function component and the processing algorithm of the service component; and a second statistics submodule configured to calculate the user traffic indexes according to the user traffic data in the second data bucket by fusing the user traffic data generated by the first station group and the second station group respectively according to the same parameters, so that the user traffic indexes are used to indicate information reflected without applying the function component and the processing algorithm of the service component.

[0029] In a deepened embodiment, the decision control module comprises: a first fitting submodule configured to fit a first curve data varying with time according to the time when the user traffic indicators of the first data bucket are generated; a second fitting submodule configured to fit a second curve data varying with time according to the time when the user traffic indicators of the second data bucket are generated; a difference comparison submodule configured to determine a time range when the service component is applied to the independent site, and compare the difference data between the first curve data and the second curve data in the time range; and a judgment output submodule configured to compare whether the difference data is lower than a preset threshold value, and output control information for indicating that the service component is offline when the difference data is lower than the preset threshold value.

[0030] In an extended embodiment, the service component troubleshooting device also comprises: an instruction generation module configured to generate an offline control instruction of the service component according to the control information; a target query module configured to query a target independent site that enables the service component from all independent sites pre-registered to the e-commerce platform in response to the offline control instruction; and an unbundling module configured to unbundle the configuration bundling information of the service component of each target independent site, so as to realize the offline of the service component of the corresponding target independent site.

[0031] In a preferred embodiment, the user traffic indicator is a click rate indicator or a conversion rate indicator.

[0032] In a preferred embodiment, the service function is an online search function of goods of the e-commerce platform, and correspondingly, the first service link is a front-end service link for performing the search of goods, and the second service link is a back-end service link for sorting and outputting the search result of goods generated by the first service link.

[0033] A computer device is provided for one of the purposes of the present application, comprising a central processing unit and a memory, and the central processing unit is configured to call and run a computer program stored in the memory to execute the steps of the service component troubleshooting method.

[0034] A computer readable storage medium is provided for another purpose of the present application, which stores a computer program implemented according to the service component troubleshooting method in the form of computer readable instructions, and the computer program is called and run by a computer to execute the steps included in the method.

[0035] A computer program product is provided for another purpose of the present application, comprising a computer program / instruction, which is executed by a processor to implement the steps of the method described in any one of the embodiments of the present application.

[0036] Compared with the prior art, the application has the following advantages:

[0037] The application adopts a first data bucket and a second data bucket to store two types of user traffic data. The first type of user traffic data is obtained by dividing different independent sites in a first site group. For an independent site in which a function plug-in of a certain business function is configured, it belongs to the first case, and the user traffic data generated by the independent site enters the first data bucket. For an independent site in which the function plug-in of the business function is not configured, the user traffic data generated by the independent site enters the second data bucket. The business function can be implemented by a business component. The business component provides the function plug-in to generate corresponding user traffic data for executing a first business link of the business function, and provides a processing algorithm to generate corresponding user traffic data for executing a second business link of the business function. The second type of user traffic data is obtained by dividing the user traffic data generated by each independent site in a second site group. When the user traffic data in the same independent site is applied to the processing algorithm of the business component, the user traffic data is stored in the first data bucket. If the processing algorithm is not applied, the user traffic data is stored in the second data bucket. Thus, the user traffic data generated in various complex situations of different business links of different cases of the business function, such as application and non-application of the business component, configuration and non-configuration of the function plug-in, application and non-application of the processing algorithm, and the like, is scientifically shunted to the two data buckets. Then, the user traffic data in the two data buckets is used to statistically analyze relevant user traffic indicators. The user traffic indicators in the first data bucket can reflect the application effect of the business component, and the user traffic indicators in the second data bucket can reflect the effect of non-application of the business component. On this basis, whether to control the business component to be offline is determined by examining whether the user traffic indicators meet preset conditions, which is accurate and effective. For the application environment of the cross-border e-commerce platform based on independent sites, the set control management and effective control of the business component can be realized.

[0038] In summary, based on the specific data processing method, the application accurately and effectively checks the effectiveness of the business component configured by the e-commerce platform through the user traffic data provided by the dispersed independent sites, facilitates the e-commerce platform to timely adjust product development, improve service functions, and improve user experience. BRIEF DESCRIPTION OF DRAWINGS

[0039] The above and / or additional aspects and advantages of the application will become apparent and more readily appreciated from the following description, taken in conjunction with the following drawings, in which:

[0040] Figure 1 A network architecture diagram for the application environment of the business component checking method;

[0041] Figure 2A flowchart of a typical embodiment of a method for troubleshooting a service component of the present application;

[0042] Figure 3 A flowchart of a process for deciding whether to take a service component offline in an embodiment of the present application;

[0043] Figure 4 A schematic diagram of a curve fitted to exemplary user traffic metrics of the present application;

[0044] Figure 5 A flowchart of a process for controlling the taking of a service component offline in an embodiment of the present application;

[0045] Figure 6 A block diagram of the principle of a troubleshooting device for a service component of the present application;

[0046] Figure 7 A structural schematic diagram of a computer device used in the present application. DETAILED DESCRIPTION

[0047] Embodiments of the present application are described in detail below with reference to the attached drawing figures, wherein the same or like reference numerals are used throughout the drawing figures to refer to the same or like elements or to elements with the same or similar functionality. The embodiments described below are illustrative examples of the present application and are not intended to be limiting of the present application.

[0048] Those skilled in the art can understand that, unless specifically stated otherwise, the singular forms "a," "an," and "the" as used herein are intended to include plural forms as well. It should be further understood that the terms "comprising," "including," "containing," "have," "including," "has," "including" and "having," when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements can be present. In addition, the word "connected" or "coupled" as used herein can include wireless connection or wireless coupling. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0049] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It should also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0050] Those skilled in the art will appreciate that the term "client", "terminal", "terminal device" as used herein encompasses both devices that are solely wireless signal receivers, devices that are wireless signal receivers without transmit capability, and devices that have receive and transmit hardware enabling two-way communications over a two-way communications link. Such devices can include cellular or other communication devices with or without a multi-line display, a plurality of displays, a single display, or a non-visual display, a Personal Communications System (PCS) device, a PDA (Personal Digital Assistant) that can include a radio frequency receiver, a pager, Internet / Intranet access, a Web browser, a notebook, a calendar, and / or a GPS (Global Positioning System) receiver, a conventional laptop, and / or palmtop computer and other devices that have or can be capable of connecting to the Internet or Intranet, and / or a conventional telephone. The term "client", "terminal", "terminal device" as used herein can be portable, transportable, installed in a vehicle (aeronautical, maritime, and / or land), or adapted and / or configured to operate locally and / or in a distributed manner, on Earth and / or in any other location in space. The term "client", "terminal", "terminal device" as used herein can also be a communication terminal, an Internet terminal, a music / video playing terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playing function, a smart television, a set-top box, and / or the like.

[0051] The term "server", "client", "service node", and the like as used herein refers to hardware that essentially has the equivalent capability of a personal computer, and is a hardware device having a central processing unit (including an arithmetic unit and a controller), a memory, an input device, and an output device, and the like necessary components disclosed by the von Neumann principle. A computer program is stored in the memory, the central processing unit loads the program stored in the external memory into the memory and runs it, executes the instructions in the program, and interacts with the input and output devices, thereby completing a specific function.

[0052] It should be noted that the concept of "server" in the present application can also be extended to the case of a server cluster. According to the principle of network deployment understood by those skilled in the art, the servers should be logically divided, and in physical space, these servers can be independent of each other but can be called through an interface, or can be integrated into a physical computer or a computer cluster. Those skilled in the art should understand this variation and should not be restricted by the implementation of the network deployment of the present application.

[0053] One or more technical features of the present application, unless explicitly specified, can be deployed on a server for implementation and accessed by a client remotely calling an online service interface provided by the server, or can be directly deployed and run on a client for implementation.

[0054] The neural network model referred to or possibly referred to in the present application, unless explicitly specified, can be deployed on a remote server and remotely called by a client, or can be deployed on a client with sufficient device capability for direct calling. In some embodiments, when it runs on a client, its corresponding intelligence can be obtained through transfer learning to reduce the requirement for client hardware running resources and avoid excessive occupation of client hardware running resources.

[0055] The various data involved in the present application, unless explicitly specified, can be remotely stored on a server or stored on a local terminal device, as long as it is suitable for being called by the technical solutions of the present application.

[0056] Those skilled in the art should know that the various methods of the present application, although based on the same concept and described to present commonality among them, are independently executable unless otherwise specified. Similarly, for each embodiment disclosed in the present application, it is based on the same inventive concept, so the same concept is understood to be equivalent, and although the concept is expressed differently, it is only a suitable transformation for convenience.

[0057] Unless it is explicitly stated that the embodiments disclosed in the present application are mutually exclusive, the technical features involved in each embodiment can be combined flexibly to construct new embodiments, as long as such combination does not deviate from the spirit of the present application and can meet the needs of the prior art or solve some deficiencies in the prior art. For this variation, those skilled in the art should know.

[0058] A business component troubleshooting method of the present application can be programmed as a computer program product and deployed in an e-commerce platform cluster server for implementation. Please refer to Figure 1The network deployment architecture of the cross-border e-commerce platform shown includes a cluster server and a large number of independent sites distributed and running, the cluster server provides registration and configuration services for each independent site, so that the two can communicate with each other, and the cluster server obtains user traffic data generated by each independent site and makes corresponding control on the registration, configuration, operation and other functions of each independent site. The independent site can be implemented by the cluster server according to a certain demand to correspond to the targeted centralized processing of different demands. This centralized processing can be logical, that is, the cluster server can regard the massive independent sites it maintains as multiple site groups existing according to a certain logical division.

[0059] Please refer to Figure 2 The business component troubleshooting method of the present application includes the following steps in its typical embodiment:

[0060] Step S1100, listen to the user traffic data generated by the independent sites of the first group and the second group in the first site group due to the execution of the first business link of the preset business function, and correspondingly store it to the first data bucket and the second data bucket; wherein the independent sites of the first group call the function plug-in provided by the business component to generate corresponding user traffic data, and the independent sites of the second group generate corresponding user traffic data without calling the function plug-in provided by the business component:

[0061] In the present application, the independent sites maintained by the e-commerce platform are at least regarded as two site groups, namely the first site group and the second site group, to adapt to the execution of the first business link and the second business link of the business function targeted by the present application. Each site group contains multiple independent sites, and each independent site independently runs to provide its own corresponding online store. Among them, the independent sites of the first site group refer to the independent sites that generate corresponding user traffic data by executing the first business link of the business function, and the independent sites of the second site group refer to the independent sites that generate corresponding user traffic data by executing the second business link of the business function. It is not difficult to understand that considering the case that the first business link and the second business link of the business function constitute the entire business chain, the independent sites of the first site group and the independent sites of the second site group can be the same independent site.

[0062] For example, for the specific application scenario of e-commerce platform product search, the process of submitting the keywords of the consumer user of the online store to the independent site for keyword association and performing search when performing product search can be regarded as the first business link of the product search business function in this scenario, and the process of sorting and outputting the product list obtained after the execution of the first business link can be regarded as the second business link of the product search business function in this scenario.

[0063] For example, for the specific application scenario of commodity category prediction of an e-commerce platform, when any user of an online store uploads image-text information of a commodity for implementing commodity category prediction, the process of submitting the image-text information for category prediction can be regarded as the first business link of the business function of category prediction, and the process of performing search and sorting after category prediction can be regarded as the second business link.

[0064] As can be seen from the above examples, for a certain business function, multiple business links can be divided according to the sequence of business logic, which together constitute part of the business chain of the business function, usually an important part. Therefore, the business function referred to in the present application generally refers to a commodity data access function in an e-commerce platform for realizing user-oriented services, which is developed and encapsulated by the developers of the e-commerce platform into corresponding algorithm code, installation package, tool package, functional plug-in, etc. carrier, and configured into the front-end or back-end code of the e-commerce platform for running and implementation.

[0065] In the examples given for better understanding, the business function is the online search function of the commodities of the e-commerce platform, which is opened to each independent site for pre-configuration. The independent site configured with the commodity search function can execute the first business link by adding the corresponding functional plug-in or using the system default function or the old version of the functional plug-in, so that the online store of the independent site is opened to the user in the front-end and implements the front-end business link for executing commodity search; and the back-end business link corresponding to the business function, i.e. the second business link, is configured as the background code of the independent site executing the preset processing algorithm or the default version, old version algorithm of the independent site, and is used for sorting and outputting the commodity search results generated by the first business link.

[0066] The functional plug-in and the preset algorithm corresponding to the first business link and the second business link of each business function belong to the same version of the functional plug-in and the preset algorithm, which constitute the business component corresponding to the business function. The business component can be placed in the cluster server of the e-commerce platform for pre-configuration by the online store of each independent site. The functional plug-in and the preset processing algorithm can be used to realize the business sub-function corresponding to the different business links of the same business chain, but the implementation forms of the two can be different, for example, the functional plug-in is used to complete the front-end business process of providing commodity search, and the processing algorithm is used to complete the sorting and optimization of the commodity search results in the background of the e-commerce platform, etc.

[0067] For the first group of stations, some of the independent stations can be configured with the functional plug-in and preset processing algorithm of the service component, and the other independent stations can use the default functional plug-in and default processing algorithm to implement the service function, or use the old version of the functional plug-in and the old version of the processing algorithm to implement the service function, thereby forming two groups of independent stations, wherein the first group of independent stations refers to the independent stations configured with the new service component corresponding to the service function, and the second group of independent stations refers to the independent stations not configured with the new service component corresponding to the service function.

[0068] In order to monitor the user traffic data generated by each station group in the e-commerce platform, two data buckets, i.e. a first data bucket and a second data bucket, are provided. In this step, the user traffic data generated by the independent stations in the first group is stored in the first data bucket, and the user traffic data generated by the independent stations in the second group is stored in the second data bucket, by listening to the user traffic data generated by the independent stations in the first group due to the execution of the first business link of the service function. Since the independent stations in the first group are configured with the functional plug-in in the service component, the user traffic data generated by the independent stations is actually triggered by the user of the corresponding independent station by calling the functional plug-in to execute the first business link of the service function. Therefore, the user traffic data generated by the user is stored in the first data bucket, and the data stored in the first data bucket belongs to the user traffic data related to the functional plug-in of the service component. The independent stations in the second group are not configured with the functional plug-in, and can use the old version of the functional plug-in or algorithm, or the system default algorithm, etc. Although they can also execute the first business link, they are different from the functional plug-in of the new service component provided by the application. Therefore, although the user can execute the first business link to generate corresponding user traffic data, the user traffic data generated by the user is not directly related to the functional plug-in provided by the service component, i.e. the user does not call the functional plug-in, so the corresponding user traffic data is diverted to the second data bucket to distinguish from the first data bucket.

[0069] The user traffic data referred to in the application is the traffic data corresponding to the service function, which can be flexibly set by those skilled in the art to adapt to different service functions and the need for subsequent statistical implementation. For example, the relevant data suitable for calculating the click rate or conversion rate of a certain commodity promotion information includes but is not limited to the number of clicks, the number of exposures and their basic statistical data, etc. It is not difficult to understand that the specific type of user traffic data and its composition and use can be understood by those skilled in the art, and do not affect the implementation of the application. For example, a user of an online store clicks on a commodity link provided by the functional plug-in, which will result in a user traffic data that can be used to calculate the exposure rate and click rate.

[0070] Step S1200, monitoring the user traffic data generated by each independent station in the second station group due to the execution of the second business link of the business function, storing the user traffic data generated by each independent station in which the processing algorithm provided by the business component is applied to the first data bucket, and storing the user traffic data of each independent station in which the processing algorithm provided by the business component is not applied to the second data bucket:

[0071] For the second station group of the present application, each independent station therein can generate corresponding user traffic data when executing the second business link of the business function. For the second business link, the e-commerce platform selectively applies the preset processing algorithm of the corresponding business component to the generation of part of the user traffic data in each independent station of the second station group, and does not apply the processing algorithm to the generation of another part of the user traffic data in the independent station. Thus, in fact, the same independent station in the second station group actually generates two types of user traffic data. In the present application, the user traffic data to which the preset processing algorithm of the business part is applied is stored in the first data bucket, so that the part of the data in the first data bucket represents the user traffic data corresponding to the use of the preset processing algorithm of the business component. Another type of user traffic data that does not apply the preset processing algorithm of the business component is stored in the second data bucket, so that the part of the data in the second data bucket represents the user traffic data corresponding to the generation without using the preset processing algorithm of the business component. The user traffic data can be the default algorithm or the old version algorithm provided by the e-commerce platform to realize the business function corresponding to the business component, but not the preset processing algorithm contained in the business component.

[0072] At this point, it can be seen that the user traffic data stored in the first data bucket is all user traffic data corresponding to the use of the functional plug-in or the preset processing algorithm of the business component, and the user traffic data stored in the second data bucket is all user traffic data corresponding to the non-use of the functional plug-in and the preset processing algorithm of the business component. However, the user traffic data in the two data buckets is all user traffic data corresponding to the execution of the same business function. Therefore, by storing different types of user traffic data in the first data bucket and the second data bucket, the user traffic data generated in the complex situation of using and not using the functional plug-in and the preset processing algorithm in the business component is orderly data-shunted for differential treatment and analysis.

[0073] Step S1300, according to the user traffic data in the first data bucket and the second data bucket, respectively counting the user traffic indicators that have applied and have not applied the business component:

[0074] For the user traffic data in the first data bucket and the second data bucket, since they are the same type of data, the parameter configurations of both are basically the same, thus, although the user traffic data in each data bucket is from two sources, one is the user traffic data corresponding to the first service link and the other is the user traffic data corresponding to the second service link, both can be directly fused for statistics, for which, as long as the statistical indicators and the statistical methods are preset, the same method can be used to perform data statistics on the first data bucket and the second data bucket respectively, so as to calculate each corresponding statistical indicator, which is referred to as the user traffic indicator.

[0075] First, according to the user traffic data in the first data bucket, the user traffic data generated by the first station group and the second station group respectively is fused according to the same parameters to determine the user traffic indicator, which is used to indicate the information reflected after the functional component and processing algorithm of the service component are applied.

[0076] Then, according to the user traffic data in the second data bucket, the user traffic data generated by the first station group and the second station group respectively is fused according to the same parameters to determine the user traffic indicator, which is used to indicate the information reflected without applying the functional component and processing algorithm of the service component.

[0077] For example, in an embodiment, the user traffic data is used to calculate the click rate as the user traffic indicator, and the statistical formula of the click rate is configured to divide the number of clicks calculated from the user traffic data by the number of exposures calculated from the same user traffic data. Accordingly, when the click rate is calculated for the first data bucket, the sum of the number of clicks calculated from the user traffic data corresponding to the application of the functional plug-in and the number of clicks calculated from the user traffic data corresponding to the application of the preset processing algorithm is divided by the sum of the number of exposures calculated from the user traffic data corresponding to the application of the functional plug-in and the number of exposures calculated from the user traffic data corresponding to the application of the preset processing algorithm, and the obtained ratio is the fusion click rate of the user traffic data of the first data bucket, which is used as the user traffic indicator and has the function of indicating the change of the click rate after the application of the service component. As a reference, for the second data bucket, the same calculation principle is used to perform statistics on the user traffic data based on the same parameters, and then the fusion click rate is calculated. Thus, it is not difficult to understand that the fusion click rates of the two data buckets have been obtained, and since the first data bucket mainly indicates the user traffic indicator corresponding to the application of the service component and the second data bucket mainly indicates the user traffic indicator corresponding to the non-application of the service component, the two have the function of comparative analysis.

[0078] Step S1400, judging whether the gap between the same user traffic indicators of the first data bucket and the second data bucket reaches a preset condition, and outputting control information for indicating the service component to be offline when the preset condition is reached:

[0079] In order to analyze the two specific cases of applying and not applying the service component, in the embodiment, the gap information between the same user traffic indicators between the first data bucket and the second data bucket can be directly compared, and then compared with the preset condition. When the preset condition is met, it can be determined whether the application of the service component meets the expectation. If the expectation is not met, the corresponding control information can be outputted to indicate the service component to be offline from each independent site.

[0080] The preset condition can be flexibly set by those skilled in the art according to the control logic to be achieved. For example, for the click rate indicator, it can be set whether the gap of the click rate indicators between the two data buckets is less than the threshold value as the preset condition. If it is less than the threshold value, it is considered that the user traffic indicators of the first data bucket do not meet the standard and the corresponding service component does not meet the requirement, and the corresponding control information is outputted. If it is greater than the threshold value, it is considered that the user traffic indicators of the first data bucket meet the standard and the corresponding service component is a high-quality component, so the service component can be retained for continuous use.

[0081] In other embodiments, the statistics of multiple user traffic indicators can be involved in step S1300, and in step S1400, the multiple user traffic indicators can be weighted and fused to finally perform a single comparison, so as to simplify the comparison and analysis scheme. Those skilled in the art can flexibly implement it.

[0082] From the analysis of the typical embodiments of the present application, it can be known that the present application adopts the first data bucket and the second data bucket to store two types of user traffic data: the first type of user traffic data is obtained by dividing different independent sites in the first station group, for the independent site in which the function plug-in of a certain business function is configured, it belongs to the first case, and the user traffic data generated by it enters the first data bucket; for the independent site in which the function plug-in of the business function is not configured, the user traffic data generated by it enters the second data bucket. The business function can be implemented by a business component, which provides the function plug-in for executing the first business link of the business function to generate corresponding user traffic data, and provides a processing algorithm for executing the second business link of the business function to generate corresponding user traffic data. The second type of user traffic data is obtained by dividing the user data traffic generated by each independent site in the second station group, when the user traffic data in the same independent site is applied to the processing algorithm of the business component, it is stored in the first data bucket, if the processing algorithm is not applied, it is stored in the second data bucket. Thus, for the user traffic data generated by the different cases of the business function of the different business links of the application and non-application of the business component, the configuration and non-configuration of the function plug-in, the application and non-application of the processing algorithm, etc., the user traffic data is scientifically shunted to the two data buckets, and then the user traffic data in the two data buckets is respectively used to count the related user traffic indicators, so that the user traffic indicators of the first data bucket can reflect the application effect of the business component, and the user traffic indicators of the second data bucket can reflect the effect of not applying the business component. On this basis, by investigating whether these user traffic indicators meet the preset condition setting, the control information for deciding whether to control the business component offline is obtained, which is accurate and effective. For the application environment of the cross-border e-commerce platform based on independent sites, the centralized management and effective control of the business component can be realized.

[0083] In summary, based on the specific data processing method, the present application accurately and effectively realizes the effectiveness of the business component configured by the e-commerce platform through the user traffic data provided by the scattered independent sites, facilitates the e-commerce platform to timely adjust product development, improve service functions, and improve user experience.

[0084] Please refer to Figure 3 In order to analyze the user traffic indicators in time span, in the deep embodiment, the step S1400, judging whether the difference between the same user traffic indicators of the first data bucket and the second data bucket reaches the preset condition, when the preset condition is reached, outputting the control information for indicating that the business component is offline, including the following steps:

[0085] Step S1410, fitting the first curve data along time variation according to the time when the user traffic index is generated for the user traffic index of the first data bucket:

[0086] The same user traffic index of a service component in a continuous time range before and after the service component is online also changes with the change of user traffic, so the change curve of the user traffic index of the two data buckets can be constructed along the time line, as shown in Figure 4 The a bucket is the first data bucket, and the b bucket is the second data bucket, and there are two curves corresponding to them, wherein the curve of the a bucket is at a high position relative to the curve of the b bucket, and the curve is fitted by the user traffic index of the data bucket along the time variation, and correspondingly, there is also corresponding curve data at the memory level, so that the first curve data after fitting is obtained relative to the first data bucket, and the second curve data after fitting is obtained relative to the second data bucket. Figure 4 It is also shown that for the two types of business functions of "associative word" and "category prediction", the time when they are online is different, but the change of the user traffic index is embodied in the curve. It is not difficult to understand that the statistics of the user traffic index can be carried out in time in units of weeks, days, hours, etc., which depends on the flexible setting of the person skilled in the art. Since the time when the user traffic index is generated has timeliness, the curve fitted by the time variation of the user traffic index also contains time information value. Accordingly, it can be known that after fitting the user traffic index of the first data bucket, the first curve data along time variation is obtained.

[0087] Step S1420, fitting the second curve data along time variation according to the time when the user traffic index is generated for the user traffic index of the second data bucket:

[0088] Similarly, the second curve data can be obtained by fitting the user traffic index of the second data bucket.

[0089] Step S1430, determining the time range when the service component is applied to the independent site, and comparing and calculating the difference data between the first curve data and the second curve data in the time range:

[0090] Since Figure 4 The two curves shown correspond to the first curve data and the second curve data of the background, and the curve data is described by the user traffic index, and the user traffic index is associated with the corresponding time information, so the relevant user traffic index in the two curve data can be queried and determined by giving a time range.

[0091] For each business component, the time when it goes online is also determined, so generally, the part of the curve data corresponding to the time range between its online time and the current time can be used to evaluate the impact of the business component on the user traffic data of the e-commerce platform. Therefore, if you want to evaluate the running effectiveness of a business component within the time range since it went online to the independent site, you can compare and determine it through the difference data between the first curve data and the second curve data corresponding to the time range.

[0092] Because there are user traffic indicators corresponding to multiple time nodes in the curve data within the same time range, the fusion index value corresponding to each curve data within the same time range can be determined by summing or averaging the user traffic indicators at different times of the same curve data. In this way, by comparing the difference between the fusion index values of the first curve data and the second curve data, the difference data between the two curve data within the same time range can be quickly obtained.

[0093] Step S1440, compare the difference data with the preset threshold value, when it is lower than the preset threshold value, it is considered to reach the preset condition, and output the control information for indicating the offline of the business component.

[0094] In combination Figure 4 It is not difficult to understand that the effectiveness of the business component after application is actually the size of the gap between the curve data corresponding to the two curves within the corresponding time range. The larger the gap, the larger the difference, the better the application effectiveness of the business component, otherwise, the smaller the gap, the smaller the difference, the worse the application effectiveness of the business component. The difference data determined in the previous step is actually an equivalent quantitative index of such effectiveness.

[0095] Therefore, for the difference data, a preset threshold value can be set to measure the effectiveness before and after the application of the business component. When the difference data is lower than the preset threshold value, it is considered to reach the aforementioned preset condition, and the control information for indicating the offline of the business component is output.

[0096] The embodiment gives the difference data corresponding to the curve data corresponding to the two data buckets through the online running of the business component corresponding to the time range, determines whether the difference data reaches the preset condition by means of the preset threshold value, and decides whether the offline control of the business component is needed, realizes the quality troubleshooting of the business component online on the e-commerce platform. Because the troubleshooting process is based on rigorous data statistics and business logic control, the troubleshooting is accurate and efficient, and the business function of the e-commerce platform can be maintained in time, so as to optimize the user experience.

[0097] Please refer to Figure 5In an extended embodiment, after the step of outputting the control information for indicating the offline of the service component in step S1400, the method further comprises the following step:

[0098] In step S1500, the offline control instruction of the service component is generated according to the control information.

[0099] In order to control the offline of the service component determined to be offline after being investigated in time, after the control information for a certain service component is input after each step is passed through the investigation of the service component, the offline control instruction for the service component can be generated by the cluster server of the e-commerce platform in response to the output of the control information, so as to start the offline operation of the service component through the offline control instruction.

[0100] In step S1600, in response to the offline control instruction, the target independent site that enables the service component is queried from the full-amount independent sites pre-registered to the e-commerce platform:

[0101] Since the independent sites configured with the service component are maintained by the cluster server of the e-commerce platform, in response to the offline control instruction, the cluster server can query the full-amount independent sites that enable the service component from the configuration information library, and determine these independent sites as target independent sites that need to perform the offline processing of the service component.

[0102] In step S1700, the configuration binding information of each target independent site to the service component is released, and the offline of the service component of the corresponding target independent site is realized.

[0103] After the target independent sites are determined, the offline control instruction for the offline of the service component is sent to each target independent site, and then the function plug-in of the service component and its preset processing algorithm are offline (if running on the target independent site, the corresponding deletion is performed, and if running on the cluster server, the cluster server is deleted), and a notification message is returned. The cluster server further deletes or marks the configuration binding information of the target independent site and the service component from the configuration information library according to the notification message, so as to realize the offline of the service component of the corresponding target independent site.

[0104] The embodiment perfects the business control process of coordinating the offline of the service component by each independent site in time after the inefficient service component is investigated, realizes full-automatic, does not need manual participation, and improves the service experience of the e-commerce platform to each independent site by offline of the inefficient service component in time, so as to further upgrade the service component to improve the user experience of the online store of the independent site.

[0105] Please refer to Figure 6The service component troubleshooting device provided by the application is a functional embodiment of the service component troubleshooting method, and the device comprises a first monitoring module 1100, a second monitoring module 1200, an index statistics module 1300, and a decision control module 1400. The first monitoring module 1100 is configured to monitor user traffic data generated by independent stations in a first group and a second group in a first station group due to execution of a first service link of a preset service function, and store the user traffic data into a first data bucket and a second data bucket. The independent stations in the first group generate corresponding user traffic data by calling a function plug-in provided by a service component, and the independent stations in the second group generate corresponding user traffic data without calling the function plug-in provided by the service component. The second monitoring module 1200 is configured to monitor user traffic data generated by each independent station in a second station group due to execution of a second service link of the service function, and store user traffic data generated by each independent station by applying a processing algorithm provided by the service component into the first data bucket, and store user traffic data of each independent station without applying the processing algorithm provided by the service component into the second data bucket. The index statistics module 1300 is configured to respectively calculate user traffic indexes of the service component that has been applied and not applied according to user traffic data in the first data bucket and the second data bucket. The decision control module 1400 is configured to determine whether a gap between the same user traffic indexes of the first data bucket and the second data bucket reaches a preset condition, and output control information for indicating that the service component is offline when the preset condition is reached.

[0106] In a deepened embodiment, the index statistics module 1300 comprises a first statistics submodule configured to calculate the user traffic indexes according to the user traffic data in the first data bucket by fusing the user traffic data generated by the first station group and the second station group according to the same parameters, so that the user traffic indexes are used to indicate information reflected after the function component and the processing algorithm of the service component are applied. The second statistics submodule is configured to calculate the user traffic indexes according to the user traffic data in the second data bucket by fusing the user traffic data generated by the first station group and the second station group according to the same parameters, so that the user traffic indexes are used to indicate information reflected without applying the function component and the processing algorithm of the service component.

[0107] In a deepened embodiment, the decision control module 1400 comprises: a first fitting submodule, configured to fit a first curve data varying along time according to the user traffic indicators of the first data bucket; a second fitting submodule, configured to fit a second curve data varying along time according to the user traffic indicators of the second data bucket; a difference comparison submodule, configured to determine a time range in which the service component is applied to the independent site, and compare the difference data between the first curve data and the second curve data in the time range; and a judgment output submodule, configured to compare whether the difference data is lower than a preset threshold, and when the difference data is lower than the preset threshold, it is considered that the preset condition is reached, and control information for indicating that the service component is offline is output.

[0108] In an extended embodiment, the service component troubleshooting device also comprises: an instruction generation module, configured to generate an offline control instruction of the service component according to the control information; a target query module, configured to query a target independent site in which the service component is enabled from all independent sites pre-registered to the e-commerce platform in response to the offline control instruction; and an unbundling module, configured to unbundle the configuration bundling information of the service component of each target independent site, so as to realize the offline of the service component of the corresponding target independent site.

[0109] In a preferred embodiment, the user traffic indicator is a click rate indicator or a conversion rate indicator.

[0110] In a preferred embodiment, the service function is a commodity online search function of an e-commerce platform, and correspondingly, the first service link is a front-end service link for executing commodity search, and the second service link is a back-end service link for sorting and outputting the commodity search results generated by the first service link.

[0111] To solve the above technical problems, the embodiments of the present application also provide a computer device. As shown in Figure 7 the internal structure diagram of the computer device. The computer device comprises a processor, a computer readable storage medium, a memory and a network interface connected through a system bus. The computer readable storage medium of the computer device stores an operating system, a database and computer readable instructions. The database can store control information sequences, and the computer readable instructions can make the processor realize a service component troubleshooting method when executed by the processor. The processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device. The memory of the computer device can store computer readable instructions, which can make the processor execute the service component troubleshooting method of the present application when executed by the processor. The network interface of the computer device is used to connect and communicate with the terminal. Those skilled in the art can understand, Figure 7The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0112] The processor in the embodiment is configured to execute the specific functions of each module and its sub-modules in the above formula, and the memory stores the program codes and various data required for executing the above modules or sub-modules. The network interface is configured to transmit data between the user terminal or the server. The memory in the embodiment stores the program codes and data required for executing all modules / sub-modules in the service component troubleshooting device of the present application, and the server can call the program codes and data of the server to execute the functions of all sub-modules. Figure 6

[0113] The present application also provides a storage medium having computer readable instructions stored therein, which, when executed by one or more processors, causes the one or more processors to perform the steps of the service component troubleshooting method of any embodiment of the present application.

[0114] The present application also provides a computer program product comprising computer programs / instructions, which, when executed by one or more processors, implement the steps of the method described in any embodiment of the present application.

[0115] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments of the present application can be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The program, when executed, can include the processes of the above-mentioned embodiments of each method. The storage medium can be a computer readable storage medium such as a magnetic disc, an optical disc, a read-only memory (ROM), or a random access memory (RAM).

[0116] In summary, based on the specific data processing method, the present application accurately and effectively troubleshoots the effectiveness of the service components configured by the e-commerce platform through the user traffic data provided by the scattered independent sites, facilitates the e-commerce platform to timely adjust product development, improves service functions, and improves user experience.

[0117] ​Those skilled in the art can understand that the steps, measures and schemes in the various operations, methods and processes discussed in the present application can be alternated, changed, combined or deleted. Further, other steps, measures and schemes in the various operations, methods and processes discussed in the present application can also be alternated, changed, rearranged, decomposed, combined or deleted. Further, the steps, measures and schemes in the various operations, methods and processes in the prior art can also be alternated, changed, rearranged, decomposed, combined or deleted.

[0118] The above only describes some embodiments of the present application. It should be pointed out that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. A service component troubleshooting method, characterized by, The method comprises the following steps: monitoring user traffic data generated by independent stations in a first group and a second group in a first station group due to execution of a first service link of a preset service function, and storing the data to a first data bucket and a second data bucket; the independent stations in the first group generate corresponding user traffic data by invoking a function plug-in provided by a service component, and the independent stations in the second group generate corresponding user traffic data without invoking the function plug-in provided by the service component; monitoring user traffic data generated by each independent station in a second station group due to execution of a second service link of the service function, and storing user traffic data generated by each independent station by applying a processing algorithm provided by the service component to the first data bucket, and storing user traffic data generated by each independent station without applying the processing algorithm provided by the service component to the second data bucket; statistically obtaining user traffic indicators of the service component that have been applied and not applied according to user traffic data in the first data bucket and the second data bucket, including: according to user traffic data in the first data bucket, fusing and calculating user traffic data generated by the first station group and the second station group according to the same parameters to determine the user traffic indicators, so that the user traffic indicators are used to indicate information reflected after the function component and the processing algorithm of the service component are applied; according to user traffic data in the second data bucket, fusing and calculating user traffic data generated by the first station group and the second station group according to the same parameters to determine the user traffic indicators, so that the user traffic indicators are used to indicate information reflected without applying the function component and the processing algorithm of the service component; determining whether the difference between the same user traffic indicators of the first data bucket and the second data bucket reaches a preset condition, and outputting control information for indicating that the service component is offline when the preset condition is reached.

2. The method of claim 1, wherein, determining whether the difference between the same user traffic indicators of the first data bucket and the second data bucket reaches a preset condition, and outputting control information for indicating that the service component is offline when the preset condition is reached, comprising the following steps: fitting first curve data along time variation according to user traffic indicators of the first data bucket; fitting second curve data along time variation according to user traffic indicators of the second data bucket; determining a time range in which the service component is applied to the independent stations, and comparing and calculating the difference value data between the first curve data and the second curve data in the time range; comparing whether the difference value data is lower than a preset threshold value, and regarding it as reaching the preset condition when it is lower than the preset threshold value, and outputting control information for indicating that the service component is offline.

3. The service component troubleshooting method according to claim 1 or 2, characterized by, After the step of outputting control information for indicating that the service component is offline, comprising the following steps: generating an offline control instruction of the service component according to the control information; in response to the offline control instruction, querying target independent stations in which the service component is enabled among all independent stations pre-registered to an e-commerce platform; Unbind the configuration binding information of the service component of each target independent station, and realize the offline of the service component of the corresponding target independent station.

4. The service component troubleshooting method according to claim 1 or 2, characterized by, The user traffic indicator is a click rate indicator or a conversion rate indicator.

5. The method of claim 1 or 2, wherein, The business function is an online search function of a commodity of an e-commerce platform, and correspondingly, the first business link is a front-end business link for performing commodity search, and the second business link is a back-end business link for sorting and outputting commodity search results generated by the first business link.

6. A service component troubleshooting apparatus, characterized by Comprise: A first monitoring module is configured to monitor user traffic data generated by a first group and a second group of independent stations in a first station group due to execution of a first business link of a preset business function, and store the data into a first data bucket and a second data bucket; wherein the independent stations of the first group generate corresponding user traffic data by calling a function plug-in provided by a business component, and the independent stations of the second group generate corresponding user traffic data without calling the function plug-in provided by the business component; A second monitoring module is configured to monitor user traffic data generated by each independent station in a second station group due to execution of a second business link of the business function, and store user traffic data generated by each independent station by applying a processing algorithm provided by the business component into the first data bucket, and store user traffic data generated by each independent station without applying the processing algorithm provided by the business component into the second data bucket; An indicator statistical module is configured to statistically obtain user traffic indicators of the business component that has been applied and not applied according to user traffic data in the first data bucket and the second data bucket, including: according to user traffic data in the first data bucket, fusing and calculating user traffic data generated by the first station group and the second station group according to the same parameters to determine the user traffic indicators, so that the user traffic indicators are used to indicate information reflected after applying the function component and the processing algorithm of the business component; according to user traffic data in the second data bucket, fusing and calculating user traffic data generated by the first station group and the second station group according to the same parameters to determine the user traffic indicators, so that the user traffic indicators are used to indicate information reflected without applying the function component and the processing algorithm of the business component; A decision control module is configured to determine whether a gap between the same user traffic indicators of the first data bucket and the second data bucket reaches a preset condition, and output control information for indicating that the business component is offline when the preset condition is reached.

7. The service component troubleshooting apparatus of claim 6, wherein, The decision control module comprises: A first fitting sub-module is configured to fit first curve data along time variation according to user traffic indicators of the first data bucket generated at different times; A second fitting sub-module is configured to fit second curve data along time variation according to user traffic indicators of the second data bucket generated at different times; A difference comparison sub-module is configured to determine a time range in which the business component is applied to the independent station, and compare and calculate difference data between the first curve data and the second curve data in the time range. A determination output sub-module is configured to compare the difference data with a preset threshold value, and when the difference data is lower than the preset threshold value, it is considered that the preset condition is reached, and control information indicating that the service component is offline is output.

8. A computer device comprising a central processing unit and a memory, characterized in that The central processing unit is configured to invoke a computer program stored in the memory to execute the steps of the method according to any one of claims 1 to 5.

9. A computer-readable storage medium, characterized in that, The computer program / instructions in the form of computer readable instructions store a computer program implemented according to the method of any one of claims 1 to 5, and when the computer program / instructions are invoked by a computer to run, the steps included in the corresponding method are executed.

10. A computer program product comprising computer programs / instructions, characterized in that, The computer program / instructions are executed by the processor to implement the steps of the method of any one of claims 1 to 5.

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