CN112948090A

CN112948090A - Big data analysis and sorting method applied to network service processing and server

Info

Publication number: CN112948090A
Application number: CN202110310725.0A
Authority: CN
Inventors: 耿赛
Original assignee: Individual
Current assignee: Information and Telecommunication Branch of State Grid Jiangsu Electric Power Co Ltd
Priority date: 2021-03-23
Filing date: 2021-03-23
Publication date: 2021-06-11
Anticipated expiration: 2041-03-23
Also published as: CN112948090B

Abstract

The method and server for analyzing and arranging big data applied to network service processing disclosed in the present application, when receiving the first network service interaction content sent by the front-end service interaction device and acquiring the second service switching thread information and second content of the back-end service switching thread After switching the loss information, the first data integration strategy is determined. By taking the content switching loss information into account, it can ensure that the loss of important data is minimized during the subsequent data integration, which not only satisfies the flexible switching of users between various business services , and can reduce the data processing pressure of the big data server. The data integration result generated based on the first data integration strategy and corresponding to the big data network service activated by the front-end service interaction device can seek a balance between the content quality and simplification of the service data, which not only meets the user's service data usage needs, but also It reduces the data processing pressure on the big data server and avoids the loss of important data during the data integration process.

Description

Big data analysis and sorting method applied to network service processing and server

Technical Field

The application relates to the technical field of big data analysis and network service processing, in particular to a big data analysis and sorting method and a server applied to network service processing.

Background

Big data (big data) is, to some extent, a leading-edge technique for data analysis. In short, big data technology is the ability to quickly obtain valuable information from a wide variety of types of data. The big data brings unprecedented big information explosion to the Internet, changes the data application mode of the Internet, and deeply influences the production and life of people. People in the big data age have realized that big data changes the understanding of data analysis from 'backward analysis' to 'forward analysis', changing the thinking mode of people, but big data also provides the difficulties of data collection, analysis and use. While solving these problems, it means that big data starts to develop in the depth direction.

Depending on the rapid development of big data, the handling of various network services is gradually mature, the data pressure borne by the cloud data server is increased, and the cloud data server is likely to crash during the peak period of handling some network services, so that normal network service handling is seriously affected. To improve this problem, the service data of the cloud data server needs to be properly sorted.

Although the related big data analyzing and sorting method can relieve the data processing pressure of the cloud data server to a certain extent, the related big data analyzing and sorting method may affect normal business handling when the business data is sorted, so that it is difficult to ensure that the sorted business data meets the business handling requirements of users.

Disclosure of Invention

One of the embodiments of the present application provides a big data analysis and sorting method applied to network service processing, which is applied to a big data server in communication connection with a front-end service interaction device, and the method includes:

receiving first network service interaction content sent by front-end service interaction equipment, and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread;

determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment based on the first network service interaction content, the second service switching thread information and the second content switching loss information;

and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment based on the first data integration strategy.

In a further embodiment of the method according to the invention,

receiving a first network service interaction content sent by a front-end service interaction device, and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread, including: receiving first network service interactive content sent by front-end service interactive equipment, wherein the first network service interactive content comprises: the method comprises the steps that interactive content of a service item activated by front-end service interaction equipment, first service switching thread information and first content switching loss information of a service switching thread of the front-end service interaction equipment are obtained, and the first service switching thread information comprises running state information and thread label information of the service switching thread of the front-end service interaction equipment; acquiring second service switching thread information and second content switching loss information of a back-end service switching thread, wherein the second service switching thread information comprises running state information and thread label information of the back-end service switching thread;

determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction device based on the first network service interaction content, the second service switching thread information and the second content switching loss information, including: determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment according to the first service switching thread information, the first content switching loss information, the second service switching thread information and the second content switching loss information;

and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment based on the first data integration strategy, wherein the data integration result corresponding to the big data network service activated by the front-end service interaction equipment is generated according to the first network service interaction content and the first data integration strategy.

In a further embodiment of the method according to the invention,

before receiving the first network service interaction content sent by the front-end service interaction device, the method further includes: sending an interactive content calling instruction to the front-end service interaction equipment, wherein the calling instruction is used for instructing the front-end service interaction equipment to execute dynamic content identification processing on a big data network service activated by a rear end so as to generate network service dynamic interactive content;

the receiving of the first network service interaction content sent by the front-end service interaction device includes: receiving network service dynamic interaction content sent by the front-end service interaction device, wherein the network service dynamic interaction content comprises: the dynamic interactive content of the service item activated by the front-end service interaction equipment, the first service switching thread information of the service switching thread of the front-end service interaction equipment and the first content switching loss information.

In a further embodiment of the method according to the invention,

the sending of the interactive content calling instruction to the front-end service interaction device includes: acquiring interactive item label information of a plurality of front-end service interaction devices selected by associated service interaction devices, and sending interactive content calling instructions to the plurality of front-end service interaction devices according to the interactive item label information of the plurality of front-end service interaction devices;

the receiving of the network service dynamic interaction content sent by the front-end service interaction device includes: receiving network service dynamic interactive contents sent by a plurality of front-end service interactive devices, wherein each front-end service interactive device corresponds to one network service dynamic interactive content, and each network service dynamic interactive content corresponds to one first service switching thread information and one first content switching loss information;

the determining, according to the first service switching thread information, the first content switching loss information, the second service switching thread information, and the second content switching loss information, a first data integration policy for performing service content data integration on a big data network service activated by the front-end service interaction device includes: and determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment according to the plurality of first service switching thread information, the plurality of first content switching loss information, the second service switching thread information and the second content switching loss information.

In a further embodiment of the method according to the invention,

the obtaining of the second service switching thread information and the second content switching loss information of the back-end service switching thread includes: acquiring second service switching thread information and second content switching loss information of each delayed service switching thread of the back-end service switching threads;

the determining, according to the multiple pieces of first service switching thread information, the multiple pieces of first content switching loss information, the second service switching thread information, and the second content switching loss information, a first data integration policy for performing service content data integration on big data network services activated by the multiple pieces of front-end service interaction equipment includes: and for each delay service switching thread, determining a first data integration strategy corresponding to the delay service switching thread for performing service content data integration on the big data network service activated by at least one front-end service interaction device according to at least one piece of first service switching thread information, at least one piece of first content switching loss information, and second service switching thread information and second content switching loss information of the delay service switching thread.

In a further embodiment, the determining, according to the multiple pieces of first service switching thread information, the multiple pieces of first content switching loss information, the second service switching thread information, and the second content switching loss information, a first data integration policy for performing service content data integration on a big data network service activated by the multiple pieces of front-end service interaction equipment includes:

determining data usage heat of text data distribution information and data usage heat of image data distribution information corresponding to each first service switching thread information based on a plurality of first service switching thread information and a plurality of first content switching loss information;

determining data usage heat of text data distribution information and data usage heat of image data distribution information corresponding to the second service switching thread information based on the second service switching thread information and the second content switching loss information;

determining a first data integration strategy for performing service content data integration on big data network services activated by a plurality of front-end service interaction devices based on the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to each first service switching thread information, the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to the second service switching thread information;

preferably, the determining a first data integration policy for performing service content data integration on a big data network service activated by a plurality of front-end service interaction devices based on the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to each first service switching thread information, and the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to each second service switching thread information includes:

when the data usage heat of the text data distribution information corresponding to the second service switching thread information is greater than the data usage heat of the image data distribution information corresponding to the second service switching thread information, selecting the data use heat of the image data distribution information with the maximum value from the data use heat of the image data distribution information corresponding to each first service switching thread information, determining a first use heat comparison result of the data use heat of the image data distribution information corresponding to the maximum image data distribution information and the second use heat comparison result of the data use heat of the image data distribution information corresponding to the second service switching thread information, and a second use heat comparison result of the global data use heat of the text data distribution information corresponding to each first service switching thread information and the data use heat of the text data distribution information corresponding to the second service switching thread information; determining a first data integration strategy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices based on the usage heat comparison result corresponding to the plurality of data scene labels in the first usage heat comparison result and the second usage heat comparison result;

when the data use heat of the text data distribution information corresponding to the second service switching thread information is not greater than the data use heat of the image data distribution information corresponding to the second service switching thread information; selecting the maximum data use heat of the text data distribution information from the data use heat of the text data distribution information corresponding to each first service switching thread information, and determining a third use heat comparison result of the maximum data use heat of the text data distribution information and the data use heat of the text data distribution information corresponding to the second service switching thread information, and a fourth use heat comparison result of the global data use heat of the image data distribution information corresponding to each first service switching thread information and the data use heat of the image data distribution information corresponding to the second service switching thread information; and determining a first data integration strategy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices based on the usage heat comparison result corresponding to the plurality of data scene labels in the third usage heat comparison result and the fourth usage heat comparison result.

constructing a plurality of network service interaction scenes of big data network services activated for a plurality of front-end service interaction devices based on a plurality of first service switching thread information and a plurality of first content switching loss information;

determining a fifth use heat comparison result between the data use heat of the text data distribution information and the data use heat of the image data distribution information corresponding to each network service interaction scene;

determining a sixth usage heat comparison result between the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to the second service switching thread information based on the second service switching thread information and the second content switching loss information;

selecting a network service interaction scene corresponding to a fifth use heat comparison result with the maximum data association degree between the sixth use heat comparison result and the sixth use heat comparison result as a target network service interaction scene;

determining a seventh usage heat comparison result of the data usage heat of the text data distribution information corresponding to the target network service interaction scene and the data usage heat of the text data distribution information corresponding to the second service switching thread information, and an eighth usage heat comparison result of the data usage heat of the image data distribution information corresponding to the target network service interaction scene and the data usage heat of the image data distribution information corresponding to the second service switching thread information;

determining a first data integration strategy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices based on the usage heat comparison result corresponding to the plurality of data scene tags in the seventh usage heat comparison result and the eighth usage heat comparison result;

the generating a data integration result corresponding to the big data network service activated by the front-end service interaction device according to the first network service interaction content and the first data integration strategy comprises:

taking the target network service interaction scene as a front-end service interaction scene corresponding to a big data network service activated by a plurality of front-end service interaction devices, and performing service content data integration on the first network service interaction content by adopting the first data integration strategy;

and generating a data integration result corresponding to the big data network service activated by the plurality of front-end service interaction devices according to the front-end service interaction scene and the first network service interaction content integrated by the service content data.

In a further embodiment, when the backend service switching thread runs an associated network service, the method further includes:

acquiring second network service interactive content of the associated network service, wherein the second network service interactive content comprises data use heat of text data distribution information of the associated network service and data use heat of image data distribution information of the associated network service;

determining a second data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment according to the first service switching thread information, the first content switching loss information, the second service switching thread information, the second content switching loss information and the second network service interaction content;

and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment according to the first network service interaction content and the second data integration strategy.

determining running state information and thread label information of the back-end service switching thread occupied by the associated network service according to the second network service interactive content and the second content switching loss;

determining a third data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment and the associated network service according to the plurality of first service switching thread information, the plurality of first content switching loss information, the second service switching thread information, the second content switching loss information, the running state information of the back-end service switching thread occupied by the associated network service and the thread label information;

and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment according to the first network service interaction content and the third data integration strategy.

One of the embodiments of the present application provides a big data server, which includes a processing engine, a network module, and a memory; the processing engine and the memory communicate through the network module, and the processing engine reads the computer program from the memory and operates to perform the above-described method.

In the description that follows, additional features will be set forth, in part, in the description. These features will be in part apparent to those skilled in the art upon examination of the following and the accompanying drawings, or may be learned by production or use. The features of the present application may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities and combinations particularly pointed out in the detailed examples that follow.

Drawings

The present application will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and like reference numerals refer to like structures throughout these embodiments.

Fig. 1 is a flow diagram illustrating an exemplary big data analytics collating method and/or process applied to network traffic processing, according to some embodiments of the present invention.

FIG. 2 is a block diagram illustrating an exemplary big data analytics collating system applied to network traffic processing, according to some embodiments of the present invention.

Fig. 3 is a block diagram of an exemplary big data analytics collating apparatus applied to network traffic processing, according to some embodiments of the present invention.

FIG. 4 is a diagram illustrating the hardware and software components of an exemplary big data server, according to some embodiments of the invention.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is obvious that the drawings in the following description are only examples or embodiments of the application, from which the application can also be applied to other similar scenarios without inventive effort for a person skilled in the art. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "device", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this application and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used herein to illustrate operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

In order to solve the technical problems in the background art, the inventor provides a big data analysis and arrangement method and a big data server applied to network service processing in a targeted manner, and can seek a balance between the content quality and the simplification degree of service data, so that the service data use requirement of a user is met, the data processing pressure of the big data server can be reduced, and the loss of important data in the data integration process can be avoided.

Referring to fig. 1, a flowchart of an exemplary big data parsing and sorting method and/or process applied to network service processing according to some embodiments of the present invention may be applied to a big data server communicatively connected to a front-end service interaction device, and the method may include the following technical solutions described in steps S100 to S300.

S100: receiving first network service interaction content sent by front-end service interaction equipment, and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread.

Referring to fig. 2, the front-end service interaction device 100 and the associated service interaction device 200 are communicatively connected through a big data server 300, where the front-end service interaction device 100 and the associated service interaction device 200 may be multiple, for example, the front-end service interaction device 100 may include a front-end service interaction device 101, a front-end service interaction device 102, and a front-end service interaction device 103, and the associated service interaction device 200 may include an associated service interaction device 201, an associated service interaction device 202, and an associated service interaction device 203. In addition, both the front-end service interaction device 100 and the associated service interaction device 200 may be deployed in the front-end, such as in the form of an interactive touch screen in a related service hall. The backend service switching thread is deployed in the big data server 300, and the big data server 300 may be deployed in the cloud. Further, the first network service interaction content may include interaction content generated after the front-end service interaction device 100 performs online interaction with other front-end service interaction devices 100, associated service interaction devices 200, or the big data server 300. Further, network services include, but are not limited to, online government cloud services, cloud gaming services, online payment services, teleworking services, teleeducation services, and the like.

In a related embodiment, the step of "receiving a first network service interaction content sent by a front-end service interaction device, and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread" may be implemented by: receiving a first network service interaction content sent by a front-end service interaction device, and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread, including: receiving first network service interactive content sent by front-end service interactive equipment, wherein the first network service interactive content comprises: the method comprises the steps that interactive content of a service item activated by front-end service interaction equipment, first service switching thread information and first content switching loss information of a service switching thread of the front-end service interaction equipment are obtained, and the first service switching thread information comprises running state information and thread label information of the service switching thread of the front-end service interaction equipment; and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread, wherein the second service switching thread information comprises running state information and thread label information of the back-end service switching thread.

For example, the service item may be a service item corresponding to an online government-enterprise cloud service, a cloud game service, an online payment service, a teleworking service, a teleeducation service, and the like, the service switching thread information is used to record log information and state information during the operation of the service switching thread, and the content switching loss information is used to represent a data loss situation during switching between different service items, for example, during the process of switching from a cloud game service item to a teleworking service item, the content switching loss information may be { miss data2}, that is, during the process of switching from a cloud game service item to a teleworking service item, there may be a loss of service data 2. In this embodiment, by analyzing and considering the content switching loss information, it can be ensured that the loss of important data is reduced as much as possible during subsequent data integration, thereby satisfying the flexible switching between various service services for the user, and reducing the data processing pressure of the large data server. In addition, thread tag information may be used to distinguish different service threads, such as thread tag information "1" to refer to an online government-enterprise cloud service, thread tag information "2" to refer to a cloud game service, thread tag information "3" to refer to an online payment service, thread tag information "4" to refer to a teleworking service, and thread tag information "5" to refer to a teleeducation service.

In a related embodiment, in order to accurately obtain dynamic interactive content to ensure the integrity of subsequent data integration, before performing step S100, the following may be further included: and sending an interactive content calling instruction to the front-end service interaction equipment, wherein the calling instruction is used for instructing the front-end service interaction equipment to execute dynamic content identification processing on the big data network service activated by the back end so as to generate network service dynamic interactive content. The interactive content calling indication can carry a calling label aiming at the dynamic interactive content, the big data network service activated by the back end can be the big data network service activated by the big data server after responding to the service behavior of the front end service interaction equipment, the dynamic interactive content of the network service can be understood as the interactive content which is continuously updated along with the change of time, and compared with the general interactive content, the dynamic interactive content has higher use value and analysis value. On the basis of the above content, the step "receiving the first network service interaction content sent by the front-end service interaction device" may further include: receiving network service dynamic interaction content sent by the front-end service interaction device, wherein the network service dynamic interaction content comprises: the dynamic interactive content of the service item activated by the front-end service interaction equipment, the first service switching thread information of the service switching thread of the front-end service interaction equipment and the first content switching loss information.

On the basis of the above content, the step "sending an interactive content calling instruction to the front-end service interaction device" may include the following content: acquiring interactive item label information of a plurality of front-end service interaction devices selected by associated service interaction devices, and sending interactive content calling instructions to the plurality of front-end service interaction devices according to the interactive item label information of the plurality of front-end service interaction devices, wherein the step of receiving network service dynamic interactive contents sent by the front-end service interaction devices comprises the following steps of: and receiving network service dynamic interactive contents sent by a plurality of front-end service interactive devices, wherein each front-end service interactive device corresponds to one network service dynamic interactive content, and each network service dynamic interactive content corresponds to one first service switching thread information and one first content switching loss information.

It can be understood that the above contents respectively show the obtaining of the network service interaction contents for one front-end service interaction device and for a plurality of front-end service interaction devices, and on the basis of the above contents, the following steps S200 and S300 may also be adaptively selected and combined.

In some embodiments, the obtaining second service switching thread information and second content switching loss information of the backend service switching thread includes: and acquiring second service switching thread information and second content switching loss information of each delayed service switching thread of the back-end service switching threads. The delayed service switching thread may be understood as a thread with service switching delay, for example, a business service switching is triggered at time t1, and the business service switching may be executed at time t2 (time t2 is later than time t 1).

S200: and determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment based on the first network service interaction content, the second service switching thread information and the second content switching loss information.

For example, the big data network service activated by the front-end service interaction device may be a big data network service activated by the front-end service interaction device and corresponding to a service initiator, and the type of the big data network service includes an online government-enterprise cloud service, a cloud game service, an online payment service, a teleworking service, a teleeducation service, and the like. Further, the first data integration policy may be used to indicate that relevant service content data is integrated, such as which part of the data is merged, which part of the data is deleted, and so on. It can be understood that, since the first data integration policy is obtained based on the first network service interaction content, the second service switching thread information, and the second content switching loss information, not only the service switching thread information (actual user requirements) but also the content switching loss information (data loss condition) are considered, so that a balance can be found between the content quality and the simplification degree of the service data, thereby not only meeting the service data use requirements of users, but also reducing the data processing pressure of a large data server, and also avoiding the loss of important data in the data integration process. Based on this, the step "determining a first data integration policy for performing service content data integration on the big data network service activated by the front-end service interaction device based on the first network service interaction content, the second service switching thread information, and the second content switching loss information" may include the following contents: and determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment according to the first service switching thread information, the first content switching loss information, the second service switching thread information and the second content switching loss information.

In some possible embodiments, on the basis of the foregoing S100, the step "determining a first data integration policy for performing service content data integration on the big data network service activated by the front-end service interaction device according to the first service switching thread information, the first content switching loss information, the second service switching thread information, and the second content switching loss information" may include the following contents: and determining a first data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment according to the plurality of first service switching thread information, the plurality of first content switching loss information, the second service switching thread information and the second content switching loss information.

On the basis of the foregoing S100, after considering the delayed service switching thread, the step "determining a first data integration policy for performing service content data integration on a big data network service activated by a plurality of front-end service interaction devices according to a plurality of pieces of first service switching thread information, a plurality of pieces of first content switching loss information, the second service switching thread information, and the second content switching loss information" may further include the following: and for each delay service switching thread, determining a first data integration strategy corresponding to the delay service switching thread for performing service content data integration on the big data network service activated by at least one front-end service interaction device according to at least one piece of first service switching thread information, at least one piece of first content switching loss information, and second service switching thread information and second content switching loss information of the delay service switching thread. By the design, the delay condition of the service switching thread can be taken into account, so that the first data integration strategy can take the difference between different business services into account as much as possible, and the data loss in the data integration process is reduced as much as possible.

In other embodiments, the first data integration policy may be determined according to the data type and the usage heat of the service content data, so that it is ensured that the result obtained by integration can meet the current usage heat of the user, thereby avoiding data processing pressure caused by the user querying related service data content for the second time. To achieve this object, the step "determining a first data integration policy for performing service content data integration on big data network services activated by a plurality of front-end service interaction devices according to a plurality of pieces of first service switching thread information, a plurality of pieces of first content switching loss information, the second service switching thread information, and the second content switching loss information" may include the following contents described in steps S210 to S230.

S210: and determining the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to each first service switching thread information based on the plurality of first service switching thread information and the plurality of first content switching loss information.

For example, there may be many types of classifications of service content data corresponding to interactive content, in this embodiment, text data and image data are used as classifications for description, and of course, the implementation mode in which text data and image data are used as classifications is not a limitation to the present solution. Further, the text data distribution information may be understood as a distribution of text data in a time sequence and under different types of business scenarios, the image data distribution information may be understood as a distribution of image data in a time sequence and under different types of business scenarios, and the distribution information may also refer to a distribution of display areas on the visualization processing interface, which is not limited herein. Further, the data usage heat may be determined according to the number of data calls and/or the number of data accesses per unit time, such as the data usage heat hrate = n/L, where n is the number of data calls and/or the number of data accesses, L is the unit time, and L may be several seconds or several minutes, which is not limited herein.

S220: and determining the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to the second service switching thread information based on the second service switching thread information and the second content switching loss information.

S230: and determining a first data integration strategy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices based on the data usage heat of the text data distribution information and the image data distribution information corresponding to each first service switching thread information, and the data usage heat of the text data distribution information and the image data distribution information corresponding to the second service switching thread information.

It can be understood that the front-end service and the back-end service can be considered simultaneously when the first data integration strategy is determined, so that different service threads are comprehensively analyzed, and data use heat of different types of data distribution information is combined for processing, so that the result obtained by integration can be ensured to meet the current user use heat, and data processing pressure caused by the fact that a user inquires related service data content for the second time is avoided.

In the related embodiment, since the tendency degrees of the users to different types of data are different, when the first data integration policy is determined, the different types of data need to be locally analyzed to ensure that the first data integration policy conforms to the actual use requirements of the users as much as possible.

In the first case, the data usage heat of the text data distribution information corresponding to the second service switching thread information is greater than the data usage heat of the image data distribution information corresponding to the second service switching thread information. Based on this, the data usage heat of the largest image data distribution information may be selected from the data usage heat of the image data distribution information corresponding to each of the first service switching thread information, and a first usage heat comparison result of the data usage heat of the largest image data distribution information and the data usage heat of the image data distribution information corresponding to the second service switching thread information may be determined, and a second usage heat comparison result of the global data usage heat of the text data distribution information corresponding to each of the first service switching thread information and the data usage heat of the text data distribution information corresponding to the second service switching thread information may be determined. Further, the first data integration strategy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices is determined based on the usage heat comparison result corresponding to the big data scene tags in the first usage heat comparison result and the second usage heat comparison result.

In the second case, the data usage heat of the text data distribution information corresponding to the second service switching thread information is not greater than the data usage heat of the image data distribution information corresponding to the second service switching thread information. Based on this, the data usage heat of the largest text data distribution information may be selected from the data usage heat of the text data distribution information corresponding to each of the first service switching thread information, and a third usage heat comparison result of the data usage heat of the largest text data distribution information and the data usage heat of the text data distribution information corresponding to the second service switching thread information may be determined, and the fourth usage heat comparison result of the global data usage heat of the image data distribution information corresponding to each of the first service switching thread information and the data usage heat of the image data distribution information corresponding to the second service switching thread information may be determined. Further, the first data integration policy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices is determined based on the usage heat comparison result corresponding to the plurality of data scene tags in the third usage heat comparison result and the fourth usage heat comparison result.

Since the embodiments of the two cases are similar, the present embodiment only adaptively describes the first case. In the first case, since the data use heat degree of the text data distribution information corresponding to the second service switching thread information is higher than the data use heat degree of the image data distribution information corresponding to the second service switching thread information, in this case, in order to ensure that the image data is not largely deleted in the integration process, it is necessary to analyze the use heat degree of the image data, and therefore, from the data use heat degrees of the image data distribution information corresponding to the respective first service switching thread information, the data use heat degree of the largest image data distribution information may be selected, and the result of comparing the data use heat degree of the largest image data distribution information with the first use heat degree of the data use heat degree of the image data distribution information corresponding to the second service switching thread information, and the result of comparing the global data use heat degree of the text data distribution information corresponding to the respective first service switching thread information with the used global data use heat degree of the text data distribution information corresponding to the respective first service switching thread information And a second usage heat comparison result of the data usage heat of the text data distribution information corresponding to the second service switching thread information. In this way, the image data of the front end and the image data of the rear end can be comprehensively analyzed, and the difference in the degree of use of the front end image data and the rear end image data can be expressed by the first degree of use comparison result. On the basis, the data scene labels can be identified for different usage heat comparison results, for example, a convolutional neural network trained in advance can be used for identification, so that usage heat comparison results corresponding to more data scene labels in the first usage heat comparison result and the second usage heat comparison result are obtained. In practical implementation, the number of data scene tags is large, which indicates that the stability of the data usage heat is high, and therefore, the first data integration policy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices may be determined according to the usage heat comparison result with the large number of data scene tags in the first usage heat comparison result and the second usage heat comparison result. Therefore, the data use heat of different data types is considered, the difference of the data use heat of the front end and the rear end is also considered, and the data scene labels are further comprehensively analyzed, so that the data of different types can be locally analyzed, and the first data integration strategy can meet the actual use requirement of a user as much as possible. It is understood that the implementation principle of the second case is similar to that of the first case, and therefore, the detailed description thereof is omitted.

In some other embodiments, when determining the first data integration policy, the network service interaction scenario may be further considered, and to achieve this, the step "determining a first data integration policy for performing service content data integration on a big data network service activated by a plurality of front-end service interaction devices according to a plurality of first service switching thread information, a plurality of first content switching loss information, the second service switching thread information, and the second content switching loss information" may include the following contents: constructing a plurality of network service interaction scenes of big data network services activated for a plurality of front-end service interaction devices based on a plurality of first service switching thread information and a plurality of first content switching loss information; determining a fifth use heat comparison result between the data use heat of the text data distribution information and the data use heat of the image data distribution information corresponding to each network service interaction scene; determining a sixth usage heat comparison result between the data usage heat of the text data distribution information and the data usage heat of the image data distribution information corresponding to the second service switching thread information based on the second service switching thread information and the second content switching loss information; selecting a network service interaction scene corresponding to a fifth use heat comparison result with the maximum data association degree between the sixth use heat comparison result and the sixth use heat comparison result as a target network service interaction scene; determining a seventh usage heat comparison result of the data usage heat of the text data distribution information corresponding to the target network service interaction scene and the data usage heat of the text data distribution information corresponding to the second service switching thread information, and an eighth usage heat comparison result of the data usage heat of the image data distribution information corresponding to the target network service interaction scene and the data usage heat of the image data distribution information corresponding to the second service switching thread information; and determining a first data integration strategy for performing service content data integration on the big data network service activated by the plurality of front-end service interaction devices based on the usage heat comparison result corresponding to the plurality of data scene tags in the seventh usage heat comparison result and the eighth usage heat comparison result.

In the above embodiment considering the network service interaction scenario, firstly, a plurality of network service interaction scenarios of the big data network service activated for the plurality of front-end service interaction devices can be constructed based on the plurality of first service switching thread information and the plurality of first content switching loss information, then, the target network service interaction scenario is determined according to the comparison result of the usage heat of different data usage heat, since the selected target network service interaction scenario is determined based on the data correlation, the service correlation between different types of data in the target network service interaction scenario can be ensured, further, by determining the seventh usage heat comparison result of the data usage heat of the text data distribution information corresponding to the target network service interaction scenario and the data usage heat of the text data distribution information corresponding to the second service switching thread information, and comparing the data use heat of the image data distribution information corresponding to the target network service interaction scene with the eighth use heat of the data use heat of the image data distribution information corresponding to the second service switching thread information, and considering the data scene label, so that different interaction scenes can be subjected to fine analysis, and the first data integration strategy can be ensured to be in accordance with the actual use scene of the user as much as possible.

S300: and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment based on the first data integration strategy.

In a related embodiment, the step of generating a data integration result corresponding to the big data network service activated by the front-end service interaction device based on the first data integration policy may include the following steps: and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment according to the first network service interaction content and the first data integration strategy. For example, the data integration result may be stored in a big data server, or may be output to the front-end service interaction device, which is not limited herein. It is understood that the generated data integration result may be obtained after integrating the service content data of the first network service interaction content, and the expression form of the data integration result includes, but is not limited to, text and diagrams.

On the basis of the implementation mode in which the network service interaction scenario is considered, described in S200, the step "generating a data integration result corresponding to the big data network service activated by the front-end service interaction device according to the first network service interaction content and the first data integration policy" may further include the following steps: taking the target network service interaction scene as a front-end service interaction scene corresponding to a big data network service activated by a plurality of front-end service interaction devices, and performing service content data integration on the first network service interaction content by adopting the first data integration strategy; and generating a data integration result corresponding to the big data network service activated by the plurality of front-end service interaction devices according to the front-end service interaction scene and the first network service interaction content integrated by the service content data. By the design, the front-end service interaction scene can be taken into consideration, so that the timeliness of the data integration result is ensured.

In an actual implementation process, because the backend service switching thread is deployed in the big data server, and the backend service switching thread may be used to switch different service items, in some cases, there may be associated network services (for example, services corresponding to other service interaction devices) in the backend service switching thread, and in this case, in order to ensure that mutual interference between different network services is minimized in the data integration process, in some embodiments, the following may also be included: acquiring second network service interactive content of the associated network service, wherein the second network service interactive content comprises data use heat of text data distribution information of the associated network service and data use heat of image data distribution information of the associated network service; determining a second data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment according to the first service switching thread information, the first content switching loss information, the second service switching thread information, the second content switching loss information and the second network service interaction content; and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment according to the first network service interaction content and the second data integration strategy. Because the second data integration strategy considers the interactive content of the second network service, when data integration is carried out based on the second data integration strategy, the mutual interference among different network services can be minimized in the data integration process, and the problems of data false deletion or data repeated integration and the like caused by the influence of the associated network service on the interactive content of the first network service in the data integration process are avoided.

In some other embodiments, in order to consider the memory resource occupation situation of the big data server, when the relevant network service is run in the backend service switching thread, the embodiment may further include the content described in the following steps: acquiring second network service interactive content of the associated network service, wherein the second network service interactive content comprises data use heat of text data distribution information of the associated network service and data use heat of image data distribution information of the associated network service; determining running state information and thread label information of the back-end service switching thread occupied by the associated network service according to the second network service interactive content and the second content switching loss; determining a third data integration strategy for performing service content data integration on the big data network service activated by the front-end service interaction equipment and the associated network service according to the plurality of first service switching thread information, the plurality of first content switching loss information, the second service switching thread information, the second content switching loss information, the running state information of the back-end service switching thread occupied by the associated network service and the thread label information; and generating a data integration result corresponding to the big data network service activated by the front-end service interaction equipment according to the first network service interaction content and the third data integration strategy. Before the third data integration strategy is determined, the running state information and the thread label information of the back-end service switching thread occupied by the associated network service are determined according to the second network service interaction content and the second content switching loss, so that when the third data integration strategy is determined, not only the running state information and the thread label information of the back-end service switching thread occupied by the associated network service can be considered, but also the running state information and the thread label information of the back-end service switching thread occupied by the associated network service can be considered, namely the memory resource occupation condition of the big data server is considered, and the determined third data integration strategy can be compatible with the data processing pressure of the big data server, when the big data server integrates data based on the umbrella-equipped data integration strategy, the occupation of memory resources can be reduced as much as possible, thereby avoiding influencing the normal handling of other services.

It can be understood that when generating a data integration result corresponding to the big data network service activated by the front-end service interaction device, the data integration may be performed according to different data integration strategies. The first data integration strategy focuses on the analysis of the data use heat, the second data integration strategy focuses on ensuring that the mutual interference among different network services is minimized in the data integration process, and the third data integration strategy focuses on reducing the memory resource occupation of the big data server, so that when the big data of the network services are analyzed and sorted, a balance can be found between the content quality and the simplification degree of the service data, thereby not only meeting the service data use requirements of users, but also reducing the data processing pressure of the big data server and avoiding the loss of important data in the data integration process.

In this embodiment, the data integration orders and data integration logics of different data integration policies may be different, and in the actual implementation process, the data integration policies may also be adaptively adjusted to meet real-time business requirements. Therefore, the method can realize high-quality arrangement of the service content data to avoid data loss, meet the actual service requirements of users as much as possible, and improve the efficiency of network service processing.

In summary, when the technical solution provided in this embodiment is applied, after receiving a first network service interaction content sent by a front-end service interaction device and acquiring second service switching thread information and second content switching loss information of a back-end service switching thread, a first data integration policy for performing service content data integration on a big data network service activated by the front-end service interaction device can be determined, and by taking the content switching loss information into consideration, it can be ensured that loss of important data is reduced as much as possible during subsequent data integration, so that flexible switching between various service services by a user is satisfied, and data processing pressure of a big data server can be reduced, and thus, a data integration result generated based on the first data integration policy and corresponding to the big data network service activated by the front-end service interaction device can seek a balance between content quality and simplification degree of service data, therefore, the service data using requirements of users are met, the data processing pressure of the big data server can be reduced, and important data loss in the data integration process can be avoided.

In view of the above big data analyzing and sorting method applied to network service processing, an exemplary big data analyzing and sorting device applied to network service processing is further provided in the embodiment of the present invention, as shown in fig. 3, the big data analyzing and sorting device 400 applied to network service processing may include the following functional modules.

The information obtaining module 410 is configured to receive a first network service interaction content sent by a front-end service interaction device, and obtain second service switching thread information and second content switching loss information of a back-end service switching thread.

A policy determining module 420, configured to determine, based on the first network service interaction content, the second service switching thread information, and the second content switching loss information, a first data integration policy for performing service content data integration on a big data network service activated by the front-end service interaction device.

A data integration module 430, configured to generate a data integration result corresponding to the big data network service activated by the front-end service interaction device based on the first data integration policy.

It can be understood that for further implementation of the information obtaining module 410, the policy determining module 420, and the data integrating module 430, reference may be made to the description of the method embodiment shown in fig. 1, which is not described herein again.

Further, referring to fig. 4 in conjunction, the big data server 300 may include a processing engine 310, a network module 320, and a memory 330, the processing engine 310 and the memory 330 communicating through the network module 320.

Processing engine 310 may process the relevant information and/or data to perform one or more of the functions described herein. For example, in some embodiments, processing engine 310 may include at least one processing engine (e.g., a single core processing engine or a multi-core processor). By way of example only, Processing engine 310 may include a Central Processing Unit (CPU), an Application-Specific Integrated Circuit (ASIC), an Application-Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a Reduced Instruction Set Computer (RISC), a microprocessor, or the like, or any combination thereof.

The network module 320 may facilitate the exchange of information and/or data. In some embodiments, the network module 320 may be any type of wired or wireless network or combination thereof. Merely by way of example, Network module 320 may include a cable Network, a wired Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a Wireless personal Area Network, a Near Field Communication (NFC) Network, and the like, or any combination thereof. In some embodiments, the network module 320 may include at least one network access point. For example, the network module 320 may include wired or wireless network access points, such as base stations and/or network access points.

The Memory 330 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 330 is used for storing a program, and the processing engine 310 executes the program after receiving an execution instruction.

It is to be understood that the configuration shown in fig. 4 is merely illustrative, and that the big data server 300 may also include more or fewer components than shown in fig. 4, or have a different configuration than shown in fig. 4. The components shown in fig. 4 may be implemented in hardware, software, or a combination thereof.

It should be appreciated that the system and its modules shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided, for example, on a carrier medium such as a diskette, CD-or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the present application may be combined as appropriate.

Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereon. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of various portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, a conventional programming language such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, Ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the numbers allow for adaptive variation. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

The entire contents of each patent, patent application publication, and other material cited in this application, such as articles, books, specifications, publications, documents, and the like, are hereby incorporated by reference into this application. Except where the application is filed in a manner inconsistent or contrary to the present disclosure, and except where the claim is filed in its broadest scope (whether present or later appended to the application) as well. It is noted that the descriptions, definitions and/or use of terms in this application shall control if they are inconsistent or contrary to the statements and/or uses of the present application in the material attached to this application.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application can be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. a method for analyzing and arranging big data applied to network service processing is characterized in that, being applied to a big data server communicatively connected with front-end service interaction equipment, the method comprises:

Receive the first network service interaction content sent by the front-end service interaction device, and obtain second service switching thread information and second content switching loss information of the back-end service switching thread;

Based on the first network service interaction content, the second service switching thread information, and the second content switching loss information, determine the first method for integrating the service content data for the big data network service activated by the front-end service interaction device data integration strategy;

Based on the first data integration strategy, a data integration result corresponding to the big data network service activated by the front-end service interaction device is generated.

2. The method according to claim 1, wherein

Receiving the first network service interaction content sent by the front-end service interaction device, and acquiring second service switching thread information and second content switching loss information of the back-end service switching thread, including: receiving the first network service interaction sent by the front-end service interaction device content, wherein the first network service interaction content includes: the interaction content of the service item activated on the front-end service interaction device, the first service switching thread information and the first content of the service switching thread of the front-end service interaction device Switching loss information, the first service switching thread information includes the running state information and thread label information of the service switching thread of the front-end service interaction device; obtain the second service switching thread information and second content switching thread information of the back-end service switching thread Loss information, wherein the second service switching thread information includes running state information and thread label information of the backend service switching thread;

Based on the first network service interaction content, the second service switching thread information, and the second content switching loss information, determine the first method for integrating the service content data for the big data network service activated by the front-end service interaction device The data integration strategy includes: determining the interaction of the front-end service according to the first service switching thread information, the first content switching loss information, the second service switching thread information and the second content switching loss information The first data integration strategy for device-activated big data network services to integrate business content data;

Based on the first data integration strategy, generating a data integration result corresponding to the big data network service activated by the front-end business interaction device includes generating a data integration result corresponding to the first network business interaction content and the first data integration strategy according to the first network business interaction content and the first data integration strategy. The data integration result corresponding to the big data network service activated by the front-end service interaction device.

3. The method of claim 2, wherein

Before receiving the first network service interaction content sent by the front-end service interaction device, the method further includes: sending an interactive content invocation instruction to the front-end service interaction device, where the invocation instruction is used to instruct the front-end service interaction device to The terminal-activated big data network service performs dynamic content recognition processing to generate dynamic interactive content of the network service;

The receiving the first network service interaction content sent by the front-end service interaction device includes: receiving the network service dynamic interaction content sent by the front-end service interaction device, where the network service dynamic interaction content includes: activating the front-end service interaction device. The dynamic interactive content of the service item, the first service switching thread information and the first content switching loss information of the service switching thread of the front-end business interaction device.

4. The method of claim 3, wherein

The sending the interactive content invocation instruction to the front-end service interaction device includes: acquiring the interaction item label information of multiple front-end service interaction devices selected by the associated service interaction device, and according to the interaction item label information of the plurality of front-end service interaction devices , sending interactive content invocation instructions to multiple front-end business interaction devices;

The receiving the network service dynamic interaction content sent by the front-end service interaction device includes: receiving a plurality of network service dynamic interaction contents sent by the front-end service interaction device, wherein each front-end service interaction device corresponds to a network service dynamic interaction device. content, each network service dynamic interactive content corresponds to a first service switching thread information and a first content switching loss information;

and determining, according to the first service switching thread information, the first content switching loss information, the second service switching thread information, and the second content switching loss information, the maximum activation time for the front-end service interaction device. A first data integration strategy for data network services to integrate service content data, including: switching thread information according to multiple first services, switching loss information of multiple first contents, the second service switching thread information, and the second content Switching loss information to determine a first data integration strategy for integrating service content data for a plurality of big data network services activated by the front-end service interaction devices.

5. The method according to claim 4, characterized in that,

The back-end service switching thread includes a plurality of delayed service switching threads, and the acquiring second service switching thread information and second content switching loss information of the back-end service switching thread includes: acquiring the information of the back-end service switching thread. Second service switching thread information and second content switching loss information of each delayed service switching thread;

determining, according to a plurality of first service switching thread information, a plurality of first content switching loss information, the second service switching thread information and the second content switching loss information, to activate the multiple front-end service interaction devices The first data integration strategy for integrating the business content data for the big data network business includes: for each delayed service switching thread, according to at least one first service switching thread information, at least one first content switching loss information, the delay The second service switching thread information and the second content switching loss information of the service switching thread, determine the first service switching thread corresponding to the delayed service switching thread for integrating the service content data for the big data network service activated by the at least one front-end service interaction device. Data integration strategy.

6 . The method according to claim 4 , wherein the switching thread information according to a plurality of first services, a plurality of first contents switching loss information, the second service switching thread information and the second content Switching loss information, and determining a first data integration strategy for integrating service content data for multiple big data network services activated by the front-end service interaction devices, including:

determining, based on a plurality of first service switching thread information and a plurality of first content switching loss information, a data usage degree of text data distribution information and a data usage degree of image data distribution information corresponding to each of the first service switching thread information;

Based on the second service switching thread information and the second content switching loss information, determine the data usage popularity of the text data distribution information and the data usage popularity of the image data distribution information corresponding to the second service switching thread information;

Based on the data usage popularity of text data distribution information and image data distribution information corresponding to each first service switching thread information, the data usage popularity and image data distribution information of the text data distribution information corresponding to the second service switching thread information The data usage popularity of the information determines the first data integration strategy for integrating the business content data for the big data network services activated by multiple front-end business interaction devices;

Preferably, the data usage based on the text data distribution information corresponding to each first service switching thread information and the data usage popularity of the image data distribution information, and the data usage of the text data distribution information corresponding to the second service switching thread information The popularity and the data usage popularity of the image data distribution information determine the first data integration strategy for business content data integration for big data network services activated by multiple front-end business interaction devices, including:

When the data usage intensity of the text data distribution information corresponding to the second service switching thread information is greater than the data usage intensity of the image data distribution information corresponding to the second service switching thread information, the thread information is switched from each of the first services In the data usage heat of the corresponding image data distribution information, select the data usage heat of the largest image data distribution information, and determine the image corresponding to the data usage heat of the largest image data distribution information and the second service switching thread information The comparison result of the first usage level of the data usage level of the data distribution information, the global data usage level of the text data distribution information corresponding to each of the first service switching thread information and the global data usage level of the second service switching thread information. The second use heat comparison result of the data use heat of the text data distribution information; based on the first use heat comparison result and the second use heat comparison result corresponding to the use heat comparison result with more data scene tags, determine the Describe a first data integration strategy for integrating business content data for a plurality of big data network services activated by the front-end business interaction devices;

When the data usage intensity of the text data distribution information corresponding to the second service switching thread information is not greater than the data usage intensity of the image data distribution information corresponding to the second service switching thread information; In the data usage heat of the text data distribution information corresponding to the information, select the data usage heat of the largest text data distribution information, and determine the data usage heat of the largest text data distribution information and the second service switching thread information. The third use heat comparison result of the data use heat of the text data distribution information, the global data use heat of the image data distribution information corresponding to each of the first service switching thread information corresponds to the second service switching thread information The fourth usage comparison result of the data usage intensity of the image data distribution information of the The first data integration strategy for integrating service content data for the big data network services activated by the plurality of front-end service interaction devices.

7. The method according to claim 4, wherein the switching thread information according to a plurality of first services, a plurality of first contents switching loss information, the second service switching thread information and the second content Switching loss information, and determining a first data integration strategy for integrating service content data for multiple big data network services activated by the front-end service interaction devices, including:

constructing multiple network service interaction scenarios for big data network services activated by multiple front-end service interaction devices based on multiple first service switching thread information and multiple first content switching loss information;

For each network service interaction scenario, determine a fifth usage heat comparison result between the data usage heat of the text data distribution information corresponding to the network service interaction scenario and the data usage heat of the image data distribution information;

Based on the second service switching thread information and the second content switching loss information, determine the difference between the data usage intensity of the text data distribution information corresponding to the second service switching thread information and the data usage intensity of the image data distribution information Sixth, use the heat comparison results;

Selecting the network service interaction scene corresponding to the fifth use degree comparison result with the largest data correlation with the sixth use degree comparison result as the target network service interaction scene;

Determine the seventh use heat comparison result of the data use heat of the text data distribution information corresponding to the target network service interaction scenario and the data use heat of the text data distribution information corresponding to the second service switching thread information, the target network service an eighth comparison result of the data usage intensity of the image data distribution information corresponding to the interactive scene and the data usage intensity of the image data distribution information corresponding to the second service switching thread information;

Determine the big data network services activated for the plurality of front-end service interaction devices based on the comparison result of the seventh usage degree and the eighth usage degree comparison result corresponding to the usage degree with more data scene tags The first data integration strategy for business content data integration;

Preferably, generating a data integration result corresponding to the big data network service activated by the front-end service interaction device according to the first network service interaction content and the first data integration strategy includes:

Taking the target network service interaction scene as a front-end service interaction scene corresponding to the big data network services activated by the plurality of front-end service interaction devices, and using the first data integration strategy to perform the first network service interaction content analysis. Business content data integration;

A data integration result corresponding to a plurality of big data network services activated by the front-end service interaction device is generated according to the front-end service interaction scene and the first network service interaction content after service content data integration.

8. The method according to claim 3, characterized in that, when an associated network service is run in the backend service switching thread, the method further comprises:

Acquire the second network service interaction content of the associated network service, wherein the second network service interaction content includes the data usage popularity of the text data distribution information of the associated network service and the image data distribution information of the associated network service data usage heat;

According to the first service switching thread information, the first content switching loss information, the second service switching thread information, the second content switching loss information, and the second network service interaction content, determine whether to A second data integration strategy for integrating the business content data by the big data network service activated by the front-end business interaction device;

According to the first network service interaction content and the second data integration strategy, a data integration result corresponding to the big data network service activated by the front-end service interaction device is generated.

9. The method according to claim 4, characterized in that, when the associated network service is executed in the backend service switching thread, the method further comprises:

determining, according to the interactive content of the second network service and the switching loss of the second content, the running state information and thread label information of the backend service switching thread occupied by the associated network service;

According to multiple pieces of the first service switching thread information, multiple pieces of the first content switching loss information, the second service switching thread information, the second content switching loss information, the running state information and thread label information of the back-end service switching thread, and determine a third data integration strategy for integrating the business content data of the big data network service activated by the front-end service interaction device and the associated network service;

According to the first network service interaction content and the third data integration strategy, a data integration result corresponding to the big data network service activated by the front-end service interaction device is generated.

10. A big data server, comprising a processing engine, a network module and a memory; the processing engine and the memory communicate through the network module, and the processing engine reads a computer program from the memory and run to perform the method of any one of claims 1-9.