Data processing method and device, computer equipment and storage medium

Abstract

The invention relates to a data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a to-be-processed data set from a request subject; splitting the to-be-processed data set according to the data types of the multiple pieces of request data in the to-be-processed data set; synchronizing the split data set to be processed to a plurality of response main bodies corresponding to the request main body; selecting one response main body from the plurality of response main bodies as a current response main body, and switching another response main body as a new current response main body under the condition that the current response main body has a fault; and indicating the current response subject to perform data processing on the to-be-processed data set. By adopting the method, complex enterprise data can be flexibly processed.

Description

Technical Field

[0001] The present application relates to the technical field of big data processing, and in particular to a data processing method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] At present, a single-server model is usually used for the management of enterprise data. However, if the enterprise data center is invaded by a virus or the computer room is destroyed due to a natural disaster, normal services cannot be provided, resulting in the leakage of enterprise data, etc., which cannot meet the needs of enterprise operations. In addition, the current single-server model cannot manage massive amounts of enterprise data in an orderly manner.

[0003] To address this situation, the related technology uses a redundant server solution for data response. However, the pre-set redundant servers can only provide directional protection for data management, and the flexibility of processing data is poor, which is not suitable for the current complex enterprise data management needs. Summary of the invention

[0004] Based on this, it is necessary to provide a data processing method, device, computer equipment, computer-readable storage medium and computer program product that can flexibly process complex enterprise data in response to the above technical problems.

[0005] In a first aspect, the present application provides a data processing method, comprising:

[0006] Get the dataset to be processed from the request body;

[0007] Splitting the data set to be processed according to data types of multiple request data in the data set to be processed;

[0008] Synchronizing the split data set to be processed to multiple response bodies corresponding to the request body;

[0009] Selecting one of the response subjects from the multiple response subjects as a current response subject, and switching another of the response subjects as a new current response subject when the current response subject fails;

[0010] Instruct the current response body to perform data processing on the data set to be processed.

[0011] In one embodiment, the data type includes an exclusive type and a shared type; and the step of splitting the data set to be processed according to the data types of the plurality of request data in the data set to be processed includes:

[0012] Splitting the request data of each exclusive type into a data slice;

[0013] The request data of the shared type is distributed to each of the data slices.

[0014] In one embodiment, before splitting the data set to be processed according to the data types of the plurality of request data in the data set to be processed, the method further comprises:

[0015] Extracting data keyword information of a plurality of request data from the data set to be processed;

[0016] The data type of the current requested data is determined according to the data keyword information.

[0017] In one of the embodiments, when the current response subject fails, switching another response subject as a new current response subject includes:

[0018] In the event that the current response body fails, intercepting a data stream corresponding to the to-be-processed data set sent to the current response body;

[0019] Stripping application data associated with the data set to be processed from the current response body;

[0020] Another of the response bodies is selected as a new current response body, and the data stream corresponding to the data set to be processed is sent to the new current response body.

[0021] In one embodiment, after stripping the application data associated with the data set to be processed in the current response body, the method further includes:

[0022] storing the application data separately;

[0023] The data source of the application data is marked.

[0024] In one embodiment, before synchronizing the split data set to be processed to the multiple response bodies corresponding to the request body, the method further includes:

[0025] In the case where a response subject corresponding to the request subject is not selected, obtaining subject keyword information of the request subject;

[0026] Determine the location information of the request subject according to the subject keyword information;

[0027] A plurality of response bodies corresponding to the request body are selected according to the location information.

[0028] In a second aspect, the present application further provides a data processing device, comprising:

[0029] A data acquisition module, used to acquire the data set to be processed from the request body;

[0030] A data splitting module, used for splitting the data set to be processed according to the data types of multiple request data in the data set to be processed;

[0031] A data synchronization module, used for synchronizing the split data set to be processed to multiple response bodies corresponding to the request body;

[0032] A subject switching module, used for selecting one of the multiple response subjects as the current response subject, and switching another response subject as the new current response subject when the current response subject fails;

[0033] The data processing module is used to instruct the current response body to perform data processing on the data set to be processed.

[0034] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0035] Get the dataset to be processed from the request body;

[0036] Splitting the data set to be processed according to data types of multiple request data in the data set to be processed;

[0037] Synchronizing the split data set to be processed to multiple response bodies corresponding to the request body;

[0038] Selecting one of the response subjects from the multiple response subjects as a current response subject, and switching another of the response subjects as a new current response subject when the current response subject fails;

[0039] Instruct the current response body to perform data processing on the data set to be processed.

[0040] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0041] Get the dataset to be processed from the request body;

[0042] Splitting the data set to be processed according to data types of multiple request data in the data set to be processed;

[0043] Synchronizing the split data set to be processed to multiple response bodies corresponding to the request body;

[0044] Selecting one of the response subjects from the multiple response subjects as a current response subject, and switching another of the response subjects as a new current response subject when the current response subject fails;

[0045] Instruct the current response body to perform data processing on the data set to be processed.

[0046] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0047] Get the dataset to be processed from the request body;

[0048] Splitting the data set to be processed according to data types of multiple request data in the data set to be processed;

[0049] Synchronizing the split data set to be processed to multiple response bodies corresponding to the request body;

[0050] Selecting one of the response subjects from the multiple response subjects as a current response subject, and switching another of the response subjects as a new current response subject when the current response subject fails;

[0051] Instruct the current response body to perform data processing on the data set to be processed.

[0052] The above-mentioned data processing method, device, computer equipment, storage medium and computer program product obtain the data set to be processed from the request subject, take the data set to be processed as the target enterprise data that needs to be flexibly processed, split the data set to be processed according to the data type of multiple request data in the data set to be processed, thereby sorting the data set to be processed according to the data type, and then synchronize the split data set to the multiple response subjects corresponding to the request subject, so that each response subject can obtain the relevant information of the data set to be processed with consistent data sharding, and ensure that the flexibly allocated response subject can keep in sync with other response subjects. Next, select a response subject from the multiple response subjects as the current response subject, and in the event of a failure in the current response subject, switch another response subject as the new current response subject, thereby instructing the current response subject to process the data set to be processed. Therefore, when the current response subject fails, another response subject can be flexibly switched to ensure the stability of data processing, and the new response subject does not need to be preset in advance according to its corresponding request subject, and can flexibly process the data processing of complex enterprise data. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 An application environment diagram of a data processing method in an embodiment;

[0055] Figure 2 is a flow chart of a data processing method in one embodiment;

[0056] Figure 3 This is a flow chart of step S208 of a data processing method in an embodiment;

[0057] Figure 4 is a flow chart of a data processing method in another embodiment;

[0058] Figure 5 is a structural block diagram of a data processing device in one embodiment;

[0059] Figure 6 is an internal structure diagram of a computer device in one embodiment;

[0060] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0062] The data processing method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the cloud platform 104 through the network. The terminal 102 can send a data analysis and processing request to the server controlled by the cloud platform 104 as a request subject, and the cloud platform 104 allocates a server as a response device to receive the data set to be processed from the terminal 102. The data storage system can store the data that the cloud platform 104 needs to process. The data storage system can be integrated on the cloud platform 104, or it can be placed on the cloud or other network servers. The data storage system can be used to store relevant information of multiple response subjects, such as subject keyword information, location information, etc., and can also be used to store data such as data keyword information. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The cloud platform 104 and the server can be implemented with an independent server or a server cluster consisting of multiple servers.

[0063] In an exemplary embodiment, Figure 2 As shown, a data processing method is provided, which is applied to Figure 1 Taking the cloud platform 104 in FIG. 1 as an example, the method includes the following steps S202 to S206. Among them:

[0064] Step S202: Obtain the data set to be processed from the request subject.

[0065] The request subject may be a terminal device of the target enterprise. For example, when the target enterprise needs to analyze enterprise data, the terminal 102 may send a data set to be processed to the server.

[0066] The data set to be processed may include basic enterprise information, enterprise promotion information, etc. The basic enterprise information may include enterprise location, enterprise category, etc.

[0067] Step S204: split the data set to be processed according to the data types of the multiple request data in the data set to be processed.

[0068] Exemplarily, the data set to be processed may include content of different categories, and different data type division methods will result in data types of different dimensions. For example, if the cloud platform 104 divides data types according to how the data is used, the data types can be divided into exclusive data and shared data; if the cloud platform 104 divides data types according to the regularity of the data, the data types can be divided into regular data and irregular data; if the cloud platform 104 divides data types according to the structure of the data, the data types can be divided into structured data and unstructured data, etc.

[0069] The data types may include exclusive types and shared types. Exclusive data refers to user-related data, such as account information, order information, etc. This part of data is exclusive to the user and can be determined as exclusive data. When the cloud platform 104 splits the data set to be processed, the exclusive data of a certain user is split into a shard; shared data refers to data shared by all users, such as configuration information, product information, label information, and index information. This part of data can be determined as shared data. When the cloud platform 104 splits the data set to be processed, each shard must contain the full amount of shared data.

[0070] Exemplarily, the cloud platform 104 can upload the data set to be processed to the cloud platform, use the cloud platform to divide the data usage form, determine exclusive data and shared data, and then split each exclusive type of request data into a data shard, and distribute the shared type of request data to each data shard to form a split data set to be processed.

[0071] Exemplarily, before splitting the data set to be processed according to the data types of the multiple request data in the data set to be processed, the cloud platform 104 may also extract data keyword information of the multiple request data in the data set to be processed, and determine the data type of the current request data according to the data keyword information.

[0072] Exemplarily, when splitting the data set to be processed, the cloud platform 104 can perform the above-mentioned data splitting based on the data keyword information of these data, such as account information, which is usually in the form of account name + password, such as order information, which usually includes time, order content, etc. The cloud platform 104 can divide the enterprise data according to these characteristic information and then perform the above-mentioned data splitting.

[0073] Step S206: synchronize the split data sets to be processed to multiple response bodies corresponding to the request body.

[0074] For example, the cloud platform 104 can synchronize the split data set to be processed to each server in the multi-active architecture in the form of broadcast. Specifically, the cloud platform 104 can split the data into exclusive data and shared data based on the data to be processed corresponding to a specific user using the user ID, and then perform secondary division and storage on the data in the database according to the user ID.

[0075] According to the above storage method, when the current server fails or cannot meet the current data processing needs, the servers can be expanded from 2 to 3. It is only necessary to route the user traffic to the new server according to the shards and migrate the corresponding shard tables. There is no need to split and merge the data. That is, the data originally stored in server A can be migrated in an orderly manner in the form of tables. If splitting and merging are required, even if the migrated data can be stored in an orderly manner, it will not cause confusion to the orderly storage of the data in server B.

[0076] Step S208: Select a response subject from the multiple response subjects as the current response subject, and switch another response subject as the new current response subject when the current response subject fails.

[0077] For example, when a server in a multi-active architecture fails, the cloud platform 104 can switch the pending data and services of the current server to be processed to another server that meets the requirements for execution. That is, when a server that the terminal wants to access fails, it can be switched to another server without being noticed to provide the corresponding service, ensuring that the access of the terminal 102 can be executed smoothly and that the enterprise data can be fed back to the terminal 102 in a timely manner.

[0078] Step S210, instructing the current response subject to perform data processing on the data set to be processed.

[0079] For example, when the terminal 102 initiates access to the current server, the cloud platform 104 can monitor the response time of the server. When the response time exceeds the set time threshold, it is determined that the server has failed, and the terminal's access service needs to be switched to another server for execution. Furthermore, the cloud platform 104 can select a new response subject based on the principle of proximity or load balancing, and can also select a new response subject based on the failure rate of the server and other principles.

[0080] In the above data processing method, by obtaining the data set to be processed from the request subject, the data set to be processed is used as the target enterprise data that needs to be flexibly processed, and the data set to be processed is split according to the data type of multiple request data in the data set to be processed, so that the data set to be processed is sorted according to the data type, and then the split data set to be processed is synchronized to the multiple response subjects corresponding to the request subject, so that each response subject can obtain the relevant information of the data set to be processed with consistent data sharding, and ensure that the flexibly allocated response subject can keep in sync with other response subjects. Next, a response subject is selected from multiple response subjects as the current response subject, and in the case of a failure in the current response subject, another response subject is switched as the new current response subject, thereby instructing the current response subject to process the data set to be processed. Therefore, when the current response subject fails, another response subject can be flexibly switched to ensure the stability of data processing, and the new response subject does not need to be preset in advance according to its corresponding request subject, and can flexibly process the data processing of complex enterprise data. Therefore, the above method can build different multi-active architectures according to different enterprises, and divide the existing enterprise data, and orderly arrange them in each server of the multi-active architecture. When a server failure occurs, it can be switched to other servers without perception to provide services.

[0081] In an exemplary embodiment, Figure 3 As shown, step S208 includes steps S302 to S306. Among them:

[0082] Step S302: when a fault occurs in the current response body, intercept the data stream corresponding to the to-be-processed data set sent to the current response body.

[0083] Exemplarily, in the event that a current response subject fails, the cloud platform 104 may instruct the current response subject to stop processing the data set to be processed, and stop the terminal 102 from sending the corresponding data stream to the failed response subject.

[0084] Step S304: stripping the application data associated with the data set to be processed in the current response body.

[0085] Exemplarily, after stripping the application data associated with the data set to be processed in the current response body, the cloud platform 104 may also store the application data separately and mark the data source of the application data.

[0086] Exemplarily, the cloud platform 104 can configure the database information of the data to be stripped in the server, configure the filtering conditions of the associated database of the database, strip the application data from the database information and the filtered associated database according to the characteristics of the application status data, and store it separately in an area. The source of the application data, such as the location of the database, needs to be marked so that after the transfer is successful, the application data can be returned to its original location before the next access request is received.

[0087] Step S306: Select another response body as a new current response body, and send the data stream corresponding to the data set to be processed to the new current response body.

[0088] Exemplarily, the cloud platform 104 may configure traffic allocation rules, wherein the traffic allocation rules may include load balancing principles, proximity principles, etc. The cloud platform 104 may allocate the intercepted traffic to the corresponding new server for execution based on the traffic allocation rules.

[0089] In an exemplary embodiment, Figure 4 As shown, before step S206, steps S402 to S406 may also be included. Among them:

[0090] Step S402: if the response subject corresponding to the request subject is not selected, obtain subject keyword information of the request subject.

[0091] For example, different target enterprises may be located in different regions, and the cloud platform 104 may deploy servers in these regions to save time and cost in network data transmission. Specifically, the target enterprise may upload its requirements through the terminal 102, or extract and analyze keywords from the enterprise's promotional information to determine the regions involved by the enterprise.

[0092] Step S404: determining the location information of the request subject according to the subject keyword information.

[0093] Exemplarily, the cloud platform 104 can further determine the areas that the enterprise may be involved in the future, and determine the keywords of the enterprise's future layout from the enterprise's promotional information through keyword matching, such as place names, etc. The cloud platform 104 can also select the response subject based on the needs of the region, such as the greening rate, and then match these keywords with the characteristics of the region to determine the areas that may be deployed in the future.

[0094] Step S406: Select multiple response bodies corresponding to the request body according to the location information.

[0095] For example, the cloud platform 104 can deploy multiple data centers in the regions involved based on the principle of proximity and economic principles to build a multi-active architecture dedicated to the enterprise. When building a multi-active architecture, the network requirements for data transmission are considered. In this embodiment, the cloud platform 104 can be used for data scheduling and operation and maintenance, and the cloud platform can be used as a middleware for data synchronization and other tasks.

[0096] Furthermore, there can be multiple cloud platforms 104. According to the distance between area A and area B, one cloud platform can be set in each of the two areas, and another cloud platform can be set in the middle of the two areas to form a tree structure, which can solve the problem of network transmission.

[0097] In an exemplary embodiment, when a data center of the cloud platform 104 is unavailable, the service needs to be allocated to another data center through traffic allocation, and the destination data center needs to have the same data as the source data center. Before the service is allocated, the cloud platform 104 needs to back up the data of the original server to the allocated server, and the cloud platform 104 can determine the data that is different from the allocated server and back up the data to the server.

[0098] Furthermore, the cloud platform 104 can also authenticate the permissions of the server to ensure that there will be no harm to the allocated server. The cloud platform 104 determines whether the data in the backup process of the failed server conflicts with its own stored data. For example, the data stored by itself is not allowed to access the underlying information, while the data in the backup process is allowed to access the underlying information. In this case, the server can refuse to be accessed.

[0099] In another exemplary embodiment, for the newly added data continuously generated by the enterprise, the cloud platform 104 can manage the data according to the data characteristics to ensure that the management mode of the newly added data is consistent with the management mode of the historical data, and avoid confusion in the storage of data. Specifically, the cloud platform 104 can analyze the newly added data, determine the data characteristics, and then determine the type of data. The cloud platform 104 can extract the keywords of the newly added data, input the keywords into the trained model, and determine the type of data. The trained model is formed by training the classifier using a sample set formed by matching the keywords with the corresponding types one by one. The above types need to correspond one by one to the types previously divided, such as exclusive data or shared data, structured data or unstructured data, so as to ensure the orderly management of the data. Next, the cloud platform 104 can use the cloud platform to store the data in a certain area of ​​the server, and store the data in the corresponding area according to the above-mentioned shard storage method.

[0100] In another exemplary embodiment, the cloud platform 104 can expand the multi-active architecture when adding new servers to cope with the increase in the amount of enterprise data, and can consider the expansion of servers, which can be the expansion of remote servers or the expansion of the area where the existing servers are located. Specifically, the cloud platform 104 first determines the reason for the expansion of the response subject, such as the increase in the areas to be involved in the enterprise, the increase in the amount of data in the existing areas, etc. The former reason requires the installation of servers in new areas, and the latter reason requires the installation of additional servers in existing areas. Subsequently, the cloud platform 104 deploys new servers in the areas where expansion is required.

[0101] Furthermore, if the newly deployed server is added in an existing area, the cloud platform 104 can only share the data of other servers in the area; if a server is added in a new area, the cloud platform 104 can broadcast the data through the cloud platform; if the newly added server is far away from the current cloud platform 104, a new cloud platform can be added first according to the tree principle, and then the corresponding server can be added to ensure the real-time data transmission.

[0102] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0103] Based on the same inventive concept, the embodiment of the present application also provides a data processing device for implementing the data processing method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more data processing device embodiments provided below can refer to the limitations on the data processing method above, and will not be repeated here.

[0104] In an exemplary embodiment, Figure 5 As shown, a data processing device is provided, including: a data acquisition module 502, a data splitting module 504, a data synchronization module 506, a subject switching module 508 and a data processing module 510, wherein:

[0105] The data acquisition module 502 is used to acquire the data set to be processed from the request subject;

[0106] A data splitting module 504 is used to split the data set to be processed according to the data types of the multiple request data in the data set to be processed;

[0107] A data synchronization module 506 is used to synchronize the split data set to be processed to multiple response bodies corresponding to the request body;

[0108] A subject switching module 508 is used to select a response subject from multiple response subjects as a current response subject, and switch another response subject as a new current response subject when a failure occurs in the current response subject;

[0109] The data processing module 510 is used to instruct the current response subject to perform data processing on the data set to be processed.

[0110] In one embodiment, the data type includes an exclusive type and a shared type; the data splitting module 504 is specifically used to: split each exclusive type request data into a data slice; and distribute the shared type request data to each data slice.

[0111] In one embodiment, the device further comprises:

[0112] A keyword extraction module is used to extract data keyword information of multiple request data in the data set to be processed;

[0113] The type determination module is used to determine the data type of the current request data based on the data keyword information.

[0114] In one embodiment, the subject switching module 508 includes:

[0115] A data interception unit, used to intercept the data stream corresponding to the to-be-processed data set sent to the current response body in the event that a failure occurs in the current response body;

[0116] A data stripping unit, used for stripping application data associated with the data set to be processed in the current response body;

[0117] The subject switching unit is used to select another response subject as a new current response subject and send the data stream corresponding to the data set to be processed to the new current response subject.

[0118] In one embodiment, the subject switching module 508 further includes:

[0119] A data storage unit, used for storing application data separately;

[0120] The data annotation unit is used to annotate the data source of the application data.

[0121] In one embodiment, the device further comprises:

[0122] A subject analysis module, used for obtaining subject keyword information of a request subject when a response subject corresponding to a request subject is not selected;

[0123] A location determination module, used to determine the location information of the request subject according to the subject keyword information;

[0124] The subject selection module is used to select multiple response subjects corresponding to the request subject according to the location information.

[0125] Each module in the above data processing device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0126] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant information of multiple response subjects, such as subject keyword information, location information, etc., and can also be used to store data such as data keyword information. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data processing method is implemented.

[0127] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a data processing method is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0128] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0129] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining a data set to be processed from a request subject; splitting the data set to be processed according to the data types of multiple request data in the data set to be processed; synchronizing the split data set to be processed to multiple response subjects corresponding to the request subject; selecting a response subject from the multiple response subjects as the current response subject, and switching another response subject as the new current response subject when the current response subject fails; and instructing the current response subject to perform data processing on the data set to be processed.

[0130] In one embodiment, when the processor executes the computer program, the following steps are further implemented: splitting each exclusive type of request data into a data slice; and allocating the shared type of request data to each data slice.

[0131] In one embodiment, when the processor executes the computer program, the following steps are also implemented: extracting data keyword information of multiple request data in the data set to be processed; and determining the data type of the current request data according to the data keyword information.

[0132] In one embodiment, when the processor executes the computer program, the following steps are also implemented: in the event that a current response body fails, the data stream corresponding to the data set to be processed sent to the current response body is intercepted; the application data associated with the data set to be processed in the current response body is stripped; another response body is selected as the new current response body, and the data stream corresponding to the data set to be processed is sent to the new current response body.

[0133] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: storing the application data separately; and marking the data source of the application data.

[0134] In one embodiment, when the processor executes the computer program, the following steps are also implemented: when a response subject corresponding to the request subject is not selected, obtaining subject keyword information of the request subject; determining location information of the request subject based on the subject keyword information; and selecting multiple response subjects corresponding to the request subject based on the location information.

[0135] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining a data set to be processed from a request subject; splitting the data set to be processed according to the data types of multiple request data in the data set to be processed; synchronizing the split data set to be processed to multiple response subjects corresponding to the request subject; selecting a response subject from the multiple response subjects as the current response subject, and switching another response subject as the new current response subject when the current response subject fails; and instructing the current response subject to perform data processing on the data set to be processed.

[0136] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: splitting each exclusive type of request data into a data slice; and allocating the shared type of request data to each data slice.

[0137] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: extracting data keyword information of multiple request data in the data set to be processed; and determining the data type of the current request data according to the data keyword information.

[0138] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: in the event that a current response body fails, intercepting a data stream corresponding to the data set to be processed that is sent to the current response body; stripping the application data associated with the data set to be processed in the current response body; selecting another response body as a new current response body, and sending the data stream corresponding to the data set to be processed to the new current response body.

[0139] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: storing the application data separately; and marking the data source of the application data.

[0140] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when a response subject corresponding to the request subject is not selected, obtaining subject keyword information of the request subject; determining location information of the request subject based on the subject keyword information; and selecting multiple response subjects corresponding to the request subject based on the location information.

[0141] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0142] Obtain the data set to be processed from the request body; split the data set to be processed according to the data types of multiple request data in the data set to be processed; synchronize the split data set to be processed to multiple response bodies corresponding to the request body; select a response body from the multiple response bodies as the current response body, and switch another response body as the new current response body when the current response body fails; instruct the current response body to process the data set to be processed.

[0143] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: splitting each exclusive type of request data into a data slice; and allocating the shared type of request data to each data slice.

[0144] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: extracting data keyword information of multiple request data in the data set to be processed; and determining the data type of the current request data according to the data keyword information.

[0145] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: in the event that a current response body fails, intercepting a data stream corresponding to the data set to be processed that is sent to the current response body; stripping the application data associated with the data set to be processed in the current response body; selecting another response body as a new current response body, and sending the data stream corresponding to the data set to be processed to the new current response body.

[0146] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: storing the application data separately; and marking the data source of the application data.

[0147] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: when a response subject corresponding to the request subject is not selected, obtaining subject keyword information of the request subject; determining location information of the request subject based on the subject keyword information; and selecting multiple response subjects corresponding to the request subject based on the location information.

[0148] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0149] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0150] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0151] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A data processing method, characterized in that: The method comprises: Get the dataset to be processed from the request body; Splitting the data set to be processed according to data types of multiple request data in the data set to be processed; Synchronizing the split data set to be processed to multiple response bodies corresponding to the request body; Selecting one of the response subjects from the multiple response subjects as a current response subject, and switching another of the response subjects as a new current response subject when the current response subject fails; Instruct the current response body to perform data processing on the data set to be processed.

2. The method according to claim 1, characterized in that: The data type includes an exclusive type and a shared type; and the step of splitting the data set to be processed according to the data types of the plurality of request data in the data set to be processed includes: Splitting the request data of each exclusive type into a data slice; The request data of the shared type is distributed to each of the data slices.

3. The method according to claim 1, characterized in that Before splitting the data set to be processed according to the data types of the plurality of request data in the data set to be processed, the method further comprises: Extracting data keyword information of a plurality of request data from the data set to be processed; The data type of the current requested data is determined according to the data keyword information.

4. The method according to claim 1, characterized in that: When the current response subject fails, switching another response subject as a new current response subject includes: In the event that the current response body fails, intercepting a data stream corresponding to the to-be-processed data set sent to the current response body; Stripping application data associated with the data set to be processed from the current response body; Another of the response bodies is selected as a new current response body, and the data stream corresponding to the data set to be processed is sent to the new current response body.

5. The method according to claim 4, characterized in that After stripping the application data associated with the to-be-processed data set in the current response body, the method further includes: storing the application data separately; The data source of the application data is marked.

6. The method according to any one of claims 1 to 5, characterized in that: Before synchronizing the split data set to be processed to the multiple response bodies corresponding to the request body, the method further includes: In the case where a response subject corresponding to the request subject is not selected, obtaining subject keyword information of the request subject; Determine the location information of the request subject according to the subject keyword information; A plurality of response bodies corresponding to the request body are selected according to the location information.

7. A data processing device, characterized in that: The device comprises: A data acquisition module, used to acquire the data set to be processed from the request body; A data splitting module, used for splitting the data set to be processed according to the data types of multiple request data in the data set to be processed; A data synchronization module, used for synchronizing the split data set to be processed to multiple response bodies corresponding to the request body; A subject switching module, used for selecting one of the multiple response subjects as the current response subject, and switching another response subject as the new current response subject when the current response subject fails; The data processing module is used to instruct the current response body to perform data processing on the data set to be processed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images