Data processing method, medium and program product
By employing data processing methods and pre-defined database structures, the problem of data being difficult to present intuitively in the service industry has been solved, enabling efficient and flexible data display on different clients, thereby improving the efficiency of data display and user experience.
Patent Information
- Application Number
- CN202510677447.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-23
- Publication Date
- 2025-10-28
AI Technical Summary
In industries such as the service sector, the business-related data that is acquired and stored is difficult to present intuitively, resulting in low efficiency due to the time and effort spent manually sorting it out.
This paper provides a data processing method that responds to data display requests from clients, determines page display information based on client type, acquires and transforms business behavior data, and utilizes multi-threaded asynchronous methods combined with a preset database structure to achieve efficient and flexible data display.
It enables efficient, convenient, and intuitive data display on different clients, adapts to different client types, and improves the flexibility and efficiency of data display.
Smart Images
Figure CN120849461A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of computer technology, and in particular to a data processing method, medium, and program product. Background Technology
[0002] In industries such as service, large amounts of business-related data are typically acquired and stored. Data related to specific objects is often difficult to present intuitively and requires significant human time and effort to organize. For instance, if a real estate agent wants to better serve a client, they usually need to spend considerable time and effort searching for and organizing relevant client information from the system database, which is inefficient. Summary of the Invention
[0003] To solve the above-mentioned technical problems, or at least partially solve them, this disclosure provides a data processing method, medium, and program product.
[0004] This disclosure provides a data processing method, the method comprising: responding to receiving a data display request from a target client, determining page display information corresponding to the target client based on the type of the target client; wherein the data display request is used to request the display of business behavior data of a target object, and the page display information includes a page display style and display data constraint information; acquiring the business behavior data of the target object, and determining target display data corresponding to the business behavior data based on the display data constraint information; and displaying the page through the target client based on the page display style and the target display data.
[0005] Optionally, determining the page display information corresponding to the target client based on the type of the target client includes: selecting a target processing instance corresponding to the target client from a set of preset data processing instances based on the type of the target client; and generating the page display information corresponding to the target client through the target processing instance.
[0006] Optionally, the preset multiple data processing instances are obtained in the following way: based on a preset data processing base class, data processing derivative classes corresponding to each of the preset multiple client types are obtained; wherein, the data processing base class is used to provide general logic for generating page display information, and the data processing derivative classes are used to provide personalized logic adapted to the client types corresponding to the data processing derivative classes according to the general logic; and the multiple data processing instances are obtained by instantiating the data processing derivative classes corresponding to each of the multiple client types.
[0007] Optionally, the business behavior data includes data of multiple business behavior types, and obtaining the business behavior data of the target object includes: for each business behavior type, calling the processing instance corresponding to that business behavior type to obtain the business behavior data of the target object corresponding to that business behavior type.
[0008] Optionally, the processing instances corresponding to the various business behavior types are invoked based on a multi-threaded asynchronous method.
[0009] Optionally, the method further includes: converting the acquired business behavior data corresponding to the various business behavior types according to a specified format.
[0010] Optionally, obtaining the business behavior data of the target object corresponding to the business behavior type includes: obtaining the business behavior data of the target object corresponding to the business behavior type from a preset target database; wherein, the target database contains business behavior data corresponding to multiple service objects.
[0011] Optionally, the target database is established as follows: N data tables are preset; where N is a preset positive integer greater than 1; for each service object among multiple service objects, the target data table corresponding to the service object is determined from the N data tables using the remainder between the service object's numerical identifier and N, and the service object's business behavior data is stored in the target data table corresponding to the service object; the target database is established based on the service object's business behavior data stored in each of the N data tables.
[0012] This disclosure also provides a computer-readable storage medium storing a computer program for performing the data processing method provided in this disclosure.
[0013] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the data processing method provided in this disclosure.
[0014] The technical solution provided in this disclosure, upon receiving a data display request from a target client (for requesting the display of business behavior data of a target object), can determine the page display information (page display style and display data constraint information) corresponding to the target client based on the type of the target client, obtain the business behavior data of the target object, and further determine the target display data corresponding to the business behavior data based on the display data constraint information. Thus, based on the page display style and the target display data, the page is displayed through the target client. This method allows for targeted display of requested data on the client based on the client type, which is not only efficient and convenient but also clear and intuitive, adaptable to different clients, and highly flexible.
[0015] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description
[0016] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.
[0017] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 A flowchart illustrating a data processing method provided in an embodiment of this disclosure;
[0019] Figure 2 This is a schematic diagram of a data processing architecture provided in an embodiment of the present disclosure;
[0020] Figure 3 A schematic diagram of database construction provided in an embodiment of this disclosure;
[0021] Figure 4 A schematic diagram of an interface provided for an embodiment of this disclosure;
[0022] Figure 5 This is a schematic diagram of the structure of a data processing apparatus provided in an embodiment of the present disclosure;
[0023] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation
[0024] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.
[0025] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.
[0026] Figure 1 This is a flowchart illustrating a data processing method provided in an embodiment of the present disclosure. The method can be executed by a data processing device, which can be implemented using software and / or hardware, and is generally integrated into an electronic device, such as a server or other device with processing capabilities. Figure 1 As shown, the method mainly includes the following steps S102 to S106:
[0027] Step S102: In response to receiving a data display request from the target client, determine the page display information corresponding to the target client based on the type of the target client; wherein, the data display request is used to request the display of the business behavior data of the target object, and the page display information includes the page display style and the display data constraint information.
[0028] In practical applications, users can initiate requests through a client. This disclosure does not limit the type of client; for example, the client type can be a PC (personal computer), an APP (application), or an H5 (HTML5) client, where H5 is short for HyperText Markup Language 5. It is understood that for a PC, users can access services or websites through a browser or a dedicated desktop application. PCs typically have larger screens and more powerful computing capabilities, enabling multitasking, and input devices include, but are not limited to, keyboards and mice, allowing for easy connection to various external devices, greater scalability, and more diverse interaction methods. For APPs, these are dedicated applications developed for mobile devices such as smartphones and tablets, offering greater flexibility, faster and more stable operation, and easier provision of personalized user experiences. For H5 clients, more complex and interactive web content can be created, with rich multimedia functions and cross-platform compatibility. These are just examples; other types of clients may exist in practical applications, which will not be described in detail here. This disclosure allows users to request the display of required data through different types of clients, providing greater flexibility. Specifically, the client type can be determined based on the content or format of the received data display request, and the page display information can be determined accordingly based on the client type. As mentioned above, different types of clients have their own characteristics, so the corresponding page display style and display data constraint information can be determined based on the client type.
[0029] In practical applications, a first correspondence between various client types and page display styles, and a second correspondence between various client types and display data constraint information can be pre-defined. Based on the target client type, the first and second correspondences can be determined efficiently and conveniently, thereby obtaining the page display information corresponding to the target client. In specific technical implementations, corresponding processing instances can also be set for different client types to obtain targeted page display information for various clients. The aforementioned page display styles include, but are not limited to, page size and layout information. The aforementioned display data constraint information includes, but is not limited to, display data content and / or display data type. For example, client 1 can display rich multimedia data such as specific animations, while client 2 may not display such multimedia data due to performance constraints. Similarly, client 2 can display a lot of text and image information, while client 3, due to screen limitations, only displays some key information in text form. Through this method, the corresponding page display information can be determined specifically for different client types, without restricting users to using a particular client and imposing constraints on them, while providing appropriate page display information regardless of the client used, effectively ensuring user experience.
[0030] This disclosure does not limit the target object; for example, the target object can be a customer to be served or an employee to be managed. The business behavior data of the target object can be business-related behavior data. This disclosure does not limit the business behavior data. Taking the real estate brokerage industry as an example, the target object is the customer. The target object's business behavior data can be the behavior related to house selection recorded from the moment the customer uses the house-viewing application, such as phone inquiries, online communication, house viewings, and transactions—the entire lifecycle of behavior trajectory data. Based on this business behavior data, it is easier for brokers to clearly understand the customer's situation, fully understand the customer's needs, and keep abreast of the customer's house-buying dynamics, thereby providing personalized services to the customer. Alternatively, the target object can also be a broker. In this case, the target object's business behavior data can be the broker's service behavior records for a specific customer, such as the broker's phone communication with the customer, online communication, sub-delegation, showing houses, follow-up and other maintenance behaviors, up to the completion of a transaction with the customer—the entire lifecycle of behavior trajectory data. Based on this business behavior data, it is easier to understand the broker's service to the customer and to more reasonably and objectively measure the broker's service quality. The above are all examples and should not be considered as limitations.
[0031] Step S104: Obtain the business behavior data of the target object, and determine the target display data corresponding to the business behavior data based on the display data constraint information.
[0032] In some specific implementations, all business behavior data of the target object can be retrieved from a pre-built database, and target display data can be extracted from the business behavior data based on display data constraint information. It is understood that for a certain type of business behavior data, some clients may only need to display the key text of the business behavior data, such as when a certain business behavior occurs, while other clients may further display the specific details of the business behavior data. Therefore, based on the display data constraint information, the target display data corresponding to the business behavior data can be determined so that it can be reasonably displayed on the corresponding clients and presented to the user.
[0033] Step S106: Based on the page display style and target display data, display the page through the target client.
[0034] In practical applications, the page display style and target display data can be sent to the target client, allowing the target client to display the page based on these settings. This method allows for targeted display of requested data directly to the client based on its type, offering high efficiency, convenience, clarity, and flexibility, while also being adaptable to different clients.
[0035] In order to effectively determine the page display information corresponding to different types of clients, in some implementations, the step of determining the page display information corresponding to the target client based on the type of the target client can be performed with reference to the following steps a and b:
[0036] Step a: Based on the type of the target client, select the target processing instance corresponding to the target client from a set of preset data processing instances. Specifically, the number of data processing instances is the same as the number of client types, and there is a one-to-one correspondence between the various data processing instances and the various clients. That is, a corresponding data processing instance can be set for each client type. For example, the preset data processing instances are obtained through the following steps (1) to (2):
[0037] Step (1): Based on the preset data processing base class, obtain the data processing derivative classes corresponding to the various preset client types; wherein, the data processing base class is used to provide general logic for generating page display information, and the data processing derivative class is used to provide personalized logic for adapting to the client type corresponding to the data processing derivative class according to the general logic.
[0038] In practical applications, a base data processing class (also known as a parent class) can be first defined, let's call it the `TraceProcessor` class. Derivative classes (also known as subclasses) inheriting from this base class can be defined for each client type, such as `PcProcessor` for PC, `AppProcessor` for APP, and `H5Processor` for H5. The base class provides general logic for generating page display information. This general logic can be represented by a general template or method, specifying how to generate the page display information and how to query, retrieve, and process the required data. Derivative classes can all use this general logic. However, since different clients have different page display styles, each derivative class can override specific methods in the general logic. These specific methods could be methods for handling page display styles, thus achieving the effect of different page display information for different clients. Understandably, if new client types are added later, only the specific methods mentioned above need to be overridden based on the general logic provided by the base class, which can reasonably and efficiently solve the adaptation problem between different platforms.
[0039] Step (2) instantiate the data processing derivative classes corresponding to the various client types to obtain various data processing instances.
[0040] In practical applications, the above data processing derived classes can be instantiated using a factory class to obtain data processing instances corresponding to different types of clients.
[0041] Step b: Generate the page display information corresponding to the target client through the target processing instance.
[0042] Using the above method, a target processing instance corresponding to the target client can be selected from a variety of preset data processing instances. Based on the personalized logic of the client, the page display information corresponding to the target client can be generated reasonably.
[0043] Considering that business behavior data may vary in type, such as customer application usage data, communication data between agents and customers, and viewing data, different data types exist. To efficiently intervene in and display different types of business behavior data, in some implementations, business behavior data includes data from multiple business behavior types. In specific implementations, the steps described above for obtaining the business behavior data of the target object can involve calling the corresponding processing instance for each business behavior type to obtain the business behavior data of the target object corresponding to that type. In other words, corresponding processor interfaces can be designed for different business behavior types, and these processor interfaces can be implemented through processing instances. The processing instances corresponding to the various business behavior types can be instantiated based on processing derivative classes (also called data acquisition derivative classes) corresponding to the various business behavior types. These processing derivative classes can all inherit from the data acquisition base class. This data acquisition base class can provide general logic for obtaining data and indicate the specific implementation method for obtaining the corresponding data. The specific acquisition method can be a database query. The processing instances corresponding to various business behavior types can be specifically queried for the corresponding business behavior type data. Afterwards, the obtained business behavior data corresponding to multiple business behavior types can be converted and processed according to a specified format. The specified format includes, for example, specified field names, the position of each specified field name, etc. For example, the business behavior data corresponding to different business behavior types may use different field names to identify time, behavior, etc. In order to facilitate unified processing later, the field names that identify time in the business behavior data corresponding to different business behavior types can be converted into specified time field names, and the field names that identify specific behaviors can also be converted into specified behavior field names, and presented in the format of "time field name: behavior field name".
[0044] To improve processing efficiency, the processing instances corresponding to the above-mentioned various business behavior types are called in a multi-threaded asynchronous manner. That is, the processing instances corresponding to the above-mentioned various business behavior types can obtain the corresponding business behavior data by using different threads. This parallel processing method can shorten the acquisition time of various business behavior data as much as possible, thereby achieving the goal of improving processing efficiency.
[0045] For easier understanding, please refer to Figure 2The diagram illustrates a data processing architecture that can generate data processing derivative classes for the APP, H5, and PC sides based on a data processing base class. It can also generate data acquisition derivative classes for business behavior type 1 to business behavior type n based on a data acquisition base class. A management class can be used to connect the data processing base class and the data acquisition base class. In practical applications, the data processing derivative classes for the APP, H5, and PC sides can be instantiated to obtain data processing instances for the APP, H5, and PC sides, respectively. Based on these instances, the corresponding page display information can be determined. Similarly, the data acquisition derivative classes for business behavior type 1 to business behavior type n can be instantiated to obtain data acquisition instances for various business behavior types. These data acquisition instances for each business behavior type are also the processing instances for that specific business behavior type, capable of acquiring the corresponding business behavior data.
[0046] In some implementations, obtaining the business behavior data of the target object corresponding to the business behavior type includes: obtaining the business behavior data of the target object corresponding to the business behavior type from a preset target database; wherein, the target database contains business behavior data corresponding to multiple service objects. For example, the target database is established through the following steps A to C:
[0047] Step A: Pre-determine N data tables; where N is a pre-defined positive integer greater than 1. The value of N can be flexibly set according to requirements; in some specific implementation examples, N = 100.
[0048] Step B involves determining the target data table corresponding to each service object from the N data tables using the remainder between the service object's numerical identifier and N, and then storing the service object's business behavior data in the target data table. In this example, the target object is also an object within the service objects, such as a customer. This embodiment of the disclosure can store data based on the service object dimension. For example, N = 100, meaning there are 100 data tables. The numerical identifier of the service object is the customer ID. The customer ID can be divided by 100, and the remainder plus a table prefix can determine the corresponding data table name, i.e., the target data table corresponding to the customer ID. Different data tables can have the same prefix, but different suffixes. For example, 100 data tables may all have the prefix "trace_data" and suffixes ranging from 0 to 99. If the remainder of a customer ID divided by 100 is 1, then the data table corresponding to that customer is named "trace_data_01". The customer's data can be stored in the data table named "trace_data_01". Subsequently, the customer's data can be retrieved directly from the data table named "trace_data_01" based on the customer ID.
[0049] By determining the corresponding data table for a customer by taking the remainder of the customer ID, the data of multiple service objects can be evenly distributed across multiple data tables. This ensures a balanced data volume across the tables, facilitates subsequent query processing, and improves data query efficiency.
[0050] Step C: Establish the target database based on the business behavior data of the service objects stored in each of the N data tables.
[0051] By employing the above method, problems such as excessive data volume and slow query speeds caused by using only a single data table to centrally store all service objects are avoided. Furthermore, in related technologies, even with multiple data tables, one table is typically filled before another is used for storage. This approach leads to uneven data distribution across different tables. The method adopted in this embodiment, however, can evenly store the data of multiple service objects across multiple data tables, thus improving subsequent query efficiency.
[0052] To ensure the comprehensiveness of business behavior data, in practical applications, the business behavior data stored in the target database is obtained through multiple pre-defined messaging channels. These messaging channels include, but are not limited to, the target system, third-party systems, designated databases, and user input. For example, data can be entered using the Dubbo API distributed service framework, a designated event center, or distributed messaging systems such as Kafka. In practical applications, business behavior data obtained from different messaging channels can also be processed uniformly according to a standard format, and the specific configuration can be flexibly adjusted.
[0053] For easier understanding, please refer to Figure 3 The diagram shown illustrates a database construction process where message channels 1 through M are all connected to the database. The database contains information such as business behavior data types, business behavior data content, time, extended information, write source, and object information. Figure 3 This is merely an illustrative example and is not intended to be limiting. In practical applications, data in a database can be standardized according to a specified format to facilitate storage and subsequent retrieval.
[0054] In summary, the data processing method provided in this disclosure can adapt and display business behavior data on different clients, and can efficiently and reliably access and display different types of business behavior data. Furthermore, it can efficiently query business behavior data through a reasonably designed database, ensuring that the data is presented on the client in a timely manner so that users can clearly and intuitively view the data they need. For example, see [link to relevant documentation]. Figure 4 The diagram shows a user interface that displays customer information, showing a customer's property viewing behavior data in chronological order. This allows agents to efficiently understand customer situations and provide better personalized services.
[0055] Corresponding to the aforementioned data processing method, this disclosure further provides a data processing apparatus. Figure 5 This is a schematic diagram of the structure of a data processing device provided in an embodiment of the present disclosure. The device can be implemented by software and / or hardware, and is generally integrated into an electronic device, such as... Figure 5 As shown, the data processing device includes:
[0056] The display information determination module 502 is used to respond to receiving a data display request from a target client and determine the page display information corresponding to the target client based on the type of the target client; wherein, the data display request is used to request the display of business behavior data of the target object, and the page display information includes page display style and display data constraint information;
[0057] The data determination module 504 is used to acquire the business behavior data of the target object and determine the target display data corresponding to the business behavior data based on the display data constraint information.
[0058] The client display module 506 is used to display the page through the target client based on the page display style and the target display data.
[0059] The aforementioned device allows for targeted display of requested data on the client based on the client type. This is not only efficient and convenient but also clear and intuitive, adaptable to different clients, and highly flexible.
[0060] In some implementations, the display information determination module 502 is specifically used to: select a target processing instance corresponding to the target client from a variety of preset data processing instances based on the type of the target client; and generate page display information corresponding to the target client through the target processing instance.
[0061] In some implementations, the preset multiple data processing instances are obtained as follows: based on a preset data processing base class, data processing derivative classes corresponding to each of the preset multiple client types are obtained; wherein, the data processing base class is used to provide general logic for generating page display information, and the data processing derivative classes are used to provide personalized logic adapted to the client types corresponding to the data processing derivative classes according to the general logic; and the multiple data processing instances are obtained by instantiating the data processing derivative classes corresponding to each of the multiple client types.
[0062] In some implementations, the business behavior data includes data of multiple business behavior types, and the data determination module 504 is specifically used to: for each business behavior type, call the processing instance corresponding to the business behavior type to obtain the business behavior data of the target object corresponding to the business behavior type.
[0063] In some implementations, the processing instances corresponding to the various business behavior types are invoked based on a multi-threaded asynchronous method.
[0064] In some embodiments, the apparatus further includes a format conversion module for converting the acquired business behavior data corresponding to the various business behavior types according to a specified format.
[0065] In some implementations, the data determination module 504 is specifically used to: obtain business behavior data of the target object corresponding to the business behavior type from a preset target database; wherein, the target database contains business behavior data corresponding to multiple service objects.
[0066] In some implementations, the target database is established as follows: N data tables are preset; where N is a preset positive integer greater than 1; for each service object among multiple service objects, the target data table corresponding to the service object is determined from the N data tables using the remainder between the service object's numerical identifier and N, and the service object's business behavior data is stored in the target data table corresponding to the service object; the target database is established based on the service object's business behavior data stored in each of the N data tables.
[0067] In some implementations, the business behavior data stored in the target database is obtained based on multiple preset messaging channels.
[0068] The data processing apparatus provided in this disclosure can execute the data processing method provided in any embodiment of this disclosure, and has the corresponding functional modules and beneficial effects for executing the method.
[0069] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described device embodiments can be referred to the corresponding process in the method embodiments, and will not be repeated here.
[0070] This disclosure provides an electronic device, which includes: a storage device storing a computer program thereon; and a processing device for executing the computer program in the storage device to implement the steps of any method of this disclosure.
[0071] The following is for reference. Figure 6 This diagram illustrates a structural schematic of an electronic device 600 suitable for implementing embodiments of the present disclosure. The terminal devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.
[0072] like Figure 6As shown, electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from storage device 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of electronic device 600. Processing device 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.
[0073] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 An electronic device 600 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.
[0074] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, it performs the functions defined in the methods of embodiments of this disclosure.
[0075] In addition to the methods and devices described above, embodiments of this disclosure can also be computer program products, comprising computer program instructions that, when executed by a processor, cause the processor to perform the methods provided in the embodiments of this disclosure. The computer program product can be written in any combination of one or more programming languages to perform the operations of the embodiments of this disclosure. These programming languages include object-oriented programming languages such as Java and C++, as well as conventional procedural programming languages such as C or similar languages. The program code can be executed entirely on a user computing device, partially on a user device, as a standalone software package, partially on a user computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0076] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the data processing method provided in embodiments of this disclosure.
[0077] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.
[0078] This disclosure also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the data processing method described in this disclosure.
[0079] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.
[0080] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.
[0081] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.
[0082] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.
[0083] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0084] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A data processing method, characterized in that, include: In response to receiving a data display request from a target client, page display information corresponding to the target client is determined based on the type of the target client; wherein, the data display request is used to request the display of business behavior data of the target object, and the page display information includes page display style and display data constraint information; Obtain the business behavior data of the target object, and determine the target display data corresponding to the business behavior data based on the display data constraint information; Based on the page display style and the target display data, the page is displayed through the target client.
2. The method according to claim 1, characterized in that, The step of determining the page display information corresponding to the target client based on the type of the target client includes: Based on the type of the target client, a target processing instance corresponding to the target client is selected from a variety of preset data processing instances; The target processing instance generates the page display information corresponding to the target client.
3. The method according to claim 2, characterized in that, The preset multiple data processing instances are obtained in the following way: Based on a preset data processing base class, data processing derivative classes corresponding to various preset client types are obtained; wherein, the data processing base class is used to provide general logic for generating page display information, and the data processing derivative classes are used to provide personalized logic adapted to the client type corresponding to the data processing derivative class according to the general logic. Based on the data processing derivative classes corresponding to the various client types, various data processing instances are obtained.
4. The method according to claim 1, characterized in that, The business behavior data includes data of various business behavior types, and obtaining the business behavior data of the target object includes: For each of the aforementioned business behavior types, the corresponding processing instance is invoked to obtain the business behavior data of the target object corresponding to that business behavior type.
5. The method according to claim 4, characterized in that, The processing instances corresponding to the various business behavior types are invoked based on a multi-threaded asynchronous method.
6. The method according to claim 4, characterized in that, The method further includes: The acquired business behavior data corresponding to the various business behavior types are converted and processed according to a specified format.
7. The method according to claim 4, characterized in that, The step of obtaining the business behavior data of the target object corresponding to the business behavior type includes: Retrieve business behavior data of the target object corresponding to the business behavior type from a preset target database; wherein, the target database contains business behavior data corresponding to multiple service objects.
8. The method according to claim 7, characterized in that, The target database was established in the following manner: There are N preset data tables; where N is a preset positive integer greater than 1. For each of the multiple service objects, the target data table corresponding to the service object is determined from the N data tables by using the remainder between the numerical identifier of the service object and N, and the business behavior data of the service object is stored in the target data table corresponding to the service object. A target database is established based on the business behavior data of the service objects stored in each of the N data tables.
9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for executing the data processing method described in any one of claims 1-8.
10. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the data processing method according to any one of claims 1-8.