Data exchange method, device and equipment, program product and storage medium

Abstract

The invention discloses a data exchange method, device and equipment, a program product and a storage medium, and relates to the technical field of big data. The method comprises the following steps: receiving each piece of shared data sent by a standard service platform at the current moment; determining a target processing moment of each piece of shared data according to predetermined data exchange demand information of a standard service platform, predetermined historical shared data state information of a personalized service platform, a current moment and a preset duration; for each piece of shared data, performing data type identification on the current shared data at the target processing moment corresponding to the current shared data to obtain the data type of the current shared data; performing data processing on the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data; and transmitting the target data corresponding to the shared data to a standard service platform. According to the invention, the computing resources of the personalized service platform can be reasonably allocated, and the data exchange efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and more particularly to a data exchange method, device, equipment, program product, and storage medium. Background Art

[0002] In the context of digital government services, in order to meet the needs of government service data sharing, government service platforms at all levels can directly exchange and share data. For example, the national government service platform can send some basic data used to support personalized government services at the provincial level to the provincial government service platforms, and the provincial government service platforms can send their business service data to the national government platform so that the national government service platform can summarize, analyze and monitor the business service data of the provincial government service platforms.

[0003] The current data exchange method between government service platforms only involves structured data such as database data, and cannot process unstructured data such as images. In addition, most government service platforms send shared data of various government services at a fixed cycle or time, and the government service platform that receives the shared data also processes the shared data and returns the data at a fixed time cycle. However, the service standards, scopes, and data volumes of each government service platform are different. This method is not flexible enough, resulting in uneven resource allocation when the government service platform processes data, delayed data return from the government service platform, or processing some data that does not need to be returned in real time, thereby squeezing the computing resources of data that needs to be processed in real time. Summary of the invention

[0004] The embodiments of the present invention provide a data exchange method, device, equipment, program product and storage medium, which can flexibly adjust the time for each personalized service platform to process shared data and reasonably allocate the computing resources of the personalized service platform, so that each personalized service platform can efficiently process structured shared data and unstructured shared data.

[0005] In a first aspect, an embodiment of the present invention provides a data exchange method, including:

[0006] Receive various shared data sent by the standard service platform at the current moment;

[0007] Determine the target processing time of each shared data according to the predetermined data exchange demand information of the standard service platform, the predetermined historical shared data status information of the personalized service platform, the current time and the preset duration;

[0008] For each of the shared data, at a target processing time corresponding to the current shared data, a data type of the current shared data is identified to obtain the data type of the current shared data; wherein the data type is structured data or unstructured data;

[0009] Performing data processing on the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data;

[0010] The target data corresponding to each of the shared data is transmitted to the standard service platform.

[0011] In a second aspect, an embodiment of the present invention further provides a data exchange device, the device comprising:

[0012] A data receiving module, used to receive various shared data sent by the standard service platform at the current moment;

[0013] A time determination module, used to determine the target processing time of each shared data according to the predetermined data exchange demand information of the standard service platform, the predetermined historical shared data status information of the personalized service platform, the current time and the preset duration;

[0014] A type determination module, for each of the shared data, identifying the data type of the current shared data at the target processing time corresponding to the current shared data, to obtain the data type of the current shared data; wherein the data type is structured data or unstructured data;

[0015] A data processing module, used for performing data processing on the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data;

[0016] The data transmission module is used to transmit the target data corresponding to each of the shared data to the standard service platform.

[0017] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a data exchange method as described in any one of the embodiments of the present invention is implemented.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the data exchange method as described in any one of the embodiments of the present invention.

[0019] In a fifth aspect, an embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the data exchange method as described in any one of the embodiments of the present invention.

[0020] In the embodiment of the present invention, the target exchange time is dynamically determined through the specific business attributes and historical exchange time of each shared data, so that the personalized service platform can give priority to the shared data that needs to be processed immediately, reasonably allocate the computing resources of the personalized service platform, and avoid the situation where the personalized service platform immediately processes the shared data that does not need to be processed immediately, thereby squeezing the computing resources of the shared data that needs to be processed immediately. Through data type identification, the personalized service platform can use different data processing methods to process different types of shared data in a timely and accurate manner, and update the business support data of the personalized service platform according to the processed shared data, so as to provide users with more reasonable and accurate business services in the future, and also facilitate the standard service platform to summarize, count and audit data according to the target data, thereby improving the efficiency of data exchange. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flow chart of a data exchange method provided by an embodiment of the present invention;

[0023] Figure 2 A flowchart for determining target data corresponding to structured data provided by an embodiment of the present invention;

[0024] Figure 3 A flowchart for determining target data corresponding to unstructured data provided by an embodiment of the present invention;

[0025] Figure 4 A schematic diagram of the structure of a data exchange device provided by an embodiment of the present invention;

[0026] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0028] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations. It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or must use the relevant content of the "solution".

[0029] Figure 1 A flowchart of a data exchange method provided in an embodiment of the present invention. The method in the embodiment of the present invention can flexibly adjust the time for each personalized service platform to process shared data, and reasonably allocate the computing resources of the personalized service platform, so that each personalized service platform can efficiently process structured shared data and unstructured shared data. The method can be executed by a data exchange device provided in an embodiment of the present invention, and the device can be implemented in software and / or hardware. The following embodiments will be described by taking the device integrated in an electronic device as an example. The electronic device can be a computer device or a server, etc. Reference Figure 1 , the method may specifically include the following steps:

[0030] Step 101: Receive various shared data sent by the standard service platform at the current moment.

[0031] Among them, the standard service platform is an integrated business service platform. The standard service platform can receive service data from various personalized service platforms and perform data processing on them. Data processing includes data aggregation, data review, data processing, data sharing and data exchange, etc. Shared data is the data that can be transmitted to each personalized service platform after the standard service platform processes the standard service data and the service data received from each personalized service platform. Shared data is used to support and constrain the personalized services provided by each personalized service platform.

[0032] In an optional implementation, when the personalized service platform needs to obtain shared data from the standard service platform, the personalized service platform can send a data request instruction to the standard service platform. After receiving the data request instruction, the standard service platform determines the shared data requested by the personalized service platform according to the data request instruction, and sends the shared data to the personalized service platform. Alternatively, the standard service platform generates new shared data during operation, and it is necessary to send the shared data to each personalized service platform in a timely manner, so that each personalized service platform can update the service data of its own platform in a timely manner according to the shared data, and provide users with accurate personalized services. After the standard service platform sends the shared data to the personalized service platform, the personalized service platform can receive the shared data sent by the standard service platform at the current moment in real time.

[0033] For example, the standard service platform records the service qualification information of a certain enterprise, including information such as the serviceable business and the validity period of the qualification. After the validity period of its qualification has expired, the enterprise promptly handles the business of updating the validity period in the standard service platform. After updating the service qualification information of the enterprise, the standard service platform generates shared data based on the updated service qualification information of the enterprise, and sends the shared data to the personalized service platform so that the personalized service platform can update the service qualification information of the enterprise in a timely manner, avoiding the situation where the user cannot handle the business related to the enterprise on the personalized service platform due to the information lag of the personalized service platform.

[0034] Step 102: determine the target processing time of each shared data according to the predetermined data exchange demand information of the standard service platform, the predetermined platform information of the personalized service platform, the historical shared data status information, the current time and the preset duration.

[0035] Among them, the data exchange demand information includes the business attribute field and exchange frequency range corresponding to each shared data. The business attribute field is used to mark the business attribute of each shared data. Business attributes include real-time update business, batch processing business, periodic update business and event-driven update business. Shared data belonging to real-time update business needs to exchange data in real time, shared data belonging to periodic update business needs to exchange data according to a predetermined period, and shared data belonging to event-driven update business needs to exchange data after the corresponding event occurs. The exchange frequency range corresponding to shared data with different business attributes is different. For example, the basic directory data of matters, electronic certificate directory data and basic matter handling data in the matters handled by the personalized service platform are all data of periodic update business. The exchange frequency range of the basic directory of matters is 0.5 hours to 1 hour; the exchange frequency range of the electronic certificate directory data is 0.5 hours to 24 hours; the exchange frequency range of the basic matter handling data is 0.5 days to 1 day.

[0036] After each execution of data exchange of shared data, the personalized service platform will record the time when the shared data completes the data exchange in the historical shared data status information, that is, the last time the shared data was exchanged. Platform information includes basic information such as the geographical location, computing power requirements, network connection information, storage capacity, computing power and hardware resources of the personalized service platform. The preset duration is the duration determined by the personalized service platform based on its own platform information, and the preset durations corresponding to different personalized service platforms may be different. The preset duration is used to measure whether the personalized service platform needs to process the shared data immediately. In this solution, optionally, the target processing time of each shared data is determined based on the data exchange demand information of the predetermined standard service platform, the platform information of the predetermined personalized service platform, the historical shared data status information, the current time and the preset duration, including the following steps A1-step A3:

[0037] Step A1: Identify the service attribute field of each shared data, and obtain the service attribute data of each shared data according to the service attribute field of each shared data.

[0038] Among them, the business attribute data is the data corresponding to the business attribute field in the shared data. Specifically, after obtaining each shared data during operation, the standard service platform determines all the business attribute fields existing in the shared data according to the pre-defined business attribute fields corresponding to each business attribute and the data content of the shared data. The business attribute fields and the corresponding data content are bound to generate a shared data including the business attribute fields and the corresponding data content.

[0039] Step A2: For each shared data, determine the target exchange time of the current shared data according to the exchange frequency range of the service attribute data of the current shared data, platform information, current time and the last exchange time of the service attribute data of the current shared data.

[0040] Among them, the current moment is the moment when the personalized service platform receives each shared data. The last exchange moment is the moment when the personalized service platform sends the business attribute data of the same business attributes to the standard service platform to exchange data. The target exchange moment is the moment when the personalized service platform processes the business attribute data and sends the personalized business service data obtained according to the business attribute data to the standard service platform. Different personalized service platforms carry different numbers of service personnel, numbers of matters to be handled, and authorities for matters to be handled, and these are different and will change. Therefore, the last exchange moments of the business attribute data of shared data of different personalized service platforms are also different. The exchange frequency ranges corresponding to shared data of different business attributes and the target exchange moments of shared data of different business attributes are also different.

[0041] In an optional implementation, after obtaining the business attribute data, the personalized service platform determines the exchange frequency range corresponding to the business attribute data of the current shared data from the exchange frequency range corresponding to each predefined business attribute field, and determines the specific exchange frequency of the business attribute data according to the platform information and service information of the personalized service platform. Further, the target exchange time of the current shared data is determined according to the last exchange time and exchange frequency of the business attribute data in the personalized service platform.

[0042] Exemplarily, personalized service platform A is a large-scale platform that processes a large amount of data and serves a large number of people. Assume that the exchange frequency range of a business attribute data is once every 2 hours to 8 hours. The last exchange time of the business attribute data of personalized service platform A is 10 o'clock. Since personalized service platform A can obtain a large amount of business service data based on the business attribute data in a short time, personalized service platform A needs to send the business service data to the standard service platform as soon as possible to complete the data exchange. Further, according to the exchange frequency range, it can be determined that the specific exchange frequency of the business attribute data of personalized service platform A is once every 2 hours, and the target exchange time of the business attribute data is determined to be 12 o'clock according to the last exchange time of the business attribute data. Personalized service platform B is a small-scale platform, and its geographical location is relatively remote, so the amount of data it processes is small. The last exchange time of the business attribute data of personalized service platform B is 10 o'clock. Since personalized service platform B generates less business service data in a short time, it is not necessary to process the business attribute data immediately, but to exchange data with the standard service platform after accumulating a certain amount of business service data. Furthermore, according to the exchange frequency range and the service status of personalized service platform B, it can be determined that the optimal exchange frequency of the business attribute data is once every 6 hours, that is, the target exchange time of the business attribute data of personalized service platform B is 16:00.

[0043] The personalized service platform dynamically determines the target exchange time based on the specific business attributes and historical exchange time of each shared data, so that the personalized service platform can adjust the data processing priority according to the actual situation. By considering the last exchange time and the exchange frequency range of the corresponding business, the personalized service platform can more effectively plan its computing and network resources to ensure the efficient operation of the personalized service platform. In particular, for businesses that need to be updated immediately, the personalized service platform can quickly respond to data changes and update data in a timely manner, reducing data delays and data lags.

[0044] Step A3: If the time between the target exchange moment of the current shared data and the current moment is greater than the preset time, determine the target processing moment of the current shared data based on the target exchange moment of the current shared data; if the time between the target exchange moment of the current shared data and the current moment is less than or equal to the preset time, obtain the real-time moment and determine the real-time moment as the target processing moment of the current shared data.

[0045] Specifically, the preset duration is the duration determined by the personalized service platform based on its own platform information, and different personalized service platforms may have different corresponding preset durations. If the target exchange moment of the current shared data is greater than the preset duration, it means that the target exchange moment is still a long time away from the current moment, and the personalized service platform does not need to process the current shared data immediately, and the moment with a preset time away from the target exchange moment can be determined as the target processing moment. If the target exchange moment of the current shared data is less than or equal to the preset duration, it means that the personalized service platform needs to process the current shared data immediately to ensure that the personalized service platform can smoothly exchange data with the standard service platform at the target exchange moment.

[0046] Exemplarily, personalized service platform A receives 2 items of shared data, namely shared data 1 and shared data 2. The exchange frequency range of shared data 1 is: once every 1 hour to 2 hours. The last exchange time of shared data 1 was 10 o'clock. The last exchange time of shared data 1 was 8 o'clock. The corresponding preset duration of personalized service platform A is 4 hours. The moment (current moment) when personalized service platform A receives each shared data is 11 o'clock. Based on its own platform information and the exchange frequency range of shared data 1, personalized service platform A determines that it is best to exchange data with the standard service platform every 2 hours, and then determines the target exchange time of shared data 1 to be 12 o'clock. It can be further determined that the time from the target exchange time of shared data 1 to the current moment is less than the preset time, then this moment (real time) is determined as the target processing time of shared data 1.

[0047] The frequency range of shared data 2 exchange is: once every 5 hours to 15 hours. The last time shared data 2 was exchanged was 8 o'clock, and the current time is 11 o'clock. Based on its own platform information and the frequency range of shared data 2 exchange, personalized service platform A determines that it is best to exchange data with the standard service platform every 10 hours, and determines the target exchange time of shared data 2 to be 18 o'clock. It can be further determined that the time from the target exchange time of shared data 1 to the current time is greater than the preset time, and the time (14 o'clock) that is still a preset time (4 hours) away from the target exchange time (18 o'clock) is determined as the target processing time of shared data 2.

[0048] In actual applications, the standard service platform may send multiple shared data to the personalized service platform at the same time, and the exchange time of each shared data is different. The target processing time of each shared data is determined according to the exchange time of each shared data, the service status of the personalized service platform, and the platform information. In this way, the personalized service platform can give priority to processing the shared data that needs to be processed immediately, reasonably allocate the computing resources of the personalized service platform, and avoid the situation where the personalized service platform processes the shared data that does not need to be processed immediately, thereby squeezing the computing resources of the shared data that needs to be processed immediately.

[0049] After determining the target processing time of each shared data, if the target processing time of the shared data is the real-time time, the shared data is processed immediately. If the target processing time of the shared data is not the real-time time, the shared data can be stored and processed at the target processing time. In an embodiment of the present invention, optionally, if the target processing time of the current shared data is not the real-time time, the current shared data and the target processing time are transmitted to the edge computing node, so that the edge computing node performs data preprocessing on the current shared data, and returns the preprocessed current shared data at the target processing time.

[0050] Among them, the edge computing node is a physical machine or virtual machine pre-deployed according to the platform information, and the platform information includes the geographical location, computing power requirements, network connection information and storage capacity of the personalized service platform. According to the platform information of the personalized service platform, it can be determined whether the personalized service platform needs to deploy edge computing nodes. If the personalized service platform needs to process a large amount of data, carries a large number of service users, has a large data computing pressure and a stable network environment, the edge computing node can be deployed near the geographical location of the personalized service platform. The personalized service platform can store shared data that does not need to be processed immediately to the edge computing node, and use the edge computing node to pre-process the shared data to reduce the computing pressure of the personalized service platform.

[0051] In an optional implementation, after determining that the target processing moment of the current shared data is not the real-time moment, the current shared data is sent to the edge computing node using a pre-configured efficient data transmission protocol. If the current shared data is structured data, the edge computing node can pre-process the current shared data after receiving the current shared data, such as checking the data format of the current shared data, correcting obvious erroneous input in the current shared input data, or eliminating duplicate data. If the current shared data is unstructured data such as images, the edge computing node can perform pre-processing such as format conversion and resolution adjustment on the received image according to the pre-configured image format requirements. After obtaining the pre-processed current shared data, the edge computing node can return the pre-processed current shared data to the personalized service platform at the target processing moment of the current shared data, so that the personalized service platform can process the current shared data at the target processing moment corresponding to the current shared data.

[0052] Storing shared data that does not need to be processed immediately to edge computing nodes enables the personalized service platform to use its core computing resources more effectively to handle high-priority or more real-time tasks. This approach can significantly improve the efficiency and response speed of the personalized service platform when the amount of data is large and the user service needs are changing. Preprocessing data using edge computing nodes that are geographically close to the personalized service platform can reduce data transmission time and delay. At the same time, edge computing nodes can preprocess shared data to ensure that the data received by the personalized service platform is clean and consistent. This improves the accuracy of data processing and reduces errors and anomalies in subsequent processing, thereby improving the reliability and stability of the overall service.

[0053] Step 103 : for each shared data, at the target processing time corresponding to the current shared data, the data type of the current shared data is identified to obtain the data type of the current shared data.

[0054] The data type is structured data or unstructured data, and the unstructured data includes image data, and the image data includes image coding, image field information, and images. In an optional implementation, when processing each shared data, the personalized service platform first performs a preliminary check on each shared data to determine whether the data is complete and whether there are obvious errors or format problems. The data type of each shared data after the check is identified, and the data is determined to be structured data or unstructured data based on information such as each shared data type label, storage format, or file suffix.

[0055] By identifying the data type of shared data, it can be ensured that the subsequent data processing flow can process data for the correct data type.

[0056] Step 104: Process the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data.

[0057] Among them, the target data is the data that the personalized service platform wants to transmit to the standard service platform for data exchange. Specifically, the shared data sent by the standard service platform to the personalized service platform is used to support and constrain the personalized services provided by each personalized service platform. The main business and service focus of each personalized service platform are different, so the shared data required by each personalized service platform will also be different. After the standard service platform sends each shared data to each personalized service platform, each personalized service platform can filter each shared data according to its own platform information and personalized service needs, and filter out the shared data required by the personalized service platform. After filtering the shared data, the business support table corresponding to the shared data in the personalized service platform is updated according to the filtered shared data, and the updated business support table is used to provide personalized services to users.

[0058] In an optional implementation, if the data type of the shared data is structured data, such as database table data, the personalized service platform can parse the shared data to obtain all identification fields in the shared data. From all identification fields in the shared data, the identification fields corresponding to the shared data required by the personalized service platform are screened out, and according to the specific data corresponding to the identification fields, the data in the business support table corresponding to the identification fields in the personalized service platform are updated. The business support table stores data used to constrain and support the personalized service platform in providing personalized services.

[0059] If the data type of the shared data is unstructured data, the personalized service platform can filter out the image codes or image identification fields corresponding to the shared data required by the personalized service platform based on the image codes and image field information of each image in the shared data, and perform image processing on the images corresponding to the image identification fields or image codes, including image recognition, image classification, image cropping, image blurring, etc. After obtaining the processed image corresponding to the current shared data, the business service image library of the personalized service platform is updated according to the processed image.

[0060] Furthermore, in the process of providing personalized services to users, the personalized service platform will store the business service data generated in the process into various business service tables or business service image libraries. After obtaining the updated business support table, the personalized service platform will filter or update the data in the corresponding business service table based on the updated business support table to obtain the target business data that needs to be sent to the standard service platform, and convert the target business data according to the data format requirements of the standard service platform to obtain the target data corresponding to the shared data.

[0061] Exemplarily, all enterprises can handle business in each personalized service platform, but each personalized service platform focuses on different enterprises. There are 5 enterprises, A, B, C, D and E, among which personalized service platform 1 mainly focuses on enterprises A and D, and personalized service platform 2 mainly focuses on enterprises B, C and E. The business service tables of enterprises A and D of personalized service platform 1 are marked as internal services, and the business service tables of enterprises B, C and E are marked as external services. The business service tables of enterprises B, C and E of personalized service platform 2 are marked as internal services, and the business service tables of enterprises A and D are marked as external services. The standard service platform adjusts the enterprises that each personalized service platform focuses on, and after the adjustment, it is as follows: personalized service platform 1 mainly focuses on enterprises A and B, and personalized service platform 2 mainly focuses on enterprises C, D and E. The standard service platform generates shared data based on the adjusted enterprise focus information of each personalized service platform, and sends the shared data to each personalized service platform. When each personalized service platform receives the shared data and determines to process it immediately, it updates each business service table according to the shared data. The updated business service table is as follows: the business service data of Enterprise A and Enterprise B of Personalized Service Platform 1 are marked as internal services, and the business service data of Enterprise C, Enterprise D and Enterprise E are marked as external services. The business service data of Enterprise C, Enterprise D and Enterprise E of Personalized Service Platform 2 are marked as internal services, and the business service data of Enterprise A and Enterprise B are marked as external services. Furthermore, Personalized Service Platform 1 and Personalized Service Platform 2 convert the format of the updated business service data to obtain the target data, and send the target data to the standard service platform so that the standard service platform can summarize, count and audit the data according to the target data.

[0062] Step 105: Transmit the target data corresponding to each shared data to the standard service platform.

[0063] Specifically, after obtaining the target data, each personalized service platform can perform data encryption and data compression on the target data to ensure the transmission security and efficiency of the target data. According to the pre-set network transmission protocol, the processed target data is transmitted to the standard service platform. After receiving the target data, the standard service platform can perform integrity and consistency checks on the target data to ensure that the target data has not been tampered with or damaged during the transmission process.

[0064] The technical solution of this embodiment receives each shared data sent by the standard service platform at the current moment; determines the target processing moment of each shared data according to the predetermined data exchange demand information of the standard service platform, the predetermined historical shared data status information of the personalized service platform, the current moment and the preset duration; for each shared data, identifies the data type of the current shared data at the target processing moment corresponding to the current shared data to obtain the data type of the current shared data; wherein the data type is structured data or unstructured data; processes the current shared data according to the data type of the current shared data to obtain the target data corresponding to the current shared data; and transmits the target data corresponding to each shared data to the standard service platform. The technical solution of this embodiment dynamically determines the target exchange moment of each shared data through the specific business attributes and historical exchange moments of each shared data, so that the personalized service platform can give priority to the shared data that needs to be processed immediately, reasonably allocate the computing resources of the personalized service platform, and avoid the situation where the personalized service platform processes the shared data that does not need to be processed immediately, thereby squeezing the computing resources of the shared data that needs to be processed immediately. By identifying data types, the personalized service platform can use different data processing methods to process different types of shared data in a timely and accurate manner. At the same time, the business support data of the personalized service platform can be updated according to the processed shared data, so as to provide users with more reasonable and accurate business services in the future. It is also convenient for the standard service platform to summarize, count and audit data according to the target data, thereby improving the efficiency of data exchange.

[0065] Figure 2 The flowchart for determining the target data corresponding to the structured data provided in the embodiment of the present invention is a refinement of the above embodiment. The specific method can be as follows Figure 2 As shown, the method may include the following steps:

[0066] Step 201: extract the various identification fields of the current shared data based on the predetermined personalized service requirements, and determine the current business support table corresponding to each identification field of the current shared data according to the data corresponding to each identification field and each business support table of the predetermined personalized service platform.

[0067] Among them, the personalized service requirements are predetermined based on the platform information of the personalized service platform, and the personalized service requirements include the business requirement information of the personalized service platform, the service object requirement information, and the business support data requirement information. Different personalized service platforms have different personalized service requirements, so different personalized service platforms require different data in the shared data. The identification field is a field used to uniquely identify each record (each data) in the shared data.

[0068] In an optional implementation, after obtaining the shared data, the personalized service platform extracts the identification fields corresponding to the data required by the personalized service platform according to the business support data demand information, etc. From all business support tables of the personalized service platform, the current business support table corresponding to each identification field is screened out.

[0069] Step 202: Update each current business support table according to the value of each data.

[0070] The value of each data item is the specific data content of each data item of the current shared data. Specifically, the shared data is used to support and constrain the personalized services provided by each personalized service platform, and the personalized service platform provides personalized services based on each business support table. Therefore, after determining the current business support table, the corresponding content in the current business support table is updated according to the value of each data item in the shared data, so that the personalized service platform can accurately and quickly provide personalized services based on the business support table.

[0071] Step 203: Generate current business service data based on the updated business support table and the predetermined historical business service data.

[0072] Among them, the historical business service data is the data generated by the personalized service platform during the personalized service process in the historical period. The historical period can be the period from the last exchange time to the current time corresponding to the business service data. When the data in the business support table changes, some data labels or data recording methods in the historical business service data will also change accordingly. Therefore, after obtaining the updated business support table, the historical business service data is adjusted and updated according to the updated business support table to obtain the updated current business service data.

[0073] Step 204: store the current business service data into each predetermined business service table according to the generation time and data content of the current business service data.

[0074] Each business service table is a data table pre-established by the personalized service platform according to the platform information and a certain data format. The business service table records the business service data of each time period. The generation time of the current business service data is the time when the historical business service data is modified to obtain the current business service data.

[0075] Specifically, the historical service table stores historical service data. After the historical service data is adjusted and updated, some data in the historical service data has changed, and the data stored in the historical service table is no longer representative. Therefore, after obtaining the current service data, the data content of the current service data is stored in the corresponding service table according to the generation time of the current service data.

[0076] Step 205: for each business service table corresponding to the current shared data, according to all the business data in the current business service table, determine the target conversion data table corresponding to the current business data table from the predetermined standard service data tables corresponding to the current shared data.

[0077] Among them, the standard service data table is used to store the standard service data of the standard service platform. The target conversion data table is a table in the standard service data table used to store the current business data of the personalized service platform. Specifically, the data storage format of the standard service platform is different from the data storage format of the personalized service platform, and the data storage format of each personalized service platform is also different. In order to reduce the pressure on the standard service platform to process the data sent by each personalized service platform, each personalized service platform can perform data format conversion on the data to be sent to the standard service platform and convert it into the data storage format of the standard service platform.

[0078] In an optional implementation, after determining each business service table to be sent to the standard service platform, the personalized service platform determines the corresponding standard service table, ie, the target conversion data table of the business service table, according to the data in the business service table.

[0079] Step 206: Determine the mapping relationship between all business data and the conversion data according to all business data and the conversion data in the target conversion data table.

[0080] Among them, the conversion data is the data in the target conversion data table, and the mapping relationship is used to ensure that the business data of the personalized service platform is correctly converted from the original format to the format of the target conversion data. In an optional implementation, the personalized service platform can compare the business data and the conversion data by field, and identify the differences in the representation of the same data in the standard service platform and the personalized service platform. For example, "enterprise number" may be identified as "ID_Number" in the personalized service platform and as "Identity_Card_No" in the standard service platform. The personalized service platform can establish a mapping relationship between business data and conversion data based on the differences in the representation of the same data, and establish a mapping rule based on this mapping relationship, so as to facilitate the subsequent format conversion of business data according to the mapping relationship.

[0081] Step 207: perform batch data conversion on all business data according to the mapping relationship to obtain target data corresponding to the current business service table.

[0082] Batch data conversion refers to processing and converting multiple data items at the same time, rather than processing them one by one. Batch data conversion can improve conversion efficiency and ensure data consistency and accuracy. In this solution, optionally, batch data conversion is performed on all business data according to the mapping relationship to obtain the target data corresponding to the current business service table, including the following steps B1-B3:

[0083] Step B1: Determine batch conversion information according to the data volume of all business data.

[0084] Among them, the batch conversion information includes the number of conversion batches, the conversion batch number and the number of data items converted in each batch; the conversion information at least includes the task name, conversion batch number, creation time, execution time, execution status, execution times and exception records. The number of conversion batches is the number of batches included in the entire data conversion task. The number of conversion batches of the batch conversion information can be determined based on information such as the total amount of business data, the processing capacity of a single batch and the computing capacity of the personalized service platform. For example, if there are 1 million business data items that need to be converted, and each batch can process 50,000 data items, a total of 20 batches are required.

[0085] The conversion batch number is a unique identifier for each batch during the processing. The batch number can be a simple serial number, such as 001, or a combination of a date and a serial number, such as 20231201_001. The batch number helps to record and track the conversion process and results of each batch, which is convenient for subsequent management and review. The number of data items converted in each batch determines the scale of data processed in each batch. A reasonable batch size can not only ensure the load balancing of the personalized service platform, but also avoid processing failures caused by excessive data volume in a single batch. For example, according to the status of historical data conversion and platform information, each batch can be set to process 10,000 data items.

[0086] Through reasonable batch division, the personalized service platform can dynamically adjust the size of each batch according to its computing power and task load, thereby optimizing the use of system resources. This approach helps balance the load of the personalized service platform and avoid overload or delay caused by processing too large data batches.

[0087] Step B2: According to the batch number and mapping relationship, the business data is converted in sequence, and the conversion information of each batch is obtained.

[0088] The conversion information includes at least the task name, conversion batch number, creation time, execution time, execution status, execution times and exception records. In an optional implementation, after determining the mapping relationship between the business data and the conversion data, the business data can be converted by an automatic data conversion tool. During the data conversion process, in order to facilitate the management and tracking of data conversion tasks, the personalized service platform will generate a corresponding task name and batch number for each conversion. At the same time, the creation time, execution time, execution status, execution times and exception records of the data conversion task are recorded.

[0089] By recording the detailed conversion information generated during the batch data conversion process, the traceability and manageability of the data conversion task are improved, and the reliability of the data conversion process is also improved.

[0090] Step B3: For each batch, if the execution status of the current batch is successful, the converted data of the current batch is determined as the target data. If the execution status of the current batch is failed, the data of the current batch is converted again at a preset time point, and the number of execution failures of the current batch is recorded; when the number of execution failures is greater than the preset number, an exception report is generated based on the conversion information of the current batch, and the exception report is displayed to the staff.

[0091] Specifically, if the execution status of the current batch is "execution successful", indicating that there is no error in the data conversion of the batch, the converted data of the current batch can be determined as the target data. If the execution status of the current batch is "execution failed", it indicates that the business data of the batch has not been successfully converted into the format of the conversion data. For batches that fail to execute, the personalized service platform can retry at a preset time point. The preset time point can be set in advance based on the batch conversion information and the conversion information of each batch. At the same time, for each batch that fails to execute, the personalized service platform will record the number of execution failures of the current batch after each execution failure.

[0092] When the number of execution failures of a batch exceeds the preset number, it means that there is a problem in the conversion process of the batch that the personalized service platform cannot automatically fix. The personalized service platform can generate a detailed exception report based on the conversion information of the current batch. The exception report includes key information such as error description, occurrence time, possible solutions, and number of failures. The exception report is displayed to relevant staff in a timely manner so that the staff can find the problem in time and take measures to successfully obtain the target data.

[0093] Through batch data conversion, the personalized service platform can process and convert multiple data items at the same time, rather than processing them one by one. This method can improve the efficiency of data conversion, especially when processing large amounts of business data. Batch processing reduces the total time of data conversion, allowing the personalized service platform to respond to user needs more quickly and provide newer business services.

[0094] The technical solution of this embodiment extracts each identification field of the current shared data based on the predetermined personalized service requirements, and determines the current business support table corresponding to each identification field of the current shared data according to each data corresponding to each identification field and each business support table of the predetermined personalized service platform. Update each current business support table according to the value of each data. Generate current business service data based on the updated business support table and the predetermined historical business service data. Store the current business service data in each predetermined business service table according to the generation time and data content of the current business service data. For each business service table corresponding to the current shared data, determine the target conversion data table corresponding to the current business data table from each standard service data table corresponding to the predetermined current shared data according to all business data in the current business service table. Determine the mapping relationship between all business data and the conversion data in the target conversion data table. Perform batch data conversion on all business data according to the mapping relationship to obtain the target data corresponding to the current business service table. The technical solution of this embodiment can automatically extract each identification field of the shared data according to the personalized service requirements, and update the business support data and business service data of the personalized service platform, thereby improving the speed and accuracy of shared data processing. Batch data conversion of business service data can quickly convert business service data into target data, improve the utilization efficiency of computing resources of the personalized service platform, and further improve the efficiency of data exchange.

[0095] Figure 3 The flowchart for determining the target data corresponding to the unstructured data provided by the embodiment of the present invention is a refinement of the above embodiment. The specific method can be as follows Figure 3 As shown, the method may include the following steps:

[0096] Step 301: for each image data in the unstructured data, perform structural analysis on the image code of the current image data according to a predetermined coding rule to obtain a target business service item corresponding to the current image code.

[0097] The encoding rules are defined by the standard service platform, and the encoding rules specify the meaning of each character in the image encoding. Specifically, after the personalized service platform receives the shared data including unstructured data, it identifies the various parts in the image encoding according to the encoding rules, obtains the part representing the business service item, and determines the target business service item corresponding to the current image.

[0098] For example, the image code of an image is a 3-digit string 123. The coding rule stipulates that the first digit indicates the image source, the second digit indicates the service type, and the third digit indicates the service item. It can be determined that the image comes from personalized service platform 1, the service type is type 2 specified in personalized service platform 1, and the service item is item 3 in service type 2. According to the image code, it can be determined that the target business service item corresponding to the image is item 3.

[0099] Step 302: perform feature point detection on the current image to obtain feature contour information of the current image.

[0100] Among them, the feature contour information of the current image includes the contours of each feature in the image and its position in the image. In an optional implementation, after obtaining the current image, the personalized service platform can convert the current image to obtain a binary image corresponding to the current image. After obtaining the binary image, the cv.findContours function in the cross-platform computer vision library can be used to retrieve the contour information from the binary image. After obtaining the contour information, the contours of each feature can be drawn on the current image through the cv.drawContours function.

[0101] Step 303: determine the protection area of ​​the current image based on the feature contour information and the target business service item, and crop the current image based on the protection area and the specified size to obtain a cropped current image.

[0102] The image requirement information includes the requirements of the personalized service platform for the image. The image requirement information includes permission information and data format information, and the data format information includes the specified size and specified pixels. The protection area is used to ensure that important image features or information will not be destroyed or lost when cropping or other operations are performed on the current image. Image cropping is used to remove unnecessary background or edge parts in the image, focus on key information, and improve processing efficiency and accuracy.

[0103] After obtaining the feature contour information of the current image, the feature information of the key features is determined according to the target business service items corresponding to the current image, and the protection area is determined according to the feature information of the key features. For example, if the target business service items are enterprise qualification matters, the protection area is the inner area of ​​the enterprise information feature contour in the image. The overall size of the image will also affect the setting of the protection area. For example, for small-sized images, the protection area may need to be set relatively small to avoid taking up too much space. In an optional embodiment, the coordinates, protection area and specified size of the cropping can be set in the automatic cropping tool in the image processing software library, and the current image can be cropped using the automatic cropping tool to obtain the cropped current image.

[0104] By reasonably setting the protection area and performing precise image cropping, the key information in the image can be effectively retained, providing a reliable basis for further image analysis and processing.

[0105] Step 304: Determine whether there is a target hidden item in the current image according to the permission information.

[0106] Among them, the image requirement information is the requirement of the personalized service platform for the image. The image requirement information includes permission information and data format information. The data format information includes the specified size and specified pixels. The permission information includes the permission for the personalized service platform to use and display the image. The target hidden item is the data in the current image that needs to be hidden in the personalized service platform. For example, the standard service platform sends a traffic condition map of a certain road section to the personalized service platform. The map includes the license plate number of a private vehicle, and the personalized service platform cannot display the license plate number. After obtaining this image, the personalized service platform determines that the business service item corresponding to the image is "traffic conditions" based on the image coding, and the corresponding target hidden item includes "license plate number". The personalized service platform can determine the characteristic contour of the license plate number based on the characteristic contour information of the image, and perform Gaussian blur processing on the license plate number feature.

[0107] Step 305: When there is a target hidden item in the current image, determine the feature contour of the target hidden item in the current image according to the feature contour information, and input the cropped current image and the feature contour of the target hidden item into a predefined Gaussian blur function to obtain a blurred image of the cropped current image.

[0108] Among them, the parameters of the Gaussian blur function are determined according to the image requirement information, and the parameters of the Gaussian blur function include and kernel size. Gaussian blur achieves the blurring effect by convolving the image with the Gaussian function. The Gaussian blur function uses normal distribution to determine the weight of the pixel points, and the closer the pixel is to the center point, the greater the weight. The cropped image and the feature contour of the target hidden item are passed as input parameters to the Gaussian blur function, and the image is blurred according to the set parameters. The degree of blurring is determined by the kernel size and standard deviation.

[0109] Using Gaussian blur to blur the target hidden item of the current image can effectively reduce the random noise in the image and improve the efficiency of image blurring. While effectively hiding or protecting some information that cannot be publicly displayed, it can also retain enough image details for other analysis.

[0110] Step 306: Obtain pixels of the blurred image, calculate the difference between the pixels of the blurred image and the specified pixels, and perform pixel compression or pixel restoration on the blurred image based on the difference to obtain a business service image corresponding to the current image.

[0111] Among them, the image requirement information includes permission information and data format information, and the data format information includes a specified size and a specified pixel. The business service image is an image that can be stored and used by the personalized service platform. After obtaining the blurred image, the blurred image is pixel-identified to obtain the pixels of the blurred image. By calculating the difference between the blurred image and the specified pixel pixel by pixel, it can be determined whether the pixels of the blurred image meet the regulations. If the pixels of the blurred image are smaller than the specified pixels, and the absolute value of the difference with the specified pixels is greater than the preset difference, it means that the pixels of the blurred image are too low, and the pixels of the blurred image can be increased by pixel recovery technology to obtain the business service image corresponding to the current image. If the pixels of the blurred image are larger than the specified pixels, and the absolute value of the difference with the specified pixels is greater than the preset difference, it means that the pixels of the blurred image are too high, which will occupy the memory resources of the personalized service platform, and the pixels of the blurred image can be reduced by pixel compression technology to obtain the business service image corresponding to the current image.

[0112] Step 307: When the current pre-image does not have the target hidden item, the cropped current image is determined as the business service image corresponding to the current image.

[0113] If the current image does not have a target hidden item, indicating that the current image does not need to be blurred, the cropped current image is determined as the business service image corresponding to the current image.

[0114] Step 308: Update the predetermined business service image library based on all business service images of the current shared data, and determine the target data corresponding to the current shared data according to the updated business service image library.

[0115] Among them, the business service image library is an image database used to support the personalized service platform to provide personalized services. After obtaining the business service image, the personalized service platform can update the business service image library according to the business service image corresponding to each shared data. After obtaining the updated business service image library, the images in the updated business service image library can be associated and sorted according to the image coding of each business service image. For example, images belonging to the same business service item are stored in a folder or an image collection, and the folder is named after the name of the business service item. According to the business service items corresponding to each shared data, the target data is filtered out in the business service database after association and sorting.

[0116] The technical solution of this embodiment is to perform structural analysis on the image code of the current image data according to a predetermined coding rule for each image data in the unstructured data, and obtain the target business service item corresponding to the current image code. Perform feature point detection on the current image to obtain the feature contour information of the current image. Determine the protection area of ​​the current image based on the feature contour information and the target business service item, and crop the current image based on the protection area and the specified size to obtain the cropped current image. Determine whether the current image has a target hidden item based on the permission information. When the current image has a target hidden item, determine the feature contour of the target hidden item of the current image based on the feature contour information, and input the cropped current image and the feature contour of the target hidden item into a predefined Gaussian blur function to obtain a blurred image of the cropped current image. Obtain the pixels of the blurred image, calculate the difference between the pixels of the blurred image and the specified pixels, and perform pixel compression or pixel restoration on the blurred image based on the difference to obtain the business service image corresponding to the current image. When the current pre-image does not have a target hidden item, the cropped current image is determined as the business service image corresponding to the current image. Based on all business service images of the current shared data, the predetermined business service image library is updated, and the target data corresponding to the current shared data is determined according to the updated business service image library. The technical solution of this embodiment performs structural analysis and feature point detection on the image data in the shared data through predetermined coding rules and Gaussian fuzzy functions, thereby improving the speed and accuracy of image processing. By determining the protection area, the retention of key information and the elimination of unnecessary information are ensured, so that the personalized service platform can update the business service image library in a timely manner according to the processed image, and determine the target data according to the updated business service image library, thereby improving the efficiency of data exchange.

[0117] Figure 4 Schematic diagram of the structure of a data exchange device provided in an embodiment of the present invention, which is suitable for executing the data exchange method provided in an embodiment of the present invention. Figure 4As shown, the device may specifically include:

[0118] The data receiving module 401 is used to receive the shared data sent by the standard service platform at the current moment;

[0119] The time determination module 402 is used to determine the target processing time of each shared data according to the predetermined data exchange requirement information of the standard service platform, the predetermined historical shared data status information of the personalized service platform, the current time and the preset duration;

[0120] The type determination module 403 is used to identify the data type of the current shared data at the target processing time corresponding to the current shared data for each of the shared data, and obtain the data type of the current shared data; wherein the data type is structured data or unstructured data;

[0121] A data processing module 404 is used to process the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data;

[0122] The data transmission module 405 is used to transmit the target data corresponding to each shared data to the standard service platform.

[0123] Optionally, the historical shared data status information includes the last exchange time of each shared data, the data exchange requirement information includes the service attribute field and exchange frequency range corresponding to each shared data, and the time determination module 402 is specifically used to: identify the service attribute field of each shared data, and obtain the service attribute data of each shared data according to the service attribute field of each shared data;

[0124] For each shared data, determining a target exchange time of the current shared data according to the exchange frequency range of the service attribute data of the current shared data, the platform information, the current time and the last exchange time of the service attribute data of the current shared data;

[0125] The target processing time of the current shared data is determined according to the target exchange time of the current shared data, the current time and the preset duration.

[0126] Optionally, the time determination module 402 is further configured to: if the time length between the target exchange time of the current shared data and the current time is greater than the preset time length, set the target exchange time of the current shared data as the target processing time of the current shared data;

[0127] If the time between the exchange time of the current shared data and the current time is less than or equal to the preset time, the real time is acquired, and the real time is determined as the target processing time of the current shared data.

[0128] Optionally, the data processing module 404 is specifically used to: if the data type of the current shared data is the structured data, extract each identification field of the current shared data based on the predetermined personalized service requirements, and determine the current business support table corresponding to each identification field of the current shared data according to each data corresponding to each identification field and each business support table of the predetermined personalized service platform;

[0129] Update each current business support table according to the value of each data;

[0130] The current shared data is processed based on the updated current business support tables to obtain target data corresponding to the current shared data.

[0131] Optionally, the data processing module 404 is further used to: generate current business service data based on the updated business support table and predetermined historical business service data;

[0132] Storing the current business service data in each predetermined current business service table according to the generation time and data content of the current business service data;

[0133] Based on the data exchange requirement, data conversion is performed on each business service table corresponding to the current shared data to obtain target data corresponding to the current shared data.

[0134] Optionally, the data processing module 404 is further configured to: for each business service table corresponding to the current shared data, determine, according to all business data of the current business service table, a target conversion data table corresponding to the current business data table from various predetermined standard service data tables corresponding to the current shared data;

[0135] Determining a mapping relationship between all the business data and the conversion data according to all the business data and the conversion data in the target conversion data table;

[0136] Batch data conversion is performed on all the business data according to the mapping relationship to obtain target data corresponding to the current business service table.

[0137] Optionally, the data processing module 404 is further used to: determine batch conversion information according to the data volume of all business data, wherein the batch conversion information includes the number of conversion batches, the conversion batch number and the number of converted data in each batch;

[0138] According to the batch number and the mapping relationship, the business data is sequentially converted, and conversion information of each batch is obtained; the conversion information at least includes a task name, a conversion batch number, a creation time, an execution time, an execution status, an execution count, and an exception record;

[0139] For each batch, if the execution status of the current batch is successful execution, the converted data of the current batch is determined as the target data.

[0140] Optionally, the data processing module 404 is further configured to: if the execution status of the current batch is execution failure, perform data conversion on the current batch again at a preset time point, and record the number of execution failures of the current batch;

[0141] When the number of execution failures is greater than a preset number, an exception report is generated according to the conversion information of the current batch, and the exception report is displayed to the staff.

[0142] Optionally, the data processing module 404 is further configured to: if the data type of the current shared data is the unstructured data, for each image data in the unstructured data, perform structural analysis on the image code of the current image data according to a predetermined coding rule to obtain a target business service item corresponding to the current image code;

[0143] According to the predetermined image requirement information of the target business service item, performing image conversion on the current image in the current image data to obtain a business service image corresponding to the current image;

[0144] A predetermined business service image library is updated based on all business service images of the current shared data, and target data corresponding to the current shared data is determined according to the updated business service image library.

[0145] Optionally, the data processing module 404 is further used to: perform feature point detection on the current image to obtain feature contour information of the current image;

[0146] Determine a protection area of ​​the current image based on the feature profile information and the target business service item, and crop the current image based on the protection area and the specified size to obtain a cropped current image;

[0147] Determine whether the current image has a target hidden item according to the permission information, and when the current image has the target hidden item, perform image blurring processing on the cropped current image based on the feature contour information to obtain a business service image corresponding to the current image;

[0148] When the current pre-image does not have a target hidden item, the cropped current image is determined as the business service image corresponding to the current image.

[0149] Optionally, the data processing module 404 is further used to: determine the characteristic contour of the target hidden item of the current image according to the characteristic contour information, and input the cropped current image and the characteristic contour of the target hidden item into a predefined Gaussian blur function to obtain a blurred image of the cropped current image; wherein the parameters of the Gaussian blur function are determined according to the image requirement information, and the parameters of the Gaussian blur function include a kernel size and a standard deviation;

[0150] Pixels of the blurred image are acquired, a difference between the pixels of the blurred image and the specified pixels is calculated, and pixel compression or pixel restoration is performed on the blurred image based on the difference to obtain a business service image corresponding to the current image.

[0151] Optionally, the data processing module 404 is also used to: for each shared data, if the target processing moment of the current shared data is the target exchange moment of the current shared data, transmit the current shared data and the target exchange moment to the edge computing node, so that the edge computing node performs data preprocessing on the current shared data and returns the preprocessed current shared data at the target exchange moment; the edge computing node is pre-deployed according to the platform information, and the platform information includes the geographical location, computing power requirements, network connection information and storage capacity of the personalized service platform.

[0152] The data exchange device provided in the embodiment of the present invention can execute the data exchange method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. The contents not described in detail in this embodiment can refer to the description in any method embodiment of the present invention.

[0153] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, referring to Figure 5 , Figure 5 The electronic device 12 shown is only an example and should not limit the functions and scope of use of the embodiments of the present application. Figure 5 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0154] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0155] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0156] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical medium) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present application.

[0157] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0158] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. It should be understood that although Figure 5 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0159] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing a data exchange method provided by an embodiment of the present invention: receiving various shared data sent by the standard service platform at the current moment; determining the target processing moment of each shared data according to the predetermined data exchange demand information of the standard service platform, the predetermined platform information of the personalized service platform, the historical shared data status information, the current moment and the preset duration; for each shared data, identifying the data type of the current shared data at the target processing moment corresponding to the current shared data to obtain the data type of the current shared data; wherein the data type is structured data or unstructured data; performing data processing on the current shared data according to the data type of the current shared data to obtain the target data corresponding to the current shared data; and transmitting the target data corresponding to each shared data to the standard service platform.

[0160] The embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, a data exchange method as provided in all the embodiments of the present invention is implemented: receiving each shared data sent by a standard service platform at the current moment; determining the target processing moment of each shared data according to the predetermined data exchange requirement information of the standard service platform, the predetermined platform information of the personalized service platform, the historical shared data status information, the current moment and the preset duration; for each shared data, identifying the data type of the current shared data at the target processing moment corresponding to the current shared data, and obtaining the data type of the current shared data; wherein the data type is structured data or unstructured data; performing data processing on the current shared data according to the data type of the current shared data, and obtaining the target data corresponding to the current shared data; transmitting the target data corresponding to each shared data to the standard service platform. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electronic device, device or device of electrical, magnetic, optical, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction-executing electronic device, apparatus, or device.

[0161] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction-executing electronic device, apparatus, or device.

[0162] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0163] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0164] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

[0165] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the data exchange method provided in any embodiment of the present application.

[0166] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0167] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A data exchange method, characterized in that: Applied to a personalized service platform, the method includes: Receive various shared data sent by the standard service platform at the current moment; Determine the target processing time of each shared data according to the predetermined data exchange requirement information of the standard service platform, the predetermined platform information of the personalized service platform, the historical shared data status information, the current time and the preset duration; For each of the shared data, at a target processing time corresponding to the current shared data, a data type of the current shared data is identified to obtain the data type of the current shared data; wherein the data type is structured data or unstructured data; Performing data processing on the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data; The target data corresponding to each of the shared data is transmitted to the standard service platform.

2. The method according to claim 1, characterized in that The historical shared data status information includes the last exchange time of each shared data, the data exchange requirement information includes the service attribute field and exchange frequency range corresponding to each shared data, and the target processing time of each shared data is determined according to the predetermined data exchange requirement information of the standard service platform, the predetermined platform information of the personalized service platform, the historical shared data status information, the current time and the preset duration, including: Identifying a service attribute field of each shared data, and obtaining service attribute data of each shared data according to the service attribute field of each shared data; For each shared data, determining a target exchange time of the current shared data according to the exchange frequency range of the service attribute data of the current shared data, the platform information, the current time, and the last exchange time of the service attribute data of the current shared data; The target processing time of the current shared data is determined according to the target exchange time of the current shared data, the current time and the preset duration.

3. The method according to claim 2, characterized in that Determining a target processing time of the current shared data according to the target exchange time of the current shared data, the current time, and the preset duration includes: If the time between the target exchange time of the current shared data and the current time is longer than the preset time, determining the target processing time of the current shared data according to the target exchange time of the current shared data; If the time between the exchange time of the current shared data and the current time is less than or equal to the preset time, the real time is acquired, and the real time is determined as the target processing time of the current shared data.

4. The method according to claim 1, characterized in that: Processing the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data includes: If the data type of the current shared data is the structured data, extracting each identification field of the current shared data based on the predetermined personalized service requirements, and determining the current business support table corresponding to each identification field of the current shared data according to each data corresponding to each identification field and each business support table of the predetermined personalized service platform; Update each current business support table according to the value of each data; The current shared data is processed based on the updated current business support tables to obtain target data corresponding to the current shared data.

5. The method according to claim 4, characterized in that The performing data processing on the current shared data based on each updated current business support table to obtain target data corresponding to the current shared data includes: generating current business service data based on the updated business support table and predetermined historical business service data; Storing the current business service data in each predetermined current business service table according to the generation time and data content of the current business service data; Based on the data exchange requirement, data conversion is performed on each business service table corresponding to the current shared data to obtain target data corresponding to the current shared data.

6. The method according to claim 5, characterized in that Based on the data exchange requirement, data conversion is performed on each business service table corresponding to the current shared data to obtain target data corresponding to the current shared data, including: For each business service table corresponding to the current shared data, according to all business data of the current business service table, determine the target conversion data table corresponding to the current business data table from each predetermined standard service data table corresponding to the current shared data; Determining a mapping relationship between all the business data and the conversion data according to all the business data and the conversion data in the target conversion data table; Batch data conversion is performed on all the business data according to the mapping relationship to obtain target data corresponding to the current business service table.

7. The method according to claim 6, characterized in that Batch data conversion is performed on all the business data according to the mapping relationship to obtain target data corresponding to the current business service table, including: Determine batch conversion information according to the data volume of all business data, wherein the batch conversion information includes the number of conversion batches, the conversion batch number, and the number of data items converted in each batch; According to the batch number and the mapping relationship, the business data is sequentially converted, and conversion information of each batch is obtained; the conversion information at least includes a task name, a conversion batch number, a creation time, an execution time, an execution status, an execution count, and an exception record; For each batch, if the execution status of the current batch is successful execution, the converted data of the current batch is determined as the target data.

8. The method according to claim 7, characterized in that The method further comprises: If the execution status of the current batch is execution failure, data conversion is performed again on the current batch at a preset time point, and the number of execution failures of the current batch is recorded; When the number of execution failures is greater than a preset number, an exception report is generated according to the conversion information of the current batch, and the exception report is displayed to the staff.

9. The method according to claim 1, characterized in that: The unstructured data includes image data, and the image data includes image code and image; Processing the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data includes: If the data type of the current shared data is the unstructured data, for each image data in the unstructured data, the image code of the current image data is structurally parsed according to a predetermined coding rule to obtain a target business service item corresponding to the current image code; According to the predetermined image requirement information of the target business service item, performing image conversion on the current image in the current image data to obtain a business service image corresponding to the current image; A predetermined business service image library is updated based on all business service images of the current shared data, and target data corresponding to the current shared data is determined according to the updated business service image library.

10. The method according to claim 9, characterized in that The image requirement information includes authority information and data format information, the data format information includes a specified size and specified pixels, and according to the predetermined image requirement information of the target business service item, performing image conversion on the current image in the current image data to obtain a business service image corresponding to the current image includes: Performing feature point detection on the current image to obtain feature contour information of the current image; Determine a protection area of ​​the current image based on the feature profile information and the target business service item, and crop the current image based on the protection area and the specified size to obtain a cropped current image; Determine whether the current image has a target hidden item according to the permission information, and when the current image has the target hidden item, perform image blurring processing on the cropped current image based on the feature contour information to obtain a business service image corresponding to the current image; When the current pre-image does not have a target hidden item, the cropped current image is determined as the business service image corresponding to the current image.

11. The method according to claim 10, characterized in that Performing image blur processing on the cropped current image based on the feature contour information to obtain a business service image corresponding to the current image includes: Determine the characteristic contour of the target hidden item of the current image according to the characteristic contour information, and input the cropped current image and the characteristic contour of the target hidden item into a predefined Gaussian blur function to obtain a blurred image of the cropped current image; wherein the parameters of the Gaussian blur function are determined according to the image requirement information, and the parameters of the Gaussian blur function include a kernel size and a standard deviation; Pixels of the blurred image are acquired, a difference between the pixels of the blurred image and the specified pixels is calculated, and pixel compression or pixel restoration is performed on the blurred image based on the difference to obtain a business service image corresponding to the current image.

12. The method according to claim 3, characterized in that Before identifying the data type of the current shared data at the target processing time corresponding to the current shared data, the method further includes: For each shared data, if the target processing time of the current shared data is not the real-time time, the current shared data and the target processing time are transmitted to the edge computing node, so that the edge computing node performs data preprocessing on the current shared data and returns the preprocessed current shared data at the target processing time; the edge computing node is pre-deployed according to the platform information, and the platform information includes the geographical location, computing power requirements, network connection information and storage capacity of the personalized service platform.

13. A data exchange device, characterized in that: include: A data receiving module, used to receive various shared data sent by the standard service platform at the current moment; A time determination module, used to determine the target processing time of each shared data according to the predetermined data exchange demand information of the standard service platform, the predetermined historical shared data status information of the personalized service platform, the current time and the preset duration; A type determination module, for each of the shared data, identifying the data type of the current shared data at the target processing time corresponding to the current shared data, to obtain the data type of the current shared data; wherein the data type is structured data or unstructured data; A data processing module, used for performing data processing on the current shared data according to the data type of the current shared data to obtain target data corresponding to the current shared data; The data transmission module is used to transmit the target data corresponding to each of the shared data to the standard service platform.

14. A data exchange electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the data exchange method according to any one of claims 1 to 12 when executing the computer program.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the data exchange method as described in any one of claims 1 to 12 is implemented.

16. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the data exchange method according to any one of claims 1 to 12.

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