Big data real-time refreshing display method and device, equipment and storage medium

Abstract

The application provides a big data real-time refreshing display method, device, equipment and storage medium, the method comprises the following steps: sending a first query request to the background at a first fixed period, returning the first total number to the foreground, and determining the first total number as foreground data; sending a second query request to the background at a second fixed period, returning the first page list data and the second total number to the foreground, and updating and merging the foreground data through an iteration algorithm; when the first total number returned to the foreground is inconsistent with the second total number, obtaining the first page list data and the second total number, and starting the cache updating strategy. According to the technical scheme of the embodiment of the application, the data can be updated in real time through polling operation, so that the list data can be displayed in real time under the condition of ensuring the stability of the database, and the refreshing speed of the list data is improved.

Description

Technical Field

[0001] This invention relates to the field of big data technology, and in particular to a method, apparatus, device, and storage medium for real-time display of big data. Background Technology

[0002] To fully support the State Grid Corporation of China's digital transformation, the application system (hereinafter referred to as the application system) is integrated into the official unified online service portal of State Grid Corporation of China—iStateGrid—and the list data is required to be viewable and refreshed in real time. The database of the application system includes the lists and list data used daily by the application system.

[0003] The application system's database contains a massive amount of data, while server resources are limited, and real-time performance is critical. When real-time calculation and display of large amounts of list data is required, the application system integrated with iGuoWang cannot use persistent connections (WebSocket) technology. Using direct CRUD (Create, Read, Update, and Delete) operations would place a huge computational burden and performance pressure on the database, potentially leading to database failure, and the data display and refresh speed would be slow. In summary, existing technologies, constrained by limited server performance and the inability of the application system to use persistent connections (WebSocket) technology, result in slow real-time display and refresh speeds for viewing and updating list data in the database, leading to a poor user experience. Summary of the Invention

[0004] This invention aims to at least solve one of the technical problems existing in the prior art. To this end, this invention proposes a method, apparatus, device, and storage medium for real-time refresh and display of big data, which can achieve real-time data updates through HTTP polling operations, thereby enabling real-time display of list data while ensuring database stability and improving the refresh speed of list data.

[0005] In a first aspect, embodiments of the present invention provide a method for real-time refresh and display of big data, applied to an application system integrated with iGuowang; the method includes: The front end generates a first query request and sends the first query request to the back end at a preset first fixed period. The back end returns a first total number of records to the front end, and the front end determines the first total number of records as front end data. The first query request includes a request to obtain the first total number of records, and the front end is connected to the back end for communication. The front-end generates a second query request and sends the second query request to the back-end at a preset second fixed period. The back-end returns the first page pagination list data and the second total number of items to the front-end. The front-end data is updated and merged through a traversal algorithm. The second query request includes a request to obtain the first page pagination list data and the second total number of items. When the first query request is executed, if the first total number of records returned to the front end is inconsistent with the second total number of records, the pagination list data of the first page and the second total number of records are obtained, and the cache update strategy is started.

[0006] According to some embodiments of the present invention, the front end is iGuoWang, and the back end includes a high-speed cache and a database that are interconnected. The high-speed cache includes a local cache, a distributed cache, and a database cache. The front-end generates a first query request and sends it to the back-end at a preset first fixed interval. The back-end returns a first total number of records to the front-end, including: The iGuoWang generates the first query request and sends the first query request to the cache. When the cache stores the first total number of entries, the cache returns the first total number of entries to the i-national network; Alternatively, if the first total number of records is not present in the cache, the cache retrieves the first total number of records from the database, reloads the first total number of records into the cache by updating the cache policy, and returns the first total number of records to the iGuo.net.

[0007] According to some embodiments of the present invention, the front-end generates a second query request and sends the second query request to the back-end at a preset second fixed interval. The back-end returns the first page pagination list data and the second total number of records to the front-end. The front-end data is updated and merged through a traversal algorithm, including: iGuo.net obtains the first page pagination list data and the second total number of records from the database. The database returns the first page pagination list data and the second total number of records to iGuo.net. The first page pagination list data is then loaded into the cache. The iGuo.net retrieves the first page pagination list data from the cache through the second query request. The cache returns the first page pagination list data, and the front-end data is updated and merged through a traversal algorithm.

[0008] According to some embodiments of the present invention, after the database returns the first page pagination list data and the second total number of records to the iGuo.net, the method further includes: The foreground performs modification operations, which include add and delete operations; Retrieve the latest first page pagination list data and the second total number of items from the database, return the first page pagination list data and the second total number of items to the front end, and update the first total number of items and the first page pagination list data in the front end data using a comparison algorithm.

[0009] According to some embodiments of the present invention, after the front-end generates the second query request, the method further includes: When the second query request changes, the backend retrieves the first page pagination list data from the database based on the changed second query request, returns the first page pagination list data to the frontend, and updates the first page pagination list data through a comparison algorithm; Alternatively, if the second query operation remains unchanged, the backend will directly return the first page pagination list data and the second total number of items obtained from the cache to the frontend.

[0010] Secondly, embodiments of the present invention provide a real-time big data refresh and display device, including at least one control processor and a memory for communicatively connecting with the at least one control processor; the memory stores instructions executable by the at least one control processor, the instructions being executed by the at least one control processor to enable the at least one control processor to perform the real-time big data refresh and display method as described in the first aspect above.

[0011] Thirdly, embodiments of the present invention provide an electronic device, including a big data real-time refresh display device as described in the second aspect above.

[0012] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer-executable instructions, the computer-executable instructions being used to execute the big data real-time refresh and display method as described in the first aspect above.

[0013] The real-time big data refresh and display method according to embodiments of the present invention has at least the following beneficial effects: A first query request is generated on the front end and sent to the back end at a preset first fixed period; the back end returns a first total number of records to the front end; the front end determines the first total number of records as front end data; wherein the first query request includes a request to obtain the first total number of records; the front end is connected to the back end. A second query request is generated on the front end and sent to the back end at a preset second fixed period; the back end returns first page pagination list data and a second total number of records to the front end; the front end data is updated and merged through a traversal algorithm; wherein the second query request includes a request to obtain the first page pagination list data and the second total number of records. When the first query request is executed, if the first total number of records returned to the front end is inconsistent with the second total number of records, the first page pagination list data and the second total number of records are obtained, and a cache update strategy is initiated. According to the technical solution of the present invention, this application adopts a combination of front-end request polling and service caching, replaces long-connection technology with HTTP polling operation, and updates multi-layer caching strategies through advanced data comparison algorithms, which greatly releases database performance and completes application functions and user experience under limited database server resources, thereby improving page user experience and data real-time performance. Attached Figure Description

[0014] Figure 1 This is a flowchart of a method for real-time refresh and display of big data provided in an embodiment of the present invention; Figure 2 This is a complete flowchart of a real-time big data refresh and display method provided in another embodiment of the present invention; Figure 3 This is a structural diagram of a big data real-time refresh display device provided in another embodiment of the present invention. Detailed Implementation

[0015] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0016] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., are based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0017] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0018] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0019] This invention provides a method, apparatus, device, and storage medium for real-time big data refresh and display. The method includes: a front-end generating a first query request and sending it to a back-end at a preset first fixed interval; the back-end returning a first total number of records to the front-end; the front-end determining the first total number of records as front-end data; wherein the first query request includes a request to retrieve the first total number of records; and the front-end is communicatively connected to the back-end. The front-end also generates a second query request and sends it to the back-end at a preset second fixed interval; the back-end returning first page pagination list data and a second total number of records to the front-end; and updating and merging the front-end data using a traversal algorithm; wherein the second query request includes a request to retrieve the first page pagination list data and the second total number of records. When the first query request is executed, if the first total number of records returned to the front-end is inconsistent with the second total number of records, the first page pagination list data and the second total number of records are retrieved, and a cache update strategy is initiated. According to the technical solution of the present invention, this application adopts a combination of front-end request polling and service caching, replaces long-connection technology with HTTP polling operation, and updates multi-layer caching strategies through advanced data comparison algorithms, which greatly releases database performance and completes application functions and user experience under limited database server resources, thereby improving page user experience and data real-time performance.

[0020] The technical solutions of the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0021] Reference Figure 1 , Figure 1 This is a flowchart illustrating a method for real-time refresh and display of big data according to an embodiment of the present invention. The method includes, but is not limited to, the following steps: S10, the front end generates a first query request and sends the first query request to the back end at a preset first fixed period. The back end returns the first total number of records to the front end, and the front end determines the first total number of records as the front end data. The first query request includes a request to obtain the first total number of records, and the front end communication is connected to the back end. S20, the front end generates a second query request and sends the second query request to the back end at a preset second fixed period. The back end returns the first page pagination list data and the second total number of items to the front end. The front end data is updated and merged through a traversal algorithm. The second query request includes a request to obtain the first page pagination list data and the second total number of items. S30, when the first query request is executed, if the total number of records returned to the front end is inconsistent with the total number of records returned to the front end, the pagination list data of the first page and the total number of records are obtained, and the cache update strategy is started.

[0022] It should be noted that this application achieves data updates through a first query request and a second query request, respectively, at preset first and second fixed intervals. That is, this application employs an HTTP polling mechanism, using timed HTTP requests instead of long-lived connections (WebSockets) to achieve real-time data updates. By reasonably setting the polling interval, it balances real-time performance and server load, and supports dynamic adjustment of the polling frequency according to business scenarios. In other words, the first and second fixed intervals are set based on actual needs, thereby reasonably setting the polling interval and balancing the real-time display of front-end data with server load.

[0023] It should be noted that the database contains all the list data required by the front-end. This application employs a massive data pagination mechanism to optimize the pagination of data lists under large amounts of data. The front-end requests a specified dataset on demand, reducing the amount of data requested per request, improving response speed, and fully optimizing user experience and system performance. For example, a query request is generated based on the data to be queried, thereby returning a paginated list of data including the data to be queried to the front-end.

[0024] It should be noted that this application uses a data comparison algorithm to monitor changes in the total amount of data in real time, thereby enabling a comparison between the first total number of records and the second total number of records. The comparison algorithm is used to determine and control the cache update strategy, precisely control the synchronization timing of each level of cache, and avoid unnecessary data transmission and computation.

[0025] In existing technologies, iGuowang is the official unified online service portal of State Grid Corporation of China, possessing core functions such as instant messaging, audio and video conferencing, and news information. It deeply integrates marketing, operation and maintenance, human resources, materials, power trading, and mobile applications from various units within the company, aggregating massive amounts of business data. It represents a typical practice of State Grid Corporation's "one platform, one system, micro-applications" approach. To fully support State Grid Corporation's digital transformation, a distribution automation system needs to be integrated into iGuowang, requiring real-time viewing and updating of list data. Due to platform limitations, long-lived connections (WebSocket) technology cannot be used, and the system database is massive, making real-time querying extremely demanding on the server. Therefore, under these limited conditions, it is difficult to achieve real-time viewing and updating of large amounts of list data. While the iGuowang platform restricts long-lived connection technology, its application systems routinely use list data, requiring high real-time performance, and server resources are limited. Constrained by limited server performance and the inability of application systems to use long-lived connections (WebSocket) technology, the real-time display and updating of list data in the database is slow, resulting in a poor user experience.

[0026] It should be noted that due to the massive amount of data required for real-time display on the front end, and given the need for real-time calculation and display of large amounts of list data, direct CRUD (Create, Read, Update, and Delete) operations on the database would incur huge computational costs and performance pressure, potentially even leading to database failures. Furthermore, long-lived connection (WebSocket) technology is unavailable due to platform limitations. To address the technical problems of existing technologies, this application proposes a solution that combines front-end request polling with service caching to overcome performance bottlenecks. By combining an HTTP polling mechanism with a massive data pagination mechanism and data comparison algorithms, this solution is applied to iGuo.net, which suffers from limitations in long-lived connection technology, limited server resources, and database performance bottlenecks, thereby enabling real-time refresh display of large data lists.

[0027] It's worth noting that this solution replaces persistent connections (WebSocket) with HTTP polling, refreshes the list data through a multi-level caching layer, and updates the multi-layer caching strategy using an advanced data comparison algorithm. This significantly improves database performance, enabling application functionality and user experience to be completed with limited database server resources. After implementation, both the page user experience and data real-time performance have been significantly improved.

[0028] In another embodiment, the front-end is iGuoWang, and the back-end includes a high-speed cache and a database that are interconnected. The high-speed cache includes a local cache, a distributed cache, and a database cache. In step S10, the front-end generates a first query request and sends the first query request to the back-end at a preset first fixed period. The back-end returns a first total number of records to the front-end. The specific steps include, but are not limited to, the following: S11, iGuowang generates the first query request and sends the first query request to the cache; S12, when the cache stores the first total number of entries, the cache returns the first total number of entries to iGuo.net; S13, or, if the first total number of records does not exist in the cache, the cache retrieves the first total number of records from the database, reloads the first total number of records into the cache by updating the cache policy, and returns the first total number of records to iGuo.net.

[0029] It should be noted that this application adopts a multi-layer caching strategy, implementing a multi-layer caching mechanism on the server side. That is, the cache of this application includes local cache, distributed cache and database cache; the application cache layer is used to store hot data and calculation results, data consistency is ensured through the cache data index invalidation mechanism, and the cache level and strategy are configured according to the database performance bottleneck to reduce the number of accesses and reduce CRUD costs.

[0030] It should be noted that frequently used list data is stored in the local cache. When a query request needs to retrieve the corresponding data, the local cache is searched first, thus shortening the data return time. If the required data is not stored in the local cache, it is retrieved from the database and then returned to the front end, thereby achieving real-time data updates. At the same time, this data is stored in the local cache because the data being requested is the list and list data that the application system uses daily but is not stored in the local cache. Therefore, storing this data in the local cache ensures that it can be returned promptly the next time the data is requested.

[0031] In another embodiment, step S20 may include, but is not limited to, the following steps: S21, iGuowang retrieves the first page pagination list data and the second total number of records from the database. The database returns the first page pagination list data and the second total number of records to iGuowang, and loads the first page pagination list data into the cache. S22, iGuowang retrieves the first page of pagination list data from the cache through the second query request. The cache returns the first page of pagination list data, and the front-end data is updated and merged through a traversal algorithm.

[0032] It should be noted that if the first page pagination list data and the second total number of items are not present in the cache, they will be retrieved from the database and loaded into the cache. This allows the first page pagination list data to be retrieved directly from the cache when needed in subsequent operations, thus enabling real-time display of the front-end data.

[0033] In another embodiment, after the database returns the first page of pagination list data and the second total number of records to iGuoWang in step S21, the following steps are included, but are not limited to: S211, The foreground performs modification operations, which include add and delete operations; S212: Retrieve the latest first page pagination list data and second total number of items from the database, return the first page pagination list data and second total number of items to the front end, and update the first total number of items and the first page pagination list data in the front end data through a comparison algorithm.

[0034] It should be noted that when operators perform add and delete operations on the front-end data, the front-end data will inevitably change. Therefore, the latest data is retrieved from the database to update the front-end data, thereby updating the total number of records.

[0035] In another embodiment, after the second query request is generated on the front end in step S20, the process further includes, but is not limited to, the following steps: S41, when the second query request changes, the backend retrieves the first page pagination list data from the database based on the changed second query request, returns the first page pagination list data to the frontend, and updates the first page pagination list data through a comparison algorithm; S42, or, if the second query operation remains unchanged, the backend will directly return the first page pagination list data and the second total number of records obtained from the cache to the frontend.

[0036] It should be noted that when the query request changes, the first page of pagination list data is retrieved from the database and returned to the front end. The first page of pagination list data in the front end is then updated based on the latest first page of pagination list data.

[0037] It should be noted that this embodiment is based on the steps when the second query request changes. Similarly, this method can also be applied to the operation when the first query request changes.

[0038] It should be noted that in this application, the present invention proposes a processing solution by combining front-end request polling with service caching, thereby solving the performance bottleneck. This application employs an HTTP polling mechanism, combined with a multi-layered caching strategy, a massive data pagination mechanism, and a data comparison algorithm structure, enabling real-time refreshing and display of large data lists even under conditions of limited long-connection technology, limited server resources, and database performance bottlenecks.

[0039] To better understand the technical solution of this application, refer to Figure 2 , Figure 2 This is a complete flowchart of a real-time big data refresh and display method provided in another embodiment of the present invention, and the following specific embodiments are provided: S51, the front-end (iGuowang) retrieves the first total number of records Num1 from the (multi-level) cache at a preset first fixed interval through the first query request (HTTP dynamic variable period frequency method Fun1). When the query result returned by the cache is empty, the cache directly retrieves the first total number of records Num1 from the database, and by calling the method, the cache (multi-level cache layer) executes the algorithm to update the cache strategy, reloads and returns the first total number of records Num1 to the front-end; or, when the first total number of records Num1 exists in the multi-level cache, it directly returns the first total number of records Num1 to the front-end. S52, the front end requests the first page pagination list data List1 and the second total number of items (total number of items counted) Num2. The back end returns the first page pagination list data List1 and the second total number of items Num2 to the front end, and loads the first page pagination list data List1 into the cache. S53, the front end retrieves the first page pagination list data List1 from the back end's cache through the second query request (HTTP variable periodicity method Fun2), the back end returns the first page pagination list data List1, and updates and merges the front end data through a traversal algorithm; S54. For front-end modification operations, the back-end directly retrieves the first page pagination list data List1 and the second total number of items Num2 from the database, returns the first page pagination list data List1 and the second total number of items Num2 to the front-end, and updates the first total number of items Num1 (updates are required when the total number of items changes) and the first page pagination list data List1 using a comparison algorithm (such as the Jaccard coefficient comparison algorithm). The modification operations include add and delete operations. S55, for the change of query request (query conditions) on the front end, the back end directly retrieves the first page pagination list data List1 from the database according to the changed query request, returns the first page pagination list data List1 to the front end, and updates the first page pagination list data List1 through comparison algorithms such as Jaccard coefficient; S56, when the first query request (HTTP dynamic variable period frequency method Fun1) is executed, if the total number of records Num1 and Num2 obtained are inconsistent, the query page number is set to 1, the backend queries the corresponding data from the cache, and when the queried data does not exist in the cache, the backend retrieves the first page pagination list data List1 and the second total number of records Num2 from the database, and returns the first page pagination list data List1 and the second total number of records Num2 to the frontend. The frontend displays the data in real time and starts the cache update strategy. S57: For query operations with unchanged conditions, the backend directly retrieves data from the cache layer and returns it.

[0040] like Figure 3 As shown, Figure 3 This is a structural diagram of a real-time big data refresh and display device provided in one embodiment of the present invention. The present invention also provides a real-time big data refresh and display device, comprising: The processor 601 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 602 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 602 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 602 and is called and executed by the processor 601 using the real-time big data refresh and display method of the embodiments of this application. The input / output interface 603 is used to implement information input and output; The communication interface 604 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 605 transmits information between various components of the device (e.g., processor 601, memory 602, input / output interface 603, and communication interface 604); The processor 601, memory 602, input / output interface 603, and communication interface 604 are connected to each other within the device via bus 605.

[0041] This application also provides an electronic device, including the big data real-time refresh display device described above.

[0042] This application embodiment also provides a storage medium, which is a computer-readable storage medium, storing a computer program that, when executed by a processor, implements the above-described method for real-time refresh and display of big data.

[0043] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof. The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separate, and may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0044] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0045] The above provides a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for real-time refresh and display of big data, characterized in that, The method is applied to an application system integrated with the iGuo.net network; the method includes: The front end generates a first query request and sends the first query request to the back end at a preset first fixed period. The back end returns a first total number of records to the front end, and the front end determines the first total number of records as front end data. The first query request includes a request to obtain the first total number of records, and the front end is connected to the back end for communication. The front-end generates a second query request and sends the second query request to the back-end at a preset second fixed period. The back-end returns the first page pagination list data and the second total number of items to the front-end. The front-end data is updated and merged through a traversal algorithm. The second query request includes a request to obtain the first page pagination list data and the second total number of items. When the first query request is executed, if the first total number of records returned to the front end is inconsistent with the second total number of records, the pagination list data of the first page and the second total number of records are obtained, and the cache update strategy is started.

2. The method for real-time refresh and display of big data according to claim 1, characterized in that, The front end is iGuoWang, and the back end includes a high-speed cache and a database that are interconnected. The high-speed cache includes a local cache, a distributed cache, and a database cache. The front-end generates a first query request and sends it to the back-end at a preset first fixed interval. The back-end returns a first total number of records to the front-end, including: The iGuoWang generates the first query request and sends the first query request to the cache. When the cache stores the first total number of entries, the cache returns the first total number of entries to the i-national network; Alternatively, if the first total number of records is not present in the cache, the cache retrieves the first total number of records from the database, reloads the first total number of records into the cache by updating the cache policy, and returns the first total number of records to the iGuo.net.

3. The method for real-time refresh and display of big data according to claim 2, characterized in that, The front-end generates a second query request and sends it to the back-end at a preset second fixed interval. The back-end returns the first page pagination list data and the second total number of items to the front-end. The front-end data is then updated and merged using a traversal algorithm, including: iGuo.net obtains the first page pagination list data and the second total number of records from the database. The database returns the first page pagination list data and the second total number of records to iGuo.net. The first page pagination list data is then loaded into the cache. The iGuo.net retrieves the first page pagination list data from the cache through the second query request. The cache returns the first page pagination list data, and the front-end data is updated and merged through a traversal algorithm.

4. The method for real-time refresh and display of big data according to claim 3, characterized in that, After the database returns the first page of paginated list data and the second total number of records to the iGuo.net, the process further includes: The foreground performs modification operations, which include add and delete operations; Retrieve the latest first page pagination list data and the second total number of items from the database, return the first page pagination list data and the second total number of items to the front end, and update the first total number of items and the first page pagination list data in the front end data using a comparison algorithm.

5. The method for real-time refresh and display of big data according to claim 2, characterized in that, After the second query request is generated on the front end, the following is also included: When the second query request changes, the backend retrieves the first page pagination list data from the database based on the changed second query request, returns the first page pagination list data to the frontend, and updates the first page pagination list data through a comparison algorithm; Alternatively, if the second query operation remains unchanged, the backend will directly return the first page pagination list data and the second total number of items obtained from the cache to the frontend.

6. A real-time big data refresh and display device, characterized in that, It includes at least one control processor and a memory for communicatively connecting to the at least one control processor; the memory stores instructions executable by the at least one control processor, which, when executed by the at least one control processor, enable the at least one control processor to perform the big data real-time refresh display method as described in any one of claims 1 to 5.

7. An electronic device, characterized in that, Includes the big data real-time refresh display device as described in claim 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the big data real-time refresh and display method as described in any one of claims 1 to 5.

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