Dynamic data column table exporting method and device, computer equipment and storage medium

Abstract

The invention relates to a dynamic data column table exporting method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a header information design operation input in a user interaction interface by a target user, acquiring customized header information corresponding to the target user; constructing a data source information export template according to the custom header information; based on the data source interface, retrieving data from the data source according to the data source information export template to obtain data source self-defined retrieval data; according to the assembly format of the data source information export template, the data source self-defined retrieval data is assembled to the data source information export template, and user-defined assembly data is obtained; and according to the user-defined assembly data, generating a user-defined data file corresponding to a file format specified in the header information design operation. By adopting the method, the workload of processing the exported data format and content can be reduced, and the convenience and accuracy of data export and format conversion are greatly improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, computer equipment and storage medium for exporting a dynamic data table. Background Art

[0002] With the development of computer technology, import and export components have become indispensable basic functional components in various information systems, greatly improving the efficiency and flexibility of data processing. However, traditional export functions often rely on fixed template designs, which are difficult to meet users' diverse needs for export data formats and content in different scenarios. In particular, when it is necessary to frequently adjust the report structure or provide personalized data reports for different user groups, the limitations of fixed templates are particularly prominent. This results in a lot of work to process the export data format and content. Summary of the invention

[0003] Based on this, it is necessary to provide a dynamic data table export method, device, computer equipment, computer-readable storage medium and computer program product that can reduce the workload required to process the exported data format and content in order to address the above technical problems.

[0004] In a first aspect, the present application provides a method for exporting a dynamic data table. The method comprises:

[0005] In response to a header information design operation input by a target user in a user interaction interface, obtaining custom header information corresponding to the target user;

[0006] Constructing a data source information export template according to the custom header information;

[0007] Based on the data source interface, a template is exported according to the data source information, data is retrieved from the data source, and data source customized retrieval data is obtained;

[0008] Assembling the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data;

[0009] A user-defined data file corresponding to the file format specified in the header information design operation is generated according to the user-defined assembly data.

[0010] In a second aspect, the present application also provides a dynamic data table export device. The device comprises:

[0011] A header information acquisition module, used to respond to a header information design operation input by a target user in a user interaction interface, and acquire custom header information corresponding to the target user;

[0012] An export template construction module, used to construct a data source information export template according to the custom header information;

[0013] A retrieval data acquisition module is used to retrieve data from the data source based on the data source interface and the data source information to obtain the data source customized retrieval data;

[0014] An assembly data obtaining module is used to assemble the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data;

[0015] A data file generation module is used to generate a user-defined data file corresponding to the file format specified in the header information design operation according to the user-defined assembly data.

[0016] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0017] In response to a header information design operation input by a target user in a user interaction interface, obtaining custom header information corresponding to the target user;

[0018] Constructing a data source information export template according to the custom header information;

[0019] Based on the data source interface, a template is exported according to the data source information, data is retrieved from the data source, and data source customized retrieval data is obtained;

[0020] Assembling the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data;

[0021] A user-defined data file corresponding to the file format specified in the header information design operation is generated according to the user-defined assembly data.

[0022] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0023] In response to a header information design operation input by a target user in a user interaction interface, obtaining custom header information corresponding to the target user;

[0024] Constructing a data source information export template according to the custom header information;

[0025] Based on the data source interface, a template is exported according to the data source information, data is retrieved from the data source, and data source customized retrieval data is obtained;

[0026] Assembling the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data;

[0027] A user-defined data file corresponding to the file format specified in the header information design operation is generated according to the user-defined assembly data.

[0028] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0029] In response to a header information design operation input by a target user in a user interaction interface, obtaining custom header information corresponding to the target user;

[0030] Constructing a data source information export template according to the custom header information;

[0031] Based on the data source interface, a template is exported according to the data source information, data is retrieved from the data source, and data source customized retrieval data is obtained;

[0032] Assembling the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data;

[0033] A user-defined data file corresponding to the file format specified in the header information design operation is generated according to the user-defined assembly data.

[0034] The above-mentioned method, device, computer equipment, storage medium and computer program product for exporting a dynamic data table obtain the custom header information corresponding to the target user by responding to the header information design operation input by the target user in the user interaction interface; construct a data source information export template according to the custom header information; based on the data source interface, retrieve data from the data source according to the data source information export template to obtain the data source custom retrieval data; assemble the data source custom retrieval data into the data source information export template according to the assembly format of the data source information export template to obtain the user-defined assembled data; generate a user-defined data file corresponding to the file format specified in the header information design operation according to the user-defined assembled data.

[0035] Users can freely define header information to meet personalized needs in different business scenarios; the system automatically generates data export templates based on custom header information, avoiding tedious manual setup steps and reducing human errors; and the system is based on standardized data source interfaces to ensure efficient and accurate data retrieval and export. In the data assembly stage, the system automatically assembles the retrieved custom data according to the template format to ensure the uniformity and consistency of the output data structure. Ultimately, users can generate custom data files that meet specific file format requirements, which can reduce the workload required to process the export data format and content, greatly improving the convenience and accuracy of data export and format conversion, and is particularly suitable for complex and changeable data processing scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] FIG1 is an application environment diagram of a method for exporting a dynamic data table in one embodiment;

[0037] FIG2 is a schematic diagram of a flow chart of a method for exporting a dynamic data table in one embodiment;

[0038] FIG3 is a schematic diagram of a process of obtaining a method for obtaining customized retrieval data from a first data source in one embodiment;

[0039] FIG4 is a schematic diagram of a flow chart of a method for obtaining customized retrieval data from a second data source in one embodiment;

[0040] FIG5 is a schematic diagram of a flow chart of a conventional method for dynamically retrieving data in one embodiment;

[0041] FIG6 is a schematic diagram of a flow chart of a first method for determining user-defined search authority data in one embodiment;

[0042] FIG7 is a schematic diagram of a flow chart of a second method for determining user-defined search authority data in one embodiment;

[0043] FIG8 is a structural block diagram of a dynamic data table exporting device in one embodiment;

[0044] FIG. 9 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0046] A method for exporting a dynamic data table provided in an embodiment of the present application can be applied in an application environment as shown in FIG. 1. The terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed on a cloud or other network server. The server 104 responds to the header information design operation input by the target user in the user interaction interface of the terminal 102, obtains the custom header information corresponding to the target user; constructs a data source information export template according to the custom header information; based on the data source interface, retrieves data from the data source according to the data source information export template to obtain the data source custom retrieval data; according to the assembly format of the data source information export template, assembles the data source custom retrieval data into the data source information export template to obtain the user-defined assembly data; generates a user-defined data file corresponding to the file format specified in the header information design operation according to the user-defined assembly data. The terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable device may be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0047] In one embodiment, as shown in FIG. 2 , a method for exporting a dynamic data table is provided, and the method is applied to the server in FIG. 1 as an example for description, including the following steps:

[0048] Step 202 , in response to a header information design operation input by a target user in a user interaction interface, obtain custom header information corresponding to the target user.

[0049] The user interaction interface can be a window for information transmission between the system and the user, through which the user can input, modify and select operations. In this interface, the user can design the table header, view data, set parameters, etc. The interface should be intuitive and friendly to facilitate users to complete various tasks required.

[0050] The header information design operation can be a step for users to set and define the header structure in the interactive interface. Users design the desired table header information by selecting fields, adjusting the field order, naming column titles, etc. This operation provides a basic format structure for subsequent data processing and export.

[0051] The custom header information can be the table header field created or adjusted by the user in the interactive interface according to specific needs. It includes the field name, sorting order, data type and display format selected by the user, reflecting the user's personalized requirements for data display or export.

[0052] Specifically, in the user interaction interface, the system listens to and captures the header information design operations input by the target user, identifies and saves the custom header information input by the target user through the header information design operations of the user interaction interface. Users can adjust the order and content of fields by selecting, dragging, inputting or using preset templates. The system updates the header information in real time based on these operations and verifies it to ensure the legitimacy and integrity of the fields. At the same time, the system supports the function of dynamically inputting headers, which can adapt to the changing needs of users and allow further editing and adjustment of header information.

[0053] Step 204: construct a data source information export template based on the custom header information.

[0054] The data source information export template can be a template file automatically generated based on the custom header information, which is used to define the format, field and order of the data. It acts as a framework for data export, ensuring that the data retrieved from the data source can be accurately organized and output according to the expected structure.

[0055] Specifically, after obtaining the custom header information, the system combines the system's built-in template engine based on the header fields to ensure compatibility with different data sources; at the same time, the system also takes into account the dependencies between fields, automatically assigns appropriate data processing logic (such as date formatting, value conversion, etc.) to specific fields, and generates a data source information export template. The data source information export template defines the specific type, length, data format and arrangement order of each field. This process combines the system's built-in template engine to ensure compatibility with different data sources. Furthermore, the system can also generate a metadata file containing field information to provide a basis for subsequent data processing.

[0056] Step 206 , based on the data source interface, a template is exported according to the data source information, data is retrieved from the data source, and data source customized retrieval data is obtained.

[0057] Among them, the data source interface can be a bridge for the system to interact with external data sources. It defines the data transmission method and protocol, enabling the system to initiate queries and obtain data from different types of data sources (such as databases, APIs, etc.) through the interface. The standardized design of the interface ensures that the system can seamlessly connect with multiple data source types.

[0058] The data source can be a system or location where data is stored, which may be a relational database, file system, API, data warehouse, etc. It contains all the raw data required by the system, and the system retrieves the information required by the user from these data sources through the data source interface.

[0059] The data source customized retrieval data can be a data set that meets the requirements retrieved from the data source according to the user-defined header information and export template. These data are filtered, sorted and converted to meet the user-defined format and field requirements for subsequent processing and export.

[0060] Specifically, the system communicates with the database or other external data sources through a standardized data source interface based on the generated data source information export template. On the basis of establishing communication, the fields defined in the data source information export template are matched with the fields in the data source, and query operations are performed to retrieve qualified data. To improve retrieval efficiency, the retrieval system can use SQL query optimization, index preprocessing and other technologies, and support multiple types of data sources (such as relational databases, APIs, data warehouses, etc.) to ensure data integrity and accuracy. The retrieval process may also involve data filtering and sorting to ensure that the results meet the user's precise needs, and ultimately obtain customized retrieval data from the data source.

[0061] Step 208, assembling the data source customized search data into the data source information export template according to the assembly format of the data source information export template, to obtain user customized assembled data.

[0062] Among them, user-defined assembled data can be the result of reorganizing, arranging and formatting the data retrieved from the data source according to the custom header and export template. It is presented in a unified structured form to ensure that it matches the user's expected output requirements.

[0063] Specifically, once the required data source custom search data is retrieved, the system will process and assemble the retrieved data source custom search data according to the assembly format requirements in the data source information export template. This step will rearrange the data source custom search data in the user-defined header order and format it according to the field type, such as adjusting the numerical precision, converting the date format, and processing text. At the same time, the system will perform necessary data cleaning operations to ensure the consistency and integrity of the data. For complex data structures, the system also supports data assembly of nested fields or multi-level headers, and finally merges all data source custom search data into structured user-defined assembly data.

[0064] Step 210, generating a user-defined data file corresponding to the file format specified in the header information design operation according to the user-defined assembly data.

[0065] Among them, the user-defined data file can be the final exported file, which is generated according to the format set by the user in the header design operation (such as CSV, Excel, JSON, etc., the default setting is Excel format). This file contains the custom assembled data and is saved in the format specified by the user for subsequent viewing, sharing or processing.

[0066] Specifically, after completing the data assembly, the system will export the assembled user-defined assembly data to the corresponding file type according to the file format specified by the user in the header design stage (such as CSV, Excel, JSON, etc.); when generating the file, the system will ensure the compatibility of the output data with the target format, and perform additional processing according to the specific requirements of the file type (such as adding worksheets in Excel, hierarchical nesting of JSON, etc.) to generate the user-defined data file. In addition, the system will also provide data integrity verification during the export process, and generate a download link or save the file to the specified path after ensuring that it is correct. Users can directly obtain the generated file through the interface and use it later as needed.

[0067] In the above-mentioned dynamic data table export method, by responding to the header information design operation input by the target user in the user interaction interface, the custom header information corresponding to the target user is obtained; according to the custom header information, a data source information export template is constructed; based on the data source interface, according to the data source information export template, data is retrieved from the data source to obtain the data source custom retrieval data; according to the assembly format of the data source information export template, the data source custom retrieval data is assembled into the data source information export template to obtain the user-defined assembled data; according to the user-defined assembled data, a user-defined data file corresponding to the file format specified in the header information design operation is generated.

[0068] Users can freely define header information to meet personalized needs in different business scenarios; the system automatically generates data export templates based on custom header information, avoiding tedious manual setup steps and reducing human errors; and the system is based on standardized data source interfaces to ensure efficient and accurate data retrieval and export. In the data assembly stage, the system automatically assembles the retrieved custom data according to the template format to ensure the uniformity and consistency of the output data structure. Ultimately, users can generate custom data files that meet specific file format requirements, which can reduce the workload required to process the export data format and content, greatly improving the convenience and accuracy of data export and format conversion, and is particularly suitable for complex and changeable data processing scenarios.

[0069] In one embodiment, as shown in FIG. 3 , based on the data source interface, a template is exported according to the data source information, and data is retrieved from the data source to obtain the data source customized retrieval data, including:

[0070] Step 302: parse the data source information export template to obtain information export template feature data.

[0071] The information export template characteristic data may be structured information extracted from the current export template, which contains detailed properties of each field in the template, such as field name, data type, length, format requirements, arrangement order, and the relationship between fields. These characteristic data are used to guide the system on how to retrieve and organize data from the data source, ensuring that the final exported data is consistent with the user-defined template.

[0072] Specifically, the system first performs a comprehensive analysis of the data source information export template. The analysis process goes deep into each field of the template to extract the field name, data type (such as string, integer, date, etc.), field length, formatting rules, and their position in the table. At the same time, the system will check the relationship between fields, such as primary keys, foreign keys or other constraints. The result of the analysis is to generate a detailed feature data set, which contains all field attributes and structure information to extract the information export template feature data. This feature data set not only provides guidance for subsequent data retrieval, but also ensures that the template and data source can be closely connected to avoid field omissions or incorrect matching.

[0073] Step 304, compare the information export template feature data with the historical export template feature data in the data source to obtain a parallel data retrieval instruction.

[0074] The historical export template feature data can be feature information saved by the system from previously used export templates, similar to the feature data of the current export template. It includes the structure and format of the field and the logic used in the historical search. The system compares the feature data of the current template with the data of the historical template to determine whether the previous search logic can be reused to improve the efficiency and accuracy of data search.

[0075] Among them, the parallel data retrieval instructions can be an instruction set generated based on the export template feature data and the results of comparing the historical template, which is used to initiate query operations to multiple data sources or multiple data tables at the same time. These instructions optimize the data query speed and system resource utilization through the parallel processing mechanism, so as to quickly retrieve the custom data that meets the export template requirements and ensure the integrity and accuracy of the data.

[0076] Specifically, after parsing the information export template feature data, the system compares the information export template feature data with the historical export template feature data of the historical export template. During the comparison process, the system will analyze the field differences, data type changes, and field order differences between the information export template feature data and the historical export template feature data. If the template feature data obtained from the partial comparison indicates that the two templates are very similar, the system can reuse the previously generated retrieval logic to avoid duplication of work; if the template feature data obtained from the partial comparison indicates that the two templates are quite different, the system will generate a new retrieval strategy based on the difference, and combine the above two parts of the retrieval strategy to generate parallel data retrieval instructions. In addition, the system will also adjust the data index or query conditions based on the comparison results to ensure the efficiency and accuracy of the retrieval.

[0077] Step 306: retrieve data from the data source according to the parallel data retrieval instruction to obtain data source customized retrieval data.

[0078] Specifically, after generating parallel data retrieval instructions, the system simultaneously initiates parallel query requests to multiple data sources or tables based on the parallel data retrieval instructions. The system adopts parallel processing technology and utilizes multi-threading or distributed computing to maximize the use of system resources and speed up the data retrieval process. Each parallel retrieval task corresponds to a specific field or data block in the template to ensure that the data is processed in the correct order and type during retrieval. In order to ensure the integrity of the retrieval results, the system automatically handles data dependencies, such as cross-table connections, filtering conditions, data sorting, etc. After the retrieval is completed, the system will integrate all sub-query results to form a complete data source custom retrieval data. The data format of the data source custom retrieval data fully meets the requirements of the export template, ensuring that the final data export can be carried out seamlessly.

[0079] In this embodiment, by parsing the data source information export template and comparing it with the historical export template feature data, a parallel data retrieval instruction is generated, thereby realizing intelligent optimization and acceleration of data retrieval. Through this method, the system can efficiently locate relevant data, avoid repeated calculations and unnecessary retrieval processes, and significantly improve the speed and accuracy of data query. At the same time, using the data features of the historical template helps to optimize the query path, reduce resource consumption, and improve the overall performance of the system and user experience.

[0080] In one embodiment, as shown in FIG. 4 , according to the parallel data retrieval instruction, data is retrieved from the data source to obtain the data source customized retrieval data, including:

[0081] Step 402: extract cache retrieval data from the cache of the data source according to the dynamic cache retrieval instruction.

[0082] The dynamic cache retrieval instruction may be an instruction for preferentially extracting data from the cache of the data source. The instruction intelligently matches the data in the cache according to the current query requirements, aiming to reduce the frequency of direct access to the database by utilizing the existing cache data, thereby improving the query speed and system response efficiency.

[0083] The cache retrieval data may be data extracted from the cache, which is usually high-frequency or frequently used data that was temporarily stored during a previous query.

[0084] Specifically, the system checks the cache area of ​​the data source according to the dynamic cache retrieval instruction, and determines to extract the cache data that meets the query conditions. The cache usually contains data generated by previous high-frequency use or approximate queries, so it can greatly reduce the time consumption of directly accessing the underlying data source. The system will intelligently match the current query conditions and the data features in the cache, reuse the previously generated retrieval logic to extract the corresponding part of the data that has been processed, calculated or stored in the load data source information export template from the cache data that meets the query conditions, and the system will also verify the validity of the cached data to ensure that the data meets the latest requirements before use, and finally obtain the cached retrieval data.

[0085] Step 404, according to the conventional dynamic search instruction, retrieve data from the data source to obtain conventional dynamic search data.

[0086] Among them, the regular dynamic retrieval instruction can be an instruction for directly extracting data from the data source. When the data in the cache is insufficient to meet the current query requirements, the system will issue multiple regular dynamic retrieval instructions to execute regular database queries in parallel. It is dynamically generated according to the user's export template and query conditions to ensure that the system can retrieve a complete data set from the underlying data source.

[0087] The conventional dynamic search data may be original data directly obtained from a database or data source through multiple conventional dynamic search instructions in parallel, which is usually complete information not available in the cache and needs to be obtained by querying a database or other external data source.

[0088] Specifically, when the template feature data indicates that the two templates are quite different, that is, the historical export template feature data does not find a match with the information export template feature data, the system initiates direct query operations on the data source based on multiple parallel regular dynamic retrieval instructions. The system generates multiple appropriate query instructions by parsing the user-defined export template, and simultaneously issues requests to the data source or other data sources. During this process, the system applies optimized query strategies, such as index usage, partition retrieval, or batch query, to ensure the efficiency of data retrieval. The system may need to interact with multiple tables or data sources in the same regular dynamic retrieval instruction to extract data that has not been cached. During the processing, the system will also dynamically adjust the retrieval scope and query parameters to respond to real-time changing query requirements to ensure that the required regular dynamic retrieval data is ultimately obtained.

[0089] Step 406: Integrate the cached search data and the conventional dynamic search data to obtain the data source customized search data.

[0090] Specifically, after obtaining the cached retrieval data and the regular dynamic retrieval data, the system first compares the format, type and structure of the two parts of data to ensure that their field names, data types and order are consistent. Subsequently, the system will merge the two parts of data according to the field requirements of the user-defined export template, remove duplicate entries, and ensure the integrity and consistency of the data. The system may also perform additional data conversion or cleaning operations based on business logic to ensure that the final customized retrieval data fully matches the user's needs.

[0091] In this embodiment, efficient data acquisition and integration are achieved by combining dynamic cache retrieval and conventional data retrieval. Cache retrieval is used to extract data that users frequently access, reducing repeated access to data sources, thereby improving retrieval speed and system performance. At the same time, conventional retrieval is combined to ensure data integrity and real-time performance, and the two are finally integrated into custom retrieval data. This method not only improves the efficiency of data retrieval, but also effectively reduces the consumption of system resources and enhances user experience.

[0092] In one embodiment, as shown in FIG5 , according to the conventional dynamic search instruction, data is retrieved from the data source to obtain conventional dynamic search data, including:

[0093] Step 502: Perform complexity analysis on the conventional dynamic search instruction to obtain the search instruction complexity information.

[0094] Complexity analysis can be a detailed evaluation of the retrieval instructions to measure the difficulty and resource consumption of the instruction execution. It takes into account factors such as the tables involved in the query, join operations, filter conditions, field indexes, etc., and predicts the query execution time and computing resource requirements.

[0095] The retrieval instruction complexity information may be a result document of complexity analysis, including detailed data on the complexity of the query instruction, and describes the complexity of various elements of the query (such as the number of tables, connection type, screening conditions, etc.).

[0096] Specifically, the system conducts a detailed analysis of the complexity of conventional dynamic retrieval instructions in order to evaluate the execution cost of the instructions. The key contents of the complexity analysis include: the number of tables involved in the query, the connection types between tables (such as INNER JOIN, OUTER JOIN, etc.), the screening complexity of the query conditions (such as multi-condition screening, subqueries, etc.), and whether there are indexes on the fields. The system calculates the logical complexity of the query, estimates the execution time and computing resource consumption of the retrieval, and identifies potential bottlenecks. The results of the complexity analysis generate a complex information document that includes the complex information of all retrieval instructions, which is used to guide subsequent retrieval optimization steps.

[0097] Step 504: Generate a data source search index based on the complex information of the search instruction.

[0098] Among them, the data source retrieval index can be a structured index generated to accelerate data query, based on the query fields, connection conditions, sorting and other characteristics. It optimizes the data storage structure to ensure that relevant data can be quickly located when executing queries, reduce full table scans and improve retrieval efficiency.

[0099] Specifically, after completing the complexity analysis, the system intelligently adjusts the existing index or creates a new index structure based on the complexity of the retrieval instructions, combined with the field usage in the query, the distribution characteristics of the data, and the access frequency, and dynamically generates an optimized data source retrieval index. The generation of indexes is to speed up the efficiency of data retrieval, including the establishment of temporary or permanent indexes for commonly used filter conditions, connection fields, and sorting fields. This process helps to quickly locate the required data during query execution and reduce the need to scan the entire table, thereby significantly reducing the query execution time and resource usage, especially when processing large-scale data sets.

[0100] Step 506: Select several target query nodes in the data source according to the data source search index.

[0101] The target query node can be a specific location or partition in the data source that contains data related to the query condition. The system analyzes the index and data distribution and intelligently selects these nodes to avoid access to irrelevant data, ensuring that the query only extracts data from the most effective nodes, thereby improving retrieval speed and resource utilization.

[0102] Specifically, based on analyzing all query nodes, it is determined that all query nodes contain data most relevant to the query conditions, and further systematically analyzing the physical storage location of the data, load balancing, and processing capabilities of the nodes, as well as the distribution location of the data, according to the location relationship, data relationship, processing relationship, etc. between the data source retrieval index and the data of each query node, the query nodes that are most suitable for performing the retrieval operation are selected as several target query nodes to ensure that the query can return results in the shortest possible time. A query node can be a specific partition, data fragment, or data storage location in the database.

[0103] Step 508: retrieve data from the data source according to the data source retrieval index and each target query node to obtain conventional dynamic retrieval data.

[0104] Specifically, the system formally initiates data retrieval operations in parallel based on the previously generated data source retrieval index and each target query node. The retrieval process uses the data source retrieval index to accelerate the location of data, and gradually extracts data that meets the query conditions from the data source according to the selected nodes. The system sends parallel query requests to multiple target nodes at the same time to reduce response time, and integrates the data returned from each node. During the integration process, the system performs necessary deduplication, sorting, or conversion operations to ensure data consistency and integrity. Finally, the system outputs these integrated data as regular dynamic retrieval data.

[0105] In this embodiment, the data retrieval process is optimized by performing complexity analysis on conventional dynamic retrieval instructions, generating a data source retrieval index, and selecting a target query node. Complexity analysis enables the system to evaluate the complexity of the retrieval task and perform targeted optimization, and the generated retrieval index accelerates the data location process. By intelligently selecting the target query node, the system effectively reduces unnecessary data scanning and resource usage. The overall method significantly improves retrieval efficiency and shortens response time, especially when processing large-scale data, improving system performance and user experience.

[0106] In one embodiment, as shown in FIG. 6 , after the step of obtaining the custom header information corresponding to the target user in response to the header information design operation input by the target user in the user interaction interface, the method further includes:

[0107] Step 602: retrieve the permission rules and permission configurations corresponding to the target user according to the custom header information.

[0108] Among them, permission rules can be regulations defined in the system to control what data users can access and what operations they can perform. They determine the scope of users' permissions in the system based on their identity, role, department and other attributes, such as the right to access, view, edit or export certain data. Permission rules ensure data security and avoid unauthorized access or operations.

[0109] Among them, permission configuration can be a specific permission setting for a specific user or user group based on permission rules. It includes detailed permission allocation for different data tables, fields or operations, such as a user can read-only access to certain fields, fully access a specific table, or restrict the modification permission of certain sensitive data. Permission configuration is the specific application of permission rules to ensure the security and compliance of system operations.

[0110] Specifically, the system first retrieves the permission rules and configuration files related to the user from the permission management system based on the user's custom header information and identity identifier (such as user ID or role). The system will confirm the user's current permission scope based on the user's role, department, historical operation records, etc. These permission rules include not only the user's access rights to specific data tables, but also the user's permission configuration for specific data fields (such as certain sensitive fields), such as read-only, hidden, or encrypted display. The system will also retrieve dynamic permissions in the configuration files that may be related to time and operation scenarios to ensure that access to data is based on the latest permission rules in the current state.

[0111] Step 604: Determine the target user's customized search permission data according to the permission rules and the permission configurations.

[0112] Among them, the custom search permission data can be the definition of specific data access permissions generated by the system according to the user's permission rules and permission configuration. These data determine the specific data fields and scopes that users can access when performing data retrieval, ensuring that users can only obtain and operate data that they have permission to view or process, thereby ensuring system security and data privacy protection.

[0113] Specifically, after retrieving and analyzing the permission rules and permission configuration, the user can change or not change the permission rules and permission configuration. The system will also parse the specific permission configuration in the permission rules, such as whether the user can access certain specific data tables, fields or records, and whether the user has the right to modify or export specific data. The system will also process special permission requirements related to sensitive data, such as masking certain fields, obfuscating data, or limiting the time range or geographic area of ​​​​the data. Through these analyses, the system generates a custom retrieval permission data based on permissions. This custom retrieval permission data will be used for subsequent query operations to ensure that users can only obtain and operate data that complies with the permission rules. The system will also generate audit logs for user operations to ensure data security and operational compliance.

[0114] In this embodiment, the user's custom search permission data is determined by retrieving the corresponding permission rules and configurations of the user according to the custom header information, thereby achieving precise control over the user's data access. This method ensures that the user can only access the data source content within his or her permission scope when retrieving data, preventing unauthorized data access. Through strict permission management, the system improves data security and compliance, while ensuring the flexibility of user operations, ensuring that users can retrieve and operate data efficiently and safely.

[0115] In one embodiment, as shown in FIG. 7 , according to the permission rules and the permission configurations, the customized search permission data of the target user is determined, including:

[0116] Step 702: Determine the data source retrieval authority of the target user according to the authority rules and the authority configurations.

[0117] Data source retrieval permissions refer to the scope of operations that users can perform when accessing data sources based on their permission rules and configurations. It defines which data tables and fields users can retrieve, whether they can view, edit or export specific data, and limits the access level of data to ensure that users can only obtain and operate data content that meets their authorization.

[0118] Specifically, the system obtains the corresponding permission rules based on the user's identity (such as user ID, role or department, etc.). These rules define the user's access rights to different data tables, fields or operations. Then, the system refines the user's permissions in combination with the permission configuration. For example, some fields may be visible to some users but hidden to other users, or some users may only be able to read-only operations on the data. The system applies these rules and configurations in combination to generate a set of specific data source retrieval permissions for the user, and uses them for subsequent data retrieval operations to ensure that users can only access data source content within their authorized scope.

[0119] Step 704 , in response to the target user's disapproval operation on the user interaction interface regarding the data source retrieval authority, return retrieval authority change information to the user interaction interface and display a retrieval authority change input box.

[0120] The retrieval authority change information may be the relevant information provided when the system prompts the target user to change the authority when the user is dissatisfied with the existing data source retrieval authority, so as to guide the modification request.

[0121] The search permission change input box can be an input area for users to submit permission modification requests in the interactive interface. Users can enter the permission information and reasons they want to change through the input box. The system captures user feedback through the input box and uses this information for subsequent permission review and adjustment processes.

[0122] Specifically, if the user agrees with the system input operation in the user interaction interface for the search authority assigned to the target user by the system administrator, the system will enter the step of "designing an operation in response to the header information input by the target user in the user interaction interface, and obtaining the custom header information corresponding to the target user" to continue execution. If the user disagrees with the system input operation in the user interaction interface for the search authority assigned to the target user by the system administrator, the system captures the user's disagreement operation in the user interaction interface and generates a feedback process. The user submits the reason or request for disagreement through the permission change input box on the interface. When the system determines that the reason or request is reasonable through judging the reason or request for disagreement, the search permission change information is sent to the user interaction interface, so that the user interaction interface displays the search permission change input box, detailing which permissions should be adjusted. This feedback mechanism allows users to have the opportunity to propose change requirements when they encounter permission restrictions that do not meet expectations, and helps system administrators or automated processes capture potential permission setting errors or update requirements. Users can raise questions or modification requirements about their permissions through this step, thereby providing a basis for subsequent permission adjustments.

[0123] Step 706, in response to the target user inputting the identity authentication information and permission change information in the retrieval permission change input box, when it is determined that the permission change information complies with the permission change rules of the target user, the permission rules and each permission configuration are adjusted to obtain updated permission rules and each updated permission configuration.

[0124] Specifically, after receiving a user permission change request, the system first requires the user to authenticate to ensure the legitimacy and security of the operation. Authentication can take many forms, such as entering a password, using two-factor authentication (such as SMS or email verification code), or biometrics (such as fingerprint or facial recognition). After verification, the system will review the permission change information entered by the user, and the server background will review it. After reviewing and determining that the permission change information complies with the permission change rules of the target user, the permission rules and configuration will be adjusted according to the permission change information. The review step may involve the administrator approval process, especially when it involves higher permission changes, to ensure compliance with organizational security policies. The system will update the permission rules based on user needs and verification results, and obtain updated permission rules and each updated permission configuration. For example, expanding its data access scope or modifying permissions for specific fields. This process ensures that permission adjustments are both flexible and secure.

[0125] Step 708: Determine the custom search permission data according to the update permission rule and each update permission configuration.

[0126] Specifically, after the system completes the update of permission rules and configurations, users can continue to change or not change permission rules and permission configurations. Based on the updated permission rules, the system will also re-parse the specific update permission configurations in the update permission rules, such as whether users can access certain specific data tables, fields or records, and whether they have the right to modify or export specific data. The system will also handle special permission requirements related to sensitive data, such as masking certain fields, obfuscating data, or limiting the time range or geographic area of ​​data. Through these analyses, the system generates a custom retrieval permission data based on the updated permissions. Through this process, the system applies the updated permissions to the user's subsequent data retrieval operations, allowing users to access data in accordance with the new permission rules, while ensuring that the operation records and audit logs of permission changes can be updated in a timely manner for future tracking and review.

[0127] In this embodiment, more flexible and accurate permission management is achieved by dynamically adjusting the user's search permissions. The system not only determines the user's data source search permissions based on the permission rules, but also allows the user to initiate permission change requests through the interactive interface when encountering permission restrictions. After identity authentication, the system adjusts the permission rules and configurations in real time to generate updated search permission data. This mechanism improves the flexibility of permission management, ensures that users can obtain appropriate access rights in a timely manner, and at the same time ensures data security and compliance, improving the overall user experience.

[0128] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0129] Based on the same inventive concept, the embodiment of the present application also provides a dynamic data table exporting device for implementing the dynamic data table exporting method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more dynamic data table exporting device embodiments provided below can refer to the limitations of a dynamic data table exporting method above, and will not be repeated here.

[0130] In one embodiment, as shown in FIG. 8 , a dynamic data table export device is provided, comprising: a table header information acquisition module 802, an export template construction module 804, a retrieval data acquisition module 806, an assembly data acquisition module 808 and a data file generation module 810, wherein:

[0131] The header information acquisition module 802 is used to obtain the custom header information corresponding to the target user in response to the header information design operation input by the target user in the user interaction interface;

[0132] The export template construction module 804 is used to construct a data source information export template according to the custom header information;

[0133] The retrieval data obtaining module 806 is used to derive a template according to the data source information based on the data source interface, retrieve data from the data source, and obtain the data source customized retrieval data;

[0134] The assembly data obtaining module 808 is used to assemble the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain the user customized assembly data;

[0135] The data file generation module 810 is used to generate a user-defined data file corresponding to the file format specified in the header information design operation according to the user-defined assembly data.

[0136] In one embodiment, the retrieval data acquisition module 806 is also used to parse the data source information export template to obtain information export template feature data; compare the information export template feature data with the historical export template feature data in the data source to obtain parallel data retrieval instructions; retrieve data from the data source according to the parallel data retrieval instructions to obtain data source customized retrieval data.

[0137] In one embodiment, the retrieval data obtaining module 806 is also used to extract cache retrieval data from the cache of the data source according to dynamic cache retrieval instructions; the cache retrieval data is the data frequently retrieved by the target user in the data source; according to regular dynamic retrieval instructions, the data is retrieved from the data source to obtain regular dynamic retrieval data; the cache retrieval data and the regular dynamic retrieval data are integrated to obtain the data source customized retrieval data.

[0138] In one embodiment, the retrieval data acquisition module 806 is also used to perform complexity analysis on conventional dynamic retrieval instructions to obtain retrieval instruction complexity information; generate a data source retrieval index based on the retrieval instruction complexity information; select several target query nodes in the data source based on the data source retrieval index; retrieve data from the data source based on the data source retrieval index and each target query node to obtain conventional dynamic retrieval data.

[0139] In one embodiment, the export template construction module 804 is also used to retrieve the permission rules and permission configurations corresponding to the target user based on the custom header information; determine the custom retrieval permission data of the target user based on the permission rules and permission configurations; the custom retrieval permission data is used to limit the scope of activities of the target user in the data source.

[0140] In one embodiment, the export template construction module 804 is also used to determine the data source retrieval authority of the target user based on the authority rules and each authority configuration; in response to the target user's disapproval operation on the user interaction interface regarding the data source retrieval authority, return the retrieval authority change information to the user interaction interface and display the retrieval authority change input box; in response to the identity authentication information and authority change information entered by the target user in the retrieval authority change input box, when it is determined that the authority change information complies with the authority change rules of the target user, adjust the authority rules and each authority configuration to obtain the update authority rules and each update authority configuration; according to the update authority rules and each update authority configuration, determine the custom retrieval authority data.

[0141] Each module in the above-mentioned dynamic data table exporting device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0142] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG9 . The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store server data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a dynamic data table export method is implemented.

[0143] Those skilled in the art will understand that the structure shown in FIG. 9 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0144] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0145] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0146] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-mentioned method embodiments.

[0147] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0149] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for exporting a dynamic data table, characterized in that: The method comprises: In response to a header information design operation input by a target user in a user interaction interface, obtaining custom header information corresponding to the target user; Constructing a data source information export template according to the custom header information; Based on the data source interface, a template is exported according to the data source information, data is retrieved from the data source, and data source customized retrieval data is obtained; Assembling the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data; A user-defined data file corresponding to the file format specified in the header information design operation is generated according to the user-defined assembly data.

2. The method according to claim 1, characterized in that: Based on the data source interface, exporting a template according to the data source information, retrieving data from the data source, and obtaining the data source customized retrieval data, includes: Parsing the data source information export template to obtain information export template feature data; Comparing the information export template feature data with the historical export template feature data in the data source to obtain a parallel data retrieval instruction; According to the parallel data retrieval instruction, data is retrieved from the data source to obtain the data source customized retrieval data.

3. The method according to claim 2, characterized in that The parallel data retrieval instructions include dynamic cache retrieval instructions and conventional dynamic retrieval instructions; the step of retrieving data from the data source according to the parallel data retrieval instructions to obtain the data source customized retrieval data includes: Extracting cache retrieval data from the cache of the data source according to the dynamic cache retrieval instruction; the cache retrieval data is data frequently retrieved by the target user in the data source; Retrieving data from the data source according to the conventional dynamic retrieval instruction to obtain conventional dynamic retrieval data; The cache retrieval data and the conventional dynamic retrieval data are integrated to obtain the data source customized retrieval data.

4. The method according to claim 3, characterized in that The retrieving data from the data source according to the conventional dynamic retrieval instruction to obtain conventional dynamic retrieval data includes: Performing complexity analysis on the conventional dynamic search instruction to obtain complex information of the search instruction; Generate a data source search index according to the complex information of the search instruction; According to the data source retrieval index, select a number of target query nodes in the data source; According to the data source retrieval index and each of the target query nodes, data is retrieved from the data source to obtain the conventional dynamic retrieval data.

5. The method according to any one of claims 1 to 4, characterized in that: Before the step of obtaining the custom header information corresponding to the target user in response to the header information design operation input by the target user in the user interaction interface, the method further includes: According to the custom header information, retrieve the permission rules and permission configurations corresponding to the target user; According to the permission rules and each permission configuration, the custom search permission data of the target user is determined; the custom search permission data is used to limit the activity scope of the target user in the data source.

6. The method according to claim 5, characterized in that Determining the custom search permission data of the target user according to the permission rule and each permission configuration, the method further comprises: Determine the data source retrieval authority of the target user according to the authority rules and each of the authority configurations; In response to the target user's disapproval operation on the user interaction interface regarding the data source retrieval authority, returning retrieval authority change information to the user interaction interface and displaying a retrieval authority change input box; In response to the identity authentication information and permission change information input by the target user in the search permission change input box, if it is determined that the permission change information complies with the permission change rule of the target user, adjusting the permission rule and each permission configuration to obtain an updated permission rule and each updated permission configuration; The customized retrieval authority data is determined according to the update authority rule and each of the update authority configurations.

7. A dynamic data table export device, characterized in that: The device comprises: A header information acquisition module, used to respond to a header information design operation input by a target user in a user interaction interface, and acquire custom header information corresponding to the target user; An export template construction module, used to construct a data source information export template according to the custom header information; A retrieval data acquisition module is used to retrieve data from the data source based on the data source interface and the data source information to obtain the data source customized retrieval data; An assembly data obtaining module is used to assemble the data source customized search data into the data source information export template according to the assembly format of the data source information export template to obtain user customized assembly data; A data file generation module is used to generate a user-defined data file corresponding to the file format specified in the header information design operation according to the user-defined assembly data.

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

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

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

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