Lightweight data display method and device integrating GIS spatial analysis capabilities

Abstract

The present application discloses a data lightweight display method and device integrating GIS spatial analysis capabilities, and relates to the field of GIS geographic information technology. The database is standardized through a parameter standardization module, and the data of different types of databases are efficiently converted into standard format data required for subsequent use, so as to be compatible with different GIS software; the standardized data is then classified using GIS software and stored in a buffer. Compared with the traditional method of searching for target data from raw data, the present application realizes data lightweight by preprocessing and encapsulating the data, speeding up the extraction speed of target data in the subsequent analysis event process, effectively improving data management capabilities, and solving problems such as slow loading speed and browser freeze when facing big data.

Description

Technical Field

[0001] The present application relates to the field of GIS geographic information technology, and in particular to a data lightweight display method and device integrating GIS spatial analysis capabilities. Background Art

[0002] At present, the Geographic Information System (GIS) has been developed very maturely both at home and abroad, but the most widely used application in the market is still map browsing, and further applications such as GIS-based visualization analysis have not yet been deepened.

[0003] There are two reasons for this problem: first, there are many types of GIS software on the market, and the technical architectures and spatial analysis methods they use are also different, which brings obstacles to cross-platform spatial data analysis; second, with the development of geographic information systems, the amount of spatial data resources is increasing, and the traditional direct loading of full data for analysis will cause a series of problems such as browser crashes and slow loading; third, existing GIS software focuses more on basic capability development and does not have a good interactive interface, resulting in a high threshold for use. Summary of the invention

[0004] Based on this, it is necessary to provide a data lightweight display method and device that integrates GIS spatial analysis capabilities to address the above technical problems, which can effectively solve problems such as the inability to load and display large amounts of spatial data and the unintuitive nature of the display, and improve the application capabilities of the GIS geographic information system.

[0005] In the first aspect, the present application provides a data lightweight display method integrating GIS spatial analysis capabilities. The method includes:

[0006] Identify the database type to be connected, call the adapted parameter standardization module for the database type, and generate standardized data; the standardized data includes the field space coefficient, which is used to characterize the spatial position;

[0007] The spatial aggregation capability of GIS software is used to classify the standardized data according to the spatial coefficient, and the classified standardized data is stored in the corresponding buffer in a distributed node structure;

[0008] The standardized data stored in the buffer is called to establish an interaction model related to the analysis event.

[0009] In one embodiment, calling an adapted parameter standardization module for a database type to generate standardized data includes:

[0010] The table field information and the records corresponding to the table field information are read from the database through the adapted parameter standardization module, several groups of configuration parameters are generated according to the table field information and the records, and the configuration parameters are cleaned and formatted to obtain standardized data.

[0011] In one embodiment, classifying the standardized data according to the spatial coefficients and storing the classified standardized data in a corresponding buffer in a distributed node structure includes:

[0012] Cluster the standardized data within the same range based on the spatial coefficient and fixed spatial resources, obtain the clustering results and assign corresponding attribute categories;

[0013] Based on the previous clustering result, the standardized data of the same attribute category are clustered, the current clustering result is obtained and the corresponding attribute category is assigned; the clustering operation is iterated until the current clustering result restores the accuracy of the standardized data, and according to each clustering result and the corresponding attribute category, the standardized data is stored in the corresponding buffer in a distributed node structure.

[0014] In one embodiment, the distributed nodes are multi-level structures, the upper level node is the master node of the lower level node, the lower level node is the child node of the upper level node, each master node corresponds to at least one child node, and each child node corresponds to only one master node;

[0015] Among them, the nodes contain data clusters composed of standardized data of the same attribute category, and the data clusters contained in the master node are divided into corresponding slave nodes according to the clustering results; the data clusters contained in each node are stored in a buffer named after the attribute category.

[0016] In one embodiment, each node includes a sub-chain distributed mapping table, and the sub-chain distributed mapping table includes at least one sub-chain identifier and a sub-node corresponding to the sub-chain identifier.

[0017] In one embodiment, a sequence number field is generated, a mapping relationship between the sequence number field and the standardized data is constructed, and the standardized data is stored in a buffer in a sequence number form according to the mapping relationship.

[0018] In the second aspect, the present application also provides a data lightweight display device integrating GIS spatial analysis capabilities. The device includes:

[0019] The standardization processing module is used to identify the type of database connected, call the adapted parameter standardization module according to the database type, and generate standardized data; the standardized data includes field space coefficients, and the space coefficients are used to represent the spatial position;

[0020] The lightweight processing module is used to classify the standardized data according to the spatial coefficient using the spatial aggregation capability of the GIS software, and store the classified standardized data in the corresponding buffer in a distributed node structure;

[0021] The spatial fusion display module is used to call the standardized data stored in the buffer and establish an interactive model related to the analysis event.

[0022] In a third aspect, the present application further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the above-mentioned data lightweight display method integrating GIS spatial analysis capabilities are implemented.

[0023] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-mentioned data lightweight display method integrating GIS spatial analysis capabilities.

[0024] In a fifth aspect, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned data lightweight display method integrating GIS spatial analysis capabilities are implemented.

[0025] The above-mentioned data lightweight display method and device integrating GIS spatial analysis capabilities include: identifying the type of database connected, calling the adapted parameter standardization module for the database type, and generating standardized data; the standardized data includes field spatial coefficients, and the spatial coefficients are used to characterize the spatial position; using the spatial aggregation capability of the GIS software to classify the standardized data according to the spatial coefficients, and storing the classified standardized data in the corresponding buffer in a distributed node structure; calling the standardized data stored in the buffer to establish an analysis event-related interaction model. The present application standardizes the database through the parameter standardization module, and efficiently converts the data of different types of databases into the standard format data required for subsequent use, so as to be compatible with different GIS software; the standardized data is then classified by the GIS software and stored in the buffer. Compared with the traditional method of searching for target data from the original data, the present application realizes data lightweight by pre-processing and encapsulating the data, which speeds up the extraction speed of target data in the subsequent analysis event process, effectively improves the data management capability, and solves the problems of slow loading speed and browser freeze when facing big data. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of a process of a data lightweight display method integrating GIS spatial analysis capabilities in one embodiment;

[0027] Figure 2 A schematic diagram of a process for generating standardized data in one embodiment;

[0028] Figure 3 A schematic diagram of a data lightweight processing flow in one embodiment;

[0029] Figure 4 is a schematic diagram of a process of clustering a standard data set in one embodiment;

[0030] Figure 5 is a schematic diagram of the structure of a distributed node in one embodiment;

[0031] Figure 6 A flowchart for visual display in an embodiment. DETAILED DESCRIPTION

[0032] 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.

[0033] The present application embodiment provides a data lightweight display method integrating GIS spatial analysis capabilities, such as Figure 1 As shown, the following steps are included:

[0034] Step 102, identifying the type of database to be connected, calling an adapted parameter standardization module for the database type, and generating standardized data; the standardized data includes a field spatial coefficient, and the spatial coefficient is used to characterize a spatial position.

[0035] The original database usually has a default database type. The front-end database is set up and all collected data is first entered into the front-end database. The original spatial data format is diverse, and the fields representing spatial attributes are also different. Conventional fields include X / Y, longitude / latitude, or independent shape space (the standard format for storing spatial data in GIS) fields. In addition, there are many formats of the front-end database, such as Postgresql, Mysql, Oracle, Elasticsearch, etc. The diverse data formats and database types make data processing very difficult.

[0036] The traditional method uses tools such as DataFileConverter data conversion tool, DataLoader database file conversion tool, etc. to manually convert different databases into the required database types and manually extract the required fields. The operation is cumbersome and has a high threshold.

[0037] Regarding this issue, Figure 2As shown, this embodiment customizes the corresponding parameter standardization module for the existing database type. For example, if the database type is A, the parameter standardization module corresponding to database A is used to store the data in the preset database. If the database type is B, the parameter standardization module corresponding to database B is used to store the data in the preset database. Different database types are finally integrated into the same database. Data in different databases can be distinguished by different names, such as table_name001, table_name002, etc.

[0038] In this embodiment, a general JAVA service model is set, which includes a number of parameter standardization modules corresponding to different database types. After the JAVA service is started, the corresponding parameter standardization module is matched according to the database type for processing.

[0039] In one embodiment, in step 102, an adapted parameter standardization module is called for the database type to generate standardized data, including: reading table field information and records corresponding to the table field information from the database through the adapted parameter standardization module, generating several groups of configuration parameters according to the table field information and records, and performing data cleaning and formatting processing on the configuration parameters to obtain standardized data.

[0040] In the preset database, connect to the front-end database, and read the table field information of the front-end database through query commands such as sp_help table_name. The table field information is such as: code, msg, cout, data, cameraId, cameraVtduID, etc., and read the records corresponding to the table field information. Based on the fields of the preset database, several groups of configuration parameters are generated and stored in the preset database.

[0041] In addition, when generating configuration parameters, gid, version, and geom field information are automatically added. gid indicates the number of the configuration parameter group, version refers to the version, and geom refers to the spatial coefficient. The spatial coefficient is obtained based on the location-related data extracted from the front-end database. For example, the longitude / latitude can be extracted to calculate the spatial coefficient, or the X / Y coordinates can be extracted to calculate the spatial coefficient. The longitude / latitude and X / Y are different expressions of the geographic coordinate system, respectively. The former is a spherical coordinate system, and the latter is a rectangular coordinate system.

[0042] Furthermore, the parameter standardization module of this embodiment will also perform data cleaning and formatting on the configuration parameters to improve data quality.

[0043] This embodiment automatically integrates different types of databases through a parameter standardization module, and automatically reads the database to uniformly generate configuration parameters in a standard format. At the same time, it automatically standardizes spatial positions in different formats into spatial coefficients. Finally, the standardized data obtained can be directly used by various GIS software, which greatly reduces the labor and time costs of data processing. The development of the parameter standardization module helps to lower the threshold of data processing and is conducive to the advancement of GIS spatial analysis.

[0044] Step 104, using the spatial aggregation capability of the GIS software to classify the standardized data according to the spatial coefficient, and storing the classified standardized data in a corresponding buffer in a distributed node structure.

[0045] The main purpose of this step is to achieve data lightweight for the standardized data stored in the preset database.

[0046] This step requires the deployment of GIS software modules. GIS software can be mainstream software on the market. The prerequisite is that it must have spatial analysis capabilities. Spatial analysis capabilities should include but not be limited to cache query, topology analysis, network analysis and other functions.

[0047] like Figure 3 As shown, this step also needs to determine whether it is standardized data. The core element of determining standardized data is that it must contain five parameters: the serial number field gid, version, geom, longitude field and latitude field. The core element is that the spatial longitude and latitude coordinate system is the CGCS2000 coordinate system. If it is not standardized data, then return to step 102 for processing. If it is already standardized data, then enter the GIS software-based processing flow.

[0048] Step 104 is mainly aimed at standardized data and distributed nodes. Standardized data is independent of distributed nodes. Distributed nodes are aggregated from standardized data. The scheduling of the underlying standardized data is completed through the spatial aggregation capability of GIS software.

[0049] Spatial aggregation capability is to aggregate according to the set model rules, assign data within the same spatial range to one class, and perform lightweight data storage. Among them, the same spatial range is determined based on the spatial coefficient. Through a fixed spatial resource model (the model specifies the size of the spatial range), the spatial computing capability of the GIS software is used to assign corresponding attribute categories and lightweight storage of the standardized data of this category. Here, lightweight storage adopts the method of attachment. Each standardized configuration parameter group generates a corresponding serial number field, and a mapping relationship between the serial number field and the standardized data is constructed. According to the mapping relationship, the standardized data is stored in the buffer in the form of a serial number, thereby improving the efficiency of data search and the utilization of storage resources, computing resources, and network resources. In addition, the attachment method can realize cross-platform operation between the database and the GIS software. When data is updated in the database, the data processed by the GIS software will also be updated accordingly to ensure data consistency.

[0050] When the standardized data is obtained, a buffer is created through GIS software. The buffer can be a point, line or surface feature, covering the given standardized data. Each buffer is used as a unit of distributed nodes. Each buffer receives the execution results of the standardized data classified by the GIS software and stores them to form a corresponding node.

[0051] In one embodiment, step 104 includes: clustering the standardized data within the same range based on the spatial coefficient and the fixed spatial resources, obtaining the clustering results and assigning the corresponding attribute categories; clustering the standardized data of the same attribute category based on the previous clustering results, obtaining the current clustering results and assigning the corresponding attribute categories; iterating the clustering operation until the current clustering result restores the accuracy of the standardized data, and storing the standardized data in the corresponding buffer in a distributed node structure according to each clustering result and the corresponding attribute category.

[0052] Specifically, if Figure 4 , cluster the standardized data a1, a2, a3, etc. in the same range according to the preset rules to obtain m classes, and assign corresponding attribute categories to each class, such as m1, m2, m3, etc. Further cluster m1 to obtain n classes, and assign corresponding attribute categories to each class, such as n1, n2, n3, etc. Further cluster n1, and so on, until the accuracy of the standardized data is restored, that is, clustering to a class with only one set of configuration parameters. Perform the above operations on other categories of the m classes. Finally, the standardized data of the same type obtained by each clustering is stored in the same buffer to form nodes, and clusters of nodes of different types form distributed nodes.

[0053] The distributed nodes have a multi-level structure. The upper-level node is the master node of the lower-level node, and the lower-level node is the child node of the upper-level node. Each master node corresponds to at least one child node, and each child node corresponds to a unique master node. The nodes contain data clusters composed of standardized data of the same attribute category. The data clusters contained in the master node are divided into corresponding slave nodes according to the clustering results. The data clusters contained in each node are stored in a buffer named after the attribute category.

[0054] The nodes are arranged hierarchically according to the number of times they are clustered, forming a multi-level distributed node structure, for example Figure 5 As shown, the first-level dispersed nodes include three nodes obtained by clustering once, and the second-level dispersed nodes include 3*n nodes obtained by clustering once again based on the first-level dispersed nodes, that is, each node of the second-level dispersed nodes has undergone two clustering operations in total. And so on.

[0055] In one embodiment, each node includes a sub-chain distributed mapping table, and the sub-chain distributed mapping table includes at least one sub-chain identifier and a sub-node corresponding to the sub-chain identifier.

[0056] The sub-node associated with the sub-chain identifier corresponding to the node can be determined in each node through the sub-chain distributed mapping table. Among them, the sub-chain distributed mapping table contains one or more sub-chain identifiers and the sub-nodes associated with each sub-chain identifier, and the number of sub-chain identifiers associated with each node is one or more. In specific implementation, the sub-chain distributed mapping table is obtained; in the sub-chain distributed mapping table, the node corresponding to the first sub-chain identifier is determined as the first sub-node, the node corresponding to the second sub-chain identifier is determined as the second sub-node, and so on.

[0057] In one embodiment, a temporary log is created to manage the process of nodes being designated for display, and to record the event chain including the subchain identifier and the node. In this embodiment, the event chain may include multiple chains, but there is a subchain identifier between two adjacent nodes in each event chain. For example, the first-level decentralized node specifies a node A1, the second-level decentralized node specifies two slave nodes B1 and B2 of node A1, and the third-level decentralized node specifies a slave node C1 of node B1. Then, the temporary log records two event chains, one is A1-B1-C1 and the other is A1-B2. Next, the number of nodes in the event chain is obtained. If the number has reached the preset number of nodes, a temporary progress bar is generated for the event chain, and interactive elements are added to the progress bar to allow specific node jumps to be achieved through interactive elements.

[0058] In addition, the temporary log also includes the time when each node is specified. If the node specified time and the previous level node specified time exceed the preset time, a mark of the node is added to the progress bar, allowing interactive elements to jump to the node position corresponding to the mark.

[0059] Through the above embodiments, the display problem that may be caused when the depth of distributed nodes is high is effectively improved. When the user needs to return to a specified node or needs to compare different nodes, the user can jump to the specified node through the event chain and progress bar recorded in the temporary log, thereby achieving more efficient spatial display capabilities.

[0060] In one embodiment, in order to ensure the integrity of the data, the key attribute field information is automatically summarized, filtered and solidified, and the data content cannot be eliminated in the process of lightweight data.

[0061] In one embodiment, further data lightweight processing can be performed by deduplication, grouping, merging and elimination methods.

[0062] In one embodiment, lightweight data can be automatically generated and manually maintained for management, such as setting range parameters and attribute attachment model parameters and other management functions, and lightweight data can be updated and stored.

[0063] In one embodiment, in order to further encapsulate the data for subsequent visual display, a data parameter value is set. When the parameter value is exceeded, a special message is displayed, thereby providing a special effect alarm function for the subsequent visual display.

[0064] Step 106, calling the standardized data stored in the buffer and establishing an analysis event-related interaction model.

[0065] This step mainly realizes data display, including two categories: spatial capability fusion display and chart visualization display.

[0066] Spatial capability fusion display uses the spatial fusion capability of GIS software to display the GIS map visualization function. The spatial algorithm of GIS software is integrated into a fixed model and used directly by the front end. The specific operations are as follows: Figure 6 As shown. Spatial capability fusion first establishes spatial analysis event-related data models (model 1, model 2, model 3, ..., model N), calls the data input model of the analysis event-related buffer, and establishes the analysis event-related interaction model. Taking the visualization display effect of regional range map model 1 as an example, the regional range parameter is set to A (i.e., spatial coefficient), the displayed data is set to parameter B (i.e., configuration parameter), A and B are input into map model 1, and the GIS geometric analysis service capability is used to output data C. Externally, only the A and B parameters need to be set to realize the visualization display of the results of C on the map as visual results.

[0067] Chart visualization encapsulates commonly used visualization charts, determines chart grouping and classification, such as chart class - bar chart; designs rendering configuration display types corresponding to chart attributes and data attributes; designs relationships corresponding to chart data source modules, and publishes components to the chart warehouse; adds published charts to the chart list of the visualization system for selection and use by the visualization system editor, including modules such as regular charts (bar charts, line charts, pie charts, etc.), text, media, events, application areas, lists, etc. Chart visualization includes management editor functions, and visualization charts added in the function include top, bottom, move up one layer, move down one layer, combine, uncombine, lock, unlock, show, hide, copy style, apply style, copy data, apply data, rename, copy, favorite, and delete functions; includes visualization operation management functions, that is, drag charts from the chart list to this area, you can arbitrarily combine charts and customize chart styles and data source configurations.

[0068] In summary, the main creativity of the present invention lies in: 1. A method for encapsulating multiple data sources, especially a processing method that protects the use of standard model services to convert the format into a standardized format of a spatial database; 2. Preprocessing and packaging data based on the capabilities of GIS software to make it lightweight.

[0069] Compared with the prior art, the advantages of the present invention are: 1. The present invention can visualize and express multi-source data, support multiple data formats, and quickly standardize storage; 2. Through a lightweight implementation method, it effectively solves the problems of large data volume, inability to load images, browser freezes, etc.; 3. It solves the problems of high difficulty in use and high debugging cost encountered by users in the process of using GIS spatial capabilities; 4. Based on the spatial capabilities and data fusion capabilities of GIS software, you can easily select the charts you need from the chart warehouse, and you can also publish your own charts to the chart market, avoiding the need for users to spend a lot of time adjusting the properties, data sources, and layout of the charts each time, greatly improving the efficiency of spatial analysis.

[0070] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0071] Based on the same inventive concept, the embodiment of the present application also provides a data lightweight display device integrating GIS spatial analysis capability for implementing the data lightweight display method integrating GIS spatial analysis capability 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 embodiments of one or more data lightweight display devices integrating GIS spatial analysis capability provided below can refer to the limitations of the data lightweight display method integrating GIS spatial analysis capability above, and will not be repeated here.

[0072] In one embodiment, a data lightweight display device integrating GIS spatial analysis capabilities is provided, including:

[0073] The standardization processing module is used to identify the type of database connected, call the adapted parameter standardization module according to the database type, and generate standardized data; the standardized data includes field space coefficients, and the space coefficients are used to represent the spatial position;

[0074] The lightweight processing module is used to classify the standardized data according to the spatial coefficient using the spatial aggregation capability of the GIS software, and store the classified standardized data in the corresponding buffer in a distributed node structure;

[0075] The spatial fusion display module is used to call the standardized data stored in the buffer and establish an interactive model related to the analysis event.

[0076] Each module in the above-mentioned data lightweight display device integrating GIS spatial analysis capabilities can be implemented in whole or in part through software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the hardware structure, or can be stored in the memory in the computer device in the software structure, so that the processor can call and execute the corresponding operations of the above modules.

[0077] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in all the above method embodiments when executing the computer program.

[0078] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in all the above method embodiments are implemented.

[0079] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in all the above method embodiments when executed by a processor.

[0080] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0081] 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 a variety of structures, 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.

[0082] 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.

[0083] 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 lightweight data display method integrating GIS spatial analysis capabilities, characterized in that: The method comprises: Identify the type of database to be connected, call an adapted parameter standardization module for the database type, and generate standardized data; the standardized data includes a field space coefficient, and the space coefficient is used to characterize a spatial position; Using the spatial aggregation capability of GIS software to classify the standardized data according to the spatial coefficient, the classified standardized data is stored in a corresponding buffer in a decentralized node structure and hanging manner; Calling the standardized data stored in the buffer to establish an analysis event-related interaction model; The distributed node is a multi-level structure, the upper level node is the master node of the lower level node, the lower level node is the child node of the upper level node, each master node corresponds to at least one child node, and each child node corresponds to a unique master node; each node includes a sub-chain distributed mapping table, and the sub-chain distributed mapping table includes at least one sub-chain identifier and the child node corresponding to the sub-chain identifier; The method also includes creating a temporary log for managing the process of each node in the decentralized node being designated for display, recording the event chain including the sub-chain identifier and the node, obtaining the number of nodes in the event chain, and if the number has reached a preset number of nodes, generating a temporary progress bar for the event chain, and adding interactive elements to the progress bar, allowing specific node jumps to be achieved through the interactive elements; the temporary log includes the time when each node is designated, and if the time difference between the current node designated time and the previous level node designated time exceeds the preset time, a mark of the current node is added to the progress bar, allowing jumps to the current node position corresponding to the mark through the interactive elements.

2. The method according to claim 1, characterized in that The calling of the adapted parameter standardization module for the database type to generate standardized data comprises: The table field information and the records corresponding to the table field information are read from the database through the adapted parameter standardization module, several groups of configuration parameters are generated according to the table field information and the records, and the configuration parameters are cleaned and formatted to obtain the standardized data.

3. The method according to claim 1, characterized in that The classifying the standardized data according to the spatial coefficient and storing the classified standardized data in a corresponding buffer in a distributed node structure includes: Clustering the standardized data within the same range based on the spatial coefficient and the fixed spatial resources, obtaining clustering results and assigning corresponding attribute categories; Based on the last clustering result, the standardized data of the same attribute category are clustered, the current clustering result is obtained and the corresponding attribute category is assigned; the clustering operation is iterated until the current clustering result restores the accuracy of the standardized data, and according to each clustering result and the corresponding attribute category, the standardized data is stored in the corresponding buffer in a distributed node structure.

4. The method according to claim 3, characterized in that: The nodes contain data clusters consisting of the standardized data of the same attribute category, and the data clusters contained in the master node are divided into corresponding slave nodes according to the clustering results; the data clusters contained in each node are correspondingly stored in the buffer named after the attribute category.

5. The method according to claim 3, characterized in that: Generate a sequence number field, construct a mapping relationship between the sequence number field and the standardized data, and store the standardized data in the buffer in a sequence number form according to the mapping relationship.

6. A data lightweight display device integrating GIS spatial analysis capabilities, characterized in that: The device comprises: A standardization processing module is used to identify the type of database connected, call an adapted parameter standardization module for the database type, and generate standardized data; the standardized data includes a field space coefficient, and the space coefficient is used to characterize the spatial position; A lightweight processing module, used to classify the standardized data according to the spatial coefficient using the spatial aggregation capability of the GIS software, and store the classified standardized data in a corresponding buffer in a decentralized node structure and attachment manner; A spatial fusion display module, used to call the standardized data stored in the buffer and establish an interactive model related to the analysis event; The distributed node is a multi-level structure, the upper level node is the master node of the lower level node, the lower level node is the child node of the upper level node, each master node corresponds to at least one child node, and each child node corresponds to a unique master node; each node includes a sub-chain distributed mapping table, and the sub-chain distributed mapping table includes at least one sub-chain identifier and the child node corresponding to the sub-chain identifier; The spatial fusion display module is also used to create a temporary log, which is used to manage the process of each node in the decentralized node being designated for display, record the event chain including the sub-chain identifier and the node, obtain the number of nodes in the event chain, and if the number has reached the preset number of nodes, generate a temporary progress bar for the event chain, and add interactive elements to the progress bar, allowing specific node jumps to be achieved through the interactive elements; the temporary log includes the time when each node is designated. If the time difference between the current node designated time and the previous level node designated time exceeds the preset time, a mark of the current node is added to the progress bar, allowing jumps to the current node position corresponding to the mark through interactive elements.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. 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 5 are implemented.

9. 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 5 are implemented.

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