A point data aggregation method, device, equipment and computer storage medium

Abstract

The application discloses a point data aggregation method and device, equipment and a computer storage medium, wherein the point data aggregation method comprises the following steps: determining a storage data table of a to-be-aggregated map, the storage data table storing pre-aggregated point data of the to-be-aggregated map at a plurality of map levels; acquiring area coordinates corresponding to the to-be-aggregated map and a target map level, the target map level being any one of the plurality of map levels; determining target point data from the storage data table, the target point data being the pre-aggregated point data located within the area coordinates at the target map level; and performing point aggregation on the target point data to obtain a point aggregation result corresponding to the to-be-aggregated map. The technical problem of browser lag and calculation delay in the prior art when aggregating point data of a digital map is solved.

Description

Technical Field

[0001] This application relates to the field of digital map technology, and in particular to a method, apparatus, device, and computer storage medium for point data aggregation. Background Technology

[0002] With the development of information technology, the functions of web pages have become more diverse. Digital maps combine traditional maps with web pages, allowing people to query location information for any place, greatly facilitating people's lives.

[0003] When displaying scattered point data on a digital map, in order to avoid the display interface from being cluttered, overlapping, or lagging due to too much data, point data within the same geographical area can be merged, which is called point aggregation.

[0004] Existing point aggregation algorithms include distance-based point aggregation algorithms, in which the full data of the target area is loaded into the browser cache. A large amount of data can cause browser lag, especially on high-resolution video walls, where the lag and delay are more pronounced. Summary of the Invention

[0005] This application provides a method, apparatus, device, and computer storage medium for point data aggregation, which solves the technical problems of browser lag and computational delay when aggregating point data on digital maps.

[0006] In view of this, the first aspect of this application provides a method for point data aggregation, including:

[0007] Determine the storage data table of the map to be aggregated, wherein the storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels;

[0008] Obtain the region coordinates and target map level corresponding to the map to be aggregated, wherein the target map level is any one of the plurality of map levels;

[0009] From the stored data table, the target point data is determined, which is the pre-aggregated point data located within the coordinates of the region under the target map level;

[0010] The target point data is aggregated to obtain the point aggregation result corresponding to the map to be aggregated.

[0011] Optionally, the configuration process for the pre-aggregated location data includes:

[0012] Obtain the base map of the map to be aggregated, wherein the base map is the map of the map to be aggregated at the highest map level;

[0013] The baseline map is divided into grids to obtain several grids;

[0014] Obtain the pre-aggregation algorithm corresponding to the first map level, where the first map level is any one of the plurality of map levels;

[0015] Using the aforementioned pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain the pre-aggregated point data under the first map level.

[0016] Optionally, the pre-aggregation algorithm is used to pre-aggregate the point data in each grid to obtain pre-aggregated point data at the first map level, specifically including:

[0017] Obtain the number of operations performed on the point data in the pre-aggregation algorithm;

[0018] According to the number of operations, the point data in each grid is grouped to obtain several groups and the point data corresponding to each group;

[0019] The point data in each group is calculated according to the pre-aggregation algorithm to obtain the pre-aggregated point data under the first map level.

[0020] Optionally, the point data in each group is calculated according to the pre-aggregation algorithm to obtain pre-aggregated point data at the first map level, specifically including:

[0021] Count the total number of data points in each group;

[0022] The average coordinates are obtained by averaging the geographic coordinates of the points in each group.

[0023] Based on the total number and average coordinates of all groups, the pre-aggregated point data under the first map level.

[0024] Optionally, the method further includes:

[0025] Render the point aggregation result, and use the rendered point aggregation result to load the map to be aggregated.

[0026] Optionally, the method further includes:

[0027] After the map to be aggregated is loaded, when a movement command for the map to be aggregated is received, the movement coordinates are obtained;

[0028] Based on the movement coordinates and the area coordinates, determine the new area coordinates corresponding to the movement command;

[0029] Based on the new region coordinates, determine the new point aggregation result corresponding to the movement command.

[0030] Optionally, the method further includes:

[0031] After the map to be aggregated is loaded, when a zoom command for the map to be aggregated is received, the zoom coordinates and the zoom map level are obtained;

[0032] Based on the scaling coordinates and the region coordinates, determine the new region coordinates corresponding to the scaling instruction;

[0033] Delete the point aggregation result, and determine the new point aggregation result corresponding to the zoom command based on the zoom map level and the new area coordinates.

[0034] A second aspect of this application provides a location data aggregation device, comprising:

[0035] The first determining unit is used to determine the storage data table of the map to be aggregated, wherein the storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels;

[0036] The first acquisition unit is used to acquire the regional coordinates and target map level corresponding to the map to be aggregated, wherein the target map level is any one of the plurality of map levels;

[0037] The second determining unit is used to determine target point data from the stored data table, wherein the target point data is pre-aggregated point data located within the area coordinates under the target map level;

[0038] The aggregation unit is used to aggregate the target point data to obtain the point aggregation result corresponding to the map to be aggregated.

[0039] A third aspect of this application provides a point data aggregation device, the aggregation device including a processor and a memory;

[0040] The memory is used to store program code and transmit the program code to the processor;

[0041] The processor is used to execute any of the point data aggregation methods described in the first aspect according to the instructions in the program code.

[0042] A fourth aspect of this application provides a computer storage medium for storing program code for executing any of the point data aggregation methods described in the first aspect.

[0043] As can be seen from the above technical solutions, this application has the following advantages:

[0044] The point data aggregation method provided in this application includes: determining a storage data table for the map to be aggregated, wherein the storage data table stores pre-aggregated point data of the map to be aggregated at several map levels; obtaining the region coordinates and target map level corresponding to the map to be aggregated, wherein the target map level is any one of the several map levels; determining target point data from the storage data table, wherein the target point data is the pre-aggregated point data located within the region coordinates at the target map level; and performing point aggregation on the target point data to obtain the point aggregation result corresponding to the map to be aggregated.

[0045] In this application, since the stored data table stores pre-aggregated point data under different map levels, the target point data located in the regional coordinates under the target map level determined from the stored data table is also pre-aggregated point data. Thus, only the pre-aggregated point data under the target area is cached in the browser, instead of the traditional raw point data. The data volume is greatly reduced, and fast aggregation can be achieved during aggregation. This solves the technical problems of browser lag and calculation delay when aggregating point data of digital maps. Attached Figure Description

[0046] To more clearly illustrate the technical methods in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating a method for aggregating location data according to an embodiment of this application.

[0048] Figure 2 This is a flowchart illustrating a second embodiment of a point data aggregation method according to the present application.

[0049] Figure 3 This is a schematic diagram of an embodiment of a point data aggregation device according to this application. Detailed Implementation

[0050] This application designs a method, apparatus, device, and computer storage medium for point data aggregation, which solves the technical problems of browser lag and computational delay when aggregating point data on digital maps.

[0051] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0052] For easier understanding, please refer to Figure 1 , Figure 1 This is a flowchart illustrating one embodiment of a point data aggregation method in this application.

[0053] like Figure 1 As shown, the point data aggregation method in this implementation specifically includes:

[0054] Step 101: Determine the storage data table of the map to be aggregated. The storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels.

[0055] In this embodiment, the map to be aggregated has a storage data table, which stores the pre-aggregated point data of the map to be aggregated at several map levels. That is, the map to be aggregated is pre-aggregated according to different map levels, and the pre-aggregated point data is stored in the storage data table.

[0056] It is understandable that a correspondence exists between the stored data tables and the maps to be aggregated. That is, different maps to be aggregated correspond to different stored data tables. When aggregating point data for a specific map to be aggregated, the corresponding stored data table is first obtained based on the correspondence between the stored data tables and the maps to be aggregated. It should be noted that the map to be aggregated can be a map of any location, any city, or any region; this embodiment does not impose any specific limitations on this.

[0057] Step 102: Obtain the region coordinates and target map level corresponding to the map to be aggregated. The target map level can be any map level among several map levels.

[0058] After determining the storage data table corresponding to the map to be aggregated, the regional coordinates and target map level of the map at the time of this aggregation are obtained. It is understood that the regional coordinates here refer to the actual geographic coordinates, and the target map level can be any map level among several map levels; this embodiment does not limit this.

[0059] It is understandable that the aggregation of the map to be aggregated is for loading. When the map to be aggregated is loaded and displayed, before the specific target map level and regional coordinates are set, the regional coordinates and target map level can be preset. The target map level can be set to a certain level, such as level 8, level 10 or level 12, etc. The region corresponding to the regional coordinates can be a rectangular region. In this case, the regional coordinates are the geographical coordinates of the four vertices of the rectangle.

[0060] Step 103: Determine the target point data from the stored data table. The target point data is the pre-aggregated point data located within the regional coordinates under the target map level.

[0061] Since the stored data table contains pre-aggregated point data for the map to be aggregated at several map levels, after determining the target map level, the pre-aggregated point data for that target map level can be determined. Then, the pre-aggregated point data (i.e., the target point data) located within the regional coordinates is matched from the pre-aggregated point data at the target map level. It can be understood that the specific implementation steps of step 103 include:

[0062] Match the target map layer with several map layers;

[0063] Use the pre-aggregated point data corresponding to the map level that matches the target map level as the matching point data;

[0064] Use the matching point data located within the area coordinates as the target point data.

[0065] It should be noted that the above implementation method is only an illustrative example. When determining the target point data, it is also possible to first match based on the regional coordinates and then match based on the target map level. For example, first filter out the pre-aggregated point data located at the regional coordinates from all the pre-aggregated point data, and then determine the data located at the target map level from the filtered pre-aggregated point data, and use this part of the data as the target point data.

[0066] Step 104: Aggregate the target point data to obtain the point aggregation result corresponding to the map to be aggregated.

[0067] In this embodiment, the pre-aggregated point data is the point data after pre-aggregation of the original point data. That is to say, the data table in this embodiment stores the pre-aggregated point data, and the target point data determined from this data is also the pre-aggregated point data, which greatly reduces the data volume when aggregating points.

[0068] In this embodiment, since the storage data table stores pre-aggregated point data under different map levels, the target point data located in the regional coordinates under the target map level determined from the storage data table is also pre-aggregated point data. Thus, only the pre-aggregated point data under the target area is cached in the browser, instead of the traditional original point data. The data volume is greatly reduced, and fast aggregation can be achieved during aggregation. This solves the existing technical problems of browser lag and calculation delay when aggregating point data on digital maps.

[0069] The above is an embodiment of a point data aggregation method provided in this application. The following is an embodiment of a point data aggregation method provided in this application.

[0070] Please see Figure 2 , Figure 2 This is a flowchart illustrating a second embodiment of a point data aggregation method in this application.

[0071] like Figure 2 As shown, the point data aggregation method in this implementation specifically includes:

[0072] Step 201: Determine the storage data table of the map to be aggregated. The storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels.

[0073] Specifically, the configuration process for pre-aggregated location data includes:

[0074] Obtain the base map of the map to be aggregated. The base map is the map of the map to be aggregated at the highest map level.

[0075] The base map is divided into grids to obtain several grids;

[0076] Obtain the pre-aggregation algorithm corresponding to the first map level, where the first map level is any one of several map levels;

[0077] Using a pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain the pre-aggregated point data under the first map level.

[0078] It is understood that the above embodiments describe the configuration method of pre-aggregated point data at one map level. The configuration methods at other map levels can refer to the description in this embodiment, and this embodiment does not make specific limitations on this.

[0079] The baseline map is the map at the highest map level of the map to be aggregated. In other words, the baseline map is the most detailed and smallest granular map of the map to be aggregated. The point data in the baseline map is the original point data of the map to be aggregated. The point data in the baseline map is also the most numerous, detailed and comprehensive. Therefore, in this embodiment, the point data in the baseline map is pre-aggregated to different degrees to obtain pre-aggregated point data at different map levels.

[0080] When dividing the grid, it can be divided into 2000 or more, the number of which depends on the number of point data in the base map.

[0081] Optionally, in one implementation, a pre-aggregation algorithm is used to pre-aggregate the point data in each grid to obtain pre-aggregated point data at the first map level, specifically including:

[0082] Obtain the number of operations performed on the point data in the pre-aggregation algorithm;

[0083] Based on the number of operations, the point data in each grid is grouped to obtain several groups and the point data corresponding to each group;

[0084] The point data in each group is calculated using a pre-aggregation algorithm to obtain the pre-aggregated point data at the first map level.

[0085] At the first map level, when performing a pre-aggregation algorithm on the point data in the base map, the number of point data operations required for the pre-aggregation algorithm is first determined. Then, the point data in each grid is grouped using this number of operations, resulting in several groups and the corresponding point data for each group. Specifically, if the total number of point data in a grid is less than the number of operations, all point data in that grid are grouped together. For example, if the number of operations used for calculation is 4, and the total number of point data in a certain grid is 3, then these 3 point data are grouped together, and these 3 point data are obtained. If the total number of point data in a grid is greater than the number of operations used for calculation, it is determined how many groups of point data can be grouped based on the number of operations required. Finally, point data that are not grouped by the number of operations are grouped together. For example, if the number of operations used for calculation is 4, and the total number of point data in a certain grid is 10, then the point data can be grouped into: group A consisting of 4 point data, group B consisting of 4 point data, and group B consisting of 2 point data.

[0086] In one optional implementation, the point data in each group is calculated using a pre-aggregation algorithm to obtain pre-aggregated point data at the first map level, specifically including:

[0087] Count the total number of data points in each group;

[0088] The average coordinates are obtained by averaging the geographic coordinates of the points in each group.

[0089] The pre-aggregated point data at the first map level is obtained by combining the total number and average coordinates of all groups.

[0090] When performing pre-aggregation calculations for each group, the pre-aggregation algorithm in this embodiment can be to calculate the average value, that is, to calculate the average value of the point data in each group, which is to calculate the average value of the geographic coordinates of the point data in each group. After obtaining the average coordinates, the average coordinates and the number of points corresponding to the point data of each group can be obtained. For example, for the above-mentioned group A, its total number is 4, and the average coordinate is A', which means that there are 4 point data with coordinate A'. At this time, the average coordinate A' and the total number of 4 are the pre-aggregated point data of group A. For the above-mentioned group C, its total number is 2, and the average coordinate is C', which means that there are 2 point data with coordinate C'. At this time, the average coordinate C' and the total number of 2 are the pre-aggregated point data of group C. By combining the pre-aggregated point data corresponding to all groups, the pre-aggregated point data under the first map level can be obtained. The corresponding storage data table stores the pre-aggregated point data under different map levels.

[0091] Step 202: Obtain the region coordinates and target map level corresponding to the map to be aggregated. The target map level can be any map level among several map levels.

[0092] The description of step 202 is the same as that of step 102 in Embodiment 1. For details, please refer to the description of step 102 above, and it will not be repeated here.

[0093] Step 203: Determine the target point data from the stored data table. The target point data is the pre-aggregated point data located within the regional coordinates under the target map level.

[0094] The description of step 203 is the same as that of step 103 in Embodiment 1. For details, please refer to the description of step 103 above, and it will not be repeated here.

[0095] Step 204: Aggregate the target point data to obtain the point aggregation result corresponding to the map to be aggregated.

[0096] When aggregating target point data, grid-based point aggregation algorithms, distance-based point aggregation algorithms, point aggregation algorithms combining grids and distance, point aggregation algorithms based on distance and minimum number of points, or other point aggregation algorithms can be used.

[0097] Step 205: Render the point aggregation results and load the map to be aggregated using the rendered point aggregation results.

[0098] It is understood that the point data aggregation method in this embodiment also includes:

[0099] After the map to be aggregated is loaded, when a movement command is received for the map to be aggregated, the movement coordinates are obtained;

[0100] Based on the movement coordinates and the area coordinates, determine the new area coordinates corresponding to the movement command;

[0101] Based on the new area coordinates, determine the new point aggregation result corresponding to the movement command.

[0102] Furthermore, the location data aggregation method in this embodiment may also include:

[0103] After the map to be aggregated is loaded, when a zoom command for the map to be aggregated is received, obtain the zoom coordinates and the zoom map level;

[0104] Based on the scaling coordinates and the region coordinates, determine the new region coordinates corresponding to the scaling command;

[0105] Delete the point aggregation results and determine the new point aggregation results corresponding to the zoom command based on the zoom map level and the new area coordinates.

[0106] When moving the map to be loaded, the same method is used to obtain the target point data. When zooming the map, the same method is used as when panning. Figure 1 Similarly, the same method is used to obtain the target point data. After obtaining the target point data, the previously obtained target point data in the browser cache is cleared, while the new data is saved and the aggregated map is rendered.

[0107] In this embodiment, since the storage data table stores pre-aggregated point data under different map levels, the target point data located in the regional coordinates under the target map level determined from the storage data table is also pre-aggregated point data. Thus, only the pre-aggregated point data under the target area is cached in the browser, instead of the traditional original point data. The data volume is greatly reduced, and fast aggregation can be achieved during aggregation. This solves the existing technical problems of browser lag and calculation delay when aggregating point data on digital maps.

[0108] The above are embodiments of a point data aggregation method provided in this application. The following are embodiments of a point data aggregation device provided in this application.

[0109] Please see Figure 3 , Figure 3 This is a schematic diagram of an embodiment of a point data aggregation device according to this application.

[0110] In this embodiment, the point data aggregation device includes: a first splicing node, a second splicing node, and a display device;

[0111] The first determining unit is used to determine the storage data table of the map to be aggregated. The storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels.

[0112] The first acquisition unit is used to acquire the region coordinates and target map level of the map to be aggregated, wherein the target map level is any one of several map levels.

[0113] The second determining unit is used to determine the target point data from the stored data table. The target point data is the pre-aggregated point data located in the regional coordinates under the target map level.

[0114] The aggregation unit is used to aggregate target point data to obtain the point aggregation result corresponding to the map to be aggregated.

[0115] Optionally, the configuration process for pre-aggregated location data includes:

[0116] Obtain the base map of the map to be aggregated. The base map is the map of the map to be aggregated at the highest map level.

[0117] The base map is divided into grids to obtain several grids;

[0118] Obtain the pre-aggregation algorithm corresponding to the first map level, where the first map level is any one of several map levels;

[0119] Using a pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain the pre-aggregated point data under the first map level.

[0120] Optionally, a pre-aggregation algorithm is used to pre-aggregate the point data in each grid to obtain pre-aggregated point data at the first map level, specifically including:

[0121] Obtain the number of operations performed on the point data in the pre-aggregation algorithm;

[0122] Based on the number of operations, the point data in each grid is grouped to obtain several groups and the point data corresponding to each group;

[0123] The point data in each group is calculated using a pre-aggregation algorithm to obtain the pre-aggregated point data at the first map level.

[0124] Optionally, the point data in each group is calculated using a pre-aggregation algorithm to obtain pre-aggregated point data at the first map level, specifically including:

[0125] Count the total number of data points in each group;

[0126] The average coordinates are obtained by averaging the geographic coordinates of the points in each group.

[0127] The pre-aggregated point data at the first map level is obtained by combining the total number and average coordinates of all groups.

[0128] Optionally, the device further includes:

[0129] The rendering unit is used to render the point aggregation results and load the map to be aggregated using the rendered point aggregation results.

[0130] Optionally, the device further includes:

[0131] The second acquisition unit is used to acquire the movement coordinates when the movement command of the map to be aggregated is obtained after the map to be aggregated is loaded;

[0132] The third determining unit is used to determine the new area coordinates corresponding to the movement command based on the movement coordinates and area coordinates;

[0133] The fourth determining unit is used to determine the new point aggregation result corresponding to the movement command based on the new area coordinates.

[0134] Optionally, the device further includes:

[0135] The third acquisition unit is used to acquire the scaling coordinates and scaling map level when the scaling instruction of the map to be aggregated is obtained after the map to be aggregated is loaded;

[0136] The fifth determining unit is used to determine the new region coordinates corresponding to the scaling command based on the scaling coordinates and region coordinates;

[0137] The delete unit is used to delete the point aggregation results and determine the new point aggregation results corresponding to the zoom command based on the zoom map level and the new area coordinates.

[0138] In this embodiment, since the storage data table stores pre-aggregated point data under different map levels, the target point data located in the regional coordinates under the target map level determined from the storage data table is also pre-aggregated point data. Thus, only the pre-aggregated point data under the target area is cached in the browser, instead of the traditional original point data. The data volume is greatly reduced, and fast aggregation can be achieved during aggregation. This solves the existing technical problems of browser lag and calculation delay when aggregating point data on digital maps.

[0139] This application also provides an embodiment of a location data aggregation device. The aggregation device in this embodiment includes a processor and a memory. The memory is used to store program code and transmit the program code to the processor. The processor is used to execute the location data aggregation method of any of the foregoing embodiments according to the instructions in the program code.

[0140] This application also provides an embodiment of a computer storage medium, wherein the computer storage medium in this embodiment is used to store program code, and the program code is used to execute the point data aggregation method of any of the foregoing embodiments.

[0141] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0142] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0143] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0144] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0145] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0147] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable computer storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned computer storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0148] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for aggregating location data, characterized in that, include: Determine the storage data table of the map to be aggregated, wherein the storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels; Obtain the region coordinates and target map level corresponding to the map to be aggregated, wherein the target map level is any one of the plurality of map levels; From the stored data table, the target point data is determined, which is the pre-aggregated point data located within the coordinates of the region under the target map level; The target point data is aggregated to obtain the point aggregation result corresponding to the map to be aggregated; The configuration process for the pre-aggregated location data includes: Obtain the base map of the map to be aggregated, wherein the base map is the map of the map to be aggregated at the highest map level; The baseline map is divided into grids to obtain several grids; Obtain the pre-aggregation algorithm corresponding to the first map level, where the first map level is any one of the plurality of map levels; Using the aforementioned pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain the pre-aggregated point data under the first map level; Using the aforementioned pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain pre-aggregated point data at the first map level, specifically including: Obtain the number of operations performed on the point data in the pre-aggregation algorithm; According to the number of operations, the point data in each grid is grouped to obtain several groups and the point data corresponding to each group; The point data in each group is calculated according to the pre-aggregation algorithm to obtain the pre-aggregated point data under the first map level; The point data in each group is calculated according to the pre-aggregation algorithm to obtain the pre-aggregated point data under the first map level, specifically including: Count the total number of data points in each group; The average coordinates are obtained by averaging the geographic coordinates of the points in each group. By combining the total number and average coordinates of all groups, the pre-aggregated point data under the first map level is obtained.

2. The point data aggregation method according to claim 1, characterized in that, The method further includes: Render the point aggregation result, and use the rendered point aggregation result to load the map to be aggregated.

3. The point data aggregation method according to claim 2, characterized in that, The method further includes: After the map to be aggregated is loaded, when a movement command for the map to be aggregated is received, the movement coordinates are obtained; Based on the movement coordinates and the area coordinates, determine the new area coordinates corresponding to the movement command; Based on the new region coordinates, determine the new point aggregation result corresponding to the movement command.

4. The point data aggregation method according to claim 2, characterized in that, The method further includes: After the map to be aggregated is loaded, when a zoom command for the map to be aggregated is received, the zoom coordinates and the zoom map level are obtained; Based on the scaling coordinates and the region coordinates, determine the new region coordinates corresponding to the scaling instruction; Delete the point aggregation result, and determine the new point aggregation result corresponding to the zoom command based on the zoom map level and the new area coordinates.

5. A point data aggregation device, characterized in that, include: The first determining unit is used to determine the storage data table of the map to be aggregated, wherein the storage data table stores the pre-aggregated point data of the map to be aggregated at several map levels; The first acquisition unit is used to acquire the regional coordinates and target map level corresponding to the map to be aggregated, wherein the target map level is any one of the plurality of map levels; The second determining unit is used to determine target point data from the stored data table, wherein the target point data is pre-aggregated point data located within the area coordinates under the target map level; An aggregation unit is used to aggregate the target point data to obtain the point aggregation result corresponding to the map to be aggregated. The configuration process for the pre-aggregated location data includes: Obtain the base map of the map to be aggregated, wherein the base map is the map of the map to be aggregated at the highest map level; The baseline map is divided into grids to obtain several grids; Obtain the pre-aggregation algorithm corresponding to the first map level, where the first map level is any one of the plurality of map levels; Using the aforementioned pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain the pre-aggregated point data under the first map level; Using the aforementioned pre-aggregation algorithm, the point data in each grid is pre-aggregated to obtain pre-aggregated point data at the first map level, specifically including: Obtain the number of operations performed on the point data in the pre-aggregation algorithm; According to the number of operations, the point data in each grid is grouped to obtain several groups and the point data corresponding to each group; The point data in each group is calculated according to the pre-aggregation algorithm to obtain the pre-aggregated point data under the first map level; The point data in each group is calculated according to the pre-aggregation algorithm to obtain the pre-aggregated point data under the first map level, specifically including: Count the total number of data points in each group; The average coordinates are obtained by averaging the geographic coordinates of the points in each group. By combining the total number and average coordinates of all groups, the pre-aggregated point data under the first map level is obtained.

6. A point data aggregation device, characterized in that, The aggregation device includes a processor and a memory; The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the point data aggregation method according to any one of claims 1 to 4 according to the instructions in the program code.

7. A computer storage medium, characterized in that, The computer storage medium is used to store program code, which is used to execute the point data aggregation method according to any one of claims 1 to 4.

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