CN112100307A

CN112100307A - Data processing method, path searching processing method and device and electronic equipment

Info

Publication number: CN112100307A
Application number: CN202011023436.4A
Authority: CN
Inventors: 王隆强; 刘伟
Original assignee: Beijing QIYI Century Science and Technology Co Ltd
Current assignee: Beijing QIYI Century Science and Technology Co Ltd
Priority date: 2020-09-25
Filing date: 2020-09-25
Publication date: 2020-12-18
Anticipated expiration: 2040-09-25
Also published as: CN112100307B

Abstract

The invention provides a data processing method, a path searching processing device and electronic equipment, wherein the method comprises the following steps: acquiring grid data in N grids from the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; generating N tuples based on the N mesh data, the tuples comprising identification fields for storing data tags of the tuples and data fields for storing the mesh data; and generating a target compilation file according to the N tuples, wherein the target compilation file comprises a target function, and when the target compilation file is loaded, the target function is used for acquiring the tuples corresponding to the data marks based on the data marks. The embodiment of the invention improves the starting efficiency of the target server.

Description

Data processing method, path searching processing method and device and electronic equipment

Technical Field

The present invention relates to the field of computer technologies, and in particular, to a data processing method, a way-finding processing device, and an electronic device.

Background

With the development of online games, map areas are larger and more, and terrains are more and more complex. Automatic route finding of game units in a map scene becomes an important indispensable function.

In a network game such as a Client/Server (C/S) architecture, a target Server in a Server group needs to import a map at the time of starting before performing a route search by using a route search algorithm, and process the map into a data structure required by the route search algorithm. Typically, the target server needs to pre-process the map data provided by the client or art at startup to process it into a data structure that is convenient for the target server to read and calculate. When the map data is large, it takes a lot of time to process the map data, resulting in slow start of the target server. It can be seen that the target server in the prior art is low in starting efficiency.

Disclosure of Invention

The embodiment of the invention aims to provide a data processing method, a path searching device and electronic equipment, so as to solve the problem that the starting efficiency of a target server in the prior art is low. The specific technical scheme is as follows:

in a first aspect of the present invention, there is provided a data processing method, including:

acquiring grid data in N grids from the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; n is a positive integer;

generating N tuples based on the N mesh data, the tuples comprising identification fields for storing data tags of the tuples and data fields for storing the mesh data;

and generating a target compilation file according to the N tuples, wherein the target compilation file comprises a target function, and when the target compilation file is loaded, the target function is used for acquiring the tuples corresponding to the data marks based on the data marks.

In a second aspect of the present invention, there is also provided a data processing apparatus comprising:

the acquisition module is used for acquiring grid data in N grids in the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; n is a positive integer;

a first generation module that generates N tuples based on the N mesh data, the tuples including identification fields for storing data tags of the tuples and data fields for storing the mesh data;

and a second generating module, configured to generate a target compiled file according to the N tuples, where the target compiled file includes a target function, and when the target compiled file is loaded, the target function is configured to obtain, based on the data tag, the tuple corresponding to the data tag.

In another aspect of the present invention, there is also provided a way-finding processing method, including:

running a target compilation file and calling a target function in the target compilation file;

taking a target data mark as an input parameter of the target function, and acquiring grid data in a target tuple corresponding to the target data mark;

carrying out route searching processing according to the grid data;

wherein the target tuple comprises an identification field for storing a target data tag of the target tuple and a data field for storing the mesh data; the mesh data is used to represent the position and shape of the mesh in a road-finding map.

In another aspect of the present invention, there is also provided a way-finding processing apparatus, including:

the running module is used for running the target compiled file and calling a target function in the target compiled file;

the acquisition module is used for taking a target data mark as an input parameter of the target function and acquiring grid data in a target tuple corresponding to the target data mark;

the processing module is used for carrying out route searching processing according to the grid data;

In yet another aspect of the present invention, there is also provided a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute any one of the above-mentioned data processing methods or any one of the above-mentioned way finding processing methods.

In yet another aspect of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform any of the above-mentioned data processing methods, or any of the above-mentioned way-finding processing methods.

According to the data processing method provided by the embodiment of the invention, the data information of each grid in the map data is converted into a tuple structure, and the target compiling file is generated according to the tuple and the corresponding data mark. When the target server uses the target compiled file and adopts a way-finding algorithm to find the way, the mesh data information corresponding to the data mark can be directly obtained through the data mark in the target compiled file. In the prior art, when the target server adopts a route searching algorithm to search a route, the corresponding grid data can be obtained only by acquiring the map data after data format conversion, which also causes the starting efficiency of the target server to be lower; in contrast, in the embodiment of the invention, when the target server is started, the data information of each grid can be obtained without converting the map data structure, so that the starting efficiency of the target server is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.

FIG. 1 is a diagram of an example scenario in an embodiment of the present invention;

FIG. 2 is a diagram of a second example of a scenario in an embodiment of the present invention;

FIG. 3 is one of the flow charts of a data processing method in an embodiment of the present invention;

FIG. 4 is a flowchart of a way finding performed by a target server according to a way finding algorithm in the embodiment of the present invention;

FIG. 5 is a second flowchart of a data processing method according to an embodiment of the present invention;

FIG. 6 is a flow chart of a way-finding processing method in the embodiment of the present invention;

FIG. 7 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention;

FIG. 8 is a schematic structural diagram of a way-finding processing device in an embodiment of the present invention;

fig. 9 is a schematic structural diagram of an electronic device in the embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.

In a network game such as a Client/Server (C/S) architecture, in general, a target Server in a Server group needs to pre-process map data provided by a Client or an art at startup before a routing algorithm is adopted for routing, so as to process the map data into a data format convenient for the target Server to read and calculate. The embodiment of the invention provides a method for processing data applied to electronic equipment in order to improve the starting efficiency of a target server.

Referring to fig. 1 to 2, fig. 1 and 2 are diagrams of two possible scenarios according to an embodiment of the present invention. The electronic device may be a target server. Alternatively, as shown in fig. 2, the electronic device may be another server device in the server group except the target server, and after the other server device processes the map data, the electronic device may send the generated target compiled file to the target server. Alternatively, as shown in fig. 1, the electronic device may be any electronic device communicatively connected to the target server. It should be understood that the electronic device may also be an electronic device such as a notebook computer, a palm top computer, an ultra-mobile personal computer (UMPC), a netbook, a Personal Digital Assistant (PDA), a Network Attached Storage (NAS), or a Personal Computer (PC), and is not limited herein.

In the embodiment of the present invention, the target server may be a server that realizes some specific functions by using map data. For example, in the aforementioned game scenario, the target server may be embodied as a game server; further, the target server may be embodied as a server module or a processor in the game server, which executes a routing algorithm using the map data.

Referring to fig. 3, fig. 3 is a flowchart of a data processing method according to an embodiment of the present invention, as shown in fig. 3, including the following steps:

step 101, acquiring grid data in N grids from the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; n is a positive integer;

102, generating N tuples based on the N mesh data, where the tuples include identification fields and data fields, the identification fields are used for storing data tags of the tuples, and the data fields are used for storing the mesh data;

step 103, generating a target compilation file according to the N tuples, wherein the target compilation file comprises a target function, and when the target compilation file is loaded, the target function is used for acquiring the tuples corresponding to the data markers based on the data markers.

In the embodiment of the present invention, for map data provided by a client or an art, the map data may be preprocessed by an electronic device as shown in fig. 1 to improve the starting efficiency of the target server, the steps 101 to 103 may be an implementation flow of preprocessing the route-finding map data by the electronic device, after the step 103, the electronic device may send a generated target compiled file to the target server, and details are subsequently expanded.

In the step 101, the route-finding map data may be used for the destination server to perform route finding by using a route-finding algorithm, so that when the map data is acquired, the map may be subjected to mesh division processing, and thus an optimal route-finding path may be determined according to a position relationship between meshes. For the meshes of the two-dimensional map, each mesh may be a convex polygon, that is, each vertex of each mesh corresponds to an internal angle smaller than 180 °, and the number of boundaries of each mesh may be the same or different. For example, two of the meshes are triangles and quadrilaterals. Since the triangle is the simplest convex polygon, in order to simplify subsequent calculation, the map area may also be divided into a plurality of triangular meshes, and the number of meshes is generally as small as possible.

Meanwhile, for the current grid during the way finding, the data of the adjacent grid is needed when the current grid traverses the adjacent grid nearest to the end point, so that at least one common edge is formed between the two adjacent triangles, and the traversal of the adjacent grid is convenient in the way finding process by adopting a way finding algorithm. The number of meshes is related to the complexity of the map shape, and the simpler the map shape is, the smaller the number of meshes is.

When the route-finding map data is acquired, the route-finding map data may be stored in the electronic device in advance or in any storage location readable by the electronic device. Preferably, the road-finding map data and other code files of the target server may be stored in the same directory, so as to facilitate unified management.

For the grids in the road-finding map, any one of all the grids obtained after the road-finding map is divided can be used. It can be understood that, for the way finding of the map, the general character model can only carry out the way finding in the walkable area, so the grid in the way finding map data can also be any grid in the walkable area of the map, and the grid can be specifically set according to the actual requirement.

Generally, map data provided by a client or art includes only data information of mesh vertices, and does not include information such as mesh boundary length, number of mesh boundaries, and the like. Therefore, the step of acquiring each mesh data in the road-finding map data may further include a step of calculating according to the road-finding map data to obtain the required mesh data. Optionally, the step 101 may specifically include but is not limited to:

determining the boundary number of each grid in the N grids according to the number of the vertexes of each grid in the N grids;

determining the coordinates of the starting point and the end point of each boundary in the N grids according to a preset sequence;

and determining the coordinates of the central point in the N grids according to the coordinates of the top points in the N grids.

In the convex-edge grid, the number of vertices of the grid is the number of boundaries of the grid. For each boundary, sequentially arranged start and end coordinates may be included. The preset sequence can be set according to actual needs, for example, coordinates of the start point and the end point of the boundary can be arranged in a clockwise or counterclockwise sequence. Further, the above-mentioned manner of determining the coordinates of the center point of the mesh from the coordinates of the vertices of the mesh may be calculated by dividing the sum of the coordinates of the vertices by the number of boundaries.

In step 102, the step of generating the corresponding tuple from the data information corresponds to performing data structure conversion on the tuple. A tuple is essentially an ordered set of multiple elements in which different types of content can be stored. It should be understood that there are general differences in the structure of tuples in different programming languages, and the embodiment of the present invention has no particular limitation on the type of structure of the tuple, and may include but is not limited to: at least one of a record tuple or a tuple.

In one embodiment, for erlang language, a record structure is a tuple, and a record structure is framed by braces and includes multiple ordered fields, adjacent fields may be separated by commas, and each field may store one type of data information, that is, may store one data or one data list. It should be understood that since one record structure in the erlang language can be nested with another record structure, the data list may further include one or more record structures. For example, { computer, [ { memory,2048}, { disaksize, 1048576} ] is a tuple in the language of erlang, where "computer" is a field representing the name of the "computer," and "{ memory,2048}, { disaksize, 1048576} ] is a data list framed by brackets, and the data list may also be a field representing computer configuration information of" memory 2GB "and" hard disk capacity 1024GB ".

In another embodiment, for python, the tuple structure is a tuple, for one tuple in phython, it may be framed with small brackets, and adjacent elements may be separated by commas, for example ('physics', 'chemistry',1997,2000) is a tuple in python, and physics, chemistry, 1997, and 2000 are elements in the tuple, and it can be seen that the tuple includes name information of "physical" and "chemical", and also includes year information of "1997" and "2000".

In the embodiment of the present invention, for a tuple, it may be regarded as a set of different types of data in a map grid, and each type of data may exist in the form of a single data or a data list.

Specifically, the tuple according to the embodiment of the present invention may be composed of a plurality of fields, including an identification field and a data field, where there may be one or more data fields, and the number of the data fields is not particularly limited. In the above description of the tuple in the erlang language, "computer" can be used as an identification field, and [ { memory,2048}, { disasse, 1048576} ] can be used as a data field.

The data tag corresponding to the tuple can be a unique item of data in the tuple, and exists in the form of an identification field. For example, the tuple corresponding to the way-finding map grid can use the field of the grid number contained in the tuple as the data mark.

The above-mentioned tuple and the association relation between the data labels corresponding to the tuple can be characterized by a constructor. For example, a code pointing to a tuple may be used as a return value of a function, a data tag corresponding to the tuple is used as an input parameter of the function, an object function is constructed, and a target compiled file is generated by taking the object function as a main body. Therefore, when the target compiling file is read, the target server can obtain the code of the output pointed tuple based on the target function by calling the target function and using the data mark as the input parameter of the target function, and further determine the tuple or the grid data stored in the tuple based on the code of the execution tuple so as to perform subsequent routing calculation.

In a specific implementation, the object function may be specifically an object function code, and what is specifically included in the object compilation file is also the object function code.

In step 103, the compiled file is generally an executable file generated by writing a source program according to the specification of the object code language, and then performing compilation and concatenation. The map data code file originally generated from the tuples and the data tags may be a map data code file composed of codes in the form of tuples. The specific flow generally comprises the steps of taking an indication code as an output parameter of an objective function in programming, taking a data mark in a tuple as an input parameter of the objective function, constructing a code of the objective function, taking the code of the objective function as a main body, supplementing necessary module name definition, header file definition, derivation function definition and the like of a code file, and finally creating a file and writing the file into a disk to obtain a map data code file. Wherein the indication code is code conforming to an object code language for pointing to a certain unary group.

The target compiled file may be obtained by compiling a map data code file, and the compiling process may be a process of compiling a compiler of a development language by the target server, so as to obtain a compiled file in the development language.

It should be noted that, for a map, a target compilation file may be generated correspondingly; and for a plurality of maps, the data in the maps can be converted into tuple forms respectively to obtain a plurality of corresponding code files, and then a plurality of corresponding target compiling files are obtained through compiling.

It should be noted that the code language adopted by the target compiled file is a code language that the target server can run. Illustratively, the target compiled file is written in a target code language, and the target code language is a code language that can be run or read by the target server. The target code language is explained in detail later.

Therefore, after the electronic device preprocesses the map data, the electronic device can send the generated target compilation file to the target server, the target server can run codes in the target compilation file, and the target server can obtain the corresponding grid data in the tuple through the data marks in the target compilation file when performing the way finding according to the way finding algorithm.

Optionally, the step 103 may include:

processing the N tuples by using a target code language to obtain N code character strings corresponding to the N tuples;

determining the objective function based on the N code strings and the N data tokens; the input of the target function is the data mark, and the output of the target function is a code character string corresponding to the data mark;

generating a data code file based on the target function;

and compiling the data code file to obtain the target compiled file.

In the embodiment of the present invention, different code languages may be used to process the N tuples, and a specific processing manner may be to convert the tuples into a data structure of a target code language.

The object code language may include a code language such as erlang, python, or C + +. For example, if the target server is developed by erlang language, the tuple may be a record structure in erlang language, and for a record structure, it includes a plurality of ordered fields. For example, the first field may be the name of the tuple, and any field after the first field may be a data or a data list, so as to represent a specific item or a type of data information. It will be appreciated that for the mesh data of the way-finding map, the first fields in the N tuples are generally all the same, and may be defined as "map _ node", for example. The identification field in the tuple may be any one of the fields after the first field with uniqueness. That is, the position of the identification field may be set in a customized manner, and this is not particularly limited in the embodiment of the present invention. For example, the identification field may be the last or first field in the tuple or may be located in the middle of the data field, for example, the identification field may be the first field in the tuple, i.e., the first field after the aforementioned name field.

In the embodiment of the present invention, there is no particular limitation on the arrangement order of each field in the tuple, and the specific arrangement order may be preset by a user. However, since the target server generally obtains data information of multiple grids at the same time when running the code in the target compiled file to perform the way finding by using the way finding algorithm, the structure of the tuple corresponding to each grid, that is, the type of the data information corresponding to the included field and the sequence of the field are the same. In other words, the number and the arrangement order of the fields in the tuple corresponding to each grid are the same, so that the target server can conveniently obtain a specific data in a single grid.

The N code strings may respectively point to the N tuples, and when the target server runs any one of the code strings, the mesh data of the tuple corresponding to the code string may be acquired.

As mentioned above, the manner of obtaining the grid data of N tuples can be realized by constructing an objective function. The input of the objective function is the data flag and the output is the code string. In this way, the code string pointing to the corresponding tuple can be acquired by inputting the data tag, so that the mesh data can be acquired according to running the corresponding code.

After the map data is converted into the data structure of tuples, a data code file composed of map data is generally obtained first. The coding language for the data code file is generally consistent with the development language of the target server, so as to obtain the code in the target compiled file which can be directly run by the target server. For example, if the target server is developed by erlang language, the compiling language of the data code file may be erlang language, and the suffix name thereof is generally ". erl"; if the target server is developed by C + +, the compiling language of the data code file may be C + +. The specific setting can be carried out according to actual needs.

Take erlang language as an example. The map data may be first stored in the form of a data code file in erlang language, and the data code file may be further compiled in order to obtain a code in a target compilation file that can be directly run by a target server. Specifically, the compiling process may be performed by a compiler, and may generally translate all source codes in the data code file into machine instructions, and add some description information to generate a new executable file, where the executable file may be loaded and run by an operating system, and the computer executes the instructions generated by the compiler in the file. The compiler can be invoked by the electronic device, or the compiler is integrated in the electronic device, which is provided with compiling capabilities.

Because the map belongs to game basic content which does not change frequently, the data code file generated after processing can be used all the time without repeatedly processing data. The embodiment of the invention can also regenerate the data code file according to the data processing method provided by the application and compile again to obtain the new version compiled file when the map data changes, and then directly replace and load the new version compiled file in the target server to realize the function of updating the map without stopping service, thereby improving the game experience of users.

The embodiment of the invention can actually utilize an erlang pattern matching method to quickly acquire the grid data, the pattern matching is the root of the erlang, and the grid data in the tuple corresponding to the data mark can be obtained in the data structure according to the matching relation between the target function and the data mark. Because the record structure under the erlang language is a static data structure, the grid data of each grid can be directly acquired through data marking, and the increase of the data quantity in a certain range does not influence the reading speed of the data, so that the time for reading the grid data is shortened, and the complexity for reading the grid data is reduced.

Optionally, the step 102 may specifically include:

and for each tuple, correspondingly generating the identification field and the data field according to the tuple name, the field name and the grid data corresponding to the tuple.

In the embodiment of the present invention, for erlang language, the record structure is defined tuple. The process of determining the tuple name and the field name is equivalent to a process of defining a record structure, that is, defining the name of the record structure and the content contained in the record structure. In this case, the name of the record structure may be the first field, the data field and the identification field may both be located after the first field, and the total number and sequence of the fields may also be determined in the process of defining the record structure. For example, the name of the record is defined as "map node", the structure of the record is defined to include "number of boundaries" and "number of vertices", the first field in each tuple is "map node", the number of data fields in each tuple is 2, and the field names are "number of boundaries" and "number of vertices", respectively. The identification field can be determined according to the grid processing sequence or can be determined by user definition. It should be understood that the above identification fields are different in each tuple. For example, in an alternative embodiment, the identification field may be stored in each tuple in the form of a numerical sequence number or an arithmetic sequence of numerical sequence numbers.

After the record structure is defined, at this time, only the data mark of the record structure needs to be stored or updated in the identification field, and the acquired way-finding map grid data is correspondingly stored or updated in the data field under the corresponding field name, that is, the data format conversion of processing the map grid data into the record structure is completed. In the embodiment of the present invention, the name of the record structure and the field name of the data field included in the record structure may be defined first, and then for each grid, specific numerical information in the data field may be generated or updated according to the grid data.

Specifically, if the mesh data in each mesh includes the number of boundaries and boundary information, the number of boundaries is generally a numerical value used to represent the number of edges of a convex polygon mesh. The number of the boundary is one data and can be used as one data field. The boundary information generally includes information such as a plurality of edges and a plurality of edge vertices, for example, vertex coordinates of each edge, a length of an edge, and a mesh number of an adjacent mesh including the common edge.

It should be understood that the more the map is complex, the more meshes are divided, meaning the greater the number of records structures. In order to obtain the specified grid data quickly, in a specific embodiment, the grid number may be stored in the tuple in the form of an identification field as a data tag of the tuple. It can be understood that the grid numbers of each grid are different, the numbers may be specifically customized numbers, and may also be determined by the processing order of the grid data, and the processing order may be the sequence in which the data in each grid is converted into the record structure. For example, the data for the first processed mesh is labeled "1", the data for the second processed mesh is labeled "2", and so on. Therefore, because the grid numbers of each grid are different, the numbers are used as the input parameters of the target function and used as the return values of the function, and only one function needs to be written, and the data information in the tuple can be read by calling the function and inputting the function parameters. When the data information of different tuples is obtained, all the fields of the record structure corresponding to the grid code can be obtained only by inputting different parameters.

Optionally, the data information of the grid may include at least one of:

the grid state is used for indicating whether the map area corresponding to the grid can walk or not;

the number of boundaries; the position coordinates of the grid center points;

a boundary data list including position coordinates of a start point and an end point of each boundary in the mesh;

a list of vertex data comprising location coordinates of vertices in the mesh.

Corresponding to the data processing method executed by the electronic device side, the embodiment of the invention also provides a way-finding processing method, which is applied to a target server. As mentioned above, the target server may be embodied as an electronic device executing the method, and at this time, the target server may execute the method described in any one of the foregoing embodiments and the way-finding processing method. Alternatively, the target server may be a server connected to the electronic device, and in this case, the target server may acquire the target compiled file from the connected electronic device. The details are as follows.

Specifically, referring to fig. 4, fig. 4 is a possible embodiment of a way-finding method adopted by a target server, and a specific flow thereof may include:

when a target server runs a target compiling file to carry out route searching by adopting a route searching algorithm, parameters such as a starting point, an end point, a radius and the like are generally given according to user input, and then whether the parameters are legal or not needs to be judged, namely, if the coordinates of the starting point and the end point are positioned in a walkable area, the parameters are legal; if the mobile terminal is not located in the walkable area, the parameters are illegal, and if the parameters are not legal, the route searching fails. The walkable region may be a region formed by walkable meshes in the mesh data, or a region formed by meshes in the target compiled file, and may be specifically set according to actual needs.

And under the condition that the parameters are legal, further judging whether the starting point and the end point can be reached in a straight line, namely whether connecting lines between the starting point and the end point are all positioned in a walking area. If the path can be reached by a straight line, a path point list which is passed by the path-finding path is generated according to the grid which is passed by the straight line.

Under the condition that a straight line cannot arrive between a starting point and an end point, calculating and determining the adjacent grid with the lowest distance evaluation between the adjacent grid and the end point in the adjacent grid of the current grid from the grid where the starting point is located, continuing to determine the adjacent grid with the lowest distance evaluation between the adjacent grid and the end point based on the adjacent grid until the grid where the end point is located is reached, and generating a node list consisting of all grids in the process. For example, assuming that the grid where the game character is currently located is used as the first grid, if a second grid with the lowest valuation between the first grid and the end point is to be determined, the first distance between each adjacent grid and the corresponding grid can be determined according to the coordinates of the start point and the center point of each adjacent grid in the first grid, the second distance between each adjacent grid and the end point can be determined according to the coordinates of the center point and the end point of each adjacent grid, and the sum of the first distance and the second distance is used as the valuation, so that the second grid is determined. In this step, all the neighboring grids of the current grid need to be traversed, and the linear distance between all the neighboring grids and the end point is calculated, and since the route-finding path from the neighboring grid to the end point may not be a straight line, the linear distance may be equivalent to distance estimation in route-finding.

Under the condition of judging the communication among all grids, namely all grids which are equivalent to the experience of the path-searching path contain common edges, the inflection point which needs to pass is calculated for the adjacent grids which are experienced by the path-searching path according to the path-searching direction, namely after the grids which are experienced by the path-searching path are determined, one common vertex of the adjacent grids is determined as the inflection point according to the path-searching direction, and the inflection point is the path point during the path-searching. And finally returning a list formed by all path points, wherein the path points comprise all inflection points when the path is searched along the grid nodes, and the path searching path can be formed by the inflection points and straight lines.

As can be seen from the above, when the target server uses the routing algorithm to perform routing, the steps of determining whether the parameters are legal, determining the neighboring grid with the lowest evaluation value between the current grid and the end point, and calculating the coordinates of the inflection point are generally performed. Therefore, the target server needs to acquire data information of multiple dimensions in the map data. For each grid, the target server generally obtains grid data of grid numbers, grid states, the number of boundaries, a boundary data list and a vertex data list, so as to perform the calculation and determination in the above-mentioned step flow.

However, since the initial map data cannot be directly acquired by the target server, the target server can calculate and judge according to the mesh data by acquiring the target compilation file and reading the mesh data in the target compilation file. The electronic device typically pre-processes the initial map data at startup, converting the initial map data into a data structure that can be read by the target server. In the embodiment of the present invention, the electronic device may convert the grid data of each grid in the route-finding map data into a data structure that can be directly acquired by the target server, generate the target compiled file, and send the target compiled file to the target server. Or, when the electronic device is a target server, the target server may generate the target compiled file in advance according to any of the foregoing embodiments, so that when performing the routing processing, the target compiled file generated in advance may be directly read.

The grid data of each grid can be converted into data in a tuple or stored in a data list form in the embodiment of the invention. The grid number may be a numerical value for indicating the processing order of each grid. And the grid state can indicate whether the grid is a grid which can be walked or not by the numerical value of '0' or '1', and all the grids which can be walked form a walkable area in the road-finding map. For example, the target server may obtain a data field of the grid state in the tuple corresponding to the grid, where the grid state may be "0" in the case that the grid is not walkable, and may be "1" in the case that the grid is walkable. It should be noted that the state of the mesh may be "undefined" without defining whether the mesh can walk.

Accordingly, the number of the boundaries may be a specific number, and is a data with the grid number and the grid state. The position coordinates of the central point of the grid can include coordinates on three coordinate axes of x, y and z, and in the embodiment of the invention, the coordinates on the three coordinate axes can be integrated into a data list for storage, and the coordinates on the three coordinate axes can also be stored in the form of three data.

For the boundary data list in one mesh, it may include coordinate data of a boundary vertex, and when the boundary is a common edge with an adjacent node, it may also include mesh number of the adjacent node, distance from a center point of the adjacent node, and the like; and for a list of vertices in the mesh, it may include coordinate data on the x, y, z axes of the mesh vertices. The boundary data and the vertex data both comprise a plurality of items of data, and at this time, the boundary data and the vertex data can be respectively integrated into two data lists for storage. It should be noted that the data in each data list may be the same or different, and is determined according to the type of the mesh data.

Referring to fig. 5, in order to better understand the present invention, a specific process of the electronic device implementing the data processing method in the present invention will be described in detail below by taking a record structure in an erlang language as an example, and the flow may include:

step 201, reading map data, wherein the map comprises a plurality of convex polygon meshes.

Step 202, generating a record structure corresponding to each convex polygon mesh according to the mesh data of each convex polygon mesh. The mesh data of each convex polygon mesh may include mesh state, number of boundaries, boundary data, vertex data, and key value of the mesh. Wherein the key value of the grid can be used as the data mark of each grid.

And step 203, deriving a target compiling file in the erlang language based on each record structure.

Wherein, the record structure is a tuple structure in erlang language. The grid data such as the grid state, the number of boundaries, the boundary data, the vertex data, and the key value of the grid may also be stored in the record structure in the form of the identification field and the data field.

The processes of steps 201 to 203 may be implemented by an electronic device, and the compiling of the routing algorithm performed by the target server on the target code file may be implemented with reference to fig. 4 and the explanation of fig. 4 in the above embodiment, which are not described herein again.

It should be noted that, various optional implementations described in the embodiments of the present invention may be implemented in combination with each other or implemented separately, and the embodiments of the present invention are not limited thereto.

Further, referring to fig. 6, an embodiment of the present invention further provides a way-finding processing method, which is applied to a target server, and the method includes:

step 301, running a target compilation file, and calling a target function in the target compilation file.

Step 302, using the target data mark as an input parameter of the target function, and obtaining the grid data in the target tuple corresponding to the target data mark.

And 303, performing path searching processing according to the grid data.

In step 301 and step 302, the target server may add the target compiled file to the startup item at startup, so as to directly run the target compiled file at startup. In this way, the target server may call the target function in the target compilation file, and obtain the mesh data of the target tuple by using the target data tag as the input parameter of the target function. The target compiled file may include N tuples, the target tuple is any tuple of the N tuples, and the target data tag is a data tag stored in an identification field included in the target tuple.

In step 303, the target server may perform the routing process according to the acquired mesh data. Specifically, a navigation grid (NavMesh) algorithm may be used to perform the route finding, and the steps may be performed according to fig. 4 and the above description, which are not described herein again.

In the embodiment of the invention, the target server can run the target compilation file generated by the electronic equipment, call the target function in the target compilation file and acquire the grid data in the corresponding target tuple according to the target data mark, so that the starting efficiency of the target server is improved.

It should be understood that, when the target server needs to acquire the grid data in multiple tuples, the grid data in multiple corresponding tuples may also be acquired according to the target function by using multiple data tags as input in the manner described above.

Further, the step 302 may specifically include:

marking target data as an input parameter of the target function;

acquiring a code character string output by the target function;

and running the code character string to obtain the grid data in the target tuple.

In the embodiment of the present invention, the output of the target function may be a code string pointing to the corresponding tuple, and the target server may quickly acquire the grid data of the corresponding tuple by running the code string and using an erlang pattern matching method, so as to improve the efficiency of the target server in acquiring the grid data.

Further, the step 303 may specifically include:

acquiring a starting point coordinate and an end point coordinate during route searching;

determining a grid through which a connecting line between the starting point and the end point passes according to the starting point coordinate, the end point coordinate and the grid data;

under the condition that grids passed by the connecting line between the starting point and the end point are all walkable grids, straight line path finding is carried out according to the connecting line between the starting point and the end point;

determining a route-finding grid list according to distance estimation under the condition that at least one grid which cannot be walked exists in grids through which a connecting line between a starting point and an end point passes; the distance valuation is a straight line distance between the current grid and the adjacent grid.

With reference to fig. 4 and the above description of fig. 4, in the embodiment of the present invention, when a straight line path is allowed to reach between the starting point and the end point, a path is found according to a connection line between the starting point and the end point, and when a straight line path is not allowed to reach between the starting point and the end point, a path-finding mesh list is determined according to meshes in which a distance estimation between a current mesh and a mesh at which an end point is located is sequentially determined to be the minimum, so that distance estimation calculation during straight line path finding is avoided, and efficiency during path finding processing is improved.

Specifically, the embodiment of the present invention may determine whether the grids passed by the connection line between the starting point and the ending point are both walkable grids by determining whether the connection line between the starting point and the ending point has an intersection with the boundary of the walkable grids. For example, if the intersection points of the grid boundary and the connecting lines between the starting point and the ending point are both located on the boundary of the walkable grid, it may be determined that the grids passed by the connecting lines between the starting point and the ending point are both walkable grids.

The walkable mesh may be a mesh in which a mesh state is indicated as walkable in the mesh data, or all meshes of the target compiled file. Correspondingly, the non-walkable mesh may be a mesh in which the mesh status indicates non-walkable mesh in the mesh data; alternatively, the non-walkable mesh may not exist in the object compilation file.

Optionally, when the grid with the smallest distance from the end point is computationally determined to be the grid with the smallest valuation among the adjacent grids of the current grid, the adjacent grids need to be sorted to find the grid with the smallest distance valuation. In the embodiment of the invention, the adjacent grid list of the current grid can be arranged according to the minimum binary heap, so that the grid with the minimum distance evaluation can be quickly determined under the condition of more adjacent grids, and the routing efficiency is improved.

Optionally, the grid data includes at least one of:

the number of boundaries; the position coordinates of the grid center points;

a list of vertex data comprising location coordinates of vertices in the mesh.

The mesh data is mesh data obtained from the road-finding map data by the electronic device in the data processing method, and is not described herein again.

Referring to fig. 7, fig. 7 is a structural diagram of a data processing apparatus 400 according to an embodiment of the present invention, and as shown in fig. 7, the data processing apparatus 400 may include:

a first obtaining module 410, configured to obtain grid data in N grids from the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; n is a positive integer;

a first generating module 420, configured to generate N tuples based on the N mesh data, where the tuples include identification fields and data fields, the identification fields are used to store data tags of the tuples, and the data fields are used to store the mesh data;

a second generating module 430, configured to generate a target compiled file according to the N tuples, where the target compiled file includes an object function, and when the target compiled file is loaded, the object function is configured to obtain, based on the data tag, the tuple corresponding to the data tag.

In the embodiment of the present invention, the data processing apparatus may obtain, by the first obtaining module, mesh data in N meshes in the route-finding map data; generating N tuples based on the N grid data through a first generation module to realize the conversion of a grid data structure; then generating a target compiling file according to the N tuples by a second generating module, so that a target server can run the target compiling file to obtain corresponding grid data and perform path searching by adopting a path searching algorithm,

optionally, the first generating module 420 may specifically include:

the processing unit is used for processing the N tuples by using a target code language to obtain N code character strings corresponding to the N tuples;

a determining unit, configured to determine the objective function based on the N code strings and the N data flags; the input of the target function is the data mark, and the output of the target function is the code character string;

a generating unit, configured to generate a data code file based on the objective function;

and the compiling unit is used for compiling the data code file to obtain the target compiling file.

Optionally, the first obtaining module 410 may specifically include:

and the calculation unit is used for calculating the road-finding map data to obtain grid data in N grids.

Optionally, the grid data may include at least one of:

the number of boundaries; the position coordinates of the grid center points;

a list of vertex data comprising location coordinates of vertices in the mesh.

The data processing apparatus provided in the embodiment of the present invention can implement each process implemented by the data processing method in the method embodiments in fig. 1 to 3, and is not described here again to avoid repetition.

Referring to fig. 8, fig. 8 is a structural diagram of a way-finding processing apparatus 500 according to an embodiment of the present invention, where the way-finding processing apparatus 500 may be the target server, and as shown in fig. 6, the way-finding processing apparatus 500 may include:

an operation module 510, configured to operate a target compiled file and call a target function in the target compiled file;

the second obtaining module 520, taking the target data mark as the input parameter of the target function, and obtaining the grid data in the target tuple corresponding to the target data mark;

a processing module 530, configured to perform a path finding process according to the mesh data;

Optionally, the second obtaining module 520 specifically includes:

an input unit for marking target data as an input parameter of the target function;

the obtaining unit is used for obtaining the code character string output by the target function;

and the operation unit operates the code character string to acquire the grid data in the target tuple.

Optionally, the grid data may include at least one of:

the number of boundaries; the position coordinates of the grid center points;

a list of vertex data comprising location coordinates of vertices in the mesh.

The route searching processing device provided by the embodiment of the present invention can implement each process implemented by the route searching processing method in the method embodiment in fig. 4, and is not described here again to avoid repetition.

An embodiment of the present invention further provides an electronic device, as shown in fig. 9, including a processor 601, a communication interface 602, a memory 603, and a communication bus 604, where the processor 601, the communication interface 602, and the memory 603 complete mutual communication through the communication bus 604,

a memory 603 for storing a computer program;

the processor 601 is configured to implement the following steps when executing the program stored in the memory 603:

acquiring grid data in N grids from the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; generating N tuples based on the N mesh data, the tuples comprising identification fields for storing data tags of the tuples and data fields for storing the mesh data; and generating a target compilation file according to the N tuples, wherein the target compilation file comprises a target function, and when the target compilation file is loaded, the target function is used for acquiring the tuples corresponding to the data marks based on the data marks.

Alternatively, the processor 601 may implement the following steps: running a target compilation file and calling a target function in the target compilation file; taking a target data mark as an input parameter of the target function, and acquiring grid data in a target tuple corresponding to the target data mark; and carrying out path searching processing according to the grid data. Wherein the target tuple comprises an identification field for storing a target data tag of the target tuple and a data field for storing the mesh data; the mesh data is used to represent the position and shape of the mesh in a road-finding map.

The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.

The communication interface is used for communication between the terminal and other equipment.

The Memory may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.

The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.

In another embodiment of the present invention, a computer-readable storage medium is further provided, where instructions are stored, and when the instructions are executed on a computer, the computer is enabled to execute any one of the data processing methods or any one of the way-finding processing methods in the foregoing embodiments.

In yet another embodiment of the present invention, a computer program product containing instructions is further provided, which when run on a computer causes the computer to execute any of the data processing methods or any of the way-finding processing methods described in the above embodiments.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims

1. A data processing method, comprising:

2. The data processing method according to claim 1, wherein the step of generating a target compiled file from the N tuples comprises:

generating a data code file based on the target function;

and compiling the data code file to obtain the target compiled file.

3. The data processing method of claim 1, wherein the step of obtaining mesh data in the N meshes comprises:

4. The data processing method of claim 1, wherein the mesh data comprises at least one of:

the number of boundaries; the position coordinates of the grid center points;

a list of vertex data comprising location coordinates of vertices in the mesh.

5. A way-finding processing method is characterized by comprising the following steps:

carrying out route searching processing according to the grid data;

6. The way-finding processing method according to claim 5, wherein the step of taking the target data tag as the input parameter of the target function and acquiring the grid data in the target tuple corresponding to the target data tag comprises:

marking target data as an input parameter of the target function;

acquiring a code character string output by the target function;

7. The way-finding processing method according to claim 5, wherein the step of performing way-finding processing according to the mesh data includes:

8. The way-finding processing method according to claim 5, wherein the mesh data includes at least one of:

the number of boundaries; the position coordinates of the grid center points;

a list of vertex data comprising location coordinates of vertices in the mesh.

9. A data processing apparatus, comprising:

the first acquisition module is used for acquiring grid data in N grids in the road-finding map data; the grid data is used for representing the position and the shape of the grid in a road-finding map; n is a positive integer;

10. A way finding processing apparatus, comprising:

the second acquisition module is used for taking a target data mark as an input parameter of the target function and acquiring the grid data in a target tuple corresponding to the target data mark;

wherein the target tuple comprises an identification field for storing a target data tag of the target tuple and a data field for storing the mesh data; the grid data is used for representing the position and the shape of the grid in a road-finding map;

and the processing module is used for carrying out route searching processing according to the grid data.

11. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;

a memory for storing a computer program;

a processor for implementing the method steps of any one of claims 1-4 or 5-8 when executing a program stored in a memory.

12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-4 or 5-8.