CN117131074A - Real-time analysis method, system and storage medium for large-scale complex vector data - Google Patents
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Abstract
The invention belongs to the technical field of data analysis, and particularly discloses a large-scale complex vector data real-time analysis method, a system and a storage medium.
Description
Technical Field
The invention belongs to the field of data analysis, and particularly relates to a large-scale complex vector data real-time analysis method, a system and a storage medium.
Background
There are large-scale complex geometric vector element data such as three-line-one-sheet data, land use status classification data, etc. in the fields of ecological environmental protection and natural resource management. Planar vector elements, often on the order of tens of millions, are contained within a provincial region. The single planar vector element is composed of a plurality of polygons, the polygons have complex geometric shapes and huge node numbers, and can reach tens of millions of nodes, so that space inquiry and analysis calculation efficiency is low, time consumption is long, great challenges are brought to efficient management and application of the data, and the operation efficiency of business informatization auxiliary systems such as ecological environment influence evaluation of major infrastructure construction projects of traffic, water conservancy and the like and homeland space planning is restricted. An effective technical scheme for real-time analysis of large-scale complex vector data is not available at present.
In the field of a traditional geographic information system (Geographic Information System, abbreviated as GIS), massive complex space data are generally stored in a Postgres, oracle large-scale relational database, and space data management and calculation are performed by using a postGIS, oracle Spatial and other space database engine plug-in matched with the database. The method needs to transfer the space data in the general format into a professional database, increases the difficulty of data application, and has the defects of low space analysis performance, large front-end and back-end development workload and the like.
Disclosure of Invention
The invention aims to provide a large-scale complex vector data real-time analysis method, a system and a storage medium, which are used for solving the problems in the prior art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
in a first aspect, a method for real-time analysis of large-scale complex vector data is provided, including:
acquiring analysis target data and analysis range values transmitted by a client, and creating an criticizing task according to the analysis target data and the analysis range values, wherein the analysis target data comprises vector data of an analysis target;
executing an criticizing task by utilizing a TooMap, and obtaining an influence area of analysis target data in a preset analysis database by taking the analysis target data as a center and an analysis range value as an expansion distance, wherein the analysis database is an ESRI file geographic database, and comprises a plurality of primitives obtained by scattering spatial basic data and basic information corresponding to each primitive;
extracting a primitive set which is positioned in an influence area and intersected with the influence area in an analysis database, and taking the primitive set as criticizing basic data;
intersecting and separating analysis is carried out on the criticizing basic data according to the analysis target data to obtain primitives intersecting and separating with the analysis target data in the criticizing basic data, wherein the primitives intersecting with the analysis target data are used as intersecting primitives, and the primitives separating from the analysis target data are used as separating primitives;
calculating, judging and analyzing a first closest point of the target data relative to the intersecting primitive, analyzing a second closest point of the target data relative to the separating primitive, and analyzing a shortest distance value of the target data and the separating primitive;
determining basic information of the intersected graphic element, basic information of the separated graphic element, coordinate information of a first nearest point and coordinate information of a second nearest point;
and generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first closest point, the coordinate information of each second closest point and each shortest distance value, and feeding back the structural analysis result to the client.
In one possible design, before performing the critique task using the TooMap, the method further includes:
acquiring space basic data, wherein the space basic data comprises vector elements of a plurality of geometric shapes, each vector element is used as an entity object, and unique object IDs and attributes are given to the vector elements;
constructing a TooMap based on a nine-cross relation model, preprocessing space basic data by utilizing a geometric scattering operator in the TooMap, splitting an entity object with a complex geometric shape in the space basic data into a plurality of primitives, and inheriting an object ID and an attribute of a corresponding entity object as basic information by each primitive;
and importing the preprocessed space basic data into an ESRI file geographic database to form an analysis database.
In one possible design, the executing the criticizing task by using the TooMap uses analysis target data as a center and uses an analysis range value as an expansion distance in a preset analysis database to obtain an influence area of the analysis target data, and the method includes:
and executing an criticizing task by utilizing the TooMap, centering on analysis target data in an analysis database, taking an analysis range value as an expansion distance, and calling a buffer area operator to perform buffer area analysis to obtain an influence area of the analysis target data.
In one possible design, the extracting the set of primitives located within and intersecting the region of interest in the analysis database includes:
and calling an intersection operator in the TooMap to perform spatial relation operation on the influence region and each primitive in the analysis database, determining each primitive which is positioned in the influence region and intersects with the influence region, and combining each primitive which is positioned in the influence region and intersects with the influence region into a primitive set.
In one possible design, the intersecting and separating analysis is performed on the criticizing basic data according to the analysis target data to obtain the primitives intersecting and separating with the analysis target data in the criticizing basic data, including:
calling an intersection operator in the TooMap to perform intersection analysis on the analysis target data and the criticizing basic data, and determining a primitive which is intersected with the analysis target data in the criticizing basic data;
and calling a phase separation operator in the TooMap to perform phase separation analysis on the analysis target data and the criticizing basic data, and determining a primitive which is separated from the analysis target data in the criticizing basic data.
In one possible design, the computing determines a first closest point of the analysis target data relative to the intersecting primitive, a second closest point of the analysis target data relative to the separating primitive, and a shortest distance value of the analysis target data and the separating primitive, including:
for the intersected graphic element, taking the intersection point of the analysis target data and the intersected graphic element as a first closest point, and taking the coordinate information of the intersection point as the coordinate information of the first closest point;
and for the isolated primitive, invoking a neighbor operator in the TooMap to calculate and analyze a second closest point, a shortest distance value and an azimuth angle of the target data relative to the isolated primitive, and determining coordinate information of the second closest point according to the shortest distance value and the azimuth angle.
In one possible design, the generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first closest point, the coordinate information of each second closest point and each shortest distance value, and feeding back the structural analysis result to the client includes:
the basic information of each intersecting graphic element, the basic information of each separating graphic element, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value are input into a preset analysis report template to generate an analysis report file, and the analysis report file is transmitted to a client side, so that the client side stores and visually displays the analysis report file.
In a second aspect, a large-scale complex vector data real-time analysis system is provided, which includes an acquisition unit, an expansion unit, an extraction unit, an analysis unit, a calculation unit, a determination unit, and a generation unit, wherein:
the system comprises an acquisition unit, a judgment unit and a judgment unit, wherein the acquisition unit is used for acquiring analysis target data and analysis range values transmitted by a client, and creating an criticizing task according to the analysis target data and the analysis range values, wherein the analysis target data comprises vector data of an analysis target;
the expansion unit is used for executing an criticizing task by utilizing the TooMap, taking analysis target data as a center and an analysis range value as an outward expansion distance in a preset analysis database to obtain an influence area of the analysis target data, wherein the analysis database is an ESRI file geographic database, and the analysis database contains a plurality of primitives obtained by scattering spatial basic data and basic information corresponding to each primitive;
the extraction unit is used for extracting a primitive set which is positioned in the influence area and intersected with the influence area in the analysis database, and the primitive set is used as criticizing basic data;
the analysis unit is used for carrying out intersection and separation analysis on the criticizing basic data according to the analysis target data to obtain primitives which are intersected with and separated from the analysis target data in the criticizing basic data, wherein the primitives which are intersected with the analysis target data are used as intersection primitives, and the primitives which are separated from the analysis target data are used as separation primitives;
the computing unit is used for computing and judging a first closest point of analysis target data relative to the intersecting primitive, a second closest point of analysis target data relative to the separating primitive and a shortest distance value of the analysis target data and the separating primitive;
a determining unit configured to determine basic information of the intersecting primitive, basic information of the separating primitive, coordinate information of a first closest point, and coordinate information of a second closest point;
the generating unit is used for generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value, and feeding back the structural analysis result to the client.
In a third aspect, a system for real-time analysis of large-scale complex vector data is provided, comprising:
a memory for storing instructions;
and a processor for reading the instructions stored in the memory and executing the method according to any one of the above first aspects according to the instructions.
In a fourth aspect, a computer readable storage medium is provided, wherein instructions are stored on the computer readable storage medium, which when run on a computer, cause the computer to perform the method of any one of the first aspects.
The beneficial effects are that: according to the invention, complex geometric figure vector data is scattered by adopting the ideas of object oriented and integral zero, the geometric figure of an entity object is split into a plurality of primitives, the primitives are associated and corresponding to the entity object, on the basis, massive entity object primitives are automatically screened based on TooMap by acquiring analysis target data and analysis range values, valuable primitives are selected, and the related analysis calculation process is promoted from semiautomatic operation requiring manual participation to full automatic operation by assembling and cascading corresponding space analysis operators, so that the data analysis flow is further simplified, and the analysis efficiency of large-scale complex vector data is improved. The invention can reduce the calculation complexity and time cost of large-scale complex geometric vector element space inquiry and analysis, improve the data analysis efficiency, improve the analysis response speed from the minute level to the second level of the traditional method, improve the automation degree of analysis and realize one-key and foolproof analysis.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram showing the steps of the method of example 1 of the present invention;
FIG. 2 is a schematic diagram showing the construction of a system in embodiment 2 of the present invention;
FIG. 3 is a schematic diagram showing the construction of a system in embodiment 3 of the present invention.
Detailed Description
It should be noted that the description of these examples is for aiding in understanding the present invention, but is not intended to limit the present invention. Specific structural and functional details disclosed herein are merely representative of example embodiments of the invention. This invention may, however, be embodied in many alternate forms and should not be construed as limited to the embodiments set forth herein.
It will be appreciated that the term "coupled" is to be interpreted broadly, and may be a fixed connection, a removable connection, or an integral connection, for example, unless explicitly stated and limited otherwise; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in the embodiments can be understood by those of ordinary skill in the art according to the specific circumstances.
In the following description, specific details are provided to provide a thorough understanding of example embodiments. However, it will be understood by those of ordinary skill in the art that the example embodiments may be practiced without these specific details. For example, a system may be shown in block diagrams in order to avoid obscuring the examples with unnecessary detail. In other embodiments, well-known processes, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
Example 1:
the embodiment provides a real-time analysis method for large-scale complex vector data, which can be applied to a corresponding background server, as shown in fig. 1, and comprises the following steps:
s1, acquiring analysis target data and analysis range values transmitted by a client, and creating an criticizing task according to the analysis target data and the analysis range values, wherein the analysis target data comprises vector data of an analysis target.
In specific implementation, based on a nine-cross relation model (Dimensionally Extended-Intersect ion Model, abbreviated as DE-9 IM), an analysis and calculation engine TooMap (Sichuan map open platform service engine) for complex space data can be constructed, wherein the TooMap comprises independent space analysis and data processing operators such as intersection, separation, inclusion, neighbor, buffer, scattering and the like. TooMap is developed into a set of dynamic link library based on C++, and is expanded to form a set of Web Service-based networked Service interfaces, which are deployed on a background server and can be called by various front ends, such as a Web end, a desktop end, a mobile end and the like, in a local or network mode. TooMap can realize access and operation to ESRI FileGDB format space database. The TooM ap can select a plurality of independent operators to dynamically assemble and connect in series according to task demands in a script command setting mode, and automatically generate an operator chain to complete a series of complex tasks.
Each complex vector element in the acquired spatial basis data can be regarded as a physical object based on object-oriented ideas, each physical object being composed of geometrical properties. The spatial basis data contains large-scale complex geometry vector elements, each vector element serving as a physical object and assigned a unique object ID and attribute. The space basic data comprise data which contains rich professional information in the industrial field and is relied by each industry department to develop business, such as three-line-one-sheet data of an environmental protection department, basic mapping result data of a mapping department, three-region three-line-and-soil map spot data of a natural resource department and the like. The space basic data has the characteristics of large scale, mass, complex geometric figure and the like, and the service functions such as criticizing, planning and the like can be realized by carrying out a series of space analysis and calculation on the space basic data and corresponding analysis target data.
Based on the idea of becoming zero, the geometric scattering operator in the TooMap is utilized to preprocess the space basic data, the entity object with complex geometric shape in the space basic data is segmented and scattered, the originally complex geometric shape is split into a plurality of simple geometric shapes, which are called as graphic elements, and each graphic element inherits the ID and the attribute of the original entity object. The split primitive geometry is a convex polygon (any one side of a polygon is infinitely extended to two ends to form a straight line, and other sides are on the same side of the straight line, so the polygon is called a convex polygon). The preprocessing function is to refine each complex geometric figure into a plurality of simple primitives, and lays a foundation for eliminating irrelevant objects in the subsequent analysis process, reducing the primitives participating in analysis and calculation to the greatest extent and saving analysis time.
And importing the preprocessed basic data into an ESRI FileGDB space database (namely an ESRI file geographic database) by utilizing a warehousing function provided by the TooMap to form an analysis database. The analysis database is deployed on a background server, establishes connection with the TooMap, and accesses and operates the data in the analysis database through a service interface of the TooMap.
The interactive operation function with the TooMap can be provided through a set of client software based on the Web browser, the simple space analysis and calculation function can be realized by directly calling the atomic service of the TooMap, and the operator chain can be automatically combined and generated by inputting script commands through a client software page to realize the complex space analysis function. And a data screening function and a loop analysis function are constructed in client software by presetting script commands, and a user selects the data screening function and the loop analysis function through a client page, uploads analysis target data and inputs an analysis range value. The analysis target data comprises vector data of an analysis target, wherein the analysis target refers to an object to be evaluated or inspected in the business process of an industry department, such as a new road as an evaluation object in the criticizing business, a planning building as an inspection object of a rule committee in the city planning business, and the like. The analysis range value refers to a range extending outward with the analysis target as the center to represent a range in which the analysis target affects the surrounding ecological environment unit, and the analysis range value of the criticizing analysis may be set to 5 km, for example. After the background server acquires analysis target data and analysis range values transmitted by the client, an criticizing task is created according to the analysis target data and the analysis range values.
S2, executing an criticizing task by utilizing a TooMap, taking analysis target data as a center in a preset analysis database, taking an analysis range value as an expansion distance, and obtaining an influence area of the analysis target data, wherein the analysis database is an ESRI file geographic database, and comprises a plurality of graphical elements obtained by scattering spatial basic data and basic information corresponding to each graphical element.
In specific implementation, the TooMap can be utilized to execute the criticizing task, and the TooMap automatically calls each analysis operator in sequence according to the corresponding operator chain to calculate. Firstly, analyzing a buffer area operator in an analysis database by taking analysis target data as a center and taking an analysis range value as an expansion distance to perform buffer area analysis, so as to obtain a range surface as an influence area of the analysis target data. .
S3, extracting a primitive set which is positioned in the influence area and intersected with the influence area in the analysis database, and taking the primitive set as criticizing basic data.
In particular, the process of extracting a set of primitives located within and intersecting an affected area in an analytical database includes: and calling an intersection operator in the TooMap to perform spatial relation operation on each primitive in the influence area and the analysis database, determining each primitive which is positioned in the influence area and intersects with the influence area, combining each primitive which is positioned in the influence area and intersects with the influence area into a primitive set, and taking the primitive set as criticizing basic data. The method can reduce the data volume of the criticizing number to the greatest extent, thereby greatly improving the analysis efficiency.
S4, intersecting and separating analysis is carried out on the criticizing basic data according to the analysis target data, so that primitives intersecting with and separating from the analysis target data in the criticizing basic data are obtained, the primitives intersecting with the analysis target data are used as intersecting primitives, and the primitives separating from the analysis target data are used as separating primitives.
In specific implementation, an intersection operator in the TooMap is called to carry out intersection analysis on analysis target data and criticizing basic data, and primitives intersecting with the analysis target data in the criticizing basic data are determined. And calling a phase separation operator in the TooMap to perform phase separation analysis on the analysis target data and the criticizing basic data, and determining a primitive which is separated from the analysis target data in the criticizing basic data. The primitive intersected with the analysis target data is taken as an intersected primitive, and the primitive separated from the analysis target data is taken as a separated primitive.
S5, calculating and judging a first closest point of analysis target data relative to the intersecting primitive, analyzing a second closest point of the target data relative to the separating primitive, and analyzing a shortest distance value of the target data and the separating primitive.
In specific implementation, for the intersecting primitive, the intersection point of the analysis target data and the intersecting primitive is taken as the first closest point, and the coordinate information of the intersection point is taken as the coordinate information of the first closest point. And for the isolated primitive, invoking a neighbor operator in the TooMap to calculate and analyze a second closest point, a shortest distance value and an azimuth angle of the target data relative to the isolated primitive, and determining coordinate information of the second closest point according to the shortest distance value and the azimuth angle.
S6, determining basic information of intersecting primitives, basic information of separating primitives, coordinate information of a first nearest point and coordinate information of a second nearest point.
In specific implementation, basic information of the intersected graphic element, basic information of the separated graphic element, coordinate information of a first nearest point and coordinate information of a second nearest point are extracted, wherein the basic information comprises an object ID and an attribute.
S7, generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value, and feeding back the structural analysis result to the client.
In the specific implementation, the basic information of each intersecting graphic element, the basic information of each separating graphic element, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value are input into a preset analysis report template to generate an analysis report file, and the analysis report file is transmitted to a client side, so that the client side stores and visually displays the analysis report file.
The method can reduce the calculation complexity and time cost of large-scale complex geometric vector element space query and analysis, improve the data analysis efficiency, improve the analysis response speed from the minute level to the second level of the traditional method, improve the automation degree of analysis and realize one-key and foolproof analysis.
Example 2:
the embodiment provides a large-scale complex vector data real-time analysis system, as shown in fig. 2, which comprises an acquisition unit, an expansion unit, an extraction unit, an analysis unit, a calculation unit, a determination unit and a generation unit, wherein:
the system comprises an acquisition unit, a judgment unit and a judgment unit, wherein the acquisition unit is used for acquiring analysis target data and analysis range values transmitted by a client, and creating an criticizing task according to the analysis target data and the analysis range values, wherein the analysis target data comprises vector data of an analysis target;
the expansion unit is used for executing an criticizing task by utilizing the TooMap, taking analysis target data as a center and an analysis range value as an outward expansion distance in a preset analysis database to obtain an influence area of the analysis target data, wherein the analysis database is an ESRI file geographic database, and the analysis database contains a plurality of primitives obtained by scattering spatial basic data and basic information corresponding to each primitive;
the extraction unit is used for extracting a primitive set which is positioned in the influence area and intersected with the influence area in the analysis database, and the primitive set is used as criticizing basic data;
the analysis unit is used for carrying out intersection and separation analysis on the criticizing basic data according to the analysis target data to obtain primitives which are intersected with and separated from the analysis target data in the criticizing basic data, wherein the primitives which are intersected with the analysis target data are used as intersection primitives, and the primitives which are separated from the analysis target data are used as separation primitives;
the computing unit is used for computing and judging a first closest point of analysis target data relative to the intersecting primitive, a second closest point of analysis target data relative to the separating primitive and a shortest distance value of the analysis target data and the separating primitive;
a determining unit configured to determine basic information of the intersecting primitive, basic information of the separating primitive, coordinate information of a first closest point, and coordinate information of a second closest point;
the generating unit is used for generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value, and feeding back the structural analysis result to the client.
Example 3:
the embodiment provides a large-scale complex vector data real-time analysis system, as shown in fig. 3, including, at a hardware level:
the data interface is used for establishing data butt joint between the processor and the client;
a memory for storing instructions;
and the processor is used for reading the instructions stored in the memory and executing the large-scale complex vector data real-time analysis method in the embodiment 1 according to the instructions.
The device also optionally includes an internal bus through which the processor and memory and data interface may be interconnected, which may be an ISA (Industry Standard Architecture ) bus, PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc.
The Memory may include, but is not limited to, random access Memory (Random Access Memory, RAM), read Only Memory (ROM), flash Memory (Flash Memory), first-in first-out Memory (First Input First Output, FIFO), and/or first-in last-out Memory (First In Last Out, FILO), etc. The processor may be a general-purpose processor including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
Example 4:
the present embodiment provides a computer-readable storage medium having instructions stored thereon that, when executed on a computer, cause the computer to perform the large-scale complex vector data real-time analysis method of embodiment 1. The computer readable storage medium refers to a carrier for storing data, and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash Memory, and/or a Memory Stick (Memory Stick), etc., where the computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable system.
The present embodiment also provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the large-scale complex vector data real-time analysis method of embodiment 1. Wherein the computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable system.
Finally, it should be noted that: the foregoing description is only of the preferred embodiments of the invention and is not intended to limit the scope of the invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The real-time analysis method for large-scale complex vector data is characterized by comprising the following steps of:
acquiring analysis target data and analysis range values transmitted by a client, and creating an criticizing task according to the analysis target data and the analysis range values, wherein the analysis target data comprises vector data of an analysis target;
executing an criticizing task by utilizing a TooMap, and obtaining an influence area of analysis target data in a preset analysis database by taking the analysis target data as a center and an analysis range value as an expansion distance, wherein the analysis database is an ESRI file geographic database, and comprises a plurality of primitives obtained by scattering spatial basic data and basic information corresponding to each primitive;
extracting a primitive set which is positioned in an influence area and intersected with the influence area in an analysis database, and taking the primitive set as criticizing basic data;
intersecting and separating analysis is carried out on the criticizing basic data according to the analysis target data to obtain primitives intersecting and separating with the analysis target data in the criticizing basic data, wherein the primitives intersecting with the analysis target data are used as intersecting primitives, and the primitives separating from the analysis target data are used as separating primitives;
calculating, judging and analyzing a first closest point of the target data relative to the intersecting primitive, analyzing a second closest point of the target data relative to the separating primitive, and analyzing a shortest distance value of the target data and the separating primitive;
determining basic information of the intersected graphic element, basic information of the separated graphic element, coordinate information of a first nearest point and coordinate information of a second nearest point;
and generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first closest point, the coordinate information of each second closest point and each shortest distance value, and feeding back the structural analysis result to the client.
2. The method for real-time analysis of large-scale complex vector data according to claim 1, wherein before performing the criticizing task using the TooMap, the method further comprises:
acquiring space basic data, wherein the space basic data comprises vector elements of a plurality of geometric shapes, each vector element is used as an entity object, and unique object IDs and attributes are given to the vector elements;
constructing a TooMap based on a nine-cross relation model, preprocessing space basic data by utilizing a geometric scattering operator in the TooMap, splitting an entity object with a geometric shape in the space basic data into a plurality of primitives, and inheriting an object ID and an attribute of a corresponding entity object as basic information by each primitive;
and importing the preprocessed space basic data into an ESRI file geographic database to form an analysis database.
3. The method for real-time analysis of large-scale complex vector data according to claim 1, wherein the performing the criticizing task using the TooMap uses analysis target data as a center in a preset analysis database, and the analyzing range value is an expansion distance, so as to obtain an influence area of the analysis target data, and the method comprises the following steps:
and executing an criticizing task by utilizing the TooMap, centering on analysis target data in an analysis database, taking an analysis range value as an expansion distance, and calling a buffer area operator to perform buffer area analysis to obtain an influence area of the analysis target data.
4. The method according to claim 1, wherein the extracting the set of primitives located in and intersecting the affected area in the analysis database comprises:
and calling an intersection operator in the TooMap to perform spatial relation operation on the influence region and each primitive in the analysis database, determining each primitive which is positioned in the influence region and intersects with the influence region, and combining each primitive which is positioned in the influence region and intersects with the influence region into a primitive set.
5. The method for real-time analysis of large-scale complex vector data according to claim 1, wherein the intersecting and separating analysis is performed on the criticizing basic data according to the analysis target data to obtain the primitives intersecting and separating from the analysis target data in the criticizing basic data, comprising:
calling an intersection operator in the TooMap to perform intersection analysis on the analysis target data and the criticizing basic data, and determining a primitive which is intersected with the analysis target data in the criticizing basic data;
and calling a phase separation operator in the TooMap to perform phase separation analysis on the analysis target data and the criticizing basic data, and determining a primitive which is separated from the analysis target data in the criticizing basic data.
6. The method according to claim 1, wherein the calculating determines a first closest point of analysis target data with respect to the intersected primitives, a second closest point of analysis target data with respect to the separated primitives, and a shortest distance value between the analysis target data and the separated primitives, comprising:
for the intersected graphic element, taking the intersection point of the analysis target data and the intersected graphic element as a first closest point, and taking the coordinate information of the intersection point as the coordinate information of the first closest point;
and for the isolated primitive, invoking a neighbor operator in the TooMap to calculate and analyze a second closest point, a shortest distance value and an azimuth angle of the target data relative to the isolated primitive, and determining coordinate information of the second closest point according to the shortest distance value and the azimuth angle.
7. The method according to claim 1, wherein generating a structured analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first closest point, the coordinate information of each second closest point, and each shortest distance value, and feeding back the structured analysis result to the client comprises:
the basic information of each intersecting graphic element, the basic information of each separating graphic element, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value are input into a preset analysis report template to generate an analysis report file, and the analysis report file is transmitted to a client side, so that the client side stores and visually displays the analysis report file.
8. The large-scale complex vector data real-time analysis system is characterized by comprising an acquisition unit, an expansion unit, an extraction unit, an analysis unit, a calculation unit, a determination unit and a generation unit, wherein:
the system comprises an acquisition unit, a judgment unit and a judgment unit, wherein the acquisition unit is used for acquiring analysis target data and analysis range values transmitted by a client, and creating an criticizing task according to the analysis target data and the analysis range values, wherein the analysis target data comprises vector data of an analysis target;
the expansion unit is used for executing an criticizing task by utilizing the TooMap, taking analysis target data as a center and an analysis range value as an outward expansion distance in a preset analysis database to obtain an influence area of the analysis target data, wherein the analysis database is an ESRI file geographic database, and the analysis database contains a plurality of primitives obtained by scattering spatial basic data and basic information corresponding to each primitive;
the extraction unit is used for extracting a primitive set which is positioned in the influence area and intersected with the influence area in the analysis database, and the primitive set is used as criticizing basic data;
the analysis unit is used for carrying out intersection and separation analysis on the criticizing basic data according to the analysis target data to obtain primitives which are intersected with and separated from the analysis target data in the criticizing basic data, wherein the primitives which are intersected with the analysis target data are used as intersection primitives, and the primitives which are separated from the analysis target data are used as separation primitives;
the computing unit is used for computing and judging a first closest point of analysis target data relative to the intersecting primitive, a second closest point of analysis target data relative to the separating primitive and a shortest distance value of the analysis target data and the separating primitive;
a determining unit configured to determine basic information of the intersecting primitive, basic information of the separating primitive, coordinate information of a first closest point, and coordinate information of a second closest point;
the generating unit is used for generating a structural analysis result according to the basic information of each intersecting primitive, the basic information of each separating primitive, the coordinate information of each first nearest point, the coordinate information of each second nearest point and each shortest distance value, and feeding back the structural analysis result to the client.
9. A large-scale complex vector data real-time analysis system, comprising:
a memory for storing instructions;
a processor for reading the instructions stored in the memory and executing the method for real-time analysis of large-scale complex vector data according to the instructions as claimed in any one of claims 1 to 7.
10. A computer readable storage medium having instructions stored thereon which, when executed on a computer, cause the computer to perform the method of real-time analysis of large-scale complex vector data according to any one of claims 1 to 7.
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