CN113626437B - Method and system for rapidly inquiring mass vector data - Google Patents

Method and system for rapidly inquiring mass vector data Download PDF

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CN113626437B
CN113626437B CN202110908176.7A CN202110908176A CN113626437B CN 113626437 B CN113626437 B CN 113626437B CN 202110908176 A CN202110908176 A CN 202110908176A CN 113626437 B CN113626437 B CN 113626437B
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vector data
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CN113626437A (en
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张春林
刘如君
常江波
张运春
刘志杰
董雷
张靖宇
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Beijing Dongfang Tongwangxin Technology Co ltd
Beijing Dongfangtong Software Co ltd
Beijing Testor Technology Co ltd
Beijing Tongtech Co Ltd
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Abstract

The invention provides a method and a system for quickly inquiring mass vector data, which comprises the steps of partitioning a global longitude and latitude coordinate in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinate according to the linear index to form a grid coordinate; carrying out funnel type filing mapping on vector data with different longitudes and latitudes through a coordinate grid, and establishing block index associated data; generating a multi-level distributed query node according to the block index association data; and determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients. The invention has the beneficial effects that: the invention can solve the problem that the data of different periods and different regions can not carry out mutual reference calculation, and can carry out vector data fast query according to the distributed query nodes.

Description

Method and system for rapidly inquiring mass vector data
Technical Field
The invention relates to the technical field of data caching, in particular to a method and a system for quickly querying massive vector data.
Background
At present, vector data is a common representation method of spatial data in a geographic information system, and is a data organization method for expressing and processing spatial ground feature features based on a vector description method, and mainly comprises point vector data, line vector data and plane vector data. The point vector is used to describe various mark points on the map, such as monitoring points, residential points, and the like. The main technical difficulties of the application of the vector data are that the data volume of the point vector data is large, the distribution is not uniform, the topological space analysis relationship is complex, and the like. At present, vector data query is mostly performed based on a relational database (spatial database) for retrieval, but the efficiency of the relational database in storing and querying massive vector data is linearly reduced, and mutual reference calculation should be performed in consideration of the requirement of vector data obtained in different periods and different regions, which cannot be achieved by a traditional vector data retrieval system based on the relational database.
Disclosure of Invention
The invention provides a method and a system for rapidly inquiring massive vector data, which are used for solving the problem that a traditional vector data retrieval system of a relational database cannot realize the mutual reference calculation of vector data obtained in different periods and different regions.
A method for rapidly querying mass vector data comprises the following steps:
partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates according to the linear index to form grid coordinates;
carrying out funnel type filing mapping on vector data with different longitudes and latitudes through grid coordinates, and establishing block index associated data;
generating a multi-level distributed query node according to the block index association data;
and determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients.
As an embodiment of the present invention: partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates to form grid coordinates, wherein the method comprises the following steps:
acquiring a global longitude and latitude map, and constructing a global coordinate frame based on a spatial coordinate system;
acquiring geographic information of each coordinate point of the global coordinate frame according to the global coordinate frame;
determining a corresponding coordinate point according to the geographic information;
according to the geographic information, partitioning the global coordinate frame to determine partitioning information;
establishing a linear index according to the block information and the corresponding coordinate point;
constructing a space grid model based on longitude and latitude coordinates according to a space coordinate system;
according to the space grid model, a mapping network based on vector data is established; wherein the mapping net comprises a first mapping set and a second mapping set;
the first set of mappings corresponds to the vector data;
the second mapping set corresponds to grid coordinates in the spatial grid model;
the mapping network is used for managing vector data and determining grid coordinates.
As an embodiment of the present invention: the funnel type filing mapping is carried out on the vector data with different longitudes and latitudes through a coordinate grid, and the block index associated data is established, and the method comprises the following steps:
acquiring vector data, and determining target vector data corresponding to each space grid after longitude and latitude coordinate gridding;
comparing the vector data with target vector data, and performing funnel-type filing on the vector data according to a comparison result;
according to the funnel type filing, the vector data are associated with the corresponding spatial grids according to geographic information;
and after the vector data are associated with the spatial grids, partitioning the vector data according to geographic information and longitude and latitude coordinates according to the linear index, and determining index associated data corresponding to each spatial grid through the linear index after partitioning.
As an embodiment of the present invention: the generating a multi-level distributed query node according to the block index association data includes:
a public message adapter and a sub-message adapter for vector data management are set up on a spatial grid in advance; wherein,
the public message adapter corresponds to geographic information;
the sub-message adapter corresponds to a certain type of vector data in the current geographic position;
determining vector data characteristics corresponding to each spatial grid according to the association of the sub-message adapters and the block indexes;
determining a sub-message adapter corresponding to each public message adapter according to the public message adapter and the block index association;
and the sub-message adapter is connected with a distributed network, and a distributed query node is generated after connection.
As an embodiment of the present invention: determining index management data of vector data according to a screening algorithm, determining correlation coefficients of the index management data and distributed query nodes, and determining a target distributed query node based on the correlation coefficients, wherein the method comprises the following steps:
step 1: screening out index management data of the vector data based on a preset algorithm, wherein the index management data is shown as the following formula:
Figure GDA0003447009500000041
wherein S represents vector data; p is a radical ofiData characteristics representing the ith data in the vector data; q. q.siIndicating the frequency of occurrence of data features of the ith data in the vector data; w is aiSemantics representing data characteristics of ith data in the vector data; 1, 2, 3 … … n; n represents the number of vector data;
step 2: determining a distribution function of the distributed query nodes according to the distributed query nodes:
Figure GDA0003447009500000042
wherein m represents the number of distributed query nodes; a isjRepresenting a corresponding geographic location of a jth distributed query node; bjRepresenting a corresponding vector data feature of a jth distributed query node; f (J)j，Wj) A geographic coordinate function representing corresponding vector data for a jth distributed query node; j. the design is a squarejA longitude representing the corresponding vector data for the jth distributed query node; wjRepresenting the latitude of the corresponding vector data of the jth distributed query node; k is a radical ofjCorresponding vector data representing a jth distributed query node; j is 1, 2, 3 … … m; m represents the total number of distributed query nodes;
and step 3: determining the correlation coefficient of the distributed query node and the index management data according to the index management data and the distribution function of the distributed query node:
Figure GDA0003447009500000051
wherein, X represents a correlation coefficient, and when X is 1, the data characteristics of the jth distributed query node and the ith data of the vector data are correlated;
and 4, step 4: and according to the correlation coefficient, taking the distributed query node corresponding to the correlation coefficient as a target distributed query node, and performing vector data query.
A massive vector data rapid query system comprises:
a mapping module: partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates according to the linear index to form grid coordinates;
an indexing module: carrying out funnel type filing mapping on vector data with different longitudes and latitudes through a coordinate grid, and establishing block index associated data;
the distributed query node generation module: generating a multi-level distributed query node according to the block index association data;
the query module: and determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients.
As an embodiment of the present invention: the mapping module includes:
a first building unit: the system comprises a global longitude and latitude map acquisition module, a global coordinate frame and a global coordinate frame, wherein the global longitude and latitude map acquisition module is used for acquiring a global longitude and latitude map and constructing the global coordinate frame based on a space coordinate system;
a first acquisition unit: the geographic information of each coordinate point of the global coordinate frame is acquired according to the global coordinate frame;
a first determination unit: the coordinate point is used for determining a corresponding coordinate point according to the geographic information;
a second determination unit: according to the geographic information, partitioning the global coordinate frame to determine partitioning information;
the establishing unit: the linear index is established according to the block information and the corresponding coordinate point;
a second building element: the system comprises a space grid model, a space grid model and a data processing module, wherein the space grid model is used for constructing a space grid model based on longitude and latitude coordinates according to a space coordinate system;
a mapping unit: according to the space grid model, a mapping network based on vector data is established; wherein,
the mapping network comprises a first mapping set and a second mapping set;
the first set of mappings corresponds to the vector data;
the second mapping set corresponds to grid coordinates in the spatial grid model;
the mapping network is used for managing vector data and determining grid coordinates.
As an embodiment of the present invention: the index module comprises:
a second acquisition unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring vector data and determining target vector data corresponding to each space grid after longitude and latitude coordinate gridding;
a comparison unit: the funnel type archiving device is used for comparing the vector data with target vector data and carrying out funnel type archiving on the vector data according to a comparison result;
a storage unit: the funnel type filing system is used for associating the vector data with the corresponding spatial grids according to geographic information;
a blocking unit: the linear index block-dividing device is used for carrying out block-dividing on the vector data according to geographic information and longitude and latitude coordinates after the vector data is associated with the spatial grids, and determining index associated data corresponding to each spatial grid through the linear index after the block-dividing.
As an embodiment of the present invention: the distributed query node generation module comprises:
building a unit: the method comprises the steps that a public message adapter and a sub message adapter for vector data management are built on a space grid in advance; wherein,
the public message adapter corresponds to geographic information;
the sub-message adapter corresponds to a certain type of vector data in the current geographic position;
a third determination unit: the vector data characteristic corresponding to each space grid is determined according to the association of the sub-message adapter and the block index;
a fourth determination unit: the system comprises a common message adapter, a block index association and a sub message adapter, wherein the common message adapter is used for determining the sub message adapter corresponding to each common message adapter according to the common message adapter and the block index association;
a docking unit: and the distributed query node is used for docking the sub-message adapter with vector data caching equipment of the distributed network and generating the distributed query node after docking.
As an embodiment of the present invention: the query module comprises:
screening unit: the index management data used for screening out the vector data based on the preset algorithm is as follows:
Figure GDA0003447009500000071
wherein S represents vector data; p is a radical ofiData characteristics representing the ith data in the vector data; q. q.siIndicating the frequency of occurrence of data features of the ith data in the vector data; w is aiSemantics representing data characteristics of ith data in the vector data; 1, 2, 3 … … n; n represents the number of vector data;
a fifth determination unit: the method is used for determining a distribution function of the distributed query nodes according to the distributed query nodes:
Figure GDA0003447009500000081
wherein m represents the number of distributed query nodes; a isjRepresenting a corresponding geographic location of a jth distributed query node; bjRepresenting a corresponding vector data feature of a jth distributed query node; f (J)j，Wj) A geographic coordinate function representing corresponding vector data for a jth distributed query node; j. the design is a squarejA longitude representing the corresponding vector data for the jth distributed query node; wjRepresenting the latitude of the corresponding vector data of the jth distributed query node; k is a radical ofjRepresenting the jth distributed query nodeThe capacity of the corresponding vector data; j is 1, 2, 3 … … m; m represents the total number of distributed query nodes;
a sixth determination unit: the correlation coefficient used for determining the distributed query node and the index management data according to the index management data and the distribution function of the distributed query node is as follows:
Figure GDA0003447009500000082
wherein, X represents a correlation coefficient, and when X is 1, the data characteristics of the jth distributed query node and the ith data of the vector data are correlated;
a cache unit: and the distributed query nodes corresponding to the correlation coefficients are used as target distributed query nodes according to the correlation coefficients, and vector data query is carried out.
The invention has the beneficial effects that: the method and the device can solve the problem that the vector data in different periods and different regions cannot be rapidly inquired, and can carry out reference calculation according to the inquired corresponding data only according to the index information of the vector data. By means of an efficient data indexing mechanism, data retrieval accuracy can be guaranteed, vector data can be rapidly queried based on the correlation between query nodes and the vector data, and data transmission is carried out.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a flowchart of a method for fast querying mass vector data according to an embodiment of the present invention;
FIG. 2 is a system diagram of a distributed query system for massive vector data according to an embodiment of the present invention;
fig. 3 is an information delivery positioning diagram of a distributed query node in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in fig. 1, the present invention is a method for fast querying mass vector data, comprising:
partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates according to the linear index to form grid coordinates; first, vector data is data representing the position and shape of a map graphic or a geographic entity in x, y coordinates in rectangular coordinates. Vector data generally represent the spatial position of a geographic entity as accurately as possible by recording coordinates. Therefore, the coordinate partitioning according to the longitude and the latitude is the simplest and most convenient partitioning method for partitioning. The linear indexing is to assemble the index items to form an index chart, and the linear indexing is realized through the index chart. The longitude and latitude coordinates of gridding mapping management are space coordinates of the longitude and latitude coordinates of any position after mapping conversion can be quickly determined by connecting and arranging the global longitude and latitude coordinates in a grid mode and in a grid mode.
Carrying out funnel type filing mapping on vector data with different longitudes and latitudes through a coordinate grid, and establishing block index associated data; the funnel type filing mapping is based on a coordinate grid, vector data are refined according to periods and data requirement links, and then are filed and mapped in a funnel mode, and the periods and the links of the vector data can be determined to be more important. After the funnel archive mapping, it can be determined that those data are more important, and the more important those vector data are, the better they can be retrieved.
Generating a multi-level distributed query node according to the block index association data;
the distributed network is a superior network structure in the prior art, and after the data is partitioned, the index relation can be established according to the blocks by indexing the associated data, so that each block can be used as a distributed query node.
And determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients. After the distributed query nodes are provided, vector data retrieval can be performed through the distributed query nodes, but in order to further improve the retrieval efficiency, a coefficient is set, and according to the coefficient, faster query is performed. The corresponding distributed nodes do not need to be found and then are queried through the distributed nodes, so that the step is reduced.
The working principle of the technical scheme is as follows: the invention mainly solves the problem that vector data obtained in different periods and different domains cannot be mutually referred and calculated and cannot be rapidly inquired. According to the invention, unique gridding coordinates are established based on the global longitude and latitude coordinates, so that vector data can be subjected to distributed query and management according to grids, homogeneous data are classified into one block based on funnel type mapping, and a high-efficiency data indexing mechanism based on blocks is realized. The established distributed query nodes can adapt the data blocks of the coordinate system to the distributed query nodes by associating the associated data with the block index, so that the vector data can be queried under a distributed query network architecture.
The beneficial effects of the above technical scheme are: the method and the device can solve the problem that the vector data in different periods and different regions cannot be rapidly inquired, and can carry out reference calculation according to the inquired corresponding data only according to the index information of the vector data. By means of an efficient data indexing mechanism, data retrieval accuracy can be guaranteed, vector data can be rapidly queried based on the correlation between query nodes and the vector data, and data transmission is carried out.
In one embodiment, pre-blocking the global latitude and longitude coordinates further comprises:
step S1: according to the global longitude and latitude coordinate model, a global coordinate model is constructed:
Figure GDA0003447009500000121
wherein x isgA horizontal axis coordinate representing the g-th longitude and latitude coordinate point; y isgA longitudinal axis coordinate representing the g-th longitude and latitude coordinate point; a. thegA longitude parameter representing a g-th longitude and latitude coordinate point; b isgRepresenting a dimension parameter of the g longitude and latitude coordinate point; vgRepresenting the position parameter of the g longitude and latitude coordinate point on the global longitude and latitude coordinate map; μ represents a coordinate conversion coefficient of longitude; θ represents a conversion coefficient of the dimensional coordinates; g is 1, 2, 3, … … G; g represents the total number of longitude and latitude coordinate points;
step S2: matching the global coordinate model with geographic information to obtain a matching value:
Figure GDA0003447009500000122
where Ψ is a match value; l (x)g，yg) A coordinate function; dhRepresenting the h-th geographic information; h is 1, 2, 3, … … H; h represents the total amount of geographical information;
step S3: calculating a weight value according to the matching value:
Figure GDA0003447009500000123
wherein R represents a weight value;
step S4: acquiring a weight value of each coordinate point in the global coordinate model, and dividing coordinate points with the same weight value into the same blocks; the coordinate points of different weights are divided into difference blocks.
The beneficial effects of the technical scheme are as follows: in step 1, the invention respectively converts longitude and latitude of any coordinate point in a global map into a longitudinal coordinate and a horizontal coordinate, and two conversion coefficients of theta and mu are calculated by cosine of a simulation mapping algorithm. In step 2, the present invention matches the geographic information with the coordinate data. L (x)g，yg) The coordinate function is a linear function, and is mainly used for introducing calculation. In step 3, the method calculates the weight value of each coordinate point, and then performs blocking based on the weight value, so that rapid blocking is facilitated.
As an embodiment of the present invention:
the pre-blocking of the global longitude and latitude coordinates, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates to form grid coordinates, comprises:
acquiring a global longitude and latitude map, and constructing a global coordinate frame based on a spatial coordinate system; the global longitude and latitude map is a data map with the functions of displaying and marking longitude and latitude, and a global coordinate frame is a frame converted into numerical coordinates according to the longitude and latitude.
Acquiring geographic information of each coordinate point of the global coordinate frame according to the global coordinate frame; the geographic information is the natural, human landscape and social information corresponding to each coordinate point.
Determining a corresponding coordinate point according to the geographic information; each piece of geographic information has its corresponding unique coordinate point.
According to the geographic information, partitioning the global coordinate frame to determine partitioning information; since regional countries, provinces, cities and the like are basically divided by humanity, nature and society in the whole global data, the invention also performs partitioning by geographic information at the time of partitioning. And after the blocks are divided, the information of each block takes the geographic information as a mark.
Establishing a linear index according to the block information and the corresponding coordinate point;
the geographic information and the coordinate points serve as landmark information, and linear index data, namely an index table, can be established.
Constructing a space grid model based on longitude and latitude coordinates according to a space coordinate system and a linear index; the spatial coordinate system can determine a spatial structure, and then the data of the index is distributed in the spatial coordinate system through the correlation of different index data in the linear index, so that a spatial grid model is generated. For example: in the spatial network, coordinate points are set according to correlation relation values among different index data, and after all the coordinate points are set, gridding is uniformly divided through edge coordinate points.
According to the space grid model, a mapping network based on vector data is established; wherein the mapping network comprises a first mapping set and a second mapping set; the mapping network is a space network formed by mapping the vector data to the space grid model. The mapping set corresponds to vector data and a grid space (a space formed by connecting a plurality of coordinates belongs to the grid space because the space is already gridded), and the coordinates on the mapping network are automatically formed after the mapping network is formed.
The first set of mappings corresponds to the vector data;
the second mapping set corresponds to grid coordinates in the spatial grid model;
the mapping network is used for managing vector data and determining grid coordinates.
The working principle of the technical scheme is as follows: when data processing is carried out, the global coordinate frame is built based on the global longitude and latitude map. In principle, the method is also a space model, and a space database is also constructed. And the vector data is accurately positioned through partitioning, indexing and number mapping management.
The beneficial effects of the above technical scheme are: the vector data can be accurately positioned, a data management mechanism of a space grid can be constructed through a grid model of the vector data, and the specific position of the vector data in a mapping space, namely the coordinate information of the vector data, is determined through the vector data quick query method, so that the vector data quick query is realized.
As an embodiment of the present invention:
the funnel type filing mapping is carried out on the vector data with different longitudes and latitudes through a coordinate grid, and the block index associated data is established, and the method comprises the following steps:
acquiring vector data, and determining target vector data corresponding to each space grid after longitude and latitude coordinate gridding; because the vector data is mapped into the spatial mesh model, each piece of vector data corresponds to a part of the mesh, i.e. a spatial region, in the spatial mesh model, and thus target vector data exists in each mesh.
Comparing the vector data with target vector data, and performing funnel-type filing on the vector data according to a comparison result; the purpose of the comparison is to determine that the target is the ratio of the two data in the total vector data, including the weights. The funnel-type filing is to file the data according to the importance of part of vector data in the total vector data;
according to the funnel type filing, the vector data are associated with the corresponding spatial grids according to geographic information; the vector data after being filed can determine the corresponding geographic information and the position of the spatial grid in the spatial network because the importance is determined, and the correlation has the effect that the vector data query can be carried out according to the geographic information and the coordinates of the spatial grid.
And after the vector data are associated with the spatial grids, partitioning the vector data according to geographic information and longitude and latitude coordinates according to the linear index, and determining index associated data corresponding to each spatial grid through the linear index after partitioning. The block function is that after the vector data index is realized by the geographic information and the spatial grid, a block network which takes the linear index as the data retrieval query information is established.
The working principle of the technical scheme is as follows: the index association established by the invention has the effect that the data can be quickly queried through the index association data, and the comparison between the vector data and the target vector data is carried out to ensure that the data is consistent with the corresponding data block, so that the query can be carried out on the corresponding distributed query node.
The beneficial effects of the above technical scheme are: the invention classifies and archives the vector data through the comparison of the space grid and the vector data, then extracts necessary vector data, and after the data block is determined, the distributed query node of the vector data is conveniently determined.
As an embodiment of the present invention:
the generating a multi-level distributed query node according to the block index association data includes:
a public message adapter and a sub-message adapter for vector data management are set up on a spatial grid in advance; wherein,
the public message adapter corresponds to geographic information;
the sub-message adapter corresponds to a certain type of vector data in the current geographic position;
the public message adapter and the sub-message adapter are used for matching with the geographic information and the vector data respectively.
Associating the sub-message adapter with the block index, and determining vector data characteristics corresponding to each spatial grid;
associating the public message adapters with the block indexes, and determining sub message adapters corresponding to each public message adapter; the purpose of this step is to correspond the geographic information to the vector data of a single type, thereby realizing more accurate retrieval and query.
And the sub-message adapter is connected with a distributed network, and a distributed query node is generated after connection.
The working principle of the technical scheme is as follows: as shown in fig. 3, in the present invention, the adapters are established to perform the cache docking of the vector data, the common message adapter determines the corresponding vector data, and the sub-message adapters determine the type of the vector data, thereby achieving the accurate positioning. The main purpose is to determine that each sub-message adapter is interfaced with that node of the distributed network by matching the correlation sum, vector data and vector data characteristics, for more accurate and faster positioning and data transmission.
The beneficial effects of the above technical scheme are: in order to realize accurate caching of vector data, the invention realizes efficient positioning and fixed point positioning of the vector data by establishing adapters with different specifications.
As an embodiment of the present invention:
the determining index management data of the vector data according to the screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and determining the target distributed query node based on the correlation coefficients includes:
step 1: screening out index management data of the vector data based on a preset algorithm, wherein the index management data is shown as the following formula:
Figure GDA0003447009500000171
wherein S represents vector data; p is a radical ofiData characteristics representing the ith data in the vector data; q. q.siIndicating the frequency of occurrence of data features of the ith data in the vector data; w is aiSemantics representing data characteristics of ith data in the vector data; 1, 2, 3 … … n; n represents the number of vector data;
in step 1, an index management function is determined by fusing a vector data frequency function and a semantic function respectively. Wherein
Figure GDA0003447009500000172
A frequency function representing vector data;
Figure GDA0003447009500000173
a semantic function representing vector data. When the ith data is introduced according to the step 1, if the final calculation result is more than or equal to 1, the data can be used as an indexData is managed because it occurs more frequently and semantics are larger in the overall vector data.
Step 2: determining a distribution function of the distributed query nodes according to the distributed query nodes:
Figure GDA0003447009500000181
wherein m represents the number of distributed query nodes; a isjRepresenting a corresponding geographic location of a jth distributed query node; bjRepresenting a corresponding vector data feature of a jth distributed query node; f (J)j，Wj) A geographic coordinate function representing corresponding vector data for a jth distributed query node; j. the design is a squarejA longitude representing the corresponding vector data for the jth distributed query node; wjRepresenting the latitude of the corresponding vector data of the jth distributed query node; k is a radical ofjRepresenting the capacity of the corresponding vector data of the jth distributed query node; j is 1, 2, 3 … … m; m represents the total number of distributed query nodes;
in step 2, the invention determines the distribution function of the vector data by calculating the geographical position of the distributed node, the vector data characteristics and the dimension and capacity functions of the vector data. The present invention can be represented by a functional image with an exponential function as a coordinate system.
And step 3: determining the correlation coefficient of the distributed query node and the index management data according to the index management data and the distribution function of the distributed query node:
Figure GDA0003447009500000182
wherein, X represents a correlation coefficient, and when X is 1, the data characteristics of the jth distributed query node and the ith data of the vector data are correlated;
in step 3, the distributed query nodes and the index management data are calculated, and the final correlation coefficient can be used as the index data to query the vector data. And is more accurate.
And 4, step 4: and according to the correlation coefficient, taking the distributed query node corresponding to the correlation coefficient as a target distributed query node, and performing vector data query.
The working principle of the technical scheme is as follows: in the process of caching the vector data, the index management data of the vector data is screened out based on a preset algorithm, so that the data can be quickly searched in a data grid. The distribution function of the distributed query nodes is determined according to the distributed query nodes, so that the distribution state of the vector data is determined, and the data is located at the position. Then, the relevance detection of the vector data and the distributed nodes is realized through a fusion algorithm, so that the accurate relation positioning of the vector data is realized, and the error of a vector data query mode is prevented.
The beneficial effects of the above technical scheme are: the data search can be rapidly carried out in the data grid. The distribution state of the vector data is determined, which data is at that location. And realizing accurate query of vector data.
As shown in the attached figure 2 of the drawings,
a massive vector data rapid query system comprises:
a mapping module: partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates according to the linear index to form grid coordinates;
an indexing module: carrying out funnel type filing mapping on vector data with different longitudes and latitudes through a coordinate grid, and establishing block index associated data;
the distributed query node generation module: generating a multi-level distributed query node according to the block index association data;
the query module: and determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients.
The working principle of the technical scheme is as follows: the invention mainly solves the problem that vector data obtained in different periods and different domains cannot be mutually referred and calculated and cannot be rapidly inquired. According to the invention, unique gridding coordinates are established based on the global longitude and latitude coordinates, so that vector data can be subjected to distributed query and management according to grids, homogeneous data are classified into one block based on funnel type mapping, and a high-efficiency data indexing mechanism based on blocks is realized. The established distributed query nodes can adapt the data blocks of the coordinate system to the distributed query nodes by associating the associated data with the block index, so that the vector data can be queried under a distributed query network architecture.
The beneficial effects of the above technical scheme are: the method and the device can solve the problem that the vector data in different periods and different regions cannot be rapidly inquired, and can carry out reference calculation according to the inquired corresponding data only according to the index information of the vector data. By means of an efficient data indexing mechanism, data retrieval accuracy can be guaranteed, vector data can be rapidly queried based on the correlation between query nodes and the vector data, and data transmission is carried out.
As an embodiment of the present invention: the mapping module includes:
a first building unit: the system comprises a global longitude and latitude map acquisition module, a global coordinate frame and a global coordinate frame, wherein the global longitude and latitude map acquisition module is used for acquiring a global longitude and latitude map and constructing the global coordinate frame based on a space coordinate system;
a first acquisition unit: the geographic information of each coordinate point of the global coordinate frame is acquired according to the global coordinate frame;
a first determination unit: the coordinate point is used for determining a corresponding coordinate point according to the geographic information;
a second determination unit: according to the geographic information, partitioning the global coordinate frame to determine partitioning information;
the establishing unit: the linear index is established according to the block information and the corresponding coordinate point;
a second building element: the system comprises a space grid model, a space grid model and a data processing module, wherein the space grid model is used for constructing a space grid model based on longitude and latitude coordinates according to a space coordinate system;
a mapping unit: according to the space grid model, a mapping network based on vector data is established; wherein,
the mapping network comprises a first mapping set and a second mapping set;
the first set of mappings corresponds to the vector data;
the second mapping set corresponds to grid coordinates in the spatial grid model;
the mapping network is used for managing vector data and determining grid coordinates.
The working principle of the technical scheme is as follows: when data processing is carried out, the global coordinate frame is built based on the global longitude and latitude map. In principle, the method is also a space model, and a space database is also constructed. And the vector data is accurately positioned through partitioning, indexing and number mapping management.
The beneficial effects of the above technical scheme are: the vector data can be accurately positioned, a data management mechanism of a space grid can be constructed through a grid model of the vector data, and the specific position of the vector data in a mapping space, namely the coordinate information of the vector data, is determined through the vector data quick query method, so that the vector data quick query is realized.
As an embodiment of the present invention: the indexing module comprises:
a second acquisition unit: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring vector data and determining target vector data corresponding to each space grid after longitude and latitude coordinate gridding;
a comparison unit: the funnel type archiving device is used for comparing the vector data with target vector data and carrying out funnel type archiving on the vector data according to a comparison result;
a storage unit: the funnel type filing system is used for associating the vector data with the corresponding spatial grids according to geographic information;
a blocking unit: the linear index block-dividing device is used for carrying out block-dividing on the vector data according to geographic information and longitude and latitude coordinates after the vector data is associated with the spatial grids, and determining index associated data corresponding to each spatial grid through the linear index after the block-dividing.
The working principle of the technical scheme is as follows: the index association established by the invention has the effect that the data can be quickly queried through the index association data, and the comparison between the vector data and the target vector data is carried out to ensure that the data is consistent with the corresponding data block, so that the query can be carried out on the corresponding distributed query node.
The beneficial effects of the above technical scheme are: the invention classifies and archives the vector data through the comparison of the space grid and the vector data, then extracts necessary vector data, and after the data block is determined, the distributed query node of the vector data is conveniently determined.
As an embodiment of the present invention: the distributed query node generation module comprises:
building a unit: the method comprises the steps that a public message adapter and a sub message adapter for vector data management are built on a space grid in advance; wherein,
the public message adapter corresponds to geographic information;
the sub-message adapter corresponds to a certain type of vector data in the current geographic position;
a third determination unit: the vector data characteristic corresponding to each space grid is determined according to the association of the sub-message adapter and the block index;
a fourth determination unit: the system comprises a common message adapter, a block index association and a sub message adapter, wherein the common message adapter is used for determining the sub message adapter corresponding to each common message adapter according to the common message adapter and the block index association;
a docking unit: and the distributed query node is used for docking the sub-message adapter with vector data caching equipment of the distributed network and generating the distributed query node after docking.
The working principle of the technical scheme is as follows: as shown in fig. 3, in the present invention, the adapters are established to perform the cache docking of the vector data, the common message adapter determines the corresponding vector data, and the sub-message adapters determine the type of the vector data, thereby achieving the accurate positioning.
The beneficial effects of the above technical scheme are: in order to realize accurate caching of vector data, the invention realizes efficient positioning and fixed point positioning of the vector data by establishing adapters with different specifications.
As an embodiment of the present invention: the query module comprises:
screening unit: the index management data used for screening out the vector data based on the preset algorithm is as follows:
Figure GDA0003447009500000231
wherein S represents vector data; p is a radical ofiData characteristics representing the ith data in the vector data; q. q.siIndicating the frequency of occurrence of data features of the ith data in the vector data; w is aiSemantics representing data characteristics of ith data in the vector data; 1, 2, 3 … … n; n represents the number of vector data;
a fifth determination unit: the method is used for determining a distribution function of the distributed query nodes according to the distributed query nodes:
Figure GDA0003447009500000232
wherein m represents the number of distributed query nodes; a isjRepresenting a corresponding geographic location of a jth distributed query node; bjRepresenting a corresponding vector data feature of a jth distributed query node; f (J)j，Wj) A geographic coordinate function representing corresponding vector data for a jth distributed query node; j. the design is a squarejA longitude representing the corresponding vector data for the jth distributed query node; wjRepresenting the latitude of the corresponding vector data of the jth distributed query node; k is a radical ofjRepresenting the capacity of the corresponding vector data of the jth distributed query node; j is 1, 2, 3 … … m; m represents the total number of distributed query nodes;
a sixth determination unit: the correlation coefficient used for determining the distributed query node and the index management data according to the index management data and the distribution function of the distributed query node is as follows:
Figure GDA0003447009500000241
wherein, X represents a correlation coefficient, and when X is 1, the data characteristics of the jth distributed query node and the ith data of the vector data are correlated;
a cache unit: and the distributed query nodes corresponding to the correlation coefficients are used as target distributed query nodes according to the correlation coefficients, and vector data query is carried out.
The working principle of the technical scheme is as follows: in the process of caching the vector data, the index management data of the vector data is screened out based on a preset algorithm, so that the data can be quickly searched in a data grid. The distribution function of the distributed query node is determined from the distributed query nodes in order to determine the distribution state of the vector data, which data is at that location. Then, the relevance detection of the vector data and the distributed nodes is realized through a fusion algorithm, so that the accurate relation positioning of the vector data is realized, and the error of a vector data query mode is prevented.
The beneficial effects of the above technical scheme are: the data search can be rapidly carried out in the data grid. The distribution state of the vector data is determined, which data is at that location. And realizing accurate query of vector data.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (8)

1. A method for rapidly querying mass vector data is characterized by comprising the following steps:
partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates according to the linear index to form grid coordinates;
carrying out funnel type filing mapping on vector data with different longitudes and latitudes through grid coordinates, and establishing block index associated data; wherein,
the funnel type filing is to file data according to the importance of partial vector data in the total vector data;
generating a multi-level distributed query node according to the block index association data;
determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients;
the generating a multi-level distributed query node according to the block index association data includes:
a public message adapter and a sub-message adapter for vector data management are set up on a spatial grid in advance; wherein,
the public message adapter corresponds to geographic information;
the sub-message adapter corresponds to a certain type of vector data in the current geographic position;
associating the sub-message adapter with the block index, and determining vector data characteristics corresponding to each spatial grid;
associating the public message adapters with the block indexes, and determining sub message adapters corresponding to each public message adapter;
and the sub-message adapter is connected with a distributed network, and a distributed query node is generated after connection.
2. The method as claimed in claim 1, wherein the fast query method of mass vector data is characterized in that the global longitude and latitude coordinates are partitioned in advance, a linear index is established, and the longitude and latitude coordinates are subjected to gridding mapping management to form grid coordinates, and the method comprises the following steps:
acquiring a global longitude and latitude map, and constructing a global coordinate frame based on a spatial coordinate system;
acquiring geographic information of each coordinate point of the global coordinate frame according to the global coordinate frame;
determining a corresponding coordinate point according to the geographic information;
according to the geographic information, partitioning the global coordinate frame to determine partitioning information;
establishing a linear index according to the block information and the corresponding coordinate point;
constructing a space grid model based on longitude and latitude coordinates according to a space coordinate system and a linear index;
according to the space grid model, a mapping network based on vector data is established; wherein the mapping network comprises a first mapping set and a second mapping set;
the first set of mappings corresponds to the vector data;
the second mapping set corresponds to grid coordinates in the spatial grid model;
the mapping network is used for managing vector data and determining grid coordinates.
3. The method for rapidly querying mass vector data according to claim 1, wherein the funnel-type filing mapping is performed on the vector data with different longitudes and latitudes through grid coordinates, and the establishing of the block index association data comprises:
acquiring vector data, and determining target vector data corresponding to each space grid after the longitude and latitude grid is coordinated;
comparing the vector data with target vector data, and performing funnel-type filing on the vector data according to a comparison result;
according to the funnel type filing, the vector data are associated with the corresponding spatial grids according to geographic information;
and after the vector data are associated with the spatial grids, partitioning the vector data according to geographic information and longitude and latitude coordinates according to the linear index, and determining index associated data corresponding to each spatial grid through the linear index after partitioning.
4. The method as claimed in claim 1, wherein the step of determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and determining the target distributed query nodes based on the correlation coefficients comprises:
step 1: based on the screening algorithm, screening out index management data of the vector data, as shown in the following formula:
Figure 868603DEST_PATH_IMAGE002
wherein,
Figure DEST_PATH_IMAGE003
representing vector data;
Figure 582481DEST_PATH_IMAGE004
representing the second in vector data
Figure DEST_PATH_IMAGE005
A data characteristic of the individual data;
Figure 424535DEST_PATH_IMAGE006
representing the second in vector data
Figure 350903DEST_PATH_IMAGE005
Frequency of occurrence of data features of the individual data;
Figure DEST_PATH_IMAGE007
representing the second in vector data
Figure 766273DEST_PATH_IMAGE005
Semantics of data characteristics of the data;
Figure 854315DEST_PATH_IMAGE008
；
Figure DEST_PATH_IMAGE009
indicating the number of data of the vector data;
step 2: determining a distribution function of the distributed query nodes according to the distributed query nodes:
Figure DEST_PATH_IMAGE011
wherein,
Figure 714823DEST_PATH_IMAGE012
representing the number of distributed query nodes;
Figure DEST_PATH_IMAGE013
is shown as
Figure 477505DEST_PATH_IMAGE014
The corresponding geographic location of each distributed query node;
Figure DEST_PATH_IMAGE015
is shown as
Figure 943122DEST_PATH_IMAGE014
Corresponding vector data characteristics of the distributed query nodes;
Figure 733223DEST_PATH_IMAGE016
is shown as
Figure 753132DEST_PATH_IMAGE014
Location of corresponding vector data of distributed query nodeA physical coordinate function;
Figure DEST_PATH_IMAGE017
is shown as
Figure 552460DEST_PATH_IMAGE014
Longitude of corresponding vector data of each distributed query node;
Figure 607004DEST_PATH_IMAGE018
is shown as
Figure 69472DEST_PATH_IMAGE014
Latitude of corresponding vector data of each distributed query node;
Figure DEST_PATH_IMAGE019
is shown as
Figure 373414DEST_PATH_IMAGE014
Capacity of corresponding vector data of the distributed query nodes;
Figure 914117DEST_PATH_IMAGE020
；
Figure DEST_PATH_IMAGE021
representing the total number of distributed query nodes;
and step 3: determining the correlation coefficient of the distributed query node and the index management data according to the index management data and the distribution function of the distributed query node:
Figure DEST_PATH_IMAGE023
wherein,
Figure 885484DEST_PATH_IMAGE024
represents a correlation coefficient when
Figure DEST_PATH_IMAGE025
When is shown as
Figure 282967DEST_PATH_IMAGE014
A distributed query node and a second of the vector data
Figure 44512DEST_PATH_IMAGE005
Data characteristic correlation of the data;
and 4, step 4: and according to the correlation coefficient, taking the distributed query node corresponding to the correlation coefficient as a target distributed query node, and performing vector data query.
5. A system for rapidly querying mass vector data is characterized by comprising:
a mapping module: partitioning global longitude and latitude coordinates in advance, establishing a linear index, and carrying out gridding mapping management on the longitude and latitude coordinates according to the linear index to form grid coordinates;
an indexing module: carrying out funnel type filing mapping on vector data with different longitudes and latitudes through grid coordinates, and establishing block index associated data; wherein,
the funnel type filing is to file data according to the importance of partial vector data in the total vector data;
the distributed query node generation module: generating a multi-level distributed query node according to the block index association data;
the query module: determining index management data of the vector data according to a screening algorithm, determining correlation coefficients of the index management data and the distributed query nodes, and performing vector data query through the corresponding distributed query nodes based on the correlation coefficients;
the distributed query node generation module comprises:
building a unit: the method comprises the steps that a public message adapter and a sub message adapter for vector data management are built on a space grid in advance; wherein,
the public message adapter corresponds to geographic information;
the sub-message adapter corresponds to a certain type of vector data in the current geographic position;
a third determination unit: the vector data characteristic corresponding to each space grid is determined according to the association of the sub-message adapter and the block index;
a fourth determination unit: the system comprises a common message adapter, a block index association and a sub message adapter, wherein the common message adapter is used for determining the sub message adapter corresponding to each common message adapter according to the common message adapter and the block index association;
a docking unit: and the distributed query node is used for docking the sub-message adapter with vector data caching equipment of the distributed network and generating the distributed query node after docking.
6. The system for rapidly querying mass vector data according to claim 5, wherein the mapping module comprises:
a first building unit: the system comprises a global longitude and latitude map acquisition module, a global coordinate frame and a global coordinate frame, wherein the global longitude and latitude map acquisition module is used for acquiring a global longitude and latitude map and constructing the global coordinate frame based on a space coordinate system;
a first acquisition unit: the geographic information of each coordinate point of the global coordinate frame is acquired according to the global coordinate frame;
a first determination unit: the coordinate point is used for determining a corresponding coordinate point according to the geographic information;
a second determination unit: according to the geographic information, partitioning the global coordinate frame to determine partitioning information;
the establishing unit: the linear index is established according to the block information and the corresponding coordinate point;
a second building element: the system comprises a space grid model, a space grid model and a data processing module, wherein the space grid model is used for constructing a space grid model based on longitude and latitude coordinates according to a space coordinate system;
a mapping unit: according to the space grid model, a mapping network based on vector data is established; wherein,
the mapping network comprises a first mapping set and a second mapping set;
the first set of mappings corresponds to the vector data;
the second mapping set corresponds to grid coordinates in the spatial grid model;
the mapping network is used for managing vector data and determining grid coordinates.
7. The system for rapidly querying mass vector data according to claim 5, wherein the indexing module comprises:
a second acquisition unit: the system is used for acquiring vector data and determining target vector data corresponding to each space grid after the longitude and latitude grid is coordinated;
a comparison unit: the funnel type archiving device is used for comparing the vector data with target vector data and carrying out funnel type archiving on the vector data according to a comparison result;
a storage unit: the funnel type filing system is used for associating the vector data with the corresponding spatial grids according to geographic information;
a blocking unit: the linear index block-dividing device is used for carrying out block-dividing on the vector data according to geographic information and longitude and latitude coordinates after the vector data is associated with the spatial grids, and determining index associated data corresponding to each spatial grid through the linear index after the block-dividing.
8. The system for rapidly querying mass vector data according to claim 5, wherein the query module comprises:
screening unit: index management data for screening out vector data based on the screening algorithm, as shown in the following formula:
Figure 388906DEST_PATH_IMAGE026
wherein,
Figure 418042DEST_PATH_IMAGE003
representing vector data;
Figure 720847DEST_PATH_IMAGE004
representing the second in vector data
Figure 202644DEST_PATH_IMAGE005
A data characteristic of the individual data;
Figure 616308DEST_PATH_IMAGE006
representing the second in vector data
Figure 234371DEST_PATH_IMAGE005
Frequency of occurrence of data features of the individual data;
Figure 708078DEST_PATH_IMAGE007
representing the second in vector data
Figure 411591DEST_PATH_IMAGE005
Semantics of data characteristics of the data;
Figure 363367DEST_PATH_IMAGE008
；
Figure 134139DEST_PATH_IMAGE009
indicating the number of data of the vector data;
a fifth determination unit: the method is used for determining a distribution function of the distributed query nodes according to the distributed query nodes:
Figure DEST_PATH_IMAGE027
wherein,
Figure 44326DEST_PATH_IMAGE012
representing the number of distributed query nodes;
Figure 500715DEST_PATH_IMAGE013
is shown as
Figure 990602DEST_PATH_IMAGE014
The corresponding geographic location of each distributed query node;
Figure 583258DEST_PATH_IMAGE015
is shown as
Figure 398767DEST_PATH_IMAGE014
Corresponding vector data characteristics of the distributed query nodes;
Figure 342452DEST_PATH_IMAGE016
is shown as
Figure 403075DEST_PATH_IMAGE014
Geographic coordinate functions of corresponding vector data of the distributed query nodes;
Figure 850236DEST_PATH_IMAGE017
is shown as
Figure 571068DEST_PATH_IMAGE014
Longitude of corresponding vector data of each distributed query node;
Figure 2049DEST_PATH_IMAGE018
is shown as
Figure 99318DEST_PATH_IMAGE014
Latitude of corresponding vector data of each distributed query node;
Figure 932145DEST_PATH_IMAGE019
is shown as
Figure 823877DEST_PATH_IMAGE014
Capacity of corresponding vector data of the distributed query nodes;
Figure 742155DEST_PATH_IMAGE020
；
Figure 643115DEST_PATH_IMAGE021
representing the total number of distributed query nodes;
a sixth determination unit: the correlation coefficient used for determining the distributed query node and the index management data according to the index management data and the distribution function of the distributed query node is as follows:
Figure 843632DEST_PATH_IMAGE023
wherein,
Figure 171845DEST_PATH_IMAGE024
represents a correlation coefficient when
Figure 311839DEST_PATH_IMAGE025
When is shown as
Figure 16490DEST_PATH_IMAGE014
A distributed query node and a second of the vector data
Figure 292751DEST_PATH_IMAGE005
Data characteristic correlation of the data;
a cache unit: and the distributed query nodes corresponding to the correlation coefficients are used as target distributed query nodes according to the correlation coefficients, and vector data query is carried out.
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