CN116226553A - Track query method and device and storage medium - Google Patents
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Abstract
The disclosure provides a track query method and device and a storage medium, and relates to the field of big data. The track inquiry method comprises the following steps: identifying a plurality of geographic grids corresponding to the query area to generate a plurality of query area partition data, wherein the ith query area partition data comprises grid codes of an ith geographic grid in the plurality of geographic grids, i is more than or equal to 1 and less than or equal to N, and N is the total number of the geographic grids; extracting a plurality of preset track partition data, wherein each track partition data comprises a track identifier and a grid code corresponding to the track identifier; matching the plurality of query region partition data with the plurality of track partition data to generate a plurality of candidate partition data; acquiring track data corresponding to track identifiers in the J candidate packet data, wherein J is more than or equal to 1 and less than or equal to J, and J is the total number of the candidate packet data; and under the condition that track data corresponding to the track identification in the j candidate packet data intersects with the query area, taking the track identification and the grid code in the j candidate packet data as query results.
Description
Technical Field
The disclosure relates to the field of big data, and in particular relates to a track query method and device and a storage medium.
Background
Track visualization refers to displaying the queried track data of the vehicle directly on a map, so that a user can more intuitively perceive the position and the driving route of the vehicle. Trajectory visualization can be applied to many urban scenarios, for example: real-time monitoring of the vehicle position, early warning of illegal route running, and the like.
At present, the method for inquiring massive track data mainly comprises the following two steps: the first scheme is to query mass offline data by using distributed storage and distributed offline computing technology. The usual method is to store and index with Hbase database, using Spark as calculation engine. And establishing a primary index in the HBase through space-time coding, screening out data, entering a Spark calculation engine, and then carrying out accurate screening. The second scheme is that for real-time scenes, kafka is utilized to access real-time track positioning points, then a single machine service internally screens each positioning point through a predefined query area, and finally the filtered positioning points are output to other consumption ends.
Disclosure of Invention
The inventor notes that in the first solution, the query needs to be performed after all data needs to be imported into HBase, so that the real-time performance is poor, and it is difficult to support the query scene of the real-time dynamic track. In the second scheme, the processing capability of the single service has a bottleneck when the data volume is large, and only a single GPS point can be screened, so that the whole track cannot be filtered.
Accordingly, the track query method can query mass data in real time.
According to a first aspect of an embodiment of the present disclosure, there is provided a track query method, including: identifying a plurality of geographic grids corresponding to the query region to generate a plurality of query region partition data, wherein the ith query region partition data comprises grid codes of the ith geographic grid in the plurality of geographic grids, i is more than or equal to 1 and less than or equal to N, and N is the total number of geographic grids; extracting a plurality of preset track partition data, wherein each track partition data comprises a track identifier and a grid code corresponding to the track identifier; matching the plurality of query region partition data with the plurality of track partition data to generate a plurality of candidate partition data; acquiring track data corresponding to track identifiers in the J candidate packet data, wherein J is more than or equal to 1 and less than or equal to J, and J is the total number of the candidate packet data; and under the condition that track data corresponding to the track identification in the j candidate packet data is intersected with the query area, taking the track identification and the grid coding in the j candidate packet data as query results.
In some embodiments, the matching the plurality of query region partition data to the plurality of track partition data comprises: extracting the grid codes in the i-th query region partition data to serve as target grid codes; and under the condition that the grid code in the mth track partition data is matched with the target grid code, correlating the mth track partition data with the ith query area partition data to generate the candidate partition data, wherein M is more than or equal to 1 and less than or equal to M, and M is the total number of track partition data.
In some embodiments, the ith query region partition data is deleted without including the target trellis code in each track partition data.
In some embodiments, the mth track partition data is deleted in the event that the mth track partition data is not associated with any of the query region partition data.
In some embodiments, the j candidate packet data is deleted in a case where the trace data corresponding to the trace identification in the j candidate packet data does not intersect the query region.
In some embodiments, the above method further comprises: generating the plurality of track partition data; wherein the generating the plurality of track partition data comprises: sorting the positioning information of each movable target in a preset time range according to time sequence to obtain track information of each movable target; dividing the track information of each movable target by using a preset geographic grid to obtain the plurality of track partition data.
In some embodiments, the geographic grid is a geohash grid.
According to a second aspect of embodiments of the present disclosure, there is provided a trajectory query device, including: the first processing module is configured to identify a plurality of geographic grids corresponding to the query area to generate a plurality of query area partition data, wherein the ith query area partition data comprises grid codes of an ith geographic grid in the plurality of geographic grids, i is more than or equal to 1 and less than or equal to N, and N is the total number of the geographic grids; the second processing module is configured to extract a plurality of preset track partition data, wherein each track partition data comprises a track identifier and a grid code corresponding to the track identifier, and match the plurality of track partition data with the plurality of query area partition data to generate a plurality of candidate partition data; the third processing module is configured to acquire track data corresponding to track identifiers in the jth candidate packet data, wherein J is more than or equal to 1 and less than or equal to J, J is the total number of the candidate packet data, and the track identifiers and the grid codes in the jth candidate packet data are used as query results under the condition that the track data corresponding to the track identifiers in the jth candidate packet data are intersected with the query area.
In some embodiments, the second processing module is configured to extract the grid code in the i-th query region partition data as a target grid code, and in a case that the grid code in the M-th track partition data matches the target grid code, associate the M-th track partition data with the i-th query region partition data to generate the candidate partition data, where 1.ltoreq.m.ltoreq.m, and M is a total number of track partition data.
In some embodiments, the second processing module is configured to delete the i-th query region partition data if the target trellis code is not included in each track partition data.
In some embodiments, the second processing module is configured to delete the mth track partition data if the mth track partition data is not associated with any of the query region partition data.
In some embodiments, the third processing module is configured to delete the j-th candidate packet data if the trace data corresponding to the trace identification in the j-th candidate packet data does not intersect the query region.
In some embodiments, the apparatus further comprises: and the fourth processing module is configured to generate the plurality of track partition data, wherein the positioning information of each movable target in a preset time range is ordered according to time sequence to obtain track information of each movable target, and the track information of each movable target is divided by utilizing a preset geographic grid to obtain the plurality of track partition data.
In some embodiments, the geographic grid is a geohash grid.
According to a third aspect of embodiments of the present disclosure, there is provided a track inquiry apparatus, including: a memory configured to store instructions; a processor coupled to the memory, the processor configured to perform a method according to any of the embodiments described above based on instructions stored in the memory.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium, wherein the computer readable storage medium stores computer instructions which, when executed by a processor, implement a method as referred to in any of the embodiments above.
Other features of the present disclosure and its advantages will become apparent from the following detailed description of exemplary embodiments of the disclosure, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present disclosure, and that other drawings may be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of a track query method according to an embodiment of the disclosure;
FIG. 2 is a schematic diagram of a query region of an embodiment of the present disclosure;
FIG. 3 is a flow chart of a method of generating track partition data according to one embodiment of the present disclosure;
FIG. 4 is a diagram of partition data association according to one embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a track inquiry apparatus according to an embodiment of the present disclosure;
FIG. 6 is a schematic diagram of a track inquiry apparatus according to another embodiment of the present disclosure;
FIG. 7 is a schematic diagram of a track inquiry apparatus according to another embodiment of the present disclosure;
fig. 8 is a schematic diagram of an implementation scenario of a track inquiry apparatus according to an embodiment of the present disclosure.
Detailed Description
The following description of the technical solutions in the embodiments of the present disclosure will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, based on the embodiments in this disclosure are intended to be within the scope of this disclosure.
The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless it is specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but should be considered part of the specification where appropriate.
In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Fig. 1 is a flow chart of a track query method according to an embodiment of the disclosure. In some embodiments, the following track query method is performed by a track query device.
In step 101, a plurality of geographic grids corresponding to the query area are identified to generate a plurality of query area partition data, wherein the ith query area partition data comprises grid codes of the ith geographic grid in the plurality of geographic grids, i is greater than or equal to 1 and less than or equal to N, and N is the total number of geographic grids.
In some embodiments, the geographic grid is a geohash grid, the geographic grid corresponding to a geographic space having a length and width of approximately 150 meters by 150 meters.
In fig. 2, 9 geographical grids are shown, each of which is marked with a corresponding grid code. The dashed box in fig. 2 is the query area. The query area occupies 4 grids, and thus a plurality of query area partition data are generated as shown in table 1.
TABLE 1
Returning to fig. 1. In step 102, a preset plurality of track partition data is extracted, wherein each track partition data includes a track identifier and a grid code corresponding to the track identifier.
In some embodiments, the track partition data generation method is as shown in FIG. 3.
In step 301, positioning information of each movable object in a preset time range is ordered in time sequence, so as to obtain track information of each movable object.
For example, the positioning information may be GPS (Global Positioning System ) positioning information, beidou positioning information, etc.
For example, the server may reside in memory for a period of time after receiving the GPS point, using t m span Representing the mth residence time period. All t m span The GPS points of the same vehicle would be assembled into a track line in time sequence. Let GPS point of vehicle i be Pt i Residence time range t m span =10 minutes, then the trajectory of vehicle i in the mth 10 minutes is Traj m i ＝<Pt i 1 ,Pt i 2 ,…,Pt i n >Wherein Pt is i j Is the j-th point of the i-th vehicle.
In step 302, the track information of each movable target is divided by using a preset geographic grid to obtain a plurality of track partition data.
As shown in fig. 2, when the track information Traj1 passes through 3 grids and the track information Traj2 passes through 2 grids, a plurality of track partition data are obtained as shown in table 2.
| 1 | <ws10k0x,Traj1> |
| 2 | <ws10k0w,Traj1> |
| 3 | <ws10k0q,Traj1> |
| 4 | <ws10k0n,Traj2> |
| 5 | <ws10k0j,Traj2> |
TABLE 2
Returning to fig. 1. In step 103, the plurality of query region partition data and the plurality of track partition data are matched to generate a plurality of candidate partition data.
In some embodiments, the grid code in the ith query region partition data is extracted from the multiple query region partition data to serve as a target grid code, and in the case that the grid code in the mth track partition data is matched with the target grid code, the mth track partition data is associated with the ith query region partition data to generate candidate partition data, wherein 1.ltoreq.m.ltoreq.M is the total number of track partition data.
In addition, in the case where the track partition data having the target mesh code is not included in the plurality of track partition data, the i-th query region partition data is deleted.
In addition, in the case where the mth track partition data is not associated with any of the query region partition data, the mth track partition data is deleted.
As shown in fig. 4, the upper left corner is the plurality of query region partition data shown in table 1, and the lower left corner is the plurality of track partition data shown in table 2.
In fig. 4, the trellis code in the 1 st query Region partition data is ws10k0q, and the trellis code in the 3 rd track partition data is also ws10k0q, so that the 1 st query Region partition data and the 3 track partition data are associated, specifically expressed as < ws10k0q, region, traj1>.
In addition, the trellis code in the 3 rd query Region partition data is ws10k0n, and the trellis code in the 4 th track partition data is also ws10k0n, so the 3 rd query Region partition data and the 4 th track partition data are associated, specifically expressed as < ws10k0n, region, traj2>.
The trellis code in the 2 nd query region partition data is ws10k0r, and none of the 5 track partition data has the trellis code of ws10k0r, in which case the 2 nd query region partition data is deleted. The 4 th query region partition data also belongs to the same case, and thus the 4 th query region partition data is deleted.
In addition, the trellis codes included in the 1 st, 2 nd and 5 th track partition data are not included in the query region partition data either, and thus the 1 st, 2 nd and 5 th track partition data are deleted.
In this case, as shown in the right part of fig. 4, the resulting 2 candidate partition data are respectively: < ws10k0q, region, traj1> and < ws10k0n, region, traj2>.
In step 104, track data corresponding to the track identifier in the J-th candidate packet data is acquired, wherein J is more than or equal to 1 and less than or equal to J, and J is the total number of the candidate packet data.
In step 105, in the case where the track data corresponding to the track identifier in the j-th candidate packet data intersects with the query area, the track identifier and the trellis code in the j-th candidate packet data are used as the query result.
In some embodiments, the j-th candidate packet data is deleted in the case where the track data corresponding to the track identifier in the j-th candidate packet data does not intersect the query region.
As shown in FIG. 2, traj1 intersects the query Region, in which case the 1 st candidate partition data < ws10k0q, region, traj1> is taken as the query result.
In addition, as shown in FIG. 2, traj2 and the query Region do not intersect, in which case the 2 nd candidate partition data < ws10k0n, region, traj2> is ignored.
It should be noted here that, in determining whether a complete track intersects the query area, a large amount of computing resources are required. By the processing, whether the part of one track in the designated grid is intersected with the query area or not is calculated, so that the calculation load is effectively reduced.
In the track query method provided in the above embodiment of the present disclosure, the tracks are partitioned by a geographic grid. When a user inquires, query region partition data are generated according to the geographic grids corresponding to the query region, and track information in the query region is obtained through matching and association of the query region partition data and track partition data, so that real-time query can be performed on mass data.
Fig. 5 is a schematic structural diagram of a track inquiry apparatus according to an embodiment of the present disclosure. As shown in fig. 5, the track inquiry apparatus includes a first processing module 51, a second processing module 52, and a third processing module 53.
The first processing module 51 is configured to identify a plurality of geographic grids corresponding to the query area to generate a plurality of query area partition data, wherein the ith query area partition data includes a grid code of an ith geographic grid in the plurality of geographic grids, and 1.ltoreq.i.ltoreq.N, where N is a total number of geographic grids.
In some embodiments, the geographic grid is a geohash grid, the geographic grid corresponding to a geographic space having a length and width of approximately 150 meters by 150 meters.
For example, query region partition data is shown in table 1.
The second processing module 52 is configured to extract a preset plurality of track partition data, where each track partition data includes a track identifier and a grid code corresponding to the track identifier, and match the plurality of track partition data with the plurality of query region partition data to generate a plurality of candidate partition data.
For example, track partition data is shown in table 2.
In some embodiments, the second processing module 52 is configured to extract the trellis code in the i-th query region partition data as a target trellis code, and in the event that the trellis code in the M-th track partition data matches the target trellis code, associate the M-th track partition data with the i-th query region partition data to generate candidate partition data, 1.ltoreq.m.ltoreq.m, where M is the total number of track partition data.
In some embodiments, the second processing module 52 is configured to delete the ith query region partition data if the target trellis code is not included in each track partition data.
In some embodiments, the second processing module 52 is configured to delete the mth track partition data if the mth track partition data is not associated with any of the query region partition data.
The third processing module 53 is configured to obtain track data corresponding to a track identifier in the jth candidate packet data, where J is 1+.j+.j, where J is the total number of candidate packet data, and in a case where the track data corresponding to the track identifier in the jth candidate packet data intersects the query area, the track identifier and the trellis code in the jth candidate packet data are used as the query result.
In some embodiments, the third processing module 53 is configured to delete the jth candidate packet data if the trace data corresponding to the trace identification in the jth candidate packet data does not intersect the query region.
Fig. 6 is a schematic structural diagram of a track inquiry apparatus according to another embodiment of the present disclosure. Fig. 6 differs from fig. 5 in that in the embodiment shown in fig. 6 the trajectory query device further comprises a fourth processing module 54.
The fourth processing module 54 is configured to generate a plurality of track partition data, wherein the positioning information of each movable object in the preset time range is ordered in time sequence to obtain track information of each movable object, and the track information of each movable object is divided by using a preset geographic grid to obtain the plurality of track partition data.
Fig. 7 is a schematic structural diagram of a track inquiry apparatus according to another embodiment of the present disclosure. As shown in fig. 7, the track inquiry apparatus includes a memory 71 and a processor 72.
The memory 71 is for storing instructions and the processor 72 is coupled to the memory 71, the processor 72 being configured to perform a method as referred to in any of the embodiments of fig. 1, 3 based on the instructions stored by the memory.
As shown in fig. 7, the track inquiry apparatus further includes a communication interface 73 for information interaction with other devices. Meanwhile, the track inquiry device further comprises a bus 74, and the processor 72, the communication interface 73 and the memory 71 are in communication with each other through the bus 74.
The memory 71 may comprise a high-speed RAM memory or may further comprise a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 71 may also be a memory array. The memory 71 may also be partitioned and the blocks may be combined into virtual volumes according to certain rules.
Further, the processor 72 may be a central processing unit CPU, or may be an application specific integrated circuit ASIC, or one or more integrated circuits configured to implement embodiments of the present disclosure.
The present disclosure also relates to a computer readable storage medium having stored thereon computer instructions which, when executed by a processor, implement a method as referred to in any of the embodiments of fig. 1, 3.
In some embodiments, the present disclosure is implemented based on a distributed real-time computing framework, flink. A specific implementation framework is shown in fig. 8.
As shown in fig. 8, implemented GPS point data is accessed using a Kafka server and provided to a link server. And the Flink server generates corresponding track partition data according to the received GPS point data. Under the condition that a user sends a query request to the Flink client through the client, the Flink client sends corresponding query region information to the Flink server, the Flink server generates query region partition data according to the geographic grid corresponding to the query region, and track information in the query region is obtained through matching and association of the query region partition data and the track partition data, and a final result is fed back to the client.
In some embodiments, the functional unit blocks described above may be implemented as general-purpose processors, programmable logic controllers (Programmable Logic Controller, abbreviated as PLCs), digital signal processors (Digital Signal Processor, abbreviated as DSPs), application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASICs), field programmable gate arrays (Field-Programmable Gate Array, abbreviated as FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or any suitable combination thereof for performing the functions described in the present disclosure.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The description of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the disclosure in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the disclosure and the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.
Claims (16)
1. A track query method, comprising:
identifying a plurality of geographic grids corresponding to the query region to generate a plurality of query region partition data, wherein the ith query region partition data comprises grid codes of the ith geographic grid in the plurality of geographic grids, i is more than or equal to 1 and less than or equal to N, and N is the total number of geographic grids;
extracting a plurality of preset track partition data, wherein each track partition data comprises a track identifier and a grid code corresponding to the track identifier;
matching the plurality of query region partition data with the plurality of track partition data to generate a plurality of candidate partition data;
acquiring track data corresponding to track identifiers in the J candidate packet data, wherein J is more than or equal to 1 and less than or equal to J, and J is the total number of the candidate packet data;
and under the condition that track data corresponding to the track identification in the j candidate packet data is intersected with the query area, taking the track identification and the grid coding in the j candidate packet data as query results.
2. The method of claim 1, wherein said matching the plurality of query region partition data to the plurality of track partition data comprises:
extracting the grid codes in the i-th query region partition data to serve as target grid codes;
and under the condition that the grid code in the mth track partition data is matched with the target grid code, correlating the mth track partition data with the ith query area partition data to generate the candidate partition data, wherein M is more than or equal to 1 and less than or equal to M, and M is the total number of track partition data.
3. The method of claim 2, further comprising:
and deleting the ith query region partition data in the case that the target grid code is not included in each track partition data.
4. The method of claim 2, further comprising:
and deleting the mth track partition data under the condition that the mth track partition data is not associated with any query area partition data.
5. The method of claim 1, further comprising:
and deleting the j candidate packet data under the condition that the track data corresponding to the track identification in the j candidate packet data does not intersect with the query area.
6. The method of any of claims 1-5, further comprising:
generating the plurality of track partition data;
wherein the generating the plurality of track partition data comprises:
sorting the positioning information of each movable target in a preset time range according to time sequence to obtain track information of each movable target;
dividing the track information of each movable target by using a preset geographic grid to obtain the plurality of track partition data.
7. The method of claim 6, wherein
The geographical grid is a geohash grid.
8. A trajectory query device, comprising:
the first processing module is configured to identify a plurality of geographic grids corresponding to the query area to generate a plurality of query area partition data, wherein the ith query area partition data comprises grid codes of an ith geographic grid in the plurality of geographic grids, i is more than or equal to 1 and less than or equal to N, and N is the total number of the geographic grids;
the second processing module is configured to extract a plurality of preset track partition data, wherein each track partition data comprises a track identifier and a grid code corresponding to the track identifier, and match the plurality of track partition data with the plurality of query area partition data to generate a plurality of candidate partition data;
the third processing module is configured to acquire track data corresponding to track identifiers in the jth candidate packet data, wherein J is more than or equal to 1 and less than or equal to J, J is the total number of the candidate packet data, and the track identifiers and the grid codes in the jth candidate packet data are used as query results under the condition that the track data corresponding to the track identifiers in the jth candidate packet data are intersected with the query area.
9. The apparatus of claim 8, wherein,
the second processing module is configured to extract the grid code in the ith query region partition data as a target grid code, and associate the mth track partition data with the ith query region partition data to generate the candidate partition data when the grid code in the mth track partition data is matched with the target grid code, wherein M is equal to or greater than 1 and equal to or less than M, and M is the total number of track partition data.
10. The apparatus of claim 9, wherein,
the second processing module is configured to delete the i-th query region partition data without including the target trellis code in each track partition data.
11. The apparatus of claim 9, wherein,
the second processing module is configured to delete the mth track partition data if the mth track partition data is not associated with any of the query region partition data.
12. The apparatus of claim 8, wherein,
the third processing module is configured to delete the j-th candidate packet data in a case where the track data corresponding to the track identifier in the j-th candidate packet data does not intersect the query region.
13. The apparatus of any of claims 8-12, further comprising:
and the fourth processing module is configured to generate the plurality of track partition data, wherein the positioning information of each movable target in a preset time range is ordered according to time sequence to obtain track information of each movable target, and the track information of each movable target is divided by utilizing a preset geographic grid to obtain the plurality of track partition data.
14. The apparatus of claim 13, wherein
The geographical grid is a geohash grid.
15. A trajectory query device, comprising:
a memory configured to store instructions;
a processor coupled to the memory, the processor configured to perform the method of any of claims 1-7 based on instructions stored by the memory.
16. A computer readable storage medium storing computer instructions which, when executed by a processor, implement the method of any one of claims 1-7.
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| CN118113705A (en) * | 2024-04-29 | 2024-05-31 | 杭州海康威视数字技术股份有限公司 | Index information generation method, device and equipment |
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