CN116010677B - Spatial index method and device and electronic equipment thereof - Google Patents
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Abstract
The application provides a spatial index method, a spatial index device and electronic equipment thereof, and relates to the technical field of information such as geographic information retrieval. The method comprises the following steps: acquiring a data request message, and acquiring a data request type according to the identification of the data request message; responding to a request type as a data query request, using a geographic position in a data request message as a spatial index, and searching layer by layer according to the hierarchical relation of each data node to obtain target service data of an interest point where the geographic position is located; and responding to the request type as a data updating request, transmitting the data updating request to the data node of the last layer, and updating the target service data in the data node according to the data updating request. The method and the device can support the rapid establishment, real-time updating and higher-level QPS inquiry of the data space index of the massive interest points, and remarkably improve the performance and throughput of the space index and support the high-real-time updating and high-performance retrieval of the massive entities through a distributed architecture and a redundant storage mode.
Description
Technical Field
The present disclosure relates to the field of information technologies such as geographic information retrieval, and in particular, to a spatial indexing method and apparatus, and an electronic device thereof.
Background
With the rapid development of the energy industry and the acceleration of the digital transformation footstep of the energy industry, the mass physical geographic position information of energy assets and carriers in the fields of wind power, thermal power, hydropower, photovoltaic power generation, distributed energy, energy storage, electricity selling, intelligent energy, coal and the like need to face increasing updating and searching demands.
In the related technology, the display of the spatial data is often built on a specific spatial data type, and the real-time updating and inquiring of the massive geographic positions cannot be realized. Therefore, how to improve the efficiency of real-time updating and querying of massive geographic locations and improve the query rate per second (QPS) of updating and querying have become one of important research directions.
Disclosure of Invention
The present application aims to solve, at least to some extent, one of the technical problems in the related art. To this end, an object of the present application is to propose a spatial indexing method.
A second object of the present application is to propose a spatial indexing device.
A third object of the present application is to propose an electronic device.
A fourth object of the present application is to propose a non-transitory computer readable storage medium.
A fifth object of the present application is to propose a computer programme product.
To achieve the above object, an embodiment of a first aspect of the present application provides a spatial indexing method, including:
acquiring a data request message, and acquiring a data request type according to the identification of the data request message;
responding to a request type as a data query request, using a geographic position in a data request message as a spatial index, and searching layer by layer according to the hierarchical relation of each data node to obtain target service data of an interest point where the geographic position is located;
and responding to the request type as a data updating request, transmitting the data updating request to the data node of the last layer, and updating the target service data in the data node according to the data updating request.
The embodiment of the application can support the rapid establishment, real-time updating and higher-level QPS inquiry of the data space index of the massive interest points, remarkably improves the performance and throughput of the space index in a distributed architecture and redundant storage mode, can be applied to various fields of new energy, and supports the high-real-time updating and high-performance retrieval of massive entities.
To achieve the above object, an embodiment of a second aspect of the present application provides a spatial index apparatus, including:
the receiving module is used for acquiring the data request message and acquiring the data request type according to the identification of the request message;
the query module is used for responding to a request type as a data query request, taking the geographic position in the data request message as a spatial index, and searching layer by layer according to the hierarchical relation of each data node to obtain target service data of the interest point where the geographic position is located;
and the updating module is used for responding to the request type as a data updating request, transmitting the data updating request to the last layer of data node, and updating the target business data in the data node according to the data updating request.
To achieve the above object, an embodiment of a third aspect of the present application provides an electronic device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the spatial indexing method provided in the embodiments of the first aspect of the present application.
To achieve the above object, an embodiment of a fourth aspect of the present application proposes a computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the spatial index method provided in the embodiment of the first aspect of the present application.
To achieve the above object, an embodiment of a fifth aspect of the present application proposes a computer program product comprising a computer program which, when executed by a processor, implements the spatial index method provided in the embodiment of the first aspect of the present application.
Drawings
FIG. 1 is a flow chart of a spatial indexing method of one embodiment of the present application;
FIG. 2 is a schematic diagram of a spatial indexing method of one embodiment of the present application;
FIG. 3 is a flow chart of a spatial indexing method of one embodiment of the present application;
FIG. 4 is a schematic diagram of a spatial indexing method of one embodiment of the present application;
FIG. 5 is a schematic diagram of a spatial indexing method of one embodiment of the present application;
FIG. 6 is a block diagram of a spatial index apparatus according to one embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
The spatial index method, the spatial index device and the electronic equipment of the embodiment of the application are described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a spatial indexing method according to one embodiment of the present application, as shown in FIG. 1, comprising the steps of:
s101, acquiring a data request message, and acquiring a data request type according to the identification of the data request message.
In the embodiment of the present application, the method may be performed by a terminal device, a server, or the like, such as a computer, a mobile phone, which is not limited in this application.
In some implementations, the data request message may be received through a different interface, and the interface is further identified, and the data request messages with different request types may be distinguished, alternatively, the request types of the data request message may include a data query request and a data update request, and in this embodiment of the present application, the data update request may include a data deletion request, a data modification request, a data addition request, and so on.
S102, responding to a request type as a data query request, using a geographic position in a data request message as a spatial index, and searching layer by layer according to the hierarchical relation of each data node to obtain target service data of the interest point where the geographic position is located.
In the embodiment of the present application, in order to improve the efficiency of updating and querying massive geographic locations in real time, the data nodes may be divided into different levels, as shown in fig. 2, in the embodiment of the present application, the data nodes include adjacent neighbor nodes, remote dictionary service redis nodes, where the neighbor nodes are the nodes of the upper layer of redis nodes, and there is a first mapping relationship between the neighbor nodes and the redis nodes.
The remote dictionary service (Remote Dictionary Server, redis) is a memory-based implemented key-value-wise non-relational (NoSQL) database. Optionally, the redis node provides the most basic spatial index for storing points of interest. It should be noted that, all interest points are not stored under one ordered list (zset) under one redis node, but stored in 1048576 (20 th power of 2) zset of a redis cluster formed by a plurality of redis nodes (corresponding to a "barrel block", if there is no data in the barrel block, there is no need to store empty zset), so that the system capacity can be greatly improved.
In some implementations, the geographic location in the data request message is used as a spatial index, and target service data of the interest point where the geographic location is located is obtained for the nearest node and the redis node respectively.
S103, responding to the request type as a data updating request, transmitting the data updating request to the data node of the last layer, and updating the target service data in the data node according to the data updating request.
In this embodiment of the present application, the node cluster of the gateway may be written in any programming language (Java or c++, etc.) capable of providing redis access capability, and for the upstream data update request, the target service data in the redis node cluster is modified directly and transparently.
In the embodiment of the application, a data request message is acquired, and a data request type is acquired according to the identification of the data request message; responding to a request type as a data query request, using a geographic position in a data request message as a spatial index, and searching layer by layer according to the hierarchical relation of each data node to obtain target service data of an interest point where the geographic position is located; and responding to the request type as a data updating request, transmitting the data updating request to the data node of the last layer, and updating the target service data in the data node according to the data updating request. The embodiment of the application can support the rapid establishment, real-time updating and higher-level QPS inquiry of the data space index of the massive interest points, remarkably improves the performance and throughput of the space index in a distributed architecture and redundant storage mode, can be applied to various fields of new energy, and supports the high-real-time updating and high-performance retrieval of massive entities.
FIG. 3 is a flow chart of a spatial indexing method of one embodiment of the present application, as shown in FIG. 3, comprising the steps of:
s301, receiving a data request message sent by an upper computer, and acquiring a data request type according to the identification of the request message.
For the description of step S301, please refer to the description of the above embodiment, and the description is omitted here.
S302, determining a target nearest node, a target redis node and a target ordered list according to the geographic position in the data request message in response to the request type as a data query request.
In this embodiment of the present application, address encoding may be performed on a geographic location based on an address encoding GeoHash algorithm, to obtain a spatial index value (GeoHash value), where GeoHash is essentially a manner of spatial indexing, and the basic principle is to understand the earth as a two-dimensional plane, recursively decompose the plane into smaller sub-blocks, where each sub-block has the same encoding within a certain latitude and longitude range. And a space index is established in a GeoHash mode, so that longitude and latitude retrieval of the space interest point poi data can be realized.
In some implementations, a target ordered list corresponding to the geographic location is obtained from a second mapping relationship of the spatial index value and the ordered list. And acquiring a target redis node where the target ordered list is located according to the association relation between the ordered list and the redis node. And acquiring a target nearest node corresponding to the target redis node according to the first mapping relation. Any ordered list is redundantly cached in adjacent multiple redis nodes, respectively.
As described above, taking GeoHash20 as an example, the entire cluster stores 1048576 (20 th power of 2) GeoHash bucket blocks (i.e. ordered list zset), and the GeoHash20 value key of the interest point is a 20-bit GeoHash value, which approximately corresponds to a geographical block of 40km by 20 km. And a spatial index is established on zset in a redundancy mode, as shown in fig. 4, any ordered list is respectively and redundantly cached in a plurality of adjacent redis nodes, and each point respectively stores 4 data. Each interest point is stored in four redundant parts, namely the interest points are respectively redundant in three adjacent barrel blocks according to the positions of geographic position coordinates in the barrel blocks. For example, the point of interest 401 in the upper right part of the binning block W4G0 may be redundantly stored in the binning blocks W4G1, W4G2, W4G 3.
That is, any point of interest has coordinates that are stored in the corresponding GeoHash bucket. The storage form uses ordered list zset storage in Redis. The GeoHash values calculated at any point in the same GeoHash block are the same, the GeoHash values calculated at points in different GeoHash blocks are different, and each interest point has a minimum granularity GeoHash value of the corresponding target service data, and the accuracy of the GeoHash value reaches the millimeter level.
And S303, searching the cache data in the target gateway node to acquire target service data.
For the upstream query request, in order to improve the performance of the target layer, the zset query is not directly initiated to the downstream redis cluster, but the cache is directly queried, and the target service data is obtained.
In the embodiment of the present application, in order to ensure a caching effect, to prevent all servers from having to cache all hotspots, hash load balancing needs to be performed. However, hash load balancing cannot solve the node hot spot problem, so we introduce a cache redundancy mechanism in an effort to trade-off between load balancing and cache data volume. As shown in fig. 5, a GeoHash value is obtained according to a requested geographic location (longitude and latitude coordinates), a requested barrel block is determined, and then a module is taken according to the requested barrel block, so as to prevent uneven load among the nearest service nodes, each barrel block is respectively redundant in a plurality of adjacent nearest nodes.
Optionally, any node can query the target service data contained in one or more redis nodes corresponding to the node in a full amount every preset time. That is, the search cluster and the Redis cluster only ensure the final consistency of the data, for example, in the embodiment of the present application, each search node may query the full amount of target service data in the Redis node in a full amount every 5 seconds by hovering update.
S304, in response to the fact that the target business data does not exist in the target node cache data, searching the target ordered list in the target redis node is continued, and therefore the target business data are obtained.
In the embodiment of the present application, only when the data in the search cache does not exist, the access to the downstream redis node cluster is initiated in real time (in this case, only no interest point is found before a certain GeoHash block, and no traffic is queried, so that the target service data of the interest point is not searched in the search cache data, and then the cache penetration occurs). Searching each interest point in the target ordered list, and taking the service data of the interest point as target service data if the geographic position of the interest point is consistent with the geographic position in the request.
S305, determining an ordered list to be updated, data to be updated and an updating operation according to the data updating request in response to the request type as a data updating request, wherein the updating operation comprises a modifying operation, a new adding operation and a deleting operation.
Analyzing the data updating request to obtain a geographic position, data to be updated and updating operation, and determining an ordered list to be updated according to the geographic position, namely longitude and latitude coordinates, so as to conveniently update the service data of interest points of corresponding coordinates in the ordered list to be updated subsequently, wherein the updating operation comprises modification operation, addition operation and deletion operation.
S306, executing updating operation on the ordered list to be updated according to the data to be updated.
The embodiment of the application can support the rapid establishment, real-time updating and higher-level QPS inquiry of the data space index of the massive interest points, remarkably improves the performance and throughput of the space index in a distributed architecture and redundant storage mode, can be applied to various fields of new energy, and supports the high-real-time updating and high-performance retrieval of massive entities.
As shown in fig. 6, based on the same application concept, the embodiment of the present application further provides a spatial index apparatus 600, including:
a receiving module 610, configured to obtain a data request message, and obtain a data request type according to an identifier of the request message;
the query module 620 is configured to perform a layer-by-layer search according to a hierarchical relationship of each data node by using the geographic location in the data request message as a spatial index in response to the request type as a data query request, and obtain target service data of the point of interest where the geographic location is located;
and the updating module 630 is configured to respond to the request type as a data updating request, transmit the data updating request to the last layer of data node, and update the target service data in the data node according to the data updating request.
In some implementations, the data node includes a neighbor node, the remote dictionary serving a redis node, the neighbor node being a higher level node of the redis node, the neighbor node having a first many-to-many mapping relationship with the redis node.
In some implementations, the query module 620 is further to:
determining a target nearest node, a target redis node and a target ordered list according to the geographic position in the data request message;
searching the cache data in the target gateway node to obtain target service data;
and responding to the fact that the target business data does not exist in the cache data of the target nearest node, and continuing to search the target ordered list in the target redis node so as to acquire the target business data.
In some implementations, any redis node is associated with multiple ordered lists, query module 620 is further configured to:
address coding is carried out according to the geographic position, a spatial index value is obtained, and a target ordered list corresponding to the geographic position is obtained according to a second mapping relation between the spatial index value and the ordered list;
acquiring a target redis node where the target ordered list is located according to the association relation between the ordered list and the redis node;
acquiring a target nearest node corresponding to the target redis node according to the first mapping relation;
in some implementations, any ordered list is redundantly cached in adjacent multiple redis nodes, respectively.
In some implementations, the update module 630 is further to:
determining an ordered list to be updated, data to be updated and updating operations according to a data updating request, wherein the updating operations comprise modification operations, new addition operations and deletion operations;
and executing updating operation on the ordered list to be updated according to the data to be updated.
The embodiment of the application can support the rapid establishment, real-time updating and higher-level QPS inquiry of the data space index of the massive interest points, remarkably improves the performance and throughput of the space index in a distributed architecture and redundant storage mode, can be applied to various fields of new energy, and supports the high-real-time updating and high-performance retrieval of massive entities.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 7, the electronic device 700 includes a memory 710, a processor 720 and a computer program product stored on the memory 710 and executable on the processor 720, which when executed implements the spatial indexing method described above.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Based on the same application concept, the embodiments of the present application also provide a computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the spatial index method in the above embodiments.
Based on the same application concept, the embodiments of the present application also provide a computer program product comprising a computer program which, when executed by a processor, performs the spatial indexing method of the above embodiments.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (6)
1. A method of spatial indexing, comprising:
acquiring a data request message, and acquiring a data request type according to the identification of the data request message;
responding to the request type as a data query request, carrying out layer-by-layer searching by taking the geographic position in the data request message as a spatial index according to the hierarchical relation of each data node, and obtaining target service data of the interest point where the geographic position is located, wherein the data node comprises a neighboring node and a remote dictionary service redis node, the neighboring node is the node of the last layer of the redis node, a first mapping relation of many to many is arranged between the neighboring node and the redis node, any redis node is associated with a plurality of ordered lists, and carrying out layer-by-layer searching by taking the geographic position in the data request message as the spatial index according to the hierarchical relation of each data node, and obtaining the target service data of the interest point where the geographic position is located comprises: address coding is carried out according to the geographic position in the data request message, a spatial index value is obtained, a target ordered list corresponding to the geographic position is obtained according to a second mapping relation between the spatial index value and the ordered list, a target redis node where the target ordered list is located is obtained according to an association relation between the ordered list and the redis node, a target nearest node corresponding to the target redis node is obtained according to the first mapping relation, cache data in the target nearest node are searched to obtain the target service data, and searching is carried out on the target ordered list in the target redis node in response to the fact that the target service data does not exist in the cache data of the target nearest node, so that the target service data is obtained;
responding to the request type as a data updating request, transmitting the data updating request to a data node of the last layer, and updating target business data in the data node according to the data updating request.
2. The method of claim 1, wherein any ordered list is redundantly cached in adjacent multiple redis nodes, respectively.
3. The method of claim 1, wherein the updating the target traffic data in the data node according to the data update request comprises:
determining an ordered list to be updated, data to be updated and updating operation according to the data updating request, wherein the updating operation comprises modification operation, addition operation and deletion operation;
and executing updating operation on the ordered list to be updated according to the data to be updated.
4. A spatial index apparatus, comprising:
the receiving module is used for acquiring the data request message and acquiring the data request type according to the identification of the request message;
the query module is used for responding to the request type as a data query request, carrying out layer-by-layer searching by taking the geographic position in the data request message as a spatial index according to the hierarchical relation of each data node to obtain target service data of the interest point where the geographic position is located, wherein the data node comprises a neighboring node and a remote dictionary service redis node, the neighboring node is the node of the last layer of the redis node, a first mapping relation of many pairs is arranged between the neighboring node and the redis node, any redis node is associated with a plurality of ordered lists, and carrying out layer-by-layer searching by taking the geographic position in the data request message as the spatial index according to the hierarchical relation of each data node to obtain the target service data of the interest point where the geographic position is located, and the target service data comprises: address coding is carried out according to the geographic position in the data request message, a spatial index value is obtained, a target ordered list corresponding to the geographic position is obtained according to a second mapping relation between the spatial index value and the ordered list, a target redis node where the target ordered list is located is obtained according to an association relation between the ordered list and the redis node, a target nearest node corresponding to the target redis node is obtained according to the first mapping relation, cache data in the target nearest node are searched to obtain the target service data, and searching is carried out on the target ordered list in the target redis node in response to the fact that the target service data does not exist in the cache data of the target nearest node, so that the target service data is obtained;
and the updating module is used for responding to the request type as a data updating request, transmitting the data updating request to the last layer of data node, and updating the target business data in the data node according to the data updating request.
5. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-3.
6. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-3.
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