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Time series shortest path query method based on neo4j database
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A query method and shortest path technology, applied in geographic information databases, other database retrieval, other database indexes, etc., can solve problems such as the problem of inability to calculate the shortest path of time series, and achieve high practical value and improve efficiency.
Active Publication Date: 2021-12-10
SUN YAT SEN UNIV
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[0011] The problem to be solved by the present invention is to overcome the defect that Neo4j cannot calculate the shortest path query problem of time series, expand the shortest path query function of Neo4j time series diagram, and embed it in the Neo4j database in the form of a plug-in
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Embodiment 1
[0060] The problem to be solved by the present invention is to overcome the defects of NEO4J unable to calculate the problem shortest circuit query problem, extend the shortest circuit query function of the NEO4J timing diagram, and in the form of the plugin to the NEO4J database.
[0061] Firstly, the relevant definition of the invention:
[0062] Definition 1 (timing diagram Temporal Graph): timing chart G = (V, E), where V is the set of vertices of G, E is the set of edges of G, e∈E group consisting of consisting of a quaternary, e = d , T a >, Where u, v∈V, u represents the trailing edge of the directed arcs, v represents the head has an arc edge, T d Departure time from u to v's, T a Is the arrival time from u to v. When applied to a timing chart G public transport network, represented by a five-tuple edge, i.e. e = d , T a , B>, b represents the vehicle at time T d From the site u, at time T a Reaching the site v.
[0063] For example, figure 1 Is a six vertices v1, v2, v3, ...
Embodiment 2
[0131] like figure 1 As shown, this is a timing chart, which can represent a traffic network. The vertices are connected between the vertices, with timing information, representing the departure time and arrival time, and the corresponding vehicle information.
example 1
[0133] Query EAP (V1, V6, 8). The present invention invokes the EAP-Temporal-Dijkstra algorithm for solving. Add a V1 to S, first of all, V1 satisfies the arrival of TD> = 8. The second iterations, select the maximum vertex V2 that is the smallest to the time t in EAT. Add V2 to S, for V2 satisfying the edges of TD> = 10, E2, E6, then update Eat, Pre, prereel table using E2, E6 timing information. The third iteration, selecting the minimum point in EAT is not in the point V6. Since V6 is the target end point, the search ends at this time. The results of EAP (V1, V6, 8) are by querying EAT, PRE, PREEREL. Figure 4 Applying for the EAP-TEMPORAL-DIJKSTRA algorithm of the present invention in figure 1 Search process. The specific iterative process is like Figure 5 Indicated.
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Abstract
The invention relates to a time series shortest path query method based on a Neo4j database, which proposes a time series shortest path query function extension and plug-in form embedding method of the Neo4j database. The invention solves the shortcoming that the built-in shortest path algorithm of the Neo4j database cannot process time series information. The Temporal-Dijkstra algorithm for three kinds of temporal shortest path queries is proposed, which solves the implementation problem of temporal shortest path on Neo4j, and specifically modifies the initialization and termination conditions of the traditional shortest path algorithm to improve efficiency, and is a function of Neo4j The extended implementation is deployed in the Neo4j database, and the corresponding query requirements are processed through specific procedure call statements. It is proved by experiments that the invention can be called correctly in the actual database and has high practical value.
Description
Technical field [0001] The present invention relates to the field of path planning, and more particularly to a timing shortest path query method based on a NEO4J database. Background technique [0002] NEO4J is a high-performance NOSQL (non-relational database) graphical database. In the NEO4J, the data is stored in the network rather than the table, and the data is saved as the relationship between the vertices and the vertices in the figure. For some application data, such as traffic road network data, social network data, etc., can directly represent the concept of the vertices and relationships of the diagram. Use NEO4J to store these data very natural and use efficiency is higher than the relational database. Many of the companies such as Facebook, Alibaba, Baidu are using Neo4J. [0003] The NEO4J's data storage model is Node (vertex) and the relationship, and the included Property. Property Saves with the two-way list of the Key -Value (value). The Node vertex saves the fi...
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