Method for improving exploration performance of Janus Graph path

Abstract

The invention discloses a method for improving exploration performance of a Janus Graph path, and belongs to the technical field of graph calculation of an application data mining technology. A bidirectional breadth-first traversal algorithm is used, the process of gradual transition from an original node to a target node is changed into the process of simultaneous traversal from two nodes, the total number of vertexes needing to be traversed is reduced, and the number of iterations is reduced. Consumption of storage memory resources can be reduced. M eanwhile, the response time is shortened,the requirements for large data volume, real-time calculation and low response time are met, and the method has good application and popularization value.

Description

technical field [0001] The invention relates to the technical field of graph calculation using data mining technology, and specifically provides a method for improving the performance of Janusgraph path exploration. Background technique [0002] Graph (Graph) is a mathematical logic object representing the relationship between entities. It is expressed in mathematics as a G=(V,E) binary group, which itself consists of N vertices (V=vertex) and M Each edge (E=edge), each vertex corresponds to multiple edges (<=M), each edge is connected to two vertices, and the edge can have a direction. If the edge contained in the graph has a direction, it is called A directed graph (oriented graph), and vice versa for an undirected graph (undirected graph). Graph Theory (Graph Theory) is a branch of mathematics with graphs as its basic research object, and the algorithm that uses graph theory to solve graphs is called graph algorithm (Graph Algorithm). [0003] In today's Internet inf...

AI Technical Summary

Problems solved by technology

[0007] (1) Poor performance and long response time: Depth-first traversal adopts an idea similar to exploring and building a maze, and needs to traverse every possible vertex of the graph. It is not suitable for real-time computing scenarios, but more suitable for offline computing;

[0008] (2) High resource consumption: when the algorithm is executed, it is necessary to record all traversed vertex information into the memory to meet the needs of the algorithm. When the amount of data calculation is relatively intensive, the memory consumption will gradually increase, which will affect the calculation. Resource requirements are also high

[0009] These problems make it difficult for Janusgraph's path exploration function to respond to external path exploration requests quickly and with low latency in the face of large amounts of data and real-time (real) requirements, and the memory consumption during the query process is very high

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