Graph data search method and device

Abstract

Embodiments of the present invention provide a graph data search method and device, the method comprising: obtaining a query request; wherein, the query request includes a query condition carrying a starting graph node, and the query request is used in the query graph data set The first graph node to be searched that matches the query condition; the second graph node to be searched that does not meet the query condition in the graph data set is filtered according to the query condition and preset available resource conditions and includes the The association relationship of the second graph node to be searched to obtain a statute subgraph; the statute subgraph includes the initial graph node, the first graph node to be searched matching the query condition, and the initial graph node and The association relationship between the nodes of the first graph to be searched; querying the statute subgraph through the query condition to obtain the nodes of the first graph to be searched. The method provided by the invention improves the efficiency of searching graph data, and saves storage resources and time resources of a computer.

Description

technical field [0001] The embodiments of the present invention relate to computer technology, and in particular to a method and device for searching graph data. Background technique [0002] With the continuous development of computer technology, the amount of data processed by computers is gradually increasing, and the current era of big data is also an era of prosperity and development of graph data, where graph data is data that is related to each other. Based on this, computers often need to analyze a large amount of big data, and obtain accurate search results through the consumption of a large amount of time resources and computer storage resources. [0003] In order to avoid the resource consumption caused by the traditional search mechanism, a data sampling query (BlinkDB) technology is proposed in the prior art, which uses a specific sampling algorithm to continuously sample the original graph data, establishes graph data samples and maintains them, and then Get t...

AI Technical Summary

Problems solved by technology

[0003] In order to avoid the resource consumption caused by the traditional search mechanism, a data sampling query (BlinkDB) technology is proposed in the prior art, which uses a specific sampling algorithm to continuously sample the original graph data, establishes graph data samples and maintains them, and then Get the corresponding search results

[0004] However, the prior art data sampling query (BlinkDB) technology needs to use additional storage overhead to maintain graph data samples, which largely wastes computer storage resources

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