Graph data searching method and device

Abstract

The embodiment of the invention provides a graph data searching method and device. The method comprises the following steps that inquiry requests are obtained, wherein the inquiry requests include inquiry conditions carrying starting graph nodes, and the inquiry requests are used for inquiring first graph nodes to be inquired matched with the inquiry conditions in an inquiry graph data set; the association relationship including the second graph nodes to be inquired and the second graph nodes to be inquired not meeting the inquiry conditions in the graph data set are filtered according to the inquiry condition and the preset available resource condition, so that a stipulation sub graph is obtained; the stipulation sub graph includes initial graph nodes, the first graph nodes to be inquired matched with the inquiry condition and the association relationship between the initial graph nodes and the first graph nodes to be inquired; the stipulation sub graph is inquired through the inquiry conditions to obtain the first graph nodes to be inquired. The method provided by the invention has the advantages that the graph data searching efficiency is improved, and in addition, memory resources and time resource of a computer are saved.

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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