Relational query method implemented on large-scale data set

Abstract

The invention discloses a relational query method implemented on a large-scale data set and belongs to the field of semantic webs. The method comprises the following steps: 1) calculating connective subgraphs (only containing a same type of tags) in a semantic data directed graph G; 2) merging the connective subgraphs, and dividing the directed graph G into a plurality of subgraphs; 3) calculating a strongest connective subgraph C in each subgraph subjected to merging, and calculating a bipartite graph of the strongest connective subgraph C; 4) storing the shortest path of all the subgraphs Cinto a path set RS; 5) recording the tags (containing two points of a non-redundant tag path) in each divided subgraph so as to obtain a tag set of each subgraph; and 6) judging whether paths conforming to the query conditions exist in the directed graph G by using the tag set, if so, returning path query results, otherwise, carrying out traversal among the subgraphs, determining subgraphs which can reach a target node according to the path set RS, and then, returning the path query results by using the tag set of the subgraph. The method disclosed by the invention is used for supporting the relational query of mass data, and is strong in expandability.

Description

technical field [0001] The invention belongs to the field of database technology and the field of semantic web, and relates to a tag-restricted relational query method on a large-scale data set. Background technique [0002] Semantic data is a kind of data that represents the attribute information of entities and the semantic relationship between entities. It is generally expressed in the form of a set of triples. The format of triples is <subject, predicate, object>. For example: <Beijing University of Aeronautics and Astronautics, President, Huai Jinpeng>, <Huai Jinpeng, graduated from, Jilin University>, ..., <Jilin University, President, Zhan Tao>. [0003] A very important use of semantic data is semantic inference. Taking the triplet above as an example, we can infer a relationship between Beijing University of Aeronautics and Astronautics and Zhantao. In traditional relational query methods, 2-hop is often used Such methods index paths, but as...

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Problems solved by technology

[0003] A very important use of semantic data is semantic inference. Taking the triplet above as an example, we can infer a relationship between Beijing University of Aeronautics and Astronautics and Zhantao. In traditional relational query methods, 2-hop is often used Such methods index paths, but as the scale of the graph continues to grow, the index calculation amount of this type of method also increases sharply, and the corresponding calculation time also increases sharply. It can be seen that the traditional relational query method can no longer meet the growing requirements. Growing Entity Relationship Query Requirements

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