摘要
gStore is an open-source native Resource Description Framework （RDF） triple store that answers SPARQL queries by subgraph matching over RDF graphs. However, there are some deficiencies in the original system design, such as answering simple queries （including one-triple pattern queries）. To improve the efficiency of the system, we reconsider the system design in this paper. Specifically, we propose a new query plan generation module that generates different query plans according to the structures of query graphs. Furthermore, we re-design our vertex encoding strategy to achieve more pruning power and a new multi-join algorithm to speed up the subgraph matching process. Extensive experiments on synthetic and real RDF datasets show that our method outperforms the state-of-the-art algorithms significantly.
gStore is an open-source native Resource Description Framework （RDF） triple store that answers SPARQL queries by subgraph matching over RDF graphs. However, there are some deficiencies in the original system design, such as answering simple queries （including one-triple pattern queries）. To improve the efficiency of the system, we reconsider the system design in this paper. Specifically, we propose a new query plan generation module that generates different query plans according to the structures of query graphs. Furthermore, we re-design our vertex encoding strategy to achieve more pruning power and a new multi-join algorithm to speed up the subgraph matching process. Extensive experiments on synthetic and real RDF datasets show that our method outperforms the state-of-the-art algorithms significantly.
