{"title":"在面向列的DBMS中存储和索引RDF数据","authors":"Xin Wang, Shuyi Wang, Pufeng Du, Zhiyong Feng","doi":"10.1109/DBTA.2010.5659025","DOIUrl":null,"url":null,"abstract":"Effcient RDF data management is an essential factor in realizing the Semantic Web vision. However, most existing RDF storage schemes based on row-store relational databases are constrained in terms of efficiency and scalability. In this paper, we propose an RDF storage scheme that implements sextuple indexing for RDF triples using a column-oriented DBMS. To evaluate the performance of our approach, large-scale datasets upto 13 million triples are generated and benchmark queries that cover important RDF join patterns are devised. The experimental results show that our approach outperforms the row-oriented DBMS approach by upto an order of magnitude and is even competitive to the best state-of-the-art native RDF store.","PeriodicalId":320509,"journal":{"name":"2010 2nd International Workshop on Database Technology and Applications","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Storing and Indexing RDF Data in a Column-Oriented DBMS\",\"authors\":\"Xin Wang, Shuyi Wang, Pufeng Du, Zhiyong Feng\",\"doi\":\"10.1109/DBTA.2010.5659025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Effcient RDF data management is an essential factor in realizing the Semantic Web vision. However, most existing RDF storage schemes based on row-store relational databases are constrained in terms of efficiency and scalability. In this paper, we propose an RDF storage scheme that implements sextuple indexing for RDF triples using a column-oriented DBMS. To evaluate the performance of our approach, large-scale datasets upto 13 million triples are generated and benchmark queries that cover important RDF join patterns are devised. The experimental results show that our approach outperforms the row-oriented DBMS approach by upto an order of magnitude and is even competitive to the best state-of-the-art native RDF store.\",\"PeriodicalId\":320509,\"journal\":{\"name\":\"2010 2nd International Workshop on Database Technology and Applications\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Workshop on Database Technology and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DBTA.2010.5659025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Workshop on Database Technology and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DBTA.2010.5659025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Storing and Indexing RDF Data in a Column-Oriented DBMS
Effcient RDF data management is an essential factor in realizing the Semantic Web vision. However, most existing RDF storage schemes based on row-store relational databases are constrained in terms of efficiency and scalability. In this paper, we propose an RDF storage scheme that implements sextuple indexing for RDF triples using a column-oriented DBMS. To evaluate the performance of our approach, large-scale datasets upto 13 million triples are generated and benchmark queries that cover important RDF join patterns are devised. The experimental results show that our approach outperforms the row-oriented DBMS approach by upto an order of magnitude and is even competitive to the best state-of-the-art native RDF store.
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