Vertical partitioning algorithms for database design
ACM Transactions on Database Systems (TODS)
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The VLDB Journal — The International Journal on Very Large Data Bases
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VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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Proceedings of the VLDB Endowment
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Proceedings of the VLDB Endowment
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The VLDB Journal — The International Journal on Very Large Data Bases
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ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Relational processing of RDF queries: a survey
ACM SIGMOD Record
An experimental evaluation of relational RDF storage and querying techniques
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
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This paper presents a flexible and adaptable approach for achieving efficient and scalable management of RDF using relational databases. The main motivation behind our approach is that several benchmarking studies have shown that each RDF dataset requires a tailored table schema in order to achieve efficient performance during query processing. We present a two-phase approach for designing efficient tailored but flexible storage solution for RDF data based on its query workload, namely: 1) a workload-aware vertical partitioning phase. 2) an automated adjustment phase that reacts to the changes in the characteristics of the continuous stream of query workloads. We perform comprehensive experiments on two real-world RDF data sets to demonstrate that our approach is superior to the state-of-the-art techniques in this domain.