A qualitative comparison study of data structures for large line segment databases
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
On the analysis of indexing schemes
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimizing Queries with Materialized Views
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
An efficient SQL-based RDF querying scheme
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
RDF-3X: a RISC-style engine for RDF
Proceedings of the VLDB Endowment
Hexastore: sextuple indexing for semantic web data management
Proceedings of the VLDB Endowment
SW-Store: a vertically partitioned DBMS for Semantic Web data management
The VLDB Journal — The International Journal on Very Large Data Bases
Query Rewrites with Views for XML in DB2
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Scalable join processing on very large RDF graphs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
The RDF-3X engine for scalable management of RDF data
The VLDB Journal — The International Journal on Very Large Data Bases
Evaluation of RDF queries via equivalence
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Performance and scalability are two issues that are becoming increasingly pressing as RDF data model is applied to real-world applications. Because neither vertical nor flat structures of RDF storage can handle frequent schema updates and meanwhile avoid possible long-chain joins, there is no clear winner between these two typical structures. In this paper, we propose an alternative storage schema called open user schema. The open user schema consists of flat tables automatically extracted from RDF query streams. A query is divided into two parts and conquered,respectively, on the flat tables in the open user schema and on the vertical table stored in a backend storage. At the core of this divide and conquer architecture with open user schema, an efficient isomorphism decision algorithm is given to guide a query to related flat tables in the open user schema. Our proposal in essence departs from existing methods in that it can accommodate schema updates without possible long-chain joins. We implement our approach and provide empirical evaluations to demonstrate both efficiency and effectiveness of our approach in evaluating complex RDF queries.