An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Database Systems Concepts
Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
An efficient SQL-based RDF querying scheme
VLDB '05 Proceedings of the 31st international conference on Very large data bases
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
Column-store support for RDF data management: not all swans are white
Proceedings of the VLDB Endowment
The Expressive Power of SPARQL
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
SW-Store: a vertically partitioned DBMS for Semantic Web data management
The VLDB Journal — The International Journal on Very Large Data Bases
Scalable join processing on very large RDF graphs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Foundations of SPARQL query optimization
Proceedings of the 13th International Conference on Database Theory
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The recent prevalence of Linked Data attracts research interest towards the efficiency of query execution over the web of data. Search and query engines crawl and index triples into a centralized repository and queries are executed locally. It has been shown in various literatures that the performance bottleneck of large scale query execution lies in joins and unions. Based on the observation that a large part of join operations result in a much smaller binding set which can be precomputed and stored, we propose to augment RDF indexes to store the bindings of complex patterns and exploit these patterns to enhance performance. In addition to the index, we also introduce two strategies of selecting these patterns: one depends on developed heuristic rules and the other employs query history to optimize time-space ratio. Our empirical study demonstrates the proposed pattern index outperforms traditional triple index by up to three orders of magnitude while keeping the overhead low.