Continuous multi-way joins over distributed hash tables
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
End-to-end support for joins in large-scale publish/subscribe systems
Proceedings of the VLDB Endowment
Publish/subscribe with RDF data over large structured overlay networks
DBISP2P'05/06 Proceedings of the 2005/2006 international conference on Databases, information systems, and peer-to-peer computing
Continuous RDF query processing over DHTs
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Performance improvement of join queries through algebraic signatures
International Journal of Intelligent Information and Database Systems
Evaluating conjunctive triple pattern queries over large structured overlay networks
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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We study the problem of continuous relational query processing in Internet-scale overlay networks realized by distributed hash tables. We concentrate on the case of continuous two-way equi-join queries. Joins are hard to evaluate in a distributed continuous query environment because data from more than one relations is needed, and this data is inserted in the network asynchronously. Each time a new tuple is inserted, the network nodes have to cooperate to check if this tuple can contribute to the satisfaction of a query when combined with previously inserted tuples. We propose a series of algorithms that initially index queries at network nodes using hashing. Then, they exploit the values of join attributes in incoming tuples to rewrite the given queries into simpler ones, and reindex them in the network where they might be satisfied by existing or future tuples. We present a detailed experimental evaluation in a simulated environment and we show that our algorithms are scalable, balance the storage and query processing load and keep the network traffic low.