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TripleRush: a fast and scalable triple store


Stutz, P; Verman, Mihaela; Fischer, Lorenz; Bernstein, Abraham (2013). TripleRush: a fast and scalable triple store. In: 9th International Workshop on Scalable Semantic Web Knowledge Base Systems, Sydney, Australia, 21 October 2013 - 22 October 2013.

Abstract

TripleRush is a parallel in-memory triple store designed to address the need for efficient graph stores that answer queries over large-scale graph data fast. To that end it leverages a novel, graph-based architecture. Specifically, TripleRush is built on our parallel and distributed graph processing framework Signal/Collect. The index structure is represented as a graph where each index vertex corresponds to a triple pattern. Partially matched copies of a query are routed in parallel along different paths of this index structure. We show experimentally that TripleRush takes less than a third of the time to answer queries compared to the fastest of three state-of-the-art triple stores, when measuring time as the geometric mean of all queries for two benchmarks. On individual queries, TripleRush is up to three orders of magnitude faster than other triple stores.

Abstract

TripleRush is a parallel in-memory triple store designed to address the need for efficient graph stores that answer queries over large-scale graph data fast. To that end it leverages a novel, graph-based architecture. Specifically, TripleRush is built on our parallel and distributed graph processing framework Signal/Collect. The index structure is represented as a graph where each index vertex corresponds to a triple pattern. Partially matched copies of a query are routed in parallel along different paths of this index structure. We show experimentally that TripleRush takes less than a third of the time to answer queries compared to the fastest of three state-of-the-art triple stores, when measuring time as the geometric mean of all queries for two benchmarks. On individual queries, TripleRush is up to three orders of magnitude faster than other triple stores.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:22 October 2013
Deposited On:04 Sep 2013 15:27
Last Modified:16 Feb 2018 20:09
Publisher:CEUR Workshop Proceedings
OA Status:Green
Other Identification Number:merlin-id:8317

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