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  1. Proceedings of the 4th International Workshop on Semantic Web Information Management (SWIM '12)
  2. SPOVC: a scalable RDF store using horizontal partitioning and column oriented DBMS
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To nest or not to nest, when and how much: representing intermediate results of graph pattern queries in MapReduce based processing
Type inference methods and performance for data in an RDBMS
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Technical Report

SPOVC: a scalable RDF store using horizontal partitioning and column oriented DBMS

Content Provider ACM Digital Library
Author Mulay, Kunal Kumar, P. Sreenivasa
Abstract Organizing and indexing RDF data for efficient evaluation of SPARQL queries has been attracting a lot of attention in the recent past. Most of the techniques proposed in this context leverage the existing RDBMS or column oriented DB technologies. In this paper, we propose an organization SPOVC that uses five indexes, namely, Subject, Predicate, Object, Value and Class, on top of any column oriented DB. The main techniques used by the proposed scheme are horizontal partitioning of the logical indices and special indices for values and classes. The SPOVC approach has the advantage of delivering better performance if the underlying column store technology improves. The proposed approach is conceptually much simpler than the state-of-the-art native-storage based proposals and roughly gives the same performance. Our proposal extends an existing approach, SW-Store, that uses column oriented DBs and vertical partitioning and obtains a two/three fold performance improvement. In addition, the proposed system is the only system that can effectively tackle SPARQL queries with filter patterns having range conditions and regular expressions.
Starting Page 1
Ending Page 8
Page Count 8
File Format PDF
ISBN 9781450314466
DOI 10.1145/2237867.2237875
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-05-20
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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