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DESCRIPTION:Click for Latest Location Information: http://semtechbizsf2012.semanticweb.com/sessionPop.cfm?confid=65&proposalid=4614\nRDF excels at data integration and SPARQL excels at expressing complex analytics on RDF data; however SPARQL performance is a concern, particularly if queries are re-run periodically to update analytics as RDF stores are updated from data streams.   As repository data increases, SPARQL analysis queries address ever larger data sets, and the effective analysis throughput will decrease.  It is clear that each subsequent wave of analysis re-computes substantial amounts of information computed in prior query waves.  SPARQL analytics performance can be dramatically improved if query processing could automatically re-use prior results.  While it is possible to explicitly manage prior results and explicitly formulate queries to re-use prior results for each specific situation, it is best done automatically.  Algebraix is leveraging newly developed data algebra to dynamically re-factor queries as algebraic expressions of prior result fragments and optimally order queries to improve result re-use.   The result is dramatically increased SPARQL performance.
DTSTART:20120606T153000
SUMMARY:Algebra Unlocks SPARQL Performance
DTEND:20120606T161459
LOCATION: See Description
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