Presentation 2014-08-20
A Preliminary Analysis on Dynamic Query Optimisation Mechanism for SPARQL Query Processing
Yuji YAMAGATA, Naoki FUKUTA,
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Abstract(in English) On a retrieval of Linked Open Data using SPARQL, a query often causes enormous consumption of endpoints' computing resources and furthermore it is sometimes difficult to predict what computations will cause such phenomena on the endpoints. Preventing such an execution of time-consuming queries, approximating the original query could reduce loads of endpoints. In this paper, we briefly discuss about a preliminary idea on building endpoints having a mechanism to (semi)-automatically avoid unwanted amount of inference or other computation by analyzing and predicting its computational costs and allowing it to transform such a query into a speed optimized and often approximated query. Our preliminary analysis shows a potential benefit and its practical difficulties on speed optimizations of query executions. We also demonstrate the design of a preliminary prototype system that could analyze such performance-related issues and it could classify whether a query execution is time-consuming or not, by using machine learning techniques at the endpoint-side.
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Keyword(in English) Linked Open Data / SPARQL / Query Processing
Paper # AI2014-15,SC2014-12
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Committee AI
Conference Date 2014/8/13(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Preliminary Analysis on Dynamic Query Optimisation Mechanism for SPARQL Query Processing
Sub Title (in English)
Keyword(1) Linked Open Data
Keyword(2) SPARQL
Keyword(3) Query Processing
1st Author's Name Yuji YAMAGATA
1st Author's Affiliation Graduate School of Informatics, Shizuoka University()
2nd Author's Name Naoki FUKUTA
2nd Author's Affiliation Graduate School of Informatics, Shizuoka University
Date 2014-08-20
Paper # AI2014-15,SC2014-12
Volume (vol) vol.114
Number (no) 181
Page pp.pp.-
#Pages 6
Date of Issue