AKSW Colloquium, 13.06.2016, SPARQL query processing with Apache Spark

In the upcoming Colloquium, Simon Bin will discuss the paper “SimonSPARQL query processing with Apache Spark” by H. Naacke et.al. that has been submitted to ISWC2016.  Abstract

The number of linked data sources and the size of the linked open data graph keep growing every day.  As a consequence, semantic RDF services are more and more confronted to various big data problems.  Query processing is one of them and needs to be efficiently addressed with executions over scalable, highly available and fault tolerant frameworks.  Data management systems requiring these properties are rarely built from scratch but are rather designed on top of an existing cluster computing engine.  In this work, we consider the processing of SPARQL queries with Apache Spark.
We propose and compare five different query processing approaches based on different join execution models and Spark components.  A detailed experimentation, on real-world and synthetic data sets, emphasizes that two approaches tailored for the RDF data model outperform the other ones on all major query shapes, i.e star, snowflake, chain and hybrid.

About the AKSW Colloquium

This event is part of a series of events about Semantic Web technology. Please see http://wiki.aksw.org/Colloquium for further information about previous and future events. As always, Bachelor and Master students are able to get points for attendance and there is complimentary coffee and cake after the session.

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