Martin Przyjaciel-Zablocki

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The MapReduce programming model has gained traction in different application areas in recent years, ranging from the analysis of log files to the computation of the RDFS closure. Yet, for most users the MapReduce abstraction is too low-level since even simple computations have to be expressed as Map and Reduce phases. In this paper we propose RDFPath, an(More)
In this paper we investigate the scalable processing of complex SPARQL queries on very large RDF datasets. As underlying platform we use Apache Hadoop, an open source implementation of Google's MapReduce for massively parallelized computations on a computer cluster. We introduce PigSPARQL, a system which gives us the opportunity to process complex SPARQL(More)
One of the major challenges in large-scale data processing with MapReduce is the smart computation of joins. Since Semantic Web datasets published in RDF have increased rapidly over the last few years, scalable join techniques become an important issue for SPARQL query processing as well. In this paper, we introduce the Map-Side Index Nested Loop Join(More)
Taste in music is of highly subjective nature, making the recommending of music tracks a challenging research task. With TRecS, our live prototype system, we present a weighted hybrid recommender approach that amalgamates three diverse recommender techniques into one comprehensive score. Moreover, our system peppers the generated result list with(More)
For processing data on the Web, recommender systems and SPARQL are two popular paradigms, which however have rather different characteristics. SPARQL is a declarative language on RDF graphs which allows a user to precisely specify the desired information. In contrast, a recommender system suggests certain items to a user, based on similarity to other users(More)
In this paper we discuss PigSPARQL, a competitive yet easy to use SPARQL query processing system on MapReduce that allows ad-hoc SPARQL query processing on large RDF graphs out of the box. Instead of a direct mapping, PigSPARQL uses the query language of Pig, a data analysis platform on top of Hadoop MapReduce, as an intermediate layer between SPARQL and(More)
—In recent times, it has been widely recognized that, due to their inherent scalability, frameworks based on MapRe-duce are indispensable for so-called " Big Data " applications. However, for Semantic Web applications using SPARQL, there is still a demand for sophisticated MapReduce join techniques for processing basic graph patterns, which are at the core(More)