Authors
Victor Anthony Arrascue Ayala, Polina Koleva, Anas Alzogbi, Matteo Cossu, Michael Färber, Patrick Philipp, Guilherme Schievelbein, Io Taxidou, Georg Lausen
Publication date
2019/7/5
Conference
Proceedings of the International Workshop on Semantic Big Data
Pages
1-6
Description
To benefit from mature database technology RDF stores are built on top of relational databases and SPARQL queries are mapped into SQL. Using a shared-nothing computer cluster is a way to achieve scalability by carrying out query processing on top of large RDF datasets in a distributed fashion. Aiming to this the current paper elaborates on the impact of relational schema design when queries are mapped into Apache Spark SQL. A single triple table, a set of tables resulting from partitioning by predicate, a single wide table covering all properties, and a set of tables based on the application model specification called domain-dependent-schema, are the considered designs. For each of the mentioned approaches, the rows of the corresponding tables are stored in the distributed file system HDFS using the columnar-store Parquet. Experiments using standard benchmarks demonstrate that the single wide property …
Scholar articles
VA Arrascue Ayala, P Koleva, A Alzogbi, M Cossu… - Proceedings of the International Workshop on …, 2019