From SPARQL to MapReduce
HyeongSik Kim, Padmashree Ravindra, Kemafor Anyanwu · Proceedings of the VLDB Endowment · 2011
MapReduce-based data processing platforms offer a promising approach for cost-effective and Web-scale processing of Semantic Web data. However, one major challenge is that this computational paradigm leads to high I/O and communication costs when processing tasks with several join operations typical in SPARQL queries. The goal of this demonstration is to show how a system RAPID+, an extension of Apache Pig, enables more efficient SPARQL query processing on MapReduce using an alternative query algebra called the Nested TripleGroup Algebra (NTGA). The demonstration will offer opportunities for users to explore NTGA-Hadoop query plans for different SPARQL query structures as well as explore relationships between query plans based on relational algebra operators and those using NTGA operators.