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- W4253488723 abstract "This chapter discusses the approaches integrated in GEMS (Graph database Engine for Multithreaded Systems) for managing and querying datasets of RDF (Resource Description Framework) triples. GEMS is a software stack that implements graph databases on top of commodity, high-performance clusters. GEMS is composed of a SPARQL-to-C++ compiler, a library of data structures and parallel graph methods, and a multithreaded runtime library. Differently from other RDF databases, which resort to more conventional relational databases approaches, and largely employ table-based methods for query processing, GEMS mostly employs graph methods. Query processing in GEMS is performed through the conversion of SPARQL queries into graph homomorphism routines, which then are directly executed on the graph database (resulting from the RDF triples ingestion) through its runtime library. The runtime library, which implements a Partitioned Global Address Space (PGAS), lightweight software multithreading, and network message aggregation, mitigates some of the typical issues of graph processing on modern commodity clusters, enabling scaling in performance and size while new cluster nodes are added. In fact, although very powerful, these systems are built for regular computation and easily partitionable workloads, while graph processing typically has an irregular behavior. The chapter explains how SPARQL queries can be naturally modeled as graph pattern-matching algorithms and details how GEMS performs the conversion to C++ routines. It briefly discusses the other components of GEMS and then shows the results of the full stack on the Berlin SPARQL Benchmark (BSBM) and the SPARQL Performance Benchmark (SP2B). We discuss effects of the automatic conversion and present a comparison with a full custom appliance for data analytics (YarcData Urika)." @default.
- W4253488723 created "2022-05-12" @default.
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- W4253488723 date "2010-09-01" @default.
- W4253488723 modified "2023-09-30" @default.
- W4253488723 title "Introduction" @default.
- W4253488723 doi "https://doi.org/10.1053/j.sart.2010.02.007" @default.
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