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RSPLab: RDF Stream Processing Benchmarking Made Easy

机译:RSPLab:简化RDF流处理基准测试

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In Stream Reasoning (SR), empirical research on RDF Stream Processing (RSP) is attracting a growing attention. The SR community proposed methodologies and benchmarks to investigate the RSP solution space and improve existing approaches. In this paper, we present RSPLab, an infrastructure that reduces the effort required to design and execute reproducible experiments as well as share their results. RSPLab integrates two existing RSP benchmarks (LSBench and CityBench) and two RSP engines (C-SPARQL engine and CQELS). It provides a programmatic environment to: deploy in the cloud RDF Streams and RSP engines, interact with them using TripleWave and RSP Services, and continuously monitor their performances and collect statistics. RSPLab is released as open-source under an Apache 2.0 license.
机译:在流推理(SR)中,对RDF流处理(RSP)的经验研究引起了越来越多的关注。 SR社区提出了研究RSP解决方案空间并改进现有方法的方法和基准。在本文中,我们介绍了RSPLab,它是一种基础结构,可减少设计和执行可重复实验以及共享其结果所需的工作量。 RSPLab集成了两个现有的RSP基准(LSBench和CityBench)和两个RSP引擎(C-SPARQL引擎和CQELS)。它提供了一个编程环境,可以:在云中部署RDF流和RSP引擎,使用TripleWave和RSP服务与它们进行交互,并持续监视它们的性能并收集统计信息。 RSPLab在Apache 2.0许可下以开源形式发布。

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