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Analysis and evaluation of the riak cluster environment in distributed databases

机译:分布式数据库中RIAK集群环境的分析与评估

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摘要

Many institutions and companies undergoing technological developments have been producing large amounts of structured and unstructured data. Special databases are required to deal with such data and NoSQL databases have thus emerged. They are widely used in cloud databases and distributed systems. In the era of big data, these databases provide a scalable solution with high availability. In this context, we need new architectures in order to store more and more different kinds of data. To obtain a good structure for large and diverse data, structures must be tested and analyzed in depth with the use of different benchmark tools. In this paper, we test the Riak key-value database to measure its performance in terms of throughput and latency, where huge amounts of data are stored and retrieved in different sizes in a distributed database environment. The throughput and latency of the NoSQL database in different types of experiments and with different sizes of data are compared. As we increase the data size in the experiments, an increase in the number of threads leads to better throughput and latency factor was reduced. High performance results are obtained for only read operations for all experiments. We observed that performance advanced when there was only read operations compared with a mix of read and update operations. Moreover, our findings intensify the understanding of the distributed database and have to help future developers through the experimental results shown in this paper.
机译:许多经历技术发展的机构和公司都生产了大量的结构化和非结构化数据。需要特殊数据库来处理此类数据,因此出现了NoSQL数据库。它们广泛用于云数据库和分布式系统。在大数据的时代,这些数据库提供了一种具有高可用性的可扩展解决方案。在此上下文中,我们需要新的架构,以存储越来越多的不同数据。为了获得大型和不同数据的良好结构,必须通过使用不同的基准工具来测试结构和分析结构。在本文中,我们测试RIAK键值数据库以在吞吐量和延迟方面测量其性能,其中在分布式数据库环境中以不同大小存储和检索大量数据。比较了NoSQL数据库在不同类型的实验中的吞吐量和等待时间以及不同大小的数据。随着我们增加实验中的数据大小,线程数的增加导致更好的吞吐量和延迟因子减少。仅获得高性能结果,仅用于所有实验的读取操作。我们观察到,当只有读取和更新操作的混合相比,只有读取操作时,表现先进。此外,我们的调查结果加剧了对分布式数据库的理解,并通过本文所示的实验结果帮助未来的开发人员。

著录项

  • 来源
    《Computer standards & interfaces》 |2020年第10期|103452.1-103452.11|共11页
  • 作者单位

    College of Engineering and Technology American University of the Middle East Kuwait Department of Computer Engineering Ankara Yildirim Beyazit University Ankara Turkey;

    Department of Computer Science Faculty of Science Al Asmarya Islamic University Zliten Libya Department of Computer Engineering Ankara Yildirim Beyazit University Ankara Turkey;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Nosql database; Big data riak; Basho-bench; Cluster Structured data;

    机译:nosql数据库;大数据riak;Basho-bechch;集群结构化数据;

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