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What can cause big data being slow?

机译:什么会导致大数据变慢?

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摘要

Companies operating in some areas can gather all the data they need with relative ease, more specifically marketing companies, social networks or internet companies to name but a few. However when it comes to analyzing these data, many problems may occur. Insufficient resources that can store all this flood of data or highly significant response time to get the results. In some definitions of Big Data, one of the main characteristics is Velocity as the results should be obtained quickly. This is why optimization is a top priority while working in a Big Data environment. In this paper we provide a state-of-the-art report of the main causes of performance related problems in a Big Data environment. Our study is mainly focused on Hadoop as it is free and the most popular solution when it comes to Big Data.
机译:在某些地区运营的公司可以相对轻松地收集他们所需的所有数据,更具体地说,是营销公司,社交网络或互联网公司。但是,在分析这些数据时,可能会出现许多问题。资源不足,无法存储所有这些数据洪流或非常重要的响应时间,无法获得结果。在大数据的某些定义中,主要特征之一是速度,因为应尽快获得结果。这就是为什么在大数据环境中工作时,优化是重中之重的原因。在本文中,我们提供了有关大数据环境中与性能相关的问题的主要原因的最新报告。我们的研究主要针对Hadoop,因为它是免费的,并且是大数据方面最受欢迎的解决方案。

著录项

  • 来源
    《2016 SAI Computing Conference》|2016年|1223-1226|共4页
  • 会议地点 London(GB)
  • 作者单位

    Systems Engineering Laboratory, Data Analysis and Security Team, National School of Applied Sciences, Campus Universitaire, B.P 241, Kénitra 14000, Morocco;

    Systems Engineering Laboratory, Data Analysis and Security Team, National School of Applied Sciences, Campus Universitaire, B.P 241, Kénitra 14000, Morocco;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Big data; Indexes; Computer architecture; Companies; Layout; File systems;

    机译:大数据;索引;计算机体系结构;公司;布局;文件系统;

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