Big Data Proprietary Platforms. The Case of Oracle Exadata
作者: Marin FotacheAlexandru TicăIonuț HrubaruTeodor Marius Spînu
作者单位: 1Alexandru Ioan Cuza University of Iaşi , Faculty of Economics and Business Administration , Iaşi , Romania
2 Alexandru Ioan Cuza University of Iaşi , Faculty of Economics and Business Administration , Iaşi , Romania
3 Alexandru Ioan Cuza University of Iaşi , Faculty of Economics and Business Administration , Iaşi , Romania
刊名: Review of Economic and Business Studies, 2018, Vol.11 (1), pp.45-78
来源数据库: De Gruyter Journal
DOI: 10.1515/rebs-2018-0064
关键词: Big DataOracle ExadataTPC-HMARSREarth packageC39C88M15
原始语种摘要: Abstract The most prominent Big Data solutions – such as NoSQL systems, Hadoop Frameworks, Spark, etc. – have been open-sourced. Nevertheless, commercial providers have targeted niches of this huge market with products more or less viable and affordable. This paper addresses the problem of benchmarking Big Data platforms with a focus on Oracle Exadata solution provided by one the most important data technologies vendor. Many classical benchmark approaches, such as TPC-H, are based on a predefined set of queries, and consequently they are not prone to predictive modeling. By contrast, for the TPC-H benchmark schema, we generate a set of 500 random queries containing not only tuple filters (WHERE), but also tuple grouping (GROUP BY) and group filters (HAVING), we collected results of the...
全文获取路径: De Gruyter 
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关键词翻译
关键词翻译
  • Data 数据
  • benchmark 基准点
  • tuple 元组
  • package 外壳
  • query 查询
  • schema 模式
  • generate 
  • grouping 组合
  • duration 持续时间
  • metrics 规格