Discussion of BigBench: A Proposed Industry Standard Performance Benchmark for Big Data

被引:12
|
作者
Baru, Chaitanya [11 ]
Bhandarkar, Milind [10 ]
Curino, Carlo [7 ]
Danisch, Manuel [1 ]
Frank, Michael [1 ]
Gowda, Bhaskar [6 ]
Jacobsen, Hans-Arno [8 ]
Jie, Huang [6 ]
Kumar, Dileep [3 ]
Nambiar, Raghunath [2 ]
Poess, Meikel [9 ]
Raab, Francois [5 ]
Rabl, Tilmann [1 ]
Ravi, Nishkam [3 ]
Sachs, Kai [12 ]
Sen, Saptak [4 ]
Yi, Lan [6 ]
Youn, Choonhan [11 ]
机构
[1] Bankmark, Passau, Germany
[2] Cisco Syst, San Jose, CA USA
[3] Cloudera, Palo Alto, CA USA
[4] Hortonworks, Santa Clara, CA USA
[5] Infosizing, Manitou Springs, CO USA
[6] Intel Corp, Santa Clara, CA USA
[7] Microsoft Corp, Redmond, WA 98052 USA
[8] Middleware Syst Res Grp, Toronto, ON, Canada
[9] Oracle Corp, Redwood City, CA USA
[10] Pivotal, Vancouver, BC, Canada
[11] San Diego Supercomp Ctr, La Jolla, CA USA
[12] SPEC Res Grp, Gainesville, FL USA
来源
PERFORMANCE CHARACTERIZATION AND BENCHMARKING: TRADITIONAL TO BIG DATA | 2015年 / 8904卷
关键词
D O I
10.1007/978-3-319-15350-6_4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Enterprises perceive a huge opportunity in mining information that can be found in big data. New storage systems and processing paradigms are allowing for ever larger data sets to be collected and analyzed. The high demand for data analytics and rapid development in technologies has led to a sizable ecosystem of big data processing systems. However, the lack of established, standardized benchmarks makes it difficult for users to choose the appropriate systems that suit their requirements. To address this problem, we have developed the BigBench benchmark specification. BigBench is the first end-to-end big data analytics benchmark suite. In this paper, we present the BigBench benchmark and analyze the workload from technical as well as business point of view. We characterize the queries in the workload along different dimensions, according to their functional characteristics, and also analyze their runtime behavior. Finally, we evaluate the suitability and relevance of the workload from the point of view of enterprise applications, and discuss potential extensions to the proposed specification in order to cover typical big data processing use cases.
引用
收藏
页码:44 / 63
页数:20
相关论文
共 50 条
  • [41] Application of Big Data in Engineering Industry
    Anatolyevich, Aleksandrov Aleksandr
    Mikhailovich, Pavlov Andrey
    XLIV ACADEMIC SPACE CONFERENCE: DEDICATED TO THE MEMORY OF ACADEMICIAN S.P. KOROLEV AND OTHER OUTSTANDING RUSSIAN SCIENTISTS - PIONEERS OF SPACE EXPLORATION, 2021, 2318
  • [42] Big data management in the mining industry
    Qi, Chong-chong
    INTERNATIONAL JOURNAL OF MINERALS METALLURGY AND MATERIALS, 2020, 27 (02) : 131 - 139
  • [43] The Importance of Big Data in the Automotive Industry
    Wang, Ying-Shun
    MODERN INDUSTRIAL IOT, BIG DATA AND SUPPLY CHAIN, IIOTBDSC 2020, 2021, 218 : 254 - 260
  • [44] A Survey of Big Data in Healthcare Industry
    Khatri, Indu
    Shrivastava, Virendra Kumar
    ADVANCED COMPUTING AND COMMUNICATION TECHNOLOGIES, 2016, 452 : 245 - 257
  • [45] Big Data and Sustainability in the Tourism Industry
    Wang, Jue
    Ban, Hyun-Jeong
    Kim, Hak-Seon
    SUSTAINABILITY, 2022, 14 (13)
  • [46] Big data management in the mining industry
    Chong-chong Qi
    International Journal of Minerals, Metallurgy and Materials, 2020, 27 : 131 - 139
  • [47] The Application of Big Data in the Fashion Industry
    Dai, Jing-Yu
    2018 3RD ANNUAL INTERNATIONAL CONFERENCE ON EDUCATION SCIENCE AND EDUCATION MANAGEMENT (ESEM 2018), 2018, : 93 - 96
  • [48] Ethical Issues in the Big Data Industry
    Martin, Kirsten E.
    MIS QUARTERLY EXECUTIVE, 2015, 14 (02) : 67 - 85
  • [49] Industry 4.0 and big data innovations
    Li, Gang
    Tan, Jianlong
    Chaudhry, Sohail S.
    ENTERPRISE INFORMATION SYSTEMS, 2019, 13 (02) : 145 - 147
  • [50] Big Data Applications in Power Industry
    Chen, Chao
    Yang, Dongshu
    Wang, Shaochen
    Yang, Desheng
    PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON INFORMATION SCIENCES, MACHINERY, MATERIALS AND ENERGY (ICISMME 2015), 2015, 126 : 1166 - 1171