WBDB2012: Workshop on Big Data Benchmarking 2012

WBDB2012：2012 年大数据基准研讨会

• 批准号: 1241838
• 负责人: Chaitanya Baru
• 金额: $ 1.5万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1241838&HistoricalAwards=false
• 关键词: WBDB2012; Workshop; Big; Data; Benchmarking

With the exponential increase in the size, complexity, and rate of acquisition of diverse types of data, there an urgent need for new techniques for managing and analyzing such data. In this context, there is a critical need for benchmarks to facilitate evaluation of alternative solutions and provide for comparisons among different solution approaches targeted to big data applications. Benchmarks need to capture a variety of characteristics of big data storage, management, and analytics including new feature sets, enormous data size, largescale and evolving system configurations, shifting loads, and the heterogeneous technologies of big-data and cloud platforms. The benchmarks are inadequate for assessing emerging big data platforms, systems and in software such as SQL, NoSQL, and the Hadoop software ecosystem; different modalities or genres of big data, including graphs, streams, scientific data, document collections, and transaction data; new options in hardware including, HDD vs SSD, different types of HDD, SSD, and main memory, and large-memory systems; and, new platform options that include dedicated commodity clusters and cloud platforms.The Workshop on Big Data Benchmarking 2012 represents an important step towards the development of a suite of benchmarks for providing objective measures of the effectiveness of hardware and software systems dealing with big data applications. The objective of this invitation-only workshop is to identify key issues and to launch an activity around the definition of reference benchmarks that can capture the essence of big data application scenarios. The effort aims to arrive at a set of objective measures and benchmark datasets to characterize and compare the performance of and the price/performance tradeoffs of alternative solutions for big data storage, retrieval, processing, and analysis problems. The workshop brings together a group of about 40 experts from academia and industry with backgrounds in big data, database systems, benchmarking and system performance, cloud storage and computing, and related areas.The industries represented range from hardware, software, analytics, and applications. The group will develop a draft of a report describing a big data benchmark suite that will be widely disseminated on the web and through presentations and oureach activities at the relevant conferences and workshops.Broader Impacts: The availability of the big data benchmark suite will facilitate research and technological advances by providing objective measures for comparing alternative solutions to key big data problems.

随着不同类型数据的规模、复杂性和获取速度呈指数级增长，迫切需要管理和分析此类数据的新技术。在这种背景下，迫切需要基准来促进替代解决方案的评估，并提供针对大数据应用的不同解决方案方法之间的比较。基准需要捕获大数据存储、管理和分析的各种特征，包括新功能集、巨大的数据量、大规模和不断发展的系统配置、负载转移以及大数据和云平台的异构技术。这些基准不足以评估新兴的大数据平台、系统以及 SQL、NoSQL 和 Hadoop 软件生态系统等软件；不同形式或类型的大数据，包括图表、流、科学数据、文档集合和交易数据；硬件方面的新选择，包括 HDD 与 SSD、不同类型的 HDD、SSD 和主内存以及大内存系统；包括专用商品集群和云平台在内的新平台选项。2012 年大数据基准测试研讨会代表了朝着开发一套基准测试迈出的重要一步，这些基准测试旨在提供处理大数据应用的硬件和软件系统有效性的客观衡量标准。此次仅限受邀参加的研讨会的目的是确定关键问题，并围绕参考基准的定义发起活动，以捕捉大数据应用场景的本质。这项工作的目的是获得一组客观的衡量标准和基准数据集，以描述和比较大数据存储、检索、处理和分析问题的替代解决方案的性能和价格/性能权衡。此次研讨会汇聚了约40位来自学术界和工业界的专家，他们拥有大数据、数据库系统、基准测试和系统性能、云存储和计算以及相关领域的背景。所代表的行业涵盖硬件、软件、分析和应用程序。 该小组将制定一份描述大数据基准套件的报告草案，该草案将在网络上以及通过相关会议和研讨会上的演示和我们的活动广泛传播。 更广泛的影响：大数据基准套件的可用性将通过提供客观的衡量标准来比较关键大数据问题的替代解决方案，从而促进研究和技术进步。