Optimizing hadoop to scale to big systems and big-data

优化 hadoop 以扩展到大系统和大数据

• 批准号: 485325-2015
• 负责人: Shriraman, Arrvindh
• 金额: $ 5.77万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=600090
• 关键词: Optimizing; hadoop; scale; big; systems

The overall `big-data' market is expected to be worth more than \$100 billion and growing roughly twice as fast as the software business as a whole [Deloitte]. The emergence of "big data", such as social media, has played critical roles in business analytics. As an IDC report indicates data analysis will play a key role in managing traffic in canadian cities (e.g., Toronto) and healthcare. Such big data is often stored in the new generation of NoSQL databases, and processed by massively parallel MapReduce/Hadoop based infrastructure. The industry

整个大数据市场的价值预计将超过1000亿美元，增长速度大约是整个软件业务的两倍[德勤]。社交媒体等“大数据”的出现，在商业分析中发挥了关键作用。正如IDC的一份报告指出的那样，数据分析将在加拿大城市(例如多伦多)和医疗保健的交通管理中发挥关键作用。这样的大数据通常存储在新一代NoSQL数据库中，并由基于MapReduce/Hadoop的大规模并行基础设施处理。这个行业