Data mining using high performance data clouds: experimental studies using sector and sphere

  • Authors:
  • Robert Grossman;Yunhong Gu

  • Affiliations:
  • University of Illinois at Chicago and Open Data Group, Chicago, IL, USA;University of Illinois at Chicago, Chicago, IL, USA

  • Venue:
  • Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2008

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Abstract

We describe the design and implementation of a high performance cloud that we have used to archive, analyze and mine large distributed data sets. By a cloud, we mean an infrastructure that provides resources and/or services over the Internet. A storage cloud provides storage services, while a compute cloud provides compute services. We describe the design of the Sector storage cloud and how it provides the storage services required by the Sphere compute cloud. We also describe the programming paradigm supported by the Sphere compute cloud. Sector and Sphere are designed for analyzing large data sets using computer clusters connected with wide area high performance networks (for example, 10+ Gb/s). We describe a distributed data mining application that we have developed using Sector and Sphere. Finally, we describe some experimental studies comparing Sector/Sphere to Hadoop.