The Implications of Diverse Applications and Scalable Data Sets in Benchmarking Big Data Systems

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Provided by: Cornell University
Topic: Data Management
Format: PDF
In the past decades, in order to store big data and provide services, more and more organizations around the world build data centers with scales varying from several nodes to hundreds of thousands of nodes. The people live in an era of big data, and big data applications are becoming more and more pervasive. How to benchmark data center computer systems running big data applications (in short big data systems) is a hot topic. In this paper, the authors focus on measuring the performance impacts of diverse applications and scalable volumes of data sets on big data systems.
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