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Algebraic Multigrid on a Dragonfly Network: First Experiences on a Cray XC30 Read chapter Read first chapter

2015 | OriginalPaper | Chapter

On the Energy Proportionality of Distributed NoSQL Data Stores

Authors : Balaji Subramaniam, Wu-chun Feng

Published in: High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation

Publisher: Springer International Publishing

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Abstract

The computing community is facing several big data challenges due to the unprecedented growth in the volume and variety of data. Many large-scale Internet companies use distributed NoSQL data stores to mitigate these challenges. These NoSQL data-store installations require massive computing infrastructure, which consume significant amount of energy and contribute to operational costs. This cost is further aggravated by the lack of energy proportionality in servers.
Therefore, in this paper, we study the energy proportionality of servers in the context of a distributed NoSQL data store, namely Apache Cassandra. Towards this goal, we measure the power consumption and performance of a Cassandra cluster. We then use power and resource provisioning techniques to improve the energy proportionality of the cluster and study the feasibility of achieving an energy-proportional data store. Our results show that a hybrid (i.e., power and resource) provisioning technique provides the best power savings — as much as 55 %.

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previous chapter Analysis of the Tradeoffs Between Energy and Run Time for Multilevel Checkpointing
Footnotes
1
The other components, denoted by “Others,” also include the power consumption of the hard disk.
 
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Metadata
Title
On the Energy Proportionality of Distributed NoSQL Data Stores
Authors
Balaji Subramaniam
Wu-chun Feng
Copyright Year
2015
Book
High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation

Print ISBN: 978-3-319-17247-7

Electronic ISBN: 978-3-319-17248-4

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-17248-4_14