NDLI: Lustre, hadoop, accumulo

Content Provider	IEEE Xplore Digital Library
Author	Kepner, J. Arcand, W. Bestor, D. Bergeron, B. Byun, C. Edwards, L. Gadepally, V. Hubbell, M. Michaleas, P. Mullen, J. Prout, A. Rosa, A. Yee, C. Reuther, A.
Copyright Year	2015
Description	Author affiliation: MIT Lincoln Lab., Lexington, MA, USA (Kepner, J.; Arcand, W.; Bestor, D.; Bergeron, B.; Byun, C.; Edwards, L.; Gadepally, V.; Hubbell, M.; Michaleas, P.; Mullen, J.; Prout, A.; Rosa, A.; Yee, C.; Reuther, A.)
Abstract	Data processing systems impose multiple views on data as it is processed by the system. These views include spreadsheets, databases, matrices, and graphs. There are a wide variety of technologies that can be used to store and process data through these different steps. The Lustre parallel file system, the Hadoop distributed file system, and the Accumulo database are all designed to address the largest and the most challenging data storage problems. There have been many ad-hoc comparisons of these technologies. This paper describes the foundational principles of each technology, provides simple models for assessing their capabilities, and compares the various technologies on a hypothetical common cluster. These comparisons indicate that Lustre provides 2x more storage capacity, is less likely to loose data during 3 simultaneous drive failures, and provides higher bandwidth on general purpose workloads. Hadoop can provide 4x greater read bandwidth on special purpose workloads. Accumulo provides $10^{5}$ lower latency on random lookups than either Lustre or Hadoop but Accumulo's bulk bandwidth is 10x less. Significant recent work has been done to enable mix-and-match solutions that allow Lustre, Hadoop, and Accumulo to be combined in different ways.
Starting Page	1
Ending Page	5
File Size	912938
Page Count	5
File Format	PDF
e-ISBN	9781467392860
DOI	10.1109/HPEC.2015.7322476
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	File systems Distributed databases Accumulo Bandwidth Insider Hadoop Metadata Big Data Hardware Lustre Servers Parallel Performance
Content Type	Text
Resource Type	Article

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