Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)

Accelerating the Shuffle Phase to Speed up MapReduce Systems

Authors
Rujie Yu, Songping Yu, Nong Xiao
Corresponding Author
Rujie Yu
Available Online December 2016.
DOI
https://doi.org/10.2991/iceeecs-16.2016.15How to use a DOI?
Keywords
RDMA; MapReduce; Shuffle Phase
Abstract

The CPU-centric traditional network protocol processing limits the utilization of network bandwidth, even with the high speed network (100Gbps); and the situation is more obvious in big data systems. The high performance network technology-Remote Direct Memory Access(RDMA), has the benefit of directly accessing remote application's memory without involving destination CPUs, broadening the performance boundary. In this paper, we build a pluggable shuffle module to boost the Map-Reduce system based on Unreliable Datagram transport of RDMA, including data fragmenting and a "Dynamic Controllably Apply and Allot" mechanism to ensure the reliability of data transmission. Experimental result shows that the performance of RDMA-based Spark is circa 16% better than that of IPoIB-based Spark.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-265-7
ISSN
2352-538X
DOI
https://doi.org/10.2991/iceeecs-16.2016.15How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Rujie Yu
AU  - Songping Yu
AU  - Nong Xiao
PY  - 2016/12
DA  - 2016/12
TI  - Accelerating the Shuffle Phase to Speed up MapReduce Systems
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 71
EP  - 74
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.15
DO  - https://doi.org/10.2991/iceeecs-16.2016.15
ID  - Yu2016/12
ER  -