Efficient Checkpoint Interval for Speculative Execution in MapReduce

Naychi Nway Nway; Ei Chaw Htoon

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Efficient Checkpoint Interval for Speculative Execution in MapReduce

http://hdl.handle.net/20.500.12678/0000005340

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Efficient Checkpoint Interval for Speculative Execution in MapReduce.pdf (903 Kb)

Publication type
		Conference paper
Upload type
		Publication
Title
	Title	Efficient Checkpoint Interval for Speculative Execution in MapReduce
	Language	en
Publication date		2018-11-01
Authors
		Naychi Nway Nway
		Ei Chaw Htoon
Description
		The MapReduce has become popular in big data environment due to its efficient parallel processing. However, MapReduce still has the problem from job delay caused by straggling tasks, which prolong job completion time. In MapReduce framework, although the existing speculative execution mechanism mitigate stragglers, its tasks are slower than their original tasks so this makes job completion time get long when straggling tasks occur. So, in this paper, a checkpoint mechanism is proposed in order to increase the efficiency of speculative execution of MapReduce, and not to prolong job completion time in case of straggling tasks. However, MapReduce produces too much intermediate data; as a result, checkpoint of every intermediate data can still decrease the performance of MapReduce. So, to avoid this problem, the proposed system evaluates checkpoint interval in order to reduce job completion time in case of stragglers. Then, the proposed system defines stragglers using LATE scheduler. The proposed checkpoint interval is based on five parameters: expected job completion time without checkpointing, checkpoint overhead time, rework time, down time and restart time. Experimental results show that the proposed system leads to less completion time, rework time and checkpoint overhead.
Keywords
		MapReduce, straggling task, big data, checkpoint interval, completion time
Conference papers
		ICAIT
		1 November, 2018
		International Conference on Advanced Information Technologies
		Yangon, Myanmar
		https://www.uit.edu.mm/icait-2018/

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