PREFETCHER FOR TUNING MAP REDUCE FRAMEWORK IN BIG DATA
Author’s Name : S Tamil Selvan | J Kokilavani
Volume 04 Issue 02 Year 2017 ISSN No: 2349-3828 Page no: 16-18
The big-data refers to the large-scale distributed data processing applications. Google’s MapReduce and Apache’s Hadoop, is an open-source framework that operates extraordinarily on large amounts of data. MapReduce framework is the framework that generates a large amount of intermediate data. Such abundant information is thrown away after the tasks finish, because MapReduce is unable to utilize them. In order to enhance efficiency of MapReduce functionality, we propose a data-aware prefetcher framework for big-data applications. In this framework tasks submit their intermediate results to the prefetcher. A task queries the prefetcher before executing the actual computing work. A novel prefetch description scheme and a prefetch request and reply protocol are designed. Experimental results show that Prefetcher significantly improves the completion time of Hadoop MapReduce job.
Big-data, Map Reduce,Hadoop, Prefetcher,Intermediate results
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