Enhanced Scheduling Algorithm for Avoiding Delay in MapReduce
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 8
Abstract
MapReduce is regarded as an adequate programming model for large scale data-intensive applications. When to start the reduce tasks is one of the main problems to elevate performance in the MapReduce. The performance of a MapReduce scheduling algorithm will be influenced seriously, when the output of map tasks becomes large. The aim is to formulate the causes for the waste of system slot resources, through analysis for the current MapReduce scheduling mechanism, which results in the reduce tasks waiting around and the proposes SARS (Self Adaptive Reduce Scheduling) for reduce tasks start times in Hadoop platform, it can determine the start time point of each reduce task dynamically according to each job context, including the completion time of the task and the size of map output. On comparing with the other algorithms SARS algorithm will decrease the job completion time, reduce completion time and system average time.
Authors and Affiliations
Nadhiya H, Nilavunesan D, Raju. S, Anitha. R, Rajalakshmi. S
Keywords
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- EP ID EP22457
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