Abstract
The International Scientific Research Organization for Science, Engineering and Technology (ISROSET) is a Non-Profit Organization; The ISROSET is dedicated to improvement in academic sectors of Science (Chemistry, Bio-chemistry, Zoology, Botany, Biotechnology, Pharmaceutical Science, Bioscience, Bioinformatics, Biometrics, Biostatistics, Microbiology, Environmental Management, Medical Science, Forensic Science, Home Science, Library Science, Material Science Military Science, Physical Science, Physical Education Science, Educational Science, Fisheries, seed technology, Agriculture, Forestry Science, Mathematics, Physics, Statistics and Geology/Earth Science), Computer Science, Engineering and Information Technology, Commerce, Management, Economics Sociology and Social Science.
Highlights
In recent years, Hadoop Map Reduce is used extensively in near real-time “Big Data” analytics like advertising, traffic log analysis, sentiment analysis, and many
We currently consider meeting deadlines for individual jobs whose input data is initially present only in internal cloud (IC). Such a scenario is encountered by enterprises that use their private data center (IC) for normal operation and employ cloud bursting only when there are load surges
In this paper we addressed the implementation of an Efficient method for word count across external cloud and internal cloud
Summary
Hadoop Map Reduce is used extensively in near real-time “Big Data” analytics like advertising, traffic log analysis, sentiment analysis, and many. Mappers in EC to perform streaming read from remote HDFS in IC which minimizes startup latencies They propose techniques to reduce the effect of elongated shuffle phase. These jobs uses on previous version of Hadoop(v1.0) that inherently causes idle cpu cycles due to fixed partitioning of map and reduce slots on a node. Such a scenario is encountered by enterprises that use their private data center (IC) for normal operation and employ cloud bursting only when there are load surges. On incoming data storm map and reduce operations over are executed; Check pointing strategies are used to enable pipelined uploading, processing and downloading of data
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