• Ms Swagita Dwivedi
• Prof.Lalitkumar P.Bhaiya

Driven by the steady extended in "conceived advanced" data, data driven registering gives new troubles in data organization and investigation in the life sciences and in various controls stretching out from coordination's (movement examination) to sociology(online organizing). These troubles are through and through not quite the same as the standard reenactment challenges since dealing with an extensive number of individual records and terabytes of data. Cutting edge investigation strategies in light of packing and requests for ordinary reenactments consistently require the examination of complex data records in an iterative methodology. In this paper we present MPI-MapReduce based clustering of complex biological dataset utilizing octree clustering technique. We performed investigates a conveyed environment utilizing MapReduce and MPI. The outcomes beats the current clustering technique which utilizes Euclidian distance. The proposed L2 standard based octree clustering demonstrates more levels of isolated ligand.

hadoop mapreduce mpi clustering

"A Combined Approach For Clustering Biological Ligand Using Hadoop and MPI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.732-737, June-2019, Available :http://www.jetir.org/papers/JETIR1906112.pdf

"A Combined Approach For Clustering Biological Ligand Using Hadoop and MPI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp732-737, June-2019, Available at : http://www.jetir.org/papers/JETIR1906112.pdf