Performance Optimization Through Data Pipeline in Heterogenious Hadoop Cluster
B Ravi Prasad

Dr B Ravi Prasad, Professor, CSE Department, Marri Laxman Reddy Institute of Technology and Management, Dundigal, Hyderabad, Telangana, India.
Manuscript received on November 11, 2019. | Revised Manuscript received on December 02, 2019. | Manuscript published on December 30, 2019. | PP: 5439-5444  | Volume-9 Issue-2, December, 2019. | Retrieval Number: B5155129219/2019©BEIESP | DOI: 10.35940/ijeat.B5155.129219
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Abstract: Big data has received a momentum from both The scholarly group and organisation. The MapReduce version has risen into a noteworthy figuring mannequin on the aspect of large information research. Hadoop, that is an open supply utilization of the MapReduce mannequin, has been generally taken up by the network. Cloud expert businesses, for example, Amazon EC2 cloud have now upheld Hadoop client applications. no matter the whole lot, a key take a seem at is that the cloud educated co-ops do not a have asset provisioning tool to satisfy client occupations with due date prerequisites. As of now, it’s miles completely the consumer duty to assess the require degree of property for his or her pastime running in an open cloud. This postulation correct-knownshows a Hadoop execution mannequin that exactly gauges the execution duration of exertions and in a similar manner arrangements the desired degree of property for a vocation to be finished indoors a due date. The proposed mannequin utilizes in the neighborhood Weighted Linear Regression (LWLR) mannequin to assess execution time of a vocation and Lagrange Multiplier device for asset provisioning to fulfill client art work with a given due date
Keywords: Hadoop, that is an open supply Utilization of the Map Reduce mannequin, has been generally taken up by the network.