Mining of Datasets using Big Data Technique: Hadoop Platform

Abstract BIG DATA IS THE FUTURE OF IT INDUSTRY. Here see the methodology i.e. ETL process used for analysis of big data by using Hadoop ecosystem. The analysis of big data extracts business values from the raw data and helps in gaining competitive advantage by different organisations. There is a drastic growth of data in the web applications and social networking and such data are said be as Big Data. It requires huge amount of time consumption to retrieve those datasets. It lacks in performance analysis. To overcome this problem the Hive queries with the integration of Hadoop are used to generate the report analysis for thousands of datasets. The objective is to store the data persistently along with the past history of the data set and performing the report analysis of that data set. The main aim of this system is to improve performance through parallelization of various operations such as loading the data, index building and evaluating the queries. Thus the performance analysis is done with parallelization. HDFS file system is used to store the data after performing the MapReduce operations and the execution time is decreased when the number of nodes gets increased. The performance analysis is tuned with the parameters such as the execution time and number of nodes.

Keywords Big Data, Hadoop, HDFS.

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Mining of Datasets using Big Data Technique: Hadoop Platform

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