Analysis of Hadoop performance and unstructured data using Zeppelin

Big data has been designed as next 20 years for innovation, competition and productivity. It helps to top opportunities and address the top challenges. Every person has 320 * times data in their library and this data can't be examined by traditional data processing application devices, within the acceptable time. The difficulties incorporate the zones of capture, storage, search, sharing, exchange, examination, and representation of this data. Management of this data which ensures that the data from varied sources is processed error free and good quality to perform analysis. Hadoop is designed to handle the extremely high volumes of data in any structure. This paper explores the Hadoop cluster on Amazon Elastic Cloud, perform the benchmark of data load time with traditional data processing application and Hadoop. Secondly we analyze the unstructured data in Zeppelin with Spark.