A Survey on Big Data Processing Using Hadoop Components

Big Data is large-volume of data generated by public web, social media and different networks, business applications, scientific instruments, types of mobile devices and different sensor technology. Data mining involves knowledge discovery from these large data sets. Different types of clustering methods are used in data mining. For processing these large amounts of data in an inexpensive and efficient way, new architecture, techniques, algorithms and analytics are require to manage it and extract value and hidden knowledge from it. Hadoop is the core platform for storing the large volume of data into Hadoop Distributed File System (HDFS) and that data get processed by MapReduce model in parallel. Hadoop is designed to scale up from a single server to thousands of machines and with a very high degree of fault tolerance. This paper presents the survey of big data, issues with big data, clustering information and how Hadoop works.