Big Data Problems:Understanding Hadoop Framework

The it industry has seen revolution from migrating from standardization to integration to virtualization to automation to the cloud. Now the industry is all set to spin around the commercialization that is data analytics-business intelligence. From all fields data is generating be it any industry sector. Thus volume, variety and velocity of the data have been extremely high. Thus to handle such enormous data where traditional databases is not possible the problem of storage, compution, low network bandwidth and less fault tolerant which lead to the introduction of bigdata. In this paper we have focused on the backend architecture and working of the parts of the hadoop framework which are themap reduce for the computational and analytics section and the hadoop distributed file system (hdfs) for the storage section.