Hadoop is an open source framework which is used for storing and processing the large scale of data sets on large clusters of hardware. • The specialty of Hadoop involves in HDFS which is used for storing data on large commodity machines and provides very huge bandwidth for the cluster.
Content • Basics of Hadoop: • Motivation for Hadoop • Large scale system training • Survey of data storage literature • Literature survey of data processing • Networking constraints • New approach requirements
Content • Basic concepts of Hadoop • What is Hadoop? • Distributed file system of Hadoop • Map reduction of Hadoop works • Hadoop cluster and its anatomy • Hadoop demons • Master demons • Name node
Content • Tracking of job • Secondary node detection • Slave daemons • Tracking of task • HDFS(Hadoop Distributed File System) • Spilts and blocks • Input Spilts • HDFS spilts
Content • Replication of data • Awareness of Hadoop racking • High availably of data • Block placement and cluster architecture • CASE STUDIES • Practices & Tuning of performances • Development of mass reduce programs • Local mode
Content • Running without HDFS • Pseudo-distributed mode • All daemons running in a single mode • Fully distributed mode • Dedicated nodes and daemon running • Hadoop administration
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