Setting up and implementing Hadoop services in a cost effective way in near to impossible for small and medium sized organizations. Large scale data driven companies and various Hadoop professional services providers can make optimum utilization of Hadoop. There are generally four modules in Hadoop- Distributed file system, Hadoop common, MapReduce, and YARN.
Distributed file system permits data storage in an easy-to-access format throughout numerous connected storage devices. In MapReduce module, the data is read from the database, put into a suitable analysis format that called as Map, and perform various calculations, i.e. count total males over 30 years of age in the database (reduce). Hadoop common offers special Java tools, which are used for reading data. YARN handles resources of the data storing systems and analysis operations.
Subsequently, Hadoop as a service (HAAS) offering ensures a managed Hadoop cluster that is ready to use with no configuration requirement or installation of other Hadoop related services on any node, such as Jobtracker, Namenode, Datanode, Tasktracker, and may offer secondary services such as Hbase or Zookeeper. There are pre-installed tools available in Hadoop services like Pig, Hive and Sqoop.