This is YARN framework which is responsible for doing Cluster Resource Management. Cluster resource management means managing the resources of the Hadoop Clusters. And by resources we mean Memory, CPU etc. YARN took over this task of cluster management from MapReduce and MapReduce is streamlined to perform Data Processing only in which it is best. YARN has central resource manager component which manages resources and allocates the resources to the application. Multiple applications can run on Hadoop via YARN and all application could share common resource management. Advantage of YARN: Yarn does efficient utilization of the resource: There are no more fixed map-reduce slots. YARN provides central resource manager. With YARN, you can now run multiple applications in Hadoop, all sharing a common resource. Yarn can even run application that do not follow MapReduce model: YARN decouples MapReduce's resource management and scheduling capabilities from the data processing component, enabling Hadoop to support more varied processing approaches and a broader array of applications. For example, Hadoop clusters can now run interactive querying and streaming data applications simultaneously with MapReduce batch jobs. This also streamlines MapReduce to do what is does best - process data. Few Important Notes about YARN: YARN is backward compatible: This means that existing MapReduce job can run on Hadoop 2.0 without any change. No more JobTracker and TaskTracker needed in Hadoop 2.0: JobTracker and TaskTracker has totally disappeared. YARN splits the two major functionalities of the JobTracker i.e. resource management and job scheduling/monitoring into 2 separate daemons (components). Resource Manager Node Manager(node specific) Central Resource Manager and node specific Node Manager together constitutes YARN. ... View more