Job tracker & Tasktracker were utilized in previous version of Hadoop, which were responsible for handling resources and checking progress management. However, Hadoop 2.0 has Resource manager and Node Manager to beat the shortfall of JobTracker & Tasktracker.

In MapReduce, a JobTracker master method oversaw resource management, scheduling and monitoring of process jobs. It created subordinate processes referred to as TaskTrackers to run individual map and reduce tasks and report back on their progress, however most of the resource allocation and coordination work was centralized in JobTracker. That created performance bottlenecks and scalability issues as cluster sizes and also the number of applications -- and associated TaskTrackers -- increased.

Apache Hadoop YARN decentralizes execution and monitoring of processing jobs by separating the various responsibilities into these components: Bigdata training in Bangalore

A global ResourceManager that accepts job submissions from users, schedules the roles and allocates resources to them
A NodeManager slave that is put in at every node and functions as a monitoring and reporting agent of the ResourceManager
An ApplicationMaster that is created for every application to negotiate for resources and work with the NodeManager to execute and monitor tasks
Resource containers that are controlled by NodeManagers and assigned the system resources allocated to individual applications