These are the main tasks of JobTracker:
- To accept jobs from the client.
- To communicate with the NameNode to determine the location of the data.
- To locate TaskTracker Nodes with available slots.
- To submit the work to the chosen TaskTracker node and monitors the progress of each task.
In Hadoop MapReduce, the JobTracker is a critical component responsible for managing and coordinating the processing of jobs submitted to the Hadoop cluster. Its main functionalities include:
- Job Scheduling: The JobTracker schedules tasks based on the availability of resources in the cluster. It decides which tasks should run on which DataNodes.
- Task Tracking: It keeps track of the progress of individual tasks and monitors their execution. If a task fails, the JobTracker can reschedule it on another node.
- Resource Management: JobTracker manages the allocation and deallocation of resources (map and reduce slots) across the cluster to efficiently execute jobs.
- Fault Tolerance: It monitors the health of TaskTrackers. If a TaskTracker fails or is unreachable, the JobTracker redistributes the tasks running on that node to other healthy nodes.
- Job Monitoring and Coordination: JobTracker provides a web interface for monitoring the status of running jobs, completed jobs, and the overall health of the cluster. It also coordinates the execution of map and reduce tasks.
It’s worth noting that as of my last knowledge update in January 2022, Hadoop has evolved, and newer technologies such as Apache YARN have replaced the JobTracker for resource management in Hadoop clusters. In YARN, the ResourceManager takes care of resource management, and the ApplicationMaster manages the execution of a specific job. Therefore, the role of JobTracker is specific to the classic MapReduce framework in older versions of Hadoop.