Which MapReduce daemon instantiates user code, and executes map and reduce tasks on a cluster running MapReduce v1 (MRv1)?

Question

Options

• ANameNode
• BDataNode
• CJobTracker
• DTaskTracker
• EResourceManager
• FApplicationMaster
• GNodeManager

• B
  9% (3)
• C
  3% (1)
• D
  81% (26)
• F
  6% (2)

Explanation

A TaskTracker is a slave node daemon in the cluster that accepts tasks (Map, Reduce and Shuffle operations) from a JobTracker. There is only One Task Tracker process run on any hadoop slave node. Task Tracker runs on its own JVM process. Every TaskTracker is configured with a set of slots, these indicate the number of tasks that it can accept. The TaskTracker starts a separate JVM processes to do the actual work (called as Task Instance) this is to ensure that process failure does not take down the task tracker. The TaskTracker monitors these task instances, capturing the output and exit codes. When the Task instances finish, successfully or not, the task tracker notifies the JobTracker. The TaskTrackers also send out heartbeat messages to the JobTracker, usually every few minutes, to reassure the JobTracker that it is still alive. These message also inform the JobTracker of the number of available slots, so the JobTracker can stay up to date with where in the cluster work can be delegated. Note: How many Daemon processes run on a Hadoop system? Hadoop is comprised of five separate daemons. Each of these daemon run in its own JVM. Following 3 Daemons run on Master nodes NameNode - This daemon stores and maintains the metadata for HDFS. Secondary NameNode - Performs housekeeping functions for the NameNode. JobTracker - Manages MapReduce jobs, distributes individual tasks to machines running the Following 2 Daemons run on each Slave nodes DataNode - Stores actual HDFS data blocks. TaskTracker - Responsible for instantiating and monitoring individual Map and Reduce tasks. Task Tracker in Hadoop? How many instances of TaskTracker run on a Hadoop Cluster

No community discussion yet for this question.