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

A.
NameNode

B.
DataNode

C.
JobTracker

D.
TaskTracker

E.
ResourceManager

F.
ApplicationMaster

G.
NodeManager

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 Task
Tracker.

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.
24 Interview Questions & Answers for Hadoop MapReduce developers, What is a
Task Tracker in Hadoop? How many instances of TaskTracker run on a Hadoop Cluster