YARN stands for Yet Another Resource Negotiator. YARN is taking care of Job tracker's work like resource management and a part of that YARN is working as a schedule as well. It Supports a variety of processing engines and Applications. When we are saying different data processing ENGINE it means it supports Graph processing, Interactive Stream processing and batch processing to run and process the data which is stored in HDFS. Basically, the Resource manager receives the Job request from the client and accordingly it will Launch Application master JVM having default memory as 1 core and 2gb.

Application Master will contact Name Node and get the location of the block, based on the availability of block in Node Manager It will check whether sufficient resources are available or not, Accordingly it will inform the Resource manager and Resource manager will provide resources to Node Manager to Launch the JVM for the JOB.

Yarn is working as a schedule it means the SCHEDULER is responsible for allocating the resources to RUNNING the Application. It will not monitor the Application as well as it will not track the Application. It will not restart the failed task whether it is failed due to Application failure or Hardware Failure.

YARN Scheduler supports three types of scheduler

1. FIFO scheduler
2. FAIR scheduler
3. Capacity Scheduler.

Based on the Application requirement Hadoop Admin will select either FIFO, FAIR or Capacity Scheduler. 

FIFO scheduling is First in First out, in our current environment, this is rarely used. Fair scheduling is a method where resources are distributed in such a way that it is more or less equally DIVIDED to each job. Capacity scheduler where you can make sure that some percentage of resources you can assign to cluster based on your demand or computing need.    

Prior to start the YARN services, start the Resource manager and node manager services. In between Resource manager and Node, the manager makes sure the resource manager should start before starting node manager services. Please start your YARN services in the sequence mentioned below.

• On the resource manager system, 

#service Hadoop-yarn-resource manager start

• On each Node manager(where data node services run) system 

#service  -yarn-nodemanager start

• To start the MapReduce job history server 

#service Hadoop-MapReduce-history server start