YARN - Yet Another Resource Negotiator
I hope you know what is BigData, Hadoop and HDFS If not, I suggest you to read above topics before read this.
What is YARN?
YARN stands for Yet Another Resource Negotiator. It's one of the Hadoop core components. YARN is use to manage the hadoop cluster. like schedule task and manage the resource.
In Hadoop V1, MapReduce is the one who handled all resource related details and task/job details. It's over load for MapRedice job. So, in Hadoop V2 they splitted resource related things separately and name as YARN.
Components:
- Resource Manager
- Node Manager
Resource Manager
It's master node in YARN. Only per cluster. It knows the slave node details. It inhabit the JobTracker of MapReduce Version 1 (MRV1).
Resource Scheduler
Resource Scheduler is responsible for allocating resource to application and it's not perform any monitoring and tracking activities like application failure, Hardware failure and so on.
App Manager
It maintain the application status like it's submitted, currently running or completed.
The app manager responsible for accepting the jobs and negotiating the first container for executing the application specific to App Master and restart the App Master on failure or by request from user.
The app manager responsible for accepting the jobs and negotiating the first container for executing the application specific to App Master and restart the App Master on failure or by request from user.
Node Manager
It's slave node in YARN. Many per cluster. It inhabit the TaskTracker of MapReduce Version 1 (MRV1).
Application Master
It will send heartbeat to resource manager periodically to confirm its health and update the record processed. It's co-ordinate and Applications executing in the cluster and manage failures.
Container
It's collection of physical resource such as RAM, CPU Cores and disk on single node. It grants rights to the application to use specific amount of resource on host.
We will see about Hadoop MapReduce in next post.
What next?
We will see about Hadoop MapReduce in next post.
Thanks for the blogger.
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