SaurabhChawla100 edited a comment on pull request #27636:
URL: https://github.com/apache/spark/pull/27636#issuecomment-642102323


   @agrawaldevesh - Thanks for checking this PR, Sure will check this PR 
https://github.com/apache/spark/pull/27864 and tried to use this in the current 
PR 
   
   Regarding this 
   
   > `I also don't fully understand the relationship b/w this PR and the 
original decommissioning PR https://github.com/apache/spark/pull/27864 
   I am trying to get a sense of the end state with all these multiple 
decommissioning PR's trying to stretch the framework in different ways.`
   
   So https://github.com/apache/spark/pull/27864 this is based on executor 
decommission where in k8s/ standalone mode the pods/worker received the SIGPWR 
and stop scheduling the task on the new task to executors on the same worker 
and creating new executors on worker. Its more of decommissioning of Executors 
   
   Where as in this current PR we are using the node information from the Yarn 
and using the information related to Node (spot node , Preemptible VM in GCP) 
to take an action. So on receiving the information related to node 
decommissioning we take the following action  as described in the PR 
description https://github.com/apache/spark/pull/27636#issue-377085357.  Its 
more of Node Decommissioning where driver is responsible for executor 
decommission and shuffle decommission. In this PR we are maintaining a life 
cycle how node decommissioned is handled
   
   This is the life cycle of the nodes which is decommissioned
   DECOMMISSIONING -> EXECUTOR_DECOMMISSIONED -> SHUFFLEDATA_DECOMMISSIONED -> 
TERMINATED.
   
   Also we can create another PR for making common parts for both PR once this 
PR is merged , the current PR and https://github.com/apache/spark/pull/27864 


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