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Jian He commented on YARN-1680: ------------------------------- On my thinking, even if we do the headroom calculation on the client side, scheduler still requires some corresponding per-app logic for the headroom calculation. And that scheduler piece of logic may end up duplicating a subset of the client side logic plus corresponding protocol changes. In that sense, I think it's simpler to do this inside scheduler. Doing the calculation in one place is still a more accurate snapshot than doing the calculations in multiple places. Also, changing MapReduce to use AMRMClient is non-trivial work. > availableResources sent to applicationMaster in heartbeat should exclude > blacklistedNodes free memory. > ------------------------------------------------------------------------------------------------------ > > Key: YARN-1680 > URL: https://issues.apache.org/jira/browse/YARN-1680 > Project: Hadoop YARN > Issue Type: Sub-task > Components: capacityscheduler > Affects Versions: 2.2.0, 2.3.0 > Environment: SuSE 11 SP2 + Hadoop-2.3 > Reporter: Rohith > Assignee: Craig Welch > Attachments: YARN-1680-WIP.patch, YARN-1680-v2.patch, > YARN-1680-v2.patch, YARN-1680.patch > > > There are 4 NodeManagers with 8GB each.Total cluster capacity is 32GB.Cluster > slow start is set to 1. > Job is running reducer task occupied 29GB of cluster.One NodeManager(NM-4) is > become unstable(3 Map got killed), MRAppMaster blacklisted unstable > NodeManager(NM-4). All reducer task are running in cluster now. > MRAppMaster does not preempt the reducers because for Reducer preemption > calculation, headRoom is considering blacklisted nodes memory. This makes > jobs to hang forever(ResourceManager does not assing any new containers on > blacklisted nodes but returns availableResouce considers cluster free > memory). -- This message was sent by Atlassian JIRA (v6.3.4#6332)