Prabhu Joseph created YARN-11403:
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Summary: Decommission Node reduces the maximumAllocation and leads
to Job Failure
Key: YARN-11403
URL: https://issues.apache.org/jira/browse/YARN-11403
Project: Hadoop YARN
Issue Type: Bug
Affects Versions: 3.3.4
Reporter: Prabhu Joseph
Assignee: Prabhu Joseph
When a node is put into Decommission, ClusterNodeTracker updates the
maximumAllocation to the totalResources in use from that node. This could lead
to Job Failure (with below error message) when the Job requests for a container
of size greater than the new maximumAllocation.
{code}
22/11/03 10:55:02 WARN ApplicationMaster: Reporter thread fails 4 time(s) in a
row.
org.apache.hadoop.yarn.exceptions.InvalidResourceRequestException: Invalid
resource request! Cannot allocate containers as requested resource is greater
than maximum allowed allocation. Requested resource type=[vcores], Requested
resource=<memory:896, max memory:2147483647, vCores:2, max vCores:2147483647>,
maximum allowed allocation=<memory:896, vCores:1>, please note that maximum
allowed allocation is calculated by scheduler based on maximum resource of
registered NodeManagers, which might be less than configured maximum
allocation=<memory:122880, vCores:128>
{code}
**Repro:**
1. Cluster with two worker nodes - node1 and node2 each with YARN NodeManager
Resource Memory 10GB and configured maxAllocation is 10GB.
2. Submit Spark Job (ApplicationMaster Size: 2GB, Executor Size: 4GB). Say
ApplicationMaster (2GB) is launched on node1. (Add a wait condition in Spark
before it requests for Executors)
3. Put node1 into Decommission and make node2 into UNHEALTHY. This makes
maxAllocation to come down to 2GB.
4. Now notify the Spark Job. It requests for 4GB executor Size but the new
maxAllocation is 2GB and so will fail.
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