Samba Shiva created SPARK-48673:
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Summary: Scheduling Across Applications in k8s mode
Key: SPARK-48673
URL: https://issues.apache.org/jira/browse/SPARK-48673
Project: Spark
Issue Type: New Feature
Components: k8s, Kubernetes, Scheduler, Spark Shell, Spark Submit
Affects Versions: 3.5.1
Reporter: Samba Shiva
I have been trying autoscaling in Kubernetes for Spark Jobs,When first job is
triggered based on load workers pods are scaling which is fine but When second
job is submitted its not getting allocating any resources as First Job is
consuming all the resources.
Second job is in Waiting State until First Job is finished.I have gone through
documentation to set max cores in standalone mode which is not a ideal solution
as we are planning autoscaling based on load and Jobs submitted.
Is there any solution for this or any alternatives ?
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