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What is the outcome that you are trying to reach?
For running batch jobs, like Spark workloads, we want to have higer resource utilization and cost efficiency to avoid spreading pods across nodes leading nodes can be scaled-in in time.
By default, the scheduling-plugin NodeResourcesFit use the LeastAllocated for score strategies. For the long running workloads, that is good because of high availability. But for batch jobs, like Spark workloads, this would have high cost. By changing the from LeastAllocated to MostAllocated, it avoids spreading pods across all running nodes, leading to higher resource utilization and better cost efficiency.
Describe the solution you would like
Support binpacking strategy.
Describe alternatives you have considered
Using the custom scheduler like Yunikorn or Volcano. But it is complicated in some scenarios that we only need the binpacking.
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Community Note
What is the outcome that you are trying to reach?
For running batch jobs, like Spark workloads, we want to have higer resource utilization and cost efficiency to avoid spreading pods across nodes leading nodes can be scaled-in in time.
By default, the scheduling-plugin NodeResourcesFit use the
LeastAllocated
for score strategies. For the long running workloads, that is good because of high availability. But for batch jobs, like Spark workloads, this would have high cost. By changing the fromLeastAllocated
toMostAllocated
, it avoids spreading pods across all running nodes, leading to higher resource utilization and better cost efficiency.Describe the solution you would like
Support binpacking strategy.
Describe alternatives you have considered
Using the custom scheduler like Yunikorn or Volcano. But it is complicated in some scenarios that we only need the binpacking.
Additional context