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I'm a bit worried about this approach because we are implementing greedy mode inside CometTaskMemoryManager, which is known to starve consumers frequently. I prefer using fair spill pool for "native memory management" mode. This makes spillable operators work properly without being starved but with the cost of memory pool under-utilization.
I'm a bit worried about this approach because we are implementing greedy mode inside CometTaskMemoryManager, which is known to starve consumers frequently. I prefer using fair spill pool for "native memory management" mode. This makes spillable operators work properly without being starved but with the cost of memory pool under-utilization.
Thanks for the feedback. I will work on a separate PR for the fair spill approach. I am moving this PR to draft for now.
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Which issue does this PR close?
Closes #996
Rationale for this change
Simplify memory configuration.
What changes are included in this PR?
Allocate one shared pool per executor, rather than one pool per native plan, when
spark.memory.offHeap.enabled=false.How are these changes tested?