andygrove opened a new pull request, #3924:
URL: https://github.com/apache/datafusion-comet/pull/3924
## Which issue does this PR close?
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Closes #3921
## Rationale for this change
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When Comet executes a shuffle, it creates two separate native plans (the
child plan and the shuffle writer plan) that run concurrently in a pipelined
fashion. Previously, each plan got its own memory pool at the full per-task
limit, effectively allowing 2x the intended memory to be consumed.
The new `fair_unified_task_shared` pool type shares a single
CometFairMemoryPool across all native plans within the same Spark task. This
ensures the total memory stays within the per-task limit while dynamically
distributing memory among operators based on how many register as memory
consumers (e.g. if the child plan is a simple scan+filter, the shuffle writer
gets 100% of the pool).
This is now the default for off-heap mode.
## What changes are included in this PR?
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## How are these changes tested?
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