AngersZhuuuu commented on a change in pull request #28541:
URL: https://github.com/apache/spark/pull/28541#discussion_r426984333
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File path: core/src/main/scala/org/apache/spark/memory/ExecutionMemoryPool.scala
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@@ -138,6 +140,11 @@ private[memory] class ExecutionMemoryPool(
if (toGrant < numBytes && curMem + toGrant < minMemoryPerTask) {
logInfo(s"TID $taskAttemptId waiting for at least 1/2N of $poolName
pool to be free")
lock.wait()
+ } else if (toGrant == 0 && memoryFree > 0) {
Review comment:
> I don't see why it's still required to wait for more memory here. If
your executor memory is not sufficient to support so many tasks, either
increase your executor memory or reduce the slots per executor.
Sometimes required 0 then cause Task throw OOM, in this case always task is
heavy, re-compute cost a lot.
For normal Spark job, we can change config to increase memory or change
slot, but for long running Spark such as Thrift server, we can't always restart
it.
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