jiangxb1987 commented on a change in pull request #28541:
URL: https://github.com/apache/spark/pull/28541#discussion_r426963366
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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:
This simply means the task has already got assigned the amount of memory
that is above average, 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.
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