Ngone51 commented on a change in pull request #32287:
URL: https://github.com/apache/spark/pull/32287#discussion_r620777695
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File path:
core/src/main/scala/org/apache/spark/storage/ShuffleBlockFetcherIterator.scala
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@@ -683,7 +694,28 @@ final class ShuffleBlockFetcherIterator(
}
}
- case FailureFetchResult(blockId, mapIndex, address, e) =>
+ // Catching OOM and do something based on it is only a workaround for
handling the
+ // Netty OOM issue, which is not the best way towards memory
management. We can
+ // get rid of it when we find a way to manage Netty's memory precisely.
+ case FailureFetchResult(blockId, mapIndex, address, size,
isNetworkReqDone, e)
+ if e.isInstanceOf[OutOfDirectMemoryError] ||
e.isInstanceOf[NettyOutOfMemoryError] =>
+ assert(address != blockManager.blockManagerId &&
+ !hostLocalBlocks.contains(blockId -> mapIndex),
+ "Netty OOM error should only happen on remote fetch requests")
+ logWarning(s"Failed to fetch block $blockId due to Netty OOM, will
retry", e)
+ NettyUtils.isNettyOOMOnShuffle = true
+ numBlocksInFlightPerAddress(address) =
numBlocksInFlightPerAddress(address) - 1
+ bytesInFlight -= size
+ if (isNetworkReqDone) {
+ reqsInFlight -= 1
+ logDebug("Number of requests in flight " + reqsInFlight)
+ }
+ val defReqQueue =
+ deferredFetchRequests.getOrElseUpdate(address, new
Queue[FetchRequest]())
+ defReqQueue.enqueue(FetchRequest(address,
Array(FetchBlockInfo(blockId, size, mapIndex))))
Review comment:
> When it is not a NettyManagedBuffer then can there still be a
OutOfDirectMemoryError?
It's possible.
In general, for a remote request, it must rely on Netty to receive the data
sent from the server, which of course consumes Netty Memory. So it doesn't
matter whatever the final stored type is, e.g., `NettyManagedBuffer` or
`FileSegmentManagedBuffer`.
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