otterc commented on a change in pull request #32287:
URL: https://github.com/apache/spark/pull/32287#discussion_r618799593
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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 an executor is not assigned enough off-heap memory, is it possible
that in this case, it keeps retrying forever? Let's say there is some skew and
one of the blocks is large and whenever this block is fetched Netty OOMs. In
this case will this keep retrying? Maybe I am missing something.
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