Ngone51 commented on a change in pull request #32287:
URL: https://github.com/apache/spark/pull/32287#discussion_r622722674
##########
File path:
core/src/main/scala/org/apache/spark/storage/ShuffleBlockFetcherIterator.scala
##########
@@ -261,14 +282,36 @@ final class ShuffleBlockFetcherIterator(
results.put(new SuccessFetchResult(BlockId(blockId),
infoMap(blockId)._2,
address, infoMap(blockId)._1, buf, remainingBlocks.isEmpty))
logDebug("remainingBlocks: " + remainingBlocks)
+ enqueueDeferredFetchRequestIfNecessary()
}
}
logTrace(s"Got remote block $blockId after
${Utils.getUsedTimeNs(startTimeNs)}")
}
override def onBlockFetchFailure(blockId: String, e: Throwable): Unit = {
logError(s"Failed to get block(s) from
${req.address.host}:${req.address.port}", e)
- results.put(new FailureFetchResult(BlockId(blockId),
infoMap(blockId)._2, address, e))
+ remainingBlocks -= blockId
+ val (size, mapIndex) = infoMap(blockId)
+ e match {
+ // 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.
+
+ // Ensure the Netty memory is at least enough for serving only one
block to avoid
+ // the endless retry. And since the Netty memory is shared among
shuffle, rpc, etc,
+ // modules, we use "1.5" for the overhead concern.
+ case _: OutOfDirectMemoryError if
PlatformDependent.maxDirectMemory() > ( 1.5 * size) =>
+ if (isNettyOOMOnShuffle.compareAndSet(false, true)) {
+ // The fetcher can fail remaining blocks in batch for the same
error. So we only
+ // log the warning once to avoid flooding the logs.
+ logWarning(s"Netty OOM happens, will retry the failed blocks")
+ }
+ deferredBlocks += blockId
Review comment:
That's interesting! But if you look at `RetryingBlockFetchListener`, it
also has protection against thread-safe.
I'll take another look too.
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