Details
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Bug
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Status: Resolved
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Major
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Resolution: Fixed
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2.4.0
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None
Description
ShuffleBlockFetcherIterator has logic to limit the number of simultaneous block fetches. By default, this logic tries to keep the number of outstanding block fetches beneath a data size limit (maxBytesInFlight). However, this limiting does not take fixed overheads into account: even though a remote block might be, say, 4KB, there are certain fixed-size internal overheads due to Netty buffer sizes which may cause the actual space requirements to be larger.
As a result, if a map stage produces a huge number of extremely tiny blocks then we may see errors like
org.apache.spark.shuffle.FetchFailedException: failed to allocate 16777216 byte(s) of direct memory (used: 39325794304, max: 39325794304) at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:554) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:485) [...] Caused by: io.netty.util.internal.OutOfDirectMemoryError: failed to allocate 16777216 byte(s) of direct memory (used: 39325794304, max: 39325794304) at io.netty.util.internal.PlatformDependent.incrementMemoryCounter(PlatformDependent.java:640) at io.netty.util.internal.PlatformDependent.allocateDirectNoCleaner(PlatformDependent.java:594) at io.netty.buffer.PoolArena$DirectArena.allocateDirect(PoolArena.java:764) at io.netty.buffer.PoolArena$DirectArena.newChunk(PoolArena.java:740) at io.netty.buffer.PoolArena.allocateNormal(PoolArena.java:244) at io.netty.buffer.PoolArena.allocate(PoolArena.java:226) at io.netty.buffer.PoolArena.allocate(PoolArena.java:146) at io.netty.buffer.PooledByteBufAllocator.newDirectBuffer(PooledByteBufAllocator.java:324) [...]
SPARK-24989 is another report of this problem (but with a different proposed fix).
This problem can currently be mitigated by setting spark.reducer.maxReqsInFlight to some some non-IntMax value (SPARK-6166), but this additional manual configuration step is cumbersome.
Instead, I think that Spark should take these fixed overheads into account in the maxBytesInFlight calculation: instead of using blocks' actual sizes, use Math.min(blockSize, minimumNettyBufferSize). There might be some tricky details involved to make this work on all configurations (e.g. to use a different minimum when direct buffers are disabled, etc.), but I think the core idea behind the fix is pretty simple.
This will improve Spark's stability and removes configuration / tuning burden from end users.
Attachments
Issue Links
- relates to
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SPARK-24989 BlockFetcher should retry while getting OutOfDirectMemoryError
- Resolved
- links to