[SPARK-27991] ShuffleBlockFetcherIterator should take Netty constant-factor overheads into account when limiting number of simultaneous block fetches

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 2.4.0
• Fix Version/s: 3.2.0
• Component/s: Shuffle, Spark Core
• Assignee: wuyi
• Reporter: Josh Rosen
• Created: 10/Jun/19 17:24
• Updated: 20/May/21 04:28
• Resolved: 20/May/21 04:27

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.

Issue Links

• relates to: SPARK-24989 BlockFetcher should retry while getting OutOfDirectMemoryError
• links to: [Github] Pull Request #32287 (Ngone51)
• links to: [Github] Pull Request #32287 (Ngone51)