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Posted to issues@spark.apache.org by "belvey (JIRA)" <ji...@apache.org> on 2019/04/01 00:12:00 UTC
[jira] [Commented] (SPARK-13510) Shuffle may throw
FetchFailedException: Direct buffer memory
[ https://issues.apache.org/jira/browse/SPARK-13510?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16806307#comment-16806307 ]
belvey commented on SPARK-13510:
--------------------------------
[~shenhong] , hello hongsheng, I am using spark2.0 facing the same issue, I am not sure if it's merged into spark2. it's very kind for you to post your pr.
> Shuffle may throw FetchFailedException: Direct buffer memory
> ------------------------------------------------------------
>
> Key: SPARK-13510
> URL: https://issues.apache.org/jira/browse/SPARK-13510
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.0
> Reporter: Hong Shen
> Priority: Major
> Attachments: spark-13510.diff
>
>
> In our cluster, when I test spark-1.6.0 with a sql, it throw exception and failed.
> {code}
> 16/02/17 15:36:03 INFO storage.ShuffleBlockFetcherIterator: Sending request for 1 blocks (915.4 MB) from 10.196.134.220:7337
> 16/02/17 15:36:03 INFO shuffle.ExternalShuffleClient: External shuffle fetch from 10.196.134.220:7337 (executor id 122)
> 16/02/17 15:36:03 INFO client.TransportClient: Sending fetch chunk request 0 to /10.196.134.220:7337
> 16/02/17 15:36:36 WARN server.TransportChannelHandler: Exception in connection from /10.196.134.220:7337
> java.lang.OutOfMemoryError: Direct buffer memory
> at java.nio.Bits.reserveMemory(Bits.java:658)
> at java.nio.DirectByteBuffer.<init>(DirectByteBuffer.java:123)
> at java.nio.ByteBuffer.allocateDirect(ByteBuffer.java:306)
> at io.netty.buffer.PoolArena$DirectArena.newChunk(PoolArena.java:645)
> at io.netty.buffer.PoolArena.allocateNormal(PoolArena.java:228)
> at io.netty.buffer.PoolArena.allocate(PoolArena.java:212)
> at io.netty.buffer.PoolArena.allocate(PoolArena.java:132)
> at io.netty.buffer.PooledByteBufAllocator.newDirectBuffer(PooledByteBufAllocator.java:271)
> at io.netty.buffer.AbstractByteBufAllocator.directBuffer(AbstractByteBufAllocator.java:155)
> at io.netty.buffer.AbstractByteBufAllocator.directBuffer(AbstractByteBufAllocator.java:146)
> at io.netty.buffer.AbstractByteBufAllocator.ioBuffer(AbstractByteBufAllocator.java:107)
> at io.netty.channel.AdaptiveRecvByteBufAllocator$HandleImpl.allocate(AdaptiveRecvByteBufAllocator.java:104)
> at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:117)
> at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
> at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
> at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
> at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
> at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
> at java.lang.Thread.run(Thread.java:744)
> 16/02/17 15:36:36 ERROR client.TransportResponseHandler: Still have 1 requests outstanding when connection from /10.196.134.220:7337 is closed
> 16/02/17 15:36:36 ERROR shuffle.RetryingBlockFetcher: Failed to fetch block shuffle_3_81_2, and will not retry (0 retries)
> {code}
> The reason is that when shuffle a big block(like 1G), task will allocate the same memory, it will easily throw "FetchFailedException: Direct buffer memory".
> If I add -Dio.netty.noUnsafe=true spark.executor.extraJavaOptions, it will throw
> {code}
> java.lang.OutOfMemoryError: Java heap space
> at io.netty.buffer.PoolArena$HeapArena.newUnpooledChunk(PoolArena.java:607)
> at io.netty.buffer.PoolArena.allocateHuge(PoolArena.java:237)
> at io.netty.buffer.PoolArena.allocate(PoolArena.java:215)
> at io.netty.buffer.PoolArena.allocate(PoolArena.java:132)
> {code}
>
> In mapreduce shuffle, it will firstly judge whether the block can cache in memery, but spark doesn't.
> If the block is more than we can cache in memory, we should write to disk.
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