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From "Sital Kedia (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-15074) Spark shuffle service bottlenecked while fetching large amount of intermediate data
Date Tue, 03 May 2016 03:57:12 GMT

    [ https://issues.apache.org/jira/browse/SPARK-15074?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15268039#comment-15268039
] 

Sital Kedia commented on SPARK-15074:
-------------------------------------

Since the index files contain 8 bytes (Long) per reduce task, if we have 10k reducers, the
index file size will be 80kb. If we have an LRU cache of few MB than we should be able to
cache a lot of index files there. Also, since the number of cache entry will be configurable,
user can control how much of memory to allocate to the cache. 

> Spark shuffle service bottlenecked while fetching large amount of intermediate data
> -----------------------------------------------------------------------------------
>
>                 Key: SPARK-15074
>                 URL: https://issues.apache.org/jira/browse/SPARK-15074
>             Project: Spark
>          Issue Type: Improvement
>          Components: Shuffle
>    Affects Versions: 1.6.1
>            Reporter: Sital Kedia
>
> While running a job which produces more than 90TB of intermediate data, we find that
about 10-15% of the reducer execution time is being spent in shuffle fetch. 
> Jstack of the shuffle service reveals that most of the time the shuffle service is reading
the index files generated by the mapper. 
> {code}
> java.lang.Thread.State: RUNNABLE
> 	at java.io.FileInputStream.readBytes(Native Method)
> 	at java.io.FileInputStream.read(FileInputStream.java:255)
> 	at java.io.DataInputStream.readFully(DataInputStream.java:195)
> 	at java.io.DataInputStream.readLong(DataInputStream.java:416)
> 	at org.apache.spark.network.shuffle.ExternalShuffleBlockResolver.getSortBasedShuffleBlockData(ExternalShuffleBlockResolver.java:277)
> 	at org.apache.spark.network.shuffle.ExternalShuffleBlockResolver.getBlockData(ExternalShuffleBlockResolver.java:190)
> 	at org.apache.spark.network.shuffle.ExternalShuffleBlockHandler.handleMessage(ExternalShuffleBlockHandler.java:85)
> 	at org.apache.spark.network.shuffle.ExternalShuffleBlockHandler.receive(ExternalShuffleBlockHandler.java:72)
> 	at org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:149)
> 	at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:102)
> 	at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:104)
> 	at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
> 	at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
> 	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
> 	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
> 	at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
> 	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
> 	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
> 	at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
> 	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
> 	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
> 	at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:86)
> 	at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
> 	at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
> 	at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
> 	at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
> 	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:745)
> {code}
> The issue is that for each shuffle fetch, we reopen the same index file again and read
it. It would be much efficient, if we can avoid opening the same file multiple times and cache
the data. We can use an LRU cache to save the index file information. This way we can also
limit the number of entries in the cache so that we don't blow up the memory indefinitely.




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