[ https://issues.apache.org/jira/browse/SPARK-27876?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
feiwang updated SPARK-27876: ---------------------------- Description: There is a limit for shuffle read. If a shuffle partition block's size is large than Integer.MaxValue(2GB) and this block is fetched from remote, an Exception will be thrown. {code:java} 2019-05-24 06:46:30,333 [9935] - WARN [shuffle-client-6-2:TransportChannelHandler@78] - Exception in connection from hadoop3747.jd.163.org/10.196.76.172:7337 java.lang.IllegalArgumentException: Too large frame: 2991947178 at org.spark_project.guava.base.Preconditions.checkArgument(Preconditions.java:119) at org.apache.spark.network.util.TransportFrameDecoder.decodeNext(TransportFrameDecoder.java:133) at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:81) at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362) {code} Then this task would throw a fetchFailedException. This task will retry and it would execute successfully only when this task was reScheduled to a executor whose host is same to this oversize shuffle partition block. However, if there are more than one oversize(>2GB) shuffle partitions block, this task would never execute successfully and it may cause the failure of application. In this PR, I propose a new method to fetch shuffle block, it would fetch multi times when the relative shuffle partition block is oversize. > [CORE][SHUFFLE] Split large shuffle partition to multi-segments to enable > transfer oversize shuffle partition block. > -------------------------------------------------------------------------------------------------------------------- > > Key: SPARK-27876 > URL: https://issues.apache.org/jira/browse/SPARK-27876 > Project: Spark > Issue Type: Improvement > Components: Shuffle, Spark Core > Affects Versions: 2.4.3, 3.1.0 > Reporter: feiwang > Priority: Major > > There is a limit for shuffle read. > If a shuffle partition block's size is large than Integer.MaxValue(2GB) and > this block is fetched from remote, an Exception will be thrown. > {code:java} > 2019-05-24 06:46:30,333 [9935] - WARN > [shuffle-client-6-2:TransportChannelHandler@78] - Exception in connection > from hadoop3747.jd.163.org/10.196.76.172:7337 > java.lang.IllegalArgumentException: Too large frame: 2991947178 > at > org.spark_project.guava.base.Preconditions.checkArgument(Preconditions.java:119) > at > org.apache.spark.network.util.TransportFrameDecoder.decodeNext(TransportFrameDecoder.java:133) > at > org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:81) > at > io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:362) > {code} > Then this task would throw a fetchFailedException. > This task will retry and it would execute successfully only when this task > was reScheduled to a executor whose host is same to this oversize shuffle > partition block. > However, if there are more than one oversize(>2GB) shuffle partitions block, > this task would never execute successfully and it may cause the failure of > application. > In this PR, I propose a new method to fetch shuffle block, it would fetch > multi times when the relative shuffle partition block is oversize. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org