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https://issues.apache.org/jira/browse/SPARK-2468?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14208013#comment-14208013
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Lianhui Wang commented on SPARK-2468:
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[~adav]yes i re-run test with preferDirectBufs=true and maxUsableCores=2 on
yarn. that cause container to be killed because Container is running beyond
physical memory limits.
if i set preferDirectBufs=false, it is ok, but setting preferDirectBufs=false
the Netty's performance is not good than NioBlockTransferService.
in my test size of shuffle data is 1-2G , executor-memory=7g,executor-cores=2,
spark.yarn.executor.memoryOverhead=1024
> Netty-based block server / client module
> ----------------------------------------
>
> Key: SPARK-2468
> URL: https://issues.apache.org/jira/browse/SPARK-2468
> Project: Spark
> Issue Type: Improvement
> Components: Shuffle, Spark Core
> Reporter: Reynold Xin
> Assignee: Reynold Xin
> Priority: Critical
> Fix For: 1.2.0
>
>
> Right now shuffle send goes through the block manager. This is inefficient
> because it requires loading a block from disk into a kernel buffer, then into
> a user space buffer, and then back to a kernel send buffer before it reaches
> the NIC. It does multiple copies of the data and context switching between
> kernel/user. It also creates unnecessary buffer in the JVM that increases GC
> Instead, we should use FileChannel.transferTo, which handles this in the
> kernel space with zero-copy. See
> http://www.ibm.com/developerworks/library/j-zerocopy/
> One potential solution is to use Netty. Spark already has a Netty based
> network module implemented (org.apache.spark.network.netty). However, it
> lacks some functionality and is turned off by default.
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