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https://issues.apache.org/jira/browse/SPARK-2468?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14207826#comment-14207826
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zzc commented on SPARK-2468:
----------------------------
Hi, Aaron Davidson, I am sure that I ran my last test with the patch #3155
applied.
configuration :
spark.shuffle.consolidateFiles true
spark.storage.memoryFraction 0.2
spark.shuffle.memoryFraction 0.2
spark.shuffle.file.buffer.kb 100
spark.reducer.maxMbInFlight 48
spark.shuffle.blockTransferService netty
spark.shuffle.io.mode nio
spark.shuffle.io.connectionTimeout 120
spark.shuffle.manager SORT
spark.shuffle.io.preferDirectBufs true
spark.shuffle.io.maxRetries 3
spark.shuffle.io.retryWaitMs 5000
spark.shuffle.io.maxUsableCores 3
command:
--num-executors 17 --executor-memory 12g --executor-cores 3
If spark.shuffle.io.preferDirectBufs=false, it's OK.
> 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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