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Lianhui Wang edited comment on SPARK-2468 at 11/7/14 2:01 PM: -------------------------------------------------------------- [~adav] yes,with https://github.com/apache/spark/pull/3155/ in my test beyond physical memory limits does not happened.but i discover that Netty's performance is not good than NioBlockTransferService. so I need to find why Netty's performance is bad than NioBlockTransferService in my test.Can you give me some suggestions? thanks.and how about your test? [~zzcclp] was (Author: lianhuiwang): [~adav] yes,with https://github.com/apache/spark/pull/3155/ in my test it does not happened.but i discover that Netty's performance is not good than NioBlockTransferService. so I need to find why Netty's performance is bad than NioBlockTransferService in my test.Can you give me some suggestions? thanks.and how about your test? [~zzcclp] > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org