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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:34:43 UTC
[jira] [Resolved] (SPARK-14849) shuffle broken when accessing
standalone cluster through NAT
[ https://issues.apache.org/jira/browse/SPARK-14849?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-14849.
----------------------------------
Resolution: Incomplete
> shuffle broken when accessing standalone cluster through NAT
> ------------------------------------------------------------
>
> Key: SPARK-14849
> URL: https://issues.apache.org/jira/browse/SPARK-14849
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.1
> Reporter: Luc Bourlier
> Priority: Major
> Labels: bulk-closed, nat, network
>
> I have the following network configuration:
> {code}
> +--------------------+
> | |
> | spark-shell |
> | |
> +- ip: 10.110.101.2 -+
> |
> |
> +- ip: 10.110.101.1 -+
> | | NAT + routing
> | spark-master | configured
> | |
> +- ip: 10.110.100.1 -+
> |
> +------------------------+
> | |
> +- ip: 10.110.101.2 -+ +- ip: 10.110.101.3 -+
> | | | |
> | spark-worker 1 | | spark-worker 2 |
> | | | |
> +--------------------+ +--------------------+
> {code}
> I have NAT, DNS and routing correctly configure such as each machine can communicate with each other.
> Launch spark-shell against the cluster works well. Simple map operations work too:
> {code}
> scala> sc.makeRDD(1 to 5).map(_ * 5).collect
> res0: Array[Int] = Array(5, 10, 15, 20, 25)
> {code}
> But operations requiring shuffling fail:
> {code}
> scala> sc.makeRDD(1 to 5).map(i => (i,1)).reduceByKey(_ + _).collect
> 16/04/22 15:33:17 WARN TaskSetManager: Lost task 4.0 in stage 2.0 (TID 19, 10.110.101.1): FetchFailed(BlockManagerId(0, 10.110.101.1, 42842), shuffleId=0, mapId=6, reduceId=4, message=
> org.apache.spark.shuffle.FetchFailedException: Failed to connect to /10.110.101.1:42842
> at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:323)
> [ ... ]
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.io.IOException: Failed to connect to /10.110.101.1:42842
> at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
> [ ... ]
> at org.apache.spark.network.shuffle.RetryingBlockFetcher.access
> [ ... ]
> {code}
> It makes sense that a connection to 10.110.101.1:42842 would fail, no part of the system should have a direct knowledge of the IP address 10.110.101.1.
> So a part of the system is wrongly discovering this IP address.
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