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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-14849) shuffle broken when accessing standalone cluster through NAT
Date Fri, 22 Apr 2016 15:19:13 GMT

     [ https://issues.apache.org/jira/browse/SPARK-14849?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-14849:
------------------------------------

    Assignee:     (was: Apache Spark)

> 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
>              Labels: 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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