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https://issues.apache.org/jira/browse/SPARK-20328?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15968411#comment-15968411
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Michael Gummelt commented on SPARK-20328:
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> The Mesos backend (I mean the code in Spark, not the Mesos service) can set
> the configs in the SparkContext's "hadoopConfiguration" object, can't it?
I suppose this would work. It would rely on the assumption that the Mesos
scheduler backend is started before the HadoopRDD is created, which happens to
be true, but ideally we wouldn't have to rely on that ordering. Right now I'm
just setting it in {{SparkSubmit}}, but that's not great either.
I filed a Hadoop ticket for the {{FileInputFormat}} issue and linked it here.
> HadoopRDDs create a MapReduce JobConf, but are not MapReduce jobs
> -----------------------------------------------------------------
>
> Key: SPARK-20328
> URL: https://issues.apache.org/jira/browse/SPARK-20328
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0, 2.1.1, 2.1.2
> Reporter: Michael Gummelt
>
> In order to obtain {{InputSplit}} information, {{HadoopRDD}} creates a
> MapReduce {{JobConf}} out of the Hadoop {{Configuration}}:
> https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala#L138
> Semantically, this is a problem because a HadoopRDD does not represent a
> Hadoop MapReduce job. Practically, this is a problem because this line:
> https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala#L194
> results in this MapReduce-specific security code being called:
> https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/security/TokenCache.java#L130,
> which assumes the MapReduce master is configured (e.g. via
> {{yarn.resourcemanager.*}}). If it isn't, an exception is thrown.
> So I'm seeing this exception thrown as I'm trying to add Kerberos support for
> the Spark Mesos scheduler:
> {code}
> Exception in thread "main" java.io.IOException: Can't get Master Kerberos
> principal for use as renewer
> at
> org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:116)
> at
> org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:100)
> at
> org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodes(TokenCache.java:80)
> at
> org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:205)
> at
> org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
> at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:202)
> {code}
> I have a workaround where I set a YARN-specific configuration variable to
> trick {{TokenCache}} into thinking YARN is configured, but this is obviously
> suboptimal.
> The proper fix to this would likely require significant {{hadoop}}
> refactoring to make split information available without going through
> {{JobConf}}, so I'm not yet sure what the best course of action is.
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