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https://issues.apache.org/jira/browse/SPARK-20328?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15968396#comment-15968396
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Marcelo Vanzin commented on SPARK-20328:
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bq. The problem can't be solved in the Mesos backend
I meant setting the configs. 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? Otherwise you'd be putting a burden on
the user to have a proper Hadoop config around with those properties set.
bq. is why in the world is FileInputFormat fetching delegation tokens
That's actually a good question. It shouldn't need to do it not for the reasons
you mention, but because Spark already the necessary credentials available
(either a TGT, or a valid delegation token for HDFS).
> 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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