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https://issues.apache.org/jira/browse/SPARK-6511?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14493585#comment-14493585
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Kannan Rajah commented on SPARK-6511:
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As requested by Patrick, here is an example of what we use in spark-env.sh for
MapR distribution.
----------------------------
MAPR_HADOOP_CLASSPATH=`hadoop classpath`
MAPR_SPARK_CLASSPATH="$MAPR_HADOOP_CLASSPATH:$MAPR_HADOOP_HBASE_VERSION"
MAPR_HADOOP_JNI_PATH=`hadoop jnipath`
export SPARK_LIBRARY_PATH=$MAPR_HADOOP_JNI_PATH
SPARK_SUBMIT_CLASSPATH=$SPARK_SUBMIT_CLASSPATH:$MAPR_SPARK_CLASSPATH
SPARK_SUBMIT_LIBRARY_PATH=$SPARK_SUBMIT_LIBRARY_PATH:$MAPR_HADOOP_JNI_PATH
export SPARK_SUBMIT_CLASSPATH
export SPARK_SUBMIT_LIBRARY_PATH
------------------------------------------------
> Publish "hadoop provided" build with instructions for different distros
> -----------------------------------------------------------------------
>
> Key: SPARK-6511
> URL: https://issues.apache.org/jira/browse/SPARK-6511
> Project: Spark
> Issue Type: Improvement
> Components: Build
> Reporter: Patrick Wendell
>
> Currently we publish a series of binaries with different Hadoop client jars.
> This mostly works, but some users have reported compatibility issues with
> different distributions.
> One improvement moving forward might be to publish a binary build that simply
> asks you to set HADOOP_HOME to pick up the Hadoop client location. That way
> it would work across multiple distributions, even if they have subtle
> incompatibilities with upstream Hadoop.
> I think a first step for this would be to produce such a build for the
> community and see how well it works. One potential issue is that our fancy
> excludes and dependency re-writing won't work with the simpler "append
> Hadoop's classpath to Spark". Also, how we deal with the Hive dependency is
> unclear, i.e. should we continue to bundle Spark's Hive (which has some fixes
> for dependency conflicts) or do we allow for linking against vanilla Hive at
> runtime.
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