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https://issues.apache.org/jira/browse/SPARK-6511?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14493183#comment-14493183
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Patrick Wendell commented on SPARK-6511:
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Just as an example I tried to wire Spark to work with stock Hadoop 2.6. Here is
how I got it running after doing a hadoop-provided build. This is pretty
clunky, so I wonder if we should just support setting HADOOP_HOME or something
and we can automatically find and add the jar files present within that folder.
{code}
export SPARK_DIST_CLASSPATH=$(find /tmp/hadoop-2.6.0/ -name *.jar | tr "\n" ";")
./bin/spark-shell
{code}
[~vanzin] for your CDH packages, what do you end up setting
SPARK_DIST_CLASSPATH to?
> 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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