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https://issues.apache.org/jira/browse/HADOOP-4577?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12645459#action_12645459
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Steve Loughran commented on HADOOP-4577:
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Ahad, I don't plan on having a heterogenous cluster, but I can imagine creating
JARs that don't care which x86 system they run on. You could have a build that
had both 32 and 64 bit images in there (possibly kept under SCM to avoid
recompile times) and they just get JARred and uploaded.
> Add Jar "lib" directory to TaskRunner's library.path setting to allow JNI
> libraries to be deployed via JAR file
> -----------------------------------------------------------------------------------------------------------------
>
> Key: HADOOP-4577
> URL: https://issues.apache.org/jira/browse/HADOOP-4577
> Project: Hadoop Core
> Issue Type: Improvement
> Components: mapred
> Affects Versions: 0.18.1
> Environment: Hadoop 18.1 Cluster with custom JNI shared libraries
> deployed in lib directory of deployment JAR.
> Reporter: Ahad Rana
> Assignee: Ahad Rana
> Fix For: 0.18.3
>
> Attachments: HADOOP-4577-v1.patch
>
>
> It is extremely convenient to be able to deploy JNI libraries utilized in a
> custom map-reduce job via the job's JAR file. The TaskRunner already
> establishes a precedent by automatically adding any jar files contained in
> the "lib" directory of the job jar to the child map/reduce process's
> classpath. Following this convention, it should also be possible to deploy
> custom JNI libraries in the same lib directory. This involves adding the path
> to the job jar's lib directory to the VM's library.path setting (after the
> jar has been expanded in the job cache directory). This does not elimintate
> the need add dependent shared libraries that may be referenced by the JNI
> libraries to the system's LD_LIBRARY_PATH variable. In our deployment
> configuration, we usually pre-install third party shared libraries across the
> cluster and only deploy our custom JNI libraries via the job jar.
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