[ 
http://issues.apache.org/jira/browse/NUTCH-209?page=comments#action_12365798 ] 

Doug Cutting commented on NUTCH-209:
------------------------------------

Andrzej, sorry, I didn't see your remark before I committed this!

A DFSClassLoader would have problems with plugins, since our plugin mechanism 
requires that we list a directory to find all defined plugins, and the 
ClassLoader API doesn't let one list directories.  That could be fixed, but 
it's not trivial.

Another way to address this concern is to permit one to specify different 
levels of DFS replication for different files.  So, while the default might be 
3, a job jar file might be replicated much more, so that individual nodes are 
not hit too hard by requests.  This is a feature that I believe Google 
implements, and one that folks at Yahoo! (who're now contributing to Hadoop) 
would like to add to Hadoop.

We could also try to make the job jar smaller, e.g., by only including enabled 
plugins.

> include nutch jar in mapred jobs
> --------------------------------
>
>          Key: NUTCH-209
>          URL: http://issues.apache.org/jira/browse/NUTCH-209
>      Project: Nutch
>         Type: Improvement
>     Versions: 0.8-dev
>     Reporter: Doug Cutting
>     Priority: Minor
>      Fix For: 0.8-dev

>
> I just added a simple way in Hadoop to specify the job jar file.  When 
> constructing a JobConf one can specify a class whose containing jar is set to 
> be the job's jar.  To take advantage of this in Nutch, we could add a util 
> class:
> public class NutchJob extends JobConf {
>   public NutchJob(Configuration conf) {
>     super(conf, NutchJob.class);
>   }
> }
> Then change all of the places where we construct a JobConf to instead 
> construct a NutchJob.
> Finally, we should add an ant target called 'job' that constructs a job jar, 
> containing all of the classes and the plugins, and make this the default 
> target.  This way all Nutch code can be distributed with each job as it is 
> submitted, and daemons would only need to be restarted when Hadoop code is 
> updated.
> Does this sound reasonable?

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