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https://issues.apache.org/jira/browse/GIRAPH-64?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13146023#comment-13146023
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Hyunsik Choi commented on GIRAPH-64:
------------------------------------

In my case, 'mvn package' is ok, but 'mvn assembly:assembly' incurs the error 
as I mentioned above.

{code}
hyunsik@code:~$ mvn --version
Apache Maven 3.0.3 (r1075438; 2011-03-01 02:31:09+0900)
Maven home: /home/hyunsik/Local/maven-3
Java version: 1.6.0_26, vendor: Sun Microsystems Inc.
Java home: /usr/lib/jvm/java-6-sun-1.6.0.26/jre
Default locale: en_US, platform encoding: UTF-8
OS name: "linux", version: "3.0.0-12-generic", arch: "amd64", family: "unix"
{code}
                
> Create VertexRunner to make it easier to run users' computations
> ----------------------------------------------------------------
>
>                 Key: GIRAPH-64
>                 URL: https://issues.apache.org/jira/browse/GIRAPH-64
>             Project: Giraph
>          Issue Type: New Feature
>            Reporter: Jakob Homan
>            Assignee: Jakob Homan
>         Attachments: GIRAPH-64.patch
>
>
> Currently, if a user wants to implement a Giraph algorithm by extending 
> {{Vertex}} they must also write all the boilerplate around the {{Tool}} 
> interface and bundle it with the Giraph jar (or get Giraph on the classpath 
> and playing nice with the implementation).  For example, what is included in 
> the PageRankBenchmark and what Kohei has done: 
> https://github.com/smly/java-Giraph-LabelPropagation  It would be better if 
> we had perhaps a Vertex implementation to be subclassed that already had all 
> the standard Tooling included such that all one had to run would be (assuming 
> the Giraph jar was already on the classpath):
> {noformat}hadoop jar my-awesome-vertex.jar my.awesome.vertex -i jazz_input -o 
> jazz_output -if org.apache.giraph.lib.in.text.adjacency-list.LongDoubleDouble 
> -of org.apache.giraph.lib.out.text.adjacency-list.LongDoubleDouble{noformat} 
> This wouldn't work with every algorithm, but would be useful in a large 
> number of cases.

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