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From "Edward J. Yoon" <edwardy...@apache.org>
Subject Re: loading vertices into RAM
Date Wed, 15 Jan 2014 00:25:17 GMT
There are few implementations.

 - ListVerticesinfo: loads vertices into array list.
 - MapVerticesinfo: loads vertices into tree map.
 - DiskVerticesInfo: loads vertices into a local file.

You can choose one of them by setting the "hama.graph.vertices.info"
in job configuration.

  > conf.setClass("hama.graph.vertices.info",
"org.apache.hama.graph.ListVerticesInfo".

With the latest 0.6.3 version, you can use only ListVerticesInfo.
Please use the TRUNK.


On Tue, Jan 14, 2014 at 11:18 PM, Ammar Sahib <ammar.sahib@yahoo.com> wrote:
> Hi
>
> According to the BSP model, the data is processed in the RAM and that is the reason why
Pregel model is faster than the MapReduce (MapReduce writedown to disk). Can someone explains
to me how to be sure that all the graph vertices are actually been loaded in RAM?
>
>
> How would HAMA behave if the vertices values are so big such that the available RAM memory
is not enough to contains all of the vertices?
>
> Regards



-- 
Best Regards, Edward J. Yoon
@eddieyoon

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