That's the paradigm of Hadoop's Map-Reduce.
> -----Original Message-----
> From: Samuel LEMOINE [mailto:[EMAIL PROTECTED]
> Sent: Thursday, August 23, 2007 2:48 PM
> To: [email protected]
> Subject: "Moving Computation is Cheaper than Moving Data"
>
> When I read the Hadoop documentation:
> The Hadoop Distributed File System: Architecture and Design
> (http://lucene.apache.org/hadoop/hdfs_design.html)
>
> a paragraph hold my attention:
>
>
> "Moving Computation is Cheaper than Moving Data"
>
> A computation requested by an application is much more
> efficient if it is executed near the data it operates on.
> This is especially true when the size of the data set is
> huge. This minimizes network congestion and increases the
> overall throughput of the system. The assumption is that it
> is often better to migrate the computation closer to where
> the data is located rather than moving the data to where the
> application is running. HDFS provides interfaces for
> applications to move themselves closer to where the data is located.
>
>
>
>
> I'd like to know how to perform that, espacially with the aim
> of distributed Lucene search ? Which Hadoop classes should I
> use to do that ?
>
> Thanks in advance,
>
> Samuel
>
