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From Martin Jaggi <m.ja...@gmail.com>
Subject Re: Qt 4.4 / QtConcurrent
Date Sun, 01 Jun 2008 13:41:18 GMT
Thanks, it's very nice to see that they integrated Map Reduce.

But as I understood it this does not work (yet) for distributed  
systems, but only on one single machine.


Am 01.06.2008 um 14:33 schrieb Brice Arnould:

> Hi !
> With Qt 4.4, Trolltech provides a GPLed implementation of an in memory
> map/reduce for many languages (at least c++ and Java) as a part of
> QtConcurrent.
> I have not used this yet, but in general their API are well tough  
> and their
> code very slick. You might want to have a look at this.
>
> Code sample :
> | QImage scaled(const QImage &image) {
> |    return image.scaled(100, 100);
> | }
> | QList<QImage> images = ...;
> | QFuture<QImage> thumbnails = QtConcurrent::mapped(images, scaled);
> Doc :
> http://doc.trolltech.com/4.4/qtconcurrentmap.html#map
> Qt 4.4 GPL :
> http://trolltech.com/downloads/opensource
> Qt 4.4 Commercial :
> http://trolltech.com/downloads/commercial
>
> Brice
>
> On dimanche 1 juin 2008, Martin Jaggi wrote:
>> Thanks for your comments!
>>
>> So in the case that all intermediate pairs fit into the RAM of the
>> cluster, does the InMemoryFileSystem already allow the intermediate
>> phase to be done without much disk access? Or what would be the
>> current bottleneck in Hadoop in this scenario (huge computational
>> load, not so much data in/out) according to your opinion?


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