On 2014-06-26, 10:12 AM, Galder Zamarreño wrote:
> On 23 Jun 2014, at 11:04, Gustavo Fernandes <[email protected]> wrote:
>
>> - I read with great interest the Spark paper [9]. Spark provides a DSL with 
>> functional language constructs like map, flatMap and filter to process 
>> distributed data in memory. In this scenario, Map Reduce is just a special 
>> case achieved by chaining functions [10]. As Spark is much more than Map 
>> Reduce, and can run many machine learning algorithms efficiently, I was 
>> wondering if we should shift attention to Spark rather than focusing too 
>> much on Map Reduce. Thoughts?
> I’m not an expert on these topics, but I like the look and the approach of 
> Spark :). The fact that it’s not tight to a single paradigm is particularly 
> interesting, and secondly, the fact that it’s tries to make the most out of 
> functional constructs, which seem to provide more elegant ways of dealing 
> with data.
>
>
Gustavo thanks for your email and the references. I like Spark as well! 
I read the Spark paper over the weekend, definitely not an easy digest 
and I will continue to read about this topic but this seems to be the 
direction we should steer ourselves - data analytics platform!

As for Hadoop implementation not sure that it make sense to 
implement/support Hadoop v1.x unless it is super easy and low 
maintenance. How hard would it be to implement YARN?

Regards,
Vladimir
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