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. Cheers, -- Galder Zamarreño [email protected] twitter.com/galderz _______________________________________________ infinispan-dev mailing list [email protected] https://lists.jboss.org/mailman/listinfo/infinispan-dev
