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From kartik saxena <kartik....@gmail.com>
Subject Re: The future of MapReduce
Date Tue, 01 Jul 2014 18:17:03 GMT
Spark https://spark.apache.org/ is also getting a lot attention with its
in-memory computations and caching features. Performance wise it is being
touted better than mahout because machine learning involves iterative
computations and Spark could cache these computations in-memory for faster
processing.


On Tue, Jul 1, 2014 at 11:07 AM, Adaryl "Bob" Wakefield, MBA <
adaryl.wakefield@hotmail.com> wrote:

>   From your answer, it sounds like you need to be able to do both.
>
>  *From:* Marco Shaw <marco.shaw@gmail.com>
> *Sent:* Tuesday, July 01, 2014 10:24 AM
> *To:* user <user@hadoop.apache.org>
> *Subject:* Re: The future of MapReduce
>
>  It depends...  It seems most are evolving from needing "lots of data
> crunched", to "lots of data crunched right now".  Most are looking for
> *real-time* fraud detection or recommendations, for example, which
> MapReduce is not ideal for.
>
> Marco
>
>
> On Tue, Jul 1, 2014 at 12:00 PM, Adaryl "Bob" Wakefield, MBA <
> adaryl.wakefield@hotmail.com> wrote:
>
>>   “The Mahout community decided to move its codebase onto modern data
>> processing systems that offer a richer programming model and more efficient
>> execution than Hadoop MapReduce.”
>>
>> Does this mean that learning MapReduce is a waste of time? Is Storm the
>> future or are both technologies necessary?
>>
>> B.
>>
>
>

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