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From Marco Shaw <marco.s...@gmail.com>
Subject Re: The future of MapReduce
Date Tue, 01 Jul 2014 20:50:39 GMT
Sorry, not sure if that's a question.

Hadoop v1=HDFS+MapReduce
Hadoop v2=HDFS+YARN (+ MapReduce part of the core, but now considered
optional to "get work done")

v2 adds a better resourcing framework.  Now you can run Storm, Spark,
MapReduce, etc. on Hadoop and mix-and-match jobs/tasks with whatever your
requirements, which may actually be both batch "stuff" and/or real-time.

Not sure if that clarifies things...  Just like you can evaluate all kinds
of Apache ecosystems products to meet your needs, MapReduce is no longer
the only kid on the bock.

On Tue, Jul 1, 2014 at 3:07 PM, 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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