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Subject: Re: Is Mahout obsolete now?
From: Pat Ferrel <pat@occamsmachete.com>
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Date: Mon, 19 Oct 2015 15:29:46 -0700
Cc: shanfeishanfei@gmail.com
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To: "user@mahout.apache.org" <user@mahout.apache.org>,
 Sean Owen <srowen@gmail.com>

BTW this use of Mahout-Samsara on Spark for recs has really expanded. =
The Samsara part I=E2=80=99m calling a Correlation Engine, it can be =
used to mix usage, content, and context to make recs. I look back on 2 =
years ago as pretty much groping around for solutions. Things are much =
clearer now (for me at least)

Check out some slides about the math, leading to the =E2=80=9Cwhole =
enchilada=E2=80=9D equation. Ted Dunning, Sean Owen, and Sebastian =
Schelter get no small credit.
http://www.slideshare.net/pferrel/unified-recommender-39986309

Even have code running using the PredicitonIO framework. This includesa =
SDK to event store to realtime query. Loosely speaking a lambda =
architecture. Most of the whole enchilada running except the content =
part of the equation, which only works on metadata for how.
https://github.com/pferrel/scala-parallel-universal-recommendation

We even do custom versions at actionML.com


On Oct 19, 2015, at 6:42 AM, Sean Owen <srowen@gmail.com> wrote:

No, this is pretty wrong. Spark is not, in general, a real-time
anything. Spark Streaming is a near-real-time streaming framework, but
it is not something you can build models with. Spark MLlib / ML are
offline / batch. Not sure what you mean by Hadoop engine, but Spark
does not build on MapReduce, if that's what you mean.

The "classic" Mahout code (<=3D 0.9) is definitely deprecated. The "new"
Mahout is not. It has a fairly different new recommender system called
Samsara. It has Scala APIs. In fact, it uses Spark. I think you're
somehow talking about the "classic" Mahout code here only.

On Mon, Oct 19, 2015 at 2:38 PM, Fei Shan <shanfeishanfei@gmail.com> =
wrote:
> Spark is a in memory , near realtime Machine Learning frameowork , has
> scala and java interface
> Mahout is an offline Machine Learning framework, no scala apis
>=20
> they both built on the HDFS and Hadoop engine
>=20
> Spark has an ecosystem like Hadoop
> Mahout is part of of Hadoop ecosystem
>=20
> Spark could beat Mahout on processing speed
> and concise programming APIs
>=20
> for online data anaysis , Spark is a better choice.
> for offline data analysis, both fits well.
>=20
>=20
>=20
> On Mon, Oct 19, 2015 at 9:14 PM, Prasad Priyadarshana Fernando <
> bppf16@gmail.com> wrote:
>=20
>> Hi,
>>=20
>> If I have used Mahout for my recommendation application, should I =
migrate
>> into Spark MLib technology? Is the mahout still supported and =
migrated?
>>=20
>> Thanks
>>=20
>> *Prasad Priyadarshana Fernando =
<http://www.linkedin.com/in/prasadfernando
>>> *
>> Mobile: +1 330 283 5827
>>=20