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From Grant Ingersoll <>
Subject Re: Commercializing Mahout: the Myrrix recommender platform
Date Fri, 06 Apr 2012 11:26:49 GMT
It's Apache licensed.  People can use it pretty much however they want per the terms in the
license.  There is no obligation for anyone to contribute back anything unless they so choose
and no one should expect anyone else to do so.  It would be great if they do contribute back,
but not required.  Just don't abuse the name/trademark and/or claim that Mahout is something
you (the royal you) own, because it isn't.  Mahout started at Apache and has always been modeled
after how Apache delivers software.  As long as there is a community here willing to maintain/develop
the code, Mahout will be here.

+1 to Sean's stuff.  I think it's awesome to see Mahout growing up.

On Apr 4, 2012, at 5:35 PM, Ted Dunning wrote:

> With this announcement, this group has a fork in the road facing us.
> We can choose the Hadoop path of forcibly excluding anybody with a slightly
> wrong commercial taint from discussions (I call this the "more GNU than
> GNU" philosophy).
> Or we can choose a real community based approach that includes vendors
> regardless of how they use the code that we freely give away via the Apache
> Mahout project (I call this "the Apache way").
> As you may guess from the way that I phrase these options, I would prefer
> the second approach.
> As such, I like it if we could resolve as a group that we very much welcome
> what Sean is doing as an augmentation rather than diminution of the major
> role that he has played in Mahout so far.  More than that, I would like to
> go on record saying that I, at least, am happy to have all kinds of
> participation in Mahout.
> Is this the consensus here?  I think it is important to bring this subject
> up early and get a definitive consensus rather than let it drift.
> On Wed, Apr 4, 2012 at 12:33 PM, Sean Owen <> wrote:
>> Dear all -- I've long promised (threatened?) to begin efforts to
>> commercialize Apache Mahout. Given my line of work in VC, I see
>> evidence for positive symbiosis between open source and commercial
>> enterprise. We have evidence from the growth in user base and mailing
>> list, as well as the Mahout in Action book, that this is becoming
>> another successful Apache project. It's time to start bringing more of
>> Mahout to the commercial world, and in turn bring those benefits back
>> into the open-source project.
>> To that endm I've been working on a heavily product-ized, somewhat
>> evolved, version of the recommender engine code available in Mahout.
>> After about six months of work, it's ready to announce. Please meet a
>> new startup company and software product, Myrrix (
>> Well, at least, it's ready for pre-launch of part of the product. The
>> announcement ( ) tells part of
>> the story, and the design doc ( ) tells more,
>> but I'll summarize key points here:
>> - Aims to add packaging, documentation and support, to product-ize
>> - Reuses Mahout APIs, some code, and certainly presented as a
>> "Mahout-based" platform
>> - Two-tier architecture: serving (or "speed") layer acting in
>> real-time, coordinating with distributed Hadoop-based computation
>> layer. Best of both worlds.
>> - Leans heavily on a variant of the alternating least squares algorithm
>> - Serving layer is free/open source and is a complete solution for
>> small-to-medium recommender problems
>> - Full distributed architecture, including hosted offering, is the
>> commercialized (read: for-pay) part
>> I would welcome community support in telling me what you like and
>> don't like about this. All the better if anyone is in a position to
>> actually run and test the Serving Layer:
>> I intend this to bring more profile, attention, and work to the Mahout
>> project, rather than subtract from it. I hope to see more
>> Mahout-related commercializations, beyond the inclusions in
>> distributions we're already seeing, in 2012, as it's key to the
>> long-term project health. It's most certainly going to be the year of
>> the application layer (analytics, machine learning) for Big Data.
>> Thank you!
>> Sean

Grant Ingersoll

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