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From "Debo Dutta (dedutta)" <dedu...@cisco.com>
Subject Re: [DISCUSS] PredictionIO incubation proposal
Date Tue, 17 May 2016 21:40:07 GMT
Thx a lot Henry. Would love to. 

Sent from my iPhone

> On May 17, 2016, at 2:19 PM, Henry Saputra <henry.saputra@gmail.com> wrote:
> 
> You are welcome, and great to have you as one of mentors for PredictionIO
> polling.
> 
> Should be a fun project to be part of =)
> 
> - Henry
> 
>> On Tue, May 17, 2016 at 2:14 PM, Suneel Marthi <smarthi@apache.org> wrote:
>> 
>> Thanks Henry
>> 
>> On Tue, May 17, 2016 at 5:11 PM, Henry Saputra <henry.saputra@gmail.com>
>> wrote:
>> 
>>> As mentor, you will have karma to commit to the source repository.
>>> 
>>> As you probably know, the initial committers and mentors will form the
>>> initial PPMCs for the podling.
>>> Hopefully for day to day operations you should not need to have
>> distinction
>>> of committer vs mentors anymore.
>>> 
>>> You do not have to be listed as committer for the proposal.
>>> 
>>> - Henry
>>> 
>>>> On Tue, May 17, 2016 at 1:57 PM, Suneel Marthi <smarthi@apache.org>
>>> wrote:
>>> 
>>>> Thanks for having me as a mentor for PIO.  I would like to be added to
>>> the
>>>> initial list of committers and am looking to actively participate in
>> the
>>>> development too. I am not sure if my being a mentor automatically
>> grants
>>> me
>>>> the 'commit' karma.
>>>> 
>>>> Its already been suggested earlier in this thread by Roman and
>>>> Jean-Baptiste that the project needs to be decoupled from Spark and
>>>> integrated with Beam.  It would be good to reduce the reliance on
>>>> Spark-Submit from what I have seen of the project so far. But let's not
>>>> talk architecture and design here when the project's not in incubator
>>> yet.
>>>> :)
>>>> 
>>>> 
>>>> 
>>>> 
>>>> On Tue, May 17, 2016 at 4:09 PM, Henry Saputra <
>> henry.saputra@gmail.com>
>>>> wrote:
>>>> 
>>>>> Cool, this will make code grant process to be easier =)
>>>>> 
>>>>> The initial committers and mentors look great.
>>>>> I am sure more will come as contributions start pouring in to the
>>>> project.
>>>>> 
>>>>> Looking forward for the VOTE thread soon.
>>>>> 
>>>>> - Henry
>>>>> 
>>>>>> On Mon, May 16, 2016 at 12:07 PM, Simon Chan <simon@salesforce.com>
>>>>> wrote:
>>>>> 
>>>>>> Yes, it includes everyone who previously contributed code from
>>>>> PredictionIO
>>>>>> before the acquisition and still want to be involved in the
>> project.
>>>>>> 
>>>>>> We may have missed "Alex Merritt", going to add him to the list
>> soon.
>>>>>> 
>>>>>> Simon
>>>>>> 
>>>>>> 
>>>>>> On Mon, May 16, 2016 at 11:58 AM, Suneel Marthi <
>> smarthi@apache.org>
>>>>>> wrote:
>>>>>> 
>>>>>>> I do have a question about the proposed list of committers.
>>>>>>> 
>>>>>>> Does the list also include all of those folks who were with
>>>>> PredictionIO
>>>>>>> (and had contributed to the project) and then chose to leave
when
>>> PIO
>>>>> was
>>>>>>> acquired by Salesforce?
>>>>>>> 
>>>>>>> 
>>>>>>> 
>>>>>>> 
>>>>>>> On Mon, May 16, 2016 at 1:13 PM, Jean-Baptiste Onofré <
>>>> jb@nanthrax.net
>>>>>> 
>>>>>>> wrote:
>>>>>>> 
>>>>>>>> By the way, we have some discussion about integrating Zeppelin
>>> with
>>>>>> Beam
>>>>>>> ;)
>>>>>>>> 
>>>>>>>> Regards
>>>>>>>> JB
>>>>>>>> 
>>>>>>>>> On 05/15/2016 02:32 AM, Roman Shaposhnik wrote:
>>>>>>>>> 
>>>>>>>>> Super excited to see this proposal! This will finally
allow us
>>> to
>>>>> have
>>>>>>>>> an ASF managed
>>>>>>>>> backend for next generation data-driven apps that I see
>> emerging
>>>>> quite
>>>>>>>>> rapidly.
>>>>>>>>> 
>>>>>>>>> The proposal looks great to me (although I'd recommend
calling
>>>> Scala
>>>>>>>>> as an implementation
>>>>>>>>> language more prominently since it may attract additional
>>>> developers
>>>>>>>>> with affinity to it).
>>>>>>>>> 
>>>>>>>>> I do have two questions about technology:
>>>>>>>>>    1. do you think it would be possible to leverage Apache
>> Beam
>>>>>>>>> (incubating)
>>>>>>>>>        for abstracting away dependency on execution
>> frameworks?
>>>> My
>>>>>>>>> understanding
>>>>>>>>>        is that PredictionIO currently only run on Spark.
>>>>>>>>>    2. is there a potential integration with Apache Zeppelin
>>>>> possible?
>>>>>>>>> 
>>>>>>>>> Thanks,
>>>>>>>>> Roman.
>>>>>>>>> 
>>>>>>>>> On Fri, May 13, 2016 at 1:41 PM, Andrew Purtell <
>>>>> apurtell@apache.org>
>>>>>>>>> wrote:
>>>>>>>>> 
>>>>>>>>>> Greetings,
>>>>>>>>>> 
>>>>>>>>>> It is my pleasure to
>>>>>>>>>> 
>>>>>>>>>> propose the PredictionIO project for incubation at
the Apache
>>>>>> Software
>>>>>>>>>> Foundation.
>>>>>>>>>> 
>>>>>>>>>> PredictionIO is a
>>>>>>>>>> popular
>>>>>>>>>> open
>>>>>>>>>> 
>>>>>>>>>> source Machine Learning Server built on top of a
>>> state-of-the-art
>>>>>> open
>>>>>>>>>> source stack, including several Apache technologies,
that
>>>>>>>>>> 
>>>>>>>>>> enables developers to manage and deploy production-ready
>>>> predictive
>>>>>>>>>> services for various kinds of machine learning tasks
>>>>>>>>>> , with more than 400 production deployments around
the world
>>> and
>>>> a
>>>>>>>>>> growing
>>>>>>>>>> contributor community.
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>> The text of the proposal is included below and is
also
>>> available
>>>> at
>>>>>>>>>> https://wiki.apache.org/incubator/PredictionIO
>>>>>>>>>> 
>>>>>>>>>> Best regards,
>>>>>>>>>> Andrew Purtell
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>> = PredictionIO Proposal =
>>>>>>>>>> 
>>>>>>>>>> === Abstract ===
>>>>>>>>>> PredictionIO is an open source Machine Learning Server
built
>> on
>>>> top
>>>>>> of
>>>>>>>>>> state-of-the-art open source stack, that enables
developers
>> to
>>>>> manage
>>>>>>> and
>>>>>>>>>> deploy production-ready predictive services for various
kinds
>>> of
>>>>>>> machine
>>>>>>>>>> learning tasks.
>>>>>>>>>> 
>>>>>>>>>> === Proposal ===
>>>>>>>>>> The PredictionIO platform consists of the following
>> components:
>>>>>>>>>> 
>>>>>>>>>>  * PredictionIO framework - provides the machine
learning
>>> stack
>>>>> for
>>>>>>>>>>  building, evaluating and deploying engines with
machine
>>>> learning
>>>>>>>>>>  algorithms. It uses Apache Spark for processing.
>>>>>>>>>> 
>>>>>>>>>>  * Event Server - the machine learning analytics
layer for
>>>>> unifying
>>>>>>>>>> events
>>>>>>>>>>  from multiple platforms. It can use Apache HBase
or any
>> JDBC
>>>>>> backends
>>>>>>>>>>  as its data store.
>>>>>>>>>> 
>>>>>>>>>> The PredictionIO community also maintains a
>>>>>>>>>> 
>>>>>>>>>> Template Gallery, a place to
>>>>>>>>>> publish and download (free or proprietary) engine
templates
>> for
>>>>>>> different
>>>>>>>>>> types of machine learning applications, and is a
complemental
>>>> part
>>>>> of
>>>>>>> the
>>>>>>>>>> project. At this point we exclude the Template Gallery
from
>> the
>>>>>>> proposal,
>>>>>>>>>> as it has a separate set of contributors and we’re
not
>> familiar
>>>>> with
>>>>>> an
>>>>>>>>>> Apache approved mechanism to maintain such a gallery.
>>>>>>>>>> 
>>>>>>>>>> You can find the Template Gallery at
>>>>>> https://templates.prediction.io/
>>>>>>>>>> 
>>>>>>>>>> === Background ===
>>>>>>>>>> PredictionIO was started with a mission to democratize
and
>>> bring
>>>>>>> machine
>>>>>>>>>> learning to the masses.
>>>>>>>>>> 
>>>>>>>>>> Machine learning has traditionally been a luxury
for big
>>>> companies
>>>>>> like
>>>>>>>>>> Google, Facebook, and Netflix. There are ML libraries
and
>> tools
>>>>> lying
>>>>>>>>>> around the internet but the effort of putting them
all
>> together
>>>> as
>>>>> a
>>>>>>>>>> production-ready infrastructure is a very resource-intensive
>>> task
>>>>>> that
>>>>>>> is
>>>>>>>>>> remotely reachable by individuals or small businesses.
>>>>>>>>>> 
>>>>>>>>>> PredictionIO is a production-ready, full stack machine
>> learning
>>>>>> system
>>>>>>>>>> that
>>>>>>>>>> allows organizations of any scale to quickly deploy
machine
>>>>> learning
>>>>>>>>>> capabilities. It comes with official and
>> community-contributed
>>>>>> machine
>>>>>>>>>> learning engine templates that are easy to customize.
>>>>>>>>>> 
>>>>>>>>>> === Rationale ===
>>>>>>>>>> As usage and number of contributors to PredictionIO
has grown
>>>>> bigger
>>>>>>> and
>>>>>>>>>> more diverse, we have sought for an independent framework
for
>>> the
>>>>>>> project
>>>>>>>>>> to keep thriving. We believe the Apache foundation
is a great
>>>> fit.
>>>>>>>>>> Joining
>>>>>>>>>> Apache would ensure that tried and true processes
and
>>> procedures
>>>>> are
>>>>>> in
>>>>>>>>>> place for the growing number of organizations interested
in
>>>>>>> contributing
>>>>>>>>>> to PredictionIO. PredictionIO is also a good fit
for the
>> Apache
>>>>>>>>>> foundation.
>>>>>>>>>> PredictionIO was built on top of several Apache projects
>>> (HBase,
>>>>>> Spark,
>>>>>>>>>> Hadoop). We are familiar with the Apache process
and believe
>>> that
>>>>> the
>>>>>>>>>> democratic and meritocratic nature of the foundation
aligns
>>> with
>>>>> the
>>>>>>>>>> project goals.
>>>>>>>>>> 
>>>>>>>>>> === Initial Goals ===
>>>>>>>>>> The initial milestones will be to move the existing
codebase
>> to
>>>>>> Apache
>>>>>>>>>> and
>>>>>>>>>> integrate with the Apache development process. Once
this is
>>>>>>> accomplished,
>>>>>>>>>> we plan for incremental development and releases
that follow
>>> the
>>>>>> Apache
>>>>>>>>>> guidelines, as well as growing our developer and
user
>>>> communities.
>>>>>>>>>> 
>>>>>>>>>> === Current Status ===
>>>>>>>>>> PredictionIO has undergone nine minor releases and
many
>>> patches.
>>>>>>>>>> PredictionIO is being used in production by Salesforce.com
as
>>>> well
>>>>> as
>>>>>>>>>> many
>>>>>>>>>> other organizations and apps. The PredictionIO codebase
is
>>>>> currently
>>>>>>>>>> hosted at GitHub, which will form the basis of the
Apache git
>>>>>>> repository.
>>>>>>>>>> 
>>>>>>>>>> ==== Meritocracy ====
>>>>>>>>>> We plan to invest in supporting a meritocracy. We
will
>> discuss
>>>> the
>>>>>>>>>> requirements in an open forum. We intend to invite
additional
>>>>>>> developers
>>>>>>>>>> to participate. We will encourage and monitor community
>>>>> participation
>>>>>>> so
>>>>>>>>>> that privileges can be extended to those that contribute.
>>>>>>>>>> 
>>>>>>>>>> ==== Community ====
>>>>>>>>>> Acceptance into the Apache foundation would bolster
the
>> already
>>>>>> strong
>>>>>>>>>> user and developer community around PredictionIO.
That
>>> community
>>>>>>> includes
>>>>>>>>>> many contributors from various other companies, and
an active
>>>>> mailing
>>>>>>>>>> list
>>>>>>>>>> composed of hundreds of users.
>>>>>>>>>> 
>>>>>>>>>> ==== Core Developers ====
>>>>>>>>>> The core developers of our project are listed in
our
>>> contributors
>>>>> and
>>>>>>>>>> initial PPMC below. Though many are employed at
>> Salesforce.com,
>>>>> there
>>>>>>> are
>>>>>>>>>> also engineers from ActionML, and independent developers.
>>>>>>>>>> 
>>>>>>>>>> === Alignment ===
>>>>>>>>>> The ASF is the natural choice to host the PredictionIO
>> project
>>> as
>>>>> its
>>>>>>>>>> goal
>>>>>>>>>> is democratizing Machine Learning by making it more
easily
>>>>> accessible
>>>>>>> to
>>>>>>>>>> every user/developer. PredictionIO is built on top
of several
>>> top
>>>>>> level
>>>>>>>>>> Apache projects as outlined above.
>>>>>>>>>> 
>>>>>>>>>> === Known Risks ===
>>>>>>>>>> 
>>>>>>>>>> ==== Orphaned products ====
>>>>>>>>>> PredictionIO has a solid and growing community. It
is
>> deployed
>>> on
>>>>>>>>>> production environments by companies of all sizes
to run
>>> various
>>>>>> kinds
>>>>>>> of
>>>>>>>>>> predictive engines.
>>>>>>>>>> 
>>>>>>>>>> In addition to the community contribution to PredictionIO
>>>>> framework,
>>>>>>> the
>>>>>>>>>> community is also actively contributing new engines
to the
>>>> Template
>>>>>>>>>> Gallery as well as SDKs and documentation for the
project.
>>>>> Salesforce
>>>>>>> is
>>>>>>>>>> committed to utilize and advance the PredictionIO
code base
>> and
>>>>>> support
>>>>>>>>>> its user community.
>>>>>>>>>> 
>>>>>>>>>> ==== Inexperience with Open Source ====
>>>>>>>>>> PredictionIO has existed as a healthy open source
project for
>>>>> almost
>>>>>>> two
>>>>>>>>>> years and is the most starred Scala project on GitHub.
All of
>>> the
>>>>>>>>>> proposed
>>>>>>>>>> committers have contributed to ASF and Linux Foundation
open
>>>> source
>>>>>>>>>> projects. Several current committers on Apache projects
and
>>>> Apache
>>>>>>>>>> Members
>>>>>>>>>> are involved in this proposal and intend to provide
>> mentorship.
>>>>>>>>>> 
>>>>>>>>>> ==== Homogeneous Developers ====
>>>>>>>>>> The initial list of committers includes developers
from
>> several
>>>>>>>>>> institutions, including Salesforce, ActionML, Channel4,
USC
>> as
>>>> well
>>>>>> as
>>>>>>>>>> unaffiliated developers.
>>>>>>>>>> 
>>>>>>>>>> ==== Reliance on Salaried Developers ====
>>>>>>>>>> Like most open source projects, PredictionIO receives
>>> substantial
>>>>>>> support
>>>>>>>>>> from salaried developers. PredictionIO development
is
>> partially
>>>>>>> supported
>>>>>>>>>> by Salesforce.com, but there are many contributors
from
>> various
>>>>> other
>>>>>>>>>> companies, and an active mailing list composed of
hundreds of
>>>>> users.
>>>>>> We
>>>>>>>>>> will continue our efforts to ensure stewardship of
the
>> project
>>> to
>>>>> be
>>>>>>>>>> independent of salaried developers by meritocratically
>>> promoting
>>>>>> those
>>>>>>>>>> contributors to committers.
>>>>>>>>>> 
>>>>>>>>>> ==== Relationships with Other Apache Product ====
>>>>>>>>>> PredictionIO relies heavily on top level apache projects
such
>>> as
>>>>>> Apache
>>>>>>>>>> Spark, HBase and Hadoop. However it brings a distinguished
>>>>>>> functionality,
>>>>>>>>>> rather than just an abstraction - Machine Learning
in a
>>>>> plug-and-play
>>>>>>>>>> fashion.
>>>>>>>>>> 
>>>>>>>>>> Compared to Apache Mahout, which focuses on the development
>> of
>>> a
>>>>> wide
>>>>>>>>>> variety of algorithms, PredictionIO offers a platform
to
>> manage
>>>> the
>>>>>>> whole
>>>>>>>>>> machine learning workflow, including data collection,
data
>>>>>> preparation,
>>>>>>>>>> modeling, deployment and management of predictive
services in
>>>>>>> production
>>>>>>>>>> environments.
>>>>>>>>>> 
>>>>>>>>>> ==== An Excessive Fascination with the Apache Brand
====
>>>>>>>>>> PredictionIO is already a widely known open source
project.
>>> This
>>>>>>> proposal
>>>>>>>>>> is not for the purpose of generating publicity. Rather,
the
>>>> primary
>>>>>>>>>> benefits to joining Apache are those outlined in
the
>> Rationale
>>>>>> section.
>>>>>>>>>> 
>>>>>>>>>> === Documentation ===
>>>>>>>>>> PredictionIO boasts rich and live documentation,
included in
>>> the
>>>>> code
>>>>>>>>>> repo
>>>>>>>>>> (docs/manual directory), is built with Middleman,
and
>> publicly
>>>>> hosted
>>>>>>> at
>>>>>>>>>> https://docs.prediction.io
>>>>>>>>>> 
>>>>>>>>>> === Initial Source and Intellectual Property Submission
Plan
>>> ===
>>>>>>>>>> Currently, the PredictionIO codebase is distributed
under the
>>>>> Apache
>>>>>>> 2.0
>>>>>>>>>> License and hosted on GitHub:
>>>>>>>>>> https://github.com/PredictionIO/PredictionIO
>>>>>>>>>> 
>>>>>>>>>> === External Dependencies ===
>>>>>>>>>> PredictionIO has the following external dependencies:
>>>>>>>>>>  * Apache Hadoop 2.4.0 (optional, required only if
YARN and
>>> HDFS
>>>>> are
>>>>>>>>>> needed)
>>>>>>>>>>  * Apache Spark 1.3.0 for Hadoop 2.4
>>>>>>>>>>  * Java SE Development Kit 8
>>>>>>>>>>  * and one of the following sets:
>>>>>>>>>> 
>>>>>>>>>>    * PostgreSQL 9.1
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>> or
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>> * MySQL 5.1
>>>>>>>>>> 
>>>>>>>>>>  or
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>>  * Apache HBase 0.98.6
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>> * Elasticsearch 1.4.0
>>>>>>>>>> 
>>>>>>>>>> Upon acceptance to the incubator, we would begin
a thorough
>>>>> analysis
>>>>>> of
>>>>>>>>>> all transitive dependencies to verify this information
and
>>>>> introduce
>>>>>>>>>> license checking into the build and release process
by
>>>> integrating
>>>>>> with
>>>>>>>>>> Apache RAT.
>>>>>>>>>> 
>>>>>>>>>> === Cryptography ===
>>>>>>>>>> PredictionIO does not include cryptographic code.
We utilize
>>>>> standard
>>>>>>>>>> JCE and JSSE APIs provided by the Java Runtime Environment.
>>>>>>>>>> 
>>>>>>>>>> === Required Resources ===
>>>>>>>>>> We request that following resources be created for
the
>> project
>>> to
>>>>> use
>>>>>>>>>> 
>>>>>>>>>> ==== Mailing lists ====
>>>>>>>>>> 
>>>>>>>>>> predictionio-private@incubator.apache.org (with moderated
>>>>>>> subscriptions)
>>>>>>>>>> 
>>>>>>>>>> predictionio-dev
>>>>>>>>>> 
>>>>>>>>>> predictionio-user
>>>>>>>>>> 
>>>>>>>>>> predictionio-commits
>>>>>>>>>> 
>>>>>>>>>> We will migrate the existing PredictionIO mailing
lists.
>>>>>>>>>> 
>>>>>>>>>> ==== Git repository ====
>>>>>>>>>> The PredictionIO team would like to use Git for source
>> control,
>>>> due
>>>>>> to
>>>>>>>>>> our
>>>>>>>>>> current use of GitHub.
>>>>>>>>>> 
>>>>>>>>>> git://git.apache.org/incubator-predictionio
>>>>>>>>>> 
>>>>>>>>>> ==== Documentation ====
>>>>>>>>>> https://predictionio.incubator.apache.org/docs/
>>>>>>>>>> 
>>>>>>>>>> ==== JIRA instance ====
>>>>>>>>>> PredictionIO currently uses the GitHub issue tracking
system
>>>>>> associated
>>>>>>>>>> with its repository:
>>>>>>> https://github.com/PredictionIO/PredictionIO/issues
>>>>>>>>>> .
>>>>>>>>>> We will migrate to Apache JIRA.
>>>>>>>>>> 
>>>>>>>>>> JIRA PREDICTIONIO
>>>>>>>>>> https://issues.apache.org/jira/browse/PREDICTIONIO
>>>>>>>>>> 
>>>>>>>>>> ==== Other Resources ====
>>>>>>>>>> * TravisCI for builds and test running.
>>>>>>>>>> 
>>>>>>>>>> * PredictionIO's documentation, included in the code
repo
>>>>>> (docs/manual
>>>>>>>>>> directory), is built with Middleman and publicly
hosted
>>>>>>>>>> https://docs.prediction.io
>>>>>>>>>> 
>>>>>>>>>> * A blog to drive adoption and excitement at
>>>>>>> https://blog.prediction.io
>>>>>>>>>> 
>>>>>>>>>> === Initial Committers ===
>>>>>>>>>> 
>>>>>>>>>> * Pat Ferrell
>>>>>>>>>> 
>>>>>>>>>> * Tamas Jambor
>>>>>>>>>> 
>>>>>>>>>> * Justin Yip
>>>>>>>>>> 
>>>>>>>>>> * Xusen Yin
>>>>>>>>>> 
>>>>>>>>>> * Lee Moon Soo
>>>>>>>>>> 
>>>>>>>>>> * Donald Szeto
>>>>>>>>>> 
>>>>>>>>>> * Kenneth Chan
>>>>>>>>>> 
>>>>>>>>>> * Tom Chan
>>>>>>>>>> 
>>>>>>>>>> * Simon Chan
>>>>>>>>>> 
>>>>>>>>>> * Marco Vivero
>>>>>>>>>> 
>>>>>>>>>> * Matthew Tovbin
>>>>>>>>>> 
>>>>>>>>>> * Yevgeny Khodorkovsky
>>>>>>>>>> 
>>>>>>>>>> * Felipe Oliveira
>>>>>>>>>> 
>>>>>>>>>> * Vitaly Gordon
>>>>>>>>>> 
>>>>>>>>>> === Affiliations ===
>>>>>>>>>> 
>>>>>>>>>> * Pat Ferrell - ActionML
>>>>>>>>>> 
>>>>>>>>>> * Tamas Jambor - Channel4
>>>>>>>>>> 
>>>>>>>>>> * Justin Yip - independent
>>>>>>>>>> 
>>>>>>>>>> * Xusen Yin - USC
>>>>>>>>>> 
>>>>>>>>>> * Lee Moon Soo - NFLabs
>>>>>>>>>> 
>>>>>>>>>> * Donald Szeto - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Kenneth Chan - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Tom Chan - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Simon Chan - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Marco Vivero - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Matthew Tovbin - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Yevgeny Khodorkovsky - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Felipe Oliveira - Salesforce
>>>>>>>>>> 
>>>>>>>>>> * Vitaly Gordon - Salesforce
>>>>>>>>>> 
>>>>>>>>>> === Sponsors ===
>>>>>>>>>> 
>>>>>>>>>> ==== Champion ====
>>>>>>>>>> 
>>>>>>>>>> Andrew Purtell <apurtell at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> ==== Nominated Mentors ====
>>>>>>>>>> 
>>>>>>>>>> * Andrew Purtell <apurtell at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> * James Taylor <jtaylor at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> * Lars Hofhansl <larsh at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> * Suneel Marthi <smarthi at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> * Xiangrui Meng <meng at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> * Luciano Resende <lresende at apache dot org>
>>>>>>>>>> 
>>>>>>>>>> ==== Sponsoring Entity ====
>>>>>>>>>> 
>>>>>>>>>> Apache Incubator PMC
>>>>> ---------------------------------------------------------------------
>>>>>>>>> To unsubscribe, e-mail:
>>> general-unsubscribe@incubator.apache.org
>>>>>>>>> For additional commands, e-mail:
>>>> general-help@incubator.apache.org
>>>>>>>> --
>>>>>>>> Jean-Baptiste Onofré
>>>>>>>> jbonofre@apache.org
>>>>>>>> http://blog.nanthrax.net
>>>>>>>> Talend - http://www.talend.com
>>>> ---------------------------------------------------------------------
>>>>>>>> To unsubscribe, e-mail:
>> general-unsubscribe@incubator.apache.org
>>>>>>>> For additional commands, e-mail:
>>> general-help@incubator.apache.org
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