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 <smar...@apache.org> wrote:

> Thanks Henry
>
> On Tue, May 17, 2016 at 5:11 PM, Henry Saputra <henry.sapu...@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 <smar...@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.sapu...@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 <si...@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 <
> smar...@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 <
> > > j...@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 <
> > > > apurt...@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-priv...@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-unsubscr...@incubator.apache.org
> > > > > > >> For additional commands, e-mail:
> > > general-h...@incubator.apache.org
> > > > > > >>
> > > > > > >>
> > > > > > > --
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