+ 1 (non-binding) Regards, Sandeep
On Wed, May 25, 2016 at 10:38 AM, Paul Fremantle <pzf...@gmail.com> wrote: > +1 (binding) > Paul > > On Wed, May 25, 2016 at 5:12 AM, Tsuyoshi Ozawa <oz...@apache.org> wrote: > > > +1 (non-binding) > > - Tsuyoshi > > > > On Wed, May 25, 2016 at 1:00 PM, Reynold Xin <r...@databricks.com> > wrote: > > > +1 (binding) > > > > > > > > > On Mon, May 23, 2016 at 3:22 PM, Andrew Purtell <apurt...@apache.org> > > wrote: > > > > > >> Since discussion on the matter of PredictionIO has died down, I would > > like > > >> to call a VOTE > > >> on accepting PredictionIO into the Apache Incubator. > > >> > > >> Proposal: https://wiki.apache.org/incubator/PredictionIO > > >> > > >> [ ] +1 Accept PredictionIO into the Apache Incubator > > >> [ ] +0 Abstain > > >> [ ] -1 Do not accept PredictionIO into the Apache Incubator, because > ... > > >> > > >> This vote will be open for at least 72 hours. > > >> > > >> My vote is +1 (binding) > > >> > > >> -- > > >> > > >> 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. > > >> > > >> 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 at > > >> 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 > > >> Alex Merritt > > >> > > >> 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 > > >> Alex Merritt - ActionML > > >> > > >> 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 > > >> > > >> > > >> -- > > >> Best regards, > > >> > > >> - Andy > > >> > > >> Problems worthy of attack prove their worth by hitting back. - Piet > Hein > > >> (via Tom White) > > >> > > > > --------------------------------------------------------------------- > > To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org > > For additional commands, e-mail: general-h...@incubator.apache.org > > > > > > > -- > Paul Fremantle > Co-Founder and CTO, WSO2 > Member of the Apache Software Foundation > OASIS WS-RX TC Co-chair > > blog: http://pzf.fremantle.org > twitter: @pzfreo >
