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From Mayank Bansal <maban...@gmail.com>
Subject Re: [VOTE] Accept Beam into the Apache Incubator
Date Thu, 28 Jan 2016 18:42:20 GMT
+1 (non-binding)

Thanks,
Mayank

On Thu, Jan 28, 2016 at 10:23 AM, Seetharam Venkatesh <
venkatesh@innerzeal.com> wrote:

> +1 (binding).
>
> Thanks!
>
> On Thu, Jan 28, 2016 at 10:19 AM Ted Dunning <ted.dunning@gmail.com>
> wrote:
>
> > +1
> >
> >
> >
> > On Thu, Jan 28, 2016 at 10:02 AM, John D. Ament <johndament@apache.org>
> > wrote:
> >
> > > +1
> > >
> > > On Thu, Jan 28, 2016 at 9:28 AM Jean-Baptiste Onofré <jb@nanthrax.net>
> > > wrote:
> > >
> > > > Hi,
> > > >
> > > > the Beam proposal (initially Dataflow) was proposed last week.
> > > >
> > > > The complete discussion thread is available here:
> > > >
> > > >
> > > >
> > >
> >
> http://mail-archives.apache.org/mod_mbox/incubator-general/201601.mbox/%3CCA%2B%3DKJmvj4wyosNTXVpnsH8PhS7jEyzkZngc682rGgZ3p28L42Q%40mail.gmail.com%3E
> > > >
> > > > As reminder the BeamProposal is here:
> > > >
> > > > https://wiki.apache.org/incubator/BeamProposal
> > > >
> > > > Regarding all the great feedbacks we received on the mailing list, we
> > > > think it's time to call a vote to accept Beam into the Incubator.
> > > >
> > > > Please cast your vote to:
> > > > [] +1 - accept Apache Beam as a new incubating project
> > > > []  0 - not sure
> > > > [] -1 - do not accept the Apache Beam project (because: ...)
> > > >
> > > > Thanks,
> > > > Regards
> > > > JB
> > > > ----
> > > > ## page was renamed from DataflowProposal
> > > > = Apache Beam =
> > > >
> > > > == Abstract ==
> > > >
> > > > Apache Beam is an open source, unified model and set of
> > > > language-specific SDKs for defining and executing data processing
> > > > workflows, and also data ingestion and integration flows, supporting
> > > > Enterprise Integration Patterns (EIPs) and Domain Specific Languages
> > > > (DSLs). Dataflow pipelines simplify the mechanics of large-scale
> batch
> > > > and streaming data processing and can run on a number of runtimes
> like
> > > > Apache Flink, Apache Spark, and Google Cloud Dataflow (a cloud
> > service).
> > > > Beam also brings DSL in different languages, allowing users to easily
> > > > implement their data integration processes.
> > > >
> > > > == Proposal ==
> > > >
> > > > Beam is a simple, flexible, and powerful system for distributed data
> > > > processing at any scale. Beam provides a unified programming model, a
> > > > software development kit to define and construct data processing
> > > > pipelines, and runners to execute Beam pipelines in several runtime
> > > > engines, like Apache Spark, Apache Flink, or Google Cloud Dataflow.
> > Beam
> > > > can be used for a variety of streaming or batch data processing goals
> > > > including ETL, stream analysis, and aggregate computation. The
> > > > underlying programming model for Beam provides MapReduce-like
> > > > parallelism, combined with support for powerful data windowing, and
> > > > fine-grained correctness control.
> > > >
> > > > == Background ==
> > > >
> > > > Beam started as a set of Google projects (Google Cloud Dataflow)
> > focused
> > > > on making data processing easier, faster, and less costly. The Beam
> > > > model is a successor to MapReduce, FlumeJava, and Millwheel inside
> > > > Google and is focused on providing a unified solution for batch and
> > > > stream processing. These projects on which Beam is based have been
> > > > published in several papers made available to the public:
> > > >
> > > >   * MapReduce - http://research.google.com/archive/mapreduce.html
> > > >   * Dataflow model  -
> http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf
> > > >   * FlumeJava - http://research.google.com/pubs/pub35650.html
> > > >   * MillWheel - http://research.google.com/pubs/pub41378.html
> > > >
> > > > Beam was designed from the start to provide a portable programming
> > > > layer. When you define a data processing pipeline with the Beam
> model,
> > > > you are creating a job which is capable of being processed by any
> > number
> > > > of Beam processing engines. Several engines have been developed to
> run
> > > > Beam pipelines in other open source runtimes, including a Beam runner
> > > > for Apache Flink and Apache Spark. There is also a “direct runner”,
> for
> > > > execution on the developer machine (mainly for dev/debug purposes).
> > > > Another runner allows a Beam program to run on a managed service,
> > Google
> > > > Cloud Dataflow, in Google Cloud Platform. The Dataflow Java SDK is
> > > > already available on GitHub, and independent from the Google Cloud
> > > > Dataflow service. Another Python SDK is currently in active
> > development.
> > > >
> > > > In this proposal, the Beam SDKs, model, and a set of runners will be
> > > > submitted as an OSS project under the ASF. The runners which are a
> part
> > > > of this proposal include those for Spark (from Cloudera), Flink (from
> > > > data Artisans), and local development (from Google); the Google Cloud
> > > > Dataflow service runner is not included in this proposal. Further
> > > > references to Beam will refer to the Dataflow model, SDKs, and
> runners
> > > > which are a part of this proposal (Apache Beam) only. The initial
> > > > submission will contain the already-released Java SDK; Google intends
> > to
> > > > submit the Python SDK later in the incubation process. The Google
> Cloud
> > > > Dataflow service will continue to be one of many runners for Beam,
> > built
> > > > on Google Cloud Platform, to run Beam pipelines. Necessarily, Cloud
> > > > Dataflow will develop against the Apache project additions, updates,
> > and
> > > > changes. Google Cloud Dataflow will become one user of Apache Beam
> and
> > > > will participate in the project openly and publicly.
> > > >
> > > > The Beam programming model has been designed with simplicity,
> > > > scalability, and speed as key tenants. In the Beam model, you only
> need
> > > > to think about four top-level concepts when constructing your data
> > > > processing job:
> > > >
> > > >   * Pipelines - The data processing job made of a series of
> > computations
> > > > including input, processing, and output
> > > >   * PCollections - Bounded (or unbounded) datasets which represent
> the
> > > > input, intermediate and output data in pipelines
> > > >   * PTransforms - A data processing step in a pipeline in which one
> or
> > > > more PCollections are an input and output
> > > >   * I/O Sources and Sinks - APIs for reading and writing data which
> are
> > > > the roots and endpoints of the pipeline
> > > >
> > > > == Rationale ==
> > > >
> > > > With Google Dataflow, Google intended to develop a framework which
> > > > allowed developers to be maximally productive in defining the
> > > > processing, and then be able to execute the program at various levels
> > of
> > > > latency/cost/completeness without re-architecting or re-writing it.
> > This
> > > > goal was informed by Google’s past experience  developing several
> > > > models, frameworks, and tools useful for large-scale and distributed
> > > > data processing. While Google has previously published papers
> > describing
> > > > some of its technologies, Google decided to take a different approach
> > > > with Dataflow. Google open-sourced the SDK and model alongside
> > > > commercialization of the idea and ahead of publishing papers on the
> > > > topic. As a result, a number of open source runtimes exist for
> > Dataflow,
> > > > such as the Apache Flink and Apache Spark runners.
> > > >
> > > > We believe that submitting Beam as an Apache project will provide an
> > > > immediate, worthwhile, and substantial contribution to the open
> source
> > > > community. As an incubating project, we believe Dataflow will have a
> > > > better opportunity to provide a meaningful contribution to OSS and
> also
> > > > integrate with other Apache projects.
> > > >
> > > > In the long term, we believe Beam can be a powerful abstraction layer
> > > > for data processing. By providing an abstraction layer for data
> > > > pipelines and processing, data workflows can be increasingly
> portable,
> > > > resilient to breaking changes in tooling, and compatible across many
> > > > execution engines, runtimes, and open source projects.
> > > >
> > > > == Initial Goals ==
> > > >
> > > > We are breaking our initial goals into immediate (< 2 months),
> > > > short-term (2-4 months), and intermediate-term (> 4 months).
> > > >
> > > > Our immediate goals include the following:
> > > >
> > > >   * Plan for reconciling the Dataflow Java SDK and various runners
> into
> > > > one project
> > > >   * Plan for refactoring the existing Java SDK for better
> extensibility
> > > > by SDK and runner writers
> > > >   * Validating all dependencies are ASL 2.0 or compatible
> > > >   * Understanding and adapting to the Apache development process
> > > >
> > > > Our short-term goals include:
> > > >
> > > >   * Moving the newly-merged lists, and build utilities to Apache
> > > >   * Start refactoring codebase and move code to Apache Git repo
> > > >   * Continue development of new features, functions, and fixes in the
> > > > Dataflow Java SDK, and Dataflow runners
> > > >   * Cleaning up the Dataflow SDK sources and crafting a roadmap and
> > plan
> > > > for how to include new major ideas, modules, and runtimes
> > > >   * Establishment of easy and clear build/test framework for Dataflow
> > > > and associated runtimes; creation of testing, rollback, and
> validation
> > > > policy
> > > >   * Analysis and design for work needed to make Beam a better data
> > > > processing abstraction layer for multiple open source frameworks and
> > > > environments
> > > >
> > > > Finally, we have a number of intermediate-term goals:
> > > >
> > > >   * Roadmapping, planning, and execution of integrations with other
> OSS
> > > > and non-OSS projects/products
> > > >   * Inclusion of additional SDK for Python, which is under active
> > > > development
> > > >
> > > > == Current Status ==
> > > >
> > > > === Meritocracy ===
> > > >
> > > > Dataflow was initially developed based on ideas from many employees
> > > > within Google. As an ASL OSS project on GitHub, the Dataflow SDK has
> > > > received contributions from data Artisans, Cloudera Labs, and other
> > > > individual developers. As a project under incubation, we are
> committed
> > > > to expanding our effort to build an environment which supports a
> > > > meritocracy. We are focused on engaging the community and other
> related
> > > > projects for support and contributions. Moreover, we are committed to
> > > > ensure contributors and committers to Dataflow come from a broad mix
> of
> > > > organizations through a merit-based decision process during
> incubation.
> > > > We believe strongly in the Beam model and are committed to growing an
> > > > inclusive community of Beam contributors.
> > > >
> > > > === Community ===
> > > >
> > > > The core of the Dataflow Java SDK has been developed by Google for
> use
> > > > with Google Cloud Dataflow. Google has active community engagement in
> > > > the SDK GitHub repository
> > > > (https://github.com/GoogleCloudPlatform/DataflowJavaSDK), on Stack
> > > > Overflow
> > > > (http://stackoverflow.com/questions/tagged/google-cloud-dataflow)
> and
> > > > has had contributions from a number of organizations and indivuduals.
> > > >
> > > > Everyday, Cloud Dataflow is actively used by a number of
> organizations
> > > > and institutions for batch and stream processing of data. We believe
> > > > acceptance will allow us to consolidate existing Dataflow-related
> work,
> > > > grow the Dataflow community, and deepen connections between Dataflow
> > and
> > > > other open source projects.
> > > >
> > > > === Core Developers ===
> > > >
> > > > The core developers for Dataflow and the Dataflow runners are:
> > > >
> > > >   * Frances Perry
> > > >   * Tyler Akidau
> > > >   * Davor Bonaci
> > > >   * Luke Cwik
> > > >   * Ben Chambers
> > > >   * Kenn Knowles
> > > >   * Dan Halperin
> > > >   * Daniel Mills
> > > >   * Mark Shields
> > > >   * Craig Chambers
> > > >   * Maximilian Michels
> > > >   * Tom White
> > > >   * Josh Wills
> > > >   * Robert Bradshaw
> > > >
> > > > === Alignment ===
> > > >
> > > > The Beam SDK can be used to create Beam pipelines which can be
> executed
> > > > on Apache Spark or Apache Flink. Beam is also related to other Apache
> > > > projects, such as Apache Crunch. We plan on expanding functionality
> for
> > > > Beam runners, support for additional domain specific languages, and
> > > > increased portability so Beam is a powerful abstraction layer for
> data
> > > > processing.
> > > >
> > > > == Known Risks ==
> > > >
> > > > === Orphaned Products ===
> > > >
> > > > The Dataflow SDK is presently used by several organizations, from
> small
> > > > startups to Fortune 100 companies, to construct production pipelines
> > > > which are executed in Google Cloud Dataflow. Google has a long-term
> > > > commitment to advance the Dataflow SDK; moreover, Dataflow is seeing
> > > > increasing interest, development, and adoption from organizations
> > > > outside of Google.
> > > >
> > > > === Inexperience with Open Source ===
> > > >
> > > > Google believes strongly in open source and the exchange of
> information
> > > > to advance new ideas and work. Examples of this commitment are active
> > > > OSS projects such as Chromium (https://www.chromium.org) and
> > Kubernetes
> > > > (http://kubernetes.io/). With Dataflow, we have tried to be
> > increasingly
> > > > open and forward-looking; we have published a paper in the VLDB
> > > > conference describing the Dataflow model
> > > > (http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf) and were quick to
> > > > release the Dataflow SDK as open source software with the launch of
> > > > Cloud Dataflow. Our submission to the Apache Software Foundation is a
> > > > logical extension of our commitment to open source software.
> > > >
> > > > === Homogeneous Developers ===
> > > >
> > > > The majority of committers in this proposal belong to Google due to
> the
> > > > fact that Dataflow has emerged from several internal Google projects.
> > > > This proposal also includes committers outside of Google who are
> > > > actively involved with other Apache projects, such as Hadoop, Flink,
> > and
> > > > Spark.  We expect our entry into incubation will allow us to expand
> the
> > > > number of individuals and organizations participating in Dataflow
> > > > development. Additionally, separation of the Dataflow SDK from Google
> > > > Cloud Dataflow allows us to focus on the open source SDK and model
> and
> > > > do what is best for this project.
> > > >
> > > > === Reliance on Salaried Developers ===
> > > >
> > > > The Dataflow SDK and Dataflow runners have been developed primarily
> by
> > > > salaried developers supporting the Google Cloud Dataflow project.
> While
> > > > the Dataflow SDK and Cloud Dataflow have been developed by different
> > > > teams (and this proposal would reinforce that separation) we expect
> our
> > > > initial set of developers will still primarily be salaried.
> > Contribution
> > > > has not been exclusively from salaried developers, however. For
> > example,
> > > > the contrib directory of the Dataflow SDK
> > > > (
> > > >
> > >
> >
> https://github.com/GoogleCloudPlatform/DataflowJavaSDK/tree/master/contrib
> > > > )
> > > > contains items from free-time contributors. Moreover, seperate
> > projects,
> > > > such as ScalaFlow (https://github.com/darkjh/scalaflow) have been
> > > > created around the Dataflow model and SDK. We expect our reliance on
> > > > salaried developers will decrease over time during incubation.
> > > >
> > > > === Relationship with other Apache products ===
> > > >
> > > > Dataflow directly interoperates with or utilizes several existing
> > Apache
> > > > projects.
> > > >
> > > >   * Build
> > > >    * Apache Maven
> > > >   * Data I/O, Libraries
> > > >    * Apache Avro
> > > >    * Apache Commons
> > > >   * Dataflow runners
> > > >    * Apache Flink
> > > >    * Apache Spark
> > > >
> > > > Beam when used in batch mode shares similarities with Apache Crunch;
> > > > however, Beam is focused on a model, SDK, and abstraction layer
> beyond
> > > > Spark and Hadoop (MapReduce.) One key goal of Beam is to provide an
> > > > intermediate abstraction layer which can easily be implemented and
> > > > utilized across several different processing frameworks.
> > > >
> > > > === An excessive fascination with the Apache brand ===
> > > >
> > > > With this proposal we are not seeking attention or publicity. Rather,
> > we
> > > > firmly believe in the Beam model, SDK, and the ability to make Beam a
> > > > powerful yet simple framework for data processing. While the Dataflow
> > > > SDK and model have been open source, we believe putting code on
> GitHub
> > > > can only go so far. We see the Apache community, processes, and
> mission
> > > > as critical for ensuring the Beam SDK and model are truly
> > > > community-driven, positively impactful, and innovative open source
> > > > software. While Google has taken a number of steps to advance its
> > > > various open source projects, we believe Beam is a great fit for the
> > > > Apache Software Foundation due to its focus on data processing and
> its
> > > > relationships to existing ASF projects.
> > > >
> > > > == Documentation ==
> > > >
> > > > The following documentation is relevant to this proposal. Relevant
> > > > portion of the documentation will be contributed to the Apache Beam
> > > > project.
> > > >
> > > >   * Dataflow website: https://cloud.google.com/dataflow
> > > >   * Dataflow programming model:
> > > > https://cloud.google.com/dataflow/model/programming-model
> > > >   * Codebases
> > > >    * Dataflow Java SDK:
> > > > https://github.com/GoogleCloudPlatform/DataflowJavaSDK
> > > >    * Flink Dataflow runner:
> > > https://github.com/dataArtisans/flink-dataflow
> > > >    * Spark Dataflow runner:
> https://github.com/cloudera/spark-dataflow
> > > >   * Dataflow Java SDK issue tracker:
> > > > https://github.com/GoogleCloudPlatform/DataflowJavaSDK/issues
> > > >   * google-cloud-dataflow tag on Stack Overflow:
> > > > http://stackoverflow.com/questions/tagged/google-cloud-dataflow
> > > >
> > > > == Initial Source ==
> > > >
> > > > The initial source for Beam which we will submit to the Apache
> > > > Foundation will include several related projects which are currently
> > > > hosted on the GitHub repositories:
> > > >
> > > >   * Dataflow Java SDK
> > > > (https://github.com/GoogleCloudPlatform/DataflowJavaSDK)
> > > >   * Flink Dataflow runner (
> > > https://github.com/dataArtisans/flink-dataflow)
> > > >   * Spark Dataflow runner (
> https://github.com/cloudera/spark-dataflow)
> > > >
> > > > These projects have always been Apache 2.0 licensed. We intend to
> > bundle
> > > > all of these repositories since they are all complimentary and should
> > be
> > > > maintained in one project. Prior to our submission, we will combine
> all
> > > > of these projects into a new git repository.
> > > >
> > > > == Source and Intellectual Property Submission Plan ==
> > > >
> > > > The source for the Dataflow SDK and the three runners (Spark, Flink,
> > > > Google Cloud Dataflow) are already licensed under an Apache 2
> license.
> > > >
> > > >   * Dataflow SDK -
> > > >
> > >
> >
> https://github.com/GoogleCloudPlatform/DataflowJavaSDK/blob/master/LICENSE
> > > >   * Flink runner -
> > > > https://github.com/dataArtisans/flink-dataflow/blob/master/LICENSE
> > > >   * Spark runner -
> > > > https://github.com/cloudera/spark-dataflow/blob/master/LICENSE
> > > >
> > > > Contributors to the Dataflow SDK have also signed the Google
> Individual
> > > > Contributor License Agreement
> > > > (https://cla.developers.google.com/about/google-individual) in order
> > to
> > > > contribute to the project.
> > > >
> > > > With respect to trademark rights, Google does not hold a trademark on
> > > > the phrase “Dataflow.” Based on feedback and guidance we receive
> during
> > > > the incubation process, we are open to renaming the project if
> > necessary
> > > > for trademark or other concerns.
> > > >
> > > > == External Dependencies ==
> > > >
> > > > All external dependencies are licensed under an Apache 2.0 or
> > > > Apache-compatible license. As we grow the Beam community we will
> > > > configure our build process to require and validate all contributions
> > > > and dependencies are licensed under the Apache 2.0 license or are
> under
> > > > an Apache-compatible license.
> > > >
> > > > == Required Resources ==
> > > >
> > > > === Mailing Lists ===
> > > >
> > > > We currently use a mix of mailing lists. We will migrate our existing
> > > > mailing lists to the following:
> > > >
> > > >   * dev@beam.incubator.apache.org
> > > >   * user@beam.incubator.apache.org
> > > >   * private@beam.incubator.apache.org
> > > >   * commits@beam.incubator.apache.org
> > > >
> > > > === Source Control ===
> > > >
> > > > The Dataflow team currently uses Git and would like to continue to do
> > > > so. We request a Git repository for Beam with mirroring to GitHub
> > > enabled.
> > > >
> > > >   * https://git-wip-us.apache.org/repos/asf/incubator-beam.git
> > > >
> > > > === Issue Tracking ===
> > > >
> > > > We request the creation of an Apache-hosted JIRA. The Dataflow
> project
> > > > is currently using both a public GitHub issue tracker and internal
> > > > Google issue tracking. We will migrate and combine from these two
> > > > sources to the Apache JIRA.
> > > >
> > > >   * Jira ID: BEAM
> > > >
> > > > == Initial Committers ==
> > > >
> > > >   * Aljoscha Krettek        [aljoscha@apache.org]
> > > >   * Amit Sela               [amitsela33@gmail.com]
> > > >   * Ben Chambers            [bchambers@google.com]
> > > >   * Craig Chambers          [chambers@google.com]
> > > >   * Dan Halperin            [dhalperi@google.com]
> > > >   * Davor Bonaci            [davor@google.com]
> > > >   * Frances Perry           [fjp@google.com]
> > > >   * James Malone            [jamesmalone@google.com]
> > > >   * Jean-Baptiste Onofré    [jbonofre@apache.org]
> > > >   * Josh Wills              [jwills@apache.org]
> > > >   * Kostas Tzoumas          [kostas@data-artisans.com]
> > > >   * Kenneth Knowles         [klk@google.com]
> > > >   * Luke Cwik               [lcwik@google.com]
> > > >   * Maximilian Michels      [mxm@apache.org]
> > > >   * Stephan Ewen            [stephan@data-artisans.com]
> > > >   * Tom White               [tom@cloudera.com]
> > > >   * Tyler Akidau            [takidau@google.com]
> > > >   * Robert Bradshaw         [robertwb@google.com]
> > > >
> > > > == Additional Interested Contributors ==
> > > >
> > > >   * Debo Dutta              [dedutta@cisco.com]
> > > >   * Henry Saputra           [hsaputra@apache.org]
> > > >   * Taylor Goetz            [ptgoetz@gmail.com]
> > > >   * James Carman            [james@carmanconsulting.com]
> > > >   * Joe Witt                [joewitt@apache.org]
> > > >   * Vaibhav Gumashta        [vgumashta@hortonworks.com]
> > > >   * Prasanth Jayachandran   [pjayachandran@hortonworks.com]
> > > >   * Johan Edstrom           [seijoed@gmail.com]
> > > >   * Hugo Louro              [hmclouro@gmail.com]
> > > >   * Krzysztof Sobkowiak     [krzys.sobkowiak@gmail.com]
> > > >   * Jeff Genender           [jgenender@apache.org]
> > > >   * Edward J. Yoon          [edward.yoon@samsung.com]
> > > >   * Hao Chen                [hao@apache.org]
> > > >   * Byung-Gon Chun          [bgchun@gmail.com]
> > > >   * Charitha Elvitigala     [charithcc@apache.org]
> > > >   * Alexander Bezzubov      [bzz@apache.org]
> > > >   * Tsuyoshi Ozawa          [ozawa@apache.org]
> > > >   * Mayank Bansal           [mabansal@gmail.com]
> > > >   * Supun Kamburugamuve     [supun@apache.org]
> > > >   * Matthias Wessendorf     [matzew@apache.org]
> > > >   * Felix Cheung            [felixcheung@apache.org]
> > > >   * Ajay Yadava             [ajay.yadav@inmobi.com]
> > > >   * Liang Chen              [chenliang613@huawei.com]
> > > >   * Renaud Richardet        [renaud (at) apache (dot) org]
> > > >   * Bakey Pan               [bakey1985@gmail.com]
> > > >   * Andreas Neumann         [anew@apache.org]
> > > >   * Suresh Marru            [smarru@apache.org]
> > > >   * Hadrian Zbarcea         [hzbarcea@gmail.com]
> > > >
> > > > == Affiliations ==
> > > >
> > > > The initial committers are from six organizations. Google developed
> > > > Dataflow and the Dataflow SDK, data Artisans developed the Flink
> > runner,
> > > > and Cloudera (Labs) developed the Spark runner.
> > > >
> > > >   * Cloudera
> > > >    * Tom White
> > > >   * Data Artisans
> > > >    * Aljoscha Krettek
> > > >    * Kostas Tzoumas
> > > >    * Maximilian Michels
> > > >    * Stephan Ewen
> > > >   * Google
> > > >    * Ben Chambers
> > > >    * Dan Halperin
> > > >    * Davor Bonaci
> > > >    * Frances Perry
> > > >    * James Malone
> > > >    * Kenneth Knowles
> > > >    * Luke Cwik
> > > >    * Tyler Akidau
> > > >    * Robert Bradshaw
> > > >   * PayPal
> > > >    * Amit Sela
> > > >   * Slack
> > > >    * Josh Wills
> > > >   * Talend
> > > >    * Jean-Baptiste Onofré
> > > >
> > > > == Sponsors ==
> > > >
> > > > === Champion ===
> > > >
> > > >   * Jean-Baptiste Onofre         [jbonofre@apache.org]
> > > >
> > > > === Nominated Mentors ===
> > > >
> > > >   * Jean-Baptiste Onofre       [jbonofre@apache.org]
> > > >   * Jim Jagielski              [jim@apache.org]
> > > >   * Venkatesh Seetharam        [venkatesh@apache.org]
> > > >   * Bertrand Delacretaz        [bdelacretaz@apache.org]
> > > >   * Ted Dunning                [tdunning@apache.org]
> > > >
> > > > === Sponsoring Entity ===
> > > >
> > > > The Apache Incubator
> > > > ----
> > > >
> > > > ---------------------------------------------------------------------
> > > > To unsubscribe, e-mail: general-unsubscribe@incubator.apache.org
> > > > For additional commands, e-mail: general-help@incubator.apache.org
> > > >
> > > >
> > >
> >
>



-- 
Thanks and Regards,
Mayank
Cell: 408-718-9370

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