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From Joe Witt <joew...@apache.org>
Subject Re: [DISCUSS] Apache Dataflow Incubator Proposal
Date Wed, 20 Jan 2016 20:00:52 GMT
Hello

This is a very interesting proposal and concept.  I'd like to contribute.

Thanks
Joe

On Wed, Jan 20, 2016 at 2:50 PM, James Carman
<james@carmanconsulting.com> wrote:
> Of course! I'd be happy to help
>
> On Wed, Jan 20, 2016 at 2:02 PM Jean-Baptiste Onofré <jb@nanthrax.net>
> wrote:
>
>> Hi James,
>>
>> Can I add your to the proposal ?
>>
>> Regards
>> JB
>>
>> On 01/20/2016 07:20 PM, James Carman wrote:
>> > Well, I for one would be very interested in this project and would be
>> happy
>> > to contribute.
>> >
>> >
>> > On Wed, Jan 20, 2016 at 12:09 PM Jean-Baptiste Onofré <jb@nanthrax.net>
>> > wrote:
>> >
>> >> Hi Sean,
>> >>
>> >> It's a fair point, but not present in most of the proposals. It's
>> >> something that we can address in the "Community" section.
>> >>
>> >> Regards
>> >> JB
>> >>
>> >> On 01/20/2016 05:55 PM, Sean Busbey wrote:
>> >>> Great proposal. I like that your proposal includes a well presented
>> >>> roadmap, but I don't see any goals that directly address building a
>> >> larger
>> >>> community. Y'all have any ideas around outreach that will help with
>> >>> adoption?
>> >>>
>> >>> As a start, I recommend y'all add a section to the proposal on the wiki
>> >>> page for "Additional Interested Contributors" so that folks who want
to
>> >>> sign up to participate in the project can do so without requesting
>> >>> additions to the initial committer list.
>> >>>
>> >>> On Wed, Jan 20, 2016 at 10:32 AM, James Malone <
>> >>> jamesmalone@google.com.invalid> wrote:
>> >>>
>> >>>> Hello everyone,
>> >>>>
>> >>>> Attached to this message is a proposed new project - Apache Dataflow,
>> a
>> >>>> unified programming model for data processing and integration.
>> >>>>
>> >>>> The text of the proposal is included below. Additionally, the proposal
>> >> is
>> >>>> in draft form on the wiki where we will make any required changes:
>> >>>>
>> >>>> https://wiki.apache.org/incubator/DataflowProposal
>> >>>>
>> >>>> We look forward to your feedback and input.
>> >>>>
>> >>>> Best,
>> >>>>
>> >>>> James
>> >>>>
>> >>>> ----
>> >>>>
>> >>>> = Apache Dataflow =
>> >>>>
>> >>>> == Abstract ==
>> >>>>
>> >>>> Dataflow 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). Dataflow also brings DSL in
>> different
>> >>>> languages, allowing users to easily implement their data integration
>> >>>> processes.
>> >>>>
>> >>>> == Proposal ==
>> >>>>
>> >>>> Dataflow is a simple, flexible, and powerful system for distributed
>> data
>> >>>> processing at any scale. Dataflow provides a unified programming
>> model,
>> >> a
>> >>>> software development kit to define and construct data processing
>> >> pipelines,
>> >>>> and runners to execute Dataflow pipelines in several runtime engines,
>> >> like
>> >>>> Apache Spark, Apache Flink, or Google Cloud Dataflow. Dataflow 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 Dataflow provides MapReduce-like parallelism, combined
with
>> >>>> support for powerful data windowing, and fine-grained correctness
>> >> control.
>> >>>>
>> >>>> == Background ==
>> >>>>
>> >>>> Dataflow started as a set of Google projects focused on making data
>> >>>> processing easier, faster, and less costly. The Dataflow 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 Dataflow 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://notes.stephenholiday.com/FlumeJava.pdf
>> >>>>
>> >>>> * MillWheel - http://research.google.com/pubs/pub41378.html
>> >>>>
>> >>>> Dataflow was designed from the start to provide a portable programming
>> >>>> layer. When you define a data processing pipeline with the Dataflow
>> >> model,
>> >>>> you are creating a job which is capable of being processed by any
>> >> number of
>> >>>> Dataflow processing engines. Several engines have been developed
to
>> run
>> >>>> Dataflow pipelines in other open source runtimes, including a Dataflow
>> >>>> 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 Dataflow 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 Dataflow 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
>> >>>> Dataflow will refer to the Dataflow model, SDKs, and runners which
>> are a
>> >>>> part of this proposal (Apache Dataflow) 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 Dataflow, built on Google
Cloud
>> >>>> Platform, to run Dataflow pipelines. Necessarily, Cloud Dataflow
will
>> >>>> develop against the Apache project additions, updates, and changes.
>> >> Google
>> >>>> Cloud Dataflow will become one user of Apache Dataflow and will
>> >> participate
>> >>>> in the project openly and publicly.
>> >>>>
>> >>>> The Dataflow programming model has been designed with simplicity,
>> >>>> scalability, and speed as key tenants. In the Dataflow 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 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 Dataflow 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 Dataflow 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 Dataflow 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
>> >>>> Dataflow model and are committed to growing an inclusive community
of
>> >>>> Dataflow 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
>> >>>>
>> >>>> === Alignment ===
>> >>>>
>> >>>> The Dataflow SDK can be used to create Dataflow pipelines which
can be
>> >>>> executed on Apache Spark or Apache Flink. Dataflow is also related
to
>> >> other
>> >>>> Apache projects, such as Apache Crunch. We plan on expanding
>> >> functionality
>> >>>> for Dataflow runners, support for additional domain specific
>> languages,
>> >> and
>> >>>> increased portability so Dataflow 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
>> >>>>
>> >>>> Dataflow when used in batch mode shares similarities with Apache
>> Crunch;
>> >>>> however, Dataflow is focused on a model, SDK, and abstraction layer
>> >> beyond
>> >>>> Spark and Hadoop (MapReduce.) One key goal of Dataflow 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 Dataflow model, SDK, and the ability to make
>> >> Dataflow
>> >>>> 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 Dataflow 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 Dataflow 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 Dataflow
>> 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 Dataflow 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 Dataflow 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@dataflow.incubator.apache.org
>> >>>>
>> >>>> * user@dataflow.incubator.apache.org
>> >>>>
>> >>>> * private@dataflow.incubator.apache.org
>> >>>>
>> >>>> * commits@dataflow.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 Dataflow with mirroring to GitHub
>> >> enabled.
>> >>>>
>> >>>> === 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.
>> >>>>
>> >>>> == 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]
>> >>>>
>> >>>> == 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
>> >>>>
>> >>>> * PayPal
>> >>>>
>> >>>> ** Amit Sela
>> >>>>
>> >>>> * Slack
>> >>>>
>> >>>> ** Josh Wills
>> >>>>
>> >>>> * Talend
>> >>>>
>> >>>> ** Jean-Baptiste Onofré
>> >>>>
>> >>>> == Sponsors ==
>> >>>>
>> >>>> === Champion ===
>> >>>>
>> >>>> * Jean-Baptiste Onofre      [jbonofre@apache.org]
>> >>>>
>> >>>> === Nominated Mentors ===
>> >>>>
>> >>>> * 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
>> >>>>
>> >>>
>> >>>
>> >>>
>> >>
>> >> --
>> >> Jean-Baptiste Onofré
>> >> jbonofre@apache.org
>> >> http://blog.nanthrax.net
>> >> Talend - http://www.talend.com
>> >>
>> >> ---------------------------------------------------------------------
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>> Jean-Baptiste Onofré
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