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From Hadrian Zbarcea <hzbar...@gmail.com>
Subject Re: [VOTE] Accept Beam into the Apache Incubator
Date Fri, 29 Jan 2016 00:48:31 GMT
+1 (binding)

Man, congrats on a job fantastically well done. This is ASF incubator 
participation at its best.

Expectations are high now. I am looking forward to exemplary governance 
and speedy graduation.

Best of luck,
Hadrian

On 01/28/2016 09:28 AM, Jean-Baptiste Onofré 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
> ----
>
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