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From Alexander Bezzubov <...@apache.org>
Subject Re: [VOTE] Accept Beam into the Apache Incubator
Date Thu, 28 Jan 2016 14:59:22 GMT
+1 (non-binding)

On Thu, Jan 28, 2016 at 3:54 PM, Joe Witt <joe.witt@gmail.com> wrote:

> +1 (non-binding)
>
> On Thu, Jan 28, 2016 at 9:48 AM, Sergio Fernández <wikier@apache.org>
> wrote:
> > +1 (binding)
> >
> > On Thu, Jan 28, 2016 at 3:28 PM, 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
> >> ----
> >>
> >> ---------------------------------------------------------------------
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> >> For additional commands, e-mail: general-help@incubator.apache.org
> >>
> >>
> >
> >
> > --
> > Sergio Fernández
> > Partner Technology Manager
> > Redlink GmbH
> > m: +43 6602747925
> > e: sergio.fernandez@redlink.co
> > w: http://redlink.co
>
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