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From Joe Witt <joe.w...@gmail.com>
Subject Re: [VOTE] Accept Beam into the Apache Incubator
Date Thu, 28 Jan 2016 14:54:12 GMT
+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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>>
>>
>
>
> --
> Sergio Fernández
> Partner Technology Manager
> Redlink GmbH
> m: +43 6602747925
> e: sergio.fernandez@redlink.co
> w: http://redlink.co

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