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From Olivier Lamy <ol...@apache.org>
Subject Re: [VOTE] Accept Beam into the Apache Incubator
Date Fri, 29 Jan 2016 09:45:11 GMT
+1

Olivier

On 29 January 2016 at 01:28, 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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>
>


-- 
Olivier Lamy
http://twitter.com/olamy | http://linkedin.com/in/olamy

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