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From Johan Edstrom <seij...@gmail.com>
Subject Re: [VOTE] Accept Beam into the Apache Incubator
Date Fri, 29 Jan 2016 03:32:36 GMT
+1

> On Jan 28, 2016, at 6:34 PM, Naresh Agarwal <naresh.agarwal@gmail.com> wrote:
> 
> +1  (non-binding)
> 
> Thanks
> Naresh
> On 29 Jan 2016 06:18, "Hadrian Zbarcea" <hzbarcea@gmail.com> wrote:
> 
>> +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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>>> For additional commands, e-mail: general-help@incubator.apache.org
>>> 
>>> 
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