+1 (non-binding) On Thu, Jan 28, 2016 at 9:48 AM, Sergio Fernández <wik...@apache.org> wrote: > +1 (binding) > > On Thu, Jan 28, 2016 at 3:28 PM, Jean-Baptiste Onofré <j...@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: >> >> * d...@beam.incubator.apache.org >> * u...@beam.incubator.apache.org >> * priv...@beam.incubator.apache.org >> * comm...@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 [aljos...@apache.org] >> * Amit Sela [amitsel...@gmail.com] >> * Ben Chambers [bchamb...@google.com] >> * Craig Chambers [chamb...@google.com] >> * Dan Halperin [dhalp...@google.com] >> * Davor Bonaci [da...@google.com] >> * Frances Perry [f...@google.com] >> * James Malone [jamesmal...@google.com] >> * Jean-Baptiste Onofré [jbono...@apache.org] >> * Josh Wills [jwi...@apache.org] >> * Kostas Tzoumas [kos...@data-artisans.com] >> * Kenneth Knowles [k...@google.com] >> * Luke Cwik [lc...@google.com] >> * Maximilian Michels [m...@apache.org] >> * Stephan Ewen [step...@data-artisans.com] >> * Tom White [t...@cloudera.com] >> * Tyler Akidau [taki...@google.com] >> * Robert Bradshaw [rober...@google.com] >> >> == Additional Interested Contributors == >> >> * Debo Dutta [dedu...@cisco.com] >> * Henry Saputra [hsapu...@apache.org] >> * Taylor Goetz [ptgo...@gmail.com] >> * James Carman [ja...@carmanconsulting.com] >> * Joe Witt [joew...@apache.org] >> * Vaibhav Gumashta [vgumas...@hortonworks.com] >> * Prasanth Jayachandran [pjayachand...@hortonworks.com] >> * Johan Edstrom [seij...@gmail.com] >> * Hugo Louro [hmclo...@gmail.com] >> * Krzysztof Sobkowiak [krzys.sobkow...@gmail.com] >> * Jeff Genender [jgenen...@apache.org] >> * Edward J. Yoon [edward.y...@samsung.com] >> * Hao Chen [h...@apache.org] >> * Byung-Gon Chun [bgc...@gmail.com] >> * Charitha Elvitigala [charit...@apache.org] >> * Alexander Bezzubov [b...@apache.org] >> * Tsuyoshi Ozawa [oz...@apache.org] >> * Mayank Bansal [maban...@gmail.com] >> * Supun Kamburugamuve [su...@apache.org] >> * Matthias Wessendorf [mat...@apache.org] >> * Felix Cheung [felixche...@apache.org] >> * Ajay Yadava [ajay.ya...@inmobi.com] >> * Liang Chen [chenliang...@huawei.com] >> * Renaud Richardet [renaud (at) apache (dot) org] >> * Bakey Pan [bakey1...@gmail.com] >> * Andreas Neumann [a...@apache.org] >> * Suresh Marru [sma...@apache.org] >> * Hadrian Zbarcea [hzbar...@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 [jbono...@apache.org] >> >> === Nominated Mentors === >> >> * Jean-Baptiste Onofre [jbono...@apache.org] >> * Jim Jagielski [j...@apache.org] >> * Venkatesh Seetharam [venkat...@apache.org] >> * Bertrand Delacretaz [bdelacre...@apache.org] >> * Ted Dunning [tdunn...@apache.org] >> >> === Sponsoring Entity === >> >> The Apache Incubator >> ---- >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org >> For additional commands, e-mail: general-h...@incubator.apache.org >> >> > > > -- > Sergio Fernández > Partner Technology Manager > Redlink GmbH > m: +43 6602747925 > e: sergio.fernan...@redlink.co > w: http://redlink.co
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