+1 (binding). Thanks!
On Thu, Jan 28, 2016 at 10:19 AM Ted Dunning <ted.dunn...@gmail.com> wrote: > +1 > > > > On Thu, Jan 28, 2016 at 10:02 AM, John D. Ament <johndam...@apache.org> > wrote: > > > +1 > > > > On Thu, Jan 28, 2016 at 9:28 AM 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 > > > > > > > > >
