+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 > >
