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From James Malone <jamesmal...@google.com.INVALID>
Subject Re: [DISCUSS] Apache Dataflow Incubator Proposal
Date Wed, 20 Jan 2016 17:39:50 GMT
> Great proposal. I like that your proposal includes a well presented
> roadmap, but I don't see any goals that directly address building a larger
> community. Y'all have any ideas around outreach that will help with
> adoption?
>

Thank you and fair point. We have a few additional ideas which we can put
into the Community section.


>
> As a start, I recommend y'all add a section to the proposal on the wiki
> page for "Additional Interested Contributors" so that folks who want to
> sign up to participate in the project can do so without requesting
> additions to the initial committer list.
>
>
This is a great idea and I think it makes a lot of sense to add an "Additional
Interested Contributors" section to the proposal.


> On Wed, Jan 20, 2016 at 10:32 AM, James Malone <
> jamesmalone@google.com.invalid> wrote:
>
> > Hello everyone,
> >
> > Attached to this message is a proposed new project - Apache Dataflow, a
> > unified programming model for data processing and integration.
> >
> > The text of the proposal is included below. Additionally, the proposal is
> > in draft form on the wiki where we will make any required changes:
> >
> > https://wiki.apache.org/incubator/DataflowProposal
> >
> > We look forward to your feedback and input.
> >
> > Best,
> >
> > James
> >
> > ----
> >
> > = Apache Dataflow =
> >
> > == Abstract ==
> >
> > Dataflow 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). Dataflow also brings DSL in different
> > languages, allowing users to easily implement their data integration
> > processes.
> >
> > == Proposal ==
> >
> > Dataflow is a simple, flexible, and powerful system for distributed data
> > processing at any scale. Dataflow provides a unified programming model, a
> > software development kit to define and construct data processing
> pipelines,
> > and runners to execute Dataflow pipelines in several runtime engines,
> like
> > Apache Spark, Apache Flink, or Google Cloud Dataflow. Dataflow 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 Dataflow provides MapReduce-like parallelism, combined with
> > support for powerful data windowing, and fine-grained correctness
> control.
> >
> > == Background ==
> >
> > Dataflow started as a set of Google projects focused on making data
> > processing easier, faster, and less costly. The Dataflow 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 Dataflow 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://notes.stephenholiday.com/FlumeJava.pdf
> >
> > * MillWheel - http://research.google.com/pubs/pub41378.html
> >
> > Dataflow was designed from the start to provide a portable programming
> > layer. When you define a data processing pipeline with the Dataflow
> model,
> > you are creating a job which is capable of being processed by any number
> of
> > Dataflow processing engines. Several engines have been developed to run
> > Dataflow pipelines in other open source runtimes, including a Dataflow
> > 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 Dataflow 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 Dataflow 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
> > Dataflow will refer to the Dataflow model, SDKs, and runners which are a
> > part of this proposal (Apache Dataflow) 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 Dataflow, built on Google Cloud
> > Platform, to run Dataflow pipelines. Necessarily, Cloud Dataflow will
> > develop against the Apache project additions, updates, and changes.
> Google
> > Cloud Dataflow will become one user of Apache Dataflow and will
> participate
> > in the project openly and publicly.
> >
> > The Dataflow programming model has been designed with simplicity,
> > scalability, and speed as key tenants. In the Dataflow 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 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 Dataflow 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 Dataflow 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 Dataflow 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
> > Dataflow model and are committed to growing an inclusive community of
> > Dataflow 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
> >
> > === Alignment ===
> >
> > The Dataflow SDK can be used to create Dataflow pipelines which can be
> > executed on Apache Spark or Apache Flink. Dataflow is also related to
> other
> > Apache projects, such as Apache Crunch. We plan on expanding
> functionality
> > for Dataflow runners, support for additional domain specific languages,
> and
> > increased portability so Dataflow 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
> >
> > Dataflow when used in batch mode shares similarities with Apache Crunch;
> > however, Dataflow is focused on a model, SDK, and abstraction layer
> beyond
> > Spark and Hadoop (MapReduce.) One key goal of Dataflow 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 Dataflow model, SDK, and the ability to make
> Dataflow
> > 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 Dataflow 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 Dataflow 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 Dataflow 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 Dataflow 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 Dataflow 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@dataflow.incubator.apache.org
> >
> > * user@dataflow.incubator.apache.org
> >
> > * private@dataflow.incubator.apache.org
> >
> > * commits@dataflow.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 Dataflow with mirroring to GitHub
> enabled.
> >
> > === 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.
> >
> > == 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]
> >
> > == 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
> >
> > * PayPal
> >
> > ** Amit Sela
> >
> > * Slack
> >
> > ** Josh Wills
> >
> > * Talend
> >
> > ** Jean-Baptiste Onofré
> >
> > == Sponsors ==
> >
> > === Champion ===
> >
> > * Jean-Baptiste Onofre      [jbonofre@apache.org]
> >
> > === Nominated Mentors ===
> >
> > * 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
> >
>
>
>
> --
> Sean
>

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