This is great proposal. Been working with Apache Flink for a while so love to help with this project.
- Henry On Wed, Jan 20, 2016 at 8:32 AM, James Malone < jamesmal...@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: > > * d...@dataflow.incubator.apache.org > > * u...@dataflow.incubator.apache.org > > * priv...@dataflow.incubator.apache.org > > * comm...@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 [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] > > == 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 [jbono...@apache.org] > > === Nominated Mentors === > > * 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 >
