Hello This is a very interesting proposal and concept. I'd like to contribute.
Thanks Joe On Wed, Jan 20, 2016 at 2:50 PM, James Carman <ja...@carmanconsulting.com> wrote: > Of course! I'd be happy to help > > On Wed, Jan 20, 2016 at 2:02 PM Jean-Baptiste Onofré <j...@nanthrax.net> > wrote: > >> Hi James, >> >> Can I add your to the proposal ? >> >> Regards >> JB >> >> On 01/20/2016 07:20 PM, James Carman wrote: >> > Well, I for one would be very interested in this project and would be >> happy >> > to contribute. >> > >> > >> > On Wed, Jan 20, 2016 at 12:09 PM Jean-Baptiste Onofré <j...@nanthrax.net> >> > wrote: >> > >> >> Hi Sean, >> >> >> >> It's a fair point, but not present in most of the proposals. It's >> >> something that we can address in the "Community" section. >> >> >> >> Regards >> >> JB >> >> >> >> On 01/20/2016 05:55 PM, Sean Busbey wrote: >> >>> 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? >> >>> >> >>> 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. >> >>> >> >>> On Wed, Jan 20, 2016 at 10:32 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 >> >>>> >> >>> >> >>> >> >>> >> >> >> >> -- >> >> Jean-Baptiste Onofré >> >> jbono...@apache.org >> >> http://blog.nanthrax.net >> >> Talend - http://www.talend.com >> >> >> >> --------------------------------------------------------------------- >> >> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org >> >> For additional commands, e-mail: general-h...@incubator.apache.org >> >> >> >> >> > >> >> -- >> Jean-Baptiste Onofré >> jbono...@apache.org >> http://blog.nanthrax.net >> Talend - http://www.talend.com >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org >> For additional commands, e-mail: general-h...@incubator.apache.org >> >> --------------------------------------------------------------------- To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org For additional commands, e-mail: general-h...@incubator.apache.org
