Charitha Elvitigala On 21 January 2016 at 16:17, Jean-Baptiste Onofré <j...@nanthrax.net> wrote:
> Hi Chatz, > > sure, what name should I use on the proposal, Charitha ? > > Regards > JB > > > On 01/21/2016 11:32 AM, chatz wrote: > >> Hi Jean, >> >> I’d be interested in contributing as well. >> >> Thanks, >> >> Chatz >> >> >> On 21 January 2016 at 14:22, Jean-Baptiste Onofré <j...@nanthrax.net> >> wrote: >> >> Sweet: you are on the proposal ;) >>> >>> Thanks ! >>> Regards >>> JB >>> >>> >>> On 01/21/2016 08:55 AM, Byung-Gon Chun wrote: >>> >>> This looks very interesting. I'm interested in contributing. >>>> >>>> Thanks. >>>> -Gon >>>> >>>> --- >>>> Byung-Gon Chun >>>> >>>> >>>> On Thu, Jan 21, 2016 at 1:32 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 > >
