+1 (binding) > On Jan 28, 2016, at 10:42 AM, Mayank Bansal <maban...@gmail.com> wrote: > > +1 (non-binding) > > Thanks, > Mayank > > On Thu, Jan 28, 2016 at 10:23 AM, Seetharam Venkatesh < > venkat...@innerzeal.com> wrote: > >> +1 (binding). >> >> Thanks! >> >> On Thu, Jan 28, 2016 at 10:19 AM Ted Dunning <ted.dunn...@gmail.com> >> wrote: >> >>> +1 >>> >>> >>> >>> On Thu, Jan 28, 2016 at 10:02 AM, John D. Ament <johndam...@apache.org> >>> wrote: >>> >>>> +1 >>>> >>>> On Thu, Jan 28, 2016 at 9:28 AM Jean-Baptiste Onofré <j...@nanthrax.net> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> the Beam proposal (initially Dataflow) was proposed last week. >>>>> >>>>> The complete discussion thread is available here: >>>>> >>>>> >>>>> >>>> >>> >> http://mail-archives.apache.org/mod_mbox/incubator-general/201601.mbox/%3CCA%2B%3DKJmvj4wyosNTXVpnsH8PhS7jEyzkZngc682rGgZ3p28L42Q%40mail.gmail.com%3E >>>>> >>>>> As reminder the BeamProposal is here: >>>>> >>>>> https://wiki.apache.org/incubator/BeamProposal >>>>> >>>>> Regarding all the great feedbacks we received on the mailing list, we >>>>> think it's time to call a vote to accept Beam into the Incubator. >>>>> >>>>> Please cast your vote to: >>>>> [] +1 - accept Apache Beam as a new incubating project >>>>> [] 0 - not sure >>>>> [] -1 - do not accept the Apache Beam project (because: ...) >>>>> >>>>> Thanks, >>>>> Regards >>>>> JB >>>>> ---- >>>>> ## page was renamed from DataflowProposal >>>>> = Apache Beam = >>>>> >>>>> == Abstract == >>>>> >>>>> Apache Beam is an open source, unified model and set of >>>>> language-specific SDKs for defining and executing data processing >>>>> workflows, and also data ingestion and integration flows, supporting >>>>> Enterprise Integration Patterns (EIPs) and Domain Specific Languages >>>>> (DSLs). Dataflow pipelines simplify the mechanics of large-scale >> batch >>>>> and streaming data processing and can run on a number of runtimes >> like >>>>> Apache Flink, Apache Spark, and Google Cloud Dataflow (a cloud >>> service). >>>>> Beam also brings DSL in different languages, allowing users to easily >>>>> implement their data integration processes. >>>>> >>>>> == Proposal == >>>>> >>>>> Beam is a simple, flexible, and powerful system for distributed data >>>>> processing at any scale. Beam provides a unified programming model, a >>>>> software development kit to define and construct data processing >>>>> pipelines, and runners to execute Beam pipelines in several runtime >>>>> engines, like Apache Spark, Apache Flink, or Google Cloud Dataflow. >>> Beam >>>>> can be used for a variety of streaming or batch data processing goals >>>>> including ETL, stream analysis, and aggregate computation. The >>>>> underlying programming model for Beam provides MapReduce-like >>>>> parallelism, combined with support for powerful data windowing, and >>>>> fine-grained correctness control. >>>>> >>>>> == Background == >>>>> >>>>> Beam started as a set of Google projects (Google Cloud Dataflow) >>> focused >>>>> on making data processing easier, faster, and less costly. The Beam >>>>> model is a successor to MapReduce, FlumeJava, and Millwheel inside >>>>> Google and is focused on providing a unified solution for batch and >>>>> stream processing. These projects on which Beam is based have been >>>>> published in several papers made available to the public: >>>>> >>>>> * MapReduce - http://research.google.com/archive/mapreduce.html >>>>> * Dataflow model - >> http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf >>>>> * FlumeJava - http://research.google.com/pubs/pub35650.html >>>>> * MillWheel - http://research.google.com/pubs/pub41378.html >>>>> >>>>> Beam was designed from the start to provide a portable programming >>>>> layer. When you define a data processing pipeline with the Beam >> model, >>>>> you are creating a job which is capable of being processed by any >>> number >>>>> of Beam processing engines. Several engines have been developed to >> run >>>>> Beam pipelines in other open source runtimes, including a Beam runner >>>>> for Apache Flink and Apache Spark. There is also a “direct runner”, >> for >>>>> execution on the developer machine (mainly for dev/debug purposes). >>>>> Another runner allows a Beam program to run on a managed service, >>> Google >>>>> Cloud Dataflow, in Google Cloud Platform. The Dataflow Java SDK is >>>>> already available on GitHub, and independent from the Google Cloud >>>>> Dataflow service. Another Python SDK is currently in active >>> development. >>>>> >>>>> In this proposal, the Beam SDKs, model, and a set of runners will be >>>>> submitted as an OSS project under the ASF. The runners which are a >> part >>>>> of this proposal include those for Spark (from Cloudera), Flink (from >>>>> data Artisans), and local development (from Google); the Google Cloud >>>>> Dataflow service runner is not included in this proposal. Further >>>>> references to Beam will refer to the Dataflow model, SDKs, and >> runners >>>>> which are a part of this proposal (Apache Beam) only. The initial >>>>> submission will contain the already-released Java SDK; Google intends >>> to >>>>> submit the Python SDK later in the incubation process. The Google >> Cloud >>>>> Dataflow service will continue to be one of many runners for Beam, >>> built >>>>> on Google Cloud Platform, to run Beam pipelines. Necessarily, Cloud >>>>> Dataflow will develop against the Apache project additions, updates, >>> and >>>>> changes. Google Cloud Dataflow will become one user of Apache Beam >> and >>>>> will participate in the project openly and publicly. >>>>> >>>>> The Beam programming model has been designed with simplicity, >>>>> scalability, and speed as key tenants. In the Beam model, you only >> need >>>>> to think about four top-level concepts when constructing your data >>>>> processing job: >>>>> >>>>> * Pipelines - The data processing job made of a series of >>> computations >>>>> including input, processing, and output >>>>> * PCollections - Bounded (or unbounded) datasets which represent >> the >>>>> input, intermediate and output data in pipelines >>>>> * PTransforms - A data processing step in a pipeline in which one >> or >>>>> more PCollections are an input and output >>>>> * I/O Sources and Sinks - APIs for reading and writing data which >> are >>>>> the roots and endpoints of the pipeline >>>>> >>>>> == Rationale == >>>>> >>>>> With Google Dataflow, Google intended to develop a framework which >>>>> allowed developers to be maximally productive in defining the >>>>> processing, and then be able to execute the program at various levels >>> of >>>>> latency/cost/completeness without re-architecting or re-writing it. >>> This >>>>> goal was informed by Google’s past experience developing several >>>>> models, frameworks, and tools useful for large-scale and distributed >>>>> data processing. While Google has previously published papers >>> describing >>>>> some of its technologies, Google decided to take a different approach >>>>> with Dataflow. Google open-sourced the SDK and model alongside >>>>> commercialization of the idea and ahead of publishing papers on the >>>>> topic. As a result, a number of open source runtimes exist for >>> Dataflow, >>>>> such as the Apache Flink and Apache Spark runners. >>>>> >>>>> We believe that submitting Beam as an Apache project will provide an >>>>> immediate, worthwhile, and substantial contribution to the open >> source >>>>> community. As an incubating project, we believe Dataflow will have a >>>>> better opportunity to provide a meaningful contribution to OSS and >> also >>>>> integrate with other Apache projects. >>>>> >>>>> In the long term, we believe Beam can be a powerful abstraction layer >>>>> for data processing. By providing an abstraction layer for data >>>>> pipelines and processing, data workflows can be increasingly >> portable, >>>>> resilient to breaking changes in tooling, and compatible across many >>>>> execution engines, runtimes, and open source projects. >>>>> >>>>> == Initial Goals == >>>>> >>>>> We are breaking our initial goals into immediate (< 2 months), >>>>> short-term (2-4 months), and intermediate-term (> 4 months). >>>>> >>>>> Our immediate goals include the following: >>>>> >>>>> * Plan for reconciling the Dataflow Java SDK and various runners >> into >>>>> one project >>>>> * Plan for refactoring the existing Java SDK for better >> extensibility >>>>> by SDK and runner writers >>>>> * Validating all dependencies are ASL 2.0 or compatible >>>>> * Understanding and adapting to the Apache development process >>>>> >>>>> Our short-term goals include: >>>>> >>>>> * Moving the newly-merged lists, and build utilities to Apache >>>>> * Start refactoring codebase and move code to Apache Git repo >>>>> * Continue development of new features, functions, and fixes in the >>>>> Dataflow Java SDK, and Dataflow runners >>>>> * Cleaning up the Dataflow SDK sources and crafting a roadmap and >>> plan >>>>> for how to include new major ideas, modules, and runtimes >>>>> * Establishment of easy and clear build/test framework for Dataflow >>>>> and associated runtimes; creation of testing, rollback, and >> validation >>>>> policy >>>>> * Analysis and design for work needed to make Beam a better data >>>>> processing abstraction layer for multiple open source frameworks and >>>>> environments >>>>> >>>>> Finally, we have a number of intermediate-term goals: >>>>> >>>>> * Roadmapping, planning, and execution of integrations with other >> OSS >>>>> and non-OSS projects/products >>>>> * Inclusion of additional SDK for Python, which is under active >>>>> development >>>>> >>>>> == Current Status == >>>>> >>>>> === Meritocracy === >>>>> >>>>> Dataflow was initially developed based on ideas from many employees >>>>> within Google. As an ASL OSS project on GitHub, the Dataflow SDK has >>>>> received contributions from data Artisans, Cloudera Labs, and other >>>>> individual developers. As a project under incubation, we are >> committed >>>>> to expanding our effort to build an environment which supports a >>>>> meritocracy. We are focused on engaging the community and other >> related >>>>> projects for support and contributions. Moreover, we are committed to >>>>> ensure contributors and committers to Dataflow come from a broad mix >> of >>>>> organizations through a merit-based decision process during >> incubation. >>>>> We believe strongly in the Beam model and are committed to growing an >>>>> inclusive community of Beam contributors. >>>>> >>>>> === Community === >>>>> >>>>> The core of the Dataflow Java SDK has been developed by Google for >> use >>>>> with Google Cloud Dataflow. Google has active community engagement in >>>>> the SDK GitHub repository >>>>> (https://github.com/GoogleCloudPlatform/DataflowJavaSDK), on Stack >>>>> Overflow >>>>> (http://stackoverflow.com/questions/tagged/google-cloud-dataflow) >> and >>>>> has had contributions from a number of organizations and indivuduals. >>>>> >>>>> Everyday, Cloud Dataflow is actively used by a number of >> organizations >>>>> and institutions for batch and stream processing of data. We believe >>>>> acceptance will allow us to consolidate existing Dataflow-related >> work, >>>>> grow the Dataflow community, and deepen connections between Dataflow >>> and >>>>> other open source projects. >>>>> >>>>> === Core Developers === >>>>> >>>>> The core developers for Dataflow and the Dataflow runners are: >>>>> >>>>> * Frances Perry >>>>> * Tyler Akidau >>>>> * Davor Bonaci >>>>> * Luke Cwik >>>>> * Ben Chambers >>>>> * Kenn Knowles >>>>> * Dan Halperin >>>>> * Daniel Mills >>>>> * Mark Shields >>>>> * Craig Chambers >>>>> * Maximilian Michels >>>>> * Tom White >>>>> * Josh Wills >>>>> * Robert Bradshaw >>>>> >>>>> === Alignment === >>>>> >>>>> The Beam SDK can be used to create Beam pipelines which can be >> executed >>>>> on Apache Spark or Apache Flink. Beam is also related to other Apache >>>>> projects, such as Apache Crunch. We plan on expanding functionality >> for >>>>> Beam runners, support for additional domain specific languages, and >>>>> increased portability so Beam is a powerful abstraction layer for >> data >>>>> processing. >>>>> >>>>> == Known Risks == >>>>> >>>>> === Orphaned Products === >>>>> >>>>> The Dataflow SDK is presently used by several organizations, from >> small >>>>> startups to Fortune 100 companies, to construct production pipelines >>>>> which are executed in Google Cloud Dataflow. Google has a long-term >>>>> commitment to advance the Dataflow SDK; moreover, Dataflow is seeing >>>>> increasing interest, development, and adoption from organizations >>>>> outside of Google. >>>>> >>>>> === Inexperience with Open Source === >>>>> >>>>> Google believes strongly in open source and the exchange of >> information >>>>> to advance new ideas and work. Examples of this commitment are active >>>>> OSS projects such as Chromium (https://www.chromium.org) and >>> Kubernetes >>>>> (http://kubernetes.io/). With Dataflow, we have tried to be >>> increasingly >>>>> open and forward-looking; we have published a paper in the VLDB >>>>> conference describing the Dataflow model >>>>> (http://www.vldb.org/pvldb/vol8/p1792-Akidau.pdf) and were quick to >>>>> release the Dataflow SDK as open source software with the launch of >>>>> Cloud Dataflow. Our submission to the Apache Software Foundation is a >>>>> logical extension of our commitment to open source software. >>>>> >>>>> === Homogeneous Developers === >>>>> >>>>> The majority of committers in this proposal belong to Google due to >> the >>>>> fact that Dataflow has emerged from several internal Google projects. >>>>> This proposal also includes committers outside of Google who are >>>>> actively involved with other Apache projects, such as Hadoop, Flink, >>> and >>>>> Spark. We expect our entry into incubation will allow us to expand >> the >>>>> number of individuals and organizations participating in Dataflow >>>>> development. Additionally, separation of the Dataflow SDK from Google >>>>> Cloud Dataflow allows us to focus on the open source SDK and model >> and >>>>> do what is best for this project. >>>>> >>>>> === Reliance on Salaried Developers === >>>>> >>>>> The Dataflow SDK and Dataflow runners have been developed primarily >> by >>>>> salaried developers supporting the Google Cloud Dataflow project. >> While >>>>> the Dataflow SDK and Cloud Dataflow have been developed by different >>>>> teams (and this proposal would reinforce that separation) we expect >> our >>>>> initial set of developers will still primarily be salaried. >>> Contribution >>>>> has not been exclusively from salaried developers, however. For >>> example, >>>>> the contrib directory of the Dataflow SDK >>>>> ( >>>>> >>>> >>> >> https://github.com/GoogleCloudPlatform/DataflowJavaSDK/tree/master/contrib >>>>> ) >>>>> contains items from free-time contributors. Moreover, seperate >>> projects, >>>>> such as ScalaFlow (https://github.com/darkjh/scalaflow) have been >>>>> created around the Dataflow model and SDK. We expect our reliance on >>>>> salaried developers will decrease over time during incubation. >>>>> >>>>> === Relationship with other Apache products === >>>>> >>>>> Dataflow directly interoperates with or utilizes several existing >>> Apache >>>>> projects. >>>>> >>>>> * Build >>>>> * Apache Maven >>>>> * Data I/O, Libraries >>>>> * Apache Avro >>>>> * Apache Commons >>>>> * Dataflow runners >>>>> * Apache Flink >>>>> * Apache Spark >>>>> >>>>> Beam when used in batch mode shares similarities with Apache Crunch; >>>>> however, Beam is focused on a model, SDK, and abstraction layer >> beyond >>>>> Spark and Hadoop (MapReduce.) One key goal of Beam is to provide an >>>>> intermediate abstraction layer which can easily be implemented and >>>>> utilized across several different processing frameworks. >>>>> >>>>> === An excessive fascination with the Apache brand === >>>>> >>>>> With this proposal we are not seeking attention or publicity. Rather, >>> we >>>>> firmly believe in the Beam model, SDK, and the ability to make Beam a >>>>> powerful yet simple framework for data processing. While the Dataflow >>>>> SDK and model have been open source, we believe putting code on >> GitHub >>>>> can only go so far. We see the Apache community, processes, and >> mission >>>>> as critical for ensuring the Beam SDK and model are truly >>>>> community-driven, positively impactful, and innovative open source >>>>> software. While Google has taken a number of steps to advance its >>>>> various open source projects, we believe Beam is a great fit for the >>>>> Apache Software Foundation due to its focus on data processing and >> its >>>>> relationships to existing ASF projects. >>>>> >>>>> == Documentation == >>>>> >>>>> The following documentation is relevant to this proposal. Relevant >>>>> portion of the documentation will be contributed to the Apache Beam >>>>> project. >>>>> >>>>> * Dataflow website: https://cloud.google.com/dataflow >>>>> * Dataflow programming model: >>>>> https://cloud.google.com/dataflow/model/programming-model >>>>> * Codebases >>>>> * Dataflow Java SDK: >>>>> https://github.com/GoogleCloudPlatform/DataflowJavaSDK >>>>> * Flink Dataflow runner: >>>> https://github.com/dataArtisans/flink-dataflow >>>>> * Spark Dataflow runner: >> https://github.com/cloudera/spark-dataflow >>>>> * Dataflow Java SDK issue tracker: >>>>> https://github.com/GoogleCloudPlatform/DataflowJavaSDK/issues >>>>> * google-cloud-dataflow tag on Stack Overflow: >>>>> http://stackoverflow.com/questions/tagged/google-cloud-dataflow >>>>> >>>>> == Initial Source == >>>>> >>>>> The initial source for Beam which we will submit to the Apache >>>>> Foundation will include several related projects which are currently >>>>> hosted on the GitHub repositories: >>>>> >>>>> * Dataflow Java SDK >>>>> (https://github.com/GoogleCloudPlatform/DataflowJavaSDK) >>>>> * Flink Dataflow runner ( >>>> https://github.com/dataArtisans/flink-dataflow) >>>>> * Spark Dataflow runner ( >> https://github.com/cloudera/spark-dataflow) >>>>> >>>>> These projects have always been Apache 2.0 licensed. We intend to >>> bundle >>>>> all of these repositories since they are all complimentary and should >>> be >>>>> maintained in one project. Prior to our submission, we will combine >> all >>>>> of these projects into a new git repository. >>>>> >>>>> == Source and Intellectual Property Submission Plan == >>>>> >>>>> The source for the Dataflow SDK and the three runners (Spark, Flink, >>>>> Google Cloud Dataflow) are already licensed under an Apache 2 >> license. >>>>> >>>>> * Dataflow SDK - >>>>> >>>> >>> >> https://github.com/GoogleCloudPlatform/DataflowJavaSDK/blob/master/LICENSE >>>>> * Flink runner - >>>>> https://github.com/dataArtisans/flink-dataflow/blob/master/LICENSE >>>>> * Spark runner - >>>>> https://github.com/cloudera/spark-dataflow/blob/master/LICENSE >>>>> >>>>> Contributors to the Dataflow SDK have also signed the Google >> Individual >>>>> Contributor License Agreement >>>>> (https://cla.developers.google.com/about/google-individual) in order >>> to >>>>> contribute to the project. >>>>> >>>>> With respect to trademark rights, Google does not hold a trademark on >>>>> the phrase “Dataflow.” Based on feedback and guidance we receive >> during >>>>> the incubation process, we are open to renaming the project if >>> necessary >>>>> for trademark or other concerns. >>>>> >>>>> == External Dependencies == >>>>> >>>>> All external dependencies are licensed under an Apache 2.0 or >>>>> Apache-compatible license. As we grow the Beam community we will >>>>> configure our build process to require and validate all contributions >>>>> and dependencies are licensed under the Apache 2.0 license or are >> under >>>>> an Apache-compatible license. >>>>> >>>>> == Required Resources == >>>>> >>>>> === Mailing Lists === >>>>> >>>>> We currently use a mix of mailing lists. We will migrate our existing >>>>> mailing lists to the following: >>>>> >>>>> * d...@beam.incubator.apache.org >>>>> * u...@beam.incubator.apache.org >>>>> * priv...@beam.incubator.apache.org >>>>> * comm...@beam.incubator.apache.org >>>>> >>>>> === Source Control === >>>>> >>>>> The Dataflow team currently uses Git and would like to continue to do >>>>> so. We request a Git repository for Beam with mirroring to GitHub >>>> enabled. >>>>> >>>>> * https://git-wip-us.apache.org/repos/asf/incubator-beam.git >>>>> >>>>> === Issue Tracking === >>>>> >>>>> We request the creation of an Apache-hosted JIRA. The Dataflow >> project >>>>> is currently using both a public GitHub issue tracker and internal >>>>> Google issue tracking. We will migrate and combine from these two >>>>> sources to the Apache JIRA. >>>>> >>>>> * Jira ID: BEAM >>>>> >>>>> == Initial Committers == >>>>> >>>>> * Aljoscha Krettek [aljos...@apache.org] >>>>> * Amit Sela [amitsel...@gmail.com] >>>>> * Ben Chambers [bchamb...@google.com] >>>>> * Craig Chambers [chamb...@google.com] >>>>> * Dan Halperin [dhalp...@google.com] >>>>> * Davor Bonaci [da...@google.com] >>>>> * Frances Perry [f...@google.com] >>>>> * James Malone [jamesmal...@google.com] >>>>> * Jean-Baptiste Onofré [jbono...@apache.org] >>>>> * Josh Wills [jwi...@apache.org] >>>>> * Kostas Tzoumas [kos...@data-artisans.com] >>>>> * Kenneth Knowles [k...@google.com] >>>>> * Luke Cwik [lc...@google.com] >>>>> * Maximilian Michels [m...@apache.org] >>>>> * Stephan Ewen [step...@data-artisans.com] >>>>> * Tom White [t...@cloudera.com] >>>>> * Tyler Akidau [taki...@google.com] >>>>> * Robert Bradshaw [rober...@google.com] >>>>> >>>>> == Additional Interested Contributors == >>>>> >>>>> * Debo Dutta [dedu...@cisco.com] >>>>> * Henry Saputra [hsapu...@apache.org] >>>>> * Taylor Goetz [ptgo...@gmail.com] >>>>> * James Carman [ja...@carmanconsulting.com] >>>>> * Joe Witt [joew...@apache.org] >>>>> * Vaibhav Gumashta [vgumas...@hortonworks.com] >>>>> * Prasanth Jayachandran [pjayachand...@hortonworks.com] >>>>> * Johan Edstrom [seij...@gmail.com] >>>>> * Hugo Louro [hmclo...@gmail.com] >>>>> * Krzysztof Sobkowiak [krzys.sobkow...@gmail.com] >>>>> * Jeff Genender [jgenen...@apache.org] >>>>> * Edward J. Yoon [edward.y...@samsung.com] >>>>> * Hao Chen [h...@apache.org] >>>>> * Byung-Gon Chun [bgc...@gmail.com] >>>>> * Charitha Elvitigala [charit...@apache.org] >>>>> * Alexander Bezzubov [b...@apache.org] >>>>> * Tsuyoshi Ozawa [oz...@apache.org] >>>>> * Mayank Bansal [maban...@gmail.com] >>>>> * Supun Kamburugamuve [su...@apache.org] >>>>> * Matthias Wessendorf [mat...@apache.org] >>>>> * Felix Cheung [felixche...@apache.org] >>>>> * Ajay Yadava [ajay.ya...@inmobi.com] >>>>> * Liang Chen [chenliang...@huawei.com] >>>>> * Renaud Richardet [renaud (at) apache (dot) org] >>>>> * Bakey Pan [bakey1...@gmail.com] >>>>> * Andreas Neumann [a...@apache.org] >>>>> * Suresh Marru [sma...@apache.org] >>>>> * Hadrian Zbarcea [hzbar...@gmail.com] >>>>> >>>>> == Affiliations == >>>>> >>>>> The initial committers are from six organizations. Google developed >>>>> Dataflow and the Dataflow SDK, data Artisans developed the Flink >>> runner, >>>>> and Cloudera (Labs) developed the Spark runner. >>>>> >>>>> * Cloudera >>>>> * Tom White >>>>> * Data Artisans >>>>> * Aljoscha Krettek >>>>> * Kostas Tzoumas >>>>> * Maximilian Michels >>>>> * Stephan Ewen >>>>> * Google >>>>> * Ben Chambers >>>>> * Dan Halperin >>>>> * Davor Bonaci >>>>> * Frances Perry >>>>> * James Malone >>>>> * Kenneth Knowles >>>>> * Luke Cwik >>>>> * Tyler Akidau >>>>> * Robert Bradshaw >>>>> * PayPal >>>>> * Amit Sela >>>>> * Slack >>>>> * Josh Wills >>>>> * Talend >>>>> * Jean-Baptiste Onofré >>>>> >>>>> == Sponsors == >>>>> >>>>> === Champion === >>>>> >>>>> * Jean-Baptiste Onofre [jbono...@apache.org] >>>>> >>>>> === Nominated Mentors === >>>>> >>>>> * Jean-Baptiste Onofre [jbono...@apache.org] >>>>> * Jim Jagielski [j...@apache.org] >>>>> * Venkatesh Seetharam [venkat...@apache.org] >>>>> * Bertrand Delacretaz [bdelacre...@apache.org] >>>>> * Ted Dunning [tdunn...@apache.org] >>>>> >>>>> === Sponsoring Entity === >>>>> >>>>> The Apache Incubator >>>>> ---- >>>>> >>>>> --------------------------------------------------------------------- >>>>> To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org >>>>> For additional commands, e-mail: general-h...@incubator.apache.org >>>>> >>>>> >>>> >>> >> > > > > -- > Thanks and Regards, > Mayank > Cell: 408-718-9370
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