I have added Ted as a mentor, so we now have some diversity in mentor affiliations. (Thanks Ted!) I also reached out to few other people in mahout community who I thought might be potentially interested, but I didn't hear from them.
I am planning to put this to a vote in 2 days. Meanwhile, please let me know if anybody else would be willing to join as a mentor. Thanks, Thejas On Fri, Feb 27, 2015 at 3:44 PM, Thejas Nair <thejas.n...@gmail.com> wrote: > Thanks Ted. That helps a lot ! > I have also reached out to few other folks in Mahout community to see > if they might also be interested. > > > On Fri, Feb 27, 2015 at 8:06 AM, Ted Dunning <ted.dunn...@gmail.com> wrote: >> Thejas, >> >> Please add me as a mentor if it helps to have diversity. I have enormous >> trust based on previous experience with him that Alan Gates would act as a >> highly impartial and effective mentor, but would be happy to help if there >> is a concern that could be addressed by having another mentor from a >> different company. >> >> >> >> On Thu, Feb 26, 2015 at 6:12 PM, Thejas Nair <thejas.n...@gmail.com> wrote: >> >>> The incubator proposal has been updated with the feedback so far. >>> We have 3 mentors now, but I think it would be good to have additional >>> mentors. Please let me know if anyone is able to help mentor this >>> project. >>> >>> I am planning to start a vote on the proposal in a day or two. >>> >>> >>> On Fri, Feb 6, 2015 at 5:21 PM, <oo...@comp.nus.edu.sg> wrote: >>> > >>> > Regarding the number of users using this project -- at this moment, the >>> > community is not big. A few local start-ups have been trying to use it >>> > (mainly due to announcement in our seminar list), eg. one is using it for >>> > image recognition (given a phone snapped by a user, it wants to be return >>> > the same the product, and a list of similar products, such as a luxury >>> bag >>> > on a passerby). Researchers from outside of NUS may have been using it >>> > since we published an application paper on cross domain/modal retrieval >>> in >>> > VLDB 2014. >>> > >>> > We have not announced the project to the outside community yet -- we >>> would >>> > announce it in dbworld etc in due course. >>> > >>> > Thanks and have a good weekend. >>> > >>> > regards >>> > beng chin >>> > >>> >> >>> >> Thanks for the comments and suggestions. >>> >> With permission from Thejas, I would like to respond to point 2. >>> >> >>> >> We have a huge team down at NUS (National University of Singapore) -- >>> >> we have about seven database/data mining data professors (not including >>> >> those in systems, networking, and machine learning). >>> >> I myself have nine PhD students in a steady state, and I have a few >>> large >>> >> grants, with a total budget of about 15 million S$ (~12 million USD), >>> that >>> >> allows me to hire a number of research fellows and research assistants >>> for >>> >> the next few years. In a constant state, I have about 20 people (PhD >>> >> students/RA/RF) working with me alone. Other professors have their own >>> >> grants (unlike other countries, it is relatively easy to get large >>> grants >>> >> in Singapore; many overseas Universities, including UIUC, MIT, ETH etc >>> >> have research labs funded by Singapore Research Foundation [equivalent >>> of >>> >> NSF]). >>> >> >>> >> SINGA is a long term project for us -- while it is a platform as it is, >>> we >>> >> are using it for healthcare predictive analytics (by working with a >>> >> hospital associated with the University). Therefore, we will be working >>> >> on SINGA, not solely as a distributed DL platform, but as a tool that >>> will >>> >> enable us to do data analytics on some business domains (eg. healthcase, >>> >> consumer etc) >>> >> >>> >> For the initial set of committers, three are tenured professors, five >>> are >>> >> students, with 2-5 years to go before they complete their PhD. Quite >>> >> often, some would stay back as a research fellow for a couple of years >>> >> before they start looking for a job outside. We will work with mentors >>> >> and new developers (from outside of NUS or Zhejiang University) in >>> >> enhancing the system. >>> >> >>> >> The project should survive in that sense. >>> >> >>> >> (I have an on-going project CIIDAA that has been around since 2008; it >>> was >>> >> started as another project, epiC, with a different grant, and then we >>> >> continue the development with a new grant for CIIDAA -- >>> >> http://www.comp.nus.edu.sg/~ciidaa/ >>> >> ) >>> >> >>> >> Thanks. >>> >> >>> >> regards >>> >> beng chin >>> >> ps: i am not sure if my email will get through to the group. >>> >> >>> >> >>> >> ---------------------------- Original Message >>> ---------------------------- >>> >> Subject: Re: [DISCUSS] [PROPOSAL] Singa for Apache Incubator >>> >> From: "Henry Saputra" <henry.sapu...@gmail.com> >>> >> Date: Thu, February 5, 2015 2:57 pm >>> >> To: "general@incubator.apache.org" <general@incubator.apache.org> >>> >> Cc: oo...@comp.nus.edu.sg >>> >> >>> -------------------------------------------------------------------------- >>> >> >>> >> Several comments: >>> >> -) How many users already using this project? I would reccomend to >>> >> drop request for singa-user list at the beginning. >>> >> -) All the initial committers come from university and seemed like >>> >> some of them already ready to leave university. I am not too sure if >>> >> this project go survive if all of the inital committers are from >>> >> university as students. >>> >> -) Need to solicit more mentors if this project ever get to Apache >>> >> incubator. >>> >> >>> >> - Henry >>> >> >>> >> On Tue, Feb 3, 2015 at 3:58 PM, Thejas Nair <thejas.n...@gmail.com> >>> wrote: >>> >>> The "Relationship with Other Apache Products" section has been >>> >>> updated. The reference to H2O in that section has been removed, and >>> >>> other projects have been added. >>> >>> Thanks for the feedback! >>> >>> >>> >>> >>> >>> On Wed, Jan 28, 2015 at 10:27 AM, Thejas Nair <thejas.n...@gmail.com> >>> >> wrote: >>> >>>> Thanks for pointing that out Henry! Yes, looks like H20 is not an >>> >>>> apache project, I should have verified that. >>> >>>> I will edit that, and revisit that section along with the folks in >>> >>>> Singa community. >>> >>>> >>> >>>> >>> >>>> On Tue, Jan 27, 2015 at 6:55 PM, Henry Saputra >>> >> <henry.sapu...@gmail.com> wrote: >>> >>>>> Quick immediate comment that "Apache H2O" is not really Apache >>> >>>>> project. >>> >>>>> >>> >>>>> I assume you are referring to https://github.com/h2oai/h2o (or >>> >>>>> https://github.com/h2oai/h2o-dev) ? >>> >>>>> >>> >>>>> - Henry >>> >>>>> >>> >>>>> On Tue, Jan 27, 2015 at 5:29 PM, Thejas Nair <thejas.n...@gmail.com> >>> >> wrote: >>> >>>>>> Hello everyone, >>> >>>>>> >>> >>>>>> I would like to propose the inclusion of Singa as an Apache >>> Incubator >>> >> project. >>> >>>>>> >>> >>>>>> Here is the proposal - >>> >>>>>> https://wiki.apache.org/incubator/SingaProposal >>> >>>>>> >>> >>>>>> Please review the proposal and give feedback. I am planning to start >>> >>>>>> a >>> >>>>>> vote after 7 days if the proposal looks good. >>> >>>>>> We are also seeking additional Apache mentors for the project. >>> >>>>>> >>> >>>>>> Thanks, >>> >>>>>> Thejas >>> >>>>>> ========================================================== >>> >>>>>> Singa Incubator Proposal >>> >>>>>> >>> >>>>>> Abstract >>> >>>>>> >>> >>>>>> SINGA is a distributed deep learning platform. >>> >>>>>> >>> >>>>>> Proposal >>> >>>>>> >>> >>>>>> SINGA is an efficient, scalable and easy-to-use distributed platform >>> >>>>>> for training deep learning models, e.g., Deep Convolutional Neural >>> >>>>>> Network and Deep Belief Network. It parallelizes the computation >>> >>>>>> (i.e., training) onto a cluster of nodes by distributing the >>> training >>> >>>>>> data and model automatically to speed up the training. Built-in >>> >>>>>> training algorithms like Back-Propagation and Contrastive Divergence >>> >>>>>> are implemented based on common abstractions of deep learning >>> models. >>> >>>>>> Users can train their own deep learning models by simply customizing >>> >>>>>> these abstractions like implementing the Mapper and Reducer in >>> >>>>>> Hadoop. >>> >>>>>> >>> >>>>>> Background >>> >>>>>> >>> >>>>>> Deep learning refers to a set of feature (or representation) >>> learning >>> >>>>>> models that consist of multiple (non-linear) layers, where different >>> >>>>>> layers learn different levels of abstractions (representations) of >>> >>>>>> the >>> >>>>>> raw input data. Larger (in terms of model parameters) and deeper (in >>> >>>>>> terms of number of layers) models have shown better performance, >>> >>>>>> e.g., >>> >>>>>> lower image classification error in Large Scale Visual Recognition >>> >>>>>> Challenge. However, a larger model requires more memory and larger >>> >>>>>> training data to reduce over-fitting. Complex numeric operations >>> make >>> >>>>>> the training computation intensive. In practice, training large deep >>> >>>>>> learning models takes weeks or months on a single node (even with >>> >>>>>> GPU). >>> >>>>>> >>> >>>>>> Rational >>> >>>>>> >>> >>>>>> Deep learning has gained a lot of attraction in both academia and >>> >>>>>> industry due to its success in a wide range of areas such as >>> computer >>> >>>>>> vision and speech recognition. However, training of such models is >>> >>>>>> computationally expensive, especially for large and deep models >>> >>>>>> (e.g., >>> >>>>>> with billions of parameters and more than 10 layers). Both Google >>> and >>> >>>>>> Microsoft have developed distributed deep learning systems to make >>> >>>>>> the >>> >>>>>> training more efficient by distributing the computations within a >>> >>>>>> cluster of nodes. However, these systems are closed source >>> softwares. >>> >>>>>> Our goal is to leverage the community of open source developers to >>> >>>>>> make SINGA efficient, scalable and easy to use. SINGA is a full >>> >>>>>> fledged distributed platform, that could benefit the community and >>> >>>>>> also benefit from the community in their involvement in contributing >>> >>>>>> to the further work in this area. We believe the nature of SINGA and >>> >>>>>> our visions for the system fit naturally to Apache's philosophy and >>> >>>>>> development framework. >>> >>>>>> >>> >>>>>> Initial Goals >>> >>>>>> >>> >>>>>> We have developed a system for SINGA running on a commodity computer >>> >>>>>> cluster. The initial goals include, * improving the system in terms >>> >>>>>> of >>> >>>>>> scalability and efficiency, e.g., using Infiniband for network >>> >>>>>> communication and multi-threading for one node computation. We would >>> >>>>>> consider extending SINGA to GPU clusters later. * benchmarking with >>> >>>>>> larger datasets (hundreds of millions of training instances) and >>> >>>>>> models (billions of parameters). * adding more built-in deep >>> learning >>> >>>>>> models. Users can train the built-in models on their datasets >>> >>>>>> directly. >>> >>>>>> >>> >>>>>> Current Status >>> >>>>>> >>> >>>>>> Meritocracy >>> >>>>>> >>> >>>>>> We would like to follow ASF meritocratic principles to encourage >>> more >>> >>>>>> developers to contribute in this project. We know that only active >>> >>>>>> and >>> >>>>>> excellent developers can make SINGA a successful project. The >>> >>>>>> committer list and PMC will be updated based on developers' >>> >>>>>> performance and commitment. We are also improving the documentation >>> >>>>>> and code to help new developers get started quickly. >>> >>>>>> >>> >>>>>> Community >>> >>>>>> >>> >>>>>> SINGA is currently being developed in the Database System Research >>> >>>>>> Lab >>> >>>>>> at the National University of Singapore (NUS) in collaboration with >>> >>>>>> Zhejiang University in China. Our lab has extensive experience in >>> >>>>>> building database related systems, including distributed systems. >>> Six >>> >>>>>> PhD students and research assistants (Jinyang Gao, Kaiping Zheng, >>> >>>>>> Sheng Wang, Wei Wang, Zhaojing Luo and Zhongle Xie) , a research >>> >>>>>> fellow (Anh Dinh) and three professors (Beng Chin Ooi, Gang Chen, >>> >>>>>> Kian >>> >>>>>> Lee Tan) have been working for a year on this project. We are open >>> to >>> >>>>>> recruiting more developers from diverse backgrounds. >>> >>>>>> >>> >>>>>> Core Developers >>> >>>>>> >>> >>>>>> Beng Chin Ooi, Gang Chen and Kian Lee Tan are professors who have >>> >>>>>> worked on distributed systems for more than 20 years. They have >>> >>>>>> collaborated with the industry and have built various large scale >>> >>>>>> systems. Anh Dinh's research is also on distributed systems, albeit >>> >>>>>> with more focus on security aspects. Wei Wang's research is on deep >>> >>>>>> learning problems including deep learning applications and large >>> >>>>>> scale >>> >>>>>> training. Sheng Wang and Jinyang are working on efficient indexing, >>> >>>>>> querying of large scale data and machine learning. Kaiping, Zhaojing >>> >>>>>> and Zhongle are new PhD students who jointed SINGA recently. They >>> >>>>>> will >>> >>>>>> work on this project for a longer time (next 4-5 years). While we >>> >>>>>> share common research interests, each member also brings diverse >>> >>>>>> expertise to the team. >>> >>>>>> >>> >>>>>> Alignment >>> >>>>>> >>> >>>>>> ASF is already the home of many distributed platforms, e.g., Hadoop, >>> >>>>>> Spark and Mahout, each of which targets a different application >>> >>>>>> domain. SINGA, being a distributed platform for large-scale deep >>> >>>>>> learning, focuses on another important domain for which there still >>> >>>>>> lacks a robust and scalable open-source platform. The recent success >>> >>>>>> of deep learning models especially for vision and speech recognition >>> >>>>>> tasks has generated interests in both applying existing deep >>> learning >>> >>>>>> models and in developing new ones. Thus, an open-source platform for >>> >>>>>> deep learning will be able to attract a large community of users and >>> >>>>>> developers. SINGA is a complex system needing many iterations of >>> >>>>>> design, implementation and testing. Apache's collaboration framework >>> >>>>>> which encourages active contribution from developers will inevitably >>> >>>>>> help improve the quality of the system, as shown in the success of >>> >>>>>> Hadoop, Spark, etc.. Equally important is the community of users >>> >>>>>> which >>> >>>>>> helps identify real-life applications of deep learning, and helps to >>> >>>>>> evaluate the system's performance and ease-of-use. We hope to >>> >>>>>> leverage >>> >>>>>> ASF for coordinating and promoting both communities, and in return >>> >>>>>> benefit the communities with another useful tool. >>> >>>>>> >>> >>>>>> Known Risks >>> >>>>>> >>> >>>>>> Orphaned products >>> >>>>>> >>> >>>>>> Four core developers (Anh, Wei Wang, Jinyang and Sheng Wang) may >>> >>>>>> leave >>> >>>>>> the lab in two to four years time. It is possible that some of them >>> >>>>>> may not have enough time to focus on this project after that. But, >>> >>>>>> SINGA is part of our other bigger research projects on building an >>> >>>>>> infrastructure for data intensive applications, which include >>> >>>>>> health-care analytics and brain-inspired computing. Beng Chin and >>> >>>>>> Kian >>> >>>>>> Lee would continue working on it and getting more people involved. >>> >>>>>> For >>> >>>>>> example, three new developers (Kaiping, Zhaojing and Zhongle) joined >>> >>>>>> us recently. Individual developers are welcome to make SINGA a >>> >>>>>> diverse >>> >>>>>> community that is robust and independent from any single developer. >>> >>>>>> >>> >>>>>> Inexperience with Open Source >>> >>>>>> >>> >>>>>> All the developers are active users and followers of open source >>> >>>>>> projects. Our research lab has a strong commitment to open source, >>> >>>>>> and >>> >>>>>> has released the source code of several systems under open source >>> >>>>>> license as a way of contributing back to the open source community. >>> >>>>>> But we do not have much real experience in open source projects with >>> >>>>>> large and well organized communities like those in Apache. This is >>> >>>>>> one >>> >>>>>> reason we choose Apache which is experienced in open source project >>> >>>>>> incubation. We hope to get the help from Apache (e.g., champion and >>> >>>>>> mentors) to establish a healthy path for SINGA. >>> >>>>>> >>> >>>>>> Homogenous Developers >>> >>>>>> >>> >>>>>> Although the current developers are researchers in the universities, >>> >>>>>> they have different research interests and project experiences, as >>> >>>>>> mentioned in the section that introduces the core developers. We >>> know >>> >>>>>> that a diverse community is helpful. Hence we are open to the idea >>> of >>> >>>>>> recruiting developers from other regions and organizations. >>> >>>>>> >>> >>>>>> Reliance on Salaried Developers >>> >>>>>> >>> >>>>>> As a research project in the university, SINGA's current developing >>> >>>>>> community consists of professors, PhD students, research assistants >>> >>>>>> and postdoctoral fellows. They are driven by their interests to work >>> >>>>>> on this project and have contributed actively since the start of the >>> >>>>>> project. The research assistants and fellows are expected to leave >>> >>>>>> when their contracts expire. However, they are keen to continue to >>> >>>>>> work on the project voluntarily. Moreover, as a long term research >>> >>>>>> project, new research assistants and fellows are likely to join the >>> >>>>>> project. >>> >>>>>> >>> >>>>>> A Excessive Fascination with the Apache Brand >>> >>>>>> >>> >>>>>> We choose Apache not for publicity. We have two purposes. First, we >>> >>>>>> want to leverage Apache's reputation to recruit more developers to >>> >>>>>> make a diverse community. Second, we hope that Apache can help us to >>> >>>>>> establish a healthy path in developing SINGA. Beng Chin and Kian-Lee >>> >>>>>> are established database and distributed system researchers, and >>> >>>>>> together with the other contributors, they sincerely believe that >>> >>>>>> there is a need for a widely accepted open source distributed deep >>> >>>>>> learning platform. The field of deep learning is still at its >>> >>>>>> infancy, >>> >>>>>> and an open source platform will fuel the research in the area. >>> >>>>>> Moreover, such a platform will enable researchers to develop new >>> >>>>>> models and algorithms, rather than spending time implementing a deep >>> >>>>>> learning system from scratch. Furthermore, the need for scalability >>> >>>>>> for such a platform is obvious. >>> >>>>>> >>> >>>>>> Relationship with Other Apache Products >>> >>>>>> >>> >>>>>> Apache H2O implemented two simple deep learning models, namely the >>> >>>>>> Multi-Layer Perceptron and Deep Auto-encoders. There are two >>> >>>>>> significant differences between H2O and SINGA. First, H2O adopts the >>> >>>>>> Map-Reduce framework which runs a set of computing nodes in parallel >>> >>>>>> againsts of the training set. Model parameters trained by all >>> >>>>>> computing nodes are averaged as the final model parameters. This >>> >>>>>> training algorithm is different from the distributed training >>> >>>>>> algorithm used by DistBelief, Adam and SINGA, which frequently >>> >>>>>> synchronizes the parameters trained from different nodes. SINGA >>> >>>>>> adopts >>> >>>>>> the parameter server framework to support a wide range of >>> distributed >>> >>>>>> training algorithms and parallelization methods (e.g., data >>> >>>>>> parallelism, model parallelism and hybrid parallelism. H2O only >>> >>>>>> support data parallelism) . Second, in H2O, users are restricted to >>> >>>>>> use the two built-in models. In SINGA, we provide simple programming >>> >>>>>> model to let users implement their own deep learning models. A new >>> >>>>>> deep learning model can be implemented by customizing the base Layer >>> >>>>>> class for each layer involved in the model. It is similar to writing >>> >>>>>> Hadoop programs where users only need to override the base Mapper >>> and >>> >>>>>> Reducer. We also provide built-in models for users to use directly. >>> >>>>>> >>> >>>>>> Documentation >>> >>>>>> >>> >>>>>> The project is hosted at >>> >>>>>> http://www.comp.nus.edu.sg/~dbsystem/project/singa.html. >>> >>>>>> Documentations can be found at the Github Wiki Page: >>> >>>>>> https://github.com/nusinga/singa/wiki. We continue to refine and >>> >>>>>> improve the documentation. >>> >>>>>> >>> >>>>>> Initial Source >>> >>>>>> >>> >>>>>> We use Github to maintain our source code, >>> >> https://github.com/nusinga/singa >>> >>>>>> >>> >>>>>> Source and Intellectual Property Submission Plan >>> >>>>>> >>> >>>>>> We plan to make our code base be under Apache License, Version 2.0. >>> >>>>>> >>> >>>>>> External Dependencies >>> >>>>>> >>> >>>>>> required by the core code base: glog, gflags, google protobuf, >>> >>>>>> open-blas, mpich, armci-mpi. >>> >>>>>> required by data preparation and preprocessing: opencv, hdfs, >>> python. >>> >>>>>> >>> >>>>>> Cryptography >>> >>>>>> >>> >>>>>> Not Applicable >>> >>>>>> >>> >>>>>> Required Resources >>> >>>>>> >>> >>>>>> Mailing Lists >>> >>>>>> >>> >>>>>> Currently, we use google group for internal discussion. The mailing >>> >>>>>> address is nusi...@googlegroup.com. We will migrate the content to >>> >>>>>> the >>> >>>>>> apache mailing lists in the future. >>> >>>>>> >>> >>>>>> singa-dev >>> >>>>>> singa-user >>> >>>>>> singa-commits >>> >>>>>> singa-private (for private discussion within PCM) >>> >>>>>> >>> >>>>>> Git Repository >>> >>>>>> >>> >>>>>> We want to continue using git for version control. Hence, a git repo >>> >>>>>> is required. >>> >>>>>> >>> >>>>>> Issue Tracking >>> >>>>>> >>> >>>>>> JIRA Singa (SINGA) >>> >>>>>> >>> >>>>>> Initial Committers >>> >>>>>> >>> >>>>>> Beng Chin Ooi (ooibc @comp.nus.edu.sg) >>> >>>>>> Kian Lee Tan (tankl @comp.nus.edu.sg) >>> >>>>>> Gang Chen (cg @zju.edu.cn) >>> >>>>>> Wei Wang (wangwei @comp.nus.edu.sg) >>> >>>>>> Dinh Tien Tuan Anh (dinhtta @comp.nus.edu.sg) >>> >>>>>> Jinyang Gao (jinyang.gao @comp.nus.edu.sg) >>> >>>>>> Sheng Wang (wangsh @comp.nus.edu.sg) >>> >>>>>> Kaiping Zheng (kaiping @comp.nus.edu.sg) >>> >>>>>> Zhaojing Luo (zhaojing @comp.nus.edu.sg) >>> >>>>>> Zhongle Xie (zhongle @comp.nus.edu.sg) >>> >>>>>> >>> >>>>>> Affiliations >>> >>>>>> >>> >>>>>> Beng Chin Ooi, National University of Singapore >>> >>>>>> Kian Lee Tan, National University of Singapore >>> >>>>>> Gang Chen, Zhejiang University >>> >>>>>> Wei Wang, National University of Singapore >>> >>>>>> Dinh Tien Tuan Anh, National University of Singapore >>> >>>>>> Jinyang Gao, National University of Singapore >>> >>>>>> Sheng Wang, National University of Singapore >>> >>>>>> Kaiping Zheng, National University of Singapore >>> >>>>>> Zhaojing Luo, National University of Singapore >>> >>>>>> Zhongle Xie, National University of Singapore >>> >>>>>> >>> >>>>>> Sponsors >>> >>>>>> >>> >>>>>> Champion >>> >>>>>> >>> >>>>>> Thejas Nair (thejas at apache.org) - Hortonworks >>> >>>>>> >>> >>>>>> Nominated Mentors >>> >>>>>> >>> >>>>>> Thejas Nair (thejas at apache.org) - Hortonworks >>> >>>>>> Alan Gates (gates at apache dot org) - Hortonworks >>> >>>>>> (Seeking more volunteers!) >>> >>>>>> >>> >>>>>> Sponsoring Entity >>> >>>>>> >>> >>>>>> We are requesting the Incubator to sponsor this project. >>> >>>>>> >>> >>>>>> >>> --------------------------------------------------------------------- >>> >>>>>> 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 >>> >>>>> >>> >>> >>> >>> --------------------------------------------------------------------- >>> >>> 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 >>> >>> --------------------------------------------------------------------- To unsubscribe, e-mail: general-unsubscr...@incubator.apache.org For additional commands, e-mail: general-h...@incubator.apache.org
