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From Atri Sharma <atri.j...@gmail.com>
Subject Re: [VOTE] Accept Apex into the Apache Incubator
Date Fri, 14 Aug 2015 03:35:40 GMT
+1 (Non Binding)
On 13 Aug 2015 22:18, "P. Taylor Goetz" <ptgoetz@apache.org> wrote:

> Following the discussion thread [1], I would like to call a VOTE for
> Accepting Apex as a new Apache Incubator project.
>
> The proposal is available on the wiki [2] and is also attached below.
>
> The VOTE will be open for at least 72 hours.
>
> [ ] +1 Accept Apex into the Incubator
> [ ] ±0 No opinion
> [ ] -1 Do not accept Apex into the Incubator because…
>
> Thanks,
>
> -Taylor
>
> [1] http://s.apache.org/apex_discuss
> [2] https://wiki.apache.org/incubator/ApexProposal
>
>
> == Abstract ==
> Apex is an enterprise grade native YARN big data-in-motion platform that
> unifies stream processing as well as batch processing. Apex processes big
> data in-motion in a highly scalable, highly performant, fault tolerant,
> stateful, secure, distributed, and an easily operable way. It provides a
> simple API that enables users to write or re-use generic Java code, thereby
> lowering the expertise needed to write big data applications.
>
> Functional and operational specifications are separated. Apex is designed
> in a way to enable users to write their own code (aka user defined
> functions) as is and leave all operability to the platform. The API is very
> simple and is designed to allow users to drop in their code as is. The
> platform mainly deals with operability and treats functional code as a
> black box. Operability includes fault tolerance, scalability, security,
> ease of use, metrics api, webservices, etc. In other words there is no
> separation of UDF (user defined functions), as all functional code is UDF.
> This frees users to focus on functional development, and lets platform
> provide operability support. The same code runs as is with different
> operability attributes. The data-in-motion architecture of Apex unifies
> stream as well as batch processing in a single platform. Since Apex is a
> native YARN application, it leverages all the components of YARN without
> duplication. Apex was developed with YARN in mind and has no overlapping
> components/functionality with YARN.
>
> The Apex platform is supplemented by project Malhar, which is a library of
> operators that implement common business logic functions needed by
> customers who want to quickly develop applications. These operators provide
> access to HDFS, S3, NFS, FTP, and other file systems;  Kafka, ActiveMQ,
> RabbitMQ, JMS, and other message systems; MySql, Cassandra, MongoDB, Redis,
> HBase, CouchDB and other databases along with JDBC connectors. The Malhar
> library also includes a host of other common business logic patterns that
> help users to significantly reduce the time it takes to go into production.
> Ease of integration with all other big data technologies is one of the
> primary missions of Malhar.
>
> == Proposal ==
> The goal of this proposal is to establish the core engine of DataTorrent
> RTS product as an Apache Software Foundation (ASF) project in order to
> build a vibrant, diverse, and self-governed open source community around
> the technology. DataTorrent will continue to sell management tools,
> application building tools, easy to use big data applications, and custom
> high end business logic operators. This proposal covers the Apex source
> code (written in Java), Apex documentation and other materials currently
> available on https://github.com/DataTorrent/Apex. This proposal also
> covers the Malhar source code (written in Java), Malhar documentation, and
> other materials currently available on
> https://github.com/DataTorrent/Malhar. We have done a trademark check on
> the name Apex, and have concluded that the Apex name is likely to be a
> suitable project name.
>
> == Background ==
> DataTorrent RTS is a mature and robust product developed as a native YARN
> application. RTS 1.0 was launched in summer of 2014; RTS 2.0 was launched
> in Jan 2015. Both were well received by customers. RTS 3.0 was launched at
> end of July 2015. RTS is among the first enterprise grade platform that was
> developed from the ground up as native YARN application. DataTorrent RTS is
> currently maintained by engineers as a closed source project. Even though
> the engineers behind RTS are experienced software engineers and are
> knowledge leaders in data-in-motion platforms, they have had little
> exposure to the open source governance process. Customers are currently
> running applications based on DataTorrent RTS in production.
>
> == Rationale ==
> Big data applications written for non-Hadoop platforms typically require
> major rewrites  to get them to work with Hadoop. This rewriting creates a
> significant bottleneck in terms of resources (expertise) which in turn
> jeopardizes the viability of such an endeavour. It is hard enough to
> acquire big data expertise, demanding additional expertise to do a major
> code conversion makes it a very hard problem for projects to successfully
> migrate to Hadoop. Also, due to the batch processing nature of Hadoop’s
> MapReduce paradigm, users often have to wait tens of minutes to see results
> and act on them due to various delays in data flow. DataTorrent’s RTS
> data-in-motion architecture is designed to address this problem. It enables
> even the non big data developer to write code and operate it in a scalable,
> fault tolerant manner. The big data-in-motion architecture of DataTorrent’s
> RTS enables ease of integration into current enterprise infrastructure.
> This goal was achieved by keeping the API simple and empowering users to
> put in the connector code as is (or with minimal changes).
>
> Malhar is a manifestation of this reality, and we or the customer
> engineers were able to create these connectors within a day or so if not
> within a week. Connectors include those to integrate with message bus(es),
> file systems, databases, other protocols, and more continue to be added.
> Over a period of time we expect users to simply pick a connector that
> already exists in Malhar and quickly begin integrating with their current
> enterprise infrastructure. Within the data-in-motion architecture a stream
> application is one with connector(s) to say Kafka, JMS, or Flume; while a
> batch application is one with connector(s) to HDFS, HBase, FTP, NFS, S3n
> etc. This allows usage of the platform for both stream as well as batch
> processing with same business logic. Complete separation of user written
> application code from all operational aspects of the system, as well as
> support code for YARN, significantly expands the potential use cases that
> can migrate to use Hadoop.
>
> Apex will enable Hadoop eco-system to migrate a lot more use cases. It
> will enable the Hadoop eco-system to deliver on a promise to rapidly
> transform current IT infrastructure. Apex will help in significantly
> increasing productization of big data projects. One of the main barometers
> of success in the Hadoop eco-system is significant reduction of time to
> market for big data applications migrating to Hadoop. We believe that Apex
> will be one of the platforms that will enable users to extract value from
> big data, by reducing time to market. This rapid innovation can be
> optimally achieved through a vibrant, diverse, self-governed community
> collectively innovating around Apex and the Malhar library, while at the
> same time cross-pollinating with various other big data platforms. ASF is
> an ideal place to meet this goal.
>
> == Initial Goals ==
> Our initial goals are to bring Apex and Malhar repositories into the ASF,
> adapt internal engineering processes to open development, and foster a
> collaborative development model in accordance with the "Apache Way."
> DataTorrent plans to develop new functionality in an open, community-driven
> way. To get there, the existing internal build, test and release processes
> will be refactored to support open development. We already have an active
> user community on google groups that we intend to migrate to Apache.
>
> == Current Status ==
> Currently, the project Apex code base is available under Apache 2.0
> license (https://github.com/DataTorrent/Apex). Project Malhar code base
> is available under Apache 2.0 license (
> https://github.com/DataTorrent/Malhar). Project Malhar was open sourced 2
> years ago which should make it easy for the project Malhar team to adapt to
> an  open, collaborative, and meritocratic environment. Contributors of
> Malhar are employees of DataTorrent or have agreed to the shift to Apache.
> Project Apex, in contrast, was developed as a proprietary, closed-source
> product, but the internal engineering practices adopted by the development
> team were common to Malhar, and should lend themselves well to an open
>  environment. DataTorrent plans to execute a software grant agreement as
> part of the launch of the incubation of Apex as an Apache project.
>
> The DataTorrent team has always focused on building a robust end user
> community of paying and non-paying customers. We think that the existing
> community centered around the existing google groups mailing list should be
> relatively easy to transform into an Apache-style community including both
> users and developers.
>
> === Meritocracy ===
> Our proposed list of initial committers include the current RTS R&D team,
> and our existing customers. This group will form a base for the broader
> community we will invite to collaborate on the codebase. We intend to
> radically expand the initial developer and user community by running the
> project in accordance with the "Apache Way". Users and new contributors
> will be treated with respect and welcomed. By participating in the
> community and providing quality patches/support that move the project
> forward, they will earn merit. They also will be encouraged to provide
> non-code contributions (documentation, events, presentations, community
> management, etc.) and will gain merit for doing so. Those with a proven
> support and quality track record will be encouraged to become committers.
>
> === Community ===
> If Apex is accepted for incubation, the primary initial goal will be
> transitioning the core community towards embracing the Apache Way of
> project governance. We will solicit major existing contributors to become
> committers on the project from the start. It should be noted that the
> existing community is already more diverse in many ways than some top-level
> Apache projects. We expect that we can encourage even more diversity.
>
> === Core Developers ===
> While a few core developers are skilled in working in openly governed
> Apache communities, most of the core developers are currently NOT
> affiliated with the ASF and would require new ICLAs before committing to
> the project. There would also be a learning curve associated with this
> on-boarding. Changing current development practices to be more open will be
> an important step.
>
> === Alignment ===
> The following existing ASF projects provide related functionality as that
> provided by Apex and should be considered when reviewing Apex proposal:
>
> Apache HadoopⓇ is a distributed storage and processing framework for very
> large datasets focusing primarily on batch processing for analytic
> purposes. Apex is a native YARN application. The Apex and Malhar roadmap
> includes plans to continue to leverage YARN, and help the YARN community
> develop the ability to support long running applications. Apex uses DFS
> interface of its core checkpoint/commit. Malhar has a large number of
> operators that leverage HDFS and other Apache projects. Our roadmap
> includes plans to continue to deepen the currently close integration with
> HDFS.
>
> Apache HBase offers tabular data stored in Hadoop based on the Google
> Bigtable model. Malhar has HBase connectors to ease integration with HBase.
> Malhar roadmap includes plans to continue to enhance integration with
> Apache HBase.
>
> Apache Kafka offers distributed and durable publish-subscribe messaging.
> Malhar integrates Kafka with Hadoop through feature rich connectors and
> supports ingest as well as analytical functions to incoming data. Raw data
> can be ingested from Kafka and results can be written to Kafka. Malhar
> roadmap includes plans to continue to enhance integration with Apache Kafka.
>
> Apache Flume is a distributed, reliable, and available service for
> efficiently collecting, aggregating, and moving large amounts of log data.
> Malhar has Flume connectors to ease integration with Flume. These
> connectors ensures that ingestion with Flume is fault tolerant and thus can
> be done in real-time with the same SLA as Flume’s HDFS connectors. Malhar
> roadmap includes plans to continue to enhance integration with Apache Flume.
>
> Apache Cassandra is a highly scalable, distributed key-value store that
> focuses on eventual consistency. Malhar has connectors to ease integration
> with Cassandra. Malhar roadmap includes plans to continue to enhance
> integration with Apache Cassandra.
>
> Apache Accumulo is a distributed key-value store based on Google’s
> BigTable design. Malhar has connectors to ease integration with Accumulo.
> The Malhar roadmap includes plans to continue to enhance integration with
> Apache Accumulo.
>
> Apache Tez is aimed at building an application framework which allows for
> a complex DAG of tasks for process data. The Apex and Malhar roadmaps
> include plans to integrate with Apache Tez but this is not currently
> supported.
>
> Apache ActiveMQ and its sub project Apache Apollo offers a powerful
> message queue framework. Malhar has ActiveMQ connectors that ease
> integration with ActiveMQ.
>
> Apache Spark is an engine for processing large datasets, typically in a
> Hadoop cluster. Malhar project makes it easy for users to integrate with
> Spark. The Malhar roadmap includes plans to continue to enhance integration
> with Apache Spark.
>
> Apache Flink is an engine for scalable batch and stream data processing.
> Malhar project makes it easy for users to integrate with Flink. There is
> overlap in how Flink leverages data-in-motion architecture for both stream
> and batch processing, and it does subscribe to our thought process that
> data-in-motion can handle both stream and batch, meanwhile a batch only
> engine will find it harder to manage streams. We differ in terms of how we
> handle operability, user defined code, metrics, webservices etc. Apex is
> very operational oriented, while Flink has much more focus on functional
> elements. Malhar and rapid availability of common business logic is another
> differentiator. We believe both these approaches are valid and the
> community and innovation will gain by through cross pollination. We plan to
> integrate with Apache Flink via HDFS for now.
>
> Apache Hive software facilitates querying and managing large datasets
> residing in distributed storage. Malhar project makes it easy for users to
> integrate with Apache Hive. The Malhar roadmap includes plans to continue
> to enhance integration with Apache Hive.
>
> Apache Pig is a platform for analyzing large data sets.  Pig consists of a
> high-level language for expressing data analysis programs, coupled with
> infrastructure for evaluating these programs. The Apex and Malhar roadmaps
> include plans to integrate with Apache Pig.
>
> Apache Storm is a distributed realtime computation system. Malhar makes it
> easy for users to integrate with Apache Storm. We plan to integrate with
> Apache Storm via HDFS for now. Malhar roadmaps include plans to continue to
> support mechanism for integration with Apache Storm.
>
> Apache Samza is a distributed stream processing framework. Malhar makes it
> easy for users to integrate with Apache Samza. We plan to integrate with
> Apache Samza via HDFS or Apache Kafka for now. Malhar roadmaps include
> plans to continue to support mechanism for integration with Apache Samza.
>
> Apache Slider is a YARN application to deploy existing distributed
> applications on YARN, monitor them, and make them larger or smaller as
> desired even when the application is running. Once Slider matures, we will
> take a look at close integration of Apex with Slider.
>
> Project Malhar and Apex are aligned to many more Apache projects and other
> open source projects as ease of integration with other technologies is one
> of the primary goals of this project. These include Apache Solr,
> ElasticSearch, MongoDB, Aerospike, ZeroMQ, CouchDB, CouchBase, MemCache,
> Redis, RabbitMQ, Apache Derby.
>
> == Known Risks ==
> Development has been sponsored mostly by a single company (DataTorrent,
> Inc.) thus far and coordinated mainly by the core DataTorrent RTS and
> Malhar team, with active participation from our current customers.
>
> For the project to fully transition to the Apache Way governance model,
> development must shift towards the merit-centric model of growing a
> community of contributors balanced with the needs for extreme stability and
> core implementation coherency.
>
> The tools and development practices in place for the DataTorrent RTS and
> Malhar products are compatible with the ASF infrastructure and thus we do
> not anticipate any on-boarding pains. Migration from the current GitHub
> repository is also expected to be straightforward.
>
> === Orphaned products ===
> DataTorrent is fully committed to DataTorrent Apex and Malhar and the
> product will continue to be based on the Apex project. Moreover,
> DataTorrent has a vested interest in making Apex succeed by driving its
> close integration with sister ASF projects. We expect this to further
> reduce the risk of orphaning the product.
>
> === Inexperience with Open Source ===
> DataTorrent has embraced open source software by open sourcing Malhar
> project under Apache 2.0 license. The DataTorrent team includes veterans
> from the Yahoo! Hadoop team. Although some of the initial committers have
> not been developers on an entirely open source, community-driven project,
> we expect to bring to bear the open development practices of Malhar to the
> Apex project. Additionally, several ASF veterans agreed to mentor the
> project and are listed in this proposal. The project will rely on their
> guidance and collective wisdom to quickly transition the entire team of
> initial committers towards practicing the Apache Way. DataTorrent is also
> driving the Kafka on YARN (KOYA) initiative.
>
> === Homogeneous Developers ===
> While most of the initial committers are employed by DataTorrent, we have
> already seen a healthy level of interest from our existing customers and
> partners. We intend to convert that interest directly into participation
> and will be investing in activities to recruit additional committers from
> other companies.
>
> === Reliance on Salaried Developers ===
> Most of the contributors are paid to work in the Big Data space. While
> they might wander from their current employers, they are unlikely to
> venture far from their core expertises and thus will continue to be engaged
> with the project regardless of their current employers.
>
> === Relationships with Other Apache Products ===
> As mentioned in the Alignment section, Apex may consider various degrees
> of integration and code exchange with Apache Hadoop (YARN and HDFS), Apache
> Kafka, Apache HBase, Apache Flume, Apache Cassandra, Apache Accumulo,
> Apache Tez, Apache Hive, Apache Pig, Apache Storm, Apache Samza, Apache
> Spark, Apache Slider. Given the success that the DataTorrent RTS product
> enjoyed, we expect integration points to be inside and outside the project.
> We look forward to collaborating with these communities as well as other
> communities under the Apache umbrella.
>
> === An Excessive Fascination with the Apache Brand ===
> While we intend to leverage the Apache ‘branding’ when talking to other
> projects as testament of our project’s ‘neutrality’, we have no plans for
> making use of Apache brand in press releases nor posting billboards
> advertising acceptance of Apex into Apache Incubator.
>
>
> == Documentation ==
> See documentation for the current state of the project documentation
> available as part of the GitHub repositories -
> https://github.com/DataTorrent/Apex; https://github.com/DataTorrent/Malhar.
> In addition a list of demos that serve as a how to guide are available at
> https://github.com/DataTorrent/Malhar/tree/master/demos
>
> == Initial Source ==
> DataTorrent has released the source code for Apex under Apache 2.0 License
> at https://github.com/DataTorrent/Apex, and that of Malhar under Apache
> 2.0 licence at https://github.com/DataTorrent/Malhar. We encourage ASF
> community members interested in this proposal to download the source code,
> review it and try out the software.
>
> == Source and Intellectual Property Submission Plan ==
> As soon as Apex is approved to join Apache Incubator, DataTorrent will
> execute a Software Grant Agreement and the source code will be transitioned
> onto ASF infrastructure. The code is already licensed under the  Apache
> Software License, version 2.0. We know of no legal encumberments that would
> inhibit the transfer of source code to the ASF.
>
> == External Dependencies ==
> All dependencies fall under the permissive licenses categories, or weak
> copy left (http://www.apache.org/legal/resolved.html#category-b). We
> intend to remove the dependencies on GPL licensed technologies on which
> APex or Malhar depend. These technologies are optional and have been marked
> as such.
>
> Embedded dependencies (relocated):
>    * None
>
> Runtime dependencies:
>    * activemq-client
>    * ant
>    * async-http-client
>    * bval-jsr303
>    * commons-beanutils
>    * commons-codec
>    * commons-lang3
>    * commons-compiler
>    * embassador
>    * fastutil
>    * guava
>    * hadoop-common
>    * hadoop-common-tests
>    * hadoop-yarn-client
>    * httpclient
>    * jackson-core-asl
>    * jackson-mapper-asl
>    * javax.mail
>    * jersey-apache-client4
>    * jersey-client
>    * jetty-servlet
>    * jetty-websocket
>    * jline
>    * kryo
>    * named-regexp
>    * netlet
>    * rhino (GPL 2.0, optional)
>    * slf4j-api
>    * slf4j-log4j12
>    * validation-api
>    * xbean-asm5-shaded
>    * zip4j
>
> Module or optional dependencies
>    * accumulo-core
>    * aerospike-client
>    * amqp-client
>    * aws-java-sdk-kinesis
>    * cassandra-driver-core
>    * couchbase-client
>    * CouchbaseMock
>    * elasticsearch
>    * geoip-api (LGPL, optional)
>    * hbase
>    * hbase-client
>    * hbase-server
>    * hive-exec
>    * hive-service
>    * hiveunit
>    * javax.mail-api
>    * jedis
>    * jms-api
>    * jri (GPL, optional)
>    * jriengine (LGPL, optional)
>    * jruby (LGPL, optional)
>    * jython (PSF License, optional)
>    * jzmq (LGPL, optional)
>    * kafka_2.10
>    * lettuce (GPL, optional)
>    * libthrift
>    * Memcached-Java-Client
>    * mongo-java-driver
>    * mqtt-client
>    * mysql-connector-java (GPL2, optional)
>    * org.ektorp
>    * rengine (LGPL, optional)
>    * rome
>    * solr-core
>    * solr-solrj
>    * spymemcached
>    * sqlite4java
>    * super-csv
>    * twitter4j-core
>    * twitter4j-stream
>    * uadetector-resources
>    * org.apache.servicemix.bundles.splunk
>
> Build only dependencies:
>    * None
>
> Test only dependencies:
>    * activemq-broker
>    * activemq-kahadb-store
>    * greenmail
>    * hadoop-yarn-server-tests
>    * hsqldb
>    * janino
>    * junit
>    * MockFtpServer
>    * mockito-all
>    * testng
>
> Cryptography N/A
>
> == Required Resources ==
> === Mailing lists ===
>    * private@apex.incubator.apache.org (moderated subscriptions)
>    * commits@apex.incubator.apache.org
>    * dev@apex.incubator.apache.org
>
> === Git Repository ===
>    * https://git-wip-us.apache.org/repos/asf/incubator-apex-core.git
>    * https://git-wip-us.apache.org/repos/asf/incubator-apex-malhar.git
>
> === Issue Tracking ===
>    * JIRA Project Apex (APEX_CORE) // If '_' is not allowed, use APEXCORE
>    * JIRA Project Malhar (APEX_MALHAR) // If '_' is not allowed use
> APEXMALHAR
>
> === Other Resources ===
>    * Means of setting up regular builds for apex-core on builds.apache.org
>    * Means of setting up regular builds for apex-malhar on
> builds.apache.org
>
> === Rationale for Malhar and Apex having separate git and jira ===
> We managed Malhar and Apex as two repos and two jiras on purpose. Both
> code bases are released under Apache 2.0 and are proposed for incubation.
> In terms of our vision to enable innovation around a native YARN
> data-in-motion that unifies stream processing as well as batch processing
> Malhar and Apex go hand in hand. Apex has base API that consists of java
> api (functional), and attributes (operability). Malhar is a manifestation
> of this api, but from user perspective, Malhar is itself an API to leverage
> business logic. Over past three years we have found that the cadence of
> release and api changes in Malhar is much rapid than Apex and it was
> operationally much easier to separate them into their own repos. Two repos
> will reflect clear separation of engine (Apex) and operators/business logic
> (Malhar). It will allow or independent release cycles (operator change
> independent of engine due to stable API). We however do not believe in two
> levels of committers. We believe there should be one community that works
> across both and innovates with ideas that Malhar and Apex combined provide
> the value proposition. We are proposing that Apache incubation process help
> us to foster development of one community (mailing list, committers), and a
> yet be ok with two repos. We are proposing that this be taken up during
> incubation. Community will learn if this works. The decision on whether to
> split them into two projects be taken after the learning curve during
> incubation.
>
> == Initial Committers ==
>    * Roma Ahuja (rahuja at directv dot com)
>    * Isha Arkatkar (isha at datatorrent dot com)
>    * Raja Ali (raji at silverspringnet dot com)
>    * Sunaina Chaudhary ( SChaudhary at directv dot com)
>    * Bhupesh Chawda (bhupesh at datatorrent dot com)
>    * Chaitanya Chelobu (chaitanya at datatorrent dot com)
>    * Bright Chen (bright at datatorrent dot com)
>    * Pradeep Dalvi (pradeep dot dalvi at datatorrent dot com)
>    * Sandeep Deshmukh (sandeep at datatorrent dot com)
>    * Yogi Devendra (yogi at datatorrent dot com)
>    * Cem Ezberci (hasan dot ezberci at ge dot com)
>    * Timothy Farkas (tim at datatorrent dot com)
>    * Ilya Ganelin (ilya dot ganelin at capitalone dot com)
>    * Vitthal Gogate (vitthal_gogate at yahoo dot com)
>    * Parag Goradia (parag dot goradia at ge dot com)
>    * Tushar Gosavi (tushar at datatorrent dot com)
>    * Priyanka Gugale (priyanka at datatorrent dot com)
>    * Gaurav Gupta (gaurav at datatorrent dot com)
>    * Sandesh Hegde (sandesh at datatorrent dot com)
>    * Siyuan Hua ( siyuan at datatorrent dot com)
>    * Ajith Joseph (ajoseph at silverspring dot com)
>    * Amol Kekre ( amol at datatorrent dot com)
>    * Chinmay Kolhatkar ( chinmay at datatorrent dot com)
>    * Pramod Immaneni ( pramod at datatorrent dot com)
>    * Anuj Lal ( anuj dot lal at ge dot com)
>    * Dongsu Lee (dlee3 at directv dot com)
>    * Vitaly Li (blossom dot valley at gmail dot com)
>    * Dean Lockgaard (dean  at datatorrent dot com)
>    * Rohan Mehta (rohan_mehta at apple dot com)
>    * Adi Mishra (apmishra at directv dot com, adi dot mishra at gmail dot
> com)
>    * Chetan Narsude (chetan  at datatorrent dot com)
>    * Darin Nee (dnee at silverspring dot com)
>    * Alexander Parfenov (sasha at datatorrent dot com)
>    * Andrew Perlitch (andy at datatorrent dot com)
>    * Shubham Phatak (shubham at datatorrent dot com)
>    * Ashwin Putta (ashwin at datatorrent dot com)
>    * Rikin Shah (shah_rikin at yahoo dot com)
>    * Luis Ramos (l dot ramos at ge dot com)
>    * Munagala Ramanath (ram at datatorrent dot com)
>    * Vlad Rozov (vlad dot rozov at datatorrent dot com)
>    * Atri Sharma (atri dot jiit at gmail dot com)
>    * Chandni Singh (chandni at datatorrent dot com)
>    * Venkatesh Sivasubramanian (venkateshs at ge dot com)
>    * Aniruddha Thombare (aniruddha at datatorrent dot com)
>    * Jessica Wang (jessica at datatorrent dot com)
>    * Thomas Weise (thomas at datatorrent dot com)
>    * David Yan (david at datatorrent dot com)
>    * Kevin Yang (yang dot k at ge dot com)
>    * Brennon York (brennon dot york at capitalone dot com)
>
> == Affiliations ==
>    * Apple: Vitaly Li, Rohan Mehta
>    * Barclays: Atri Sharma
>    * Class Software: Justin Mclean
>    * CapitalOne: Ilya Ganelin, Brennon York
>    * DataTorrent: everyone else on this proposal
>    * Datachief: Rikin Shah
>    * DirecTV: Roma Ahuja, Sunaina Chaudhary, Dongsu Lee, Adi Mishra
>    * E8security: Vitthal Gogate
>    * General Electric: Cem Ezberci, Parag Goradia, Anuj Lal, Luis Ramos,
> Venkatesh Sivasubramanian, Kevin Yang
>    * Hortonworks: Alan Gates, Taylor Goetz, Chris Nauroth, Hitesh Shah
>    * MapR: Ted Dunning
>    * SilverSpring Networks: Raja Ali, Ajith Joseph, Darin Nee
>
> == Sponsors ==
>
> === Champion ===
> Ted Dunning
>
> === Nominated Mentors ===
>
> The initial mentors are listed below:
>    * Ted Dunning - Apache Member, MapR
>    * Alan Gates - Apache Member, Hortonworks
>    * Taylor Goetz - Apache Member, Hortonworks
>    * Justin Mclean - Apache Member, Class Software
>    * Chris Nauroth - Apache Member, Hortonworks
>    * Hitesh Shah: Apache Member, Hortonworks
>
> === Sponsoring Entity ===
>
> We would like to propose Apache incubator to sponsor this project.
>
>

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