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From Luke Han <luke...@gmail.com>
Subject Re: [VOTE] Accept Apex into the Apache Incubator
Date Fri, 14 Aug 2015 02:23:29 GMT
+1 (Non-binding)


Best Regards!
---------------------

Luke Han

On Fri, Aug 14, 2015 at 9:52 AM, Amol Kekre <amol@datatorrent.com> wrote:

> +1 (Non-binding)
>
> Amol
>
> On Thu, Aug 13, 2015 at 7:48 AM, 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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