+1 (binding) -Taylor
> On Aug 13, 2015, at 10:48 AM, P. Taylor Goetz <ptgo...@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 <http://s.apache.org/apex_discuss> > [2] https://wiki.apache.org/incubator/ApexProposal > <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 <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 > <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 <https://github.com/DataTorrent/Apex>). > Project Malhar code base is available under Apache 2.0 license > (https://github.com/DataTorrent/Malhar > <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/Apex>; > https://github.com/DataTorrent/Malhar > <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 > <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 <https://github.com/DataTorrent/Apex>, > and that of Malhar under Apache 2.0 licence at > https://github.com/DataTorrent/Malhar > <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 > <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 === > * priv...@apex.incubator.apache.org > <mailto:priv...@apex.incubator.apache.org> (moderated subscriptions) > * comm...@apex.incubator.apache.org > <mailto:comm...@apex.incubator.apache.org> > * d...@apex.incubator.apache.org <mailto:d...@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-core.git> > * https://git-wip-us.apache.org/repos/asf/incubator-apex-malhar.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 > <http://builds.apache.org/> > * Means of setting up regular builds for apex-malhar on builds.apache.org > <http://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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