+1 (Non-binding) -Gaurav
> On Aug 13, 2015, at 10:22 AM, Pramod Immaneni <pra...@datatorrent.com> wrote: > > +1 (Non-binding) > > On Thu, Aug 13, 2015 at 7:48 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 >> [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 === >> * priv...@apex.incubator.apache.org (moderated subscriptions) >> * comm...@apex.incubator.apache.org >> * 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-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. >> >>
