+1 binding On Thu, Aug 13, 2015 at 8:18 PM, 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. > >
