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From Luke Han <luke...@gmail.com>
Subject [RESULT] [VOTE] Accept Kylin into the Apache Incubator
Date Tue, 25 Nov 2014 10:45:37 GMT
The vote has passed with 7 binding +1, 1 non binding +1, no 0 and -1s.

Binding +1s :
John D. Ament
Henry Saputra
Andrew Purtell
Ted Dunning
Bertrand Delacretaz
Sergio Fernández
Alan D. Cabrera


Non Binding +1s:
Nick Dimiduk

Thanks everyone for voting. We will proceed with the next steps as per the
IPMC guidelines.

Thanks
Luke


2014-11-21 6:31 GMT+08:00 Luke Han <luke.hq@gmail.com>:

> Following the discussion earlier in the thread:
>
> http://mail-archives.apache.org/mod_mbox/incubator-general/201411.mbox/%3cCAKmQrOb22+n+R++dAte33f3pCpyUjhFoEaqRMS3T-UdJwK66GQ@mail.gmail.com%3e
>
> I would like to call a VOTE for accepting Kylin as a new incubator project.
>
> The proposal is available at:
> https://wiki.apache.org/incubator/KylinProposal
>
> and posted the text of the proposal below also.
>
> Vote is open until 24th November 2014, 23:59:00 UTC
>
> [ ] +1 accept Kylin in the Incubator
> [ ] ±0
> [ ] -1 because...
>
>
> Thanks
> Luke
>
>
> Kylin Proposal
> ==============
>
> # Abstract
>
> Kylin is a distributed and scalable OLAP engine built on Hadoop to
> support extremely large datasets.
>
> # Proposal
>
> Kylin is an open source Distributed Analytics Engine that provides
> multi-dimensional analysis (MOLAP) on Hadoop. Kylin is designed to
> accelerate analytics on Hadoop by allowing the use of SQL-compatible
> tools. Kylin provides a SQL interface and multi-dimensional analysis
> (MOLAP) on Hadoop to support extremely large datasets and tightly
> integrate with Hadoop ecosystem.
>
> ## Overview of Kylin
>
> Kylin platform has two parts of data processing and interactive:
> First, Kylin will read data from source, Hive, and run a set of tasks
> including Map Reduce job, shell script to pre-calcuate results for a
> specified data model, then save the resulting OLAP cube into storage
> such as HBase. Once these OLAP cubes are ready, a user can submit a
> request from any SQL-based tool or third party applications to Kylin’s
> REST server. The Server calls the Query Engine to determine if the
> target dataset already exists. If so, the engine directly accesses the
> target data in the form of a predefined cube, and returns the result
> with sub-second latency. Otherwise, the engine is designed to route
> non-matching queries to whichever SQL on Hadoop tool is already
> available on a Hadoop cluster, such as Hive.
>
> Kylin platform includes:
>
> - Metadata Manager: Kylin is a metadata-driven application. The Kylin
> Metadata Manager is the key component that manages all metadata stored
> in Kylin including all cube metadata. All other components rely on the
> Metadata Manager.
>
> - Job Engine: This engine is designed to handle all of the offline
> jobs including shell script, Java API, and Map Reduce jobs. The Job
> Engine manages and coordinates all of the jobs in Kylin to make sure
> each job executes and handles failures.
>
> - Storage Engine: This engine manages the underlying storage –
> specifically, the cuboids, which are stored as key-value pairs. The
> Storage Engine uses HBase – the best solution from the Hadoop
> ecosystem for leveraging an existing K-V system. Kylin can also be
> extended to support other K-V systems, such as Redis.
>
> - Query Engine: Once the cube is ready, the Query Engine can receive
> and parse user queries. It then interacts with other components to
> return the results to the user.
>
> - REST Server: The REST Server is an entry point for applications to
> develop against Kylin. Applications can submit queries, get results,
> trigger cube build jobs, get metadata, get user privileges, and so on.
>
> - ODBC Driver: To support third-party tools and applications – such as
> Tableau – we have built and open-sourced an ODBC Driver. The goal is
> to make it easy for users to onboard.
>
> # Background
>
> The challenge we face at eBay is that our data volume is becoming
> bigger and bigger while our user base is becoming more diverse. For
> e.g. our business users and analysts consistently ask for minimal
> latency when visualizing data on Tableau and Excel. So, we worked
> closely with our internal analyst community and outlined the product
> requirements for Kylin:
>
> - Sub-second query latency on billions of rows
> - ANSI SQL availability for those using SQL-compatible tools
> - Full OLAP capability to offer advanced functionality
> - Support for high cardinality and very large dimensions
> - High concurrency for thousands of users
> - Distributed and scale-out architecture for analysis in the TB to PB size
> range
>
> Existing SQL-on-Hadoop solutions commonly need to perform partial or
> full table or file scans to compute the results of queries. The cost
> of these large data scans can make many queries very slow (more than a
> minute). The core idea of MOLAP (multi-dimensional OLAP) is to
> pre-compute data along dimensions of interest and store resulting
> aggregates as a "cube". MOLAP is much faster but is inflexible. We
> realized that no existing product met our exact requirements
> externally – especially in the open source Hadoop community. To meet
> our emerging business needs, we built a platform from scratch to
> support MOLAP for these business requirements and then to support more
> others include ROLAP. With an excellent development team and several
> pilot customers, we have been able to bring the Kylin platform into
> production as well as open source it.
>
> # Rationale
>
> When data grows to petabyte scale, the process of pre-calculation of a
> query takes a long time and costly and powerful hardware. However,
> with the benefit of Hadoop’s distributed computing architecture, jobs
> can leverage hundreds or thousands of Hadoop data nodes. There still
> exists a big gap between the growing volume of data and interactive
> analytics:
>
> - Existing Business Intelligence (OLAP) platforms cannot scale out to
> support fast growing data.
> - Existing SQL on Hadoop projects are not designed for OLAP use cases,
> huge tables joins will always take long time to scan and calculate.
> - No mature OLAP solution exists on Hadoop
>
> As mentioned in the background, the business requirements triggered by
> increase in data volume drove eBay to invest in building a solution
> from scratch to offer Analytics capability on Hadoop cluster. With
> Hadoop’s power of distributed computing Kylin can perform
> pre-calculations in parallel and merge the final results, thereby
> significantly reducing the processing time.
>
> To serve queries by the analyst community, Kylin generates cuboids
> with all possible combinations of dimensions, and calculate all
> metrics at different levels. The cuboids are then integrated to form a
> pre-calculated OLAP cube. All cuboids are key-value structured: keys
> are composites formed from combinations of multiple dimensions and
> values are aggregations results for that particular combination of
> dimensions. Kylin uses HBase to store cubes. HBase is useful because
> it supports efficient searches across ranges of data.
>
> # Current Status
>
> ## Meritocracy
>
> Kylin has been deployed in production at eBay and is processing
> extremely large datasets. The platform has demonstrated great
> performance benefits and has proved to be a better way for analysts to
> leverage data on Hadoop with a more convenient approach using their
> favorite tool.
>
> ## Community
>
> Kylin seeks to develop developer and user communities during incubation.
>
> ## Core Developers
>
> Kylin is currently being designed and developed by six engineers from
> eBay Inc. – Jiang Xu, Luke Han, Yang Li, George Song, Hongbin Ma and
> Xiaodong Duo. In addition, some outside contributors are actively
> contributing in design and development. Among them, Julian Hyde from
> Hortonworks is a very important contributor. All of these core
> developers have deep expertise in Hadoop and the Hadoop Ecosystem in
> general.
>
> ## Alignment
>
> The ASF is a natural host for Kylin given that it is already the home
> of Hadoop, Pig, Hive, and other emerging cloud software projects.
> Kylin was designed to offer OLAP capability on Hadoop from the
> beginning in order to solve data access and analysis challenges in
> Hadoop clusters. Kylin complements the existing Hadoop analytics area
> by providing a comprehensive solution based on pre-computed views.
>
> In Kylin, we are leveraging an open-source dynamic data management
> framework called Apache Calcite to parse SQL and plug in our code.
> Apache Calcite was previously called Optiq, was originally authored by
> Julian Hyde and is now an Apache Incubator project.
>
> # Known Risks
>
> ## Orphaned Products
>
> The core developers of Kylin team plan to work full time on this
> project. There is very little risk of Kylin getting orphaned since at
> least one large company (eBay) is extensively using it in their
> production Hadoop clusters. For example, currently there are 3 use
> cases with more that 12+Billion rows and 1000 activity requests per
> day using Kylin in production. Furthermore, since Kylin was open
> sourced at the beginning of October 2014, it has received more than
> 280 stars and been forked nearly 100 times. Kylin has one major
> release so far and and received 5 pull requests from contributors in
> the first month pull requests from external sources in the last month,
> which further demonstrates Kylin as a very active project. We plan to
> extend and diversify this community further through Apache.
>
> ## Inexperience with Open Source
>
> The core developers are all active users and followers of open source.
> They are already committers and contributors to the Kylin Github
> project. All have been involved with the source code that has been
> released under an open source license, and several of them also have
> experience developing code in an open source environment. Though the
> core set of Developers do not have Apache Open Source experience,
> there are plans to onboard individuals with Apache open source
> experience on to the project.
>
> ## Homogenous Developers
>
> The core developers include developers from eBay, Ctrip and
> Hortonworks. Apache Incubation process encourages an open and diverse
> meritocratic community. Apache Kylin has the required amount of
> diversity with committers from three different organizations, but is
> also aware that bulk of the commits come from a single entity. Kylin
> intends to make every possible effort to build a diverse, vibrant and
> involved community and has already received substantial interest from
> various organizations
>
> ## Reliance on Salaried Developers
>
> eBay invested in Kylin as the OLAP solution on top of Hadoop clusters
> and some of its key engineers are working full time on the project. In
> addition, since there is a growing Big Data need for scalable OLAP
> solutions on Hadoop, we look forward to other Apache developers and
> researchers to contribute to the project. Additional contributors,
> including Apache committers have plans to join this effort shortly.
> Also key to addressing the risk associated with relying on Salaried
> developers from a single entity is to increase the diversity of the
> contributors and actively lobby for Domain experts in the BI space to
> contribute. Apache Kylin intends to do this. One approach already
> taken is to approach the Apache Drill project to explore possible
> cooperation.
>
> ## Relationships with Other Apache Products
>
> Kylin has a strong relationship and dependency with Apache Hadoop
> HBase, Hive and Calcite. Being part of Apache’s Incubation community,
> could help with a closer collaboration among these four projects and
> as well as others.
>
> Kylin is likely to have substantial value to Apache Drill due to the
> common use of Calcite as a query optimization engine and similar
> approaches between Kylin's approach to cubing and Drill's approach to
> input sources.
>
> ## An Excessive Fascination with the Apache Brand
>
> Kylin is proposing to enter incubation at Apache in order to help
> efforts to diversify the committer-base, not so much to capitalize on
> the Apache brand. The Kylin project is in production use already
> inside EBay, but is not expected to be an EBay product for external
> customers. As such, the Kylin project is not seeking to use the Apache
> brand as a marketing tool.
>
> # Documentation
>
> Information about Kylin can be found at
> https://github.com/KylinOLAP/Kylin. The following links provide more
> information about Kylin in open source:
>
> - Kylin web site: http://kylin.io
> - Codebase at Github: https://github.com/KylinOLAP/Kylin
> - Issue Tracking: https://github.com/KylinOLAP/Kylin/issues
> - User community: https://groups.google.com/forum/#!forum/kylin-olap
>
> ## Initial Source
>
> Kylin has been under development since 2013 by a team of engineers at
> eBay Inc. It is currently hosted on Github.com under an Apache license
> at https://github.com/KylinOLAP/Kylin
>
> ## External Dependencies
>
> Kylin has the following external dependencies.
>
> * Basic
>
> - JDK 1.6+
> - Apache Maven
> - JUnit
> - DBUnit
> - Log4j
> - Slf4j
> - Apache Commons
> - Google Guava
> - Jackson
>
> * Hadoop
>
> - Apache Hadoop
> - Apache HBase
> - Apache Hive
> - Apache Zookeeper
> - Apache Curator
>
> * Utility
>
> - H2
> - JSCH
>
> * REST Service
>
> - Spring
>
> * Query
>
> - Antlr
> - Apache Calcite (formerly Optiq)
> - Linq4j
>
> * Job
>
> - Quartz
>
> * Web build tool
>
> - NPM
> - Grunt
> - bower
>
> * Web
>
> - Angular JS
> - jQuery
> - Bootstrap
> - D3 JS
> - ACE
>
> ##Cryptography
>
> Kylin will eventually support encryption on the wire. This is not one
> of the initial goals, and we do not expect Kylin to be a controlled
> export item due to the use of encryption. Kylin supports but does not
> require the Kerberos authentication mechanism to access secured Hadoop
> services.
>
> # Required Resources
>
> ## Mailing List
>
> - kylin-private for private PMC discussions (with moderated subscriptions)
> - kylin-dev
> - kylin-commits
>
> ##Subversion Directory
>
> Git is the preferred source control system: git://git.apache.org/Kylin
>
> ## Issue Tracking
>
> JIRA Kylin (KYLIN)
>
> ## Other Resources
>
> The existing code already has unit tests so we will make use of
> existing Apache continuous testing infrastructure. The resulting load
> should not be very large.
>
> # Initial Committers
>
> - Jiang Xu < jiangxu.china at gmail dot com>
> - Luke Han <lukhan at ebay dot com>
> - Yang Li <yangli9 at ebay dot com>
> - George Song <ysong1 at ebay dot com>
> - Hongbin Ma <honma at ebay dot com>
> - Xiaodong Duo < oranjedog at gmail dot com>
> - Julian Hyde < jhyde at apache dot org >
> - Ankur Bansal < abansal at ebay dot com>
>
> ## Affiliations
>
> The initial committers are employees of eBay Inc., Ctrip and
> Hortonworks. The nominated mentors are employees of Hortonworks, MapR
> Technologies and Pivotal.
>
> # Sponsors
>
> ## Champion
>
> - Owen O’Malley < omalley at apache dot org >
> - Ted Dunning <tdunning at apache dot org>
>
> ## Nominated Mentors
>
> - Owen O’Malley < omalley at apache dot org > - Apache IPMC member,
> Co-founder and Senior Architect, Hortonworks
> - Ted Dunning < tdunning at apache dot org> - Apache IPMC member,
> Chief Architect, MapR Technologies
> - Henry Saputra <hsaputra at apache dot org> - Apache IPMC member, Pivotal
> - Jacques Nadeau <jacques at apache dot org> (pending admission to
> IPMC) - Apache Drill PMC Chair, MapR Technologies
>
> #Sponsoring Entity
>
> We are requesting the Incubator to sponsor this project.
>
>


-- 

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

Luke Han

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