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From Dave Fisher <dave2w...@comcast.net>
Subject Re: [PROPOSAL] Onyx - proposal for Apache Incubation
Date Sat, 27 Jan 2018 14:31:02 GMT
Checking “Serf Software” which sounds the same.

(1) there is already Apache Serf
(2) Serf is a product from Hashicorp at https://www.serf.io/. This would definitely confuse
as it is apparently comparable to ZooKeeper.

Regards,
Dave

Sent from my iPhone

> On Jan 27, 2018, at 3:12 AM, sebb <sebbaz@gmail.com> wrote:
> 
> A brief search for 'Surf Software' shows quite a few hits.
> I have not looked to see if they would be likely to be confused with
> this project or cause problems for others.
> 
> But it as though there might be a problem:
> Surfer -  Golden Software
> surf @ sourceforge
> Surf Software company
> 
> 
>> On 27 January 2018 at 08:03, Byung-Gon Chun <bgchun@gmail.com> wrote:
>> Since we cannot use the name Onyx, we would like to change the project name
>> to Surf.
>> I hope that this name works.
>> 
>> -Gon
>> 
>> ---
>> Byung-Gon Chun
>> 
>> 
>>> On Sat, Jan 27, 2018 at 4:57 AM, Byung-Gon Chun <bgchun@gmail.com> wrote:
>>> 
>>> 
>>> 
>>>> On Sat, Jan 27, 2018 at 4:09 AM, Davor Bonaci <davor@apache.org> wrote:
>>>> 
>>>> Great work -- I think this technology has a lot of promise, and I'd love
>>>> to
>>>> see its evolution inside the Foundation.
>>>> 
>>>> 
>>> Thanks, Davor!
>>> 
>>> 
>>>> Parts of it, like the Onyx Intermediate Representation [1], overlap with
>>>> the work-in-progress inside the Apache Beam project ("portability"). We'd
>>>> love to work together on this -- would you be open to such collaboration?
>>>> If so, it may not be necessary to start from scratch, and leverage the
>>>> work
>>>> already done.
>>>> 
>>>> 
>>> Sure. We're open to collaboration.
>>> 
>>> 
>>>> Regarding the name, Onyx would likely have to be renamed, due to a
>>>> conflict
>>>> with a related technology [2].
>>>> 
>>>> 
>>> Thanks for pointing it out. It's difficult to come up with a good short
>>> name. :)
>>> Do you have any suggestion?
>>> 
>>> Thanks!
>>> -Gon
>>> 
>>> ---
>>> Byung-Gon Chun
>>> 
>>> 
>>> 
>>>> Davor
>>>> 
>>>> [1] https://snuspl.github.io/onyx/docs/ir/
>>>> [2] http://www.onyxplatform.org/
>>>> 
>>>>> On Thu, Jan 25, 2018 at 3:28 PM, Byung-Gon Chun <bgchun@gmail.com>
wrote:
>>>>> 
>>>>> Dear Apache Incubator Community,
>>>>> 
>>>>> Please accept the following proposal for presentation and discussion:
>>>>> https://wiki.apache.org/incubator/OnyxProposal
>>>>> 
>>>>> Onyx is a data processing system that aims to flexibly control the
>>>> runtime
>>>>> behaviors of a job to adapt to varying deployment characteristics (e.g.,
>>>>> harnessing transient resources in datacenters, cross-datacenter
>>>> deployment,
>>>>> changing runtime based on job characteristics, etc.). Onyx provides
>>>> ways to
>>>>> extend the system’s capabilities and incorporate the extensions to
the
>>>>> flexible job execution.
>>>>> Onyx translates a user program (e.g., Apache Beam, Apache Spark) into
an
>>>>> Intermediate Representation (IR) DAG, which Onyx optimizes and deploys
>>>>> based on a deployment policy.
>>>>> 
>>>>> I've attached the proposal below.
>>>>> 
>>>>> Best regards,
>>>>> Byung-Gon Chun
>>>>> 
>>>>> = OnyxProposal =
>>>>> 
>>>>> == Abstract ==
>>>>> Onyx is a data processing system for flexible employment with
>>>>> different execution scenarios for various deployment characteristics
>>>>> on clusters.
>>>>> 
>>>>> == Proposal ==
>>>>> Today, there is a wide variety of data processing systems with
>>>>> different designs for better performance and datacenter efficiency.
>>>>> They include processing data on specific resource environments and
>>>>> running jobs with specific attributes. Although each system
>>>>> successfully solves the problems it targets, most systems are designed
>>>>> in the way that runtime behaviors are built tightly inside the system
>>>>> core to hide the complexity of distributed computing. This makes it
>>>>> hard for a single system to support different deployment
>>>>> characteristics with different runtime behaviors without substantial
>>>>> effort.
>>>>> 
>>>>> Onyx is a data processing system that aims to flexibly control the
>>>>> runtime behaviors of a job to adapt to varying deployment
>>>>> characteristics. Moreover, it provides a means of extending the
>>>>> system’s capabilities and incorporating the extensions to the flexible
>>>>> job execution.
>>>>> 
>>>>> In order to be able to easily modify runtime behaviors to adapt to
>>>>> varying deployment characteristics, Onyx exposes runtime behaviors to
>>>>> be flexibly configured and modified at both compile-time and runtime
>>>>> through a set of high-level graph pass interfaces.
>>>>> 
>>>>> We hope to contribute to the big data processing community by enabling
>>>>> more flexibility and extensibility in job executions. Furthermore, we
>>>>> can benefit more together as a community when we work together as a
>>>>> community to mature the system with more use cases and understanding
>>>>> of diverse deployment characteristics. The Apache Software Foundation
>>>>> is the perfect place to achieve these aspirations.
>>>>> 
>>>>> == Background ==
>>>>> Many data processing systems have distinctive runtime behaviors
>>>>> optimized and configured for specific deployment characteristics like
>>>>> different resource environments and for handling special job
>>>>> attributes.
>>>>> 
>>>>> For example, much research have been conducted to overcome the
>>>>> challenge of running data processing jobs on cheap, unreliable
>>>>> transient resources. Likewise, techniques for disaggregating different
>>>>> types of resources, like memory, CPU and GPU, are being actively
>>>>> developed to use datacenter resources more efficiently. Many
>>>>> researchers are also working to run data processing jobs in even more
>>>>> diverse environments, such as across distant datacenters. Similarly,
>>>>> for special job attributes, many works take different approaches, such
>>>>> as runtime optimization, to solve problems like data skew, and to
>>>>> optimize systems for data processing jobs with small-scale input data.
>>>>> 
>>>>> Although each of the systems performs well with the jobs and in the
>>>>> environments they target, they perform poorly with unconsidered cases,
>>>>> and do not consider supporting multiple deployment characteristics on
>>>>> a single system in their designs.
>>>>> 
>>>>> For an application writer to optimize an application to perform well
>>>>> on a certain system engraved with its underlying behaviors, it
>>>>> requires a deep understanding of the system itself, which is an
>>>>> overhead that often requires a lot of time and effort. Moreover, for
a
>>>>> developer to modify such system behaviors, it requires modifications
>>>>> of the system core, which requires an even deeper understanding of the
>>>>> system itself.
>>>>> 
>>>>> With this background, Onyx is designed to represent all of its jobs as
>>>>> an Intermediate Representation (IR) DAG. In the Onyx compiler, user
>>>>> applications from various programming models (ex. Apache Beam) are
>>>>> submitted, transformed to an IR DAG, and optimized/customized for the
>>>>> deployment characteristics. In the IR DAG optimization phase, the DAG
>>>>> is modified through a series of compiler “passes” which reshape or
>>>>> annotate the DAG with an expression of the underlying runtime
>>>>> behaviors. The IR DAG is then submitted as an execution plan for the
>>>>> Onyx runtime. The runtime includes the unmodified parts of data
>>>>> processing in the backbone which is transparently integrated with
>>>>> configurable components exposed for further extension.
>>>>> 
>>>>> == Rationale ==
>>>>> Onyx’s vision lies in providing means for flexibly supporting a wide
>>>>> variety of job execution scenarios for users while facilitating system
>>>>> developers to extend the execution framework with various
>>>>> functionalities at the same time. The capabilities of the system can
>>>>> be extended as it grows to meet a more variety of execution scenarios.
>>>>> We require inputs from users and developers from diverse domains in
>>>>> order to make it a more thriving and useful project. The Apache
>>>>> Software Foundation provides the best tools and community to support
>>>>> this vision.
>>>>> 
>>>>> == Initial Goals ==
>>>>> Initial goals will be to move the existing codebase to Apache and
>>>>> integrate with the Apache development process. We further plan to
>>>>> develop our system to meet the needs for more execution scenarios for
>>>>> a more variety of deployment characteristics.
>>>>> 
>>>>> == Current Status ==
>>>>> Onyx codebase is currently hosted in a repository at github.com. The
>>>>> current version has been developed by system developers at Seoul
>>>>> National University, Viva Republica, Samsung, and LG.
>>>>> 
>>>>> == Meritocracy ==
>>>>> We plan to strongly support meritocracy. We will discuss the
>>>>> requirements in an open forum, and those that continuously contribute
>>>>> to Onyx with the passion to strengthen the system will be invited as
>>>>> committers. Contributors that enrich Onyx by providing various use
>>>>> cases, various implementations of the configurable components
>>>>> including ideas for optimization techniques will be especially
>>>>> welcome. Committers with a deep understanding of the system’s
>>>>> technical aspects as a whole and its philosophy will definitely be
>>>>> voted as the PMC. We will monitor community participation so that
>>>>> privileges can be extended to those that contribute.
>>>>> 
>>>>> == Community ==
>>>>> We hope to expand our contribution community by becoming an Apache
>>>>> incubator project. The contributions will come from both users and
>>>>> system developers interested in flexibility and extensibility of job
>>>>> executions that Onyx can support. We expect users to mainly contribute
>>>>> to diversify the use cases and deployment characteristics, and
>>>>> developers to  contribute to implement them.
>>>>> 
>>>>> == Alignment ==
>>>>> Apache Spark is one of many popular data processing frameworks. The
>>>>> system is designed towards optimizing jobs using RDDs in memory and
>>>>> many other optimizations built tightly within the framework. In
>>>>> contrast to Spark, Onyx aims to provide more flexibility for job
>>>>> execution in an easy manner.
>>>>> 
>>>>> Apache Tez enables developers to build complex task DAGs with control
>>>>> over the control plane of job execution. In Onyx, a high-level
>>>>> programming layer (ex. Apache Beam) is automatically converted to a
>>>>> basic IR DAG and can be converted to any IR DAG through a series of
>>>>> easy user writable passes, that can both reshape and modify the
>>>>> annotation (of execution properties) of the DAG. Moreover, Onyx leaves
>>>>> more parts of the job execution configurable, such as the scheduler
>>>>> and the data plane. As opposed to providing a set of properties for
>>>>> solid optimization, Onyx’s configurable parts can be easily extended
>>>>> and explored by implementing the pre-defined interfaces. For example,
>>>>> an arbitrary intermediate data store can be added.
>>>>> 
>>>>> Onyx currently supports Apache Beam programs and we are working on
>>>>> supporting Apache Spark programs as well. Onyx also utilizes Apache
>>>>> REEF for container management, which allows Onyx to run in Apache YARN
>>>>> and Apache Mesos clusters. If necessary, we plan to contribute to and
>>>>> collaborate with these other Apache projects for the benefit of all.
>>>>> We plan to extend such integrations with more Apache softwares. Apache
>>>>> software foundation already hosts many major big-data systems, and we
>>>>> expect to help further growth of the big-data community by having Onyx
>>>>> within the Apache foundation.
>>>>> 
>>>>> == Known Risks ==
>>>>> === Orphaned Products ===
>>>>> The risk of the Onyx project being orphaned is minimal. There is
>>>>> already plenty of work that arduously support different deployment
>>>>> characteristics, and we propose a general way to implement them with
>>>>> flexible and extensible configuration knobs. The domain of data
>>>>> processing is already of high interest, and this domain is expected to
>>>>> evolve continuously with various other purposes, such as resource
>>>>> disaggregation and using transient resources for better datacenter
>>>>> resource utilization.
>>>>> 
>>>>> === Inexperience with Open Source ===
>>>>> The initial committers include PMC members and committers of other
>>>>> Apache projects. They have experience with open source projects,
>>>>> starting from their incubation to the top-level. They have been
>>>>> involved in the open source development process, and are familiar with
>>>>> releasing code under an open source license.
>>>>> 
>>>>> === Homogeneous Developers ===
>>>>> The initial set of committers is from a limited set of organizations,
>>>>> but we expect to attract new contributors from diverse organizations
>>>>> and will thus grow organically once approved for incubation. Our prior
>>>>> experience with other open source projects will help various
>>>>> contributors to actively participate in our project.
>>>>> 
>>>>> === Reliance on Salaried Developers ===
>>>>> Many developers are from Seoul National University. This is not
>>>> applicable.
>>>>> 
>>>>> === Relationships with Other Apache Products ===
>>>>> Onyx positions itself among multiple Apache products. It runs on
>>>>> Apache REEF for container management. It also utilizes many useful
>>>>> development tools including Apache Maven, Apache Log4J, and multiple
>>>>> Apache Commons components. Onyx supports the Apache Beam programming
>>>>> model for user applications. We are currently working on supporting
>>>>> the Apache Spark programming APIs as well.
>>>>> 
>>>>> === An Excessive Fascination with the Apache Brand ===
>>>>> We hope to make Onyx a powerful system for data processing, meeting
>>>>> various needs for different deployment characteristics, under a more
>>>>> variety of environments. We see the limitations of simply putting code
>>>>> on GitHub, and we believe the Apache community will help the growth of
>>>>> Onyx for the project to become a positively impactful and innovative
>>>>> open source software. We believe Onyx is a great fit for the Apache
>>>>> Software Foundation due to the collaboration it aims to achieve from
>>>>> the big data processing community.
>>>>> 
>>>>> == Documentation ==
>>>>> The current documentation for Onyx is at https://snuspl.github.io/onyx/
>>>> .
>>>>> 
>>>>> == Initial Source ==
>>>>> The Onyx codebase is currently hosted at https://github.com/snuspl/onyx
>>>> .
>>>>> 
>>>>> == External Dependencies ==
>>>>> To the best of our knowledge, all Onyx dependencies are distributed
>>>>> under Apache compatible licenses. Upon acceptance to the incubator, we
>>>>> would begin a thorough analysis of all transitive dependencies to
>>>>> verify this fact and further introduce license checking into the build
>>>>> and release process.
>>>>> 
>>>>> == Cryptography ==
>>>>> Not applicable.
>>>>> 
>>>>> == Required Resources ==
>>>>> === Mailing Lists ===
>>>>> We will operate two mailing lists as follows:
>>>>>   * Onyx PMC discussions: private@onyx.incubator.apache.org
>>>>>   * Onyx developers: dev@onyx.incubator.apache.org
>>>>> 
>>>>> === Git Repositories ===
>>>>> Upon incubation: https://github.com/apache/incubator-onyx.
>>>>> After the incubation, we would like to move the existing repo
>>>>> https://github.com/snuspl/onyx to the Apache infrastructure
>>>>> 
>>>>> === Issue Tracking ===
>>>>> Onyx currently tracks its issues using the Github issue tracker:
>>>>> https://github.com/snuspl/onyx/issues. We plan to migrate to Apache
>>>>> JIRA.
>>>>> 
>>>>> == Initial Committers ==
>>>>>  * Byung-Gon Chun
>>>>>  * Jeongyoon Eo
>>>>>  * Geon-Woo Kim
>>>>>  * Joo Yeon Kim
>>>>>  * Gyewon Lee
>>>>>  * Jung-Gil Lee
>>>>>  * Sanha Lee
>>>>>  * Wooyeon Lee
>>>>>  * Yunseong Lee
>>>>>  * JangHo Seo
>>>>>  * Won Wook Song
>>>>>  * Taegeon Um
>>>>>  * Youngseok Yang
>>>>> 
>>>>> == Affiliations ==
>>>>>  * SNU (Seoul National University)
>>>>>    * Byung-Gon Chun
>>>>>    * Jeongyoon Eo
>>>>>    * Geon-Woo Kim
>>>>>    * Gyewon Lee
>>>>>    * Sanha Lee
>>>>>    * Wooyeon Lee
>>>>>    * Yunseong Lee
>>>>>    * JangHo Seo
>>>>>    * Won Wook Song
>>>>>    * Taegeon Um
>>>>>    * Youngseok Yang
>>>>> 
>>>>>  * LG
>>>>>    * Jung-Gil Lee
>>>>> 
>>>>>  * Samsung
>>>>>    * Joo Yeon Kim
>>>>> 
>>>>>  * Viva Republica
>>>>>    * Geon-Woo Kim
>>>>> 
>>>>> == Sponsors ==
>>>>> === Champions ===
>>>>> Byung-Gon Chun
>>>>> 
>>>>> === Mentors ===
>>>>>  * Hyunsik Choi
>>>>>  * Byung-Gon Chun
>>>>>  * Markus Weimer
>>>>>  * Reynold Xin
>>>>> 
>>>>> === Sponsoring Entity ===
>>>>> The Apache Incubator
>>>>> 
>>>>> 
>>>>> 
>>>>> --
>>>>> Byung-Gon Chun
>>>>> 
>>>> 
>>> 
>>> 
>>> 
>>> --
>>> Byung-Gon Chun
>>> 
>> 
>> 
>> 
>> --
>> Byung-Gon Chun
> 
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