Hi Tim,

We can definitely add one for that if the component grows larger or becomes 
harder to maintain. The main reason I didn't propose one is that the Mesos 
integration is actually a lot simpler than YARN at the moment, partly because 
we support several YARN versions that have incompatible APIs. But so far our 
modus operandi has been to ask Mesos contributors to review patches that touch 
it.

We didn't want to add a lot of components at the beginning partly to minimize 
overhead, but we can revisit it later. It would definitely be bad if we break 
Mesos support.

Matei

> On Nov 5, 2014, at 5:35 PM, Timothy Chen <tnac...@gmail.com> wrote:
> 
> Hi Matei,
> 
> Definitely in favor of moving into this model for exactly the reasons
> you mentioned.
> 
> From the module list though, the module that I'm mostly involved with
> and is not listed is the Mesos integration piece.
> 
> I believe we also need a maintainer for Mesos, and I wonder if there
> is someone that can be added to that?
> 
> Tim
> 
> On Wed, Nov 5, 2014 at 5:31 PM, Matei Zaharia <matei.zaha...@gmail.com> wrote:
>> Hi all,
>> 
>> I wanted to share a discussion we've been having on the PMC list, as well as 
>> call for an official vote on it on a public list. Basically, as the Spark 
>> project scales up, we need to define a model to make sure there is still 
>> great oversight of key components (in particular internal architecture and 
>> public APIs), and to this end I've proposed implementing a maintainer model 
>> for some of these components, similar to other large projects.
>> 
>> As background on this, Spark has grown a lot since joining Apache. We've had 
>> over 80 contributors/month for the past 3 months, which I believe makes us 
>> the most active project in contributors/month at Apache, as well as over 500 
>> patches/month. The codebase has also grown significantly, with new libraries 
>> for SQL, ML, graphs and more.
>> 
>> In this kind of large project, one common way to scale development is to 
>> assign "maintainers" to oversee key components, where each patch to that 
>> component needs to get sign-off from at least one of its maintainers. Most 
>> existing large projects do this -- at Apache, some large ones with this 
>> model are CloudStack (the second-most active project overall), Subversion, 
>> and Kafka, and other examples include Linux and Python. This is also 
>> by-and-large how Spark operates today -- most components have a de-facto 
>> maintainer.
>> 
>> IMO, adopting this model would have two benefits:
>> 
>> 1) Consistent oversight of design for that component, especially regarding 
>> architecture and API. This process would ensure that the component's 
>> maintainers see all proposed changes and consider them to fit together in a 
>> good way.
>> 
>> 2) More structure for new contributors and committers -- in particular, it 
>> would be easy to look up who’s responsible for each module and ask them for 
>> reviews, etc, rather than having patches slip between the cracks.
>> 
>> We'd like to start with in a light-weight manner, where the model only 
>> applies to certain key components (e.g. scheduler, shuffle) and user-facing 
>> APIs (MLlib, GraphX, etc). Over time, as the project grows, we can expand it 
>> if we deem it useful. The specific mechanics would be as follows:
>> 
>> - Some components in Spark will have maintainers assigned to them, where one 
>> of the maintainers needs to sign off on each patch to the component.
>> - Each component with maintainers will have at least 2 maintainers.
>> - Maintainers will be assigned from the most active and knowledgeable 
>> committers on that component by the PMC. The PMC can vote to add / remove 
>> maintainers, and maintained components, through consensus.
>> - Maintainers are expected to be active in responding to patches for their 
>> components, though they do not need to be the main reviewers for them (e.g. 
>> they might just sign off on architecture / API). To prevent inactive 
>> maintainers from blocking the project, if a maintainer isn't responding in a 
>> reasonable time period (say 2 weeks), other committers can merge the patch, 
>> and the PMC will want to discuss adding another maintainer.
>> 
>> If you'd like to see examples for this model, check out the following 
>> projects:
>> - CloudStack: 
>> https://cwiki.apache.org/confluence/display/CLOUDSTACK/CloudStack+Maintainers+Guide
>>  
>> <https://cwiki.apache.org/confluence/display/CLOUDSTACK/CloudStack+Maintainers+Guide>
>> - Subversion: https://subversion.apache.org/docs/community-guide/roles.html 
>> <https://subversion.apache.org/docs/community-guide/roles.html>
>> 
>> Finally, I wanted to list our current proposal for initial components and 
>> maintainers. It would be good to get feedback on other components we might 
>> add, but please note that personnel discussions (e.g. "I don't think Matei 
>> should maintain *that* component) should only happen on the private list. 
>> The initial components were chosen to include all public APIs and the main 
>> core components, and the maintainers were chosen from the most active 
>> contributors to those modules.
>> 
>> - Spark core public API: Matei, Patrick, Reynold
>> - Job scheduler: Matei, Kay, Patrick
>> - Shuffle and network: Reynold, Aaron, Matei
>> - Block manager: Reynold, Aaron
>> - YARN: Tom, Andrew Or
>> - Python: Josh, Matei
>> - MLlib: Xiangrui, Matei
>> - SQL: Michael, Reynold
>> - Streaming: TD, Matei
>> - GraphX: Ankur, Joey, Reynold
>> 
>> I'd like to formally call a [VOTE] on this model, to last 72 hours. The 
>> [VOTE] will end on Nov 8, 2014 at 6 PM PST.
>> 
>> Matei


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