Hi BC, The point is exactly to ensure that the maintainers have looked at each patch to that component and consider it to fit consistently into its architecture. The issue is not about "rogue" committers, it's about making sure that changes don't accidentally sneak in that we want to roll back, particularly because we have frequent releases and we guarantee API stability. This process is meant to ensure that whichever committer reviews a patch also forwards it to its maintainers.
Note that any committer is able to review patches in any component. The maintainer sign-off is just a second requirement for some core components (central parts of the system and public APIs). But I expect that most maintainers will let others do the bulk of the reviewing and focus only on changes to the architecture or API. Ultimately, the core motivation is that the project has grown to the point where it's hard to expect every committer to have full understanding of every component. Some committers know a ton about systems but little about machine learning, some are algorithmic whizzes but may not realize the implications of changing something on the Python API, etc. This is just a way to make sure that a domain expert has looked at the areas where it is most likely for something to go wrong. Matei > On Nov 6, 2014, at 10:53 AM, bc Wong <bcwal...@cloudera.com> wrote: > > Hi Matei, > > Good call on scaling the project itself. Identifying domain experts in > different areas is a good thing. But I have some questions about the > implementation. Here's my understanding of the proposal: > > (1) The PMC votes on a list of components and their maintainers. Changes to > that list requires PMC approval. > (2) No committer shall commit changes to a component without a +1 from a > maintainer of that component. > > I see good reasons for #1, to help people navigate the project and identify > expertise. For #2, I'd like to understand what problem it's trying to solve. > Do we have rogue committers committing to areas that they don't know much > about? If that's the case, we should address it directly, instead of adding > new processes. > > To point out the obvious, it completely changes what "committers" means in > Spark. Do we have clear promotion criteria from "committer" to "maintainer"? > Is there a max number of maintainers per area Currently, as committers gains > expertise in new areas, they could start reviewing code in those areas and > give +1. This encourages more contributions and cross-component knowledge > sharing. Under the new proposal, they now have to be promoted to > "maintainers" first. That reduces our review bandwidth. > > Again, if there is a quality issue with code reviews, let's talk to those > committers and help them do better. There are non-process ways to solve the > problem. > > So I think we shouldn't require "maintainer +1". I do like the idea of having > explicit maintainers on a volunteer basis. These maintainers should watch > their jira and PR traffic, and be very active in design & API discussions. > That leads to better consistency and long-term design choices. > > Cheers, > bc > > On Wed, Nov 5, 2014 at 5:31 PM, Matei Zaharia <matei.zaha...@gmail.com > <mailto: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><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><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
