+1 (binding), assuming that this is for public stable APIs, not APIs that are marked as unstable, evolving, etc.
On Mon, Mar 9, 2020 at 1:10 AM Ismaël Mejía <ieme...@gmail.com> wrote: > +1 (non-binding) > > Michael's section on the trade-offs of maintaining / removing an API are > one of > the best reads I have seeing in this mailing list. Enthusiast +1 > > On Sat, Mar 7, 2020 at 8:28 PM Dongjoon Hyun <dongjoon.h...@gmail.com> > wrote: > > > > This new policy has a good indention, but can we narrow down on the > migration from Apache Spark 2.4.5 to Apache Spark 3.0+? > > > > I saw that there already exists a reverting PR to bring back Spark 1.4 > and 1.5 APIs based on this AS-IS suggestion. > > > > The AS-IS policy is clearly mentioning that JVM/Scala-level difficulty, > and it's nice. > > > > However, for the other cases, it sounds like `recommending older APIs as > much as possible` due to the following. > > > > > How long has the API been in Spark? > > > > We had better be more careful when we add a new policy and should aim > not to mislead the users and 3rd party library developers to say "older is > better". > > > > Technically, I'm wondering who will use new APIs in their examples (of > books and StackOverflow) if they need to write an additional warning like > `this only works at 2.4.0+` always . > > > > Bests, > > Dongjoon. > > > > On Fri, Mar 6, 2020 at 7:10 PM Mridul Muralidharan <mri...@gmail.com> > wrote: > >> > >> I am in broad agreement with the prposal, as any developer, I prefer > >> stable well designed API's :-) > >> > >> Can we tie the proposal to stability guarantees given by spark and > >> reasonable expectation from users ? > >> In my opinion, an unstable or evolving could change - while an > >> experimental api which has been around for ages should be more > >> conservatively handled. > >> Which brings in question what are the stability guarantees as > >> specified by annotations interacting with the proposal. > >> > >> Also, can we expand on 'when' an API change can occur ? Since we are > >> proposing to diverge from semver. > >> Patch release ? Minor release ? Only major release ? Based on 'impact' > >> of API ? Stability guarantees ? > >> > >> Regards, > >> Mridul > >> > >> > >> > >> On Fri, Mar 6, 2020 at 7:01 PM Michael Armbrust <mich...@databricks.com> > wrote: > >> > > >> > I'll start off the vote with a strong +1 (binding). > >> > > >> > On Fri, Mar 6, 2020 at 1:01 PM Michael Armbrust < > mich...@databricks.com> wrote: > >> >> > >> >> I propose to add the following text to Spark's Semantic Versioning > policy and adopt it as the rubric that should be used when deciding to > break APIs (even at major versions such as 3.0). > >> >> > >> >> > >> >> I'll leave the vote open until Tuesday, March 10th at 2pm. As this > is a procedural vote, the measure will pass if there are more favourable > votes than unfavourable ones. PMC votes are binding, but the community is > encouraged to add their voice to the discussion. > >> >> > >> >> > >> >> [ ] +1 - Spark should adopt this policy. > >> >> > >> >> [ ] -1 - Spark should not adopt this policy. > >> >> > >> >> > >> >> <new policy> > >> >> > >> >> > >> >> Considerations When Breaking APIs > >> >> > >> >> The Spark project strives to avoid breaking APIs or silently > changing behavior, even at major versions. While this is not always > possible, the balance of the following factors should be considered before > choosing to break an API. > >> >> > >> >> > >> >> Cost of Breaking an API > >> >> > >> >> Breaking an API almost always has a non-trivial cost to the users of > Spark. A broken API means that Spark programs need to be rewritten before > they can be upgraded. However, there are a few considerations when thinking > about what the cost will be: > >> >> > >> >> Usage - an API that is actively used in many different places, is > always very costly to break. While it is hard to know usage for sure, there > are a bunch of ways that we can estimate: > >> >> > >> >> How long has the API been in Spark? > >> >> > >> >> Is the API common even for basic programs? > >> >> > >> >> How often do we see recent questions in JIRA or mailing lists? > >> >> > >> >> How often does it appear in StackOverflow or blogs? > >> >> > >> >> Behavior after the break - How will a program that works today, work > after the break? The following are listed roughly in order of increasing > severity: > >> >> > >> >> Will there be a compiler or linker error? > >> >> > >> >> Will there be a runtime exception? > >> >> > >> >> Will that exception happen after significant processing has been > done? > >> >> > >> >> Will we silently return different answers? (very hard to debug, > might not even notice!) > >> >> > >> >> > >> >> Cost of Maintaining an API > >> >> > >> >> Of course, the above does not mean that we will never break any > APIs. We must also consider the cost both to the project and to our users > of keeping the API in question. > >> >> > >> >> Project Costs - Every API we have needs to be tested and needs to > keep working as other parts of the project changes. These costs are > significantly exacerbated when external dependencies change (the JVM, > Scala, etc). In some cases, while not completely technically infeasible, > the cost of maintaining a particular API can become too high. > >> >> > >> >> User Costs - APIs also have a cognitive cost to users learning Spark > or trying to understand Spark programs. This cost becomes even higher when > the API in question has confusing or undefined semantics. > >> >> > >> >> > >> >> Alternatives to Breaking an API > >> >> > >> >> In cases where there is a "Bad API", but where the cost of removal > is also high, there are alternatives that should be considered that do not > hurt existing users but do address some of the maintenance costs. > >> >> > >> >> > >> >> Avoid Bad APIs - While this is a bit obvious, it is an important > point. Anytime we are adding a new interface to Spark we should consider > that we might be stuck with this API forever. Think deeply about how new > APIs relate to existing ones, as well as how you expect them to evolve over > time. > >> >> > >> >> Deprecation Warnings - All deprecation warnings should point to a > clear alternative and should never just say that an API is deprecated. > >> >> > >> >> Updated Docs - Documentation should point to the "best" recommended > way of performing a given task. In the cases where we maintain legacy > documentation, we should clearly point to newer APIs and suggest to users > the "right" way. > >> >> > >> >> Community Work - Many people learn Spark by reading blogs and other > sites such as StackOverflow. However, many of these resources are out of > date. Update them, to reduce the cost of eventually removing deprecated > APIs. > >> >> > >> >> > >> >> </new policy> > >> > >> --------------------------------------------------------------------- > >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org > >> > > --------------------------------------------------------------------- > To unsubscribe e-mail: dev-unsubscr...@spark.apache.org > >
