I am still a bit lost about why we are discussing options without giving any arguments or reasons for the options? Why is 2 modules better than 3 or 3 better than 2, or even better, what forces us to have something different than a single module?
What are the reasons for wanting to have separate jars? If the issue is that the code is unfinished or not passing the tests, the impact for end users is minimal because they cannot accidentally end up running the new runner, and if they decide to do so we can warn them it is at their own risk and not ready for production in the documentation + runner. If the fear is that new code may end up being intertwined with the classic and portable runners and have some side effects. We have the ValidatesRunner + Nexmark in the CI to cover this so again I do not see what is the problem that requires modules to be separate. If the issue is being uncomfortable about having in-progress code in released artifacts we have been doing this in Beam forever, for example most of the work on portability and Schema/SQL, and all of those were still part of artifacts long time before they were ready for prime use, so I still don't see why this case is different to require different artifacts. I have the impression we are trying to solve a non-issue by adding a lot of artificial complexity (in particular to the users), or am I missing something else? On Wed, Oct 30, 2019 at 7:40 PM Kenneth Knowles <[email protected]> wrote: > > Oh, I mean that we ship just 2 jars. > > And since Spark users always build an uber jar, they can still depend on both > of ours and be able to switch runners with a flag. > > I really dislike projects shipping overlapping jars. It is confusing and > causes major diamond dependency problems. > > Kenn > > On Wed, Oct 30, 2019 at 11:12 AM Alexey Romanenko <[email protected]> > wrote: >> >> Yes, agree, two jars included in uber jar will work in the similar way. >> Though having 3 jars looks still quite confusing for me. >> >> On 29 Oct 2019, at 23:54, Kenneth Knowles <[email protected]> wrote: >> >> Is it just as easy to have two jars and build an uber jar with both >> included? Then the runner can still be toggled with a flag. >> >> Kenn >> >> On Tue, Oct 29, 2019 at 9:38 AM Alexey Romanenko <[email protected]> >> wrote: >>> >>> Hmm, I don’t think that jar size should play a big role comparing to the >>> whole size of shaded jar of users job. Even more, I think it will be quite >>> confusing for users to choose which jar to use if we will have 3 different >>> ones for similar purposes. Though, let’s see what others think. >>> >>> On 29 Oct 2019, at 15:32, Etienne Chauchot <[email protected]> wrote: >>> >>> Hi Alexey, >>> >>> Thanks for your opinion ! >>> >>> Comments inline >>> >>> Etienne >>> >>> On 28/10/2019 17:34, Alexey Romanenko wrote: >>> >>> Let me share some of my thoughts on this. >>> >>> - shall we filter out the package name from the release? >>> >>> Until new runner is not ready to be used in production (or, at least, be >>> used for beta testing but users should be clearly warned about that in this >>> case), I believe we need to filter out its classes from published jar to >>> avoid a confusion. >>> >>> Yes that is what I think also >>> >>> - should we release 2 jars: one for the old and one for the new ? >>> >>> - should we release 3 jars: one for the new, one for the new and one >>> for both ? >>> >>> Once new runner will be released, then I think we need to provide only one >>> single jar and allow user to switch between different Spark runners with >>> CLI option. >>> >>> I would vote for 3 jars: one for new, one for old, and one for both. >>> Indeed, in some cases, users are looking very closely at the size of jars. >>> This solution meets all use cases >>> >>> - should we create a special entry to the capability matrix ? >>> >>> Sure, since it has its own uniq characteristics and implementation, but >>> again, only once new runner will be "officially released". >>> >>> +1 >>> >>> >>> >>> On 28 Oct 2019, at 10:27, Etienne Chauchot <[email protected]> wrote: >>> >>> Hi guys, >>> >>> Any opinions on the point2 communication to users ? >>> >>> Etienne >>> >>> On 24/10/2019 15:44, Etienne Chauchot wrote: >>> >>> Hi guys, >>> >>> I'm glad to announce that the PR for the merge to master of the new runner >>> based on Spark Structured Streaming framework is submitted: >>> >>> https://github.com/apache/beam/pull/9866 >>> >>> >>> 1. Regarding the status of the runner: >>> >>> -the runner passes 93% of the validates runner tests in batch mode. >>> >>> -Streaming mode is barely started (waiting for the multi-aggregations >>> support in spark Structured Streaming framework from the Spark community) >>> >>> -Runner can execute Nexmark >>> >>> -Some things are not wired up yet >>> >>> -Beam Schemas not wired with Spark Schemas >>> >>> -Optional features of the model not implemented: state api, timer api, >>> splittable doFn api, … >>> >>> >>> 2. Regarding the communication to users: >>> >>> - for reasons explained by Ismael: the runner is in the same module as the >>> "older" one. But it is in a different sub-package and both runners share >>> the same build. >>> >>> - How should we communicate to users: >>> >>> - shall we filter out the package name from the release? >>> >>> - should we release 2 jars: one for the old and one for the new ? >>> >>> - should we release 3 jars: one for the new, one for the new and one >>> for both ? >>> >>> - should we create a special entry to the capability matrix ? >>> >>> WDYT ? >>> >>> Best >>> >>> Etienne >>> >>> >>> On 23/10/2019 19:11, Mikhail Gryzykhin wrote: >>> >>> +1 to merge. >>> >>> It is worth keeping things in master with explicitly marked status. It will >>> make effort more visible to users and easier to get feedback upon. >>> >>> --Mikhail >>> >>> On Wed, Oct 23, 2019 at 8:36 AM Etienne Chauchot <[email protected]> >>> wrote: >>>> >>>> Hi guys, >>>> >>>> The new spark runner now supports beam coders and passes 93% of the batch >>>> validates runner tests (+4%). I think it is time to merge it to master. I >>>> will submit a PR in the coming days. >>>> >>>> next steps: support schemas and thus better leverage catalyst optimizer >>>> (among other things optims based on data), port perfs optims that were >>>> done in the current runner. >>>> >>>> Best >>>> >>>> Etienne >>>> >>>> On 11/10/2019 22:48, Pablo Estrada wrote: >>>> >>>> +1 for merging : ) >>>> >>>> On Fri, Oct 11, 2019 at 12:43 PM Robert Bradshaw <[email protected]> >>>> wrote: >>>>> >>>>> Sounds like a good plan to me. >>>>> >>>>> On Fri, Oct 11, 2019 at 6:20 AM Etienne Chauchot <[email protected]> >>>>> wrote: >>>>>> >>>>>> Comments inline >>>>>> >>>>>> On 10/10/2019 23:44, Ismaël Mejía wrote: >>>>>> >>>>>> +1 >>>>>> >>>>>> The earlier we get to master the better to encourage not only code >>>>>> contributions but as important to have early user feedback. >>>>>> >>>>>> Question is: do we keep the "old" spark runner for a while or not (or >>>>>> just keep on previous version/tag on git) ? >>>>>> >>>>>> It is still too early to even start discussing when to remove the >>>>>> classical runner given that the new runner is still a WIP. However the >>>>>> overall goal is that this runner becomes the de-facto one once the VR >>>>>> tests and the performance become at least equal to the classical >>>>>> runner, in the meantime the best for users is that they co-exist, >>>>>> let’s not forget that the other runner has been already battle tested >>>>>> for more than 3 years and has had lots of improvements in the last >>>>>> year. >>>>>> >>>>>> +1 on what Ismael says: no soon removal, >>>>>> >>>>>> The plan I had in mind at first (that I showed at the apacheCon) was >>>>>> this but I'm proposing moving the first gray label to before the red box. >>>>>> >>>>>> <beogijnhpieapoll.png> >>>>>> >>>>>> >>>>>> I don't think the number of commits should be an issue--we shouldn't >>>>>> just squash years worth of history away. (OTOH, if this is a case of >>>>>> this branch containing lots of little, irrelevant commits that would >>>>>> have normally been squashed away in the normal review process we do >>>>>> for the main branch, then, yes, some cleanup could be nice.) >>>>>> >>>>>> About the commits we should encourage a clear history but we have also >>>>>> to remove useless commits that are still present in the branch, >>>>>> commits of the “Fix errorprone” / “Cleaning” kind and even commits >>>>>> that make a better narrative sense together should be probably >>>>>> squashed, because they do not bring much to the history. It is not >>>>>> about more or less commits it is about its relevance as Robert >>>>>> mentions. >>>>>> >>>>>> I think our experiences with things that go to master early have been >>>>>> very good. So I am in favor ASAP. We can exclude it from releases easily >>>>>> until it is ready for end users. >>>>>> I have the same question as Robert - how much is modifications and how >>>>>> much is new? I notice it is in a subdirectory of the beam-runners-spark >>>>>> module. >>>>>> >>>>>> In its current form we cannot exclude it but this relates to the other >>>>>> question, so better to explain a bit of history: The new runner used >>>>>> to live in its own module and subdirectory because it is a full blank >>>>>> page rewrite and the decision was not to use any of the classical >>>>>> runner classes to not be constrained by its evolution. >>>>>> >>>>>> However the reason to put it back in the same module as a subdirectory >>>>>> was to encourage early use, in more detail: The way you deploy spark >>>>>> jobs today is usually by packaging and staging an uber jar (~200MB of >>>>>> pure dependency joy) that contains the user pipeline classes, the >>>>>> spark runner module and its dependencies. If we have two spark runners >>>>>> in separate modules the user would need to repackage and redeploy >>>>>> their pipelines every time they want to switch from the classical >>>>>> Spark runner to the structured streaming runner which is painful and >>>>>> time and space consuming compared with the one module approach where >>>>>> they just change the name of the runner class and that’s it. The idea >>>>>> here is to make easy for users to test the new runner, but at the same >>>>>> time to make easy to come back to the classical runner in case of any >>>>>> issue. >>>>>> >>>>>> Ismaël >>>>>> >>>>>> On Thu, Oct 10, 2019 at 9:02 PM Kenneth Knowles <[email protected]> wrote: >>>>>> >>>>>> +1 >>>>>> >>>>>> I think our experiences with things that go to master early have been >>>>>> very good. So I am in favor ASAP. We can exclude it from releases easily >>>>>> until it is ready for end users. >>>>>> >>>>>> I have the same question as Robert - how much is modifications and how >>>>>> much is new? I notice it is in a subdirectory of the beam-runners-spark >>>>>> module. >>>>>> >>>>>> I did not see any major changes to dependencies but I will also ask if >>>>>> it has major version differences so that you might want a separate >>>>>> artifact? >>>>>> >>>>>> Kenn >>>>>> >>>>>> On Thu, Oct 10, 2019 at 11:50 AM Robert Bradshaw <[email protected]> >>>>>> wrote: >>>>>> >>>>>> On Thu, Oct 10, 2019 at 12:39 AM Etienne Chauchot <[email protected]> >>>>>> wrote: >>>>>> >>>>>> Hi guys, >>>>>> >>>>>> You probably know that there has been for several months an work >>>>>> developing a new Spark runner based on Spark Structured Streaming >>>>>> framework. This work is located in a feature branch here: >>>>>> https://github.com/apache/beam/tree/spark-runner_structured-streaming >>>>>> >>>>>> To attract more contributors and get some user feedback, we think it is >>>>>> time to merge it to master. Before doing so, some steps need to be >>>>>> achieved: >>>>>> >>>>>> - finish the work on spark Encoders (that allow to call Beam coders) >>>>>> because, right now, the runner is in an unstable state (some transforms >>>>>> use the new way of doing ser/de and some use the old one, making a >>>>>> pipeline incoherent toward serialization) >>>>>> >>>>>> - clean history: The history contains commits from November 2018, so >>>>>> there is a good amount of work, thus a consequent number of commits. >>>>>> They were already squashed but not from September 2019 >>>>>> >>>>>> I don't think the number of commits should be an issue--we shouldn't >>>>>> just squash years worth of history away. (OTOH, if this is a case of >>>>>> this branch containing lots of little, irrelevant commits that would >>>>>> have normally been squashed away in the normal review process we do >>>>>> for the main branch, then, yes, some cleanup could be nice.) >>>>>> >>>>>> Regarding status: >>>>>> >>>>>> - the runner passes 89% of the validates runner tests in batch mode. We >>>>>> hope to pass more with the new Encoders >>>>>> >>>>>> - Streaming mode is barely started (waiting for the multi-aggregations >>>>>> support in spark SS framework from the Spark community) >>>>>> >>>>>> - Runner can execute Nexmark >>>>>> >>>>>> - Some things are not wired up yet >>>>>> >>>>>> - Beam Schemas not wired with Spark Schemas >>>>>> >>>>>> - Optional features of the model not implemented: state api, timer >>>>>> api, splittable doFn api, … >>>>>> >>>>>> WDYT, can we merge it to master once the 2 steps are done ? >>>>>> >>>>>> I think that as long as it sits parallel to the existing runner, and >>>>>> is clearly marked with its status, it makes sense to me. How many >>>>>> changes does it make to the existing codebase (as opposed to add new >>>>>> code)? >>> >>> >>> >>
