> Making downstream to diverge their implementation heavily between minor versions (say, 2.4 vs 2.5) wouldn't be a good experience
You're right that the API has been evolving in the 2.x line. But, it is now reasonably stable with respect to the current feature set and we should not need to break compatibility in the 3.x line. Because we have reached our goals for the 3.0 release, we can backport at least those features to 2.x and confidently have an API that works in both a 2.x release and is compatible with 3.0, if not 3.1 and later releases as well. > I'd rather say preparation of Spark 2.5 should be started after Spark 3.0 is officially released The reason I'm suggesting this is that I'm already going to do the work to backport the 3.0 release features to 2.4. I've been asked by several people when DSv2 will be released, so I know there is a lot of interest in making this available sooner than 3.0. If I'm already doing the work, then I'd be happy to share that with the community. I don't see why 2.5 and 3.0 are mutually exclusive. We can work on 2.5 while preparing the 3.0 preview and fixing bugs. For DSv2, the work is about complete so we can easily release the same set of features and API in 2.5 and 3.0. If we decide for some reason to wait until after 3.0 is released, I don't know that there is much value in a 2.5. The purpose is to be a step toward 3.0, and releasing that step after 3.0 doesn't seem helpful to me. It also wouldn't get these features out any sooner than 3.0, as a 2.5 release probably would, given the work needed to validate the incompatible changes in 3.0. > DSv2 change would be the major backward incompatibility which Spark 2.x users may hesitate to upgrade As I pointed out, DSv2 has been changing in the 2.x line, so this is expected. I don't think it will need incompatible changes in the 3.x line. On Fri, Sep 20, 2019 at 9:25 PM Jungtaek Lim <kabh...@gmail.com> wrote: > Just 2 cents, I haven't tracked the change of DSv2 (though I needed to > deal with this as the change made confusion on my PRs...), but my bet is > that DSv2 would be already changed in incompatible way, at least who works > for custom DataSource. Making downstream to diverge their implementation > heavily between minor versions (say, 2.4 vs 2.5) wouldn't be a good > experience - especially we are not completely closed the chance to further > modify DSv2, and the change could be backward incompatible. > > If we really want to bring the DSv2 change to 2.x version line to let end > users avoid forcing to upgrade Spark 3.x to enjoy new DSv2, I'd rather say > preparation of Spark 2.5 should be started after Spark 3.0 is officially > released, honestly even later than that, say, getting some reports from > Spark 3.0 about DSv2 so that we feel DSv2 is OK. I hope we don't make Spark > 2.5 be a kind of "tech-preview" which Spark 2.4 users may be frustrated to > upgrade to next minor version. > > Btw, do we have any specific target users for this? Personally DSv2 change > would be the major backward incompatibility which Spark 2.x users may > hesitate to upgrade, so they might be already prepared to migrate to Spark > 3.0 if they are prepared to migrate to new DSv2. > > On Sat, Sep 21, 2019 at 12:46 PM Dongjoon Hyun <dongjoon.h...@gmail.com> > wrote: > >> Do you mean you want to have a breaking API change between 3.0 and 3.1? >> I believe we follow Semantic Versioning ( >> https://spark.apache.org/versioning-policy.html ). >> >> > We just won’t add any breaking changes before 3.1. >> >> Bests, >> Dongjoon. >> >> >> On Fri, Sep 20, 2019 at 11:48 AM Ryan Blue <rb...@netflix.com.invalid> >> wrote: >> >>> I don’t think we need to gate a 3.0 release on making a more stable >>> version of InternalRow >>> >>> Sounds like we agree, then. We will use it for 3.0, but there are known >>> problems with it. >>> >>> Thinking we’d have dsv2 working in both 3.x (which will change and >>> progress towards more stable, but will have to break certain APIs) and 2.x >>> seems like a false premise. >>> >>> Why do you think we will need to break certain APIs before 3.0? >>> >>> I’m only suggesting that we release the same support in a 2.5 release >>> that we do in 3.0. Since we are nearly finished with the 3.0 goals, it >>> seems like we can certainly do that. We just won’t add any breaking changes >>> before 3.1. >>> >>> On Fri, Sep 20, 2019 at 11:39 AM Reynold Xin <r...@databricks.com> >>> wrote: >>> >>>> I don't think we need to gate a 3.0 release on making a more stable >>>> version of InternalRow, but thinking we'd have dsv2 working in both 3.x >>>> (which will change and progress towards more stable, but will have to break >>>> certain APIs) and 2.x seems like a false premise. >>>> >>>> To point out some problems with InternalRow that you think are already >>>> pragmatic and stable: >>>> >>>> The class is in catalyst, which states: >>>> https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/package.scala >>>> >>>> /** >>>> * Catalyst is a library for manipulating relational query plans. All >>>> classes in catalyst are >>>> * considered an internal API to Spark SQL and are subject to change >>>> between minor releases. >>>> */ >>>> >>>> There is no even any annotation on the interface. >>>> >>>> The entire dependency chain were created to be private, and tightly >>>> coupled with internal implementations. For example, >>>> >>>> >>>> https://github.com/apache/spark/blob/master/common/unsafe/src/main/java/org/apache/spark/unsafe/types/UTF8String.java >>>> >>>> /** >>>> * A UTF-8 String for internal Spark use. >>>> * <p> >>>> * A String encoded in UTF-8 as an Array[Byte], which can be used for >>>> comparison, >>>> * search, see http://en.wikipedia.org/wiki/UTF-8 for details. >>>> * <p> >>>> * Note: This is not designed for general use cases, should not be used >>>> outside SQL. >>>> */ >>>> >>>> >>>> >>>> https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ArrayData.scala >>>> >>>> (which again is in catalyst package) >>>> >>>> >>>> If you want to argue this way, you might as well argue we should make >>>> the entire catalyst package public to be pragmatic and not allow any >>>> changes. >>>> >>>> >>>> >>>> >>>> On Fri, Sep 20, 2019 at 11:32 AM, Ryan Blue <rb...@netflix.com> wrote: >>>> >>>>> When you created the PR to make InternalRow public >>>>> >>>>> This isn’t quite accurate. The change I made was to use InternalRow >>>>> instead of UnsafeRow, which is a specific implementation of >>>>> InternalRow. Exposing this API has always been a part of DSv2 and >>>>> while both you and I did some work to avoid this, we are still in the >>>>> phase >>>>> of starting with that API. >>>>> >>>>> Note that any change to InternalRow would be very costly to implement >>>>> because this interface is widely used. That is why I think we can >>>>> certainly >>>>> consider it stable enough to use here, and that’s probably why >>>>> UnsafeRow was part of the original proposal. >>>>> >>>>> In any case, the goal for 3.0 was not to replace the use of >>>>> InternalRow, it was to get the majority of SQL working on top of the >>>>> interface added after 2.4. That’s done and stable, so I think a 2.5 >>>>> release >>>>> with it is also reasonable. >>>>> >>>>> On Fri, Sep 20, 2019 at 11:23 AM Reynold Xin <r...@databricks.com> >>>>> wrote: >>>>> >>>>> To push back, while I agree we should not drastically change >>>>> "InternalRow", there are a lot of changes that need to happen to make it >>>>> stable. For example, none of the publicly exposed interfaces should be in >>>>> the Catalyst package or the unsafe package. External implementations >>>>> should >>>>> be decoupled from the internal implementations, with cheap ways to convert >>>>> back and forth. >>>>> >>>>> When you created the PR to make InternalRow public, the understanding >>>>> was to work towards making it stable in the future, assuming we will start >>>>> with an unstable API temporarily. You can't just make a bunch internal >>>>> APIs >>>>> tightly coupled with other internal pieces public and stable and call it a >>>>> day, just because it happen to satisfy some use cases temporarily assuming >>>>> the rest of Spark doesn't change. >>>>> >>>>> >>>>> >>>>> On Fri, Sep 20, 2019 at 11:19 AM, Ryan Blue <rb...@netflix.com> wrote: >>>>> >>>>> > DSv2 is far from stable right? >>>>> >>>>> No, I think it is reasonably stable and very close to being ready for >>>>> a release. >>>>> >>>>> > All the actual data types are unstable and you guys have completely >>>>> ignored that. >>>>> >>>>> I think what you're referring to is the use of `InternalRow`. That's a >>>>> stable API and there has been no work to avoid using it. In any case, I >>>>> don't think that anyone is suggesting that we delay 3.0 until a >>>>> replacement >>>>> for `InternalRow` is added, right? >>>>> >>>>> While I understand the motivation for a better solution here, I think >>>>> the pragmatic solution is to continue using `InternalRow`. >>>>> >>>>> > If the goal is to make DSv2 work across 3.x and 2.x, that seems too >>>>> invasive of a change to backport once you consider the parts needed to >>>>> make >>>>> dsv2 stable. >>>>> >>>>> I believe that those of us working on DSv2 are confident about the >>>>> current stability. We set goals for what to get into the 3.0 release >>>>> months >>>>> ago and have very nearly reached the point where we are ready for that >>>>> release. >>>>> >>>>> I don't think instability would be a problem in maintaining >>>>> compatibility between the 2.5 version and the 3.0 version. If we find that >>>>> we need to make API changes (other than additions) then we can make those >>>>> in the 3.1 release. Because the goals we set for the 3.0 release have been >>>>> reached with the current API and if we are ready to release 3.0, we can >>>>> release a 2.5 with the same API. >>>>> >>>>> On Fri, Sep 20, 2019 at 11:05 AM Reynold Xin <r...@databricks.com> >>>>> wrote: >>>>> >>>>> DSv2 is far from stable right? All the actual data types are unstable >>>>> and you guys have completely ignored that. We'd need to work on that and >>>>> that will be a breaking change. If the goal is to make DSv2 work across >>>>> 3.x >>>>> and 2.x, that seems too invasive of a change to backport once you consider >>>>> the parts needed to make dsv2 stable. >>>>> >>>>> >>>>> >>>>> On Fri, Sep 20, 2019 at 10:47 AM, Ryan Blue <rb...@netflix.com.invalid >>>>> > wrote: >>>>> >>>>> Hi everyone, >>>>> >>>>> In the DSv2 sync this week, we talked about a possible Spark 2.5 >>>>> release based on the latest Spark 2.4, but with DSv2 and Java 11 support >>>>> added. >>>>> >>>>> A Spark 2.5 release with these two additions will help people migrate >>>>> to Spark 3.0 when it is released because they will be able to use a single >>>>> implementation for DSv2 sources that works in both 2.5 and 3.0. Similarly, >>>>> upgrading to 3.0 won't also require also updating to Java 11 because users >>>>> could update to Java 11 with the 2.5 release and have fewer major changes. >>>>> >>>>> Another reason to consider a 2.5 release is that many people are >>>>> interested in a release with the latest DSv2 API and support for DSv2 SQL. >>>>> I'm already going to be backporting DSv2 support to the Spark 2.4 line, so >>>>> it makes sense to share this work with the community. >>>>> >>>>> This release line would just consist of backports like DSv2 and Java >>>>> 11 that assist compatibility, to keep the scope of the release small. The >>>>> purpose is to assist people moving to 3.0 and not distract from the 3.0 >>>>> release. >>>>> >>>>> Would a Spark 2.5 release help anyone else? Are there any concerns >>>>> about this plan? >>>>> >>>>> >>>>> rb >>>>> >>>>> >>>>> -- >>>>> Ryan Blue >>>>> Software Engineer >>>>> Netflix >>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> Ryan Blue >>>>> Software Engineer >>>>> Netflix >>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> Ryan Blue >>>>> Software Engineer >>>>> Netflix >>>>> >>>> >>>> >>> >>> -- >>> Ryan Blue >>> Software Engineer >>> Netflix >>> >> > > -- > Name : Jungtaek Lim > Blog : http://medium.com/@heartsavior > Twitter : http://twitter.com/heartsavior > LinkedIn : http://www.linkedin.com/in/heartsavior > -- Ryan Blue Software Engineer Netflix
