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From Hyukjin Kwon <gurwls...@gmail.com>
Subject Re: [DISCUSS] Spark 2.5 release
Date Mon, 23 Sep 2019 01:39:29 GMT
+1 for Matei's as well.

On Sun, 22 Sep 2019, 14:59 Marco Gaido, <marcogaido91@gmail.com> wrote:

> I agree with Matei too.
>
> Thanks,
> Marco
>
> Il giorno dom 22 set 2019 alle ore 03:44 Dongjoon Hyun <
> dongjoon.hyun@gmail.com> ha scritto:
>
>> +1 for Matei's suggestion!
>>
>> Bests,
>> Dongjoon.
>>
>> On Sat, Sep 21, 2019 at 5:44 PM Matei Zaharia <matei.zaharia@gmail.com>
>> wrote:
>>
>>> If the goal is to get people to try the DSv2 API and build DSv2 data
>>> sources, can we recommend the 3.0-preview release for this? That would get
>>> people shifting to 3.0 faster, which is probably better overall compared to
>>> maintaining two major versions. There’s not that much else changing in 3.0
>>> if you already want to update your Java version.
>>>
>>> On Sep 21, 2019, at 2:45 PM, Ryan Blue <rblue@netflix.com.INVALID>
>>> wrote:
>>>
>>> > If you insist we shouldn't change the unstable temporary API in 3.x .
>>> . .
>>>
>>> Not what I'm saying at all. I said we should carefully consider whether
>>> a breaking change is the right decision in the 3.x line.
>>>
>>> All I'm suggesting is that we can make a 2.5 release with the feature
>>> and an API that is the same as the one in 3.0.
>>>
>>> > I also don't get this backporting a giant feature to 2.x line
>>>
>>> I am planning to do this so we can use DSv2 before 3.0 is released. Then
>>> we can have a source implementation that works in both 2.x and 3.0 to make
>>> the transition easier. Since I'm already doing the work, I'm offering to
>>> share it with the community.
>>>
>>>
>>> On Sat, Sep 21, 2019 at 2:36 PM Reynold Xin <rxin@databricks.com> wrote:
>>>
>>>> Because for example we'd need to move the location of InternalRow,
>>>> breaking the package name. If you insist we shouldn't change the unstable
>>>> temporary API in 3.x to maintain compatibility with 3.0, which is totally
>>>> different from my understanding of the situation when you exposed it, then
>>>> I'd say we should gate 3.0 on having a stable row interface.
>>>>
>>>> I also don't get this backporting a giant feature to 2.x line ... as
>>>> suggested by others in the thread, DSv2 would be one of the main reasons
>>>> people upgrade to 3.0. What's so special about DSv2 that we are doing this?
>>>> Why not abandoning 3.0 entirely and backport all the features to 2.x?
>>>>
>>>>
>>>>
>>>> On Sat, Sep 21, 2019 at 2:31 PM, Ryan Blue <rblue@netflix.com> wrote:
>>>>
>>>>> Why would that require an incompatible change?
>>>>>
>>>>> We *could* make an incompatible change and remove support for
>>>>> InternalRow, but I think we would want to carefully consider whether
that
>>>>> is the right decision. And in any case, we would be able to keep 2.5
and
>>>>> 3.0 compatible, which is the main goal.
>>>>>
>>>>> On Sat, Sep 21, 2019 at 2:28 PM Reynold Xin <rxin@databricks.com>
>>>>> wrote:
>>>>>
>>>>> How would you not make incompatible changes in 3.x? As discussed the
>>>>> InternalRow API is not stable and needs to change.
>>>>>
>>>>> On Sat, Sep 21, 2019 at 2:27 PM Ryan Blue <rblue@netflix.com> wrote:
>>>>>
>>>>> > 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 <kabhwan@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.hyun@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 <rblue@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 <rxin@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 <rblue@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 <rxin@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 <rblue@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 <rxin@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 <rblue@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
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> Ryan Blue
>>>>> Software Engineer
>>>>> Netflix
>>>>>
>>>>
>>>>
>>>
>>> --
>>> Ryan Blue
>>> Software Engineer
>>> Netflix
>>>
>>>
>>>

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