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From Ryan Blue <rb...@netflix.com.INVALID>
Subject Re: [DISCUSS] Spark 2.5 release
Date Tue, 24 Sep 2019 19:56:15 GMT
>From those questions, I can see that there is significant confusion about
what I'm proposing, so let me try to clear it up.

> 1. Is DSv2 stable in `master`?

DSv2 has reached a stable API that is capable of supporting all of the
features we intend to deliver for Spark 3.0. The proposal is to backport
the same API and features for Spark 2.5.

I am not saying that this API won't change after 3.0. Notably, Reynold
wants to change the use of InternalRow. But, these changes are after 3.0
and don't affect the compatibility I'm proposing, between the 2.5 and 3.0
releases. I also doubt that breaking changes would happen by 3.1.

> 2. If then, what subset of DSv2 patches does Ryan is suggesting
backporting?

I am proposing backporting what we intend to deliver for 3.0: the API
currently in master, SQL support, and multi-catalog support.

> 3. How much those backporting DSv2 patches looks differently in
`branch-2.4`?

DSv2 is mostly an addition located in the `connector` package. It also
changes some parts of the SQL parser and adds parsed plans, as well as new
rules to convert from parsed plans. This is not an invasive change because
we kept most of DSv2 separate. DSv2 should be nearly identical between the
two branches.

> 4. What does he mean by `without breaking changes? Is it technically
feasible?

DSv2 is marked unstable in the 2.x line and changes between releases. The
API changed between 2.3 and 2.4, so this would be no different. But, we
would keep the API the same between 2.5 and 3.0 to assist migration.

This is technically feasible because what we are planning to deliver for
3.0 is nearly ready, and the API has not needed to change recently.

> Apache Spark 2.4.x and 2.5.x DSv2 should be compatible.

This has not been a requirement for DSv2 development so far. If this is a
new requirement, then we should not do a 2.5 release.

> 5. How long does it take? Is it possible before 3.0.0-preview? Who will
work on that backporting?

As I said, I'm already going to do this work, so I'm offering to release it
to the community. I don't know how long it will take, but this work and
3.0-preview are not mutually exclusive.

> 6. Is this meaningful if 2.5 and 3.1 become different again too soon (in
2020 Summer)?

It is useful to me, so I assume it is useful to others.

I also think it is unlikely that 3.1 will need to make API changes to DSv2.
There may be some bugs found, but I don't think we will break API
compatibility so quickly. Most of the changes to the API will require only
additions.

> If you have a working branch, please share with us.

I don't have a branch to share.


On Mon, Sep 23, 2019 at 6:47 PM Dongjoon Hyun <dongjoon.hyun@gmail.com>
wrote:

> Hi, Ryan.
>
> This thread has many replied as you see. That is the evidence that the
> community is interested in your suggestion a lot.
>
> > I'm offering to help build a stable release without breaking changes.
> But if there is no community interest in it, I'm happy to drop this.
>
> In this thread, the root cause of the disagreement is due to the lack of
> supporting evidence for your claims.
>
> 1. Is DSv2 stable in `master`?
> 2. If then, what subset of DSv2 patches does Ryan is suggesting
> backporting?
> 3. How much those backporting DSv2 patches looks differently in
> `branch-2.4`?
> 4. What does he mean by `without breaking changes? Is it technically
> feasible?
>     Apache Spark 2.4.x and 2.5.x DSv2 should be compatible. (Not between
> 2.5.x DSv2 and 3.0.0 DSv2)
> 5. How long does it take? Is it possible before 3.0.0-preview? Who will
> work on that backporting?
> 6. Is this meaningful if 2.5 and 3.1 become different again too soon (in
> 2020 Summer)?
>
> We are SW engineers.
> If you have a working branch, please share with us.
> It will help us understand your suggestion and this discussion.
> We can help you verify that branch achieves your goal.
> The branch is tested already, isn't it?
>
> Bests,
> Dongjoon.
>
>
>
>
> On Mon, Sep 23, 2019 at 10:44 AM Holden Karau <holden@pigscanfly.ca>
> wrote:
>
>> I would personally love to see us provide a gentle migration path to
>> Spark 3 especially if much of the work is already going to happen anyways.
>>
>> Maybe giving it a different name (eg something like
>> Spark-2-to-3-transitional) would make it more clear about its intended
>> purpose and encourage folks to move to 3 when they can?
>>
>> On Mon, Sep 23, 2019 at 9:17 AM Ryan Blue <rblue@netflix.com.invalid>
>> wrote:
>>
>>> My understanding is that 3.0-preview is not going to be a
>>> production-ready release. For those of us that have been using backports of
>>> DSv2 in production, that doesn't help.
>>>
>>> It also doesn't help as a stepping stone because users would need to
>>> handle all of the incompatible changes in 3.0. Using 3.0-preview would be
>>> an unstable release with breaking changes instead of a stable release
>>> without the breaking changes.
>>>
>>> I'm offering to help build a stable release without breaking changes.
>>> But if there is no community interest in it, I'm happy to drop this.
>>>
>>> On Sun, Sep 22, 2019 at 6:39 PM Hyukjin Kwon <gurwls223@gmail.com>
>>> wrote:
>>>
>>>> +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
>>>>>>>>>
>>>>>>>> --
>> Twitter: https://twitter.com/holdenkarau
>> Books (Learning Spark, High Performance Spark, etc.):
>> https://amzn.to/2MaRAG9  <https://amzn.to/2MaRAG9>
>> YouTube Live Streams: https://www.youtube.com/user/holdenkarau
>>
>

-- 
Ryan Blue
Software Engineer
Netflix

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