Very good points. We definitely ship a lot of code/features in very
early stages, and there seems to be no problem.
I intend mostly to leave this judgment to people like you who know
better about Spark users.
But I do think 1 or 2 jars is better than 3. I really don't like "3
jars" and I did give two reasons:
1. diamond deps where things overlap
2. figuring out which thing to depend on
Both are annoying for users. I am not certain if it could lead to a
real unsolvable situation. This is just a Java ecosystem problem so I
feel qualified to comment.
I did also ask if there were major dependency differences between the
two that could cause problems for users. This question was dropped and
no one cares to comment so I assume it is not an issue. So then I
favor having just 1 jar with both runners.
Kenn
On Wed, Oct 30, 2019 at 2:46 PM Ismaël Mejía <[email protected]
<mailto:[email protected]>> wrote:
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]
<mailto:[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] <mailto:[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]
<mailto:[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] <mailto:[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] <mailto:[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] <mailto:[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] <mailto:[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] <mailto:[email protected]>> wrote:
>>>>>
>>>>> Sounds like a good plan to me.
>>>>>
>>>>> On Fri, Oct 11, 2019 at 6:20 AM Etienne Chauchot
<[email protected] <mailto:[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] <mailto:[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] <mailto:[email protected]>> wrote:
>>>>>>
>>>>>> On Thu, Oct 10, 2019 at 12:39 AM Etienne Chauchot
<[email protected] <mailto:[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)?
>>>
>>>
>>>
>>
