I agree, it would be the easiest way and allow users to switch easily as
well using a single artifact.
Regards
JB
On 29/10/2019 23:54, Kenneth Knowles 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)?
