The problem with having a distribution with "popular" stuff is that it
doesn't really /solve/ a problem, it just hides it for users who fall
into these particular use-cases.
Move out of it and you once again run into exact same problems out-lined.
This is exactly why I like the tooling approach; you have to deal with
it from the start and transitioning to a custom use-case is easier.
Would users following instructions really be such a big problem?
I would expect that users generally know /what /they need, just not
necessarily how it is assembled correctly (where do get which jar, which
directory to put it in).
It seems like these are exactly the problem this would solve?
I just don't see how moving a jar corresponding to some feature from opt
to some directory (lib/plugins) is less error-prone than just selecting
the feature and having the tool handle the rest.
As for re-distributions, it depends on the form that the tool would take.
It could be an application that runs locally and works against maven
central (note: not necessarily /using/ maven); this should would work in
China, no?
A web tool would of course be fancy, but I don't know how feasible this
is with the ASF infrastructure.
You wouldn't be able to mirror the distribution, so the load can't be
distributed. I doubt INFRA would like this.
Note that third-parties could also start distributing use-case oriented
distributions, which would be perfectly fine as far as I'm concerned.
On 16/04/2020 16:57, Kurt Young wrote:
I'm not so sure about the web tool solution though. The concern I have for
this approach is the final generated
distribution is kind of non-deterministic. We might generate too many
different combinations when user trying to
package different types of connector, format, and even maybe hadoop
releases. As far as I can tell, most open
source projects and apache projects will only release some
pre-defined distributions, which most users are already
familiar with, thus hard to change IMO. And I also have went through in
some cases, users will try to re-distribute
the release package, because of the unstable network of apache website from
China. In web tool solution, I don't
think this kind of re-distribution would be possible anymore.
In the meantime, I also have a concern that we will fall back into our trap
again if we try to offer this smart & flexible
solution. Because it needs users to cooperate with such mechanism. It's
exactly the situation what we currently fell
into:
1. We offered a smart solution.
2. We hope users will follow the correct instructions.
3. Everything will work as expected if users followed the right
instructions.
In reality, I suspect not all users will do the second step correctly. And
for new users who only trying to have a quick
experience with Flink, I would bet most users will do it wrong.
So, my proposal would be one of the following 2 options:
1. Provide a slim distribution for advanced product users and provide a
distribution which will have some popular builtin jars.
2. Only provide a distribution which will have some popular builtin jars.
If we are trying to reduce the distributions we released, I would prefer 2
1.
Best,
Kurt
On Thu, Apr 16, 2020 at 9:33 PM Till Rohrmann <trohrm...@apache.org> wrote:
I think what Chesnay and Dawid proposed would be the ideal solution.
Ideally, we would also have a nice web tool for the website which generates
the corresponding distribution for download.
To get things started we could start with only supporting to
download/creating the "fat" version with the script. The fat version would
then consist of the slim distribution and whatever we deem important for
new users to get started.
Cheers,
Till
On Thu, Apr 16, 2020 at 11:33 AM Dawid Wysakowicz <dwysakow...@apache.org>
wrote:
Hi all,
Few points from my side:
1. I like the idea of simplifying the experience for first time users.
As for production use cases I share Jark's opinion that in this case I
would expect users to combine their distribution manually. I think in
such scenarios it is important to understand interconnections.
Personally I'd expect the slimmest possible distribution that I can
extend further with what I need in my production scenario.
2. I think there is also the problem that the matrix of possible
combinations that can be useful is already big. Do we want to have a
distribution for:
SQL users: which connectors should we include? should we include
hive? which other catalog?
DataStream users: which connectors should we include?
For both of the above should we include yarn/kubernetes?
I would opt for providing only the "slim" distribution as a release
artifact.
3. However, as I said I think its worth investigating how we can improve
users experience. What do you think of providing a tool, could be e.g. a
shell script that constructs a distribution based on users choice. I
think that was also what Chesnay mentioned as "tooling to
assemble custom distributions" In the end how I see the difference
between a slim and fat distribution is which jars do we put into the
lib, right? It could have a few "screens".
1. Which API are you interested in:
a. SQL API
b. DataStream API
2. [SQL] Which connectors do you want to use? [multichoice]:
a. Kafka
b. Elasticsearch
...
3. [SQL] Which catalog you want to use?
...
Such a tool would download all the dependencies from maven and put them
into the correct folder. In the future we can extend it with additional
rules e.g. kafka-0.9 cannot be chosen at the same time with
kafka-universal etc.
The benefit of it would be that the distribution that we release could
remain "slim" or we could even make it slimmer. I might be missing
something here though.
Best,
Dawdi
On 16/04/2020 11:02, Aljoscha Krettek wrote:
I want to reinforce my opinion from earlier: This is about improving
the situation both for first-time users and for experienced users that
want to use a Flink dist in production. The current Flink dist is too
"thin" for first-time SQL users and it is too "fat" for production
users, that is where serving no-one properly with the current
middle-ground. That's why I think introducing those specialized
"spins" of Flink dist would be good.
By the way, at some point in the future production users might not
even need to get a Flink dist anymore. They should be able to have
Flink as a dependency of their project (including the runtime) and
then build an image from this for Kubernetes or a fat jar for YARN.
Aljoscha
On 15.04.20 18:14, wenlong.lwl wrote:
Hi all,
Regarding slim and fat distributions, I think different kinds of jobs
may
prefer different type of distribution:
For DataStream job, I think we may not like fat distribution
containing
connectors because user would always need to depend on the connector
in
user code, it is easy to include the connector jar in the user lib.
Less
jar in lib means less class conflicts and problems.
For SQL job, I think we are trying to encourage user to user pure
sql(DDL +
DML) to construct their job, In order to improve user experience, It
may be
important for flink, not only providing as many connector jar in
distribution as possible especially the connector and format we have
well
documented, but also providing an mechanism to load connectors
according
to the DDLs,
So I think it could be good to place connector/format jars in some
dir like
opt/connector which would not affect jobs by default, and introduce a
mechanism of dynamic discovery for SQL.
Best,
Wenlong
On Wed, 15 Apr 2020 at 22:46, Jingsong Li <jingsongl...@gmail.com>
wrote:
Hi,
I am thinking both "improve first experience" and "improve production
experience".
I'm thinking about what's the common mode of Flink?
Streaming job use Kafka? Batch job use Hive?
Hive 1.2.1 dependencies can be compatible with most of Hive server
versions. So Spark and Presto have built-in Hive 1.2.1 dependency.
Flink is currently mainly used for streaming, so let's not talk
about hive.
For streaming jobs, first of all, the jobs in my mind is (related to
connectors):
- ETL jobs: Kafka -> Kafka
- Join jobs: Kafka -> DimJDBC -> Kafka
- Aggregation jobs: Kafka -> JDBCSink
So Kafka and JDBC are probably the most commonly used. Of course,
also
includes CSV, JSON's formats.
So when we provide such a fat distribution:
- With CSV, JSON.
- With flink-kafka-universal and kafka dependencies.
- With flink-jdbc.
Using this fat distribution, most users can run their jobs well.
(jdbc
driver jar required, but this is very natural to do)
Can these dependencies lead to kinds of conflicts? Only Kafka may
have
conflicts, but if our goal is to use kafka-universal to support all
Kafka
versions, it is hopeful to target the vast majority of users.
We don't want to plug all jars into the fat distribution. Only need
less
conflict and common. of course, it is a matter of consideration to
put
which jar into fat distribution.
We have the opportunity to facilitate the majority of users, but
also left
opportunities for customization.
Best,
Jingsong Lee
On Wed, Apr 15, 2020 at 10:09 PM Jark Wu <imj...@gmail.com> wrote:
Hi,
I think we should first reach an consensus on "what problem do we
want to
solve?"
(1) improve first experience? or (2) improve production experience?
As far as I can see, with the above discussion, I think what we
want to
solve is the "first experience".
And I think the slim jar is still the best distribution for
production,
because it's easier to assembling jars
than excluding jars and can avoid potential class conflicts.
If we want to improve "first experience", I think it make sense to
have a
fat distribution to give users a more smooth first experience.
But I would like to call it "playground distribution" or something
like
that to explicitly differ from the "slim production-purpose
distribution".
The "playground distribution" can contains some widely used jars,
like
universal-kafka-sql-connector, elasticsearch7-sql-connector, avro,
json,
csv, etc..
Even we can provide a playground docker which may contain the fat
distribution, python3, and hive.
Best,
Jark
On Wed, 15 Apr 2020 at 21:47, Chesnay Schepler <ches...@apache.org>
wrote:
I don't see a lot of value in having multiple distributions.
The simple reality is that no fat distribution we could provide
would
satisfy all use-cases, so why even try.
If users commonly run into issues for certain jars, then maybe
those
should be added to the current distribution.
Personally though I still believe we should only distribute a slim
version. I'd rather have users always add required jars to the
distribution than only when they go outside our "expected"
use-cases.
Then we might finally address this issue properly, i.e., tooling to
assemble custom distributions and/or better error messages if
Flink-provided extensions cannot be found.
On 15/04/2020 15:23, Kurt Young wrote:
Regarding to the specific solution, I'm not sure about the "fat"
and
"slim"
solution though. I get the idea
that we can make the slim one even more lightweight than current
distribution, but what about the "fat"
one? Do you mean that we would package all connectors and formats
into
this? I'm not sure if this is
feasible. For example, we can't put all versions of kafka and hive
connector jars into lib directory, and
we also might need hadoop jars when using filesystem connector to
access
data from HDFS.
So my guess would be we might hand-pick some of the most
frequently
used
connectors and formats
into our "lib" directory, like kafka, csv, json metioned above,
and
still
leave some other connectors out of it.
If this is the case, then why not we just provide this
distribution
to
user? I'm not sure i get the benefit of
providing another super "slim" jar (we have to pay some costs to
provide
another suit of distribution).
What do you think?
Best,
Kurt
On Wed, Apr 15, 2020 at 7:08 PM Jingsong Li <
jingsongl...@gmail.com
wrote:
Big +1.
I like "fat" and "slim".
For csv and json, like Jark said, they are quite small and don't
have
other
dependencies. They are important to kafka connector, and
important
to upcoming file system connector too.
So can we move them to both "fat" and "slim"? They're so
important,
and
they're so lightweight.
Best,
Jingsong Lee
On Wed, Apr 15, 2020 at 4:53 PM godfrey he <godfre...@gmail.com>
wrote:
Big +1.
This will improve user experience (special for Flink new users).
We answered so many questions about "class not found".
Best,
Godfrey
Dian Fu <dian0511...@gmail.com> 于2020年4月15日周三 下午4:30写道：
+1 to this proposal.
Missing connector jars is also a big problem for PyFlink users.
Currently,
after a Python user has installed PyFlink using `pip`, he has
to
manually
copy the connector fat jars to the PyFlink installation
directory
for
the
connectors to be used if he wants to run jobs locally. This
process
is
very
confuse for users and affects the experience a lot.
Regards,
Dian
在 2020年4月15日，下午3:51，Jark Wu <imj...@gmail.com> 写道：
+1 to the proposal. I also found the "download additional jar"
step
is
really verbose when I prepare webinars.
At least, I think the flink-csv and flink-json should in the
distribution,
they are quite small and don't have other dependencies.
Best,
Jark
On Wed, 15 Apr 2020 at 15:44, Jeff Zhang <zjf...@gmail.com>
wrote:
Hi Aljoscha,
Big +1 for the fat flink distribution, where do you plan to
put
these
connectors ? opt or lib ?
Aljoscha Krettek <aljos...@apache.org> 于2020年4月15日周三
下午3:30写道：
Hi Everyone,
I'd like to discuss about releasing a more full-featured
Flink
distribution. The motivation is that there is friction for
SQL/Table
API
users that want to use Table connectors which are not there
in
the
current Flink Distribution. For these users the workflow is
currently
roughly:
- download Flink dist
- configure csv/Kafka/json connectors per configuration
- run SQL client or program
- decrypt error message and research the solution
- download additional connector jars
- program works correctly
I realize that this can be made to work but if every SQL
user
has
this
as their first experience that doesn't seem good to me.
My proposal is to provide two versions of the Flink
Distribution
in
the
future: "fat" and "slim" (names to be discussed):
- slim would be even trimmer than todays distribution
- fat would contain a lot of convenience connectors (yet
to
be
determined which one)
And yes, I realize that there are already more dimensions of
Flink
releases (Scala version and Java version).
For background, our current Flink dist has these in the opt
directory:
- flink-azure-fs-hadoop-1.10.0.jar
- flink-cep-scala_2.12-1.10.0.jar
- flink-cep_2.12-1.10.0.jar
- flink-gelly-scala_2.12-1.10.0.jar
- flink-gelly_2.12-1.10.0.jar
- flink-metrics-datadog-1.10.0.jar
- flink-metrics-graphite-1.10.0.jar
- flink-metrics-influxdb-1.10.0.jar
- flink-metrics-prometheus-1.10.0.jar
- flink-metrics-slf4j-1.10.0.jar
- flink-metrics-statsd-1.10.0.jar
- flink-oss-fs-hadoop-1.10.0.jar
- flink-python_2.12-1.10.0.jar
- flink-queryable-state-runtime_2.12-1.10.0.jar
- flink-s3-fs-hadoop-1.10.0.jar
- flink-s3-fs-presto-1.10.0.jar
-
flink-shaded-netty-tcnative-dynamic-2.0.25.Final-9.0.jar
- flink-sql-client_2.12-1.10.0.jar
- flink-state-processor-api_2.12-1.10.0.jar
- flink-swift-fs-hadoop-1.10.0.jar
Current Flink dist is 267M. If we removed everything from
opt
we
would
go down to 126M. I would reccomend this, because the large
majority
of
the files in opt are probably unused.
What do you think?
Best,
Aljoscha
--
Best Regards
Jeff Zhang
--
Best, Jingsong Lee
--
Best, Jingsong Lee
