I think this problem should be tackled inside Kafka, not Flink.
Kafka already has internal control messages to write transaction
markers. Those could be extended to carry watermark information. It
would be best to generalize those as "user control messages" and
watermarks could just be one application.
In addition, we might need something link a "producer group" to track
how many producers are writing into a partition: this would allow to
inform downstream consumer how many different watermarks they need to track.
It's not an easy problem to solve, but without integrating with the
storage layer, but trying to solve it at the processing layer, it's even
harder.
-Matthias
On 12/20/21 01:57, Niels Basjes wrote:
I'm reading the Pulsar PIP and noticed another thing to take into account:
multiple applications (with each a different parallelism) that all write
into the same topic.
On Mon, 20 Dec 2021, 10:45 Niels Basjes, <ni...@basjes.nl> wrote:
Hi Till,
This morning I also realized what you call an 'effective watermark' is
indeed what is needed.
I'm going to read up on what Pulsar has planned.
What I realized is that the consuming application must be aware of the
parallelism of the producing application, which is independent of the
partitions in the intermediate transport.
Assume I produce in parallel 2 and have 5 kafka partition which I then
read in parallel 3; then in the consuming (parallel 3) application I must
wait for watermarks from each original input before I can continue: which
is 2
Also we must assume that those watermarks are created at different
timestamps.
So my current assessment is that the watermark records must include at
least the timestamp, the number of the thread for this watermark and the
total number of threads .
Niels
On Mon, Dec 20, 2021 at 10:10 AM Till Rohrmann <trohrm...@apache.org>
wrote:
Hi Niels,
if you have multiple inputs going into a single Kafka partition then you
have to calculate the effective watermark by looking at the min watermark
from all inputs. You could insert a Flink operator that takes care of it
and then writes to a set of partitions in 1:n relationship. Alternatively,
you could take a look at Pulsar that wants to support this functionality
out of the box [1].
[1] https://github.com/apache/pulsar/issues/12267
Cheers,
Till
On Sun, Dec 19, 2021 at 4:46 PM Niels Basjes <ni...@basjes.nl> wrote:
Hi,
About a year ago I spoke at the Flink Forward conference (
https://www.youtube.com/watch?v=wqRDyrE3dwg ) about handling
development
problems regarding streaming applications and handling the lack of
events
in a stream.
Something I spoke about towards the end of this talk was the idea to
ship
the watermarks of a Flink topology into the intermediate transport
between
applications so you wouldn't need to recreate them.
At that time it was just an idea, today I'm actually trying to build
that
and see if this idea is actually possible.
So the class of applications I work on usually do a keyBy on something
like
a SessionId, SensorId or IP address.
In low traffic scenarios this means that in Kafka some partitions are
completely idle which makes Windows/GroupBy type operations impossible
(in
my talk I explain it a lot better).
I have a test setup right now to play around with this and I'm running
into
a bit of a conceptual hurdle for which I'm looking for help.
My goal is to ship the watermarks from within a topology into Kafka and
then let a follow up application extract those watermarks again and
simply
continue.
The new SinkWriter interface has a void writeWatermark(Watermark
watermark) method
that seems intended for this kind of thing.
The basic operations like writing a watermark into Kafka, reading it
again
and then recreating the watermark again works in my test setup (very
messy
code but it works).
My hurdle has to do with the combination of
- different parallelism numbers between Flink and Kafka (how do I ship 2
watermarks into 3 partitions)
- the fact that if you do a keyBy (both in Flink and Kafka) there is a
likely mismatch between the Flink 'partition' and the Kafka `partition`.
- processing speed differences between various threads (like session "A"
needs more CPU cycles/time/processing than session "B") will lead to
skewing of the progression between them.
- watermarks in separate threads in a single Flink topology are not
synchronized (they cannot and should not be).
Has anyone any pointers on possible ways to handle this?
Right now my only idea is to ship the watermark into all partitions (as
they do not have a key!) and let the consuming application determine the
"real watermark" based on the mix of watermarks coming in from the
upstream
threads.
All suggestions and ideas are appreciated.
--
Best regards / Met vriendelijke groeten,
Niels Basjes
--
Best regards / Met vriendelijke groeten,
Niels Basjes
