Thank you for sharing these, Lukasz!
Great question, Wayne!
As for pipeline shutdown, Flink users typically take a snapshot and then
cancel the pipeline with Flink tools.
The Beam tooling needs to be improved to support cancelling as well. If
snapshotting is enabled, the Beam job could also be restored from a
snapshot instead of explicitly taking a savepoint.
Related issue for cancelling:
https://issues.apache.org/jira/browse/BEAM-593 I think we should address
this soon for the next release.
Thanks,
Max
On 03.12.18 17:53, Lukasz Cwik wrote:
There are propoosals for pipeline drain[1] and also for snapshot and
update[2] for Apache Beam. We would love contributions in this space.
1:
https://docs.google.com/document/d/1NExwHlj-2q2WUGhSO4jTu8XGhDPmm3cllSN8IMmWci8
2:
https://docs.google.com/document/d/1UWhnYPgui0gUYOsuGcCjLuoOUlGA4QaY91n8p3wz9MY
On Mon, Dec 3, 2018 at 7:05 AM Wayne Collins <[email protected]
<mailto:[email protected]>> wrote:
Hi JC,
Thanks for the quick response!
I had hoped for an in-pipeline solution for runner portability but
it is nice to know we're not the only ones stepping outside to
interact with runner management. :-)
Wayne
On 2018-12-03 01:23, Juan Carlos Garcia wrote:
Hi Wayne,
We have the same setup and we do daily updates to our pipeline.
The way we do it is using the flink tool via a Jenkins.
Basically our deployment job do as follow:
1. Detect if the pipeline is running (it matches via job name)
2. If found, do a flink cancel with a savepoint (we uses hdfs for
checkpoint / savepoint) under a given directory.
3. It uses the flink run command for the new job and specify the
savepoint from step 2.
I don't think there is any support to achieve the same from within
the pipeline. You need to do this externally as explained above.
Best regards,
JC
Am Mo., 3. Dez. 2018, 00:46 hat Wayne Collins <[email protected]
<mailto:[email protected]>> geschrieben:
Hi all,
We have a number of Beam pipelines processing unbounded
streams sourced from Kafka on the Flink runner and are very
happy with both the platform and performance!
The problem is with shutting down the pipelines...for version
upgrades, system maintenance, load management, etc. it would
be nice to be able to gracefully shut these down under
software control but haven't been able to find a way to do so.
We're in good shape on checkpointing and then cleanly
recovering but shutdowns are all destructive to Flink or the
Flink TaskManager.
Methods tried:
1) Calling cancel on FlinkRunnerResult returned from
pipeline.run()
This would be our preferred method but p.run() doesn't return
until termination and even if it did, the runner code simply
throws:
"throw new UnsupportedOperationException("FlinkRunnerResult
does not support cancel.");"
so this doesn't appear to be a near-term option.
2) Inject a "termination" message into the pipeline via Kafka
This does get through, but calling exit() from a stage in the
pipeline also terminates the Flink TaskManager.
3) Inject a "sleep" message, then manually restart the cluster
This is our current method: we pause the data at the source,
flood all branches of the pipeline with a "we're going down"
msg so the stages can do a bit of housekeeping, then hard-stop
the entire environment and re-launch with the new version.
Is there a "Best Practice" method for gracefully terminating
an unbounded pipeline from within the pipeline or from the
mainline that launches it?
Thanks!
Wayne
--
Wayne Collins
dades.ca <http://dades.ca> Inc.
mailto:[email protected]
cell:416-898-5137
--
Wayne Collins
dades.ca <http://dades.ca> Inc.
mailto:[email protected]
cell:416-898-5137
