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Re: Graceful shutdown of long-running Beam pipeline on Flink


There are propoosals for pipeline drain[1] and also for snapshot and update[2] for Apache Beam. We would love contributions in this space.


On Mon, Dec 3, 2018 at 7:05 AM Wayne Collins <wayneco@xxxxxxxx> 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 <wayneco@xxxxxxxx> 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 Inc.
mailto:wayneco@xxxxxxxx
cell:416-898-5137

-- 
Wayne Collins
dades.ca Inc.
mailto:wayneco@xxxxxxxx
cell:416-898-5137