Aljoscha Krettek wrote
> Hi,
> zero-downtime updates are currently not supported. What is supported in
> Flink right now is a savepoint-shutdown-restore cycle. With this, you
> first
> draw a savepoint (which is essentially a checkpoint with some meta data),
> then you cancel your job, then you do whatever you need to do (update
> machines, update Flink, update Job) and restore from the savepoint.
> 
> A possible solution for zero-downtime update would be to do a savepoint,
> then start a second Flink job from that savepoint, then shutdown the first
> job. With this, your data sinks would need to be able to handle being
> written to by 2 jobs at the same time, i.e. writes should probably be
> idempotent.
> 
> This is the link to the savepoint doc:
> https://ci.apache.org/projects/flink/flink-docs-release-1.2/setup/savepoints.html
> 
> Does that help?
> 
> Cheers,
> Aljoscha
> 
> On Fri, 16 Dec 2016 at 18:16 Andrew Hoblitzell <

> ahoblitzell@

> >
> wrote:
> 
>> Hi. Does Apache Flink currently have support for zero down time or the =
>> ability to do rolling upgrades?
>>
>> If so, what are concerns to watch for and what best practices might =
>> exist? Are there version management and data inconsistency issues to =
>> watch for?=
>>

When a second job instance is started in parallel from a savepoint, my
incoming kafka messages would get sharded between the 2 running instances of
the job (since they both would belong to the same consumer group). So when I
stop the older version of the job, i stand to lose data (inspite of the fact
that my downstream consumer is idempotent)

If I used a different consumer group for the new job version (and start it
from a savepoint), will the savepoint ensure that the second job instance
starts from the correct offset? Do I need to do anything extra to make this
work? (example set the uid on the source of the job).

Thanks!
Moiz



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