Hello,
From a user perspective: we have some (rare) use cases where we use “coarse
grain” datasets, with big beans and tasks that do lengthy operation (such as ML
training). In these cases we had to increase the time out to huge values
(heartbeat.timeout: 50) so that our app is not killed.
CC user ML
Hi Dhirendra,
Thanks for reaching out. A good way to start is to have a look at [1] and [2].
Once you have everything setup it should be possible to delete the pod of the
JobManager while an application is running and the job successfully recovers.
You can use one of the example Flink applicati
Hi Dan,
1) In general, there is no guarantee that your downstream operator is on the
same TM although working on the same key group. Nevertheless, you can try force
this kind of behaviour to prevent the network transfer by either chaining the
two operators (if no shuffle is in between) or confi
Thanks for your inputs Gen and Arnaud.
I do agree with you, Gen, that we need better guidance for our users on
when to change the heartbeat configuration. I think this should happen in
any case. I am, however, not so sure whether we can give hard threshold
like 5000 tasks, for example, because as
Good day Flink community,
Apache Flink/Ververica Community Edition - Question
I am having an issue with my Flink SQL jobs since updating from Flink
1.12/Ververica 2.4 to Ververica 2.5 . For all the jobs running on parquet
and S3 i am getting the following error continuously:
INITIALIZING to FAI
Thanks, Till. There are many reasons to reduce the heartbeat interval and
timeout. But I am not sure what values are suitable. In our cases, the GC
time and big job can be related factors. Since most flink jobs are pipeline
and a total failover can cost some time, we should tolerate some stop-world
Hi Dhiru,
No worries I completely understand your point. Usually all the executable
scripts from Flink can be found in the main repository [1].
We also provide a community edition of our commercial product [2] which manages
the lifecycle of the cluster and you do not have to use these scripts an
If you run `kubectl describe pod ...` on the affected pod, you should see a
reason why the previous pod has terminated (eg. OOM killed by Kubernetes).
Best,
D.
On Thu, Jul 22, 2021 at 9:30 AM Fabian Paul
wrote:
> CC user ML
>
>
Hi Natu,
Ververica Platform 2.5 has updated the bundled Hadoop version but this
should not result in a NoClassDefFoundError exception. How are you
submitting your SQL jobs? You don't use Ververica's SQL service but have
built a regular JAR file, right? If this is the case, can you share your
Hey Timo,
Thanks for the reply.
No custom file as we are using Flink SQL and submitting the job directly
through the SQL Editor UI. We are using Flink 1.13.1 as the supported flink
version. No custom code all through Flink SQL on UI no jars.
Thanks,
Natu
On Thu, Jul 22, 2021 at 2:08 PM Timo Wal
Maybe you can share also which connector/format you are using? What is
the DDL?
Regards,
Timo
On 22.07.21 14:11, Natu Lauchande wrote:
Hey Timo,
Thanks for the reply.
No custom file as we are using Flink SQL and submitting the job directly
through the SQL Editor UI. We are using Flink 1.13
Sure.
That's how the ddl table looks like:
CREATE TABLE tablea (
`a` BIGINT,
`b` BIGINT,
`c` BIGINT
)
COMMENT ''
WITH (
'auto-compaction' = 'false',
'connector' = 'filesystem',
'format' = 'parquet',
'parquet.block.size' = '134217728',
'parquet.compression' = 'SNAPPY',
Thanks, this should definitely work with the pre-packaged connectors of
Ververica platform.
I guess we have to investigate what is going on. Until then, a
workaround could be to add Hadoop manually and set the HADOOP_CLASSPATH
environment variable. The root cause seems that Hadoop cannot be fo
Hey Thomas,
Hmm, I see no reason why you should not be able to update the checkpoint
interval at runtime, and don't believe that information is stored in a
savepoint. Can you share the JobManager logs of the job where this is
ignored?
Thanks,
Austin
On Wed, Jul 21, 2021 at 11:47 AM Thms Hmm wro
I'm wondering if this discussion isn't going in the wrong direction.
It is clear that we cannot support all use-case with the defaults, so
let's not try that. We won't find it.
And I would argue that is also not their purpose; they are configurable
for a reason.
I would say the defaults should p
@d...@spark.apache.org @user
I am looking for an example around the observability framework for Apache
Flink pipelines.
This could be message tracing across multiple flink pipelines or query on
the past state of a message that was processed by any flink pipeline.
If anyone has done similar work a
Please note that when the job is canceled, the HA data(including the
checkpoint pointers) stored in the ConfigMap/ZNode will be deleted.
But it is strange that the "-s/--fromSavepoint" does not take effect when
redeploying the Flink application. The JobManager logs could help a lot to
find the roo
David's suggestion makes a lot of sense. You need to check whether the
TaskManager is killed by Kubernetes via `kubectl describe pod` for exit
code or the kubelet logs.
If it is not killed by Kubernetes, then it might crashed internally. Please
use `kubectl logs --previous` to check the logs.
Be
Thanks for sharing the thoughts Chesnay, and I overall agree with you. We
can't give a default value suitable for all jobs, but we can figure out
whether the current default value is too large for most of the jobs, and
that is the guideline for this topic. Configurability is reserved for the
others
Hi:
I followed instructions described in
[https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/table/hive]
and tested hive streaming sink, met this exception
Caused by: java.lang.ClassNotFoundException:
org.apache.hadoop.mapred.JobConf
[http://apache-flink.147419.n
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