Hi,
I'm interested to know if there is an available feature for integrating
Apache Flink with Apache Ranger. If so, could you kindly share the relevant
documentation with me?
Thanks and regards,
Arjun S
Hi, wenjiang
It does seem a bit odd that it could theoretically work either way. I think
you can check the Flink JobManager log to find more information.
Best,
Ron
傅文江 于2023年7月24日周一 17:37写道：
>
> When I use ESSink, I find that I need to set Flink’s
> jobmanager.memory.off-heap.size to 256MB.
Hi,
Lijuan
> 1 - It seems for flink job using flink operator to realize autoscaling,
the only option to realize autoscaling is to enable the Autoscaler feature,
and KEDA won’t work, right?
What is KEDA mean?
> 2 - I noticed from the document that we need to upgrade to flink version
of 1.17 to u
Hi, David
Regarding the N-way join, this feature aims to address the issue of state
simplification, it is on the roadmap. Technically there are no limitations,
but we'll need some time to find a sensible solution.
Best,
Ron
David Anderson 于2023年8月9日周三 10:38写道：
> This join optimization sounds p
Hi, Flavio
IMO, the current DataStream API is not aligned with DataSet in terms of
capabilities, I think you can try it with GlobalWindow. Another possible
solution is to convert the DataStream to a table[1] first and then try it
with a join on the Table API.
[1]
https://nightlies.apache.org/flin
This join optimization sounds promising, but I'm wondering why Flink
SQL isn't taking advantage of the N-Ary Stream Operator introduced in
FLIP-92 [1][2] to implement a n-way join in a single operator. Is
there something that makes this impossible/impractical?
[1] https://cwiki.apache.org/confluen
Hi David and Xiangyu,
For more context,
We have a job running on our cluster aggregating StatsD metrics in tumbling
window, which causes CPU usage spikes due to concurrent executions. While
staggering the windows using StaggerWindow could help this will impact the
job's accuracy. Instead, we
Hi Flink team,
This is Lijuan. I am working on our flink job to realize autoscaling. We are
currently using flink version of 1.16.1, and using flink operator version of
1.5.0. I have some questions need to confirm with you.
1 - It seems for flink job using flink operator to realize autoscaling,
