Hi Ruibin,
I think it may be hard to say which provider is alway more recommended than
the other. The answer to your question depends heavily on your team's
technical stack, your platform and your expectations on the new cluster.
I *cannot* give you any advice but I just want share some observation
Hi Danny-
Thanks for your response!
At first glance, I’m not sure, will drill in to look deeper. For
clarification, a few points I probably should have expressed initially:
1. I’m running flink as a Kinesis Data Application (AWS serverless
application)
2. The reason I want to use strea
Hello David,
There is a FLIP [1] to add native Glue Catalog support and we already have
Glue Schema Registry format plugins [2][3], however these are data
stream API only. Are you intending on just using the Glue schema features
or leveraging other features? Would either of the things I mentioned
Hi Ruibin,
Given that you are starting fresh I would recommend going with Kubernetes
and specifically checking out the Flink Kubernetes Operator. [1] I have
worked with Yarn for years before I transitioned to Kubernetes a year ago
and I am pleased that we made the jump. To address you point on a v
I actually managed to fixed this already :) For those wondering, I grouped by
both window start and end first. That did it!
> On 19. Dec 2022, at 15:43, Theodor Wübker wrote:
>
> Hey everyone,
>
> I would like to run a Windowing-SQL query with a group-by clause on a Kafka
> topic and write th
Hi Raihan,
As the description of PipelinedRegion says, a pipelined region is a set of
vertices connected via pipelined data exchanges. For example in a job with
such a dag A->B, both of the tasks have two subtasks. If the edge between A
and B is a forward edge, there are two pipelined regions: (A1
Hi Sunny,
Welcome to Flink 😊.
The next thing for you to consider is to setup checkpointing [1] which allows a
failing job to pick up from where it stopped.
Sincere greetings from the supposed close-by Zurich 😊
Thias
[1]
https://nightlies.apache.org/flink/flink-docs-master/docs/dev/datastre
