I have been struggling for two days with an issue using the DataStream API
in Batch Execution mode.
It seems as though my side-output has no elements available to downstream
operators.
However, I am certain that the downstream operator received events.
I logged the side-output element just before
Hi Yun Gao,
Thank you for your prompt response.
I've changed the table 'format' from 'parquet' to 'raw' as in your example
and I've been able to access the file:
Job has been submitted with JobID 441e7518bb615109624c1f33f222475b
++
|url
Hello,
Following dependency vulnerabilities found with flink 1.12.3 version. Please
provide your input on this.
1. commons-io-2.7
Severity: High
Description: Apache Commons IO contains a flaw that is due to
the program failing to restrict which class can be ser
Hi Robert,
Thanks for the advice! Checking Flink Forward talks seems like a good idea,
will do 👍
On Sat, May 22, 2021 at 4:19 AM Robert Metzger wrote:
> Hi Yaroslav,
>
> My recommendation is to go with the 2nd pattern you've described, but I
> only have limited insights into real world producti
Hi Bob,
if you don't need any time characteristics, go with processing time.
Ingestion time will call System.currentTimeMillis() on every incoming
record, which is an somewhat expensive call.
Event time (and ingestion time) will attach a long field to each record,
making the records 8 bytes larger
Hi,
can you provide the jobmanager log of that run? it seems that the operation
timed out. The JobManager log will help us to give some insights into the
root cause.
On Tue, May 18, 2021 at 1:42 PM V N, Suchithra (Nokia - IN/Bangalore) <
suchithra@nokia.com> wrote:
> Hi,
>
>
>
> Stop command
Hi Theo,
Since you are running Flink locally it would be quite easy to attach a
profiler to Flink to see where most of the CPU cycles are burned (or: check
if you are maybe IO bound?) .. this could provide us with valuable data on
deciding for the next steps.
On Tue, May 18, 2021 at 5:26 PM Theo
Hi Yaroslav,
My recommendation is to go with the 2nd pattern you've described, but I
only have limited insights into real world production workloads.
Besides the parallelism configuration, I also recommend looking into slot
sharing groups, and maybe disabling operator chaining.
I'm pretty sure so
Hi Igor,
In my understanding, checkpoints are managed by the system (Flink decides
when to create and delete them), while savepoints are managed by the user
(they decide when to create and delete them).
Indeed, only checkpoints can be incremental (if that feature is enabled).
> it's made on-dema
