Hi Fabian,
+1 👍
Cheers
Dhanuka
On Mon, 14 Jan 2019, 21:29 Fabian Hueske Hi,
>
> That's a Java limitation. Methods cannot be larger than 64kb and code that
> is generated for this predicate exceeds the limit.
> There is a Jira issue to fix the problem.
>
> In the meantime, I'd follow a hybrid ap
Hi,
That's a Java limitation. Methods cannot be larger than 64kb and code that
is generated for this predicate exceeds the limit.
There is a Jira issue to fix the problem.
In the meantime, I'd follow a hybrid approach and UNION ALL only as many
tables as you need to avoid the code compilation exc
Hi Fabian ,
I was encounter below error with 200 OR operators so I guess this is JVM
level limitation.
Error :
of class "datastreamcalcrule" grows beyond 64 kb
Cheers
Dhanuka
On Mon, 14 Jan 2019, 20:30 Fabian Hueske Hi,
>
> you should avoid the UNION ALL approach because the query will scan
Hi,
you should avoid the UNION ALL approach because the query will scan the
(identical?) Kafka topic 200 times which is highly inefficient.
You should rather use your second approach and scale the query
appropriately.
Best, Fabian
Am Mo., 14. Jan. 2019 um 08:39 Uhr schrieb dhanuka ranasinghe <
d
Hi dhanuka,
> I am trying to deploy 200 SQL unions and it seems all the tasks getting
failing after some time.
Would be great if you can show us some information(say exception stack)
about the failure. Is it caused by OOM of job manager?
> How do i allocate memory for task manager and job manager
Hi Fabian,
Thanks for the prompt reply and its working 🤗.
I am trying to deploy 200 SQL unions and it seems all the tasks getting
failing after some time.
How do i allocate memory for task manager and job manager. What are the
factors need to be considered .
Cheers
Dhanuka
On Sun, 13 Jan 2019,
Hi Dhanuka,
The important error message here is "AppendStreamTableSink requires that
Table has only insert changes".
This is because you use UNION instead of UNION ALL, which implies duplicate
elimination.
Unfortunately, UNION is currently internally implemented as a regular
aggregration which pro