Hi Gyula,
there exists a related issue [1]. Fixing this issue will move the state
restoration in the state DEPLOYING. This means that when you see a task
being in state RUNNING, then it will have restored all of its eager state.
[1] https://issues.apache.org/jira/browse/FLINK-4714
Cheers,
Till
Hi,
Any updates here? I'm sure many would have faced similar issues like
these, any help here is highly appreciated.
Best Regards
CVP
On Tue, Mar 28, 2017 at 5:47 PM, Chakravarthy varaga <
chakravarth...@gmail.com> wrote:
> Hi Team,
>
>If the flink cluster is conainerized and managed th
Thanks Till,
This is exactly what I was looking for :)
Gyula
Till Rohrmann ezt írta (időpont: 2017. márc. 29.,
Sze, 10:23):
> Hi Gyula,
>
> there exists a related issue [1]. Fixing this issue will move the state
> restoration in the state DEPLOYING. This means that when you see a task
> being i
Hi guys,
I’m using flink on production in Mapp. We recently swapped from storm.
Before I have put this live I was doing performance tests and I found
something that “feels” a bit off.
I have a simple streaming job reading from kafka, doing window for 3
seconds and then storing into hbase.
Initial
Hi guys,
I can’t found on web which graph partitioning are supported by Gelly.
During my search I found this link. But the ticket is still open.
https://cwiki.apache.org/confluence/display/FLINK/Flink+Gelly
Thanks for help!
Best
Marc
Hi Ufuk, hi Stefan,
thanks a lot for your replies.
Ufuk, we are using the HDFS state backend.
Stefan, I installed 1.1.5 on our machines and built our software with
the Flink 1.1.5 dependency, but the problem remains. Below are the logs
for savepoint creation [1] and savepoint disposal [2] as we
Hello,
The cancel-with-savepoint command is not available in 0.10.1 .
I'm pretty sure it was added in 1.2 , so you'll have to upgrade the
runtime-web dependency.
Note that all Flink dependencies should always have the same version.
Regards,
Chesnay
On 28.03.2017 18:12, Sendoh wrote:
Hi Flin
Hi Kamil,
the performance implications might be the result of which state the
underlying functions are using internally. WindowFunctions use ListState
or ReducingState, fold() uses FoldingState. It also depends on the size
of your state and the state backend you are using. I recommend the
fol
Hi Marc,
maybe Greg (in CC) can help answering your question?
Regards,
Timo
Am 29/03/17 um 11:50 schrieb Kaepke, Marc:
Hi guys,
I can’t found on web which graph partitioning are supported by Gelly.
During my search I found this link. But the ticket is still open.
https://cwiki.apache.org/co
For 1., I think the standard approach would be to specify from without what
the heap size should be. If you want an *x* MB heap, you could set your
container memory limit to 1.3 * *x* or so (to account for overhead)
and set taskmanager.heap.mb:
*x* in your config.
The other way around—e.g. from in
Hi Marc,
I’ll defer to Vasia’s comment below from FLINK-1536 as she has much more
knowledge and experience with graph partitioning. This is certainly an area of
interest so please let us know if you would like to contribute!
The referenced list of papers is at:
http://www.citeulike.org/user/v
Hi Ufuk,
yes the class is part of the jar.
Actually, don't worry about this issue too much, we were just wondering
if we broke something. Since that does not seem to be the case, we will
deal with this until we have 1.2. So no need to write a tool, but thanks
for the offer :)
We want to upgrade t
Thanks for providing the logs. It looks like the JARs are uploaded
(modulo any bugs ;-))... could you double check that the class is
actually part of the JAR and has not been moved around via
jar -tf | grep EventDataRecord
If everything looks good in the JAR, I could write a short tool that
pri
Hallo everyone,
I have a Flink batch job, which reads four CSV files. The rows in the files=
will be read and grouped together.
When the four CSV Files are small enough, the job can finish successfully. =
However when the input files are large, the job could not successfully exec=
uted an
Hi Dominique,
What your plan A is suggesting is that a downstream operator can provide
signals to upstream operators and alter their behaviour.
In general, this isn’t possible, as in a distributed streaming environment it’s
hard to guarantee what records exactly will be altered by the behaviour.
Sounds like a cool event! Thanks for sharing this!
On March 27, 2017 at 11:40:24 PM, Lior Amar (lior.a...@parallelmachines.com)
wrote:
Hi all,
My name is Lior and I am working at Parallel Machines (a startup company
located in the Silicon Valley).
We are hosting a Flink Hackathon on April 10
Hi Dominik,
Was the job running with processing time or event time? If event time, how are
you producing the watermarks?
Normally to understand how windows are firing in Flink, these two factors would
be the place to look at.
I can try to further explain this once you provide info with these. Al
Hi Gordon,
The job was run using processing time. The Kafka broker version I’ve used was
0.10.1.1.
Dominik
> On 30 Mar 2017, at 08:35, Tzu-Li (Gordon) Tai wrote:
>
> Hi Dominik,
>
> Was the job running with processing time or event time? If event time, how
> are you producing the watermark
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