Thank you,
This is following
https://ci.apache.org/projects/flink/flink-docs-stable/monitoring/metrics.html#prometheus-orgapacheflinkmetricsprometheusprometheusreporter
.
What might I be doing wrong ?
metrics.reporters: prom
metrics.reporter.prom.port: 9610 .
metrics.reporter.pr
Since you're using Prometheus I would recommend setting up a
PrometheusReporter as described in the metrics documentation and scrape
each JM/TM individually. Scraping through the REST API is more expensive
and you loose out on a lot of features.
The REST API calls are primarily aimed at the Web
It is a mistake. Thank you :)
On Fri, Mar 22, 2019 at 10:26 AM Pablo Estrada wrote:
> Hi Peter,
> You'll have to email user-subscr...@flink.apache.org to be able to
> subscribe : )
> Best
> -P.
>
> On Fri, Mar 22, 2019 at 10:22 AM Peter Huang
> wrote:
>
>>
>>
Hi Peter,
You'll have to email user-subscr...@flink.apache.org to be able to
subscribe : )
Best
-P.
On Fri, Mar 22, 2019 at 10:22 AM Peter Huang
wrote:
>
>
Our implementation has quite a bit more going on just to deal with
serialization of types, but here is pretty much the core of what we do in
(psuedo) scala:
class DynamoSink[...](...) extends RichProcessFunction[T] with
ProcessingTimeCallback {
private var curTimer: Option[Long] = None
privat
Hi there,
We have implemented a dynamo sink, have had no real issues, but obviously,
it is at-least-once and so we work around that by just structuring our
transformations so that they produce idempotent writes.
What we do is pretty similar to what you suggest, we collect the records in
a buffer
A simple query, Is the route to /metrics execute an access to an in memory
registry of stats collected OR does it contend with access from JM or do
expensive access or computation. I see occasionally our Prometheus scrape
fail with the error pasted below. We have had the scrapper do much more
el
Thanks Rong,
Yes for some reason i thought i need a table function, but scalar works!
Yes the map constructor is what i started with but then figured it doesn't
support conditional entries.
On Thu, Mar 21, 2019 at 6:07 PM Rong Rong wrote:
> Based on what I saw in the implementation, I think you
Hello,
Thank you for your replay. I will use MapPartition for anomaly detection
for batch job. But i saw that flink has planned to unify stream and batch
according to the folowing link
https://flink.apache.org/news/2019/02/13/unified-batch-streaming-blink.html
, so in this case how can i use MapPar
Hello,
I am currently using Dynamodb as a persistent store in my application, and in
process of transforming the application into streaming pipeline utilizing
Flink. Pipeline is simple and stateless, consume data from Kafka, apply some
transformation and write records to Dynamodb.
I would wan
-- Forwarded message -
From: Piotr Nowojski
Date: jeu. 21 mars 2019 à 14:09
Subject: Re: StochasticOutlierSelection
To: anissa moussaoui , user <
user@flink.apache.org>
(Adding back user mailing list)
Hi Anissa,
Thank you for coming back with the results. I hope this might be h
Done! https://issues.apache.org/jira/browse/FLINK-11996
Op vr 22 mrt. 2019 om 11:52 schreef Chesnay Schepler :
> It is likely that the documentation is outdated. Could open a JIRA for
> updating the documentation?
>
> On 22/03/2019 10:12, Wouter Zorgdrager wrote:
> > Hey all,
> >
> > Since Scala
That makes sense. Thanks for the clarification.
--
Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/
It is likely that the documentation is outdated. Could open a JIRA for
updating the documentation?
On 22/03/2019 10:12, Wouter Zorgdrager wrote:
Hey all,
Since Scala 2.11 the amount of fields in a case class isn't restricted
to 22 anymore [1]. I was wondering if Flink still uses this limit
i
Hey all,
Since Scala 2.11 the amount of fields in a case class isn't restricted to
22 anymore [1]. I was wondering if Flink still uses this limit internally,
if I check the documentation [2] I also see a max of 22 fields. However, I
just ran a simple test setup with a case class > 22 fields and th
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