ly make it into the next
> Flink release.
>
> Best,
> Aljoscha
>
>
> On 13. Sep 2018, at 14:40, Jared Stehler intellifylearning.com> wrote:
>
> I'm encountering an error on init with StreamingFileSink and presto-fs;
> before I continue down what appe
I'm encountering an error on init with StreamingFileSink and presto-fs;
before I continue down what appears to be a classpath issue, can someone
stop me if StreamingFileSink doesn't support presto-fs?
Error I'm seeing is:
java.lang.UnsupportedOperationException: Not implemented by the
PrestoS3Fil
or job
A, and Y heap for job B?
Is this slated for the 1.5 release? I’m trying to get a sense for what flip-6
will look like when it drops, and what its current state is on the master / 1.5
branch; I’m interested in helping test it out.
--
Jared Stehler
Chief Architect - Intellify Lear
org.apache.zookeeper.ClientCnxn$SendThread.primeConnection(ClientCnxn.java:926)
at
com.intellify.flink.shaded.zookeeper.org.apache.zookeeper.ClientCnxnSocketNIO.doTransport(ClientCnxnSocketNIO.java:363)
at
com.intellify.flink.shaded.zookeeper.org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1141)
--
Jared Ste
ink.shaded.zookeeper.org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1141)
Locked ownable synchronizers:
- None
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Jan 11, 2018, at 10:07 AM, Jared Stehler
> wrote:
>
> I’m seeing spor
Transport(ClientCnxnSocketNIO.java:363)
at
com.intellify.flink.shaded.zookeeper.org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1141)
Does anyone have any insight into what might be happening here? Does this seem
like I’m not closing a thread properly, or something else entirely?
--
Jared Steh
able to
override the port for the app master
(-Dmetrics.reporter.prom_reporter.port=$PORT1) but this carries over to the
task managers and can collide with the assigned data port, etc.
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
No problem, thanks!
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Dec 14, 2017, at 3:59 PM, Eron Wright wrote:
>
> Jared, I think you're correct that the shaded `ObjectMapper` is missing.
> Based on the above details and a quick look
org.apache.flink.mesos.shaded.com.fasterxml.jackson
--
Jared Stehler
Chief Architect - Intellify Learning
o
I see a shaded jackson class with jackson2 in the package, but none with the
path shown below.
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Dec 14, 2017, at 3:05 PM, Jared Stehler
> wrote:
>
> Getting the following error on app master startu
(Launcher.java:338)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at com.netflix.fenzo.ConstraintFailure.(ConstraintFailure.java:35)
...
(10 additional frame(s) were not displayed)
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
I had been excluding all transitive dependencies from the lib dir; it seems to
be working when I added the following deps:
commons-configuration
commons-configuration
1.7
commons-lang
commons-lang
2.6
--
Jared Stehler
Chief Architect
${flink.version}
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Dec 12, 2017, at 2:10 PM, Chesnay Schepler wrote:
>
> Could you look into the flink-shaded-hadoop jar to check whether the missing
> class is actually contained?
>
> Where di
log4j-over-slf4j-1.7.25.jarsentry-logback-1.5.3.jar
flink-metrics-prometheus-1.4.0.jar jackson-core-2.8.10.jar
logback-classic-1.1.11.jar
flink-python_2.11-1.4.0.jarjcl-over-slf4j-1.7.25.jar
logback-core-1.1.11.jar
--
Jared Stehler
Chief Architect - Intellify
Protobuf is notorious for throwing things like “class not found” when built
and run with different versions of the library; I believe flink is using
protobuf 2.5.0 and you mentioned using 2.6.1, which I think would be a
possible cause of this issue.
--
Jared Stehler
Chief Architect - Intellify
+= jobVertex.getParallelism();
}
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Oct 27, 2017, at 2:30 PM, Jared Stehler
> wrote:
>
> Is there a way to determine via an API the required number of task manager
> slots for a particular job graph?
Is there a way to determine via an API the required number of task manager
slots for a particular job graph? I’ve looked at
"flink.getStreamGraph().getJobGraph().getNumberOfVertices()” but it doesn’t
seem to correspond with what the job actually ends up using.
--
Jared Stehler
Chief Arch
false
true
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Oct 19, 2017, at 5:12 AM, Piotr Nowojski wrote:
>
> Hi,
>
> What versions of Flink/logback are you using?
>
&g
ERROR
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
able to
analyze further.
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Jul 3, 2017, at 6:02 AM, Stefan Richter
> wrote:
>
> Hi,
>
> I have two quick questions about this problem report:
>
> 1) Which state backend are you using?
&g
) be contained in
that operator’s UID?
Basically, is the UID similar to overriding hashcode and equals for POJOs, or
is it more like overriding serializableVersionUID?
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
signature.asc
Description: Message signed with
te any insights you might have on this.
Thanks
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
signature.asc
Description: Message signed with OpenPGP using GPGMail
Is there a way to direct the mesos application master to scale task manager
tasks up or down, or to redeploy them? For example, when I want to roll out a
new docker image for task managers?
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
signature.asc
Description
It appears that this change is only included in the as-yet-to-be-released
metrics-graphite 3.1.3.
--
Jared Stehler
Chief Architect - Intellify Learning
o: 617.701.6330 x703
> On Feb 1, 2017, at 7:22 AM, Philipp Bussche wrote:
>
> Hi there,
> after moving my graphite service to
I have a use case where I need to start a stream replaying historical data, and
then have it continue processing on a live kafka source, and am looking for
guidance / best practices for implementation.
Basically, I want to start up a new “version” of the stream job, and have it
process each ele
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