Sachin Goel created FLINK-2187:
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Summary: KMeans clustering is not present in release-0.9-rc1
Key: FLINK-2187
URL: https://issues.apache.org/jira/browse/FLINK-2187
Project: Flink
Issue Type:
Hi. I have a problem running `mvn clean verify` command.
TaskManagerFailsWithSlotSharingITCase hangs in Oracle JDK 7 (1.7.0_80). But in
Oracle JDK 8 the test case doesn’t hang.
I’ve investigated about this problem but I cannot found the bug.
Regards,
Chiwan Park
On Jun 9, 2015, at 2:11 AM,
Hi. I’m very excited about preparing a new major release. :)
I just picked two tests. I will report status as soon as possible.
Regards,
Chiwan Park
On Jun 9, 2015, at 1:52 AM, Maximilian Michels m...@apache.org wrote:
Hi everyone!
As previously discussed, the Flink developer community is
Added F7 Running against Kafka cluster for me in the doc. Doing it
tomorrow.
On Mon, Jun 8, 2015 at 7:00 PM, Chiwan Park chiwanp...@icloud.com wrote:
Hi. I’m very excited about preparing a new major release. :)
I just picked two tests. I will report status as soon as possible.
Regards,
Hi everyone!
As previously discussed, the Flink developer community is very eager to get
out a new major release. Apache Flink 0.9.0 will contain lots of new
features and many bugfixes. This time, I'll try to coordinate the release
process. Feel free to correct me if I'm doing something wrong
Hey Chiwan!
Is the problem reproducible? Does it always deadlock? Can you please wait
for it to deadlock and then post a stacktrace (jps and jstack) of the
process? Please post it to this issue: FLINK-2183.
Thanks :)
– Ufuk
On Monday, June 8, 2015, Chiwan Park chiwanp...@icloud.com
I have now created the JIRA:
https://issues.apache.org/jira/browse/FLINK-2181
Best regards,
Gabor
2015-06-08 0:55 GMT+02:00 Robert Metzger rmetz...@apache.org:
What is the status of this issue?
I think we should at least file a JIRA for it to have it around as a TODO.
On Thu, May 28, 2015
Gabor Gevay created FLINK-2181:
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Summary: SessionWindowing example has a memleak
Key: FLINK-2181
URL: https://issues.apache.org/jira/browse/FLINK-2181
Project: Flink
Issue Type: Bug
The problem is still there. @Aljoscha: It would be great if you could take
it.
On Mon, Jun 8, 2015 at 9:41 AM, Gyula Fóra gyf...@apache.org wrote:
I agree with Marton. I thought Aljoscha was working on that.
On Monday, June 8, 2015, Márton Balassi balassi.mar...@gmail.com wrote:
FLINK-2054
You're right Felix. You need to provide the `FitOperation` and
`PredictOperation` for the `Predictor` you want to use and the
`FitOperation` and `TransformOperation` for all `Transformer`s you want to
chain in front of the `Predictor`.
Specifying which features to take could be a solution.
Aljoscha Krettek created FLINK-2182:
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Summary: Add stateful Streaming Sequence Source
Key: FLINK-2182
URL: https://issues.apache.org/jira/browse/FLINK-2182
Project: Flink
Issue Type:
Yes. I agree too. It makes no sense for the learning algorithm to have
extra payload. Only relevant data makes sense.
Further, adding ID to the predict operation type definition seems a
legitimate choice. +1 from my side.
Regards
Sachin Goel
On Mon, Jun 8, 2015 at 4:06 PM, Theodore Vasiloudis
I am in favor of efficiency. Therefore I would be prefer to introduce new
methods, in order to save memory and network traffic. This would also solve
the problem of how to come up with ids?
Best regards,
Felix
Am 08.06.2015 12:52 nachm. schrieb Sachin Goel sachingoel0...@gmail.com:
I think if
That would be better of course. My opinion had to do with
not-implementing-exactly-the-same-thing-twice. Perhaps Till could weigh in
here.
We really do need to come up with a general mechanism for this. Testing
labeled vectors has exactly the same problem. I'll look into how Spark and
sci-kit
I think if the user doesn't provide IDs, we can safely assume that they
don't need it. We can just simply assign an ID of one as a temporary
measure and return the result, with no IDs [just to make the interface
cleaner].
If the IDs are provided, in that case, we simply use those IDs.
A possible
I agree with Mikio; ids would be useful overall, and feature selection
should not be a part of learning algorithms,
all features in a LabeledVector should be assumed to be relevant by the
learners.
On Mon, Jun 8, 2015 at 12:00 PM, Mikio Braun mikiobr...@googlemail.com
wrote:
Hi all,
I think
My gut feeling is also that a `Transformer` would be a good place to
implement feature selection. Then you can simply reuse it across multiple
algorithms by simply chaining them together.
However, I don't know yet what's the best way to realize the IDs. One way
would be to add an ID field to
Gábor Hermann created FLINK-2184:
Summary: Cannot get last element with maxBy/minBy
Key: FLINK-2184
URL: https://issues.apache.org/jira/browse/FLINK-2184
Project: Flink
Issue Type:
Theodore Vasiloudis created FLINK-2186:
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Summary: Reworj SVM import to support very wide files
Key: FLINK-2186
URL: https://issues.apache.org/jira/browse/FLINK-2186
Project: Flink
Issue
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