Dawid Wysakowicz created FLINK-21117:
Summary: KafkaProducerExactlyOnceITCase fails with "Exceeded
checkpoint tolerable failure threshold."
Key: FLINK-21117
URL:
Dawid Wysakowicz created FLINK-21116:
Summary: DefaultDispatcherRunnerITCase hangs on azure
Key: FLINK-21116
URL: https://issues.apache.org/jira/browse/FLINK-21116
Project: Flink
Issue
Thanks Robert for creating this FLIP and starting the discussion.
This is a great start point to make Flink work with auto scaling service.
The reactive mode
is very useful in containerized environment(e.g. docker, Kubernetes). For
example, combined
with Kubernetes "Horizontal Pod Autoscaler"[1],
Wei Zhong created FLINK-21115:
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Summary: Add AggregatingState and corresponding StateDescriptor
for Python DataStream API
Key: FLINK-21115
URL: https://issues.apache.org/jira/browse/FLINK-21115
Project:
Wei Zhong created FLINK-21114:
-
Summary: Support ReducingState in Python DataStream API
Key: FLINK-21114
URL: https://issues.apache.org/jira/browse/FLINK-21114
Project: Flink
Issue Type:
Shuiqiang Chen created FLINK-21113:
--
Summary: Add State access API for KeyedStream RuntimeContext.
Key: FLINK-21113
URL: https://issues.apache.org/jira/browse/FLINK-21113
Project: Flink
Shuiqiang Chen created FLINK-21112:
--
Summary: Add ValueState/ListState/MapState and corresponding
StateDescriptors for Python DataStream API
Key: FLINK-21112
URL:
Shuiqiang Chen created FLINK-2:
--
Summary: Support State access in Python DataStream API
Key: FLINK-2
URL: https://issues.apache.org/jira/browse/FLINK-2
Project: Flink
Issue
Zhilong Hong created FLINK-21110:
Summary: Optimize Scheduler Performance for Large-Scale Jobs
Key: FLINK-21110
URL: https://issues.apache.org/jira/browse/FLINK-21110
Project: Flink
Issue
Hi all,
I would like to propose introducing a new method "retractAccumulators()" to
the `AggregateFunction` in Table/SQL.
*Motivation*
The motivation is to improve the performance of hopping (sliding) windows.
Currently, we have paned (or called sliced) optimization for the hopping
windows in
Jark Wu created FLINK-21109:
---
Summary: Introduce "retractAccumulators" interface for
AggregateFunction in Table/SQL API
Key: FLINK-21109
URL: https://issues.apache.org/jira/browse/FLINK-21109
Project:
In flink table planner module, I can not find the rule that convert calcite
Filter or LogicalFilter into flink physicalNode. how flink implement the filter
operator. Is there any class like DataStreamScan that implement the TableScan.
laughing.sh...@qq.com
Hi Till,
Sorry for late response, I just did some investigations about Spark. Spark
adopted the SPI way to obtain delegations for different components. It has a
+1 (non-binding)
- checked/verified signatures and checksums
- built from source code succeeded
- checked that there are no missed dependency artifacts
- started a cluster, WebUI was accessible, ran a wordcount job , no suspicious
log output
- tested using SQL Client to submit a simple SQL job
Thanks for preparing the FLIP and starting the discussion, Robert.
## Cluster vs. Job configuration
As I have commented on the FLIP-160 discussion thread [1], I'm a bit unsure
about activating the reactive execution mode via a cluster level
configuration option. I'm aware that in the first step
Xiaoguang Sun created FLINK-21108:
-
Summary: Flink runtime rest server and history server webmonitor
do not require authentication.
Key: FLINK-21108
URL: https://issues.apache.org/jira/browse/FLINK-21108
Maybe, it's worth a try: I created issue #560 [1] for this. Let's see what
happens.
[1] https://github.com/google/google-java-format/issues/560
On Sun, Jan 24, 2021 at 4:17 AM Jark Wu wrote:
> Hi Matthias,
>
> I also have the same problem when creating a new Java class. This is quite
>
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