After read FLIP-198 & FLIP-201，I confuse that this feature can be used on
Yarn mode and how to confige a deterministic `taskmanager.resource-id` ?Or
just suit for k8s mode.
Nicholas Jiang created FLINK-28560:
--
Summary: Support Spark 3.3 profile for SparkSource
Key: FLINK-28560
URL: https://issues.apache.org/jira/browse/FLINK-28560
Project: Flink
Issue Type:
Huang Xingbo created FLINK-28559:
Summary: Support DataStream PythonKeyedProcessOperator in Thread
Mode
Key: FLINK-28559
URL: https://issues.apache.org/jira/browse/FLINK-28559
Project: Flink
Thanks for starting this discussion.
Have we considered introducing a listPartitionWithStats() in Catalog?
Best,
Jingsong
On Fri, Jul 15, 2022 at 10:08 AM Jark Wu wrote:
>
> Hi Jing,
>
> Thanks for starting this discussion. The bulk fetch is a great improvement
> for the optimizer.
> The FLIP
Xintong Song created FLINK-28558:
Summary: HistoryServer log retrieval configuration improvement
Key: FLINK-28558
URL: https://issues.apache.org/jira/browse/FLINK-28558
Project: Flink
Issue
Huang Xingbo created FLINK-28557:
Summary:
CheckpointCoordinatorTriggeringTest.discardingTriggeringCheckpointWillExecuteNextCheckpointRequest
Process produced no output for 900 seconds
Key: FLINK-28557
URL:
Yingjie Cao created FLINK-28556:
---
Summary: Extract header fields of Buffer into a BufferHeader class
for blocking shuffle file IO
Key: FLINK-28556
URL: https://issues.apache.org/jira/browse/FLINK-28556
Xintong Song created FLINK-28555:
Summary: Update history server documentation
Key: FLINK-28555
URL: https://issues.apache.org/jira/browse/FLINK-28555
Project: Flink
Issue Type: Sub-task
Hi Jing,
Thanks for starting this discussion. The bulk fetch is a great improvement
for the optimizer.
The FLIP looks good to me.
Best,
Jark
On Fri, 8 Jul 2022 at 17:36, Jing Ge wrote:
> Hi devs,
>
> After having multiple discussions with Jark and Goldfrey, I'd like to start
> a discussion on
Thanks all, @Yang Wang and @Yikun Jiang.
Hi Martijn,
We understand your concern. And do the above emails clear your doubts?
"
Thanks for the info! I think I see that you've already updated the FLIP to
reflect how customized schedulers are beneficial for both batch and
streaming jobs.
"
>>>
Hi all,
Circling back on this--I have created a first draft document in confluence:
https://cwiki.apache.org/confluence/display/FLINK/FLIP-246%3A+Multi+Cluster+Kafka+Source
.
Looking forward to hear all your feedback in this email thread!
Best,
Mason
On Thu, Jun 30, 2022 at 6:57 AM Thomas
Tim created FLINK-28554:
---
Summary: Kubernetes-Operator allow readOnlyRootFilesystem
securityContext
Key: FLINK-28554
URL: https://issues.apache.org/jira/browse/FLINK-28554
Project: Flink
Issue Type:
-> If so, I think you can set Task1 and Task2 to the same parallelism and
set them in the same slot sharing group. In this way, Task1 and Task2 will
be deployed into the same slot(That is, the same task manager).
*Updating task details *
*Task1- Source some static data over HTTPS and keep it in
Hi Steve,
If your intended implementation involves changes to the Source API, it
should certainly be a separate FLIP.
Looking forward to your proposals.
Best,
Alexandere Fedulov
On Thu, Jul 14, 2022 at 7:18 AM Steve Yurong Su wrote:
> Hi Alexander,
>
> The reference [3] mentioned in my
Hangxiang Yu created FLINK-28553:
Summary: The serializer in StateMap has not been updated when
metaInfo of StateTable updated
Key: FLINK-28553
URL: https://issues.apache.org/jira/browse/FLINK-28553
> And maybe we also could ping Yikun Jiang who has done similar things in
Spark.
Thanks for @wangyang ping. Yes, I was involved in Spark's customized
scheduler support work and as the main completer.
For customized scheduler support, I can share scheduler's requirement in
here:
1. Help
Jane Chan created FLINK-28552:
-
Summary: GenerateUtils#generateCompare supports MULTISET and MAP
Key: FLINK-28552
URL: https://issues.apache.org/jira/browse/FLINK-28552
Project: Flink
Issue
Yingjie Cao created FLINK-28551:
---
Summary: Store the number of bytes instead of the number of
buffers in index entry for sort-shuffle
Key: FLINK-28551
URL: https://issues.apache.org/jira/browse/FLINK-28551
Yingjie Cao created FLINK-28550:
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Summary: Remove the unused field in SortMergeSubpartitionReader
Key: FLINK-28550
URL: https://issues.apache.org/jira/browse/FLINK-28550
Project: Flink
Issue
I think we could go over the customized scheduler plugin mechanism again
with YuniKorn to make sure that it is common enough.
But the implementation could be deferred.
And maybe we also could ping Yikun Jiang who has done similar things in
Spark.
For the e2e tests, I admit that they could be
Huang Xingbo created FLINK-28549:
Summary: Support DataStream PythonProcessOperator in Thread Mode
Key: FLINK-28549
URL: https://issues.apache.org/jira/browse/FLINK-28549
Project: Flink
Hi Bo,
Thanks for the info! I think I see that you've already updated the FLIP to
reflect how customized schedulers are beneficial for both batch and
streaming jobs.
The reason why I'm not too happy that we would only create a reference
implementation for Volcano is that we don't know if the
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