+1 (binding)
- Ran e2e local tests for Flink read/write/compaction, especially for spilling
- Ran some tests for CDC feature
- Go through the Flink quick start with Flink 1.16 bundle jar
Best,
Danny
Shiyan Xu 于2023年2月17日周五 01:31写道:
>
> +1 (binding)
>
> - Ran some quickstart spark read/write
+1 Thanks Lvhu for bringing up the idea. As Alexey suggested, it would be
good for you to write down the proposal with design details for discussion
in the community.
On Thu, Feb 16, 2023 at 11:28 AM Alexey Kudinkin wrote:
> Thanks for your contribution, Lvhu!
>
> I think we should actually
Thanks for your contribution, Lvhu!
I think we should actually kick-start this effort with an small RFC
outlining proposed changes first, as this is modifying the core read-flow
for all Hudi tables and we want to make sure our approach there is
rock-solid.
On Thu, Feb 16, 2023 at 6:34 AM 吕虎
+1 (binding)
- Ran some quickstart spark read/write examples
- Ran example dataset write with deltastreamer
- Ran metaserver locally with spark read/write
On Thu, Feb 16, 2023 at 10:23 AM sagar sumit wrote:
> +1 (non-binding)
>
> - Ran spark quickstart guide
> - Ran deltastremer
> - Ran Hive
+1 (non-binding)
- Ran spark quickstart guide
- Ran deltastremer
- Ran Hive sync and queried using Presto and Trino
Regards,
Sagar
On Thu, Feb 16, 2023 at 9:42 PM Rahil C wrote:
> +1 non binding
>
> Ran emr integ tests against 0.13.0 release artifacts
>
> On Thu, Feb 16, 2023 at 7:59 AM
+1 non binding
Ran emr integ tests against 0.13.0 release artifacts
On Thu, Feb 16, 2023 at 7:59 AM Sivabalan wrote:
> +1 Binding.
>
> - Ran release validation script.
> - Verified checksums
> - Ran quick start
> - Ran tests with detlastreamer, spark-ds, etc.
>
>
> On Mon, 13 Feb 2023 at
+1 Binding.
- Ran release validation script.
- Verified checksums
- Ran quick start
- Ran tests with detlastreamer, spark-ds, etc.
On Mon, 13 Feb 2023 at 08:53, Y Ethan Guo wrote:
> Hi everyone,
>
> Please review and vote on the release candidate #3 for the version 0.13.0,
> as follows:
>
> [
Hi folks,
PR 7984【 https://github.com/apache/hudi/pull/7984 】 implements hash
partitioning.
As you know, It is often difficult to find an appropriate partition key
in the existing big data. Hash partitioning can easily solve this problem. it
can greatly improve the performance of