Re: [DISCUSS] Releasing Flink ML 2.2.0

[Dong Lin]

Thanks everyone for the comments!

We will go ahead to release Flink ML 2.2.0. Please see here
 for the
release plan.

Best Regards,
Dong


On Fri, Mar 31, 2023 at 6:50 PM Yu Li  wrote:

> +1. Great to know the (exciting) progress and thanks for the efforts!
>
> Best Regards,
> Yu
>
>
> On Fri, 31 Mar 2023 at 14:39, Fan Hong  wrote:
>
>> Hi Dong and Zhipeng,
>>
>> Thanks for starting the discussion. Glad to see a new release of Flink ML.
>>
>> Cheers!
>>
>> On Fri, Mar 31, 2023 at 2:34 PM Zhipeng Zhang 
>> wrote:
>>
>> > Hi Dong,
>> >
>> > Thanks for starting the discussion. +1 for the Flink ML 2.1.0 release.
>> >
>>
>

Re: [DISCUSS] Releasing Flink ML 2.2.0

[Yu Li]

+1. Great to know the (exciting) progress and thanks for the efforts!

Best Regards,
Yu


On Fri, 31 Mar 2023 at 14:39, Fan Hong  wrote:

> Hi Dong and Zhipeng,
>
> Thanks for starting the discussion. Glad to see a new release of Flink ML.
>
> Cheers!
>
> On Fri, Mar 31, 2023 at 2:34 PM Zhipeng Zhang 
> wrote:
>
> > Hi Dong,
> >
> > Thanks for starting the discussion. +1 for the Flink ML 2.1.0 release.
> >
>

Re: [DISCUSS] Releasing Flink ML 2.2.0

[Fan Hong]

Hi Dong and Zhipeng,

Thanks for starting the discussion. Glad to see a new release of Flink ML.

Cheers!

On Fri, Mar 31, 2023 at 2:34 PM Zhipeng Zhang 
wrote:

> Hi Dong,
>
> Thanks for starting the discussion. +1 for the Flink ML 2.1.0 release.
>

Re: [DISCUSS] Releasing Flink ML 2.2.0

[Zhipeng Zhang]

Hi Dong,

Thanks for starting the discussion. +1 for the Flink ML 2.1.0 release.

[DISCUSS] Releasing Flink ML 2.2.0

[Dong Lin]

Hi devs,

Zhipeng and I would like to start a discussion regarding the release of
Flink ML 2.2.0. And I would like to volunteer as the release manager.

Over the past few months, we've been focused on enhancing Flink ML's
feature engineering capabilities. We're happy to report that the library
now includes 33 feature engineering algorithms, covering 28 out of the 33
feature engineering algorithms provided in Spark ML.

Here are some highlighted improvements we've made since the last release:

- Added 27 new feature engineering algorithms.

- Introduced APIs and infrastructure for online serving via FLIP-289,
allowing you to serve models online. To start, we've provided the
LogisticRegressionModelServable to serve the logistic regression model
online, and we'll continue to add more servables in the future.

- Added Python support for every algorithm in Flink ML, which means you can
run every algorithm using Python.

- Added two online algorithms (AgglomerativeClustering and
OnlineStandardScaler) which have been deployed in production to classify
error logs in real-time. These algorithms will soon be integrated into the
open-source project alibaba/SREWorks.

With the above improvements, we believe it is time to release Flink ML
2.2.0. We hope that these new features and improvements will assist Flink
users in their machine learning tasks.

Please feel free to provide your feedback.

Best Regards,
Dong