In case this helps, here are the versions I was working with when I was
experimenting with this last year:

https://github.com/ottomata/flink-cdc-spike/blob/main/dockerfiles/build_env_1.17.env
https://github.com/ottomata/flink-cdc-spike/blob/main/dockerfiles/download_dependencies.sh

I was trying many things though (flink-cdc, paimon action, etc.) so YMMV.

Good luck!

On Tue, Mar 11, 2025 at 9:14 AM Taher Koitawala <taher...@gmail.com> wrote:

> Hi All,
>          I am facing issues finding a class
>
> Org.apache.flink.cdc.connectors.shaded.org.apache.kafka.connect.json.JsonConverter
>
>
> I have added
> 1. Flink-connector-base 1.18.1
> Flink-connector-debezium
> 3.1.0
> Flink-cdc-pipeline-connectors-values
> 3.1.0
> Flink-cdc-base
> 3.1.0
> Flink-cdc-pipeline-connector-kafka 3.1.0
>
>
> What am i missing?
>
>
> On Fri, 7 Mar 2025 at 8:13 AM, Taher Koitawala <taher...@gmail.com> wrote:
>
>> Hi Leonard,
>>      Yes i did see Xianqian’s reply however i thought my email did not go
>> through as the community is often very active but I did not receive a
>> response until Xianqian’s reply.
>>
>> Thank you Xianqian we are currently trying out the suggestions for
>> altering schema via the catalog.
>>
>> Thank you Andrew Otto for the docs as i will I will take a look at this.
>>
>>
>>
>>
>> On Wed, 5 Mar 2025 at 5:47 AM, Leonard Xu <xbjt...@gmail.com> wrote:
>>
>>> Hey Taher,
>>>
>>> Xianqian has replied your email, did you subscribe Flink dev
>>> mailing-list?
>>>
>>> Best,
>>> Leonard
>>>
>>> > 2025年2月11日 16:52,Xiqian YU <kono....@outlook.com> 写道:
>>> >
>>> > Hi Taher,
>>> >
>>> > Since we’re creating a DataStream-based pipeline job with SQL Server
>>> CDC, schema change events must be handled manually. A possible approach
>>> would be:
>>> >
>>> > 1) Enable schema change events with `.includeSchemaChanges(true)`
>>> option, so DDL events will be parsed and encoded in `SourceRecord`s.
>>> >
>>> > 2) Write a customized `DebeziumDeserializationSchema` class and parse
>>> schema change events.
>>> `MySqlEventDeserializer#deserializeSchemaChangeRecord` could be used as a
>>> reference [1].
>>> >
>>> > 3) Evolve sink schema of Paimon tables with `PaimonCatalog` manually.
>>> `PaimonMetadataApplier` [2] is an existing schema evolving implementation
>>> supporting a few frequently used schema change events.
>>> >
>>> > Also, CDC Pipeline framework [3] has provided a fully-automatic schema
>>> sensing and evolving solution, but unfortunately Microsoft SQL Server
>>> source is not supported yet until we close #3445 [4] or #3507 [5].
>>> >
>>> > [1]
>>> https://github.com/apache/flink-cdc/blob/master/flink-cdc-connect/flink-cdc-pipeline-connectors/flink-cdc-pipeline-connector-mysql/src/main/java/org/apache/flink/cdc/connectors/mysql/source/MySqlEventDeserializer.java
>>> > [2]
>>> https://github.com/apache/flink-cdc/blob/master/flink-cdc-connect/flink-cdc-pipeline-connectors/flink-cdc-pipeline-connector-paimon/src/main/java/org/apache/flink/cdc/connectors/paimon/sink/PaimonMetadataApplier.java
>>> > [3]
>>> https://nightlies.apache.org/flink/flink-cdc-docs-release-3.3/docs/core-concept/data-pipeline/
>>> > [4] https://github.com/apache/flink-cdc/pull/3445
>>> > [5] https://github.com/apache/flink-cdc/pull/3507
>>> >
>>> > Best Regards,
>>> > Xiqian
>>> >
>>> > Taher Koitawala <taher...@gmail.com> 於 2025年2月11日 15:59 寫道:
>>> >
>>> > Hi Devs,
>>> >      As a POC we are trying to create a steaming pipeline from MSSQL
>>> cdc
>>> > to Paimon:
>>> >
>>> > To do this we are doing
>>> > 1. msSql server cdc operator
>>> > 2. Transform operator
>>> > 3. paimon sink
>>> >
>>> > We have written the cdc connector with is a
>>> JsonDebeziumDeserialisedSchema
>>> > String
>>> >
>>> > I wish to write this paimon in a table format with same columns as
>>> source.
>>> >
>>> > As far as i know paimon automatically handles schema updates like new
>>> field
>>> > additions.
>>> >
>>> > Please can someone point me on how to write this stream efficiently to
>>> > paimon table with schema updates?
>>> >
>>> > For now i have SouceFunction<String>
>>> >
>>> > Which is the record mentioned above!
>>> >
>>> > Regards,
>>> > Taher Koitawala
>>> >
>>>
>>>

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