Re: AvroRowDeserializationSchema
Oh, I just missed your last question, sorry for that. The offset is stored in the checkpoint and it will recover the offset from the checkpoint when the job failover. Things which you may need to pay attention to: 1) Enable the checkpoint and configure it if necessary [1] 2) Specify the start up mode via `scan.startup.mode` for Kafka connector which works when the job start from scratch when there is no offset available for use 3) It will restore from the latest checkpoint when the job failovers. However, when you manually suspend/start a job, then you need to specify the checkpoint/savepoint manually. see [2][3][4] for more details. Things done in Flink (so you don't need to care): 1) The offset checkpoint and restoring Regards, Dian [1] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/datastream/fault-tolerance/checkpointing/#enabling-and-configuring-checkpointing [2] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/deployment/cli/#creating-a-savepoint [3] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/deployment/cli/#stopping-a-job-gracefully-creating-a-final-savepoint [4] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/deployment/cli/#starting-a-job-from-a-savepoint On Thu, Apr 28, 2022 at 5:45 PM lan tran wrote: > Don’t expect that answer =)) > However, I am very appreciate everything you did > Thanks again for helping me out. > > Best, > Quynh. > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Thursday, April 28, 2022 2:59 PM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Yes, I think so~ > > > > On Thu, Apr 28, 2022 at 11:00 AM lan tran > wrote: > > Hi Dian, > > Sorry for missing your mail, so if I did as your suggestion and the Flink > somehow crashed and we have to restart the service, does the Flink job know > the offset where does it read from Kafka ? > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Tuesday, April 26, 2022 7:54 AM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Hi Quynh, > > The same code in my last reply showed how to set the UID for the source > operator generated using Table API. I meant that you could firstly create a > source using Table API, then convert it to a DataStream API and set uid for > the source operator using the same code above, then perform operations with > DataStream API. > > Regards, > Dian > > > > On Mon, Apr 25, 2022 at 9:27 PM lan tran wrote: > > Hi Dian, > > Thank again for fast response. > > As your suggestion above, we can apply to set the UID for only for the > DataStream state (as you suggest to convert from table to data stream). > > However, at the first phase which is collecting the data from Kafka ( > having Debezium format), the UID cannot be set since we are using Table API > (auto generate the UID). > > Therefore, if there is some crashed or needed revert using SavePoint, we > cannot use it in the first phase since we cannot set the UID for this => so > how can we revert it ?. > > As a result of that, we want to use DebeziumAvroRowDeserializationSchema > and DebeziumJsonRowDeserializationSchema in the DataStream job to be able > to use the Savepoint for the whole full flow. > > Best, > Quynh > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Monday, April 25, 2022 7:46 PM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Hi Quynh, > > You could try the following code (also it may be a little hacky): > ``` > > def set_uid_for_source(ds: DataStream, uid: str): > > transformation = ds._j_data_stream.getTransformation() > > > > source_transformation = transformation > > while not source_transformation.getInputs().isEmpty(): > > source_transformation = source_transformation.getInputs().get(0) > > > > source_transformation.setUid(uid) > > ``` > > Besides, could you describe your use case a bit and also how you want to > use DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for > the sources with these formats, it will send UPDATE messages to downstream > operators. > > Regards > Dian > > > > On Mon, Apr 25, 2022 at 12:31 PM lan tran > wrote: > > Yeah, I already tried that way. However, if we did
RE: AvroRowDeserializationSchema
Don’t expect that answer =))However, I am very appreciate everything you did Thanks again for helping me out.Best,Quynh. Sent from Mail for Windows From: Dian FuSent: Thursday, April 28, 2022 2:59 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Yes, I think so~ On Thu, Apr 28, 2022 at 11:00 AM lan tran <indigoblue7...@gmail.com> wrote:Hi Dian,Sorry for missing your mail, so if I did as your suggestion and the Flink somehow crashed and we have to restart the service, does the Flink job know the offset where does it read from Kafka ? Sent from Mail for Windows From: Dian FuSent: Tuesday, April 26, 2022 7:54 AMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,The same code in my last reply showed how to set the UID for the source operator generated using Table API. I meant that you could firstly create a source using Table API, then convert it to a DataStream API and set uid for the source operator using the same code above, then perform operations with DataStream API.Regards,Dian On Mon, Apr 25, 2022 at 9:27 PM lan tran <indigoblue7...@gmail.com> wrote:Hi Dian, Thank again for fast response.As your suggestion above, we can apply to set the UID for only for the DataStream state (as you suggest to convert from table to data stream). However, at the first phase which is collecting the data from Kafka ( having Debezium format), the UID cannot be set since we are using Table API (auto generate the UID). Therefore, if there is some crashed or needed revert using SavePoint, we cannot use it in the first phase since we cannot set the UID for this => so how can we revert it ?. As a result of that, we want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job to be able to use the Savepoint for the whole full flow.Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 7:46 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,You could try the following code (also it may be a little hacky):```def set_uid_for_source(ds: DataStream, uid: str):transformation = ds._j_data_stream.getTransformation() source_transformation = transformationwhile not source_transformation.getInputs().isEmpty():source_transformation = source_transformation.getInputs().get(0) source_transformation.setUid(uid)```Besides, could you describe your use case a bit and also how you want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for the sources with these formats, it will send UPDATE messages to downstream operators. RegardsDian On Mon, Apr 25, 2022 at 12:31 PM lan tran <indigoblue7...@gmail.com> wrote:Yeah, I already tried that way. However, if we did not use DataStream at first. We cannot implement the Savepoint since through the doc if we use TableAPI (SQL API), the uid is generated automatically which means we cannot revert if the system is crashed. Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 11:04 AMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema are still not supported in Python DataStream API. Just take a further look at the Java implementation of DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, the results type is RowData instead of Row and so it should be not that easy to be directly supported in Python DataStream API. However, it supports conversion between Table API & DataStream API[1]. Could you firstly create a Table which consumes data from kafka and then convert it to a DataStream API?Regards,Dian[1] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors On Mon, Apr 25, 2022 at 11:48 AM Dian Fu <dian0511...@gmail.com> wrote:Yes, we should support them. For now, if you want to use them, you could create ones in your own project. You could refer to AvroRowDeserializationSchema[1] as an example. It should not be complicated as it's simply a wrapper of the Java implementation.Regards,Dian[1] https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308 On Mon, Apr 25, 2022 at 11:27 AM lan tran <indigoblue7...@gmail.com> wrote:Thank Dian !! Very appreciate this.However, I have another questions related to this. In current version or any updating in future, does DataStream support DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the documentation and seem it is not supported yet.Best,QuynhSent from Mail for Windows From: Dian FuSent: Friday, April 22, 2022 9:36 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Q
Re: AvroRowDeserializationSchema
Yes, I think so~ On Thu, Apr 28, 2022 at 11:00 AM lan tran wrote: > Hi Dian, > > Sorry for missing your mail, so if I did as your suggestion and the Flink > somehow crashed and we have to restart the service, does the Flink job know > the offset where does it read from Kafka ? > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Tuesday, April 26, 2022 7:54 AM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Hi Quynh, > > The same code in my last reply showed how to set the UID for the source > operator generated using Table API. I meant that you could firstly create a > source using Table API, then convert it to a DataStream API and set uid for > the source operator using the same code above, then perform operations with > DataStream API. > > Regards, > Dian > > > > On Mon, Apr 25, 2022 at 9:27 PM lan tran wrote: > > Hi Dian, > > Thank again for fast response. > > As your suggestion above, we can apply to set the UID for only for the > DataStream state (as you suggest to convert from table to data stream). > > However, at the first phase which is collecting the data from Kafka ( > having Debezium format), the UID cannot be set since we are using Table API > (auto generate the UID). > > Therefore, if there is some crashed or needed revert using SavePoint, we > cannot use it in the first phase since we cannot set the UID for this => so > how can we revert it ?. > > As a result of that, we want to use DebeziumAvroRowDeserializationSchema > and DebeziumJsonRowDeserializationSchema in the DataStream job to be able > to use the Savepoint for the whole full flow. > > Best, > Quynh > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Monday, April 25, 2022 7:46 PM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Hi Quynh, > > You could try the following code (also it may be a little hacky): > ``` > > def set_uid_for_source(ds: DataStream, uid: str): > > transformation = ds._j_data_stream.getTransformation() > > > > source_transformation = transformation > > while not source_transformation.getInputs().isEmpty(): > > source_transformation = source_transformation.getInputs().get(0) > > > > source_transformation.setUid(uid) > > ``` > > Besides, could you describe your use case a bit and also how you want to > use DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for > the sources with these formats, it will send UPDATE messages to downstream > operators. > > Regards > Dian > > > > On Mon, Apr 25, 2022 at 12:31 PM lan tran > wrote: > > Yeah, I already tried that way. However, if we did not use DataStream at > first. We cannot implement the Savepoint since through the doc if we use > TableAPI (SQL API), the uid is generated automatically which means we > cannot revert if the system is crashed. > > Best, > Quynh > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Monday, April 25, 2022 11:04 AM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema are still not supported in > Python DataStream API. > > Just take a further look at the Java implementation of > DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, > the results type is RowData instead of Row and so it should be not that > easy to be directly supported in Python DataStream API. However, it > supports conversion between Table API & DataStream API[1]. Could you > firstly create a Table which consumes data from kafka and then convert it > to a DataStream API? > > Regards, > Dian > > [1] > https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors > > > > On Mon, Apr 25, 2022 at 11:48 AM Dian Fu wrote: > > Yes, we should support them. > > For now, if you want to use them, you could create ones in your own > project. You could refer to AvroRowDeserializationSchema[1] as an example. > It should not be complicated as it's simply a wrapper of the > Java implementation. > > Regards, > Dian > > [1] > https://github.com/apache/flink/
RE: AvroRowDeserializationSchema
Hi Dian,Sorry for missing your mail, so if I did as your suggestion and the Flink somehow crashed and we have to restart the service, does the Flink job know the offset where does it read from Kafka ? Sent from Mail for Windows From: Dian FuSent: Tuesday, April 26, 2022 7:54 AMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,The same code in my last reply showed how to set the UID for the source operator generated using Table API. I meant that you could firstly create a source using Table API, then convert it to a DataStream API and set uid for the source operator using the same code above, then perform operations with DataStream API.Regards,Dian On Mon, Apr 25, 2022 at 9:27 PM lan tran <indigoblue7...@gmail.com> wrote:Hi Dian, Thank again for fast response.As your suggestion above, we can apply to set the UID for only for the DataStream state (as you suggest to convert from table to data stream). However, at the first phase which is collecting the data from Kafka ( having Debezium format), the UID cannot be set since we are using Table API (auto generate the UID). Therefore, if there is some crashed or needed revert using SavePoint, we cannot use it in the first phase since we cannot set the UID for this => so how can we revert it ?. As a result of that, we want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job to be able to use the Savepoint for the whole full flow.Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 7:46 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,You could try the following code (also it may be a little hacky):```def set_uid_for_source(ds: DataStream, uid: str):transformation = ds._j_data_stream.getTransformation() source_transformation = transformationwhile not source_transformation.getInputs().isEmpty():source_transformation = source_transformation.getInputs().get(0) source_transformation.setUid(uid)```Besides, could you describe your use case a bit and also how you want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for the sources with these formats, it will send UPDATE messages to downstream operators. RegardsDian On Mon, Apr 25, 2022 at 12:31 PM lan tran <indigoblue7...@gmail.com> wrote:Yeah, I already tried that way. However, if we did not use DataStream at first. We cannot implement the Savepoint since through the doc if we use TableAPI (SQL API), the uid is generated automatically which means we cannot revert if the system is crashed. Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 11:04 AMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema are still not supported in Python DataStream API. Just take a further look at the Java implementation of DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, the results type is RowData instead of Row and so it should be not that easy to be directly supported in Python DataStream API. However, it supports conversion between Table API & DataStream API[1]. Could you firstly create a Table which consumes data from kafka and then convert it to a DataStream API?Regards,Dian[1] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors On Mon, Apr 25, 2022 at 11:48 AM Dian Fu <dian0511...@gmail.com> wrote:Yes, we should support them. For now, if you want to use them, you could create ones in your own project. You could refer to AvroRowDeserializationSchema[1] as an example. It should not be complicated as it's simply a wrapper of the Java implementation.Regards,Dian[1] https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308 On Mon, Apr 25, 2022 at 11:27 AM lan tran <indigoblue7...@gmail.com> wrote:Thank Dian !! Very appreciate this.However, I have another questions related to this. In current version or any updating in future, does DataStream support DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the documentation and seem it is not supported yet.Best,QuynhSent from Mail for Windows From: Dian FuSent: Friday, April 22, 2022 9:36 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,I have added an example on how to use AvroRowDeserializationSchema in Python DataStream API in [1]. Please take a look at if that helps for you~Regards,Dian[1] https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py On Fri, Apr 22, 2022 at 7:24 PM Dian Fu <dian0511...@gmail.com> wrote:Hi Quynh,Could you show some sample code on
Re: AvroRowDeserializationSchema
Hi Quynh, The same code in my last reply showed how to set the UID for the source operator generated using Table API. I meant that you could firstly create a source using Table API, then convert it to a DataStream API and set uid for the source operator using the same code above, then perform operations with DataStream API. Regards, Dian On Mon, Apr 25, 2022 at 9:27 PM lan tran wrote: > Hi Dian, > > Thank again for fast response. > > As your suggestion above, we can apply to set the UID for only for the > DataStream state (as you suggest to convert from table to data stream). > > However, at the first phase which is collecting the data from Kafka ( > having Debezium format), the UID cannot be set since we are using Table API > (auto generate the UID). > > Therefore, if there is some crashed or needed revert using SavePoint, we > cannot use it in the first phase since we cannot set the UID for this => so > how can we revert it ?. > > As a result of that, we want to use DebeziumAvroRowDeserializationSchema > and DebeziumJsonRowDeserializationSchema in the DataStream job to be able > to use the Savepoint for the whole full flow. > > Best, > Quynh > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Monday, April 25, 2022 7:46 PM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Hi Quynh, > > You could try the following code (also it may be a little hacky): > ``` > > def set_uid_for_source(ds: DataStream, uid: str): > > transformation = ds._j_data_stream.getTransformation() > > > > source_transformation = transformation > > while not source_transformation.getInputs().isEmpty(): > > source_transformation = source_transformation.getInputs().get(0) > > > > source_transformation.setUid(uid) > > ``` > > Besides, could you describe your use case a bit and also how you want to > use DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for > the sources with these formats, it will send UPDATE messages to downstream > operators. > > Regards > Dian > > > > On Mon, Apr 25, 2022 at 12:31 PM lan tran > wrote: > > Yeah, I already tried that way. However, if we did not use DataStream at > first. We cannot implement the Savepoint since through the doc if we use > TableAPI (SQL API), the uid is generated automatically which means we > cannot revert if the system is crashed. > > Best, > Quynh > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Monday, April 25, 2022 11:04 AM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema are still not supported in > Python DataStream API. > > Just take a further look at the Java implementation of > DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, > the results type is RowData instead of Row and so it should be not that > easy to be directly supported in Python DataStream API. However, it > supports conversion between Table API & DataStream API[1]. Could you > firstly create a Table which consumes data from kafka and then convert it > to a DataStream API? > > Regards, > Dian > > [1] > https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors > > > > On Mon, Apr 25, 2022 at 11:48 AM Dian Fu wrote: > > Yes, we should support them. > > For now, if you want to use them, you could create ones in your own > project. You could refer to AvroRowDeserializationSchema[1] as an example. > It should not be complicated as it's simply a wrapper of the > Java implementation. > > Regards, > Dian > > [1] > https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308 > > > > On Mon, Apr 25, 2022 at 11:27 AM lan tran > wrote: > > Thank Dian !! Very appreciate this. > > However, I have another questions related to this. In current version or > any updating in future, does DataStream support > DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the > documentation and seem it is not supported yet. > > Best, > Quynh > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian
RE: AvroRowDeserializationSchema
Hi Dian, Thank again for fast response. As your suggestion above, we can apply to set the UID for only for the DataStream state (as you suggest to convert from table to data stream). However, at the first phase which is collecting the data from Kafka ( having Debezium format), the UID cannot be set since we are using Table API (auto generate the UID). Therefore, if there is some crashed or needed revert using SavePoint, we cannot use it in the first phase since we cannot set the UID for this => so how can we revert it ?. As a result of that, we want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job to be able to use the Savepoint for the whole full flow.Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 7:46 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,You could try the following code (also it may be a little hacky):```def set_uid_for_source(ds: DataStream, uid: str):transformation = ds._j_data_stream.getTransformation() source_transformation = transformationwhile not source_transformation.getInputs().isEmpty():source_transformation = source_transformation.getInputs().get(0) source_transformation.setUid(uid)```Besides, could you describe your use case a bit and also how you want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for the sources with these formats, it will send UPDATE messages to downstream operators. RegardsDian On Mon, Apr 25, 2022 at 12:31 PM lan tran <indigoblue7...@gmail.com> wrote:Yeah, I already tried that way. However, if we did not use DataStream at first. We cannot implement the Savepoint since through the doc if we use TableAPI (SQL API), the uid is generated automatically which means we cannot revert if the system is crashed. Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 11:04 AMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema are still not supported in Python DataStream API. Just take a further look at the Java implementation of DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, the results type is RowData instead of Row and so it should be not that easy to be directly supported in Python DataStream API. However, it supports conversion between Table API & DataStream API[1]. Could you firstly create a Table which consumes data from kafka and then convert it to a DataStream API?Regards,Dian[1] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors On Mon, Apr 25, 2022 at 11:48 AM Dian Fu <dian0511...@gmail.com> wrote:Yes, we should support them. For now, if you want to use them, you could create ones in your own project. You could refer to AvroRowDeserializationSchema[1] as an example. It should not be complicated as it's simply a wrapper of the Java implementation.Regards,Dian[1] https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308 On Mon, Apr 25, 2022 at 11:27 AM lan tran <indigoblue7...@gmail.com> wrote:Thank Dian !! Very appreciate this.However, I have another questions related to this. In current version or any updating in future, does DataStream support DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the documentation and seem it is not supported yet.Best,QuynhSent from Mail for Windows From: Dian FuSent: Friday, April 22, 2022 9:36 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,I have added an example on how to use AvroRowDeserializationSchema in Python DataStream API in [1]. Please take a look at if that helps for you~Regards,Dian[1] https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py On Fri, Apr 22, 2022 at 7:24 PM Dian Fu <dian0511...@gmail.com> wrote:Hi Quynh,Could you show some sample code on how you use it?Regards,Dian On Fri, Apr 22, 2022 at 1:42 PM lan tran <indigoblue7...@gmail.com> wrote:Wonder if this is a bug or not but if I use AvroRowDeserializationSchema,In PyFlink the error still occure ?py4j.protocol.Py4JError: An error occurred while calling None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor org.apache.flink.formats.avro.AvroRowDeserializationSchema([class org.apache.avro.Schema$RecordSchema]) does not existTherefore, please help check. ThanksBest,Quynh Sent from Mail for Windows From: lan tranSent: Thursday, April 21, 2022 1:43 PMTo: user@flink.apache.orgSubject: AvroRowDeserializationSchema Hi team, I want to implement AvroRowDeserializationSc
Re: AvroRowDeserializationSchema
Hi Quynh, You could try the following code (also it may be a little hacky): ``` def set_uid_for_source(ds: DataStream, uid: str): transformation = ds._j_data_stream.getTransformation() source_transformation = transformation while not source_transformation.getInputs().isEmpty(): source_transformation = source_transformation.getInputs().get(0) source_transformation.setUid(uid) ``` Besides, could you describe your use case a bit and also how you want to use DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in the DataStream job? Note that for the sources with these formats, it will send UPDATE messages to downstream operators. Regards Dian On Mon, Apr 25, 2022 at 12:31 PM lan tran wrote: > Yeah, I already tried that way. However, if we did not use DataStream at > first. We cannot implement the Savepoint since through the doc if we use > TableAPI (SQL API), the uid is generated automatically which means we > cannot revert if the system is crashed. > > Best, > Quynh > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Monday, April 25, 2022 11:04 AM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema are still not supported in > Python DataStream API. > > Just take a further look at the Java implementation of > DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, > the results type is RowData instead of Row and so it should be not that > easy to be directly supported in Python DataStream API. However, it > supports conversion between Table API & DataStream API[1]. Could you > firstly create a Table which consumes data from kafka and then convert it > to a DataStream API? > > Regards, > Dian > > [1] > https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors > > > > On Mon, Apr 25, 2022 at 11:48 AM Dian Fu wrote: > > Yes, we should support them. > > For now, if you want to use them, you could create ones in your own > project. You could refer to AvroRowDeserializationSchema[1] as an example. > It should not be complicated as it's simply a wrapper of the > Java implementation. > > Regards, > Dian > > [1] > https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308 > > > > On Mon, Apr 25, 2022 at 11:27 AM lan tran > wrote: > > Thank Dian !! Very appreciate this. > > However, I have another questions related to this. In current version or > any updating in future, does DataStream support > DebeziumAvroRowDeserializationSchema and > DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the > documentation and seem it is not supported yet. > > Best, > Quynh > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *Dian Fu > *Sent: *Friday, April 22, 2022 9:36 PM > *To: *lan tran > *Cc: *user@flink.apache.org > *Subject: *Re: AvroRowDeserializationSchema > > > > Hi Quynh, > > I have added an example on how to use AvroRowDeserializationSchema in > Python DataStream API in [1]. Please take a look at if that helps for you~ > > Regards, > Dian > > [1] > https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py > > > > On Fri, Apr 22, 2022 at 7:24 PM Dian Fu wrote: > > Hi Quynh, > > Could you show some sample code on how you use it? > > Regards, > Dian > > > > On Fri, Apr 22, 2022 at 1:42 PM lan tran wrote: > > Wonder if this is a bug or not but if I use > *AvroRowDeserializationSchema,* > > In PyFlink the error still occure ? > > py4j.protocol.Py4JError: An error occurred while calling > None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace: > > org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor > org.apache.flink.formats.avro.AvroRowDeserializationSchema([class > org.apache.avro.Schema$RecordSchema]) does not exist > > Therefore, please help check. Thanks > Best, > Quynh > > > > > > Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for > Windows > > > > *From: *lan tran > *Sent: *Thursday, April 21, 2022 1:43 PM > *To: *user@flink.apache.org > *Subject: *AvroRowDeserializationSchema > > > > Hi team, > > I want to implement AvroRowDeserializationSchema when consume data from >
RE: AvroRowDeserializationSchema
Yeah, I already tried that way. However, if we did not use DataStream at first. We cannot implement the Savepoint since through the doc if we use TableAPI (SQL API), the uid is generated automatically which means we cannot revert if the system is crashed. Best,Quynh Sent from Mail for Windows From: Dian FuSent: Monday, April 25, 2022 11:04 AMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema are still not supported in Python DataStream API. Just take a further look at the Java implementation of DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema, the results type is RowData instead of Row and so it should be not that easy to be directly supported in Python DataStream API. However, it supports conversion between Table API & DataStream API[1]. Could you firstly create a Table which consumes data from kafka and then convert it to a DataStream API?Regards,Dian[1] https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors On Mon, Apr 25, 2022 at 11:48 AM Dian Fu <dian0511...@gmail.com> wrote:Yes, we should support them. For now, if you want to use them, you could create ones in your own project. You could refer to AvroRowDeserializationSchema[1] as an example. It should not be complicated as it's simply a wrapper of the Java implementation.Regards,Dian[1] https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308 On Mon, Apr 25, 2022 at 11:27 AM lan tran <indigoblue7...@gmail.com> wrote:Thank Dian !! Very appreciate this.However, I have another questions related to this. In current version or any updating in future, does DataStream support DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the documentation and seem it is not supported yet.Best,QuynhSent from Mail for Windows From: Dian FuSent: Friday, April 22, 2022 9:36 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,I have added an example on how to use AvroRowDeserializationSchema in Python DataStream API in [1]. Please take a look at if that helps for you~Regards,Dian[1] https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py On Fri, Apr 22, 2022 at 7:24 PM Dian Fu <dian0511...@gmail.com> wrote:Hi Quynh,Could you show some sample code on how you use it?Regards,Dian On Fri, Apr 22, 2022 at 1:42 PM lan tran <indigoblue7...@gmail.com> wrote:Wonder if this is a bug or not but if I use AvroRowDeserializationSchema,In PyFlink the error still occure ?py4j.protocol.Py4JError: An error occurred while calling None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor org.apache.flink.formats.avro.AvroRowDeserializationSchema([class org.apache.avro.Schema$RecordSchema]) does not existTherefore, please help check. ThanksBest,Quynh Sent from Mail for Windows From: lan tranSent: Thursday, April 21, 2022 1:43 PMTo: user@flink.apache.orgSubject: AvroRowDeserializationSchema Hi team, I want to implement AvroRowDeserializationSchema when consume data from Kafka, however from the documentation, I did not understand what are avro_schema_string and record_class ? I would be great if you can give me the example on this (I only have the example on Java, however, I was doing it using PyFlink ).As my understanding avro_schema_string is schema_registry_url ? Does it support this 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like in TableAPI ?Best,Quynh.Sent from Mail for Windows
Re: AvroRowDeserializationSchema
DebeziumAvroRowDeserializationSchema and
DebeziumJsonRowDeserializationSchema are still not supported in
Python DataStream API.
Just take a further look at the Java implementation of
DebeziumAvroDeserializationSchema and DebeziumJsonDeserializationSchema,
the results type is RowData instead of Row and so it should be not that
easy to be directly supported in Python DataStream API. However, it
supports conversion between Table API & DataStream API[1]. Could you
firstly create a Table which consumes data from kafka and then convert it
to a DataStream API?
Regards,
Dian
[1]
https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/python/datastream/intro_to_datastream_api/#create-using-table--sql-connectors
On Mon, Apr 25, 2022 at 11:48 AM Dian Fu wrote:
> Yes, we should support them.
>
> For now, if you want to use them, you could create ones in your own
> project. You could refer to AvroRowDeserializationSchema[1] as an example.
> It should not be complicated as it's simply a wrapper of the
> Java implementation.
>
> Regards,
> Dian
>
> [1]
> https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308
>
> On Mon, Apr 25, 2022 at 11:27 AM lan tran
> wrote:
>
>> Thank Dian !! Very appreciate this.
>>
>> However, I have another questions related to this. In current version or
>> any updating in future, does DataStream support
>> DebeziumAvroRowDeserializationSchema and
>> DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the
>> documentation and seem it is not supported yet.
>>
>> Best,
>> Quynh
>>
>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
>> Windows
>>
>>
>>
>> *From: *Dian Fu
>> *Sent: *Friday, April 22, 2022 9:36 PM
>> *To: *lan tran
>> *Cc: *user@flink.apache.org
>> *Subject: *Re: AvroRowDeserializationSchema
>>
>>
>>
>> Hi Quynh,
>>
>> I have added an example on how to use AvroRowDeserializationSchema in
>> Python DataStream API in [1]. Please take a look at if that helps for you~
>>
>> Regards,
>> Dian
>>
>> [1]
>> https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py
>>
>>
>>
>> On Fri, Apr 22, 2022 at 7:24 PM Dian Fu wrote:
>>
>> Hi Quynh,
>>
>> Could you show some sample code on how you use it?
>>
>> Regards,
>> Dian
>>
>>
>>
>> On Fri, Apr 22, 2022 at 1:42 PM lan tran
>> wrote:
>>
>> Wonder if this is a bug or not but if I use
>> *AvroRowDeserializationSchema,*
>>
>> In PyFlink the error still occure ?
>>
>> py4j.protocol.Py4JError: An error occurred while calling
>> None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:
>>
>> org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor
>> org.apache.flink.formats.avro.AvroRowDeserializationSchema([class
>> org.apache.avro.Schema$RecordSchema]) does not exist
>>
>> Therefore, please help check. Thanks
>> Best,
>> Quynh
>>
>>
>>
>>
>>
>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
>> Windows
>>
>>
>>
>> *From: *lan tran
>> *Sent: *Thursday, April 21, 2022 1:43 PM
>> *To: *user@flink.apache.org
>> *Subject: *AvroRowDeserializationSchema
>>
>>
>>
>> Hi team,
>>
>> I want to implement AvroRowDeserializationSchema when consume data from
>> Kafka, however from the documentation, I did not understand what are
>> avro_schema_string and record_class ? I would be great if you can give me
>> the example on this (I only have the example on Java, however, I was doing
>> it using PyFlink ).
>>
>> As my understanding avro_schema_string is schema_registry_url ? Does it
>> support this
>> 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like
>> in TableAPI ?
>>
>> Best,
>> Quynh.
>>
>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
>> Windows
>>
>>
>>
>>
>>
>>
>>
>
Re: AvroRowDeserializationSchema
Yes, we should support them.
For now, if you want to use them, you could create ones in your own
project. You could refer to AvroRowDeserializationSchema[1] as an example.
It should not be complicated as it's simply a wrapper of the
Java implementation.
Regards,
Dian
[1]
https://github.com/apache/flink/blob/e11a5c52c613e121f7a7868cbbfd9e7c21551394/flink-python/pyflink/common/serialization.py#L308
On Mon, Apr 25, 2022 at 11:27 AM lan tran wrote:
> Thank Dian !! Very appreciate this.
>
> However, I have another questions related to this. In current version or
> any updating in future, does DataStream support
> DebeziumAvroRowDeserializationSchema and
> DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the
> documentation and seem it is not supported yet.
>
> Best,
> Quynh
>
> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
> Windows
>
>
>
> *From: *Dian Fu
> *Sent: *Friday, April 22, 2022 9:36 PM
> *To: *lan tran
> *Cc: *user@flink.apache.org
> *Subject: *Re: AvroRowDeserializationSchema
>
>
>
> Hi Quynh,
>
> I have added an example on how to use AvroRowDeserializationSchema in
> Python DataStream API in [1]. Please take a look at if that helps for you~
>
> Regards,
> Dian
>
> [1]
> https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py
>
>
>
> On Fri, Apr 22, 2022 at 7:24 PM Dian Fu wrote:
>
> Hi Quynh,
>
> Could you show some sample code on how you use it?
>
> Regards,
> Dian
>
>
>
> On Fri, Apr 22, 2022 at 1:42 PM lan tran wrote:
>
> Wonder if this is a bug or not but if I use
> *AvroRowDeserializationSchema,*
>
> In PyFlink the error still occure ?
>
> py4j.protocol.Py4JError: An error occurred while calling
> None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:
>
> org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor
> org.apache.flink.formats.avro.AvroRowDeserializationSchema([class
> org.apache.avro.Schema$RecordSchema]) does not exist
>
> Therefore, please help check. Thanks
> Best,
> Quynh
>
>
>
>
>
> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
> Windows
>
>
>
> *From: *lan tran
> *Sent: *Thursday, April 21, 2022 1:43 PM
> *To: *user@flink.apache.org
> *Subject: *AvroRowDeserializationSchema
>
>
>
> Hi team,
>
> I want to implement AvroRowDeserializationSchema when consume data from
> Kafka, however from the documentation, I did not understand what are
> avro_schema_string and record_class ? I would be great if you can give me
> the example on this (I only have the example on Java, however, I was doing
> it using PyFlink ).
>
> As my understanding avro_schema_string is schema_registry_url ? Does it
> support this
> 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like
> in TableAPI ?
>
> Best,
> Quynh.
>
> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
> Windows
>
>
>
>
>
>
>
RE: AvroRowDeserializationSchema
Thank Dian !! Very appreciate this.However, I have another questions related to this. In current version or any updating in future, does DataStream support DebeziumAvroRowDeserializationSchema and DebeziumJsonRowDeserializationSchema in PyFlink ? Since I look at the documentation and seem it is not supported yet.Best,QuynhSent from Mail for Windows From: Dian FuSent: Friday, April 22, 2022 9:36 PMTo: lan tranCc: user@flink.apache.orgSubject: Re: AvroRowDeserializationSchema Hi Quynh,I have added an example on how to use AvroRowDeserializationSchema in Python DataStream API in [1]. Please take a look at if that helps for you~Regards,Dian[1] https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py On Fri, Apr 22, 2022 at 7:24 PM Dian Fu <dian0511...@gmail.com> wrote:Hi Quynh,Could you show some sample code on how you use it?Regards,Dian On Fri, Apr 22, 2022 at 1:42 PM lan tran <indigoblue7...@gmail.com> wrote:Wonder if this is a bug or not but if I use AvroRowDeserializationSchema,In PyFlink the error still occure ?py4j.protocol.Py4JError: An error occurred while calling None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor org.apache.flink.formats.avro.AvroRowDeserializationSchema([class org.apache.avro.Schema$RecordSchema]) does not existTherefore, please help check. ThanksBest,Quynh Sent from Mail for Windows From: lan tranSent: Thursday, April 21, 2022 1:43 PMTo: user@flink.apache.orgSubject: AvroRowDeserializationSchema Hi team, I want to implement AvroRowDeserializationSchema when consume data from Kafka, however from the documentation, I did not understand what are avro_schema_string and record_class ? I would be great if you can give me the example on this (I only have the example on Java, however, I was doing it using PyFlink ).As my understanding avro_schema_string is schema_registry_url ? Does it support this 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like in TableAPI ?Best,Quynh.Sent from Mail for Windows
Re: AvroRowDeserializationSchema
Hi Quynh,
I have added an example on how to use AvroRowDeserializationSchema in
Python DataStream API in [1]. Please take a look at if that helps for you~
Regards,
Dian
[1]
https://github.com/apache/flink/blob/release-1.15/flink-python/pyflink/examples/datastream/formats/avro_format.py
On Fri, Apr 22, 2022 at 7:24 PM Dian Fu wrote:
> Hi Quynh,
>
> Could you show some sample code on how you use it?
>
> Regards,
> Dian
>
> On Fri, Apr 22, 2022 at 1:42 PM lan tran wrote:
>
>> Wonder if this is a bug or not but if I use
>> *AvroRowDeserializationSchema,*
>>
>> In PyFlink the error still occure ?
>>
>> py4j.protocol.Py4JError: An error occurred while calling
>> None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:
>>
>> org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor
>> org.apache.flink.formats.avro.AvroRowDeserializationSchema([class
>> org.apache.avro.Schema$RecordSchema]) does not exist
>>
>> Therefore, please help check. Thanks
>> Best,
>> Quynh
>>
>>
>>
>>
>>
>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
>> Windows
>>
>>
>>
>> *From: *lan tran
>> *Sent: *Thursday, April 21, 2022 1:43 PM
>> *To: *user@flink.apache.org
>> *Subject: *AvroRowDeserializationSchema
>>
>>
>>
>> Hi team,
>>
>> I want to implement AvroRowDeserializationSchema when consume data from
>> Kafka, however from the documentation, I did not understand what are
>> avro_schema_string and record_class ? I would be great if you can give me
>> the example on this (I only have the example on Java, however, I was doing
>> it using PyFlink ).
>>
>> As my understanding avro_schema_string is schema_registry_url ? Does it
>> support this
>> 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like
>> in TableAPI ?
>>
>> Best,
>> Quynh.
>>
>> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
>> Windows
>>
>>
>>
>>
>>
>
Re: AvroRowDeserializationSchema
Hi Quynh,
Could you show some sample code on how you use it?
Regards,
Dian
On Fri, Apr 22, 2022 at 1:42 PM lan tran wrote:
> Wonder if this is a bug or not but if I use
> *AvroRowDeserializationSchema,*
>
> In PyFlink the error still occure ?
>
> py4j.protocol.Py4JError: An error occurred while calling
> None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:
>
> org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor
> org.apache.flink.formats.avro.AvroRowDeserializationSchema([class
> org.apache.avro.Schema$RecordSchema]) does not exist
>
> Therefore, please help check. Thanks
> Best,
> Quynh
>
>
>
>
>
> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
> Windows
>
>
>
> *From: *lan tran
> *Sent: *Thursday, April 21, 2022 1:43 PM
> *To: *user@flink.apache.org
> *Subject: *AvroRowDeserializationSchema
>
>
>
> Hi team,
>
> I want to implement AvroRowDeserializationSchema when consume data from
> Kafka, however from the documentation, I did not understand what are
> avro_schema_string and record_class ? I would be great if you can give me
> the example on this (I only have the example on Java, however, I was doing
> it using PyFlink ).
>
> As my understanding avro_schema_string is schema_registry_url ? Does it
> support this
> 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like
> in TableAPI ?
>
> Best,
> Quynh.
>
> Sent from Mail <https://go.microsoft.com/fwlink/?LinkId=550986> for
> Windows
>
>
>
>
>
RE: AvroRowDeserializationSchema
Wonder if this is a bug or not but if I use AvroRowDeserializationSchema,In PyFlink the error still occure ?py4j.protocol.Py4JError: An error occurred while calling None.org.apache.flink.formats.avro.AvroRowDeserializationSchema. Trace:org.apache.flink.api.python.shaded.py4j.Py4JException: Constructor org.apache.flink.formats.avro.AvroRowDeserializationSchema([class org.apache.avro.Schema$RecordSchema]) does not existTherefore, please help check. ThanksBest,Quynh Sent from Mail for Windows From: lan tranSent: Thursday, April 21, 2022 1:43 PMTo: user@flink.apache.orgSubject: AvroRowDeserializationSchema Hi team, I want to implement AvroRowDeserializationSchema when consume data from Kafka, however from the documentation, I did not understand what are avro_schema_string and record_class ? I would be great if you can give me the example on this (I only have the example on Java, however, I was doing it using PyFlink ).As my understanding avro_schema_string is schema_registry_url ? Does it support this 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like in TableAPI ?Best,Quynh.Sent from Mail for Windows
AvroRowDeserializationSchema
Hi team, I want to implement AvroRowDeserializationSchema when consume data from Kafka, however from the documentation, I did not understand what are avro_schema_string and record_class ? I would be great if you can give me the example on this (I only have the example on Java, however, I was doing it using PyFlink ).As my understanding avro_schema_string is schema_registry_url ? Does it support this 'debezium-avro-confluent.schema-registry.url'='{schema_registry_url}' like in TableAPI ?Best,Quynh.Sent from Mail for Windows
