ted in PyFlink currently.
Is there a way to convert this Generic Records returned
by ConfluentRegistryAvroDeserializationSchema to into Flink rows like how
existing AvroRowDeserializationSchema is returning ?
Could you please suggest how to do this or any othe
me","type":"string","doc":"String
Value"},{"name":"id","type":"string","doc":"String Value"}]}") is not
supported in PyFlink currently.
Is there a way to convert this Generic Records returned
by Conflue
.org.apache.avro.Schema.Parser
> value_schema = JSchemaParser().parse(value_schema_str)
> ```
>
> The reason is that ```value_schema = avro.schema.parse( here>) ``` will create a Python object instead of Java object.
>
> Regards,
> Dian
>
> 2021年5月19日 下午5:23，Z
_url = "http://host:port";
How can I create Java Schema object from this schema string and pass it
from python method ?
Regards,
Zerah
On Wed, May 19, 2021 at 1:57 PM Dian Fu wrote:
> Hi Zerah,
>
> What’s the type of value_schema? It should be a Java object of type
> Sch
istryAvroDeserializationSchema if needed. It’s just a wrapper
> for the Java implementation and so it’s will be very easy to implement. You
> could take a look at AvroRowDeserializationSchema [1] as an example.
>
> Regards,
> Dian
>
> [1]
> https://github.com/apache/flink/blob/release-1
Hi,
I have below use case
1. Read streaming data from Kafka topic using Flink Python API
2. Apply transformations on the data stream
3. Write back to different kafka topics based on the incoming data
Input data is coming from Confluent Avro Producer. By using the existing
pyflink.common.serializ
