Dippatel98 opened a new pull request, #26560:
URL: https://github.com/apache/beam/pull/26560
The Kafka Transform has two control flows depending on how you provide the
schema and it takes different logical paths based on that.
* Explicit Schema: The KafkaIO reader reads the source data and deserializes
it as bytes and then applies a mapper fn to map it to the schema. In case of
schema mismatch records can fail during the mapping and can be rerouted to a
dlq.
* Confluent Schema Registry Url: The KafkaIO reader reads the source data
and deserializes it using the schema and creates GenericRecords. In case of
schema mismatch records fail during the read operation. These records will have
to rerouted in the I/O.
This PR addresses the first mode of operation. I have added dlq support in
the Kafka Read schema transform by tagging with an appropriate TupleTag and a
Counter to keep track of the number of failed elements in a bundle.
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