I am producing Avro data on my Kafka cluster that is integrated with the Confluent Schema Registry. After a schema change that is incompatible, I know my data will be rejected. Which component will reject the data?
Correct Answer:
A
The Confluent Schema Registry is your safeguard against incompatible schema changes and will be the component that ensures no breaking schema evolution will be possible. Kafka Brokers do not look at your payload and your payload schema, and therefore will not reject data
An ecommerce wesbite sells some custom made goods. What's the natural way of modeling this data in Kafka streams?
Correct Answer:
B
Mostly-static data is modeled as a table whereas business transactions should be modeled as a stream.
By default, which replica will be elected as a partition leader? (select two)
Correct Answer:
BD
Preferred leader is a broker that was leader when topic was created. It is preferred because when partitions are first created, the leaders are balanced between brokers. Otherwise, any of the in-sync replicas (ISR) will be elected leader, as long as unclean.leader.election=false (by default)
In Avro, adding an element to an enum without a default is a schema evolution
Correct Answer:
A
Since Confluent 5.4.0, Avro 1.9.1 is used. Since default value was added to enum complex type , the schema resolution changed from:
(<1>=1.9.1) if both are enums:
if the writer's symbol is not present in the reader's enum and the reader has a default value, then that value is used, otherwise an error is signalled.
A consumer starts and has auto.offset.reset=latest, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group has committed the offset 643 for the topic before. Where will the consumer read from?
Correct Answer:
C
The offsets are already committed for this consumer group and topic partition, so the property auto.offset.reset is ignored
