CCDAK Confluent Certified Developer for Apache Kafka Certification Examination Questions and Answers

The correct option is the only one where the two consumers share an equal number of partitions amongst the two topics of three partitions. An interesting article to read ishttps://medium.com/@anyili0928/what-i-have-learned-from-kafka-partition-assignment-strategy-799fdf15d3ab

A kafka broker automatically creates a topic under the following circumstances- When a producer starts writing messages to the topic - When a consumer starts reading messages from the topic - When any client requests metadata for the topic

Producer idempotence helps prevent the network introduced duplicates. More details herehttps://cwiki.apache.org/confluence/display/KAFKA/Idempotent+Producer

Seehttps://kafka.apache.org/20/documentation/streams/developer-guide/dsl-api.html#stateless-transformations

1 is not possible as it doesn't provide resilience to failure, 2 is not enough as if we take a broker down for maintenance, we cannot tolerate a broker failure, and 6 is impossible as we only have 3 brokers (RF cannot be greater than the number of brokers). Here the correct answer is 3

Producers can set acks=1 to get acknowledgement from partition leader only.

doc represents optional description of message

subscribe() and assign() cannot be called by the same consumer, subscribe() is used to leverage the consumer group mechanism, while assign() is used to manually control partition assignment and reads assignment

acks is a producer setting min.insync.replicas is a topic or broker setting and is only effective when acks=all

The Controller is a broker that is responsible for electing partition leaders

we have two tables, so the max number of tasks is 2

Consumers can set auto.offset.reset property to earliest to start consuming from beginning. For KSQL, SET 'auto.offset.reset'='earliest';

here, we have three tables, but the max.tasks is 2, so that's the maximum number of tasks that will be created

GlobalKTables have their datasets replicated on each Kafka Streams instance and therefore no repartitioning is required

Please note that as of Kafka 2.2, the --zookeeper option is deprecated and you can now usekafka-topics.sh --bootstrap-server localhost:9092 --describe --unavailable-partitions

Kafka transfers data with zero copy and no transformation. Any transformation (including compression) is the responsibility of clients.

Result is aggregated into a table with key as the unique word and value its frequency. We have to enable log compaction for this topic to align the topic's cleanup policy with KTable semantics.

tick time is 2000 ms, and initLimit is the config taken into account when establishing a connection to Zookeeper, so the answer is 2000 * 20 = 40000 ms = 40s

Increasing the number of partition causes new messages keys to get hashed differently, and breaks the guarantee "same keys goes to the same partition". Kafka logs are immutable and the previous messages are not re-shuffled