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

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kafka-topics.sh --bootstrap-server localhost:9092 --describe --unavailable- partitions

kafka-topics.sh --zookeeper localhost:2181 --describe --unavailable- partitions

kafka-topics.sh --broker-list localhost:9092 --describe --under-replicated-partitions

kafka-topics.sh --zookeeper localhost:2181 --describe --under-replicated-partitions

Commit the offsets on disk, after processing the data

Do not commit any offsets and read from beginning

Commit the offsets in Kafka, after processing the data

Commit the offsets in Kafka, before processing the data

min.insync.replicas is a producer setting

acks is a topic setting

acks is a producer setting

min.insync.replicas is a topic setting

min.insync.replicas matters regardless of the values of acks

min.insync.replicas only matters if acks=all

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KTable

GlobalKTable

You choose between KStream or KTable

Kstream

All the existing records will get rebalanced among the partitions to balance load

New records with the same key will get written to the partition where old records with that key were written

New records may get written to a different partition

Old records will stay in their partitions

Every time a new partition is created

Every time a segment is closed

Every time a message is sent to Kafka

Every time a message is flushed to disk

Money made until now

The transaction stream

Items returned

Inventory contents right now

consumer.subscribe(Pattern.compile("topic\..*"));

consumer.subscribe("topic.history"); consumer.subscribe("topic.sports"); consumer.subscribe("topic.politics");

consumer.subscribePrefix("topic.");

consumer.subscribe(Arrays.asList("topic.history", "topic.sports", "topic.politics"));

tasks-

application.id

group.id

kafka-streams-

bin/kafka-topics.sh --create --broker-list localhost:9092 --replication-factor 3 --partitions 3 --topic test

bin/kafka-topics-create.sh --zookeeper localhost:9092 --replication-factor 3 --partitions 3 --topic test

bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 3 --partitions 3 --topic test

bin/kafka-topics.sh --create --bootstrap-server localhost:2181 --replication-factor 3 --partitions 3 --topic test

KafkaProducer divides messages into sizes of max.request.size and sends them in order

KafkaProducer divides messages into sizes of message.max.bytes and sends them in order

MessageSizeTooLarge exception will be thrown, KafkaProducer will not retry and return exception immediately

MessageSizeTooLarge exception will be thrown, KafkaProducer retries until the number of retries are exhausted

contains all the topics and all the partitions

knows all the metadata for all topics and partitions

is a controller

knows the metadata for the topics and partitions it has on its disk

is a bootstrap broker

contains only a subset of the topics and the partitions

Repartition the purchase topic to have 3 partitions

Repartition customer topic to have 5 partitions

Model customer as a GlobalKTable

Do a KStream / KTable join after a repartition step

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value.deserializer

auto.offset.resets

group.id

enable.auto.commit

Kafka => Kafka

Kafka => External

External => Kafka

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