Describe the Apache Kafka Queueing System and Architecture DATA-ENGINEERING-OPTIMIZE Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   In Kafka, how do consumers in the same consumer group share the load of reading from a topic?

   • AEach consumer reads all messages from all partitions.
   • BEach consumer is assigned a subset of the topic's partitions.
   • CConsumers take turns reading messages sequentially from a single shared log.
   • DConsumers randomly pick messages to process.
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2. 17expert · hard

   A team is building a Kafka-based system to process financial transactions. They need exactly-once processing semantics. They have enabled idempotent producers and set `acks=all`. What additional configuration is required to achieve exactly-once end-to-end processing?

   • AConfigure the consumer to use `read_committed` isolation level and use Kafka transactions.
   • BSet the consumer's `enable.auto.commit` to false and manually commit offsets after processing.
   • CIncrease the replication factor to 5.
   • DUse a single partition for the topic.
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4. 18foundation · easy

   What feature does Kafka provide to enable exactly-once semantics for producers?

   • AIdempotent producers
   • BConsumer group rebalancing
   • CLog compaction
   • DPartition replication
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5. 19foundation · easy

   What is the role of an offset in Kafka's data flow?

   • AIt is the number of replicas for a partition.
   • BIt is the timestamp when a message was produced.
   • CIt is a unique identifier for a broker in the cluster.
   • DIt is a sequential position number that identifies a message within a partition.
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6. 20expert · medium

   A company has a Kafka topic with 10 partitions. They have a consumer group with 3 consumers. The processing time per message is high, and they want to increase throughput. They add 2 more consumers to the group. What is the expected impact on throughput?

   • AThroughput will increase because more consumers can process partitions in parallel.
   • BThroughput will increase only if the topic is re-partitioned to have more partitions.
   • CThroughput will remain the same because the number of partitions is unchanged.
   • DThroughput will decrease because of rebalancing overhead.
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