5 exercises on event streaming and Kafka vocabulary.
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What is the fundamental data structure in Apache Kafka?
Kafka topic: a durable, append-only log split into partitions. Records are retained for a configurable period regardless of consumption, letting multiple consumers replay at their own offsets independently.
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What is a consumer group in Kafka?
Consumer group: Kafka assigns each partition to exactly one consumer within a group, enabling parallel processing. Different groups each get a full copy of every message, enabling independent read patterns.
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What is the significance of a Kafka offset?
Offset: each record in a partition gets an immutable integer offset. Consumers commit their offset to track which messages have been processed. On restart or rebalance, a consumer resumes from the last committed offset.
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How does Kafka achieve at-least-once delivery semantics by default?
At-least-once: if the producer does not receive an acknowledgement, it retries. This risks duplicates. For exactly-once semantics, Kafka supports idempotent producers and transactional APIs, at higher complexity.
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What is log compaction in Kafka and when is it useful?
Log compaction: rather than time/size-based retention, Kafka retains at least the most recent value per key. This makes topics suitable as a source of truth: consumers can replay the compacted topic to rebuild the latest state of each entity.