For Kafka Streams to perform joins, topics must be co-partitioned, meaning:

They have the same number of partitions (A), and

They use the same partitioning strategy (typically by key) (B)

From Kafka Streams Documentation > Joins:

“Co-partitioning is required for Kafka Streams joins. Topics must have the same number of partitions and use the same key-based partitioner.”

Value schema (C) and retention time (D) have no bearing on join compatibility.

Session windows are ideal for tracking periods of activity separated by inactivity, such as user sessions.

From Kafka Streams Documentation > Windowing:

“A session window captures streams of events that are intermittent and separated by a gap of inactivity.”

Tumbling/Hopping/Sliding windows are fixed in size

Session windows are dynamic and close after inactivity timeout

This makes them perfect for identifying gaps in user interaction.

A: Kafka batches store compression metadata in their headers, indicating how the batch was compressed.

B: Compression is controlled via the producer config compression.type, which defaults to none. Producers explicitly set Gzip or other formats.

From Kafka Producer Docs:

“Compression is done by the producer, and the type is stored in the message batch metadata. The broker does not recompress.”

C is false: messages are serialized before compression.

D is false: messages without keys are distributed across multiple partitions.

To reset offsets for an existing consumer group, you must use the kafka-consumer-groups.sh tool with the --reset-offsets and --to-earliest flags.

From Kafka Consumer Group Tool Documentation:

“You can use the kafka-consumer-groups tool to reset offsets for a consumer group. This is required if the consumer has already committed offsets.”

Setting auto.offset.reset=earliest only works if no committed offset exists.

Starting a new consumer with the same group won’t reset offsets.

Retention settings don’t affect committed offsets.