Cooperative vs eager rebalancing in Kafka - Practice Questions

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of consumer group rebalance with eager strategy

Consider a Kafka consumer group with two consumers consuming from four partitions. The group uses eager rebalancing. What is the expected behavior during a rebalance when a new consumer joins?

Kafka

Consumer group with 2 consumers consuming 4 partitions.
New consumer joins triggering eager rebalance.
What happens to partition assignment during rebalance?

A All consumers stop consuming, partitions are revoked from all, then reassigned to all consumers.

B Only the new consumer starts consuming immediately, others continue without interruption.

C Partitions are reassigned incrementally without stopping any consumer.

D Consumers continue consuming old partitions until manually restarted.

💡 Hint

Think about how eager rebalancing handles partition revocation and assignment.

Eager rebalancing revokes all partitions from all consumers before reassigning them. This causes a full stop and restart of consumption during rebalance.

❓ Predict Output

intermediate

Output behavior with cooperative rebalancing

In a Kafka consumer group using cooperative rebalancing, what happens when a new consumer joins the group?

Kafka

Consumer group with 3 consumers consuming 6 partitions.
New consumer joins triggering cooperative rebalance.
What is the behavior during partition reassignment?

A Partitions are revoked and reassigned incrementally, allowing consumers to continue processing some partitions without interruption.

B All partitions are revoked from all consumers before reassignment, causing a full stop.

C New consumer cannot join until all consumers restart manually.

D Partitions are duplicated temporarily to all consumers during rebalance.

💡 Hint

Cooperative rebalancing tries to minimize disruption. How does it do that?

Cooperative rebalancing revokes partitions incrementally, so consumers keep processing some partitions while others are reassigned, reducing downtime.

🧠 Conceptual

advanced

Why choose cooperative over eager rebalancing?

Which of the following is the main advantage of cooperative rebalancing compared to eager rebalancing in Kafka consumer groups?

A It guarantees faster rebalancing by revoking all partitions at once.

B It requires fewer network resources by disabling partition reassignment.

C It allows consumers to consume duplicate partitions temporarily.

D It reduces consumer downtime by allowing incremental partition revocation and assignment.

💡 Hint

Think about how downtime affects consumer processing.

Cooperative rebalancing reduces downtime by revoking partitions incrementally, so consumers keep processing some partitions during rebalance.

❓ Predict Output

advanced

Error raised when using cooperative rebalancing with unsupported client

What error will a Kafka consumer raise if it tries to use cooperative rebalancing but the client library does not support it?

Kafka

KafkaConsumer consumer = new KafkaConsumer(props);
consumer.subscribe(topics, new CooperativeRebalanceListener());
consumer.poll(Duration.ofMillis(100));

A java.lang.NullPointerException

B org.apache.kafka.common.errors.UnsupportedVersionException

C org.apache.kafka.common.errors.TimeoutException

D No error, cooperative rebalancing silently falls back to eager

💡 Hint

Check what happens when a feature is not supported by the Kafka broker or client.

If the client or broker does not support cooperative rebalancing, an UnsupportedVersionException is thrown indicating the feature is unavailable.

🚀 Application

expert

Designing a consumer group for minimal downtime during rebalance

You are designing a Kafka consumer group for a critical application that must minimize downtime during rebalances caused by scaling consumers up or down. Which rebalance strategy and configuration should you choose?

A Use eager rebalancing but increase session timeout to delay rebalances.

B Use eager rebalancing with default full partition revocation and assignment.

C Use cooperative rebalancing with incremental partition revocation and assignment enabled.

D Disable rebalancing and manually assign partitions to consumers.

💡 Hint

Consider which strategy reduces consumer downtime and supports dynamic scaling.

Cooperative rebalancing allows incremental partition revocation and assignment, minimizing downtime during scaling events, making it ideal for critical applications.