Replication factor in Kafka - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the replication factor in Kafka?

The replication factor is the number of copies of each partition that Kafka keeps across different brokers to ensure data durability and availability.

beginner

Why is having a replication factor greater than 1 important?

It helps protect data from loss if a broker fails by keeping copies on other brokers, so the system can continue working without losing messages.

beginner

What happens if the replication factor is set to 1?

There is only one copy of each partition, so if the broker holding that partition fails, the data is lost and unavailable until the broker recovers.

intermediate

How does Kafka decide which brokers hold replicas of a partition?

Kafka distributes replicas across brokers to balance load and increase fault tolerance, ensuring replicas are on different brokers to avoid single points of failure.

intermediate

What is the relationship between replication factor and fault tolerance?

Higher replication factor means more copies of data, which increases fault tolerance because the system can survive more broker failures without losing data.

What does a replication factor of 3 mean in Kafka?

A Each partition has 3 copies on different brokers

B There are 3 partitions in the topic

C The topic can only have 3 messages

D The broker can handle 3 clients

Replication factor 3 means each partition is copied 3 times on different brokers for safety.

If a broker fails, what helps Kafka keep data available?

A Disabling replication

B Replication factor greater than 1

C Using a single broker

D Having only one partition

Replication factor > 1 means copies exist on other brokers, so data stays available.

What risk does a replication factor of 1 pose?

A Data loss if the broker fails

B Too many copies of data

C Slower message delivery

D More disk space used

With only one copy, if the broker fails, data is lost.

How does Kafka improve fault tolerance with replication?

A By limiting the number of partitions

B By deleting old messages

C By storing replicas on different brokers

D By using a single broker

Replicas on different brokers prevent single points of failure.

What is a downside of increasing the replication factor?

A Fewer brokers needed

B Less data safety

C Messages get lost faster

D More disk space and network usage

More replicas use more disk space and network resources.

Explain what the replication factor is and why it matters in Kafka.

Think about how Kafka keeps copies of data to avoid losing it.

Describe what happens when the replication factor is set to 1 and a broker fails.

Consider what happens if there is no backup copy.