What is the purpose of consumer groups in Kafka?
To store messages persistently on disk.
To allow multiple consumers to subscribe to the same topic and each process a subset of messages.
To replicate messages across multiple data centers.
To guarantee message ordering for all consumers.
In KSQL, what is a 'STREAM' analogous to in traditional database terminology?
A trigger
A view
A table
A stored procedure
How does Kafka ensure data durability and availability in the event of a broker failure?
By replicating partitions across multiple brokers.
All of the above.
By using a distributed commit log for tracking message offsets.
By writing all messages to a persistent disk before acknowledging them.
What is the primary benefit of using Kafka's idempotent producer feature?
Improved message ordering guarantees within a partition.
Increased throughput by reducing the need for message acknowledgments.
Elimination of duplicate messages on the broker due to producer retries.
Automatic data balancing across multiple Kafka brokers.
What is a key difference between Source Connectors and Sink Connectors in Kafka Connect?
Source Connectors are stateful, while Sink Connectors are stateless.
Source Connectors require custom coding, while Sink Connectors use pre-built configurations.
Source Connectors handle real-time data, while Sink Connectors handle batch data.
Source Connectors push data, while Sink Connectors pull data.
What does JMX stand for in the context of Kafka monitoring?
Java Management eXtensions
Java Message eXport
JSON Metric eXchange
Just Monitor XML
What is the purpose of stateful operations in Kafka Streams?
To store processed data permanently in a relational database.
To maintain and update information across multiple messages in a stream.
To ensure exactly-once message delivery semantics.
To filter and route messages based on content.
How can you access Kafka's JMX metrics?
By reading the Kafka log files located on the broker servers
By accessing the Kafka web console
By connecting to the Kafka broker's JMX port using a JMX client
By querying the Kafka command-line tools
Which partitioning strategy in Kafka is most suitable when you need messages with the same key to be processed by the same consumer instance?
Time-based Partitioning
Round Robin Partitioning
Key-based Partitioning
Random Partitioning
What is the primary purpose of monitoring Kafka metrics?
To understand and optimize Kafka cluster performance and health
To track the number of messages consumed by each consumer group
To debug application code that interacts with Kafka
To identify and troubleshoot security vulnerabilities in Kafka