How does Kafka Streams achieve fault tolerance?
By relying solely on message acknowledgments from consumers.
By using a single, centralized processing unit.
By replicating stream processing tasks across multiple nodes.
By storing all processed data in a separate, redundant database.
What is the primary function of Kafka Streams?
Managing cluster resources for Kafka brokers
Performing real-time data analysis and transformations on streams
Guaranteeing exactly-once message delivery
Storing and persisting streaming data
What is the significance of the 'unclean.leader.election.enable' configuration parameter during broker failures?
It controls the replication factor for partitions.
It defines the time a broker is considered dead before triggering a leader election.
It allows for faster leader election but might lead to data loss.
It ensures no data loss during leader election but might increase unavailability.
How does increasing the replication factor of a topic affect the availability and durability of data in Kafka?
Higher replication factor increases both availability and durability without any drawbacks.
Higher replication factor increases durability but may slightly reduce write availability.
Higher replication factor increases availability but reduces durability.
Higher replication factor has no impact on availability or durability.
What is the significance of 'Exactly Once Semantics' in Kafka Streams?
It ensures that records are processed in the exact order they were produced.
It guarantees that each record is processed at least once.
It prevents duplicate processing of records even in the event of failures.
It prioritizes speed over accuracy in data processing.
What is the purpose of consumer groups in Kafka?
To store messages persistently on disk.
To guarantee message ordering for all consumers.
To replicate messages across multiple data centers.
To allow multiple consumers to subscribe to the same topic and each process a subset of messages.
What is the role of a Kafka Controller in a cluster?
Performing load balancing of messages
Monitoring and managing the health of brokers
Handling data replication between brokers
Managing message consumption rates
In Kafka, which configuration setting controls the duration for which message acknowledgments from consumers are tracked?
replica.lag.time.max.ms
group.max.session.timeout.ms
message.timeout.ms
offsets.retention.minutes
KSQL provides an SQL-like interface for interacting with Kafka. What type of language is KSQL categorized as?
Query language
Object-oriented programming language
Domain-specific language
Markup language
What is a key advantage of using KSQL for stream processing in Kafka?
It allows for direct manipulation of Kafka's underlying storage files.
It offers significantly better performance compared to using Kafka Streams API.
It provides a simpler, SQL-based abstraction for building stream processing applications.
It eliminates the need for any programming, relying solely on SQL commands.