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| Section | Weight | Objectives |
|---|---|---|
| Kafka Connect | 15% | - Connect architecture: workers, connectors, tasks, converters - Source and sink connectors configuration - Data transformation and integration patterns |
| Apache Kafka Application Development | 28% | - Consumer API: configuration, offset management, consumer groups, rebalancing - Producer API: configuration, serialization, partitioning, error handling - Transactional messaging and idempotence - Schema management: Confluent Schema Registry, compatibility rules, evolution |
| Apache Kafka Fundamentals | 23% | - Core concepts: brokers, topics, partitions, replicas, offsets - Configuration basics and cluster setup - Delivery semantics: at-most-once, at-least-once, exactly-once - Kafka architecture and data flow |
| Application Observability | 13% | - Error diagnosis and troubleshooting - Tracing and performance tuning - Logging and monitoring metrics |
| Apache Kafka Streams | 12% | - Stream processing operations: map, filter, join, aggregation - Error handling and state management - Streams API concepts: topology, processors, state stores - Windowing and time semantics |
| Application Testing | 8% | - Integration testing and test clusters - Mocking and test utilities - Unit testing producers and consumers |
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NEW QUESTION # 56
You are working on a Kafka cluster with three nodes. You create a topic named orders with:
* replication.factor = 3
* min.insync.replicas = 2
* acks = allWhat exception will be generated if two brokers are down due to network delay?
Answer: D
Explanation:
With acks=all and min.insync.replicas=2, Kafka requiresat least two in-sync replicasto acknowledge a write.
If onlyone broker is alive, the condition fails, andNotEnoughReplicasExceptionis thrown by the producer.
FromKafka Producer Exception Docs:
"NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas."
* NetworkException is generic and not raised here.
* NotCoordinatorException is related to consumer group coordination.
* NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.
Reference:Kafka Producer Error Handling
NEW QUESTION # 57
What happens when broker.rack configuration is provided in broker configuration in Kafka cluster?
Answer: C
Explanation:
Partitions for newly created topics are assigned in a rack alternating manner, this is the only change broker.rack does
NEW QUESTION # 58
(You want to read messages from all partitions of a topic in every consumer instance of your application.
How do you do this?)
Answer: B
Explanation:
According to the Apache Kafka Consumer API documentation, the assign() method allows a consumer to manually assign specific partitions to itself, bypassing Kafka's consumer group coordination and rebalancing mechanism. When a consumer uses assign() with all partitions of a topic, that consumer will read from every partition, regardless of how many other consumers exist.
This behavior is required when every consumer instance must independently read the full dataset, such as in auditing, monitoring, or replication use cases. In contrast, subscribe() is designed for consumer group usage, where partitions are distributed among consumers, ensuring that each partition is consumed by only one consumer in the group.
Option B is invalid because assign() requires a collection of TopicPartition objects, not just a topic name.
Option C still uses group coordination and does not guarantee all partitions per consumer. Option D is invalid because an empty group ID is not supported by Kafka.
Thus, explicitly calling assign() with all topic partitions is the only correct and documented way to ensure each consumer reads from all partitions.
NEW QUESTION # 59
You need to configure a sink connector to write records that fail into a dead letter queue topic.
Requirements:
* Topic name: DLQ-Topic
* Headers containing error context must be added to the messagesWhich three configuration parameters are necessary?(Select three.)
Answer: A,D,E
Explanation:
To send failed records to adead letter queue (DLQ), you must configure:
* errors.tolerance=all: Tells the connector tonot failon errors but handle them (e.g., send to DLQ).
* errors.deadletterqueue.topic.name=DLQ-Topic: Specifies the DLQ topic.
* errors.deadletterqueue.context.headers.enable=true: Includes error context in message headers.
FromKafka Connect Error Handling Docs:
"Kafka Connect supports directing problematic records to a separate topic (DLQ) using errors.* configs.
Headers can include failure metadata."
Options D, E, F are related tologging, not DLQ behavior.
Reference:Kafka Connect Configurations > Error Handling
NEW QUESTION # 60
A consumer starts and has auto.offset.reset=none, and the topic partition currently has data for offsets going from 45 to 2311. The consumer group has committed the offset 10 for the topic before. Where will the consumer read from?
Answer: C
Explanation:
auto.offset.reset=none means that the consumer will crash if the offsets it's recovering from have been deleted from Kafka, which is the case here, as 10 < 45
NEW QUESTION # 61
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