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| Section | Weight | Objectives |
|---|
| Apache Kafka Fundamentals | 23% | - Kafka architecture and data flow - Core concepts: brokers, topics, partitions, replicas, offsets - Configuration basics and cluster setup - Delivery semantics: at-most-once, at-least-once, exactly-once
|
| Application Testing | 8% | - Integration testing and test clusters - Unit testing producers and consumers - Mocking and test utilities
|
| Application Observability | 13% | - Error diagnosis and troubleshooting - Tracing and performance tuning - Logging and monitoring metrics
|
| Apache Kafka Application Development | 28% | - Consumer API: configuration, offset management, consumer groups, rebalancing - Schema management: Confluent Schema Registry, compatibility rules, evolution - Transactional messaging and idempotence - Producer API: configuration, serialization, partitioning, error handling
|
| Kafka Connect | 15% | - Data transformation and integration patterns - Source and sink connectors configuration - Connect architecture: workers, connectors, tasks, converters
|
| Apache Kafka Streams | 12% | - Streams API concepts: topology, processors, state stores - Error handling and state management - Windowing and time semantics - Stream processing operations: map, filter, join, aggregation
|
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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q42-Q47):
NEW QUESTION # 42
What is a consequence of increasing the number of partitions in an existing Kafka topic?
- A. Consumers will need to process data from more partitions which will significantly increase consumer lag.
- B. The acknowledgment process will increase latency for producers using acks=all.
- C. Existing data will be redistributed across the new number of partitions temporarily increasing cluster load.
- D. Records with the same key could be located in different partitions.
Answer: A
Explanation:
Increasing partitions increases parallelism, but also means:
Consumers in a group may have to handle more partitions, especially if the number of consumers is lower than the number of partitions.
This can result in increased lag, especially under high load.
From Kafka Topic Management Docs:
"Increasing the number of partitions increases consumer work, and if consumers can't keep up, lag can accumulate." A is false: existing data is not redistributed.
B is false: records with the same key always map to the same partition based on hash.
D is not directly impacted by the partition count.
Reference: Kafka Topic Management > Adding Partitions
NEW QUESTION # 43
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 2. How many brokers can go down before a producer with acks=1 can't produce?
Answer: D
Explanation:
min.insync.replicas does not impact producers when acks=1 (only when acks=all)
NEW QUESTION # 44
What are the requirements for a Kafka broker to connect to a Zookeeper ensemble? (select two)
- A. All the brokers must share the same zookeeper.connect parameter
- B. All the brokers must share the same broker.id
- C. Unique values for each broker's broker.id parameter
- D. Unique value for each broker's zookeeper.connect parameter
Answer: A,C
Explanation:
Each broker must have a unique broker id and connect to the same zk ensemble and root zNode
NEW QUESTION # 45
Your company has three Kafka clusters: Development, Testing, and Production.
The Production cluster is running out of storage, so you add a new node.
Which two statements about the new node are true?
(Select two.)
- A. A newly added node will have KRaft controller role by default.
- B. A new node can be added without stopping existing cluster nodes.
- C. A new node will not have any partitions assigned to it unless a new topic is created or reassignment occurs.
- D. A node ID will be assigned to the new node automatically.
Answer: B,C
Explanation:
* C is true: When a new broker is added,no partitions are assigned to itunless you create new topics or reassign existing onesusing kafka-reassign-partitions.sh.
* D is true: Kafka brokers arehot-pluggable; no need to stop the cluster when scaling.
FromKafka Operations Guide:
"A newly added broker won't be assigned partitions until reassignments or new topic creation."
"Kafka allows dynamic scaling by adding brokers without downtime."
* A is false: Broker IDs must bemanually setunless using dynamic broker registration in KRaft mode.
* B is false unless the cluster usesKRaft modeand the broker isspecifically assigneda controller role.
Reference:Kafka Operations > Adding Brokers
NEW QUESTION # 46
You need to consume messages from Kafka using the command-line interface (CLI).
Which command should you use?
- A. kafka-consume
- B. kafka-consumer
- C. kafka-get-messages
- D. kafka-console-consumer
Answer: D
Explanation:
The official CLI utility for consuming messages from Kafka topics is kafka-console-consumer.sh. It connects to the broker, consumes messages, and prints them to standard output.
FromKafka CLI Tools Documentation:
"kafka-console-consumer.sh is used to read data from a Kafka topic and write it to standard output." The other options are not valid Kafka CLI tools.
Reference:Apache Kafka Documentation > kafka-console-consumer.sh
NEW QUESTION # 47
......
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