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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Apache Kafka Fundamentals | 23% | - Configuration basics and cluster setup - Delivery semantics: at-most-once, at-least-once, exactly-once - Kafka architecture and data flow - Core concepts: brokers, topics, partitions, replicas, offsets |
| Topic 3: Application Testing | 8% | - Mocking and test utilities - Unit testing producers and consumers - Integration testing and test clusters |
| Topic 4: Application Observability | 13% | - Error diagnosis and troubleshooting - Logging and monitoring metrics - Tracing and performance tuning |
| Topic 5: Apache Kafka Application Development | 28% | - Schema management: Confluent Schema Registry, compatibility rules, evolution - Producer API: configuration, serialization, partitioning, error handling - Consumer API: configuration, offset management, consumer groups, rebalancing - Transactional messaging and idempotence |
| Topic 6: Kafka Connect | 15% | - Source and sink connectors configuration - Data transformation and integration patterns - Connect architecture: workers, connectors, tasks, converters |
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NEW QUESTION # 50
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: A
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 # 51
You have a Kafka cluster and all the topics have a replication factor of 3. One intern at your company stopped a broker, and accidentally deleted all the data of that broker on the disk. What will happen if the broker is restarted?
Answer: C
Explanation:
Kafka replication mechanism makes it resilient to the scenarios where the broker lose data on disk, but can recover from replicating from other brokers. This makes Kafka amazing!
NEW QUESTION # 52
(You are developing a Java application that includes a Kafka consumer.
You need to integrate Kafka client logs with your own application logs.
Your application is using the Log4j2 logging framework.
Which Java library dependency must you include in your project?)
Answer: B
Explanation:
According to the official Apache Kafka client documentation, Kafka uses SLF4J (Simple Logging Facade for Java) for all client-side logging. SLF4J is only an abstraction layer and requires a concrete logging implementation to route log messages to the actual logging framework used by the application.
Since the application uses Log4j2, an SLF4J-to-Log4j2 binding must be provided. The correct and officially recommended dependency is org.apache.logging.log4j:log4j-slf4j-impl. This dependency acts as the SLF4J implementation and forwards all Kafka client log messages to Log4j2, ensuring consistent logging across the application.
Option B is incorrect because it targets the legacy Log4j 1.2 framework, which is deprecated and incompatible with Log4j2. Option C is insufficient because Log4j2 alone does not satisfy Kafka's SLF4J dependency. Option D is incorrect because Kafka intentionally does not include a logging implementation transitively, allowing applications to choose their preferred logging framework.
Therefore, including the SLF4J implementation for Log4j2 is required to properly integrate Kafka client logs.
NEW QUESTION # 53
You create a topic named loT-Data with 10 partitions and replication factor of three.
A producer sends 1 MB messages compressed with Gzip.
Which two statements are true in this scenario?
(Select two.)
Answer: B,D
Explanation:
A: Kafka batches store compression metadata in their headers, indicating how the batch was compressed.
B: Compression is controlled via the producer config compression.type, which defaults to none. Producers explicitly set Gzip or other formats.
From Kafka Producer Docs:
"Compression is done by the producer, and the type is stored in the message batch metadata. The broker does not recompress." C is false: messages are serialized before compression.
D is false: messages without keys are distributed across multiple partitions.
Reference: Kafka Producer Configs > compression.type
NEW QUESTION # 54
Which of the following is NOT a supported serialization format in ksqlDB?
Answer: B
NEW QUESTION # 55
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