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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 2: Apache Kafka Application Development | 28% | - Schema management: Confluent Schema Registry, compatibility rules, evolution - Transactional messaging and idempotence - Consumer API: configuration, offset management, consumer groups, rebalancing - Producer API: configuration, serialization, partitioning, error handling |
| Topic 3: Application Testing | 8% | - Integration testing and test clusters - Unit testing producers and consumers - Mocking and test utilities |
| Topic 4: Kafka Connect | 15% | - Data transformation and integration patterns - Connect architecture: workers, connectors, tasks, converters - Source and sink connectors configuration |
| Topic 5: Apache Kafka Streams | 12% | - Stream processing operations: map, filter, join, aggregation - Windowing and time semantics - Error handling and state management - Streams API concepts: topology, processors, state stores |
| Topic 6: Application Observability | 13% | - Tracing and performance tuning - Error diagnosis and troubleshooting - Logging and monitoring metrics |
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NEW QUESTION # 19
Your application is consuming from a topic configured with a deserializer.
It needs to be resilient to badly formatted records ("poison pills"). You surround the poll() call with a try/catch for RecordDeserializationException.
You need to log the bad record, skip it, and continue processing.
Which action should you take in the catch block?
Answer: C
Explanation:
To skip a corrupted record and avoid failing the application, you must seek past the failed offset manually using consumer.seek(). This allows the application to resume consumption from the next offset.
From Kafka Consumer Error Handling Docs:
"On deserialization failure, you can catch RecordDeserializationException, log the error, and call seek() to the next offset to skip the bad record." A does not prevent re-processing the bad record.
C is invalid; there's no skip() method in the Kafka consumer API.
D results in service interruption - not ideal for resiliency.
Reference: Kafka Consumer API - Exception Handling and seek()
NEW QUESTION # 20
What data format isn't natively available with the Confluent REST Proxy?
Answer: C
Explanation:
Protocol buffers isn't a natively supported type for the Confluent REST Proxy, but you may use the binary format instead
NEW QUESTION # 21
A producer is configured with the default partitioner. It is sending records to a topic that is configured with five partitions. The record does not contain any key.
What is the result of this?
Answer: B
Explanation:
If a key isnot specified, thedefault Kafka partitioner uses round-robinlogic to assign partitions. This leads toeven distributionof messages across all partitions.
FromKafka Producer Design:
"If the key is null, the producer will assign the partition in a round-robin fashion to achieve load balancing." There isno error, and partition 0 isnot alwayschosen in this case.
Reference:Kafka Producer Partitioner Behavior - Official Docs
NEW QUESTION # 22
A consumer application runs once a week and reads from a Kafka topic. The last time the application ran, the last offset processed was 217. The application is configured with auto.offset.reset set to "latest". The current offsets in the topic start at 318 and end at 588.
What offset will the application start reading when it starts up for its next run?
Answer: C
NEW QUESTION # 23
How do you read a table or stream from the beginning of a topic?
Answer: H
NEW QUESTION # 24
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