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| Section | Weight | Objectives |
|---|---|---|
| Installing and Configuring Kafka | 5-10% | - Partition Assignment Strategies - Broker Configuration Parameters - ZooKeeper vs KRaft Mode - Topic Creation and Configuration |
| Developing with Kafka Producers | 15-20% | - Producer Configuration and Tuning - Error Handling and Retry Logic - Exactly-Once Semantics - Partitioning Strategies - Serialization (JSON, Avro, Protobuf) - Idempotent Producers - Producer Interceptors |
| Kafka Streams | 20-25% | - Interactive Queries - Exactly-Once Processing - Testing Kafka Streams Applications - Streams Architecture and Topology - Windowed Operations (Tumbling, Hopping, Session) - State Stores and Processors - Transformation Operations (map, filter, join, aggregate) |
| Kafka Connect | 10-15% | - Offset Management in Connect - Converters and Transforms - Source and Sink Connectors - Single Message Transformations (SMT) - Connect Architecture (Workers, Connectors, Tasks) - Connector Configuration |
| Monitoring and Operations | 5-10% | - Consumer Lag and Health Checks - Cross-region Replication - Log Compaction - Kafka Metrics and Monitoring - Disaster Recovery |
| Schema Management | 5-10% | - Avro Schemas - Schema Evolution and Compatibility - Protobuf and JSON Schemas - Schema Registration and Retrieval - Schema Registry Architecture |
| Developing with Kafka Consumers | 15-20% | - Consumer Groups and Rebalancing - Offset Management - Commit Strategies (Auto, Manual, Cooperative) - Multi-threaded Consumers - Consumer Configuration and Tuning - Consumer Interceptors - Deserialization |
| Kafka Fundamentals | 10-15% | - Producer and Consumer Basics - Log Segments and Retention - Topics, Partitions, and Offsets - Brokers and Clusters - Replication Factor and ISR |
| Security | 5-10% | - Encryption in Transit - Authorization (ACLs) - Securing Schema Registry - Authentication (SASL, SSL/TLS) |
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NEW QUESTION # 39
An application is writing AVRO messages using Schema Registry to topic t1. During this process, the Schema Registry becomes unavailable for a few seconds.
What is the expected impact to the application?
Answer: D
NEW QUESTION # 40
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?
Answer: B
Explanation:
Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.idempotence=true which takes care of the out of ordering case on its own. Seehttps://issues.apache.org/jira/browse/KAFKA-5494
NEW QUESTION # 41
You have a Kafka consumer in production actively reading from a critical topic.
You need to update the offset of your consumer to start reading from the beginning of the topic.
Which action should you take?
Answer: A
Explanation:
To reset offsets for an existing consumer group, you must use the kafka-consumer-groups.sh tool with the -- reset-offsets and --to-earliest flags.
From Kafka Consumer Group Tool Documentation:
"You can use the kafka-consumer-groups tool to reset offsets for a consumer group. This is required if the consumer has already committed offsets." Setting auto.offset.reset=earliest only works if no committed offset exists.
Starting a new consumer with the same group won't reset offsets.
Retention settings don't affect committed offsets.
Reference: Kafka Consumer Group CLI Tool
NEW QUESTION # 42
Kafka producers can batch messages going to the same partition.
Which statement is correct about producer batching?
Answer: B
Explanation:
Kafka producers can group messages destined for different partitions into separate batches, and send multiple batches in one request to optimize network usage.
From Kafka Producer Internals:
"The producer maintains buffers (batches) for each partition and can send multiple of these batches together in a single request to the broker." Message size is not a constraint for batching (A is false).
Broker failures don't disable batching (B is false).
There is no separate thread per batch (C is false).
Reference: Kafka Producer Architecture and Internals
NEW QUESTION # 43
(You need to send a JSON message on the wire. The message key is a string.
How would you do this?)
Answer: B
Explanation:
According to the Apache Kafka producer documentation, serialization is configured independently for message keys and values. The key and value can use different serializers depending on their data types.
In this scenario, the message key is a string, so the producer must be configured with org.apache.kafka.
common.serialization.StringSerializer for the key. The value contains JSON, so a suitable JSON serializer must be configured for the value, such as a custom JSON serializer, a library-based serializer, or a byte-array serializer after converting the JSON to bytes.
Option B correctly reflects this separation by specifying a string serializer for the key and a JSON serializer for the value. Kafka does not automatically infer serializers, and setting a serializer to null is invalid.
Additionally, there is no built-in "JSON" serializer for keys, making Option D incorrect.
Therefore, the correct approach-fully aligned with Kafka's producer configuration model-is to explicitly configure a StringSerializer for the key and a JSON-capable serializer for the value.
NEW QUESTION # 44
......
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