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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Broker Configuration Parameters - Partition Assignment Strategies |
| Topic 2: Kafka Streams | 20-25% | - Transformation Operations (map, filter, join, aggregate) - Exactly-Once Processing - Windowed Operations (Tumbling, Hopping, Session) - State Stores and Processors - Testing Kafka Streams Applications - Interactive Queries - Streams Architecture and Topology |
| Topic 3: Developing with Kafka Producers | 15-20% | - Producer Configuration and Tuning - Error Handling and Retry Logic - Producer Interceptors - Serialization (JSON, Avro, Protobuf) - Idempotent Producers - Exactly-Once Semantics - Partitioning Strategies |
| Topic 4: Kafka Connect | 10-15% | - Offset Management in Connect - Connector Configuration - Single Message Transformations (SMT) - Source and Sink Connectors - Connect Architecture (Workers, Connectors, Tasks) - Converters and Transforms |
| Topic 5: Developing with Kafka Consumers | 15-20% | - Consumer Configuration and Tuning - Consumer Groups and Rebalancing - Commit Strategies (Auto, Manual, Cooperative) - Consumer Interceptors - Multi-threaded Consumers - Deserialization - Offset Management |
| Topic 6: Schema Management | 5-10% | - Avro Schemas - Schema Registration and Retrieval - Schema Registry Architecture - Protobuf and JSON Schemas - Schema Evolution and Compatibility |
| Topic 7: Security | 5-10% | - Securing Schema Registry - Authorization (ACLs) - Authentication (SASL, SSL/TLS) - Encryption in Transit |
| Topic 8: Kafka Fundamentals | 10-15% | - Brokers and Clusters - Replication Factor and ISR - Topics, Partitions, and Offsets - Log Segments and Retention - Producer and Consumer Basics |
| Topic 9: Monitoring and Operations | 5-10% | - Cross-region Replication - Log Compaction - Disaster Recovery - Kafka Metrics and Monitoring - Consumer Lag and Health Checks |
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NEW QUESTION # 17
(You are writing a producer application and need to ensure proper delivery.
You configure the producer with acks=all.
Which two actions should you take to ensure proper error handling?
Select two.)
Answer: A,B
Explanation:
The Apache Kafka producer API is asynchronous by default, and proper error handling requires explicit mechanisms. The official documentation recommends using a callback function with producer.send() to determine whether a record was successfully acknowledged or failed due to an exception. The callback provides access to both RecordMetadata and any exception encountered during sending.
Additionally, certain errors-such as serialization errors or configuration issues-are thrown synchronously when calling producer.send(). These must be handled using a try/catch block that catches KafkaException or its subclasses.
Option A is invalid because ProducerRecord has no status() method. Option C is incorrect because producer.
send() returns a Future<RecordMetadata>, not a RecordMetadata object directly.
Thus, combining a callback for asynchronous errors and a try/catch block for synchronous errors is the correct and officially documented approach to ensure reliable producer error handling when using acks=all.
NEW QUESTION # 18
Your Kafka cluster has five brokers. The topic t1 on the cluster has two partitions, and it has replication.factor
= 4, min.insync.replicas = 3.
You want to have strong durability guarantees for messages written to topic t1.
If you configure a producer 'acks=all', how many brokers need to acknowledge a message before it is considered committed?
Answer: C
NEW QUESTION # 19
What is the default maximum size of a message the Apache Kafka broker can accept?
Answer: A
Explanation:
The default maximum message size that a Kafka broker accepts is1MB (1,048,576 bytes), controlled by the config propertymessage.max.bytes.
FromKafka Broker Configuration Docs:
"The default maximum message size is 1MB. To accept larger messages, configure message.max.bytes and the producer's max.request.size." Producers also have a matching limit via max.request.size, and consumers via fetch.message.max.bytes.
Reference:Kafka Broker Configuration > message.max.bytes
NEW QUESTION # 20
A client connects to a broker in the cluster and sends a fetch request for a partition in a topic. It gets an exception Not Leader For Partition Exception in the response. How does client handle this situation?
Answer: B
Explanation:
In case the consumer has the wrong leader of a partition, it will issue a metadata request. The Metadata request can be handled by any node, so clients know afterwards which broker are the designated leader for the topic partitions. Produce and consume requests can only be sent to the node hosting partition leader.
NEW QUESTION # 21
Which two statements about Kafka Connect Single Message Transforms (SMTs) are correct?
(Select two.)
Answer: A,B
Explanation:
SMTs (Single Message Transforms) arelightweight transformationsapplied to individual messages as they pass through Kafka Connect.
* Chaining SMTs: You can applymultiple SMTsin sequence by defining them in order in the connector config.
* Masking or modifying fieldsis acommon use case(e.g., redacting sensitive data).
FromKafka Connect Documentation:
"Single Message Transforms (SMTs) are applied to individual messages. You can chain multiple SMTs together."
* SMTsdo not perform joins(B is incorrect).
* Converters and SMTs areseparate concerns(D is incorrect).
Reference:Kafka Connect Transformations Guide
NEW QUESTION # 22
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