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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 5-10% | - Encryption in Transit - Authentication (SASL, SSL/TLS) - Authorization (ACLs) - Securing Schema Registry |
| Topic 2: Monitoring and Operations | 5-10% | - Consumer Lag and Health Checks - Cross-region Replication - Disaster Recovery - Kafka Metrics and Monitoring - Log Compaction |
| Topic 3: Kafka Connect | 10-15% | - Connector Configuration - Offset Management in Connect - Source and Sink Connectors - Converters and Transforms - Single Message Transformations (SMT) - Connect Architecture (Workers, Connectors, Tasks) |
| Topic 4: Developing with Kafka Producers | 15-20% | - Idempotent Producers - Partitioning Strategies - Producer Interceptors - Producer Configuration and Tuning - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf) - Error Handling and Retry Logic |
| Topic 5: Kafka Fundamentals | 10-15% | - Topics, Partitions, and Offsets - Log Segments and Retention - Producer and Consumer Basics - Replication Factor and ISR - Brokers and Clusters |
| Topic 6: Schema Management | 5-10% | - Protobuf and JSON Schemas - Schema Evolution and Compatibility - Schema Registry Architecture - Avro Schemas - Schema Registration and Retrieval |
| Topic 7: Kafka Streams | 20-25% | - Exactly-Once Processing - Streams Architecture and Topology - Interactive Queries - Testing Kafka Streams Applications - Windowed Operations (Tumbling, Hopping, Session) - Transformation Operations (map, filter, join, aggregate) - State Stores and Processors |
| Topic 8: Developing with Kafka Consumers | 15-20% | - Offset Management - Consumer Groups and Rebalancing - Multi-threaded Consumers - Deserialization - Commit Strategies (Auto, Manual, Cooperative) - Consumer Interceptors - Consumer Configuration and Tuning |
| Topic 9: Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Partition Assignment Strategies - Broker Configuration Parameters |
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NEW QUESTION # 17
You need to configure a sink connector to write records that fail into a dead letter queue topic.
Requirements:
* Topic name: DLQ-Topic
* Headers containing error context must be added to the messagesWhich three configuration parameters are necessary?(Select three.)
Answer: A,D,E
Explanation:
To send failed records to adead letter queue (DLQ), you must configure:
* errors.tolerance=all: Tells the connector tonot failon errors but handle them (e.g., send to DLQ).
* errors.deadletterqueue.topic.name=DLQ-Topic: Specifies the DLQ topic.
* errors.deadletterqueue.context.headers.enable=true: Includes error context in message headers.
FromKafka Connect Error Handling Docs:
"Kafka Connect supports directing problematic records to a separate topic (DLQ) using errors.* configs.
Headers can include failure metadata."
Options D, E, F are related tologging, not DLQ behavior.
Reference:Kafka Connect Configurations > Error Handling
NEW QUESTION # 18
What exceptions may be caught by the following producer? (select two)
ProducerRecord<String, String> record =
new ProducerRecord<>("topic1", "key1", "value1");
try {
producer.send(record);
} catch (Exception e) {
e.printStackTrace();
}
Answer: B,D
Explanation:
These are the client side exceptions that may be encountered before message is sent to the broker, and before a future is returned by the .send() method.
NEW QUESTION # 19
How much should be the heap size of a broker in a production setup on a machine with 256 GB of RAM, in PLAINTEXT mode?
Answer: B
Explanation:
In Kafka, a small heap size is needed, while the rest of the RAM goes automatically to the page cache (managed by the OS). The heap size goes slightly up if you need to enable SSL
NEW QUESTION # 20
When using plain JSON data with Connect, you see the following error messageorg.apache.kafka.connect.
errors.DataExceptionJsonDeserializer with schemas.enable requires "schema" and "payload" fields and may not contain additional fields. How will you fix the error?
Answer: A
Explanation:
You will need to set the schemas.enable parameters for the converter to false for plain text with no schema.
NEW QUESTION # 21
(You are writing to a Kafka topic with producer configuration acks=all.
The producer receives acknowledgements from the broker but still creates duplicate messages due to network timeouts and retries.
You need to ensure that duplicate messages are not created.
Which producer configuration should you set?)
Answer: A
Explanation:
The official Apache Kafka producer documentation states that setting enable.idempotence=true guarantees that messages are written to a partition exactly once, even in the presence of retries caused by network failures or broker timeouts. This feature prevents duplicate records by assigning producer sequence numbers and validating them on the broker side.
For idempotent producers to work correctly, retries must be enabled, which is why Kafka recommends a very large value such as retries=2147483647. Additionally, limiting max.in.flight.requests.per.connection to 1 ensures strict ordering during retries, preventing message reordering in older Kafka versions and providing the safest configuration.
Option A is irrelevant to producers. Option B explicitly disables idempotence, which causes duplicates.
Option D disables retries, which increases the risk of message loss.
Therefore, the correct and fully documented solution to eliminate duplicate messages is enabling idempotence with retries and a safe in-flight request limit, as shown in Option C.
NEW QUESTION # 22
......
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